A variable-instar climate-driven individual beetle-based phenology model for the invasive Asian longhorned beetle (Coleoptera: Cerambycidae)

Treesearch

R. Talbot Trotter, III; Melody A. Keena

2016-01-01

Efforts to manage and eradicate invasive species can benefit from an improved understanding of the physiology, biology, and behavior of the target species, and ongoing efforts to eradicate the Asian longhorned beetle (Anoplophora glabripennis Motschulsky) highlight the roles this information may play. Here, we present a climate-driven phenology...

Lessons learned while integrating habitat, dispersal, disturbance, and life-history traits into species habitat models under climate change

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew P. Peters

2011-01-01

We present an approach to modeling potential climate-driven changes in habitat for tree and bird species in the eastern United States. First, we took an empirical-statistical modeling approach, using randomForest, with species abundance data from national inventories combined with soil, climate, and landscape variables, to build abundance-based habitat models for 134...

Climate and dengue transmission: evidence and implications.

PubMed

Morin, Cory W; Comrie, Andrew C; Ernst, Kacey

2013-01-01

Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent. We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change. We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance. Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host-species interactions. Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence.

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

Climate-driven longitudinal trends in pasture-borne helminth infections of dairy cattle.

PubMed

Charlier, Johannes; Ghebretinsae, Aklilu H; Levecke, Bruno; Ducheyne, Els; Claerebout, Edwin; Vercruysse, Jozef

2016-12-01

Helminth parasites of grazing ruminants are highly prevalent globally and impact negatively on animal productivity and food security. There is a growing concern that climate change increases helminth disease frequency and intensity. In Europe, these concerns stem from case reports and theoretical life cycle models assessing the effects of climate change scenarios on helminth epidemiology. We believe this study is the first to investigate climate-driven trends in helminth infections of cattle on a cohort of randomly selected farms. One thousand, six hundred and eighty dairy farms were monitored over an 8year period for the two major helminth infections in temperate climate regions and climate-driven trends were investigated by multivariable linear mixed models. The general levels of exposure to Fasciola hepatica decreased over the study period while those to Ostertagia ostertagi increased, and this could at least be partially explained by meteorological factors (i.e. the number of rainy (precipitation >1mm) and warm days (average daily temperature >10°C) in a year). The longitudinal trends varied according to the altitude and the agricultural region of the farm. This study shows that longitudinal epidemiological data from sentinel farms combined with meteorological datasets can significantly contribute to understanding the effects of climate on infectious disease dynamics. When local environmental conditions are taken into account, the effects of climate change on disease dynamics can also be understood at more local scales. We recommend setting up a longitudinal sampling strategy across Europe in order to monitor climate-driven changes in helminth disease risk to inform adaptation strategies to promote animal health and productivity. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling.

PubMed

Iglesias, Virginia; Yospin, Gabriel I; Whitlock, Cathy

2014-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling

PubMed Central

Iglesias, Virginia; Yospin, Gabriel I.; Whitlock, Cathy

2015-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity. PMID:25657652

Catchments as non-linear filters: evaluating data-driven approaches for spatio-temporal predictions in ungauged basins

NASA Astrophysics Data System (ADS)

Bellugi, D. G.; Tennant, C.; Larsen, L.

2016-12-01

Catchment and climate heterogeneity complicate prediction of runoff across time and space, and resulting parameter uncertainty can lead to large accumulated errors in hydrologic models, particularly in ungauged basins. Recently, data-driven modeling approaches have been shown to avoid the accumulated uncertainty associated with many physically-based models, providing an appealing alternative for hydrologic prediction. However, the effectiveness of different methods in hydrologically and geomorphically distinct catchments, and the robustness of these methods to changing climate and changing hydrologic processes remain to be tested. Here, we evaluate the use of machine learning techniques to predict daily runoff across time and space using only essential climatic forcing (e.g. precipitation, temperature, and potential evapotranspiration) time series as model input. Model training and testing was done using a high quality dataset of daily runoff and climate forcing data for 25+ years for 600+ minimally-disturbed catchments (drainage area range 5-25,000 km2, median size 336 km2) that cover a wide range of climatic and physical characteristics. Preliminary results using Support Vector Regression (SVR) suggest that in some catchments this nonlinear-based regression technique can accurately predict daily runoff, while the same approach fails in other catchments, indicating that the representation of climate inputs and/or catchment filter characteristics in the model structure need further refinement to increase performance. We bolster this analysis by using Sparse Identification of Nonlinear Dynamics (a sparse symbolic regression technique) to uncover the governing equations that describe runoff processes in catchments where SVR performed well and for ones where it performed poorly, thereby enabling inference about governing processes. This provides a robust means of examining how catchment complexity influences runoff prediction skill, and represents a contribution towards the integration of data-driven inference and physically-based models.

Projected increase in El Niño-driven tropical cyclone frequency in the Pacific

NASA Astrophysics Data System (ADS)

Chand, Savin S.; Tory, Kevin J.; Ye, Hua; Walsh, Kevin J. E.

2017-02-01

The El Niño/Southern Oscillation (ENSO) drives substantial variability in tropical cyclone (TC) activity around the world. However, it remains uncertain how the projected future changes in ENSO under greenhouse warming will affect TC activity, apart from an expectation that the overall frequency of TCs is likely to decrease for most ocean basins. Here we show robust changes in ENSO-driven variability in TC occurrence by the late twenty-first century. In particular, we show that TCs become more frequent (~20-40%) during future-climate El Niño events compared with present-climate El Niño events--and less frequent during future-climate La Niña events--around a group of small island nations (for example, Fiji, Vanuatu, Marshall Islands and Hawaii) in the Pacific. We examine TCs across 20 models from the Coupled Model Intercomparison Project phase 5 database, forced under historical and greenhouse warming conditions. The 12 most realistic models identified show a strong consensus on El Niño-driven changes in future-climate large-scale environmental conditions that modulate development of TCs over the off-equatorial western Pacific and the central North Pacific regions. These results have important implications for climate change and adaptation pathways for the vulnerable Pacific island nations.

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2014-04-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and Dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall, including well-known associations from prior climate knowledge, as well as promising discoveries that invite further research by the climate science community.

Managing uncertainty in climate-driven ecological models to inform adaptation to climate change

Treesearch

Jeremy S. Littell; Donald McKenzie; Becky K. Kerns; Samuel Cushman; Charles G. Shaw

2011-01-01

The impacts of climate change on forest ecosystems are likely to require changes in forest planning and natural resource management. Changes in tree growth, disturbance extent and intensity, and eventually species distributions are expected. In natural resource management and planning, ecosystem models are typically used to provide a "best estimate" about how...

The tropical rain belts with an annual cycle and a continent model intercomparison project: TRACMIP

DOE PAGES

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; ...

2016-11-16

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

The Tropical Rain Belts with an Annual Cycle and a Continent Model Intercomparison Project: TRACMIP

NASA Technical Reports Server (NTRS)

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; Bader, Juergen; Bordoni, Simona; Codron, Francis; Dixon, Ross D.; Jonas, Jeffrey; Kang, Sarah M.; Klingaman, Nicholas P.;

Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

NASA Astrophysics Data System (ADS)

Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

2015-04-01

At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.

Motivational climate, staff and members' behaviors, and members' psychological well-being at a national fitness franchise.

PubMed

Brown, Theresa C; Fry, Mary D

2014-06-01

The purpose of this study was to examine the association between members' perceptions of staffs behaviors, motivational climate, their own behaviors, commitment to future exercise, and life satisfaction in a group-fitness setting. The theory-driven hypothesized mediating role of perceptions of the climate was also tested. Members (N = 5,541) of a national group-fitness studio franchise completed a survey regarding their class experiences. The survey included questions that measured participants' perceptions of the motivational climate (caring, task-involving, ego-involving), perceptions of staff's behaviors, their own behaviors, commitment to exercise, and life satisfaction. Structural equation modeling was used to assess both the association between variables and the theoretically driven predictive relationships. The participants perceived the environment as highly caring and task-involving and low ego-involving. They reported high exercise commitment and moderately high life satisfaction and perceived that the staffs and their own behaviors reflected caring, task-involving characteristics. Structural equation modeling demonstrated that those who perceived a higher caring, task-involving climate and lower ego-involving climate were more likely to report more task-involving, caring behaviors among the staff and themselves as well as greater commitment to exercise. In addition, a theory-driven mediational model suggested that staff behaviors may be an antecedent to members' exercise experiences by impacting their perceptions of the climate. The results of this study give direction to specific behaviors in which staff of group-fitness programs might engage to positively influence members' exercise experiences.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico.

PubMed

Johansson, Michael A; Reich, Nicholas G; Hota, Aditi; Brownstein, John S; Santillana, Mauricio

2016-09-26

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

PubMed Central

Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

2016-01-01

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model. PMID:27665707

An ecohydrological model of malaria outbreaks

NASA Astrophysics Data System (ADS)

Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.

2012-08-01

Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission driven by climatic time series. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear ecohydrological model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.

Interannual bumble bee abundance is driven by indirect climate effects on floral resource phenology.

PubMed

Ogilvie, Jane E; Griffin, Sean R; Gezon, Zachariah J; Inouye, Brian D; Underwood, Nora; Inouye, David W; Irwin, Rebecca E

2017-12-01

Climate change can influence consumer populations both directly, by affecting survival and reproduction, and indirectly, by altering resources. However, little is known about the relative importance of direct and indirect effects, particularly for species important to ecosystem functioning, like pollinators. We used structural equation modelling to test the importance of direct and indirect (via floral resources) climate effects on the interannual abundance of three subalpine bumble bee species. In addition, we used long-term data to examine how climate and floral resources have changed over time. Over 8 years, bee abundances were driven primarily by the indirect effects of climate on the temporal distribution of floral resources. Over 43 years, aspects of floral phenology changed in ways that indicate species-specific effects on bees. Our study suggests that climate-driven alterations in floral resource phenology can play a critical role in governing bee population responses to global change. © 2017 John Wiley & Sons Ltd/CNRS.

Modelling climate change and malaria transmission.

PubMed

Parham, Paul E; Michael, Edwin

2010-01-01

The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here offers a theoretical framework upon which this future research may be developed.

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

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten

2017-12-01

Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model-data integration approaches can guide the future development of global process-oriented vegetation-fire models.

Land use compounds habitat losses under projected climate change in a threatened California ecosystem.

PubMed

Riordan, Erin Coulter; Rundel, Philip W

2014-01-01

Given the rapidly growing human population in mediterranean-climate systems, land use may pose a more immediate threat to biodiversity than climate change this century, yet few studies address the relative future impacts of both drivers. We assess spatial and temporal patterns of projected 21(st) century land use and climate change on California sage scrub (CSS), a plant association of considerable diversity and threatened status in the mediterranean-climate California Floristic Province. Using a species distribution modeling approach combined with spatially-explicit land use projections, we model habitat loss for 20 dominant shrub species under unlimited and no dispersal scenarios at two time intervals (early and late century) in two ecoregions in California (Central Coast and South Coast). Overall, projected climate change impacts were highly variable across CSS species and heavily dependent on dispersal assumptions. Projected anthropogenic land use drove greater relative habitat losses compared to projected climate change in many species. This pattern was only significant under assumptions of unlimited dispersal, however, where considerable climate-driven habitat gains offset some concurrent climate-driven habitat losses. Additionally, some of the habitat gained with projected climate change overlapped with projected land use. Most species showed potential northern habitat expansion and southern habitat contraction due to projected climate change, resulting in sharply contrasting patterns of impact between Central and South Coast Ecoregions. In the Central Coast, dispersal could play an important role moderating losses from both climate change and land use. In contrast, high geographic overlap in habitat losses driven by projected climate change and projected land use in the South Coast underscores the potential for compounding negative impacts of both drivers. Limiting habitat conversion may be a broadly beneficial strategy under climate change. We emphasize the importance of addressing both drivers in conservation and resource management planning.

Climate impacts of deforestation/land-use changes in Central South America in the PRECIS regional climate model: mean precipitation and temperature response to present and future deforestation scenarios.

PubMed

Canziani, Pablo O; Carbajal Benitez, Gerardo

2012-01-01

Deforestation/land-use changes are major drivers of regional climate change in central South America, impacting upon Amazonia and Gran Chaco ecoregions. Most experimental and modeling studies have focused on the resulting perturbations within Amazonia. Using the Regional Climate Model PRECIS, driven by ERA-40 reanalysis and ECHAM4 Baseline model for the period 1961-2000 (40-year runs), potential effects of deforestation/land-use changes in these and other neighboring ecoregions are evaluated. Current 2002 and estimated 2030 land-use scenarios are used to assess PRECIS's response during 1960-2000. ERA-40 and ECHAM4 Baseline driven runs yield similar results. Precipitation changes for 2002 and 2030 land-use scenarios, while significant within deforested areas, do not result in significant regional changes. For temperature significant changes are found within deforested areas and beyond, with major temperature enhancements during winter and spring. Given the current climate, primary effects of deforestation/land-use changes remain mostly confined to the tropical latitudes of Gran Chaco, and Amazonia.

Climate Impacts of Deforestation/Land-Use Changes in Central South America in the PRECIS Regional Climate Model: Mean Precipitation and Temperature Response to Present and Future Deforestation Scenarios

PubMed Central

Canziani, Pablo O.; Carbajal Benitez, Gerardo

2012-01-01

Deforestation/land-use changes are major drivers of regional climate change in central South America, impacting upon Amazonia and Gran Chaco ecoregions. Most experimental and modeling studies have focused on the resulting perturbations within Amazonia. Using the Regional Climate Model PRECIS, driven by ERA-40 reanalysis and ECHAM4 Baseline model for the period 1961–2000 (40-year runs), potential effects of deforestation/land-use changes in these and other neighboring ecoregions are evaluated. Current 2002 and estimated 2030 land-use scenarios are used to assess PRECIS's response during 1960–2000. ERA-40 and ECHAM4 Baseline driven runs yield similar results. Precipitation changes for 2002 and 2030 land-use scenarios, while significant within deforested areas, do not result in significant regional changes. For temperature significant changes are found within deforested areas and beyond, with major temperature enhancements during winter and spring. Given the current climate, primary effects of deforestation/land-use changes remain mostly confined to the tropical latitudes of Gran Chaco, and Amazonia. PMID:22645487

Risky Business and the American Climate Prospectus: Economic Risks of Climate Change in the United States"

NASA Astrophysics Data System (ADS)

Gordon, K.; Houser, T.; Kopp, R. E., III; Hsiang, S. M.; Larsen, K.; Jina, A.; Delgado, M.; Muir-Wood, R.; Rasmussen, D.; Rising, J.; Mastrandrea, M.; Wilson, P. S.

2014-12-01

The United States faces a range of economic risks from global climate change - from increased flooding and storm damage, to climate-driven changes in crop yields and labor productivity, to heat-related strains on energy and public health systems. The Risky Business Project commissioned a groundbreaking new analysis of these and other climate risks by region of the country and sector of the economy. The American Climate Prospectus (ACP) links state-of-the-art climate models with econometric research of human responses to climate variability and cutting edge private sector risk assessment tools, the ACP offers decision-makers a data driven assessment of the specific risks they face. We describe the challenge, methods, findings, and policy implications of the national risk analysis, with particular focus on methodological innovations and novel insights.

A climate-driven mechanistic population model of Aedes albopictus with diapause.

PubMed

Jia, Pengfei; Lu, Liang; Chen, Xiang; Chen, Jin; Guo, Li; Yu, Xiao; Liu, Qiyong

2016-03-24

The mosquito Aedes albopitus is a competent vector for the transmission of many blood-borne pathogens. An important factor that affects the mosquitoes' development and spreading is climate, such as temperature, precipitation and photoperiod. Existing climate-driven mechanistic models overlook the seasonal pattern of diapause, referred to as the survival strategy of mosquito eggs being dormant and unable to hatch under extreme weather. With respect to diapause, several issues remain unaddressed, including identifying the time when diapause eggs are laid and hatched under different climatic conditions, demarcating the thresholds of diapause and non-diapause periods, and considering the mortality rate of diapause eggs. Here we propose a generic climate-driven mechanistic population model of Ae. albopitus applicable to most Ae. albopictus-colonized areas. The new model is an improvement over the previous work by incorporating the diapause behaviors with many modifications to the stage-specific mechanism of the mosquitoes' life-cycle. monthly Container Index (CI) of Ae. albopitus collected in two Chinese cities, Guangzhou and Shanghai is used for model validation. The simulation results by the proposed model is validated with entomological field data by the Pearson correlation coefficient r (2) in Guangzhou (r (2) = 0.84) and in Shanghai (r (2) = 0.90). In addition, by consolidating the effect of diapause-related adjustments and temperature-related parameters in the model, the improvement is significant over the basic model. The model highlights the importance of considering diapause in simulating Ae. albopitus population. It also corroborates that temperature and photoperiod are significant in affecting the population dynamics of the mosquito. By refining the relationship between Ae. albopitus population and climatic factors, the model serves to establish a mechanistic relation to the growth and decline of the species. Understanding this relationship in a better way will benefit studying the transmission and the spatiotemporal distribution of mosquito-borne epidemics and eventually facilitating the early warning and control of the diseases.

Mountain Glaciers and Ice Caps

USGS Publications Warehouse

Ananichheva, Maria; Arendt, Anthony; Hagen, Jon-Ove; Hock, Regine; Josberger, Edward G.; Moore, R. Dan; Pfeffer, William Tad; Wolken, Gabriel J.

2011-01-01

Projections of future rates of mass loss from mountain glaciers and ice caps in the Arctic focus primarily on projections of changes in the surface mass balance. Current models are not yet capable of making realistic forecasts of changes in losses by calving. Surface mass balance models are forced with downscaled output from climate models driven by forcing scenarios that make assumptions about the future rate of growth of atmospheric greenhouse gas concentrations. Thus, mass loss projections vary considerably, depending on the forcing scenario used and the climate model from which climate projections are derived. A new study in which a surface mass balance model is driven by output from ten general circulation models (GCMs) forced by the IPCC (Intergovernmental Panel on Climate Change) A1B emissions scenario yields estimates of total mass loss of between 51 and 136 mm sea-level equivalent (SLE) (or 13% to 36% of current glacier volume) by 2100. This implies that there will still be substantial glacier mass in the Arctic in 2100 and that Arctic mountain glaciers and ice caps will continue to influence global sea-level change well into the 22nd century.

Climate-change driven range shifts of anchovy biomass projected by bio-physical coupling individual based model in the marginal seas of East Asia

NASA Astrophysics Data System (ADS)

Jung, Sukgeun; Pang, Ig-Chan; Lee, Joon-ho; Lee, Kyunghwan

2016-12-01

Recent studies in the western North Pacific reported a declining standing stock biomass of anchovy ( Engraulis japonicus) in the Yellow Sea and a climate-driven southward shift of anchovy catch in Korean waters. We investigated the effects of a warming ocean on the latitudinal shift of anchovy catch by developing and applying individual-based models (IBMs) based on a regional ocean circulation model and an IPCC climate change scenario. Despite the greater uncertainty, our two IBMs projected that, by the 2030s, the strengthened Tsushima warm current in the Korea Strait and the East Sea, driven by global warming, and the subsequent confinement of the relatively cold water masses within the Yellow Sea will decrease larval anchovy biomass in the Yellow Sea, but will increase it in the Korea Strait and the East Sea. The decreasing trend of anchovy biomass in the Yellow Sea was reproduced by our models, but further validation and enhancement of the models is required together with extended ichthyoplankton surveys to understand and reliably project range shifts of anchovy and the impacts such range shifts will have on the marine ecosystems and fisheries in the region.

Youth Climate Summits: Empowering & Engaging Youth to Lead on Climate Change

NASA Astrophysics Data System (ADS)

Kretser, J.

2017-12-01

The Wild Center's Youth Climate Summits is a program that engages youth in climate literacy from knowledge and understanding to developing action in their schools and communities. Each Youth Climate Summit is a one to three day event that brings students and teachers together to learn about climate change science, impacts and solutions at a global and local level. Through speakers, workshops and activities, the Summit culminates in a student-driven Climate Action Plan that can be brought back to schools and communities. The summits have been found to be powerful vehicles for inspiration, learning, community engagement and youth leadership development. Climate literacy with a focus on local climate impacts and solutions is a key component of the Youth Climate Summit. The project-based learning surrounding the creation of a unique, student driven, sustainability and Climate Action Plan promotes leadership skills applicable and the tools necessary for a 21st Century workforce. Student driven projects range from school gardens and school energy audits to working with NYS officials to commit to going 100% renewable electricty at the three state-owned downhill ski facilities. The summit model has been scaled and replicated in other communities in New York State, Vermont, Ohio, Michigan and Washington states as well as internationally in Finland, Germany and Sri Lanka.

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.

Coupling records of fluvial activity from the last interglacial-glacial cycle with climate forcing using both geochronology and numerical modelling

NASA Astrophysics Data System (ADS)

Briant, Rebecca; Mottram, Gareth; Wainwright, John

2010-05-01

River systems are a critical component of the landscape. An understanding of their response to variations in the Earth's climate is vital in light of the expected changes in global climate (e.g. 1.8 to 4.8°C temperature rise) that are forecast to occur over the next c. 100 years. Over the longer term, it becomes increasingly likely that the changes we will see may even be of a magnitude for which the most appropriate analogue we have is the glacial-interglacial scale (c. 10°C temperature change) and other climate changes typical of the Quaternary period (last 2 million years). Therefore it is crucial to apply our understanding of climate-driven changes during the Quaternary to future projections of both climate and landscape change, especially since landscape instability is a key characteristic of the Quaternary. Linking river activity to climate requires both the recognition of potentially climate-driven changes within the fluvial sedimentary record and the linkage of these to external climate records using various geochronological techniques. To this end, this paper firstly presents results from the Welland catchment, Fenland Basin where climatically-driven phases of river activity have been identified using detailed sedimentological analysis and palaeontological environmental reconstruction. Dating of these using radiocarbon and optically-stimulated luminescence dating has shown broad correspondence to external climate fluctuations at a marine isotope substage scale over the last interglacial-glacial cycle (MIS 5d onwards). The precision and accuracy of the two different age techniques varies in different parts of this time period and this will be discussed. Limitations in the precision of these geochronological techniques have prompted the use of a further, complementary to improve understanding of these sequences, i.e. ensemble numerical modeling. The rationale behind this approach is that river response to climate can be traced within the model and validated against the known geological record. If the known geological record can be replicated, then the detailed linkages between climate and river activity shown in the model can be used understand to the relationships between climate change and river activity more clearly. This paper will present the results of three-dimensional cellular automata modeling of the Welland catchment, compare them to the geological record, and draw out what this means for our understanding of earth surface processes.

On the Edge: the Impact of Climate Change, Climate Extremes, and Climate-driven Disturbances on the Food-Energy-Water Nexus in the Colorado River Basin

NASA Astrophysics Data System (ADS)

Bennett, K. E.; McDowell, N. G.; Tidwell, V. C.; Xu, C.; Solander, K.; Jonko, A. K.; Wilson, C. J.; Middleton, R. S.

2016-12-01

The Colorado River Basin (CRB) is a critical watershed in terms of vulnerability to climate change and supporting the food-energy-water nexus. Climate-driven disturbances in the CRB—including wildfire, drought, and pests—threaten the watershed's ability to reliably support a wide array of ecosystem services while meeting the interrelated demands of the food-energy-water nexus. Our work illustrates future changes for upper Colorado River headwater basins using the Variable Infiltration Capacity hydrologic model driven by downscaled CMIP5 global climate data coupled with pseudo-dynamic vegetation shifts associated with changing fire and drought conditions. We examine future simulated streamflow within the context of an operational model framework to consider the impacts on water operators and managers who rely upon the timely and continual delivery of streamflow. We focus on results for a large case study basin within the CRB—the San Juan River—showing future scenarios where this ecosystem is pushed towards the extremes. Our findings illustrate that landscape change in the CRB cause delayed snowmelt and increased evapotranspiration from shrublands, which leads to increases in the frequency and magnitude of both droughts and floods within disturbed systems. By 2080, coupled climate and landscape change produces a dramatically altered hydrograph resulting in larger peak flows, reduced lower flows, and lower overall streamflow. Operationally, this results in increased future water delivery challenges and lower reservoir storages driven by changes in the headwater basins. Ultimately, our work shows that the already-stressed CRB ecosystem could, in the future, be pushed over a tipping point, significantly impacting the basin's ability to reliably supply water for food, energy, and urban uses.

CWRF performance at downscaling China climate characteristics

NASA Astrophysics Data System (ADS)

Liang, Xin-Zhong; Sun, Chao; Zheng, Xiaohui; Dai, Yongjiu; Xu, Min; Choi, Hyun I.; Ling, Tiejun; Qiao, Fengxue; Kong, Xianghui; Bi, Xunqiang; Song, Lianchun; Wang, Fang

2018-05-01

The performance of the regional Climate-Weather Research and Forecasting model (CWRF) for downscaling China climate characteristics is evaluated using a 1980-2015 simulation at 30 km grid spacing driven by the ECMWF Interim reanalysis (ERI). It is shown that CWRF outperforms the popular Regional Climate Modeling system (RegCM4.6) in key features including monsoon rain bands, diurnal temperature ranges, surface winds, interannual precipitation and temperature anomalies, humidity couplings, and 95th percentile daily precipitation. Even compared with ERI, which assimilates surface observations, CWRF better represents the geographic distributions of seasonal mean climate and extreme precipitation. These results indicate that CWRF may significantly enhance China climate modeling capabilities.

Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

Treesearch

Shiyuan Zhong; Xiuping Li; Xindi Bian; Warren E. Heilman; L. Ruby Leung; William I. Jr. Gustafson

2012-01-01

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990-1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-...

Adapting the Biome-BGC Model to New Zealand Pastoral Agriculture: Climate Change and Land-Use Change

NASA Astrophysics Data System (ADS)

Keller, E. D.; Baisden, W. T.; Timar, L.

2011-12-01

We have adapted the Biome-BGC model to make climate change and land-use scenario estimates of New Zealand's pasture production in 2020 and 2050, with comparison to a 2005 baseline. We take an integrated modelling approach with the aim of enabling the model's use for policy assessments across broadly related issues such as climate change mitigation and adaptation, land-use change, and greenhouse gas projections. The Biome-BGC model is a biogeochemical model that simulates carbon, water, and nitrogen cycles in terrestrial ecosystems. We introduce two new 'ecosystems', sheep/beef and dairy pasture, within the existing structure of the Biome-BGC model and calibrate its ecophysiological parameters against pasture clipping data from diverse sites around New Zealand to form a baseline estimate of total New Zealand pasture production. Using downscaled AR4 climate projections, we construct mid- and upper-range climate change scenarios in 2020 and 2050. We produce land-use change scenarios in the same years by combining the Biome-BGC model with the Land Use in Rural New Zealand (LURNZ) model. The LURNZ model uses econometric approaches to predict future land-use change driven by changes in net profits driven by expected pricing, including the introduction of an emission trading system. We estimate the relative change in national pasture production from our 2005 baseline levels for both sheep/beef and dairy systems under each scenario.

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

NASA Astrophysics Data System (ADS)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D. M. H.

2013-04-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10-90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.

Contribution of climate-driven change in continental water storage to recent sea-level rise

PubMed Central

Milly, P. C. D.; Cazenave, A.; Gennero, C.

2003-01-01

Using a global model of continental water balance, forced by interannual variations in precipitation and near-surface atmospheric temperature for the period 1981–1998, we estimate the sea-level changes associated with climate-driven changes in storage of water as snowpack, soil water, and ground water; storage in ice sheets and large lakes is not considered. The 1981–1998 trend is estimated to be 0.12 mm/yr, and substantial interannual fluctuations are inferred; for 1993–1998, the trend is 0.25 mm/yr. At the decadal time scale, the terrestrial contribution to eustatic (i.e., induced by mass exchange) sea-level rise is significantly smaller than the estimated steric (i.e., induced by density changes) trend for the same period, but is not negligibly small. In the model the sea-level rise is driven mainly by a downtrend in continental precipitation during the study period, which we believe was generated by natural variability in the climate system. PMID:14576277

Contribution of climate-driven change in continental water storage to recent sea-level rise

USGS Publications Warehouse

Milly, P.C.D.; Cazenave, A.; Gennero, M.C.

2003-01-01

Using a global model of continental water balance, forced by interannual variations in precipitation and near-surface atmospheric temperature for the period 1981-1998, we estimate the sea-level changes associated with climate-driven changes in storage of water as snowpack, soil water, and ground water; storage in ice sheets and large lakes is not considered. The 1981-1998 trend is estimated to be 0.12 mm/yr, and substantial interannual fluctuations are inferred; for 1993-1998, the trend is 0.25 mm/yr. At the decadal time scale, the terrestrial contribution to eustatic (i.e., induced by mass exchange) sea-level rise is significantly smaller than the estimated steric (i.e., induced by density changes) trend for the same period, but is not negligibly small. In the model the sea-level rise is driven mainly by a downtrend in continental precipitation during the study period, which we believe was generated by natural variability in the climate system.

Probabilistic Estimates of Climate Impacts of the Paris Agreement and Contributions from Different Countries.

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Paltsev, S.; Chen, Y. H. H.; Monier, E.; Libardoni, A. G.; Forest, C. E.

2017-12-01

In December of 2015 during COP21 meeting in Paris almost 200 countries signed an agreement pledging to reduce their anthropogenic greenhouse gas (GHG) emissions. Recently USA announced plans to withdraw from the agreement. In this study, we estimate an impact of this decision on future climate using the MIT Integrated Global System Model, which consists of the human activity model, Economic Projection and Policy Analysis (EPPA) model, and a climate model of intermediate complexity, the MIT Earth System Model (MESM). For comparison, we also estimated impacts of possible withdrawals of China, Europe or India. In addition to the "no climate policy" scenario, we consider five emissions scenarios: Paris, Paris_no_USA, Paris_no_EUR and so on. Climate simulations were carried out from 1861 to 2005 driven by prescribed changes in GHGs and natural forcings and them continued to 2100 driven by GHG emissions produced by EPPA model. Because Paris agreement only cover the period up to 2030, last five scenarios were created assuming that emissions or carbon intensity will continue to decrease after 2030 at the same rate as in the 2020-2030 period. To account for uncertainty in climate system response to external forcing, we carry out 400 member ensembles on climate simulations for each scenario. Probability distributions for climate parameters are obtained by comparing simulated climate for 1861 to 2010 with observations. Our analysis shows that, full implementation of Paris agreement (under above-descried assumptions) will increase probability of surface air temperature in the last decade of this century increasing by less than 3oC relative to pre-industrial form about 20% for "no climate policy" to about 86%. Withdrawal of USA, China, Europe or India will decrease this probability to about 63, 67, 75 and 82%, respectively.

Overlooked Role of Mesoscale Winds in Powering Ocean Diapycnal Mixing.

PubMed

Jing, Zhao; Wu, Lixin; Ma, Xiaohui; Chang, Ping

2016-11-16

Diapycnal mixing affects the uptake of heat and carbon by the ocean as well as plays an important role in global ocean circulations and climate. In the thermocline, winds provide an important energy source for furnishing diapycnal mixing primarily through the generation of near-inertial internal waves. However, this contribution is largely missing in the current generation of climate models. In this study, it is found that mesoscale winds at scales of a few hundred kilometers account for more than 65% of near-inertial energy flux into the North Pacific basin and 55% of turbulent kinetic dissipation rate in the thermocline, suggesting their dominance in powering diapycnal mixing in the thermocline. Furthermore, a new parameterization of wind-driven diapycnal mixing in the ocean interior for climate models is proposed, which, for the first time, successfully captures both temporal and spatial variations of wind-driven diapycnal mixing in the thermocline. It is suggested that as mesoscale winds are not resolved by the climate models participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) due to insufficient resolutions, the diapycnal mixing is likely poorly represented, raising concerns about the accuracy and robustness of climate change simulations and projections.

Overlooked Role of Mesoscale Winds in Powering Ocean Diapycnal Mixing

PubMed Central

Jing, Zhao; Wu, Lixin; Ma, Xiaohui; Chang, Ping

2016-01-01

Diapycnal mixing affects the uptake of heat and carbon by the ocean as well as plays an important role in global ocean circulations and climate. In the thermocline, winds provide an important energy source for furnishing diapycnal mixing primarily through the generation of near-inertial internal waves. However, this contribution is largely missing in the current generation of climate models. In this study, it is found that mesoscale winds at scales of a few hundred kilometers account for more than 65% of near-inertial energy flux into the North Pacific basin and 55% of turbulent kinetic dissipation rate in the thermocline, suggesting their dominance in powering diapycnal mixing in the thermocline. Furthermore, a new parameterization of wind-driven diapycnal mixing in the ocean interior for climate models is proposed, which, for the first time, successfully captures both temporal and spatial variations of wind-driven diapycnal mixing in the thermocline. It is suggested that as mesoscale winds are not resolved by the climate models participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) due to insufficient resolutions, the diapycnal mixing is likely poorly represented, raising concerns about the accuracy and robustness of climate change simulations and projections. PMID:27849059

Modeling aspen responses to climatic warming and insect defoliation in western Canada

Treesearch

E. H. Ted Hogg

2001-01-01

Effects of climate change at three aspen sites in Saskatchewan were explored using a climate-driven model that includes insect defoliation. A simulated warming of 4-5 °C caused complete mortality due to drought at all three sites. A simulated warming of 2-2.5 °C caused complete mortality of aspen at the parkland site, while aspen growth at two boreal sites showed...

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2015-01-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. These relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño-Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.

On the data-driven inference of modulatory networks in climate science: An application to West African rainfall

DOE PAGES

Gonzalez, II, D. L.; Angus, M. P.; Tetteh, I. K.; ...

2015-01-13

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression,more » and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.« less

How will climate change affect watershed mercury export in a representative Coastal Plain watershed?

NASA Astrophysics Data System (ADS)

Golden, H. E.; Knightes, C. D.; Conrads, P. A.; Feaster, T.; Davis, G. M.; Benedict, S. T.; Bradley, P. M.

2012-12-01

Future climate change is expected to drive variations in watershed hydrological processes and water quality across a wide range of physiographic provinces, ecosystems, and spatial scales. How such shifts in climatic conditions will impact watershed mercury (Hg) dynamics and hydrologically-driven Hg transport is a significant concern. We simulate the responses of watershed hydrological and total Hg (HgT) fluxes and concentrations to a unified set of past and future climate change projections in a Coastal Plain basin using multiple watershed models. We use two statistically downscaled global precipitation and temperature models, ECHO, a hybrid of the ECHAM4 and HOPE-G models, and the Community Climate System Model (CCSM3) across two thirty-year simulations (1980 to 2010 and 2040 to 2070). We apply three watershed models to quantify and bracket potential changes in hydrologic and HgT fluxes, including the Visualizing Ecosystems for Land Management Assessment Model for Hg (VELMA-Hg), the Grid Based Mercury Model (GBMM), and TOPLOAD, a water quality constituent model linked to TOPMODEL hydrological simulations. We estimate a decrease in average annual HgT fluxes in response to climate change using the ECHO projections and an increase with the CCSM3 projections in the study watershed. Average monthly HgT fluxes increase using both climate change projections between in the late spring (March through May), when HgT concentrations and flow are high. Results suggest that hydrological transport associated with changes in precipitation and temperature is the primary mechanism driving HgT flux response to climate change. Our multiple model/multiple projection approach allows us to bracket the relative response of HgT fluxes to climate change, thereby illustrating the uncertainty associated with the projections. In addition, our approach allows us to examine potential variations in climate change-driven water and HgT export based on different conceptualizations of watershed HgT dynamics and the representative mathematical structures underpinning existing watershed Hg models.

10Be in late deglacial climate simulated by ECHAM5-HAM - Part 2: Isolating the solar signal from 10Be deposition

NASA Astrophysics Data System (ADS)

Heikkilä, U.; Shi, X.; Phipps, S. J.; Smith, A. M.

2013-10-01

This study investigates the effect of deglacial climate on the deposition of the solar proxy 10Be globally, and at two specific locations, the GRIP site at Summit, Central Greenland, and the Law Dome site in coastal Antarctica. The deglacial climate is represented by three 30 yr time slice simulations of 10 000 BP (years before present = 1950 CE), 11 000 BP and 12 000 BP, compared with a preindustrial control simulation. The model used is the ECHAM5-HAM atmospheric aerosol-climate model, driven with sea surface temperatures and sea ice cover simulated using the CSIRO Mk3L coupled climate system model. The focus is on isolating the 10Be production signal, driven by solar variability, from the weather or climate driven noise in the 10Be deposition flux during different stages of climate. The production signal varies on lower frequencies, dominated by the 11yr solar cycle within the 30 yr time scale of these experiments. The climatic noise is of higher frequencies. We first apply empirical orthogonal functions (EOF) analysis to global 10Be deposition on the annual scale and find that the first principal component, consisting of the spatial pattern of mean 10Be deposition and the temporally varying solar signal, explains 64% of the variability. The following principal components are closely related to those of precipitation. Then, we apply ensemble empirical decomposition (EEMD) analysis on the time series of 10Be deposition at GRIP and at Law Dome, which is an effective method for adaptively decomposing the time series into different frequency components. The low frequency components and the long term trend represent production and have reduced noise compared to the entire frequency spectrum of the deposition. The high frequency components represent climate driven noise related to the seasonal cycle of e.g. precipitation and are closely connected to high frequencies of precipitation. These results firstly show that the 10Be atmospheric production signal is preserved in the deposition flux to surface even during climates very different from today's both in global data and at two specific locations. Secondly, noise can be effectively reduced from 10Be deposition data by simply applying the EOF analysis in the case of a reasonably large number of available data sets, or by decomposing the individual data sets to filter out high-frequency fluctuations.

Land Use Compounds Habitat Losses under Projected Climate Change in a Threatened California Ecosystem

PubMed Central

Riordan, Erin Coulter; Rundel, Philip W.

2014-01-01

Given the rapidly growing human population in mediterranean-climate systems, land use may pose a more immediate threat to biodiversity than climate change this century, yet few studies address the relative future impacts of both drivers. We assess spatial and temporal patterns of projected 21st century land use and climate change on California sage scrub (CSS), a plant association of considerable diversity and threatened status in the mediterranean-climate California Floristic Province. Using a species distribution modeling approach combined with spatially-explicit land use projections, we model habitat loss for 20 dominant shrub species under unlimited and no dispersal scenarios at two time intervals (early and late century) in two ecoregions in California (Central Coast and South Coast). Overall, projected climate change impacts were highly variable across CSS species and heavily dependent on dispersal assumptions. Projected anthropogenic land use drove greater relative habitat losses compared to projected climate change in many species. This pattern was only significant under assumptions of unlimited dispersal, however, where considerable climate-driven habitat gains offset some concurrent climate-driven habitat losses. Additionally, some of the habitat gained with projected climate change overlapped with projected land use. Most species showed potential northern habitat expansion and southern habitat contraction due to projected climate change, resulting in sharply contrasting patterns of impact between Central and South Coast Ecoregions. In the Central Coast, dispersal could play an important role moderating losses from both climate change and land use. In contrast, high geographic overlap in habitat losses driven by projected climate change and projected land use in the South Coast underscores the potential for compounding negative impacts of both drivers. Limiting habitat conversion may be a broadly beneficial strategy under climate change. We emphasize the importance of addressing both drivers in conservation and resource management planning. PMID:24466116

Simulating Climate Change in Ireland

NASA Astrophysics Data System (ADS)

Nolan, P.; Lynch, P.

2012-04-01

At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at high spatial resolution. To address the issue of model uncertainty, a Multi-Model Ensemble (MME) approach is used. The ensemble method uses different RCMs, driven by several Global Climate Models (GCMs), to simulate climate change. Through the MME approach, the uncertainty in the RCM projections is quantified, enabling us to estimate the probability density function of predicted changes, and providing a measure of confidence in the predictions. The RCMs were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCMs exhibit reasonable and realistic features as documented in the historical data record. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 GCM, the UK Met Office HadGEM2-ES GCM and the CGCM3.1 GCM from the Canadian Centre for Climate Modelling. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B, A2, B1, RCP 4.5 & RCP 8.5 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in precipitation and wind speed for the future winter months and a decrease during the summer months. The predicted annual change in temperature is approximately 1.1°C over Ireland. To date, all RCM projections are in general agreement, thus increasing our confidence in the robustness of the results.

Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

NASA Astrophysics Data System (ADS)

Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

2012-12-01

General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

Substantial large-scale feedbacks between natural aerosols and climate

NASA Astrophysics Data System (ADS)

Scott, C. E.; Arnold, S. R.; Monks, S. A.; Asmi, A.; Paasonen, P.; Spracklen, D. V.

2018-01-01

The terrestrial biosphere is an important source of natural aerosol. Natural aerosol sources alter climate, but are also strongly controlled by climate, leading to the potential for natural aerosol-climate feedbacks. Here we use a global aerosol model to make an assessment of terrestrial natural aerosol-climate feedbacks, constrained by observations of aerosol number. We find that warmer-than-average temperatures are associated with higher-than-average number concentrations of large (>100 nm diameter) particles, particularly during the summer. This relationship is well reproduced by the model and is driven by both meteorological variability and variability in natural aerosol from biogenic and landscape fire sources. We find that the calculated extratropical annual mean aerosol radiative effect (both direct and indirect) is negatively related to the observed global temperature anomaly, and is driven by a positive relationship between temperature and the emission of natural aerosol. The extratropical aerosol-climate feedback is estimated to be -0.14 W m-2 K-1 for landscape fire aerosol, greater than the -0.03 W m-2 K-1 estimated for biogenic secondary organic aerosol. These feedbacks are comparable in magnitude to other biogeochemical feedbacks, highlighting the need for natural aerosol feedbacks to be included in climate simulations.

A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier

NASA Astrophysics Data System (ADS)

Strigaro, Daniele; Moretti, Massimiliano; Mattavelli, Matteo; Frigerio, Ivan; Amicis, Mattia De; Maggi, Valter

2016-09-01

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.

Human Responses to Climate Variability: The Case of South Africa

NASA Astrophysics Data System (ADS)

Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.

2014-12-01

Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa's population base vulnerable to future climate change. In this study, we utilize two complementary statistical models - one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

PubMed Central

Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241

Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

PubMed

Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

Regional Climate Simulations with COSMO-CLM for West Africa using three different soil-vegetation-atmosphere-transfer (SVAT) module

NASA Astrophysics Data System (ADS)

Breil, Marcus; Panitz, Hans-Jürgen

2014-05-01

Climate predictions on decadal timescales constitute a new field of research, closing the gap between short-term and seasonal weather predictions and long-term climate projections. Therefore, the Federal Ministry of Education and Research in Germany (BMBF) has recently funded the research program MiKlip (Mittelfristige Klimaprognosen), which aims to create a model system that can provide reliable decadal climate forecasts. Recent studies have suggested that one region with high potential decadal predictability is West Africa. Therefore, the project DEPARTURE (DEcadal Prediction of African Rainfall and ATlantic HURricanE Activity) was established within the MiKlip program to assess the feasibility and the potential added value of regional decadal climate predictions for West Africa. To quantify the potential decadal climate predictability, a multi-model approach with the three different regional climate models REMO, WRF and COSMO-CLM (CCLM) will be realized. The presented research will contribute to DEPARTURE by performing hindcast ensemble simulations with CCLM, driven by global decadal MPI-ESM-LR simulations. Thereby, one focus is on the dynamic soil-vegetation-climate interaction on decadal timescales. Recent studies indicate that there are significant feedbacks between the land-surface and the atmosphere, which might influence the decadal climate variability substantially. To investigate this connection, two different SVATs (Community Land Model (CLM), and VEG3D) will be coupled with the CCLM, replacing TERRA_ML, the standard SVAT implemented in CCLM. Thus, sensitive model parameters shall be identified, whereby the understanding of important processes might be improved. As a first step, TERRA_ML is substituted by VEG3D, a SVAT developed at the IMK-TRO, Karlsruhe, Germany. Compared to TERRA_ML, VEG3D includes an explicit vegetation layer by using a big leaf approach, inducing higher correlations with observations as it has been shown in previous studies. The coupling of VEG3D with CCLM is performed by using the OASIS3-MCT coupling software, developed by CERFACS, Toulouse, France. Results of CCLM simulations using both SVATs are analysed and compared for the DEPARTURE model domain. Thereby ERA-Interim driven CCLM simulations with VEG3D showed better agreement with observational data than simulations with TERRA_ML, especially for dense vegetaded areas. This will be demonstrated exemplarily. Additionally, results for MPI-ESM-LR driven decadal hindcast simulations (1966 - 1975) are analysed and presented.

Quantifying the effect of varying GHG's concentration in Regional Climate Models

NASA Astrophysics Data System (ADS)

López-Romero, Jose Maria; Jerez, Sonia; Palacios-Peña, Laura; José Gómez-Navarro, Juan; Jiménez-Guerrero, Pedro; Montavez, Juan Pedro

2017-04-01

Regional Climate Models (RCMs) are driven at the boundaries by Global Circulation Models (GCM), and in the particular case of Climate Change projections, such simulations are forced by varying greenhouse gases (GHGs) concentrations. In hindcast simulations driven by reanalysis products, the climate change signal is usually introduced in the assimilation process as well. An interesting question arising in this context is whether GHGs concentrations have to be varied within the RCMs model itself, or rather they should be kept constant. Some groups keep the GHGs concentrations constant under the assumption that information about climate change signal is given throughout the boundaries; sometimes certain radiation parameterization schemes do not permit such changes. Other approaches vary these concentrations arguing that this preserves the physical coherence respect to the driving conditions for the RCM. This work aims to shed light on this topic. For this task, various regional climate simulations with the WRF model for the 1954-2004 period have been carried out for using a Euro-CORDEX compliant domain. A series of simulations with constant and variable GHGs have been performed using both, a GCM (ECHAM6-OM) and a reanalysis product (ERA-20C) data. Results indicate that there exist noticeable differences when introducing varying GHGs concentrations within the RCM domain. The differences in 2-m temperature series between the experiments with varying or constant GHGs concentration strongly depend on the atmospheric conditions, appearing a strong interannual variability. This suggests that short-term experiments are not recommended if the aim is to assess the role of varying GHGs. In addition, and consistently in both GCM and reanalysis-driven experiments, the magnitude of temperature trends, as well as the spatial pattern represented by varying GHGs experiment, are closer to the driving dataset than in experiments keeping constant the GHGs concentration. These results point towards the need for the inclusion of varying GHGs concentration within the RCM itself when dynamically downscaling global datasets, both in GCM and hindcast simulations.

Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change.

PubMed

Galbraith, David; Levy, Peter E; Sitch, Stephen; Huntingford, Chris; Cox, Peter; Williams, Mathew; Meir, Patrick

2010-08-01

*The large-scale loss of Amazonian rainforest under some future climate scenarios has generally been considered to be driven by increased drying over Amazonia predicted by some general circulation models (GCMs). However, the importance of rainfall relative to other drivers has never been formally examined. *Here, we conducted factorial simulations to ascertain the contributions of four environmental drivers (precipitation, temperature, humidity and CO(2)) to simulated changes in Amazonian vegetation carbon (C(veg)), in three dynamic global vegetation models (DGVMs) forced with climate data based on HadCM3 for four SRES scenarios. *Increased temperature was found to be more important than precipitation reduction in causing losses of Amazonian C(veg) in two DGVMs (Hyland and TRIFFID), and as important as precipitation reduction in a third DGVM (LPJ). Increases in plant respiration, direct declines in photosynthesis and increases in vapour pressure deficit (VPD) all contributed to reduce C(veg) under high temperature, but the contribution of each mechanism varied greatly across models. Rising CO(2) mitigated much of the climate-driven biomass losses in the models. *Additional work is required to constrain model behaviour with experimental data under conditions of high temperature and drought. Current models may be overly sensitive to long-term elevated temperatures as they do not account for physiological acclimation.

Evaluation of Probable Maximum Precipitation and Flood under Climate Change in the 21st Century

NASA Astrophysics Data System (ADS)

Gangrade, S.; Kao, S. C.; Rastogi, D.; Ashfaq, M.; Naz, B. S.; Kabela, E.; Anantharaj, V. G.; Singh, N.; Preston, B. L.; Mei, R.

2016-12-01

Critical infrastructures are potentially vulnerable to extreme hydro-climatic events. Under a warming environment, the magnitude and frequency of extreme precipitation and flood are likely to increase enhancing the needs to more accurately quantify the risks due to climate change. In this study, we utilized an integrated modeling framework that includes the Weather Research Forecasting (WRF) model and a high resolution distributed hydrology soil vegetation model (DHSVM) to simulate probable maximum precipitation (PMP) and flood (PMF) events over Alabama-Coosa-Tallapoosa River Basin. A total of 120 storms were selected to simulate moisture maximized PMP under different meteorological forcings, including historical storms driven by Climate Forecast System Reanalysis (CFSR) and baseline (1981-2010), near term future (2021-2050) and long term future (2071-2100) storms driven by Community Climate System Model version 4 (CCSM4) under Representative Concentrations Pathway 8.5 emission scenario. We also analyzed the sensitivity of PMF to various antecedent hydrologic conditions such as initial soil moisture conditions and tested different compulsive approaches. Overall, a statistical significant increase is projected for future PMP and PMF, mainly attributed to the increase of background air temperature. The ensemble of simulated PMP and PMF along with their sensitivity allows us to better quantify the potential risks associated with hydro-climatic extreme events on critical energy-water infrastructures such as major hydropower dams and nuclear power plants.

Energy-balance climate models

NASA Technical Reports Server (NTRS)

North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

1980-01-01

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

Energy balance climate models

NASA Technical Reports Server (NTRS)

North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

1981-01-01

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

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

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

A Geographic Mosaic of Climate Change Impacts on Terrestrial Vegetation: Which Areas Are Most at Risk?

PubMed Central

Ackerly, David D.; Cornwell, William K.; Weiss, Stuart B.; Flint, Lorraine E.; Flint, Alan L.

2015-01-01

Changes in climate projected for the 21st century are expected to trigger widespread and pervasive biotic impacts. Forecasting these changes and their implications for ecosystem services is a major research goal. Much of the research on biotic responses to climate change has focused on either projected shifts in individual species distributions or broad-scale changes in biome distributions. Here, we introduce a novel application of multinomial logistic regression as a powerful approach to model vegetation distributions and potential responses to 21st century climate change. We modeled the distribution of 22 major vegetation types, most defined by a single dominant woody species, across the San Francisco Bay Area. Predictor variables included climate and topographic variables. The novel aspect of our model is the output: a vector of relative probabilities for each vegetation type in each location within the study domain. The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles. We found that sensitivity of vegetation to climate change is highly heterogeneous across the region. Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation. While such sites may provide refugia for mesic and cool-adapted vegetation in the face of a warming climate, the model suggests they will still be highly dynamic and relatively sensitive to climate-driven vegetation transitions. The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia. Projections provide a foundation for conservation planning and land management, and highlight the need for a greater understanding of the mechanisms and time scales of potential climate-driven vegetation transitions. PMID:26115485

US Food Security and Climate Change: Mid-Century Projections of Commodity Crop Production by the IMPACT Model

NASA Astrophysics Data System (ADS)

Takle, E. S.; Gustafson, D. I.; Beachy, R.; Nelson, G. C.; Mason-D'Croz, D.; Palazzo, A.

2013-12-01

Agreement is developing among agricultural scientists on the emerging inability of agriculture to meet growing global food demands. The lack of additional arable land and availability of freshwater have long been constraints on agriculture. Changes in trends of weather conditions that challenge physiological limits of crops, as projected by global climate models, are expected to exacerbate the global food challenge toward the middle of the 21st century. These climate- and constraint-driven crop production challenges are interconnected within a complex global economy, where diverse factors add to price volatility and food scarcity. We use the DSSAT crop modeling suite, together with mid-century projections of four AR4 global models, as input to the International Food Policy Research Institute IMPACT model to project the impact of climate change on food security through the year 2050 for internationally traded crops. IMPACT is an iterative model that responds to endogenous and exogenous drivers to dynamically solve for the world prices that ensure global supply equals global demand. The modeling methodology reconciles the limited spatial resolution of macro-level economic models that operate through equilibrium-driven relationships at a national level with detailed models of biophysical processes at high spatial resolution. The analysis presented here suggests that climate change in the first half of the 21st century does not represent a near-term threat to food security in the US due to the availability of adaptation strategies (e.g., loss of current growing regions is balanced by gain of new growing regions). However, as climate continues to trend away from 20th century norms current adaptation measures will not be sufficient to enable agriculture to meet growing food demand. Climate scenarios from higher-level carbon emissions exacerbate the food shortfall, although uncertainty in climate model projections (particularly precipitation) is a limitation to impact studies.

Erosion of Northern Hemisphere blanket peatlands under 21st-century climate change

NASA Astrophysics Data System (ADS)

Li, Pengfei; Holden, Joseph; Irvine, Brian; Mu, Xingmin

2017-04-01

Peatlands are important terrestrial carbon stores particularly in the Northern Hemisphere. Many peatlands, such as those in the British Isles, Sweden, and Canada, have undergone increased erosion, resulting in degraded water quality and depleted soil carbon stocks. It is unclear how climate change may impact future peat erosion. Here we use a physically based erosion model (Pan-European Soil Erosion Risk Assessment-PEAT), driven by seven different global climate models (GCMs), to predict fluvial blanket peat erosion in the Northern Hemisphere under 21st-century climate change. After an initial decline, total hemispheric blanket peat erosion rates are found to increase during 2070-2099 (2080s) compared with the baseline period (1961-1990) for most of the GCMs. Regional erosion variability is high with changes to baseline ranging between -1.27 and +21.63 t ha-1 yr-1 in the 2080s. These responses are driven by effects of temperature (generally more dominant) and precipitation change on weathering processes. Low-latitude and warm blanket peatlands are at most risk to fluvial erosion under 21st-century climate change.

(Un)certainty in climate change impacts on global energy consumption

NASA Astrophysics Data System (ADS)

van Ruijven, B. J.; De Cian, E.; Sue Wing, I.

2017-12-01

Climate change is expected to have an influence on the energy sector, especially on energy demand. For many locations, this change in energy demand is a balance between increase of demand for space cooling and a decrease of space heating demand. We perform a large-scale uncertainty analysis to characterize climate change risk on energy consumption as driven by climate and socioeconomic uncertainty. We combine a dynamic econometric model1 with multiple realizations of temperature projections from all 21 CMIP5 models (from the NASA Earth Exchange Global Daily Downscaled Projections2) under moderate (RCP4.5) and vigorous (RCP8.5) warming. Global spatial population projections for five SSPs are combined with GDP projections to construct scenarios for future energy demand driven by socioeconomic change. Between the climate models, we find a median global increase in climate-related energy demand of around 24% by 2050 under RCP8.5 with an interquartile range of 18-38%. Most climate models agree on increases in energy demand of more than 25% or 50% in tropical regions, the Southern USA and Southern China (see Figure). With respect to socioeconomic scenarios, we find wide variations between the SSPs for the number of people in low-income countries who are exposed to increases in energy demand. Figure attached: Number of models that agree on total climate-related energy consumption to increase or decrease by more than 0, 10, 25 or 50% by 2050 under RCP8.5 and SSP5 as result of the CMIP5 ensemble of temperature projections. References1. De Cian, E. & Sue Wing, I. Global Energy Demand in a Warming Climate. (FEEM, 2016). 2. Thrasher, B., Maurer, E. P., McKellar, C. & Duffy, P. B. Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol Earth Syst Sci 16, 3309-3314 (2012).

10Be in late deglacial climate simulated by ECHAM5-HAM - Part 2: Isolating the solar signal from 10Be deposition

NASA Astrophysics Data System (ADS)

Heikkilä, U.; Shi, X.; Phipps, S. J.; Smith, A. M.

2014-04-01

This study investigates the effect of deglacial climate on the deposition of the solar proxy 10Be globally, and at two specific locations, the GRIP site at Summit, Central Greenland, and the Law Dome site in coastal Antarctica. The deglacial climate is represented by three 30 year time slice simulations of 10 000 BP (years before present = 1950 CE), 11 000 and 12 000 BP, compared with a preindustrial control simulation. The model used is the ECHAM5-HAM atmospheric aerosol-climate model, driven with sea-surface temperatures and sea ice cover simulated using the CSIRO Mk3L coupled climate system model. The focus is on isolating the 10Be production signal, driven by solar variability, from the weather- or climate-driven noise in the 10Be deposition flux during different stages of climate. The production signal varies at lower frequencies, dominated by the 11 year solar cycle within the 30 year timescale of these experiments. The climatic noise is of higher frequencies than 11 years during the 30 year period studied. We first apply empirical orthogonal function (EOF) analysis to global 10Be deposition on the annual scale and find that the first principal component, consisting of the spatial pattern of mean 10Be deposition and the temporally varying solar signal, explains 64% of the variability. The following principal components are closely related to those of precipitation. Then, we apply ensemble empirical decomposition (EEMD) analysis to the time series of 10Be deposition at GRIP and at Law Dome, which is an effective method for adaptively decomposing the time series into different frequency components. The low-frequency components and the long-term trend represent production and have reduced noise compared to the entire frequency spectrum of the deposition. The high-frequency components represent climate-driven noise related to the seasonal cycle of e.g. precipitation and are closely connected to high frequencies of precipitation. These results firstly show that the 10Be atmospheric production signal is preserved in the deposition flux to surface even during climates very different from today's both in global data and at two specific locations. Secondly, noise can be effectively reduced from 10Be deposition data by simply applying the EOF analysis in the case of a reasonably large number of available data sets, or by decomposing the individual data sets to filter out high-frequency fluctuations.

Simulations of the Montréal urban heat island

NASA Astrophysics Data System (ADS)

Roberge, François; Sushama, Laxmi; Fanta, Gemechu

2017-04-01

The current population of Montreal is around 3.8 million and this number is projected to go up in the coming years to decades, which will lead to vast expansion of urban areas. It is well known that urban morphology impacts weather and climate, and therefore should be taken into consideration in urban planning. This is particularly important in the context of a changing climate, as the intensity and frequency of temperature extremes such as hot spells are projected to increase in future climate, and Urban Heat Island (UHI) can potentially raise already stressful temperatures during such events, which can have significant effects on human health and energy consumption. High-resolution regional climate model simulations can be utilized to understand better urban-weather/climate interactions in current and future climates, particularly the spatio-temporal characteristics of the Urban Heat Island and its impact on other weather/climate characteristics such as urban flows, precipitation etc. This paper will focus on two high-resolution (250 m) simulations performed with (1) the Canadian Land Surface Scheme (CLASS) and (2) CLASS and TEB (Town Energy Balance) model; TEB is a single layer urban canopy model and is used to model the urban fractions. The two simulations are performed over a domain covering Montreal for the 1960-2015 period, driven by atmospheric forcing data coming from a high-resolution Canadian Regional Climate Model (CRCM5) simulation, driven by ERA-Interim. The two simulations are compared to assess the impact of urban regions on selected surface fields and the simulation with both CLASS and TEB is then used to study the spatio-temporal characteristics of the UHI over the study domain. Some preliminary results from a coupled simulation, i.e. CRCM5+CLASS+TEB, for selected years, including extreme warm years, will also be presented.

Climate and air pollution impacts on habitat suitability of Austrian forest ecosystems

PubMed Central

Djukic, Ika; Kitzler, Barbara; Kobler, Johannes; Mol-Dijkstra, Janet P.; Posch, Max; Reinds, Gert Jan; Schlutow, Angela; Starlinger, Franz; Wamelink, Wieger G. W.

2017-01-01

Climate change and excess deposition of airborne nitrogen (N) are among the main stressors to floristic biodiversity. One particular concern is the deterioration of valuable habitats such as those protected under the European Habitat Directive. In future, climate-driven shifts (and losses) in the species potential distribution, but also N driven nutrient enrichment may threaten these habitats. We applied a dynamic geochemical soil model (VSD+) together with a novel niche-based plant response model (PROPS) to 5 forest habitat types (18 forest sites) protected under the EU Directive in Austria. We assessed how future climate change and N deposition might affect habitat suitability, defined as the capacity of a site to host its typical plant species. Our evaluation indicates that climate change will be the main driver of a decrease in habitat suitability in the future in Austria. The expected climate change will increase the occurrence of thermophilic plant species while decreasing cold-tolerant species. In addition to these direct impacts, climate change scenarios caused an increase of the occurrence probability of oligotrophic species due to a higher N immobilisation in woody biomass leading to soil N depletion. As a consequence, climate change did offset eutrophication from N deposition, even when no further reduction in N emissions was assumed. Our results show that climate change may have positive side-effects in forest habitats when multiple drivers of change are considered. PMID:28898262

Climate and air pollution impacts on habitat suitability of Austrian forest ecosystems.

PubMed

Dirnböck, Thomas; Djukic, Ika; Kitzler, Barbara; Kobler, Johannes; Mol-Dijkstra, Janet P; Posch, Max; Reinds, Gert Jan; Schlutow, Angela; Starlinger, Franz; Wamelink, Wieger G W

2017-01-01

Climate change and excess deposition of airborne nitrogen (N) are among the main stressors to floristic biodiversity. One particular concern is the deterioration of valuable habitats such as those protected under the European Habitat Directive. In future, climate-driven shifts (and losses) in the species potential distribution, but also N driven nutrient enrichment may threaten these habitats. We applied a dynamic geochemical soil model (VSD+) together with a novel niche-based plant response model (PROPS) to 5 forest habitat types (18 forest sites) protected under the EU Directive in Austria. We assessed how future climate change and N deposition might affect habitat suitability, defined as the capacity of a site to host its typical plant species. Our evaluation indicates that climate change will be the main driver of a decrease in habitat suitability in the future in Austria. The expected climate change will increase the occurrence of thermophilic plant species while decreasing cold-tolerant species. In addition to these direct impacts, climate change scenarios caused an increase of the occurrence probability of oligotrophic species due to a higher N immobilisation in woody biomass leading to soil N depletion. As a consequence, climate change did offset eutrophication from N deposition, even when no further reduction in N emissions was assumed. Our results show that climate change may have positive side-effects in forest habitats when multiple drivers of change are considered.

Bridging the Gap Between the iLEAPS and GEWEX Land-Surface Modeling Communities

NASA Technical Reports Server (NTRS)

Bonan, Gordon; Santanello, Joseph A., Jr.

2013-01-01

Models of Earth's weather and climate require fluxes of momentum, energy, and moisture across the land-atmosphere interface to solve the equations of atmospheric physics and dynamics. Just as atmospheric models can, and do, differ between weather and climate applications, mostly related to issues of scale, resolved or parameterised physics,and computational requirements, so too can the land models that provide the required surface fluxes differ between weather and climate models. Here, however, the issue is less one of scale-dependent parameterisations.Computational demands can influence other minor land model differences, especially with respect to initialisation, data assimilation, and forecast skill. However, the distinction among land models (and their development and application) is largely driven by the different science and research needs of the weather and climate communities.

Global peatland initiation driven by regionally asynchronous warming.

PubMed

Morris, Paul J; Swindles, Graeme T; Valdes, Paul J; Ivanovic, Ruza F; Gregoire, Lauren J; Smith, Mark W; Tarasov, Lev; Haywood, Alan M; Bacon, Karen L

2018-05-08

Widespread establishment of peatlands since the Last Glacial Maximum represents the activation of a globally important carbon sink, but the drivers of peat initiation are unclear. The role of climate in peat initiation is particularly poorly understood. We used a general circulation model to simulate local changes in climate during the initiation of 1,097 peatlands around the world. We find that peat initiation in deglaciated landscapes in both hemispheres was driven primarily by warming growing seasons, likely through enhanced plant productivity, rather than by any increase in effective precipitation. In Western Siberia, which remained ice-free throughout the last glacial period, the initiation of the world's largest peatland complex was globally unique in that it was triggered by an increase in effective precipitation that inhibited soil respiration and allowed wetland plant communities to establish. Peat initiation in the tropics was only weakly related to climate change, and appears to have been driven primarily by nonclimatic mechanisms such as waterlogging due to tectonic subsidence. Our findings shed light on the genesis and Holocene climate space of one of the world's most carbon-dense ecosystem types, with implications for understanding trajectories of ecological change under changing future climates.

Climate-driven ichthyoplankton drift model predicts growth of top predator young.

PubMed

Myksvoll, Mari S; Erikstad, Kjell E; Barrett, Robert T; Sandvik, Hanno; Vikebø, Frode

2013-01-01

Climate variability influences seabird population dynamics in several ways including access to prey near colonies during the critical chick-rearing period. This study addresses breeding success in a Barents Sea colony of common guillemots Uria aalge where trophic conditions vary according to changes in the northward transport of warm Atlantic Water. A drift model was used to simulate interannual variations in transport of cod Gadus morhua larvae along the Norwegian coast towards their nursery grounds in the Barents Sea. The results showed that the arrival of cod larvae from southern spawning grounds had a major effect on the size of common guillemot chicks at fledging. Furthermore, the fraction of larvae from the south was positively correlated to the inflow of Atlantic Water into the Barents Sea thus clearly demonstrating the mechanisms by which climate-driven bottom-up processes influence interannual variations in reproductive success in a marine top predator.

Climate-Driven Ichthyoplankton Drift Model Predicts Growth of Top Predator Young

PubMed Central

Myksvoll, Mari S.; Erikstad, Kjell E.; Barrett, Robert T.; Sandvik, Hanno; Vikebø, Frode

2013-01-01

Climate variability influences seabird population dynamics in several ways including access to prey near colonies during the critical chick-rearing period. This study addresses breeding success in a Barents Sea colony of common guillemots Uria aalge where trophic conditions vary according to changes in the northward transport of warm Atlantic Water. A drift model was used to simulate interannual variations in transport of cod Gadus morhua larvae along the Norwegian coast towards their nursery grounds in the Barents Sea. The results showed that the arrival of cod larvae from southern spawning grounds had a major effect on the size of common guillemot chicks at fledging. Furthermore, the fraction of larvae from the south was positively correlated to the inflow of Atlantic Water into the Barents Sea thus clearly demonstrating the mechanisms by which climate-driven bottom-up processes influence interannual variations in reproductive success in a marine top predator. PMID:24265761

Mitigating the Impacts of Climate Nonstationarity on Seasonal Streamflow Predictability in the U.S. Southwest

NASA Astrophysics Data System (ADS)

Lehner, Flavio; Wood, Andrew W.; Llewellyn, Dagmar; Blatchford, Douglas B.; Goodbody, Angus G.; Pappenberger, Florian

2017-12-01

Seasonal streamflow predictions provide a critical management tool for water managers in the American Southwest. In recent decades, persistent prediction errors for spring and summer runoff volumes have been observed in a number of watersheds in the American Southwest. While mostly driven by decadal precipitation trends, these errors also relate to the influence of increasing temperature on streamflow in these basins. Here we show that incorporating seasonal temperature forecasts from operational global climate prediction models into streamflow forecasting models adds prediction skill for watersheds in the headwaters of the Colorado and Rio Grande River basins. Current dynamical seasonal temperature forecasts now show sufficient skill to reduce streamflow forecast errors in snowmelt-driven regions. Such predictions can increase the resilience of streamflow forecasting and water management systems in the face of continuing warming as well as decadal-scale temperature variability and thus help to mitigate the impacts of climate nonstationarity on streamflow predictability.

Short-lived halocarbons efficient at influencing climate through ozone loss in the upper troposphere-lower stratosphere

NASA Astrophysics Data System (ADS)

Hossaini, Ryan; Chipperfield, Martyn; Montzka, Steven; Rap, Alex; Dhomse, Sandip; Feng, Wuhu

2015-04-01

Halogenated very short-lived substances (VSLS) of both natural and anthropogenic origin are a significant source of atmospheric bromine, chlorine and iodine. Due to relatively short atmospheric lifetimes (typically <6 months), VSLS breakdown in the upper troposphere-lower stratosphere (UTLS), where ozone perturbations drive a disproportionately large climate impact compared to other altitudes. Here we present chemical transport model simulations that quantify VSLS-driven ozone loss in the UTLS and infer the climate relevance of these ozone perturbations using a radiative transfer model. Our results indicate that through their impact on UTLS ozone, VSLS are efficient at influencing climate. We calculate a whole atmosphere global mean radiative effect (RE) of -0.20 (-0.16 to -0.23) Wm-2 from natural and anthropogenic VSLS-driven ozone loss, including a tropospheric contribution of -0.12 Wm-2. In the stratosphere, the RE due to ozone loss from natural bromine-containing VSLS (e.g. CHBr3, CH2Br2) is almost half of that from long-lived anthropogenic compounds (e.g. CFCs) and normalized by equivalent chlorine is ~4 times larger. We show that the anthropogenic chlorine-containing VSLS, not regulated by the Montreal Protocol, also contribute to ozone loss in the UTLS and that the atmospheric concentration of dichloromethane (CH2Cl2), the most abundant of these, is increasing rapidly. Finally, we present evidence that VSLS have made a small yet previously unrecognized contribution to the ozone-driven radiative forcing of climate since pre-industrial times of -0.02 (-0.01 to -0.03) Wm-2. Given the climate leverage that VSLS possess, future increases to their emissions, either through continued industrial or altered natural processes, may be important for future climate forcing.

A Curriculum Experiment in Climate Change Education Using an Integrated Approach of Content Knowledge Instruction and Student-Driven Research, Year 2

NASA Astrophysics Data System (ADS)

Adams, P. E.; Heinrichs, J. F.

2010-12-01

One of the greatest challenges facing the world is climate change. Coupled with this challenge is an under-informed population that has not received a rigorous education about climate change other than what is available through the media. Fort Hays State University is in a second year of piloting a course on climate change targeted to students early in their academic careers. The course is modeled after our past work (NSF DUE-0088818) of integrating content knowledge instruction and student-driven research where there was a positive correlation between student research engagement and student knowledge gains. The second pilot offering utilizes a mix of inquiry-based instruction, problem-based learning, and student-driven research to educate and engage the students in understanding climate change. The course was collaboratively developed by a geoscientist and science educator both of whom are active in citizen science programs. The course model is unique in that 50% of the course is dedicated to developing core knowledge and technical skills (e.g. global climate change, critical analysis, writing, data acquisition, data representation, and research design), and 50% to conducting a research project using available data sets from federal agencies and research groups. A key element of the course is a focus on data sets to make climate change relevant to the students. The research serves as a means of civic engagement by the students as they are tasked to understand their role in communicating their research findings to the community and coping with the local and regional changes they find through their research. The impacts of course changes from the first offering to the second offering of the course will be reported, as well as the structure of the course.

Vegetation-climate feedbacks modulate rainfall patterns in Africa under future climate change

NASA Astrophysics Data System (ADS)

Wu, Minchao; Schurgers, Guy; Rummukainen, Markku; Smith, Benjamin; Samuelsson, Patrick; Jansson, Christer; Siltberg, Joe; May, Wilhelm

2016-07-01

Africa has been undergoing significant changes in climate and vegetation in recent decades, and continued changes may be expected over this century. Vegetation cover and composition impose important influences on the regional climate in Africa. Climate-driven changes in vegetation structure and the distribution of forests versus savannah and grassland may feed back to climate via shifts in the surface energy balance, hydrological cycle and resultant effects on surface pressure and larger-scale atmospheric circulation. We used a regional Earth system model incorporating interactive vegetation-atmosphere coupling to investigate the potential role of vegetation-mediated biophysical feedbacks on climate dynamics in Africa in an RCP8.5-based future climate scenario. The model was applied at high resolution (0.44 × 0.44°) for the CORDEX-Africa domain with boundary conditions from the CanESM2 general circulation model. We found that increased tree cover and leaf-area index (LAI) associated with a CO2 and climate-driven increase in net primary productivity, particularly over subtropical savannah areas, not only imposed important local effect on the regional climate by altering surface energy fluxes but also resulted in remote effects over central Africa by modulating the land-ocean temperature contrast, Atlantic Walker circulation and moisture inflow feeding the central African tropical rainforest region with precipitation. The vegetation-mediated feedbacks were in general negative with respect to temperature, dampening the warming trend simulated in the absence of feedbacks, and positive with respect to precipitation, enhancing rainfall reduction over the rainforest areas. Our results highlight the importance of accounting for vegetation-atmosphere interactions in climate projections for tropical and subtropical Africa.

Enabling data-driven provenance in NetCDF, via OGC WPS operations. Climate Analysis services use case.

NASA Astrophysics Data System (ADS)

Mihajlovski, A.; Spinuso, A.; Plieger, M.; Som de Cerff, W.

2016-12-01

Modern Climate analysis platforms provide generic and standardized ways of accessing data and processing services. These are typically supported by a wide range of OGC formats and interfaces. However, the problem of instrumentally tracing the lineage of the transformations occurring on a dataset and its provenance remains an open challenge. It requires standard-driven and interoperable solutions to facilitate understanding, sharing of self-describing data products, fostering collaboration among peers. The CLIPC portal provided us real use case, where the need of an instrumented provenance management is fundamental. CLIPC provides a single point of access for scientific information on climate change. The data about the physical environment which is used to inform climate change policy and adaptation measures comes from several categories: satellite measurements, terrestrial observing systems, model projections and simulations and from re-analyses. This is made possible through the Copernicus Earth Observation Programme for Europe. With a backbone combining WPS and OPeNDAP services, CLIPC has two themes: 1. Harmonized access to climate datasets derived from models, observations and re-analyses 2. A climate impact tool kit to evaluate, rank and aggregate indicators The climate impact tool kit is realised with the orchestration of a number of WPS that ingest, normalize and combine NetCDF files. The WPS allowing this specific computation are hosted by the climate4impact portal, which is a more generic climate data-access and processing service. In this context, guaranteeing validation and reproducibility of results, is a clearly stated requirement to improve the quality of the results obtained by the combined analysis Two core contributions made, are the enabling of a provenance wrapper around WPS services and the enabling of provenance tracing within the NetCDF format, which adopts and extends the W3C's PROV model. To disseminate indicator data and create transformed data products, a standardized provenance, metadata and processing infrastructure is researched for CLIPC. These efforts will lead towards the provision of tools for further web service processing development and optimisation, opening up possibilities to scale and administer abstract users and data driven workflows.

Vegetation-mediated Climate Impacts on Historical and Future Ozone Air Quality

NASA Astrophysics Data System (ADS)

Tai, A. P. K.; Fu, Y.; Mickley, L. J.; Heald, C. L.; Wu, S.

2014-12-01

Changes in climate, natural vegetation and human land use are expected to significantly influence air quality in the coming century. These changes and their interactions have important ramifications for the effectiveness of air pollution control strategies. In a series of studies, we use a one-way coupled modeling framework (GEOS-Chem driven by different combinations of historical and future meteorological, land cover and emission data) to investigate the effects of climate-vegetation changes on global and East Asian ozone air quality from 30 years ago to 40 years into the future. We find that future climate and climate-driven vegetation changes combine to increase summertime ozone by 2-6 ppbv in populous regions of the US, Europe, East Asia and South Asia by year 2050, but including the interaction between CO2 and biogenic isoprene emission reduces the climate impacts by more than half. Land use change such as cropland expansion has the potential to either mostly offset the climate-driven ozone increases (e.g., in the US and Europe), or greatly increase ozone (e.g., in Southeast Asia). The projected climate-vegetation effects in East Asia are particularly uncertain, reflecting a less understood ozone production regime. We thus further study how East Asian ozone air quality has evolved since the early 1980s in response to climate, vegetation and emission changes to shed light on its likely future course. We find that warming alone has led to a substantial increase in summertime ozone in populous regions by 1-4 ppbv. Despite significant cropland expansion and urbanization, increased summertime leafiness of vegetation in response to warming and CO2 fertilization has reduced ozone by 1-2 ppbv, driven by enhanced ozone deposition dominating over elevated biogenic emission and partially offsetting the warming effect. The historical role of CO2-isoprene interaction in East Asia, however, remains highly uncertain. Our findings demonstrate the important roles of land cover and vegetation in modulating climate-chemistry interactions, and highlight aspects that warrant further investigation.

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

A water resources model to explore the implications of energy alternatives in the southwestern US

NASA Astrophysics Data System (ADS)

Yates, D.; Averyt, Kristen; Flores-Lopez, Francisco; Meldrum, J.; Sattler, S.; Sieber, J.; Young, C.

2013-12-01

This letter documents the development and validation of a climate-driven, southwestern-US-wide water resources planning model that is being used to explore the implications of extended drought and climate warming on the allocation of water among competing uses. These model uses include a separate accounting for irrigated agriculture; municipal indoor use based on local population and per-capita consumption; climate-driven municipal outdoor turf and amenity watering; and thermoelectric cooling. The model simulates the natural and managed flows of rivers throughout the southwest, including the South Platte, the Arkansas, the Colorado, the Green, the Salt, the Sacramento, the San Joaquin, the Owens, and more than 50 others. Calibration was performed on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. Goodness of fit statistics and other measures of performance are shown for a select number of locations and are used to summarize the model’s ability to represent monthly streamflow, reservoir storages, surface and ground water deliveries, etc, under 1980-2010 levels of sectoral water use.

Constraints on long-term carbon-climate feedbacks from spatially resolved CO2 growth rate fluctuations linked to temperature and precipitation

NASA Astrophysics Data System (ADS)

Keppel-Aleks, G.; Hoffman, F. M.

2014-12-01

Feedbacks between the global carbon cycle and climate represent one of the largest uncertainties in climate prediction. A promising method for reducing uncertainty in predictions of carbon-climate feedbacks is based on identifying an "emergent constraint" that leverages correlations between mechanistically linked long-term feedbacks and short-term variations within the model ensemble. By applying contemporary observations to evaluate model skill in simulating short-term variations, we may be able to better assess the probability of simulated long-term feedbacks. We probed the constraint on long-term terrestrial carbon stocks provided by climate-driven fluctuations in the atmospheric CO2 growth rate at contemporary timescales. We considered the impact of both temperature and precipitation anomalies on terrestrial ecosystem exchange and further separated the direct influence of fire where possible. When we explicitly considered the role of atmospheric transport in smoothing the imprint of climate-driven flux anomalies on atmospheric CO2 patterns, we found that the extent of temporal averaging of both the observations and ESM output leads to estimates for the long-term climate sensitivity of tropical land carbon storage that are different by a factor of two. In the context of these results, we discuss strategies for applying emergent constraints for benchmarking biogeochemical feedbacks in ESMs. Specifically, our results underscore the importance of selecting appropriate observational benchmarks and, for future model intercomparison projects, outputting fields that most closely correspond to available observational datasets.

Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

NASA Astrophysics Data System (ADS)

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, P.; Williams, C.; Ardö, J.; Boucher, M.; Cappelaere, B.; de Grandcourt, A.; Nickless, A.; Nouvellon, Y.; Scholes, R.; Kutsch, W.

2013-03-01

Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

Transient climate-carbon simulations of planetary geoengineering.

PubMed

Matthews, H Damon; Caldeira, Ken

2007-06-12

Geoengineering (the intentional modification of Earth's climate) has been proposed as a means of reducing CO2-induced climate warming while greenhouse gas emissions continue. Most proposals involve managing incoming solar radiation such that future greenhouse gas forcing is counteracted by reduced solar forcing. In this study, we assess the transient climate response to geoengineering under a business-as-usual CO2 emissions scenario by using an intermediate-complexity global climate model that includes an interactive carbon cycle. We find that the climate system responds quickly to artificially reduced insolation; hence, there may be little cost to delaying the deployment of geoengineering strategies until such a time as "dangerous" climate change is imminent. Spatial temperature patterns in the geoengineered simulation are comparable with preindustrial temperatures, although this is not true for precipitation. Carbon sinks in the model increase in response to geoengineering. Because geoengineering acts to mask climate warming, there is a direct CO2-driven increase in carbon uptake without an offsetting temperature-driven suppression of carbon sinks. However, this strengthening of carbon sinks, combined with the potential for rapid climate adjustment to changes in solar forcing, leads to serious consequences should geoengineering fail or be stopped abruptly. Such a scenario could lead to very rapid climate change, with warming rates up to 20 times greater than present-day rates. This warming rebound would be larger and more sustained should climate sensitivity prove to be higher than expected. Thus, employing geoengineering schemes with continued carbon emissions could lead to severe risks for the global climate system.

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.

2015-07-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealized, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all models showing an increase in surface temperature focussed in the Northern Hemisphere mid and (especially) high latitudes, and showing a corresponding increase in global mean precipitation. Changes in precipitation patterns are driven mostly by a northward shift in the ITCZ (Intertropical Convergence Zone), consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker response, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.; Samset, B. H.

2015-02-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealised, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all three models showing an increase in surface temperature focussed in the northern hemisphere high latitudes, and a corresponding increase in global mean precipitation and run-off. Changes in precipitation and run-off patterns are driven mostly by a northward shift in the ITCZ, consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker forcing signal, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

Rainfall extremes, weather and climatic characterization over complex terrain: A data-driven approach based on signal enhancement methods and extreme value modeling

NASA Astrophysics Data System (ADS)

Pineda, Luis E.; Willems, Patrick

2017-04-01

Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather and climate drivers, allows identification of well-known features of the regional climate in a purely data-driven fashion. Thus, this approach shows potential for characterization of precipitation extremes in data-scarce and orographically complex regions in which model reconstructions are the only climate proxies References [1] Mínguez, R., F.J. Méndez, C. Izaguirre, M. Menéndez, and I.J. Losada (2010), Pseudooptimal parameter selection of non-stationary generalized extreme value models for environmental variables, Environ. Modell. Softw. 25, 1592-1607. [2] Pineda, L., P. Willems (2016), Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific-Andean River Basins in Ecuador and Peru using a non-homogenous hidden Markov model, J. Hydrometeor, 17(2), 481-498, doi:10.1175/JHM-D-15-0040.1, http://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0040.1

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

PubMed Central

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

2012-01-01

Simple Summary Parasitic helminths represent one of the most pervasive challenges to livestock, and their intensity and distribution will be influenced by climate change. There is a need for long-term predictions to identify potential risks and highlight opportunities for control. We explore the approaches to modelling future helminth risk to livestock under climate change. One of the limitations to model creation is the lack of purpose driven data collection. We also conclude that models need to include a broad view of the livestock system to generate meaningful predictions. Abstract Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed. PMID:26486780

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Genomic signals of selection predict climate-driven population declines in a migratory bird.

PubMed

Bay, Rachael A; Harrigan, Ryan J; Underwood, Vinh Le; Gibbs, H Lisle; Smith, Thomas B; Ruegg, Kristen

2018-01-05

The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler ( Setophaga petechia ). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts. Copyright © 2018, American Association for the Advancement of Science.

Evaluating the impact of chemical boundary conditions on near surface ozone in regional climate-air quality simulations over Europe

NASA Astrophysics Data System (ADS)

Akritidis, D.; Zanis, P.; Katragkou, E.; Schultz, M. G.; Tegoulias, I.; Poupkou, A.; Markakis, K.; Pytharoulis, I.; Karacostas, Th.

2013-12-01

A modeling system based on the air quality model CAMx driven off-line by the regional climate model RegCM3 is used for assessing the impact of chemical lateral boundary conditions (LBCs) on near surface ozone over Europe for the period 1996-2000. The RegCM3 and CAMx simulations were performed on a 50 km × 50 km grid over Europe with RegCM3 driven by the NCEP meteorological reanalysis fields and CAMx with chemical LBCs from ECHAM5/MOZART global model. The recent past period (1996-2000) was simulated in three experiments. The first simulation was forced using time and space invariant LBCs, the second was based on ECHAM5/MOZART chemical LBCs fixed for the year 1996 and the third was based on ECHAM5/MOZART chemical LBCs with interannual variability. Anthropogenic and biogenic emissions were kept identical for the three sensitivity runs.

Forest response to elevated CO2 is conserved across a broad range of productivity

Treesearch

R. Norby; E. DeLucia; B. Gielen; C. Calfapietra; C. Giardina; J. King; J. Ledford; H. McCarthy; D. Moore; R. Ceulemans; P. De Angelis; A. C. Finzi; D. F. Karnosky; M. E. Kubiske; M. Lukac; K. S. Pregitzer; G. E. Scarascia-Mugnozza; W. Schlesinger and R. Oren.

2005-01-01

Climate change predictions derived from coupled carbon-climate models are highly dependent on assumptions about feedbacks between the biosphere and atmosphere. One critical feedback occurs if C uptake by the biosphere increases in response to the fossil-fuel driven increase in atmospheric [CO2] ("CO2 fertilization...

Effects of Topography-driven Micro-climatology on Evaporation

NASA Astrophysics Data System (ADS)

Adams, D. D.; Boll, J.; Wagenbrenner, N. S.

2017-12-01

The effects of spatial-temporal variation of climatic conditions on evaporation in micro-climates are not well defined. Current spatially-based remote sensing and modeling for evaporation is limited for high resolutions and complex topographies. We investigated the effect of topography-driven micro-climatology on evaporation supported by field measurements and modeling. Fourteen anemometers and thermometers were installed in intersecting transects over the complex topography of the Cook Agronomy Farm, Pullman, WA. WindNinja was used to create 2-D vector maps based on recorded observations for wind. Spatial analysis of vector maps using ArcGIS was performed for analysis of wind patterns and variation. Based on field measurements, wind speed and direction show consequential variability based on hill-slope location in this complex topography. Wind speed and wind direction varied up to threefold and more than 45 degrees, respectively for a given time interval. The use of existing wind models enables prediction of wind variability over the landscape and subsequently topography-driven evaporation patterns relative to wind. The magnitude of the spatial-temporal variability of wind therefore resulted in variable evaporation rates over the landscape. These variations may contribute to uneven crop development patterns observed during the late growth stages of the agricultural crops at the study location. Use of hill-slope location indexes and appropriate methods for estimating actual evaporation support development of methodologies to better define topography-driven heterogeneity in evaporation. The cumulative effects of spatially-variable climatic factors on evaporation are important to quantify the localized water balance and inform precision farming practices.

Characterizing bias correction uncertainty in wheat yield predictions

NASA Astrophysics Data System (ADS)

Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam

2017-04-01

Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models.

Quantifying the effect of trend, fluctuation, and extreme event of climate change on ecosystem productivity.

PubMed

Liu, Yupeng; Yu, Deyong; Su, Yun; Hao, Ruifang

2014-12-01

Climate change comprises three fractions of trend, fluctuation, and extreme event. Assessing the effect of climate change on terrestrial ecosystem requires an understanding of the action mechanism of these fractions, respectively. This study examined 11 years of remotely sensed-derived net primary productivity (NPP) to identify the impacts of the trend and fluctuation of climate change as well as extremely low temperatures caused by a freezing disaster on ecosystem productivity in Hunan province, China. The partial least squares regression model was used to evaluate the contributions of temperature, precipitation, and photosynthetically active radiation (PAR) to NPP variation. A climatic signal decomposition and contribution assessment model was proposed to decompose climate factors into trend and fluctuation components. Then, we quantitatively evaluated the contributions of each component of climatic factors to NPP variation. The results indicated that the total contribution of the temperature, precipitation, and PAR to NPP variation from 2001 to 2011 in Hunan province is 85 %, and individual contributions of the temperature, precipitation, and PAR to NPP variation are 44 % (including 34 % trend contribution and 10 % fluctuation contribution), 5 % (including 4 % trend contribution and 1 % fluctuation contribution), and 36 % (including 30 % trend contribution and 6 % fluctuation contribution), respectively. The contributions of temperature fluctuation-driven NPP were higher in the north and lower in the south, and the contributions of precipitation trend-driven NPP and PAR fluctuation-driven NPP are higher in the west and lower in the east. As an instance of occasionally triggered disturbance in 2008, extremely low temperatures and a freezing disaster produced an abrupt decrease of NPP in forest and grass ecosystems. These results prove that the climatic trend change brought about great impacts on ecosystem productivity and that climatic fluctuations and extreme events can also alter the ecosystem succession process, even resulting in an alternative trajectory. All of these findings could improve our understanding of the impacts of climate change on the provision of ecosystem functions and services and can also provide a basis for policy makers to apply adaptive measures to overcome the unfavorable influence of climate change.

A Curriculum Experiment in Climate Change Education Using and Integrated Approach of Content Knowledge Instruction and Student-Driven Research to Promote Civic Engagement

NASA Astrophysics Data System (ADS)

Adams, P. E.; Heinrichs, J. F.

2009-12-01

One of the greatest challenges facing the world is climate change. Coupled with this challenge is an under-informed population that has not received a rigorous education about climate change other than what is available through the media. Fort Hays State University is piloting a course on climate change targeted to students early in their academic careers. The course is modeled after our past work (NSF DUE-0088818) of integrating content knowledge instruction and student-driven research where there was a positive correlation between student research engagement and student knowledge gains. The current course, based on prior findings, utilizes a mix of inquiry-based instruction, problem-based learning, and student-driven research to educate and engage the students in understanding climate change. The course was collaboratively developed by a geoscientist and science educator both of whom are active in citizen science programs. The emphasis on civic engagement by students is reflected in the course structure. The course model is unique in that 50% of the course is dedicated to developing core knowledge and technical skills (e.g. critical analysis, writing, data acquisition, data representation, and research design), and 50% to conducting a research project using available data sets from federal agencies and research groups. A key element of the course is a focus on local and regional data sets to make climate change relevant to the students. The research serves as a means of civic engagement by the students as they are tasked to understand their role in communicating their research findings to the community and coping with the local and regional changes they find through their research.

Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

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

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less

Effects of fire suppression under a changing climate in Pacific Northwest mixed-pine forests

NASA Astrophysics Data System (ADS)

Hanan, E. J.; Tague, C.; Bart, R. R.; Kennedy, M. C.; Abatzoglou, J. T.; Kolden, C.; Adam, J. C.

2017-12-01

The frequency of large and severe wildfires has increased over recent decades in many regions across the Western U.S., including the Pacific and Inland Northwest. This increase is likely driven in large part by wildfire suppression, which has promoted fuel accumulation in western landscapes. Recent studies also suggest that anthropogenic climate change intensifies wildfire activity by increasing fuel aridity. However, the contribution of these drivers to observed changes in fire regime is not well quantified at regional scales. Understanding the relative influence of climate and fire suppression is crucial for both projecting the effects of climate change on future fire spread, and for developing site-specific fuel management strategies under a new climate paradigm. To quantify the extent to which fire suppression and climate change have contributed to increases in wildfire activity in the Pacific Northwest, we conduct a modeling experiment using the ecohydrologic model RHESSys and the coupled stochastic fire spread model WMFire. Specifically, we use historical climate inputs from GCMs, combined with fire suppression scenarios to gauge the extent to which these drivers promote the spread of severe wildfires in Johnson Creek, a large (565-km2) mixed-pine dominated subcatchment of the Southfork Salmon River; part of the larger Columbia River Basin. We run 500 model iterations for suppressed, intermediate, and unsuppressed fire management scenarios, both with and without climate change in a factorial design, focusing on fire spread surrounding two extreme fire years in Johnson Creek (1998 and 2007). After deriving fire spread "fingerprints" for each combination of possible drivers, we evaluate the extent to which these fingerprints match observations in the fire record. We expect that climate change plays a role in the spread of large and severe wildfires in Johnson Creek, but the magnitude of this effect is mediated by prior suppression. Preliminary results suggest that management strategies aimed at reducing the extent of contiguous even-aged fuels may help curtail climate-driven increases in wildfire severity in Pacific Northwest watersheds.

The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines

NASA Astrophysics Data System (ADS)

Quataert, Ellen; Storlazzi, Curt; Rooijen, Arnold; Cheriton, Olivia; Dongeren, Ap

2015-08-01

A numerical model, XBeach, calibrated and validated on field data collected at Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands, was used to examine the effects of different coral reef characteristics on potential coastal hazards caused by wave-driven flooding and how these effects may be altered by projected climate change. The results presented herein suggest that coasts fronted by relatively narrow reefs with steep fore reef slopes (~1:10 and steeper) and deeper, smoother reef flats are expected to experience the highest wave runup. Wave runup increases for higher water levels (sea level rise), higher waves, and lower bed roughness (coral degradation), which are all expected effects of climate change. Rising sea levels and climate change will therefore have a significant negative impact on the ability of coral reefs to mitigate the effects of coastal hazards in the future.

The influence of coral reefs and climate change on wave-driven flooding of tropical coastlines

USGS Publications Warehouse

Quataert, Ellen; Storlazzi, Curt; van Rooijen, Arnold; van Dongeren, Ap; Cheriton, Olivia

2015-01-01

A numerical model, XBeach, calibrated and validated on field data collected at Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands, was used to examine the effects of different coral reef characteristics on potential coastal hazards caused by wave-driven flooding and how these effects may be altered by projected climate change. The results presented herein suggest that coasts fronted by relatively narrow reefs with steep fore reef slopes (~1:10 and steeper) and deeper, smoother reef flats are expected to experience the highest wave runup. Wave runup increases for higher water levels (sea level rise), higher waves, and lower bed roughness (coral degradation), which are all expected effects of climate change. Rising sea levels and climate change will therefore have a significant negative impact on the ability of coral reefs to mitigate the effects of coastal hazards in the future.

Chemical reaction path modeling of hydrothermal processes on Mars: Preliminary results

NASA Technical Reports Server (NTRS)

Plumlee, Geoffrey S.; Ridley, W. Ian

1992-01-01

Hydrothermal processes are thought to have had significant roles in the development of surficial mineralogies and morphological features on Mars. For example, a significant proportion of the Martian soil could consist of the erosional products of hydrothermally altered impact melt sheets. In this model, impact-driven, vapor-dominated hydrothermal systems hydrothermally altered the surrounding rocks and transported volatiles such as S and Cl to the surface. Further support for impact-driven hydrothermal alteration on Mars was provided by studies of the Ries crater, Germany, where suevite deposits were extensively altered to montmorillonite clays by inferred low-temperature (100-130 C) hydrothermal fluids. It was also suggested that surface outflow from both impact-driven and volcano-driven hydrothermal systems could generate the valley networks, thereby eliminating the need for an early warm wet climate. We use computer-driven chemical reaction path calculation to model chemical processes which were likely associated with postulated Martian hydrothermal systems.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

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

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

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

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Bioenergetic response by steelhead to variation in diet, thermal habitat, and climate in the north Pacific Ocean

USGS Publications Warehouse

Atcheson, Margaret E.; Myers, Katherine W.; Beauchamp, David A.; Mantua, Nathan J.

2012-01-01

Energetic responses of steelhead Oncorhynchus mykiss to climate-driven changes in marine conditions are expected to affect the species’ ocean distribution, feeding, growth, and survival. With a unique 18-year data series (1991–2008) for steelhead sampled in the open ocean, we simulated interannual variation in prey consumption and growth efficiency of steelhead using a bioenergetics model to evaluate the temperature-dependent growth response of steelhead to past climate events and to estimate growth potential of steelhead under future climate scenarios. Our results showed that annual ocean growth of steelhead is highly variable depending on prey quality, consumption rates, total consumption, and thermal experience. At optimal growing temperatures, steelhead can compensate for a low-energy diet by increasing consumption rates and consuming more prey, if available. Our findings suggest that steelhead have a narrow temperature window in which to achieve optimal growth, which is strongly influenced by climate-driven changes in ocean temperature.

Late Noachian Climate Of Mars: Constraints From Valley Network System Formation Times And The Intermittencies (Episodic/Periodic And Punctuated).

NASA Astrophysics Data System (ADS)

Head, James

2017-04-01

Formation of Late Noachian-Early Hesperian (LN-EH) valley network systems (VNS) signaled the presence of warm/wet conditions generating several hypotheses for climates permissive of these conditions. To constrain options for the ambient Noachian climate, we examine estimates for time required to carve channels/deltas and total duration implied by plausible intermittencies. Formation Times for VN, OBL, Deltas, Fans: A synthesis of required timescales show that even with the longest estimated continuous duration of VN formation/intermittencies, total time to carve the VN does not exceed 106 years, <˜0.25% of the total Noachian. Intermittency/episodicity assumptions are climate-model dependent (e.g., most workers use Earth-like fluvial activity and intermittency). Noachian-Early Hesperian Climate Models: 1) Warm and wet/semiarid/arid climate: Sustained background MAT >273 K, hydrological system vertically integrated, and rainfall occurs to recharge the aquifer. Two subtypes: a) "Rainfall/Fluvial Erosion-Dominated Warm and Wet Model": "Rainfall and surface runoff" persist throughout Noachian to explain crater degradation, and a LN-EH short rapidly ending terminal epoch. b) "Recharge Evaporation/Evaporite Dominated Warm and Wet Model": Sustained period of equatorial/mid-latitude precipitation and a vertically integrated hydrological system driven by evaporative upwelling and fluctuating shallow water table playa environments account for sulfate evaporate environments at Meridiani Planum. Sustained temperatures >273 K are required for extended periods (107-108 years). 2) Cold and icy climate: Sustained background temperatures extremely low (MAT ˜225 K), cryosphere is globally continuous, hydrological system is horizontally stratified, separating groundwater system from surface; no combination of spin-axis/orbital perturbations can raise MAT to 273 K. Adiabatic cooling effects transfer water to high altitudes, leading to "Late Noachian Icy Highlands Model". VNS cannot form in this nominal climate environment without special circumstances (e.g., impacts or volcanic eruptions elevate of temperatures by >˜50 K to induce melting and fluvial/lacustrine activity). 3) Cold and Icy climate warmed by greenhouse gases: The climate is sustained cold/icy model, but greenhouse gases of unspecified nature/amount/duration elevate MAT by several tens of Kelvins (say 25 K, to MAT 250 K), bringing annual temperature range into the realm where peak seasonal temperatures (PST) exceed 273 K. In this climate environment, analogous to the Antarctic Dry Valleys, seasonal summer temperatures above 273 K are sufficient to melt snow/ice and form fluvial and lacustrine features, but MAT is well below 273 K (253 K). Fluvial systems driven by episodic/periodic intermittency typically involve short intermittency time-scales (10-106 years) but require a warm climate (MAT >273 K) to be sustained for >0.4 x 109 years. Fluvial systems driven by punctuated intermittency typically involve short duration time-scales (10-105 years) but only require a warm climate (MAT >273 K) for the very short duration of the climatic impact of the punctuated event (102-105 years). We conclude that a cold and icy background climate with punctuated intermittency of warming and melting events is consistent with: 1) the estimated durations of continuous VN formation (<105 years) and 2) VN system estimated recurrence rates (106-107 years).

Historical anthropogenic radiative forcing of changes in biogenic secondary aerosol

NASA Astrophysics Data System (ADS)

Acosta Navarro, Juan; D'Andrea, Stephen; Pierce, Jeffrey; Ekman, Annica; Struthers, Hamish; Zorita, Eduardo; Guenther, Alex; Arneth, Almut; Smolander, Sampo; Kaplan, Jed; Farina, Salvatore; Scott, Catherine; Rap, Alexandru; Farmer, Delphine; Spracklen, Domink; Riipinen, Ilona

2016-04-01

Human activities have lead to changes in the energy balance of the Earth and the global climate. Changes in atmospheric aerosols are the second largest contributor to climate change after greenhouse gases since 1750 A.D. Land-use practices and other environmental drivers have caused changes in the emission of biogenic volatile organic compounds (BVOCs) and secondary organic aerosol (SOA) well before 1750 A.D, possibly causing climate effects through aerosol-radiation and aerosol-cloud interactions. Two numerical emission models LPJ-GUESS and MEGAN were used to quantify the changes in aerosol forming BVOC emissions in the past millennium. A chemical transport model of the atmosphere (GEOS-Chem-TOMAS) was driven with those BVOC emissions to quantify the effects on radiation caused by millennial changes in SOA. We found that global isoprene emissions decreased after 1800 A.D. by about 12% - 15%. This decrease was dominated by losses of natural vegetation, whereas monoterpene and sesquiterpene emissions increased by about 2% - 10%, driven mostly by rising surface air temperatures. From 1000 A.D. to 1800 A.D, isoprene, monoterpene and sesquiterpene emissions decline by 3% - 8% driven by both, natural vegetation losses, and the moderate global cooling between the medieval climate anomaly and the little ice age. The millennial reduction in BVOC emissions lead to a 0.5% to 2% reduction in climatically relevant aerosol particles (> 80 nm) and cause a direct radiative forcing between +0.02 W/m² and +0.07 W/m², and an indirect radiative forcing between -0.02 W/m² and +0.02 W/m².

Thermokarst transformation of permafrost preserved glaciated landscapes.

NASA Astrophysics Data System (ADS)

Kokelj, S.; Tunnicliffe, J. F.; Fraser, R.; Kokoszka, J.; Lacelle, D.; Lantz, T. C.; Lamoureux, S. F.; Rudy, A.; Shakil, S.; Tank, S. E.; van der Sluijs, J.; Wolfe, S.; Zolkos, S.

2017-12-01

Thermokarst is the fundamental mechanism of landscape change and a primary driver of downstream effects in a warming circumpolar world. Permafrost degradation is inherently non-linear because latent heat effects can inhibit thawing. However, once this thermal transition is crossed thermokarst can accelerate due to the interaction of thermal, physical and ecological feedbacks. In this paper we highlight recent climate and precipitation-driven intensification of thaw slumping that is transforming permafrost preserved glaciated landscapes in northwestern Canada. The continental distribution of slump affected terrain reflects glacial extents and recessional positions of the Laurentide Ice sheet. On this basis and in conjunction with intense thermokarst in cold polar environments, we highlight the critical roles of geological legacy and climate history in dictating the sensitivity of permafrost terrain. These glaciated landscapes, maintained in a quasi-stable state throughout much of the late Holocene are now being transformed into remarkably dynamic environments by climate-driven thermokarst. Individual disturbances displace millions of cubic metres of previously frozen material downslope, converting upland sedimentary stores into major source areas. Precipitation-driven evacuation of sediment by fluidized mass flows perpetuates non-linear enlargement of disturbances. The infilling of valleys with debris deposits tens of metres thick increases stream base-levels and promotes rapid valley-side erosion. These processes destabilize adjacent slopes and proliferate disturbance effects. Physically-based modeling of thaw slump development provides insight into the trajectories of landscape change, and the mapping of fluvial linkages portrays the cascade of effects across watershed scales. Post-glacial or "paraglacial" models of landscape evolution provide a useful framework for understanding the nature and magnitude of climate-driven changes in permafrost preserved glaciated landscapes.

Potential influence of wildfire in modulating climate-induced forest redistribution in a central Rocky Mountain landscape

USGS Publications Warehouse

Campbell, John L.; Shinneman, Douglas

2017-01-01

IntroductionClimate change is expected to impose significant tension on the geographic distribution of tree species. Yet, tree species range shifts may be delayed by their long life spans, capacity to withstand long periods of physiological stress, and dispersal limitations. Wildfire could theoretically break this biological inertia by killing forest canopies and facilitating species redistribution under changing climate. We investigated the capacity of wildfire to modulate climate-induced tree redistribution across a montane landscape in the central Rocky Mountains under three climate scenarios (contemporary and two warmer future climates) and three wildfire scenarios (representing historical, suppressed, and future fire regimes).MethodsDistributions of four common tree species were projected over 90 years by pairing a climate niche model with a forest landscape simulation model that simulates species dispersal, establishment, and mortality under alternative disturbance regimes and climate scenarios.ResultsThree species (Douglas-fir, lodgepole pine, subalpine fir) declined in abundance over time, due to climate-driven contraction in area suitable for establishment, while one species (ponderosa pine) was unable to exploit climate-driven expansion of area suitable for establishment. Increased fire frequency accelerated declines in area occupied by Douglas-fir, lodgepole pine, and subalpine fir, and it maintained local abundance but not range expansion of ponderosa pine.ConclusionsWildfire may play a larger role in eliminating these conifer species along trailing edges of their distributions than facilitating establishment along leading edges, in part due to dispersal limitations and interspecific competition, and future populations may increasingly depend on persistence in locations unfavorable for their establishment.

A comparison of fisheries biological reference points estimated from temperature-specific multi-species and single-species climate-enhanced stock assessment models

NASA Astrophysics Data System (ADS)

Holsman, Kirstin K.; Ianelli, James; Aydin, Kerim; Punt, André E.; Moffitt, Elizabeth A.

2016-12-01

Multi-species statistical catch at age models (MSCAA) can quantify interacting effects of climate and fisheries harvest on species populations, and evaluate management trade-offs for fisheries that target several species in a food web. We modified an existing MSCAA model to include temperature-specific growth and predation rates and applied the modified model to three fish species, walleye pollock (Gadus chalcogrammus), Pacific cod (Gadus macrocephalus) and arrowtooth flounder (Atheresthes stomias), from the eastern Bering Sea (USA). We fit the model to data from 1979 through 2012, with and without trophic interactions and temperature effects, and use projections to derive single- and multi-species biological reference points (BRP and MBRP, respectively) for fisheries management. The multi-species model achieved a higher over-all goodness of fit to the data (i.e. lower negative log-likelihood) for pollock and Pacific cod. Variability from water temperature typically resulted in 5-15% changes in spawning, survey, and total biomasses, but did not strongly impact recruitment estimates or mortality. Despite this, inclusion of temperature in projections did have a strong effect on BRPs, including recommended yield, which were higher in single-species models for Pacific cod and arrowtooth flounder that included temperature compared to the same models without temperature effects. While the temperature-driven multi-species model resulted in higher yield MBPRs for arrowtooth flounder than the same model without temperature, we did not observe the same patterns in multi-species models for pollock and Pacific cod, where variability between harvest scenarios and predation greatly exceeded temperature-driven variability in yield MBRPs. Annual predation on juvenile pollock (primarily cannibalism) in the multi-species model was 2-5 times the annual harvest of adult fish in the system, thus predation represents a strong control on population dynamics that exceeds temperature-driven changes to growth and is attenuated through harvest-driven reductions in predator populations. Additionally, although we observed differences in spawning biomasses at the accepted biological catch (ABC) proxy between harvest scenarios and single- and multi-species models, discrepancies in spawning stock biomass estimates did not translate to large differences in yield. We found that multi-species models produced higher estimates of combined yield for aggregate maximum sustainable yield (MSY) targets than single species models, but were more conservative than single-species models when individual MSY targets were used, with the exception of scenarios where minimum biomass thresholds were imposed. Collectively our results suggest that climate and trophic drivers can interact to affect MBRPs, but for prey species with high predation rates, trophic- and management-driven changes may exceed direct effects of temperature on growth and predation. Additionally, MBRPs are not inherently more conservative than single-species BRPs. This framework provides a basis for the application of MSCAA models for tactical ecosystem-based fisheries management decisions under changing climate conditions.

Process model simulations of the divergence effect

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Evans, M. N.; D'Arrigo, R. D.; Smerdon, J. E.; Hughes, M. K.; Kaplan, A.; Vaganov, E. A.

2007-12-01

We explore the extent to which the Vaganov-Shashkin (VS) model of conifer tree-ring formation can explain evidence for changing relationships between climate and tree growth over recent decades. The VS model is driven by daily environmental forcing (temperature, soil moisture, and solar radiation), and simulates tree-ring growth cell-by-cell as a function of the most limiting environmental control. This simplified representation of tree physiology allows us to examine using a selection of case studies whether instances of divergence may be explained in terms of changes in limiting environmental dependencies or transient climate change. Identification of model-data differences permits further exploration of the effects of tree-ring standardization, atmospheric composition, and additional non-climatic factors.

Climate conditions and drought assessment with the Palmer Drought Severity Index in Iran: evaluation of CORDEX South Asia climate projections (2070-2099)

NASA Astrophysics Data System (ADS)

Senatore, Alfonso; Hejabi, Somayeh; Mendicino, Giuseppe; Bazrafshan, Javad; Irannejad, Parviz

2018-03-01

Climate change projections were evaluated over both the whole Iran and six zones having different precipitation regimes considering the CORDEX South Asia dataset, for assessing space-time distribution of drought occurrences in the future period 2070-2099 under RCP4.5 scenario. Initially, the performances of eight available CORDEX South Asia Regional Climate Models (RCMs) were assessed for the baseline period 1970-2005 through the GPCC v.7 precipitation dataset and the CFSR temperature dataset, which were previously selected as the most reliable within a set of five global datasets compared to 41 available synoptic stations. Though the CCLM RCM driven by the MPI-ESM-LR General Circulation Model is in general the most suitable for temperature and, together with the REMO 2009 RCM also driven by MPI-ESM-LR, for precipitation, their performances do not overwhelm other models for every season and zone in which Iranian territory was divided according to a principal component analysis approach. Hence, a weighting approach was tested and adopted to take into account useful information from every RCM in each of the six zones. The models resulting more reliable compared to current climate show a strong precipitation decrease. Weighted average predicts an overall yearly precipitation decrease of about 20%. Temperature projections provide a mean annual increase of 2.4 °C. Future drought scenarios were depicted by means of the self-calibrating version of the Palmer drought severity index (SC-PDSI) model. Weighted average predicts a sharp drying that can be configured as a real shift in mean climate conditions, drastically affecting water resources of the country.

High Resolution Modelling of Crop Response to Climate Change

NASA Astrophysics Data System (ADS)

Mirmasoudi, S. S.; Byrne, J. M.; MacDonald, R. J.; Lewis, D.

2014-12-01

Crop production is one of the most vulnerable sectors to climatic variability and change. Increasing atmospheric CO2 concentration and other greenhouse gases are causing increases in global temperature. In western North America, water supply is largely derived from mountain snowmelt. Climate change will have a significant impact on mountain snowpack and subsequently, the snow-derived water supply. This will strain water supplies and increase water demand in areas with substantial irrigation agriculture. Increasing temperatures may create heat stress for some crops regardless of soil water supply, and increasing surface O3 and other pollutants may damage crops and ecosystems. CO2 fertilization may or may not be an advantage in future. This work is part of a larger study that will address a series of questions based on a range of future climate scenarios for several watersheds in western North America. The key questions are: (1) how will snowmelt and rainfall runoff vary in future; (2) how will seasonal and inter-annual soil water supply vary, and how might that impacts food supplies; (3) how might heat stress impact (some) crops even with adequate soil water; (4) will CO2 fertilization alter crop yields; and (5) will pollution loads, particularly O3, cause meaningful changes to crop yields? The Generate Earth Systems Science (GENESYS) Spatial Hydrometeorological Model is an innovative, efficient, high-resolution model designed to assess climate driven changes in mountain snowpack derived water supplies. We will link GENESYS to the CROPWAT crop model system to assess climate driven changes in water requirement and associated crop productivity for a range of future climate scenarios. Literature bases studies will be utilised to develop approximate crop response functions for heat stress, CO2 fertilization and for O3 damages. The overall objective is to create modeling systems that allows meaningful assessment of agricultural productivity at a watershed scale under a range of climate scenarios.

A model of strength

USGS Publications Warehouse

Johnson, Douglas H.; Cook, R.D.

2013-01-01

In her AAAS News & Notes piece "Can the Southwest manage its thirst?" (26 July, p. 362), K. Wren quotes Ajay Kalra, who advocates a particular method for predicting Colorado River streamflow "because it eschews complex physical climate models for a statistical data-driven modeling approach." A preference for data-driven models may be appropriate in this individual situation, but it is not so generally, Data-driven models often come with a warning against extrapolating beyond the range of the data used to develop the models. When the future is like the past, data-driven models can work well for prediction, but it is easy to over-model local or transient phenomena, often leading to predictive inaccuracy (1). Mechanistic models are built on established knowledge of the process that connects the response variables with the predictors, using information obtained outside of an extant data set. One may shy away from a mechanistic approach when the underlying process is judged to be too complicated, but good predictive models can be constructed with statistical components that account for ingredients missing in the mechanistic analysis. Models with sound mechanistic components are more generally applicable and robust than data-driven models.

Tectonic-driven climate change and the diversification of angiosperms.

PubMed

Chaboureau, Anne-Claire; Sepulchre, Pierre; Donnadieu, Yannick; Franc, Alain

2014-09-30

In 1879, Charles Darwin characterized the sudden and unexplained rise of angiosperms during the Cretaceous as an "abominable mystery." The diversification of this clade marked the beginning of a rapid transition among Mesozoic ecosystems and floras formerly dominated by ferns, conifers, and cycads. Although the role of environmental factors has been suggested [Coiffard C, Gómez B (2012) Geol Acta 10(2):181-188], Cretaceous global climate change has barely been considered as a contributor to angiosperm radiation, and focus was put on biotic factors to explain this transition. Here we use a fully coupled climate model driven by Mesozoic paleogeographic maps to quantify and discuss the impact of continental drift on angiosperm expansion and diversification. We show that the decrease of desertic belts between the Triassic and the Cretaceous and the subsequent onset of long-lasting humid conditions during the Late Cretaceous were driven by the breakup of Pangea and were contemporaneous with the first rise of angiosperm diversification. Positioning angiosperm-bearing fossil sites on our paleobioclimatic maps shows a strong match between the location of fossil-rich outcrops and temperate humid zones, indicating that climate change from arid to temperate dominance may have set the stage for the ecological expansion of flowering plants.

A weather-driven model of malaria transmission.

PubMed

Hoshen, Moshe B; Morse, Andrew P

2004-09-06

Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.

Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models

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

Fu, Weiwei; Randerson, James T.; Moore, J. Keith

We examine climate change impacts on net primary production (NPP) and export production (sinking particulate flux; EP) with simulations from nine Earth system models (ESMs) performed in the framework of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Global NPP and EP are reduced by the end of the century for the intense warming scenario of Representative Concentration Pathway (RCP) 8.5. Relative to the 1990s, NPP in the 2090s is reduced by 2–16% and EP by 7–18%. The models with the largest increases in stratification (and largest relative declines in NPP and EP) also show the largest positivemore » biases in stratification for the contemporary period, suggesting overestimation of climate change impacts on NPP and EP. All of the CMIP5 models show an increase in stratification in response to surface–ocean warming and freshening, which is accompanied by decreases in surface nutrients, NPP and EP. There is considerable variability across the models in the magnitudes of NPP, EP, surface nutrient concentrations and their perturbations by climate change. The negative response of NPP and EP to increasing stratification reflects primarily a bottom-up control, as upward nutrient flux declines at the global scale. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP. This pattern is driven by phytoplankton community composition shifts, with reductions in productivity by large phytoplankton as smaller phytoplankton (which export less efficiently) are favored under the increasing nutrient stress. Thus, the projections of the NPP response to climate change are critically dependent on the simulated phytoplankton community structure, the efficiency of the biological pump and the resulting levels of regenerated production, which vary widely across the models. In conclusion, community structure is represented simply in the CMIP5 models, and should be expanded to better capture the spatial patterns and climate-driven changes in export efficiency.« less

Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models

DOE PAGES

Fu, Weiwei; Randerson, James T.; Moore, J. Keith

2016-09-16

We examine climate change impacts on net primary production (NPP) and export production (sinking particulate flux; EP) with simulations from nine Earth system models (ESMs) performed in the framework of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Global NPP and EP are reduced by the end of the century for the intense warming scenario of Representative Concentration Pathway (RCP) 8.5. Relative to the 1990s, NPP in the 2090s is reduced by 2–16% and EP by 7–18%. The models with the largest increases in stratification (and largest relative declines in NPP and EP) also show the largest positivemore » biases in stratification for the contemporary period, suggesting overestimation of climate change impacts on NPP and EP. All of the CMIP5 models show an increase in stratification in response to surface–ocean warming and freshening, which is accompanied by decreases in surface nutrients, NPP and EP. There is considerable variability across the models in the magnitudes of NPP, EP, surface nutrient concentrations and their perturbations by climate change. The negative response of NPP and EP to increasing stratification reflects primarily a bottom-up control, as upward nutrient flux declines at the global scale. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP. This pattern is driven by phytoplankton community composition shifts, with reductions in productivity by large phytoplankton as smaller phytoplankton (which export less efficiently) are favored under the increasing nutrient stress. Thus, the projections of the NPP response to climate change are critically dependent on the simulated phytoplankton community structure, the efficiency of the biological pump and the resulting levels of regenerated production, which vary widely across the models. In conclusion, community structure is represented simply in the CMIP5 models, and should be expanded to better capture the spatial patterns and climate-driven changes in export efficiency.« less

System Dynamics to Climate-Driven Water Budget Analysis in the Eastern Snake Plains Aquifer

NASA Astrophysics Data System (ADS)

Ryu, J.; Contor, B.; Wylie, A.; Johnson, G.; Allen, R. G.

2010-12-01

Climate variability, weather extremes and climate change continue to threaten the sustainability of water resources in the western United States. Given current climate change projections, increasing temperature is likely to modify the timing, form, and intensity of precipitation events, which consequently affect regional and local hydrologic cycles. As a result, drought, water shortage, and subsequent water conflicts may become an increasing threat in monotone hydrologic systems in arid lands, such as the Eastern Snake Plain Aquifer (ESPA). The ESPA, in particular, is a critical asset in the state of Idaho. It is known as the economic lifeblood for more than half of Idaho’s population so that water resources availability and aquifer management due to climate change is of great interest, especially over the next few decades. In this study, we apply system dynamics as a methodology with which to address dynamically complex problems in ESPA’s water resources management. Aquifer recharge and discharge dynamics are coded in STELLA modeling system as input and output, respectively to identify long-term behavior of aquifer responses to climate-driven hydrological changes.

Response of salt-marsh carbon accumulation to climate change.

PubMed

Kirwan, Matthew L; Mudd, Simon M

2012-09-27

About half of annual marine carbon burial takes place in shallow water ecosystems where geomorphic and ecological stability is driven by interactions between the flow of water, vegetation growth and sediment transport. Although the sensitivity of terrestrial and deep marine carbon pools to climate change has been studied for decades, there is little understanding of how coastal carbon accumulation rates will change and potentially feed back on climate. Here we develop a numerical model of salt marsh evolution, informed by recent measurements of productivity and decomposition, and demonstrate that competition between mineral sediment deposition and organic-matter accumulation determines the net impact of climate change on carbon accumulation in intertidal wetlands. We find that the direct impact of warming on soil carbon accumulation rates is more subtle than the impact of warming-driven sea level rise, although the impact of warming increases with increasing rates of sea level rise. Our simulations suggest that the net impact of climate change will be to increase carbon burial rates in the first half of the twenty-first century, but that carbon-climate feedbacks are likely to diminish over time.

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Hydroregime prediction models for ephemeral groundwater-driven sinkhole wetlands: a planning tool for climate change and amphibian conservation

Treesearch

C. H. Greenberg; S. Goodrick; J. D. Austin; B. R. Parresol

2015-01-01

Hydroregimes of ephemeral wetlands affect reproductive success of many amphibian species and are sensitive to altered weather patterns associated with climate change.We used 17 years of weekly temperature, precipitation, and waterdepth measurements for eight small, ephemeral, groundwaterdriven sinkhole wetlands in Florida sandhills to develop a hydroregime predictive...

Effect of climate fluctuation on long-term vegetation dynamics in Carolina bay wetlands

Treesearch

Chrissa Stroh; Diane De Steven; Glenn Guntenspergen

2008-01-01

Carolina bays and similar depression wetlands of the U. S. Southeastern Coastal Plain have hydrologic regimes that are driven primarily by rainfall. Therefore, climate fluctuations such as drought cycles have the potential to shape long-term vegetation dynamics. Models suggest two potential long-term responses to hydrologic fluctuations, either cyclic change...

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

PubMed

MacLeod, D A; Morse, A P

2014-12-02

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk

NASA Astrophysics Data System (ADS)

MacLeod, D. A.; Morse, A. P.

2014-12-01

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Predicting Chronic Climate-Driven Disturbances and Their Mitigation

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

McDowell, Nate G.; Michaletz, Sean T.; Bennett, Katrina E.

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

Predicting Chronic Climate-Driven Disturbances and Their Mitigation

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

McDowell, Nate G.; Michaletz, Sean T.; Bennett, Katrina E.

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

Predicting Chronic Climate-Driven Disturbances and Their Mitigation

DOE PAGES

McDowell, Nate G.; Michaletz, Sean T.; Bennett, Katrina E.; ...

2017-11-13

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

Fast and Slow Precipitation Responses to Individual Climate Forcers: A PDRMIP Multimodel Study

NASA Technical Reports Server (NTRS)

Samset, B. H.; Myhre, G.; Forster, P.M.; Hodnebrog, O.; Andrews, T.; Faluvegi, G.; Flaschner, D.; Kasoar, M.; Kharin, V.; Kirkevag, A.;

[Research on quality regionalization of cultivated Pseudostellaria heterophylla based on climate factors].

PubMed

Kang, Chuan-Zhi; Zhou, Tao; Jiang, Wei-Ke; Guo, Lan-Ping; Zhang, Xiao-Bo; Xiao, Cheng-Hong; Zhao, Dan

2016-07-01

Maxent model was applied in the study to filtering the climate factors layer by layer. Polysaccharides and pseudostellarin B the two internal quality evaluation index were combined to analyse the interlinkages between climate factors and chemical constituents in order to search for the critical climate factors of Pseudostellaria heterophylla. Then based on the key climate factors to explicit the quality spatial distribution of P. heterophylla. The results showed that polysaccharides and climatic factors had no significant correlation, suggesting that the indicator was not climate-driven metabolites. Pseudostellarin B could construct regression model with the precipitation. And quality regionalization results showed that pseudostellarin B content presented firstly increased and then decreased trend from southeast to northwest, which was the consistent change with precipitation. It clearly proposed that precipitation was the key climate factor, which affected the accumulation of cyclopeptide compound for Pseudostellariae Radix. Copyright© by the Chinese Pharmaceutical Association.

Climate Change, the Energy-water-food Nexus, and the "New" Colorado River Basin

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Bennett, K. E.; Solander, K.; Hopkins, E.

2017-12-01

Climate change, extremes, and climate-driven disturbances are anticipated to have substantial impacts on regional water resources, particularly in the western and southwestern United States. These unprecedented conditions—a no-analog future—will result in challenges to adaptation, mitigation, and resilience planning for the energy-water-food nexus. We have analyzed the impact of climate change on Colorado River flows for multiple climate and disturbance scenarios: 12 global climate models and two CO2 emission scenarios (RCP 4.5 and RCP 8.5) from the Intergovernmental Panel on Climate Change's Coupled Model Intercomparison Study, version 5, and multiple climate-driven forest disturbance scenarios including temperature-drought vegetation mortality and insect infestations. Results indicate a wide range of potential streamflow projections and the potential emergence of a "new" Colorado River basin. Overall, annual streamflow tends to increase under the majority of modeled scenarios due to projected increases in precipitation across the basin, though a significant number of scenarios indicate moderate and potentially substantial reductions in water availability. However, all scenarios indicate severe changes in seasonality of flows and strong variability across headwater systems. This leads to increased fall and winter streamflow, strong reductions in spring and summer flows, and a shift towards earlier snowmelt timing. These impacts are further exacerbated in headwater systems, which are key to driving Colorado River streamflow and hence water supply for both internal and external basin needs. These results shed a new and important slant on the Colorado River basin, where an emergent streamflow pattern may result in difficulties to adjust to these new regimes, resulting in increased stress to the energy-water-food nexus.

Evaluation of the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

2016-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.

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.

Land-use change may exacerbate climate change impacts on water resources in the Ganges basin

NASA Astrophysics Data System (ADS)

Tsarouchi, Gina; Buytaert, Wouter

2018-02-01

Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000-2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000-2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030-2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.

Impact of climate change and climate anomalies on hydrologic and biogeochemical processes in an agricultural catchment of the Chesapeake Bay watershed, USA.

PubMed

Wagena, Moges B; Collick, Amy S; Ross, Andrew C; Najjar, Raymond G; Rau, Benjamin; Sommerlot, Andrew R; Fuka, Daniel R; Kleinman, Peter J A; Easton, Zachary M

2018-05-16

Nutrient export from agricultural landscapes is a water quality concern and the cause of mitigation activities worldwide. Climate change impacts hydrology and nutrient cycling by changing soil moisture, stoichiometric nutrient ratios, and soil temperature, potentially complicating mitigation measures. This research quantifies the impact of climate change and climate anomalies on hydrology, nutrient cycling, and greenhouse gas emissions in an agricultural catchment of the Chesapeake Bay watershed. We force a calibrated model with seven downscaled and bias-corrected regional climate models and derived climate anomalies to assess their impact on hydrology and the export of nitrate (NO 3 -), phosphorus (P), and sediment, and emissions of nitrous oxide (N 2 O) and di-nitrogen (N 2 ). Model-average (±standard deviation) results indicate that climate change, through an increase in precipitation and temperature, will result in substantial increases in winter/spring flow (10.6 ± 12.3%), NO 3 - (17.3 ± 6.4%), dissolved P (32.3 ± 18.4%), total P (24.8 ± 16.9%), and sediment (25.2 ± 16.6%) export, and a slight increases in N 2 O (0.3 ± 4.8%) and N 2 (0.2 ± 11.8%) emissions. Conversely, decreases in summer flow (-29.1 ± 24.6%) and the export of dissolved P (-15.5 ± 26.4%), total P (-16.3 ± 20.7%), sediment (-20.7 ± 18.3%), and NO 3 - (-29.1 ± 27.8%) are driven by greater evapotranspiration from increasing summer temperatures. Decreases in N 2 O (-26.9 ± 15.7%) and N 2 (-36.6 ± 22.9%) are predicted in the summer and driven by drier soils. While the changes in flow are related directly to changes in precipitation and temperature, the changes in nutrient and sediment export are, to some extent, driven by changes in agricultural management that climate change induces, such as earlier spring tillage and altered nutrient application timing and by alterations to nutrient cycling in the soil. Copyright © 2018 Elsevier B.V. All rights reserved.

Statistical modeling of interannual shoreline change driven by North Atlantic climate variability spanning 2000-2014 in the Bay of Biscay

NASA Astrophysics Data System (ADS)

Robinet, A.; Castelle, B.; Idier, D.; Le Cozannet, G.; Déqué, M.; Charles, E.

2016-12-01

Modeling studies addressing daily to interannual coastal evolution typically relate shoreline change with waves, currents and sediment transport through complex processes and feedbacks. For wave-dominated environments, the main driver (waves) is controlled by the regional atmospheric circulation. Here a simple weather regime-driven shoreline model is developed for a 15-year shoreline dataset (2000-2014) collected at Truc Vert beach, Bay of Biscay, SW France. In all, 16 weather regimes (four per season) are considered. The centroids and occurrences are computed using the ERA-40 and ERA-Interim reanalyses, applying k-means and EOF methods to the anomalies of the 500-hPa geopotential height over the North Atlantic Basin. The weather regime-driven shoreline model explains 70% of the observed interannual shoreline variability. The application of a proven wave-driven equilibrium shoreline model to the same period shows that both models have similar skills at the interannual scale. Relation between the weather regimes and the wave climate in the Bay of Biscay is investigated and the primary weather regimes impacting shoreline change are identified. For instance, the winter zonal regime characterized by a strengthening of the pressure gradient between the Iceland low and the Azores high is associated with high-energy wave conditions and is found to drive an increase in the shoreline erosion rate. The study demonstrates the predictability of interannual shoreline change from a limited number of weather regimes, which opens new perspectives for shoreline change modeling and encourages long-term shoreline monitoring programs.

Ontology development for provenance tracing in National Climate Assessment of the US Global Change Research Program

NASA Astrophysics Data System (ADS)

Fu, Linyun; Ma, Xiaogang; Zheng, Jin; Goldstein, Justin; Duggan, Brian; West, Patrick; Aulenbach, Steve; Tilmes, Curt; Fox, Peter

2014-05-01

This poster will show how we used a case-driven iterative methodology to develop an ontology to represent the content structure and the associated provenance information in a National Climate Assessment (NCA) report of the US Global Change Research Program (USGCRP). We applied the W3C PROV-O ontology to implement a formal representation of provenance. We argue that the use case-driven, iterative development process and the application of a formal provenance ontology help efficiently incorporate domain knowledge from earth and environmental scientists in a well-structured model interoperable in the context of the Web of Data.

Surface Water and Energy Budgets for Sub-Saharan Africa in GFDL Coupled Climate Model

NASA Astrophysics Data System (ADS)

Tian, D.; Wood, E. F.; Vecchi, G. A.; Jia, L.; Pan, M.

2015-12-01

This study compare surface water and energy budget variables from the Geophysical Fluid Dynamics Laboratory (GFDL) FLOR models with the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), Princeton University Global Meteorological Forcing Dataset (PGF), and PGF-driven Variable Infiltration Capacity (VIC) model outputs, as well as available observations over the sub-Saharan Africa. The comparison was made for four configurations of the FLOR models that included FLOR phase 1 (FLOR-p1) and phase 2 (FLOR-p2) and two phases of flux adjusted versions (FLOR-FA-p1 and FLOR-FA-p2). Compared to p1, simulated atmospheric states in p2 were nudged to the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The seasonal cycle and annual mean of major surface water (precipitation, evapotranspiration, runoff, and change of storage) and energy variables (sensible heat, ground heat, latent heat, net solar radiation, net longwave radiation, and skin temperature) over a 34-yr period during 1981-2014 were compared in different regions in sub-Saharan Africa (West Africa, East Africa, and Southern Africa). In addition to evaluating the means in three sub-regions, empirical orthogonal functions (EOFs) analyses were conducted to compare both spatial and temporal characteristics of water and energy budget variables from four versions of GFDL FLOR, NCEP CFSR, PGF, and VIC outputs. This presentation will show how well each coupled climate model represented land surface physics and reproduced spatiotemporal characteristics of surface water and energy budget variables. We discuss what caused differences in surface water and energy budgets in land surface components of coupled climate model, climate reanalysis, and reanalysis driven land surface model. The comparisons will reveal whether flux adjustment and nudging would improve depiction of the surface water and energy budgets in coupled climate models.

Extreme climate events counteract the effects of climate and land-use changes in Alpine treelines

PubMed Central

Barros, Ceres; Guéguen, Maya; Douzet, Rolland; Carboni, Marta; Boulangeat, Isabelle; Zimmermann, Niklaus E.; Münkemüller, Tamara; Thuiller, Wilfried

2017-01-01

Summary 1. Climate change and extreme events, such as drought, threaten ecosystems worldwide and in particular mountain ecosystems, where species often live at their environmental tolerance limits. In the European Alps, plant communities are also influenced by land-use abandonment leading to woody encroachment of subalpine and alpine grasslands. 2. In this study, we explored how the forest–grassland ecotone of Alpine treelines will respond to gradual climate warming, drought events and land-use change in terms of forest expansion rates, taxonomic diversity and functional composition. We used a previously validated dynamic vegetation model, FATE-HD, parameterised for plant communities in the Ecrins National Park in the French Alps. 3. Our results showed that intense drought counteracted the forest expansion at higher elevations driven by land-use abandonment and climate change, especially when combined with high drought frequency (occurring every 2 or less than 2 years). 4. Furthermore, intense and frequent drought accelerated the rates of taxonomic change and resulted in overall higher taxonomic spatial heterogeneity of the ecotone than would be expected under gradual climate and land-use changes only. 5. Synthesis and applications. The results from our model show that intense and frequent drought counteracts forest expansion driven by climate and land-use changes in the forest–grassland ecotone of Alpine treelines. We argue that land-use planning must consider the effects of extreme events, such as drought, as well as climate and land-use changes, since extreme events might interfere with trends predicted under gradual climate warming and agricultural abandonment. PMID:28670002

Empirical evidence of climate's role in Rocky Mountain landscape evolution

NASA Astrophysics Data System (ADS)

Riihimaki, Catherine A.; Reiners, Peter W.

2012-06-01

Climate may be the dominant factor affecting landscape evolution during the late Cenozoic, but models that connect climate and landscape evolution cannot be tested without precise ages of landforms. Zircon (U-Th)/He ages of clinker, metamorphosed rock formed by burning of underlying coal seams, provide constraints on the spatial and temporal patterns of Quaternary erosion in the Powder River basin of Wyoming and Montana. The age distribution of 86 sites shows two temporal patterns: (1) a bias toward younger ages because of erosion of older clinker and (2) periodic occurrence of coal fires likely corresponding with particular climatic regimes. Statistical t tests of the ages and spectral analyses of the age probability density function indicate that these episodes of frequent coal fires most likely correspond with times of high eccentricity in Earth's orbit, possibly driven by increased seasonality in the region causing increased erosion rates and coal exhumation. Correlation of ages with interglacial time periods is weaker. The correlations between climate and coal fires improve when only samples greater than 50 km from the front of the Bighorn Range, the site of the nearest alpine glaciation, are compared. Together, these results indicate that the interaction between upstream glaciation and downstream erosion is likely not the dominant control on Quaternary landscape evolution in the Powder River basin, particularly since 0.5 Ma. Instead, incision rates are likely controlled by the response of streams to climate shifts within the basin itself, possibly changes in local precipitation rates or frequency-magnitude distributions, with no discernable lag time between climate changes and landscape responses. Clinker ages are consistent with numerical models in which stream erosion is driven by fluctuations in stream power on thousand year timescales within the basins, possibly as a result of changing precipitation patterns, and is driven by regional rock uplift on million year timescales.

Coupled Atmosphere-Surface Modeling of Lake Levels of the North American Great Lakes under Climate Change

NASA Astrophysics Data System (ADS)

Lofgren, B. M.; Xiao, C.

2016-12-01

The influence of projected climate change on the water levels of the Great Lakes is subject to considerable uncertainty, and methods that have long been used to determine this sensitivity have been discredited. A strong candidate, albeit expensive, to replace problematic methods is to use outputs that result from dynamical downscaling of future climate simulations, focused on the hydroclimate of the Great Lakes basin. We have produced initial estimates of Great Lakes water levels in the mid- and late 21st century using the Weather Research and Forecasting (WRF) model, including its lake module, driven by lateral boundary conditions from the Geophysical Fluid Dynamics Lab Climate Model version 3.0 (GFDL CM3), under RCP4.5 and 8.5 scenarios. Future lake levels are influenced by the balance between projected general increases in precipitation and increases in evapotranspiration from both land and lake in the basin, driven primarily by the surface radiative energy budget and secondarily by air temperature. The net result was drops in lake level of up to 15 cm, in contrast to the results from much-used older methods, which often projected drops exceeding 1 m. Future plans include increased detail in the simulation of water flow overland and in river channels using WRF-Hydro, and full coupling of regional atmospheric systems with 3-dimensional dynamical lake implementation of the Finite Volume Community Ocean Model (FVCOM).

A HYPOTHESIS-DRIVEN FRAMEWORK FOR ASSESSING ...

EPA Pesticide Factsheets

Understanding how climate change will alter the availability of coastal final ecosystem goods and services (FEGS; such as food provisioning from fisheries, property protection, and recreation) has significant implications for coastal planning and the development of adaptive management strategies to maximize sustainability of natural resources. The dynamic social and physical settings of these important resources means that there is not a “one-size-fits-all” model to predict the specific changes in coastal FEGS that will occur as a result of climate change. Instead, we propose a hypothesis-driven approach that builds on available literature to understand the likely effects of climate change on FEGS across coastal regions of the United States. We present an analysis for three FEGS: food provisioning from fisheries, recreation, and property protection. Hypotheses were restricted to changes precipitated by four prominent climate stressors projected in coastal areas: 1) sea-level rise, 2) ocean acidification, 3) increased temperatures, and 4) intensification of coastal storms. Our approach identified links between these stressors and the ecological processes that produce the FEGS, with the capacity to incorporate regional differences in FEGS availability. Linkages were first presented in a logic model to conceptualize the framework. For each region, we developed hypotheses regarding the effects of climate stressors on FEGS by examining case studies For example, w

Impacts of climate change on the formation and stability of late Quaternary sand sheets and falling dunes, Black Mesa region, southern Colorado Plateau, USA

USGS Publications Warehouse

Ellwein, Amy L.; Mahan, Shannon; McFadden, Leslie D.

2015-01-01

Widely used predictive models of eolian system dynamics are typically based entirely on climatic variables and do not account for landscape complexity and geomorphic history. Climate-only assumptions fail to give accurate predictions of the dynamics of this and many other dune fields. A growing body of work suggests that eolian deposits in wind-driven semiarid climates may be more strongly related to increases in sediment supply than to increases in aridity.

What is the importance of climate model bias when projecting the impacts of climate change on land surface processes?

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

Liu, M. L.; Rajagopalan, K.; Chung, S. H.

2014-05-16

Regional climate change impact (CCI) studies have widely involved downscaling and bias-correcting (BC) Global Climate Model (GCM)-projected climate for driving land surface models. However, BC may cause uncertainties in projecting hydrologic and biogeochemical responses to future climate due to the impaired spatiotemporal covariance of climate variables and a breakdown of physical conservation principles. Here we quantify the impact of BC on simulated climate-driven changes in water variables(evapotranspiration, ET; runoff; snow water equivalent, SWE; and water demand for irrigation), crop yield, biogenic volatile organic compounds (BVOC), nitric oxide (NO) emissions, and dissolved inorganic nitrogen (DIN) export over the Pacific Northwest (PNW)more » Region. We also quantify the impacts on net primary production (NPP) over a small watershed in the region (HJ Andrews). Simulation results from the coupled ECHAM5/MPI-OM model with A1B emission scenario were firstly dynamically downscaled to 12 km resolutions with WRF model. Then a quantile mapping based statistical downscaling model was used to downscale them into 1/16th degree resolution daily climate data over historical and future periods. Two series climate data were generated according to the option of bias-correction (i.e. with bias-correction (BC) and without bias-correction, NBC). Impact models were then applied to estimate hydrologic and biogeochemical responses to both BC and NBC meteorological datasets. These im20 pact models include a macro-scale hydrologic model (VIC), a coupled cropping system model (VIC-CropSyst), an ecohydrologic model (RHESSys), a biogenic emissions model (MEGAN), and a nutrient export model (Global-NEWS). Results demonstrate that the BC and NBC climate data provide consistent estimates of the climate-driven changes in water fluxes (ET, runoff, and water demand), VOCs (isoprene and monoterpenes) and NO emissions, mean crop yield, and river DIN export over the PNW domain. However, significant differences rise from projected SWE, crop yield from dry lands, and HJ Andrews’s ET between BC and NBC data. Even though BC post-processing has no significant impacts on most of the studied variables when taking PNW as a whole, their effects have large spatial variations and some local areas are substantially influenced. In addition, there are months during which BC and NBC post-processing produces significant differences in projected changes, such as summer runoff. Factor-controlled simulations indicate that BC post-processing of precipitation and temperature both substantially contribute to these differences at region scales. We conclude that there are trade-offs between using BC climate data for offline CCI studies vs. direct modeled climate data. These trade-offs should be considered when designing integrated modeling frameworks for specific applications; e.g., BC may be more important when considering impacts on reservoir operations in mountainous watersheds than when investigating impacts on biogenic emissions and air quality (where VOCs are a primary indicator).« less

A meteorologically driven maize stress indicator model

NASA Technical Reports Server (NTRS)

Taylor, T. W.; Ravet, F. W. (Principal Investigator)

1981-01-01

A maize soil moisture and temperature stress model is described which was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions in the major maize-producing areas of the world. The model also identifies optimum climatic conditions and planting/harvest problems associated with poor tractability.

Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers.

PubMed

Axelsen, Jacob Bock; Yaari, Rami; Grenfell, Bryan T; Stone, Lewi

2014-07-01

Human influenza occurs annually in most temperate climatic zones of the world, with epidemics peaking in the cold winter months. Considerable debate surrounds the relative role of epidemic dynamics, viral evolution, and climatic drivers in driving year-to-year variability of outbreaks. The ultimate test of understanding is prediction; however, existing influenza models rarely forecast beyond a single year at best. Here, we use a simple epidemiological model to reveal multiannual predictability based on high-quality influenza surveillance data for Israel; the model fit is corroborated by simple metapopulation comparisons within Israel. Successful forecasts are driven by temperature, humidity, antigenic drift, and immunity loss. Essentially, influenza dynamics are a balance between large perturbations following significant antigenic jumps, interspersed with nonlinear epidemic dynamics tuned by climatic forcing.

Climate-driven reduction in soil loss due to the dynamic role of vegetation

NASA Astrophysics Data System (ADS)

Constantine, J. A.; Ciampalini, R.; Walker-Springett, K.; Hales, T. C.; Ormerod, S.; Gabet, E. J.; Hall, I. R.

2016-12-01

Simulations of 21st century climate change predict increases in seasonal precipitation that may lead to widespread soil loss and reduced soil carbon stores by increasing the likelihood of surface runoff. Vegetation may counteract this increase through its dynamic response to climate change, possibly mitigating any impact on soil erosion. Here, we document for the first time the potential for vegetation to prevent widespread soil loss by surface-runoff mechanisms (i.e., rill and inter-rill erosion) by implementing a process-based soil erosion model across catchments of Great Britain with varying land-cover, topographic, and soil characteristics. Our model results reveal that, even under a significantly wetter climate, warmer air temperatures can limit soil erosion across areas with permanent vegetation cover because of its role in enhancing primary productivity, which improves leaf interception, soil infiltration-capacity, and the erosive resistance of soil. Consequently, any increase in air temperature associated with climate change will increase the threshold change in rainfall required to accelerate soil loss, and rates of soil erosion could therefore decline by up to 50% from 2070-2099 compared to baseline values under the IPCC-defined medium-emissions scenario SRES A1B. We conclude that enhanced primary productivity due to climate change can introduce a negative-feedback mechanism that limits soil loss by surface runoff as vegetation-induced impacts on soil hydrology and erodibility offset precipitation increases, highlighting the need to expand areas of permanent vegetation cover to reduce the potential for climate-driven soil loss.

Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge

NASA Astrophysics Data System (ADS)

Bakker, Pepijn; Clark, Peter U.; Golledge, Nicholas R.; Schmittner, Andreas; Weber, Michael E.

2017-01-01

Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods. Proposed explanations for the discrepancy include ocean-atmosphere coupling that is too weak in models, insufficient energy cascades from smaller to larger spatial and temporal scales, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations, and are likely to be important in future climate change. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.

Present-day and future Antarctic ice sheet climate and surface mass balance in the Community Earth System Model

DOE PAGES

Lenaerts, Jan T. M.; Vizcaino, Miren; Fyke, Jeremy Garmeson; ...

2016-02-01

Here, we present climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS) as simulated by the global, coupled ocean–atmosphere–land Community Earth System Model (CESM) with a horizontal resolution of ~1° in the past, present and future (1850–2100). CESM correctly simulates present-day Antarctic sea ice extent, large-scale atmospheric circulation and near-surface climate, but fails to simulate the recent expansion of Antarctic sea ice. The present-day Antarctic ice sheet SMB equals 2280 ± 131Gtyear –1, which concurs with existing independent estimates of AIS SMB. When forced by two CMIP5 climate change scenarios (high mitigation scenario RCP2.6 and high-emission scenariomore » RCP8.5), CESM projects an increase of Antarctic ice sheet SMB of about 70 Gtyear –1 per degree warming. This increase is driven by enhanced snowfall, which is partially counteracted by more surface melt and runoff along the ice sheet’s edges. This intensifying hydrological cycle is predominantly driven by atmospheric warming, which increases (1) the moisture-carrying capacity of the atmosphere, (2) oceanic source region evaporation, and (3) summer AIS cloud liquid water content.« less

Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

2005-12-01

In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.

Performance evaluation of a non-hydrostatic regional climate model over the Mediterranean/Black Sea area and climate projections for the XXI century

NASA Astrophysics Data System (ADS)

Mercogliano, Paola; Bucchignani, Edoardo; Montesarchio, Myriam; Zollo, Alessandra Lucia

2013-04-01

In the framework of the Work Package 4 (Developing integrated tools for environmental assessment) of PERSEUS Project, high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes the Mediterranean and Black Seas, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate trend but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Assessment of temperature and precipitation over Mediterranean Area and Black Sea with non hydrostatic high resolution regional climate model

NASA Astrophysics Data System (ADS)

Mercogliano, P.; Montesarchio, M.; Zollo, A.; Bucchignani, E.

2012-12-01

In the framework of the Italian GEMINA Project (program of expansion and development of the Euro-Mediterranean Center for Climate Change (CMCC), high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes all the Mediterranean Sea, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate patterns but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Explaining geographic gradients in winter selection of landscapes by boreal caribou with implications under global changes in Eastern Canada.

PubMed

Beguin, Julien; McIntire, Eliot J B; Fortin, Daniel; Cumming, Steven G; Raulier, Frédéric; Racine, Pierre; Dussault, Claude

2013-01-01

Many animal species exhibit broad-scale latitudinal or longitudinal gradients in their response to biotic and abiotic components of their habitat. Although knowing the underlying mechanism of these patterns can be critical to the development of sound measures for the preservation or recovery of endangered species, few studies have yet identified which processes drive the existence of geographical gradients in habitat selection. Using extensive spatial data of broad latitudinal and longitudinal extent, we tested three hypotheses that could explain the presence of geographical gradients in landscape selection of the endangered boreal woodland caribou (Rangifer tarandus caribou) during winter in Eastern Canadian boreal forests: 1) climate-driven selection, which postulates that geographic gradients are surrogates for climatic gradients; 2) road-driven selection, which proposes that boreal caribou adjust their selection for certain habitat classes as a function of proximity to roads; and 3) an additive effect of both roads and climate. Our data strongly supported road-driven selection over climate influences. Thus, direct human alteration of landscapes drives boreal caribou distribution and should likely remain so until the climate changes sufficiently from present conditions. Boreal caribou avoided logged areas two-fold more strongly than burnt areas. Limiting the spread of road networks and accounting for the uneven impact of logging compared to wildfire should therefore be integral parts of any habitat management plan and conservation measures within the range of the endangered boreal caribou. The use of hierarchical spatial models allowed us to explore the distribution of spatially-structured errors in our models, which in turn provided valuable insights for generating alternative hypotheses about processes responsible for boreal caribou distribution.

Ensemble tropical-extratropical cyclone coastal flood hazard assessment with climate change

NASA Astrophysics Data System (ADS)

Orton, P. M.; Lin, N.; Colle, B.

2016-12-01

A challenge with quantifying future changes in coastal flooding for the U.S. East Coast is that climate change has varying effects on different types of storms, in addition to raising mean sea levels. Moreover, future flood hazard uncertainties are large and come from many sources. Here, a new coastal flood hazard assessment approach is demonstrated that separately evaluates and then combines probabilities of storm tide generated from tropical cyclones (TCs) and extratropical cyclones (ETCs). The separation enables us to incorporate climate change impacts on both types of storms. The assessment accounts for epistemic storm tide uncertainty using an ensemble of different prior studies and methods of assessment, merged with uncertainty in climate change effects on storm tides and sea levels. The assessment is applied for New York Harbor, under the auspices of the New York City Panel on Climate Change (NPCC). In the New York Bight region and much of the U.S. East Coast, differing flood exceedance curve slopes for TCs and ETCs arise due to their differing physics. It is demonstrated how errors can arise for this region from mixing together storm types in an extreme value statistical analysis, a common practice when using observations. The effects of climate change on TC and ETC flooding have recently been assessed for this region, for TCs using a Global Climate Model (GCM) driven hurricane model with hydrodynamic modeling, and for ETCs using a GCM-driven multilinear regression-based storm surge model. The results of these prior studies are applied to our central estimates of the flood exceedance curve probabilities, transforming them for climate change effects. The results are useful for decision-makers because they highlight the large uncertainty in present-day and future flood risk, and also for scientists because they identify the areas where further research is most needed.

Projecting the future of an alpine ungulate under climate change scenarios.

PubMed

White, Kevin S; Gregovich, David P; Levi, Taal

2018-03-01

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key "early warning signs" about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37-year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate-driven effects influence mountain goat populations, we developed an age-structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70-year time window (2015-2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., "thermoneutral") summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%-86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate-linked bottom-up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence. © 2017 John Wiley & Sons Ltd.

An integrated land change model for projecting future climate and land change scenarios

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Lamsal, Aashis; Liu, Zhihua; Hawbaker, Todd J.

2013-01-01

Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.

Climate Change and the Long-term Viability of the World's Busiest Heavy Haul Ice Road

NASA Astrophysics Data System (ADS)

Mullan, D.

2016-12-01

Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world's busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR.

Climate change and the long-term viability of the World's busiest heavy haul ice road

NASA Astrophysics Data System (ADS)

Mullan, Donal; Swindles, Graeme; Patterson, Tim; Galloway, Jennifer; Macumber, Andrew; Falck, Hendrik; Crossley, Laura; Chen, Jie; Pisaric, Michael

2017-08-01

Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world's busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR.

Designing optimized multi-species monitoring networks to detect range shifts driven by climate change: a case study with bats in the North of Portugal.

PubMed

Amorim, Francisco; Carvalho, Sílvia B; Honrado, João; Rebelo, Hugo

2014-01-01

Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.

Elevated temperature alters carbon cycling in a model microbial community

NASA Astrophysics Data System (ADS)

Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

2013-12-01

Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.

Future drying of the southern Amazon and central Brazil

NASA Astrophysics Data System (ADS)

Yoon, J.; Zeng, N.; Cook, B.

2008-12-01

Recent climate modeling suggests that the Amazon rainforest could exhibit considerable dieback under future climate change, a prediction that has raised considerable interest as well as controversy. To determine the likelihood and causes of such changes, we analyzed the output of 15 models from the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC/AR4) and a dynamic vegetation model VEGAS driven by these climate output. Our results suggest that the core of the Amazon rainforest should remain largely stable. However, the periphery, notably the southern edge, is in danger of drying out, driven by two main processes. First, a decline in precipitation of 24% in the southern Amazon lengthens the dry season and reduces soil moisture, despite of an increase in precipitation during the wet season, due to the nonlinear response in hydrology and ecosystem dynamics. Two dynamical mechanisms may explain the lower dry season precipitation: (1) a stronger north-south tropical Atlantic sea surface temperature gradient; (2) a general subtropical drying under global warming when the dry season southern Amazon is under the control of the subtropical high pressure. Secondly, evaporation will increase due to the general warming, thus also reducing soil moisture. As a consequence, the median of the models projects a reduction of vegetation by 20%, and enhanced fire carbon flux by 10-15% in the southern Amazon, central Brazil, and parts of the Andean Mountains. Because the southern Amazon is also under intense human influence, the double pressure of deforestation and climate change may subject the region to dramatic changes in the 21st century.

The Martian climate: Energy balance models with CO2/H2O atmospheres

NASA Technical Reports Server (NTRS)

Hoffert, M. I.

1984-01-01

Progress in the development of a multi-reservoir, time dependent energy balance climate model for Mars driven by prescribed insolation at the top of the atmosphere is reported. The first approximately half-year of the program was devoted to assembling and testing components of the full model. Specific accomplishments were made on a longwave radiation code, coupling seasonal solar input to a ground temperature simulation, and conceptualizing an approach to modeling the seasonal pressure waves that develop in the Martian atmosphere as a result of sublimation and condensation of CO2 in polar regions.

A weather-driven model of malaria transmission

PubMed Central

Hoshen, Moshe B; Morse, Andrew P

2004-01-01

Background Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. Methods This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Results Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. Conclusion A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts. PMID:15350206

Climate change scenarios of heat waves in Central Europe and their uncertainties

NASA Astrophysics Data System (ADS)

Lhotka, Ondřej; Kyselý, Jan; Farda, Aleš

2018-02-01

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970-1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020-2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070-2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.

Climate simulation of the twenty-first century with interactive land-use changes

NASA Astrophysics Data System (ADS)

Voldoire, Aurore; Eickhout, Bas; Schaeffer, Michiel; Royer, Jean-François; Chauvin, Fabrice

2007-08-01

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.

Climate driven egg and hatchling mortality threatens survival of eastern Pacific leatherback turtles.

PubMed

Santidrián Tomillo, Pilar; Saba, Vincent S; Blanco, Gabriela S; Stock, Charles A; Paladino, Frank V; Spotila, James R

2012-01-01

Egg-burying reptiles need relatively stable temperature and humidity in the substrate surrounding their eggs for successful development and hatchling emergence. Here we show that egg and hatchling mortality of leatherback turtles (Dermochelys coriacea) in northwest Costa Rica were affected by climatic variability (precipitation and air temperature) driven by the El Niño Southern Oscillation (ENSO). Drier and warmer conditions associated with El Niño increased egg and hatchling mortality. The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) projects a warming and drying in Central America and other regions of the World, under the SRES A2 development scenario. Using projections from an ensemble of global climate models contributed to the IPCC report, we project that egg and hatchling survival will rapidly decline in the region over the next 100 years by ∼50-60%, due to warming and drying in northwestern Costa Rica, threatening the survival of leatherback turtles. Warming and drying trends may also threaten the survival of sea turtles in other areas affected by similar climate changes.

Effects of simultaneous climate change and geomorphic evolution on thermal characteristics of a shallow Alaskan lake

USGS Publications Warehouse

Griffiths, Jennifer R.; Schindler, Daniel E.; Balistrieri, Laurie S.; Ruggerone, Gregory T.

2011-01-01

We used a hydrodynamics model to assess the consequences of climate warming and contemporary geomorphic evolution for thermal conditions in a large, shallow Alaskan lake. We evaluated the effects of both known climate and landscape change, including rapid outlet erosion and migration of the principal inlet stream, over the past 50 yr as well as future scenarios of geomorphic restoration. Compared to effects of air temperature during the past 50 yr, lake thermal properties showed little sensitivity to substantial (~60%) loss of lake volume, as the lake maximum depth declined from 6 m to 4 m driven by outlet erosion. The direction and magnitude of future lake thermal responses will be driven largely by the extent of inlet stream migration when it occurs simultaneously with outlet erosion. Maintaining connectivity with inlet streams had substantial effects on buffering lake thermal responses to warming climate. Failing to account for changing rates and types of geomorphic processes under continuing climate change may misidentify the primary drivers of lake thermal responses and reduce our ability to understand the consequences for aquatic organisms.

Performance Investigation of a Solar Heat Driven Adsorption Chiller under Two Different Climatic Conditions

NASA Astrophysics Data System (ADS)

Choudhury, Biplab; Chatterjee, Pradip Kumar; Habib, Khairul; Saha, Bidyut Baran

2018-06-01

The demand for cooling, especially in the developing economies, is rising at a fast rate. Fast-depleting sources of fossil fuel and environmental concerns necessitate looking for alternative cooling solutions. Solar heat driven adsorption based cooling cycles are environmentally friendly due to their use of natural refrigerants and the thermal compression process. In this paper, a performance simulation study of a basic two-bed solar adsorption chiller has been performed through a transient model for two different climatic locations in India. Effect of operating temperatures and cycle time on the chiller performance has been studied. It is observed that the solar hot water temperature obtained in the composite climate of Delhi (28.65°N, 77.25°E) can run the basic adsorption cooling cycle efficiently throughout the year. Whereas, the monsoon months of July and August in the warm and humid climate of Durgapur (23.48°N, 87.32°E) are unable to supply the required driving heat.

Life cycle ecophysiology of small pelagic fish and climate-driven changes in populations

NASA Astrophysics Data System (ADS)

Peck, Myron A.; Reglero, Patricia; Takahashi, Motomitsu; Catalán, Ignacio A.

2013-09-01

Due to their population characteristics and trophodynamic role, small pelagic fishes are excellent bio-indicators of climate-driven changes in marine systems world-wide. We argue that making robust projections of future changes in the productivity and distribution of small pelagics will require a cause-and-effect understanding of historical changes based upon physiological principles. Here, we reviewed the ecophysiology of small pelagic (clupeiform) fishes including a matrix of abiotic and biotic extrinsic factors (e.g., temperature, salinity, light, and prey characteristics) and stage-specific vital rates: (1) adult spawning, (2) survival and development of eggs and yolk sac larvae, and (3) feeding and growth of larvae, post-larvae and juveniles. Emphasis was placed on species inhabiting Northwest Pacific and Northeast Atlantic (European) waters for which summary papers are particularly scarce compared to anchovy and sardine in upwelling systems. Our review revealed that thermal niches (optimal and sub-optimal ranges in temperatures) were species- and stage-specific but that temperature effects only partly explained observed changes in the distribution and/or productivity of populations in the Northwest Pacific and Northeast Atlantic; changes in temperature may be necessary but not sufficient to induce population-level shifts. Prey availability during the late larval and early juvenile period was a common, density-dependent mechanism linked to fluctuations in populations but recruitment mechanisms were system-specific suggesting that generalizations of climate drivers across systems should be avoided. We identified gaps in knowledge regarding basic elements of the growth physiology of each life stage that will require additional field and laboratory study. Avenues of research are recommended that will aid the development of models that provide more robust, physiological-based projections of the population dynamics of these and other small pelagic fish. In our opinion, the continued development of biophysical models that close the life cycle (depict all life stages) offers the best chance of revealing processes causing historical fluctuations on the productivity and distribution of small pelagic fishes and to project future climate-driven impacts. Correctly representing physiological-based mechanisms will increase confidence in the outcomes of models simulating the potential impacts of bottom-up processes, a first step towards evaluating the mixture of factors and processes (e.g. intra-guild dynamics, predation, fisheries exploitation) which interact with climate to affect populations of small pelagic fishes. Understand the impacts of reduced growth rates during the juvenile stage on the process of maturation and spawning condition of small pelagic fishes. Examine the effects of changes in prey quality on the duration and magnitude of spawning by small pelagic fishes to capture how climate-driven changes in zooplankton species composition might act as a “bottom-up” regulator of fish productivity. Identify the drivers for spawning location and timing to better understand how spawning dynamics may be influenced by climate change (e.g. changes in water salinity or turbidity resulting from changes in river discharges or wind-driven turbulence, respectively).

Implementation and evaluation of a monthly water balance model over the US on an 800 m grid

USGS Publications Warehouse

Hostetler, Steven W.; Alder, Jay R.

2016-01-01

We simulate the 1950–2010 water balance for the conterminous U.S. (CONUS) with a monthly water balance model (MWBM) using the 800 m Parameter-elevation Regression on Independent Slopes Model (PRISM) data set as model input. We employed observed snow and streamflow data sets to guide modification of the snow and potential evapotranspiration components in the default model and to evaluate model performance. Based on various metrics and sensitivity tests, the modified model yields reasonably good simulations of seasonal snowpack in the West (range of bias of ±50 mm at 68% of 713 SNOTEL sites), the gradients and magnitudes of actual evapotranspiration, and runoff (median correlation of 0.83 and median Nash-Sutcliff efficiency of 0.6 between simulated and observed annual time series at 1427 USGS gage sites). The model generally performs well along the Pacific Coast, the high elevations of the Basin and Range and over the Midwest and East, but not as well over the dry areas of the Southwest and upper Plains regions due, in part, to the apportioning of direct versus delayed runoff. Sensitivity testing and application of the MWBM to simulate the future water balance at four National Parks when driven by 30 climate models from the Climate Model Intercomparison Program Phase 5 (CMIP5) demonstrate that the model is useful for evaluating first-order, climate driven hydrologic change on monthly and annual time scales.

Baroclinic Adjustment of the Eddy-Driven Jet

NASA Astrophysics Data System (ADS)

Novak, Lenka; Ambaum, Maarten H. P.; Harvey, Ben J.

2017-04-01

The prediction of poleward shift in the midlatitude eddy-driven jets due to anthropogenic climate change is now a robust feature of climate models, but the magnitude of this shift or the processes responsible for it are less certain. This uncertainty comes from the complex response in storm tracks to large-scale forcing and their nonlinear modulation of the jet. This study uses global circulation models to reveal a relationship between eddy growth rate (referred to as baroclinicity) and eddy activity, whereby baroclinicity responds most rapidly to an eddy-dissipating forcing whereas eddy activity responds most rapidly to a baroclinicity-replenishing forcing. This nonlinearity can be generally explained using a two-dimensional dynamical system essentially describing the baroclinic adjustment as a predator-prey relationship. Despite this nonlinearity, the barotropic changes in the eddy-driven jet appear to be of a comparable magnitude for the ranges of both types of forcing tested in this study. It is implied that while changes in eddy activity or baroclinicity may indicate the sign of latitudinal jet shifting, the precise magnitude of this shifting is a result of a balance between these two quantities.

Eastern South African hydroclimate over the past 270,000 years

NASA Astrophysics Data System (ADS)

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J. C.; Hall, Ian R.

2015-12-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years.

PubMed

Simon, Margit H; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J C; Hall, Ian R

2015-12-21

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years

PubMed Central

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J.C.; Hall, Ian R.

2015-01-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique. PMID:26686943

Tectonic-driven climate change and the diversification of angiosperms

PubMed Central

Chaboureau, Anne-Claire; Sepulchre, Pierre; Donnadieu, Yannick; Franc, Alain

2014-01-01

In 1879, Charles Darwin characterized the sudden and unexplained rise of angiosperms during the Cretaceous as an “abominable mystery.” The diversification of this clade marked the beginning of a rapid transition among Mesozoic ecosystems and floras formerly dominated by ferns, conifers, and cycads. Although the role of environmental factors has been suggested [Coiffard C, Gómez B (2012) Geol Acta 10(2):181–188], Cretaceous global climate change has barely been considered as a contributor to angiosperm radiation, and focus was put on biotic factors to explain this transition. Here we use a fully coupled climate model driven by Mesozoic paleogeographic maps to quantify and discuss the impact of continental drift on angiosperm expansion and diversification. We show that the decrease of desertic belts between the Triassic and the Cretaceous and the subsequent onset of long-lasting humid conditions during the Late Cretaceous were driven by the breakup of Pangea and were contemporaneous with the first rise of angiosperm diversification. Positioning angiosperm-bearing fossil sites on our paleobioclimatic maps shows a strong match between the location of fossil-rich outcrops and temperate humid zones, indicating that climate change from arid to temperate dominance may have set the stage for the ecological expansion of flowering plants. PMID:25225405

Bridging the Gap between Policy-Driven Land Use Changes and Regional Climate Projections

NASA Astrophysics Data System (ADS)

Berckmans, J.; Hamdi, R.; Dendoncker, N.; Ceulemans, R.

2017-12-01

Land use land cover changes (LULCC) can impact the regional climate by two mechanisms: biogeochemical and biogeophysical. The biogeochemical mechanism of the LULCC alters the chemical composition of the atmosphere by greenhouse gas emissions. The biogeophysical mechanism forces changes in the heat and moisture transfer between the land and the atmosphere. The different representations of the future LULCC under influence of the biogeochemical mechanism are included in the IPCC Radiative Concentration Pathways (RCPs). In contrast, the RCPs do not incorporate the biogeophysical effects. Although considerable research has been devoted to the biogeophysical effects of LULCC on climate, less attention has been paid to assessing the full (both biogeochemical and biogeophysical) LULCC impact on the regional climate in modeling studies. Due to the large variety of small changes in the landscape of Western Europe, the small scale climate impact by the LULCC has been achieved using high-resolution scenarios. The "ALARM" project that was governed by the European Commission generated LULCC data on a resolution of 250x250 m for three time steps: 2020, 2050 and 2080. The CNRM-CM5.1 global climate model has been downscaled to perform simulations with ALARO-SURFEX for the near-term future. Both climate changes and land cover changes have been assessed based on RCP and ALARM scenarios. The use of the land surface model SURFEX with its tiling approach allowed us to accurately represent the small scale changes in the landscape. The largest landscape changes contain the abandonment of agricultural land and the increase in forestry and urban areas. Our results show that the conversions from rural areas to urban areas and arable land to forest in Western Europe considerable affect the near-surface temperature and to a lesser extent the precipitation. These results are related to modifications demonstrated in the surface energy budget. The LULCC have a significant impact compared to the near-term future climate changes. They provide valuable information for landscape planning to mitigate and adapt to climate change. The strength of this study is the use of policy-driven LULCC data combined with an accurate representation of the land by the climate model.

Quantifying the impact of Teleconnections on Hydrologic Regimes in Texas

NASA Astrophysics Data System (ADS)

Bhatia, N.; Singh, V. P.; Srivastav, R. K.

2016-12-01

Climate change is being alleged to have led to the increased frequency of extreme flooding events and the resulting damages are severe, especially where the flood-plain population densities are higher. Much research in the field of hydroclimatology is focusing on improving real-time flood forecasting models. Recent studies show that, in the state of Texas, extreme regional floods are actually triggered by abruptly higher precipitation intensities. Such intensities are further driven by sea-surface temperature and pressure anomalies, defined by certain patterns of teleconnections. In this study, climate variability is defined on the basis of five major Atlantic and Pacific Ocean related teleconnections: (i) Atlantic Multidecadal Oscillation (AMO), (ii) North Atlantic Oscillation (NAO), (iii) Pacific Decadal Oscillation (PDO), (iv) Pacific North American Pattern (PNA), and (v) Southern Oscillation Index (SOI). Hydrologic extremes will be modeled using probabilistic distributions. Leave-One-Out-Test (LOOT) will be employed to address the outliers in the extremes, and to eventually obtain the robust correlation coefficient. The variation in the effect of most correlated teleconnection with respect to hydrologic attributes will be investigated for the entire state. This study will attempt to identify potential teleconnection inputs for data-driven hydrologic models under varying climatic conditions.

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

USGS Publications Warehouse

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

2013-01-01

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

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

PubMed

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

2013-06-04

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

AGU Climate Scientists Offer Question-and-Answer Service for Media

NASA Astrophysics Data System (ADS)

Jackson, Stacy

2010-03-01

In fall 2009, AGU launched a member-driven pilot project to improve the accuracy of climate science coverage in the media and to improve public understanding of climate science. The project's goal was to increase the accessibility of climate science experts to journalists across the full spectrum of media outlets. As a supplement to the traditional one-to-one journalist-expert relationship model, the project tested the novel approach of providing a question-and-answer (Q&A) service with a pool of expert scientists and a Web-based interface with journalists. Questions were explicitly limited to climate science to maintain a nonadvocacy, nonpartisan perspective.

A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming.

PubMed

Cotto, Olivier; Wessely, Johannes; Georges, Damien; Klonner, Günther; Schmid, Max; Dullinger, Stefan; Thuiller, Wilfried; Guillaume, Frédéric

2017-05-05

Withstanding extinction while facing rapid climate change depends on a species' ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species' range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species' responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species' local abundance rather than their range may likely better inform on species' extinction risks under climate change.

Testing competing forms of the Milankovitch hypothesis: A multivariate approach

NASA Astrophysics Data System (ADS)

Kaufmann, Robert K.; Juselius, Katarina

2016-02-01

We test competing forms of the Milankovitch hypothesis by estimating the coefficients and diagnostic statistics for a cointegrated vector autoregressive model that includes 10 climate variables and four exogenous variables for solar insolation. The estimates are consistent with the physical mechanisms postulated to drive glacial cycles. They show that the climate variables are driven partly by solar insolation, determining the timing and magnitude of glaciations and terminations, and partly by internal feedback dynamics, pushing the climate variables away from equilibrium. We argue that the latter is consistent with a weak form of the Milankovitch hypothesis and that it should be restated as follows: internal climate dynamics impose perturbations on glacial cycles that are driven by solar insolation. Our results show that these perturbations are likely caused by slow adjustment between land ice volume and solar insolation. The estimated adjustment dynamics show that solar insolation affects an array of climate variables other than ice volume, each at a unique rate. This implies that previous efforts to test the strong form of the Milankovitch hypothesis by examining the relationship between solar insolation and a single climate variable are likely to suffer from omitted variable bias.

Synergy between land use and climate change increases future fire risk in Amazon forests

NASA Astrophysics Data System (ADS)

Le Page, Yannick; Morton, Douglas; Hartin, Corinne; Bond-Lamberty, Ben; Cardoso Pereira, José Miguel; Hurtt, George; Asrar, Ghassem

2017-12-01

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change - Representative Concentration Pathway (RCP) 8.5 - projected understory fires increase in frequency and duration, burning 4-28 times more forest in 2080-2100 than during 1990-2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9-5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

Multi-model projections of Indian summer monsoon climate changes under A1B scenario

NASA Astrophysics Data System (ADS)

Niu, X.; Wang, S.; Tang, J.

2016-12-01

As part of the Regional Climate Model Intercomparison Project for Asia, the projections of Indian summer monsoon climate changes are constructed using three global climate models (GCMs) and seven regional climate models (RCMs) during 2041-2060 based on the Intergovernmental Panel on Climate Change A1B emission scenario. For the control climate of 1981-2000, most nested RCMs show advantage over the driving GCM of European Centre/Hamburg Fifth Generation (ECHAM5) in the temporal-spatial distributions of temperature and precipitation over Indian Peninsula. Following the driving GCM of ECHAM5, most nested RCMs produce advanced monsoon onset in the control climate. For future climate widespread summer warming is projected over Indian Peninsula by all climate models, with the Multi-RCMs ensemble mean (MME) temperature increasing of 1°C to 2.5°C and the maximum warming center located in northern Indian Peninsula. While for the precipitation, a large inter-model spread is projected by RCMs, with wetter condition in MME projections and significant increase over southern India. Driven by the same GCM, most RCMs project advanced monsoon onset while delayed onset is found in two Regional Climate Model (RegCM3) projections, indicating uncertainty can be expected in the Indian Summer Monsoon onset. All climate models except Conformal-Cubic Atmospheric Model with equal resolution (referred as CCAMP) and two RegCM3 models project stronger summer monsoon during 2041-2060. The disagreement in precipitation projections by RCMs indicates that the surface climate change on regional scale is not only dominated by the large-scale forcing which is provided by driving GCM but also sensitive to RCM' internal physics.

Change in terrestrial ecosystem water-use efficiency over the last three decades.

PubMed

Huang, Mengtian; Piao, Shilong; Sun, Yan; Ciais, Philippe; Cheng, Lei; Mao, Jiafu; Poulter, Ben; Shi, Xiaoying; Zeng, Zhenzhong; Wang, Yingping

2015-06-01

Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m(-2)  mm(-1)  yr(-1) under the single effect of rising CO2 ('CO2 '), climate change ('CLIM') and nitrogen deposition ('NDEP'), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (-0.0005 g C m(-2)  mm(-1)  yr(-1) ), which differs from process-model (0.0064 g C m(-2)  mm(-1)  yr(-1) ) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt , GPP×VPD/TR) in response to rising CO2 , climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon-water interactions over terrestrial ecosystems under global change. © 2015 John Wiley & Sons Ltd.

Modeling U.S. water resources under climate change

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Strzepek, Kenneth; Schlosser, Adam; Jacoby, Henry; Gueneau, Arthur; Fant, Charles; Rausch, Sebastian; Reilly, John

2014-04-01

Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select "wet" and "dry" patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

Hierarchical, parallel computing strategies using component object model for process modelling responses of forest plantations to interacting multiple stresses

Treesearch

J. G. Isebrands; G. E. Host; K. Lenz; G. Wu; H. W. Stech

2000-01-01

Process models are powerful research tools for assessing the effects of multiple environmental stresses on forest plantations. These models are driven by interacting environmental variables and often include genetic factors necessary for assessing forest plantation growth over a range of different site, climate, and silvicultural conditions. However, process models are...

A model of nitrous oxide evolution from soil driven by rainfall events. I - Model structure and sensitivity. II - Model applications

NASA Technical Reports Server (NTRS)

Changsheng, LI; Frolking, Steve; Frolking, Tod A.

1992-01-01

Simulations of N2O and CO2 emissions from soils were conducted with a rain-event driven, process-oriented model (DNDC) of nitrogen and carbon cycling processes in soils. The magnitude and trends of simulated N2O (or N2O + N2) and CO2 emissions were consistent with the results obtained in field experiments. The successful simulation of these emissions from the range of soil types examined demonstrates that the DNDC will be a useful tool for the study of linkages among climate, soil-atmosphere interactions, land use, and trace gas fluxes.

Effects of biotic feedback and harvest management on boreal forest fire activity under climate change.

PubMed

Krawchuk, Meg A; Cumming, Steve G

2011-01-01

Predictions of future fire activity over Canada's boreal forests have primarily been generated from climate data following assumptions that direct effects of weather will stand alone in contributing to changes in burning. However, this assumption needs explicit testing. First, areas recently burned can be less likely to burn again in the near term, and this endogenous regulation suggests the potential for self-limiting, negative biotic feedback to regional climate-driven increases in fire. Second, forest harvest is ongoing, and resulting changes in vegetation structure have been shown to affect fire activity. Consequently, we tested the assumption that fire activity will be driven by changes in fire weather without regulation by biotic feedback or regional harvest-driven changes in vegetation structure in the mixedwood boreal forest of Alberta, Canada, using a simulation experiment that includes the interaction of fire, stand dynamics, climate change, and clear cut harvest management. We found that climate change projected with fire weather indices calculated from the Canadian Regional Climate Model increased fire activity, as expected, and our simulations established evidence that the magnitude of regional increase in fire was sufficient to generate negative feedback to subsequent fire activity. We illustrate a 39% (1.39-fold) increase in fire initiation and 47% (1.47-fold) increase in area burned when climate and stand dynamics were included in simulations, yet 48% (1.48-fold) and 61% (1.61-fold) increases, respectively, when climate was considered alone. Thus, although biotic feedbacks reduced burned area estimates in important ways, they were secondary to the direct effect of climate on fire. We then show that ongoing harvest management in this region changed landscape composition in a way that led to reduced fire activity, even in the context of climate change. Although forest harvesting resulted in decreased regional fire activity when compared to unharvested conditions, forest composition and age structure was shifted substantially, illustrating a trade-off between management goals to minimize fire and conservation goals to emulate natural disturbance.

Ocean Heat Uptake Slows 21st Century Surface Warming Driven by Extratropical Cloud Feedbacks

NASA Astrophysics Data System (ADS)

Frey, W.; Maroon, E.; Pendergrass, A. G.; Kay, J. E.

2017-12-01

Equilibrium climate sensitivity (ECS), the warming in response to instantaneously doubled CO2, has long been used to compare climate models. In many models, ECS is well correlated with warming produced by transient forcing experiments. Modifications to cloud phase at high latitudes in a state-of-the-art climate model, the Community Earth System Model (CESM), produce a large increase in ECS (1.5 K) via extratropical cloud feedbacks. However, only a small surface warming increase occurs in a realistic 21st century simulation including a full-depth dynamic ocean and the "business as usual" RCP8.5 emissions scenario. In fact, the increase in surface warming is only barely above the internal variability-generated range in the CESM Large Ensemble. The small change in 21st century warming is attributed to subpolar ocean heat uptake in both hemispheres. In the Southern Ocean, the mean-state circulation takes up heat while in the North Atlantic a slowdown in circulation acts as a feedback to slow surface warming. These results show the importance of subpolar ocean heat uptake in controlling the pace of warming and demonstrate that ECS cannot be used to reliably infer transient warming when it is driven by extratropical feedbacks.

Vulnerability of Forests in India: A National Scale Assessment.

PubMed

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N H

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Vulnerability of Forests in India: A National Scale Assessment

NASA Astrophysics Data System (ADS)

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N. H.

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

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

Rastogi, Deeksha; Kao, Shih-Chieh; Ashfaq, Moetasim

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) river basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms,more » were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Here, our results showed that PMP driven by projected future climate forcings is higher than 1981-2010 baseline values by around 20% in the 2021-2050 near-future and 44% in the 2071-2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserves more in-depth examination.« less

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

NASA Astrophysics Data System (ADS)

Rastogi, Deeksha; Kao, Shih-Chieh; Ashfaq, Moetasim; Mei, Rui; Kabela, Erik D.; Gangrade, Sudershan; Naz, Bibi S.; Preston, Benjamin L.; Singh, Nagendra; Anantharaj, Valentine G.

2017-05-01

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) River Basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms, were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Our results showed that PMP driven by projected future climate forcings is higher than 1981-2010 baseline values by around 20% in the 2021-2050 near-future and 44% in the 2071-2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserve more in-depth examination.

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

DOE PAGES

Rastogi, Deeksha; Kao, Shih-Chieh; Ashfaq, Moetasim; ...

2017-04-13

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) river basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms,more » were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Here, our results showed that PMP driven by projected future climate forcings is higher than 1981-2010 baseline values by around 20% in the 2021-2050 near-future and 44% in the 2071-2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserves more in-depth examination.« less

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach.

PubMed

Taylor, Lyla L; Banwart, Steve A; Valdes, Paul J; Leake, Jonathan R; Beerling, David J

2012-02-19

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO(2)) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean-atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal-geosphere interactions at the global scale, which constitutes a first step towards developing 'next-generation' geochemical models.

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach

PubMed Central

Taylor, Lyla L.; Banwart, Steve A.; Valdes, Paul J.; Leake, Jonathan R.; Beerling, David J.

2012-01-01

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO2) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean–atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal–geosphere interactions at the global scale, which constitutes a first step towards developing ‘next-generation’ geochemical models. PMID:22232768

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa.

PubMed

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-06-14

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of Knowledge(SM) databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa

PubMed Central

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-01-01

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of KnowledgeSM databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably. PMID:27314369

WebStart WEPS: Remote data access and model execution functionality added to WEPS

USDA-ARS?s Scientific Manuscript database

The Wind Erosion Prediction System (WEPS) is a daily time step, process based wind erosion model developed by the United States Department of Agriculture - Agricultural Research Service (USDA-ARS). WEPS simulates climate and management driven changes to the surface/vegetation/soil state on a daily b...

A universal model for predicting human migration under climate change: examining future sea level rise in Bangladesh

NASA Astrophysics Data System (ADS)

Frankel Davis, Kyle; Bhattachan, Abinash; D’Odorico, Paolo; Suweis, Samir

2018-06-01

Climate change is expected to impact the habitability of many places around the world in significant and unprecedented ways in the coming decades. While previous studies have provided estimates of populations potentially exposed to various climate impacts, little work has been done to assess the number of people that may actually be displaced or where they will choose to go. Here we modify a diffusion-based model of human mobility in combination with population, geographic, and climatic data to estimate the sources, destinations, and flux of potential migrants as driven by sea level rise (SLR) in Bangladesh in the years 2050 and 2100. Using only maps of population and elevation, we predict that 0.9 million people (by year 2050) to 2.1 million people (by year 2100) could be displaced by direct inundation and that almost all of this movement will occur locally within the southern half of the country. We also find that destination locations should anticipate substantial additional demands on jobs (594 000), housing (197 000), and food (783 × 109 calories) by mid-century as a result of those displaced by SLR. By linking the sources of migrants displaced by SLR with their likely destinations, we demonstrate an effective approach for predicting climate-driven migrant flows, especially in data-limited settings.

Quantifying the importance of model-to-model variability in integrated assessments of 21st century climate

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Calvin, K. V.

2016-12-01

The C4MIP and CMIP5 model intercomparison projects (MIPs) highlighted uncertainties in climate projections, driven to a large extent by interactions between the terrestrial carbon cycle and climate feedbacks. In addition, the importance of feedbacks between human (energy and economic) systems and natural (carbon and climate) systems is poorly understood, and not considered in the previous MIP protocols. The experiments conducted under the previous Integrated Earth System Model (iESM) project, which coupled a earth system model with an integrated assessment model (GCAM), found that the inclusion of climate feedbacks on the terrestrial system in an RCP4.5 scenario increased ecosystem productivity, resulting in declines in cropland extent and increases in bioenergy production and forest cover. As a follow-up to these studies and to further understand climate-carbon cycle interactions and feedbacks, we examined the robustness of these results by running a suite of GCAM-only experiments using changes in ecosystem productivity derived from both the CMIP5 archive and the Agricultural Model Intercomparison Project. In our results, the effects of climate on yield in an RCP8.5 scenario tended to be more positive than those of AgMIP, but more negative than those of the other CMIP models. We discuss these results and the implications of model-to-model variability for integrated coupling studies of the future earth system.

Energy-Water-Land-Climate Nexus: Modeling Impacts from the Asset to Regional Scale

NASA Astrophysics Data System (ADS)

Tidwell, V. C.; Bennett, K. E.; Middleton, R. S.; Behery, S.; Macknick, J.; Corning-Padilla, A.; Brinkman, G.; Meng, M.

2016-12-01

A critical challenge for the energy-water-land nexus is understanding and modeling the connection between the natural system—including changes in climate, land use/cover, and streamflow—and the engineered system including water for energy, agriculture, and society. Equally important is understanding the linkage across scales; that is, how impacts at the asset level aggregate to influence behavior at the local to regional scale. Toward this need, a case study was conducted featuring multi-sector and multi-scale modeling centered on the San Juan River basin (a watershed that accounts for one-tenth of the Colorado River drainage area). Simulations were driven by statistically downscaled climate data from three global climate models (emission scenario RCP 8.5) and planned growth in regional water demand. The Variable Infiltration Capacity (VIC) hydrologic model was fitted with a custom vegetation mortality sub-model and used to estimate tributary inflows to the San Juan River and estimate reservoir evaporation. San Juan River operations, including releases from Navajo Reservoir, were subsequently modeled using RiverWare to estimate impacts on water deliveries out to the year 2100. Major water demands included two large coal-fired power plants, a local electric utility, river-side irrigation, the Navajo Indian Irrigation Project and instream flows managed for endangered aquatic species. Also tracked were basin exports, including water (downstream flows to the Colorado River and interbasin transfers to the Rio Grande) and interstate electric power transmission. Implications for the larger western electric grid were assessed using PLEXOS, a sub-hourly dispatch, electric production-cost model. Results highlight asset-level interactions at the energy-water-land nexus driven by climate and population dynamics; specifically, growing vulnerabilities to shorted water deliveries. Analyses also explored linkages across geographic scales from the San Juan to the larger Colorado River and Rio Grande basins as well as the western power grid.

Modeling the Impacts of Hydromodification on Water Quantity and Quality

EPA Science Inventory

Hydromodification activities are driven by human population growth and resource extraction and consumption including urbanization, agriculture, forestry, mining, water withdrawal, climate change, and flow regulation by dams and impoundments. These anthropogenic activities alter n...

Simulating seasonal tropical cyclone intensities at landfall along the South China coast

NASA Astrophysics Data System (ADS)

Lok, Charlie C. F.; Chan, Johnny C. L.

2018-04-01

A numerical method is developed using a regional climate model (RegCM3) and the Weather Forecast and Research (WRF) model to predict seasonal tropical cyclone (TC) intensities at landfall for the South China region. In designing the model system, three sensitivity tests have been performed to identify the optimal choice of the RegCM3 model domain, WRF horizontal resolution and WRF physics packages. Driven from the National Centers for Environmental Prediction Climate Forecast System Reanalysis dataset, the model system can produce a reasonable distribution of TC intensities at landfall on a seasonal scale. Analyses of the model output suggest that the strength and extent of the subtropical ridge in the East China Sea are crucial to simulating TC landfalls in the Guangdong and Hainan provinces. This study demonstrates the potential for predicting TC intensities at landfall on a seasonal basis as well as projecting future climate changes using numerical models.

Impacts of climate change on peanut yield in China simulated by CMIP5 multi-model ensemble projections

NASA Astrophysics Data System (ADS)

Xu, Hanqing; Tian, Zhan; Zhong, Honglin; Fan, Dongli; Shi, Runhe; Niu, Yilong; He, Xiaogang; Chen, Maosi

2017-09-01

Peanut is one of the major edible vegetable oil crops in China, whose growth and yield are very sensitive to climate change. In addition, agriculture climate resources are expected to be redistributed under climate change, which will further influence the growth, development, cropping patterns, distribution and production of peanut. In this study, we used the DSSAT-Peanut model to examine the climate change impacts on peanut production, oil industry and oil food security in China. This model is first calibrated using site observations including 31 years' (1981-2011) climate, soil and agronomy data. This calibrated model is then employed to simulate the future peanut yield based on 20 climate scenarios from 5 Global Circulation Models (GCMs) developed by the InterSectoral Impact Model Intercomparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs). Results indicate that the irrigated peanut yield will decrease 2.6% under the RCP 2.6 scenario, 9.9% under the RCP 4.5 scenario and 29% under the RCP 8.5 scenario, respectively. Similarly, the rain-fed peanut yield will also decrease, with a 2.5% reduction under the RCP 2.6 scenario, 11.5% reduction under the RCP 4.5 scenario and 30% reduction under the RCP 8.5 scenario, respectively.

Downscaled climate change projections with uncertainty assessment over India using a high resolution multi-model approach.

PubMed

Kumar, Pankaj; Wiltshire, Andrew; Mathison, Camilla; Asharaf, Shakeel; Ahrens, Bodo; Lucas-Picher, Philippe; Christensen, Jens H; Gobiet, Andreas; Saeed, Fahad; Hagemann, Stefan; Jacob, Daniela

2013-12-01

This study presents the possible regional climate change over South Asia with a focus over India as simulated by three very high resolution regional climate models (RCMs). One of the most striking results is a robust increase in monsoon precipitation by the end of the 21st century but regional differences in strength. First the ability of RCMs to simulate the monsoon climate is analyzed. For this purpose all three RCMs are forced with ECMWF reanalysis data for the period 1989-2008 at a horizontal resolution of ~25 km. The results are compared against independent observations. In order to simulate future climate the models are driven by lateral boundary conditions from two global climate models (GCMs: ECHAM5-MPIOM and HadCM3) using the SRES A1B scenario, except for one RCM, which only used data from one GCM. The results are presented for the full transient simulation period 1970-2099 and also for several time slices. The analysis concentrates on precipitation and temperature over land. All models show a clear signal of gradually wide-spread warming throughout the 21st century. The ensemble-mean warming over India is 1.5°C at the end of 2050, whereas it is 3.9°C at the end of century with respect to 1970-1999. The pattern of projected precipitation changes shows considerable spatial variability, with an increase in precipitation over the peninsular of India and coastal areas and, either no change or decrease further inland. From the analysis of a larger ensemble of global climate models using the A1B scenario a wide spread warming (~3.2°C) and an overall increase (~8.5%) in mean monsoon precipitation by the end of the 21st century is very likely. The influence of the driving GCM on the projected precipitation change simulated with each RCM is as strong as the variability among the RCMs driven with one. Copyright © 2013 Elsevier B.V. All rights reserved.

Carbon-climate-human interactions in an integrated human-Earth system model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.

2016-12-01

The C4MIP and CMIP5 results highlighted large uncertainties in climate projections, driven to a large extent by limited understanding of the interactions between terrestrial carbon-cycle and climate feedbacks, and their associated uncertainties. These feedbacks are dominated by uncertainties in soil processes, disturbance dynamics, ecosystem response to climate change, and agricultural productivity, and land-use change. This research addresses three questions: (1) how do terrestrial feedbacks vary across different levels of climate change, (2) what is the relative contribution of CO2 fertilization and climate change, and (3) how robust are the results across different models and methods? We used a coupled modeling framework that integrates an Integrated Assessment Model (modeling economic and energy activity) with an Earth System Model (modeling the natural earth system) to examine how business-as-usual (RCP 8.5) climate change will affect ecosystem productivity, cropland extent, and other aspects of the human-Earth system. We find that higher levels of radiative forcing result in higher productivity growth, that increases in CO2 concentrations are the dominant contributors to that growth, and that our productivity increases fall in the middle of the range when compared to other CMIP5 models and the AgMIP models. These results emphasize the importance of examining both the anthropogenic and natural components of the earth system, and their long-term interactive feedbacks.

Evaluation of large-scale meteorological patterns associated with temperature extremes in the NARCCAP regional climate model simulations

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Lee, Huikyo; Neelin, J. David; Lintner, Benjamin R.; McGinnis, Seth; Mearns, Linda O.; Kim, Jinwon

2015-12-01

Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of well-simulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts.

Assessing the capability of high resolution climatic model experiments to simulate Mediterranean cyclonic tracks

NASA Astrophysics Data System (ADS)

Hatzaki, M.; Flocas, H. A.; Giannakopoulos, C.; Kostopoulou, E.; Kouroutzoglou, I.; Keay, K.; Simmonds, I.

2010-09-01

In this study, a comparison of a reanalysis driven simulation to a GCM driven simulation of a regional climate model is performed in order to assess the model's ability to capture the climatic characteristics of cyclonic tracks in the Mediterranean in the present climate. The ultimate scope of the study will be to perform a future climate projection related to cyclonic tracks in order to better understand and assess climate change in the Mediterranean. The climatology of the cyclonic tracks includes inter-monthly variations, classification of tracks according to their origin domain, dynamic and kinematic characteristics, as well as trend analysis. For this purpose, the ENEA model is employed based on PROTHEUS system composed of the RegCM atmospheric regional model and the MITgcm ocean model, coupled through the OASIS3 flux coupler. 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. Two experiments are employed; a) the ERA402 with lateral Boundary conditions from ERA40 for the 43-year period 1958-2000, and b) the EH5OM_20C3M where the lateral boundary conditions for the atmosphere (1951-2000) are taken from the ECHAM5-MPIOM 20c3m global simulation (run3) included in the IPCC-AR4. 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. This approach is considered to be crucial, since open lows are also incorporated into the storm life-cycle, preventing possible inappropriate time series breaks, if a temporary weakening to an open-low state occurs. The model experiments verify that considerable inter-monthly variations of track density occur in the Mediterranean region, consistent with previous studies. The classification of the tracks according to their origin domain show that the vast majority originate within the examined area itself. The study of the kinematic and dynamic parameters of tracks according to their origin demonstrate that deeper cyclones follow the SW track. 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.

New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

An Analysis of the Potential Impact of Climate Change on Dengue Transmission in the Southeastern United States.

PubMed

Butterworth, Melinda K; Morin, Cory W; Comrie, Andrew C

2017-04-01

Dengue fever, caused by a mosquito-transmitted virus, is an increasing health concern in the Americas. Meteorological variables such as temperature and precipitation can affect disease distribution and abundance through biophysical impacts on the vector and on the virus. Such tightly coupled links may facilitate further spread of dengue fever under a changing climate. In the southeastern United States, the dengue vector is widely established and exists on the current fringe of dengue transmission. We assessed projected climate change-driven shifts in dengue transmission risk in this region. We used a dynamic mosquito population and virus transmission model driven by meteorological data to simulate Aedes aegypti populations and dengue cases in 23 locations in the southeastern United States under current climate conditions and future climate projections. We compared estimates for each location with simulations based on observed data from San Juan, Puerto Rico, where dengue is endemic. Our simulations based on current climate data suggest that dengue transmission at levels similar to those in San Juan is possible at several U.S. locations during the summer months, particularly in southern Florida and Texas. Simulations that include climate change projections suggest that conditions may become suitable for virus transmission in a larger number of locations and for a longer period of time during each year. However, in contrast with San Juan, U.S. locations would not sustain year-round dengue transmission according to our model. Our findings suggest that Dengue virus (DENV) transmission is limited by low winter temperatures in the mainland United States, which are likely to prevent its permanent establishment. Although future climate conditions may increase the length of the mosquito season in many locations, projected increases in dengue transmission are limited to the southernmost locations.

Climate change and land use drivers of fecal bacteria in tropical Hawaiian rivers

Treesearch

Ayron M. Strauch; Richard A. Mackenzie; Gregory L. Bruland; Ralph Tingley; Christian P. Giardina

2014-01-01

Potential shifts in rainfall driven by climate change are anticipated to affect watershed processes (e.g., soil moisture, runoff, stream flow), yet few model systems exist in the tropics to test hypotheses about how these processes may respond to these shifts. We used a sequence of nine watersheds on Hawaii Island spanning 3000 mm (7500–4500 mm) of mean annual rainfall...

The Impact Snow Albedo Feedback over Mountain Regions as Examined through High-Resolution Regional Climate Change Experiments over the Rocky Mountains

NASA Astrophysics Data System (ADS)

Letcher, Theodore

As the climate warms, the snow albedo feedback (SAF) will play a substantial role in shaping the climate response of mid-latitude mountain regions with transient snow cover. One such region is the Rocky Mountains of the western United States where large snow packs accumulate during the winter and persist throughout the spring. In this dissertation, the Weather Research and Forecast model (WRF) configured as a regional climate model is used to investigate the role of the SAF in determining the regional climate response to forced anthropogenic climate change. The regional effects of climate change are investigated by using the pseudo global warming (PGW) framework, which is an experimental configuration in a which a mean climate perturbation is added to the boundary forcing of a regional model, thus preserving the large-scale circulation entering the region through the model boundaries and isolating the mesoscale climate response. Using this framework, the impact of the SAF on the regional energetics and atmospheric dynamics is examined and quantified. Linear feedback analysis is used to quantify the strength of the SAF over the Headwaters region of the Colorado Rockies for a series of high-resolution PGW experiments. This technique is used to test sensitivity of the feedback strength to model resolution and land surface model. Over the Colorado Rockies, and integrated over the entire spring season, the SAF strength is largely insensitive to model resolution, however there are more substantial differences on the sub-seasonal (monthly) timescale. In contrast, the SAF strength over this region is very sensitive to choice of land surface model. These simulations are also used to investigate how spatial and diurnal variability in warming caused by the SAF influences the dynamics of thermally driven mountain-breeze circulations. It is shown that, the SAF causes stronger daytime mountain-breeze circulations by increasing the warming on the mountains slopes thus enhancing the thermal contrast between the mountain slopes and the surrounding lowlands which drives these wind systems. This analysis is extended to investigate the impacts that the SAF has on the large-scale mountain-plain circulation that develops east of the Rockies over the Great Plains. To help isolate the SAF, a more idealized regional climate experiment which isolates the SAF is performed. It was found that SAF may influence thermally driven atmospheric dynamics up-to 200km east of the Mountains where the SAF originates, suggesting broader regional impacts of the SAF which may not be well resolved by coarser resolution global climate models. The implications of these changes on pollution transport and moist convection are also explored using these simulations.

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.

Climate-Based Models for Understanding and Forecasting Dengue Epidemics

PubMed Central

Descloux, Elodie; Mangeas, Morgan; Menkes, Christophe Eugène; Lengaigne, Matthieu; Leroy, Anne; Tehei, Temaui; Guillaumot, Laurent; Teurlai, Magali; Gourinat, Ann-Claire; Benzler, Justus; Pfannstiel, Anne; Grangeon, Jean-Paul; Degallier, Nicolas; De Lamballerie, Xavier

2012-01-01

Background Dengue dynamics are driven by complex interactions between human-hosts, mosquito-vectors and viruses that are influenced by environmental and climatic factors. The objectives of this study were to analyze and model the relationships between climate, Aedes aegypti vectors and dengue outbreaks in Noumea (New Caledonia), and to provide an early warning system. Methodology/Principal Findings Epidemiological and meteorological data were analyzed from 1971 to 2010 in Noumea. Entomological surveillance indices were available from March 2000 to December 2009. During epidemic years, the distribution of dengue cases was highly seasonal. The epidemic peak (March–April) lagged the warmest temperature by 1–2 months and was in phase with maximum precipitations, relative humidity and entomological indices. Significant inter-annual correlations were observed between the risk of outbreak and summertime temperature, precipitations or relative humidity but not ENSO. Climate-based multivariate non-linear models were developed to estimate the yearly risk of dengue outbreak in Noumea. The best explicative meteorological variables were the number of days with maximal temperature exceeding 32°C during January–February–March and the number of days with maximal relative humidity exceeding 95% during January. The best predictive variables were the maximal temperature in December and maximal relative humidity during October–November–December of the previous year. For a probability of dengue outbreak above 65% in leave-one-out cross validation, the explicative model predicted 94% of the epidemic years and 79% of the non epidemic years, and the predictive model 79% and 65%, respectively. Conclusions/Significance The epidemic dynamics of dengue in Noumea were essentially driven by climate during the last forty years. Specific conditions based on maximal temperature and relative humidity thresholds were determinant in outbreaks occurrence. Their persistence was also crucial. An operational model that will enable health authorities to anticipate the outbreak risk was successfully developed. Similar models may be developed to improve dengue management in other countries. PMID:22348154

Future projections of insured losses in the German private building sector following the A1B climatic change scenario

NASA Astrophysics Data System (ADS)

Held, H.; Gerstengarbe, F.-W.; Hattermann, F.; Pinto, J. G.; Ulbrich, U.; Böhm, U.; Born, K.; Büchner, M.; Donat, M. G.; Kücken, M.; Leckebusch, G. C.; Nissen, K.; Nocke, T.; Österle, H.; Pardowitz, T.; Werner, P. C.; Burghoff, O.; Broecker, U.; Kubik, A.

2012-04-01

We present an overview of a complementary-approaches impact project dealing with the consequences of climate change for the natural hazard branch of the insurance industry in Germany. The project was conducted by four academic institutions together with the German Insurance Association (GDV) and finalized in autumn 2011. A causal chain is modeled that goes from global warming projections over regional meteorological impacts to regional economic losses for private buildings, hereby fully covering the area of Germany. This presentation will focus on wind storm related losses, although the method developed had also been applied in part to hail and flood impact losses. For the first time, the GDV supplied their collected set of insurance cases, dating back for decades, for such an impact study. These data were used to calibrate and validate event-based damage functions which in turn were driven by three different types of regional climate models to generate storm loss projections. The regional models were driven by a triplet of ECHAM5 experiments following the A1B scenario which were found representative in the recent ENSEMBLES intercomparison study. In our multi-modeling approach we used two types of regional climate models that conceptually differ at maximum: a dynamical model (CCLM) and a statistical model based on the idea of biased bootstrapping (STARS). As a third option we pursued a hybrid approach (statistical-dynamical downscaling). For the assessment of climate change impacts, the buildings' infrastructure and their economic value is kept at current values. For all three approaches, a significant increase of average storm losses and extreme event return levels in the German private building sector is found for future decades assuming an A1B-scenario. However, the three projections differ somewhat in terms of magnitude and regional differentiation. We have developed a formalism that allows us to express the combined effect of multi-source uncertainty on return levels within the framework of a generalized Pareto distribution.

One-way coupling of an integrated assessment model and a water resources model: evaluation and implications of future changes over the US Midwest

NASA Astrophysics Data System (ADS)

Voisin, N.; Liu, L.; Hejazi, M.; Tesfa, T.; Li, H.; Huang, M.; Liu, Y.; Leung, L. R.

2013-11-01

An integrated model is being developed to advance our understanding of the interactions between human activities, terrestrial system and water cycle, and to evaluate how system interactions will be affected by a changing climate at the regional scale. As a first step towards that goal, a global integrated assessment model, which includes a water-demand model driven by socioeconomics at regional and global scales, is coupled in a one-way fashion with a land surface hydrology-routing-water resources management model. To reconcile the scale differences between the models, a spatial and temporal disaggregation approach is developed to downscale the annual regional water demand simulations into a daily time step and subbasin representation. The model demonstrates reasonable ability to represent the historical flow regulation and water supply over the US Midwest (Missouri, Upper Mississippi, and Ohio river basins). Implications for future flow regulation, water supply, and supply deficit are investigated using climate change projections with the B1 and A2 emission scenarios, which affect both natural flow and water demand. Although natural flow is projected to increase under climate change in both the B1 and A2 scenarios, there is larger uncertainty in the changes of the regulated flow. Over the Ohio and Upper Mississippi river basins, changes in flow regulation are driven by the change in natural flow due to the limited storage capacity. However, both changes in flow and demand have effects on the Missouri River Basin summer regulated flow. Changes in demand are driven by socioeconomic factors, energy and food demands, global markets and prices with rainfed crop demand handled directly by the land surface modeling component. Even though most of the changes in supply deficit (unmet demand) and the actual supply (met demand) are driven primarily by the change in natural flow over the entire region, the integrated framework shows that supply deficit over the Missouri River Basin sees an increasing sensitivity to changes in demand in future periods. It further shows that the supply deficit is six times as sensitive as the actual supply to changes in flow and demand. A spatial analysis of the supply deficit demonstrates vulnerabilities of urban areas located along mainstream with limited storage.

Ecosystem Evapotranspiration as a Response to Climate and Vegetation Coverage Changes in Northwest Yunnan, China

PubMed Central

Yang, Hao; Luo, Peng; Wang, Jun; Mou, Chengxiang; Mo, Li; Wang, Zhiyuan; Fu, Yao; Lin, Honghui; Yang, Yongping; Bhatta, Laxmi Dutt

2015-01-01

Climate and human-driven changes play an important role in regional droughts. Northwest Yunnan Province is a key region for biodiversity conservation in China, and it has experienced severe droughts since the beginning of this century; however, the extent of the contributions from climate and human-driven changes remains unclear. We calculated the ecosystem evapotranspiration (ET) and water yield (WY) of northwest Yunnan Province, China from 2001 to 2013 using meteorological and remote sensing observation data and a Surface Energy Balance System (SEBS) model. Multivariate regression analyses were used to differentiate the contribution of climate and vegetation coverage to ET. The results showed that the annual average vegetation coverage significantly increased over time with a mean of 0.69 in spite of the precipitation fluctuation. Afforestation/reforestation and other management efforts attributed to vegetation coverage increase in NW Yunnan. Both ET and WY considerably fluctuated with the climate factors, which ranged from 623.29 mm to 893.8 mm and –51.88 mm to 384.40 mm over the time period. Spatially, ET in the southeast of NW Yunnan (mainly in Lijiang) increased significantly, which was in line with the spatial trend of vegetation coverage. Multivariate linear regression analysis indicated that climatic factors accounted for 85.18% of the ET variation, while vegetation coverage explained 14.82%. On the other hand, precipitation accounted for 67.5% of the WY. We conclude that the continuous droughts in northwest Yunnan were primarily climatically driven; however, man-made land cover and vegetation changes also increased the vulnerability of local populations to drought. Because of the high proportion of the water yield consumed for subsistence and poor infrastructure for water management, local populations have been highly vulnerable to climate drought conditions. We suggest that conservation of native vegetation and development of water-conserving agricultural practices should be implemented as adaptive strategies to mitigate climate change. PMID:26237220

Ecosystem Evapotranspiration as a Response to Climate and Vegetation Coverage Changes in Northwest Yunnan, China.

PubMed

Yang, Hao; Luo, Peng; Wang, Jun; Mou, Chengxiang; Mo, Li; Wang, Zhiyuan; Fu, Yao; Lin, Honghui; Yang, Yongping; Bhatta, Laxmi Dutt

2015-01-01

Climate and human-driven changes play an important role in regional droughts. Northwest Yunnan Province is a key region for biodiversity conservation in China, and it has experienced severe droughts since the beginning of this century; however, the extent of the contributions from climate and human-driven changes remains unclear. We calculated the ecosystem evapotranspiration (ET) and water yield (WY) of northwest Yunnan Province, China from 2001 to 2013 using meteorological and remote sensing observation data and a Surface Energy Balance System (SEBS) model. Multivariate regression analyses were used to differentiate the contribution of climate and vegetation coverage to ET. The results showed that the annual average vegetation coverage significantly increased over time with a mean of 0.69 in spite of the precipitation fluctuation. Afforestation/reforestation and other management efforts attributed to vegetation coverage increase in NW Yunnan. Both ET and WY considerably fluctuated with the climate factors, which ranged from 623.29 mm to 893.8 mm and -51.88 mm to 384.40 mm over the time period. Spatially, ET in the southeast of NW Yunnan (mainly in Lijiang) increased significantly, which was in line with the spatial trend of vegetation coverage. Multivariate linear regression analysis indicated that climatic factors accounted for 85.18% of the ET variation, while vegetation coverage explained 14.82%. On the other hand, precipitation accounted for 67.5% of the WY. We conclude that the continuous droughts in northwest Yunnan were primarily climatically driven; however, man-made land cover and vegetation changes also increased the vulnerability of local populations to drought. Because of the high proportion of the water yield consumed for subsistence and poor infrastructure for water management, local populations have been highly vulnerable to climate drought conditions. We suggest that conservation of native vegetation and development of water-conserving agricultural practices should be implemented as adaptive strategies to mitigate climate change.

A large ozone-circulation feedback and its implications for global warming assessments.

PubMed

Nowack, Peer J; Abraham, N Luke; Maycock, Amanda C; Braesicke, Peter; Gregory, Jonathan M; Joshi, Manoj M; Osprey, Annette; Pyle, John A

2015-01-01

State-of-the-art climate models now include more climate processes which are simulated at higher spatial resolution than ever 1 . Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations 1,2 . Here we present evidence that how stratospheric ozone is represented in climate models can have a first order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere-ocean chemistry-climate model, we find an increase in global mean surface warming of around 1°C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO 2 forcing. The difference is primarily attributed to changes in longwave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies 1,2 in which participating models often use simplified treatments of atmospheric composition changes that are neither consistent with the specified greenhouse gas forcing scenario nor with the associated atmospheric circulation feedbacks 3-5 .

Insights on the energy-water nexus through modeling of the integrated water cycle

NASA Astrophysics Data System (ADS)

Leung, L. R.; Li, H. Y.; Zhang, X.; Wan, W.; Voisin, N.; Leng, G.

2016-12-01

For sustainable energy planning, understanding the impacts of climate change, land use change, and water management is essential as they all exert notable controls on streamflow and stream temperature that influence energy production. An integrated water model representing river processes, irrigation water use and water management has been developed and coupled to a land surface model to investigate the energy-water nexus. Simulations driven by two climate change projections with the RCP 4.5 and RCP 8.5 emissions scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature. The simulations revealed important impacts of climate change and water management on both floods and droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the climate mitigation (RCP 4.5) and business as usual (RCP 8.5) scenarios that influence streamflow and stream temperature, with important consequences to energy production. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME) to enable investigation of the energy-water nexus in the fully coupled Earth system.

Analysis of the variability of the North Atlantic eddy-driven jet stream in CMIP5

NASA Astrophysics Data System (ADS)

Iqbal, Waheed; Leung, Wai-Nang; Hannachi, Abdel

2017-09-01

The North Atlantic eddy-driven jet is a dominant feature of extratropical climate and its variability is associated with the large-scale changes in the surface climate of midlatitudes. Variability of this jet is analysed in a set of General Circulation Models (GCMs) from the Coupled Model Inter-comparison Project phase-5 (CMIP5) over the North Atlantic region. The CMIP5 simulations for the 20th century climate (Historical) are compared with the ERA40 reanalysis data. The jet latitude index, wind speed and jet persistence are analysed in order to evaluate 11 CMIP5 GCMs and to compare them with those from CMIP3 integrations. The phase of mean seasonal cycle of jet latitude and wind speed from historical runs of CMIP5 GCMs are comparable to ERA40. The wind speed mean seasonal cycle by CMIP5 GCMs is overestimated in winter months. A positive (negative) jet latitude anomaly in historical simulations relative to ERA40 is observed in summer (winter). The ensemble mean of jet latitude biases in historical simulations of CMIP3 and CMIP5 with respect to ERA40 are -2.43° and -1.79° respectively. Thus indicating improvements in CMIP5 in comparison to the CMIP3 GCMs. The comparison of historical and future simulations of CMIP5 under RCP4.5 and RCP8.5 for the period 2076-2099, shows positive anomalies in the jet latitude implying a poleward shifted jet. The results from the analysed models offer no specific improvements in simulating the trimodality of the eddy-driven jet.

An assessment of the distribution and spread of the tick Hyalomma marginatum in the western Palearctic under different climate scenarios.

PubMed

Estrada-Peña, Agustín; Sánchez, Nely; Estrada-Sánchez, Adrián

2012-09-01

We applied a process-driven model to evaluate the impact of climate scenarios for the years 2020, 2050, and 2080 on the life cycle of Hyalomma marginatum ticks in the western Palearctic. The net growth rate of the tick populations increased in every scenario tested compared to the current climate baseline. These results support the expectations of increased tick survival and increased population turnover in future climate scenarios. We included a basic evaluation of host movement based on rules connected to altitude, slope, size of the near patches, and inter-patch distances in the real landscape over the target area. Data on landscape were obtained from medium-resolution MODIS satellite imagery, which allowed us to test the potential spread of the populations. Such a model of host dispersal linked to the process-driven life cycle model demonstrated that eastern (Turkey, Russia, and Balkans) populations of H. marginatum currently are well separated and have little mixing with western (Italy, Spain, and northern Africa) populations. The northern limit is marked by the cold areas in the Balkans, Alps, and Pyrenees. Under the warmer conditions predicted by the climate scenarios, the exchange of ticks throughout new areas, previously free of the vector, is expected to increase, mainly in the Balkans and southern Russia, over the limit of the mountain ranges. Therefore, the northern limit of the tick range would increase. Additional studies are necessary to understand the implications of host changes in range and abundance for H. marginatum and Crimean-Congo hemorrhagic fever virus.

A Statistical Modeling Framework for Projecting Future Ambient Ozone and its Health Impact due to Climate Change

PubMed Central

Chang, Howard H.; Hao, Hua; Sarnat, Stefanie Ebelt

2014-01-01

The adverse health effects of ambient ozone are well established. Given the high sensitivity of ambient ozone concentrations to meteorological conditions, the impacts of future climate change on ozone concentrations and its associated health effects are of concern. We describe a statistical modeling framework for projecting future ozone levels and its health impacts under a changing climate. This is motivated by the continual effort to evaluate projection uncertainties to inform public health risk assessment. The proposed approach was applied to the 20-county Atlanta metropolitan area using regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program. Future ozone levels and ozone-related excesses in asthma emergency department (ED) visits were examined for the period 2041–2070. The computationally efficient approach allowed us to consider 8 sets of climate model outputs based on different combinations of 4 RCMs and 4 general circulation models. Compared to the historical period of 1999–2004, we found consistent projections across climate models of an average 11.5% higher ozone levels (range: 4.8%, 16.2%), and an average 8.3% (range: −7% to 24%) higher number of ozone exceedance days. Assuming no change in the at-risk population, this corresponds to excess ozone-related ED visits ranging from 267 to 466 visits per year. Health impact projection uncertainty was driven predominantly by uncertainty in the health effect association and climate model variability. Calibrating climate simulations with historical observations reduced differences in projections across climate models. PMID:24764746

Structural uncertainty of downscaled climate model output in a difficult-to-resolve environment: data sparseness and parameterization error contribution to statistical and dynamical downscaling output in the U.S. Caribbean region

NASA Astrophysics Data System (ADS)

Terando, A. J.; Grade, S.; Bowden, J.; Henareh Khalyani, A.; Wootten, A.; Misra, V.; Collazo, J.; Gould, W. A.; Boyles, R.

2016-12-01

Sub-tropical island nations may be particularly vulnerable to anthropogenic climate change because of predicted changes in the hydrologic cycle that would lead to significant drying in the future. However, decision makers in these regions have seen their adaptation planning efforts frustrated by the lack of island-resolving climate model information. Recently, two investigations have used statistical and dynamical downscaling techniques to develop climate change projections for the U.S. Caribbean region (Puerto Rico and U.S. Virgin Islands). We compare the results from these two studies with respect to three commonly downscaled CMIP5 global climate models (GCMs). The GCMs were dynamically downscaled at a convective-permitting scale using two different regional climate models. The statistical downscaling approach was conducted at locations with long-term climate observations and then further post-processed using climatologically aided interpolation (yielding two sets of projections). Overall, both approaches face unique challenges. The statistical approach suffers from a lack of observations necessary to constrain the model, particularly at the land-ocean boundary and in complex terrain. The dynamically downscaled model output has a systematic dry bias over the island despite ample availability of moisture in the atmospheric column. Notwithstanding these differences, both approaches are consistent in projecting a drier climate that is driven by the strong global-scale anthropogenic forcing.

Comparing the Global Charcoal Database with Burned Area Trends from an Offline Fire Model Driven by the NCAR Last Millennium Ensemble

NASA Astrophysics Data System (ADS)

Schaefer, A.; Magi, B. I.; Marlon, J. R.; Bartlein, P. J.

2017-12-01

This study uses an offline fire model driven by output from the NCAR Community Earth System Model Last Millennium Ensemble (LME) to evaluate how climate, ecological, and human factors contributed to burned area over the past millennium, and uses the Global Charcoal Database (GCD) record of fire activity as a constraint. The offline fire model is similar to the fire module within the NCAR Community Land Model. The LME experiment includes 13 simulations of the Earth system from 850 CE through 2005 CE, and the fire model simulates burned area using LME climate and vegetation with imposed land use and land cover change. The fire model trends are compared to GCD records of charcoal accumulation rates derived from sediment cores. The comparisons are a way to assess the skill of the fire model, but also set up a methodology to directly test hypotheses of the main drivers of fire patterns over the past millennium. The focus is on regions selected from the GCD with high data density, and that have lake sediment cores that best capture the last millennium. Preliminary results are based on a fire model which excludes burning cropland and pasture land cover types, but this allows some assessment of how climate variability is captured by the fire model. Generally, there is good agreement between modeled burned area trends and fire trends from GCD for many regions of interest, suggesting the strength of climate variability as a control. At the global scale, trends and features are similar from 850 to 1700, which includes the Medieval Climate Anomaly and the Little Ice Age. After 1700, the trends significantly deviate, which may be due to non-cultivated land being converted to cultivated. In key regions of high data density in the GCD such as the Western USA, the trends agree from 850 to 1200 but diverge from 1200 to 1300. From 1300 to 1800, the trends show good agreement again. Implementing processes to include burning cultivated land within the fire model is anticipated to improve the agreement, but also to test the sensitivity of models to different drivers of fire.

Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate.

PubMed

Williams, Hefin Wyn; Cross, Dónall Eoin; Crump, Heather Louise; Drost, Cornelis Jan; Thomas, Christopher James

2015-08-28

There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors. We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs). Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution. By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of climate change in the future.

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

Kyle, G. Page; Mueller, C.; Calvin, Katherine V.

This study assesses how climate impacts on agriculture may change the evolution of the agricultural and energy systems in meeting the end-of-century radiative forcing targets of the Representative Concentration Pathways (RCPs). We build on the recently completed ISI-MIP exercise that has produced global gridded estimates of future crop yields for major agricultural crops using climate model projections of the RCPs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For this study we use the bias-corrected outputs of the HadGEM2-ES climate model as inputs to the LPJmL crop growth model, and the outputs of LPJmL to modify inputs to themore » GCAM integrated assessment model. Our results indicate that agricultural climate impacts generally lead to an increase in global cropland, as compared with corresponding emissions scenarios that do not consider climate impacts on agricultural productivity. This is driven mostly by negative impacts on wheat, rice, other grains, and oil crops. Still, including agricultural climate impacts does not significantly increase the costs or change the technological strategies of global, whole-system emissions mitigation. In fact, to meet the most aggressive climate change mitigation target (2.6 W/m2 in 2100), the net mitigation costs are slightly lower when agricultural climate impacts are considered. Key contributing factors to these results are (a) low levels of climate change in the low-forcing scenarios, (b) adaptation to climate impacts, simulated in GCAM through inter-regional shifting in the production of agricultural goods, and (c) positive average climate impacts on bioenergy crop yields.« less

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

NASA Astrophysics Data System (ADS)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Synergy between land use and climate change increases future fire risk in Amazon forests

DOE PAGES

Le Page, Yannick; Morton, Douglas; Hartin, Corinne; ...

2017-12-20

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactionsmore » between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.« less

Synergy between land use and climate change increases future fire risk in Amazon forests

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

Le Page, Yannick; Morton, Douglas; Hartin, Corinne

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactionsmore » between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.« less

An eco-hydrologic model of malaria outbreaks

NASA Astrophysics Data System (ADS)

Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.

2012-03-01

Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission and their consideration alongside climatic datasets. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear eco-hydrologic model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.

Climate-driven uncertainties in modeling terrestrial gross primary production: a site level to global-scale analysis.

PubMed

Barman, Rahul; Jain, Atul K; Liang, Miaoling

2014-05-01

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2)  yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes using a single modeling framework. © 2013 John Wiley & Sons Ltd.

The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies

NASA Astrophysics Data System (ADS)

Pincus, R.; Stevens, B. B.; Forster, P.; Collins, W.; Ramaswamy, V.

2014-12-01

The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies An enormous amount of attention has been paid to the diversity of responses in the CMIP and other multi-model ensembles. This diversity is normally interpreted as a distribution in climate sensitivity driven by some distribution of feedback mechanisms. Identification of these feedbacks relies on precise identification of the forcing to which each model is subject, including distinguishing true error from model diversity. The Radiative Forcing Model Intercomparison Project (RFMIP) aims to disentangle the role of forcing from model sensitivity as determinants of varying climate model response by carefully characterizing the radiative forcing to which such models are subject and by coordinating experiments in which it is specified. RFMIP consists of four activities: 1) An assessment of accuracy in flux and forcing calculations for greenhouse gases under past, present, and future climates, using off-line radiative transfer calculations in specified atmospheres with climate model parameterizations and reference models 2) Characterization and assessment of model-specific historical forcing by anthropogenic aerosols, based on coordinated diagnostic output from climate models and off-line radiative transfer calculations with reference models 3) Characterization of model-specific effective radiative forcing, including contributions of model climatology and rapid adjustments, using coordinated climate model integrations and off-line radiative transfer calculations with a single fast model 4) Assessment of climate model response to precisely-characterized radiative forcing over the historical record, including efforts to infer true historical forcing from patterns of response, by direct specification of non-greenhouse-gas forcing in a series of coordinated climate model integrations This talk discusses the rationale for RFMIP, provides an overview of the four activities, and presents preliminary motivating results.

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

Influence of climate drivers on colonization and extinction dynamics of wetland-dependent species

USGS Publications Warehouse

Ray, Andrew M.; Gould, William R.; Hossack, Blake R.; Sepulveda, Adam; Thoma, David P.; Patla, Debra A.; Daley, Rob; Al-Chokhachy, Robert K.

2016-01-01

Freshwater wetlands are particularly vulnerable to climate change. Specifically, changes in temperature, precipitation, and evapotranspiration (i.e., climate drivers) are likely to alter flooding regimes of wetlands and affect the vital rates, abundance, and distributions of wetland-dependent species. Amphibians may be among the most climate-sensitive wetland-dependent groups, as many species rely on shallow or intermittently flooded wetland habitats for breeding. Here, we integrated multiple years of high-resolution gridded climate and amphibian monitoring data from Grand Teton and Yellowstone National Parks to explicitly model how variations in climate drivers and habitat conditions affect the occurrence and breeding dynamics (i.e., annual extinction and colonization rates) of amphibians. Our results showed that models incorporating climate drivers outperformed models of amphibian breeding dynamics that were exclusively habitat based. Moreover, climate-driven variation in extinction rates, but not colonization rates, disproportionately influenced amphibian occupancy in monitored wetlands. Long-term monitoring from national parks coupled with high-resolution climate data sets will be crucial to describing population dynamics and characterizing the sensitivity of amphibians and other wetland-dependent species to climate change. Further, long-term monitoring of wetlands in national parks will help reduce uncertainty surrounding wetland resources and strengthen opportunities to make informed, science-based decisions that have far-reaching benefits.

Human amplification of drought-driven fire in tropical regions

NASA Astrophysics Data System (ADS)

Tosca, Michael

2015-04-01

The change in globally-measured radiative forcing from the pre-industrial to the present due to interactions between aerosol particles and cloud cover has the largest uncertainty of all anthropogenic factors. Uncertainties are largest in the tropics, where total cloud amount and incoming solar radiation are highest, and where 50% of all aerosol emissions originate from anthropogenic fire. It is well understood that interactions between smoke particles and cloud droplets modify cloud cover , which in turn affects climate, however, few studies have observed the temporal nature of aerosol-cloud interactions without the use of a model. Here we apply a novel approach to measure the effect of fire aerosols on convective clouds in tropical regions (Brazil, Africa and Indonesia) through a combination of remote sensing and meteorological data. We attribute a reduction in cloud fraction during periods of high aerosol optical depths to a smoke-driven inhibition of convection. We find that higher smoke burdens limit vertical updrafts, increase surface pressure, and increase low- level divergence-meteorological indicators of convective suppression. These results are corroborated by climate model simulations that show a smoke-driven increase in regionally averaged shortwave tropospheric heating and boundary layer stratification, and a decrease in vertical velocity and precipitation during the fire season (December-February). We then quantify the human response to decreased cloud cover using a combination of socioeconomic and climate data Our results suggest that, in tropical regions, anthropogenic fire initiates a positive feedback loop where increased aerosol emissions limit convection, dry the surface and enable increased fire activity via human ignition. This result has far-reaching implications for fire management and climate policy in emerging countries along the equator that utilize fire.

The role of climate in the global patterns of ecosystem carbon turnover rates - contrasts between data and models

NASA Astrophysics Data System (ADS)

Carvalhais, N.; Forkel, M.; Khomik, M.; Bellarby, J.; Migliavacca, M.; Thurner, M.; Beer, C.; Jung, M.; Mu, M.; Randerson, J. T.; Saatchi, S. S.; Santoro, M.; Reichstein, M.

2012-12-01

The turnover rates of carbon in terrestrial ecosystems and their sensitivity to climate are instrumental properties for diagnosing the interannual variability and forecasting trends of biogeochemical processes and carbon-cycle-climate feedbacks. We propose to globally look at the spatial distribution of turnover rates of carbon to explore the association between bioclimatic regimes and the rates at which carbon cycles in terrestrial ecosystems. Based on data-driven approaches of ecosystem carbon fluxes and data-based estimates of ecosystem carbon stocks it is possible to build fully observationally supported diagnostics. These data driven diagnostics support the benchmarking of CMIP5 model outputs (Coupled Model Intercomparison Project Phase 5) with observationally based estimates. The models' performance is addressed by confronting spatial patterns of carbon fluxes and stocks with data, as well as the global and regional sensitivities of turnover rates to climate. Our results show strong latitudinal gradients globally, mostly controlled by temperature, which are not always paralleled by CMIP5 simulations. In northern colder regions is also where the largest difference in temperature sensitivity between models and data occurs. Interestingly, there seem to be two different statistical populations in the data (some with high, others with low apparent temperature sensitivity of carbon turnover rates), where the different models only seem to describe either one or the other population. Additionally, the comparisons within bioclimatic classes can even show opposite patterns between turnover rates and temperature in water limited regions. Overall, our analysis emphasizes the role of finding patterns and intrinsic properties instead of plain magnitudes of fluxes for diagnosing the sensitivities of terrestrial biogeochemical cycles to climate. Further, our regional analysis suggests a significant gap in addressing the partial influence of water in the ecosystem carbon turnover rates especially in very cold or water limited regions.

An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

NASA Astrophysics Data System (ADS)

Velázquez, J. A.; Schmid, J.; Ricard, S.; Muerth, M. J.; Gauvin St-Denis, B.; Minville, M.; Chaumont, D.; Caya, D.; Ludwig, R.; Turcotte, R.

2012-06-01

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs' members over a reference (1971-2000) and a future (2041-2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

DTIC Science & Technology

2012-09-30

characterization of extratropical storms and extremes and link these to LFV modes. Mingfang Ting, Yochanan Kushnir, Andrew W. Robertson...simulating and predicting a wide range of climate phenomena including ENSO, tropical Atlantic sea surface temperatures (SSTs), storm track variability...into empirical prediction models. Use observations to improve low-order dynamical MJO models. Adam Sobel, Daehyun Kim. Extratropical variability

Test Driven Development of a Parameterized Ice Sheet Component

NASA Astrophysics Data System (ADS)

Clune, T.

2011-12-01

Test driven development (TDD) is a software development methodology that offers many advantages over traditional approaches including reduced development and maintenance costs, improved reliability, and superior design quality. Although TDD is widely accepted in many software communities, the suitability to scientific software is largely undemonstrated and warrants a degree of skepticism. Indeed, numerical algorithms pose several challenges to unit testing in general, and TDD in particular. Among these challenges are the need to have simple, non-redundant closed-form expressions to compare against the results obtained from the implementation as well as realistic error estimates. The necessity for serial and parallel performance raises additional concerns for many scientific applicaitons. In previous work I demonstrated that TDD performed well for the development of a relatively simple numerical model that simulates the growth of snowflakes, but the results were anecdotal and of limited relevance to far more complex software components typical of climate models. This investigation has now been extended by successfully applying TDD to the implementation of a substantial portion of a new parameterized ice sheet component within a full climate model. After a brief introduction to TDD, I will present techniques that address some of the obstacles encountered with numerical algorithms. I will conclude with some quantitative and qualitative comparisons against climate components developed in a more traditional manner.

On the stability of the Atlantic meridional overturning circulation.

PubMed

Hofmann, Matthias; Rahmstorf, Stefan

2009-12-08

One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC.

Climate-based models for West Nile Culex mosquito vectors in the Northeastern US

NASA Astrophysics Data System (ADS)

Gong, Hongfei; Degaetano, Arthur T.; Harrington, Laura C.

2011-05-01

Climate-based models simulating Culex mosquito population abundance in the Northeastern US were developed. Two West Nile vector species, Culex pipiens and Culex restuans, were included in model simulations. The model was optimized by a parameter-space search within biological bounds. Mosquito population dynamics were driven by major environmental factors including temperature, rainfall, evaporation rate and photoperiod. The results show a strong correlation between the timing of early population increases (as early warning of West Nile virus risk) and decreases in late summer. Simulated abundance was highly correlated with actual mosquito capture in New Jersey light traps and validated with field data. This climate-based model simulates the population dynamics of both the adult and immature mosquito life stage of Culex arbovirus vectors in the Northeastern US. It is expected to have direct and practical application for mosquito control and West Nile prevention programs.

The Biasing Influence of Worldview on Climate Change Attitudes

NASA Astrophysics Data System (ADS)

Cook, J.

2012-12-01

It is well established that political ideology has a strong influence on public opinion about climate change. According to one survey (Leiserowitz et al 2011), the percentage of Democrats accepting that climate change is happening is over double the percentage of Tea Partiers. There is also evidence of ideologically driven belief polarization, where two people receiving the same evidence update their beliefs in opposite direction. Presenting scientific evidence can result in a backfire effect where conservatives become more sceptical of climate change. It is possible to model (and hence better understand) the backfire effect using Bayesian Networks which simulate belief updating using Bayes Law. In this model, trust in science is the driving force behind polarization and worldview is the knob that controls trust. One consequence of this model is that attempts to increase trust in science are expected to be largely ineffective for conservatives. It suggests that a potentially constructive approach is to reduce the biasing influence of worldview by affirming conservative values while presenting climate messages. Experimental data comparing the effectiveness of various interventions are presented and discussed in the context of the Bayesian Network model.

A method for physically based model analysis of conjunctive use in response to potential climate changes

USGS Publications Warehouse

Hanson, R.T.; Flint, L.E.; Flint, A.L.; Dettinger, M.D.; Faunt, C.C.; Cayan, D.; Schmid, W.

2012-01-01

Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater-surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply-constrained and demand-driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation-runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL-A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley-wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento-San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.

Climate-driven thresholds for chemical weathering in postglacial soils of New Zealand

NASA Astrophysics Data System (ADS)

Dixon, Jean L.; Chadwick, Oliver A.; Vitousek, Peter M.

2016-09-01

Chemical weathering in soils dissolves and alters minerals, mobilizes metals, liberates nutrients to terrestrial and aquatic ecosystems, and may modulate Earth's climate over geologic time scales. Climate-weathering relationships are often considered fundamental controls on the evolution of Earth's surface and biogeochemical cycles. However, surprisingly little consensus has emerged on if and how climate controls chemical weathering, and models and data from published literature often give contrasting correlations and predictions for how weathering rates and climate variables such as temperature or moisture are related. Here we combine insights gained from the different approaches, methods, and theory of the soil science, biogeochemistry, and geomorphology communities to tackle the fundamental question of how rainfall influences soil chemical properties. We explore climate-driven variations in weathering and soil development in young, postglacial soils of New Zealand, measuring soil elemental geochemistry along a large precipitation gradient (400-4700 mm/yr) across the Waitaki basin on Te Waipounamu, the South Island. Our data show a strong climate imprint on chemical weathering in these young soils. This climate control is evidenced by rapid nonlinear changes along the gradient in total and exchangeable cations in soils and in the increased movement and redistribution of metals with rainfall. The nonlinear behavior provides insight into why climate-weathering relationships may be elusive in some landscapes. These weathering thresholds also have significant implications for how climate may influence landscape evolution and the release of rock-derived nutrients to ecosystems, as landscapes that transition to wetter climates across this threshold may weather and deplete rapidly.

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

NASA Technical Reports Server (NTRS)

Hoffert, M. I.

1986-01-01

Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout

USGS Publications Warehouse

Bassar, Ronald D.; Letcher, Benjamin H.; Nislow, Keith H.; Whiteley, Andrew R.

2016-01-01

Understanding how multiple extrinsic (density-independent) factors and intrinsic (density-dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density-dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) versus density-dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10-year capture-mark-recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete-time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density-dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate-driven environmental change.

On the long-term memory of the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Rogozhina, I.; Martinec, Z.; Hagedoorn, J. M.; Thomas, M.; Fleming, K.

2011-03-01

In this study, the memory of the Greenland Ice Sheet (GIS) with respect to its past states is analyzed. According to ice core reconstructions, the present-day GIS reflects former climatic conditions dating back to at least 250 thousand years before the present (kyr BP). This fact must be considered when initializing an ice sheet model. The common initialization techniques are paleoclimatic simulations driven by atmospheric forcing inferred from ice core records and steady state simulations driven by the present-day or past climatic conditions. When paleoclimatic simulations are used, the information about the past climatic conditions is partly reflected in the resulting present-day state of the GIS. However, there are several important questions that need to be clarified. First, for how long does the model remember its initial state? Second, it is generally acknowledged that, prior to 100 kyr BP, the longest Greenland ice core record (GRIP) is distorted by ice-flow irregularities. The question arises as to what extent do the uncertainties inherent in the GRIP-based forcing influence the resulting GIS? Finally, how is the modeled thermodynamic state affected by the choice of initialization technique (paleo or steady state)? To answer these questions, a series of paleoclimatic and steady state simulations is carried out. We conclude that (1) the choice of an ice-covered initial configuration shortens the initialization simulation time to 100 kyr, (2) the uncertainties in the GRIP-based forcing affect present-day modeled ice-surface topographies and temperatures only slightly, and (3) the GIS forced by present-day climatic conditions is overall warmer than that resulting from a paleoclimatic simulation.

Socio-Hydrology Modelling for an Uncertain Future, with Examples from the USA and Canada (Invited)

NASA Astrophysics Data System (ADS)

White, D. D.; Gober, P.; Sampson, D. A.; Quay, R.; Kirkwood, C.

2013-12-01

Socio-hydrology brings an interest in human values, markets, social organizations and public policy to the traditional emphasis of water science on climate, hydrology, toxicology,and ecology. It also conveys a decision focus in the form of decision support tools, engagement, and new knowledge about the science-policy interface. This paper demonstrates how policy decisions and human behavior can be better integrated into climate and hydrological models to improve their usefulness for support in decision making. Examples from the Southwest USA and Western Canada highlight uncertainties, vulnerabilities, and critical tradeoffs facing water decision makers in the face of rapidly changing environmental and societal conditions. Irreducible uncertainties in downscaled climate and hydrological models limit the usefulness of climate-driven, predict-and-plan methods of water resource planning and management. Thus, it is argued that such methods should be replaced by approaches that use exploratory modelling, scenario planning, and risk assessment in which the emphasis is on managing uncertainty rather than on reducing it.

Projected changes to short- and long-duration precipitation extremes over the Canadian Prairie Provinces

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2017-09-01

The effects of climate change on April-October short- and long-duration precipitation extremes over the Canadian Prairie Provinces were evaluated using a multi-Regional Climate Model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by the National Centre for Environmental Prediction (NCEP) reanalysis II product for the 1981-2000 period and those driven by four Atmosphere-Ocean General Circulation Models (AOGCMs) for the current 1971-2000 and future 2041-2070 periods (i.e. a total of 11 current-to-future period simulation pairs). A regional frequency analysis approach was used to develop 2-, 5-, 10-, 25-, and 50-year return values of precipitation extremes from NCEP and AOGCM-driven current and future period simulations that respectively were used to study the performance of RCMs and projected changes for selected return values at regional, grid-cell and local scales. Performance errors due to internal dynamics and physics of RCMs studied for the 1981-2000 period reveal considerable variation in the performance of the RCMs. However, the performance errors were found to be much smaller for RCM ensemble averages than for individual RCMs. Projected changes in future climate to selected regional return values of short-duration (e.g. 15- and 30-min) precipitation extremes and for longer return periods (e.g. 50-year) were found to be mostly larger than those to the longer duration (e.g. 24- and 48-h) extremes and short return periods (e.g. 2-year). Overall, projected changes in precipitation extremes were larger for southeastern regions followed by southern and northern regions and smaller for southwestern and western regions of the study area. The changes to return values were also found to be statistically significant for the majority of the RCM-AOGCM simulation pairs. These projections might be useful as a key input for the future planning of urban drainage infrastructure and development of strategic climate change adaptation measures.

Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades

USGS Publications Warehouse

Zhu, Qiuan; Peng, Changhui; Liu, Jinxun; Jiang, Hong; Fang, Xiuqin; Chen, Huai; Niu, Zhichun; Gong, Peng; Lin, Guanghui; Wang, Meng; Yang, Yanzheng; Chang, Jie; Ge, Ying; Xiang, Wenhua; Deng, Xiangwen; He, Jin-Sheng

2016-01-01

Both anthropogenic activities and climate change can affect the biogeochemical processes of natural wetland methanogenesis. Quantifying possible impacts of changing climate and wetland area on wetland methane (CH4) emissions in China is important for improving our knowledge on CH4 budgets locally and globally. However, their respective and combined effects are uncertain. We incorporated changes in wetland area derived from remote sensing into a dynamic CH4 model to quantify the human and climate change induced contributions to natural wetland CH4 emissions in China over the past three decades. Here we found that human-induced wetland loss contributed 34.3% to the CH4 emissions reduction (0.92 TgCH4), and climate change contributed 20.4% to the CH4 emissions increase (0.31 TgCH4), suggesting that decreasing CH4 emissions due to human-induced wetland reductions has offset the increasing climate-driven CH4 emissions. With climate change only, temperature was a dominant controlling factor for wetland CH4 emissions in the northeast (high latitude) and Qinghai-Tibet Plateau (high altitude) regions, whereas precipitation had a considerable influence in relative arid north China. The inevitable uncertainties caused by the asynchronous for different regions or periods due to inter-annual or seasonal variations among remote sensing images should be considered in the wetland CH4 emissions estimation.

Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades

PubMed Central

Zhu, Qiuan; Peng, Changhui; Liu, Jinxun; Jiang, Hong; Fang, Xiuqin; Chen, Huai; Niu, Zhenguo; Gong, Peng; Lin, Guanghui; Wang, Meng; Wang, Han; Yang, Yanzheng; Chang, Jie; Ge, Ying; Xiang, Wenhua; Deng, Xiangwen; He, Jin-Sheng

2016-01-01

Both anthropogenic activities and climate change can affect the biogeochemical processes of natural wetland methanogenesis. Quantifying possible impacts of changing climate and wetland area on wetland methane (CH4) emissions in China is important for improving our knowledge on CH4 budgets locally and globally. However, their respective and combined effects are uncertain. We incorporated changes in wetland area derived from remote sensing into a dynamic CH4 model to quantify the human and climate change induced contributions to natural wetland CH4 emissions in China over the past three decades. Here we found that human-induced wetland loss contributed 34.3% to the CH4 emissions reduction (0.92 TgCH4), and climate change contributed 20.4% to the CH4 emissions increase (0.31 TgCH4), suggesting that decreasing CH4 emissions due to human-induced wetland reductions has offset the increasing climate-driven CH4 emissions. With climate change only, temperature was a dominant controlling factor for wetland CH4 emissions in the northeast (high latitude) and Qinghai-Tibet Plateau (high altitude) regions, whereas precipitation had a considerable influence in relative arid north China. The inevitable uncertainties caused by the asynchronous for different regions or periods due to inter-annual or seasonal variations among remote sensing images should be considered in the wetland CH4 emissions estimation. PMID:27892535

Development of a database-driven system for simulating water temperature in the lower Yakima River main stem, Washington, for various climate scenarios

USGS Publications Warehouse

Voss, Frank; Maule, Alec

2013-01-01

A model for simulating daily maximum and mean water temperatures was developed by linking two existing models: one developed by the U.S. Geological Survey and one developed by the Bureau of Reclamation. The study area included the lower Yakima River main stem between the Roza Dam and West Richland, Washington. To automate execution of the labor-intensive models, a database-driven model automation program was developed to decrease operation costs, to reduce user error, and to provide the capability to perform simulations quickly for multiple management and climate change scenarios. Microsoft© SQL Server 2008 R2 Integration Services packages were developed to (1) integrate climate, flow, and stream geometry data from diverse sources (such as weather stations, a hydrologic model, and field measurements) into a single relational database; (2) programmatically generate heavily formatted model input files; (3) iteratively run water temperature simulations; (4) process simulation results for export to other models; and (5) create a database-driven infrastructure that facilitated experimentation with a variety of scenarios, node permutations, weather data, and hydrologic conditions while minimizing costs of running the model with various model configurations. As a proof-of-concept exercise, water temperatures were simulated for a "Current Conditions" scenario, where local weather data from 1980 through 2005 were used as input, and for "Plus 1" and "Plus 2" climate warming scenarios, where the average annual air temperatures used in the Current Conditions scenario were increased by 1degree Celsius (°C) and by 2°C, respectively. Average monthly mean daily water temperatures simulated for the Current Conditions scenario were compared to measured values at the Bureau of Reclamation Hydromet gage at Kiona, Washington, for 2002-05. Differences ranged between 1.9° and 1.1°C for February, March, May, and June, and were less than 0.8°C for the remaining months of the year. The difference between current conditions and measured monthly values for the two warmest months (July and August) were 0.5°C and 0.2°C, respectively. The model predicted that water temperature generally becomes less sensitive to air temperature increases as the distance from the mouth of the river decreases. As a consequence, the difference between climate warming scenarios also decreased. The pattern of decreasing sensitivity is most pronounced from August to October. Interactive graphing tools were developed to explore the relative sensitivity of average monthly and mean daily water temperature to increases in air temperature for model output locations along the lower Yakima River main stem.

Untangling climate signals from autogenic changes in long-term peatland development

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Baird, Andy J.; Young, Dylan M.; Swindles, Graeme T.

2015-12-01

Peatlands represent important archives of Holocene paleoclimatic information. However, autogenic processes may disconnect peatland hydrological behavior from climate and overwrite climatic signals in peat records. We use a simulation model of peatland development driven by a range of Holocene climate reconstructions to investigate climate signal preservation in peat records. Simulated water-table depths and peat decomposition profiles exhibit homeostatic recovery from prescribed changes in rainfall, whereas changes in temperature cause lasting alterations to peatland structure and function. Autogenic ecohydrological feedbacks provide both high- and low-pass filters for climatic information, particularly rainfall. Large-magnitude climatic changes of an intermediate temporal scale (i.e., multidecadal to centennial) are most readily preserved in our simulated peat records. Simulated decomposition signals are offset from the climatic changes that generate them due to a phenomenon known as secondary decomposition. Our study provides the mechanistic foundations for a framework to separate climatic and autogenic signals in peat records.

Convection-Resolving Climate Change Simulations: Intensification of Heavy Hourly Precipitation Events

NASA Astrophysics Data System (ADS)

Ban, N.; Schmidli, J.; Schar, C.

2014-12-01

Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavy precipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Schӓr (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478

Climate and southern Africa's water-energy-food nexus

NASA Astrophysics Data System (ADS)

Conway, Declan; van Garderen, Emma Archer; Deryng, Delphine; Dorling, Steve; Krueger, Tobias; Landman, Willem; Lankford, Bruce; Lebek, Karen; Osborn, Tim; Ringler, Claudia; Thurlow, James; Zhu, Tingju; Dalin, Carole

2015-09-01

In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven, for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and gross domestic product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose: the Southern African Development Community, the Southern African Power Pool and trade of agricultural products amounting to significant transfers of embedded water.

Non-linear responses of glaciated prairie wetlands to climate warming

USGS Publications Warehouse

Johnson, W. Carter; Werner, Brett; Guntenspergen, Glenn R.

2016-01-01

The response of ecosystems to climate warming is likely to include threshold events when small changes in key environmental drivers produce large changes in an ecosystem. Wetlands of the Prairie Pothole Region (PPR) are especially sensitive to climate variability, yet the possibility that functional changes may occur more rapidly with warming than expected has not been examined or modeled. The productivity and biodiversity of these wetlands are strongly controlled by the speed and completeness of a vegetation cover cycle driven by the wet and dry extremes of climate. Two thresholds involving duration and depth of standing water must be exceeded every few decades or so to complete the cycle and to produce highly functional wetlands. Model experiments at 19 weather stations employing incremental warming scenarios determined that wetland function across most of the PPR would be diminished beyond a climate warming of about 1.5–2.0 °C, a critical temperature threshold range identified in other climate change studies.

Continental-scale temperature covariance in proxy reconstructions and climate models

NASA Astrophysics Data System (ADS)

Hartl-Meier, Claudia; Büntgen, Ulf; Smerdon, Jason; Zorita, Eduardo; Krusic, Paul; Ljungqvist, Fredrik; Schneider, Lea; Esper, Jan

2017-04-01

Inter-continental temperature variability over the past millennium has been reported to be more coherent in climate model simulations than in multi-proxy-based reconstructions, a finding that undermines the representation of spatial variability in either of these approaches. We assess the covariance of summer temperatures among Northern Hemisphere continents by comparing tree-ring based temperature reconstructions with state-of-the-art climate model simulations over the past millennium. We find inter-continental temperature covariance to be larger in tree-ring-only reconstructions compared to those derived from multi-proxy networks, thus enhancing the agreement between proxy- and model-based spatial representations. A detailed comparison of simulated temperatures, however, reveals substantial spread among the models. Over the past millennium, inter-continental temperature correlations are driven by the cooling after major volcanic eruptions in 1257, 1452, 1601, and 1815. The coherence of these synchronizing events appears to be elevated in several climate simulations relative to their own covariance baselines and the proxy reconstructions, suggesting these models overestimate the amplitude of cooling in response to volcanic forcing at large spatial scales.

Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing

NASA Astrophysics Data System (ADS)

Vecchi, Gabriel A.; Soden, Brian J.; Wittenberg, Andrew T.; Held, Isaac M.; Leetmaa, Ants; Harrison, Matthew J.

2006-05-01

Since the mid-nineteenth century the Earth's surface has warmed, and models indicate that human activities have caused part of the warming by altering the radiative balance of the atmosphere. Simple theories suggest that global warming will reduce the strength of the mean tropical atmospheric circulation. An important aspect of this tropical circulation is a large-scale zonal (east-west) overturning of air across the equatorial Pacific Ocean-driven by convection to the west and subsidence to the east-known as the Walker circulation. Here we explore changes in tropical Pacific circulation since the mid-nineteenth century using observations and a suite of global climate model experiments. Observed Indo-Pacific sea level pressure reveals a weakening of the Walker circulation. The size of this trend is consistent with theoretical predictions, is accurately reproduced by climate model simulations and, within the climate models, is largely due to anthropogenic forcing. The climate model indicates that the weakened surface winds have altered the thermal structure and circulation of the tropical Pacific Ocean. These results support model projections of further weakening of tropical atmospheric circulation during the twenty-first century.

Importance of ensembles in projecting regional climate trends

NASA Astrophysics Data System (ADS)

Arritt, Raymond; Daniel, Ariele; Groisman, Pavel

2016-04-01

We have performed an ensemble of simulations using RegCM4 to examine the ability to reproduce observed trends in precipitation intensity and to project future changes through the 21st century for the central United States. We created a matrix of simulations over the CORDEX North America domain for 1950-2099 by driving the regional model with two different global models (HadGEM2-ES and GFDL-ESM2M, both for RCP8.5), by performing simulations at both 50 km and 25 km grid spacing, and by using three different convective parameterizations. The result is a set of 12 simulations (two GCMs by two resolutions by three convective parameterizations) that can be used to systematically evaluate the influence of simulation design on predicted precipitation. The two global models were selected to bracket the range of climate sensitivity in the CMIP5 models: HadGEM2-ES has the highest ECS of the CMIP5 models, while GFDL-ESM2M has one of the lowestt. Our evaluation metrics differ from many other RCM studies in that we focus on the skill of the models in reproducing past trends rather than the mean climate state. Trends in frequency of extreme precipitation (defined as amounts exceeding 76.2 mm/day) for most simulations are similar to the observed trend but with notable variations depending on RegCM4 configuration and on the driving GCM. There are complex interactions among resolution, choice of convective parameterization, and the driving GCM that carry over into the future climate projections. We also note that biases in the current climate do not correspond to biases in trends. As an example of these points the Emanuel scheme is consistently "wet" (positive bias in precipitation) yet it produced the smallest precipitation increase of the three convective parameterizations when used in simulations driven by HadGEM2-ES. However, it produced the largest increase when driven by GFDL-ESM2M. These findings reiterate that ensembles using multiple RCM configurations and driving GCMs are essential for projecting regional climate change, even when a single RCM is used. This research was sponsored by the U.S. Department of Agriculture National Institute of Food and Agriculture.

Impacts of climate change on river discharge in the northern Tien Shan: Results from the long-term observations and modelling

NASA Astrophysics Data System (ADS)

Shahgedanova, Maria; Afzal, Muhammad; Usmanova, Zamira; Kapitsa, Vasilii; Mayr, Elisabeth; Hagg, Wilfried; Severskiy, Igor; Zhumabayev, Dauren

2017-04-01

The study presents results of investigation of the observed and projected changes in discharge of seven snow- and glacier-nourished rivers of the northern Tien Shan (south-eastern Kazakhstan). The observed trends were assessed using the long-term (40-60 years) homogeneous daily records of discharge from the gauging stations located in the mountains and unaffected by human activities including water abstraction. Positive trends in discharge were registered at most sites between the 1950s and 2010s with the strongest increase in summer and autumn particularly in 2000-2010s in line with the positive temperature trends. The observed increase was most prominent in the catchments with a higher proportion of glacierized area. At the Ulken Almatinka and Kishi Almatinka rivers, where 16% and 12% of the catchment areas are glacierized, positive trends in summer and autumn discharge exceeded 1% per year. The strongest increase was observed in September indicating that melting period extends in the early autumn. In September-November, the number of days with extreme discharge values, defined as daily values exceeding 95th percentile (calculated for each meteorological season), increased at all rivers. Future changes in discharge were modelled using HBV-ETH hydrological model and four climate change scenarios derived using regional climate model PRECIS with 25 km spatial resolution driven by HadGEM GCM for RCP 2.6 and RCP 8.5 scenarios and HadCM3Q0 and ECHAM5 GCM for A1B scenario. A range of glacier change scenarios was considered. All climate experiments project increase in temperature with the strongest warming projected by the HadGEM-driven simulation for RCP 8.5 scenario and HadCM3Q0-driven simulation for A1B scenario. The projected changes in precipitation varied between models and seasons, however, most experiments did not show significant trends in precipitation within the studied catchments. The exception is a simulation driven by HadGEM GCM for 8.5 RCP scenario which projects summer drying. All simulations project that in the 2020s, discharge will remain close to its baseline (1990-2005) values suggesting that peak flow has been reached in the northern Tien Shan. Significant decrease in discharge is projected for the post 2030s period for June-September. The strongest changes are expected in July and August when discharge values are projected to decrease by 25-38% in 2030-2060 and decline further to up 50% of the baseline values in 2060-2099.

Climate Change driven evolution of hazards to Europe's transport infrastructure throughout the twenty-first century

NASA Astrophysics Data System (ADS)

Matulla, Christoph; Hollósi, Brigitta; Andre, Konrad; Gringinger, Julia; Chimani, Barbara; Namyslo, Joachim; Fuchs, Tobias; Auerbach, Markus; Herrmann, Carina; Sladek, Brigitte; Berghold, Heimo; Gschier, Roland; Eichinger-Vill, Eva

2017-06-01

Road authorities, freight, and logistic industries face a multitude of challenges in a world changing at an ever growing pace. While globalization, changes in technology, demography, and traffic, for instance, have received much attention over the bygone decades, climate change has not been treated with equal care until recently. However, since it has been recognized that climate change jeopardizes many business areas in transport, freight, and logistics, research programs investigating future threats have been initiated. One of these programs is the Conference of European Directors of Roads' (CEDR) Transnational Research Programme (TRP), which emerged about a decade ago from a cooperation between European National Road Authorities and the EU. This paper presents findings of a CEDR project called CliPDaR, which has been designed to answer questions from road authorities concerning climate-driven future threats to transport infrastructure. Pertaining results are based on two potential future socio-economic pathways of mankind (one strongly economically oriented "A2" and one more balanced scenario "A1B"), which are used to drive global climate models (GCMs) producing global and continental scale climate change projections. In order to achieve climate change projections, which are valid on regional scales, GCM projections are downscaled by regional climate models. Results shown here originate from research questions raised by European Road Authorities. They refer to future occurrence frequencies of severely cold winter seasons in Fennoscandia, to particularly hot summer seasons in the Iberian Peninsula and to changes in extreme weather phenomena triggering landslides and rutting in Central Europe. Future occurrence frequencies of extreme winter and summer conditions are investigated by empirical orthogonal function analyses of GCM projections driven with by A2 and A1B pathways. The analysis of future weather phenomena triggering landslides and rutting events requires downscaled climate change projections. Hence, corresponding results are based on an ensemble of RCM projections, which was available for the A1B scenario. All analyzed risks to transport infrastructure are found to increase over the decades ahead with accelerating pace towards the end of this century. Mean Fennoscandian winter temperatures by the end of this century may match conditions of rather warm winter season experienced in the past and particularly warm future winter temperatures have not been observed so far. This applies in an even more pronounced manner to summer seasons in the Iberian Peninsula. Occurrence frequencies of extreme climate phenomena triggering landslides and rutting events in Central Europe are also projected to rise. Results show spatially differentiated patterns and indicate accelerated rates of increases.

The foundation for climate services in Belgium: CORDEX.be

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Termonia, Piet; De Ridder, Koen; Fettweis, Xavier; Gobin, Anne; Luyten, Patrick; Marbaix, Philippe; Pottiaux, Eric; Stavrakou, Trissevgeni; Van Lipzig, Nicole; van Ypersele, Jean-Pascal; Willems, Patrick

2017-04-01

According to the Global Framework for Climate Services (GFCS) there are four pillars required to build climate services. As the first step towards the realization of a climate center in Belgium, the national project CORDEX.be focused on one pillar: research modelling and projection. By bringing together the Belgian climate and impact modeling research of nine groups a data-driven capacity development and community building in Belgium based on interactions with users. The project is based on the international CORDEX ("COordinated Regional Climate Downscaling Experiment") project where ".be" indicates it will go beyond for Belgium. Our national effort links to the regional climate initiatives through the contribution of multiple high-resolution climate simulations over Europe following the EURO-CORDEX guidelines. Additionally the same climate simulations were repeated at convection-permitting resolutions over Belgium (3 to 5 km). These were used to drive different local impact models to investigate the impact of climate change on urban effects, storm surges and waves, crop production and changes in emissions from vegetation. Akin to international frameworks such as CMIP and CORDEX a multi-model approach is adopted allowing for uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. However, due to the lack of a large set of high resolution model runs, a combination of all available climate information is supplemented with the statistical downscaling approach. The organization of the project, together with its main results will be outlined. The proposed coordination framework could serve as a demonstration case for regions or countries where the climate-research capacity is present but a structure is required to assemble it coherently. Based on interactions and feedback with stakeholders different applications are planned, demonstrating the use of the climate data.

Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

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

Wagener, Thorsten; Mann, Michael; Crane, Robert

2014-04-29

This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach tomore » establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.« less

Improving niche projections of plant species under climate change: Silene acaulis on the British Isles as a case study

NASA Astrophysics Data System (ADS)

Ferrarini, Alessandro; Alsafran, Mohammed H. S. A.; Dai, Junhu; Alatalo, Juha M.

2018-04-01

Empirical works to assist in choosing climatically relevant variables in the attempt to predict climate change impacts on plant species are limited. Further uncertainties arise in choice of an appropriate niche model. In this study we devised and tested a sharp methodological framework, based on stringent variable ranking and filtering and flexible model selection, to minimize uncertainty in both niche modelling and successive projection of plant species distributions. We used our approach to develop an accurate, parsimonious model of Silene acaulis (L.) presence/absence on the British Isles and to project its presence/absence under climate change. The approach suggests the importance of (a) defining a reduced set of climate variables, actually relevant to species presence/absence, from an extensive list of climate predictors, and (b) considering climate extremes instead of, or together with, climate averages in projections of plant species presence/absence under future climate scenarios. Our methodological approach reduced the number of relevant climate predictors by 95.23% (from 84 to only 4), while simultaneously achieving high cross-validated accuracy (97.84%) confirming enhanced model performance. Projections produced under different climate scenarios suggest that S. acaulis will likely face climate-driven fast decline in suitable areas on the British Isles, and that upward and northward shifts to occupy new climatically suitable areas are improbable in the future. Our results also imply that conservation measures for S. acaulis based upon assisted colonization are unlikely to succeed on the British Isles due to the absence of climatically suitable habitat, so different conservation actions (seed banks and/or botanical gardens) are needed.

The geographic distribution and economic value of climate change-related ozone health impacts in the United States in 2030.

PubMed

Fann, Neal; Nolte, Christopher G; Dolwick, Patrick; Spero, Tanya L; Brown, Amanda Curry; Phillips, Sharon; Anenberg, Susan

2015-05-01

In this United States-focused analysis we use outputs from two general circulation models (GCMs) driven by different greenhouse gas forcing scenarios as inputs to regional climate and chemical transport models to investigate potential changes in near-term U.S. air quality due to climate change. We conduct multiyear simulations to account for interannual variability and characterize the near-term influence of a changing climate on tropospheric ozone-related health impacts near the year 2030, which is a policy-relevant time frame that is subject to fewer uncertainties than other approaches employed in the literature. We adopt a 2030 emissions inventory that accounts for fully implementing anthropogenic emissions controls required by federal, state, and/or local policies, which is projected to strongly influence future ozone levels. We quantify a comprehensive suite of ozone-related mortality and morbidity impacts including emergency department visits, hospital admissions, acute respiratory symptoms, and lost school days, and estimate the economic value of these impacts. Both GCMs project average daily maximum temperature to increase by 1-4°C and 1-5 ppb increases in daily 8-hr maximum ozone at 2030, though each climate scenario produces ozone levels that vary greatly over space and time. We estimate tens to thousands of additional ozone-related premature deaths and illnesses per year for these two scenarios and calculate an economic burden of these health outcomes of hundreds of millions to tens of billions of U.S. dollars (2010$). Near-term changes to the climate have the potential to greatly affect ground-level ozone. Using a 2030 emission inventory with regional climate fields downscaled from two general circulation models, we project mean temperature increases of 1 to 4°C and climate-driven mean daily 8-hr maximum ozone increases of 1-5 ppb, though each climate scenario produces ozone levels that vary significantly over space and time. These increased ozone levels are estimated to result in tens to thousands of ozone-related premature deaths and illnesses per year and an economic burden of hundreds of millions to tens of billions of U.S. dollars (2010$).

Predicting sea-level rise vulnerability of terrestrial habitat and wildlife of the Northwestern Hawaiian Islands

USGS Publications Warehouse

Reynolds, Michelle H.; Berkowitz, Paul; Courtot, Karen N.; Krause, Crystal M.; Reynolds, Michelle H.; Berkowitz, Paul; Courtot, Karen N.; Krause, Crystal M.

2012-01-01

If current climate change trends continue, rising sea levels may inundate low-lying islands across the globe, placing island biodiversity at risk. Recent models predict a rise of approximately one meter (1 m) in global sea level by 2100, with larger increases possible in areas of the Pacific Ocean. Pacific Islands are unique ecosystems home to many endangered endemic plant and animal species. The Northwestern Hawaiian Islands (NWHI), which extend 1,930 kilometers (km) beyond the main Hawaiian Islands, are a World Heritage Site and part of the Papahanaumokuakea Marine National Monument. These NWHI support the largest tropical seabird rookery in the world, providing breeding habitat for 21 species of seabirds, 4 endemic land bird species and essential foraging, breeding, or haul-out habitat for other resident and migratory wildlife. In recent years, concern has grown about the increasing vulnerability of the NWHI and their wildlife populations to changing climatic patterns, particularly the uncertainty associated with potential impacts from global sea-level rise (SLR) and storms. In response to the need by managers to adapt future resource protection strategies to climate change variability and dynamic island ecosystems, we have synthesized and down scaled analyses for this important region. This report describes a 2-year study of a remote northwestern Pacific atoll ecosystem and identifies wildlife and habitat vulnerable to rising sea levels and changing climate conditions. A lack of high-resolution topographic data for low-lying islands of the NWHI had previously precluded an extensive quantitative model of the potential impacts of SLR on wildlife habitat. The first chapter (chapter 1) describes the vegetation and topography of 20 islands of Papahanaumokuakea Marine National Monument, the distribution and status of wildlife populations, and the predicted impacts for a range of SLR scenarios. Furthermore, this chapter explores the potential effects of SLR on wildlife breeding habitats for each island. The subsequent chapter (chapter 2) details a study of the Laysan Island ecosystem, describing a quantitative model that incorporates SLR, storm wave, and rising groundwater inundation. Wildlife, storm, and oceanographic data allowed for an assessment of the phenological and spatial vulnerability of Laysan Island's breeding bird species to SLR and storms. Using remote sensing and geospatial techniques, we estimated topography, classified vegetation, modeled SLR, and evaluated a range of climate change scenarios. On the basis of high-resolution airborne data collected during 2010-11 (root-mean-squared error = 0.05-0.18 m), we estimated the maximum elevation of 20 individual islands extending from Kure Atoll to French Frigate Shoals (range: 1.8-39.7 m) and computed the mean elevation (1.7 m, standard deviation 1.1 m) across all low-lying islands. We also analyzed general climate models to describe rainfall and temperature scenarios expected to influence adaptation of some plants and animals for this region. Outcomes for the NWHI predicted an increase in temperature of 1.8-2.6 degrees Celsius (°C) and an annual decrease in precipitation of 24.7-76.3 millimeters (mm) across the NWHI by 2100. Our models of passive SLR (excluding wave-driven effects, erosion, and accretion) showed that approximately 4 percent of the total land area in the NWHI will be lost with scenarios of +1.0 m of SLR and 26 percent will be lost with +2.0 m of SLR. Some atolls are especially vulnerable to SLR. For example, at Pearl and Hermes Atoll our analysis indicated substantial habitat losses with 43 percent of the land area inundated at +1.0 m SLR and 92 percent inundated at +2.0 m SLR. Across the NWHI, seven islands will be completely submerged with +2.0 m SLR. The limited global ranges of some tropical nesting birds make them particularly vulnerable to climate change impacts in the NWHI. Climate change scenarios and potential SLR impacts presented here emphasize the need for early climate change adaptation and mitigation planning, especially for species with limited breeding distributions and/or ranges restricted primarily to the low-lying NWHI: Cyperus pennatiformis var. bryanii, Black-footed Albatross (Phoebastria nigripes), Laysan Albatross (P. immutabilis), Bonin Petrel (Pterodroma hypoleuca), Gray-backed Tern (Onychoprion lunatus), Laysan Teal (Anas laysanensis), Laysan Finch (Telespiza cantans), and Hawaiian monk seal (Monachus schauinslandi). Furthermore, SLR scenarios that include the effects of wave dynamics and groundwater rise may indicate amplified vulnerability to climate change driven habitat loss on low-lying islands. In chapter 2, we incorporated the combined effects of SLR, dynamic wave-driven inundation, and rising groundwater in a quantitative study specifically for the Laysan Island ecosystem. This is the first hydrodynamic model to simulate the combined impacts of SLR and wave-driven inundation in the NWHI. We developed a high-resolution digital elevation model (mean vertical accuracy of 0.32 m) for the island. Then using recent satellite imagery, geospatial models, and historical oceanographic, storm, and biological data we estimated potential inundation extent, habitat loss, and wildlife population impacts for a range of potential SLR scenarios (0.00, +0.50, +1.00, +1.50, and +2.00 m) that may occur over the next century. Additionally, we estimated the carrying capacity of Laysan Island for five species based on the available population monitoring data and described how potential losses in nesting habitat could influence population dynamics for Black-footed Albatross, Laysan Albatross, Red-footed Booby (Sula sula), Laysan Teal, and Laysan Finch. For some other seabird populations (Masked Booby, S. dactylatra; Brown Booby, S. leucogaster; Great Frigatebird, Fregata minor; and Sooty Tern, Onychoprion fuscata), we used recent colony distribution data, land cover maps, and nesting behavior to estimate potential losses of nesting habitat from SLR and wave-driven inundation. We observed far greater potential impacts of SLR to wildlife with the dynamic wave-driven modeling approach than with the passive modeling approach. Depending on SLR scenario and coastal orientation, during storms under a +2.00 m SLR scenario, the wave-driven inundation model predicted three times more inundation than the passive model (17.2 percent of total terrestrial area versus 4.6 percent, respectively). Large-wave events generally added 1 m of water height to passive inundation surfaces, therefore our dynamic models (during storm events) forecasted comparable inundation extents earlier than passive models. Although wave-driven water levels were highest in the northwest quadrant of Laysan Island, the greatest extent of inundation occurred in the southeast where coastal dunes less than 3 m above mean sea level provide little protection from wave-driven inundation. When wave-driven inundation was included in the SLR model for Laysan Island greater nesting habitat loss and potential impacts on wildlife population dynamics were predicted. The consequences of habitat loss due to SLR may be worse for species with colonies in the wave-exposed coastal zones (for example, Black-footed Albatross) and for populations already near the island's carrying capacity (for example, Laysan Teal). Species whose peak incubation and chick-rearing periods coincide with seasonally high wave heights also will be increasingly vulnerable, especially those species nesting on the ground in areas vulnerable to inundation, such as Gray-backed Tern and Black-footed Albatross. Other species that have space for population growth, or are not restricted to a narrow range of habitat types on Laysan (for instance, Sooty Terns), may be less sensitive to habitat loss from SLR over the next century. Our assessments of inundation risk, habitat loss, and wildlife species vulnerability synthesize current knowledge about individual islands and contribute to a broader understanding of the impacts of inundation from SLR and storm-induced waves. Yet, most NWHI and their bird populations lack monitoring data to evaluate adaptations to and impacts of climate change. Exceptions include some data sets from long-term monitoring of wildlife populations, tides, or weather at French Frigate Shoals, Laysan Island, and Midway Atoll. These data sets are potentially valuable baselines, which could be informative for adaptive learning (integrating management and science) to predict, adapt, and mitigate the effects of climate change on NWHI wildlife in the future. This study provides the first quantitative vulnerability assessment for all of the low-lying NWHI, and results identify biological communities, locales, and resident endangered species of Papahanaumokuakea Marine National Monument expected to be at risk from SLR. This report is also intended as a reference for managers and conservation planners, a tool to identify and potentially reduce uncertainty, and a starting place for developing climate change monitoring priorities and future scientific studies.

Tropical climate trends inferred from coral δ18O: a comparison of CMIP5 forward-model results with paleoclimatic observations

NASA Astrophysics Data System (ADS)

Thompson, D. M.; Evans, M. N.; Cole, J. E.; Ault, T. R.; Emile-Geay, J.

2011-12-01

The response of the tropical Pacific Ocean to anthropogenic climate change remains highly uncertain, in part because of the disagreement among 20th-century trends derived from observations and coupled general circulation models (CGCMs). We use a model of reef coral oxygen isotopic composition (δ18O) to compare the observational coral network with synthetic corals ('pseudocorals') modeled from CGCM sea-surface temperature (SST) and sea-surface salinity (SSS). When driven with historical data, we found that a linear temperature and salinity driven model for δ18Ocoral was able to capture the spatial and temporal pattern of ENSO and the linear trend observed in 23 Indo-Pacific coral records between 1958 and 1990. However, we found that none of the pseudocoral networks obtained from a subset of 20th-century AR4 CGCM runs reproduced the magnitude of the secular trend, the change in mean state, or the change in ENSO-related variance observed in the coral network from 1890 to 1990 (Thompson et al., 2011). We believe differences between corals and AR4 CGCM simulated pseudocorals arose from uncertainties in the observed coral network or linear bivariate coral model, undersensitivity of AR4 CGCMs to radiative forcing during the 20th century, and/or biases in the simulated AR4 CGCM SSS fields. Here we apply the same approach to an extended temperature and salinity reanalysis product (SODA v2.2.4, 1871-2008) and CMIP 5 historical simulations to further address 20th-century tropical climate trends and assess remaining uncertainties in both the proxies and models. We explore whether model improvements in the tropical Pacific have led to a stronger agreement between simulated and observed tropical climate trends. [Thompson, D. M., T. R. Ault, M. N. Evans, J. E. Cole, and J. Emile-Geay (2011), Comparison of observed and simulated tropical climate trends using a forward model of coral δ18O, Geophys. Res. Lett., 38, L14706, doi:10.1029/2011GL048224.

Projected effect of 2000-2050 changes in climate and emissions on aerosol levels in China and associated transboundary transport

EPA Science Inventory

We investigate projected 2000–2050 changes in concentrations of aerosols in China and the associated transboundary aerosol transport by using the chemical transport model GEOS-Chem driven by the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 3 at 4° × ...

Potential climate effect of mineral aerosols over West Africa. Part I: model validation and contemporary climate evaluation

NASA Astrophysics Data System (ADS)

Ji, Zhenming; Wang, Guiling; Pal, Jeremy S.; Yu, Miao

2016-02-01

Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated.

Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models

NASA Astrophysics Data System (ADS)

Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R.

2011-12-01

Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.

Is There Any Evidence for Rapid, Genetically-Based, Climatic Niche Expansion in the Invasive Common Ragweed?

PubMed

Gallien, Laure; Thuiller, Wilfried; Fort, Noémie; Boleda, Marti; Alberto, Florian J; Rioux, Delphine; Lainé, Juliette; Lavergne, Sébastien

2016-01-01

Climatic niche shifts have been documented in a number of invasive species by comparing the native and adventive climatic ranges in which they occur. However, these shifts likely represent changes in the realized climatic niches of invasive species, and may not necessarily be driven by genetic changes in climatic affinities. Until now the role of rapid niche evolution in the spread of invasive species remains a challenging issue with conflicting results. Here, we document a likely genetically-based climatic niche expansion of an annual plant invader, the common ragweed (Ambrosia artemisiifolia L.), a highly allergenic invasive species causing substantial public health issues. To do so, we looked for recent evolutionary change at the upward migration front of its adventive range in the French Alps. Based on species climatic niche models estimated at both global and regional scales we stratified our sampling design to adequately capture the species niche, and localized populations suspected of niche expansion. Using a combination of species niche modeling, landscape genetics models and common garden measurements, we then related the species genetic structure and its phenotypic architecture across the climatic niche. Our results strongly suggest that the common ragweed is rapidly adapting to local climatic conditions at its invasion front and that it currently expands its niche toward colder and formerly unsuitable climates in the French Alps (i.e. in sites where niche models would not predict its occurrence). Such results, showing that species climatic niches can evolve on very short time scales, have important implications for predictive models of biological invasions that do not account for evolutionary processes.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Climate-driven changes to the spatio-temporal distribution of the parasitic nematode, Haemonchus contortus, in sheep in Europe.

PubMed

Rose, Hannah; Caminade, Cyril; Bolajoko, Muhammad Bashir; Phelan, Paul; van Dijk, Jan; Baylis, Matthew; Williams, Diana; Morgan, Eric R

2016-03-01

Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio-temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q0 , adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan-European spatio-temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q0 simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within-host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q0 simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2-3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary control strategies, and potentially drive local adaptation to climate change in parasite populations. © 2015 John Wiley & Sons Ltd.

Understanding and Improving Ocean Mixing Parameterizations for modeling Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Clarke, J.; Cheng, Y.; Canuto, V.; Dubovikov, M. S.

2017-12-01

Climate is vital. Earth is only habitable due to the atmosphere&oceans' distribution of energy. Our Greenhouse Gas emissions shift overall the balance between absorbed and emitted radiation causing Global Warming. How much of these emissions are stored in the ocean vs. entering the atmosphere to cause warming and how the extra heat is distributed depends on atmosphere&ocean dynamics, which we must understand to know risks of both progressive Climate Change and Climate Variability which affect us all in many ways including extreme weather, floods, droughts, sea-level rise and ecosystem disruption. Citizens must be informed to make decisions such as "business as usual" vs. mitigating emissions to avert catastrophe. Simulations of Climate Change provide needed knowledge but in turn need reliable parameterizations of key physical processes, including ocean mixing, which greatly impacts transport&storage of heat and dissolved CO2. The turbulence group at NASA-GISS seeks to use physical theory to improve parameterizations of ocean mixing, including smallscale convective, shear driven, double diffusive, internal wave and tidal driven vertical mixing, as well as mixing by submesoscale eddies, and lateral mixing along isopycnals by mesoscale eddies. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. We write our own programs in MATLAB and FORTRAN to visualize and process output of ocean simulations including producing statistics to help judge impacts of different parameterizations on fidelity in reproducing realistic temperatures&salinities, diffusivities and turbulent power. The results can help upgrade the parameterizations. Students are introduced to complex system modeling and gain deeper appreciation of climate science and programming skills, while furthering climate science. We are incorporating climate projects into the Medgar Evers college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293 And NASA Award NNX17AC81G.

In ecoregions across western USA streamflow increases during post-wildfire recovery

NASA Astrophysics Data System (ADS)

Wine, Michael L.; Cadol, Daniel; Makhnin, Oleg

2018-01-01

Continued growth of the human population on Earth will increase pressure on already stressed terrestrial water resources required for drinking water, agriculture, and industry. This stress demands improved understanding of critical controls on water resource availability, particularly in water-limited regions. Mechanistic predictions of future water resource availability are needed because non-stationary conditions exist in the form of changing climatic conditions, land management paradigms, and ecological disturbance regimes. While historically ecological disturbances have been small and could be neglected relative to climatic effects, evidence is accumulating that ecological disturbances, particularly wildfire, can increase regional water availability. However, wildfire hydrologic impacts are typically estimated locally and at small spatial scales, via disparate measurement methods and analysis techniques, and outside the context of climate change projections. Consequently, the relative importance of climate change driven versus wildfire driven impacts on streamflow remains unknown across the western USA. Here we show that considering wildfire in modeling streamflow significantly improves model predictions. Mixed effects modeling attributed 2%-14% of long-term annual streamflow to wildfire effects. The importance of this wildfire-linked streamflow relative to predicted climate change-induced streamflow reductions ranged from 20%-370% of the streamflow decrease predicted to occur by 2050. The rate of post-wildfire vegetation recovery and the proportion of watershed area burned controlled the wildfire effect. Our results demonstrate that in large areas of the western USA affected by wildfire, regional predictions of future water availability are subject to greater structural uncertainty than previously thought. These results suggest that future streamflows may be underestimated in areas affected by increased prevalence of hydrologically relevant ecological disturbances such as wildfire.

Investigating Added Value of Regional Climate Modeling in North American Winter Storm Track Simulations

NASA Astrophysics Data System (ADS)

Poan, E.; Gachon, P., Sr.; Laprise, R.; Aider, R.; Dueymes, G.

2017-12-01

This study describes a framework using possibilities given by regional climate models (RCMs) to gain insight into extratropical cyclone (EC) activity during winter over North America (NA). Recent past climate period (1981 - 2005) is firstly considered using the NCEP regional reanalysis (NARR) as a reference, along with the European global reanalysis ERA-Interim (ERAI) and two CMIP5 Global Climate Models (GCMs) used to drive the Canadian RCM - version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological EC track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while their intensity is well captured. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over the eastern coast. In addition, storm occurrence from GCMs over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with main relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value from the CRCM5 is less prominent and systematic, except over western areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Finally, time period near the end of the 21st century (2071-2100) is considered to analyze EC characteristic trends and changes relative to the current climate conditions, showing important modifications in storm activity for certain winter months, especially in term of intensity over the eastern coast.

Boundary Condition Effects on Hillslope Form and Soil Development Along a Climatic Gradient From Semiarid to Hyperarid in Northern Chile

NASA Astrophysics Data System (ADS)

Owen, J. J.; Dietrich, W. E.; Nishiizumi, K.; Bellugi, D.; Amundson, R.

2008-12-01

Modeling the development of hillslopes using mass balance equations has generated many testable hypotheses related to morphology, process rates, and soil properties, however it is only relatively recently that techniques for constraining these models (such as cosmogenic radionuclides) have become commonplace. As such, many hypotheses related to the effects of boundary conditions or climate on process rates and soil properties have been left untested. We selected pairs of hillslopes along a precipitation gradient in northern Chile (24°-30° S) which were either bounded by actively eroding (bedrock-bedded) channels or by stable or aggradational landforms (pediments, colluvial aprons, valley bottoms). For each hillslope we measured soil properties, atmospheric deposition rates, and bedrock denudation rates. We observe significant changes in soil properties with climate: there is a shift from thick, weathered soils in the semiarid south, to the near absence of soil in the arid middle, to salt-rich soils in the hyperarid north. Coincident with these are dramatic changes in the types and rates of processes acting on the soils. We found relatively quick, biotically-driven soil formation and transport in the south, and very slow, salt-driven processes in the north. Additionally, we observe systematic differences between hillslopes of different boundary condition within the same climate zone, such as thicker soils, gentler slopes, and slower erosion rates on hillslopes with a non-eroding boundary versus an eroding boundary. These support general predictions based on hillslope soil mass balance equations and geomorphic transport laws. Using parameters derived from our field data, we attempt to use a mass balance model of hillslope development to explore the effect of changing boundary conditions and/or shifting climate.

Climate-driven effects of fire on winter habitat for caribou in the Alaskan-Yukon Arctic.

PubMed

Gustine, David D; Brinkman, Todd J; Lindgren, Michael A; Schmidt, Jennifer I; Rupp, T Scott; Adams, Layne G

2014-01-01

Climatic warming has direct implications for fire-dominated disturbance patterns in northern ecosystems. A transforming wildfire regime is altering plant composition and successional patterns, thus affecting the distribution and potentially the abundance of large herbivores. Caribou (Rangifer tarandus) are an important subsistence resource for communities throughout the north and a species that depends on terrestrial lichen in late-successional forests and tundra systems. Projected increases in area burned and reductions in stand ages may reduce lichen availability within caribou winter ranges. Sufficient reductions in lichen abundance could alter the capacity of these areas to support caribou populations. To assess the potential role of a changing fire regime on winter habitat for caribou, we used a simulation modeling platform, two global circulation models (GCMs), and a moderate emissions scenario to project annual fire characteristics and the resulting abundance of lichen-producing vegetation types (i.e., spruce forests and tundra >60 years old) across a modeling domain that encompassed the winter ranges of the Central Arctic and Porcupine caribou herds in the Alaskan-Yukon Arctic. Fires were less numerous and smaller in tundra compared to spruce habitats throughout the 90-year projection for both GCMs. Given the more likely climate trajectory, we projected that the Porcupine caribou herd, which winters primarily in the boreal forest, could be expected to experience a greater reduction in lichen-producing winter habitats (-21%) than the Central Arctic herd that wintered primarily in the arctic tundra (-11%). Our results suggest that caribou herds wintering in boreal forest will undergo fire-driven reductions in lichen-producing habitats that will, at a minimum, alter their distribution. Range shifts of caribou resulting from fire-driven changes to winter habitat may diminish access to caribou for rural communities that reside in fire-prone areas.

Climate-driven effects of fire on winter habitat for caribou in the Alaskan-Yukon Arctic

USGS Publications Warehouse

Gustine, David D.; Brinkman, Todd J.; Lindgren, Michael A.; Schmidt, Jennifer I.; Rupp, T. Scott; Adams, Layne G.

2014-01-01

Climatic warming has direct implications for fire-dominated disturbance patterns in northern ecosystems. A transforming wildfire regime is altering plant composition and successional patterns, thus affecting the distribution and potentially the abundance of large herbivores. Caribou (Rangifer tarandus) are an important subsistence resource for communities throughout the north and a species that depends on terrestrial lichen in late-successional forests and tundra systems. Projected increases in area burned and reductions in stand ages may reduce lichen availability within caribou winter ranges. Sufficient reductions in lichen abundance could alter the capacity of these areas to support caribou populations. To assess the potential role of a changing fire regime on winter habitat for caribou, we used a simulation modeling platform, two global circulation models (GCMs), and a moderate emissions scenario to project annual fire characteristics and the resulting abundance of lichen-producing vegetation types (i.e., spruce forests and tundra >60 years old) across a modeling domain that encompassed the winter ranges of the Central Arctic and Porcupine caribou herds in the Alaskan-Yukon Arctic. Fires were less numerous and smaller in tundra compared to spruce habitats throughout the 90-year projection for both GCMs. Given the more likely climate trajectory, we projected that the Porcupine caribou herd, which winters primarily in the boreal forest, could be expected to experience a greater reduction in lichen-producing winter habitats (−21%) than the Central Arctic herd that wintered primarily in the arctic tundra (−11%). Our results suggest that caribou herds wintering in boreal forest will undergo fire-driven reductions in lichen-producing habitats that will, at a minimum, alter their distribution. Range shifts of caribou resulting from fire-driven changes to winter habitat may diminish access to caribou for rural communities that reside in fire-prone areas.

Effects of different representations of transport in the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Kreyling, Daniel; Rex, Markus

2017-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Interactively coupled chemistry climate models (CCMs) provide a means to realistically simulate the interaction between atmospheric chemistry and dynamics. The calculation of chemistry in CCMs, however, is computationally expensive which renders the use of complex chemistry models not suitable for ensemble simulations or simulations with multiple climate change scenarios. In these simulations ozone is therefore usually prescribed as a climatological field or included by incorporating a fast linear ozone scheme into the model. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. An alternative approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. When using SWIFT in EMAC, there are several possibilities to represent the effect of transport inside the polar vortex: the semi-Lagrangian transport scheme of EMAC and a transport parameterisation that can be useful when using SWIFT in models not having transport of their own. Here, we present results of equivalent simulations with different handling of transport, compare with EMAC simulations with full interactive chemistry and evaluate the results with observations.

Ocean Carbon Cycle Feedbacks Under Negative Emissions

NASA Astrophysics Data System (ADS)

Schwinger, Jörg; Tjiputra, Jerry

2018-05-01

Negative emissions will most likely be needed to achieve ambitious climate targets, such as limiting global warming to 1.5°. Here we analyze the ocean carbon-concentration and carbon-climate feedback in an Earth system model under an idealized strong CO2 peak and decline scenario. We find that the ocean carbon-climate feedback is not reversible by means of negative emissions on decadal to centennial timescales. When preindustrial surface climate is restored, the oceans, due to the carbon-climate feedback, still contain about 110 Pg less carbon compared to a simulation without climate change. This result is unsurprising but highlights an issue with a widely used carbon cycle feedback metric. We show that this metric can be greatly improved by using ocean potential temperature as a proxy for climate change. The nonlinearity (nonadditivity) of climate and CO2-driven feedbacks continues to grow after the atmospheric CO2 peak.

Tropical nighttime warming as a dominant driver of variability in the terrestrial carbon sink

Treesearch

William R. L. Anderegg; Ashley P. Ballantyne; W. Kolby Smith; Joseph Majkut; Sam Rabin; Claudie Beaulieu; Richard Birdsey; John P. Dunne; Richard A. Houghton; Ranga B. Myneni; Yude Pan; Jorge L. Sarmiento; Nathan Serota; Elena Shevliakova; Pieter Tans; Stephen W. Pacala

2015-01-01

The terrestrial biosphere is currently a strong carbon (C) sink but may switch to a source in the 21st century as climate-driven losses exceed CO2-driven C gains, thereby accelerating global warming. Although it has long been recognized that tropical climate plays a critical role in regulating interannual climate variability, the causal link...

Transport of ice into the stratosphere and the humidification of the stratosphere over the 21st century.

PubMed

Dessler, A E; Ye, H; Wang, T; Schoeberl, M R; Oman, L D; Douglass, A R; Butler, A H; Rosenlof, K H; Davis, S M; Portmann, R W

2016-03-16

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by ~1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50-80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales - on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community.

Transport of ice into the stratosphere and the humidification of the stratosphere over the 21st century

PubMed Central

Dessler, A.E.; Ye, H.; Wang, T.; Schoeberl, M.R.; Oman, L.D.; Douglass, A.R.; Butler, A.H.; Rosenlof, K.H.; Davis, S.M.; Portmann, R.W.

2018-01-01

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by ~1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50–80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales — on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community. PMID:29551841

Transport of Ice into the Stratosphere and the Humidification of the Stratosphere over the 21st Century

NASA Technical Reports Server (NTRS)

Dessler, A. E.; Ye, H.; Wang, T.; Schoeberl, M. R.; Oman, L. D.; Douglass, A. R.; Butler, A. H.; Rosenlof, K. H.; Davis, S. M.; Portmann, R. W.

2016-01-01

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by approx. 1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50-80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales - on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community.

Narrowing of the Upwelling Branch of the Brewer-Dobson Circulation and Hadley Cell in Chemistry-Climate Model Simulations of the 21st Century

NASA Technical Reports Server (NTRS)

Li, Feng; Stolarski, Richard S.; Pawson, Steven; Newman, Paul A.; Waugh, Darryn

2010-01-01

Changes in the width of the upwelling branch of the Brewer-Dobson circulation and Hadley cell in the 21st Century are investigated using simulations from a coupled chemistry-climate model. In these model simulations the tropical upwelling region narrows in the troposphere and lower stratosphere. The narrowing of the Brewer-Dobson circulation is caused by an equatorward shift of Rossby wave critical latitudes and Eliassen-Palm flux convergence in the subtropical lower stratosphere. In the troposphere, the model projects an expansion of the Hadley cell's poleward boundary, but a narrowing of the Hadley rising branch. Model results suggest that the narrowing of the Hadley cell ascent is also eddy-driven.

A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change

USGS Publications Warehouse

Milly, Paul; Dunne, Krista A.

2017-01-01

For water-resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (Ep) as inputs. Because Ep is not a climate-model output, an intermediary model of Ep must be introduced to connect the climate model to the hydrologic model. Several Ep methods are used. The suitability of each can be assessed by noting a credible Ep method for offline analyses should be able to reproduce climate models’ ACC-driven changes in actual evapotranspiration in regions and seasons of negligible water stress (Ew). We quantified this ability for seven commonly used Ep methods and for a simple proportionality with available energy (“energy-only” method). With the exception of the energy-only method, all methods tend to overestimate substantially the increase in Ep associated with ACC. In an offline hydrologic model, the Ep-change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC-induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water-resource impact analyses.

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

A data-driven emulation framework for representing water-food nexus in a changing cold region

NASA Astrophysics Data System (ADS)

Nazemi, A.; Zandmoghaddam, S.; Hatami, S.

2017-12-01

Water resource systems are under increasing pressure globally. Growing population along with competition between water demands and emerging effects of climate change have caused enormous vulnerabilities in water resource management across many regions. Diagnosing such vulnerabilities and provision of effective adaptation strategies requires the availability of simulation tools that can adequately represent the interactions between competing water demands for limiting water resources and inform decision makers about the critical vulnerability thresholds under a range of potential natural and anthropogenic conditions. Despite a significant progress in integrated modeling of water resource systems, regional models are often unable to fully represent the contemplating dynamics within the key elements of water resource systems locally. Here we propose a data-driven approach to emulate a complex regional water resource system model developed for Oldman River Basin in southern Alberta, Canada. The aim of the emulation is to provide a detailed understanding of the trade-offs and interaction at the Oldman Reservoir, which is the key to flood control and irrigated agriculture in this over-allocated semi-arid cold region. Different surrogate models are developed to represent the dynamic of irrigation demand and withdrawal as well as reservoir evaporation and release individually. The nan-falsified offline models are then integrated through the water balance equation at the reservoir location to provide a coupled model for representing the dynamic of reservoir operation and water allocation at the local scale. The performance of individual and integrated models are rigorously examined and sources of uncertainty are highlighted. To demonstrate the practical utility of such surrogate modeling approach, we use the integrated data-driven model for examining the trade-off in irrigation water supply, reservoir storage and release under a range of changing climate, upstream streamflow and local irrigation conditions.

Forward modeling of tree-ring data: a case study with a global network

NASA Astrophysics Data System (ADS)

Breitenmoser, P. D.; Frank, D.; Brönnimann, S.

2012-04-01

Information derived from tree-rings is one of the most powerful tools presently available for studying past climatic variability as well as identifying fundamental relationships between tree-growth and climate. Climate reconstructions are typically performed by extending linear relationships, established during the overlapping period of instrumental and climate proxy archives into the past. Such analyses, however, are limited by methodological assumptions, including stationarity and linearity of the climate-proxy relationship. We investigate climate and tree-ring data using the Vaganov-Shashkin-Lite (VS-Lite) forward model of tree-ring width formation to examine the relations among actual tree growth and climate (as inferred from the simulated chronologies) to reconstruct past climate variability. The VS-lite model has been shown to produce skill comparable to that achieved using classical dendrochronological statistical modeling techniques when applied on simulations of a network of North American tree-ring chronologies. Although the detailed mechanistic processes such as photosynthesis, storage, or cell processes are not modeled directly, the net effect of the dominating nonlinear climatic controls on tree-growth are implemented into the model by the principle of limiting factors and threshold growth response functions. The VS-lite model requires as inputs only latitude, monthly mean temperature and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree-rings to monthly climate conditions obtained from the 20th century reanalysis project back to 1871. These simulated tree-ring chronologies are compared to the climate-driven variability in worldwide observed tree-ring chronologies from the International Tree Ring Database. Results point toward the suitability of the relationship among actual tree growth and climate (as inferred from the simulated chronologies) for use in global palaeoclimate reconstructions.

Groundwater vulnerability to climate variability: modelling experience and field observations in the lower Magra Valley (Liguria, Italy)

NASA Astrophysics Data System (ADS)

Menichini, Matia; Doveri, Marco; El Mansoury, Bouabid; El Mezouary, Lhoussaine; Lelli, Matteo; Raco, Brunella; Scozzari, Andrea; Soldovieri, Francesco

2016-04-01

The aquifer of the Lower Magra Valley (SE Liguria, Italy) extends in a flat plain, where two main rivers (Magra and Vara) flow. These rivers are characterized by a wide variation of water level and water chemical composition (TDS, Cl and SO4) due to the combination of rainfall regime and the presence of thermal springs in the inner part of the catchment area. Groundwater flow is apparently controlled by stream water infiltration, which affects both water levels and water quality. In particular, the wide range of variation of some particular chemical species in the stream water influences the groundwater chemistry on a seasonal basis. In the area of interest, there is an important well-field, which supplies most of the drinking water to the nearby city of La Spezia. In this context, the groundwater system is exposed to a high degree of vulnerability, both in terms of quality and quantity. This study is aimed to develop a predictive flow and transport model in order to assess the vulnerability s.l. of the Magra Valley aquifer system and to evaluate its behaviour in awaited climate scenarios. A flow and transport model was developed by using MODFLOW and MT3DMS codes, and it's been calibrated in both steady state and transient conditions. The model confirmed the importance of the Magra river in the water balance and chemical composition of the extracted groundwater. In addition, a data-driven modelling approach was applied in order to determine boundary conditions (e.g. rivers and constant head or general head boundaries) of the physical model under hypothetic future climate scenarios. For this purpose, fully synthetic datasets have been generated as a training set of the data-driven scheme, with input variables inspired by selected climate models and input/output relationships estimated by past observations. An experimental run of the flow-transport model for 30 years ahead was performed, based on such hypothetic scenarios. This approach highlighted how the groundwater flow of the studied aquifer is highly vulnerable and sensitive to climate conditions.

Bias-correction of CORDEX-MENA projections using the Distribution Based Scaling method

NASA Astrophysics Data System (ADS)

Bosshard, Thomas; Yang, Wei; Sjökvist, Elin; Arheimer, Berit; Graham, L. Phil

2014-05-01

Within the Regional Initiative for the Assessment of the Impact of Climate Change on Water Resources and Socio-Economic Vulnerability in the Arab Region (RICCAR) lead by UN ESCWA, CORDEX RCM projections for the Middle East Northern Africa (MENA) domain are used to drive hydrological impacts models. Bias-correction of newly available CORDEX-MENA projections is a central part of this project. In this study, the distribution based scaling (DBS) method has been applied to 6 regional climate model projections driven by 2 RCP emission scenarios. The DBS method uses a quantile mapping approach and features a conditional temperature correction dependent on the wet/dry state in the climate model data. The CORDEX-MENA domain is particularly challenging for bias-correction as it spans very diverse climates showing pronounced dry and wet seasons. Results show that the regional climate models simulate too low temperatures and often have a displaced rainfall band compared to WATCH ERA-Interim forcing data in the reference period 1979-2008. DBS is able to correct the temperature biases as well as some aspects of the precipitation biases. Special focus is given to the analysis of the influence of the dry-frequency bias (i.e. climate models simulating too few rain days) on the bias-corrected projections and on the modification of the climate change signal by the DBS method.

Climate change-driven cliff and beach evolution at decadal to centennial time scales

USGS Publications Warehouse

Erikson, Li; O'Neill, Andrea; Barnard, Patrick; Vitousek, Sean; Limber, Patrick

2017-01-01

Here we develop a computationally efficient method that evolves cross-shore profiles of sand beaches with or without cliffs along natural and urban coastal environments and across expansive geographic areas at decadal to centennial time-scales driven by 21st century climate change projections. The model requires projected sea level rise rates, extrema of nearshore wave conditions, bluff recession and shoreline change rates, and cross-shore profiles representing present-day conditions. The model is applied to the ~470-km long coast of the Southern California Bight, USA, using recently available projected nearshore waves and bluff recession and shoreline change rates. The results indicate that eroded cliff material, from unarmored cliffs, contribute 11% to 26% to the total sediment budget. Historical beach nourishment rates will need to increase by more than 30% for a 0.25 m sea level rise (~2044) and by at least 75% by the year 2100 for a 1 m sea level rise, if evolution of the shoreline is to keep pace with rising sea levels.

Linking the variability of atmospheric carbon monoxide to climate modes in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Buchholz, Rebecca; Monks, Sarah; Hammerling, Dorit; Worden, Helen; Deeter, Merritt; Emmons, Louisa; Edwards, David

2017-04-01

Biomass burning is a major driver of atmospheric carbon monoxide (CO) variability in the Southern Hemisphere. The magnitude of emissions, such as CO, from biomass burning is connected to climate through both the availability and dryness of fuel. We investigate the link between CO and climate using satellite measured CO and climate indices. Observations of total column CO from the satellite instrument MOPITT are used to build a record of interannual variability in CO since 2001. Four biomass burning regions in the Southern Hemisphere are explored. Data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Southern Annular Mode (SAM). Stepwise forward and backward regression is used to select the best statistical model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Implications of the model results are discussed for the Maritime Southeast Asia and Australasia regions. We also draw on the chemistry-climate model CAM-chem to explain the source contribution as well as the relative contributions of emissions and meteorology to CO variability.

Nowhere to Go but Up: Impacts of Climate Change on Demographics of a Short-Range Endemic (Crotalus willardi obscurus) in the Sky-Islands of Southwestern North America.

PubMed

Davis, Mark A; Douglas, Marlis R; Webb, Colleen T; Collyer, Michael L; Holycross, Andrew T; Painter, Charles W; Kamees, Larry K; Douglas, Michael E

2015-01-01

Biodiversity elements with narrow niches and restricted distributions (i.e., 'short range endemics,' SREs) are particularly vulnerable to climate change. The New Mexico Ridge-nosed Rattlesnake (Crotalus willardi obscurus, CWO), an SRE listed under the U.S. Endangered Species Act within three sky islands of southwestern North America, is constrained at low elevation by drought and at high elevation by wildfire. We combined long-term recapture and molecular data with demographic and niche modeling to gauge its climate-driven status, distribution, and projected longevity. The largest population (Animas) is numerically constricted (N = 151), with few breeding adults (Nb = 24) and an elevated inbreeding coefficient (ΔF = 0.77; 100 years). Mean home range (0.07 km2) is significantly smaller compared to other North American rattlesnakes, and movements are within, not among sky islands. Demographic values, when gauged against those displayed by other endangered/Red-Listed reptiles [e.g., Loggerhead Sea Turtle (Caretta caretta)], are either comparable or markedly lower. Survival rate differs significantly between genders (female

Nowhere to Go but Up: Impacts of Climate Change on Demographics of a Short-Range Endemic (Crotalus willardi obscurus) in the Sky-Islands of Southwestern North America

PubMed Central

Davis, Mark A.; Douglas, Marlis R.; Webb, Colleen T.; Collyer, Michael L.; Holycross, Andrew T.; Painter, Charles W.; Kamees, Larry K.; Douglas, Michael E.

2015-01-01

Biodiversity elements with narrow niches and restricted distributions (i.e., ‘short range endemics,’ SREs) are particularly vulnerable to climate change. The New Mexico Ridge-nosed Rattlesnake (Crotalus willardi obscurus, CWO), an SRE listed under the U.S. Endangered Species Act within three sky islands of southwestern North America, is constrained at low elevation by drought and at high elevation by wildfire. We combined long-term recapture and molecular data with demographic and niche modeling to gauge its climate-driven status, distribution, and projected longevity. The largest population (Animas) is numerically constricted (N = 151), with few breeding adults (Nb = 24) and an elevated inbreeding coefficient (ΔF = 0.77; 100 years). Mean home range (0.07km2) is significantly smaller compared to other North American rattlesnakes, and movements are within, not among sky islands. Demographic values, when gauged against those displayed by other endangered/Red-Listed reptiles [e.g., Loggerhead Sea Turtle ( Caretta caretta )], are either comparable or markedly lower. Survival rate differs significantly between genders (female

Modeling high resolution space-time variations in energy demand/CO2 emissions of human inhabited landscapes in the United States under a changing climate

NASA Astrophysics Data System (ADS)

Godbole, A. V.; Gurney, K. R.

2010-12-01

With urban and exurban areas now accounting for more than 50% of the world's population, projected to increase 20% by 2050 (UN World Urbanization Prospects, 2009), urban-climate interactions are of renewed interest to the climate change scientific community (Karl et. al, 1988; Kalnay and Cai, 2003; Seto and Shepherd, 2009). Until recently, climate modeling efforts treated urban-human systems as independent of the earth system. With studies pointing to the disproportionately large influence of urban areas on their surrounding environment (Small et. al, 2010), modeling efforts have begun to explicitly account for urban processes in land models, like the CLM 4.0 urban layer, for example (Oleson.et. al, 2008, 2010). A significant portion of the urban energy demand comes from the space heating and cooling requirement of the residential and commercial sectors - as much as 51% (DOE, RECS 2005) and 11% (Belzer, D. 2006) respectively, in the United States. Thus, these sectors are both responsible for a significant fraction of fossil fuel CO2 emissions and will be influenced by a changing climate through changes in energy use and energy supply planning. This points to the possibility of interactive processes and feedbacks with the climate system. Space conditioning energy demand is strongly driven by external air temperature (Ruth, M. et.al, 2006) in addition to other socio-economic variables such as building characteristics (age of structure, activity cycle, weekend/weekday usage profile), occupant characteristics (age of householder, household income) and energy prices (Huang, 2006; Santin et. al, 2009; Isaac and van Vuuren, 2009). All of these variables vary both in space and time. Projections of climate change have begun to simulate changes in temperature at much higher resolution than in the past (Diffenbaugh et. al, 2005). Hence, in order to understand how climate change and variability will potentially impact energy use/emissions and energy planning, these two components of the human-climate system must be coupled in climate modeling efforts to better understand the impacts and feedbacks. To implement modeling strategies for coupling the human and climate systems, their interactions must first be examined in greater detail at high spatial and temporal resolutions. This work attempts to quantify the impact of high resolution variations in projected climate change on energy use/emissions in the United States. We develop a predictive model for the space heating component of residential and commercial energy demand by leveraging results from the high resolution fossil fuel CO2 inventory of the Vulcan Project (Gurney et al., 2009). This predictive model is driven by high resolution temperature data from the RegCM3 model obtained by implementing a downscaling algorithm (Chow and Levermore, 2007). We will present the energy use/emissions in both the space and time domain from two different predictive models highlighting strengths and weaknesses in both. Furthermore, we will explore high frequency variations in the projected temperature field and how these might place potentially large burdens on energy supply and delivery.

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

A continuous latitudinal energy balance model to explore non-uniform climate engineering strategies

NASA Astrophysics Data System (ADS)

Bonetti, F.; McInnes, C. R.

2016-12-01

Current concentrations of atmospheric CO2 exceed measured historical levels in modern times, largely attributed to anthropogenic forcing since the industrial revolution. The required decline in emissions rates has never been achieved leading to recent interest in climate engineering for future risk-mitigation strategies. Climate engineering aims to offset human-driven climate change. It involves techniques developed both to reduce the concentration of CO2 in the atmosphere (Carbon Dioxide Removal (CDR) methods) and to counteract the radiative forcing that it generates (Solar Radiation Management (SRM) methods). In order to investigate effects of SRM technologies for climate engineering, an analytical model describing the main dynamics of the Earth's climate has been developed. The model is a time-dependent Energy Balance Model (EBM) with latitudinal resolution and allows for the evaluation of non-uniform climate engineering strategies. A significant disadvantage of climate engineering techniques involving the management of solar radiation is regional disparities in cooling. This model offers an analytical approach to design multi-objective strategies that counteract climate change on a regional basis: for example, to cool the Artic and restrict undesired impacts at mid-latitudes, or to control the equator-to-pole temperature gradient. Using the Green's function approach the resulting partial differential equation allows for the computation of the surface temperature as a function of time and latitude when a 1% per year increase in the CO2 concentration is considered. After the validation of the model through comparisons with high fidelity numerical models, it will be used to explore strategies for the injection of the aerosol precursors in the stratosphere. In particular, the model involves detailed description of the optical properties of the particles, the wash-out dynamics and the estimation of the radiative cooling they can generate.

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements

NASA Astrophysics Data System (ADS)

Lucas, S. E.; Todd, J. F.

2015-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.

Application of data on climate extremes for the southwestern United States

NASA Astrophysics Data System (ADS)

Redmond, K. T.; Fleishman, E.; Cayan, D. R.; Daudert, B.; Gershunov, A.

2015-12-01

We are improving the scientific capacity to evaluate responses of natural resources to climate extremes. We also are enhancing a platform for derivation of and access to customized climate information for the full extent or any subset of the southwestern United States. Extreme climate can have substantial effects on species, ecological and evolutionary processes, and the health of visitors to public lands. We are working with federal and state managers and with researchers who collaborate with decision-makers to use data on climate extremes to inform resource management. Current applications include sudden oak death, estuarine management, and fine-resolution manipulation of montane vegetation. To facilitate practical use of data on climate extremes, we are screening global climate models on the basis of their realism in representing natural regional patterns and extremes of temperature and precipitation, including those driven by El Niño and La Niña. We are assessing how well each model represents different climate elements. We also are delivering point and gridded observations and downscaled model projections, all at daily and 6 km resolution, on past and future climate extremes. Additionally, we are using the downscaled outputs to drive a hydrologic model and derive multiple probabilistic measures of water availability, flood, and drought. Moreover, we are extending the capacity of the Southwest Climate and Environmental Information Collaborative (SCENIC; wrcc.dri.edu/csc/scenic), a product developed by the Western Regional Climate Center, to provide access to diverse observed and simulated data on regional weather and climate, particularly on extremes.

Climatic and ecological future of the Amazon: likelihood and causes of change

NASA Astrophysics Data System (ADS)

Cook, B.; Zeng, N.; Yoon, J.-H.

2010-05-01

Some recent climate modeling results suggested a possible dieback of the Amazon rainforest under future climate change, a prediction that raised considerable interest as well as controversy. To determine the likelihood and causes of such changes, we analyzed the output of 15 models from the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC/AR4) and a dynamic vegetation model VEGAS driven by these climate output. Our results suggest that the core of the Amazon rainforest should remain largely stable as rainfall is projected to increase in nearly all models. However, the periphery, notably the southern edge of the Amazon and further south in central Brazil, are in danger of drying out, driven by two main processes. Firstly, a decline in precipitation of 22% in the southern Amazon's dry season (May-September) reduces soil moisture, despite an increase in precipitation during the wet season, due to nonlinear responses in hydrology and ecosystem dynamics. Two dynamical mechanisms may explain the lower dry season rainfall: (1) a general subtropical drying under global warming when the dry season southern Amazon is under the control of the subtropical high pressure; (2) a stronger north-south tropical Atlantic sea surface temperature gradient, and to lesser degree a warmer eastern equatorial Pacific. Secondly, evaporation demand will increase due to the general warming, further reducing soil moisture. In terms of ecosystem response, higher maintenance cost and reduced productivity under warming may also have additional adverse impact. The drying corresponds to a lengthening of the dry season by 11 days. As a consequence, the median of the models projects a reduction of 20% in vegetation carbon stock in the southern Amazon, central Brazil, and parts of the Andean Mountains. Further, VEGAS predicts enhancement of fire risk by 10-15%. The increase in fire is primarily due to the reduction in soil moisture, and the decrease in dry season rainfall, which is when fire danger reaches its peak. Because the southern Amazon is also under intense human influence as a result of deforestation and land use, added pressure to the region's ecosystems from climate change may subject the region to profound changes in the 21st century.

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.

Consequence of climate mitigation on the risk of hunger.

PubMed

Hasegawa, Tomoko; Fujimori, Shinichiro; Shin, Yonghee; Tanaka, Akemi; Takahashi, Kiyoshi; Masui, Toshihiko

2015-06-16

Climate change and mitigation measures have three major impacts on food consumption and the risk of hunger: (1) changes in crop yields caused by climate change; (2) competition for land between food crops and energy crops driven by the use of bioenergy; and (3) costs associated with mitigation measures taken to meet an emissions reduction target that keeps the global average temperature increase to 2 °C. In this study, we combined a global computable general equilibrium model and a crop model (M-GAEZ), and we quantified the three impacts on risk of hunger through 2050 based on the uncertainty range associated with 12 climate models and one economic and demographic scenario. The strong mitigation measures aimed at attaining the 2 °C target reduce the negative effects of climate change on yields but have large negative impacts on the risk of hunger due to mitigation costs in the low-income countries. We also found that in a strongly carbon-constrained world, the change in food consumption resulting from mitigation measures depends more strongly on the change in incomes than the change in food prices.

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas

NASA Astrophysics Data System (ADS)

Moore, B., III

2014-12-01

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. Berrien Moore III (University of Oklahoma) The South Central Climate Science Center (CSC) is one of eight regional centers established by the Department of the Interior (DoI) under Secretarial Order 3289 to address the impacts of climate change on America's water, land, and other natural and cultural resources. Under DoI leadership and funding, these CSCs will provide scientific information tools and techniques to study impacts of climate change synthesize and integrate climate change impact data develop tools that the DoI managers and partners can use when managing the DOI's land, water, fish and wildlife, and cultural heritage resources (emphasis added) The network of Climate Science Centers will provide decision makers with the science, tools, and information they need to address the impacts of climate variability and change on their areas of responsibility. Note from Webster, a tool is a device for doing work; it makes outcomes more realizable and more cost effective, and, in a word, better. Prior to the existence of CSCs, the university and federal scientific world certainly contained a large "set" of scientists with considerable strength in the physical, biological, natural, and social sciences to address the complexities and interdisciplinary nature of the challenges in the areas of climate variability, change, impacts, and adaptation. However, this set of scientists were hardly an integrated community let alone a focused team, but rather a collection of distinguished researchers, educators, and practitioners that were working with disparate though at times linked objectives, and they were rarely aligning themselves formally to an overarching strategic pathway. In addition, data, models, research results, tools, and products were generally somewhat "disconnected" from the broad range of stakeholders. I should note also that NOAA's Regional Integrated Sciences and Assessments ( RISA) program is an earlier "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. This contribution will discuss the important cultural shift that has flowed from Secretarial Order 3289.

Fire as the dominant driver of central Canadian boreal forest carbon balance.

PubMed

Bond-Lamberty, Ben; Peckham, Scott D; Ahl, Douglas E; Gower, Stith T

2007-11-01

Changes in climate, atmospheric carbon dioxide concentration and fire regimes have been occurring for decades in the global boreal forest, with future climate change likely to increase fire frequency--the primary disturbance agent in most boreal forests. Previous attempts to assess quantitatively the effect of changing environmental conditions on the net boreal forest carbon balance have not taken into account the competition between different vegetation types on a large scale. Here we use a process model with three competing vascular and non-vascular vegetation types to examine the effects of climate, carbon dioxide concentrations and fire disturbance on net biome production, net primary production and vegetation dominance in 100 Mha of Canadian boreal forest. We find that the carbon balance of this region was driven by changes in fire disturbance from 1948 to 2005. Climate changes affected the variability, but not the mean, of the landscape carbon balance, with precipitation exerting a more significant effect than temperature. We show that more frequent and larger fires in the late twentieth century resulted in deciduous trees and mosses increasing production at the expense of coniferous trees. Our model did not however exhibit the increases in total forest net primary production that have been inferred from satellite data. We find that poor soil drainage decreased the variability of the landscape carbon balance, which suggests that increased climate and hydrological changes have the potential to affect disproportionately the carbon dynamics of these areas. Overall, we conclude that direct ecophysiological changes resulting from global climate change have not yet been felt in this large boreal region. Variations in the landscape carbon balance and vegetation dominance have so far been driven largely by increases in fire frequency.

A Variable-Instar Climate-Driven Individual Beetle-Based Phenology Model for the Invasive Asian Longhorned Beetle (Coleoptera: Cerambycidae).

PubMed

Trotter, R Talbot; Keena, Melody A

2016-12-01

Efforts to manage and eradicate invasive species can benefit from an improved understanding of the physiology, biology, and behavior of the target species, and ongoing efforts to eradicate the Asian longhorned beetle (Anoplophora glabripennis Motschulsky) highlight the roles this information may play. Here, we present a climate-driven phenology model for A. glabripennis that provides simulated life-tables for populations of individual beetles under variable climatic conditions that takes into account the variable number of instars beetles may undergo as larvae. Phenology parameters in the model are based on a synthesis of published data and studies of A. glabripennis, and the model output was evaluated using a laboratory-reared population maintained under varying temperatures mimicking those typical of Central Park in New York City. The model was stable under variations in population size, simulation length, and the Julian dates used to initiate individual beetles within the population. Comparison of model results with previously published field-based phenology studies in native and invasive populations indicates both this new phenology model, and the previously published heating-degree-day model show good agreement in the prediction of the beginning of the flight season for adults. However, the phenology model described here avoids underpredicting the cumulative emergence of adults through the season, in addition to providing tables of life stages and estimations of voltinism for local populations. This information can play a key role in evaluating risk by predicting the potential for population growth, and may facilitate the optimization of management and eradication efforts. Published by Oxford University Press on behalf of Entomological Society of America 2016. This work is written by US Government employees and is in the public domain in the US.

Local cooling and warming effects of forests based on satellite observations.

PubMed

Li, Yan; Zhao, Maosheng; Motesharrei, Safa; Mu, Qiaozhen; Kalnay, Eugenia; Li, Shuangcheng

2015-03-31

The biophysical effects of forests on climate have been extensively studied with climate models. However, models cannot accurately reproduce local climate effects due to their coarse spatial resolution and uncertainties, and field observations are valuable but often insufficient due to their limited coverage. Here we present new evidence acquired from global satellite data to analyse the biophysical effects of forests on local climate. Results show that tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually; and boreal forests have strong warming in winter and moderate cooling in summer with net warming annually. The spatiotemporal cooling or warming effects are mainly driven by the two competing biophysical effects, evapotranspiration and albedo, which in turn are strongly influenced by rainfall and snow. Implications of our satellite-based study could be useful for informing local forestry policies.

Local cooling and warming effects of forests based on satellite observations

PubMed Central

Li, Yan; Zhao, Maosheng; Motesharrei, Safa; Mu, Qiaozhen; Kalnay, Eugenia; Li, Shuangcheng

2015-01-01

The biophysical effects of forests on climate have been extensively studied with climate models. However, models cannot accurately reproduce local climate effects due to their coarse spatial resolution and uncertainties, and field observations are valuable but often insufficient due to their limited coverage. Here we present new evidence acquired from global satellite data to analyse the biophysical effects of forests on local climate. Results show that tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually; and boreal forests have strong warming in winter and moderate cooling in summer with net warming annually. The spatiotemporal cooling or warming effects are mainly driven by the two competing biophysical effects, evapotranspiration and albedo, which in turn are strongly influenced by rainfall and snow. Implications of our satellite-based study could be useful for informing local forestry policies. PMID:25824529

Spatial match-mismatch between juvenile fish and prey provides a mechanism for recruitment variability across contrasting climate conditions in the eastern Bering Sea.

PubMed

Siddon, Elizabeth Calvert; Kristiansen, Trond; Mueter, Franz J; Holsman, Kirstin K; Heintz, Ron A; Farley, Edward V

2013-01-01

Understanding mechanisms behind variability in early life survival of marine fishes through modeling efforts can improve predictive capabilities for recruitment success under changing climate conditions. Walleye pollock (Theragra chalcogramma) support the largest single-species commercial fishery in the United States and represent an ecologically important component of the Bering Sea ecosystem. Variability in walleye pollock growth and survival is structured in part by climate-driven bottom-up control of zooplankton composition. We used two modeling approaches, informed by observations, to understand the roles of prey quality, prey composition, and water temperature on juvenile walleye pollock growth: (1) a bioenergetics model that included local predator and prey energy densities, and (2) an individual-based model that included a mechanistic feeding component dependent on larval development and behavior, local prey densities and size, and physical oceanographic conditions. Prey composition in late-summer shifted from predominantly smaller copepod species in the warmer 2005 season to larger species in the cooler 2010 season, reflecting differences in zooplankton composition between years. In 2010, the main prey of juvenile walleye pollock were more abundant, had greater biomass, and higher mean energy density, resulting in better growth conditions. Moreover, spatial patterns in prey composition and water temperature lead to areas of enhanced growth, or growth 'hot spots', for juvenile walleye pollock and survival may be enhanced when fish overlap with these areas. This study provides evidence that a spatial mismatch between juvenile walleye pollock and growth 'hot spots' in 2005 contributed to poor recruitment while a higher degree of overlap in 2010 resulted in improved recruitment. Our results indicate that climate-driven changes in prey quality and composition can impact growth of juvenile walleye pollock, potentially severely affecting recruitment variability.

How does Interactive Chemistry Influence the Representation of Stratosphere-Troposphere Coupling in a Climate Model?

NASA Astrophysics Data System (ADS)

Haase, S.; Matthes, K. B.

2017-12-01

Changes in stratospheric ozone can trigger tropospheric circulation changes. In the Southern hemisphere (SH), the observed shift of the Southern Annular Mode was attributed to the observed trend in lower stratospheric ozone. In the Northern Hemisphere (NH), a recent study showed that extremely low stratospheric ozone conditions during spring produce robust anomalies in the troposphere (zonal wind, temperature and precipitation). This could only be reproduced in a coupled chemistry climate model indicating that chemical-dynamical feedbacks are also important on the NH. To further investigate the importance of interactive chemistry for surface climate, we conducted a set of experiments using NCAR's Community Earth System Model (CESM1) with the Whole Atmosphere Community Climate Model (WACCM) as the atmosphere component. WACCM contains a fully interactive stratospheric chemistry module in its standard configuration. It also allows for an alternative configuration, referred to as SC-WACCM, in which the chemistry (O3, NO, O, O2, CO2 and chemical and shortwave heating rates) is specified as a 2D field in the radiation code. A comparison of the interactive vs. the specified chemistry version enables us to evaluate the relative importance of interactive chemistry by systematically inhibiting the feedbacks between chemistry and dynamics. To diminish the effect of temporal interpolation when prescribing ozone, we use daily resolved zonal mean ozone fields for the specified chemistry run. Here, we investigate the differences in stratosphere-troposphere coupling between the interactive and specified chemistry simulations for the mainly chemically driven SH as well as for the mainly dynamically driven NH. We will especially consider years that are characterized by extremely low stratospheric ozone on the one hand and by large dynamical disturbances, i.e. Sudden Stratospheric Warmings, on the other hand.

Characteristics of Quasi-Biennial Oscillation simulation in the Meteorological Research Institute earth system model

NASA Astrophysics Data System (ADS)

Yoshida, K.; Naoe, H.

2016-12-01

Whether climate models drive Quasi-Biennial Oscillation (QBO) appropriately is important to assess QBO impact on climate change such as global warming and solar related variation. However, there were few models generating QBO in the Coupled Model Intercomparison Project Phase 5 (CMIP5). This study focuses on dynamical structure of the QBO and its sensitivity to background wind pattern and model configuration. We present preliminary results of experiments designed by "Towards Improving the QBO in Global Climate Models (QBOi)", which is derived from the Stratosphere-troposphere processes and their role in climate (SPARC), in the Meteorological Research Institute earth system model, MRI-ESM2. The simulations were performed in present-day climate condition, repeated annual cycle condition with various CO2 level and sea surface temperatures, and QBO hindcast. In the present climate simulation, zonal wind in the equatorial stratosphere generally exhibits realistic behavior of the QBO. Equatorial zonal wind variability associated with QBO is overestimated in upper stratosphere and underestimated in lower stratosphere. In the MRI-ESM2, the QBO behavior is mainly driven by gravity wave drag parametrization (GWDP) introduced in Hines (1997). Comparing to reanalyses, shortage of resolved wave forcing is found especially in equatorial lower stratosphere. These discrepancies can be attributed to difference in wave forcing, background wind pattern and model configuration. We intend to show results of additional sensitivity experiments to examine how model configuration and background wind pattern affect resolved wave source, wave propagation characteristics, and QBO behavior.

Climate driven crop planting date in the ACME Land Model (ALM): Impacts on productivity and yield

NASA Astrophysics Data System (ADS)

Drewniak, B.

2017-12-01

Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical crops will be explored. Those impacts include discussions on productivity, yield, and influences on carbon and energy fluxes.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

The El Nino-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with Coupled General Circulation Models (CGCMs) to investigate how regional precipitation in the 21st century may be affected by changes in both ENSO-driven precipitation variability and slowly-evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of 20th century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in 21st century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with 20th century observations and more stationary during the 21st century. Finally, the model-predicted 21st century rainfall response to cENSO is decomposed into the sum of three terms: 1) the 21st century change in the mean state of precipitation; 2) the historical precipitation response to the cENSO pattern; and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Potential evapotranspiration and continental drying

USGS Publications Warehouse

Milly, Paul C.D.; Dunne, Krista A.

2016-01-01

By various measures (drought area and intensity, climatic aridity index, and climatic water deficits), some observational analyses have suggested that much of the Earth’s land has been drying during recent decades, but such drying seems inconsistent with observations of dryland greening and decreasing pan evaporation. ‘Offline’ analyses of climate-model outputs from anthropogenic climate change (ACC) experiments portend continuation of putative drying through the twenty-first century, despite an expected increase in global land precipitation. A ubiquitous increase in estimates of potential evapotranspiration (PET), driven by atmospheric warming, underlies the drying trends, but may be a methodological artefact. Here we show that the PET estimator commonly used (the Penman–Monteith PET for either an open-water surface or a reference crop) severely overpredicts the changes in non-water-stressed evapotranspiration computed in the climate models themselves in ACC experiments. This overprediction is partially due to neglect of stomatal conductance reductions commonly induced by increasing atmospheric CO2 concentrations in climate models. Our findings imply that historical and future tendencies towards continental drying, as characterized by offline-computed runoff, as well as other PET-dependent metrics, may be considerably weaker and less extensive than previously thought.

Understanding Water-Energy-Ecology Nexus from an Integrated Earth-Human System Perspective

NASA Astrophysics Data System (ADS)

Li, H. Y.; Zhang, X.; Wan, W.; Zhuang, Y.; Hejazi, M. I.; Leung, L. R.

2017-12-01

Both Earth and human systems exert notable controls on streamflow and stream temperature that influence energy production and ecosystem health. An integrated water model representing river processes and reservoir regulations has been developed and coupled to a land surface model and an integrated assessment model of energy, land, water, and socioeconomics to investigate the energy-water-ecology nexus in the context of climate change and water management. Simulations driven by two climate change projections following the RCP 4.5 and RCP 8.5 radiative forcing scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature in the U.S. The simulations revealed important impacts of climate change and water management on hydrological droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the RCP 4.5 and RCP 8.5 scenarios that influence streamflow and stream temperature, with important consequences to thermoelectricity production and future survival of juvenile Salmon. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME), a coupled Earth System Model, to enable future investigations of the energy-water-ecology nexus in the integrated Earth-Human system.

Evaluating the Performance of a Climate-Driven Mortality Model during Heat Waves and Cold Spells in Europe

PubMed Central

Lowe, Rachel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R.; Rodó, Xavier

2015-01-01

The impact of climate change on human health is a serious concern. In particular, changes in the frequency and intensity of heat waves and cold spells are of high relevance in terms of mortality and morbidity. This demonstrates the urgent need for reliable early-warning systems to help authorities prepare and respond to emergency situations. In this study, we evaluate the performance of a climate-driven mortality model to provide probabilistic predictions of exceeding emergency mortality thresholds for heat wave and cold spell scenarios. Daily mortality data corresponding to 187 NUTS2 regions across 16 countries in Europe were obtained from 1998–2003. Data were aggregated to 54 larger regions in Europe, defined according to similarities in population structure and climate. Location-specific average mortality rates, at given temperature intervals over the time period, were modelled to account for the increased mortality observed during both high and low temperature extremes and differing comfort temperatures between regions. Model parameters were estimated in a Bayesian framework, in order to generate probabilistic simulations of mortality across Europe for time periods of interest. For the heat wave scenario (1–15 August 2003), the model was successfully able to anticipate the occurrence or non-occurrence of mortality rates exceeding the emergency threshold (75th percentile of the mortality distribution) for 89% of the 54 regions, given a probability decision threshold of 70%. For the cold spell scenario (1–15 January 2003), mortality events in 69% of the regions were correctly anticipated with a probability decision threshold of 70%. By using a more conservative decision threshold of 30%, this proportion increased to 87%. Overall, the model performed better for the heat wave scenario. By replacing observed temperature data in the model with forecast temperature, from state-of-the-art European forecasting systems, probabilistic mortality predictions could potentially be made several months ahead of imminent heat waves and cold spells. PMID:25625407

Evaluating the performance of a climate-driven mortality model during heat waves and cold spells in Europe.

PubMed

Lowe, Rachel; Ballester, Joan; Creswick, James; Robine, Jean-Marie; Herrmann, François R; Rodó, Xavier

2015-01-23

The impact of climate change on human health is a serious concern. In particular, changes in the frequency and intensity of heat waves and cold spells are of high relevance in terms of mortality and morbidity. This demonstrates the urgent need for reliable early-warning systems to help authorities prepare and respond to emergency situations. In this study, we evaluate the performance of a climate-driven mortality model to provide probabilistic predictions of exceeding emergency mortality thresholds for heat wave and cold spell scenarios. Daily mortality data corresponding to 187 NUTS2 regions across 16 countries in Europe were obtained from 1998-2003. Data were aggregated to 54 larger regions in Europe, defined according to similarities in population structure and climate. Location-specific average mortality rates, at given temperature intervals over the time period, were modelled to account for the increased mortality observed during both high and low temperature extremes and differing comfort temperatures between regions. Model parameters were estimated in a Bayesian framework, in order to generate probabilistic simulations of mortality across Europe for time periods of interest. For the heat wave scenario (1-15 August 2003), the model was successfully able to anticipate the occurrence or non-occurrence of mortality rates exceeding the emergency threshold (75th percentile of the mortality distribution) for 89% of the 54 regions, given a probability decision threshold of 70%. For the cold spell scenario (1-15 January 2003), mortality events in 69% of the regions were correctly anticipated with a probability decision threshold of 70%. By using a more conservative decision threshold of 30%, this proportion increased to 87%. Overall, the model performed better for the heat wave scenario. By replacing observed temperature data in the model with forecast temperature, from state-of-the-art European forecasting systems, probabilistic mortality predictions could potentially be made several months ahead of imminent heat waves and cold spells.

Committed climate change due to historical land use and management: the concept

NASA Astrophysics Data System (ADS)

Freibauer, Annette; Dolman, Han; Don, Axel; Poeplau, Christopher

2013-04-01

A significant fraction of the European land surface has changed its land use over the last 50 years. Management practices have changed in the same period in most land use systems. These changes have affected the carbon and greenhouse gas (GHG) balance of the European land surface. Land use intensity, defined here loosely as the degree to which humans interfere with the land, strongly affects GHG emissions. Land use and land management changes suggest that the variability of the carbon balance and of GHG emissions of cultivated land areas in Europe is much more driven by land use history and management than driven by climate. Importantly changes in land use and its management have implications for future GHG emissions, and therefore present a committed climate change, defined as inevitable future additional climate change induced by past human activity. It is one of the key goals of the large-scale integrating research project "GHG-Europe - Greenhouse gas management in European land use systems" to quantify the committed climate change due to legacy effects by land use and management. The project is funded by the European Commission in the 7th framework programme (Grant agreement no.: 244122). This poster will present the conceptual approach taken to reach this goal. (1) First of all we need to proof that at site, or regional level the management effects are larger than climate effects on carbon balance and GHG emissions. Observations from managed sites and regions will serve as empirical basis. Attribution experiments with models based on process understanding are run on managed sites and regions will serve to demonstrate that the observed patterns of the carbon balance and GHG emissions can only be reproduced when land use and management are included as drivers. (2) The legacy of land use changes will be quantified by combining spatially explicit time series of land use changes with response functions of carbon pools. This will allow to separate short-term and long-term effects of land-use changes, to quantify how much current changes in biomass and soil carbon are driven by past land use change and how much future changes in biomass and soil carbon have already been committed by past and present land use changes. (3) The legacy of land management changes will be quantified by combining spatially explicit time series of land management activities with response functions and relatively simple models of carbon pools and greenhouse gases. This will allow to detect major trends and spatial patterns in carbon and GHG fluxes driven by intensification or extensification over the last decades. The poster will concentrate on background, concept of the legacy analysis, data sources and the scientific strategy for deriving the climate change committed by past and present land use and management in Europe.

Modelling marine community responses to climate-driven species redistribution to guide monitoring and adaptive ecosystem-based management.

PubMed

Marzloff, Martin Pierre; Melbourne-Thomas, Jessica; Hamon, Katell G; Hoshino, Eriko; Jennings, Sarah; van Putten, Ingrid E; Pecl, Gretta T

2016-07-01

As a consequence of global climate-driven changes, marine ecosystems are experiencing polewards redistributions of species - or range shifts - across taxa and throughout latitudes worldwide. Research on these range shifts largely focuses on understanding and predicting changes in the distribution of individual species. The ecological effects of marine range shifts on ecosystem structure and functioning, as well as human coastal communities, can be large, yet remain difficult to anticipate and manage. Here, we use qualitative modelling of system feedback to understand the cumulative impacts of multiple species shifts in south-eastern Australia, a global hotspot for ocean warming. We identify range-shifting species that can induce trophic cascades and affect ecosystem dynamics and productivity, and evaluate the potential effectiveness of alternative management interventions to mitigate these impacts. Our results suggest that the negative ecological impacts of multiple simultaneous range shifts generally add up. Thus, implementing whole-of-ecosystem management strategies and regular monitoring of range-shifting species of ecological concern are necessary to effectively intervene against undesirable consequences of marine range shifts at the regional scale. Our study illustrates how modelling system feedback with only limited qualitative information about ecosystem structure and range-shifting species can predict ecological consequences of multiple co-occurring range shifts, guide ecosystem-based adaptation to climate change and help prioritise future research and monitoring. © 2016 John Wiley & Sons Ltd.

Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: an important first step for assessing impact of future climate.

PubMed

Dixit, Prakash N; Telleria, Roberto

2015-04-01

Inter-annual and seasonal variability in climatic parameters, most importantly rainfall, have potential to cause climate-induced risk in long-term crop production. Short-term field studies do not capture the full nature of such risk and the extent to which modifications to crop, soil and water management recommendations may be made to mitigate the extent of such risk. Crop modeling studies driven by long-term daily weather data can predict the impact of climate-induced risk on crop growth and yield however, the availability of long-term daily weather data can present serious constraints to the use of crop models. To tackle this constraint, two weather generators namely, LARS-WG and MarkSim, were evaluated in order to assess their capabilities of reproducing frequency distributions, means, variances, dry spell and wet chains of observed daily precipitation, maximum and minimum temperature, and solar radiation for the eight locations across cropping areas of Northern Syria and Lebanon. Further, the application of generated long-term daily weather data, with both weather generators, in simulating barley growth and yield was also evaluated. We found that overall LARS-WG performed better than MarkSim in generating daily weather parameters and in 50 years continuous simulation of barley growth and yield. Our findings suggest that LARS-WG does not necessarily require long-term e.g., >30 years observed weather data for calibration as generated results proved to be satisfactory with >10 years of observed data except in area with higher altitude. Evaluating these weather generators and the ability of generated weather data to perform long-term simulation of crop growth and yield is an important first step to assess the impact of future climate on yields, and to identify promising technologies to make agricultural systems more resilient in the given region. Copyright © 2015 Elsevier B.V. All rights reserved.

Tree mortality from drought, insects, and their interactions in a changing climate

USGS Publications Warehouse

Anderegg, William R.L.; Hicke, Jeffrey A.; Fisher, Rosie A.; Allen, Craig D.; Aukema, Juliann E.; Bentz, Barbara; Hood, Sharon; Lichstein, Jeremy W.; Macalady, Alison K.; McDowell, Nate G.; Pan, Yude; Raffa, Kenneth; Sala, Anna; Shaw, John D.; Stephenson, Nathan L.; Tague, Christina L.; Zeppel, Melanie

2015-01-01

Climate change is expected to drive increased tree mortality through drought, heat stress, and insect attacks, with manifold impacts on forest ecosystems. Yet, climate-induced tree mortality and biotic disturbance agents are largely absent from process-based ecosystem models. Using data sets from the western USA and associated studies, we present a framework for determining the relative contribution of drought stress, insect attack, and their interactions, which is critical for modeling mortality in future climates. We outline a simple approach that identifies the mechanisms associated with two guilds of insects – bark beetles and defoliators – which are responsible for substantial tree mortality. We then discuss cross-biome patterns of insect-driven tree mortality and draw upon available evidence contrasting the prevalence of insect outbreaks in temperate and tropical regions. We conclude with an overview of tools and promising avenues to address major challenges. Ultimately, a multitrophic approach that captures tree physiology, insect populations, and tree–insect interactions will better inform projections of forest ecosystem responses to climate change.

Protected areas' role in climate-change mitigation.

PubMed

Melillo, Jerry M; Lu, Xiaoliang; Kicklighter, David W; Reilly, John M; Cai, Yongxia; Sokolov, Andrei P

2016-03-01

Globally, 15.5 million km(2) of land are currently identified as protected areas, which provide society with many ecosystem services including climate-change mitigation. Combining a global database of protected areas, a reconstruction of global land-use history, and a global biogeochemistry model, we estimate that protected areas currently sequester 0.5 Pg C annually, which is about one fifth of the carbon sequestered by all land ecosystems annually. Using an integrated earth systems model to generate climate and land-use scenarios for the twenty-first century, we project that rapid climate change, similar to high-end projections in IPCC's Fifth Assessment Report, would cause the annual carbon sequestration rate in protected areas to drop to about 0.3 Pg C by 2100. For the scenario with both rapid climate change and extensive land-use change driven by population and economic pressures, 5.6 million km(2) of protected areas would be converted to other uses, and carbon sequestration in the remaining protected areas would drop to near zero by 2100.

A decade of sea level rise slowed by climate-driven hydrology.

PubMed

Reager, J T; Gardner, A S; Famiglietti, J S; Wiese, D N; Eicker, A; Lo, M-H

2016-02-12

Climate-driven changes in land water storage and their contributions to sea level rise have been absent from Intergovernmental Panel on Climate Change sea level budgets owing to observational challenges. Recent advances in satellite measurement of time-variable gravity combined with reconciled global glacier loss estimates enable a disaggregation of continental land mass changes and a quantification of this term. We found that between 2002 and 2014, climate variability resulted in an additional 3200 ± 900 gigatons of water being stored on land. This gain partially offset water losses from ice sheets, glaciers, and groundwater pumping, slowing the rate of sea level rise by 0.71 ± 0.20 millimeters per year. These findings highlight the importance of climate-driven changes in hydrology when assigning attribution to decadal changes in sea level. Copyright © 2016, American Association for the Advancement of Science.

Natural and anthropogenic land cover change and its impact on the regional climate and hydrological extremes over Sanjiangyuan region

NASA Astrophysics Data System (ADS)

Ji, P.; Yuan, X.

2017-12-01

Located in the northern Tibetan Plateau, Sanjiangyuan is the headwater region of the Yellow River, Yangtze River and Mekong River. Besides climate change, natural and human-induced land cover change (e.g., Graze for Grass Project) is also influencing the regional hydro-climate and hydrological extremes significantly. To quantify their impacts, a land surface model (LSM) with consideration of soil moisture-lateral surface flow interaction and quasi-three-dimensional subsurface flow, is used to conduct long-term high resolution simulations driven by China Meteorological Administration Land Data Assimilation System forcing data and different land cover scenarios. In particular, the role of surface and subsurface lateral flows is also analyzed by comparing with typical one-dimensional models. Lateral flows help to simulate soil moisture variability caused by topography at hyper-resolution (e.g., 100m), which is also essential for simulating hydrological extremes including soil moisture dryness/wetness and high/low flows. The LSM will also be coupled with a regional climate model to simulate the effect of natural and anthropogenic land cover change on regional climate, with particular focus on the land-atmosphere coupling at different resolutions with different configurations in modeling land surface hydrology.

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh

PubMed Central

Banu, Shahera; Guo, Yuming; Hu, Wenbiao; Dale, Pat; Mackenzie, John S.; Mengersen, Kerrie; Tong, Shilu

2015-01-01

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects. PMID:26537857

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh.

PubMed

Banu, Shahera; Guo, Yuming; Hu, Wenbiao; Dale, Pat; Mackenzie, John S; Mengersen, Kerrie; Tong, Shilu

2015-11-05

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects.

A vulnerability driven approach to identify adverse climate and land use change combinations for critical hydrologic indicator thresholds: Application to a watershed in Pennsylvania, USA

NASA Astrophysics Data System (ADS)

Singh, R.; Wagener, T.; Crane, R.; Mann, M. E.; Ning, L.

2014-04-01

Large uncertainties in streamflow projections derived from downscaled climate projections of precipitation and temperature can render such simulations of limited value for decision making in the context of water resources management. New approaches are being sought to provide decision makers with robust information in the face of such large uncertainties. We present an alternative approach that starts with the stakeholder's definition of vulnerable ranges for relevant hydrologic indicators. Then the modeled system is analyzed to assess under what conditions these thresholds are exceeded. The space of possible climates and land use combinations for a watershed is explored to isolate subspaces that lead to vulnerability, while considering model parameter uncertainty in the analysis. We implement this concept using classification and regression trees (CART) that separate the input space of climate and land use change into those combinations that lead to vulnerability and those that do not. We test our method in a Pennsylvania watershed for nine ecological and water resources related streamflow indicators for which an increase in temperature between 3°C and 6°C and change in precipitation between -17% and 19% is projected. Our approach provides several new insights, for example, we show that even small decreases in precipitation (˜5%) combined with temperature increases greater than 2.5°C can push the mean annual runoff into a slightly vulnerable regime. Using this impact and stakeholder driven strategy, we explore the decision-relevant space more fully and provide information to the decision maker even if climate change projections are ambiguous.

Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States.

PubMed

Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H

2017-02-21

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment ]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today's technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual.

Model uncertainties do not affect observed patterns of species richness in the Amazon.

PubMed

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo; Loyola, Rafael

2017-01-01

Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale-patterns of species richness and species vulnerability to climate change-are affected by the inputs used to model and project species distribution. We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species.

Model uncertainties do not affect observed patterns of species richness in the Amazon

PubMed Central

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo

2017-01-01

Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. PMID:29023503

Impacts of climate change and internal climate variability on french rivers streamflows

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Eric

2016-04-01

The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?

NASA Astrophysics Data System (ADS)

Ban, Nikolina; Schmidli, Juerg; Schär, Christoph

2015-04-01

Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6-7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that sub-daily (e.g. hourly) precipitation extremes may increase at about twice this rate (referred to as super-adiabatic scaling). Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parameterize convective precipitation (i.e. thunderstorms and rain showers). Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with environmental temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Consistent with previous results, projections reveal a significant decrease of mean summer precipitation (by 30%). However, unlike previous studies, we find that increase in both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation in 2km simulation (Ban et al. 2015). Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day super-adiabatic precipitation scaling into the future. The applicability of the Clausius-Clapeyron scaling across the whole event spectrum is a potentially useful result for climate impact adaptation. Ban, N., J. Schmidli and C. Schär (2015): Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster? Submitted to GRL. Ban, N., J. Schmidli and C. Schär (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478

Investigating added value of regional climate modeling in North American winter storm track simulations

NASA Astrophysics Data System (ADS)

Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

2018-03-01

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

Introducing the Met Office 2.2-km Europe-wide convection-permitting regional climate simulations

NASA Astrophysics Data System (ADS)

Kendon, Elizabeth J.; Chan, Steven C.; Berthou, Segolene; Fosser, Giorgia; Roberts, Malcolm J.; Fowler, Hayley J.

2017-04-01

The Met Office is currently conducting Europe-wide 2.2-km convection-permitting model (CPM) simulations driven by ERA-Interim reanalysis and present/future-climate GCM simulations. Here, we present the preliminary results of these new European simulations examining daily and sub-daily precipitation outputs in comparison with observations across Europe, 12-km European and 1.5-km UK climate model simulations. As the simulations are not yet complete, we focus on diagnostics that are relatively robust with a limited amount of data; for instance, the diurnal cycle and the probability distribution of daily and sub-daily precipitation intensities. We will also present specific case studies that showcase the benefits of using continental-scale CPM simulations over previously-available small-domain CPM simulations.

Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

USGS Publications Warehouse

Jeton, A.E.; Dettinger, M.D.; Smith, J. LaRue

1996-01-01

Precipitation-runoff models of the East Fork Carson and North Fork American Rivers were developed and calibrated for use in evaluating the sensitivity of streamflow in the north-central Sierra Nevada to climate change. The East Fork Carson River drains part of the rain-shadowed, eastern slope of the Sierra Nevada and is generally higher than the North Fork American River, which drains the wetter, western slope. First, a geographic information system was developed to describe the spatial variability of basin characteristics and to help estimate model parameters. The result was a partitioning of each basin into noncontiguous, but hydrologically uniform, land units. Hydrologic descriptions of these units were developed and the Precipitation- Runoff Modeling System (PRMS) was used to simulate water and energy balances for each unit in response to daily weather conditions. The models were calibrated and verified using historical streamflows over 22-year (Carson River) and 42-year (American River) periods. Simulated annual streamflow errors average plus 10 percent of the observed flow for the East Fork Carson River basin and plus 15 percent for the North Fork American River basin. Interannual variability is well simulated overall, but, at daily scales, wet periods are simulated more accurately than drier periods. The simulated water budgets for the two basins are significantly different in seasonality of streamflow, sublimation, evapotranspiration, and snowmelt. The simulations indicate that differences in snowpack and snowmelt timing can play pervasive roles in determining the sensitivity of water resources to climate change, in terms of both resource availability and amount. The calibrated models were driven by more than 25 hypothetical climate-change scenarios, each 100 years long. The scenarios were synthesized and spatially disaggregated by methods designed to preserve realistic daily, monthly, annual, and spatial statistics. Simulated streamflow timing was not very sensitive to changes in mean precipitation, but was sensitive to changes in mean temperatures. Changes in annual streamflow amounts were amplified reflections of imposed mean precipitation changes, with especially large responses to wetter climates. In contrast, streamflow amount was surprisingly insensitive to mean temperature changes as a result of temporal links between peak snowmelt and the beginning of warm-season evapotranspiration. Comparisons of simulations driven by temporally detailed climate-model changes in which mean temperature changes vary from month to month and simulations in which uniform climate changes were imposed throughout the year indicate that the snowpack accumulates the influences of short-term conditions so that season average climate changes were more important than shorter term changes.

Implications of between-isolate variation for climate change impact modelling of Haemonchus contortus populations.

PubMed

Rose Vineer, H; Steiner, J; Knapp-Lawitzke, F; Bull, K; von Son-de Fernex, E; Bosco, A; Hertzberg, H; Demeler, J; Rinaldi, L; Morrison, A A; Skuce, P; Bartley, D J; Morgan, E R

2016-10-15

The impact of climate change on parasites and parasitic diseases is a growing concern and numerous empirical and mechanistic models have been developed to predict climate-driven spatial and temporal changes in the distribution of parasites and disease risk. Variation in parasite phenotype and life-history traits between isolates could undermine the application of such models at broad spatial scales. Seasonal variation in the transmission of the haematophagous gastrointestinal nematode Haemonchus contortus, one of the most pathogenic helminth species infecting sheep and goats worldwide, is primarily determined by the impact of environmental conditions on the free-living stages. To evaluate variability in the development success and mortality of the free-living stages of H. contortus and the impact of this variability on future climate impact modelling, three isolates of diverse origin were cultured at a range of temperatures between 15°C and 37°C to determine their development success compared with simulations using the GLOWORM-FL H. contortus model. No significant difference was observed in the developmental success of the three isolates of H. contortus tested, nor between isolates and model simulations. However, development success of all isolates at 37°C was lower than predicted by the model, suggesting the potential for overestimation of transmission risk at higher temperatures, such as those predicted under some scenarios of climate change. Recommendations are made for future climate impact modelling of gastrointestinal nematodes. Copyright © 2016 Elsevier B.V. All rights reserved.

A Coupled Economic and Physical Model of Coastal Adaptation and Abandonment: Are human occupied coastlines a bubble waiting to burst?

NASA Astrophysics Data System (ADS)

McNamara, D.; Keeler, A.

2011-12-01

Policy discussions of adaptation by coastal residents to increasing rates of sea level rise and changing frequency of damaging storms have focused on community land use planning processes. This view neglects the role that market dynamics and climate change expectations play in the way coastal communities choose among risk mitigation options and manage land use decisions in an environment of escalating risks. We use a model coupling physical coastal processes with an agent-based model of behavior in real estate and mitigation markets to examine the interplay of climate-driven coastal hazards, collective mitigation decisions, and individual beliefs. The physical component model simulates barrier island processes that respond to both storms and slow scale dynamics associated with sea level rise. The economic component model is an agent-based model of economic behavior where agents are rational economic actors working off different assessments of future climate-driven events. Agents differentially update their beliefs based on a) how much emphasis they give to observed coastal changes and b) how much weight they give to scientific predictions. In essence, agents differ along a spectrum of how much they believe that the past is the best guide to the future and how quickly they react to new information. We use the coupled model to explore three questions of interest to coastal policy. First, how do the interplay of costal processes, beliefs, and mitigation choices affect the level and stability of real estate prices? Second, how does this interplay affect the incentives for community investments in shoreline protection? Third, how do expectations and reactions to observed events, as well as mitigation investments, affect the built environment in circumstances when climate risks reach very high levels? This last question relates to a key aspect of climate change adaptation on the coast - when does mitigation give way to abandonment as an optimal adaptation strategy? Results suggest that subjective expectations about climate risk and about the effectiveness of mitigation in high-risk environments are critical in determining when the market starts to reflect the possibility that property might no longer be inhabitable. Results will be presented that contrast the dynamics of abandonment over a range of sea level rise and storminess scenarios.

Climate and air quality impacts of altered BVOC fluxes from land cover change in Southeast Asia 1990 - 2010

NASA Astrophysics Data System (ADS)

Harper, Kandice; Yue, Xu; Unger, Nadine

2016-04-01

Large-scale transformation of the natural rainforests of Southeast Asia in recent decades, driven primarily by logging and agroforestry activities, including rapid expansion of plantations of high-isoprene-emitting oil palm (Elaeis guineensis) trees at the expense of comparatively low-emitting natural dipterocarp rainforests, may have altered the prevailing regime of biogenic volatile organic compound (BVOC) fluxes from this tropical region. Chemical processing of isoprene in the atmosphere impacts the magnitude and distribution of several short-lived climate forcers, including ozone and secondary organic aerosols. Consequently, modification of the fluxes of isoprene and other BVOCs from vegetation serves as a mechanism by which tropical land cover change impacts both air quality and climate. We apply satellite-derived snapshots of land cover for the period 1990 - 2010 to the NASA ModelE2-Yale Interactive Terrestrial Biosphere (ModelE2-YIBs) global carbon-chemistry-climate model to quantify the impact of Southeast Asian land cover change on atmospheric chemical composition and climate driven by changes in isoprene emission. NASA ModelE2-YIBs features a fully interactive land carbon cycle and includes a BVOC emission algorithm which energetically couples isoprene production to photosynthesis. The time-slice simulations are nudged with large-scale winds from the GMAO reanalysis dataset and are forced with monthly anthropogenic and biomass burning reactive air pollution emissions from the MACCity emissions inventory. Relative to the year 1990, regional isoprene emissions in 2010 increased by 2.6 TgC/yr from the expansion of Southeast Asian oil palm plantations and decreased by 0.7 TgC/yr from the loss of regional dipterocarp rainforest. Considering only the impact of land-cover-change-induced isoprene emission changes in Southeast Asia over this period, we calculate a spatially heterogeneous impact on regional seasonal surface-level ozone concentrations (minimum: -1.0 ppb, maximum: +1.3 ppb) in conjunction with an increase in ozone concentration in the free tropical troposphere (maximum zonal-average increase of 1.3 ppb in the climate-sensitive upper tropical troposphere). The resulting long-wave radiative forcing from changes in the ozone concentration exhibits a moderate regional signature in the tropics (+4 mW/m2 tropical average).

Carbon dynamics of forest in Washington, USA: 21st century projections based on climate-driven changes in fire regimes

Treesearch

Crystal L. Raymond; Donald McKenzie

2012-01-01

During the 21st century, climate-driven changes in fire regimes will be a key agent of change in forests of the U.S. Pacific Northwest (PNW). Understanding the response of forest carbon (C) dynamics to increases in fire will help quantify limits on the contribution of forest C storage to climate change mitigation and prioritize forest types for...

Sensitivity study of heavy precipitation in Limited Area Model climate simulations: influence of the size of the domain and the use of the spectral nudging technique

NASA Astrophysics Data System (ADS)

Colin, Jeanne; Déqué, Michel; Radu, Raluca; Somot, Samuel

2010-10-01

We assess the impact of two sources of uncertainties in a limited area model (LAM) on the representation of intense precipitation: the size of the domain of integration and the use of the spectral nudging technique (driving of the large-scale within the domain of integration). We work in a perfect-model approach where the LAM is driven by a general circulation model (GCM) run at the same resolution and sharing the same physics and dynamics as the LAM. A set of three 50 km resolution simulations run over Western Europe with the LAM ALADIN-Climate and the GCM ARPEGE-Climate are performed to address this issue. Results are consistent with previous studies regarding the seasonal-mean fields. Furthermore, they show that neither the use of the spectral nudging nor the choice of a small domain are detrimental to the modelling of heavy precipitation in the present experiment.

On the stability of the Atlantic meridional overturning circulation

PubMed Central

Hofmann, Matthias; Rahmstorf, Stefan

2009-01-01

One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC. PMID:19897722

Investigation of tropical diurnal convection biases in a climate model using TWP-ICE observations and convection-permitting simulations

NASA Astrophysics Data System (ADS)

Lin, W.; Xie, S.; Jackson, R. C.; Endo, S.; Vogelmann, A. M.; Collis, S. M.; Golaz, J. C.

2017-12-01

Climate models are known to have difficulty in simulating tropical diurnal convections that exhibit distinct characteristics over land and open ocean. While the causes are rooted in deficiencies in convective parameterization in general, lack of representations of mesoscale dynamics in terms of land-sea breeze, convective organization, and propagation of convection-induced gravity waves also play critical roles. In this study, the problem is investigated at the process-level with the U.S. Department of Energy Accelerated Climate Modeling for Energy (ACME) model in short-term hindcast mode using the Cloud Associated Parameterization Testbed (CAPT) framework. Convective-scale radar retrievals and observation-driven convection-permitting simulations for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) cases are used to guide the analysis of the underlying processes. The emphasis will be on linking deficiencies in representation of detailed process elements to the model biases in diurnal convective properties and their contrast among inland, coastal and open ocean conditions.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers

PubMed Central

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell’Aquila, Alessandro

2014-01-01

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests. PMID:24706833

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers.

PubMed

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell'Aquila, Alessandro

2014-04-15

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.

Climate-driven regime shift of a temperate marine ecosystem.

PubMed

Wernberg, Thomas; Bennett, Scott; Babcock, Russell C; de Bettignies, Thibaut; Cure, Katherine; Depczynski, Martial; Dufois, Francois; Fromont, Jane; Fulton, Christopher J; Hovey, Renae K; Harvey, Euan S; Holmes, Thomas H; Kendrick, Gary A; Radford, Ben; Santana-Garcon, Julia; Saunders, Benjamin J; Smale, Dan A; Thomsen, Mads S; Tuckett, Chenae A; Tuya, Fernando; Vanderklift, Mathew A; Wilson, Shaun

2016-07-08

Ecosystem reconfigurations arising from climate-driven changes in species distributions are expected to have profound ecological, social, and economic implications. Here we reveal a rapid climate-driven regime shift of Australian temperate reef communities, which lost their defining kelp forests and became dominated by persistent seaweed turfs. After decades of ocean warming, extreme marine heat waves forced a 100-kilometer range contraction of extensive kelp forests and saw temperate species replaced by seaweeds, invertebrates, corals, and fishes characteristic of subtropical and tropical waters. This community-wide tropicalization fundamentally altered key ecological processes, suppressing the recovery of kelp forests. Copyright © 2016, American Association for the Advancement of Science.

Effects of climate change on residential infiltration and air pollution exposure.

PubMed

Ilacqua, Vito; Dawson, John; Breen, Michael; Singer, Sarany; Berg, Ashley

2017-01-01

Air exchange through infiltration is driven partly by indoor/outdoor temperature differences, and as climate change increases ambient temperatures, such differences could vary considerably even with small ambient temperature increments, altering patterns of exposures to both indoor and outdoor pollutants. We calculated changes in air fluxes through infiltration for prototypical detached homes in nine metropolitan areas in the United States (Atlanta, Boston, Chicago, Houston, Los Angeles, Minneapolis, New York, Phoenix, and Seattle) from 1970-2000 to 2040-2070. The Lawrence Berkeley National Laboratory model of infiltration was used in combination with climate data from eight regionally downscaled climate models from the North American Regional Climate Change Assessment Program. Averaged over all study locations, seasons, and climate models, air exchange through infiltration would decrease by ~5%. Localized increased infiltration is expected during the summer months, up to 20-30%. Seasonal and daily variability in infiltration are also expected to increase, particularly during the summer months. Diminished infiltration in future climate scenarios may be expected to increase exposure to indoor sources of air pollution, unless these ventilation reductions are otherwise compensated. Exposure to ambient air pollution, conversely, could be mitigated by lower infiltration, although peak exposure increases during summer months should be considered, as well as other mechanisms.

Ecological opportunity and the evolution of habitat preferences in an arid-zone bird: implications for speciation in a climate-modified landscape

PubMed Central

Norman, Janette A.; Christidis, Les

2016-01-01

Bioclimatic models are widely used to investigate the impacts of climate change on species distributions. Range shifts are expected to occur as species track their current climate niche yet the potential for exploitation of new ecological opportunities that may arise as ecosystems and communities remodel is rarely considered. Here we show that grasswrens of the Amytornis textilis-modestus complex responded to new ecological opportunities in Australia’s arid biome through shifts in habitat preference following the development of chenopod shrublands during the late Plio-Pleistocene. We find evidence of spatially explicit responses to climatically driven landscape changes including changes in niche width and patterns of population growth. Conservation of structural and functional aspects of the ancestral niche appear to have facilitated recent habitat shifts, while demographic responses to late Pleistocene climate change provide evidence for the greater resilience of populations inhabiting the recently evolved chenopod shrubland communities. Similar responses could occur under future climate change in species exposed to novel ecological conditions, or those already occupying spatially heterogeneous landscapes. Mechanistic models that consider structural and functional aspects of the niche along with regional hydro-dynamics may be better predictors of future climate responses in Australia’s arid biome than bioclimatic models alone. PMID:26787111

Modeling climate change impacts on overwintering bald eagles.

PubMed

Harvey, Chris J; Moriarty, Pamela E; Salathé, Eric P

2012-03-01

Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperature, precipitation, wind, and longwave radiation estimates at the mouths of three Puget Sound tributaries (the Skagit, Hamma Hamma, and Nisqually rivers) in two decades, the 1970s and the 2050s. Climate data were used to drive bald eagle bioenergetics models from December to February for each river, year, and decade. Bald eagle bioenergetics were insensitive to climate change: despite warmer winters in the 2050s, particularly near the Nisqually River, bald eagle food requirements declined only slightly (<1%). However, the warming climate caused salmon carcasses to decompose more rapidly, resulting in 11% to 14% less annual carcass biomass available to eagles in the 2050s. That estimate is likely conservative, as it does not account for decreased availability of carcasses due to anticipated increases in winter stream flow. Future climate-driven declines in winter food availability, coupled with a growing bald eagle population, may force eagles to seek alternate prey in the Puget Sound area or in more remote ecosystems.

Modeling climate change impacts on overwintering bald eagles

PubMed Central

Harvey, Chris J; Moriarty, Pamela E; Salathé Jr, Eric P

2012-01-01

Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperature, precipitation, wind, and longwave radiation estimates at the mouths of three Puget Sound tributaries (the Skagit, Hamma Hamma, and Nisqually rivers) in two decades, the 1970s and the 2050s. Climate data were used to drive bald eagle bioenergetics models from December to February for each river, year, and decade. Bald eagle bioenergetics were insensitive to climate change: despite warmer winters in the 2050s, particularly near the Nisqually River, bald eagle food requirements declined only slightly (<1%). However, the warming climate caused salmon carcasses to decompose more rapidly, resulting in 11% to 14% less annual carcass biomass available to eagles in the 2050s. That estimate is likely conservative, as it does not account for decreased availability of carcasses due to anticipated increases in winter stream flow. Future climate-driven declines in winter food availability, coupled with a growing bald eagle population, may force eagles to seek alternate prey in the Puget Sound area or in more remote ecosystems. PMID:22822430

Spatially-explicit and spectral soil carbon modeling in Florida

USDA-ARS?s Scientific Manuscript database

Profound shifts have occurred over the last three centuries in which human actions have become the main driver to global environmental change. In this new epoch, the Anthropocene, human-driven changes such as population growth, climate and land use change, are pushing the Earth system well outside i...

Learning to love the rain in Bergen (Norway) and other lessons from a Climate Services neophyte

NASA Astrophysics Data System (ADS)

Sobolowski, Stefan; Wakker, Joyce

2014-05-01

A question that is often asked of regional climate modelers generally, and Climate Service providers specifically, is: "What is the added-value of regional climate simulations and how can I use this information?" The answer is, unsurprisingly, not straightforward and depends greatly on what one needs to know. In particular it is important for scientist to communicate directly with the users of this information to determine what kind of information is important for them to do their jobs. This study is part of the ECLISE project (Enabling Climate Information Services for Europe) and involves a user at the municipality of Bergen's (Norway) water and drainage administration and a provider from Uni Research and the Bjerknes Center for Climate Research. The water and drain administration is responsible for communicating potential future changes in extreme precipitation, particularly short-term high-intensity rainfall, which is common in Bergen and making recommendations to the engineering department for changes in design criteria. Thus, information that enables better decision-making is crucial. This study then actually has two relevant components for climate services: 1) is a scientific exercise to evaluate the performance of high resolution regional climate simulations and their ability to reproduce high intensity short duration precipitation and 2) an exercise in communication between a provider community and user community with different concerns, mandates, methodological approaches and even vocabularies. A set of Weather Research and Forecasting (WRF) simulations was run at high resolution (8km) over a large domain covering much of Scandinavia and Northern Europe. One simulation was driven by so-called "perfect" boundary conditions taken from reanalysis data (ERA-interim, 1989-2010) the second and third simulations used Norway's global climate model as boundary forcing (NorESM) and were run for a historical period (1950-2005) and a 30yr. end of the century time slice under the rcp4.5 "middle of the road" emissions scenario (2071-2100). A unique feature of the WRF modeling system is the ability to write data for selected locations at every time step, thus creating time series of very high temporal resolution which can be compared to observations. This high temporal resolution also allowed us to directly calculate intensity-duration-frequency (IDF) curves for intense precipitation of short to long duration (5 minutes - 1 day) for a number of return periods (2-100 years) with out resorting to factors to calculate rainfall intensities at higher temporal resolutions, as is commonly done. We investigated the IDF curves using a number of parametric and non-parametric approaches. Given the relatively short time periods of the modeled data the standard Gumble approach is presented here. This is also done to maintain consistency with previous calculations by the water and drain administration. Curves were also generated from observed time series at two locations in Bergen. Both the historical, GCM-driven simulation and the ERA-interim driven simulation closely match the observed IDF curves for all return periods up to durations of about 10 minutes where WRF then fails to reproduce the very short, very high intensity events. IDF curves under future conditions were also generated and the changes were compared with the current standard approach of applying climate change-factors to observed extreme precipitation in order to account for structural errors in global and regional climate models. Our investigation suggests that high-resolution regional simulations can capture many of the topographic features and dynamical processes necessary to accurately model extreme rainfall, even in at highly local scales and over complex terrain such as Bergen, Norway. The exercise also produced many lessons for climate service providers and users alike.

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

The mineralogic evolution of the Martian surface through time: Implications from chemical reaction path modeling studies

NASA Technical Reports Server (NTRS)

Plumlee, G. S.; Ridley, W. I.; Debraal, J. D.; Reed, M. H.

1993-01-01

Chemical reaction path calculations were used to model the minerals that might have formed at or near the Martian surface as a result of volcano or meteorite impact driven hydrothermal systems; weathering at the Martian surface during an early warm, wet climate; and near-zero or sub-zero C brine-regolith reactions in the current cold climate. Although the chemical reaction path calculations carried out do not define the exact mineralogical evolution of the Martian surface over time, they do place valuable geochemical constraints on the types of minerals that formed from an aqueous phase under various surficial and geochemically complex conditions.

Direct effects dominate responses to climate perturbations in grassland plant communities.

PubMed

Chu, Chengjin; Kleinhesselink, Andrew R; Havstad, Kris M; McClaran, Mitchel P; Peters, Debra P; Vermeire, Lance T; Wei, Haiyan; Adler, Peter B

2016-06-08

Theory predicts that strong indirect effects of environmental change will impact communities when niche differences between competitors are small and variation in the direct effects experienced by competitors is large, but empirical tests are lacking. Here we estimate negative frequency dependence, a proxy for niche differences, and quantify the direct and indirect effects of climate change on each species. Consistent with theory, in four of five communities indirect effects are strongest for species showing weak negative frequency dependence. Indirect effects are also stronger in communities where there is greater variation in direct effects. Overall responses to climate perturbations are driven primarily by direct effects, suggesting that single species models may be adequate for forecasting the impacts of climate change in these communities.

An Empirical Approach to Predicting Effects of Climate Change on Stream Water Chemistry

NASA Astrophysics Data System (ADS)

Olson, J. R.; Hawkins, C. P.

2014-12-01

Climate change may affect stream solute concentrations by three mechanisms: dilution associated with increased precipitation, evaporative concentration associated with increased temperature, and changes in solute inputs associated with changes in climate-driven weathering. We developed empirical models predicting base-flow water chemistry from watershed geology, soils, and climate for 1975 individual stream sites across the conterminous USA. We then predicted future solute concentrations (2065 and 2099) by applying down-scaled global climate model predictions to these models. The electrical conductivity model (EC, model R2 = 0.78) predicted mean increases in EC of 19 μS/cm by 2065 and 40 μS/cm by 2099. However predicted responses for individual streams ranged from a 43% decrease to a 4x increase. Streams with the greatest predicted decreases occurred in the southern Rocky Mountains and Mid-West, whereas southern California and Sierra Nevada streams showed the greatest increases. Generally, streams in dry areas underlain by non-calcareous rocks were predicted to be the most vulnerable to increases in EC associated with climate change. Predicted changes in other water chemistry parameters (e.g., Acid Neutralization Capacity (ANC), SO4, and Ca) were similar to EC, although the magnitude of ANC and SO4 change was greater. Predicted changes in ANC and SO4 are in general agreement with those changes already observed in seven locations with long term records.

Analysis of the present and future winter Pacific-North American teleconnection in the ECHAM5 global and RegCM3 regional climate models

USGS Publications Warehouse

Allan, Andrea M.; Hostetler, Steven W.; Alder, Jay R.

2014-01-01

We use the NCEP/NCAR Reanalysis (NCEP) and the MPI/ECHAM5 general circulation model to drive the RegCM3 regional climate model to assess the ability of the models to reproduce the spatiotemporal aspects of the Pacific-North American teleconnection (PNA) pattern. Composite anomalies of the NCEP-driven RegCM3 simulations for 1982–2000 indicate that the regional model is capable of accurately simulating the key features (500-hPa heights, surface temperature, and precipitation) of the positive and negative phases of the PNA with little loss of information in the downscaling process. The basic structure of the PNA is captured in both the ECHAM5 global and ECHAM5-driven RegCM3 simulations. The 1950–2000 ECHAM5 simulation displays similar temporal and spatial variability in the PNA index as that of NCEP; however, the magnitudes of the positive and negative phases are weaker than those of NCEP. The RegCM3 simulations clearly differentiate the climatology and associated anomalies of snow water equivalent and soil moisture of the positive and negative PNA phases. In the RegCM3 simulations of the future (2050–2100), changes in the location and extent of the Aleutian low and the continental high over North America alter the dominant flow patterns associated with positive and negative PNA modes. The future projections display a shift in the patterns of the relationship between the PNA and surface climate variables, which suggest the potential for changes in the PNA-related surface hydrology of North America.

Comparison of Malaria Simulations Driven by Meteorological Observations and Reanalysis Products in Senegal.

PubMed

Diouf, Ibrahima; Rodriguez-Fonseca, Belen; Deme, Abdoulaye; Caminade, Cyril; Morse, Andrew P; Cisse, Moustapha; Sy, Ibrahima; Dia, Ibrahima; Ermert, Volker; Ndione, Jacques-André; Gaye, Amadou Thierno

2017-09-25

The analysis of the spatial and temporal variability of climate parameters is crucial to study the impact of climate-sensitive vector-borne diseases such as malaria. The use of malaria models is an alternative way of producing potential malaria historical data for Senegal due to the lack of reliable observations for malaria outbreaks over a long time period. Consequently, here we use the Liverpool Malaria Model (LMM), driven by different climatic datasets, in order to study and validate simulated malaria parameters over Senegal. The findings confirm that the risk of malaria transmission is mainly linked to climate variables such as rainfall and temperature as well as specific landscape characteristics. For the whole of Senegal, a lag of two months is generally observed between the peak of rainfall in August and the maximum number of reported malaria cases in October. The malaria transmission season usually takes place from September to November, corresponding to the second peak of temperature occurring in October. Observed malaria data from the Programme National de Lutte contre le Paludisme (PNLP, National Malaria control Programme in Senegal) and outputs from the meteorological data used in this study were compared. The malaria model outputs present some consistencies with observed malaria dynamics over Senegal, and further allow the exploration of simulations performed with reanalysis data sets over a longer time period. The simulated malaria risk significantly decreased during the 1970s and 1980s over Senegal. This result is consistent with the observed decrease of malaria vectors and malaria cases reported by field entomologists and clinicians in the literature. The main differences between model outputs and observations regard amplitude, but can be related not only to reanalysis deficiencies but also to other environmental and socio-economic factors that are not included in this mechanistic malaria model framework. The present study can be considered as a validation of the reliability of reanalysis to be used as inputs for the calculation of malaria parameters in the Sahel using dynamical malaria models.

The relationship between climate change and the endangered rainforest shrub Triunia robusta (Proteaceae) endemic to southeast Queensland, Australia

NASA Astrophysics Data System (ADS)

Shimizu-Kimura, Yoko; Accad, Arnon; Shapcott, Alison

2017-04-01

Threatened species in rainforests may be vulnerable to climate change, because of their potentially narrow thermal tolerances, small population sizes and restricted distributions. This study modelled climate induced changes on the habitat distribution of the endangered rainforest plant Triunia robusta, endemic to southeast Queensland, Australia. Species distribution models were developed for eastern Australia at 250 m grids and southeast Queensland at 25 m grids using ground-truthed presence records and environmental predictor data. The species’ habitat distribution under the current climate was modelled, and the future potential habitat distributions were projected for the epochs 2030, 2050 and 2070. The eastern Australia model identified several spatially disjunct, broad habitat areas of coastal eastern Australia consistent with the current distribution of rainforests, and projected a southward and upslope contraction driven mainly by average temperatures exceeding current range limits. The southeast Queensland models suggest a dramatic upslope contraction toward locations where the majority of known populations are found. Populations located in the Sunshine Coast hinterland, consistent with past rainforest refugia, are likely to persist long-term. Upgrading the level of protection for less formal nature reserves containing viable populations is a high priority to better protect refugial T. robusta populations with respect to climate change.

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

PubMed

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

2012-03-06

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

The relationship between climate change and the endangered rainforest shrub Triunia robusta (Proteaceae) endemic to southeast Queensland, Australia

PubMed Central

Shimizu-Kimura, Yoko; Accad, Arnon; Shapcott, Alison

2017-01-01

Threatened species in rainforests may be vulnerable to climate change, because of their potentially narrow thermal tolerances, small population sizes and restricted distributions. This study modelled climate induced changes on the habitat distribution of the endangered rainforest plant Triunia robusta, endemic to southeast Queensland, Australia. Species distribution models were developed for eastern Australia at 250 m grids and southeast Queensland at 25 m grids using ground-truthed presence records and environmental predictor data. The species’ habitat distribution under the current climate was modelled, and the future potential habitat distributions were projected for the epochs 2030, 2050 and 2070. The eastern Australia model identified several spatially disjunct, broad habitat areas of coastal eastern Australia consistent with the current distribution of rainforests, and projected a southward and upslope contraction driven mainly by average temperatures exceeding current range limits. The southeast Queensland models suggest a dramatic upslope contraction toward locations where the majority of known populations are found. Populations located in the Sunshine Coast hinterland, consistent with past rainforest refugia, are likely to persist long-term. Upgrading the level of protection for less formal nature reserves containing viable populations is a high priority to better protect refugial T. robusta populations with respect to climate change. PMID:28422136

Irreducible Uncertainty in Terrestrial Carbon Projections

NASA Astrophysics Data System (ADS)

Lovenduski, N. S.; Bonan, G. B.

2016-12-01

We quantify and isolate the sources of uncertainty in projections of carbon accumulation by the ocean and terrestrial biosphere over 2006-2100 using output from Earth System Models participating in the 5th Coupled Model Intercomparison Project. We consider three independent sources of uncertainty in our analysis of variance: (1) internal variability, driven by random, internal variations in the climate system, (2) emission scenario, driven by uncertainty in future radiative forcing, and (3) model structure, wherein different models produce different projections given the same emission scenario. Whereas uncertainty in projections of ocean carbon accumulation by 2100 is 100 Pg C and driven primarily by emission scenario, uncertainty in projections of terrestrial carbon accumulation by 2100 is 50% larger than that of the ocean, and driven primarily by model structure. This structural uncertainty is correlated with emission scenario: the variance associated with model structure is an order of magnitude larger under a business-as-usual scenario (RCP8.5) than a mitigation scenario (RCP2.6). In an effort to reduce this structural uncertainty, we apply various model weighting schemes to our analysis of variance in terrestrial carbon accumulation projections. The largest reductions in uncertainty are achieved when giving all the weight to a single model; here the uncertainty is of a similar magnitude to the ocean projections. Such an analysis suggests that this structural uncertainty is irreducible given current terrestrial model development efforts.

Sensitivity of Antarctic sea ice to the Southern Annular Mode in coupled climate models

NASA Astrophysics Data System (ADS)

Holland, Marika M.; Landrum, Laura; Kostov, Yavor; Marshall, John

2017-09-01

We assess the sea ice response to Southern Annular Mode (SAM) anomalies for pre-industrial control simulations from the Coupled Model Intercomparison Project (CMIP5). Consistent with work by Ferreira et al. (J Clim 28:1206-1226, 2015. doi: 10.1175/JCLI-D-14-00313.1), the models generally simulate a two-timescale response to positive SAM anomalies, with an initial increase in ice followed by an eventual sea ice decline. However, the models differ in the cross-over time at which the change in ice response occurs, in the overall magnitude of the response, and in the spatial distribution of the response. Late twentieth century Antarctic sea ice trends in CMIP5 simulations are related in part to different modeled responses to SAM variability acting on different time-varying transient SAM conditions. This explains a significant fraction of the spread in simulated late twentieth century southern hemisphere sea ice extent trends across the model simulations. Applying the modeled sea ice response to SAM variability but driven by the observed record of SAM suggests that variations in the austral summer SAM, which has exhibited a significant positive trend, have driven a modest sea ice decrease. However, additional work is needed to narrow the considerable model uncertainty in the climate response to SAM variability and its implications for 20th-21st century trends.

Modeling Forest Composition and Carbon Dynamics Under Projected Climate-Fire Interactions in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liang, S.; Hurteau, M. D.; Westerling, A. L.

2014-12-01

The Sierra Nevada Mountains are occupied by a diversity of forest types that sort by elevation. The interaction of changing climate and altered disturbance regimes (e.g. fire) has the potential to drive changes in forest distribution as a function of species-specific response. Quantifying the effects of these drivers on species distributions and productivity under future climate-fire interactions is necessary for informing mitigation and adaptation efforts. In this study, we assimilated forest inventory and soil survey data and species life history traits into a landscape model, LANDIS-II, to quantify the response of forest dynamics to the interaction of climate change and large wildfire frequency in the Sierra Nevada. We ran 100-year simulations forced with historical climate and climate projections from three models (GFDL, CNRM and CCSM3) driven by the A2 emission scenario. We found that non-growing season NPP is greatly enhanced by 15%-150%, depending on the specific climate projection. The greatest increase occurs in subalpine forests. Species-specific response varied as a function of life history characteristics. The distribution of drought and fire-tolerant species, such as ponderosa pine, expanded by 7.3-9.6% from initial conditions, while drought and fire-intolerant species, such as white fir, showed little change in the absence of fire. Changes in wildfire size and frequency influence species distributions by altering the successional stage of burned patches. The range of responses to different climate models demonstrates the sensitivity of these forests to climate variability. The scale of climate projections relative to the scale of forest simulations presents a source of uncertainty, particularly at the ecotone between forest types and for identifying topographically mediated climate refugia. Improving simulations will likely require higher resolution climate projections.

Suggestions for Forest Conservation Policy under Climate Change

NASA Astrophysics Data System (ADS)

Choe, H.; Thorne, J. H.; Lee, D. K.; Seo, C.

2015-12-01

Climate change and the destruction of natural habitats by land-use change are two main factors in decreasing terrestrial biodiversity. Studying land-use and climate change and their impact under different scenarios can help suggest policy directions for future events. This study explores the spatial results of different land use and climate models on the extent of species rich areas in South Korea. We built land use models of forest conversion and created four 2050 scenarios: (1) a loss trend following current levels, resulting in 15.5% lost; (2) similar loss, but with forest conservation in areas with suitable future climates; (3) a reduction of forest loss by 50%; and (4) a combination of preservation of forest climate refugia and overall reduction of loss by 50%. Forest climate refugia were identified through the use of species distribution models run on 1,031 forest plant species to project current and 2050 distributions. We calculated change in species richness under four climate projections, permitting an assessment of forest refugia zones. We then crossed the four land use models with the climate-driven change in species richness. Forest areas predominantly convert to agricultural areas, while climate-suitable extents for forest plants decline and move northward, especially to higher elevations. Scenario 2, that has the higher level of deforestation but protects future species rich areas, conserves nearly as much future biodiversity as scenario 3, which reduced deforestation rates by 50%. This points to the importance of including biogeographic climate dynamics in forest policy. Scenario 4 was the most effective at conserving forest biodiversity. We suggest conserving forest areas with suitable climates for biodiversity conservation and the establishment of monoculture plantations targeted to areas where species richness will decline based on our results.

Analyzing the responses of species assemblages to climate change across the Great Basin, USA.

NASA Astrophysics Data System (ADS)

Henareh Khalyani, A.; Falkowski, M. J.; Crookston, N.; Yousef, F.

2016-12-01

The potential impacts of climate change on the future distribution of tree species in not well understood. Climate driven changes in tree species distribution could cause significant changes in realized species niches, potentially resulting in the loss of ecotonal species as well as the formation on novel assemblages of overlapping tree species. In an effort to gain a better understating of how the geographic distribution of tree species may respond to climate change, we model the potential future distribution of 50 different tree species across 70 million ha in the Great Basin, USA. This is achieved by leveraging a species realized niche model based on non-parametric analysis of species occurrences across climatic, topographic, and edaphic variables. Spatially explicit, high spatial resolution (30 m) climate variables (e.g., precipitation, and minimum, maximum, and mean temperature) and associated climate indices were generated on an annual basis between 1981-2010 by integrating climate station data with digital elevation data (Shuttle Radar Topographic Mission (SRTM) data) in a thin plate spline interpolation algorithm (ANUSPLIN). Bioclimate models of species niches in in the cotemporary period and three following 30 year periods were then generated by integrating the climate variables, soil data, and CMIP 5 general circulation model projections. Our results suggest that local scale contemporary variations in species realized niches across space are influenced by edaphic and topographic variables as well as climatic variables. The local variability in soil properties and topographic variability across space also affect the species responses to climate change through time and potential formation of species assemblages in future. The results presented here in will aid in the development of adaptive forest management techniques aimed at mitigating negative impacts of climate change on forest composition, structure, and function.

What Can Earth Paleoclimates Reveal About the Resiliency of Habitable States? An Example from the Neoproterozoic Snowball Earth

NASA Astrophysics Data System (ADS)

Sohl, L.

2014-04-01

The Neoproterozoic "Snowball Earth" glaciations ( 750-635 Ma) have been a special focus for outer habitable zone investigations, owing in large part to a captivating and controversial hypothesis suggesting that Earth may have only narrowly escaped a runaway icehouse state on multiple occasions (a.k.a. "the hard snowball"; Hoffman and Schrag 2001). A review of climate simulations exploring snowball inception (Godderis et al. 2011) reveals that a broad range of models (EBMs, EMICs and AGCMs) tend to yield hard snowball solutions, whereas models with greater 3-D dynamic response capabilities (AOGCMs) typically do not, unless some of their climate feedback responses (e.g., wind-driven ocean circulation, cloud forcings) are disabled (Poulsen and Jacobs 2004). This finding raises the likelihood that models incorporating dynamic climate feedbacks are essential to understanding how much flexibility there may be in the definition of a planet's habitable zone boundaries for a given point in its history. In the first of a series of new Snowball Earth simulations, we use the NASA/GISS ModelE2 Global Climate Model - a 3-D coupled atmosphere/ocean model with dynamic sea ice response - to explore the impacts of wind-driven ocean circulation, clouds and deep ocean circulation on the sea ice front when solar luminosity and atmospheric carbon dioxide are reduced to Neoproterozoic levels (solar = 94%, CO2 = 40 ppmv). The simulation includes a realistic Neoproterozoic land mass distribution, which is concentrated at mid- to tropical latitudes. After 300 years, the sea ice front is established near 30 degrees latitude, and after 600 years it remains stable. As with earlier coupled model simulations we conclude that runaway glacial states would have been difficult to achieve during the Neoproterozoic, and would be more likely to have occurred during earlier times in Earth history when solar luminosity was less. Inclusion of dynamic climate feedback capabilities in habitable zone modeling studies is likely to result in an expansion of our view of what a "Goldilocks" state can entail. Future simulations with a modified version of the NASA/GISS GCM, ROCKE-3D, will take advantage of newly-added model capabilities that evaluate the influence of rotation rate, solar spectral variability, CO2 surface condensation and CO2 clouds on the outer edge of Earth's habitable zone.

Assessing the Role of Climate Variability on Liver Fluke Risk in the UK Through Mechanistic Hydro-Epidemiological Modelling

NASA Astrophysics Data System (ADS)

Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

2016-12-01

Liver fluke is a flatworm parasite infecting grazing animals worldwide. In the UK, it causes considerable production losses to cattle and sheep industries and costs farmers millions of pounds each year due to reduced growth rates and lower milk yields. Large part of the parasite life-cycle takes place outside of the host, with its survival and development strongly controlled by climatic and hydrologic conditions. Evidence of climate-driven changes in the distribution and seasonality of fluke disease already exists, as the infection is increasingly expanding to new areas and becoming a year-round problem. Therefore, it is crucial to assess current and potential future impacts of climate variability on the disease to guide interventions at the farm scale and mitigate risk. Climate-based fluke risk models have been available since the 1950s, however, they are based on empirical relationships derived between historical climate and incidence data, and thus are unlikely to be robust for simulating risk under changing conditions. Moreover, they are not dynamic, but estimate risk over large regions in the UK based on monthly average climate conditions, so they do not allow investigating the effects of climate variability for supporting farmers' decisions. In this study, we introduce a mechanistic model for fluke, which represents habitat suitability for disease development at 25m resolution with a daily time step, explicitly linking the parasite life-cycle to key hydro-climate conditions. The model is used on a case study in the UK and sensitivity analysis is performed to better understand the role of climate variability on the space-time dynamics of the disease, while explicitly accounting for uncertainties. Comparisons are presented with experts' knowledge and a widely used empirical model.

Biophysical modeling of the temporal niche: from first principles to the evolution of activity patterns.

PubMed

Levy, Ofir; Dayan, Tamar; Kronfeld-Schor, Noga; Porter, Warren P

2012-06-01

Most mammals can be characterized as nocturnal or diurnal. However infrequently, species may overcome evolutionary constraints and alter their activity patterns. We modeled the fundamental temporal niche of a diurnal desert rodent, the golden spiny mouse, Acomys russatus. This species can shift into nocturnal activity in the absence of its congener, the common spiny mouse, Acomys cahirinus, suggesting that it was competitively driven into diurnality and that this shift in a small desert rodent may involve physiological costs. Therefore, we compared metabolic costs of diurnal versus nocturnal activity using a biophysical model to evaluate the preferred temporal niche of this species. The model predicted that energy expenditure during foraging is almost always lower during the day except during midday in summer at the less sheltered microhabitat. We also found that a shift in summer to foraging in less sheltered microhabitats in response to predation pressure and food availability involves a significant physiological cost moderated by midday reduction in activity. Thus, adaptation to diurnality may reflect the "ghost of competition past"; climate-driven diurnality is an alternative but less likely hypothesis. While climate is considered to play a major role in the physiology and evolution of mammals, this is the first study to model its potential to affect the evolution of activity patterns of mammals.

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Tropically driven and externally forced patterns of Antarctic sea ice change: reconciling observed and modeled trends

NASA Astrophysics Data System (ADS)

Schneider, David P.; Deser, Clara

2018-06-01

Recent work suggests that natural variability has played a significant role in the increase of Antarctic sea ice extent during 1979-2013. The ice extent has responded strongly to atmospheric circulation changes, including a deepened Amundsen Sea Low (ASL), which in part has been driven by tropical variability. Nonetheless, this increase has occurred in the context of externally forced climate change, and it has been difficult to reconcile observed and modeled Antarctic sea ice trends. To understand observed-model disparities, this work defines the internally driven and radiatively forced patterns of Antarctic sea ice change and exposes potential model biases using results from two sets of historical experiments of a coupled climate model compared with observations. One ensemble is constrained only by external factors such as greenhouse gases and stratospheric ozone, while the other explicitly accounts for the influence of tropical variability by specifying observed SST anomalies in the eastern tropical Pacific. The latter experiment reproduces the deepening of the ASL, which drives an increase in regional ice extent due to enhanced ice motion and sea surface cooling. However, the overall sea ice trend in every ensemble member of both experiments is characterized by ice loss and is dominated by the forced pattern, as given by the ensemble-mean of the first experiment. This pervasive ice loss is associated with a strong warming of the ocean mixed layer, suggesting that the ocean model does not locally store or export anomalous heat efficiently enough to maintain a surface environment conducive to sea ice expansion. The pervasive upper-ocean warming, not seen in observations, likely reflects ocean mean-state biases.

Tropically driven and externally forced patterns of Antarctic sea ice change: reconciling observed and modeled trends

NASA Astrophysics Data System (ADS)

Schneider, David P.; Deser, Clara

2017-09-01

Recent work suggests that natural variability has played a significant role in the increase of Antarctic sea ice extent during 1979-2013. The ice extent has responded strongly to atmospheric circulation changes, including a deepened Amundsen Sea Low (ASL), which in part has been driven by tropical variability. Nonetheless, this increase has occurred in the context of externally forced climate change, and it has been difficult to reconcile observed and modeled Antarctic sea ice trends. To understand observed-model disparities, this work defines the internally driven and radiatively forced patterns of Antarctic sea ice change and exposes potential model biases using results from two sets of historical experiments of a coupled climate model compared with observations. One ensemble is constrained only by external factors such as greenhouse gases and stratospheric ozone, while the other explicitly accounts for the influence of tropical variability by specifying observed SST anomalies in the eastern tropical Pacific. The latter experiment reproduces the deepening of the ASL, which drives an increase in regional ice extent due to enhanced ice motion and sea surface cooling. However, the overall sea ice trend in every ensemble member of both experiments is characterized by ice loss and is dominated by the forced pattern, as given by the ensemble-mean of the first experiment. This pervasive ice loss is associated with a strong warming of the ocean mixed layer, suggesting that the ocean model does not locally store or export anomalous heat efficiently enough to maintain a surface environment conducive to sea ice expansion. The pervasive upper-ocean warming, not seen in observations, likely reflects ocean mean-state biases.

On evolutionary climate tracks in deep mantle volatile cycle computed from numerical mantle convection simulations and its impact on the habitability of the Earth-like planets

NASA Astrophysics Data System (ADS)

Nakagawa, T.; Tajika, E.; Kadoya, S.

2017-12-01

Discussing an impact of evolution and dynamics in the Earth's deep interior on the surface climate change for the last few decades (see review by Ehlmann et al., 2016), the mantle volatile (particularly carbon) degassing in the mid-oceanic ridges seems to play a key role in understanding the evolutionary climate track for Earth-like planets (e.g. Kadoya and Tajika, 2015). However, since the mantle degassing occurs not only in the mid-oceanic ridges but also in the wedge mantle (island arc volcanism) and hotspots, to incorporate more accurate estimate of mantle degassing flux into the climate evolution framework, we developed a coupled model of surface climate-deep Earth evolution in numerical mantle convection simulations, including more accurate deep water and carbon cycle (e.g. Nakagawa and Spiegelman, 2017) with an energy balance theory of climate change. Modeling results suggest that the evolution of planetary climate computed from a developed model is basically consistent with an evolutionary climate track in simplified mantle degassing model (Kadoya and Tajika, 2015), but an occurrence timing of global (snowball) glaciation is strongly dependent on mantle degassing rate occurred with activities of surface plate motions. With this implication, the surface plate motion driven by deep mantle dynamics would play an important role in the planetary habitability of such as the Earth and Earth-like planets over geologic time-scale.

Climate change: evidence of human causes and arguments for emissions reduction.

PubMed

Baum, Seth D; Haqq-Misra, Jacob D; Karmosky, Chris

2012-06-01

In a recent editorial, Raymond Spier expresses skepticism over claims that climate change is driven by human actions and that humanity should act to avoid climate change. This paper responds to this skepticism as part of a broader review of the science and ethics of climate change. While much remains uncertain about the climate, research indicates that observed temperature increases are human-driven. Although opinions vary regarding what should be done, prominent arguments against action are based on dubious factual and ethical positions. Thus, the skepticisms in the recent editorial are unwarranted. This does not diminish the general merits of skeptical intellectual inquiry.

Global Air Quality and Climate

NASA Technical Reports Server (NTRS)

Fiore, Arlene M.; Naik, Vaishali; Steiner, Allison; Unger, Nadine; Bergmann, Dan; Prather, Michael; Righi, Mattia; Rumbold, Steven T.; Shindell, Drew T.; Skeie, Ragnhild B.;

weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Greenhouse gas policy influences climate via direct effects of land-use change

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

Jones, Andrew D.; Collins, William D.; Edmonds, James A.

2013-06-01

Proposed climate mitigation measures do not account for direct biophysical climate impacts of land-use change (LUC), nor do the stabilization targets modeled for the 5th Climate Model Intercomparison Project (CMIP5) Representative Concentration Pathways (RCPs). To examine the significance of such effects on global and regional patterns of climate change, a baseline and alternative scenario of future anthropogenic activity are simulated within the Integrated Earth System Model, which couples the Global Change Assessment Model, Global Land-use Model, and Community Earth System Model. The alternative scenario has high biofuel utilization and approximately 50% less global forest cover compared to the baseline, standardmore » RCP4.5 scenario. Both scenarios stabilize radiative forcing from atmospheric constituents at 4.5 W/m2 by 2100. Thus, differences between their climate predictions quantify the biophysical effects of LUC. Offline radiative transfer and land model simulations are also utilized to identify forcing and feedback mechanisms driving the coupled response. Boreal deforestation is found to strongly influence climate due to increased albedo coupled with a regional-scale water vapor feedback. Globally, the alternative scenario yields a 21st century warming trend that is 0.5 °C cooler than baseline, driven by a 1 W/m2 mean decrease in radiative forcing that is distributed unevenly around the globe. Some regions are cooler in the alternative scenario than in 2005. These results demonstrate that neither climate change nor actual radiative forcing are uniquely related to atmospheric forcing targets such as those found in the RCP’s, but rather depend on particulars of the socioeconomic pathways followed to meet each target.« less

Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes

PubMed Central

García-Palacios, Pablo; Maestre, Fernando T.; Kattge, Jens; Wall, Diana H.

2015-01-01

Climate and litter quality have been identified as major drivers of litter decomposition at large spatial scales. However, the role played by soil fauna remains largely unknown, despite its importance for litter fragmentation and microbial activity. We synthesized litterbag studies to quantify the effect sizes of soil fauna on litter decomposition rates at the global and biome scales, and to assess how climate, litter quality and soil fauna interact to determine such rates. Soil fauna consistently enhanced litter decomposition at both global and biome scales (average increment ~27%). However, climate and litter quality differently modulated the effects of soil fauna on decomposition rates between biomes, from climate-driven biomes to those where climate effects were mediated by changes in litter quality. Our results advocate for the inclusion of biome-specific soil fauna effects on litter decomposition as a mean to reduce the unexplained variation in large-scale decomposition models. PMID:23763716

The role of the Gulf Stream in European climate.

PubMed

Palter, Jaime B

2015-01-01

The Gulf Stream carries the warm, poleward return flow of the wind-driven North Atlantic subtropical gyre and the Atlantic Meridional Overturning Circulation. This northward flow drives a significant meridional heat transport. Various lines of evidence suggest that Gulf Stream heat transport profoundly influences the climate of the entire Northern Hemisphere and, thus, Europe's climate on timescales of decades and longer. The Gulf Stream's influence is mediated through feedback processes between the ocean, atmosphere, and cryosphere. This review synthesizes paleoclimate archives, model simulations, and the instrumental record, which collectively suggest that decadal and longer-scale variability of the Gulf Stream's heat transport manifests in changes in European temperature, precipitation, and storminess. Given that anthropogenic climate change is projected to weaken the Atlantic Meridional Overturning Circulation, associated changes in European climate are expected. However, large uncertainty in the magnitude of the anticipated weakening undermines the predictability of the future climate in Europe.

Climate-Driven Risk of Large Fire Occurrence in the Western United States, 1500 to 2003

NASA Astrophysics Data System (ADS)

Crockett, J.; Westerling, A. L.

2017-12-01

Spatially comprehensive fire climatology has provided managers with tools to understand thecauses and consequences of large forest wildfires, but a paleoclimate context is necessary foranticipating the trajectory of future climate-fire relationships. Although accumulated charcoalrecords and tree scars have been utilized in high resolution, regional fire reconstructions, there isuncertainty as to how current climate-fire relationships of the western United States (WUS) fitwithin the natural long-term variability. While contemporary PDSI falls within the naturalvariability of the past, contemporary temperatures skew higher. Here, we develop a WUSfire reconstruction by applying climate-fire-topography model built on the 1972 to 2003 periodto the past 500 years, validated by recently updated fire-scar histories from WUS forests. Theresultant narrative provides insight into changing climate-fire relationships during extendedperiods of high aridity and temperature, providing land managers with historical precedent toeffectively anticipate disturbances during future climate change.

Drivers of Arctic Ocean warming in CMIP5 models

NASA Astrophysics Data System (ADS)

Burgard, Clara; Notz, Dirk

2017-05-01

We investigate changes in the Arctic Ocean energy budget simulated by 26 general circulation models from the Coupled Model Intercomparison Project Phase 5 framework. Our goal is to understand whether the Arctic Ocean warming between 1961 and 2099 is primarily driven by changes in the net atmospheric surface flux or by changes in the meridional oceanic heat flux. We find that the simulated Arctic Ocean warming is driven by positive anomalies in the net atmospheric surface flux in 11 models, by positive anomalies in the meridional oceanic heat flux in 11 models, and by positive anomalies in both energy fluxes in four models. The different behaviors are mainly characterized by the different changes in meridional oceanic heat flux that lead to different changes in the turbulent heat loss to the atmosphere. The multimodel ensemble mean is hence not representative of a consensus across the models in Arctic climate projections.

Soil Moisture-Atmosphere Feedbacks on Atmospheric Tracers: The Effects of Soil Moisture on Precipitation and Near-Surface Chemistry

NASA Astrophysics Data System (ADS)

Tawfik, Ahmed B.

The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.

Modeling Climate and Societal Resilience in the Mediterranean During the Last Millennium

NASA Astrophysics Data System (ADS)

Wagner, S.; Xoplaki, E.; Luterbacher, J.; Zorita, E.; Fleitmann, D.; Preiser-Kapeller, J.; Toreti, A., , Dr; Sargent, A. M.; Bozkurt, D.; White, S.; Haldon, J. F.; Akçer-Ön, S.; Izdebski, A.

2017-12-01

Past civilisations were influenced by complex external and internal forces, including changes in the environment, climate, politics and economy. A geographical hotspot of the interplay between those agents is the Mediterranean, a cradle of cultural and scientific development. We analyse a novel compilation of high-quality hydroclimate proxy records and spatial reconstructions from the Mediterranean and compare them with two Earth System Model simulations (CCSM4, MPI-ESM-P) for three historical time intervals - the Crusaders, 1095-1290 CE; the Mamluk regime in Transjordan, 1260-1516 CE; and the Ottoman crisis and Celâlî Rebellion, 1580-1610 CE - when environmental and climatic stress tested the resilience of complex societies. ESMs provide important information on the dynamical mechanisms and underlying processes that led to anomalous hydroclimatic conditions of the past. We find that the multidecadal precipitation and drought variations in the Central and Eastern Mediterranean during the three periods cannot be explained by external forcings (solar variations, tropical volcanism); rather they were driven by internal climate dynamics. The integrated analysis of palaeoclimate proxies, climate reconstructions and model simulations sheds light on our understanding of past climate change and its societal impact. Finally, our research emphasises the need to further study the societal dimension of environmental and climate change in the past, in order to properly understand the role that climate has played in human history.

Evidence for climate-driven synchrony of marine and terrestrial ecosystems in northwest Australia.

PubMed

Ong, Joyce J L; Rountrey, Adam N; Zinke, Jens; Meeuwig, Jessica J; Grierson, Pauline F; O'Donnell, Alison J; Newman, Stephen J; Lough, Janice M; Trougan, Mélissa; Meekan, Mark G

2016-08-01

The effects of climate change are difficult to predict for many marine species because little is known of their response to climate variations in the past. However, long-term chronologies of growth, a variable that integrates multiple physical and biological factors, are now available for several marine taxa. These allow us to search for climate-driven synchrony in growth across multiple taxa and ecosystems, identifying the key processes driving biological responses at very large spatial scales. We hypothesized that in northwest (NW) Australia, a region that is predicted to be strongly influenced by climate change, the El Niño Southern Oscillation (ENSO) phenomenon would be an important factor influencing the growth patterns of organisms in both marine and terrestrial environments. To test this idea, we analyzed existing growth chronologies of the marine fish Lutjanus argentimaculatus, the coral Porites spp. and the tree Callitris columellaris and developed a new chronology for another marine fish, Lethrinus nebulosus. Principal components analysis and linear model selection showed evidence of ENSO-driven synchrony in growth among all four taxa at interannual time scales, the first such result for the Southern Hemisphere. Rainfall, sea surface temperatures, and sea surface salinities, which are linked to the ENSO system, influenced the annual growth of fishes, trees, and corals. All four taxa had negative relationships with the Niño-4 index (a measure of ENSO status), with positive growth patterns occurring during strong La Niña years. This finding implies that future changes in the strength and frequency of ENSO events are likely to have major consequences for both marine and terrestrial taxa. Strong similarities in the growth patterns of fish and trees offer the possibility of using tree-ring chronologies, which span longer time periods than those of fish, to aid understanding of both historical and future responses of fish populations to climate variation. © 2016 John Wiley & Sons Ltd.

Highly-seasonal monsoons controlled by Central Asian Eocene epicontinental sea

NASA Astrophysics Data System (ADS)

Bougeois, Laurie; Tindall, Julia; de Rafélis, Marc; Reichart, Gert-Jan; de Nooijer, Lennart; Dupont-Nivet, Guillaume

2015-04-01

Modern Asian climate is mainly controlled by seasonal reverse winds driven by continent-ocean thermal contrast. This yields monsoon pattern characterized by a strong seasonality in terms of precipitation and temperature and a duality between humidity along southern and eastern Asia and aridity in Central Asia. According to climate models, Asian Monsoons and aridification have been governed by Tibetan plateau uplift, global climate changes and the retreat of a vast epicontinental sea (the Proto-Paratethys sea) that used to cover Eurasia in Eocene times (55 to 34 Myr ago). Evidence for Asian aridification and monsoons a old as Eocene, are emerging from proxy and model data, however, the role of the Proto-Paratethys sea remains to be established by proxy data. By applying a novel infra-annual geochemical multi-proxy methodology on Eocene oyster shells of the Proto-Paratethys sea and comparing results to climate simulations, we show that the Central Asian region was generally arid with high seasonality from hot and arid summers to wetter winters. This high seasonality in Central Asia supports a monsoonal circulation was already established although the climate pattern was significantly different than today. During winter months, a strong influence of the Proto-Paratethys moisture is indicated by enhanced precipitations significantly higher than today. Precipitation probably dwindled because of the subsequent sea retreat as well as the uplift of the Tibetan and Pamir mountains shielding the westerlies. During Eocene summers, the local climate was hotter and more arid than today despite the presence of the Proto Paratethys. This may be explained by warmer Eocene global conditions with a strong anticyclonic Hadley cell descending at Central Asian latitudes (25 to 45 N). urthermore, the Tibetan plateau emerging at this time to the south must have already contributed a stronger Foehn effect during summer months bringing warm and dry air into Central Asia. Proto-Paratethys moisture driven into Asia by the westerlies during winters provides a potential mechanical link between Eocene global climate and Asian aridification through sea level fluctuations.

Spatial heterogeneity of climate change as an experiential basis for skepticism

PubMed Central

Kaufmann, Robert K.; Mann, Michael L.; Gopal, Sucharita; Liederman, Jackie A.; Howe, Peter D.; Pretis, Felix; Gilmore, Michelle

2017-01-01

We postulate that skepticism about climate change is partially caused by the spatial heterogeneity of climate change, which exposes experiential learners to climate heuristics that differ from the global average. This hypothesis is tested by formalizing an index that measures local changes in climate using station data and comparing this index with survey-based model estimates of county-level opinion about whether global warming is happening. Results indicate that more stations exhibit cooling and warming than predicted by random chance and that spatial variations in these changes can account for spatial variations in the percentage of the population that believes that “global warming is happening.” This effect is diminished in areas that have experienced more record low temperatures than record highs since 2005. Together, these results suggest that skepticism about climate change is driven partially by personal experiences; an accurate heuristic for local changes in climate identifies obstacles to communicating ongoing changes in climate to the public and how these communications might be improved. PMID:27994143

Spatial heterogeneity of climate change as an experiential basis for skepticism.

PubMed

Kaufmann, Robert K; Mann, Michael L; Gopal, Sucharita; Liederman, Jackie A; Howe, Peter D; Pretis, Felix; Tang, Xiaojing; Gilmore, Michelle

2017-01-03

We postulate that skepticism about climate change is partially caused by the spatial heterogeneity of climate change, which exposes experiential learners to climate heuristics that differ from the global average. This hypothesis is tested by formalizing an index that measures local changes in climate using station data and comparing this index with survey-based model estimates of county-level opinion about whether global warming is happening. Results indicate that more stations exhibit cooling and warming than predicted by random chance and that spatial variations in these changes can account for spatial variations in the percentage of the population that believes that "global warming is happening." This effect is diminished in areas that have experienced more record low temperatures than record highs since 2005. Together, these results suggest that skepticism about climate change is driven partially by personal experiences; an accurate heuristic for local changes in climate identifies obstacles to communicating ongoing changes in climate to the public and how these communications might be improved.

Expansion Under Climate Change: The Genetic Consequences.

PubMed

Garnier, Jimmy; Lewis, Mark A

2016-11-01

Range expansion and range shifts are crucial population responses to climate change. Genetic consequences are not well understood but are clearly coupled to ecological dynamics that, in turn, are driven by shifting climate conditions. We model a population with a deterministic reaction-diffusion model coupled to a heterogeneous environment that develops in time due to climate change. We decompose the resulting travelling wave solution into neutral genetic components to analyse the spatio-temporal dynamics of its genetic structure. Our analysis shows that range expansions and range shifts under slow climate change preserve genetic diversity. This is because slow climate change creates range boundaries that promote spatial mixing of genetic components. Mathematically, the mixing leads to so-called pushed travelling wave solutions. This mixing phenomenon is not seen in spatially homogeneous environments, where range expansion reduces genetic diversity through gene surfing arising from pulled travelling wave solutions. However, the preservation of diversity is diminished when climate change occurs too quickly. Using diversity indices, we show that fast expansions and range shifts erode genetic diversity more than slow range expansions and range shifts. Our study provides analytical insight into the dynamics of travelling wave solutions in heterogeneous environments.

Frost for the trees: Did climate increase erosion in unglaciated landscapes during the late Pleistocene?

PubMed

Marshall, Jill A; Roering, Joshua J; Bartlein, Patrick J; Gavin, Daniel G; Granger, Darryl E; Rempel, Alan W; Praskievicz, Sarah J; Hales, Tristram C

2015-11-01

Understanding climatic influences on the rates and mechanisms of landscape erosion is an unresolved problem in Earth science that is important for quantifying soil formation rates, sediment and solute fluxes to oceans, and atmospheric CO2 regulation by silicate weathering. Glaciated landscapes record the erosional legacy of glacial intervals through moraine deposits and U-shaped valleys, whereas more widespread unglaciated hillslopes and rivers lack obvious climate signatures, hampering mechanistic theory for how climate sets fluxes and form. Today, periglacial processes in high-elevation settings promote vigorous bedrock-to-regolith conversion and regolith transport, but the extent to which frost processes shaped vast swaths of low- to moderate-elevation terrain during past climate regimes is not well established. By combining a mechanistic frost weathering model with a regional Last Glacial Maximum (LGM) climate reconstruction derived from a paleo-Earth System Model, paleovegetation data, and a paleoerosion archive, we propose that frost-driven sediment production was pervasive during the LGM in our unglaciated Pacific Northwest study site, coincident with a 2.5 times increase in erosion relative to modern rates. Our findings provide a novel framework to quantify how climate modulates sediment production over glacial-interglacial cycles in mid-latitude unglaciated terrain.

Test of High-resolution Global and Regional Climate Model Projections

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Do planetary seasons play a role in attaining stable climates?

NASA Astrophysics Data System (ADS)

Olsen, Kasper Wibeck; Bohr, Jakob

2018-05-01

A simple phenomenological account for planetary climate instabilities is presented. The description is based on the standard model where the balance of incoming stellar radiation and outward thermal radiation is described by the effective planet temperature. Often, it is found to have three different points, or temperatures, where the influx of radiation is balanced with the out-flux, even with conserved boundary conditions. Two of these points are relatively long-term stable, namely the point corresponding to a cold climate and the point corresponding to a hot climate. In a classical sense these points are equilibrium balance points. The hypothesis promoted in this paper is the possibility that the intermediate third point can become long-term stable by being driven dynamically. The initially unstable point is made relatively stable over a long period by the presence of seasonal climate variations.

Project Summary (2012-2015) – Carbon Dynamics of the Greater Everglades Watershed and Implications of Climate Change

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

Hinkle, Ross; Benscoter, Brian; Comas, Xavier

2015-04-07

Carbon Dynamics of the Greater Everglades Watershed and Implications of Climate Change The objectives of this project are to: 1) quantify above- and below-ground carbon stocks of terrestrial ecosystems along a seasonal hydrologic gradient in the headwaters region of the Greater Everglades watershed; 2) develop budgets of ecosystem gaseous carbon exchange (carbon dioxide and methane) across the seasonal hydrologic gradient; 3) assess the impact of climate drivers on ecosystem carbon exchange in the Greater Everglades headwater region; and 4) integrate research findings with climate-driven terrestrial ecosystem carbon models to examine the potential influence of projected future climate change on regionalmore » carbon cycling. Note: this project receives a one-year extension past the original performance period - David Sumner (USGS) is not included in this extension.« less

An application of a hydraulic model simulator in flood risk assessment under changing climatic conditions

NASA Astrophysics Data System (ADS)

Doroszkiewicz, J. M.; Romanowicz, R. J.

2016-12-01

The standard procedure of climate change impact assessment on future hydrological extremes consists of a chain of consecutive actions, starting from the choice of GCM driven by an assumed CO2 scenario, through downscaling of climatic forcing to a catchment scale, estimation of hydrological extreme indices using hydrological modelling tools and subsequent derivation of flood risk maps with the help of a hydraulic model. Among many possible sources of uncertainty, the main are the uncertainties related to future climate scenarios, climate models, downscaling techniques and hydrological and hydraulic models. Unfortunately, we cannot directly assess the impact of these different sources of uncertainties on flood risk in future due to lack of observations of future climate realizations. The aim 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 processes involved, 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-sections. The study shows that the application of a simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. 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.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Tools for Virtual Collaboration Designed for High Resolution Hydrologic Research with Continental-Scale Data Support

NASA Astrophysics Data System (ADS)

Duffy, Christopher; Leonard, Lorne; Shi, Yuning; Bhatt, Gopal; Hanson, Paul; Gil, Yolanda; Yu, Xuan

2015-04-01

Using a series of recent examples and papers we explore some progress and potential for virtual (cyber-) collaboration inspired by access to high resolution, harmonized public-sector data at continental scales [1]. The first example describes 7 meso-scale catchments in Pennsylvania, USA where the watershed is forced by climate reanalysis and IPCC future climate scenarios (Intergovernmental Panel on Climate Change). We show how existing public-sector data and community models are currently able to resolve fine-scale eco-hydrologic processes regarding wetland response to climate change [2]. The results reveal that regional climate change is only part of the story, with large variations in flood and drought response associated with differences in terrain, physiography, landuse and/or hydrogeology. The importance of community-driven virtual testbeds are demonstrated in the context of Critical Zone Observatories, where earth scientists from around the world are organizing hydro-geophysical data and model results to explore new processes that couple hydrologic models with land-atmosphere interaction, biogeochemical weathering, carbon-nitrogen cycle, landscape evolution and ecosystem services [3][4]. Critical Zone cyber-research demonstrates how data-driven model development requires a flexible computational structure where process modules are relatively easy to incorporate and where new data structures can be implemented [5]. From the perspective of "Big-Data" the paper points out that extrapolating results from virtual observatories to catchments at continental scales, will require centralized or cloud-based cyberinfrastructure as a necessary condition for effectively sharing petabytes of data and model results [6]. Finally we outline how innovative cyber-science is supporting earth-science learning, sharing and exploration through the use of on-line tools where hydrologists and limnologists are sharing data and models for simulating the coupled impacts of catchment hydrology on lake eco-hydrology (NSF-INSPIRE, IIS1344272). The research attempts to use a virtual environment (www.organicdatascience.org) to break down disciplinary barriers and support emergent communities of science. [1] Source: Leonard and Duffy, 2013, Environmental Modelling & Software; [2] Source: Yu et al, 2014, Computers in Geoscience; [3] Source: Duffy et al, 2014, Procedia Earth and Planetary Science; [4] Source: Shi et al, Journal of Hydrometeorology, 2014; [5] Source: Bhatt et al, 2014, Environmental Modelling & Software ; [6] Leonard and Duffy, 2014, Environmental Modelling and Software.

Deep uncertainty and broad heterogeneity in country-level social cost of carbon

NASA Astrophysics Data System (ADS)

Ricke, K.; Drouet, L.; Caldeira, K.; Tavoni, M.

2017-12-01

The social cost of carbon (SCC) is a commonly employed metric of the expected economic damages expected from carbon dioxide (CO2) emissions. Recent estimates of SCC range from approximately 10/tonne of CO2 to as much as 1000/tCO2, but these have been computed at the global level. While useful in an optimal policy context, a world-level approach obscures the heterogeneous geography of climate damages and vast differences in country-level contributions to global SCC, as well as climate and socio-economic uncertainties, which are much larger at the regional level. For the first time, we estimate country-level contributions to SCC using recent climate and carbon-cycle model projections, empirical climate-driven economic damage estimations, and information from the Shared Socio-economic Pathways. Central specifications show high global SCC values (median: 417 /tCO2, 66% confidence intervals: 168 - 793 /tCO2) with country-level contributions ranging from -11 (-8 - -14) /tCO2 to 86 (50 - 158) /tCO2. We quantify climate-, scenario- and economic damage- driven uncertainties associated with the calculated values of SCC. We find that while the magnitude of country-level social cost of carbon is highly uncertain, the relative positioning among countries is consistent. Countries incurring large fractions of the global cost include India, China, and the United States. The share of SCC distributed among countries is robust, indicating climate change winners and losers from a geopolitical perspective.

Photosynthetic Control of Atmospheric Carbonyl Sulfide during the Growing Season

NASA Technical Reports Server (NTRS)

Campbell, J. Elliott; Carmichael, Gregory R.; Chai, T.; Mena-Carrasco, M.; Tang, Y.; Blake, D. R.; Blake, N. J.; Vay, Stephanie A.; Collatz, G. James; Baker, I.;

Foraminifera Models to Interrogate Ostensible Proxy-Model Discrepancies During Late Pliocene

NASA Astrophysics Data System (ADS)

Jacobs, P.; Dowsett, H. J.; de Mutsert, K.

2017-12-01

Planktic foraminifera faunal assemblages have been used in the reconstruction of past oceanic states (e.g. the Last Glacial Maximum, the mid-Piacenzian Warm Period). However these reconstruction efforts have typically relied on inverse modeling using transfer functions or the modern analog technique, which by design seek to translate foraminifera into one or two target oceanic variables, primarily sea surface temperature (SST). These reconstructed SST data have then been used to test the performance of climate models, and discrepancies have been attributed to shortcomings in climate model processes and/or boundary conditions. More recently forward proxy models or proxy system models have been used to leverage the multivariate nature of proxy relationships to their environment, and to "bring models into proxy space". Here we construct ecological models of key planktic foraminifera taxa, calibrated and validated with World Ocean Atlas (WO13) oceanographic data. Multiple modeling methods (e.g. multilayer perceptron neural networks, Mahalanobis distance, logistic regression, and maximum entropy) are investigated to ensure robust results. The resulting models are then driven by a Late Pliocene climate model simulation with biogeochemical as well as temperature variables. Similarities and differences with previous model-proxy comparisons (e.g. PlioMIP) are discussed.

A prognostic pollen emissions model for climate models (PECM1.0)

NASA Astrophysics Data System (ADS)

Wozniak, Matthew C.; Steiner, Allison L.

2017-11-01

We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

Contrasting impacts of local and non-local anthropogenic aerosols detected on 20th century monsoon precipitation over West Africa and South Asia

NASA Astrophysics Data System (ADS)

Hegerl, G. C.; Polson, D.; Bollasina, M. A.; Ming, Y.

2015-12-01

Anthropogenic aerosols are a key driver 4 of historical changes in Summer monsoon precipition in the Northern Hemisphere. Detection and attribution studies have shown that the reduction in Northern Hemisphere precipitation over the second half of the 20th century is driven by anthropogenic aerosol emissions. Here we apply these same methods to investigate changes in the West African and South Asian monsoons and identify the source regions of the anthropogenic aerosols that drive the observed changes. Historical climate model simulations are used to derive fingerprints of aerosol forcing for different regions of the globe. Comparing model changes with observations show that the changes in West African monsoon preciptiation are driven by remote aerosol emissions from North America and Europe, while changes in South Asian monsoon precipitation are driven by local aerosol emissions.

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

PubMed

Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

2018-05-01

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

Modeling the Pineapple Express phenomenon via Multivariate Extreme Value Theory

NASA Astrophysics Data System (ADS)

Weller, G.; Cooley, D. S.

2011-12-01

The pineapple express (PE) phenomenon is responsible for producing extreme winter precipitation events in the coastal and mountainous regions of the western United States. Because the PE phenomenon is also associated with warm temperatures, the heavy precipitation and associated snowmelt can cause destructive flooding. In order to study impacts, it is important that regional climate models from NARCCAP are able to reproduce extreme precipitation events produced by PE. We define a daily precipitation quantity which captures the spatial extent and intensity of precipitation events produced by the PE phenomenon. We then use statistical extreme value theory to model the tail dependence of this quantity as seen in an observational data set and each of the six NARCCAP regional models driven by NCEP reanalysis. We find that most NCEP-driven NARCCAP models do exhibit tail dependence between daily model output and observations. Furthermore, we find that not all extreme precipitation events are pineapple express events, as identified by Dettinger et al. (2011). The synoptic-scale atmospheric processes that drive extreme precipitation events produced by PE have only recently begun to be examined. Much of the current work has focused on pattern recognition, rather than quantitative analysis. We use daily mean sea-level pressure (MSLP) fields from NCEP to develop a "pineapple express index" for extreme precipitation, which exhibits tail dependence with our observed precipitation quantity for pineapple express events. We build a statistical model that connects daily precipitation output from the WRFG model, daily MSLP fields from NCEP, and daily observed precipitation in the western US. Finally, we use this model to simulate future observed precipitation based on WRFG output driven by the CCSM model, and our pineapple express index derived from future CCSM output. Our aim is to use this model to develop a better understanding of the frequency and intensity of extreme precipitation events produced by PE under climate change.

An Analysis of the Potential Impact of Climate Change on Dengue Transmission in the Southeastern United States

PubMed Central

Butterworth, Melinda K.; Morin, Cory W.; Comrie, Andrew C.

2016-01-01

Background: Dengue fever, caused by a mosquito-transmitted virus, is an increasing health concern in the Americas. Meteorological variables such as temperature and precipitation can affect disease distribution and abundance through biophysical impacts on the vector and on the virus. Such tightly coupled links may facilitate further spread of dengue fever under a changing climate. In the southeastern United States, the dengue vector is widely established and exists on the current fringe of dengue transmission. Objectives: We assessed projected climate change–driven shifts in dengue transmission risk in this region. Methods: We used a dynamic mosquito population and virus transmission model driven by meteorological data to simulate Aedes aegypti populations and dengue cases in 23 locations in the southeastern United States under current climate conditions and future climate projections. We compared estimates for each location with simulations based on observed data from San Juan, Puerto Rico, where dengue is endemic. Results: Our simulations based on current climate data suggest that dengue transmission at levels similar to those in San Juan is possible at several U.S. locations during the summer months, particularly in southern Florida and Texas. Simulations that include climate change projections suggest that conditions may become suitable for virus transmission in a larger number of locations and for a longer period of time during each year. However, in contrast with San Juan, U.S. locations would not sustain year-round dengue transmission according to our model. Conclusions: Our findings suggest that Dengue virus (DENV) transmission is limited by low winter temperatures in the mainland United States, which are likely to prevent its permanent establishment. Although future climate conditions may increase the length of the mosquito season in many locations, projected increases in dengue transmission are limited to the southernmost locations. Citation: Butterworth MK, Morin CW, Comrie AC. 2017. An analysis of the potential impact of climate change on dengue transmission in the southeastern United States. Environ Health Perspect 125:579–585; http://dx.doi.org/10.1289/EHP218 PMID:27713106

The effect of education on climate change risks

NASA Astrophysics Data System (ADS)

O'Neill, B. C.; KC, S.; Jiang, L.; Fuchs, R.; Pachauri, S.; Ren, X.; Zhang, T.; Laidlaw, E.

2017-12-01

Changes in the demographic and socio-economic compositions of populations are relevant to the climate change issue because these characteristics can be important determinants both of the capacity to adapt to climate change impacts as well as of energy use and greenhouse gas emissions, and therefore climate change. However, the incorporation of major trends such as aging, urbanization, and changes in household size into projections of future energy use and emissions is rare. Here we build on our previous work in this area by exploring the implications of future changes in educational attainment for the climate issue. Changes in the educational composition of the population may reduce the vulnerability of the population to climate change impacts, reducing risks. However they may also have effects on energy use and land use, and the resulting greenhouse gas emissions that drive climate change and increase risks. The direction of the effect of education on emissions is itself ambiguous. On the one hand, improvements in education can be expected to lead to faster fertility decline and slower population growth which, all else equal, would be expected to reduce emissions. On the other hand, education can also be expected to lead to faster economic growth, which would tend to increase emissions, and also to changes in consumption patterns. We employ iPETS, an integrated assessment model that includes a multi-region model of the world economy, driven with a new set of country-specific projections of future educational composition, to test the net effect of education on energy use and emissions on four world regions (China, India, Latin America, and Rest of Asia + Middle East) and therefore on climate. We also calculate the Human Development Index (HDI) for each region resulting from these scenarios, as an indicator of vulnerability to climate impacts. We find that the net effect of improved education is to increase emissions in the medium term driven primarily by increased labor productivity, but decrease emissions in the long term primarily as a result of slower population growth. At the same time, improved education positively affects all aspects of the HDI at all time horizons. Important caveats include the uncertainty in the effect of education on economic growth.

Relative contributions of mean-state shifts and ENSO-driven variability to precipitation changes in a warming climate

DOE PAGES

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; ...

2015-12-18

The El Niño–Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change.more » Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. Lastly, by examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.« less

Nudging and predictability in regional climate modelling: investigation in a nested quasi-geostrophic model

NASA Astrophysics Data System (ADS)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2010-05-01

In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.

Simulations of snow distribution and hydrology in a mountain basin

USGS Publications Warehouse

Hartman, Melannie D.; Baron, Jill S.; Lammers, Richard B.; Cline, Donald W.; Band, Larry E.; Liston, Glen E.; Tague, Christina L.

1999-01-01

We applied a version of the Regional Hydro-Ecologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and wind-driven sublimation to Loch Vale Watershed (LVWS), an alpine-subalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating wind-driven sublimation was necessary to predict moisture losses.

A regime perspective on the North Atlantic eddy-driven jet stream response to sudden stratospheric warmings

NASA Astrophysics Data System (ADS)

Maycock, A.; Masukwedza, G.; Hitchcock, P.

2017-12-01

The winter North Atlantic eddy-driven jet (NAJ) has been shown to exhibit three preferred latitudinal positions. Here we examine, for the first time, the influence of major Sudden Stratospheric Warmings (SSWs) on the regime behaviour of the NAJ using an ensemble of climate model experiments with stratospheric conditions nudged towards a major SSW, but with each ensemble member having freely evolving tropospheric conditions. The SSW experiment is compared to a control ensemble in which stratospheric variability is absent. The experiments show that the SSW leads to an increased occupancy of the southerly NAJ state and reduced occupancy of the northerly state. This effect is distinct from the mean southward shift of the NAJ identified in many previous studies, and instead suggests changes to the characteristics of NAJ variability as a result of SSWs. These results may aid in understanding the mechanisms by which SSWs impact on Euro-Atlantic climate.

Fire severity mediates climate-driven shifts in understorey community composition of black spruce stands of interior Alaska

Treesearch

Emily L. Bernhardt; Teresa N. Hollingsworth; F. Stuart Chapin

2011-01-01

Question: How do pre-fire conditions (community composition and environmental characteristics) and climate-driven disturbance characteristics (fire severity) affect post-fire community composition in black spruce stands? Location: Northern boreal forest, interior Alaska. Methods: We compared plant community composition and environmental stand characteristics in 14...

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

Evaluation of high-resolution climate simulations for West Africa using COSMO-CLM

NASA Astrophysics Data System (ADS)

Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Laux, Patrick; Heinzeller, Dominikus; Kunstmann, Harald; Sarr, Abdoulaye; Thierno Gaye, Amadou

2017-04-01

The climate change modeling activities within the WASCAL program (West African Science Service Center on Climate Change and Adapted Land Use) concentrate on the provisioning of future climate change scenario data at high spatial and temporal resolution and quality in West Africa. Such information is highly required for impact studies in water resources and agriculture for the development of reliable climate change adaptation and mitigation strategies. In this study, we present a detailed evaluation of high simulation runs based on the regional climate model, COSMO model in CLimate Mode (COSMO-CLM). The model is applied over West Africa in a nested approach with two simulation domains at 0.44° and 0.11° resolution using reanalysis data from ERA-Interim (1979-2013). The models runs are compared to several state-of-the-art observational references (e.g., CRU, CHIRPS) including daily precipitation data provided by national meteorological services in West Africa. Special attention is paid to the reproduction of the dynamics of the West African Monsoon (WMA), its associated precipitation patterns and crucial agro-climatological indices such as the onset of the rainy season. In addition, first outcomes of the regional climate change simulations driven by MPI-ESM-LR are presented for a historical period (1980 to 2010) and two future periods (2020 to 2050, 2070 to 2100). The evaluation of the reanalysis runs shows that COSMO-CLM is able to reproduce the observed major climate characteristics including the West African Monsoon within the range of comparable RCM evaluations studies. However, substantial uncertainties remain, especially in the Sahel zone. The added value of the higher resolution of the nested run is reflected in a smaller bias in extreme precipitation statistics with respect to the reference data.

Projection of climatic suitability for Aedes albopictus Skuse (Culicidae) in Europe under climate change conditions

NASA Astrophysics Data System (ADS)

Fischer, Dominik; Thomas, Stephanie Margarete; Niemitz, Franziska; Reineking, Björn; Beierkuhnlein, Carl

2011-07-01

During the last decades the disease vector Aedes albopictus ( Ae. albopictus) has rapidly spread around the globe. The spread of this species raises serious public health concerns. Here, we model the present distribution and the future climatic suitability of Europe for this vector in the face of climate change. In order to achieve the most realistic current prediction and future projection, we compare the performance of four different modelling approaches, differentiated by the selection of climate variables (based on expert knowledge vs. statistical criteria) and by the geographical range of presence records (native range vs. global range). First, models of the native and global range were built with MaxEnt and were either based on (1) statistically selected climatic input variables or (2) input variables selected with expert knowledge from the literature. Native models show high model performance (AUC: 0.91-0.94) for the native range, but do not predict the European distribution well (AUC: 0.70-0.72). Models based on the global distribution of the species, however, were able to identify all regions where Ae. albopictus is currently established, including Europe (AUC: 0.89-0.91). In a second step, the modelled bioclimatic envelope of the global range was projected to future climatic conditions in Europe using two emission scenarios implemented in the regional climate model COSMO-CLM for three time periods 2011-2040, 2041-2070, and 2071-2100. For both global-driven models, the results indicate that climatically suitable areas for the establishment of Ae. albopictus will increase in western and central Europe already in 2011-2040 and with a temporal delay in eastern Europe. On the other hand, a decline in climatically suitable areas in southern Europe is pronounced in the Expert knowledge based model. Our projections appear unaffected by non-analogue climate, as this is not detected by Multivariate Environmental Similarity Surface analysis. The generated risk maps can aid in identifying suitable habitats for Ae. albopictus and hence support monitoring and control activities to avoid disease vector establishment.

Comparison of Interglacial fire dynamics in Southern Africa

NASA Astrophysics Data System (ADS)

Brücher, Tim; Daniau, Anne-Laure

2016-04-01

Responses of fire activity to a change in climate are still uncertain and biases exist by integrating this non-linear process into global modeling of the Earth system. Warming and regional drying can force fire activity in two opposite directions: an increase in fire in fuel supported ecosystems or a fire reduction in fuel-limited ecosystems. Therefore, climate variables alone can not be used to estimate the fire risk because vegetation variability is an important determinant of fire dynamics and responds itself to change in climate. Southern Africa (south of 20°S) paleofire history reconstruction obtained from the analysis of microcharcoal preserved in a deep-sea core located off Namibia reveals changes of fire activity on orbital timescales in the precession band. In particular, increase in fire is observed during glacial periods, and reduction of fire during interglacials such as the Eemian and the Holocene. The Holocene was characterized by even lower level of fire activity than Eemian. Those results suggest the alternance of grass-fueled fires during glacials driven by increase in moisture and the development of limited fueled ecosystems during interglacials characterized by dryness. Those results question the simulated increase in the fire risk probability projected for this region under a warming and drying climate obtained by Pechony and Schindell (2010). To explore the validity of the hypotheses we conducted a data-model comparison for both interglacials from 126.000 to 115.000 BP for the Eemian and from 8.000 to 2.000 BP for the Holocene. Data out of a transient, global modeling study with a Vegetation-Fire model of full complexity (JSBACH) is used, driven by a Climate model of intermediate complexity (CLIMBER). Climate data like precipitation and temperature as well as vegetation data like soil moisture, productivity (NPP) on plant functional type level are used to explain trends in fire activity. The comparison of trends in fire activity during the Eemian (126.000 to 120.000 BP) and the Holocene (8.000 to 200 BP) shows an increase in fire data and in simulated fire. Lower level of fire during the Holocene than Eemian can be explained by differences due to unequal trends in vegetation as a result of climate forcing due to orbital changes: while woody type vegetation plays a major role during the Eemian, the Holocene is influenced by grass land. From the modelling perspective changes in the seasonal precipitation drives the vegetation pattern.

Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States

PubMed Central

Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H.

2017-01-01

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today’s technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual. PMID:28167756

Flood frequency matters: Why climate change degrades deep-water quality of peri-alpine lakes

NASA Astrophysics Data System (ADS)

Fink, Gabriel; Wessels, Martin; Wüest, Alfred

2016-09-01

Sediment-laden riverine floods transport large quantities of dissolved oxygen into the receiving deep layers of lakes. Hence, the water quality of deep lakes is strongly influenced by the frequency of riverine floods. Although flood frequency reflects climate conditions, the effects of climate variability on the water quality of deep lakes is largely unknown. We quantified the effects of climate variability on the potential shifts in the flood regime of the Alpine Rhine, the main catchment of Lake Constance, and determined the intrusion depths of riverine density-driven underflows and the subsequent effects on water exchange rates in the lake. A simplified hydrodynamic underflow model was developed and validated with observed river inflow and underflow events. The model was implemented to estimate underflow statistics for different river inflow scenarios. Using this approach, we integrated present and possible future flood frequencies to underflow occurrences and intrusion depths in Lake Constance. The results indicate that more floods will increase the number of underflows and the intensity of deep-water renewal - and consequently will cause higher deep-water dissolved oxygen concentrations. Vice versa, fewer floods weaken deep-water renewal and lead to lower deep-water dissolved oxygen concentrations. Meanwhile, a change from glacial nival regime (present) to a nival pluvial regime (future) is expected to decrease deep-water renewal. While flood frequencies are not expected to change noticeably for the next decades, it is most likely that increased winter discharge and decreased summer discharge will reduce the number of deep density-driven underflows by 10% and favour shallower riverine interflows in the upper hypolimnion. The renewal in the deepest layers is expected to be reduced by nearly 27%. This study underlines potential consequences of climate change on the occurrence of deep river underflows and water residence times in deep lakes.

Assessing Climate Vulnerability and Resilience of a Major Water Resource System - Inverting the Paradigm for Specific Risk Quantification at Decision Making Points of Impact

NASA Astrophysics Data System (ADS)

Murphy, K. W.; Ellis, A. W.; Skindlov, J. A.

2015-12-01

Water resource systems have provided vital support to transformative growth in the Southwest United States and the Phoenix, Arizona metropolitan area where the Salt River Project (SRP) currently satisfies 40% of the area's water demand from reservoir storage and groundwater. Large natural variability and expectations of climate changes have sensitized water management to risks posed by future periods of excess and drought. The conventional approach to impacts assessment has been downscaled climate model simulations translated through hydrologic models; but, scenario ranges enlarge as uncertainties propagate through sequential levels of modeling complexity. The research often does not reach the stage of specific impact assessments, rendering future projections frustratingly uncertain and unsuitable for complex decision-making. Alternatively, this study inverts the common approach by beginning with the threatened water system and proceeding backwards to the uncertain climate future. The methodology is built upon reservoir system response modeling to exhaustive time series of climate-driven net basin supply. A reservoir operations model, developed with SRP guidance, assesses cumulative response to inflow variability and change. Complete statistical analyses of long-term historical watershed climate and runoff data are employed for 10,000-year stochastic simulations, rendering the entire range of multi-year extremes with full probabilistic characterization. Sets of climate change projections are then translated by temperature sensitivity and precipitation elasticity into future inflow distributions that are comparatively assessed with the reservoir operations model. This approach provides specific risk assessments in pragmatic terms familiar to decision makers, interpretable within the context of long-range planning and revealing a clearer meaning of climate change projections for the region. As a transferable example achieving actionable findings, the approach can guide other communities confronting water resource planning challenges.

Ice sheet climate modeling: past achievements, ongoing challenges, and future endeavors

NASA Astrophysics Data System (ADS)

Lenaerts, J.

2017-12-01

Fluctuations in surface mass balance (SMB) mask out a substantial portion of contemporary Greenland and Antarctic ice sheet mass loss. That implies that we need accurate, consistent, and long-term SMB time series to isolate the mass loss signal. This in turn requires understanding of the processes driving SMB, and how they interplay. The primary controls on present-day ice sheet SMB are snowfall, which is regulated by large-scale atmospheric variability, and surface meltwater production at the ice sheet's edges, which is a complex result of atmosphere-surface interactions. Additionally, wind-driven snow redistribution and sublimation are large SMB contributors on the downslope areas of the ice sheets. Climate models provide an integrated framework to simulate all these individual ice sheet components. Recent developments in RACMO2, a regional climate model bound by atmospheric reanalyses, have focused on enhancing horizontal resolution, including blowing snow, snow albedo, and meltwater processes. Including these physics not only enhanced our understanding of the ice sheet climate system, but also enabled to obtain increasingly accurate estimates of ice sheet SMB. However, regional models are not suitable to capture the mutual interactions between ice sheet and the remainder of the global climate system in transient climates. To take that next step, global climate models are essential. In this talk, I will highlight our present work on improving ice sheet climate in the Community Earth System Model (CESM). In particular, we focus on an improved representation of polar firn, ice sheet clouds, and precipitation. For this exercise, we extensively use field observations, remote sensing data, as well as RACMO2. Next, I will highlight how CESM is used to enhance our understanding of ice sheet SMB, its drivers, and past and present changes.

The impact of climate change on the distribution of two threatened Dipterocarp trees.

PubMed

Deb, Jiban C; Phinn, Stuart; Butt, Nathalie; McAlpine, Clive A

2017-04-01

Two ecologically and economically important, and threatened Dipterocarp trees Sal ( Shorea robusta ) and Garjan ( Dipterocarpus turbinatus ) form mono-specific canopies in dry deciduous, moist deciduous, evergreen, and semievergreen forests across South Asia and continental parts of Southeast Asia. They provide valuable timber and play an important role in the economy of many Asian countries. However, both Dipterocarp trees are threatened by continuing forest clearing, habitat alteration, and global climate change. While climatic regimes in the Asian tropics are changing, research on climate change-driven shifts in the distribution of tropical Asian trees is limited. We applied a bioclimatic modeling approach to these two Dipterocarp trees Sal and Garjan. We used presence-only records for the tree species, five bioclimatic variables, and selected two climatic scenarios (RCP4.5: an optimistic scenario and RCP8.5: a pessimistic scenario) and three global climate models (GCMs) to encompass the full range of variation in the models. We modeled climate space suitability for both species, projected to 2070, using a climate envelope modeling tool "MaxEnt" (the maximum entropy algorithm). Annual precipitation was the key bioclimatic variable in all GCMs for explaining the current and future distributions of Sal and Garjan (Sal: 49.97 ± 1.33; Garjan: 37.63 ± 1.19). Our models predict that suitable climate space for Sal will decline by 24% and 34% (the mean of the three GCMs) by 2070 under RCP4.5 and RCP8.5, respectively. In contrast, the consequences of imminent climate change appear less severe for Garjan, with a decline of 17% and 27% under RCP4.5 and RCP8.5, respectively. The findings of this study can be used to set conservation guidelines for Sal and Garjan by identifying vulnerable habitats in the region. In addition, the natural habitats of Sal and Garjan can be categorized as low to high risk under changing climates where artificial regeneration should be undertaken for forest restoration.

Effect of Technology Driven Agricultural Land Use Change on Regional Hydroclimate

NASA Astrophysics Data System (ADS)

Arritt, R. W.; Sines, T. R.; Groisman, P. Y.; Gelder, B. K.

2017-12-01

During the mid-20th century motorized equipment replaced work animals in the central U.S. This led to a 95% decrease in farmland for producing oats, which had mostly been used as feed for horses. Much of this land was converted to more profitable crops such as soybeans and maize. The same period also saw a strong shift of the central U.S. precipitation intensity spectrum toward heavier events. Was this a coincidence, or is there a causal relationship? We investigate possible connections between this technology-driven land use change and regional hydroclimate by performing multi-decadal simulations over the central U.S. using the WRF-ARW regional climate model coupled with the Community Land Model (CLM 4.5). Cropland planted in maize, soybean, winter wheat, small grains (which includes oats and spring wheat), and other C3 and C4 crops were reconstructed on a decade by decade basis from 1940-2010 using county-level crop data. These crop distributions were used as land surface boundary conditions for two multi-decadal regional climate simulations, one with 1940s land use and another with modern (circa 2010) land use. Modern land use produced a shift in the simulated daily precipitation intensity spectrum toward heavy events, with higher frequencies of heavy precipitation amounts and lower frequencies of light amounts compared to 1940s land use. The results suggest that replacement of work animals by mechanized transport led to land use changes that produced about 10-30% of the observed trend toward more intense precipitation over the central United States. We therefore recommend that policy- and technology-driven changes in crop type be taken into account when projecting future climate and water resources.

Military Potential Test of the Model PA23-250B Fixed-Wing Instrument Trainer

DTIC Science & Technology

1964-11-30

cabin heater was installed in the test airplane. Existing climatic conditions precluded actual tests to determine the capability of the heater to...housed within the engine contol pedestal under the engine conr- trol levers. r , aulic pressure is supplied to the control unit by an engine-driven

Community College Dual Enrollment Faculty Orientation: A Utilization-Focused Approach

ERIC Educational Resources Information Center

Charlier, Hara D.; Duggan, Molly H.

2010-01-01

The current climate of accountability demands that institutions engage in data-driven program evaluation. In order to promote quality dual enrollment (DE) programs, institutions must support the adjunct faculty teaching college courses in high schools. This study uses Patton's utilization-focused model (1997) to conduct a formative evaluation of a…

Measuring and Modeling Tree Stand Level Transpiration

Treesearch

J.M. Vose; G.J. Harvey; K.J. Elliott; B.D. Clinton

2003-01-01

Transpiration is a key process in the application of phytoremediation to soil or groundwater pollutants. To be successful, vegetation must transpire enough water from the soil or groundwater to control or take up the contaminant. Transpiration is driven by a combination of abiotic (climate, soil water availability, and groundwater depth) and biotic (leaf area, stomatal...

Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

NASA Technical Reports Server (NTRS)

Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams

2010-01-01

This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

Climate mode links to atmospheric carbon monoxide over fire regions

NASA Astrophysics Data System (ADS)

Buchholz, R. R.; Hammerling, D.; Worden, H. M.; Monks, S. A.; Edwards, D. P.; Deeter, M. N.; Emmons, L. K.

2017-12-01

Fire is a strong contributor to variability in atmospheric carbon monoxide (CO), particularly for the Southern Hemisphere and tropics. The magnitude of emissions, such as CO, from biomass burning are related to climate through both the availability and dryness of fuel. We investigate this link between CO and climate using satellite measured CO and climate indices. Interannual variability in satellite-measured CO is determined for the time period covering 2001-2016. We use MOPITT total column retrievals and focus on biomass burning regions of the Southern Hemisphere and tropics. In each of the regions, data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Antarctic Oscillation (AAO). Step-wise forward and backward regression combined with the Bayesian Information Criterion is used to select the best predictive model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Generally, over 50% of the variability can be explained, with over 70% for the Maritime Southeast Asia and North Australasia regions. To help interpret variability, we draw on the chemistry-climate model CAM-chem, which provides information on source contributions and the relative influence of emissions and meteorology. Our results have implications for applications such as air quality forecasting and verifying climate-chemistry models.

The potential of air-sea interactions for improving summertime North Atlantic seasonal forecasts

NASA Astrophysics Data System (ADS)

Ossó, Albert; Shaffrey, Len; Dong, Buwen; Sutton, Rowan

2017-04-01

Delivering skillful summertime seasonal forecasts of the Northern Hemisphere (NH) mid-latitude climate is a key unresolved issue for the climate science community. Current climate models have some skill in forecasting the wintertime NH mid-latitude circulation but very limited skill during summertime. To explore the potential predictability of the summertime climate we analyze lagged correlation patterns between the SSTs and summer atmospheric circulation in the North Atlantic both in observations and climate model outputs. We find observational evidence in the ERA-Interim (1979-2015) reanalysis and the HadSLP2 and HadISST data of an SST pattern forced by late winter atmospheric circulation persisting from winter to early summer that excites an anticyclonic summer SLP anomaly west of the British Isles. We show that the atmospheric response is driven through the action of turbulent heat fluxes and changes on the background baroclinicity. The lagged atmospheric response to the SSTs could be exploited for summertime predictability over Western Europe. We find a statistical significant correlation of over 0.6 between April-May North Atlantic SSTs and the June-August North Atlantic SLP anomaly. The previous findings are further explored using 120 years of coupled ocean-atmosphere HadGEM3-GC2 model simulation. The climate model qualitatively reproduces the observed spatial relationship between the late winter and spring SSTs and summertime circulation, although the correlations are substantially weaker than observed.

Predicting Dengue Fever Outbreaks in French Guiana Using Climate Indicators.

PubMed

Adde, Antoine; Roucou, Pascal; Mangeas, Morgan; Ardillon, Vanessa; Desenclos, Jean-Claude; Rousset, Dominique; Girod, Romain; Briolant, Sébastien; Quenel, Philippe; Flamand, Claude

2016-04-01

Dengue fever epidemic dynamics are driven by complex interactions between hosts, vectors and viruses. Associations between climate and dengue have been studied around the world, but the results have shown that the impact of the climate can vary widely from one study site to another. In French Guiana, climate-based models are not available to assist in developing an early warning system. This study aims to evaluate the potential of using oceanic and atmospheric conditions to help predict dengue fever outbreaks in French Guiana. Lagged correlations and composite analyses were performed to identify the climatic conditions that characterized a typical epidemic year and to define the best indices for predicting dengue fever outbreaks during the period 1991-2013. A logistic regression was then performed to build a forecast model. We demonstrate that a model based on summer Equatorial Pacific Ocean sea surface temperatures and Azores High sea-level pressure had predictive value and was able to predict 80% of the outbreaks while incorrectly predicting only 15% of the non-epidemic years. Predictions for 2014-2015 were consistent with the observed non-epidemic conditions, and an outbreak in early 2016 was predicted. These findings indicate that outbreak resurgence can be modeled using a simple combination of climate indicators. This might be useful for anticipating public health actions to mitigate the effects of major outbreaks, particularly in areas where resources are limited and medical infrastructures are generally insufficient.

Future climate and surface mass balance of Svalbard glaciers in an RCP8.5 climate scenario: a study with the regional climate model MAR forced by MIROC5

NASA Astrophysics Data System (ADS)

Lang, C.; Fettweis, X.; Erpicum, M.

2015-05-01

We have performed a future projection of the climate and surface mass balance (SMB) of Svalbard with the MAR (Modèle Atmosphérique Régional) regional climate model forced by MIROC5 (Model for Interdisciplinary Research on Climate), following the RCP8.5 scenario at a spatial resolution of 10 km. MAR predicts a similar evolution of increasing surface melt everywhere in Svalbard followed by a sudden acceleration of melt around 2050, with a larger melt increase in the south compared to the north of the archipelago. This melt acceleration around 2050 is mainly driven by the albedo-melt feedback associated with the expansion of the ablation/bare ice zone. This effect is dampened in part as the solar radiation itself is projected to decrease due to a cloudiness increase. The near-surface temperature is projected to increase more in winter than in summer as the temperature is already close to 0 °C in summer. The model also projects a stronger winter west-to-east temperature gradient, related to the large decrease of sea ice cover around Svalbard. By 2085, SMB is projected to become negative over all of Svalbard's glaciated regions, leading to the rapid degradation of the firn layer.

Attribution of trends in global vegetation greenness from 1982 to 2011

NASA Astrophysics Data System (ADS)

Zhu, Z.; Xu, L.; Bi, J.; Myneni, R.; Knyazikhin, Y.

2012-12-01

Time series of remotely sensed vegetation indices data provide evidence of changes in terrestrial vegetation activity over the past decades in the world. However, it is difficult to attribute cause-and-effect to vegetation trends because variations in vegetation productivity are driven by various factors. This study investigated changes in global vegetation productivity first, and then attributed the global natural vegetation with greening trend. Growing season integrated normalized difference vegetation index (GSI NDVI) derived from the new GIMMS NDVI3g dataset (1982-2011was analyzed. A combined time series analysis model, which was developed from simper linear trend model (SLT), autoregressive integrated moving average model (ARIMA) and Vogelsang's t-PST model shows that productivity of all vegetation types except deciduous broadleaf forest predominantly showed increasing trends through the 30-year period. The evolution of changes in productivity in the last decade was also investigated. Area of greening vegetation monotonically increased through the last decade, and both the browning and no change area monotonically decreased. To attribute the predominant increase trend of productivity of global natural vegetation, trends of eight climate time series datasets (three temperature, three precipitation and two radiation datasets) were analyzed. The attribution of trends in global vegetation greenness was summarized as relaxation of climatic constraints, fertilization and other unknown reasons. Result shows that nearly all the productivity increase of global natural vegetation was driven by relaxation of climatic constraints and fertilization, which play equally important role in driving global vegetation greenness.; Area fraction and productivity change fraction of IGBP vegetation land cover classes showing statistically significant (10% level) trend in GSI NDVIt;

Evaluating the relative impact of climate and economic changes on forest and agricultural ecosystem services in mountain regions.

PubMed

Briner, Simon; Elkin, Ché; Huber, Robert

2013-11-15

Provisioning of ecosystem services (ES) in mountainous regions is predicted to be influenced by i) the direct biophysical impacts of climate change, ii) climate mediated land use change, and iii) socioeconomic driven changes in land use. The relative importance and the spatial distribution of these factors on forest and agricultural derived ES, however, is unclear, making the implementation of ES management schemes difficult. Using an integrated economic-ecological modeling framework, we evaluated the impact of these driving forces on the provision of forest and agricultural ES in a mountain region of southern Switzerland. Results imply that forest ES will be strongly influenced by the direct impact of climate change, but that changes in land use will have a comparatively small impact. The simulation of direct impacts of climate change affects forest ES at all elevations, while land use changes can only be found at high elevations. In contrast, changes to agricultural ES were found to be primarily due to shifts in economic conditions that alter land use and land management. The direct influence of climate change on agriculture is only predicted to be substantial at high elevations, while socioeconomic driven shifts in land use are projected to affect agricultural ES at all elevations. Our simulation results suggest that policy schemes designed to mitigate the negative impact of climate change on forests should focus on suitable adaptive management plans, accelerating adaptation processes for currently forested areas. To maintain provision of agricultural ES policy needs to focus on economic conditions rather than on supporting adaptation to new climate. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of high-resolution simulations for the Black Forest region from a point of view of tourism climatology - a comparison between two regional climate models (REMO and CLM)

NASA Astrophysics Data System (ADS)

Endler, Christina; Matzarakis, Andreas

2011-03-01

An analysis of climate simulations from a point of view of tourism climatology based on two regional climate models, namely REMO and CLM, was performed for a regional domain in the southwest of Germany, the Black Forest region, for two time frames, 1971-2000 that represents the twentieth century climate and 2021-2050 that represents the future climate. In that context, the Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and B1 are used. The analysis focuses on human-biometeorological and applied climatologic issues, especially for tourism purposes - that means parameters belonging to thermal (physiologically equivalent temperature, PET), physical (precipitation, snow, wind), and aesthetic (fog, cloud cover) facets of climate in tourism. In general, both models reveal similar trends, but differ in their extent. The trend of thermal comfort is contradicting: it tends to decrease in REMO, while it shows a slight increase in CLM. Moreover, REMO reveals a wider range of future climate trends than CLM, especially for sunshine, dry days, and heat stress. Both models are driven by the same global coupled atmosphere-ocean model ECHAM5/MPI-OM. Because both models are not able to resolve meso- and micro-scale processes such as cloud microphysics, differences between model results and discrepancies in the development of even those parameters (e.g., cloud formation and cover) are due to different model parameterization and formulation. Climatic changes expected by 2050 are small compared to 2100, but may have major impacts on tourism as for example, snow cover and its duration are highly vulnerable to a warmer climate directly affecting tourism in winter. Beyond indirect impacts are of high relevance as they influence tourism as well. Thus, changes in climate, natural environment, demography, tourists' demands, among other things affect economy in general. The analysis of the CLM results and its comparison with the REMO results complete the analysis performed within the project Climate Trends and Sustainable Development of Tourism in Coastal and Low Mountain Range Regions (CAST) funded by the German Federal Ministry of Education and Research (BMBF).

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.

Characterizing the "Time of Emergence" of Air Quality Climate Penalties

NASA Astrophysics Data System (ADS)

Rothenberg, D. A.; Garcia-Menendez, F.; Monier, E.; Solomon, S.; Selin, N. E.

2017-12-01

By driving not only local changes in temperature, but also precipitation and regional-scale changes in seasonal circulation patterns, climate change can directly and indirectly influence changes in air quality and its extremes. These changes - often referred to as "climate penalties" - can have important implications for human health, which is often targeted when assessing the potential co-benefits of climate policy. But because climate penalties are driven by slow, spatially-varying, temporal changes in the climate system, their emergence in the real world should also have a spatio-temporal component following regional variability in background air quality. In this work, we attempt to estimate the spatially-varying "time of emergence" of climate penalty signals by using an ensemble modeling framework based on the MIT Integrated Global System Model (MIT IGSM). With this framework we assess three climate policy scenarios assuming three different underlying climate sensitivities, and conduct a 5-member ensemble for each case to capture internal variability within the model. These simulations are used to drive offline chemical transport modeling (using CAM-Chem and GEOS-Chem). In these simulations, we find that the air quality response to climate change can vary dramatically across different regions of the globe. To analyze these regionally-varying climate signals, we employ a hierarchical clustering technique to identify regions with similar seasonal patterns of air quality change. Our simulations suggest that the earliest emergence of ozone climate penalties would occur in Southern Europe (by 2035), should the world neglect climate change and rely on a "business-as-usual" emissions policy. However, even modest climate policy dramatically pushes back the time of emergence of these penalties - to beyond 2100 - across most of the globe. The emergence of climate-forced changes in PM2.5 are much more difficult to detect, partially owing to the large role that changes in the frequency and spatial distribution of precipitation play in limiting the accumulation and duration of particulate pollution episodes.

Impacts of oak pollen on allergic asthma in the United States ...

EPA Pesticide Factsheets

Oak pollen season length for moderate (RCP4.5) and severe climate change scenarios (RCP8.5) are estimated through 2090 using five climate models and published relationships between temperature, precipitation, and oak pollen season length. We calculated asthma ED visit counts associated with 1994-2010 average oak pollen concentrations and simulated future oak pollen season length changes using the Environmental Benefits Mapping and Analysis Program (BenMAP-CE), driven by epidemiologically-derived concentration-response relationships. Future climate change is expected to lengthen and intensify pollen seasons in the U.S., potentially increasing incidence of allergic asthma. We developed a proof-of-concept approach for estimating asthma emergency department (ED) visits in the U.S. associated with present-day and climate-induced changes in oak pollen.

Use of Giovanni System in Public Health Application

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina; Kiang, Richard K.

2012-01-01

The role of environment and climate in propagating infectious disease has long been recognized since the 5th century. The effect is particularly evident in vector-borne diseases such as malaria where temperature, precipitation and humidity influence the lifecycle of the pathogens and mosquitoes. Likewise, the transmission of respiratory diseases is also often associated with climatic factors. For example, a recent study showed that low humidity and temperature provides efficient condition for seasonal influenza transmission. Understanding of how environment and climate affect infectious diseases would essentially provide guides to prevent and control the spread of disease. Toward this end, our group has developed models for infectious disease risk such as for malaria, dengue and influenza that are driven by climatic and environmental inputs. Results will be presented, especially those that used TRMM data from GIOVANNI.

Downscaling of RCM outputs for representative catchments in the Mediterranean region, for the 1951-2100 time-frame

NASA Astrophysics Data System (ADS)

Deidda, Roberto; Marrocu, Marino; Pusceddu, Gabriella; Langousis, Andreas; Mascaro, Giuseppe; Caroletti, Giulio

2013-04-01

Within the activities of the EU FP7 CLIMB project (www.climb-fp7.eu), we developed downscaling procedures to reliably assess climate forcing at hydrologically relevant scales, and applied them to six representative hydrological basins located in the Mediterranean region: Riu Mannu and Noce in Italy, Chiba in Tunisia, Kocaeli in Turkey, Thau in France, and Gaza in Palestine. As a first step towards this aim, we used daily precipitation and temperature data from the gridded E-OBS project (www.ecad.eu/dailydata), as reference fields, to rank 14 Regional Climate Model (RCM) outputs from the ENSEMBLES project (http://ensembles-eu.metoffice.com). The four best performing model outputs were selected, with the additional constraint of maintaining 2 outputs obtained from running different RCMs driven by the same GCM, and 2 runs from the same RCM driven by different GCMs. For these four RCM-GCM model combinations, a set of downscaling techniques were developed and applied, for the period 1951-2100, to variables used in hydrological modeling (i.e. precipitation; mean, maximum and minimum daily temperatures; direct solar radiation, relative humidity, magnitude and direction of surface winds). The quality of the final products is discussed, together with the results obtained after applying a bias reduction procedure to daily temperature and precipitation fields.

Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

NASA Astrophysics Data System (ADS)

Takhsha, Maryam; Nikiéma, Oumarou; Lucas-Picher, Philippe; Laprise, René; Hernández-Díaz, Leticia; Winger, Katja

2017-10-01

As part of the CORDEX project, the fifth-generation Canadian Regional Climate Model (CRCM5) is used over the Arctic for climate simulations driven by reanalyses and by the MPI-ESM-MR coupled global climate model (CGCM) under the RCP8.5 scenario. The CRCM5 shows adequate skills capturing general features of mean sea level pressure (MSLP) for all seasons. Evaluating 2-m temperature (T2m) and precipitation is more problematic, because of inconsistencies between observational reference datasets over the Arctic that suffer of a sparse distribution of weather stations. In our study, we additionally investigated the effect of large-scale spectral nudging (SN) on the hindcast simulation driven by reanalyses. The analysis shows that SN is effective in reducing the spring MSLP bias, but otherwise it has little impact. We have also conducted another experiment in which the CGCM-simulated sea-surface temperature (SST) is empirically corrected and used as lower boundary conditions over the ocean for an atmosphere-only global simulation (AGCM), which in turn provides the atmospheric lateral boundary conditions to drive the CRCM5 simulation. This approach, so-called 3-step approach of dynamical downscaling (CGCM-AGCM-RCM), which had considerably improved the CRCM5 historical simulations over Africa, exhibits reduced impact over the Arctic domain. The most notable positive effect over the Arctic is a reduction of the T2m bias over the North Pacific Ocean and the North Atlantic Ocean in all seasons. Future projections using this method are compared with the results obtained with the traditional 2-step dynamical downscaling (CGCM-RCM) to assess the impact of correcting systematic biases of SST upon future-climate projections. The future projections are mostly similar for the two methods, except for precipitation.

Avoided climate impacts of urban and rural heat and cold waves over the U.S. using large climate model ensembles for RCP8.5 and RCP4.5

PubMed Central

Anderson, G.B.; Jones, B.; McGinnis, S.A.; Sanderson, B.

2015-01-01

Previous studies examining future changes in heat/cold waves using climate model ensembles have been limited to grid cell-average quantities. Here, we make use of an urban parameterization in the Community Earth System Model (CESM) that represents the urban heat island effect, which can exacerbate extreme heat but may ameliorate extreme cold in urban relative to rural areas. Heat/cold wave characteristics are derived for U.S. regions from a bias-corrected CESM 30-member ensemble for climate outcomes driven by the RCP8.5 forcing scenario and a 15-member ensemble driven by RCP4.5. Significant differences are found between urban and grid cell-average heat/cold wave characteristics. Most notably, urban heat waves for 1981–2005 are more intense than grid cell-average by 2.1°C (southeast) to 4.6°C (southwest), while cold waves are less intense. We assess the avoided climate impacts of urban heat/cold waves in 2061–2080 when following the lower forcing scenario. Urban heat wave days per year increase from 6 in 1981–2005 to up to 92 (southeast) in RCP8.5. Following RCP4.5 reduces heat wave days by about 50%. Large avoided impacts are demonstrated for individual communities; e.g., the longest heat wave for Houston in RCP4.5 is 38 days while in RCP8.5 there is one heat wave per year that is longer than a month with some lasting the entire summer. Heat waves also start later in the season in RCP4.5 (earliest are in early May) than RCP8.5 (mid-April), compared to 1981–2005 (late May). In some communities, cold wave events decrease from 2 per year for 1981–2005 to one-in-five year events in RCP4.5 and one-in-ten year events in RCP8.5. PMID:29520121

Climate Change Impacts on Peak Electricity Consumption: US vs. Europe.

NASA Astrophysics Data System (ADS)

Auffhammer, M.

2016-12-01

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond. This finding is at odds with the relatively modest increase in climate driven impacts on consumption. Comprehensive high frequency load balancing authority level data have not been used previously to parameterize the relationship between electric demand and temperature for any major economy. Using statistical models we analyze multi-year data from load balancing authorities in the United States of America and the European Union, which are responsible for more than 90% of the electricity delivered to residential, industrial, commercial and agricultural customers. We couple the estimated response functions between total daily consumption and daily peak load with an ensemble of downscaled GCMs from the CMIP5 archive to simulate climate change driven impacts on both outcomes. We show moderate and highly spatially heterogeneous changes in consumption. The results of our peak load simulations, however, suggest significant changes in the intensity and frequency of peak events throughout the United States and Europe. As the electricity grid is built to endure maximum load, which usually occurs on the hottest day of the year, our findings have significant implications for the construction of costly peak generating and transmission capacity.

Climate change and marine ecosystems (Invited)

NASA Astrophysics Data System (ADS)

Chavez, F.

2013-12-01

Impacts of climate variability on marine ecosystems are pervasive. Those associated with the interannual El Ni~no phenomena are the most studied and better understood. Longer term variations associated with the Atlantic Multidecadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO) and the North Pacific Gyre Oscillation (NPGO) have become more evident as the present-day instrumental record has increased in length. The biological (chlorophyll to fish) and chemical (nutrients, oxygen, carbon) consequences of these climate-driven variations are discussed with an emphasis on the eastern and equatorial Pacific. During warmer periods biological productivity in the eastern Pacific is reduced and larger mobile organisms dramatically change their abundance and/or geographic distributions. At the same time biological productivity in the western Pacific increases highlighting that present (and future) climate-driven changes in biological productivity and chemical distributions are not (and will not) be uniform. The presentation documents present day variations using global scale information from satellites and in situ databases, model simulations and data collected by intensive local time series. Paradoxically longer term changes associated with phenomena like the Little Ice Age (LIA), captured in the sedimentary record, do not seem to follow the same warm (poor), cold (productive) patterns in the eastern Pacific, in fact these are reversed. The presentation ends with speculation regarding long term changes associated with a warmer world.

Heat-related mortality in a warming climate: projections for 12 U.S. cities.

PubMed

Petkova, Elisaveta P; Bader, Daniel A; Anderson, G Brooke; Horton, Radley M; Knowlton, Kim; Kinney, Patrick L

2014-10-31

Heat is among the deadliest weather-related phenomena in the United States, and the number of heat-related deaths may increase under a changing climate, particularly in urban areas. Regional adaptation planning is unfortunately often limited by the lack of quantitative information on potential future health responses. This study presents an assessment of the future impacts of climate change on heat-related mortality in 12 cities using 16 global climate models, driven by two scenarios of greenhouse gas emissions. Although the magnitude of the projected heat effects was found to differ across time, cities, climate models and greenhouse pollution emissions scenarios, climate change was projected to result in increases in heat-related fatalities over time throughout the 21st century in all of the 12 cities included in this study. The increase was more substantial under the high emission pathway, highlighting the potential benefits to public health of reducing greenhouse gas emissions. Nearly 200,000 heat-related deaths are projected to occur in the 12 cities by the end of the century due to climate warming, over 22,000 of which could be avoided if we follow a low GHG emission pathway. The presented estimates can be of value to local decision makers and stakeholders interested in developing strategies to reduce these impacts and building climate change resilience.

Heat-Related Mortality in a Warming Climate: Projections for 12 U.S. Cities

NASA Technical Reports Server (NTRS)

Petkova, Elisaveta P.; Bader, Daniel A.; Anderson, G. Brooke; Horton, Radley M.; Knowlton, Kim; Kinney, Patrick L.

2014-01-01

Heat is among the deadliest weather-related phenomena in the United States, and the number of heat-related deaths may increase under a changing climate, particularly in urban areas. Regional adaptation planning is unfortunately often limited by the lack of quantitative information on potential future health responses. This study presents an assessment of the future impacts of climate change on heat-related mortality in 12 cities using 16 global climate models, driven by two scenarios of greenhouse gas emissions. Although the magnitude of the projected heat effects was found to differ across time, cities, climate models and greenhouse pollution emissions scenarios, climate change was projected to result in increases in heat-related fatalities over time throughout the 21st century in all of the 12 cities included in this study. The increase was more substantial under the high emission pathway, highlighting the potential benefits to public health of reducing greenhouse gas emissions. Nearly 200,000 heat-related deaths are projected to occur in the 12 cities by the end of the century due to climate warming, over 22,000 of which could be avoided if we follow a low GHG emission pathway. The presented estimates can be of value to local decision makers and stakeholders interested in developing strategies to reduce these impacts and building climate change resilience.

Creating Dynamically Downscaled Seasonal Climate Forecast and Climate Change Projection Information for the North American Monsoon Region Suitable for Decision Making Purposes

NASA Astrophysics Data System (ADS)

Castro, C. L.; Dominguez, F.; Chang, H.

2010-12-01

Current seasonal climate forecasts and climate change projections of the North American monsoon are based on the use of course-scale information from a general circulation model. The global models, however, have substantial difficulty in resolving the regional scale forcing mechanisms of precipitation. This is especially true during the period of the North American Monsoon in the warm season. Precipitation is driven primarily due to the diurnal cycle of convection, and this process cannot be resolve in coarse-resolution global models that have a relatively poor representation of terrain. Though statistical downscaling may offer a relatively expedient method to generate information more appropriate for the regional scale, and is already being used in the resource decision making processes in the Southwest U.S., its main drawback is that it cannot account for a non-stationary climate. Here we demonstrate the use of a regional climate model, specifically the Weather Research and Forecast (WRF) model, for dynamical downscaling of the North American Monsoon. To drive the WRF simulations, we use retrospective reforecasts from the Climate Forecast System (CFS) model, the operational model used at the U.S. National Center for Environmental Prediction, and three select “well performing” IPCC AR 4 models for the A2 emission scenario. Though relatively computationally expensive, the use of WRF as a regional climate model in this way adds substantial value in the representation of the North American Monsoon. In both cases, the regional climate model captures a fairly realistic and reasonable monsoon, where none exists in the driving global model, and captures the dominant modes of precipitation anomalies associated with ENSO and the Pacific Decadal Oscillation (PDO). Long-term precipitation variability and trends in these simulations is considered via the standardized precipitation index (SPI), a commonly used metric to characterize long-term drought. Dynamically downscaled climate projection data will be integrated into future water resource projections in the state of Arizona, through a cooperative effort involving numerous water resource stakeholders.

Impacts of historical climate and land cover changes on fine particulate matter (PM2.5) air quality in East Asia between 1980 and 2010

NASA Astrophysics Data System (ADS)

Fu, Yu; Tai, Amos P. K.; Liao, Hong

2016-08-01

To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981-1985 and 2007-2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0-12.0 µg m-3 in northern China, but to an increase in summertime PM2.5 by 6.0-8.0 µg m-3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2-0.8 µg m-3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (-2.1 to +1.3 µg m-3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (-0.4 to +1.2 µg m-3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by -12.0 to +12.0 µg m-3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.

Development of ALARO-Climate regional climate model for a very high resolution

NASA Astrophysics Data System (ADS)

Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan

2013-04-01

ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main features of the RCM ALARO-Climate and results of the first model simulations on longer time-scales (1961-1990). The model was driven by the ERA-40/Interim re-analyses and run on the large pan-European integration domain ("ENSEMBLES / Euro-Cordex domain") with spatial resolution of 25 km. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version 7 dataset. The validation of the first ERA-40 simulation has revealed significant cold biases in all seasons (between -4 and -2 °C) and overestimation of precipitation on 20% to 60% in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The consequent adaptations in the model and their effect on the simulated properties of climate variables are illustrated. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).

Response to Comment on "Satellites reveal contrasting responses of regional climate to the widespread greening of Earth".

PubMed

Forzieri, Giovanni; Alkama, Ramdane; Miralles, Diego G; Cescatti, Alessandro

2018-06-15

Li et al contest the idea that vegetation greening has contributed to boreal warming and argue that the sensitivity of temperature to leaf area index (LAI) is instead likely driven by the climate impact on vegetation. We provide additional evidence that the LAI-climate interplay is indeed largely driven by the vegetation impact on temperature and not vice versa, thus corroborating our original conclusions. Copyright © 2018, American Association for the Advancement of Science.

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use.

PubMed

Zhang, Ke; de Almeida Castanho, Andrea D; Galbraith, David R; Moghim, Sanaz; Levine, Naomi M; Bras, Rafael L; Coe, Michael T; Costa, Marcos H; Malhi, Yadvinder; Longo, Marcos; Knox, Ryan G; McKnight, Shawna; Wang, Jingfeng; Moorcroft, Paul R

2015-02-20

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO 2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO 2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO 2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO 2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO 2 fertilization effects, fire, and land use - to the fate of the Amazon over the coming century. © 2015 John Wiley & Sons Ltd.

Tree mortality from drought, insects, and their interactions in a changing climate.

PubMed

Anderegg, William R L; Hicke, Jeffrey A; Fisher, Rosie A; Allen, Craig D; Aukema, Juliann; Bentz, Barbara; Hood, Sharon; Lichstein, Jeremy W; Macalady, Alison K; McDowell, Nate; Pan, Yude; Raffa, Kenneth; Sala, Anna; Shaw, John D; Stephenson, Nathan L; Tague, Christina; Zeppel, Melanie

2015-11-01

Climate change is expected to drive increased tree mortality through drought, heat stress, and insect attacks, with manifold impacts on forest ecosystems. Yet, climate-induced tree mortality and biotic disturbance agents are largely absent from process-based ecosystem models. Using data sets from the western USA and associated studies, we present a framework for determining the relative contribution of drought stress, insect attack, and their interactions, which is critical for modeling mortality in future climates. We outline a simple approach that identifies the mechanisms associated with two guilds of insects - bark beetles and defoliators - which are responsible for substantial tree mortality. We then discuss cross-biome patterns of insect-driven tree mortality and draw upon available evidence contrasting the prevalence of insect outbreaks in temperate and tropical regions. We conclude with an overview of tools and promising avenues to address major challenges. Ultimately, a multitrophic approach that captures tree physiology, insect populations, and tree-insect interactions will better inform projections of forest ecosystem responses to climate change. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Response of the European ecosystems to climate change: a modelling approach for the 21st century.

NASA Astrophysics Data System (ADS)

Dury, Marie; Warnant, Pierre; François, Louis; Henrot, Alexandra; Favre, Eric; Hambuckers, Alain

2010-05-01

According to projections, over the 21st century, significant climatic changes appear and will be strengthened all over the world with the continuing increase of the atmospheric CO2 level. Climate will be generally warmer with notably changes in the seasonality and in the precipitation regime. These changes will have major impacts on the environment and on the biodiversity of natural ecosystems. Geographic distribution of ecosystems may be modified since species will be driven to migrate towards more suitable areas (e. g., shifting of the arctic tree lines). The CARAIB dynamic vegetation model (Carbon Assimilation in the Biosphere) forced with 21st century climate scenarios of the IPCC (ARPEGE-Climat model) is used to illustrate and analyse the potential impacts of climate change on tree species distribution and productivity over Europe. Changes in hydrological budget (e. g., runoff) and fire effects on forests will also be shown. Transient runs (1975-2100) with a new dynamic module introduced in CARAIB are performed to follow the future evolutions. In the new module, the processes of species establishment, competition and mortality due to stresses and disturbances have been improved. Among others, increased atmospheric CO2 and warmer climate increase tree productivity while drier conditions decrease it. Regions with more severe droughts will also be affected by an increase of wildfire frequency, which may have large impacts on vegetation density and distribution.

Climate-Driven Effects of Fire on Winter Habitat for Caribou in the Alaskan-Yukon Arctic

PubMed Central

Gustine, David D.; Brinkman, Todd J.; Lindgren, Michael A.; Schmidt, Jennifer I.; Rupp, T. Scott; Adams, Layne G.

2014-01-01

Climatic warming has direct implications for fire-dominated disturbance patterns in northern ecosystems. A transforming wildfire regime is altering plant composition and successional patterns, thus affecting the distribution and potentially the abundance of large herbivores. Caribou (Rangifer tarandus) are an important subsistence resource for communities throughout the north and a species that depends on terrestrial lichen in late-successional forests and tundra systems. Projected increases in area burned and reductions in stand ages may reduce lichen availability within caribou winter ranges. Sufficient reductions in lichen abundance could alter the capacity of these areas to support caribou populations. To assess the potential role of a changing fire regime on winter habitat for caribou, we used a simulation modeling platform, two global circulation models (GCMs), and a moderate emissions scenario to project annual fire characteristics and the resulting abundance of lichen-producing vegetation types (i.e., spruce forests and tundra >60 years old) across a modeling domain that encompassed the winter ranges of the Central Arctic and Porcupine caribou herds in the Alaskan-Yukon Arctic. Fires were less numerous and smaller in tundra compared to spruce habitats throughout the 90-year projection for both GCMs. Given the more likely climate trajectory, we projected that the Porcupine caribou herd, which winters primarily in the boreal forest, could be expected to experience a greater reduction in lichen-producing winter habitats (−21%) than the Central Arctic herd that wintered primarily in the arctic tundra (−11%). Our results suggest that caribou herds wintering in boreal forest will undergo fire-driven reductions in lichen-producing habitats that will, at a minimum, alter their distribution. Range shifts of caribou resulting from fire-driven changes to winter habitat may diminish access to caribou for rural communities that reside in fire-prone areas. PMID:24991804

Planet-wide sand motion on mars

USGS Publications Warehouse

Bridges, N.T.; Bourke, M.C.; Geissler, P.E.; Banks, M.E.; Colon, C.; Diniega, S.; Golombek, M.P.; Hansen, C.J.; Mattson, S.; McEwen, A.S.; Mellon, M.T.; Stantzos, N.; Thomson, B.J.

2012-01-01

Prior to Mars Reconnaissance Orbiter data, images of Mars showed no direct evidence for dune and ripple motion. This was consistent with climate models and lander measurements indicating that winds of sufficient intensity to mobilize sand were rare in the low-density atmosphere. We show that many sand ripples and dunes across Mars exhibit movement of as much as a few meters per year, demonstrating that Martian sand migrates under current conditions in diverse areas of the planet. Most motion is probably driven by wind gusts that are not resolved in global circulation models. A past climate with a thicker atmosphere is only required to move large ripples that contain coarse grains. ?? 2012 Geological Society of America.

Mechanistic Lake Modeling to Understand and Predict Heterogeneous Responses to Climate Warming

NASA Astrophysics Data System (ADS)

Read, J. S.; Winslow, L. A.; Rose, K. C.; Hansen, G. J.

2016-12-01

Substantial warming has been documented for of hundreds globally distributed lakes, with likely impacts on ecosystem processes. Despite a clear pattern of widespread warming, thermal responses of individual lakes to climate change are often heterogeneous, with the warming rates of neighboring lakes varying across depths and among seasons. We aggregated temperature observations and parameterized mechanistic models for 9,000 lakes in the U.S. states of Minnesota, Wisconsin, and Michigan to examine broad-scale lake warming trends and among-lake diversity. Daily lake temperature profiles and ice-cover dynamics were simulated using the General Lake Model for the contemporary period (1979-2015) using drivers from the North American Land Data Assimilation System (NLDAS-2) and for contemporary and future periods (1980-2100) using downscaled data from six global circulation models driven by the Representative Climate Pathway 8.5 scenario. For the contemporary period, modeled vs observed summer mean surface temperatures had a root mean squared error of 0.98°C with modeled warming trends similar to observed trends. Future simulations under the extreme 8.5 scenario predicted a median lake summer surface warming rate of 0.57°C/decade until mid-century, with slower rates in the later half of the 21st century (0.35°C/decade). Modeling scenarios and analysis of field data suggest that the lake-specific properties of size, water clarity, and depth are strong controls on the sensitivity of lakes to climate change. For example, a simulated 1% annual decline in water clarity was sufficient to override the effects of climate warming on whole lake water temperatures in some - but not all - study lakes. Understanding heterogeneous lake responses to climate variability can help identify lake-specific features that influence resilience to climate change.

Modeled response of the West Nile virus vector Culex quinquefasciatus to changing climate using the dynamic mosquito simulation model

NASA Astrophysics Data System (ADS)

Morin, Cory W.; Comrie, Andrew C.

2010-09-01

Climate can strongly influence the population dynamics of disease vectors and is consequently a key component of disease ecology. Future climate change and variability may alter the location and seasonality of many disease vectors, possibly increasing the risk of disease transmission to humans. The mosquito species Culex quinquefasciatus is a concern across the southern United States because of its role as a West Nile virus vector and its affinity for urban environments. Using established relationships between atmospheric variables (temperature and precipitation) and mosquito development, we have created the Dynamic Mosquito Simulation Model (DyMSiM) to simulate Cx. quinquefasciatus population dynamics. The model is driven with climate data and validated against mosquito count data from Pasco County, Florida and Coachella Valley, California. Using 1-week and 2-week filters, mosquito trap data are reproduced well by the model ( P < 0.0001). Dry environments in southern California produce different mosquito population trends than moist locations in Florida. Florida and California mosquito populations are generally temperature-limited in winter. In California, locations are water-limited through much of the year. Using future climate projection data generated by the National Center for Atmospheric Research CCSM3 general circulation model, we applied temperature and precipitation offsets to the climate data at each location to evaluate mosquito population sensitivity to possible future climate conditions. We found that temperature and precipitation shifts act interdependently to cause remarkable changes in modeled mosquito population dynamics. Impacts include a summer population decline from drying in California due to loss of immature mosquito habitats, and in Florida a decrease in late-season mosquito populations due to drier late summer conditions.

Carbon Dioxide Physiological Forcing Dominates Projected Eastern Amazonian Drying

NASA Astrophysics Data System (ADS)

Richardson, T. B.; Forster, P. M.; Andrews, T.; Boucher, O.; Faluvegi, G.; Fläschner, D.; Kasoar, M.; Kirkevâg, A.; Lamarque, J.-F.; Myhre, G.; Olivié, D.; Samset, B. H.; Shawki, D.; Shindell, D.; Takemura, T.; Voulgarakis, A.

2018-03-01

Future projections of east Amazonian precipitation indicate drying, but they are uncertain and poorly understood. In this study we analyze the Amazonian precipitation response to individual atmospheric forcings using a number of global climate models. Black carbon is found to drive reduced precipitation over the Amazon due to temperature-driven circulation changes, but the magnitude is uncertain. CO2 drives reductions in precipitation concentrated in the east, mainly due to a robustly negative, but highly variable in magnitude, fast response. We find that the physiological effect of CO2 on plant stomata is the dominant driver of the fast response due to reduced latent heating and also contributes to the large model spread. Using a simple model, we show that CO2 physiological effects dominate future multimodel mean precipitation projections over the Amazon. However, in individual models temperature-driven changes can be large, but due to little agreement, they largely cancel out in the model mean.

Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

NASA Astrophysics Data System (ADS)

Fisher, Jeremy Isaac

Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat) and 500m Moderate Resolution Imaging Spectrometer (MODIS). A robust logistic-growth model of canopy cover was employed to determine phenological characteristics at each forest stand. The duel analyses revealed important findings: (a) local phenological gradients from microclimatic structures are highly influential in broad-scale phenological observations; (b) satellite observed phenology reflects observations of canopy growth from field studies; (c) phenological anomalies in urban areas which were previously attributed to urban heat may be a function of urban-specific land cover (i.e. green lawns); and (d) patterns of interannual variability in phenology at the regional scale have high spatial coherency and appear to be driven by broad-scale climatic change. Satellite-observed phenology may reflect temperatures during spring and provides a proxy of climate variability.

Functional Resilience against Climate-Driven Extinctions – Comparing the Functional Diversity of European and North American Tree Floras

PubMed Central

Liebergesell, Mario; Stahl, Ulrike; Freiberg, Martin; Welk, Erik; Kattge, Jens; Cornelissen, J. Hans C.; Peñuelas, Josep

2016-01-01

Future global change scenarios predict a dramatic loss of biodiversity for many regions in the world, potentially reducing the resistance and resilience of ecosystem functions. Once before, during Plio-Pleistocene glaciations, harsher climatic conditions in Europe as compared to North America led to a more depauperate tree flora. Here we hypothesize that this climate driven species loss has also reduced functional diversity in Europe as compared to North America. We used variation in 26 traits for 154 North American and 66 European tree species and grid-based co-occurrences derived from distribution maps to compare functional diversity patterns of the two continents. First, we identified similar regions with respect to contemporary climate in the temperate zone of North America and Europe. Second, we compared the functional diversity of both continents and for the climatically similar sub-regions using the functional dispersion-index (FDis) and the functional richness index (FRic). Third, we accounted in these comparisons for grid-scale differences in species richness, and, fourth, investigated the associated trait spaces using dimensionality reduction. For gymnosperms we find similar functional diversity on both continents, whereas for angiosperms functional diversity is significantly greater in Europe than in North America. These results are consistent across different scales, for climatically similar regions and considering species richness patterns. We decomposed these differences in trait space occupation into differences in functional diversity vs. differences in functional identity. We show that climate-driven species loss on a continental scale might be decoupled from or at least not linearly related to changes in functional diversity. This might be important when analyzing the effects of climate-driven biodiversity change on ecosystem functioning. PMID:26848836

Cross-scale assessment of potential habitat shifts in a rapidly changing climate

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.

2014-01-01

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

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

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

Quantifying the role of ocean initial conditions in decadal prediction

NASA Astrophysics Data System (ADS)

Matei, D.; Pohlmann, H.; Müller, W.; Haak, H.; Jungclaus, J.; Marotzke, J.

2009-04-01

The forecast skill of decadal climate predictions is investigated using two different initialization strategies. First we apply an assimilation of ocean synthesis data provided by the GECCO project (Köhl and Stammer 2008) as initial conditions for the coupled model ECHAM5/MPI-OM. The results show promising skill up to decadal time scales particularly over the North Atlantic (see also Pohlmann et al. 2009). However, mismatches between the ocean climates of GECCO and the MPI-OM model may lead to inconsistencies in the representation of water masses. Therefore, we pursue an alternative approach to the representation of the observed North Atlantic climate for the period 1948-2007. Using the same MPI-OM ocean model as in the coupled system, we perform an ensemble of four NCEP integrations. The ensemble mean temperature and salinity anomalies are then nudged into the coupled model, followed by hindcast/forecast experiments. The model gives dynamically consistent three-dimensional temperature and salinity fields, thereby avoiding the problems of model drift that were encountered when the assimilation experiment was only driven by reconstructed SSTs (Keenlyside et al. 2008, Pohlmann et al. 2009). Differences between the two assimilation approaches are discussed by comparing them with the observational data in key regions and processes, such as North Atlantic and Tropical Pacific climate, MOC variability, Subpolar Gyre variability.

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

DOE PAGES

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.; ...

2015-12-21

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Soares, Pedro; Hertig, Elke; Brands, Swen; Huth, Radan; Cardoso, Rita; Kotlarski, Sven; Casado, Maria; Pongracz, Rita; Bartholy, Judit

2016-04-01

Until recently, the evaluation of downscaled climate model simulations has typically been limited to surface climatologies, including long term means, spatial variability and extremes. But these aspects are often, at least partly, tuned in regional climate models to match observed climate. The tuning issue is of course particularly relevant for bias corrected regional climate models. In general, a good performance of a model for these aspects in present climate does therefore not imply a good performance in simulating climate change. It is now widely accepted that, to increase our condidence in climate change simulations, it is necessary to evaluate how climate models simulate relevant underlying processes. In other words, it is important to assess whether downscaling does the right for the right reason. Therefore, VALUE has carried out a broad process-based evaluation study based on its perfect predictor experiment simulations: the downscaling methods are driven by ERA-Interim data over the period 1979-2008, reference observations are given by a network of 85 meteorological stations covering all European climates. More than 30 methods participated in the evaluation. In order to compare statistical and dynamical methods, only variables provided by both types of approaches could be considered. This limited the analysis to conditioning local surface variables on variables from driving processes that are simulated by ERA-Interim. We considered the following types of processes: at the continental scale, we evaluated the performance of downscaling methods for positive and negative North Atlantic Oscillation, Atlantic ridge and blocking situations. At synoptic scales, we considered Lamb weather types for selected European regions such as Scandinavia, the United Kingdom, the Iberian Pensinsula or the Alps. At regional scales we considered phenomena such as the Mistral, the Bora or the Iberian coastal jet. Such process-based evaluation helps to attribute biases in surface variables to underlying processes and ultimately to improve climate models.

Physical and economic consequences of climate change in Europe.

PubMed

Ciscar, Juan-Carlos; Iglesias, Ana; Feyen, Luc; Szabó, László; Van Regemorter, Denise; Amelung, Bas; Nicholls, Robert; Watkiss, Paul; Christensen, Ole B; Dankers, Rutger; Garrote, Luis; Goodess, Clare M; Hunt, Alistair; Moreno, Alvaro; Richards, Julie; Soria, Antonio

2011-02-15

Quantitative estimates of the economic damages of climate change usually are based on aggregate relationships linking average temperature change to loss in gross domestic product (GDP). However, there is a clear need for further detail in the regional and sectoral dimensions of impact assessments to design and prioritize adaptation strategies. New developments in regional climate modeling and physical-impact modeling in Europe allow a better exploration of those dimensions. This article quantifies the potential consequences of climate change in Europe in four market impact categories (agriculture, river floods, coastal areas, and tourism) and one nonmarket impact (human health). The methodology integrates a set of coherent, high-resolution climate change projections and physical models into an economic modeling framework. We find that if the climate of the 2080s were to occur today, the annual loss in household welfare in the European Union (EU) resulting from the four market impacts would range between 0.2-1%. If the welfare loss is assumed to be constant over time, climate change may halve the EU's annual welfare growth. Scenarios with warmer temperatures and a higher rise in sea level result in more severe economic damage. However, the results show that there are large variations across European regions. Southern Europe, the British Isles, and Central Europe North appear most sensitive to climate change. Northern Europe, on the other hand, is the only region with net economic benefits, driven mainly by the positive effects on agriculture. Coastal systems, agriculture, and river flooding are the most important of the four market impacts assessed.

Physical and economic consequences of climate change in Europe

PubMed Central

Ciscar, Juan-Carlos; Iglesias, Ana; Feyen, Luc; Szabó, László; Van Regemorter, Denise; Amelung, Bas; Nicholls, Robert; Watkiss, Paul; Christensen, Ole B.; Dankers, Rutger; Garrote, Luis; Goodess, Clare M.; Hunt, Alistair; Moreno, Alvaro; Richards, Julie; Soria, Antonio

2011-01-01

Quantitative estimates of the economic damages of climate change usually are based on aggregate relationships linking average temperature change to loss in gross domestic product (GDP). However, there is a clear need for further detail in the regional and sectoral dimensions of impact assessments to design and prioritize adaptation strategies. New developments in regional climate modeling and physical-impact modeling in Europe allow a better exploration of those dimensions. This article quantifies the potential consequences of climate change in Europe in four market impact categories (agriculture, river floods, coastal areas, and tourism) and one nonmarket impact (human health). The methodology integrates a set of coherent, high-resolution climate change projections and physical models into an economic modeling framework. We find that if the climate of the 2080s were to occur today, the annual loss in household welfare in the European Union (EU) resulting from the four market impacts would range between 0.2–1%. If the welfare loss is assumed to be constant over time, climate change may halve the EU's annual welfare growth. Scenarios with warmer temperatures and a higher rise in sea level result in more severe economic damage. However, the results show that there are large variations across European regions. Southern Europe, the British Isles, and Central Europe North appear most sensitive to climate change. Northern Europe, on the other hand, is the only region with net economic benefits, driven mainly by the positive effects on agriculture. Coastal systems, agriculture, and river flooding are the most important of the four market impacts assessed. PMID:21282624

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.

Molecular proxies for climate maladaptation in a long-lived tree (Pinus pinaster Aiton, Pinaceae).

PubMed

Jaramillo-Correa, Juan-Pablo; Rodríguez-Quilón, Isabel; Grivet, Delphine; Lepoittevin, Camille; Sebastiani, Federico; Heuertz, Myriam; Garnier-Géré, Pauline H; Alía, Ricardo; Plomion, Christophe; Vendramin, Giovanni G; González-Martínez, Santiago C

2015-03-01

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP-climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change. Copyright © 2015 by the Genetics Society of America.

Molecular Proxies for Climate Maladaptation in a Long-Lived Tree (Pinus pinaster Aiton, Pinaceae)

PubMed Central

Jaramillo-Correa, Juan-Pablo; Rodríguez-Quilón, Isabel; Grivet, Delphine; Lepoittevin, Camille; Sebastiani, Federico; Heuertz, Myriam; Garnier-Géré, Pauline H.; Alía, Ricardo; Plomion, Christophe; Vendramin, Giovanni G.; González-Martínez, Santiago C.

2015-01-01

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP–climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change. PMID:25549630

Sensitivity of Regulated Flow Regimes to Climate Change in the Western United States

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

Zhou, Tian; Voisin, Nathalie; Leng, Guoyong

Water management activities or flow regulations modify water fluxes at the land surface and affect water resources in space and time. We hypothesize that flow regulations change the sensitivity of river flow to climate change with respect to unmanaged water resources. Quantifying these changes in sensitivity could help elucidate the impacts of water management at different spatiotemporal scales and inform climate adaptation decisions. In this study, we compared the emergence of significant changes in natural and regulated river flow regimes across the Western United States from simulations driven by multiple climate models and scenarios. We find that significant climate change-inducedmore » alterations in natural flow do not cascade linearly through water management activities. At the annual time scale, 50% of the Hydrologic Unit Code 4 (HUC4) sub-basins over the Western U.S. regions tend to have regulated flow regime more sensitive to the climate change than natural flow regime. Seasonality analyses show that the sensitivity varies remarkably across the seasons. We also find that the sensitivity is related to the level of water management. For 35% of the HUC4 sub-basins with the highest level of water management, the summer and winter flows tend to show a heightened sensitivity to climate change due to the complexity of joint reservoir operations. We further demonstrate that the impacts of considering water management in models are comparable to those that arises from uncertainties across climate models and emission scenarios. This prompts further climate adaptation studies research about nonlinearity effects of climate change through water management activities.« less

Anthropology is missing: on the World Development Report 2010: Development and Climate Change.

PubMed

Trostle, James

2010-07-01

When the World Bank publishes a report on climate change, the world takes notice. What are its diagnoses and treatments, and how present is anthropology in this analysis? The 2010 World Development Report on climate change provides few new diagnostic tools and no clear Bank policy revisions. It often fails to harmonize neoliberal development rhetoric with new climate-change imperatives. It nods to the importance of social context and risk perception yet refers primarily to behavioral economics and psychological constructs. Although anthropologists are documenting the local effects and human responses to larger-scale, climate-driven processes, our work is absent in the report. To play a role at global scale we would do well to learn more about concepts like nonlinearity and emergence, systems analysis, modeling, and disease dynamics. Our adroitness in developing metaphors and methods for crossing scale will make our efforts more visible and applicable.

A climate-associated multispecies cryptic cline in the northwest Atlantic

PubMed Central

DiBacco, Claudio; Lowen, Ben; Beiko, Robert G.; Bentzen, Paul; Brickman, David; Johnson, Catherine; Wang, Zeliang; Wringe, Brendan F.; Bradbury, Ian R.

2018-01-01

The spatial genetic structure of most species in the open marine environment remains largely unresolved. This information gap creates uncertainty in the sustainable management, recovery, and associated resilience of marine communities and our capacity to extrapolate beyond the few species for which such information exists. We document a previously unidentified multispecies biogeographic break aligned with a steep climatic gradient and driven by seasonal temperature minima in the northwest Atlantic. The coherence of this genetic break across our five study species with contrasting life histories suggests a pervasive macroecological phenomenon. The integration of this genetic structure with habitat suitability models and climate forecasts predicts significant variation in northward distributional shifts among populations and availability of suitable habitat in future oceans. The results of our integrated approach provide new perspective on how cryptic intraspecific diversity associated with climatic variation influences species and community response to climate change beyond simple poleward shifts. PMID:29600272

Dengue burden in India: recent trends and importance of climatic parameters.

PubMed

Mutheneni, Srinivasa Rao; Morse, Andrew P; Caminade, Cyril; Upadhyayula, Suryanaryana Murty

2017-08-09

For the past ten years, the number of dengue cases has gradually increased in India. Dengue is driven by complex interactions among host, vector and virus that are influenced by climatic factors. In the present study, we focused on the extrinsic incubation period (EIP) and its variability in different climatic zones of India. The EIP was calculated by using daily and monthly mean temperatures for the states of Punjab, Haryana, Gujarat, Rajasthan and Kerala. Among the studied states, a faster/low EIP in Kerala (8-15 days at 30.8 and 23.4 °C) and a generally slower/high EIP in Punjab (5.6-96.5 days at 35 and 0 °C) were simulated with daily temperatures. EIPs were calculated for different seasons, and Kerala showed the lowest EIP during the monsoon period. In addition, a significant association between dengue cases and precipitation was also observed. The results suggest that temperature is important in virus development in different climatic regions and may be useful in understanding spatio-temporal variations in dengue risk. Climate-based disease forecasting models in India should be refined and tailored for different climatic zones, instead of use of a standard model.

Dengue burden in India: recent trends and importance of climatic parameters

PubMed Central

Mutheneni, Srinivasa Rao; Morse, Andrew P; Caminade, Cyril; Upadhyayula, Suryanaryana Murty

2017-01-01

For the past ten years, the number of dengue cases has gradually increased in India. Dengue is driven by complex interactions among host, vector and virus that are influenced by climatic factors. In the present study, we focused on the extrinsic incubation period (EIP) and its variability in different climatic zones of India. The EIP was calculated by using daily and monthly mean temperatures for the states of Punjab, Haryana, Gujarat, Rajasthan and Kerala. Among the studied states, a faster/low EIP in Kerala (8–15 days at 30.8 and 23.4 °C) and a generally slower/high EIP in Punjab (5.6–96.5 days at 35 and 0 °C) were simulated with daily temperatures. EIPs were calculated for different seasons, and Kerala showed the lowest EIP during the monsoon period. In addition, a significant association between dengue cases and precipitation was also observed. The results suggest that temperature is important in virus development in different climatic regions and may be useful in understanding spatio-temporal variations in dengue risk. Climate-based disease forecasting models in India should be refined and tailored for different climatic zones, instead of use of a standard model. PMID:28790459

Evaluating the response of Lake Prespa (SW Balkan) to future climate change projections from a high-resolution model

NASA Astrophysics Data System (ADS)

van der Schriek, Tim; Varotsos, Konstantinos V.; Giannakopoulos, Christos

2017-04-01

The Mediterranean stands out globally due to its sensitivity to (future) climate change. Projections suggest that the Balkans will experience precipitation and runoff decreases of up to 30% by 2100. However, these projections show large regional spatial variability. Mediterranean lake-wetland systems are particularly threatened by projected climate changes that compound increasingly intensive human impacts (e.g. water extraction, drainage, pollution and dam-building). Protecting the remaining systems is extremely important for supporting global biodiversity. This protection should be based on a clear understanding of individual lake-wetland hydrological responses to future climate changes, which requires fine-resolution projections and a good understanding of the impact of hydro-climate variability on individual lakes. Climate change may directly affect lake level (variability), volume and water temperatures. In turn, these variables influence lake-ecology, habitats and water quality. Land-use intensification and water abstraction multiply these climate-driven changes. To date, there are no projections of future water level and -temperature of individual Mediterranean lakes under future climate scenarios. These are, however, of crucial importance to steer preservation strategies on the relevant catchment-scale. Here we present the first projections of water level and -temperature of the Prespa Lakes covering the period 2071-2100. These lakes are of global significance for biodiversity, and of great regional socio-economic importance as a water resource and tourist attraction. Impact projections are assessed by the Regional Climate Model RCA4 of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Max Planck Institute for Meteorology global climate model MPI-ESM-LR under two RCP future emissions scenarios, the RCP4.5 and the RCP8.5, with the simulations carried out in the framework of EURO-CORDEX. Temperature, evapo(transpi)ration and precipitation over the Prespa catchment were simulated with this high horizontal resolution (12 × 12 km) regional climate model. Lake temperatures were derived from surface temperatures based on physical models, while water levels were calculated with the lake water balance model. Climate simulations indicate that annual- and wet season catchment precipitation does not significantly change by the end of the century. The median precipitation decreases, while precipitation variability increases. The percentage of annual precipitation falling in the wet season increases by 5-10%, indicating a stronger seasonality in the precipitation regime. Summer (lake) temperatures and lake surface evaporation will rise significantly under both explored climate change scenarios. Lake impact projections indicate that evaporation changes will cause the water level of Lake Megali Prespa to fall by 5m to 840-839m. The increased precipitation variability will cause large inter-annual water level fluctuations. Average water level may fall even further if: (1) drier summers lead to more water abstraction for irrigation, and (2) there is a reduction in winter snowfall/accumulation and thus less discharge. These findings are of key importance for developing sustainable lake water resource management in a region that is highly vulnerable to future climate change and already experiences significant water stress. Research paves the way for innovative management adaptation strategies focussed on decreasing water abstraction, for example through introducing smart irrigation and selecting more water efficient crops.

Contradictory cooling in a warmer world? the climate of the Mediterranean region during the ';Holocene Thermal Maximum'

NASA Astrophysics Data System (ADS)

Davis, B.

2013-12-01

Extensive evidence from high latitudes of the Northern Hemisphere indicates that temperatures were warmer than present during the early-mid Holocene, a period known as the Holocene thermal maximum (HTM). The existence of the HTM over lower mid-latitudes and the sub-tropics however is less clear, with pollen-based reconstructions in particular actually indicating a contrary cooling at this time in these regions. This apparent cooling is controversial because it is not shown in climate model simulations, which indicate that the HTM occurred across all extra-tropical latitudes of the Northern Hemisphere. This is also supported by alkenone based SST reconstructions, which also show a much more widespread HTM than indicated by the pollen data. Here this problem is investigated by reviewing the evidence both for, and against, the HTM in the Mediterranean region, which represents one of the most intensively studied regions of sub-tropical climate in the Northern Hemisphere. This evidence includes a large number of both marine and terrestrial records that can be directly compared due to their close proximity around the Mediterranean Sea. The results highlight the potential for bias in both marine and terrestrial climate proxies, but despite many criticisms of the pollen-based record, it is shown that the existence of more extensive temperate vegetation in the early-mid Holocene in the Mediterranean is difficult to explain by anything other than a cooler climate. For instance, vegetation models driven by climate model output show that the warmer climate suggested by the models produces a HTM vegetation even more arid than today. The results have important implications in the interpretation of proxy records, but perhaps most importantly, the potential for climate models to underestimate cooling processes in a warmer world needs further investigation.

The CAMI Project - Weather and Climate Services for Caribbean Food Security

NASA Astrophysics Data System (ADS)

Trotman, Adrian; Van Meerbeeck, Cedric

2013-04-01

Food security is major focus of Caribbean governments, with production being of particular concern. For the past three decades, Caribbean agriculture has been declining in relative importance, both in terms of its contribution to GDP and its share of the labour force. One of the problems Caribbean agriculture faces is the destructive impacts from weather and climate extremes. These include flood, drought, extreme temperatures, and strong winds from tropical cyclones. Other potential disasters, such as from pests and diseases attacks, are also weather and climate driven. These make weather and climate information critically important to decision-making in agriculture in the Caribbean region. In an effort to help reduce weather and climate related risks to the food security sector, The Caribbean Institute for Meteorology and Hydrology, along with its partners the Caribbean Agricultural Research and Development Institute, the World Meteorological Organization (WMO) and ten National Meteorological Services from within the Caribbean Community launched and implemented the Caribbean Agrometeorological Initiative (CAMI). From 2010 to 2013, CAMI set out to provide relevant information to farmers, and the industry in general, for decision and policy making. The project is funded by the European Union through the Science and Technology Programme of the African, Caribbean and Pacific Group of Countries' (ACP). The overarching objective of CAMI was to increase and sustain agricultural productivity at the farm level in the Caribbean region through improved applications of weather and climate information, using an integrated and coordinated approach. Currently, this is done through (i) provision of relevant climate information appropriately disseminated, (ii) predictions on seasonal rainfall and temperature, (iii) support for improved irrigation management, (iv) the development of strategically selected weather-driven pest and disease models, (v) use of crop simulation models, (vi) training of staff of National Meteorological Services (NMS) and two relevant regional research institutions (vi) and the staging of forums for farmers and Agriculture Extension officers. With its innovative actions and generated products, the thrusts of CAMI link well to the components of the WMO's Global Framework for Climate Services.