Coastal Wetland Ecosystem Responses to Climate Change: the Role of Macroclimatic Drivers along the Northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Osland, M. J.; Enwright, N.; Day, R. H.; Gabler, C. A.; Stagg, C. L.; From, A. S.

2014-12-01

Across the globe, macroclimatic drivers greatly influence coastal wetland ecosystem structure and function. However, changing macroclimatic conditions are rarely incorporated into coastal wetland vulnerability assessments. Here, we quantify the influence of macroclimatic drivers upon coastal wetland ecosystems along the Northern Gulf of Mexico (NGOM) coast. From a global perspective, the NGOM coast provides several excellent opportunities to examine the effects of climate change upon coastal wetlands. The abundant coastal wetland ecosystems in the region span two major climatic gradients: (1) a winter temperature gradient that crosses temperate to tropical climatic zones; and (2) a precipitation gradient that crosses humid to semi-arid zones. We present analyses where we used geospatial data (historical climate, hydrology, and coastal wetland coverage) and field data (soil, elevation, and plant community composition and structure) to quantify climate-mediated ecological transitions. We identified winter climate and precipitation-based thresholds that separate mangrove forests from salt marshes and vegetated wetlands from unvegetated wetlands, respectively. We used simple distribution and abundance models to evaluate the potential ecological effects of alternative future climate change scenarios. Our results illustrate and quantify the importance of macroclimatic drivers and indicate that climate change could result in landscape-scale changes in coastal wetland ecosystem structure and function. These macroclimate-mediated ecological changes could affect the supply of some ecosystem goods and services as well as the resilience of these ecosystems to stressors, including accelerated sea level rise. Collectively, our findings highlight the importance of incorporating macroclimatic drivers within future-focused coastal wetland vulnerability assessments.

Spatial heterogeneity in the timing of birch budburst in response to future climate warming in Ireland

NASA Astrophysics Data System (ADS)

Caffarra, Amelia; Zottele, Fabio; Gleeson, Emily; Donnelly, Alison

2014-05-01

In order to predict the impact of future climate warming on trees it is important to quantify the effect climate has on their development. Our understanding of the phenological response to environmental drivers has given rise to various mathematical models of the annual growth cycle of plants. These models simulate the timing of phenophases by quantifying the relationship between development and its triggers, typically temperature. In addition, other environmental variables have an important role in determining the timing of budburst. For example, photoperiod has been shown to have a strong influence on phenological events of a number of tree species, including Betula pubescens (birch). A recently developed model for birch (DORMPHOT), which integrates the effects of temperature and photoperiod on budburst, was applied to future temperature projections from a 19-member ensemble of regional climate simulations (on a 25 km grid) generated as part of the ENSEMBLES project, to simulate the timing of birch budburst in Ireland each year up to the end of the present century. Gridded temperature time series data from the climate simulations were used as input to the DORMPHOT model to simulate future budburst timing. The results showed an advancing trend in the timing of birch budburst over most regions in Ireland up to 2100. Interestingly, this trend appeared greater in the northeast of the country than in the southwest, where budburst is currently relatively early. These results could have implications for future forest planning, species distribution modeling, and the birch allergy season.

AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

DOE PAGES

Collins, William J.; Lamarque, Jean -François; Schulz, Michael; ...

2017-02-09

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and theirmore » climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. As a result, specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.« less

Quantifying the risks of winter damage on overwintering crops under future climates: Will low-temperature damage be more likely in warmer climates?

NASA Astrophysics Data System (ADS)

Vico, G.; Weih, M.

2014-12-01

Autumn-sown crops act as winter cover crop, reducing soil erosion and nutrient leaching, while potentially providing higher yields than spring varieties in many environments. Nevertheless, overwintering crops are exposed for longer periods to the vagaries of weather conditions. Adverse winter conditions, in particular, may negatively affect the final yield, by reducing crop survival or its vigor. The net effect of the projected shifts in climate is unclear. On the one hand, warmer temperatures may reduce the frequency of low temperatures, thereby reducing damage risk. On the other hand, warmer temperatures, by reducing plant acclimation level and the amount and duration of snow cover, may increase the likelihood of damage. Thus, warmer climates may paradoxically result in more extensive low temperature damage and reduced viability for overwintering plants. The net effect of a shift in climate is explored by means of a parsimonious probabilistic model, based on a coupled description of air temperature, snow cover, and crop tolerable temperature. Exploiting an extensive dataset of winter wheat responses to low temperature exposure, the risk of winter damage occurrence is quantified under conditions typical of northern temperate latitudes. The full spectrum of variations expected with climate change is explored, quantifying the joint effects of alterations in temperature averages and their variability as well as shifts in precipitation. The key features affecting winter wheat vulnerability to low temperature damage under future climates are singled out.

AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

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

Collins, William J.; Lamarque, Jean -François; Schulz, Michael

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and theirmore » climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. As a result, specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.« less

Quantifying Uncertainty in Projections of Stratospheric Ozone Over the 21st Century

NASA Technical Reports Server (NTRS)

Charlton-Perez, A. J.; Hawkins, E.; Eyring, V.; Cionni, I.; Bodeker, G. E.; Kinnison, D. E.; Akiyoshi, H.; Frith, S. M.; Garcia, R.; Gettelman, A.;

Assessing the impact of future climate extremes on the US corn and soybean production

NASA Astrophysics Data System (ADS)

Jin, Z.

2015-12-01

Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.

4. Carbon Changes in U.S. Forests

Treesearch

R.A. Birdsey; L.S. Heath

1995-01-01

Global concern about increasing atmospheric concentrations of greenhouse gases, particularly carbon dioxide (CO2), and the possible consequences of future climate changes, has generated interest in understanding and quantifying the role of terrestrial ecosystems in the global carbon cycle. Recent efforts to quantify the global carbon budget have...

Conjunctive management of surface and groundwater resources under projected future climate change scenarios

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

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

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

Conjunctive management of surface and groundwater resources under projected future climate change scenarios

DOE PAGES

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

2016-06-16

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

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.

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

NASA Astrophysics Data System (ADS)

Di Vittorio, A. V.; Mao, J.; Shi, X.; Chini, L.; Hurtt, G.; Collins, W. D.

2018-01-01

Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. Here we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO2 in 2004, and generates carbon uncertainty that is equivalent to 80% of the net effects of CO2 and climate and 124% of the effects of nitrogen deposition during 1850-2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. We conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

DOE PAGES

Di Vittorio, A. V.; Mao, J.; Shi, X.; ...

2018-01-03

Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. In this paper, we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO 2 in 2004, and generates carbon uncertainty that is equivalentmore » to 80% of the net effects of CO 2 and climate and 124% of the effects of nitrogen deposition during 1850–2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. Finally, we conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.« less

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

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

Di Vittorio, A. V.; Mao, J.; Shi, X.

Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. In this paper, we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO 2 in 2004, and generates carbon uncertainty that is equivalentmore » to 80% of the net effects of CO 2 and climate and 124% of the effects of nitrogen deposition during 1850–2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. Finally, we conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.« less

Modelling carbon in permafrost soils from preindustrial to the future

NASA Astrophysics Data System (ADS)

Kleinen, T.; Brovkin, V.

2015-12-01

The carbon release from thawing permafrost soils constitutes one of the large uncertainties in the carbon cycle under future climate change. Analysing the problem further, this uncertainty results from an uncertainty about the total amount of C that is stored in frozen soils, combined with an uncertainty about the areas where soils might thaw under a particular climate change scenario, as well as an uncertainty about the decomposition product since some of the decomposed C might result the release of CH4 as well as CO2. We use the land surface model JSBACH, part of the Max Planck Institute Earth System Model MPI-ESM, to quantify the release of soil carbon from thawing permafrost soils. We have extended the soil carbon model YASSO by introducing carbon storages in frozen soils, with increasing fractions of C being available to decomposition as permafrost thaws. In order to quantify the amount of carbon released as CH4, as opposed to CO2, we have also implemented a TOPMODEL-based wetland scheme, as well as anaerobic C decomposition and methane transport. We initialise the soil C pools for the preindustrial climate state from the Northern Circumpolar Soil Carbon Database to insure initial C pool sizes close to measurements. We then determine changes in soil C storage in transient model experiments following historical and future climate changes under RCP 8.5. Based on these experiments, we quantify the greenhouse gas release from permafrost C decomposition, determining both CH4 and CO2 emissions.

INTERACTION OF CLIMATE AND LAND USE IN FUTURE TERRESTRIAL CARBON STORAGE AND RELEASE

EPA Science Inventory

The processes controlling total carbon (C) storage and release from the terrestrial biosphere are still poorly quantified. e conclude from analysis of paleodata and climate biome model output that terrestrial C exchanges since the last glacial maximum (LGM) were dominated by slow...

Mangroves as a protection from storm surges in a changing climate.

PubMed

Blankespoor, Brian; Dasgupta, Susmita; Lange, Glenn-Marie

2017-05-01

Adaptation to climate change includes addressing sea-level rise (SLR) and increased storm surges in many coastal areas. Mangroves can substantially reduce vulnerability of the adjacent coastal land from inundation but SLR poses a threat to the future of mangroves. This paper quantifies coastal protection services of mangroves for 42 developing countries in the current climate, and a future climate change scenario with a 1-m SLR and 10  % intensification of storms. Findings demonstrate that while SLR and increased storm intensity would increase storm surge areas, the greatest impact is from the expected loss of mangroves. Under current climate and mangrove coverage, 3.5 million people and GDP worth roughly US $400 million are at risk. In the future climate change scenario, vulnerable population and GDP at risk would increase by 103 and 233  %. The greatest risk is in East Asia, especially in Indonesia and the Philippines as well as Myanmar.

A Bayesian model for quantifying the change in mortality associated with future ozone exposures under climate change.

PubMed

Alexeeff, Stacey E; Pfister, Gabriele G; Nychka, Doug

2016-03-01

Climate change is expected to have many impacts on the environment, including changes in ozone concentrations at the surface level. A key public health concern is the potential increase in ozone-related summertime mortality if surface ozone concentrations rise in response to climate change. Although ozone formation depends partly on summertime weather, which exhibits considerable inter-annual variability, previous health impact studies have not incorporated the variability of ozone into their prediction models. A major source of uncertainty in the health impacts is the variability of the modeled ozone concentrations. We propose a Bayesian model and Monte Carlo estimation method for quantifying health effects of future ozone. An advantage of this approach is that we include the uncertainty in both the health effect association and the modeled ozone concentrations. Using our proposed approach, we quantify the expected change in ozone-related summertime mortality in the contiguous United States between 2000 and 2050 under a changing climate. The mortality estimates show regional patterns in the expected degree of impact. We also illustrate the results when using a common technique in previous work that averages ozone to reduce the size of the data, and contrast these findings with our own. Our analysis yields more realistic inferences, providing clearer interpretation for decision making regarding the impacts of climate change. © 2015, The International Biometric Society.

Modeling the influence of climate change on watershed systems: Adaptation through targeted practices

NASA Astrophysics Data System (ADS)

Dudula, John; Randhir, Timothy O.

2016-10-01

Climate change may influence hydrologic processes of watersheds (IPCC, 2013) and increased runoff may cause flooding, eroded stream banks, widening of stream channels, increased pollutant loading, and consequently impairment of aquatic life. The goal of this study was to quantify the potential impacts of climate change on watershed hydrologic processes and to evaluate scale and effectiveness of management practices for adaptation. We simulate baseline watershed conditions using the Hydrological Simulation Program Fortran (HSPF) simulation model to examine the possible effects of changing climate on watershed processes. We also simulate the effects of adaptation and mitigation through specific best management strategies for various climatic scenarios. With continuing low-flow conditions and vulnerability to climate change, the Ipswich watershed is the focus of this study. We quantify fluxes in runoff, evapotranspiration, infiltration, sediment load, and nutrient concentrations under baseline and climate change scenarios (near and far future). We model adaptation options for mitigating climate effects on watershed processes using bioretention/raingarden Best Management Practices (BMPs). It was observed that climate change has a significant impact on watershed runoff and carefully designed and maintained BMPs at subwatershed scale can be effective in mitigating some of the problems related to stormwater runoff. Policy options include implementation of BMPs through education and incentives for scale-dependent and site specific bioretention units/raingardens to increase the resilience of the watershed system to current and future climate change.

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.

Storylines of socio-economic and climatic drivers for land use and their hydrological impacts in alpine catchments - the STELLA project example

NASA Astrophysics Data System (ADS)

Strasser, Ulrich; Formayer, Herbert; Förster, Kristian; Marke, Thomas; Meißl, Gertraud; Schermer, Markus; Stotten, Friederike; Themessl, Matthias

2016-04-01

Future land use in Alpine catchments is controlled by the evolution of socio-economy and climate. Estimates of their coupled development should hence fulfill the principles of plausibility (be convincing) and consistency (be unambiguous). In the project STELLA, coupled future climate and land use scenarios are used as input in a hydrological modelling exercise with the physically-based, distributed water balance model WaSiM. The aim of the project is to quantify the effects of these two framing components on the future water cycle. The test site for the simulations is the catchment of the Brixentaler Ache in Tyrol/Austria (47.5°N, 322 km2). The so-called „storylines" of future coupled climate and forest/land use management, policy, social cooperation, tourism and economy have jointly been developed in an inter- and transdisciplinary assessment with local actors. The climate background is given by simulations for the A1B (temperature conditions like today in Merano/Italy, 46.7°N) and RCP 8.5 (temperature conditions like today in Bologna/Italy, 44.5°N) emission scenarios. These two climate scenarios were combined with three potential socio-economic developments („local"/„glocal"/ „superglobal"), each in a positive and in a negative specification. From these twelve storylines of coupled climate/land use future, a set of four storylines was selected to be used in transient hydrological modelling experiments. Historical simulations of the water balance for the test site reveal the pattern of land use being the most prominent factor for the spatial distribution of its components. A new prototype for a snow-canopy interaction simulation module provides explicit rates of intercepted and sublimated snow from the trees and stems of the different forest stands in the catchment. This new canopy module will be used to model the coupled climate/land use future storylines for the Brixental. The aim is to quantify the effects of climate change and land use on the water balance and streamflow, both separately and in their respective combination.

Impacts of Future Climate, Emission, and Land Use Changes on Aerosols and Air Quality over the Continental

EPA Science Inventory

Changes in climate, emission, and land use in the U.S. over the next century are imminent. The response of geologic, biogenic, and anthropogenic aerosol to interactions between these changes, however, are more uncertain and difficult to quantify. To explore these interactions, ...

Uncertainties Associated with Quantifying Climate Change Impacts on Human Health: A Case Study for Diarrhea

PubMed Central

Kolstad, Erik W.; Johansson, Kjell Arne

2011-01-01

Background Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase. Objectives The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century. Methods We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed. Results The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8–11% (with SDs of 3–5%) by 2010–2039 and 22–29% (SDs of 9–12%) by 2070–2099. Conclusions Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate–health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health. PMID:20929684

Implications of climate change for agricultural productivity in the early twenty-first century.

PubMed

Gornall, Jemma; Betts, Richard; Burke, Eleanor; Clark, Robin; Camp, Joanne; Willett, Kate; Wiltshire, Andrew

2010-09-27

This paper reviews recent literature concerning a wide range of processes through which climate change could potentially impact global-scale agricultural productivity, and presents projections of changes in relevant meteorological, hydrological and plant physiological quantities from a climate model ensemble to illustrate key areas of uncertainty. Few global-scale assessments have been carried out, and these are limited in their ability to capture the uncertainty in climate projections, and omit potentially important aspects such as extreme events and changes in pests and diseases. There is a lack of clarity on how climate change impacts on drought are best quantified from an agricultural perspective, with different metrics giving very different impressions of future risk. The dependence of some regional agriculture on remote rainfall, snowmelt and glaciers adds to the complexity. Indirect impacts via sea-level rise, storms and diseases have not been quantified. Perhaps most seriously, there is high uncertainty in the extent to which the direct effects of CO(2) rise on plant physiology will interact with climate change in affecting productivity. At present, the aggregate impacts of climate change on global-scale agricultural productivity cannot be reliably quantified.

Implications of climate change for agricultural productivity in the early twenty-first century

PubMed Central

Gornall, Jemma; Betts, Richard; Burke, Eleanor; Clark, Robin; Camp, Joanne; Willett, Kate; Wiltshire, Andrew

2010-01-01

This paper reviews recent literature concerning a wide range of processes through which climate change could potentially impact global-scale agricultural productivity, and presents projections of changes in relevant meteorological, hydrological and plant physiological quantities from a climate model ensemble to illustrate key areas of uncertainty. Few global-scale assessments have been carried out, and these are limited in their ability to capture the uncertainty in climate projections, and omit potentially important aspects such as extreme events and changes in pests and diseases. There is a lack of clarity on how climate change impacts on drought are best quantified from an agricultural perspective, with different metrics giving very different impressions of future risk. The dependence of some regional agriculture on remote rainfall, snowmelt and glaciers adds to the complexity. Indirect impacts via sea-level rise, storms and diseases have not been quantified. Perhaps most seriously, there is high uncertainty in the extent to which the direct effects of CO2 rise on plant physiology will interact with climate change in affecting productivity. At present, the aggregate impacts of climate change on global-scale agricultural productivity cannot be reliably quantified. PMID:20713397

How Novel are 21st Century Climates? A Global Assessment of Future Climates and their Analogs Back Through the Eocene

NASA Astrophysics Data System (ADS)

Burke, K. D.; Williams, J. W.; Jackson, S. T.

2016-12-01

Climate change is a multivariate process, where changes in the environmental space of a location will likely drive biotic responses of the flora and fauna that inhabit the region. In the face of a rapidly changing climate it is important to understand what the future may hold for ecosystems. One method commonly applied to understand how dissimilar future climates will be relative to the modern period is no-analog analysis. This has been done for 21st century climates relative to the modern period, but has not been extended through the paleorecord. Using HadCM3, CCSM3 TraCE-21ka, PMIP3, PlioMIP2 and EoMIP climate simulations, we assess global and regional climatic novelty by identifying the closest analogs in these periods for both future (21st century) and modern climates. This baseline offers a full range climate space with significant overlap of modern and future projected climates, and allows us to assess both emergences and disappearances of analog climate conditions throughout the past. This extended baseline includes past glacial and interglacial climates, as well as past earth warm periods. Past earth warm periods such as the middle to late Pliocene and the early Eocene may be most similar to projections of future climate, so it is important to evaluate our understanding of these global climates. Here we calculate dissimilarity to quantify novelty and no-analog conditions using the Standardized Euclidian Distance, as well as the Mahalanobis distance. Our work shows that nearest climate analogs for the modern period, as well as future climates, existed and disappeared during past warm periods. These results suggest that though climate change may be regionally novel relative to the modern period for some locations, analogs do exist through the paleorecord which in some cases reduce novelty. Nevertheless, novelty remains high in some locations suggesting that some future climates may be unprecedented.

Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography

NASA Astrophysics Data System (ADS)

Crossman, J.; Futter, M. N.; Whitehead, P. G.; Stainsby, E.; Baulch, H. M.; Jin, L.; Oni, S. K.; Wilby, R. L.; Dillon, P. J.

2014-07-01

Hydrological processes determine the transport of nutrients and passage of diffuse pollution. Consequently, catchments are likely to exhibit individual hydrochemical responses (sensitivities) to climate change, which is expected to alter the timing and amount of runoff, and to impact in-stream water quality. In developing robust catchment management strategies and quantifying plausible future hydrochemical conditions it is therefore equally important to consider the potential for spatial variability in, and causal factors of, catchment sensitivity, as to explore future changes in climatic pressures. This study seeks to identify those factors which influence hydrochemical sensitivity to climate change. A perturbed physics ensemble (PPE), derived from a series of Global Climate Model (GCM) variants with specific climate sensitivities was used to project future climate change and uncertainty. Using the Integrated Catchment Model of Phosphorus Dynamics (INCA-P), we quantified potential hydrochemical responses in four neighbouring catchments (with similar land use but varying topographic and geological characteristics) in southern Ontario, Canada. Responses were assessed by comparing a 30 year baseline (1968-1997) to two future periods: 2020-2049 and 2060-2089. Although projected climate change and uncertainties were similar across these catchments, hydrochemical responses (sensitivity) were highly varied. Sensitivity was governed by soil type (influencing flow pathways) and nutrient transport mechanisms. Clay-rich catchments were most sensitive, with total phosphorus (TP) being rapidly transported to rivers via overland flow. In these catchments large annual reductions in TP loads were projected. Sensitivity in the other two catchments, dominated by sandy-loams, was lower due to a larger proportion of soil matrix flow, longer soil water residence times and seasonal variability in soil-P saturation. Here smaller changes in TP loads, predominantly increases, were projected. These results suggest that the clay content of soils could be a good indicator of the sensitivity of catchments to climatic input, and reinforces calls for catchment-specific management plans.

Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography

NASA Astrophysics Data System (ADS)

Crossman, J.; Futter, M. N.; Whitehead, P. G.; Stainsby, E.; Baulch, H. M.; Jin, L.; Oni, S. K.; Wilby, R. L.; Dillon, P. J.

2014-12-01

Hydrological processes determine the transport of nutrients and passage of diffuse pollution. Consequently, catchments are likely to exhibit individual hydrochemical responses (sensitivities) to climate change, which are expected to alter the timing and amount of runoff, and to impact in-stream water quality. In developing robust catchment management strategies and quantifying plausible future hydrochemical conditions it is therefore equally important to consider the potential for spatial variability in, and causal factors of, catchment sensitivity, as it is to explore future changes in climatic pressures. This study seeks to identify those factors which influence hydrochemical sensitivity to climate change. A perturbed physics ensemble (PPE), derived from a series of global climate model (GCM) variants with specific climate sensitivities was used to project future climate change and uncertainty. Using the INtegrated CAtchment model of Phosphorus dynamics (INCA-P), we quantified potential hydrochemical responses in four neighbouring catchments (with similar land use but varying topographic and geological characteristics) in southern Ontario, Canada. Responses were assessed by comparing a 30 year baseline (1968-1997) to two future periods: 2020-2049 and 2060-2089. Although projected climate change and uncertainties were similar across these catchments, hydrochemical responses (sensitivities) were highly varied. Sensitivity was governed by quaternary geology (influencing flow pathways) and nutrient transport mechanisms. Clay-rich catchments were most sensitive, with total phosphorus (TP) being rapidly transported to rivers via overland flow. In these catchments large annual reductions in TP loads were projected. Sensitivity in the other two catchments, dominated by sandy loams, was lower due to a larger proportion of soil matrix flow, longer soil water residence times and seasonal variability in soil-P saturation. Here smaller changes in TP loads, predominantly increases, were projected. These results suggest that the clay content of soils could be a good indicator of the sensitivity of catchments to climatic input, and reinforces calls for catchment-specific management plans.

Cropping and tillage systems effects on soil erosion under climate change in Oklahoma

USDA-ARS?s Scientific Manuscript database

Soil erosion under future climate change is very likely to increase due to projected increases in frequency and magnitude of heavy storms. The objective of this study is to quantify the effects of common cropping and tillage systems on soil erosion and surface runoff during 2010-2039 in central Okl...

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

Treesearch

S. Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter Caldwell; K. Duan; Y. Zhang

2015-01-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model)...

Changes in groundwater recharge under projected climate in the upper Colorado River basin

USGS Publications Warehouse

Tillman, Fred; Gangopadhyay, Subhrendu; Pruitt, Tom

2016-01-01

Understanding groundwater-budget components, particularly groundwater recharge, is important to sustainably manage both groundwater and surface water supplies in the Colorado River basin now and in the future. This study quantifies projected changes in upper Colorado River basin (UCRB) groundwater recharge from recent historical (1950–2015) through future (2016–2099) time periods, using a distributed-parameter groundwater recharge model with downscaled climate data from 97 Coupled Model Intercomparison Project Phase 5 climate projections. Simulated future groundwater recharge in the UCRB is generally expected to be greater than the historical average in most decades. Increases in groundwater recharge in the UCRB are a consequence of projected increases in precipitation, offsetting reductions in recharge that would result from projected increased temperatures.

Using changes in agricultural utility to quantify future climate-induced risk to conservation.

PubMed

Estes, Lyndon D; Paroz, Lydie-Line; Bradley, Bethany A; Green, Jonathan M H; Hole, David G; Holness, Stephen; Ziv, Guy; Oppenheimer, Michael G; Wilcove, David S

2014-04-01

Much of the biodiversity-related climate change impacts research has focused on the direct effects to species and ecosystems. Far less attention has been paid to the potential ecological consequences of human efforts to address the effects of climate change, which may equal or exceed the direct effects of climate change on biodiversity. One of the most significant human responses is likely to be mediated through changes in the agricultural utility of land. As farmers adapt their practices to changing climates, they may increase pressure on some areas that are important to conserve (conservation lands) whereas lessening it on others. We quantified how the agricultural utility of South African conservation lands may be altered by climate change. We assumed that the probability of an area being farmed is linked to the economic benefits of doing so, using land productivity values to represent production benefit and topographic ruggedness as a proxy for costs associated with mechanical workability. We computed current and future values of maize and wheat production in key conservation lands using the DSSAT4.5 model and 36 crop-climate response scenarios. Most conservation lands had, and were predicted to continue to have, low agricultural utility because of their location in rugged terrain. However, several areas were predicted to maintain or gain high agricultural utility and may therefore be at risk of near-term or future conversion to cropland. Conversely, some areas were predicted to decrease in agricultural utility and may therefore prove easier to protect from conversion. Our study provides an approximate but readily transferable method for incorporating potential human responses to climate change into conservation planning. © 2013 Society for Conservation Biology.

Forecasting Western U.S. Snowpack

NASA Astrophysics Data System (ADS)

Kapnick, S. B.; Yang, X.; Vecchi, G. A.; Delworth, T. L.; Gudgel, R.; Malyshev, S.; Milly, C.; Shevliakova, E.; Underwood, S.; Margulis, S. A.

2017-12-01

Cold season mountain snow accumulation in the western United States plays a critical role in regional hydroclimate and water supply. While climate projections provide estimates of future snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions and hazards out to two weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), particularly beyond 6 months. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate our dynamical system's feasibility of seasonal snowpack predictions and quantify the limits of predictive skill more than 2 seasons in advance for snowpack—snow that accumulates on the ground in the mountains. Our ability to predict snowpack is reliant on both temperature and precipitation prediction skill modulating both the amount of frozen precipitation that falls and how much snow accumulates and stays on the ground throughout the season. We will quantify prediction skill and outline areas necessary for the future advancement of seasonal hydroclimate prediction.

Quantifying density-independent mortality of temperate tree species

Treesearch

Heather E Lintz; Andrew N. Gray; Andrew Yost; Richard Sniezko; Chris Woodall; Matt Reilly; Karen Hutten; Mark Elliott

2016-01-01

Forest resilience to climate change is a topic of national concern as our standing assets and future forestsare important to our livelihood. Many tree species are predicted to decline or disappear while othersmay be able to adapt or migrate. Efforts to quantify and disseminate the current condition of forests areurgently needed to guide management and policy. Here, we...

Impacts of elevated CO2 concentration on the productivity and surface energy budget of the soybean and maize agroecosystem in the Midwest US

USDA-ARS?s Scientific Manuscript database

The physiological response of vegetation to increasing atmospheric carbon dioxide concentration ([CO2]) modifies productivity and surface energy and water fluxes. Quantifying this response is required for assessments of future climate change. Many global climate models account for this response; how...

Effects of cropping and tillage systems on soil erosion under climate change in Oklahoma

USDA-ARS?s Scientific Manuscript database

Soil erosion under future climate change is very likely to increase due to projected increases in frequency and magnitude of heavy storms. The objective of this study is to quantify the effects of common cropping and tillage systems on soil erosion and surface runoff during 2010-2039 in central Okl...

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Using AQUACROP to model the impacts of future climates on crop production and possible adaptation strategies in Sardinia and Tunisia

NASA Astrophysics Data System (ADS)

Bird, Neil; Benabdallah, Sihem; Gouda, Nadine; Hummel, Franz; La Jeunesse, Isabelle; Meyer, Swen; Soddu, Antonino; Woess-Gallasch, Susanne

2014-05-01

A work package in the FP-7 funded CLIMB Project - Climate Induced Changes on the Hydrology of Mediterranean Basins Reducing Uncertainty and Quantifying Risk through an Integrated Monitoring and Modeling System had the goal of assessing socioeconomic vulnerability in two super-sites in future climates (2040-2070). The work package had deliverables to describe of agricultural adaptation measures appropriate to each site under future water availability scenarios and assess the risk of income losses due to water shortages in agriculture. The FAO model AQUACROP was used to estimate losses of agricultural productivity and indicate possible adaptation strategies. The presentation will focus on two interesting crops which show extreme vulnerability to expected changes in climate; irrigated lettuce in Sardinia and irrigated tomatoes in Tunisia. Modelling methodology, results and possible adaptation strategies will be presented.

Uncertainty in future projections of global and regional marine fisheries catches

NASA Astrophysics Data System (ADS)

Reygondeau, G.; Cheung, W. W. L.; Froelicher, T. L.; Stock, C. A.; Jones, M. C.; Sarmiento, J. L.

2016-02-01

Previous studies have projected the global redistribution of potential marine fisheries catches by mid-21st century under climate change, with increases in high latitude regions and pronounced decreases in tropical biomes. However, quantified confidence levels of such projections are not available, rendering it difficult to interpret the associated risk to society. This paper quantifies the confidence of changes in future fish production using a 30-member ensemble simulation of the Geophysical Fluid Dynamics Laboratory ESM2M (representing internal variability of oceanographic conditions), three structural variants of a mechanistic species distribution model (representing uncertainty in fisheries models and different greenhouse gas emission and fishing scenarios (representing scenario uncertainty). We project that total potential catches of 500 exploited fish and invertebrate stocks, that contribute most to regional fisheries catches and their variability, will likely decrease in the 21st century under a `business-as-usual' greenhouse gas emission scenario (RCP8.5). Fishing and it's management remains a main factor determining future fish stocks and their catches. Internal variability of projected ocean conditions, including temperature, oxygen level, pH, net primary production and sea ice contributes substantially to the uncertainty of potential catch projections. Regionally, climate-driven decreases in potential catches in tropical oceans and increases in the Arctic polar regions are projected with higher confidence than other regions, while the direction of changes in most mid-latitude (or temperate) regions is uncertain. Under a stringent greenhouse gas mitigation scenario (RCP 2.6), climate change impacts on potential catches may not emerge from their uncertainties. Overall, this study provides a foundation for quantifying risks of climate change impacts on marine fisheries globally and regionally, and how such risk may be altered by policy interventions.

Uncertainty Quantification in Climate Modeling and Projection

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

Qian, Yun; Jackson, Charles; Giorgi, Filippo

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes.

PubMed

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2017-11-01

Currently, the temperate forest biome cools the earth's climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (-10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems.

An uncertainty-based framework to quantifying climate change impacts on coastal flood vulnerability: case study of New York City.

PubMed

Zahmatkesh, Zahra; Karamouz, Mohammad

2017-10-17

The continued development efforts around the world, growing population, and the increased probability of occurrence of extreme hydrologic events have adversely affected natural and built environments. Flood damages and loss of lives from the devastating storms, such as Irene and Sandy on the East Coast of the USA, are examples of the vulnerability to flooding that even developed countries have to face. The odds of coastal flooding disasters have been increased due to accelerated sea level rise, climate change impacts, and communities' interest to live near the coastlines. Climate change, for instance, is becoming a major threat to sustainable development because of its adverse impacts on the hydrologic cycle. Effective management strategies are thus required for flood vulnerability reduction and disaster preparedness. This paper is an extension to the flood resilience studies in the New York City coastal watershed. Here, a framework is proposed to quantify coastal flood vulnerability while accounting for climate change impacts. To do so, a multi-criteria decision making (MCDM) approach that combines watershed characteristics (factors) and their weights is proposed to quantify flood vulnerability. Among the watershed characteristics, potential variation in the hydrologic factors under climate change impacts is modeled utilizing the general circulation models' (GCMs) outputs. The considered factors include rainfall, extreme water level, and sea level rise that exacerbate flood vulnerability through increasing exposure and susceptibility to flooding. Uncertainty in the weights as well as values of factors is incorporated in the analysis using the Monte Carlo (MC) sampling method by selecting the best-fitted distributions to the parameters with random nature. A number of low impact development (LID) measures are then proposed to improve watershed adaptive capacity to deal with coastal flooding. Potential range of current and future vulnerability to flooding is estimated with and without consideration of climate change impacts and after implementation of LIDs. Results show that climate change has the potential to increase rainfall intensity, flood volume, floodplain extent, and flood depth in the watershed. The results also reveal that improving system resilience by reinforcing the adaptation capacity through implementing LIDs could mitigate flood vulnerability. Moreover, the results indicate the significant effect of uncertainties, arising from the factors' weights as well as climate change, impacts modeling approach, on quantifying flood vulnerability. This study underlines the importance of developing applicable schemes to quantify coastal flood vulnerability for evolving future responses to adverse impacts of climate change.

Assessing the role of internal climate variability in Antarctica's contribution to future sea-level rise

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2017-12-01

The Antarctic ice sheet (AIS) has the potential to be a major contributor to future sea-level rise (SLR). Current projections of SLR due to AIS mass loss remain highly uncertain. Better understanding of how ice sheets respond to future climate forcing and variability is essential for assessing the long-term risk of SLR. However, the predictability of future climate is limited by uncertainties from emission scenarios, model structural differences, and the internal variability that is inherently generated within the fully coupled climate system. Among those uncertainties, the impact of internal variability on the AIS changes has not been explicitly assessed. In this study, we quantify the effect of internal variability on the AIS evolutions by using climate fields from two large-ensemble experiments using the Community Earth System Model to force a three-dimensional ice sheet model. We find that internal variability of climate fields, particularly atmospheric fields, among ensemble members leads to significantly different AIS responses. Our results show that the internal variability can cause about 80 mm differences of AIS contribution to SLR by 2100 compared to the ensemble-mean contribution of 380-450 mm. Moreover, using ensemble-mean climate fields as the forcing in the ice sheet model does not produce realistic simulations of the ice loss. Instead, it significantly delays the onset of retreat of the West Antarctic Ice Sheet for up to 20 years and significantly underestimates the AIS contribution to SLR by 0.07-0.11 m in 2100 and up to 0.34 m in the 2250's. Therefore, because the uncertainty caused by internal variability is irreducible, we seek to highlight a critical need to assess the role of internal variability in projecting the AIS loss over the next few centuries. By quantifying the impact of internal variability on AIS contribution to SLR, policy makers can obtain more robust estimates of SLR and implement suitable adaptation strategies.

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Assessing uncertainties in land cover projections.

PubMed

Alexander, Peter; Prestele, Reinhard; Verburg, Peter H; Arneth, Almut; Baranzelli, Claudia; Batista E Silva, Filipe; Brown, Calum; Butler, Adam; Calvin, Katherine; Dendoncker, Nicolas; Doelman, Jonathan C; Dunford, Robert; Engström, Kerstin; Eitelberg, David; Fujimori, Shinichiro; Harrison, Paula A; Hasegawa, Tomoko; Havlik, Petr; Holzhauer, Sascha; Humpenöder, Florian; Jacobs-Crisioni, Chris; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Lavalle, Carlo; Lenton, Tim; Liu, Jiayi; Meiyappan, Prasanth; Popp, Alexander; Powell, Tom; Sands, Ronald D; Schaldach, Rüdiger; Stehfest, Elke; Steinbuks, Jevgenijs; Tabeau, Andrzej; van Meijl, Hans; Wise, Marshall A; Rounsevell, Mark D A

2017-02-01

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. © 2016 John Wiley & Sons Ltd.

Response of North American freshwater lakes to simulated future climates

USGS Publications Warehouse

Hostetler, S.W.; Small, E.E.

1999-01-01

We apply a physically based lake model to assess the response of North American lakes to future climate conditions as portrayed by the transient trace-gas simulations conducted with the Max Planck Institute (ECHAM4) and the Canadian Climate Center (CGCM1) atmosphere-ocean general circulation models (A/OGCMs). To quantify spatial patterns of lake responses (temperature, mixing, ice cover, evaporation) we ran the lake model for theoretical lakes of specified area, depth, and transparency over a uniformly spaced (50 km) grid. The simulations were conducted for two 10-year periods that represent present climatic conditions and those around the time of CO2 doubling. Although the climate model output produces simulated lake responses that differ in specific regional details, there is broad agreement with regard to the direction and area of change. In particular, lake temperatures are generally warmer in the future as a result of warmer climatic conditions and a substantial loss (> 100 days/yr) of winter ice cover. Simulated summer lake temperatures are higher than 30??C ever the Midwest and south, suggesting the potential for future disturbance of existing aquatic ecosystems. Overall increases in lake evaporation combine with disparate changes in A/OGCM precipitation to produce future changes in net moisture (precipitation minus evaporation) that are of less fidelity than those of lake temperature.

Future Water Management in the South Platte River Basin: Impacts of Hydraulic Fracturing, Population, Agriculture, and Climate Change in a Semi-Arid Region.

NASA Astrophysics Data System (ADS)

Walker, E. L.; Hogue, T. S.; Anderson, A. M.; Read, L.

2015-12-01

In semi-arid basins across the world, the gap between water supply and demand is growing due to climate change, population growth, and shifts in agriculture and unconventional energy development. Water conservation efforts among residential and industrial water users, recycling and reuse techniques and innovative regulatory frameworks for water management strive to mitigate this gap, however, the extent of these strategies are often difficult to quantify and not included in modeling water allocations. Decision support systems (DSS) are purposeful for supporting water managers in making informed decisions when competing demands create the need to optimize water allocation between sectors. One region of particular interest is the semi-arid region of the South Platte River basin in northeastern Colorado, where anthropogenic and climatic effects are expected to increase the gap between water supply and demand in the near future. Specifically, water use in the South Platte is impacted by several high-intensity activities, including unconventional energy development, i.e. hydraulic fracturing, and large withdrawals for agriculture; these demands are in addition to a projected population increase of 100% by 2050. The current work describes the development of a DSS for the South Platte River basin, using the Water Evaluation and Planning system software (WEAP) to explore scenarios of how variation in future water use in the energy, agriculture, and municipal sectors will impact water allocation decisions. Detailed data collected on oil and gas water use in the Niobrara shale play will be utilized to predict future sector use. We also employ downscaled climate projections for the region to quantify the potential range of water availability in the basin under each scenario, and observe whether or not, and to what extent, climate may impact management decisions at the basin level.

Data informatics for the Detection, Characterization, and Attribution of Climate Extremes

NASA Astrophysics Data System (ADS)

Collins, W.; Wehner, M. F.; O'Brien, T. A.; Paciorek, C. J.; Krishnan, H.; Johnson, J. N.; Prabhat, M.

2015-12-01

The potential for increasing frequency and intensity of extremephenomena including downpours, heat waves, and tropical cyclonesconstitutes one of the primary risks of climate change for society andthe environment. The challenge of characterizing these risks is thatextremes represent the "tails" of distributions of atmosphericphenomena and are, by definition, highly localized and typicallyrelatively transient. Therefore very large volumes of observationaldata and projections of future climate are required to quantify theirproperties in a robust manner. Massive data analytics are required inorder to detect individual extremes, accumulate statistics on theirproperties, quantify how these statistics are changing with time, andattribute the effects of anthropogenic global warming on thesestatistics. We describe examples of the suite of techniques the climate communityis developing to address these analytical challenges. The techniquesinclude massively parallel methods for detecting and trackingatmospheric rivers and cyclones; data-intensive extensions togeneralized extreme value theory to summarize the properties ofextremes; and multi-model ensembles of hindcasts to quantify theattributable risk of anthropogenic influence on individual extremes.We conclude by highlighting examples of these methods developed by ourCASCADE (Calibrated and Systematic Characterization, Attribution, andDetection of Extremes) project.

Potential Impacts of Future Climate Change on Regional Air Quality and Public Health over China

NASA Astrophysics Data System (ADS)

Hong, C.; Zhang, Q.; Zhang, Y.; He, K.

2017-12-01

Future climate change would affect public health through changing air quality. Climate extremes and poor weather conditions are likely to occur at a higher frequency in China under a changing climate, but the air pollution-related health impacts due to future climate change remain unclear. Here the potential impacts of future climate change on regional air quality and public health over China is projected using a coupling of climate, air quality and epidemiological models. We present the first assessment of China's future air quality in a changing climate under the Representative Concentration Pathway 4.5 (RCP4.5) scenario using the dynamical downscaling technique. In RCP4.5 scenario, we estimate that climate change from 2006-2010 to 2046-2050 is likely to adversely affect air quality covering more than 86% of population and 55% of land area in China, causing an average increase of 3% in O3 and PM2.5 concentrations, which are found to be associated with the warmer climate and the more stable atmosphere. Our estimate of air pollution-related mortality due to climate change in 2050 is 26,000 people per year in China. Of which, the PM2.5-related mortality is 18,700 people per year, and the O3-related mortality is 7,300 people per year. The climate-induced air pollution and health impacts vary spatially. The climate impacts are even more pronounced on the urban areas where is densely populated and polluted. 90% of the health loss is concentrated in 20% of land areas in China. We use a simple statistical analysis method to quantify the contributions of climate extremes and find more intense climate extremes play an important role in climate-induced air pollution-related health impacts. Our results indicate that global climate change will likely alter the level of pollutant management required to meet future air quality targets as well as the efforts to protect public health in China.

The impact of changing climate conditions on the hydrological behavior of several Mediterranean sub-catchments in Crete

NASA Astrophysics Data System (ADS)

Eirini Vozinaki, Anthi; Tapoglou, Evdokia; Tsanis, Ioannis

2017-04-01

Climate change, although is already happening, consists of a big threat capable of causing lots of inconveniences in future societies and their economies. In this work, the climate change impact on the hydrological behavior of several Mediterranean sub-catchments, in Crete, is presented. The sensitivity of these hydrological systems to several climate change scenarios is also provided. The HBV hydrological model has been used, calibrated and validated for the study sub-catchments against measured weather and streamflow data and inputs. The impact of climate change on several hydro-meteorological parameters (i.e. precipitation, streamflow etc.) and hydrological signatures (i.e. spring flood peak, length and volume, base flow, flow duration curves, seasonality etc.) have been statistically elaborated and analyzed, defining areas of increased probability risk associated additionally to flooding or drought. The potential impacts of climate change on current and future water resources have been quantified by driving HBV model with current and future scenarios, respectively, for specific climate periods. This work aims to present an integrated methodology for the definition of future climate and hydrological risks and the prediction of future water resources behavior. Future water resources management could be rationally effectuated, in Mediterranean sub-catchments prone to drought or flooding, using the proposed methodology. The research reported in this paper was fully supported by the Project "Innovative solutions to climate change adaptation and governance in the water management of the Region of Crete - AQUAMAN" funded within the framework of the EEA Financial Mechanism 2009-2014.

Methane Feedbacks to the Global Climate System in a Warmer World

NASA Astrophysics Data System (ADS)

Dean, Joshua F.; Middelburg, Jack J.; Röckmann, Thomas; Aerts, Rien; Blauw, Luke G.; Egger, Matthias; Jetten, Mike S. M.; de Jong, Anniek E. E.; Meisel, Ove H.; Rasigraf, Olivia; Slomp, Caroline P.; in't Zandt, Michiel H.; Dolman, A. J.

2018-03-01

Methane (CH4) is produced in many natural systems that are vulnerable to change under a warming climate, yet current CH4 budgets, as well as future shifts in CH4 emissions, have high uncertainties. Climate change has the potential to increase CH4 emissions from critical systems such as wetlands, marine and freshwater systems, permafrost, and methane hydrates, through shifts in temperature, hydrology, vegetation, landscape disturbance, and sea level rise. Increased CH4 emissions from these systems would in turn induce further climate change, resulting in a positive climate feedback. Here we synthesize biological, geochemical, and physically focused CH4 climate feedback literature, bringing together the key findings of these disciplines. We discuss environment-specific feedback processes, including the microbial, physical, and geochemical interlinkages and the timescales on which they operate, and present the current state of knowledge of CH4 climate feedbacks in the immediate and distant future. The important linkages between microbial activity and climate warming are discussed with the aim to better constrain the sensitivity of the CH4 cycle to future climate predictions. We determine that wetlands will form the majority of the CH4 climate feedback up to 2100. Beyond this timescale, CH4 emissions from marine and freshwater systems and permafrost environments could become more important. Significant CH4 emissions to the atmosphere from the dissociation of methane hydrates are not expected in the near future. Our key findings highlight the importance of quantifying whether CH4 consumption can counterbalance CH4 production under future climate scenarios.

Comparative Synthesis of Current and Future Urban Stormwater Runoff Scenarios in Tampa Bay Basin under a Changing Climate

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2016-12-01

Changes in climatic regimes and basin characteristics such as imperviousness, roughness and land use types would lead to potential changes in stormwater budget. In this study we quantified reference sensitivities of stormwater runoff to the potential climatic and land use/cover changes by developing a large-scale, mechanistic rainfall-runoff model for the Tampa Bay Basin of Florida using the US EPA Storm Water Management Model (SWMM 5.1). Key processes of urban hydrology, its dynamic interactions with groundwater and sea level, hydro-climatic variables and land use/cover characteristics were incorporated within the model. The model was calibrated and validated with historical streamflow data. We then computed the historical (1970-2000) and potential 2050s stormwater budgets for the Tampa Bay Basin. Climatic scenario projected by the global climate models (GCMs) and the regional climate models (RCMs), along with sea level and land use/cover projections, were utilized to anticipate the future stormwater budget. The comparative assessment of current and future stormwater scenario will aid a proactive management of stormwater runoff under a changing climate in the Tampa Bay Basin and similar urban basins around the world.

When will we be committed to crossing 1.5 and 2 °C temperature thresholds?

NASA Astrophysics Data System (ADS)

Armour, K.; Proistosescu, C.; Roe, G.; Huybers, P. J.

2017-12-01

The zero-emissions climate commitment is a key metric for science and policy. It is the future warming we face given only to-date emissions, independent of future human influence on climate. Following a cessation of emissions, future global temperature change depends on (i) the atmospheric lifetimes of aerosols and greenhouse gases (GHGs), and (ii) the physical climate response to radiative forcing (Armour and Roe 2011). The cooling effect of aerosols diminishes within weeks; GHG concentrations get drawn down on timescales ranging from months to millennia; and ocean heat uptake diminishes as climate equilibrates with the residual CO2 forcing. Whether global temperature increases, stays stable, or declines following emission cessation depends on these competing factors. There is substantial uncertainty in the zero-emissions commitment due to a combination of (i) correlated uncertainties in aerosol radiative forcing and climate sensitivity, (ii) uncertainty in the atmospheric lifetime of CO2, and (iii) uncertainty in how climate sensitivity will evolve in the future. Here we quantify climate commitment in a Bayesian framework of an idealized model constrained by observations of global warming and energy imbalance, combined with estimates of global radiative forcing. At present, our committed warming is 1.2°C (median), with a 25% chance that it already exceeds 1.5°C and a 5% chance that it exceeds 2°C; the range comes primarily from uncertainty in the degree to which aerosols currently mask GHG forcing. We further quantify how climate commitment, and its uncertainty, changes with emissions scenario and over time. Under high emissions (RCP8.5), we will reach a >50% risk of a 2°C zero-emission climate commitment by the year 2035, about two decades before that temperature would be reached if emissions continued unabated. Committed warming is substantially reduced for lower-emissions scenarios, depending on the mix of aerosol and GHG mitigation. For the next few decades the primary uncertainty in climate commitment comes from correlated uncertainties in aerosol forcing and climate sensitivity; later in the century it comes from uncertainties in the carbon cycle (setting the lifetime and residual concentration of CO2) and in how climate sensitivity changes over time.

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.

Identifying traits for genotypic adaptation using crop models.

PubMed

Ramirez-Villegas, Julian; Watson, James; Challinor, Andrew J

2015-06-01

Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Quantifying Terrestrial Ecosystem Carbon Stocks for Future GHG Mitigation, Sustainable Land-Use Planning and Adaptation to Climate Change in Quebec, Canada.

NASA Astrophysics Data System (ADS)

Garneau, M.; van Bellen, S.

2016-12-01

Based on various databases, carbon stocks of terrestrial ecosystems in the boreal and arctic biomes of Quebec were quantified as part of an evaluation of their capacity to mitigate anthropogenic greenhouse gas (GHG) emissions and estimate their vulnerability with respect to recent climate change and land use changes. The results of this project are contributing to the establishment of the Strategy for Climate Change Adaptation as well as the 2013-2020 Climate Change Action Plan of the Quebec Ministry of Environment, which aim to adapt the Quebec society to the effects of climate change and the reduction of GHG emissions. The total carbon stock of the soils of the forest and peatland ecosystems of Quebec was quantified at 18.00 Gt C or 66.0 Gt CO2-equivalent, of which 95% corresponds to the boreal and arctic regions. The mean carbon mass per unit area (kg C m-2) of peatlands is about nine times higher than that of forests, with values of 100,0 kg C m-2 for peatlands and 10,9 kg C m-2 for forest stands. In 2013, total anthropogenic emissions in Quebec were quantified at 82.6 Mt CO2-equivalent (Environment Canada, 2015), or 1.25‰ of the total Quebec ecosystem carbon stock. The total stock thus represents the equivalent of about 800 years of anthropogenic emissions at the current rate, divided between 478 years for peatlands and 321 years for forest soils. Future GHG mitigation policies and sustainable land-use planning should be supported by scientific data on terrestrial ecosystems carbon stocks. An increase in investments in peatland, wetland and forest conservation, management and rehabilitation may contribute to limit greenhouse gas emissions. It is therefore essential, that, following the objectives of multiple international organisations, the management of terrestrial carbon stocks becomes part of the national engagement to reduce GHG emissions.

The effect of future outdoor air pollution on human health and the contribution of climate change

NASA Astrophysics Data System (ADS)

Silva, R.; West, J. J.; Lamarque, J.; Shindell, D.; Collins, W.; Dalsoren, S. B.; Faluvegi, G. S.; Folberth, G.; Horowitz, L. W.; Nagashima, T.; Naik, V.; Rumbold, S.; Skeie, R.; Sudo, K.; Takemura, T.; Bergmann, D. J.; Cameron-Smith, P. J.; Cionni, I.; Doherty, R. M.; Eyring, V.; Josse, B.; MacKenzie, I. A.; Plummer, D.; Righi, M.; Stevenson, D. S.; Strode, S. A.; Szopa, S.; Zeng, G.

2013-12-01

At present, exposure to outdoor air pollution from ozone and fine particulate matter (PM2.5) causes over 2 million deaths per year, due to respiratory and cardiovascular diseases and lung cancer. Future ambient concentrations of ozone and PM2.5 will be affected by both air pollutant emissions and climate change. Here we estimate the potential impact of future outdoor air pollution on premature human mortality, and isolate the contribution of future climate change due to its effect on air quality. We use modeled present-day (2000) and future global ozone and PM2.5 concentrations from simulations with an ensemble of chemistry-climate models from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Future air pollution was modeled for global greenhouse gas and air pollutant emissions in the four IPCC AR5 Representative Concentration Pathway (RCP) scenarios, for 2030, 2050 and 2100. All model outputs are regridded to a common 0.5°x0.5° horizontal resolution. Future premature mortality is estimated for each RCP scenario and year based on changes in concentrations of ozone and PM2.5 relative to 2000. Using a health impact function, changes in concentrations for each RCP scenario are combined with future population and cause-specific baseline mortality rates as projected by a single independent scenario in which the global incidence of cardiopulmonary diseases is expected to increase. The effect of climate change is isolated by considering the difference between air pollutant concentrations from simulations with 2000 emissions and a future year climate and simulations with 2000 emissions and climate. Uncertainties in the results reflect the uncertainty in the concentration-response function and that associated with variability among models. Few previous studies have quantified the effects of future climate change on global human health via changes in air quality, and this is the first such study to use an ensemble of global models.

A probabilistic framework for assessing vulnerability to climate variability and change: The case of the US water supply system

Treesearch

Romano Foti; Jorge A. Ramirez; Thomas C. Brown

2014-01-01

We introduce a probabilistic framework for vulnerability analysis and use it to quantify current and future vulnerability of the US water supply system. We also determine the contributions of hydro-climatic and socio-economic drivers to the changes in projected vulnerability. For all scenarios and global climatemodels examined, the US Southwest including California and...

Impact of lakes and wetlands on present and future boreal climate

NASA Astrophysics Data System (ADS)

Poutou, E.; Krinner, G.; Genthon, C.

2002-12-01

Impact of lakes and wetlands on present and future boreal climate The role of lakes and wetlands in present-day high latitude climate is quantified using a general circulation model of the atmosphere. The atmospheric model includes a lake module which is presented and validated. Seasonal and spatial wetland distribution is calculated as a function of the hydrological budget of the wetlands themselves and of continental soil whose runoff feeds them. Wetland extent is simulated and discussed both in simulations forced by observed climate and in general circulation model simulations. In off-line simulations, forced by ECMWF reanalyses, the lake model simulates correctly observed lake ice durations, while the wetland extent is somewhat underestimated in the boreal regions. Coupled to the general circulation model, the lake model yields satisfying ice durations, although the climate model biases have impacts on the modeled lake ice conditions. Boreal wetland extents are overestimated in the general circulation model as simulated precipitation is too high. The impact of inundated surfaces on the simulated climate is strongest in summer when these surfaces are ice-free. Wetlands seem to play a more important role than lakes in cooling the boreal regions in summer and in humidifying the atmosphere. The role of lakes and wetlands in future climate change is evaluated by analyzing simulations of present and future climate with and without prescribed inland water bodies.

A methodological framework to assess PMP and PMF in snow-dominated watersheds under changing climate conditions - A case study of three watersheds in Québec (Canada)

NASA Astrophysics Data System (ADS)

Rouhani, Hassan; Leconte, Robert

2018-06-01

Climate change will affect precipitation and flood regimes. It is anticipated that the Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) will be modified in a changing climate. This paper aims to quantify and analyze climate change influences on PMP and PMF in three watersheds with different climatic conditions across the province of Québec, Canada. Output data from the Canadian Regional Climate Model (CRCM) was used to estimate PMP and Probable Maximum Snow Accumulation (PMSA) in future climate projections, which was then used to force the SWAT hydrological model to estimate PMF. PMP and PMF values were estimated for two time horizons each spanning 30 years: 1961-1990 (recent past) and 2041-2070 (future). PMP and PMF were separately analyzed for two seasons: summer-fall and spring. Results show that PMF in the watershed located in southern Québec would remain unchanged in the future horizon, but the trend for the watersheds located in the northeastern and northern areas of the province is an increase of up to 11%.

Implementation Targets for the Paris Climate Agreement

NASA Astrophysics Data System (ADS)

Bennett, B.; Hope, A. P.; Tribett, W. R.; Salawitch, R. J.; Canty, T. P.

2016-12-01

We provide an overview of reductions in the emission of greenhouse gases (GHGs) needed to achieve either the target (1.5 °C warming) or upper limit (2.0 °C warming) of the Paris Climate Agreement. We will show how much energy must be produced, either by renewables that do not emit significant levels of atmospheric GHGs or via carbon capture and sequestration (CCS) coupled to fossil fuel power plants, to meet forecast global energy demand out to 2060. These projections will be based on two modeling frameworks: our empirical model of global climate (EM-GC) and the CMIP 5 GCMs used throughout IPCC (2013). For each framework, we will show estimates of transient climate response to cumulative emission of carbon to place limits on future emission of CO2 via the combustion of fossil fuel. We will also quantify the impact of future atmospheric CH4 on achieving the goals of the Paris Climate Agreement.

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

Methodology to assess and map the potential development of forest ecosystems exposed to climate change and atmospheric nitrogen deposition: A pilot study in Germany.

PubMed

Schröder, Winfried; Nickel, Stefan; Jenssen, Martin; Riediger, Jan

2015-07-15

A methodology for mapping ecosystems and their potential development under climate change and atmospheric nitrogen deposition was developed using examples from Germany. The methodology integrated data on vegetation, soil, climate change and atmospheric nitrogen deposition. These data were used to classify ecosystem types regarding six ecological functions and interrelated structures. Respective data covering 1961-1990 were used for reference. The assessment of functional and structural integrity relies on comparing a current or future state with an ecosystem type-specific reference. While current functions and structures of ecosystems were quantified by measurements, potential future developments were projected by geochemical soil modelling and data from a regional climate change model. The ecosystem types referenced the potential natural vegetation and were mapped using data on current tree species coverage and land use. In this manner, current ecosystem types were derived, which were related to data on elevation, soil texture, and climate for the years 1961-1990. These relations were quantified by Classification and Regression Trees, which were used to map the spatial patterns of ecosystem type clusters for 1961-1990. The climate data for these years were subsequently replaced by the results of a regional climate model for 1991-2010, 2011-2040, and 2041-2070. For each of these periods, one map of ecosystem type clusters was produced and evaluated with regard to the development of areal coverage of ecosystem type clusters over time. This evaluation of the structural aspects of ecological integrity at the national level was added by projecting potential future values of indicators for ecological functions at the site level by using the Very Simple Dynamic soil modelling technique based on climate data and two scenarios of nitrogen deposition as input. The results were compared to the reference and enabled an evaluation of site-specific ecosystem changes over time which proved to be both, positive and negative. Copyright © 2015 Elsevier B.V. All rights reserved.

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes

PubMed Central

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2018-01-01

Currently, the temperate forest biome cools the earth’s climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (−10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems. PMID:29628526

Spatially Refined Aerosol Direct Radiative Focusing Efficiencies

EPA Science Inventory

Global aerosol direct radiative forcing (DRF) is an important metric for assessing potential climate impacts of future emissions changes. However, the radiative consequences of emissions perturbations are not readily quantified nor well understood at the level of detail necessary...

Spatially Refined Aerosol Direct Radiative Forcing Efficiencies

EPA Science Inventory

Global aerosol direct radiative forcing (DRF) is an important metric for assessing potential climate impacts of future emissions changes. However, the radiative consequences of emissions perturbations are not readily quantified nor well understood at the level of detail necessary...

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

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

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

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

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

An ecohydrological model to quantify the risk of drought-induced forest mortality events across climate regimes

NASA Astrophysics Data System (ADS)

Parolari, A.; Katul, G. G.; Porporato, A. M.

2013-12-01

Regional scale drought-induced forest mortality events are projected to become more frequent under future climates due to changes in rainfall patterns. However, the ability to predict the conditions under which such events occur is currently lacking. To quantify and understand the underlying causes of drought-induced forest mortality, we propose a stochastic ecohydrological model that explicitly couples tree water and carbon use strategies with climate characteristics, such as the frequency and severity of drought. Using the model and results from a controlled drought experiment, we identify the soil, vegetation, and climate factors that underlie tree water and carbon deficits and, ultimately, the risk of drought-induced forest mortality. This mortality risk is then compared across the spectrum of anisohydric-isohydric stomatal control strategies and a range of rainfall regimes. These results suggest certain soil-plant combinations may maximize the survivable drought length in a given climate. Finally, we discuss how this approach can be expanded to estimate the effect of anticipated climate change on drought-induced forest mortality and associated consequences for forest water and carbon balances.

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

DOE PAGES

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

2016-09-03

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

Modeling groundwater quality in an arid agricultural environment in the face of an uncertain climate: the case of Mewat District, India

NASA Astrophysics Data System (ADS)

Weber, M. C.; Ward, A. S.; Muste, M.

2014-12-01

The salinization of groundwater resources is a widespread problem in arid agricultural environments. In Mewat District (Haryana, India), groundwater salinity has rendered much of the accessible supply unfit for human consumption or agriculture. Historically, this closed basin retained fresh pockets of water at the foothills of the Aravalli Hills, where monsoonal precipitation runoff from the mountains was recharged through infiltration or facilitated by man-made structures. To date, an increasing number of pumps supply the region with fresh water for consumption and agriculture leading to shrinking the freshwater zone at an accelerated pace. The potential for increased human consumption corroborated with the effects of climate change bring uncertainty about the future of water security for the Mewat communities, most of them critically bound to the existence of local water. This study addresses the sustainability of the freshwater supply under a range of land interventions and climate scenarios, using a 2-D groundwater flow and transport model. Our results quantify potential futures for this arid, groundwater-dependent location, using numerical groundwater modeling to quantify interactions between human water use, infrastructure, and climate. Outcomes of this modeling study will inform an NGO active in the area on sustainable management of groundwater resources.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Nitrogen deposition's role in determining forest photosynthetic capacity; a FLUXNET synthesis

NASA Astrophysics Data System (ADS)

Fleischer, K.; Rebel, K.; van der Molen, M.; Erisman, J.; Wassen, M.; Dolman, H.

2011-12-01

There is growing evidence that nitrogen (N) deposition stimulates forest growth, as many forest ecosystems are N-limited. However, the significance of N deposition in determining the strength of the present and future terrestrial carbon sink is strongly debated. We investigated and quantified the effect of N deposition on ecosystem photosynthetic capacity (Amax) with the FLUXNET database, including 80 forest sites, covering the major forest types and climates of the world. The relative effect of climate and N deposition on photosynthesis was assessed with regression models. We found a significant positive correlation of Amax and N deposition for evergreen needleleaf forests in our dataset. We further found indications that foliar N and LAI scale positively with N deposition, reflecting the 2 mechanisms at which N is believed to cause an increase in carbon gain. We can support the hypothesis that foliar N is the principal scaling factor for canopy Amax across all forest types. Deciduous forests are less diverse in terms of climate and nutritional conditions for the included sites and these forests exhibited weak to no correlations with the included climate and N predictor variables. Quantifying the effect of N deposition on photosynthetic rates at the canopy level is an essential step for quantifying its contribution to the terrestrial carbon sink and for predicting vegetation response to N fertilization and global change in the future. The approach shows that eddy-covariance measurements of carbon fluxes at the canopy scale allow us to test hypotheses with respect to the expected nitrogen-photosynthesis relationships at the canopy scale.

Can We Asses the Impact of Water Factor on Ecosystems and Agriculture under Future Climate Conditions? Case Study from Poland.

NASA Astrophysics Data System (ADS)

Okruszko, T.; O'Keeffe, J.; Marcinkowski, P.; Utratna, M.; Szcześniak, M.; Piniewski, M.

2016-12-01

This study presents a broad overview of climate change impacts on eco- and agro-systems in Poland using an index-based approach for the Vistula and Odra river basins in Poland. The issues of risks to biodiversity and agricultural productivity caused by climate change (CC) are explicitly addressed. The biodiversity issue is tackled by the analysis of two types of ecosystems: instream and wetland (both river-and groundwater fed). Agro-systems are analyzed using key crops (spring and winter grains, potatoes, corn and grasslands),including their regional differentiation and dominant soil types. The study was accomplished in the following steps: (1) development of historical climate dataset and its application for bias correction of climate projections, (2) modelling the hydrological system using the SWAT model for historical and future climate, (3) development of indices quantifying the impact of water factoron eco- and agro-systems based on the SWAT model results, (4) calculation and critical analysis of results for two emission scenarios (RCPs) and two time horizons. The 5-km resolution precipitation and temperature dataset (10.5194/essd-8-127-2016) was developed and applied for bias correction of the multi-model ensemble of 9 CORDEX RCMs under two RCPs 4.5 and 8.5. Comprehensive calibration/validation of SWAT showed overall good results across a range of catchment sizes in Poland. The ensemble median increase (relative to historical period) ranged between 6 and 16 % for precipitation and between 18 and 48 % for water yield simulated by SWAT, depending on the future time horizon and RCP. The Indicators of Hydrological Alteration (IHA) quantifying the natural flow regime were used as a proxy for quantifying the CC effect on instream biota (notably fish). Changes in frequency and magnitude of the identified flood events informed about the alteration to the water supply for riparian wetlands. Changes in groundwater recharge are used as a proxy for water conditions in mires. The SWAT output on water stress has proven to be a good indicator of agricultural drought. The results showed that developed indicators are highly sensitive to projected changes in water conditions under changing climate. It means that they can be used for agriculture adaptation programs and in conservation policy.

The future demographic niche of a declining grassland bird fails to shift poleward in response to climate change

USGS Publications Warehouse

McCauley, Lisa A.; Ribic, Christine; Pomara, Lars Y.; Zuckerberg, Benjamin

2017-01-01

ContextTemperate grasslands and their dependent species are exposed to high variability in weather and climate due to the lack of natural buffers such as forests. Grassland birds are particularly vulnerable to this variability, yet have failed to shift poleward in response to recent climate change like other bird species in North America. However, there have been few studies examining the effect of weather on grassland bird demography and consequent influence of climate change on population persistence and distributional shifts.ObjectivesThe goal of this study was to estimate the vulnerability of Henslow’s Sparrow (Ammodramus henslowii), an obligate grassland bird that has been declining throughout much of its range, to past and future climatic variability.MethodsWe conducted a demographic meta-analysis from published studies and quantified the relationship between nest success rates and variability in breeding season climate. We projected the climate-demography relationships spatially, throughout the breeding range, and temporally, from 1981 to 2050. These projections were used to evaluate population dynamics by implementing a spatially explicit population model.ResultsWe uncovered a climate-demography linkage for Henslow’s Sparrow with summer precipitation, and to a lesser degree, temperature positively affecting nest success. We found that future climatic conditions—primarily changes in precipitation—will likely contribute to reduced population persistence and a southwestward range contraction.ConclusionsFuture distributional shifts in response to climate change may not always be poleward and assessing projected changes in precipitation is critical for grassland bird conservation and climate change adaptation.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

PubMed

Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

2016-01-01

Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

Forecasting conditional climate-change using a hybrid approach

USGS Publications Warehouse

Esfahani, Akbar Akbari; Friedel, Michael J.

2014-01-01

A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

ScienceCast 151: NASA to Launch Carbon Observatory

NASA Image and Video Library

2014-06-24

NASA is about to launch a satellite dedicated to the study of the greenhouse gas carbon dioxide. The Orbiting Carbon Observatory (OCO-2) will quantify global CO2 sources and sinks, and help researchers predict the future of climate change.

What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference? Results from ISI-MIP the first Inter-Sectoral Impact Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Frieler, K.; Huber, V.; Piontek, F.; Schewe, J.; Serdeczny, O.; Warszawski, L.

2012-12-01

The Inter-sectoral Impact Model Intercomparison Project (ISI-MIP) aims to synthesize the state-of-the-art knowledge of climate change impacts at different levels of global warming. Over 25 climate impact modelling teams from around the world, working within the agriculture, water, biomes, infrastructure and health sectors, are collaborating to find answers to the question "What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference?". The analysis is based on common, bias-corrected climate projections, and socio-economic pathways. The first, fast-tracked phase of the ISI-MIP has a focus on global impact models. The project's experimental design is formulated to distinguish the uncertainty introduced by the impact models themselves, from the inherent uncertainty in the climate projections and the variety of plausible socio-economic futures. Novel metrics, developed to emphasize societal impacts, will be used to identify regional 'hot-spots' of climate change impacts, as well as to quantify the cross-sectoral impact of the increasing frequency of extreme events in future climates. We present here first results from the Fast-Track phase of the project covering impact simulations in the biomes, agriculture and water sectors, in which the societal impacts of climate change are quantified for different levels of global warming. We also discuss the design of the scenario set-up and impact indicators chosen to suit the unique cross-sectoral, multi-model nature of the project.

The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

NASA Astrophysics Data System (ADS)

Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian

2017-09-01

The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

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

PubMed Central

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

2017-01-01

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

Projecting Age-Stratified Risk of Exposure to Inland Flooding and Wildfire Smoke in the United States under Two Climate Scenarios.

PubMed

Mills, David; Jones, Russell; Wobus, Cameron; Ekstrom, Julia; Jantarasami, Lesley; St Juliana, Alexis; Crimmins, Allison

2018-04-17

The public health community readily recognizes flooding and wildfires as climate-related health hazards, but few studies quantify changes in risk of exposure, particularly for vulnerable children and older adults. This study quantifies future populations potentially exposed to inland flooding and wildfire smoke under two climate scenarios, highlighting the populations in particularly vulnerable age groups (≤4 y old and ≥65 y old). Spatially explicit projections of inland flooding and wildfire under two representative concentration pathways (RCP8.5 and RCP4.5) are integrated with static (2010) and dynamic (2050 and 2090) age-stratified projections of future contiguous U.S. populations at the county level. In both 2050 and 2090, an additional one-third of the population will live in areas affected by larger and more frequent inland flooding under RCP8.5 than under RCP4.5. Approximately 15 million children and 25 million older adults could avoid this increased risk of flood exposure each year by 2090 under a moderate mitigation scenario (RCP4.5 compared with RCP8.5). We also find reduced exposure to wildfire smoke under the moderate mitigation scenario. Nearly 1 million young children and 1.7 million older adults would avoid exposure to wildfire smoke each year under RCP4.5 than under RCP8.5 by the end of the century. By integrating climate-driven hazard and population projections, newly created county-level exposure maps identify locations of potential significant future public health risk. These potential exposure results can help inform actions to prevent and prepare for associated future adverse health outcomes, particularly for vulnerable children and older adults. https://doi.org/10.1289/EHP2594.

Quantifying uncertainties of permafrost carbon-climate feedbacks

NASA Astrophysics Data System (ADS)

Burke, Eleanor J.; Ekici, Altug; Huang, Ye; Chadburn, Sarah E.; Huntingford, Chris; Ciais, Philippe; Friedlingstein, Pierre; Peng, Shushi; Krinner, Gerhard

2017-06-01

The land surface models JULES (Joint UK Land Environment Simulator, two versions) and ORCHIDEE-MICT (Organizing Carbon and Hydrology in Dynamic Ecosystems), each with a revised representation of permafrost carbon, were coupled to the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) intermediate-complexity climate and ocean carbon uptake model. IMOGEN calculates atmospheric carbon dioxide (CO2) and local monthly surface climate for a given emission scenario with the land-atmosphere CO2 flux exchange from either JULES or ORCHIDEE-MICT. These simulations include feedbacks associated with permafrost carbon changes in a warming world. Both IMOGEN-JULES and IMOGEN-ORCHIDEE-MICT were forced by historical and three alternative future-CO2-emission scenarios. Those simulations were performed for different climate sensitivities and regional climate change patterns based on 22 different Earth system models (ESMs) used for CMIP3 (phase 3 of the Coupled Model Intercomparison Project), allowing us to explore climate uncertainties in the context of permafrost carbon-climate feedbacks. Three future emission scenarios consistent with three representative concentration pathways were used: RCP2.6, RCP4.5 and RCP8.5. Paired simulations with and without frozen carbon processes were required to quantify the impact of the permafrost carbon feedback on climate change. The additional warming from the permafrost carbon feedback is between 0.2 and 12 % of the change in the global mean temperature (ΔT) by the year 2100 and 0.5 and 17 % of ΔT by 2300, with these ranges reflecting differences in land surface models, climate models and emissions pathway. As a percentage of ΔT, the permafrost carbon feedback has a greater impact on the low-emissions scenario (RCP2.6) than on the higher-emissions scenarios, suggesting that permafrost carbon should be taken into account when evaluating scenarios of heavy mitigation and stabilization. Structural differences between the land surface models (particularly the representation of the soil carbon decomposition) are found to be a larger source of uncertainties than differences in the climate response. Inertia in the permafrost carbon system means that the permafrost carbon response depends on the temporal trajectory of warming as well as the absolute amount of warming. We propose a new policy-relevant metric - the frozen carbon residence time (FCRt) in years - that can be derived from these complex land surface models and used to quantify the permafrost carbon response given any pathway of global temperature change.

The integrated effects of future climate and hydrologic uncertainty on sustainable flood risk management

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Wi, S.; Brown, C. M.

2013-12-01

Flood risk management performance is investigated within the context of integrated climate and hydrologic modeling uncertainty to explore system robustness. The research question investigated is whether structural and hydrologic parameterization uncertainties are significant relative to other uncertainties such as climate change when considering water resources system performance. Two hydrologic models are considered, a conceptual, lumped parameter model that preserves the water balance and a physically-based model that preserves both water and energy balances. In the conceptual model, parameter and structural uncertainties are quantified and propagated through the analysis using a Bayesian modeling framework with an innovative error model. Mean climate changes and internal climate variability are explored using an ensemble of simulations from a stochastic weather generator. The approach presented can be used to quantify the sensitivity of flood protection adequacy to different sources of uncertainty in the climate and hydrologic system, enabling the identification of robust projects that maintain adequate performance despite the uncertainties. The method is demonstrated in a case study for the Coralville Reservoir on the Iowa River, where increased flooding over the past several decades has raised questions about potential impacts of climate change on flood protection adequacy.

Quantifying the historic and future distribution of fire in Alaskan tundra ecosystems

NASA Astrophysics Data System (ADS)

Young, A. M.; Higuera, P. E.; Duffy, P. A.

2012-12-01

During the past 60 years fire has been relatively rare and small in size within tundra ecosystems. However, historical observations and paleoecological evidence indicates that fire regimes vary widely across Alaskan tundra, in both space and time. These lines of evidence suggest that fire occupies a highly specified niche or ecological space in Alaskan tundra, which may change significantly with future climate warming. The objective of this research was to quantify the relationships between fire occurrence and different seasonal climate variables, and to begin to make inferences about future distributions of fire across the tundra landscape. The results of this research will ultimately contribute to the goal of summarizing the linkages that exist among climate, vegetation, and fire in the historical record, and for making predictions concerning fire disturbance in tundra ecosystems throughout the next century. Historic tundra fires occurred non-randomly across space, and a relationship exists between fire occurrence and warm, dry climates. We quantified this relationship with generalized boosting models (GBM) using datasets of downscaled temperature and precipitation (2 km, 1971-2000), and historic records of tundra area burned (1950-2010). The GBM used six seasonal climate variables, focused on growing season temperature and precipitation, to predict the probability of fire occurrence over the 1950-2010 time period. To understand implications of these historic relationships given ongoing climate warming, we constructed future climatologies of temperature and precipitation for the five GCMs which performed best in Alaska under the IPCC AR4 A1B (middle-of-the-road) emissions scenario for the time period 2021-2050. The GBM performed well predicting the observed spatial distribution of tundra area burned, capturing key regions which experienced the most fire activity from 1950-2010. The mean temperature of the warmest month (MeanMaxTemp) was the most influential variable in the GBM, and partial dependence plots revealed a strong non-linear relationship between the probability of fire and MeanMaxTemp, with a distinct temperature threshold of approximately 12.0 oC. Climate projections in Alaskan tundra (2021-2050) from the five GCMs was on average 2.1 oC warmer (SD = 0.3 oC) than the 1971-2000 mean. During the 1971-2000 period, 62% of tundra existed above the 12.0 oC threshold. In contrast, four of the five GCMs predicted more tundra area will exist above this same temperature threshold during the 2021-2050 period (mean=77%, min=48%, max=93%), with large increases occurring on the North Slope. Ongoing work includes applying this GBM to future climate conditions to provide quantitative estimates of future tundra burning. Our results suggest that the ecological space that currently supports tundra burning will become more common during the next century. A more flammable tundra landscape could contribute to increased land surface temperatures through feedbacks between fire, increased carbon flux from the soil to atmosphere, and decreased albedo through vegetation succession. Given the rapid environmental changes projected for the Arctic throughout the next century, it is imperative that we understand when and where fire regimes are changing, not only across Alaskan tundra but across the global tundra biome as well.

Quantifying changes in water use and groundwater availability in a megacity using novel integrated systems modeling

NASA Astrophysics Data System (ADS)

Hyndman, D. W.; Xu, T.; Deines, J. M.; Cao, G.; Nagelkirk, R.; Viña, A.; McConnell, W.; Basso, B.; Kendall, A. D.; Li, S.; Luo, L.; Lupi, F.; Ma, D.; Winkler, J. A.; Yang, W.; Zheng, C.; Liu, J.

2017-08-01

Water sustainability in megacities is a growing challenge with far-reaching effects. Addressing sustainability requires an integrated, multidisciplinary approach able to capture interactions among hydrology, population growth, and socioeconomic factors and to reflect changes due to climate variability and land use. We developed a new systems modeling framework to quantify the influence of changes in land use, crop growth, and urbanization on groundwater storage for Beijing, China. This framework was then used to understand and quantify causes of observed decreases in groundwater storage from 1993 to 2006, revealing that the expansion of Beijing's urban areas at the expense of croplands has enhanced recharge while reducing water lost to evapotranspiration, partially ameliorating groundwater declines. The results demonstrate the efficacy of such a systems approach to quantify the impacts of changes in climate and land use on water sustainability for megacities, while providing a quantitative framework to improve mitigation and adaptation strategies that can help address future water challenges.

Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context.

PubMed

Palazzo, Amanda; Vervoort, Joost M; Mason-D'Croz, Daniel; Rutting, Lucas; Havlík, Petr; Islam, Shahnila; Bayala, Jules; Valin, Hugo; Kadi Kadi, Hamé Abdou; Thornton, Philip; Zougmore, Robert

2017-07-01

The climate change research community's shared socioeconomic pathways (SSPs) are a set of alternative global development scenarios focused on mitigation of and adaptation to climate change. To use these scenarios as a global context that is relevant for policy guidance at regional and national levels, they have to be connected to an exploration of drivers and challenges informed by regional expertise. In this paper, we present scenarios for West Africa developed by regional stakeholders and quantified using two global economic models, GLOBIOM and IMPACT, in interaction with stakeholder-generated narratives and scenario trends and SSP assumptions. We present this process as an example of linking comparable scenarios across levels to increase coherence with global contexts, while presenting insights about the future of agriculture and food security under a range of future drivers including climate change. In these scenarios, strong economic development increases food security and agricultural development. The latter increases crop and livestock productivity leading to an expansion of agricultural area within the region while reducing the land expansion burden elsewhere. In the context of a global economy, West Africa remains a large consumer and producer of a selection of commodities. However, the growth in population coupled with rising incomes leads to increases in the region's imports. For West Africa, climate change is projected to have negative effects on both crop yields and grassland productivity, and a lack of investment may exacerbate these effects. Linking multi-stakeholder regional scenarios to the global SSPs ensures scenarios that are regionally appropriate and useful for policy development as evidenced in the case study, while allowing for a critical link to global contexts.

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.

Response surfaces of vulnerability to climate change: The Colorado River Basin, the High Plains, and California

Treesearch

Romano Foti; Jorge A. Ramirez; Thomas C. Brown

2014-01-01

We quantify the vulnerability of water supply to shortage for the Colorado River Basin and basins of the High Plains and California and assess the sensitivity of their water supply system to future changes in the statistical variability of supply and demand. We do so for current conditions and future socio-economic scenarios within a probabilistic framework that...

Present-day and future contributions of glacier runoff to summertime flows in a Pacific Northwest watershed: implications for water resources

Treesearch

Anne W. Nolin; Jeff Phillippe; Anne Jefferson; Sarah L. Lewis

2010-01-01

While the impacts of long-term climate change trends on glacier hydrology have received much attention, little has been done to quantify direct glacier runoff contributions to streamflow. This paper presents an approach for determining glacier runoff contributions to streamflow and estimating the effects of increased temperature and decreased glacier area on future...

Robust signals of future projections of Indian summer monsoon rainfall by IPCC AR5 climate models: Role of seasonal cycle and interannual variability

NASA Astrophysics Data System (ADS)

Jayasankar, C. B.; Surendran, Sajani; Rajendran, Kavirajan

2015-05-01

Coupled Model Intercomparison Project phase 5 (Fifth Assessment Report of Intergovernmental Panel on Climate Change) coupled global climate model Representative Concentration Pathway 8.5 simulations are analyzed to derive robust signals of projected changes in Indian summer monsoon rainfall (ISMR) and its variability. Models project clear future temperature increase but diverse changes in ISMR with substantial intermodel spread. Objective measures of interannual variability (IAV) yields nearly equal chance for future increase or decrease. This leads to discrepancy in quantifying changes in ISMR and variability. However, based primarily on the physical association between mean changes in ISMR and its IAV, and objective methods such as k-means clustering with Dunn's validity index, mean seasonal cycle, and reliability ensemble averaging, projections fall into distinct groups. Physically consistent groups of models with the highest reliability project future reduction in the frequency of light rainfall but increase in high to extreme rainfall and thereby future increase in ISMR by 0.74 ± 0.36 mm d-1, along with increased future IAV. These robust estimates of future changes are important for useful impact assessments.

Changes in future fire regimes under climate change

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; von Bloh, Werner; Lutz, Julia; Knorr, Wolfgang; Wu, Minchao; Arneth, Almut

2013-04-01

Fires are expected to change under future climate change, climatic fire is is increasing due to increase in droughts and heat waves affecting vegetation productivity and ecosystem function. Vegetation productivity influences fuel production, but can also limit fire spread. Vegetation-fire models allow investigating the interaction between wildfires and vegetation dynamics, thus non-linear effects between changes in fuel composition and production on fire as well as changes in fire regimes on fire-related plant mortality and fuel combustion. Here we present results from simulation experiments, where the vegetation-fire models LPJmL-SPITFIRE and LPJ-GUESS are applied to future climate change scenarios from regional climate models in Europe and Northern Africa. Climate change impacts on fire regimes, vegetation dynamics and carbon fluxes are quantified and presented. New fire-prone regions are mapped and changes in fire regimes of ecosystems with a long-fire history are analyzed. Fuel limitation is likely to increase in Mediterranean-type ecosystems, indicating non-linear connection between increasing fire risk and fuel production. Increased warming in temperate ecosystems in Eastern Europe and continued fuel production leads to increases not only in climatic fire risk, but also area burnt and biomass burnt. This has implications for fire management, where adaptive capacity to this new vulnerability might be limited.

Fire and reduced vigor facilitate vegetation shifts: MC2 results for the conterminous US with CMIP5 climate futures

NASA Astrophysics Data System (ADS)

Bachelet, D. M.; Ferschweiler, K.; Baker, B.; Sleeter, B. M.

2016-12-01

Climate variability and a warming trend during the 21st century ensures fuel build-up and episodic catastrophic wildfires. We used downscaled (2.5 arcmin) CMIP5 climate futures from 20 models under RCP 8.5 to run the dynamic global vegetation model MC2 over the conterminous US and identify key drivers of land cover change. We show regional and temporal differences in the magnitude of projected C losses due to fire over the 21st century. We also look at the vigor (NPP/LAI) of forest lands and estimate the loss in C capture due to declines in production as well as the increase in heterotrophic respiration due to increased mortality. We compare simulated the carbon sequestration potential of terrestrial biomes and the risk of carbon losses through disturbance. We quantify uncertainty in model results by showing the distribution of possible future impacts under 20 futures. We explore the effects of land use and highlight the challenges we met to simulate credible transient management practices throughout the 20th century and into the future.

Return periods of losses associated with European windstorm series in a changing climate

NASA Astrophysics Data System (ADS)

Karremann, Melanie K.; Pinto, Joaquim G.; Reyers, Mark; Klawa, Matthias

2015-04-01

During the last decades, several windstorm series hit Europe leading to large aggregated losses. Such storm series are examples of serial clustering of extreme cyclones, presenting a considerable risk for the insurance industry. Clustering of events and return periods of storm series affecting Europe are quantified based on potential losses using empirical models. Moreover, possible future changes of clustering and return periods of European storm series with high potential losses are quantified. Historical storm series are identified using 40 winters of NCEP reanalysis data (1973/1974 - 2012/2013). Time series of top events (1, 2 or 5 year return levels) are used to assess return periods of storm series both empirically and theoretically. Return periods of historical storm series are estimated based on the Poisson and the negative binomial distributions. Additionally, 800 winters of ECHAM5/MPI-OM1 general circulation model simulations for present (SRES scenario 20C: years 1960- 2000) and future (SRES scenario A1B: years 2060- 2100) climate conditions are investigated. Clustering is identified for most countries in Europe, and estimated return periods are similar for reanalysis and present day simulations. Future changes of return periods are estimated for fixed return levels and fixed loss index thresholds. For the former, shorter return periods are found for Western Europe, but changes are small and spatially heterogeneous. For the latter, which combines the effects of clustering and event ranking shifts, shorter return periods are found everywhere except for Mediterranean countries. These changes are generally not statistically significant between recent and future climate. However, the return periods for the fixed loss index approach are mostly beyond the range of preindustrial natural climate variability. This is not true for fixed return levels. The quantification of losses associated with storm series permits a more adequate windstorm risk assessment in a changing climate.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network.

PubMed

Batllori, Enric; Parisien, Marc-André; Parks, Sean A; Moritz, Max A; Miller, Carol

2017-08-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform a continent-wide climate change vulnerability assessment whereby we compare the baseline climate of the protected area network in North America (Canada, United States, México-NAM) to the projected end-of-century climate (2071-2100). We estimated the projected pace at which climatic conditions may redistribute across NAM (i.e., climate velocity), and identified future nearest climate analogs to quantify patterns of climate relocation within, among, and outside protected areas. Also, we interpret climatic relocation patterns in terms of associated land-cover types. Our analysis suggests that the conservation capacity of the NAM protection network is likely to be severely compromised by a changing climate. The majority of protected areas (~80%) might be exposed to high rates of climate displacement that could promote important shifts in species abundance or distribution. A small fraction of protected areas (<10%) could be critical for future conservation plans, as they will host climates that represent analogs of conditions currently characterizing almost a fifth of the protected areas across NAM. However, the majority of nearest climatic analogs for protected areas are in nonprotected locations. Therefore, unprotected landscapes could pose additional threats, beyond climate forcing itself, as sensitive biota may have to migrate farther than what is prescribed by the climate velocity to reach a protected area destination. To mitigate future threats to the conservation capacity of the NAM protected area network, conservation plans will need to capitalize on opportunities provided by the existing availability of natural land-cover types outside the current network of NAM protected areas. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

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

PubMed

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

2018-06-04

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

Integrated Framework for an Urban Climate Adaptation Tool

NASA Astrophysics Data System (ADS)

Omitaomu, O.; Parish, E. S.; Nugent, P.; Mei, R.; Sylvester, L.; Ernst, K.; Absar, M.

2015-12-01

Cities have an opportunity to become more resilient to future climate change through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. In this paper, we present some of the methods that drive each of the modules and demo some of the capabilities available to-date using the City of Knoxville in Tennessee as a case study.

Population response to climate change: linear vs. non-linear modeling approaches.

PubMed

Ellis, Alicia M; Post, Eric

2004-03-31

Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.

Human-water interactions in Colorado: Evaluating the impacts of population growth, energy development and dynamic industries on water resource management

NASA Astrophysics Data System (ADS)

Hogue, Terri; Walker, Ella; Read, Laura

2016-04-01

The gap between water supply and demand is growing in the western U.S. due to climate change, rapid population growth, intensive agricultural production, wide-spread energy development and changing industrial use. Water conservation efforts among residential and industrial water users, recycling and reuse techniques, and innovative regulatory frameworks strive to mitigate this gap, however, the extent of these management strategies are often difficult to quantify and are typically not included in prediction of future water allocations. Water use on the eastern slope in Colorado (Denver-Metro region) is impacted by high-intensity activities, including unconventional energy development, large withdrawals for agriculture, and increasing demand for recreational industries. These demands are in addition to a projected population increase of 100% by 2050 in the South Platte River basin, which encompasses the Denver-Metro region. The current presentation focuses on the quantification of regional sector water use utilzing a range of observations and technologies (including remote sensing) and integration into a regional decision support system. We explore scenarios of future water use in the energy, agriculture, and municipal/industrial sectors, and discuss the potential water allocation tradeoffs to various stakeholders. We also employ climate projections to quantify the potential range of water availability under various scenarios and observe the extent to which future climate may influence regional management decisions.

Signal to noise quantification of regional climate projections

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Quantifying the past and future impact of climate on outbreak patterns of bank voles (Myodes glareolus).

PubMed

Imholt, Christian; Reil, Daniela; Eccard, Jana A; Jacob, Daniela; Hempelmann, Nils; Jacob, Jens

2015-02-01

Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics. Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance. Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. © 2014 Society of Chemical Industry.

Conservation assessments in climate change scenarios: spatial perspectives for present and future in two Pristidactylus (Squamata: Leiosauridae) lizards from Argentina.

PubMed

Minoli, Ignacio; Avila, Luciano Javier

2017-02-26

The consequences of global climate change can already be seen in many physical and biological systems and these effects could change the distribution of suitable areas for a wide variety of organisms to the middle of this century. We analyzed the current habitat use and we projected the suitable area of present conditions into the geographical space of future scenarios (2050), to assess and quantify whether future climate change would affect the distribution and size of suitable environments in two Pristidactylus lizard species. Comparing the habitat use and future forecasts of the two studied species, P. achalensis showed a more restricted use of available resource units (RUs) and a moderate reduction of the potential future area. On the contrary, P. nigroiugulus uses more available RUs and has a considerable area decrease for both future scenarios. These results suggest that both species have a moderately different trend towards reducing available area of suitable habitats, the persistent localities for both 2050 CO2 concentration models, and in the available RUs used. We discussed the relation between size and use of the current habitat, changes in future projections along with the protected areas from present-future and the usefulness of these results in conservation plans. This work illustrates how ectothermic organisms might have to face major changes in their availability suitable areas as a consequence of the effect of future climate change.

Spatio-temporal trends of nitrogen deposition and climate effects on Sphagnum productivity in European peatlands.

PubMed

Granath, Gustaf; Limpens, Juul; Posch, Maximilian; Mücher, Sander; de Vries, Wim

2014-04-01

To quantify potential nitrogen (N) deposition impacts on peatland carbon (C) uptake, we explored temporal and spatial trends in N deposition and climate impacts on the production of the key peat forming functional group (Sphagnum mosses) across European peatlands for the period 1900-2050. Using a modelling approach we estimated that between 1900 and 1950 N deposition impacts remained limited irrespective of geographical position. Between 1950 and 2000 N deposition depressed production between 0 and 25% relative to 1900, particularly in temperate regions. Future scenarios indicate this trend will continue and become more pronounced with climate warming. At the European scale, the consequences for Sphagnum net C-uptake remained small relative to 1900 due to the low peatland cover in high-N areas. The predicted impacts of likely changes in N deposition on Sphagnum productivity appeared to be less than those of climate. Nevertheless, current critical loads for peatlands are likely to hold under a future climate. Copyright © 2014 Elsevier Ltd. All rights reserved.

Informing the NCA: EPA's Climate Change Impact and Risk Analysis Framework

NASA Astrophysics Data System (ADS)

Sarofim, M. C.; Martinich, J.; Kolian, M.; Crimmins, A. R.

2017-12-01

The Climate Change Impact and Risk Analysis (CIRA) framework is designed to quantify the physical impacts and economic damages in the United States under future climate change scenarios. To date, the framework has been applied to 25 sectors, using scenarios and projections developed for the Fourth National Climate Assessment. The strength of this framework has been in the use of consistent climatic, socioeconomic, and technological assumptions and inputs across the impact sectors to maximize the ease of cross-sector comparison. The results of the underlying CIRA sectoral analyses are informing the sustained assessment process by helping to address key gaps related to economic valuation and risk. Advancing capacity and scientific literature in this area has created opportunity to consider future applications and strengthening of the framework. This presentation will describe the CIRA framework, present results for various sectors such as heat mortality, air & water quality, winter recreation, and sea level rise, and introduce potential enhancements that can improve the utility of the framework for decision analysis.

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

PubMed Central

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

2015-01-01

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

The uncertainty of future water supply adequacy in megacities: Effects of population growth and climate change

NASA Astrophysics Data System (ADS)

Alarcon, T.; Garcia, M. E.; Small, D. L.; Portney, K.; Islam, S.

2013-12-01

Providing water to the expanding population of megacities, which have over 10 million people, with a stressed and aging water infrastructure creates unprecedented challenges. These challenges are exacerbated by dwindling supply and competing demands, altered precipitation and runoff patterns in a changing climate, fragmented water utility business models, and changing consumer behavior. While there is an extensive literature on the effects of climate change on water resources, the uncertainty of climate change predictions continues to be high. This hinders the value of these predictions for municipal water supply planning. The ability of water utilities to meet future water needs will largely depend on their capacity to make decisions under uncertainty. Water stressors, like changes in demographics, climate, and socioeconomic patterns, have varying degrees of uncertainty. Identifying which stressors will have a greater impact on water resources, may reduce the level of future uncertainty for planning and managing water utilities. Within this context, we analyze historical and projected changes of population and climate to quantify the relative impacts of these two stressors on water resources. We focus on megacities that rely primarily on surface water resources to evaluate (a) population growth pattern from 1950-2010 and projected population for 2010-2060; (b) climate change impact on projected climate change scenarios for 2010-2060; and (c) water access for 1950-2010; projected needs for 2010-2060.

Quantifying the impact of climate change on crop yield and water footprint of rice in the Nam Oon Irrigation Project, Thailand.

PubMed

Shrestha, Sangam; Chapagain, Ranju; Babel, Mukand S

2017-12-01

Northeast Thailand makes a significant contribution to fragrant and high-quality rice consumed within Thailand and exported to other countries. The majority of rice is produced in rainfed conditions while irrigation water is supplied to rice growers in the dry season. This paper quantifies the potential impact of climate change on the water footprint of rice production using the DSSAT (CERES-Rice) crop growth model for the Nam Oon Irrigation Project located in Northeast Thailand. Crop phenology data was obtained from field experiments and used to set up and validate the CERES-Rice model. The present and future water footprint of rice, the amount of water evaporated during the growing period, was calculated under current and future climatic condition for the irrigation project area. The outputs of three regional climate models (ACCESS-CSIRO-CCAM, CNRM-CM5-CSIRO-CCAM, and MPI-ESM-LR-CSIRO-CCAM) for scenarios RCP 4.5 and RCP 8.5 were downscaled using quantile mapping method. Simulation results show a considerably high increase in the water footprint of KDML-105 and RD-6 rice varieties ranging from 56.5 to 92.2% and 27.5 to 29.7%. respectively for the future period under RCP 4.5, and 71.4 to 76.5% and 27.9 to 37.6%, respectively under RCP 8.5 relative to the simulated baseline water footprint for the period 1976-2005. Conversely, the ChaiNat-1 variety shows a decrease in projected water footprint of 42.1 to 39.4% under RCP 4.5 and 38.5 to 31.7% under RCP 8.5. The results also indicate a huge increase in the future blue water footprint, which will consequently cause a high increment in the irrigation water requirement in order to meet the plant's evaporation demand. The research outcome highlights the importance of proper adaptation strategies to reduce or maintain acceptable water footprints under future climate conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

A Multivariate and Probabilistic Assessment of Drought in the Pacific Northwest under Observed and Future Climate.

NASA Astrophysics Data System (ADS)

Mortuza, M. R.; Demissie, Y. K.

2015-12-01

In lieu with the recent and anticipated more server and frequently droughts incidences in Yakima River Basin (YRB), a reliable and comprehensive drought assessment is deemed necessary to avoid major crop production loss and better manage the water right issues in the region during low precipitation and/or snow accumulation years. In this study, we have conducted frequency analysis of hydrological droughts and quantified associated uncertainty in the YRB under both historical and changing climate. Streamflow drought index (SDI) was employed to identify mutually correlated drought characteristics (e.g., severity, duration and peak). The historical and future characteristics of drought were estimated by applying tri-variate copulas probability distribution, which effectively describe the joint distribution and dependence of drought severity, duration, and peak. The associated prediction uncertainty, related to parameters of the joint probability and climate projections, were evaluated using the Bayesian approach with bootstrap resampling. For the climate change scenarios, two future representative pathways (RCP4.5 and RCP8.5) from University of Idaho's Multivariate Adaptive Constructed Analogs (MACA) database were considered. The results from the study are expected to provide useful information towards drought risk management in YRB under anticipated climate changes.

Predicting the Future Impact of Droughts on Ungulate Populations in Arid and Semi-Arid Environments

PubMed Central

Duncan, Clare; Chauvenet, Aliénor L. M.; McRae, Louise M.; Pettorelli, Nathalie

2012-01-01

Droughts can have a severe impact on the dynamics of animal populations, particularly in semi-arid and arid environments where herbivore populations are strongly limited by resource availability. Increased drought intensity under projected climate change scenarios can be expected to reduce the viability of such populations, yet this impact has seldom been quantified. In this study, we aim to fill this gap and assess how the predicted worsening of droughts over the 21st century is likely to impact the population dynamics of twelve ungulate species occurring in arid and semi-arid habitats. Our results provide support to the hypotheses that more sedentary, grazing and mixed feeding species will be put at high risk from future increases in drought intensity, suggesting that management intervention under these conditions should be targeted towards species possessing these traits. Predictive population models for all sedentary, grazing or mixed feeding species in our study show that their probability of extinction dramatically increases under future emissions scenarios, and that this extinction risk is greater for smaller populations than larger ones. Our study highlights the importance of quantifying the current and future impacts of increasing extreme natural events on populations and species in order to improve our ability to mitigate predicted biodiversity loss under climate change. PMID:23284700

Climate sensitivity of Tibetan Plateau glaciers - past and future implications

NASA Astrophysics Data System (ADS)

Heyman, Jakob; Hubbard, Alun; Stroeven, Arjen P.; Harbor, Jonathan M.

2013-04-01

The Tibetan Plateau is one of the most extensively glaciated, non-Polar regions of the world, and its mountain glaciers are the primary source of melt water for several of the largest Asian rivers. During glacial cycles, Tibetan Plateau glaciers advanced and retreated multiple times, but remained restricted to the highest mountain areas as valley glaciers and ice caps. Because glacier extent is dominantly controlled by climate, the past extent of Tibetan glaciers provide information on regional climate. Here we present a study analyzing the past maximum extents of glaciers on the Tibetan Plateau with the output of a 3D glacier model, in an effort to quantify Tibetan Plateau climate. We have mapped present-day glaciers and glacial landforms deposited by formerly more extensive glaciers in eight mountain regions across the Tibetan Plateau, allowing us to define present-day and past maximum glacier outlines. Using a high-resolution (250 m) higher-order glacier model calibrated against present-day glacier extents, we have quantified the climate perturbations required to expand present-day glaciers to their past maximum extents. We find that a modest cooling of at most 6°C for a few thousand years is enough to attain past maximum extents, even with 25-75% precipitation reduction. This evidence for limited cooling indicates that the temperature of the Tibetan Plateau remained relatively stable over Quaternary glacial cycles. Given the significant sensitivity to temperature change, the expectation is perhaps that a future warmer climate might result in intense glacier reduction. We have tested this hypothesis and modeled the future glacier development for the three mountain regions with the largest present-day glacier cover using a projected warming of 2.8 to 6.2°C within 100 years (envelope limits from IPCC). These scenarios result in dramatic glacier reductions, including 24-100% ice volume loss after 100 years and 77-100% ice volume loss after 300 years.

Antecedent conditions influence soil respiration differences in shrub and grass patches

USDA-ARS?s Scientific Manuscript database

Quantifying the response of soil respiration to past environmental conditions is critical for predicting how future climate and vegetation change will impact ecosystem carbon balance. Increased shrub dominance in semiarid grasslands has potentially large effects on soil carbon cycling. The goal of t...

Quantifying the effect of nighttime interactions between roots and canopy physiology and their control of water and carbon cycling on feedbacks between soil moisture and terrestrial climatology under variable environmental conditions

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

Domec, Jean-Christophe; Palmroth, Sari; Oren, Ram

The primary objective of this project is to characterize and quantify how the temporal variability of hydraulic redistribution (HR) and its physiological regulation in unmanaged and complex forests is affecting current water and carbon exchange and predict how future climate scenarios will affect these relationships and potentially feed back to the climate. Specifically, a detailed study of ecosystem water uptake and carbon exchange in relation to root functioning was proposed in order to quantify the mechanisms controlling temporal variability of soil moisture dynamic and HR in three active AmeriFlux sites, and to use published data of two other inactive AmeriFluxmore » sites. Furthermore, data collected by our research group at the Duke Free Air CO2 enrichment (FACE) site was also being utilized to further improve our ability to forecast future environmental impacts of elevated CO2 concentration on soil moisture dynamic and its effect on carbon sequestration and terrestrial climatology. The overarching objective being to forecast, using a soil:plant:atmosphere model coupled with a biosphere:atmosphere model, the impact of root functioning on land surface climatology. By comparing unmanaged sites to plantations, we also proposed to determine the effect of land use change on terrestrial carbon sequestration and climatology through its effect on soil moisture dynamic and HR. Our simulations of HR by roots indicated that in some systems HR is an important mechanism that buffers soil water deficit, affects energy and carbon cycling; thus having significant implications for seasonal climate. HR maintained roots alive and below 70% loss of conductivity and our simulations also showed that the increased vapor pressure deficit at night under future conditions was sufficient to drive significant nighttime transpiration at all sites, which reduced HR. This predicted reduction in HR under future climate conditions played an important regulatory role in land atmosphere interactions by affecting whole ecosystem carbon and water balance. Under future climatic scenarios, HR was reduced thus affecting negatively plant water use and carbon assimilation. The discrepancy between the predicted and actual surface warming and atmospheric water vapor caused by the persistence of evapotranspiration during the dry season, increasing energy transfer in the form of latent heat. Under those simulations, we also evaluated how the hydraulic properties of soil and xylem limited the rate of carbon uptake, and carbon net ecosystem exchange. The multilayered hydraulically driven soil vegetation atmosphere carbon and water transfer model was designed to represent processes common to vascular plants, so that ecosystem atmosphere exchange could be captured by the same processes at different sites. Those models shown to be well suited for investigating the impact of drought on forest ecosystems because of its explicit treatment of water transport to leaves. This modeling work also confirmed that unmanaged, mixed hardwood site are more resilient to climatic variations than an adjacent pine plantation, but that future climatic conditions will reverse this trends.« less

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.

Quantifying the consequences of changing hydroclimatic extremes on protection levels for the Rhine

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek; Hegnauer, Mark; Buiteveld, Hendrik; Lammersen, Rita; van den Boogaard, Henk; Beersma, Jules

2017-04-01

The Dutch method for quantifying the magnitude and frequency of occurrence of discharge extremes in the Rhine basin and the potential influence of climate change hereon are presented. In the Netherlands flood protection design requires estimates of discharge extremes for return periods of 1000 up to 100,000 years. Observed discharge records are too short to derive such extreme return discharges, therefore extreme value assessment is based on very long synthetic discharge time-series generated with the Generator of Rainfall And Discharge Extremes (GRADE). The GRADE instrument consists of (1) a stochastic weather generator based on time series resampling of historical f rainfall and temperature and (2) a hydrological model optimized following the GLUE methodology and (3) a hydrodynamic model to simulate the propagation of flood waves based on the generated hydrological time-series. To assess the potential influence of climate change, the four KNMI'14 climate scenarios are applied. These four scenarios represent a large part of the uncertainty provided by the GCMs used for the IPCC 5th assessment report (the CMIP5 GCM simulations under different climate forcings) and are for this purpose tailored to the Rhine and Meuse river basins. To derive the probability distributions of extreme discharges under climate change the historical synthetic rainfall and temperature series simulated with the weather generator are transformed to the future following the KNMI'14 scenarios. For this transformation the Advanced Delta Change method, which allows that the changes in the extremes differ from those in the means, is used. Subsequently the hydrological model is forced with the historical and future (i.e. transformed) synthetic time-series after which the propagation of the flood waves is simulated with the hydrodynamic model to obtain the extreme discharge statistics both for current and future climate conditions. The study shows that both for 2050 and 2085 increases in discharge extremes for the river Rhine at Lobith are projected by all four KNMI'14 climate scenarios. This poses increased requirements for flood protection design in order to prepare for changing climate conditions.

Assessing the resilience of Norway spruce forests through a model-based reanalysis of thinning trials☆

PubMed Central

Seidl, Rupert; Vigl, Friedrich; Rössler, Günter; Neumann, Markus; Rammer, Werner

2017-01-01

As a result of a rapidly changing climate the resilience of forests is an increasingly important property for ecosystem management. Recent efforts have improved the theoretical understanding of resilience, yet its operational quantification remains challenging. Furthermore, there is growing awareness that resilience is not only a means to addressing the consequences of climate change but is also affected by it, necessitating a better understanding of the climate sensitivity of resilience. Quantifying current and future resilience is thus an important step towards mainstreaming resilience thinking into ecosystem management. Here, we present a novel approach for quantifying forest resilience from thinning trials, and assess the climate sensitivity of resilience using process-based ecosystem modeling. We reinterpret the wide range of removal intensities and frequencies in thinning trials as an experimental gradient of perturbation, and estimate resilience as the recovery rate after perturbation. Our specific objectives were (i) to determine how resilience varies with stand and site conditions, (ii) to assess the climate sensitivity of resilience across a range of potential future climate scenarios, and (iii) to evaluate the robustness of resilience estimates to different focal indicators and assessment methodologies. We analyzed three long-term thinning trials in Norway spruce (Picea abies (L.) Karst.) forests across an elevation gradient in Austria, evaluating and applying the individual-based process model iLand. The resilience of Norway spruce was highest at the montane site, and decreased at lower elevations. Resilience also decreased with increasing stand age and basal area. The effects of climate change were strongly context-dependent: At the montane site, where precipitation levels were ample even under climate change, warming increased resilience in all scenarios. At lower elevations, however, rising temperatures decreased resilience, particularly at precipitation levels below 750–800 mm. Our results were largely robust to different focal variables and resilience definitions. Based on our findings management can improve the capacity to recover from partial disturbances by avoiding overmature and overstocked conditions. At increasingly water limited sites a strongly decreasing resilience of Norway spruce will require a shift towards tree species better adapted to the expected future conditions. PMID:28860674

Participatory Scenario Planning for Climate Change Adaptation: the Maui Groundwater Project

NASA Astrophysics Data System (ADS)

Keener, V. W.; Brewington, L.; Finucane, M.

2015-12-01

For the last century, the island of Maui in Hawai'i has been the center of environmental, agricultural, and legal conflict with respect to both surface and groundwater allocation. Planning for sustainable future freshwater supply in Hawai'i requires adaptive policies and decision-making that emphasizes private and public partnerships and knowledge transfer between scientists and non-scientists. We have downscaled dynamical climate models to 1 km resolution in Maui and coupled them with a USGS Water Budget model and a participatory scenario building process to quantify future changes in island-scale climate and groundwater recharge under different land uses. Although these projections are uncertain, the integrated nature of the Pacific RISA research program has allowed us to take a multi-pronged approach to facilitate the uptake of climate information into policy and management. This presentation details the ongoing work to support the development of Hawai'i's first island-wide water use plan under the new climate adaptation directive. Participatory scenario planning began in 2012 to bring together a diverse group of ~100 decision-makers in state and local government, watershed restoration, agriculture, and conservation to 1) determine the type of information (climate variables, land use and development, agricultural practices) they would find helpful in planning for climate change, and 2) develop a set of nested scenarios that represent alternative climate and management futures. This integration of knowledge is an iterative process, resulting in flexible and transparent narratives of complex futures comprised of information at multiple scales. We will present an overview of the downscaling, scenario building, hydrological modeling processes, and stakeholder response.

Collaborative Research: Quantifying Climate Feedbacks of the Terrestrial Biosphere under Thawing Permafrost Conditions in the Arctic

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

Melillo, Jerry

Our overall goal in this research was to quantify the potential for threshold changes in natural emission rates of trace gases, particularly methane and carbon dioxide, from pan-arctic terrestrial systems under the spectrum of anthropogenically-forced climate warming, and the conditions under which these emissions provide a strong feedback mechanism to global climate warming. This goal was motivated under the premise that polar amplification of global climate warming will induce widespread thaw and degradation of the permafrost, and would thus cause substantial changes to the landscape of wetlands and lakes, especially thermokarst (thaw) lakes, across the Arctic. Through a suite ofmore » numerical experiments that encapsulate the fundamental processes governing methane emissions and carbon exchanges – as well as their coupling to the global climate system - we tested the following hypothesis in the proposed research: There exists a climate warming threshold beyond which permafrost degradation becomes widespread and stimulates large increases in methane emissions (via thermokarst lakes and poorly-drained wetland areas upon thawing permafrost along with microbial metabolic responses to higher temperatures) and increases in carbon dioxide emissions from well-drained areas. Besides changes in biogeochemistry, this threshold will also influence global energy dynamics through effects on surface albedo, evapotranspiration and water vapor. These changes would outweigh any increased uptake of carbon (e.g. from peatlands and higher plant photosynthesis) and would result in a strong, positive feedback to global climate warming. In collaboration with our Purdue and MIT colleagues, we have attempted to quantify global climate warming effects on land-atmosphere interactions, land-river network interactions, permafrost degradation, vegetation shifts, and land use influence water, carbon, and nitrogen fluxes to and from terrestrial ecosystems in the pan-arctic along with their uncertainties. Based on our study results along with a review of observed and projected climate changes in Northern Eurasia by others, we have also outlined a more integrated modelling approach that may be developed and applied in future studies to better capture the influence of earth system feedbacks and human activities on the evolution of climate change effects over time. Specifically, we have examined: 1) how evapotranspiration and water availability have been changing in Northern Eurasia and may change in the future including the impact of forcing uncertainties (Liu et al., 2013, 2014, 2015); 2) how soil consumption of atmospheric methane across the globe have been influenced and may be influenced by climate change and nitrogen deposition during the 20th and 21st centuries (Zhuang et al., 2013); 3) how wetland inundation extent influences net CO2 and CH4 fluxes from northern high latitudes (Zhuang et al., 2015); 4) the relative effects of various environmental factors (including permafrost degradation) on terrestrial dissolved organic carbon (DOC) loading of river networks across the pan-Arctic and how they have changed over the 20th century (Kicklighter et al., 2013); 5) the impacts of recent and future permafrost thaw on land-atmosphere greenhouse gas exchange across the pan-Arctic (Gao et al., 2012, 2013; Hayes et al., 2014; Kicklighter et al. 2015a, 2018); 6) how climate-induced vegetation shifts may affect carbon fluxes and future land use in Northern Eurasia (Jiang et al., 2012, 2016; Kicklighter et al., 2014a) and the globe (Zhuang et al. 2015b); 7) the relative importance of legacies from past land use, future land-use change and climate change on projections of terrestrial carbon fluxes (Monier et al., 2015; Kicklighter et al., 2016); and 8) how the effects of earth system feedbacks and human activities can be better incorporated in assessments of climate change impacts (Monier et al., 2017; Groisman et al., 2018).« less

Integrated Modeling and Participatory Scenario Planning for Climate Adaptation: the Maui Groundwater Project

NASA Astrophysics Data System (ADS)

Keener, V. W.; Finucane, M.; Brewington, L.

2014-12-01

For the last century, the island of Maui, Hawaii, has been the center of environmental, agricultural, and legal conflict with respect to surface and groundwater allocation. Planning for adequate future freshwater resources requires flexible and adaptive policies that emphasize partnerships and knowledge transfer between scientists and non-scientists. In 2012 the Hawai'i state legislature passed the Climate Change Adaptation Priority Guidelines (Act 286) law requiring county and state policy makers to include island-wide climate change scenarios in their planning processes. This research details the ongoing work by researchers in the NOAA funded Pacific RISA to support the development of Hawaii's first island-wide water use plan under the new climate adaptation directive. This integrated project combines several models with participatory future scenario planning. The dynamically downscaled triply nested Hawaii Regional Climate Model (HRCM) was modified from the WRF community model and calibrated to simulate the many microclimates on the Hawaiian archipelago. For the island of Maui, the HRCM was validated using 20 years of hindcast data, and daily projections were created at a 1 km scale to capture the steep topography and diverse rainfall regimes. Downscaled climate data are input into a USGS hydrological model to quantify groundwater recharge. This model was previously used for groundwater management, and is being expanded utilizing future climate projections, current land use maps and future scenario maps informed by stakeholder input. Participatory scenario planning began in 2012 to bring together a diverse group of over 50 decision-makers in government, conservation, and agriculture to 1) determine the type of information they would find helpful in planning for climate change, and 2) develop a set of scenarios that represent alternative climate/management futures. This is an iterative process, resulting in flexible and transparent narratives at multiple scales. The resulting climate, land use, and groundwater recharge maps give stakeholders a common set of future scenarios that they understand through the participatory scenario process, and identify the vulnerabilities, trade-offs, and adaptive priorities for different groundwater management and land uses in an uncertain future.

Quantifying the Value of Downscaled Climate Model Information for Adaptation Decisions: When is Downscaling a Smart Decision?

NASA Astrophysics Data System (ADS)

Terando, A. J.; Wootten, A.; Eaton, M. J.; Runge, M. C.; Littell, J. S.; Bryan, A. M.; Carter, S. L.

2015-12-01

Two types of decisions face society with respect to anthropogenic climate change: (1) whether to enact a global greenhouse gas abatement policy, and (2) how to adapt to the local consequences of current and future climatic changes. The practice of downscaling global climate models (GCMs) is often used to address (2) because GCMs do not resolve key features that will mediate global climate change at the local scale. In response, the development of downscaling techniques and models has accelerated to aid decision makers seeking adaptation guidance. However, quantifiable estimates of the value of information are difficult to obtain, particularly in decision contexts characterized by deep uncertainty and low system-controllability. Here we demonstrate a method to quantify the additional value that decision makers could expect if research investments are directed towards developing new downscaled climate projections. As a proof of concept we focus on a real-world management problem: whether to undertake assisted migration for an endangered tropical avian species. We also take advantage of recently published multivariate methods that account for three vexing issues in climate impacts modeling: maximizing climate model quality information, accounting for model dependence in ensembles of opportunity, and deriving probabilistic projections. We expand on these global methods by including regional (Caribbean Basin) and local (Puerto Rico) domains. In the local domain, we test whether a high resolution (2km) dynamically downscaled GCM reduces the multivariate error estimate compared to the original coarse-scale GCM. Initial tests show little difference between the downscaled and original GCM multivariate error. When propagated through to a species population model, the Value of Information analysis indicates that the expected utility that would accrue to the manager (and species) if this downscaling were completed may not justify the cost compared to alternative actions.

The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review.

PubMed

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

2017-01-01

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

C-LAMP Subproject Description:Climate Forcing by the Terrestrial Biosphere During the Second Half of the 20th Century

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

Covey, Curt; Hoffman, Forrest

2008-10-02

This project will quantify selected components of climate forcing due to changes in the terrestrial biosphere over the period 1948-2004, as simulated by the climate / carboncycle models participating in C-LAMP (the Carbon-Land Model Intercomparison Project; see http://www.climatemodeling.org/c-lamp). Unlike other C-LAMP projects that attempt to close the carbon budget, this project will focus on the contributions of individual biomes in terms of the resulting climate forcing. Bala et al. (2007) used a similar (though more comprehensive) model-based technique to assess and compare different components of biospheric climate forcing, but their focus was on potential future deforestation rather than the historicalmore » period.« less

The effects of climate change on storm surges around the United Kingdom.

PubMed

Lowe, J A; Gregory, J M

2005-06-15

Coastal flooding is often caused by extreme events, such as storm surges. In this study, improved physical models have been used to simulate the climate system and storm surges, and to predict the effect of increased atmospheric concentrations of greenhouse gases on the surges. In agreement with previous studies, this work indicates that the changes in atmospheric storminess and the higher time-average sea-level predicted for the end of the twenty-first century will lead to changes in the height of water levels measured relative to the present day tide. However, the details of these projections differ somewhat from earlier assessments. Uncertainty in projections of future extreme water levels arise from uncertainty in the amount and timing of future greenhouse gas emissions, uncertainty in the physical models used to simulate the climate system and from the natural variability of the system. The total uncertainty has not yet been reliably quantified and achieving this should be a priority for future research.

Future frequencies of extreme weather events in the National Wildlife Refuges of the conterminous U.S.

USGS Publications Warehouse

Martinuzzi, Sebastian; Allstadt, Andrew J.; Bateman, Brooke L.; Heglund, Patricia J.; Pidgeon, Anna M.; Thogmartin, Wayne E.; Vavrus, Stephen J.; Radeloff, Volker C.

2016-01-01

Climate change is a major challenge for managers of protected areas world-wide, and managers need information about future climate conditions within protected areas. Prior studies of climate change effects in protected areas have largely focused on average climatic conditions. However, extreme weather may have stronger effects on wildlife populations and habitats than changes in averages. Our goal was to quantify future changes in the frequency of extreme heat, drought, and false springs, during the avian breeding season, in 415 National Wildlife Refuges in the conterminous United States. We analyzed spatially detailed data on extreme weather frequencies during the historical period (1950–2005) and under different scenarios of future climate change by mid- and late-21st century. We found that all wildlife refuges will likely experience substantial changes in the frequencies of extreme weather, but the types of projected changes differed among refuges. Extreme heat is projected to increase dramatically in all wildlife refuges, whereas changes in droughts and false springs are projected to increase or decrease on a regional basis. Half of all wildlife refuges are projected to see increases in frequency (> 20% higher than the current rate) in at least two types of weather extremes by mid-century. Wildlife refuges in the Southwest and Pacific Southwest are projected to exhibit the fastest rates of change, and may deserve extra attention. Climate change adaptation strategies in protected areas, such as the U.S. wildlife refuges, may need to seriously consider future changes in extreme weather, including the considerable spatial variation of these changes.

Effects of changing climate on aquatic habitat and connectivity for remnant populations of a wide-ranging frog species in an arid landscape.

PubMed

Pilliod, David S; Arkle, Robert S; Robertson, Jeanne M; Murphy, Melanie A; Funk, W Chris

2015-09-01

Amphibian species persisting in isolated streams and wetlands in desert environments can be susceptible to low connectivity, genetic isolation, and climate changes. We evaluated the past (1900-1930), recent (1981-2010), and future (2071-2100) climate suitability of the arid Great Basin (USA) for the Columbia spotted frog (Rana luteiventris) and assessed whether changes in surface water may affect connectivity for remaining populations. We developed a predictive model of current climate suitability and used it to predict the historic and future distribution of suitable climates. We then modeled changes in surface water availability at each time period. Finally, we quantified connectivity among existing populations on the basis of hydrology and correlated it with interpopulation genetic distance. We found that the area of the Great Basin with suitable climate conditions has declined by approximately 49% over the last century and will likely continue to decline under future climate scenarios. Climate conditions at currently occupied locations have been relatively stable over the last century, which may explain persistence at these sites. However, future climates at these currently occupied locations are predicted to become warmer throughout the year and drier during the frog's activity period (May - September). Fall and winter precipitation may increase, but as rain instead of snow. Earlier runoff and lower summer base flows may reduce connectivity between neighboring populations, which is already limited. Many of these changes could have negative effects on remaining populations over the next 50-80 years, but milder winters, longer growing seasons, and wetter falls might positively affect survival and dispersal. Collectively, however, seasonal shifts in temperature, precipitation, and stream flow patterns could reduce habitat suitability and connectivity for frogs and possibly other aquatic species inhabiting streams in this arid region.

Global Pyrogeography: the Current and Future Distribution of Wildfire

PubMed Central

Krawchuk, Meg A.; Moritz, Max A.; Parisien, Marc-André; Van Dorn, Jeff; Hayhoe, Katharine

2009-01-01

Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning. PMID:19352494

Making Sense of Palaeoclimate Sensitivity

NASA Technical Reports Server (NTRS)

Rohling, E. J.; Sluijs, A.; DeConto, R.; Drijfhout, S. S.; Fedorov, A.; Foster, G. L.; Ganopolski, A.; Hansen, J.; Honisch, B.; Hooghiemstra, H.;

Re-Shuffling of Species with Climate Disruption: A No-Analog Future for California Birds?

PubMed Central

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

2009-01-01

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

Climate change impacts on selected global rangeland ecosystem services.

PubMed

Boone, Randall B; Conant, Richard T; Sircely, Jason; Thornton, Philip K; Herrero, Mario

2018-03-01

Rangelands are Earth's dominant land cover and are important providers of ecosystem services. Reliance on rangelands is projected to grow, thus understanding the sensitivity of rangelands to future climates is essential. We used a new ecosystem model of moderate complexity that allows, for the first time, to quantify global changes expected in rangelands under future climates. The mean global annual net primary production (NPP) may decline by 10 g C m -2  year -1 in 2050 under Representative Concentration Pathway (RCP) 8.5, but herbaceous NPP is projected to increase slightly (i.e., average of 3 g C m -2  year -1 ). Responses vary substantially from place-to-place, with large increases in annual productivity projected in northern regions (e.g., a 21% increase in productivity in the US and Canada) and large declines in western Africa (-46% in sub-Saharan western Africa) and Australia (-17%). Soil organic carbon is projected to increase in Australia (9%), the Middle East (14%), and central Asia (16%) and decline in many African savannas (e.g., -18% in sub-Saharan western Africa). Livestock are projected to decline 7.5 to 9.6%, an economic loss of from $9.7 to $12.6 billion. Our results suggest that forage production in Africa is sensitive to changes in climate, which will have substantial impacts on the livelihoods of the more than 180 million people who raise livestock on those rangelands. Our approach and the simulation tool presented here offer considerable potential for forecasting future conditions, highlight regions of concern, and support analyses where costs and benefits of adaptations and policies may be quantified. Otherwise, the technical options and policy and enabling environment that are needed to facilitate widespread adaptation may be very difficult to elucidate. © 2017 John Wiley & Sons Ltd.

A robust impact assessment that informs actionable climate change adaptation: future sunburn browning risk in apple

NASA Astrophysics Data System (ADS)

Webb, Leanne; Darbyshire, Rebecca; Erwin, Tim; Goodwin, Ian

2017-05-01

Climate change impact assessments are predominantly undertaken for the purpose of informing future adaptation decisions. Often, the complexity of the methodology hinders the actionable outcomes. The approach used here illustrates the importance of considering uncertainty in future climate projections, at the same time providing robust and simple to interpret information for decision-makers. By quantifying current and future exposure of Royal Gala apple to damaging temperature extremes across ten important pome fruit-growing locations in Australia, differences in impact to ripening fruit are highlighted, with, by the end of the twenty-first century, some locations maintaining no sunburn browning risk, while others potentially experiencing the risk for the majority of the January ripening period. Installation of over-tree netting can reduce the impact of sunburn browning. The benefits from employing this management option varied across the ten study locations. The two approaches explored to assist decision-makers assess this information (a) using sunburn browning risk analogues and (b) through identifying hypothetical sunburn browning risk thresholds, resulted in varying recommendations for introducing over-tree netting. These recommendations were location and future time period dependent with some sites showing no benefit for sunburn protection from nets even by the end of the twenty-first century and others already deriving benefits from employing this adaptation option. Potential best and worst cases of sunburn browning risk and its potential reduction through introduction of over-tree nets were explored. The range of results presented highlights the importance of addressing uncertainty in climate projections that result from different global climate models and possible future emission pathways.

A robust impact assessment that informs actionable climate change adaptation: future sunburn browning risk in apple.

PubMed

Webb, Leanne; Darbyshire, Rebecca; Erwin, Tim; Goodwin, Ian

2017-05-01

Climate change impact assessments are predominantly undertaken for the purpose of informing future adaptation decisions. Often, the complexity of the methodology hinders the actionable outcomes. The approach used here illustrates the importance of considering uncertainty in future climate projections, at the same time providing robust and simple to interpret information for decision-makers. By quantifying current and future exposure of Royal Gala apple to damaging temperature extremes across ten important pome fruit-growing locations in Australia, differences in impact to ripening fruit are highlighted, with, by the end of the twenty-first century, some locations maintaining no sunburn browning risk, while others potentially experiencing the risk for the majority of the January ripening period. Installation of over-tree netting can reduce the impact of sunburn browning. The benefits from employing this management option varied across the ten study locations. The two approaches explored to assist decision-makers assess this information (a) using sunburn browning risk analogues and (b) through identifying hypothetical sunburn browning risk thresholds, resulted in varying recommendations for introducing over-tree netting. These recommendations were location and future time period dependent with some sites showing no benefit for sunburn protection from nets even by the end of the twenty-first century and others already deriving benefits from employing this adaptation option. Potential best and worst cases of sunburn browning risk and its potential reduction through introduction of over-tree nets were explored. The range of results presented highlights the importance of addressing uncertainty in climate projections that result from different global climate models and possible future emission pathways.

Climate change-related temperature impacts on warm season heat mortality: a proof-of-concept methodology using BenMAP.

PubMed

Voorhees, A Scott; Fann, Neal; Fulcher, Charles; Dolwick, Patrick; Hubbell, Bryan; Bierwagen, Britta; Morefield, Philip

2011-02-15

Climate change is anticipated to raise overall temperatures and is likely to increase heat-related human health morbidity and mortality risks. The objective of this work was to develop a proof-of-concept approach for estimating excess heat-related premature deaths in the continental United States resulting from potential changes in future temperature using the BenMAP model. In this approach we adapt the methods and tools that the US Environmental Protection Agency uses to assess air pollution health impacts by incorporating temperature modeling and heat mortality health impact functions. This new method demonstrates the ability to apply the existing temperature-health literature to quantify prospective changes in climate-sensitive heat-related mortality. We compared estimates of future temperature with and without climate change and applied heat-mortality health functions to estimate relative changes in heat-related premature mortality. Using the A1B emissions scenario, we applied the GISS-II global circulation model downscaled to 36-km using MM5 and formatted using the Meteorology-Chemistry Interface Processor. For averaged temperatures derived from the 5 years 2048-2052 relative to 1999-2003 we estimated for the warm season May-September a national U.S. estimate of annual incidence of heat-related mortality to be 3700-3800 from all causes, 3500 from cardiovascular disease, and 21 000-27 000 from nonaccidental death, applying various health impact functions. Our estimates of mortality, produced to validate the application of a new methodology, suggest the importance of quantifying heat impacts in economic assessments of climate change.

Comparing extraction rates of fossil fuel producers against global climate goals

NASA Astrophysics Data System (ADS)

Rekker, Saphira A. C.; O'Brien, Katherine R.; Humphrey, Jacquelyn E.; Pascale, Andrew C.

2018-06-01

Meeting global and national climate goals requires action and cooperation from a multitude of actors1,2. Current methods to define greenhouse gas emission targets for companies fail to acknowledge the unique influence of fossil fuel producers: combustion of reported fossil fuel reserves has the potential to push global warming above 2 °C by 2050, regardless of other efforts to mitigate climate change3. Here, we introduce a method to compare the extraction rates of individual fossil fuel producers against global climate targets, using two different approaches to quantify a burnable fossil fuel allowance (BFFA). BFFAs are calculated and compared with cumulative extraction since 2010 for the world's ten largest investor-owned companies and ten largest state-owned entities (SOEs), for oil and for gas, which together account for the majority of global oil and gas reserves and production. The results are strongly influenced by how BFFAs are quantified; allocating based on reserves favours SOEs over investor-owned companies, while allocating based on production would require most reduction to come from SOEs. Future research could refine the BFFA to account for equity, cost-effectiveness and emissions intensity.

Adapting wheat to uncertain future

NASA Astrophysics Data System (ADS)

Semenov, Mikhail; Stratonovitch, Pierre

2015-04-01

This study describes integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator, which delivers an attractive option for downscaling of large-scale climate projections from global climate models (GCMs) to local-scale climate scenarios for impact assessments. A subset of 18 GCMs from the CMIP5 ensemble and 2 RCPs, RCP4.5 and RCP8.5, were integrated with LARS-WG. Climate sensitivity indexes for temperature and precipitation were computed for all GCMs and for 21 regions in the world. For computationally demanding impact assessments, where it is not practical to explore all possible combinations of GCM × RCP, climate sensitivity indexes could be used to select a subset of GCMs from CMIP5 with contrasting climate sensitivity. This would allow to quantify uncertainty in impacts resulting from the CMIP5 ensemble by conducting fewer simulation experiments. As an example, an in silico design of wheat ideotype optimised for future climate scenarios in Europe was described. Two contrasting GCMs were selected for the analysis, "hot" HadGEM2-ES and "cool" GISS-E2-R-CC, along with 2 RCPs. Despite large uncertainty in climate projections, several wheat traits were identified as beneficial for the high-yielding wheat ideotypes that could be used as targets for wheat improvement by breeders.

Increasing impacts of climate extremes on critical infrastructures in Europe

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Bianchi, Alessandra; Feyen, Luc; Silva, Filipe Batista e.; Marin, Mario; Lavalle, Carlo; Leblois, Antoine

2016-04-01

The projected increases in exposure to multiple climate hazards in many regions of Europe, emphasize the relevance of a multi-hazard risk assessment to comprehensively quantify potential impacts of climate change and develop suitable adaptation strategies. In this context, quantifying the future impacts of climatic extremes on critical infrastructures is crucial due to their key role for human wellbeing and their effects on the overall economy. Critical infrastructures describe the existing assets and systems that are essential for the maintenance of vital societal functions, health, safety, security, economic or social well-being of people, and the disruption or destruction of which would have a significant impact as a result of the failure to maintain those functions. We assess the direct damages of heat and cold waves, river and coastal flooding, droughts, wildfires and windstorms to energy, transport, industry and social infrastructures in Europe along the 21st century. The methodology integrates in a coherent framework climate hazard, exposure and vulnerability components. Overall damage is expected to rise up to 38 billion €/yr, ten time-folds the current climate damage, with drastic variations in risk scenarios. Exemplificative are drought and heat-related damages that could represent 70% of the overall climate damage in 2080s versus the current 12%. Many regions, prominently Southern Europe, will likely suffer multiple stresses and systematic infrastructure failures due to climate extremes if no suitable adaptation measures will be taken.

Globalization to amplify economic climate losses

NASA Astrophysics Data System (ADS)

Otto, C.; Wenz, L.; Levermann, A.

2015-12-01

Economic welfare under enhanced anthropogenic carbon emissions and associated future warming poses a major challenge for a society with an evolving globally connected economy. Unabated climate change will impact economic output for example through heat-stress-related reductions in productivity. Since meteorologically-induced production reductions can propagate along supply chains, structural changes in the economic network may influence climate-related losses. The role of the economic network evolution for climate impacts has been neither quantified nor qualitatively understood. Here we show that since the beginning of the 21st century the structural change of the global supply network has been such that an increase of spillover losses due to unanticipated climatic events has to be expected. We quantify primary, secondary and higher-order losses from reduced labor productivity under past and present economic and climatic conditions and find that indirect losses are significant and increase with rising temperatures. The connectivity of the economic network has increased in such a way as to foster the propagation of production loss. This supply chain connectivity robustly exhibits the characteristic distribution of self-organized criticality which has been shifted towards higher values since 2001. Losses due to this structural evolution dominated over the effect of comparably weak climatic changes during this decade. Our finding suggests that the current form of globalization may amplify losses due to climatic extremes and thus necessitate structural adaptation that requires more foresight than presently prevalent.

Assessing vulnerable and expanding vegetation stands and species in the San Francisco Bay Area for conservation management under climate change

NASA Astrophysics Data System (ADS)

Morueta-Holme, N.; Heller, N. E.; McLaughlin, B.; Weiss, S. B.; Ackerly, D.

2015-12-01

The distribution of suitable climatic areas for species and vegetation types is expected to shift due to ongoing climate change. While the pace at which current distributions will shift is hard to quantify, predictions of where climatically suitable areas will be in the future can allow us to map 1) areas currently occupied by a species or vegetation type unlikely to persist through the end of this century (vulnerable stands), 2) areas likely to do better in the future and serve as nuclei for population expansion (expanding stands), and 3) areas likely to act as climate refugia (persisting stands). We quantified the vulnerability of 27 individual plant species and 27 vegetation types in the San Francisco Bay Area as well as the conservation importance, vulnerability, and resilience of selected management sites for climate change resilient conservation. To this end, we developed California-wide models of species and vegetation distributions using climate data from the 2014 California Basin Characterization Model at a 270 m resolution, projected to 18 different end-of century climate change scenarios. Combining these distribution models with high resolution maps of current vegetation, we were able to map projected vulnerable, expanding, and persisting stands within the Bay Area. We show that vegetation and species are expected to shift considerably within the study region over the next decades; although we also identify refugia potentially able to offset some of the negative impacts of climate change. We discuss the implications for managers that wish to incorporate climate change in conservation decisions, in particular related to choosing species for restoration, identifying areas to collect seeds for restoration, and preparing for expected major vegetation changes. Our evaluation of individual management sites highlights the need for stronger coordination of efforts across sites to prioritize monitoring and protection of species whose ranges are contracting elsewhere. Finally, we present and discuss novel ways in visualizing and communicating condensed predictions and their uncertainty to land managers and challenges inherent. This work is part of the Terrestrial Biodiversity and Climate Change Collaborative, committed to developing a scientific basis for climate adaptation conservation strategies.

Quantifying Changes in Future Intensity-Duration-Frequency Curves Using Multimodel Ensemble Simulations

NASA Astrophysics Data System (ADS)

Ragno, Elisa; AghaKouchak, Amir; Love, Charlotte A.; Cheng, Linyin; Vahedifard, Farshid; Lima, Carlos H. R.

2018-03-01

During the last century, we have observed a warming climate with more intense precipitation extremes in some regions, likely due to increases in the atmosphere's water holding capacity. Traditionally, infrastructure design and rainfall-triggered landslide models rely on the notion of stationarity, which assumes that the statistics of extremes do not change significantly over time. However, in a warming climate, infrastructures and natural slopes will likely face more severe climatic conditions, with potential human and socioeconomical consequences. Here we outline a framework for quantifying climate change impacts based on the magnitude and frequency of extreme rainfall events using bias corrected historical and multimodel projected precipitation extremes. The approach evaluates changes in rainfall Intensity-Duration-Frequency (IDF) curves and their uncertainty bounds using a nonstationary model based on Bayesian inference. We show that highly populated areas across the United States may experience extreme precipitation events up to 20% more intense and twice as frequent, relative to historical records, despite the expectation of unchanged annual mean precipitation. Since IDF curves are widely used for infrastructure design and risk assessment, the proposed framework offers an avenue for assessing resilience of infrastructure and landslide hazard in a warming climate.

Determining climate effects on US total agricultural productivity.

PubMed

Liang, Xin-Zhong; Wu, You; Chambers, Robert G; Schmoldt, Daniel L; Gao, Wei; Liu, Chaoshun; Liu, Yan-An; Sun, Chao; Kennedy, Jennifer A

2017-03-21

The sensitivity of agricultural productivity to climate has not been sufficiently quantified. The total factor productivity (TFP) of the US agricultural economy has grown continuously for over half a century, with most of the growth typically attributed to technical change. Many studies have examined the effects of local climate on partial productivity measures such as crop yields and economic returns, but these measures cannot account for national-level impacts. Quantifying the relationships between TFP and climate is critical to understanding whether current US agricultural productivity growth will continue into the future. We analyze correlations between regional climate variations and national TFP changes, identify key climate indices, and build a multivariate regression model predicting the growth of agricultural TFP based on a physical understanding of its historical relationship with climate. We show that temperature and precipitation in distinct agricultural regions and seasons explain ∼70% of variations in TFP growth during 1981-2010. To date, the aggregate effects of these regional climate trends on TFP have been outweighed by improvements in technology. Should these relationships continue, however, the projected climate changes could cause TFP to drop by an average 2.84 to 4.34% per year under medium to high emissions scenarios. As a result, TFP could fall to pre-1980 levels by 2050 even when accounting for present rates of innovation. Our analysis provides an empirical foundation for integrated assessment by linking regional climate effects to national economic outcomes, offering a more objective resource for policy making.

Determining climate effects on US total agricultural productivity

PubMed Central

Wu, You; Chambers, Robert G.; Schmoldt, Daniel L.; Gao, Wei; Liu, Chaoshun; Liu, Yan-An; Sun, Chao; Kennedy, Jennifer A.

2017-01-01

The sensitivity of agricultural productivity to climate has not been sufficiently quantified. The total factor productivity (TFP) of the US agricultural economy has grown continuously for over half a century, with most of the growth typically attributed to technical change. Many studies have examined the effects of local climate on partial productivity measures such as crop yields and economic returns, but these measures cannot account for national-level impacts. Quantifying the relationships between TFP and climate is critical to understanding whether current US agricultural productivity growth will continue into the future. We analyze correlations between regional climate variations and national TFP changes, identify key climate indices, and build a multivariate regression model predicting the growth of agricultural TFP based on a physical understanding of its historical relationship with climate. We show that temperature and precipitation in distinct agricultural regions and seasons explain ∼70% of variations in TFP growth during 1981–2010. To date, the aggregate effects of these regional climate trends on TFP have been outweighed by improvements in technology. Should these relationships continue, however, the projected climate changes could cause TFP to drop by an average 2.84 to 4.34% per year under medium to high emissions scenarios. As a result, TFP could fall to pre-1980 levels by 2050 even when accounting for present rates of innovation. Our analysis provides an empirical foundation for integrated assessment by linking regional climate effects to national economic outcomes, offering a more objective resource for policy making. PMID:28265075

Determining climate effects on US total agricultural productivity

NASA Astrophysics Data System (ADS)

Liang, Xin-Zhong; Wu, You; Chambers, Robert G.; Schmoldt, Daniel L.; Gao, Wei; Liu, Chaoshun; Liu, Yan-An; Sun, Chao; Kennedy, Jennifer A.

2017-03-01

The sensitivity of agricultural productivity to climate has not been sufficiently quantified. The total factor productivity (TFP) of the US agricultural economy has grown continuously for over half a century, with most of the growth typically attributed to technical change. Many studies have examined the effects of local climate on partial productivity measures such as crop yields and economic returns, but these measures cannot account for national-level impacts. Quantifying the relationships between TFP and climate is critical to understanding whether current US agricultural productivity growth will continue into the future. We analyze correlations between regional climate variations and national TFP changes, identify key climate indices, and build a multivariate regression model predicting the growth of agricultural TFP based on a physical understanding of its historical relationship with climate. We show that temperature and precipitation in distinct agricultural regions and seasons explain ˜70% of variations in TFP growth during 1981-2010. To date, the aggregate effects of these regional climate trends on TFP have been outweighed by improvements in technology. Should these relationships continue, however, the projected climate changes could cause TFP to drop by an average 2.84 to 4.34% per year under medium to high emissions scenarios. As a result, TFP could fall to pre-1980 levels by 2050 even when accounting for present rates of innovation. Our analysis provides an empirical foundation for integrated assessment by linking regional climate effects to national economic outcomes, offering a more objective resource for policy making.

Past and predicted future effects of housing growth on open space conservation opportunity areas and habitat connectivity around National Wildlife Refuges

USGS Publications Warehouse

Hamilton, Christopher M.; Baumann, Matthias; Pidgeon, Anna M.; Helmers, David P.; Thogmartin, Wayne E.; Heglund, Patricia J.; Radeloff, Volker C.

2016-01-01

ContextHousing growth can alter suitability of matrix habitats around protected areas, strongly affecting movements of organisms and, consequently, threatening connectivity of protected area networks.ObjectivesOur goal was to quantify distribution and growth of housing around the U.S. Fish and Wildlife Service National Wildlife Refuge System. This is important information for conservation planning, particularly given promotion of habitat connectivity as a climate change adaptation measure.MethodsWe quantified housing growth from 1940 to 2000 and projected future growth to 2030 within three distances from refuges, identifying very low housing density open space, “opportunity areas” (contiguous areas with <6.17 houses/km2), both nationally and by USFWS administrative region. Additionally, we quantified number and area of habitat corridors within these opportunity areas in 2000.ResultsOur results indicated that the number and area of open space opportunity areas generally decreased with increasing distance from refuges and with the passage of time. Furthermore, total area in habitat corridors was much lower than in opportunity areas. In addition, the number of corridors sometimes exceeded number of opportunity areas as a result of habitat fragmentation, indicating corridors are likely vulnerable to land use change. Finally, regional differences were strong and indicated some refuges may have experienced so much housing growth already that they are effectively too isolated to adapt to climate change, while others may require extensive habitat restoration work.ConclusionsWildlife refuges are increasingly isolated by residential housing development, potentially constraining the movement of wildlife and, therefore, their ability to adapt to a changing climate.

Sensitivity of future U.S. water shortages to socioeconomic and climate drivers: A case study in Georgia using an integrated human-earth system modeling framework

DOE PAGES

Scott, Michael J.; Daly, Don S.; Hejazi, Mohamad I.; ...

2016-02-06

Here, one of the most important interactions between humans and climate is in the demand and supply of water. Humans withdraw, use, and consume water and return waste water to the environment for a variety of socioeconomic purposes, including domestic, commercial, and industrial use, production of energy resources and cooling thermal-electric power plants, and growing food, fiber, and chemical feed stocks for human consumption. Uncertainties in the future human demand for water interact with future impacts of climatic change on water supplies to impinge on water management decisions at the international, national, regional, and local level, but until recently toolsmore » were not available to assess the uncertainties surrounding these decisions. This paper demonstrates the use of a multi-model framework in a structured sensitivity analysis to project and quantify the sensitivity of future deficits in surface water in the context of climate and socioeconomic change for all U.S. states and sub-basins. The framework treats all sources of water demand and supply consistently from the world to local level. The paper illustrates the capabilities of the framework with sample results for a river sub-basin in the U.S. state of Georgia.« less

Climate change and agricultural development: adapting Polish agriculture to reduce future nutrient loads in a coastal watershed.

PubMed

Piniewski, Mikołaj; Kardel, Ignacy; Giełczewski, Marek; Marcinkowski, Paweł; Okruszko, Tomasz

2014-09-01

Currently, there is a major concern about the future of nutrient loads discharged into the Baltic Sea from Polish rivers because they are main contributors to its eutrophication. To date, no watershed-scale studies have properly addressed this issue. This paper fills this gap by using a scenario-modeling framework applied in the Reda watershed, a small (482 km²) agricultural coastal area in northern Poland. We used the SWAT model to quantify the effects of future climate, land cover, and management changes under multiple scenarios up to the 2050s. The combined effect of climate and land use change on N-NO3 and P-PO4 loads is an increase by 20-60 and 24-31 %, respectively, depending on the intensity of future agricultural usage. Using a scenario that assumes a major shift toward a more intensive agriculture following the Danish model would bring significantly higher crop yields but cause a great deterioration of water quality. Using vegetative cover in winter and spring (VC) would be a very efficient way to reduce future P-PO4 loads so that they are lower than levels observed at present. However, even the best combination of measures (VC, buffer zones, reduced fertilization, and constructed wetlands) would not help to remediate heavily increased N-NO3 loads due to climate change and agricultural intensification.

The Finer Details: Climate Modeling

NASA Technical Reports Server (NTRS)

2000-01-01

If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

Albedo feedbacks to future climate via climate change impacts on dryland biocrusts.

PubMed

Rutherford, William A; Painter, Thomas H; Ferrenberg, Scott; Belnap, Jayne; Okin, Gregory S; Flagg, Cody; Reed, Sasha C

2017-03-10

Drylands represent the planet's largest terrestrial biome and evidence suggests these landscapes have large potential for creating feedbacks to future climate. Recent studies also indicate that dryland ecosystems are responding markedly to climate change. Biological soil crusts (biocrusts) ‒ soil surface communities of lichens, mosses, and/or cyanobacteria ‒ comprise up to 70% of dryland cover and help govern fundamental ecosystem functions, including soil stabilization and carbon uptake. Drylands are expected to experience significant changes in temperature and precipitation regimes, and such alterations may impact biocrust communities by promoting rapid mortality of foundational species. In turn, biocrust community shifts affect land surface cover and roughness-changes that can dramatically alter albedo. We tested this hypothesis in a full-factorial warming (+4 °C above ambient) and altered precipitation (increased frequency of 1.2 mm monsoon-type watering events) experiment on the Colorado Plateau, USA. We quantified changes in shortwave albedo via multi-angle, solar-reflectance measurements. Warming and watering treatments each led to large increases in albedo (>30%). This increase was driven by biophysical factors related to treatment effects on cyanobacteria cover and soil surface roughness following treatment-induced moss and lichen mortality. A rise in dryland surface albedo may represent a previously unidentified feedback to future climate.

Albedo feedbacks to future climate via climate change impacts on dryland biocrusts

NASA Astrophysics Data System (ADS)

Rutherford, William A.; Painter, Thomas H.; Ferrenberg, Scott; Belnap, Jayne; Okin, Gregory S.; Flagg, Cody; Reed, Sasha C.

2017-03-01

Drylands represent the planet’s largest terrestrial biome and evidence suggests these landscapes have large potential for creating feedbacks to future climate. Recent studies also indicate that dryland ecosystems are responding markedly to climate change. Biological soil crusts (biocrusts) ‒ soil surface communities of lichens, mosses, and/or cyanobacteria ‒ comprise up to 70% of dryland cover and help govern fundamental ecosystem functions, including soil stabilization and carbon uptake. Drylands are expected to experience significant changes in temperature and precipitation regimes, and such alterations may impact biocrust communities by promoting rapid mortality of foundational species. In turn, biocrust community shifts affect land surface cover and roughness—changes that can dramatically alter albedo. We tested this hypothesis in a full-factorial warming (+4 °C above ambient) and altered precipitation (increased frequency of 1.2 mm monsoon-type watering events) experiment on the Colorado Plateau, USA. We quantified changes in shortwave albedo via multi-angle, solar-reflectance measurements. Warming and watering treatments each led to large increases in albedo (>30%). This increase was driven by biophysical factors related to treatment effects on cyanobacteria cover and soil surface roughness following treatment-induced moss and lichen mortality. A rise in dryland surface albedo may represent a previously unidentified feedback to future climate.

Albedo feedbacks to future climate via climate change impacts on dryland biocrusts

USGS Publications Warehouse

Rutherford, William A.; Painter, Thomas H.; Ferrenberg, Scott; Belnap, Jayne; Okin, Gregory S.; Flagg, Cody B.; Reed, Sasha C.

2017-01-01

Drylands represent the planet’s largest terrestrial biome and evidence suggests these landscapes have large potential for creating feedbacks to future climate. Recent studies also indicate that dryland ecosystems are responding markedly to climate change. Biological soil crusts (biocrusts) ‒ soil surface communities of lichens, mosses, and/or cyanobacteria ‒ comprise up to 70% of dryland cover and help govern fundamental ecosystem functions, including soil stabilization and carbon uptake. Drylands are expected to experience significant changes in temperature and precipitation regimes, and such alterations may impact biocrust communities by promoting rapid mortality of foundational species. In turn, biocrust community shifts affect land surface cover and roughness—changes that can dramatically alter albedo. We tested this hypothesis in a full-factorial warming (+4 °C above ambient) and altered precipitation (increased frequency of 1.2 mm monsoon-type watering events) experiment on the Colorado Plateau, USA. We quantified changes in shortwave albedo via multi-angle, solar-reflectance measurements. Warming and watering treatments each led to large increases in albedo (>30%). This increase was driven by biophysical factors related to treatment effects on cyanobacteria cover and soil surface roughness following treatment-induced moss and lichen mortality. A rise in dryland surface albedo may represent a previously unidentified feedback to future climate.

Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity.

PubMed

Mercado, Lina M; Medlyn, Belinda E; Huntingford, Chris; Oliver, Rebecca J; Clark, Douglas B; Sitch, Stephen; Zelazowski, Przemyslaw; Kattge, Jens; Harper, Anna B; Cox, Peter M

2018-06-01

Plant temperature responses vary geographically, reflecting thermally contrasting habitats and long-term species adaptations to their climate of origin. Plants also can acclimate to fast temporal changes in temperature regime to mitigate stress. Although plant photosynthetic responses are known to acclimate to temperature, many global models used to predict future vegetation and climate-carbon interactions do not include this process. We quantify the global and regional impacts of biogeographical variability and thermal acclimation of temperature response of photosynthetic capacity on the terrestrial carbon (C) cycle between 1860 and 2100 within a coupled climate-carbon cycle model, that emulates 22 global climate models. Results indicate that inclusion of biogeographical variation in photosynthetic temperature response is most important for present-day and future C uptake, with increasing importance of thermal acclimation under future warming. Accounting for both effects narrows the range of predictions of the simulated global land C storage in 2100 across climate projections (29% and 43% globally and in the tropics, respectively). Contrary to earlier studies, our results suggest that thermal acclimation of photosynthetic capacity makes tropical and temperate C less vulnerable to warming, but reduces the warming-induced C uptake in the boreal region under elevated CO 2 . © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Use of NARCCAP Model Projections to Develop a Future Typical Meteorological Year and Estimate the Impact of a Changing Climate on Building Energy Consumption

NASA Astrophysics Data System (ADS)

Patton, S. L.; Takle, E. S.; Passe, U.; Kalvelage, K.

2013-12-01

Current simulations of building energy consumption use weather input files based on the past thirty years of climate observations. These 20th century climate conditions may be inadequate when designing buildings meant to function well into the 21st century. An alternative is using model projections of climate change to estimate future risk to the built environment. In this study, model-projected changes in climate were combined with existing typical meteorological year data to create future typical meteorological year data. These data were then formatted for use in EnergyPlus simulation software to evaluate their potential impact on commercial building energy consumption. The modeled climate data were taken from the North American Regional Climate Change Assessment Program (NARCCAP). NARCCAP uses results of global climate models to drive regional climate models, also known as dynamical downscaling. This downscaling gives higher resolution results over specific locations, and the multiple global/regional climate model combinations provide a unique opportunity to quantify the uncertainty of climate change projections and their impacts. Our results show a projected decrease in heating energy consumption and a projected increase in cooling energy consumption for nine locations across the United States for all model combinations. Warmer locations may expect a decrease in heating load of around 30% to 45% and an increase in cooling load of around 25% to 35%. Colder locations may expect a decrease in heating load of around 15% to 25% and an increase in cooling load of around 40% to 70%. The change in net energy consumption is determined by the balance between the magnitudes of heating change and cooling change. Net energy consumption is projected to increase by an average of 5% for lower-latitude locations and decrease by an average of 5% for higher-latitude locations. With these projected annual and seasonal changes presenting strong evidence for the unsuitable nature of current building practices holding up under future climate change, we recommend using our methods and results to make modifications and adaptations to existing buildings and to aid in the design of future buildings.

Risk based adaptation of infrastructures to floods and storm surges induced by climate change.

NASA Astrophysics Data System (ADS)

Luna, Byron Quan; Garrè, Luca; Hansen, Peter Friis

2014-05-01

Coastal natural hazards are changing in frequency and intensity associated to climate change. These extreme events combined with an increase in the extent of vulnerable societies will lead to an increase of substantial monetary losses. For this reason, adaptive measures are required to identify the effective and adequate measures to withstand the impacts of climate change. Decision strategies are needed for the timing of investments and for the allocation of resources to safeguard the future in a sustainable manner. Adapting structures to climate change requires decision making under uncertainties. Therefore, it is vital that risk assessments are generated on a reliable and appropriate evaluation of the involved uncertainties. Linking a Bayesian network (BN) to a Geographic Information System (GIS) for a risk assessment enables to model all the relevant parameters, their causal relations and the involved uncertainties. The integration of the probabilistic approach into a GIS allows quantifying and visualizing uncertainties in a spatial manner. By addressing these uncertainties, the Bayesian Network approach allows quantifying their effects; and facilitates the identification of future model improvements and where other efforts should be concentrated. The final results can be applied as a supportive tool for presenting reliable risk assessments to decision-makers. Based on this premises, a case study was performed to assess how the storm surge magnitude and flooding extent of an event with similar characteristics to the Sandy Super storm will occur in 2050 and 2090.

Diver Down: Remote Sensing of Carbon Climate Feedbacks

NASA Astrophysics Data System (ADS)

Schimel, D.; Chatterjee, A.; Baker, D. F.; Basu, S.; Denning, A. S.; Schuh, A. E.; Crowell, S.; Jacobson, A. R.; Bowman, K. W.; Liu, J.; O'Dell, C.

2016-12-01

What controls the rate of increase of CO2 and CH4 in the atmosphere? It may seem self-evident but actually remains mysterious. The increases of CO2 and CH4 result from a combination of forcing from anthropogenic emissions and Earth System feedbacks that dampen or amplify the effects of those emissions on atmospheric concentrations. The fraction of anthropogenic CO2 remaining in the atmosphere has remained remarkably constant over the last 59 years but has shown recent dynamics and if it changes in the future, will affect the climate impact of any given fossil fuel regime. While greenhouse gases affect the global atmosphere, their sources and sinks are remarkably heterogeneous in time and space, and traditional in situ observing systems do not provide the coverage and resolution to quantify carbon-climate feedbacks or reduce the uncertainty of model predictions. Here we describe an methodology for estimating critical carbon-climate feedback effects of current spaceborne XCO2 measurements, developed by the OCO-2 Flux Group, and applied to OCO-2 and GOSAT data. The methodology allows integration of the space-based carbon budgets with other global data sets, and exposes the impact of residual bias error on the estimated fluxes, allowing the uncertainty of the estimated feedbacks to be quantified. The approach is limited by the short timeseries currently available, but suggests dramatic changes to the carbon cycle over the recent past. We present the methodology, early results and implications for a future, sustained carbon observing system.

Increasing weather-related impacts on European population under climate and demographic change

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Cescatti, Alessandro; Batista e Silva, Filipe; Kovats, Sari R.; Feyen, Luc

2017-04-01

Over the last three decades the overwhelming majority of disasters have been caused by weather-related events. The observed rise in weather-related disaster losses has been largely attributed to increased exposure and to a lesser degree to global warming. Recent studies suggest an intensification in the climatology of multiple weather extremes in Europe over the coming decades in view of climate change, while urbanization continues. In view of these pressures, understanding and quantifying the potential impacts of extreme weather events on future societies is imperative in order to identify where and to what extent their livelihoods will be at risk in the future, and develop timely and effective adaptation and disaster risk reduction strategies. Here we show a comprehensive assessment of single- and multi-hazard impacts on the European population until the year 2100. For this purpose, we developed a novel methodology that quantifies the human impacts as a multiplicative function of hazard, exposure and population vulnerability. We focus on seven of the most impacting weather-related hazards - including heat and cold waves, wildfires, droughts, river and coastal floods and windstorms - and evaluated their spatial and temporal variations in intensity and frequency under a business-as-usual climate scenario. Long-term demographic dynamics were modelled to assess exposure developments under a corresponding middle-of-the-road scenario. Vulnerability of humans to weather extremes was appraised based on more than 2300 records of weather-related disasters. The integration of these elements provides a range of plausible estimates of extreme weather-related risks for future European generations. Expected impacts on population are quantified in terms of fatalities and number of people exposed. We find a staggering rise in fatalities from extreme weather events, with the projected death toll by the end of the century amounting to more than 50 times the present number of people killed. Approximately two-thirds of European citizens could then be exposed to a weather-related disaster each year, which will bring about huge rises in health costs to society. Future impacts show a prominent spatial gradient towards southern regions, where weather extremes could become the greatest environmental risk factor for people. The projected changes are dominated by global warming, mainly through a rise in heatwaves, but ongoing urbanization, development in hazard-prone areas and ageing population will likely further increase human risk. The results call for immediate action to achieve the Paris goals on climate mitigation and adaptation in order to protect future European generations.

Improving assessment and modelling of climate change impacts on global terrestrial biodiversity.

PubMed

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

2011-05-01

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

Meltwater Contributions to Irrigation in High Mountain Asia Under a Changing Climate

NASA Astrophysics Data System (ADS)

Grogan, D. S.; Wisser, D.; Proussevitch, A. A.; Lammers, R. B.; Frolking, S. E.

2016-12-01

Snow melt and glacier melt are known to contribute significantly to river flows in High Mountain Asia. This region is also an important agricultural producer, and relies heavily on irrigation. In this study we use a hydrologic model coupled with a glacier model to quantify the historical contribution of snow melt and glacier melt to irrigation water use in High Mountain Asia, with detailed basin-level budgets of meltwater use, re-use, and contributions to crop evapotranspiration. We find that it is important to quantify not only how much meltwater is extracted from rivers and reservoirs for irrigation, but also to track this water through irrigation return flows and downstream re-use. We also project future basin-level meltwater use for irrigation, making use of a suite of climate model projections and associated glacier model projections. We assess the relative importance of snow melt and glacier melt to irrigation supplies across seasons, and for future projections we compare temporal shifts in meltwater hydrographs to potential shifts in crop planting dates due to increasing temperatures and shifts in monsoon onset. Results show that, historically (c. 2000), meltwater for irrigation is most important in the Indus and Ganges basins, which use 90 km3yr-1 and 20 km3yr-1 meltwater, respectively. In both basins, snow melt contributions to annual irrigation use are larger than glacier melt contributions, but the relative importance of these two meltwater sources shifts through the growing season. Uncertainties in future precipitation projections lead to large differences in the direction of change of future meltwater use for irrigation: depending upon the climate model and pathway used, we find that meltwater availability may decrease or increase in 2070-2099 compared to historical results.

Technical Note: Linking climate change and downed woody debris decomposition across forests of the eastern United States

USGS Publications Warehouse

Russell, Matthew B.; Woodall, Christopher W.; D'Amato, Anthony W.; Fraver, Shawn; Bradford, John B.

2014-01-01

Forest ecosystems play a critical role in mitigating greenhouse gas emissions. Forest carbon (C) is stored through photosynthesis and released via decomposition and combustion. Relative to C fixation in biomass, much less is known about C depletion through decomposition of woody debris, particularly under a changing climate. It is assumed that the increased temperatures and longer growing seasons associated with projected climate change will increase the decomposition rates (i.e., more rapid C cycling) of downed woody debris (DWD); however, the magnitude of this increase has not been previously addressed. Using DWD measurements collected from a national forest inventory of the eastern United States, we show that the residence time of DWD may decrease (i.e., more rapid decomposition) by as much as 13% over the next 200 years, depending on various future climate change scenarios and forest types. Although existing dynamic global vegetation models account for the decomposition process, they typically do not include the effect of a changing climate on DWD decomposition rates. We expect that an increased understanding of decomposition rates, as presented in this current work, will be needed to adequately quantify the fate of woody detritus in future forests. Furthermore, we hope these results will lead to improved models that incorporate climate change scenarios for depicting future dead wood dynamics in addition to a traditional emphasis on live-tree demographics.

The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review

PubMed Central

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

2017-01-01

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

Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

NASA Astrophysics Data System (ADS)

Taner, M. U.; Wi, S.; Brown, C.

2017-12-01

The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

Climate change and maize yield in southern Africa: what can farm management do?

PubMed

Rurinda, Jairos; van Wijk, Mark T; Mapfumo, Paul; Descheemaeker, Katrien; Supit, Iwan; Giller, Ken E

2015-12-01

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid-December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010-2039 and 2040-2069 and by 20% for 2070-2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070-2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change. © 2015 John Wiley & Sons Ltd.

A strategy for assessing potential future changes in climate, hydrology, and vegetation in the Western United States

USGS Publications Warehouse

Thompson, Robert Stephen; Hostetler, Steven W.; Bartlein, Patrick J.; Anderson, Katherine H.

1998-01-01

Historical and geological data indicate that significant changes can occur in the Earth's climate on time scales ranging from years to millennia. In addition to natural climatic change, climatic changes may occur in the near future due to increased concentrations of carbon dioxide and other trace gases in the atmosphere that are the result of human activities. International research efforts using atmospheric general circulation models (AGCM's) to assess potential climatic conditions under atmospheric carbon dioxide concentrations of twice the pre-industrial level (a '2 X CO2' atmosphere) conclude that climate would warm on a global basis. However, it is difficult to assess how the projected warmer climatic conditions would be distributed on a regional scale and what the effects of such warming would be on the landscape, especially for temperate mountainous regions such as the Western United States. In this report, we present a strategy to assess the regional sensitivity to global climatic change. The strategy makes use of a hierarchy of models ranging from an AGCM, to a regional climate model, to landscape-scale process models of hydrology and vegetation. A 2 X CO2 global climate simulation conducted with the National Center for Atmospheric Research (NCAR) GENESIS AGCM on a grid of approximately 4.5o of latitude by 7.5o of longitude was used to drive the NCAR regional climate model (RegCM) over the Western United States on a grid of 60 km by 60 km. The output from the RegCM is used directly (for hydrologic models) or interpolated onto a 15-km grid (for vegetation models) to quantify possible future environmental conditions on a spatial scale relevant to policy makers and land managers.

Quantifying and Valuing Potential Climate Change Impacts on Coral Reefs in the United States

NASA Astrophysics Data System (ADS)

Wobus, C. W.; Lane, D.; Buddemeier, R. W.; Ready, R. C.; Shouse, K. C.; Martinich, J.

2012-12-01

Global climate change presents a two-pronged threat to coral reef ecosystems: increasing sea surface temperatures will increase the likelihood of episodic bleaching events, while increasing ocean carbon dioxide concentrations will change the carbonate chemistry that drives coral growth. Because coral reefs have important societal as well as ecological benefits, climate change mitigation policies that ameliorate these impacts may create substantial economic value. We present a model that evaluates both the ecological and the economic impacts of climate change on coral reefs in the United States. We use a coral reef mortality and bleaching model to project future coral reef declines under a range of climate change policy scenarios for south Florida, Puerto Rico and Hawaii. Using a benefits transfer approach, the outputs from the physical model are then used to quantify the economic impacts of these coral reef declines for each of these regions. We find that differing climate change trajectories create substantial changes in projected coral cover and value for Hawaii, but that the ecological and economic benefits of more stringent emissions scenarios are less clear for Florida and Puerto Rico. Overall, our results indicate that the effectiveness of climate change mitigation policies may be region-specific, but that these policies could result in a net increase of nearly $10 billion in economic value from coral reef-related recreational activities alone, over the 21st century.

Investigation of Climate Change Impact on Water Resources for an Alpine Basin in Northern Italy: Implications for Evapotranspiration Modeling Complexity

PubMed Central

Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco

2014-01-01

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required beacause of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied. PMID:25285917

Investigation of climate change impact on water resources for an Alpine basin in northern Italy: implications for evapotranspiration modeling complexity.

PubMed

Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco

2014-01-01

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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.

Climate Observations from Space

NASA Astrophysics Data System (ADS)

Briggs, Stephen

2016-07-01

The latest Global Climate Observing System (GCOS) Status Report on global climate observations, delivered to the UNFCCC COP21 in November 2016, showed how satellite data are critical for observations relating to climate. Of the 50 Essential Climate Variables (ECVs) identified by GCOS as necessary for understanding climate change, about half are derived only from satellite data while half of the remainder have a significant input from satellites. Hence data from Earth observing satellite systems are now a fundamental requirement for understanding the climate system and for managing the consequences of climate change. Following the Paris Agreement of COP21 this need is only greater. Not only will satellites have to continue to provide data for modelling and predicting climate change but also for a much wider range of actions relating to climate. These include better information on loss and damage, resilience, improved adaptation to change, and on mitigation including information on greenhouse gas emissions. In addition there is an emerging need for indicators of the risks associated with future climate change which need to be better quantified, allowing policy makers both to understand what decisions need to be taken, and to see the consequences of their actions. The presentation will set out some of the ways in which satellite data are important in all aspects of understanding, managing and predicting climate change and how they may be used to support future decisions by those responsible for policy related to managing climate change and its consequences.

Climate change as a driver for future human migration

NASA Astrophysics Data System (ADS)

Chen, M.; Ricke, K.; Caldeira, K.

2016-12-01

Human migration is driven by a multitude of factors, both socioeconomic and environmental. However, as impacts of anthropogenic climate change emerge and grow, it is widely conjectured that climate change will induce migration of human populations from areas that are adversely affected by climate change to areas that are less adversely or positively affected by climate change. Both low- and high-frequency climate changes have been empirically linked to migration in areas across the globe, but there has been little global-scale quantitative analysis projecting the scale and geography of climate-motivated migration. Considering temperature and precipitation in isolation from all other factors, here we project climate-driven impacts on the areal-density of human population. From this, we infer potential destinations and origins for the climate-motivated migration. Our results indicate that tropical and sub-tropical countries are the largest likely sources of migrants, with India being the country with the greatest number of potential climate emigrants. Global warming has the potential to motivate hundreds of millions of people to migrate in the coming decades, largely from warm tropical and subtropical countries to cooler temperate countries. Migration decisions will depend on many factors beyond climate; nevertheless our work establishes a foundation for quantifying future climate-motivated migration that can act as a starting point of more comprehensive assessments. The large number of potential climate migrants indicated by our analyses provides additional incentive to reduce greenhouse gas emissions, take adaptive measures, and carefully consider migration policy.

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

NASA Astrophysics Data System (ADS)

Guo, Lanli; Sheng, Jinyu

2017-05-01

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

Flooding in the future--predicting climate change, risks and responses in urban areas.

PubMed

Ashley, R M; Balmforth, D J; Saul, A J; Blanskby, J D

2005-01-01

Engineering infrastructure is provided at high cost and is expected to have a useful operational life of decades. However, it is clear that the future is uncertain. Traditional approaches to designing and operating urban storm drainage assets have relied on past performance of natural systems and the ability to extrapolate this performance, together with that of the assets across the usable lifetime. Whether or not climate change is going to significantly alter future weather patterns in Europe, it is clear that it is now incumbent on designers and operators of storm drainage systems to prepare for greater uncertainty in the effectiveness of storm drainage systems. A recent U.K. Government study considered the potential effects of climate and socio-economic change in the U.K. in terms of four future scenarios and what the implications are for the performance of existing storm drainage facilities. In this paper the modelling that was undertaken to try to quantify the changes in risk, together with the effectiveness of responses in managing that risk, are described. It shows that flood risks may increase by a factor of almost 30 times and that traditional engineering measures alone are unlikely to be able to provide protection.

Genetic diversity is related to climatic variation and vulnerability in threatened bull trout

USGS Publications Warehouse

Kovach, Ryan; Muhlfeld, Clint C.; Wade, Alisa A.; Hand, Brian K.; Whited, Diane C.; DeHaan, Patrick W.; Al-Chokhachy, Robert K.; Luikart, Gordon

2015-01-01

Understanding how climatic variation influences ecological and evolutionary processes is crucial for informed conservation decision-making. Nevertheless, few studies have measured how climatic variation influences genetic diversity within populations or how genetic diversity is distributed across space relative to future climatic stress. Here, we tested whether patterns of genetic diversity (allelic richness) were related to climatic variation and habitat features in 130 bull trout (Salvelinus confluentus) populations from 24 watersheds (i.e., ~4–7th order river subbasins) across the Columbia River Basin, USA. We then determined whether bull trout genetic diversity was related to climate vulnerability at the watershed scale, which we quantified on the basis of exposure to future climatic conditions (projected scenarios for the 2040s) and existing habitat complexity. We found a strong gradient in genetic diversity in bull trout populations across the Columbia River Basin, where populations located in the most upstream headwater areas had the greatest genetic diversity. After accounting for spatial patterns with linear mixed models, allelic richness in bull trout populations was positively related to habitat patch size and complexity, and negatively related to maximum summer temperature and the frequency of winter flooding. These relationships strongly suggest that climatic variation influences evolutionary processes in this threatened species and that genetic diversity will likely decrease due to future climate change. Vulnerability at a watershed scale was negatively correlated with average genetic diversity (r = −0.77;P < 0.001); watersheds containing populations with lower average genetic diversity generally had the lowest habitat complexity, warmest stream temperatures, and greatest frequency of winter flooding. Together, these findings have important conservation implications for bull trout and other imperiled species. Genetic diversity is already depressed where climatic vulnerability is highest; it will likely erode further in the very places where diversity may be most needed for future persistence.

Xanthos

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

2017-05-30

Xanthos is a Python package designed to quantify and analyze global water availability in history and in future at 0.5° × 0.5° spatial resolution and a monthly time step under a changing climate. Its performance was also tested through real applications. It is open-source, extendable and convenient to researchers who work on long-term climate data for studies of global water supply, and Global Change Assessment Model (GCAM). This package integrates inherent global gridded data maps, I/O modules, Water-Balance Model modules and diagnostics modules by user-defined configuration.

States at Risk: America's Preparedness Report Card

NASA Astrophysics Data System (ADS)

Yu, R. M. S.; Strauss, B.; Kulp, S. A.; Bronzan, J.; Rodehorst, B.; Bhat, C.; Dix, B.; Savonis, M.; Wiles, R.

2015-12-01

Many states are already experiencing the costly impacts of extreme climate and weather events. The occurrence, frequency and intensity of these events may change under future climates. Preparing for these changes takes time, and state government agencies and communities need to recognize the risks they could potentially face and the response actions already undertaken. The States at Risk: America's Preparedness Report Card project is the first-ever study that quantifies five climate-change-driven hazards, and the relevant state government response actions in each of the 50 states. The changing characteristics of extreme heat, drought, wildfires, inland and coastal flooding were assessed for the baseline period (around year 2000) through the years 2030 and 2050 across all 50 states. Bias-corrected statistically-downscaled (BCSD) climate projections (Reclamation, 2013) and hydrology projections (Reclamation, 2014) from the Coupled Model Intercomparison Project phase 5 (CMIP5) under RCP8.5 were used. The climate change response action analysis covers five critical sectors: Transportation, Energy, Water, Human Health and Communities. It examined whether there is evidence that the state is taking action to (1) reduce current risks, (2) raise its awareness of future risks, (3) plan for adaptation to the future risks, and (4) implement specific actions to reduce future risks for each applicable hazards. Results from the two analyses were aggregated and translated into a rating system that standardizes assessments across states, which can be easily understood by both technical and non-technical audiences. The findings in this study not only serve as a screening tool for states to recognize the hazards they could potentially face as climate changes, but also serve as a roadmap for states to address the gaps in response actions, and to improve climate preparedness and resilience.

Assessing climate change impacts on fresh water resources of the Athabasca River Basin, Canada.

PubMed

Shrestha, Narayan Kumar; Du, Xinzhong; Wang, Junye

2017-12-01

Proper management of blue and green water resources is important for the sustainability of ecosystems and for the socio-economic development of river basins such as the Athabasca River Basin (ARB) in Canada. For this reason, quantifying climate change impacts on these water resources at a finer temporal and spatial scale is often necessary. In this study, we used a Soil and Water Assessment Tool (SWAT) to assess climate change impacts on fresh water resources, focusing explicitly on the impacts to both blue and green water. We used future climate data generated by the Canadian Center for Climate Modelling and Analysis Regional Climate Model (CanRCM4) with a spatial resolution of 0.22°×0.22° (~25km) for two emission scenarios (RCP 4.5 and 8.5). Results projected the climate of the ARB to be wetter by 21-34% and warmer by 2-5.4°C on an annual time scale. Consequently, the annual average blue and green water flow was projected to increase by 16-54% and 11-34%, respectively, depending on the region, future period, and emission scenario. Furthermore, the annual average green water storage at the boreal region was expected to increase by 30%, while the storage was projected to remain fairly stable or decrease in other regions, especially during the summer season. On average, the fresh water resources in the ARB are likely to increase in the future. However, evidence of temporal and spatial heterogeneity could pose many future challenges to water resource planners and managers. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Modelling the effects of land cover and climate change on soil water partitioning in a boreal headwater catchment

NASA Astrophysics Data System (ADS)

Wang, Hailong; Tetzlaff, Doerthe; Soulsby, Chris

2018-03-01

Climate and land cover are two major factors affecting the water fluxes and balance across spatiotemporal scales. These two factors and their impacts on hydrology are often interlinked. The quantification and differentiation of such impacts is important for developing sustainable land and water management strategies. Here, we calibrated the well-known Hydrus-1D model in a data-rich boreal headwater catchment in Scotland to assess the role of two dominant vegetation types (shrubs vs. trees) in regulating the soil water partitioning and balance. We also applied previously established climate projections for the area and replaced shrubs with trees to imitate current land use change proposals in the region, so as to quantify the potential impacts of climate and land cover changes on soil hydrology. Under tree cover, evapotranspiration and deep percolation to recharge groundwater was about 44% and 57% of annual precipitation, whilst they were about 10% lower and 9% higher respectively under shrub cover in this humid, low energy environment. Meanwhile, tree canopies intercepted 39% of annual precipitation in comparison to 23% by shrubs. Soils with shrub cover stored more water than tree cover. Land cover change was shown to have stronger impacts than projected climate change. With a complete replacement of shrubs with trees under future climate projections at this site, evapotranspiration is expected to increase by ∼39% while percolation to decrease by 21% relative to the current level, more pronounced than the modest changes in the two components (<8%) with climate change only. The impacts would be particularly marked in warm seasons, which may result in water stress experienced by the vegetation. The findings provide an important evidence base for adaptive management strategies of future changes in low-energy humid environments, where vegetation growth is usually restricted by radiative energy and not water availability while few studies that quantify soil water partitioning exist.

Designing the Climate Observing System of the Future

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Evolution of the potential distribution area of french mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-02-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growths with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE - MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20 and 21 centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5°K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak, respectively) at the end of the 21 century. While both species have complementary growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21 century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

A new paradigm of quantifying ecosystem stress through chemical signatures

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

Kravitz, Ben; Guenther, Alex B.; Gu, Lianhong

Stress-induced emissions of biogenic volatile organic compounds (VOCs) from terrestrial ecosystems may be one of the dominant sources of VOC emissions world-wide. Understanding the ecosystem stress response could reveal how ecosystems will respond and adapt to climate change and, in turn, quantify changes in the atmospheric burden of VOC oxidants and secondary organic aerosols. Here we argue, based on preliminary evidence from several opportunistic measurement sources, that chemical signatures of stress can be identified and quantified at the ecosystem scale. We also outline future endeavors that we see as next steps toward uncovering quantitative signatures of stress, including new advancesmore » in both VOC data collection and analysis of "big data."« less

Attribution of future US ozone pollution to regional emissions, climate change, long-range transport, and model deficiency

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Quantitative Estimation of the Climatic Effects of Carbon Transferred by International Trade.

PubMed

Wei, Ting; Dong, Wenjie; Moore, John; Yan, Qing; Song, Yi; Yang, Zhiyong; Yuan, Wenping; Chou, Jieming; Cui, Xuefeng; Yan, Xiaodong; Wei, Zhigang; Guo, Yan; Yang, Shili; Tian, Di; Lin, Pengfei; Yang, Song; Wen, Zhiping; Lin, Hui; Chen, Min; Feng, Guolin; Jiang, Yundi; Zhu, Xian; Chen, Juan; Wei, Xin; Shi, Wen; Zhang, Zhiguo; Dong, Juan; Li, Yexin; Chen, Deliang

2016-06-22

Carbon transfer via international trade affects the spatial pattern of global carbon emissions by redistributing emissions related to production of goods and services. It has potential impacts on attribution of the responsibility of various countries for climate change and formulation of carbon-reduction policies. However, the effect of carbon transfer on climate change has not been quantified. Here, we present a quantitative estimate of climatic impacts of carbon transfer based on a simple CO2 Impulse Response Function and three Earth System Models. The results suggest that carbon transfer leads to a migration of CO2 by 0.1-3.9 ppm or 3-9% of the rise in the global atmospheric concentrations from developed countries to developing countries during 1990-2005 and potentially reduces the effectiveness of the Kyoto Protocol by up to 5.3%. However, the induced atmospheric CO2 concentration and climate changes (e.g., in temperature, ocean heat content, and sea-ice) are very small and lie within observed interannual variability. Given continuous growth of transferred carbon emissions and their proportion in global total carbon emissions, the climatic effect of traded carbon is likely to become more significant in the future, highlighting the need to consider carbon transfer in future climate negotiations.

GCOS reference upper air network (GRUAN): Steps towards assuring future climate records

NASA Astrophysics Data System (ADS)

Thorne, P. W.; Vömel, H.; Bodeker, G.; Sommer, M.; Apituley, A.; Berger, F.; Bojinski, S.; Braathen, G.; Calpini, B.; Demoz, B.; Diamond, H. J.; Dykema, J.; Fassò, A.; Fujiwara, M.; Gardiner, T.; Hurst, D.; Leblanc, T.; Madonna, F.; Merlone, A.; Mikalsen, A.; Miller, C. D.; Reale, T.; Rannat, K.; Richter, C.; Seidel, D. J.; Shiotani, M.; Sisterson, D.; Tan, D. G. H.; Vose, R. S.; Voyles, J.; Wang, J.; Whiteman, D. N.; Williams, S.

2013-09-01

The observational climate record is a cornerstone of our scientific understanding of climate changes and their potential causes. Existing observing networks have been designed largely in support of operational weather forecasting and continue to be run in this mode. Coverage and timeliness are often higher priorities than absolute traceability and accuracy. Changes in instrumentation used in the observing system, as well as in operating procedures, are frequent, rarely adequately documented and their impacts poorly quantified. For monitoring changes in upper-air climate, which is achieved through in-situ soundings and more recently satellites and ground-based remote sensing, the net result has been trend uncertainties as large as, or larger than, the expected emergent signals of climate change. This is more than simply academic with the tropospheric temperature trends issue having been the subject of intense debate, two international assessment reports and several US congressional hearings. For more than a decade the international climate science community has been calling for the instigation of a network of reference quality measurements to reduce uncertainty in our climate monitoring capabilities. This paper provides a brief history of GRUAN developments to date and outlines future plans. Such reference networks can only be achieved and maintained with strong continuing input from the global metrological community.

Improving Climate Projections Using "Intelligent" Ensembles

NASA Technical Reports Server (NTRS)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

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

Future carbon storage in harvested wood products from Ontario's Crown forests

Treesearch

Jiaxin Chen; Stephen J. Colombo; Michael T. Ter-Mikaelian; Linda S. Heath

2008-01-01

This analysis quantifies projected carbon (C) storage in harvested wood products (HWP) from Ontario's Crown forests. The large-scale forest C budget model, FORCARB-ON, was applied to estimate HWP C stock changes using the production approach defined by the Intergovernmental Panel on Climate Change. Harvested wood volume was converted to C mass and allocated to...

Downstream Warming and Headwater Acidity May Diminish Coldwater Habitat in Southern Appalachian Mountain Streams

Treesearch

T. C. McDonnell; M. R. Sloat; T. J. Sullivan; C. A. Dolloff; P. F. Hessburg; N. A. Povak; W. A Jackson; C. Sams

2015-01-01

Stream-dwelling species in the U.S. southern Appalachian Mountains region are particularly vulnerable to climate change and acidification. The objectives of this study were to quantify the spatial extent of contemporary suitable habitat for acid- and thermally sensitive aquatic species and to forecast future habitat loss resulting from expected temperature increases on...

Linking climate, gross primary productivity, and site index across forests of the western United States

Treesearch

Aaron R. Weiskittel; Nicholas L. Crookston; Philip J. Radtke

2011-01-01

Assessing forest productivity is important for developing effective management regimes and predicting future growth. Despite some important limitations, the most common means for quantifying forest stand-level potential productivity is site index (SI). Another measure of productivity is gross primary production (GPP). In this paper, SI is compared with GPP estimates...

A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models

Treesearch

Hailemariam Temesgen; David Affleck; Krishna Poudel; Andrew Gray; John Sessions

2015-01-01

Accurate biomass measurements and analyses are critical components in quantifying carbon stocks and sequestration rates, assessing potential impacts due to climate change, locating bio-energy processing plants, and mapping and planning fuel treatments. To this end, biomass equations will remain a key component of future carbon measurements and estimation. As...

Hydro-meteorological drought event sets in the UK based on a large ensemble of global-regional climate simulations: climatology, drivers and changes in the future

NASA Astrophysics Data System (ADS)

Guillod, B. P.; Massey, N.; Otto, F. E. L.; Allen, M. R.; Jones, R.; Hall, J. W.

2016-12-01

Extreme events being rare by definition, accurately quantifying the probabilities associated with a given event is difficult. This is particularly true for droughts, for which only few events are available in the observational record owing to their long-lasting characteristics. The MaRIUS project (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity) aims at quantifying present and future risks associated with droughts in the UK. To do so, a large number of modelled weather time series for "synthetic" drought events are being fed into hydrological and impact models to assess their impacts on various sectors (social sciences, economy, industry, agriculture, and ecosystems). Here, we present and analyse the hydro-meteorological drought event sets that have been produced with a new version of weather@home [1] for MaRIUS. Using idle processor time on volunteers' computers around the world, we have run a very large number (10'000s) of Global Climate Model simulations, downscaled at 25km over Europe by a nested Regional Climate Model. Simulations include the past 100 years as well as two future time slices (2030s and 2080s), and provide a large number of sequences of spatio-temporally coherent weather, which are consistent with the boundary forcing such as the ocean, greenhouse gases and solar forcing. Beside presenting the methodology and validation of the event sets, we provide insights into drought risk in the UK and the drivers of drought. In particular, we examine their sensitivity to sea surface temperature and sea ice patterns, both in the recent past and for future projections. How drought risk in the UK can be expected to change in the future will also be discussed. Finally, we assess the applicability of this methodology to other regions. Reference: [1] Massey, N. et al., 2014, Q. J. R. Meteorol. Soc.

Data-model synthesis of grassland carbon metabolism. Quantifying direct, indirect & interactive effects of warming & elevated CO 2

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

Pendall, Elise; Ogle, Kiona; Parton, William

2016-02-29

This research project improved understanding of how climate change (elevated atmospheric CO 2, warming and altered precipitation) can affect grassland ecosystem productivity and nutrient availability. Our advanced experimental and modeling methods allowed us to test 21 specific hypotheses. We found that ecosystem changes over years of exposure to climate change can shift the plant communities and potentially make them more resilient to future climate changes. These changes in plant communities may be related to increased growth of belowground roots and enhanced nutrient uptake by some species. We also found that climate change can increase the spread of invasive and noxiousmore » weeds. These findings are important for land managers to make adaptive planning decisions for domestic livestock production in response to climate variability in semi-arid grasslands.« less

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

Current and future climate- and air pollution-mediated impacts on human health.

PubMed

Doherty, Ruth M; Heal, Mathew R; Wilkinson, Paul; Pattenden, Sam; Vieno, Massimo; Armstrong, Ben; Atkinson, Richard; Chalabi, Zaid; Kovats, Sari; Milojevic, Ai; Stevenson, David S

2009-12-21

We describe a project to quantify the burden of heat and ozone on mortality in the UK, both for the present-day and under future emission scenarios. Mortality burdens attributable to heat and ozone exposure are estimated by combination of climate-chemistry modelling and epidemiological risk assessment. Weather forecasting models (WRF) are used to simulate the driving meteorology for the EMEP4UK chemistry transport model at 5 km by 5 km horizontal resolution across the UK; the coupled WRF-EMEP4UK model is used to simulate daily surface temperature and ozone concentrations for the years 2003, 2005 and 2006, and for future emission scenarios. The outputs of these models are combined with evidence on the ozone-mortality and heat-mortality relationships derived from epidemiological analyses (time series regressions) of daily mortality in 15 UK conurbations, 1993-2003, to quantify present-day health burdens. During the August 2003 heatwave period, elevated ozone concentrations > 200 microg m-3 were measured at sites in London and elsewhere. This and other ozone photochemical episodes cause breaches of the UK air quality objective for ozone. Simulations performed with WRF-EMEP4UK reproduce the August 2003 heatwave temperatures and ozone concentrations. There remains day-to-day variability in the high ozone concentrations during the heatwave period, which on some days may be explained by ozone import from the European continent.Preliminary calculations using extended time series of spatially-resolved WRF-EMEP4UK model output suggest that in the summers (May to September) of 2003, 2005 & 2006 over 6000 deaths were attributable to ozone and around 5000 to heat in England and Wales. The regional variation in these deaths appears greater for heat-related than for ozone-related burdens.Changes in UK health burdens due to a range of future emission scenarios will be quantified. These future emissions scenarios span a range of possible futures from assuming current air quality legislation is fully implemented, to a more optimistic case with maximum feasible reductions, through to a more pessimistic case with continued strong economic growth and minimal implementation of air quality legislation. Elevated surface ozone concentrations during the 2003 heatwave period led to exceedences of the current UK air quality objective standards. A coupled climate-chemistry model is able to reproduce these temperature and ozone extremes. By combining model simulations of surface temperature and ozone with ozone-heat-mortality relationships derived from an epidemiological regression model, we estimate present-day and future health burdens across the UK. Future air quality legislation may need to consider the risk of increases in future heatwaves.

Quantifying effects of humans and climate on groundwater resources of Hawaii through sharp-interface modeling

NASA Astrophysics Data System (ADS)

Rotzoll, K.; Izuka, S. K.; Nishikawa, T.; Fienen, M. N.; El-Kadi, A. I.

2016-12-01

Some of the volcanic-rock aquifers of the islands of Hawaii are substantially developed, leading to concerns related to the effects of groundwater withdrawals on saltwater intrusion and stream base-flow reduction. A numerical modeling analysis using recent available information (e.g., recharge, withdrawals, hydrogeologic framework, and conceptual models of groundwater flow) advances current understanding of groundwater flow and provides insight into the effects of human activity and climate change on Hawaii's water resources. Three island-wide groundwater-flow models (Kauai, Oahu, and Maui) were constructed using MODFLOW 2005 coupled with the Seawater-Intrusion Package (SWI2), which simulates the transition between saltwater and freshwater in the aquifer as a sharp interface. This approach allowed coarse vertical discretization (maximum of two layers) without ignoring the freshwater-saltwater system at the regional scale. Model construction (FloPy3), parameter estimation (PEST), and analysis of results were streamlined using Python scripts. Model simulations included pre-development (1870) and recent (average of 2001-10) scenarios for each island. Additionally, scenarios for future withdrawals and climate change were simulated for Oahu. We present our streamlined approach and results showing estimated effects of human activity on the groundwater resource by quantifying decline in water levels, rise of the freshwater-saltwater interface, and reduction in stream base flow. Water-resource managers can use this information to evaluate consequences of groundwater development that can constrain future groundwater availability.

Future Precipitation Extremes in China Under Climate Change and Their Possible Mechanisms by Regional Climate Model and Earth System Model Simulations

NASA Astrophysics Data System (ADS)

Qin, P.; Xie, Z.

2017-12-01

Future precipitation extremes in China for the mid and end of 21st century were detected with six simulations using the regional climate model RegCM4 (RCM) and 17 global climate models (GCM) participated in the coupled Model Intercomparison Project Phase 5 (CMIP5). Prior to understanding the future changes in precipitation extremes, we overviewed the performance of precipitation extremes simulated by the CMIP5s and RCMs, and found both CMIP5s and RCMs could capture the temporal and spatial pattern of the historical precipitation extremes in China. In the mid-future period 2039-2058 (MF) and far-future 2079-2098 (FF), more wet precipitation extremes will occur in most area of China relative to the present period 1982-2001 (RF). We quantified the rates of the changes in precipitation extremes in China with the changes in air surface temperature (T2M) for the MF and FF period. Changes in precipitation extremes R95p were found around 5% K-1 for the MF period and 10% K-1 for the FF period, and changes in maximum 5 day precipitation (Rx5day) were detected around 4% K-1 for the MF period and 7% K-1 for the FF period, respectively. Finally, the possible physical mechanisms behind the changes in precipitation extremes in China were also discussed through the changes in specific humidity and vertical wind.

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.

Effects of climate change and variability on population dynamics in a long-lived shorebird.

PubMed

van de Pol, Martijn; Vindenes, Yngvild; Saether, Bernt-Erik; Engen, Steinar; Ens, Bruno J; Oosterbeek, Kees; Tinbergen, Joost M

2010-04-01

Climate change affects both the mean and variability of climatic variables, but their relative impact on the dynamics of populations is still largely unexplored. Based on a long-term study of the demography of a declining Eurasian Oystercatcher (Haematopus ostralegus) population, we quantify the effect of changes in mean and variance of winter temperature on different vital rates across the life cycle. Subsequently, we quantify, using stochastic stage-structured models, how changes in the mean and variance of this environmental variable affect important characteristics of the future population dynamics, such as the time to extinction. Local mean winter temperature is predicted to strongly increase, and we show that this is likely to increase the population's persistence time via its positive effects on adult survival that outweigh the negative effects that higher temperatures have on fecundity. Interannual variation in winter temperature is predicted to decrease, which is also likely to increase persistence time via its positive effects on adult survival that outweigh the negative effects that lower temperature variability has on fecundity. Overall, a 0.1 degrees C change in mean temperature is predicted to alter median time to extinction by 1.5 times as many years as would a 0.1 degrees C change in the standard deviation in temperature, suggesting that the dynamics of oystercatchers are more sensitive to changes in the mean than in the interannual variability of this climatic variable. Moreover, as climate models predict larger changes in the mean than in the standard deviation of local winter temperature, the effects of future climatic variability on this population's time to extinction are expected to be overwhelmed by the effects of changes in climatic means. We discuss the mechanisms by which climatic variability can either increase or decrease population viability and how this might depend both on species' life histories and on the vital rates affected. This study illustrates that, for making reliable inferences about population consequences in species in which life history changes with age or stage, it is crucial to investigate the impact of climate change on vital rates across the entire life cycle. Disturbingly, such data are unavailable for most species of conservation concern.

Response of Groundwater Recharge to Potential Future Climate Change in the Grand River Watershed

NASA Astrophysics Data System (ADS)

Jyrkama, M. I.; Sykes, J. F.

2004-05-01

The Grand River watershed is situated in south-western Ontario, draining an area of nearly 7000 square kilometres into Lake Erie. Approximately eighty percent of the population in the watershed derive their drinking water from groundwater sources. Quantifying the recharge input to the groundwater system and the impact of climate variability due to climate change is, therefore, essential for ensuring the quantity and sustainability of the watershed's drinking water resources in the future. The primary goal of this study is to investigate the impact of potential future climate changes on groundwater recharge in the Grand River watershed. The physically based hydrologic model HELP3 is used in conjunction with GIS to simulate the past conditions and future changes in evapotranspiration, potential surface runoff, and groundwater recharge rates as a result of projected changes in the regions climate. The climate change projections are based on the general predictions reported by the Intergovernmental Panel on Climate Change (IPCC) in 2001. Forty years of daily historical weather data are used as the reference condition. The impact of climate change on the hydrologic cycle over a forty year study period is modelled by perturbing the HELP3 model input parameters using predicted future changes in precipitation, temperature, and solar radiation. The changes in land use and vegetation cover over time were not considered in the study. The results of the study indicate that the overall simulated rate of groundwater recharge is predicted to increase in the watershed as a result of the projected future climate change. Warmer winter temperatures will reduce the extent and duration of ground frost and shift the springmelt from spring toward winter months, allowing more water to infiltrate into the ground. This results in decreased surface runoff, higher infiltration, and subsequently increased groundwater recharge. The predicted higher intensity and frequency of future precipitation will not only contribute significantly to increased surface runoff, but also results in higher evapotranspiration and groundwater recharge rates due to increased amounts of available water. Changes in the incoming solar radiation have a minimal impact on the simulated hydrologic processes. The overall simulated average annual recharge in the watershed is predicted to increase by approximately 100 mm/year over the next forty years from 189 mm/year to 289 mm/year.

Effects of changing climate on aquatic habitat and connectivity for remnant populations of a wide-ranging frog species in an arid landscape

USGS Publications Warehouse

Pilliod, David S.; Arkle, Robert S.; Robertson, Jeanne M; Murphy, Melanie; Funk, W. Chris

2015-01-01

Amphibian species persisting in isolated streams and wetlands in desert environments can be susceptible to low connectivity, genetic isolation, and climate changes. We evaluated the past (1900–1930), recent (1981–2010), and future (2071–2100) climate suitability of the arid Great Basin (USA) for the Columbia spotted frog (Rana luteiventris) and assessed whether changes in surface water may affect connectivity for remaining populations. We developed a predictive model of current climate suitability and used it to predict the historic and future distribution of suitable climates. We then modeled changes in surface water availability at each time period. Finally, we quantified connectivity among existing populations on the basis of hydrology and correlated it with interpopulation genetic distance. We found that the area of the Great Basin with suitable climate conditions has declined by approximately 49% over the last century and will likely continue to decline under future climate scenarios. Climate conditions at currently occupied locations have been relatively stable over the last century, which may explain persistence at these sites. However, future climates at these currently occupied locations are predicted to become warmer throughout the year and drier during the frog's activity period (May – September). Fall and winter precipitation may increase, but as rain instead of snow. Earlier runoff and lower summer base flows may reduce connectivity between neighboring populations, which is already limited. Many of these changes could have negative effects on remaining populations over the next 50–80 years, but milder winters, longer growing seasons, and wetter falls might positively affect survival and dispersal. Collectively, however, seasonal shifts in temperature, precipitation, and stream flow patterns could reduce habitat suitability and connectivity for frogs and possibly other aquatic species inhabiting streams in this arid region.

Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates

PubMed Central

Garcia, Raquel A; Burgess, Neil D; Cabeza, Mar; Rahbek, Carsten; Araújo, Miguel B

2012-01-01

Africa is predicted to be highly vulnerable to 21st century climatic changes. Assessing the impacts of these changes on Africa's biodiversity is, however, plagued by uncertainties, and markedly different results can be obtained from alternative bioclimatic envelope models or future climate projections. Using an ensemble forecasting framework, we examine projections of future shifts in climatic suitability, and their methodological uncertainties, for over 2500 species of mammals, birds, amphibians and snakes in sub-Saharan Africa. To summarize a priori the variability in the ensemble of 17 general circulation models, we introduce a consensus methodology that combines co-varying models. Thus, we quantify and map the relative contribution to uncertainty of seven bioclimatic envelope models, three multi-model climate projections and three emissions scenarios, and explore the resulting variability in species turnover estimates. We show that bioclimatic envelope models contribute most to variability, particularly in projected novel climatic conditions over Sahelian and southern Saharan Africa. To summarize agreements among projections from the bioclimatic envelope models we compare five consensus methodologies, which generally increase or retain projection accuracy and provide consistent estimates of species turnover. Variability from emissions scenarios increases towards late-century and affects southern regions of high species turnover centred in arid Namibia. Twofold differences in median species turnover across the study area emerge among alternative climate projections and emissions scenarios. Our ensemble of projections underscores the potential bias when using a single algorithm or climate projection for Africa, and provides a cautious first approximation of the potential exposure of sub-Saharan African vertebrates to climatic changes. The future use and further development of bioclimatic envelope modelling will hinge on the interpretation of results in the light of methodological as well as biological uncertainties. Here, we provide a framework to address methodological uncertainties and contextualize results.

Estimated effects of projected climate change on the basic reproductive number of the Lyme disease vector Ixodes scapularis.

PubMed

Ogden, Nicholas H; Radojevic, Milka; Wu, Xiaotian; Duvvuri, Venkata R; Leighton, Patrick A; Wu, Jianhong

2014-06-01

The extent to which climate change may affect human health by increasing risk from vector-borne diseases has been under considerable debate. We quantified potential effects of future climate change on the basic reproduction number (R0) of the tick vector of Lyme disease, Ixodes scapularis, and explored their importance for Lyme disease risk, and for vector-borne diseases in general. We applied observed temperature data for North America and projected temperatures using regional climate models to drive an I. scapularis population model to hindcast recent, and project future, effects of climate warming on R0. Modeled R0 increases were compared with R0 ranges for pathogens and parasites associated with variations in key ecological and epidemiological factors (obtained by literature review) to assess their epidemiological importance. R0 for I. scapularis in North America increased during the years 1971-2010 in spatio-temporal patterns consistent with observations. Increased temperatures due to projected climate change increased R0 by factors (2-5 times in Canada and 1.5-2 times in the United States), comparable to observed ranges of R0 for pathogens and parasites due to variations in strains, geographic locations, epidemics, host and vector densities, and control efforts. Climate warming may have co-driven the emergence of Lyme disease in northeastern North America, and in the future may drive substantial disease spread into new geographic regions and increase tick-borne disease risk where climate is currently suitable. Our findings highlight the potential for climate change to have profound effects on vectors and vector-borne diseases, and the need to refocus efforts to understand these effects.

Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America - Ecoregions of North America

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Pelltier, Richard T.; Shafer, Sarah L.; Bartlein, Patrick J.

2007-01-01

Climate is the primary factor controlling the continental-scale distribution of plant species, although the relations between climatic parameters and species' ranges are only now beginning to be quantified. This volume examines the relations between climate and the distributions of (1) Kuchler's 'potential natural vegetation' categories for the 48 contiguous States of the United States of America, (2) Bailey's ecoregions of North America, and (3) World Wildlife Fund's ecoregions of North America. For these analyses, we employed a 25-kilometer equal-area grid of modern climatic and bioclimatic parameters for North America, coupled with presence-absence data for the occurrence of each ecoregion under the three classification systems under consideration. The resulting relations between climate and ecoregion distributions are presented in graphical and tabular form. Presentation of ecoregion-climate relations here is intended to be useful for a greater understanding of ecosystem evolution, ecosystem dynamics, and potential effects of future climate change on ecoregions.

Projected future changes in vegetation in western North America in the 21st century

USGS Publications Warehouse

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

2013-01-01

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

Will Outer Tropical Cyclone Size Change due to Anthropogenic Warming?

NASA Astrophysics Data System (ADS)

Schenkel, B. A.; Lin, N.; Chavas, D. R.; Vecchi, G. A.; Knutson, T. R.; Oppenheimer, M.

2017-12-01

Prior research has shown significant interbasin and intrabasin variability in outer tropical cyclone (TC) size. Moreover, outer TC size has even been shown to vary substantially over the lifetime of the majority of TCs. However, the factors responsible for both setting initial outer TC size and determining its evolution throughout the TC lifetime remain uncertain. Given these gaps in our physical understanding, there remains uncertainty in how outer TC size will change, if at all, due to anthropogenic warming. The present study seeks to quantify whether outer TC size will change significantly in response to anthropogenic warming using data from a high-resolution global climate model and a regional hurricane model. Similar to prior work, the outer TC size metric used in this study is the radius in which the azimuthal-mean surface azimuthal wind equals 8 m/s. The initial results from the high-resolution global climate model data suggest that the distribution of outer TC size shifts significantly towards larger values in each global TC basin during future climates, as revealed by 1) statistically significant increase of the median outer TC size by 5-10% (p<0.05) according to a 1,000-sample bootstrap resampling approach with replacement and 2) statistically significant differences between distributions of outer TC size from current and future climate simulations as shown using two-sample Kolmogorov Smirnov testing (p<<0.01). Additional analysis of the high-resolution global climate model data reveals that outer TC size does not uniformly increase within each basin in future climates, but rather shows substantial locational dependence. Future work will incorporate the regional mesoscale hurricane model data to help focus on identifying the source of the spatial variability in outer TC size increases within each basin during future climates and, more importantly, why outer TC size changes in response to anthropogenic warming.

Technical Note: Linking climate change and downed woody debris decomposition across forests of the eastern United States

NASA Astrophysics Data System (ADS)

Russell, M. B.; Woodall, C. W.; D'Amato, A. W.; Fraver, S.; Bradford, J. B.

2014-06-01

Forest ecosystems play a critical role in mitigating greenhouse gas emissions. Long-term forest carbon (C) storage is determined by the balance between C fixation into biomass through photosynthesis and C release via decomposition and combustion. Relative to C fixation in biomass, much less is known about C depletion through decomposition of woody debris, particularly under a changing climate. It is assumed that the increased temperatures and longer growing seasons associated with projected climate change will increase the decomposition rates (i.e., more rapid C cycling) of downed woody debris (DWD); however, the magnitude of this increase has not been previously addressed. Using DWD measurements collected from a national forest inventory of the eastern United States, we show that the residence time of DWD may decrease (i.e., more rapid decomposition) by as much as 13% over the next 200 years depending on various future climate change scenarios and forest types. Although existing dynamic global vegetation models account for the decomposition process, they typically do not include the effect of a changing climate on DWD decomposition rates. We expect that an increased understanding of decomposition rates, as presented in this current work, will be needed to adequately quantify the fate of woody detritus in future forests. Furthermore, we hope these results will lead to improved models that incorporate climate change scenarios for depicting future dead wood dynamics, in addition to a traditional emphasis on live tree demographics.

Assessing changes in failure probability of dams in a changing climate

NASA Astrophysics Data System (ADS)

Mallakpour, I.; AghaKouchak, A.; Moftakhari, H.; Ragno, E.

2017-12-01

Dams are crucial infrastructures and provide resilience against hydrometeorological extremes (e.g., droughts and floods). In 2017, California experienced series of flooding events terminating a 5-year drought, and leading to incidents such as structural failure of Oroville Dam's spillway. Because of large socioeconomic repercussions of such incidents, it is of paramount importance to evaluate dam failure risks associated with projected shifts in the streamflow regime. This becomes even more important as the current procedures for design of hydraulic structures (e.g., dams, bridges, spillways) are based on the so-called stationary assumption. Yet, changes in climate are anticipated to result in changes in statistics of river flow (e.g., more extreme floods) and possibly increasing the failure probability of already aging dams. Here, we examine changes in discharge under two representative concentration pathways (RCPs): RCP4.5 and RCP8.5. In this study, we used routed daily streamflow data from ten global climate models (GCMs) in order to investigate possible climate-induced changes in streamflow in northern California. Our results show that while the average flow does not show a significant change, extreme floods are projected to increase in the future. Using the extreme value theory, we estimate changes in the return periods of 50-year and 100-year floods in the current and future climates. Finally, we use the historical and future return periods to quantify changes in failure probability of dams in a warming climate.

Global Air Quality and Climate Impacts of Mitigating Short-lived Climate Pollution in China

NASA Astrophysics Data System (ADS)

Harper, K.; Unger, N.; Heyes, C.; Kiesewetter, G.; Klimont, Z.; Schoepp, W.; Wagner, F.

2014-12-01

China is a major emitter of harmful air pollutants, including the short-lived climate pollutants (SLCPs) and their precursors. Implementation of pollution control technologies provides a mechanism for simultaneously protecting human and ecosystem health and achieving near-term climate co-benefits; however, predicting the outcomes of technical and policy interventions is challenging because the SLCPs participate in both climate warming and cooling and share many common emission sources. Here, we present the results of a combined regional integrated assessment and global climate modeling study aimed at quantifying the near-term climate and air quality co-benefits of selective control of Chinese air pollution emissions. Results from IIASA's Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) integrated assessment model indicate that methane emission reductions make up > 75% of possible CO2-equivalent emission reductions of the SLCPs and their precursors in China in 2030. A multi-pollutant emission reduction scenario incorporating the 2030 Chinese pollution control measures with the highest potential for future climate impact is applied to the NASA ModelE2 - Yale Interactive Terrestrial Biosphere (NASA ModelE2-YIBs) global carbon - chemistry - climate model to assess the regional and long-range impacts of Chinese SLCP mitigation measures. Using model simulations that incorporate dynamic methane emissions and photosynthesis-dependent isoprene emissions, we quantify the impacts of Chinese reductions of the short-lived air pollutants on radiative forcing and on surface ozone and particulate air pollution. Present-day modeled methane mole fractions are evaluated against SCIAMACHY methane columns and NOAA ESRL/GMD surface flask measurements.

Climate Change Accuracy: Requirements and Economic Value

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R.; Mlynczak, M. G.; Lukashin, C.; Thome, K. J.; Baize, R. R.

2014-12-01

Higher than normal accuracy is required to rigorously observe decadal climate change. But what level is needed? How can this be quantified? This presentation will summarize a new more rigorous and quantitative approach to determining the required accuracy for climate change observations (Wielicki et al., 2013, BAMS). Most current global satellite observations cannot meet this accuracy level. A proposed new satellite mission to resolve this challenge is CLARREO (Climate Absolute Radiance and Refractivity Observatory). CLARREO is designed to achieve advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra (Wielicki et al., Oct. 2013 BAMS). The CLARREO spectrometers are designed to serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and to greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar passive satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, SPOT, etc). Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A study has been carried out to quantify the economic benefits of such an advance as part of a rigorous and complete climate observing system. The study concludes that the economic value is $12 Trillion U.S. dollars in Net Present Value for a nominal discount rate of 3% (Cooke et al. 2013, J. Env. Sys. Dec.). A brief summary of these two studies and their implications for the future of climate science will be presented.

Modelling the response of shallow groundwater levels to combined climate and water-diversion scenarios in Beijing-Tianjin-Hebei Plain, China

NASA Astrophysics Data System (ADS)

Li, Xue; Ye, Si-Yuan; Wei, Ai-Hua; Zhou, Peng-Peng; Wang, Li-Heng

2017-09-01

A three-dimensional groundwater flow model was implemented to quantify the temporal variation of shallow groundwater levels in response to combined climate and water-diversion scenarios over the next 40 years (2011-2050) in Beijing-Tianjin-Hebei (Jing-Jin-Ji) Plain, China. Groundwater plays a key role in the water supply, but the Jing-Jin-Ji Plain is facing a water crisis. Groundwater levels have declined continuously over the last five decades (1961-2010) due to extensive pumping and climate change, which has resulted in decreased recharge. The implementation of the South-to-North Water Diversion Project (SNWDP) will provide an opportunity to restore the groundwater resources. The response of groundwater levels to combined climate and water-diversion scenarios has been quantified using a groundwater flow model. The impacts of climate change were based on the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset for future high (A2), medium (A1B), and low (B1) greenhouse gas scenarios; precipitation data from CMIP3 were applied in the model. The results show that climate change will slow the rate of decrease of the shallow groundwater levels under three climate-change scenarios over the next 40 years compared to the baseline scenario; however, the shallow groundwater levels will rise significantly (maximum of 6.71 m) when considering scenarios that combine climate change and restrictions on groundwater exploitation. Restrictions on groundwater exploitation for water resource management are imperative to control the decline of levels in the Jing-Jin-Ji area.

The Portuguese Climate Portal

NASA Astrophysics Data System (ADS)

Gomes, Sandra; Deus, Ricardo; Nogueira, Miguel; Viterbo, Pedro; Miranda, Miguel; Antunes, Sílvia; Silva, Alvaro; Miranda, Pedro

2016-04-01

The Portuguese Local Warming Website (http://portaldoclima.pt) has been developed in order to support the society in Portugal in preparing for the adaptation to the ongoing and future effects of climate change. The climate portal provides systematic and easy access to authoritative scientific data ready to be used by a vast and diverse user community from different public and private sectors, key players and decision makers, but also to high school students, contributing to the increase in knowledge and awareness on climate change topics. A comprehensive set of regional climate variables and indicators are computed, explained and graphically presented. Variables and indicators were built in agreement with identified needs after consultation of the relevant social partners from different sectors, including agriculture, water resources, health, environment and energy and also in direct cooperation with the Portuguese National Strategy for Climate Change Adaptation (ENAAC) group. The visual interface allows the user to dynamically interact, explore, quickly analyze and compare, but also to download and import the data and graphics. The climate variables and indicators are computed from state-of-the-art regional climate model (RCM) simulations (e.g., CORDEX project), at high space-temporal detail, allowing to push the limits of the projections down to local administrative regions (NUTS3) and monthly or seasonal periods, promoting local adaptation strategies. The portal provides both historical data (observed and modelled for the 1971-2000 period) and future climate projections for different scenarios (modelled for the 2011-2100 period). A large effort was undertaken in order to quantify the impacts of the risk of extreme events, such as heavy rain and flooding, droughts, heat and cold waves, and fires. Furthermore the different climate scenarios and the ensemble of RCM models, with high temporal (daily) and spatial (~11km) detail, is taken advantage in order to quantify a plausible evolution of climate impacts and its uncertainties. Clear information on the data value and limitations is also provided. The portal is expected to become a reference tool for evaluation of impacts and vulnerabilities due to climate change, increased awareness and promotion of local adaptation and sustainable development in Portugal. The Portuguese Local Warming Website is part of the ADAPT programme, and is co-funded by the EEA financial mechanism and the Portuguese Carbon Fund.

A window of opportunity for climate-change adaptation: Easing tree mortality by reducing forest basal area

USGS Publications Warehouse

Bradford, John B.; Bell, David M.

2017-01-01

Increasing aridity as a result of climate change is expected to exacerbate tree mortality. Reducing forest basal area – the cross-sectional area of tree stems within a given ground area – can decrease tree competition, which may reduce drought-induced tree mortality. However, neither the magnitude of expected mortality increases, nor the potential effectiveness of basal area reduction, has been quantified in dryland forests such as those of the drought-prone Southwest US. We used thousands of repeatedly measured forest plots to show that unusually warm and dry conditions are related to high tree mortality rates and that mortality is positively related to basal area. Those relationships suggest that while increasing high temperature extremes forecasted by climate models may lead to elevated tree mortality during the 21st century, future tree mortality might be partly ameliorated by reducing stand basal area. This adaptive forest management strategy may provide a window of opportunity for forest managers and policy makers to guide forest transitions to species and/or genotypes more suited to future climates.

Quantification of increased flood risk due to global climate change for urban river management planning.

PubMed

Morita, M

2011-01-01

Global climate change is expected to affect future rainfall patterns. These changes should be taken into account when assessing future flooding risks. This study presents a method for quantifying the increase in flood risk caused by global climate change for use in urban flood risk management. Flood risk in this context is defined as the product of flood damage potential and the probability of its occurrence. The study uses a geographic information system-based flood damage prediction model to calculate the flood damage caused by design storms with different return periods. Estimation of the monetary damages these storms produce and their return periods are precursors to flood risk calculations. The design storms are developed from modified intensity-duration-frequency relationships generated by simulations of global climate change scenarios (e.g. CGCM2A2). The risk assessment method is applied to the Kanda River basin in Tokyo, Japan. The assessment provides insights not only into the flood risk cost increase due to global warming, and the impact that increase may have on flood control infrastructure planning.

Review article: Hydrological modeling in glacierized catchments of central Asia - status and challenges

NASA Astrophysics Data System (ADS)

Chen, Yaning; Li, Weihong; Fang, Gonghuan; Li, Zhi

2017-02-01

Meltwater from glacierized catchments is one of the most important water supplies in central Asia. Therefore, the effects of climate change on glaciers and snow cover will have increasingly significant consequences for runoff. Hydrological modeling has become an indispensable research approach to water resources management in large glacierized river basins, but there is a lack of focus in the modeling of glacial discharge. This paper reviews the status of hydrological modeling in glacierized catchments of central Asia, discussing the limitations of the available models and extrapolating these to future challenges and directions. After reviewing recent efforts, we conclude that the main sources of uncertainty in assessing the regional hydrological impacts of climate change are the unreliable and incomplete data sets and the lack of understanding of the hydrological regimes of glacierized catchments of central Asia. Runoff trends indicate a complex response to changes in climate. For future variation of water resources, it is essential to quantify the responses of hydrologic processes to both climate change and shrinking glaciers in glacierized catchments, and scientific focus should be on reducing uncertainties linked to these processes.

eSACP - a new Nordic initiative towards developing statistical climate services

NASA Astrophysics Data System (ADS)

Thorarinsdottir, Thordis; Thejll, Peter; Drews, Martin; Guttorp, Peter; Venälainen, Ari; Uotila, Petteri; Benestad, Rasmus; Mesquita, Michel d. S.; Madsen, Henrik; Fox Maule, Cathrine

2015-04-01

The Nordic research council NordForsk has recently announced its support for a new 3-year research initiative on "statistical analysis of climate projections" (eSACP). eSACP will focus on developing e-science tools and services based on statistical analysis of climate projections for the purpose of helping decision-makers and planners in the face of expected future challenges in regional climate change. The motivation behind the project is the growing recognition in our society that forecasts of future climate change is associated with various sources of uncertainty, and that any long-term planning and decision-making dependent on a changing climate must account for this. At the same time there is an obvious gap between scientists from different fields and between practitioners in terms of understanding how climate information relates to different parts of the "uncertainty cascade". In eSACP we will develop generic e-science tools and statistical climate services to facilitate the use of climate projections by decision-makers and scientists from all fields for climate impact analyses and for the development of robust adaptation strategies, which properly (in a statistical sense) account for the inherent uncertainty. The new tool will be publically available and include functionality to utilize the extensive and dynamically growing repositories of data and use state-of-the-art statistical techniques to quantify the uncertainty and innovative approaches to visualize the results. Such a tool will not only be valuable for future assessments and underpin the development of dedicated climate services, but will also assist the scientific community in making more clearly its case on the consequences of our changing climate to policy makers and the general public. The eSACP project is led by Thordis Thorarinsdottir, Norwegian Computing Center, and also includes the Finnish Meteorological Institute, the Norwegian Meteorological Institute, the Technical University of Denmark and the Bjerknes Centre for Climate Research, Norway. This poster will present details of focus areas in the project and show some examples of the expected analysis tools.

Scenarios for the risk of hunger in the twenty-first century using Shared Socioeconomic Pathways

NASA Astrophysics Data System (ADS)

Hasegawa, Tomoko; Fujimori, Shinichiro; Takahashi, Kiyoshi; Masui, Toshihiko

2015-01-01

Shared socioeconomic pathways (SSPs) are being developed internationally for cross-sectoral assessments of climate change impacts, adaptation, and mitigation. These are five scenarios that include both qualitative and quantitative information for mitigation and adaptation challenges to climate change. In this study, we quantified scenarios for the risk of hunger in the 21st century using SSPs, and clarified elements that influence future hunger risk. There were two primary findings: (1) risk of hunger in the 21st-century greatly differed among five SSPs; and (2) population growth, improvement in the equality of food distribution within a country, and increases in food consumption mainly driven by income growth greatly influenced future hunger risk and were important elements in its long-term assessment.

Modelling the climatic niche of turtles: a deep-time perspective

PubMed Central

Schmidt, Daniela N.; Valdes, Paul J.; Holroyd, Patricia A.; Farnsworth, Alexander

2016-01-01

Ectotherms have close physiological ties with the thermal environment; consequently, the impact of future climate change on their biogeographic distributions is of major interest. Here, we use the modern and deep-time fossil record of testudines (turtles, tortoises, and terrapins) to provide the first test of climate on the niche limits of both extant and extinct (Late Cretaceous, Maastrichtian) taxa. Ecological niche models are used to assess niche overlap in model projections for key testudine ecotypes and families. An ordination framework is applied to quantify metrics of niche change (stability, expansion, and unfilling) between the Maastrichtian and present day. Results indicate that niche stability over evolutionary timescales varies between testudine clades. Groups that originated in the Early Cretaceous show climatic niche stability, whereas those diversifying towards the end of the Cretaceous display larger niche expansion towards the modern. Temperature is the dominant driver of modern and past distributions, whereas precipitation is important for freshwater turtle ranges. Our findings demonstrate that testudines were able to occupy warmer climates than present day in the geological record. However, the projected rate and magnitude of future environmental change, in concert with other conservation threats, presents challenges for acclimation or adaptation. PMID:27655766

Quantifying the role of climate variability on extreme total water level impacts: An application of a full simulation model to Ocean Beach, California

NASA Astrophysics Data System (ADS)

Serafin, K.; Ruggiero, P.; Stockdon, H. F.; Barnard, P.; Long, J.

2014-12-01

Many coastal communities worldwide are vulnerable to flooding and erosion driven by extreme total water levels (TWL), potentially dangerous events produced by the combination of large waves, high tides, and high non-tidal residuals. The West coast of the United States provides an especially challenging environment to model these processes due to its complex geological setting combined with uncertain forecasts for sea level rise (SLR), changes in storminess, and possible changes in the frequency of major El Niños. Our research therefore aims to develop an appropriate methodology to assess present-day and future storm-induced coastal hazards along the entire U.S. West coast, filling this information gap. We present the application of this framework in a pilot study at Ocean Beach, California, a National Park site within the Golden Gate National Recreation Area where existing event-scale coastal change data can be used for model calibration and verification. We use a probabilistic, full simulation TWL model (TWL-FSM; Serafin and Ruggiero, in press) that captures the seasonal and interannual climatic variability in extremes using functions of regional climate indices, such as the Multivariate ENSO index (MEI), to represent atmospheric patterns related to the El Niño-Southern Oscillation (ENSO). In order to characterize the effect of climate variability on TWL components, we refine the TWL-FSM by splitting non-tidal residuals into low (monthly mean sea level anomalies) and high frequency (storm surge) components. We also develop synthetic climate indices using Markov sequences to reproduce the autocorrelated nature of ENSO behavior. With the refined TWL-FSM, we simulate each TWL component, resulting in synthetic TWL records providing robust estimates of extreme return level events (e.g., the 100-yr event) and the ability to examine the relative contribution of each TWL component to these extreme events. Extreme return levels are then used to drive storm impact models to examine the probability of coastal change (Stockdon et al., 2013) and thus, the vulnerability to storm-induced coastal hazards that Ocean Beach faces. Future climate variability is easily incorporated into this framework, allowing us to quantify how an evolving climate will alter future extreme TWLs and their related coastal impacts.

The Coordinated Ocean Wave Climate Project

NASA Astrophysics Data System (ADS)

Hemer, Mark; Dobrynin, Mikhail; Erikson, Li; Lionello, Piero; Mori, Nobuhito; Semedo, Alvaro; Wang, Xiaolan

2016-04-01

Future 21st Century changes in wind-wave climate have broad implications for marine and coastal infrastructure and ecosystems. Atmosphere-ocean general circulation models (GCM) are now routinely used for assessing and providing future projections of climatological parameters such as temperature and precipitation, but generally these provide no information on ocean wind-waves. To fill this information gap a growing number of studies are using GCM outputs and independently producing global and regional scale wind-wave climate projections. Furthermore, additional studies are actively coupling wind-wave dependent atmosphere-ocean exchanges into GCMs, to improve physical representation and quantify the impact of waves in the coupled climate system, and can also deliver wave characteristics as another variable in the climate system. To consolidate these efforts, understand the sources of variance between projections generated by different methodologies and International groups, and ultimately provide a robust picture of the role of wind-waves in the climate system and their projected changes, we present outcomes of the JCOMM supported Coordinated Ocean Wave Climate Project (COWCLIP). The objective of COWCLIP is twofold: to make community based ensembles of wave climate projections openly accessible, to provide the necessary information to support diligent marine and coastal impacts of climate change studies; and to understand the effects and feedback influences of wind-waves in the coupled ocean-atmosphere climate system. We will present the current status of COWCLIP, providing an overview of the objectives, analysis and results of the initial phase - now complete - and the progress of ongoing phases of the project.

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

PubMed

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

2010-01-01

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

Contrasting climate change impact on river flows from high-altitude catchments in the Himalayan and Andes Mountains.

PubMed

Ragettli, Silvan; Immerzeel, Walter W; Pellicciotti, Francesca

2016-08-16

Mountain ranges are the world's natural water towers and provide water resources for millions of people. However, their hydrological balance and possible future changes in river flow remain poorly understood because of high meteorological variability, physical inaccessibility, and the complex interplay between climate, cryosphere, and hydrological processes. Here, we use a state-of-the art glacio-hydrological model informed by data from high-altitude observations and the latest climate change scenarios to quantify the climate change impact on water resources of two contrasting catchments vulnerable to changes in the cryosphere. The two study catchments are located in the Central Andes of Chile and in the Nepalese Himalaya in close vicinity of densely populated areas. Although both sites reveal a strong decrease in glacier area, they show a remarkably different hydrological response to projected climate change. In the Juncal catchment in Chile, runoff is likely to sharply decrease in the future and the runoff seasonality is sensitive to projected climatic changes. In the Langtang catchment in Nepal, future water availability is on the rise for decades to come with limited shifts between seasons. Owing to the high spatiotemporal resolution of the simulations and process complexity included in the modeling, the response times and the mechanisms underlying the variations in glacier area and river flow can be well constrained. The projections indicate that climate change adaptation in Central Chile should focus on dealing with a reduction in water availability, whereas in Nepal preparedness for flood extremes should be the policy priority.

Contrasting climate change impact on river flows from high-altitude catchments in the Himalayan and Andes Mountains

PubMed Central

Pellicciotti, Francesca

2016-01-01

Mountain ranges are the world’s natural water towers and provide water resources for millions of people. However, their hydrological balance and possible future changes in river flow remain poorly understood because of high meteorological variability, physical inaccessibility, and the complex interplay between climate, cryosphere, and hydrological processes. Here, we use a state-of-the art glacio-hydrological model informed by data from high-altitude observations and the latest climate change scenarios to quantify the climate change impact on water resources of two contrasting catchments vulnerable to changes in the cryosphere. The two study catchments are located in the Central Andes of Chile and in the Nepalese Himalaya in close vicinity of densely populated areas. Although both sites reveal a strong decrease in glacier area, they show a remarkably different hydrological response to projected climate change. In the Juncal catchment in Chile, runoff is likely to sharply decrease in the future and the runoff seasonality is sensitive to projected climatic changes. In the Langtang catchment in Nepal, future water availability is on the rise for decades to come with limited shifts between seasons. Owing to the high spatiotemporal resolution of the simulations and process complexity included in the modeling, the response times and the mechanisms underlying the variations in glacier area and river flow can be well constrained. The projections indicate that climate change adaptation in Central Chile should focus on dealing with a reduction in water availability, whereas in Nepal preparedness for flood extremes should be the policy priority. PMID:27482082

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

PubMed

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

2014-01-01

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

Wetter subtropics in a warmer world: Contrasting past and future hydrological cycles

NASA Astrophysics Data System (ADS)

Burls, Natalie J.; Fedorov, Alexey V.

2017-12-01

During the warm Miocene and Pliocene Epochs, vast subtropical regions had enough precipitation to support rich vegetation and fauna. Only with global cooling and the onset of glacial cycles some 3 Mya, toward the end of the Pliocene, did the broad patterns of arid and semiarid subtropical regions become fully developed. However, current projections of future global warming caused by CO2 rise generally suggest the intensification of dry conditions over these subtropical regions, rather than the return to a wetter state. What makes future projections different from these past warm climates? Here, we investigate this question by comparing a typical quadrupling-of-CO2 experiment with a simulation driven by sea-surface temperatures closely resembling available reconstructions for the early Pliocene. Based on these two experiments and a suite of other perturbed climate simulations, we argue that this puzzle is explained by weaker atmospheric circulation in response to the different ocean surface temperature patterns of the Pliocene, specifically reduced meridional and zonal temperature gradients. Thus, our results highlight that accurately predicting the response of the hydrological cycle to global warming requires predicting not only how global mean temperature responds to elevated CO2 forcing (climate sensitivity) but also accurately quantifying how meridional sea-surface temperature patterns will change (structural climate sensitivity).

Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology

NASA Astrophysics Data System (ADS)

Shen, Mingxi; Chen, Jie; Zhuan, Meijia; Chen, Hua; Xu, Chong-Yu; Xiong, Lihua

2018-01-01

Uncertainty estimation of climate change impacts on hydrology has received much attention in the research community. The choice of a global climate model (GCM) is usually considered as the largest contributor to the uncertainty of climate change impacts. The temporal variation of GCM uncertainty needs to be investigated for making long-term decisions to deal with climate change. Accordingly, this study investigated the temporal variation (mainly long-term) of uncertainty related to the choice of a GCM in predicting climate change impacts on hydrology by using multi-GCMs over multiple continuous future periods. Specifically, twenty CMIP5 GCMs under RCP4.5 and RCP8.5 emission scenarios were adapted to adequately represent this uncertainty envelope, fifty-one 30-year future periods moving from 2021 to 2100 with 1-year interval were produced to express the temporal variation. Future climatic and hydrological regimes over all future periods were compared to those in the reference period (1971-2000) using a set of metrics, including mean and extremes. The periodicity of climatic and hydrological changes and their uncertainty were analyzed using wavelet analysis, while the trend was analyzed using Mann-Kendall trend test and regression analysis. The results showed that both future climate change (precipitation and temperature) and hydrological response predicted by the twenty GCMs were highly uncertain, and the uncertainty increased significantly over time. For example, the change of mean annual precipitation increased from 1.4% in 2021-2050 to 6.5% in 2071-2100 for RCP4.5 in terms of the median value of multi-models, but the projected uncertainty reached 21.7% in 2021-2050 and 25.1% in 2071-2100 for RCP4.5. The uncertainty under a high emission scenario (RCP8.5) was much larger than that under a relatively low emission scenario (RCP4.5). Almost all climatic and hydrological regimes and their uncertainty did not show significant periodicity at the P = .05 significance level, but their temporal variation could be well modeled by using the fourth-order polynomial. Overall, this study further emphasized the importance of using multiple GCMs for studying climate change impacts on hydrology. Furthermore, the temporal variation of uncertainty sourced from GCMs should be given more attention.

Suspended sediment source areas and future climate impact on soil erosion and sediment yield in a New York City water supply watershed, USA

NASA Astrophysics Data System (ADS)

Mukundan, Rajith; Pradhanang, Soni M.; Schneiderman, Elliot M.; Pierson, Donald C.; Anandhi, Aavudai; Zion, Mark S.; Matonse, Adão H.; Lounsbury, David G.; Steenhuis, Tammo S.

2013-02-01

High suspended sediment loads and the resulting turbidity can impact the use of surface waters for water supply and other designated uses. Changes in fluvial sediment loads influence material fluxes, aquatic geochemistry, water quality, channel morphology, and aquatic habitats. Therefore, quantifying spatial and temporal patterns in sediment loads is important both for understanding and predicting soil erosion and sediment transport processes as well as watershed-scale management of sediment and associated pollutants. A case study from the 891 km2 Cannonsville watershed, one of the major watersheds in the New York City water supply system is presented. The objective of this study was to apply Soil and Water Assessment Tool-Water Balance (SWAT-WB), a physically based semi-distributed model to identify suspended sediment generating source areas under current conditions and to simulate potential climate change impacts on soil erosion and suspended sediment yield in the study watershed for a set of future climate scenarios representative of the period 2081-2100. Future scenarios developed using nine global climate model (GCM) simulations indicate a sharp increase in the annual rates of soil erosion although a similar result in sediment yield at the watershed outlet was not evident. Future climate related changes in soil erosion and sediment yield appeared more significant in the winter due to a shift in the timing of snowmelt and also due to a decrease in the proportion of precipitation received as snow. Although an increase in future summer precipitation was predicted, soil erosion and sediment yield appeared to decrease owing to an increase in soil moisture deficit and a decrease in water yield due to increased evapotranspiration.

Linear and nonlinear effects of temperature and precipitation on ecosystem properties in tidal saline wetlands

USGS Publications Warehouse

Feher, Laura C.; Osland, Michael J.; Griffith, Kereen T.; Grace, James B.; Howard, Rebecca J.; Stagg, Camille L.; Enwright, Nicholas M.; Krauss, Ken W.; Gabler, Christopher A.; Day, Richard H.; Rogers, Kerrylee

2017-01-01

Climate greatly influences the structure and functioning of tidal saline wetland ecosystems. However, there is a need to better quantify the effects of climatic drivers on ecosystem properties, particularly near climate-sensitive ecological transition zones. Here, we used climate- and literature-derived ecological data from tidal saline wetlands to test hypotheses regarding the influence of climatic drivers (i.e., temperature and precipitation regimes) on the following six ecosystem properties: canopy height, biomass, productivity, decomposition, soil carbon density, and soil carbon accumulation. Our analyses quantify and elucidate linear and nonlinear effects of climatic drivers. We quantified positive linear relationships between temperature and above-ground productivity and strong positive nonlinear (sigmoidal) relationships between (1) temperature and above-ground biomass and canopy height and (2) precipitation and canopy height. Near temperature-controlled mangrove range limits, small changes in temperature are expected to trigger comparatively large changes in biomass and canopy height, as mangrove forests grow, expand, and, in some cases, replace salt marshes. However, within these same transition zones, temperature-induced changes in productivity are expected to be comparatively small. Interestingly, despite the significant above-ground height, biomass, and productivity relationships across the tropical–temperate mangrove–marsh transition zone, the relationships between temperature and soil carbon density or soil carbon accumulation were not significant. Our literature review identifies several ecosystem properties and many regions of the world for which there are insufficient data to fully evaluate the influence of climatic drivers, and the identified data gaps can be used by scientists to guide future research. Our analyses indicate that near precipitation-controlled transition zones, small changes in precipitation are expected to trigger comparatively large changes in canopy height. However, there are scant data to evaluate the influence of precipitation on other ecosystem properties. There is a need for more decomposition data across climatic gradients, and to advance understanding of the influence of changes in precipitation and freshwater availability, additional ecological data are needed from tidal saline wetlands in arid climates. Collectively, our results can help scientists and managers better anticipate the linear and nonlinear ecological consequences of climate change for coastal wetlands.

Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

PubMed

Avise, Jeremy; Abraham, Rodrigo Gonzalez; Chung, Serena H; Chen, Jack; Lamb, Brian; Salathé, Eric P; Zhang, Yongxin; Nolte, Christopher G; Loughlin, Daniel H; Guenther, Alex; Wiedinmyer, Christine; Duhl, Tiffany

2012-09-01

The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

DOE PAGES

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.; ...

2017-01-24

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

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

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

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

PubMed Central

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

2013-01-01

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

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

USGS Publications Warehouse

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

2013-01-01

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

Escalating heat-stress mortality risk due to global warming in the Middle East and North Africa (MENA).

PubMed

Ahmadalipour, Ali; Moradkhani, Hamid

2018-08-01

Climate change will substantially exacerbate extreme temperature and heatwaves. The impacts will be more intense across the Middle East and North Africa (MENA), a region mostly characterized by hot and arid climate, already intolerable for human beings in many parts. In this study, daily climate data from 17 fine-resolution Regional Climate Models (RCMs) are acquired to calculate wet-bulb temperature and investigate the mortality risk for people aged over 65 years caused by excessive heat stress across the MENA region. Spatially adaptive temperature thresholds are implemented for quantifying the mortality risk, and the analysis is conducted for the historical period of 1951-2005 and two future scenarios of RCP4.5 and RCP8.5 during the 2006-2100 period. Results show that the mortality risk will increase in distant future to 8-20 times higher than that of the historical period if no climate change mitigation is implemented. The coastal regions of the Red sea, Persian Gulf, and Mediterranean Sea indicate substantial increase in mortality risk. Nonetheless, the risk ratio will be limited to 3-7 times if global warming is limited to 2 °C. Climate change planning and adaptation is imperative for mitigating heat-related mortality risk across the region. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

NASA Astrophysics Data System (ADS)

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; Brovkin, Victor; Calvin, Kate V.; Jones, Andrew D.; Jones, Chris D.; Lawrence, Peter J.; de Noblet-Ducoudré, Nathalie; Pongratz, Julia; Seneviratne, Sonia I.; Shevliakova, Elena

2016-09-01

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

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

Lawrence, David M.; Hurtt, George C.; Arneth, Almut

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

DOE PAGES

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; ...

2016-09-02

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

a New Framework for Characterising Simulated Droughts for Future Climates

NASA Astrophysics Data System (ADS)

Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross-Dependence across Multiple Time Scales: Implications for Downscaling, Journal of Climate, 29(10), 3519-3539. Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 50, 650-660, doi:10.1002/2013WR013845.

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation

PubMed Central

Sultan, Benjamin; Gaetani, Marco

2016-01-01

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation. PMID:27625660

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation.

PubMed

Sultan, Benjamin; Gaetani, Marco

2016-01-01

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation.

JPL's Role in Advancing Earth System Science to Meet the Challenges of Climate and Environmental Change

NASA Technical Reports Server (NTRS)

Evans, Diane

2012-01-01

Objective 2.1.1: Improve understanding of and improve the predictive capability for changes in the ozone layer, climate forcing, and air quality associated with changes in atmospheric composition. Objective 2.1.2: Enable improved predictive capability for weather and extreme weather events. Objective 2.1.3: Quantify, understand, and predict changes in Earth s ecosystems and biogeochemical cycles, including the global carbon cycle, land cover, and biodiversity. Objective 2.1.4: Quantify the key reservoirs and fluxes in the global water cycle and assess water cycle change and water quality. Objective 2.1.5: Improve understanding of the roles of the ocean, atmosphere, land and ice in the climate system and improve predictive capability for its future evolution. Objective 2.1.6: Characterize the dynamics of Earth s surface and interior and form the scientific basis for the assessment and mitigation of natural hazards and response to rare and extreme events. Objective 2.1.7: Enable the broad use of Earth system science observations and results in decision-making activities for societal benefits.

Effectiveness of time of sowing and cultivar choice for managing climate change: wheat crop phenology and water use efficiency.

PubMed

Luo, Qunying; O'Leary, Garry; Cleverly, James; Eamus, Derek

2018-06-01

Climate change (CC) presents a challenge for the sustainable development of wheat production systems in Australia. This study aimed to (1) quantify the impact of future CC on wheat grain yield for the period centred on 2030 from the perspectives of wheat phenology, water use and water use efficiency (WUE) and (2) evaluate the effectiveness of changing sowing times and cultivars in response to the expected impacts of future CC on wheat grain yield. The daily outputs of CSIRO Conformal-Cubic Atmospheric Model for baseline and future periods were used by a stochastic weather generator to derive changes in mean climate and in climate variability and to construct local climate scenarios, which were then coupled with a wheat crop model to achieve the two research aims. We considered three locations in New South Wales, Australia, six times of sowing (TOS) and three bread wheat (Triticum aestivum L.) cultivars in this study. Simulation results show that in 2030 (1) for impact analysis, wheat phenological events are expected to occur earlier and crop water use is expected to decrease across all cases (the combination of three locations, six TOS and three cultivars), wheat grain yield would increase or decrease depending on locations and TOS; and WUE would increase in most of the cases; (2) for adaptation considerations, the combination of TOS and cultivars with the highest yield varied across locations. Wheat growers at different locations will require different strategies in managing the negative impacts or taking the opportunities of future CC.

Effectiveness of time of sowing and cultivar choice for managing climate change: wheat crop phenology and water use efficiency

NASA Astrophysics Data System (ADS)

Luo, Qunying; O'Leary, Garry; Cleverly, James; Eamus, Derek

2018-06-01

Climate change (CC) presents a challenge for the sustainable development of wheat production systems in Australia. This study aimed to (1) quantify the impact of future CC on wheat grain yield for the period centred on 2030 from the perspectives of wheat phenology, water use and water use efficiency (WUE) and (2) evaluate the effectiveness of changing sowing times and cultivars in response to the expected impacts of future CC on wheat grain yield. The daily outputs of CSIRO Conformal-Cubic Atmospheric Model for baseline and future periods were used by a stochastic weather generator to derive changes in mean climate and in climate variability and to construct local climate scenarios, which were then coupled with a wheat crop model to achieve the two research aims. We considered three locations in New South Wales, Australia, six times of sowing (TOS) and three bread wheat ( Triticum aestivum L .) cultivars in this study. Simulation results show that in 2030 (1) for impact analysis, wheat phenological events are expected to occur earlier and crop water use is expected to decrease across all cases (the combination of three locations, six TOS and three cultivars), wheat grain yield would increase or decrease depending on locations and TOS; and WUE would increase in most of the cases; (2) for adaptation considerations, the combination of TOS and cultivars with the highest yield varied across locations. Wheat growers at different locations will require different strategies in managing the negative impacts or taking the opportunities of future CC.

Effectiveness of time of sowing and cultivar choice for managing climate change: wheat crop phenology and water use efficiency

NASA Astrophysics Data System (ADS)

Luo, Qunying; O'Leary, Garry; Cleverly, James; Eamus, Derek

2018-02-01

Climate change (CC) presents a challenge for the sustainable development of wheat production systems in Australia. This study aimed to (1) quantify the impact of future CC on wheat grain yield for the period centred on 2030 from the perspectives of wheat phenology, water use and water use efficiency (WUE) and (2) evaluate the effectiveness of changing sowing times and cultivars in response to the expected impacts of future CC on wheat grain yield. The daily outputs of CSIRO Conformal-Cubic Atmospheric Model for baseline and future periods were used by a stochastic weather generator to derive changes in mean climate and in climate variability and to construct local climate scenarios, which were then coupled with a wheat crop model to achieve the two research aims. We considered three locations in New South Wales, Australia, six times of sowing (TOS) and three bread wheat (Triticum aestivum L.) cultivars in this study. Simulation results show that in 2030 (1) for impact analysis, wheat phenological events are expected to occur earlier and crop water use is expected to decrease across all cases (the combination of three locations, six TOS and three cultivars), wheat grain yield would increase or decrease depending on locations and TOS; and WUE would increase in most of the cases; (2) for adaptation considerations, the combination of TOS and cultivars with the highest yield varied across locations. Wheat growers at different locations will require different strategies in managing the negative impacts or taking the opportunities of future CC.

Future changes in Yuan River ecohydrology: Individual and cumulative impacts of climates change and cascade hydropower development on runoff and aquatic habitat quality.

PubMed

Wen, Xin; Liu, Zhehua; Lei, Xiaohui; Lin, Rongjie; Fang, Guohua; Tan, Qiaofeng; Wang, Chao; Tian, Yu; Quan, Jin

2018-08-15

The eco-hydrological system in southwestern China is undergoing great changes in recent decades owing to climate change and extensive cascading hydropower exploitation. With a growing recognition that multiple drivers often interact in complex and nonadditive ways, the purpose of this study is to predict the potential future changes in streamflow and fish habitat quality in the Yuan River and quantify the individual and cumulative effect of cascade damming and climate change. The bias corrected and spatial downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) General Circulation Model (GCM) projections are employed to drive the Soil and Water Assessment Tool (SWAT) hydrological model and to simulate and predict runoff responses under diverse scenarios. Physical habitat simulation model is established to quantify the relationship between river hydrology and fish habitat, and the relative change rate is used to assess the individual and combined effects of cascade damming and climate change. Mean annual temperature, precipitation and runoff in 2015-2100 show an increasing trend compared with that in 1951-2010, with a particularly pronounced difference between dry and wet years. The ecological habitat quality is improved under cascade hydropower development since that ecological requirement has been incorporated in the reservoir operation policy. As for middle reach, the runoff change from January to August is determined mainly by damming, and climate change influence becomes more pronounced in dry seasons from September to December. Cascade development has an effect on runoff of lower reach only in dry seasons due to the limited regulation capacity of reservoirs, and climate changes have an effect on runoff in wet seasons. Climate changes have a less significant effect on fish habitat quality in middle reach than damming, but a more significant effect in lower reach. In addition, the effect of climate changes on fish habitat quality in lower reach is high in dry seasons but low in flood seasons. Copyright © 2018 Elsevier B.V. All rights reserved.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO 2

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

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali

Heat and drought stresses are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentration. Here we present a study that quantified the current and future yield responses of US rainfed maize and soybean to climate extremes, and for the first time characterized spatial shifts in the relative importance of temperature, heat and drought stress. Crop yields are simulated using the Agricultural Production Systems sIMulator (APSIM), driven by the high-resolution (12 km) Weather Research and Forecasting (WRF) Model downscaled futuremore » climate scenarios at two time slices (1995-2005 and 2085-2094). Our results show that climatic yield gaps and interannual variability are greater in the core production area than in the remaining US by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of change is highly dependent on the current climate sensitivity and vulnerability. Elevated CO2 partially offsets the climatic yield gaps and reduces interannual yield variability, and effect is more prominent in soybean than in maize. We demonstrate that drought will continue to be the largest threat to US rainfed maize and soybean production, although its dominant role gradually gives way to other impacts of heat extremes. We also reveal that shifts in the geographic distributions of dominant stressors are characterized by increases in the concurrent stress, especially for the US Midwest. These findings imply the importance of considering drought and extreme heat simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management.« less

Crop connectivity under climate change: future environmental and geographic risks of potato late blight in Scotland.

PubMed

Skelsey, Peter; Cooke, David E L; Lynott, James S; Lees, Alison K

2016-11-01

The impact of climate change on dispersal processes is largely ignored in risk assessments for crop diseases, as inoculum is generally assumed to be ubiquitous and nonlimiting. We suggest that consideration of the impact of climate change on the connectivity of crops for inoculum transmission may provide additional explanatory and predictive power in disease risk assessments, leading to improved recommendations for agricultural adaptation to climate change. In this study, a crop-growth model was combined with aerobiological models and a newly developed infection risk model to provide a framework for quantifying the impact of future climates on the risk of disease occurrence and spread. The integrated model uses standard meteorological variables and can be easily adapted to various crop pathosystems characterized by airborne inoculum. In a case study, the framework was used with data defining the spatial distribution of potato crops in Scotland and spatially coherent, probabilistic climate change data to project the future connectivity of crop distributions for Phytophthora infestans (causal agent of potato late blight) inoculum and the subsequent risk of infection. Projections and control recommendations are provided for multiple combinations of potato cultivar and CO 2 emissions scenario, and temporal and spatial averaging schemes. Overall, we found that relative to current climatic conditions, the risk of late blight will increase in Scotland during the first half of the potato growing season and decrease during the second half. To guide adaptation strategies, we also investigated the potential impact of climate change-driven shifts in the cropping season. Advancing the start of the potato growing season by 1 month proved to be an effective strategy from both an agronomic and late blight management perspective. © 2016 John Wiley & Sons Ltd.

Asymmetries in Climate Change Feedbacks: Why the Future may be Hotter Than you Think

NASA Astrophysics Data System (ADS)

Torn, M. S.; Harte, J.

2006-12-01

Feedbacks in the climate system are major sources of uncertainty, and climate predictions do not yet include one key set of feedbacks, namely biospheric greenhouse gas (GhG) feedbacks. Historical evidence shows that atmospheric GhG concentrations increase during periods of warming, implying a positive feedback to future climate change. We quantify this feedback for carbon dioxide (CO2) and methane (CH4) by combining the mathematics of feedback with both empirical ice-core information and general circulation model climate sensitivity. We find that a warming of 1.7-5.8°C predicted for the year 2100 is amplified to a warming commitment of 1.9-7.7°C, with the range deriving from different GCM simulations and paleo temperature records. Thus, anthropogenic emissions result in higher final GhG concentrations, and therefore more warming, than would be predicted in the absence of this feedback. Uncertainty in climate change predictions have been used as a rationale for inaction against the threat of global warming, based on a prevailing view that the uncertainties are symmetric, giving equal support to climate "optimists" (who think it will be a small problem) and "pessimists," (it will be a big problem). Our results show that even a symmetrical uncertainty in any component of feedback, whether positive or negative, produces an asymmetrical distribution of expected temperatures skewed towards higher temperature. For both reasons, the omission of key positive feedbacks and asymmetrical uncertainty from feedbacks, it is likely that the future will be hotter than we think, which implies more severe climate change impacts. Thus, these results suggest that a conservative policy approach would employ lower emission targets and tighter stabilization time horizons than would otherwise be required.

Changes in the probability of co-occurring extreme climate events

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2017-12-01

Extreme climate events such as floods, droughts, heatwaves, and severe storms exert acute stresses on natural and human systems. When multiple extreme events co-occur, either in space or time, the impacts can be substantially compounded. A diverse set of human interests - including supply chains, agricultural commodities markets, reinsurance, and deployment of humanitarian aid - have historically relied on the rarity of extreme events to provide a geographic hedge against the compounded impacts of co-occuring extremes. However, changes in the frequency of extreme events in recent decades imply that the probability of co-occuring extremes is also changing, and is likely to continue to change in the future in response to additional global warming. This presentation will review the evidence for historical changes in extreme climate events and the response of extreme events to continued global warming, and will provide some perspective on methods for quantifying changes in the probability of co-occurring extremes in the past and future.

Development of new impact functions for global risk caused by climate change

NASA Astrophysics Data System (ADS)

Miyazaki, C.

2014-12-01

The purpose of our study is to identify and quantify global-scale risks which can be caused by future climate change. In particular, we focus on the global-scale risks which have critical impacts to human environments. Use of impact functions is one of the common way to quantify global-scale risks. Output of impact function is climate impacts (e.g. economic damage by temperature increasing) and input can be global temperature increasing and/or socioeconomic condition (e.g. GDP). As the first step of study, we referred to AR5 WG II report (AR5, hereafter) and comprehensive inventories of climate change risks developed by Strategic R&D Area Project of the Environment Research and Technology Development Fund (ICA-RUS project). Then we extracted information which can be used to develop impact function from them. By following SPM/AR5, we focused on 11 sectors and extracted quantitative description on climate impacts from the AR5 and paper/reports cited in AR5. As a result, we identified about 40 risk items to focus as global-scale risks by climate change. Using the collected information, we tentatively made impact function on sea level rise and so on. In addition, we also extracted the impact functions used in Integrated Assessment Models (IAMs). The literature survey on IAM suggested the risk items considered in IAMs are limited. For instance, although FUND model provides detailed impact functions compared with most of other IAMs, its impact functions deal with only several sectors (e.g. agriculture, forestry, biodiversity, sea level rise, human health, energy demand and water resources). The survey on impact functions in IAMs also suggested impact function for abrupt climate change (so-called Tipping Element) is premature. Moreover, as example for quantifying health risk by our calculation, we also present the result on global-scale projection of the health burden attributable to childhood undernutrition (Ishida et al., 2014, ERL).

Nonlinear Interactions between Climate and Atmospheric Carbon Dioxide Drivers of Terrestrial and Marine Carbon Cycle Changes

NASA Astrophysics Data System (ADS)

Hoffman, F. M.; Randerson, J. T.; Moore, J. K.; Goulden, M.; Fu, W.; Koven, C.; Swann, A. L. S.; Mahowald, N. M.; Lindsay, K. T.; Munoz, E.

2017-12-01

Quantifying interactions between global biogeochemical cycles and the Earth system is important for predicting future atmospheric composition and informing energy policy. We applied a feedback analysis framework to three sets of Historical (1850-2005), Representative Concentration Pathway 8.5 (2006-2100), and its extension (2101-2300) simulations from the Community Earth System Model version 1.0 (CESM1(BGC)) to quantify drivers of terrestrial and ocean responses of carbon uptake. In the biogeochemically coupled simulation (BGC), the effects of CO2 fertilization and nitrogen deposition influenced marine and terrestrial carbon cycling. In the radiatively coupled simulation (RAD), the effects of rising temperature and circulation changes due to radiative forcing from CO2, other greenhouse gases, and aerosols were the sole drivers of carbon cycle changes. In the third, fully coupled simulation (FC), both the biogeochemical and radiative coupling effects acted simultaneously. We found that climate-carbon sensitivities derived from RAD simulations produced a net ocean carbon storage climate sensitivity that was weaker and a net land carbon storage climate sensitivity that was stronger than those diagnosed from the FC and BGC simulations. For the ocean, this nonlinearity was associated with warming-induced weakening of ocean circulation and mixing that limited exchange of dissolved inorganic carbon between surface and deeper water masses. For the land, this nonlinearity was associated with strong gains in gross primary production in the FC simulation, driven by enhancements in the hydrological cycle and increased nutrient availability. We developed and applied a nonlinearity metric to rank model responses and driver variables. The climate-carbon cycle feedback gain at 2300 was 42% higher when estimated from climate-carbon sensitivities derived from the difference between FC and BGC than when derived from RAD. We re-analyzed other CMIP5 model results to quantify the effects of such nonlinearities on their projected climate-carbon cycle feedback gains.

Reservoirs performances under climate variability: a case study

NASA Astrophysics Data System (ADS)

Longobardi, A.; Mautone, M.; de Luca, C.

2014-09-01

A case study, the Piano della Rocca dam (southern Italy) is discussed here in order to quantify the system performances under climate variability conditions. Different climate scenarios have been stochastically generated according to the tendencies in precipitation and air temperature observed during recent decades for the studied area. Climate variables have then been filtered through an ARMA model to generate, at the monthly scale, time series of reservoir inflow volumes. Controlled release has been computed considering the reservoir is operated following the standard linear operating policy (SLOP) and reservoir performances have been assessed through the calculation of reliability, resilience and vulnerability indices (Hashimoto et al. 1982), comparing current and future scenarios of climate variability. The proposed approach can be suggested as a valuable tool to mitigate the effects of moderate to severe and persistent droughts periods, through the allocation of new water resources or the planning of appropriate operational rules.

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

PubMed Central

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-01-01

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (−) and one month ago (−)), and average relative humidity (current and 9 months ago (−)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future. PMID:26848675

Final Technical Report for DOE Award SC0006616

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

Robertson, Andrew

2015-08-01

This report summarizes research carried out by the project "Collaborative Research, Type 1: Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoonal Asia. This collaborative project brought together climate dynamicists (UCLA, IRI), dendroclimatologists (LDEO Tree Ring Laboratory), computer scientists (UCI), and hydrologists (Columbia Water Center, CWC), together with applied scientists in climate risk management (IRI) to create new scientific approaches to quantify and exploit the role of climate variability and change in the growing water crisis across southern and eastern Asia. This project developed new tree-ring based streamflow reconstructions for rivers in monsoonal Asia; improved understanding of hydrologic spatio-temporal modesmore » of variability over monsoonal Asia on interannual-to-centennial time scales; assessed decadal predictability of hydrologic spatio-temporal modes; developed stochastic simulation tools for creating downscaled future climate scenarios based on historical/proxy data and GCM climate change; and developed stochastic reservoir simulation and optimization for scheduling hydropower, irrigation and navigation releases.« less

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan.

PubMed

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-02-03

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (-) and one month ago (-)), and average relative humidity (current and 9 months ago (-)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

Climate Change Impacts at Department of Defense

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

Kotamarthi, Rao; Wang, Jiali; Zoebel, Zach

This project is aimed at providing the U.S. Department of Defense (DoD) with a comprehensive analysis of the uncertainty associated with generating climate projections at the regional scale that can be used by stakeholders and decision makers to quantify and plan for the impacts of future climate change at specific locations. The merits and limitations of commonly used downscaling models, ranging from simple to complex, are compared, and their appropriateness for application at installation scales is evaluated. Downscaled climate projections are generated at selected DoD installations using dynamic and statistical methods with an emphasis on generating probability distributions of climatemore » variables and their associated uncertainties. The sites selection and selection of variables and parameters for downscaling was based on a comprehensive understanding of the current and projected roles that weather and climate play in operating, maintaining, and planning DoD facilities and installations.« less

Climate Change and Neotectonic History of Northwestern China

NASA Technical Reports Server (NTRS)

Farr, Tom G.; Chadwick, Oliver; Evans, Diane; Gillespie, Alan; Peltzer, Gilles; Tapponnier, Paul

1996-01-01

The progress, results and future plans for the following objectives are presented: (1) To compare the types, rates, and magnitudes of surficial modification processes that have operated in Northwest China and the Southwestern U.S.; (2) To quantify and understand the basis of the remote sensing signatures of these processes to allow extrapolation from field sites to regional maps and to allow comparisons between widely separated arid regions; (3) To use the resulting chronologies to help define the temporal and spatial distribution of continental climate changes; and (4) Determine the ages of movements on some of the active faults in Northwestern China.

Synthetic drought event sets: thousands of meteorological drought events for risk-based management under present and future conditions

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Massey, Neil; Otto, Friederike E. L.; Allen, Myles R.; Jones, Richard; Hall, Jim W.

2016-04-01

Droughts and related water scarcity can have large impacts on societies and consist of interactions between a number of natural and human factors. Meteorological conditions are usually the first natural trigger of droughts, and climate change is expected to impact these and thereby the frequency and intensity of the events. However, extreme events such as droughts are, by definition, rare, and accurately quantifying the risk related to such events is therefore difficult. The MaRIUS project (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity) aims at quantifying the risks associated with droughts in the UK under present and future conditions. To do so, a large number of drought events, from climate model simulations downscaled at 25km over Europe, are being fed into hydrological models of various complexity and used for the estimation of drought risk associated with human and natural systems, including impacts on the economy, industry, agriculture, terrestrial and aquatic ecosystems, and socio-cultural aspects. Here, we present the hydro-meteorological drought event set that has been produced by weather@home [1] for MaRIUS. Using idle processor time on volunteers' computers around the world, we have run a very large number (10'000s) of Global Climate Model (GCM) simulations, downscaled at 25km over Europe by a nested Regional Climate Model (RCM). Simulations include the past 100 years as well as two future horizons (2030s and 2080s), and provide a large number of sequences of spatio-temporally consistent weather, which are consistent with the boundary forcing such as the ocean, greenhouse gases and solar forcing. The drought event set for use in impact studies is constructed by extracting sequences of dry conditions from these model runs, leading to several thousand drought events. In addition to describing methodological and validation aspects of the synthetic drought event sets, we provide insights into drought risk in the UK, its meteorological drivers, and how it can be expected to change in the future. Finally, we assess the applicability of this methodology to other regions. [1] Massey, N. et al., 2014, Q. J. R. Meteorol. Soc.

A new framework for quantifying uncertainties in modelling studies for future climates - how more certain are CMIP5 precipitation and temperature simulations compared to CMIP3?

NASA Astrophysics Data System (ADS)

Sharma, A.; Woldemeskel, F. M.; Sivakumar, B.; Mehrotra, R.

2014-12-01

We outline a new framework for assessing uncertainties in model simulations, be they hydro-ecological simulations for known scenarios, or climate simulations for assumed scenarios representing the future. This framework is illustrated here using GCM projections for future climates for hydrologically relevant variables (precipitation and temperature), with the uncertainty segregated into three dominant components - model uncertainty, scenario uncertainty (representing greenhouse gas emission scenarios), and ensemble uncertainty (representing uncertain initial conditions and states). A novel uncertainty metric, the Square Root Error Variance (SREV), is used to quantify the uncertainties involved. The SREV requires: (1) Interpolating raw and corrected GCM outputs to a common grid; (2) Converting these to percentiles; (3) Estimating SREV for model, scenario, initial condition and total uncertainty at each percentile; and (4) Transforming SREV to a time series. The outcome is a spatially varying series of SREVs associated with each model that can be used to assess how uncertain the system is at each simulated point or time. This framework, while illustrated in a climate change context, is completely applicable for assessment of uncertainties any modelling framework may be subject to. The proposed method is applied to monthly precipitation and temperature from 6 CMIP3 and 13 CMIP5 GCMs across the world. For CMIP3, B1, A1B and A2 scenarios whereas for CMIP5, RCP2.6, RCP4.5 and RCP8.5 representing low, medium and high emissions are considered. For both CMIP3 and CMIP5, model structure is the largest source of uncertainty, which reduces significantly after correcting for biases. Scenario uncertainly increases, especially for temperature, in future due to divergence of the three emission scenarios analysed. While CMIP5 precipitation simulations exhibit a small reduction in total uncertainty over CMIP3, there is almost no reduction observed for temperature projections. Estimation of uncertainty in both space and time sheds lights on the spatial and temporal patterns of uncertainties in GCM outputs, providing an effective platform for risk-based assessments of any alternate plans or decisions that may be formulated using GCM simulations.

A Review of Frameworks for Developing Environmental Health Indicators for Climate Change and Health

PubMed Central

Hambling, Tammy; Weinstein, Philip; Slaney, David

2011-01-01

The role climate change may play in altering human health, particularly in the emergence and spread of diseases, is an evolving area of research. It is important to understand this relationship because it will compound the already significant burden of diseases on national economies and public health. Authorities need to be able to assess, anticipate, and monitor human health vulnerability to climate change, in order to plan for, or implement action to avoid these eventualities. Environmental health indicators (EHIs) provide a tool to assess, monitor, and quantify human health vulnerability, to aid in the design and targeting of interventions, and measure the effectiveness of climate change adaptation and mitigation activities. Our aim was to identify the most suitable framework for developing EHIs to measure and monitor the impacts of climate change on human health and inform the development of interventions. Using published literature we reviewed the attributes of 11 frameworks. We identified the Driving force-Pressure-State-Exposure-Effect-Action (DPSEEA) framework as the most suitable one for developing EHIs for climate change and health. We propose the use of EHIs as a valuable tool to assess, quantify, and monitor human health vulnerability, design and target interventions, and measure the effectiveness of climate change adaptation and mitigation activities. In this paper, we lay the groundwork for the future development of EHIs as a multidisciplinary approach to link existing environmental and epidemiological data and networks. Analysis of such data will contribute to an enhanced understanding of the relationship between climate change and human health. PMID:21845162

Leveraging federal science data and tools to help communities & business build climate resilience

NASA Astrophysics Data System (ADS)

Herring, D.

2016-12-01

Decision-makers in every sector and region of the United States are seeking actionable science-based information to help them understand and manage their climate-related risks. Translating data, tools and information from the domain of climate science to the domains of municipal, social, and economic decision-making raises complex questions—e.g., how to communicate causes and impacts of climate variability and change; how to show projections of plausible future climate scenarios; how to characterize and quantify vulnerabilities, risks, and opportunities facing communities and businesses; and how to make and implement "win-win" adaptation plans. These are the types of challenges being addressed by a public-private partnership of federal agencies, academic institutions, non-governmental organizations, and private businesses that are contributing to the development of the U.S. Climate Resilience Toolkit (toolkit.climate.gov), a new website designed to help people build resilience to extreme events caused by both natural climate variability and long-term climate change. The site's Climate Explorer is designed to help people understand potential climate conditions over the course of this century. It offers easy access to downloadable maps, graphs, and data tables of observed and projected temperature, precipitation and other decision-relevant climate variables dating back to 1950 and out to 2100. Of course, climate change is only one of many variables affecting decisions about the future so the Toolkit also ties climate information to a wide range of other relevant tools and information to help users to explore their vulnerabilities and risks. In this session, we will describe recent enhancements to the Toolkit, lessons learned from user engagements, and evidence that our approach of coupling scientific information with actionable decision-making processes is helping Americans build resilience to climate-related impacts.

Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Science Goals and Preliminary Analysis

NASA Astrophysics Data System (ADS)

Shields, C. A.; Rutz, J. J.; Wehner, M. F.; Ralph, F. M.; Leung, L. R.

2017-12-01

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is a community effort whose purpose is to quantify uncertainties in atmospheric river (AR) research solely due to different identification and tracking techniques. Atmospheric rivers transport significant amounts of moisture in long, narrow filamentary bands, typically travelling from the subtropics to the mid-latitudes. They are an important source of regional precipitation impacting local hydroclimate, and in extreme cases, cause severe flooding and infrastructure damage in local communities. Our understanding of ARs, from forecast skill to future climate projections, all hinge on how we define ARs. By comparing a diverse set of detection algorithms, the uncertainty in our definition of ARs, (including statistics and climatology), and the implications of those uncertainties, can be analyzed and quantified. ARTMIP is divided into two broad phases that aim to answer science questions impacted by choice of detection algorithm. How robust are AR metrics such as climatology, storm duration, and relationship to extreme precipitation? How are the AR metrics in future climate projections impacted by choice of algorithm? Some algorithms rely on threshold values for water vapor. In a warmer world, the background state, by definition, is moister due to the Clausius-Clapeyron relationship, and could potentially skew results. Can uncertainty bounds be accurately placed on each metric? Tier 1 participants will apply their algorithms to a high resolution common dataset (MERRA2) and provide the greater group AR metrics (frequency, location, duration, etc). Tier 2 research will encompass sensitivity studies regarding resolution, reanalysis choice, and future climate change scenarios. ARTMIP is currently in the Tier 1 Phase and will begin Tier 2 in 2018. Preliminary metrics and analysis from Tier 1 will be presented.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern US

USGS Publications Warehouse

Gremer, Jennifer; Bradford, John B.; Munson, Seth M.; Duniway, Michael C.

2015-01-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20 to 56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40 to 60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States.

PubMed

Gremer, Jennifer R; Bradford, John B; Munson, Seth M; Duniway, Michael C

2015-11-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Recent range expansion of a terrestrial orchid corresponds with climate-driven variation in its population dynamics.

PubMed

van der Meer, Sascha; Jacquemyn, Hans; Carey, Peter D; Jongejans, Eelke

2016-06-01

The population dynamics and distribution limits of plant species are predicted to change as the climate changes. However, it remains unclear to what extent climate variables affect population dynamics, which vital rates are most sensitive to climate change, and whether the same vital rates drive population dynamics in different populations. In this study, we used long-term demographic data from two populations of the terrestrial orchid Himantoglossum hircinum growing at the northern edge of their geographic range to quantify the influence of climate change on demographic vital rates. Integral projection models were constructed to study how climate conditions between 1991 and 2006 affected population dynamics and to assess how projected future climate change will affect the long-term viability of this species. Based on the parameterised vital rate functions and the observed climatic conditions, one of the studied populations had an average population growth rate above 1 (λ = 1.04), while the other was declining at ca. 3 % year(-1) (λ = 0.97). Variation in temperature and precipitation mainly affected population growth through their effect on survival and fecundity. Based on UK Climate Projection 2009 estimates of future climate conditions for three greenhouse gas emission scenarios, population growth rates are expected to increase in one of the studied populations. Overall, our results indicate that the observed changes in climatic conditions appeared to be beneficial to the long-term survival of the species in the UK and suggest that they may have been the driving force behind the current range expansion of H. hircinum in England.

Development of probabilistic regional climate scenario in East Asia

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Ishizaki, N. N.

2015-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in East Asia (CORDEX-EA and Japan), the probability distribution of 2m air temperature was estimated by using developed regression model. The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. Probabilistic climate information in present (1969-1998) and future (2069-2098) climate was developed using CMIP3 SRES A1b scenarios 21 models and the observation data (CRU_TS3.22 & University of Delaware in CORDEX-EA, NIAES AMeDAS mesh data in Japan). The prototype of probabilistic information in CORDEX-EA and Japan represent the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Appropriate combination of statistical methods and optimization of climate ensemble experiments using multi-General Circulation Models (GCMs) and multi-regional climate models (RCMs) ensemble downscaling experiments are investigated.

Modeling Urban Energy Savings Scenarios Using Earth System Microclimate and Urban Morphology

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rose, A.; New, J. R.; Yuan, J.; Omitaomu, O.; Sylvester, L.; Branstetter, M. L.; Carvalhaes, T. M.; Seals, M.; Berres, A.

2017-12-01

We analyze and quantify the relationships among climatic conditions, urban morphology, population, land cover, and energy use so that these relationships can be used to inform energy-efficient urban development and planning. We integrate different approaches across three research areas: earth system modeling; impacts, adaptation and vulnerability; and urban planning in order to address three major gaps in the existing capability in these areas: i) neighborhood resolution modeling and simulation of urban micrometeorological processes and their effect on and from regional climate; ii) projections for future energy use under urbanization and climate change scenarios identifying best strategies for urban morphological development and energy savings; iii) analysis and visualization tools to help planners optimally use these projections.

Quantifying the economic risks of climate change

NASA Astrophysics Data System (ADS)

Diaz, Delavane; Moore, Frances

2017-11-01

Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost-benefit integrated assessment models, with guidance for future work.

Forest legacies, climate change, altered disturbance regimes, invasive species and water

USGS Publications Warehouse

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

2007-01-01

The factors that must be considered in seeking to predict changes in water availability has been examined. These factors are the following: forest legacies including logging, mining, agriculture, grazing, elimination of large carnivores, human-caused wildfire, and pollution; climate change and stream flow; altered disturbances such as frequency intensity and pattern of wildfires and insect outbreaks as well as flood control; lastly, invasive species like forest pests and pathogens. An integrated approach quantifying the current and past condition trends can be combined with spatial and temporal modeling to develop future change in forest structures and water supply. The key is a combination of geographic information system technologies with climate and land use scenarios, while preventing and minimizing the effects of harmful invasive species.

Decomposing the uncertainty in climate impact projections of Dynamic Vegetation Models: a test with the forest models LANDCLIM and FORCLIM

NASA Astrophysics Data System (ADS)

Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald

2015-04-01

Different levels of uncertainty should be considered in climate impact projections by Dynamic Vegetation Models (DVMs), particularly when it comes to managing climate risks. Such information is useful to detect the key processes and uncertainties in the climate model - impact model chain and may be used to support recommendations for future improvements in the simulation of both climate and biological systems. In addition, determining which uncertainty source is dominant is an important aspect to recognize the limitations of climate impact projections by a multi-model ensemble mean approach. However, to date, few studies have clarified how each uncertainty source (baseline climate data, greenhouse gas emission scenario, climate model, and DVM) affects the projection of ecosystem properties. Focusing on one greenhouse gas emission scenario, we assessed the uncertainty in the projections of a forest landscape model (LANDCLIM) and a stand-scale forest gap model (FORCLIM) that is caused by linking climate data with an impact model. LANDCLIM was used to assess the uncertainty in future landscape properties of the Visp valley in Switzerland that is due to (i) the use of different 'baseline' climate data (gridded data vs. data from weather stations), and (ii) differences in climate projections among 10 GCM-RCM chains. This latter point was also considered for the projections of future forest properties by FORCLIM at several sites along an environmental gradient in Switzerland (14 GCM-RCM chains), for which we also quantified the uncertainty caused by (iii) the model chain specific statistical properties of the climate time-series, and (iv) the stochasticity of the demographic processes included in the model, e.g., the annual number of saplings that establish, or tree mortality. Using methods of variance decomposition analysis, we found that (i) The use of different baseline climate data strongly impacts the prediction of forest properties at the lowest and highest, but not so much at medium elevations. (ii) Considering climate change, the variability that is due to the GCM-RCM chains is much greater than the variability induced by the uncertainty in the initial climatic conditions. (iii) The uncertainties caused by the intrinsic stochasticity in the DVMs and by the random generation of the climate time-series are negligible. Overall, our results indicate that DVMs are quite sensitive to the climate data, highlighting particularly (1) the limitations of using one single multi-model average climate change scenario in climate impact studies and (2) the need to better consider the uncertainty in climate model outputs for projecting future vegetation changes.

Assessing the impacts of climate change and dams on floodplain inundation and wetland connectivity in the wet-dry tropics of northern Australia

NASA Astrophysics Data System (ADS)

Karim, Fazlul; Dutta, Dushmanta; Marvanek, Steve; Petheram, Cuan; Ticehurst, Catherine; Lerat, Julien; Kim, Shaun; Yang, Ang

2015-03-01

Floodplain wetlands and their hydrological connectivity with main river channels in the Australian wet-dry tropics are under increasing pressure from global climate change and water resource development, and there is a need for modelling tools to estimate the time dynamics of connectivity. This paper describes an integrated modelling framework combining conceptual rainfall-runoff modelling, river system modelling and hydrodynamic (HD) modelling to estimate hydrological connectivity between wetlands and rivers in the Flinders and Gilbert river catchments in northern Australia. Three historical flood events ranging from a mean annual flood to a 35-year return period flood were investigated using a two dimensional HD model (MIKE 21). Inflows from upstream catchments were estimated using a river network model. Local runoff within the HD modelling domain was simulated using the Sacramento rainfall-runoff model. The Shuttle Radar Topography Mission (SRTM) derived 30 m DEM was used to reproduce floodplain topography, stream networks and wetlands in the HD model. The HD model was calibrated using stream gauge data and inundation maps derived from satellite (MODIS: MODerate resolution Imaging Spectroradiometer) imagery. An algorithm was developed to combine the simulated water heights with the DEM to quantify inundation and flow connection between wetlands and rivers. The connectivity of 18 ecologically important wetlands on the Flinders floodplain and 7 on the Gilbert floodplain were quantified. The impacts of climate change and water resource development on connectivity to individual wetlands were assessed under a projected dry climate (2nd driest of 15 GCMs), wet climate (2nd wettest of 15 GCMs) and dam conditions. The results indicate that changes in rainfall under a wetter and drier future climate could have large impacts on area, duration and frequency of inundation and connectivity. Topographic relief, river bank elevation and flood magnitude were found to be the key factors contributing to the level of connectivity. Under a wetter future climate the average duration of connection of wetlands to the main river channel increased by 7% and under a drier climate it decreased by 18%. Construction of a 248 GL dam in the Flinders catchment and two (498 and 271 GL capacity) in the Gilbert catchment could reduce the average duration of connectivity by 1% and 2% in the Flinders and Gilbert catchments respectively. This information is potentially useful to future studies on the flood-dependent ecology in this region.

Climate change adaptation and Integrated Water Resource Management in the water sector

NASA Astrophysics Data System (ADS)

Ludwig, Fulco; van Slobbe, Erik; Cofino, Wim

2014-10-01

Integrated Water Resources Management (IWRM) was introduced in 1980s to better optimise water uses between different water demanding sectors. However, since it was introduced water systems have become more complicated due to changes in the global water cycle as a result of climate change. The realization that climate change will have a significant impact on water availability and flood risks has driven research and policy making on adaptation. This paper discusses the main similarities and differences between climate change adaptation and IWRM. The main difference between the two is the focus on current and historic issues of IWRM compared to the (long-term) future focus of adaptation. One of the main problems of implementing climate change adaptation is the large uncertainties in future projections. Two completely different approaches to adaptation have been developed in response to these large uncertainties. A top-down approach based on large scale biophysical impacts analyses focussing on quantifying and minimizing uncertainty by using a large range of scenarios and different climate and impact models. The main problem with this approach is the propagation of uncertainties within the modelling chain. The opposite is the bottom up approach which basically ignores uncertainty. It focusses on reducing vulnerabilities, often at local scale, by developing resilient water systems. Both these approaches however are unsuitable for integrating into water management. The bottom up approach focuses too much on socio-economic vulnerability and too little on developing (technical) solutions. The top-down approach often results in an “explosion” of uncertainty and therefore complicates decision making. A more promising direction of adaptation would be a risk based approach. Future research should further develop and test an approach which starts with developing adaptation strategies based on current and future risks. These strategies should then be evaluated using a range of future scenarios in order to develop robust adaptation measures and strategies.

Understanding and Predicting the Fate of Semivolatile Organic Pesticides in a Glacier-Fed Lake Using a Multimedia Chemical Fate Model.

PubMed

Wu, Xiaolin; Davie-Martin, Cleo L; Steinlin, Christine; Hageman, Kimberly J; Cullen, Nicolas J; Bogdal, Christian

2017-10-17

Melting glaciers release previously ice-entrapped chemicals to the surrounding environment. As glacier melting accelerates under future climate warming, chemical release may also increase. This study investigated the behavior of semivolatile pesticides over the course of one year and predicted their behavior under two future climate change scenarios. Pesticides were quantified in air, lake water, glacial meltwater, and streamwater in the catchment of Lake Brewster, an alpine glacier-fed lake located in the Southern Alps of New Zealand. Two historic-use pesticides (endosulfan I and hexachlorobenzene) and three current-use pesticides (dacthal, triallate, and chlorpyrifos) were frequently found in both air and water samples from the catchment. Regression analysis indicated that the pesticide concentrations in glacial meltwater and lake water were strongly correlated. A multimedia environmental fate model was developed for these five chemicals in Brewster Lake. Modeling results indicated that seasonal lake ice cover melt, and varying contributions of input from glacial melt and streamwater, created pulses in pesticide concentrations in lake water. Under future climate scenarios, the concentration pulse was altered and glacial melt made a greater contribution (as mass flux) to pesticide input in the lake water.

Trend Patterns of Vegetative Coverage and Their Underlying Causes in the Deserts of Northwest China over 1982 – 2008

PubMed Central

Zhang, Tianyi; Wang, Hesong

2015-01-01

We identified the spatiotemporal patterns of the Normalized Difference Vegetation Index (NDVI) for the years 1982–2008 in the desert areas of Northwest China and quantified the impacts of climate and non-climate factors on NDVI changes. The results indicate that although the mean NDVI has improved in 24.7% of the study region; 16.3% among the region has been stagnating in recent years and only 8.4% had a significantly increasing trend. Additionally, 45.3% of the region has maintained a stable trend over the study period and 30.0% has declined. A multiple regression model suggests that a wetter climate (quantified by the Palmer Drought Severity Index, PDSI) is associated with higher NDVI in most areas (18.1% of significance) but these historical changes in PDSI only caused an average improvement of approximately 0.4% over the study region. Contrasting the regression results under different trend patterns, no significant differences in PDSI impacts were detected among the four trend patterns. Therefore, we conclude that climate is not the primary driver for vegetative coverage in Northwest China. Future studies will be required to identify the impacts of specific non-climatic factors on vegetative coverage based on high-resolution data, which will be beneficial in creating an effective strategy to combat the recent desertification trend in China. PMID:25961563

Solar Spectral Irradiance and Climate

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Woods, T.; Cahalan, R.

2012-01-01

Spectrally resolved solar irradiance is recognized as being increasingly important to improving our understanding of the manner in which the Sun influences climate. There is strong empirical evidence linking total solar irradiance to surface temperature trends - even though the Sun has likely made only a small contribution to the last half-century's global temperature anomaly - but the amplitudes cannot be explained by direct solar heating alone. The wavelength and height dependence of solar radiation deposition, for example, ozone absorption in the stratosphere, absorption in the ocean mixed layer, and water vapor absorption in the lower troposphere, contribute to the "top-down" and "bottom-up" mechanisms that have been proposed as possible amplifiers of the solar signal. New observations and models of solar spectral irradiance are needed to study these processes and to quantify their impacts on climate. Some of the most recent observations of solar spectral variability from the mid-ultraviolet to the near-infrared have revealed some unexpected behavior that was not anticipated prior to their measurement, based on an understanding from model reconstructions. The atmospheric response to the observed spectral variability, as quantified in climate model simulations, have revealed similarly surprising and in some cases, conflicting results. This talk will provide an overview on the state of our understanding of the spectrally resolved solar irradiance, its variability over many time scales, potential climate impacts, and finally, a discussion on what is required for improving our understanding of Sun-climate connections, including a look forward to future observations.

Modeling land surface hydrology sensitivity in the Colorado River Basin to historical climate variability

NASA Astrophysics Data System (ADS)

Whitney, K. M.; Bohn, T. J.; Vivoni, E. R.

2017-12-01

Over the past century, the Colorado River Basin (CRB) has experienced substantial warming and interannual climate variations, including prolonged drought periods. These patterns are projected to accelerate in the 21st century, with major consequences for water resources in the southwestern U.S. and northwestern Mexico. To evaluate future projections appropriately, however, it is important to first quantify the regional hydrologic response to historical climate variability in the CRB. In the current effort, we force the Variable Infiltration Capacity (VIC) land surface hydrology model and a river routing model with historical meteorological data to estimate water balance components and naturalized streamflow response in the CRB at 1/16o spatial resolution and at an hourly time step over the period 1950-2013. We utilize data products from satellite remote sensing to specify spatiotemporal variations in vegetation parameters and include an irrigation scheme to account for evapotranspiration from croplands in the CRB. Furthermore, we apply recent modifications in VIC to more properly account for bare soil evaporation in arid and semiarid ecosystems. Analyses of the historical model simulations are focused on quantifying the spatiotemporal variability of the soil moisture, evapotranspiration, streamflow and snowmelt response and their linkages to extreme meteorological events. Here we characterize the annual and monthly distributions, trends, and statistical extremes and central tendencies of water balance terms averaged over the CRB and its sub-basins for the entire study period 1950-2013. By building a model-based hydrologic climatology and catalog of historical extreme events for the CRB, we aim to construct a basis for future activities that analyze the impact of statistically downscaled climate change projections on the hydrology of the CRB and its urban areas.

Aboveground carbon sequestration in dry temperate forests varies with climate not fire regime.

PubMed

Gordon, Christopher E; Bendall, Eli R; Stares, Mitchell G; Collins, Luke; Bradstock, Ross A

2018-06-01

The storage of carbon in plant tissues and debris has been proposed as a method to offset anthropogenic increases in atmospheric [CO 2 ]. Temperate forests represent significant above-ground carbon (AGC) "sinks" because their relatively fast growth and slow decay rates optimise carbon assimilation. Fire is a common disturbance event in temperate forests globally that should strongly influence AGC because: discrete fires consume above-ground biomass releasing carbon to the atmosphere, and the long-term application of different fire-regimes select for specific plant communities that sequester carbon at different rates. We investigated the latter process by quantifying AGC storage at 104 sites in the Sydney Basin Bioregion, Australia, relative to differences in components of the fire regime: frequency, severity and interfire interval. To predict the potential impacts of future climate change on fire/AGC interactions, we stratified our field sites across gradients of mean annual temperature and precipitation and quantified within- and between-factor interactions between the fire and climate variables. In agreement with previous studies, large trees were the primary AGC sink, accounting for ~70% of carbon at sites. Generalised additive models showed that mean annual temperature was the strongest predictor of AGC storage, with a 54% near-linear decrease predicted across the 6.1°C temperature range experienced at sites. Mean annual precipitation, fire frequency, fire severity and interfire interval were consistently poor predictors of total above-ground storage, although there were some significant relationships with component stocks. Our results show resilience of AGC to frequent and severe wildfire and suggest temperature mediated decreases in forest carbon storage under future climate change predictions. © 2018 John Wiley & Sons Ltd.

Particulate Matter and Ozone Prediction and Source Attribution for U.S. Air Quality Management in a Changing World

NASA Astrophysics Data System (ADS)

Sanyal, S.; Wuebbles, D. J.

2017-12-01

In this study, the focus is on how global changes in climate and emissions will affect the U.S. air quality, especially on fine particulate matter and ozone, projecting their future trends and quantifying key source attribution. We are conducting three primary experiments : (1) historical simulations for period 1994-2013 to establish the credibility of the system and refine process-level understanding of U.S. regional air quality; (2) projections for period 2041-2060 to quantify individual and combined impacts of global climate and emissions changes under multiple scenarios; (3) sensitivity analyses to determine future changes in pollution sources and their relative contributions from anthropogenic and natural emissions, long-range pollutant transport, and climate change effects. Here we will present the result from the first experiment with the global model CESM1.2 (with fully coupled chemistry using CAM-chem5) driven by NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis data at 0.9o x 1.25o resolution. We will present the comparison between the results from model simulation with observation data from EPA database. Since there is always a challenge in comparing gridded prediction from model data with point data from the observation databases, because the model simulations calculate the average outcome over a grid for a given set of conditions while the stochastic component (e.g. sub-grid variations) embedded in the observations are not accounted for, we are using extensive statistical measure to do the comparison. We will also determine relative contributions from multiscale (local, regional, global) processes, major source regions (Mexico, Canada, Asia, Africa) and types (natural, anthropogenic) and associated uncertainties (climate decadal oscillations/interannual variations, emissions and model structure errors).

Quantification of climate tourism potential of Croatia based on measured data and regional modeling.

PubMed

Brosy, Caroline; Zaninovic, Ksenija; Matzarakis, Andreas

2014-08-01

Tourism is one of the most important economic sectors in Croatia. The Adriatic coast is a popular travel destination for tourists, especially during the summer months. During their activities, tourists are affected by atmospheric conditions and therefore by weather and climate. Therefore, it is important to have reliable information about thermal conditions as well as their impacts on human beings. Here, the climate tourism potential of Croatia is presented and quantified on the basis of three selected stations in different climatic regions. The physiologically equivalent temperature is used for analysis as well as other climatic parameters relevant for tourism and recreation. The results already point to hot conditions for outdoor activities in summer during afternoons, especially along the coast but also for continental regions, resulting in a reduction of the climate tourism potential. In the future, this trend looks set to increase, possibly leading to a changing tourism sector in Croatia requiring adaptation and new strategies.

Large storage operations under climate change: expanding uncertainties and evolving tradeoffs

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Anghileri, Daniela; Castelletti, Andrea; Vu, Phuong Nam; Soncini-Sessa, Rodolfo

2016-03-01

In a changing climate and society, large storage systems can play a key role for securing water, energy, and food, and rebalancing their cross-dependencies. In this letter, we study the role of large storage operations as flexible means of adaptation to climate change. In particular, we explore the impacts of different climate projections for different future time horizons on the multi-purpose operations of the existing system of large dams in the Red River basin (China-Laos-Vietnam). We identify the main vulnerabilities of current system operations, understand the risk of failure across sectors by exploring the evolution of the system tradeoffs, quantify how the uncertainty associated to climate scenarios is expanded by the storage operations, and assess the expected costs if no adaptation is implemented. Results show that, depending on the climate scenario and the time horizon considered, the existing operations are predicted to change on average from -7 to +5% in hydropower production, +35 to +520% in flood damages, and +15 to +160% in water supply deficit. These negative impacts can be partially mitigated by adapting the existing operations to future climate, reducing the loss of hydropower to 5%, potentially saving around 34.4 million US year-1 at the national scale. Since the Red River is paradigmatic of many river basins across south east Asia, where new large dams are under construction or are planned to support fast growing economies, our results can support policy makers in prioritizing responses and adaptation strategies to the changing climate.

Future Climate Change Impacts on Surface Hydrology over Texas River Basins

NASA Astrophysics Data System (ADS)

Lee, K.; Gao, H.; Huang, M.; Sheffield, J.

2014-12-01

Future freshwater availability is a pressing issue in Texas due to frequent drought events and fast population growth. Even though the science community has well investigated future temperature trends, it is still unclear whether precipitation will increase or decrease in this region. Furthermore, there is a lack of understanding on how the changing climate will affect water resources across different spatial-temporal scales. This study aims to quantify the impacts of climate change on surface hydrology at the basin scale under different future emission scenarios. The Variable Infiltration Capacity (VIC) model, forced by an ensemble of statistically downscaled climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, is employed to predict the future hydrology. The VIC model parameters are adopted from the North American Land Data Assimilation System (NLDAS) at a spatial resolution of 1/8°. The CMIP5 projections contain four different scenarios in terms of Representative Concentration Pathway (RCP) (i.e. 2.6, 4.5, 6.0 and 8.5 w/m2). The analysis is carried out in three steps. First, the observed streamflows are used to evaluate the performance of VIC simulations forced by CMIP5 models during historical period. Second, VIC outputs under multiple CMIP5 model scenarios from 1950 to 2099 are analyzed to identify how soil moisture, evapotranspiration, runoff, and routed streamflows change in time and space. Third, the spatial patterns of seasonal temperature, seasonal precipitation, and the Palmer Drought Severity Index (PDSI)—over four 20-year periods (1980-1999, 2010-2029, 2040-2059 and 2080-2099)—are used to pinpoint the regions that will be most affected by climate change (among the 13 Texan river basins). Furthermore, the role of groundwater in meeting the increasing needs for water supply is discussed. The results are expected to contribute to various future water resources management decisions in Texas.

The utility of the historical record in assessing future carbon budgets

NASA Astrophysics Data System (ADS)

Millar, R.; Friedlingstein, P.; Allen, M. R.

2017-12-01

It has long been known that the cumulative emissions of carbon dioxide (CO2) is the most physically relevant determiner of long-lived anthropogenic climate change, with an approximately linear relationship between CO2-induced global mean surface warming and cumulative emissions. The historical observational record offers a way to constrain the relationship between cumulative carbon dioxide emission and global mean warming using observations to date. Here we show that simple regression analysis indicates that the 1.5°C carbon budget would be exhausted after nearly three decades of current emissions, substantially in excess of many estimates from Earth System Models. However, there are many reasons to be cautious about carbon budget assessments from the historical record alone. Accounting for the uncertainty in non-CO2 radiative forcing using a simple climate model and a standard optimal fingerprinting detection attribution technique gives substantial uncertainty in the contribution of CO2 warming to date, and hence the transient climate response to cumulative emissions. Additionally, the existing balance between CO2 and non-CO2 forcing may change in the future under ambitious mitigation scenarios as non-CO2 emissions become more (or less) important to global mean temperature changes. Natural unforced variability can also have a substantial impact on estimates of remaining carbon budgets. By examining all warmings of a given magnitude in both the historical record and past and future ESM simulations we quantify the impact unforced climate variability may have on estimates of remaining carbon budgets, derived as a function of estimated non-CO2 warming and future emission scenario. In summary, whilst the historical record can act as a useful test of climate models, uncertainties in the response to future cumulative emissions remain large and extrapolations of future carbon budgets from the historical record alone should be treated with caution.

A vicious circle of fire, deforestation and climate change: an integrative study for the Amazon region

NASA Astrophysics Data System (ADS)

Thonicke, K.; Rammig, A.; Gumpenberger, M.; Vohland, K.; Poulter, B.; Cramer, W.

2009-04-01

The Amazon rainforest is threatened by deforestation due to wood extraction and agricultural production leading to increasing forest fragmentation and forest degradation. These changes in land surface characteristics and water fluxes are expected to further reduce convective precipitation. Under future climate change the stability of the Amazon rainforest is likely to decrease thus leading to forest dieback (savannization) or forest degradation (secondarization). This puts the Amazon rainforest at risk to reduce the generation of precipitation, to act as a carbon sink and biodiversity hotspot. Fires increased in the past during drought years and in open vegetation thereby further accelerating forest degradation. Deforestation as a result of socioeconomic development in the Amazon basin is projected to further increase in the 21st century and brings climate-induced changes forward. Combined effects of deforestation vs. climate change on the stability of the Amazon rainforest and the role of fire in this system need to be quantified in an integrated study. We present simulation results from future climate (AR4) and deforestation (SimAmazon) experiments using the LPJmL-SPITFIRE vegetation model. Land use change is the main driving factor of forest degradation before 2050, whereas extreme climate change scenarios lead to forest degradation by the end of 2100. Forest fires increase with increasing drought conditions during the 21st century. The resulting effects on vegetation secondarization and savannization and their feedbacks on fire spread and emissions will be presented. The effect of wildfires and intentional burning on forest degradation under future climate and socioeconomic change will be discussed, and recommendations for an integrated land use and fire management are given.

Twenty-first century wave climate projections for Ireland and surface winds in the North Atlantic Ocean

NASA Astrophysics Data System (ADS)

Gallagher, Sarah; Gleeson, Emily; Tiron, Roxana; McGrath, Ray; Dias, Frédéric

2016-04-01

Ireland has a highly energetic wave and wind climate, and is therefore uniquely placed in terms of its ocean renewable energy resource. The socio-economic importance of the marine resource to Ireland makes it critical to quantify how the wave and wind climate may change in the future due to global climate change. Projected changes in winds, ocean waves and the frequency and severity of extreme weather events should be carefully assessed for long-term marine and coastal planning. We derived an ensemble of future wave climate projections for Ireland using the EC-Earth global climate model and the WAVEWATCH III® wave model, by comparing the future 30-year period 2070-2099 to the period 1980-2009 for the RCP4.5 and the RCP8.5 forcing scenarios. This dataset is currently the highest resolution wave projection dataset available for Ireland. The EC-Earth ensemble predicts decreases in mean (up to 2 % for RCP4.5 and up to 3.5 % for RCP8.5) 10 m wind speeds over the North Atlantic Ocean (5-75° N, 0-80° W) by the end of the century, which will consequently affect swell generation for the Irish wave climate. The WAVEWATCH III® model predicts an overall decrease in annual and seasonal mean significant wave heights around Ireland, with the largest decreases in summer (up to 15 %) and winter (up to 10 %) for RCP8.5. Projected decreases in mean significant wave heights for spring and autumn were found to be small for both forcing scenarios (less than 5 %), with no significant decrease found for RCP4.5 off the west coast in those seasons.

Key drivers of ozone change and its radiative forcing over the 21st century

NASA Astrophysics Data System (ADS)

Iglesias-Suarez, Fernando; Kinnison, Douglas E.; Rap, Alexandru; Maycock, Amanda C.; Wild, Oliver; Young, Paul J.

2018-05-01

Over the 21st century changes in both tropospheric and stratospheric ozone are likely to have important consequences for the Earth's radiative balance. In this study, we investigate the radiative forcing from future ozone changes using the Community Earth System Model (CESM1), with the Whole Atmosphere Community Climate Model (WACCM), and including fully coupled radiation and chemistry schemes. Using year 2100 conditions from the Representative Concentration Pathway 8.5 (RCP8.5) scenario, we quantify the individual contributions to ozone radiative forcing of (1) climate change, (2) reduced concentrations of ozone depleting substances (ODSs), and (3) methane increases. We calculate future ozone radiative forcings and their standard error (SE; associated with inter-annual variability of ozone) relative to year 2000 of (1) 33 ± 104 m Wm-2, (2) 163 ± 109 m Wm-2, and (3) 238 ± 113 m Wm-2 due to climate change, ODSs, and methane, respectively. Our best estimate of net ozone forcing in this set of simulations is 430 ± 130 m Wm-2 relative to year 2000 and 760 ± 230 m Wm-2 relative to year 1750, with the 95 % confidence interval given by ±30 %. We find that the overall long-term tropospheric ozone forcing from methane chemistry-climate feedbacks related to OH and methane lifetime is relatively small (46 m Wm-2). Ozone radiative forcing associated with climate change and stratospheric ozone recovery are robust with regard to background climate conditions, even though the ozone response is sensitive to both changes in atmospheric composition and climate. Changes in stratospheric-produced ozone account for ˜ 50 % of the overall radiative forcing for the 2000-2100 period in this set of simulations, highlighting the key role of the stratosphere in determining future ozone radiative forcing.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US.

PubMed

Hurteau, Matthew D

2017-01-01

Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C) sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC), but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010-2019), mid (2050-2059), and late (2090-2099) century climate projections for a ponderosa pine (Pinus ponderosa) dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn) and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE) for the different treatments. Over the simulation period, 32.8-48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US

PubMed Central

2017-01-01

Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C) sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC), but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010–2019), mid (2050–2059), and late (2090–2099) century climate projections for a ponderosa pine (Pinus ponderosa) dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn) and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE) for the different treatments. Over the simulation period, 32.8–48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink. PMID:28046079

Systematic review of current efforts to quantify the impacts of climate change on undernutrition.

PubMed

Phalkey, Revati K; Aranda-Jan, Clara; Marx, Sabrina; Höfle, Bernhard; Sauerborn, Rainer

2015-08-18

Malnutrition is a challenge to the health and productivity of populations and is viewed as one of the five largest adverse health impacts of climate change. Nonetheless, systematic evidence quantifying these impacts is currently limited. Our aim was to assess the scientific evidence base for the impact of climate change on childhood undernutrition (particularly stunting) in subsistence farmers in low- and middle-income countries. A systematic review was conducted to identify peer-reviewed and gray full-text documents in English with no limits for year of publication or study design. Fifteen manuscripts were reviewed. Few studies use primary data to investigate the proportion of stunting that can be attributed to climate/weather variability. Although scattered and limited, current evidence suggests a significant but variable link between weather variables, e.g., rainfall, extreme weather events (floods/droughts), seasonality, and temperature, and childhood stunting at the household level (12 of 15 studies, 80%). In addition, we note that agricultural, socioeconomic, and demographic factors at the household and individual levels also play substantial roles in mediating the nutritional impacts. Comparable interdisciplinary studies based on primary data at a household level are urgently required to guide effective adaptation, particularly for rural subsistence farmers. Systemization of data collection at the global level is indispensable and urgent. We need to assimilate data from long-term, high-quality agricultural, environmental, socioeconomic, health, and demographic surveillance systems and develop robust statistical methods to establish and validate causal links, quantify impacts, and make reliable predictions that can guide evidence-based health interventions in the future.

Systematic review of current efforts to quantify the impacts of climate change on undernutrition

PubMed Central

Phalkey, Revati K.; Aranda-Jan, Clara; Marx, Sabrina; Höfle, Bernhard; Sauerborn, Rainer

2015-01-01

Malnutrition is a challenge to the health and productivity of populations and is viewed as one of the five largest adverse health impacts of climate change. Nonetheless, systematic evidence quantifying these impacts is currently limited. Our aim was to assess the scientific evidence base for the impact of climate change on childhood undernutrition (particularly stunting) in subsistence farmers in low- and middle-income countries. A systematic review was conducted to identify peer-reviewed and gray full-text documents in English with no limits for year of publication or study design. Fifteen manuscripts were reviewed. Few studies use primary data to investigate the proportion of stunting that can be attributed to climate/weather variability. Although scattered and limited, current evidence suggests a significant but variable link between weather variables, e.g., rainfall, extreme weather events (floods/droughts), seasonality, and temperature, and childhood stunting at the household level (12 of 15 studies, 80%). In addition, we note that agricultural, socioeconomic, and demographic factors at the household and individual levels also play substantial roles in mediating the nutritional impacts. Comparable interdisciplinary studies based on primary data at a household level are urgently required to guide effective adaptation, particularly for rural subsistence farmers. Systemization of data collection at the global level is indispensable and urgent. We need to assimilate data from long-term, high-quality agricultural, environmental, socioeconomic, health, and demographic surveillance systems and develop robust statistical methods to establish and validate causal links, quantify impacts, and make reliable predictions that can guide evidence-based health interventions in the future. PMID:26216952

Which climate change path are we following? Bad news from Scots pine

PubMed Central

D’Andrea, Ettore; Rezaie, Negar; Cammarano, Mario; Matteucci, Giorgio

2017-01-01

Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated. PMID:29252985

Water resources sensitivity to the isolated effects of land use, water demand and climate change under 2 degree global warming

NASA Astrophysics Data System (ADS)

Bisselink, Berny; Bernhard, Jeroen; de Roo, Ad

2017-04-01

One of the key impacts of global change are the future water resources. These water resources are influenced by changes in land use (LU), water demand (WD) and climate change. Recent developments in scenario modelling opened new opportunities for an integrated assessment. However, for identifying water resource management strategies it is helpful to focus on the isolated effects of possible changes in LU, WD and climate that may occur in the near future. In this work, we quantify the isolated contribution of LU, WD and climate to the integrated total water resources assuming a linear model behavior. An ensemble of five EURO-CORDEX RCP8.5 climate projections for the 31-year periods centered on the year of exceeding the global-mean temperature of 2 degree is used to drive the fully distributed hydrological model LISFLOOD for multiple river catchments in Europe. The JRC's Land Use Modelling Platform LUISA was used to obtain a detailed pan-European reference land use scenario until 2050. Water demand is estimated based on socio-economic (GDP, population estimates etc.), land use and climate projections as well. For each climate projection, four model runs have been performed including an integrated (LU, WD and climate) simulation and other three simulations to isolate the effect of LU, WD and climate. Changes relative to the baseline in terms of water resources indicators of the ensemble means of the 2 degree warming period and their associated uncertainties will reveal the integrated and isolated effect of LU, WD and climate change on water resources.

Which climate change path are we following? Bad news from Scots pine.

PubMed

Bombi, Pierluigi; D'Andrea, Ettore; Rezaie, Negar; Cammarano, Mario; Matteucci, Giorgio

2017-01-01

Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated.

Probabilistic Climate Scenario Information for Risk Assessment

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Takayabu, I.

2014-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in Japan, we compared the physics ensemble experiments using the 60km global atmospheric model of the Meteorological Research Institute (MRI-AGCM) with multi-model ensemble experiments with global atmospheric-ocean coupled models (CMIP3) of SRES A1b scenario experiments. The MRI-AGCM shows relatively good skills particularly in tropics for temperature and geopotential height. Variability in surface air temperature of physical ensemble experiments with MRI-AGCM was within the range of one standard deviation of the CMIP3 model in the Asia region. On the other hand, the variability of precipitation was relatively well represented compared with the variation of the CMIP3 models. Models which show the similar reproducibility in the present climate shows different future climate change. We couldn't find clear relationships between present climate and future climate change in temperature and precipitation. We develop a new method to produce probabilistic information of climate change scenarios by weighting model ensemble experiments based on a regression model (Krishnamurti et al., Science, 1999). The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. The prototype of probabilistic information in Japan represents the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Acknowledgments: This study was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

Model Projections and their Uncertainties of Future Intensity Change of Typhoon Haiyan (2013)

NASA Astrophysics Data System (ADS)

Yoshino, J.; Toyoda, M.; Shinohara, K.; Kobayashi, T.

2017-12-01

The IPCC fifth assessment report indicated that the global mean maximum wind speed and precipitation of tropical cyclone (TC) are likely to increase by the end of 21st century. However, the specific characteristics of future changes are not yet well quantified and there are high uncertainties in region-specific projections. Such uncertainties in future projections may be attributed to the uncertainties of general circulation models (GCMs) and global warming scenarios (GWSs). In order to quantify uncertainties of future changes of TC intensity among 15 GCMs and 9 GWSs, a present climate experiment (PCE), future climate experiments (FCEs) and sensitivity experiments on TC intensity are carried out in this study using a high-resolution typhoon model, coupled with sea spray, dissipative heating, ocean mixed layer parameterizations and automatic-TC tracking moving nests. The initial and boundary conditions for FCEs are produced by the method of pseudo-global warming downscaling technique. Typhoon Haiyan (2013) is selected as the worst case of a TC under the present climate. Using the high-resolution typhoon model with a grid spacing of 3km, PCE reproduces a peak intensity (minimum central pressure) of about 897.1hPa, which is in close agreement with the besttrack data (895hPa). Comparing the results between 9 FCEs driven by 9 GCMs fixed by one of GCMs (HadCM3) and 15 FCEs driven by 15 GWSs fixed by one of GWSs (in the 2090s of SRES A1B), the TC intensities are slightly weakened by +7.9hPa for GCMs and +3.7hPa for GWSs. The standard deviations of future changes of the peak intensity are 9.47hPa for GCMs and 5.89hPa for GWSs. Thus, the uncertainty of future changes of TC intensity among GCMs is approximately two times larger than that among GWSs. Sensitivity experiments, in which each of global warming differences derived from GCMs are separately added to the initial and boundary conditions of PCE, suggest that the future changes of sea surface temperature in GCMs are responsible for intensifying Haiyan by -19.6hPa while the future changes of air temperature in GCMs are accountable for weakening Haiyan by +45.5hPa. Furthermore, the future changes of air temperature and wind speed in GCMs especially reduce the reliabilities of future projections with standard deviations of 7.82hPa and 9.04hPa, respectively.

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

NASA Astrophysics Data System (ADS)

Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y.

2015-12-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12 digit Hydrologic Unit Code level) in the conterminous US (CONUS), and evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or 2-digit HUCs. Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8 °C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 g C m-2 yr-1 (9 %) increase in GPP. Response to climate change was highly variable across the 82, 773 watersheds, but in general, the majority would see consistent increases in all variables evaluated. Over half of the 82 773 watersheds, mostly found in the northeast and the southern part of the southwest would have an increase in annual Q (>100 mm yr-1 or 20 %). This study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results will be useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

Individual-scale inference to anticipate climate-change vulnerability of biodiversity.

PubMed

Clark, James S; Bell, David M; Kwit, Matthew; Stine, Anne; Vierra, Ben; Zhu, Kai

2012-01-19

Anticipating how biodiversity will respond to climate change is challenged by the fact that climate variables affect individuals in competition with others, but interest lies at the scale of species and landscapes. By omitting the individual scale, models cannot accommodate the processes that determine future biodiversity. We demonstrate how individual-scale inference can be applied to the problem of anticipating vulnerability of species to climate. The approach places climate vulnerability in the context of competition for light and soil moisture. Sensitivities to climate and competition interactions aggregated from the individual tree scale provide estimates of which species are vulnerable to which variables in different habitats. Vulnerability is explored in terms of specific demographic responses (growth, fecundity and survival) and in terms of the synthetic response (the combination of demographic rates), termed climate tracking. These indices quantify risks for individuals in the context of their competitive environments. However, by aggregating in specific ways (over individuals, years, and other input variables), we provide ways to summarize and rank species in terms of their risks from climate change.

The Dependencies of Ecosystem Pattern, Structure, and Dynamics on Climate, Climate Variability, and Climate Change

NASA Astrophysics Data System (ADS)

Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

2012-12-01

A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED's output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data shown in the database construction and by the model reinforces the need for high-resolution datasets and stresses the importance of understanding and incorporating climate change scenarios into earth system models.

Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest

USGS Publications Warehouse

Wylie, Bruce K.; Rigge, Matthew B.; Brisco, Brian; Mrnaghan, Kevin; Rover, Jennifer R.; Long, Jordan

2014-01-01

A warming climate influences boreal forest productivity, dynamics, and disturbance regimes. We used ecosystem models and 250 m satellite Normalized Difference Vegetation Index (NDVI) data averaged over the growing season (GSN) to model current, and estimate future, ecosystem performance. We modeled Expected Ecosystem Performance (EEP), or anticipated productivity, in undisturbed stands over the 2000–2008 period from a variety of abiotic data sources, using a rule-based piecewise regression tree. The EEP model was applied to a future climate ensemble A1B projection to quantify expected changes to mature boreal forest performance. Ecosystem Performance Anomalies (EPA), were identified as the residuals of the EEP and GSN relationship and represent performance departures from expected performance conditions. These performance data were used to monitor successional events following fire. Results suggested that maximum EPA occurs 30–40 years following fire, and deciduous stands generally have higher EPA than coniferous stands. Mean undisturbed EEP is projected to increase 5.6% by 2040 and 8.7% by 2070, suggesting an increased deciduous component in boreal forests. Our results contribute to the understanding of boreal forest successional dynamics and its response to climate change. This information enables informed decisions to prepare for, and adapt to, climate change in the Yukon River Basin forest.

Climate change impact assessment on hydrology of a small watershed using semi-distributed model

NASA Astrophysics Data System (ADS)

Pandey, Brij Kishor; Gosain, A. K.; Paul, George; Khare, Deepak

2017-07-01

This study is an attempt to quantify the impact of climate change on the hydrology of Armur watershed in Godavari river basin, India. A GIS-based semi-distributed hydrological model, soil and water assessment tool (SWAT) has been employed to estimate the water balance components on the basis of unique combinations of slope, soil and land cover classes for the base line (1961-1990) and future climate scenarios (2071-2100). Sensitivity analysis of the model has been performed to identify the most critical parameters of the watershed. Average monthly calibration (1987-1994) and validation (1995-2000) have been performed using the observed discharge data. Coefficient of determination (R2), Nash-Sutcliffe efficiency (ENS) and root mean square error (RMSE) were used to evaluate the model performance. Calibrated SWAT setup has been used to evaluate the changes in water balance components of future projection over the study area. HadRM3, a regional climatic data, have been used as input of the hydrological model for climate change impact studies. In results, it was found that changes in average annual temperature (+3.25 °C), average annual rainfall (+28 %), evapotranspiration (28 %) and water yield (49 %) increased for GHG scenarios with respect to the base line scenario.

Quantifying PM2.5-Meteorology Sensitivities in a Global Climate Model

NASA Technical Reports Server (NTRS)

Westervelt, D. M.; Horowitz, L. W.; Naik, V.; Tai, A. P. K.; Fiore, A. M.; Mauzerall, D. L.

2016-01-01

Climate change can influence fine particulate matter concentrations (PM2.5) through changes in air pollution meteorology. Knowledge of the extent to which climate change can exacerbate or alleviate air pollution in the future is needed for robust climate and air pollution policy decision-making. To examine the influence of climate on PM2.5, we use the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 (GFDL CM3), a fully-coupled chemistry-climate model, combined with future emissions and concentrations provided by the four Representative Concentration Pathways (RCPs). For each of the RCPs, we conduct future simulations in which emissions of aerosols and their precursors are held at 2005 levels while other climate forcing agents evolve in time, such that only climate (and thus meteorology) can influence PM2.5 surface concentrations. We find a small increase in global, annual mean PM2.5 of about 0.21 micro-g/cu m3 (5%) for RCP8.5, a scenario with maximum warming. Changes in global mean PM2.5 are at a maximum in the fall and are mainly controlled by sulfate followed by organic aerosol with minimal influence of black carbon. RCP2.6 is the only scenario that projects a decrease in global PM2.5 with future climate changes, albeit only by -0.06 micro-g/cu m (1.5%) by the end of the 21st century. Regional and local changes in PM2.5 are larger, reaching upwards of 2 micro-g/cu m for polluted (eastern China) and dusty (western Africa) locations on an annually averaged basis in RCP8.5. Using multiple linear regression, we find that future PM2.5 concentrations are most sensitive to local temperature, followed by surface wind and precipitation. PM2.5 concentrations are robustly positively associated with temperature, while negatively related with precipitation and wind speed. Present-day (2006-2015) modeled sensitivities of PM2.5 to meteorological variables are evaluated against observations and found to agree reasonably well with observed sensitivities (within 10e50% over the eastern United States for several variables), although the modeled PM2.5 is less sensitive to precipitation than in the observations due to weaker convective scavenging. We conclude that the hypothesized "climate penalty" of future increases in PM2.5 is relatively minor on a global scale compared to the influence of emissions on PM2.5 concentrations.

A Water Grid for the UK

NASA Astrophysics Data System (ADS)

Leathard, A.; Fowler, H. J.; Kilsby, C. G.

2009-04-01

Anthropogenically aggravated climate change associated with intensive expansion of the global economy has increased the demand for water whilst simultaneously altering natural variability in its distribution, straining water resources unsustainably and inequitably in many parts of the world, increasing drought risk, and encouraging decision-makers to reconsider the security of water supply. Indeed, in the absence of additional resource development, contemporary planning forecasts imply increased water stress across much of the United Kingdom. The regulatory authorities of the UK currently promote increased efficiency of water delivery and consumption combined with a portfolio of financial instruments as a means of reducing water stress, maintaining present levels of consumer service without significant further exploitation of the environment. Despite an increasingly sophisticated understanding of climate change and its effects, significant uncertainty remains in the quantification of its impacts on the water sector, and questions persist as to the effectiveness of such demand management measures compared to that of more traditional infrastructure improvements. Faced with possible futures provided for by detrimentally over-stressed resources, what opportunities remain for future strategic development in the UK? Is there a single national strategy that is both politically and socially acceptable? This ongoing study aims to evolve robust national adaptation strategies by quantifying the projected impacts of climate change across mainland UK using multi-model and perturbed-physics ensembles of projected future climate, encapsulating uncertainties in a scenario-driven integrated water resources model incorporating socio-economic elements.

Climate change, estuaries and anadromous fish habitat in the northeastern United States: models, downscaling and uncertainty

NASA Astrophysics Data System (ADS)

Muhling, B.; Gaitan, C. F.; Tommasi, D.; Saba, V. S.; Stock, C. A.; Dixon, K. W.

2016-02-01

Estuaries of the northeastern United States provide essential habitat for many anadromous fishes, across a range of life stages. Climate change is likely to impact estuarine environments and habitats through multiple pathways. Increasing air temperatures will result in a warming water column, and potentially increased stratification. In addition, changes to precipitation patterns may alter freshwater inflow dynamics, leading to altered seasonal salinity regimes. However, the spatial resolution of global climate models is generally insufficient to resolve these processes at the scale of individual estuaries. Global models can be downscaled to a regional resolution using a variety of dynamical and statistical methods. In this study, we examined projections of estuarine conditions, and future habitat extent, for several anadromous fishes in the Chesapeake Bay using different statistical downscaling methods. Sources of error from physical and biological models were quantified, and key areas of uncertainty were highlighted. Results suggested that future projections of the distribution and recruitment of species most strongly linked to freshwater flow dynamics had the highest levels of uncertainty. The sensitivity of different life stages to environmental conditions, and the population-level responses of anadromous species to climate change, were identified as important areas for further research.

Climate change and the global malaria recession.

PubMed

Gething, Peter W; Smith, David L; Patil, Anand P; Tatem, Andrew J; Snow, Robert W; Hay, Simon I

2010-05-20

The current and potential future impact of climate change on malaria is of major public health interest. The proposed effects of rising global temperatures on the future spread and intensification of the disease, and on existing malaria morbidity and mortality rates, substantively influence global health policy. The contemporary spatial limits of Plasmodium falciparum malaria and its endemicity within this range, when compared with comparable historical maps, offer unique insights into the changing global epidemiology of malaria over the last century. It has long been known that the range of malaria has contracted through a century of economic development and disease control. Here, for the first time, we quantify this contraction and the global decreases in malaria endemicity since approximately 1900. We compare the magnitude of these changes to the size of effects on malaria endemicity proposed under future climate scenarios and associated with widely used public health interventions. Our findings have two key and often ignored implications with respect to climate change and malaria. First, widespread claims that rising mean temperatures have already led to increases in worldwide malaria morbidity and mortality are largely at odds with observed decreasing global trends in both its endemicity and geographic extent. Second, the proposed future effects of rising temperatures on endemicity are at least one order of magnitude smaller than changes observed since about 1900 and up to two orders of magnitude smaller than those that can be achieved by the effective scale-up of key control measures. Predictions of an intensification of malaria in a warmer world, based on extrapolated empirical relationships or biological mechanisms, must be set against a context of a century of warming that has seen marked global declines in the disease and a substantial weakening of the global correlation between malaria endemicity and climate.

Global wheat production potentials and management flexibility under the representative concentration pathways

NASA Astrophysics Data System (ADS)

Balkovič, Juraj; van der Velde, Marijn; Skalský, Rastislav; Xiong, Wei; Folberth, Christian; Khabarov, Nikolay; Smirnov, Alexey; Mueller, Nathaniel D.; Obersteiner, Michael

2014-11-01

Wheat is the third largest crop globally and an essential source of calories in human diets. Maintaining and increasing global wheat production is therefore strongly linked to food security. A large geographic variation in wheat yields across similar climates points to sizeable yield gaps in many nations, and indicates a regionally variable flexibility to increase wheat production. Wheat is particularly sensitive to a changing climate thus limiting management opportunities to enable (sustainable) intensification with potentially significant implications for future wheat production. We present a comprehensive global evaluation of future wheat yields and production under distinct Representative Concentration Pathways (RCPs) using the Environmental Policy Integrated Climate (EPIC) agro-ecosystem model. We project, in a geographically explicit manner, future wheat production pathways for rainfed and irrigated wheat systems. We explore agricultural management flexibility by quantifying the development of wheat yield potentials under current, rainfed, exploitable (given current irrigation infrastructure), and irrigated intensification levels. Globally, because of climate change, wheat production under conventional management (around the year 2000) would decrease across all RCPs by 37 to 52 and 54 to 103 Mt in the 2050s and 2090s, respectively. However, the exploitable and potential production gap will stay above 350 and 580 Mt, respectively, for all RCPs and time horizons, indicating that negative impacts of climate change can globally be offset by adequate intensification using currently existing irrigation infrastructure and nutrient additions. Future world wheat production on cropland already under cultivation can be increased by ~ 35% through intensified fertilization and ~ 50% through increased fertilization and extended irrigation, if sufficient water would be available. Significant potential can still be exploited, especially in rainfed wheat systems in Russia, Eastern Europe and North America.

Climate Change and Future Pollen Allergy in Europe.

PubMed

Lake, Iain R; Jones, Natalia R; Agnew, Maureen; Goodess, Clare M; Giorgi, Filippo; Hamaoui-Laguel, Lynda; Semenov, Mikhail A; Solomon, Fabien; Storkey, Jonathan; Vautard, Robert; Epstein, Michelle M

2017-03-01

Globally, pollen allergy is a major public health problem, but a fundamental unknown is the likely impact of climate change. To our knowledge, this is the first study to quantify the consequences of climate change upon pollen allergy in humans. We produced quantitative estimates of the potential impact of climate change upon pollen allergy in humans, focusing upon common ragweed ( Ambrosia artemisiifolia ) in Europe. A process-based model estimated the change in ragweed's range under climate change. A second model simulated current and future ragweed pollen levels. These findings were translated into health burdens using a dose-response curve generated from a systematic review and from current and future population data. Models considered two different suites of regional climate/pollen models, two greenhouse gas emissions scenarios [Representative Concentration Pathways (RCPs) 4.5 and 8.5], and three different plant invasion scenarios. Our primary estimates indicated that sensitization to ragweed will more than double in Europe, from 33 to 77 million people, by 2041-2060. According to our projections, sensitization will increase in countries with an existing ragweed problem (e.g., Hungary, the Balkans), but the greatest proportional increases will occur where sensitization is uncommon (e.g., Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also increase the severity of symptoms. Our model projections were driven predominantly by changes in climate (66%) but were also influenced by current trends in the spread of this invasive plant species. Assumptions about the rate at which ragweed spreads throughout Europe had a large influence upon the results. Our quantitative estimates indicate that ragweed pollen allergy will become a common health problem across Europe, expanding into areas where it is currently uncommon. Control of ragweed spread may be an important adaptation strategy in response to climate change. Citation: Lake IR, Jones NR, Agnew M, Goodess CM, Giorgi F, Hamaoui-Laguel L, Semenov MA, Solomon F, Storkey J, Vautard R, Epstein MM. 2017. Climate change and future pollen allergy in Europe. Environ Health Perspect 125:385-391; http://dx.doi.org/10.1289/EHP173.

Accounting for Global Climate Model Projection Uncertainty in Modern Statistical Downscaling

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

Johannesson, G

2010-03-17

Future climate change has emerged as a national and a global security threat. To carry out the needed adaptation and mitigation steps, a quantification of the expected level of climate change is needed, both at the global and the regional scale; in the end, the impact of climate change is felt at the local/regional level. An important part of such climate change assessment is uncertainty quantification. Decision and policy makers are not only interested in 'best guesses' of expected climate change, but rather probabilistic quantification (e.g., Rougier, 2007). For example, consider the following question: What is the probability that themore » average summer temperature will increase by at least 4 C in region R if global CO{sub 2} emission increases by P% from current levels by time T? It is a simple question, but one that remains very difficult to answer. It is answering these kind of questions that is the focus of this effort. The uncertainty associated with future climate change can be attributed to three major factors: (1) Uncertainty about future emission of green house gasses (GHG). (2) Given a future GHG emission scenario, what is its impact on the global climate? (3) Given a particular evolution of the global climate, what does it mean for a particular location/region? In what follows, we assume a particular GHG emission scenario has been selected. Given the GHG emission scenario, the current batch of the state-of-the-art global climate models (GCMs) is used to simulate future climate under this scenario, yielding an ensemble of future climate projections (which reflect, to some degree our uncertainty of being able to simulate future climate give a particular GHG scenario). Due to the coarse-resolution nature of the GCM projections, they need to be spatially downscaled for regional impact assessments. To downscale a given GCM projection, two methods have emerged: dynamical downscaling and statistical (empirical) downscaling (SDS). Dynamic downscaling involves configuring and running a regional climate model (RCM) nested within a given GCM projection (i.e., the GCM provides bounder conditions for the RCM). On the other hand, statistical downscaling aims at establishing a statistical relationship between observed local/regional climate variables of interest and synoptic (GCM-scale) climate predictors. The resulting empirical relationship is then applied to future GCM projections. A comparison of the pros and cons of dynamical versus statistical downscaling is outside the scope of this effort, but has been extensively studied and the reader is referred to Wilby et al. (1998); Murphy (1999); Wood et al. (2004); Benestad et al. (2007); Fowler et al. (2007), and references within those. The scope of this effort is to study methodology, a statistical framework, to propagate and account for GCM uncertainty in regional statistical downscaling assessment. In particular, we will explore how to leverage an ensemble of GCM projections to quantify the impact of the GCM uncertainty in such an assessment. There are three main component to this effort: (1) gather the necessary climate-related data for a regional SDS study, including multiple GCM projections, (2) carry out SDS, and (3) assess the uncertainty. The first step is carried out using tools written in the Python programming language, while analysis tools were developed in the statistical programming language R; see Figure 1.« less

Impact of Climate Change on Energy Demand in the Midwestern USA

NASA Astrophysics Data System (ADS)

Yan, M. B.; Zhang, F.; Franklin, M.; Kotamarthi, V. R.

2008-12-01

The impact of climate change on energy demand and use is a significant issue for developing future GHG emission scenarios and developing adaptation and mitigation strategies. A number of studies have evaluated the increase in GHG emissions as a result of changes in energy production from fossil fuels, but the consequences of climate change on energy consumption have not been the focus of many studies. Here we focus on the impacts of climate change on energy use at a regional scale using the Midwestern USA as a test. The paper presents results of analyzing energy use in response to ambient temperature changes in a 17-year period from 1989 to 2006 and projection of energy use under future climate scenarios (2010-2061). This study consisted of a two-step procedure. In the first step, sensitivity of historic energy demand, specifically electricity and natural gas in residential and commercial sectors (42% of end-use energy), with respect to many climatic and non-climatic variables was examined. State-specific regression models were developed to quantify the relationship between energy use and climatic variables using degree days. We found that model parameters and base temperatures for estimating heating and cooling days varied by state and energy sector, mainly depending on climate conditions, infrastructure, economic factors, and seasonal change in energy use. In the second step, we applied these models to predict future energy demand using output data generated by the Community Climate System Model (CCSM) for the SRES A1B scenario used in the IPCC AR-4. The annual demands of electricity and natural gas were predicted for each state from 2010 to 2061. The model results indicate that the average annual electricity demand will increase 3%-5% for the southern states and 1%-3% for the northern states in the region by 2061 and that the demand for natural gas is expected to be reduced in all states. A seasonal analysis of energy distribution in response to climate variables identifies a significant peak in demand in July-August (11%-16% in southern states and 6%-10% in the northern states). These findings suggest that the energy sector is vulnerable to climate change even in the northern Midwest region of the US. Furthermore, we demonstrate that a state-level assessment can help to better identify adaptation strategies for future regional energy sector changes.

Changes of the potential distribution area of French Mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-11-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growth with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20th and 21st centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5 K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak respectively) at the end of the 21st century. While both species have different growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21st century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

Understanding the drivers of the future water gap in the Indus-Ganges-Brahmaputra basins

NASA Astrophysics Data System (ADS)

Immerzeel, W. W.; Wijngaard, R. R.; Biemans, H.; Lutz, A. F.

2017-12-01

The Indus, Ganges, and Brahmaputra (IGB) river systems provide water resources for the agricultural, domestic and industrial sectors sustaining the lives of about 700 million people. The region is globally a hotspot for climate change as the headwaters of these rivers are fed by melt water from snow and glaciers, both strongly influenced by temperature change. In addition, the hydrology in the region is determined by the monsoon and its future dynamics as a results of climate change remains very uncertain. Simultaneously, the population is projected to grow rapidly over the coming decades, which in combination with strong economic developments, will likely result in a rapid increase in water demand. In this study we attempt to quantify the future water gap in the IGB and attribute this water gap to climate change and socio-economic growth. For the upstream mountainous parts of the basins we use the SPHY model, which is calibrated based on historical streamflow and glacier mass balance data and forced by the latest CMIP5 future climate model data for RCP4.5 and 8.5. Output of this model feeds into the downstream LPJmL model, which allows assessment of downstream climate change impacts and projected changes in water demand as a result of socio-economic developments. The LPJmL model is run for different combinations of RCPs and Shared Socio Economic Pathways (SSPs). Our results show that for the IGB as a whole climate change will increase water availability in the coming decades, due to an overall, albeit uncertain, increase in monsoon precipitation in combination with a sustained melt water supply from the upstream parts of the basins. However, irrespective of the SSP and RCP, the water demand as a result of socio-economic growth is expected to increase extremely fast in the near future and this is likely to be the main adaptation challenge for the IGB as far as water shortages are concerned. Our results also show that regional and temporal variation in the water gap is large and that basin specific adaptation measures are required that take into account both socio-economic developments as well as climate change.

Can metric-based approaches really improve multi-model climate projections? A perfect model framework applied to summer temperature change in France.

NASA Astrophysics Data System (ADS)

Boé, Julien; Terray, Laurent

2014-05-01

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

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, N.; Fowler, H. J.; Blenkinsop, S.; Burton, A.; Kilsby, C. G.; Archer, D. R.; Harpham, C.; Hashmi, M. Z.

2014-09-01

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961-1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961-1990) and future (2071-2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region.

Urban-Climate Adaptation Tool: Optimizing Green Infrastructure

NASA Astrophysics Data System (ADS)

Fellows, J. D.; Bhaduri, B. L.

2016-12-01

Cities have an opportunity to become more resilient to future climate change and green through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection and other environmental information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). The initial focus of Urban-CAT is to optimize the placement of green infrastructure (e.g., green roofs, porous pavements, retention basins, etc.) to be better control stormwater runoff and lower the ambient urban temperature. Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic and other environmental data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. This presentation will highlight the methods that drive each of the modules, demo some of the capabilities using Knoxville Tennessee as a case study, and discuss the challenges of working with communities to incorporate climate change into their planning. Next steps on Urban-CAT is to additional capabilities to create a comprehensive climate adaptation tool, including energy, transportation, health, and other key urban services.

Co-benefits of air quality and climate change policies on air quality of the Mediterranean

NASA Astrophysics Data System (ADS)

Pozzoli, Luca; Mert Gokturk, Ozan; Unal, Alper; Kindap, Tayfun; Janssens-Maenhout, Greet

2015-04-01

The Mediterranean basin is one of the regions of the world where significant impacts due to climate changes are predicted to occur in the future. Observations and model simulations are used to provide to the policy makers scientifically based estimates of the necessity to adjust national emission reductions needed to achieve air quality objectives in the context of a changing climate, which is not only driven by GHGs, but also by short lived climate pollutants, such as tropospheric ozone and aerosols. There is an increasing interest and need to design cost-benefit emission reduction strategies, which could improve both regional air quality and global climate change. In this study we used the WRF-CMAQ air quality modelling system to quantify the contribution of anthropogenic emissions to ozone and particulate matter concentrations in Europe and the Eastern Mediterranean and to understand how this contribution could change in different future scenarios. We have investigated four different future scenarios for year 2050 defined during the European Project CIRCE: a "business as usual" scenario (BAU) where no or just actual measures are taken into account; an "air quality" scenario (BAP) which implements the National Emission Ceiling directive 2001/81/EC member states of the European Union (EU-27); a "climate change" scenario (CC) which implements global climate policies decoupled from air pollution policies; and an "integrated air quality and climate policy" scenario (CAP) which explores the co-benefit of global climate and EU-27 air pollution policies. The BAP scenario largely decreases summer ozone concentrations over almost the entire continent, while the CC and CAP scenarios similarly determine lower decreases in summer ozone but extending all over the Mediterranean, the Middle East countries and Russia. Similar patterns are found for winter PM concentrations; BAP scenario improves pollution levels only in the Western EU countries, and the CAP scenario determines the largest PM reductions over the entire continent and the Mediterranean basin.

Impacts of sea level rise and climate change on coastal plant species in the central California coast

PubMed Central

Chang, Michelle Y.; Fulda, Matthew T.; Berlin, Jonathan A.; Freed, Rachel E.; Soo-Hoo, Melissa M.; Revell, Dave L.; Ikegami, Makihiko; Flint, Lorraine E.; Flint, Alan L.; Kendall, Bruce E.

2015-01-01

Local increases in sea level caused by global climate change pose a significant threat to the persistence of many coastal plant species through exacerbating inundation, flooding, and erosion. In addition to sea level rise (SLR), climate changes in the form of air temperature and precipitation regimes will also alter habitats of coastal plant species. Although numerous studies have analyzed the effect of climate change on future habitats through species distribution models (SDMs), none have incorporated the threat of exposure to SLR. We developed a model that quantified the effect of both SLR and climate change on habitat for 88 rare coastal plant species in San Luis Obispo, Santa Barbara, and Ventura Counties, California, USA (an area of 23,948 km2). Our SLR model projects that by the year 2100, 60 of the 88 species will be threatened by SLR. We found that the probability of being threatened by SLR strongly correlates with a species’ area, elevation, and distance from the coast, and that 10 species could lose their entire current habitat in the study region. We modeled the habitat suitability of these 10 species under future climate using a species distribution model (SDM). Our SDM projects that 4 of the 10 species will lose all suitable current habitats in the region as a result of climate change. While SLR accounts for up to 9.2 km2 loss in habitat, climate change accounts for habitat suitability changes ranging from a loss of 1,439 km2 for one species to a gain of 9,795 km2 for another species. For three species, SLR is projected to reduce future suitable area by as much as 28% of total area. This suggests that while SLR poses a higher risk, climate changes in precipitation and air temperature represents a lesser known but potentially larger risk and a small cumulative effect from both. PMID:26020011

A framework for evaluating statistical downscaling performance under changing climatic conditions (Invited)

NASA Astrophysics Data System (ADS)

Dixon, K. W.; Balaji, V.; Lanzante, J.; Radhakrishnan, A.; Hayhoe, K.; Stoner, A. K.; Gaitan, C. F.

2013-12-01

Statistical downscaling (SD) methods may be viewed as generating a value-added product - a refinement of global climate model (GCM) output designed to add finer scale detail and to address GCM shortcomings via a process that gleans information from a combination of observations and GCM-simulated climate change responses. Making use of observational data sets and GCM simulations representing the same historical period, cross-validation techniques allow one to assess how well an SD method meets this goal. However, lacking observations of future, the extent to which a particular SD method's skill might degrade when applied to future climate projections cannot be assessed in the same manner. Here we illustrate and describe extensions to a 'perfect model' experimental design that seeks to quantify aspects of SD method performance both for a historical period (1979-2008) and for late 21st century climate projections. Examples highlighting cases in which downscaling performance deteriorates in future climate projections will be discussed. Also, results will be presented showing how synthetic datasets having known statistical properties may be used to further isolate factors responsible for degradations in SD method skill under changing climatic conditions. We will describe a set of input files used to conduct these analyses that are being made available to researchers who wish to utilize this experimental framework to evaluate SD methods they have developed. The gridded data sets cover a region centered on the contiguous 48 United States with a grid spacing of approximately 25km, have daily time resolution (e.g., maximum and minimum near-surface temperature and precipitation), and represent a total of 120 years of model simulations. This effort is consistent with the 2013 National Climate Predictions and Projections Platform Quantitative Evaluation of Downscaling Workshop goal of supporting a community approach to promote the informed use of downscaled climate projections.

Impacts of sea level rise and climate change on coastal plant species in the central California coast.

PubMed

Garner, Kendra L; Chang, Michelle Y; Fulda, Matthew T; Berlin, Jonathan A; Freed, Rachel E; Soo-Hoo, Melissa M; Revell, Dave L; Ikegami, Makihiko; Flint, Lorraine E; Flint, Alan L; Kendall, Bruce E

2015-01-01

Local increases in sea level caused by global climate change pose a significant threat to the persistence of many coastal plant species through exacerbating inundation, flooding, and erosion. In addition to sea level rise (SLR), climate changes in the form of air temperature and precipitation regimes will also alter habitats of coastal plant species. Although numerous studies have analyzed the effect of climate change on future habitats through species distribution models (SDMs), none have incorporated the threat of exposure to SLR. We developed a model that quantified the effect of both SLR and climate change on habitat for 88 rare coastal plant species in San Luis Obispo, Santa Barbara, and Ventura Counties, California, USA (an area of 23,948 km(2)). Our SLR model projects that by the year 2100, 60 of the 88 species will be threatened by SLR. We found that the probability of being threatened by SLR strongly correlates with a species' area, elevation, and distance from the coast, and that 10 species could lose their entire current habitat in the study region. We modeled the habitat suitability of these 10 species under future climate using a species distribution model (SDM). Our SDM projects that 4 of the 10 species will lose all suitable current habitats in the region as a result of climate change. While SLR accounts for up to 9.2 km(2) loss in habitat, climate change accounts for habitat suitability changes ranging from a loss of 1,439 km(2) for one species to a gain of 9,795 km(2) for another species. For three species, SLR is projected to reduce future suitable area by as much as 28% of total area. This suggests that while SLR poses a higher risk, climate changes in precipitation and air temperature represents a lesser known but potentially larger risk and a small cumulative effect from both.

Interdependency in Multimodel Climate Projections: Component Replication and Result Similarity

NASA Astrophysics Data System (ADS)

Boé, Julien

2018-03-01

Multimodel ensembles are the main way to deal with model uncertainties in climate projections. However, the interdependencies between models that often share entire components make it difficult to combine their results in a satisfactory way. In this study, how the replication of components (atmosphere, ocean, land, and sea ice) between climate models impacts the proximity of their results is quantified precisely, in terms of climatological means and future changes. A clear relationship exists between the number of components shared by climate models and the proximity of their results. Even the impact of a single shared component is generally visible. These conclusions are true at both the global and regional scales. Given available data, it cannot be robustly concluded that some components are more important than others. Those results provide ways to estimate model interdependencies a priori rather than a posteriori based on their results, in order to define independence weights.

An Investigation of Bomb Cyclone Climatology: Reanalysis vs. NCEP's CFS Model

NASA Astrophysics Data System (ADS)

Alvarez, F. M.; Eichler, T.; Gottschalck, J.

2009-12-01

Given the concerns and potential impacts of climate change, the need for climate models to simulate weather phenomena is as important as ever. An example of such phenomena is rapidly intensifying cyclones, also known as "bombs." These intense cyclones have devastating effects on residential and marine commercial interests as well as the transportation industry. In this study, we generate a climatology of rapid cyclogenesis using the National Centers for Environmental Prediction’s (NCEP) Climate Forecast System (CFS) model. Results are compared to NCEP’s global reanalysis data to determine if the CFS model is capable of producing a realistic extreme storm climatology. This represents the first step in quantifying rapidly intensifying cyclones in the CFS model, which will be useful in contributing towards future model improvements, as well as gauging its ability in determining the role of synoptic-scale storms in climate change.

14CO2 in combination with root-exclusion can be used to estimate plant-induced decomposition of soil organic matter

NASA Astrophysics Data System (ADS)

Heinonsalo, Jussi; Kulmala, Liisa; Mäkelä, Annikki; Oinonen, Markku; Fontaine, Sebastien; Palonen, Vesa; Pumpanen, Jukka

2017-04-01

In ecosystem models, the decomposition of soil organic matter (SOM) is estimated using temperature and moisture as main controlling parameters. However, there is increasing evidence that the decomposition is significantly affected by easily available carbohydrates. The C assimilation by the boreal forest trees will increase in the future due to climate change. As trees allocate large part of assimilated C to roots and soil microorganisms, particularly to ectomycorrhizal fungi, the rhizosphere priming effect (RPE) is assumed to increase. The aim of the experiment was to identify and quantify RPE in the field conditions. We established a three-year long trenching experiment in a boreal Scots pine forest where the belowground C flow from standing pine forest was controlled using root-exclusion with mesh fabrics. The mesh size of 1 μm excluded both tree roots and fungal hyphae and served as priming controls with decreased C supply. The unaltered C input entered the non-trenched field plots. Soil CO2 flux and 14C concentrations were measured. We were able to quantify the RPE in field conditions and show that plant-derived C flow into the soil increases SOM decomposition. Quantification of RPE allows more detailed estimation of soil organic matter decomposition in future changing climate.

Interactive effects of environmental change and management strategies on regional forest carbon emissions.

PubMed

Hudiburg, Tara W; Luyssaert, Sebastiaan; Thornton, Peter E; Law, Beverly E

2013-11-19

Climate mitigation activities in forests need to be quantified in terms of the long-term effects on forest carbon stocks, accumulation, and emissions. The impacts of future environmental change and bioenergy harvests on regional forest carbon storage have not been quantified. We conducted a comprehensive modeling study and life-cycle assessment of the impacts of projected changes in climate, CO2 concentration, and N deposition, and region-wide forest management policies on regional forest carbon fluxes. By 2100, if current management strategies continue, then the warming and CO2 fertilization effect in the given projections result in a 32-68% increase in net carbon uptake, overshadowing increased carbon emissions from projected increases in fire activity and other forest disturbance factors. To test the response to new harvesting strategies, repeated thinnings were applied in areas susceptible to fire to reduce mortality, and two clear-cut rotations were applied in productive forests to provide biomass for wood products and bioenergy. The management strategies examined here lead to long-term increased carbon emissions over current harvesting practices, although semiarid regions contribute little to the increase. The harvest rates were unsustainable. This comprehensive approach could serve as a foundation for regional place-based assessments of management effects on future carbon sequestration by forests in other locations.

Review: Regional groundwater flow modeling in heavily irrigated basins of selected states in the western United States

NASA Astrophysics Data System (ADS)

Rossman, Nathan R.; Zlotnik, Vitaly A.

2013-09-01

Water resources in agriculture-dominated basins of the arid western United States are stressed due to long-term impacts from pumping. A review of 88 regional groundwater-flow modeling applications from seven intensively irrigated western states (Arizona, California, Colorado, Idaho, Kansas, Nebraska and Texas) was conducted to provide hydrogeologists, modelers, water managers, and decision makers insight about past modeling studies that will aid future model development. Groundwater models were classified into three types: resource evaluation models (39 %), which quantify water budgets and act as preliminary models intended to be updated later, or constitute re-calibrations of older models; management/planning models (55 %), used to explore and identify management plans based on the response of the groundwater system to water-development or climate scenarios, sometimes under water-use constraints; and water rights models (7 %), used to make water administration decisions based on model output and to quantify water shortages incurred by water users or climate changes. Results for 27 model characteristics are summarized by state and model type, and important comparisons and contrasts are highlighted. Consideration of modeling uncertainty and the management focus toward sustainability, adaptive management and resilience are discussed, and future modeling recommendations, in light of the reviewed models and other published works, are presented.

Sources of global climate data and visualization portals

USGS Publications Warehouse

Douglas, David C.

2014-01-01

Climate is integral to the geophysical foundation upon which ecosystems are structured. Knowledge about mechanistic linkages between the geophysical and biological environments is essential for understanding how global warming may reshape contemporary ecosystems and ecosystem services. Numerous global data sources spanning several decades are available that document key geophysical metrics such as temperature and precipitation, and metrics of primary biological production such as vegetation phenology and ocean phytoplankton. This paper provides an internet directory to portals for visualizing or servers for downloading many of the more commonly used global datasets, as well as a description of how to write simple computer code to efficiently retrieve these data. The data are broadly useful for quantifying relationships between climate, habitat availability, and lower-trophic-level habitat quality - especially in Arctic regions where strong seasonality is accompanied by intrinsically high year-to-year variability. If defensible linkages between the geophysical (climate) and the biological environment can be established, general circulation model (GCM) projections of future climate conditions can be used to infer future biological responses. Robustness of this approach is, however, complicated by the number of direct, indirect, or interacting linkages involved. For example, response of a predator species to climate change will be influenced by the responses of its prey and competitors, and so forth throughout a trophic web. The complexities of ecological systems warrant sensible and parsimonious approaches for assessing and establishing the role of natural climate variability in order to substantiate inferences about the potential effects of global warming.

Alpine bird distributions along elevation gradients: the consistency of climate and habitat effects across geographic regions.

PubMed

Chamberlain, Dan; Brambilla, Mattia; Caprio, Enrico; Pedrini, Paolo; Rolando, Antonio

2016-08-01

Many species have shown recent shifts in their distributions in response to climate change. Patterns in species occurrence or abundance along altitudinal gradients often serve as the basis for detecting such changes and assessing future sensitivity. Quantifying the distribution of species along altitudinal gradients acts as a fundamental basis for future studies on environmental change impacts, but in order for models of altitudinal distribution to have wide applicability, it is necessary to know the extent to which altitudinal trends in occurrence are consistent across geographically separated areas. This was assessed by fitting models of bird species occurrence across altitudinal gradients in relation to habitat and climate variables in two geographically separated alpine regions, Piedmont and Trentino. The ten species studied showed non-random altitudinal distributions which in most cases were consistent across regions in terms of pattern. Trends in relation to altitude and differences between regions could be explained mostly by habitat or a combination of habitat and climate variables. Variation partitioning showed that most variation explained by the models was attributable to habitat, or habitat and climate together, rather than climate alone or geographic region. The shape and position of the altitudinal distribution curve is important as it can be related to vulnerability where the available space is limited, i.e. where mountains are not of sufficient altitude for expansion. This study therefore suggests that incorporating habitat and climate variables should be sufficient to construct models with high transferability for many alpine species.

Planning protected areas network that are relevant today and under future climate change is possible: the case of Atlantic Forest endemic birds.

PubMed

Vale, Mariana M; Souza, Thiago V; Alves, Maria Alice S; Crouzeilles, Renato

2018-01-01

A key strategy in biodiversity conservation is the establishment of protected areas. In the future, however, the redistribution of species in response to ongoing climate change is likely to affect species' representativeness in those areas. Here we quantify the effectiveness of planning protected areas network to represent 151 birds endemic to the Brazilian Atlantic Forest hotspot, under current and future climate change conditions for 2050. We combined environmental niche modeling and systematic conservation planning using both a county and a regional level planning strategy. We recognized the conflict between biodiversity conservation and economic development, including socio-economic targets (as opposed to biological only) and using planning units that are meaningful for policy-makers. We estimated an average contraction of 29,500 km 2 in environmentally suitable areas for birds, representing 52% of currently suitable areas. Still, the most cost-effective solution represented almost all target species, requiring only ca. 10% of the Atlantic Forest counties to achieve that representativeness, independent of strategy. More than 50% of these counties were selected both in the current and future planned networks, representing >83% of the species. Our results indicate that: (i) planning protected areas network currently can be useful to represent species under climate change; (ii) the overlapped planning units in the best solution for both current and future conditions can be considered as "no regret" areas; (iii) priority counties are spread throughout the biome, providing specific guidance wherever the possibility of creating protected area arises; and (iv) decisions can occur at different administrative spheres (Federal, State or County) as we found quite similar numerical solutions using either county or regional level strategies.

Planning protected areas network that are relevant today and under future climate change is possible: the case of Atlantic Forest endemic birds

PubMed Central

Souza, Thiago V.; Alves, Maria Alice S.; Crouzeilles, Renato

2018-01-01

Background A key strategy in biodiversity conservation is the establishment of protected areas. In the future, however, the redistribution of species in response to ongoing climate change is likely to affect species’ representativeness in those areas. Here we quantify the effectiveness of planning protected areas network to represent 151 birds endemic to the Brazilian Atlantic Forest hotspot, under current and future climate change conditions for 2050. Methods We combined environmental niche modeling and systematic conservation planning using both a county and a regional level planning strategy. We recognized the conflict between biodiversity conservation and economic development, including socio-economic targets (as opposed to biological only) and using planning units that are meaningful for policy-makers. Results We estimated an average contraction of 29,500 km2 in environmentally suitable areas for birds, representing 52% of currently suitable areas. Still, the most cost-effective solution represented almost all target species, requiring only ca. 10% of the Atlantic Forest counties to achieve that representativeness, independent of strategy. More than 50% of these counties were selected both in the current and future planned networks, representing >83% of the species. Discussion Our results indicate that: (i) planning protected areas network currently can be useful to represent species under climate change; (ii) the overlapped planning units in the best solution for both current and future conditions can be considered as “no regret” areas; (iii) priority counties are spread throughout the biome, providing specific guidance wherever the possibility of creating protected area arises; and (iv) decisions can occur at different administrative spheres (Federal, State or County) as we found quite similar numerical solutions using either county or regional level strategies. PMID:29844952

Attribution of climate forcing to economic sectors.

PubMed

Unger, Nadine; Bond, Tami C; Wang, James S; Koch, Dorothy M; Menon, Surabi; Shindell, Drew T; Bauer, Susanne

2010-02-23

A much-cited bar chart provided by the Intergovernmental Panel on Climate Change displays the climate impact, as expressed by radiative forcing in watts per meter squared, of individual chemical species. The organization of the chart reflects the history of atmospheric chemistry, in which investigators typically focused on a single species of interest. However, changes in pollutant emissions and concentrations are a symptom, not a cause, of the primary driver of anthropogenic climate change: human activity. In this paper, we suggest organizing the bar chart according to drivers of change-that is, by economic sector. Climate impacts of tropospheric ozone, fine aerosols, aerosol-cloud interactions, methane, and long-lived greenhouse gases are considered. We quantify the future evolution of the total radiative forcing due to perpetual constant year 2000 emissions by sector, most relevant for the development of climate policy now, and focus on two specific time points, near-term at 2020 and long-term at 2100. Because sector profiles differ greatly, this approach fosters the development of smart climate policy and is useful to identify effective opportunities for rapid mitigation of anthropogenic radiative forcing.

Attribution of climate forcing to economic sectors

PubMed Central

Unger, Nadine; Bond, Tami C.; Wang, James S.; Koch, Dorothy M.; Menon, Surabi; Shindell, Drew T.; Bauer, Susanne

2010-01-01

A much-cited bar chart provided by the Intergovernmental Panel on Climate Change displays the climate impact, as expressed by radiative forcing in watts per meter squared, of individual chemical species. The organization of the chart reflects the history of atmospheric chemistry, in which investigators typically focused on a single species of interest. However, changes in pollutant emissions and concentrations are a symptom, not a cause, of the primary driver of anthropogenic climate change: human activity. In this paper, we suggest organizing the bar chart according to drivers of change—that is, by economic sector. Climate impacts of tropospheric ozone, fine aerosols, aerosol-cloud interactions, methane, and long-lived greenhouse gases are considered. We quantify the future evolution of the total radiative forcing due to perpetual constant year 2000 emissions by sector, most relevant for the development of climate policy now, and focus on two specific time points, near-term at 2020 and long-term at 2100. Because sector profiles differ greatly, this approach fosters the development of smart climate policy and is useful to identify effective opportunities for rapid mitigation of anthropogenic radiative forcing. PMID:20133724

Projecting Poverty at the Household Scale to Assess the Impact of Climate Change on Poor People

NASA Astrophysics Data System (ADS)

Hallegatte, S.; Rozenberg, J.

2015-12-01

This paper quantifies the potential impacts of climate change on poverty in 2030 and 2050, in 92 countries covering 90% of the developing world population. It accounts for the deep uncertainties that characterize future socio-economic evolutions and the lack of data regarding the condition and livelihood of poor people. It also considers many impacts of climate change, another source of uncertainty. We use a micro-simulation model based on household surveys and explore a wide range of uncertainties on future structural change, productivity growth or demographic changes. This results, for each country, in the creation of several hundred scenarios for future income growth and income distribution. We then explore the resulting space of possible futures and use scenario discovery techniques to identify the main drivers of inequalities and poverty reduction. We find that redistribution and structural change are powerful drivers of poverty and inequality reduction, except in low-income countries. In the poorest countries in Africa, reducing poverty cannot rely on redistribution but requires low population growth and productivity growth in agriculture. Once we have explored the space of possible outcomes for poverty and inequalities, we choose two representative scenarios of the best and worst cases and model the impacts of climate change in each of these two scenarios. Climate change impacts are modeled through 4 channels. First, climate change has an impact on labor productivity growth for people who work outside because of higher temperatures. Second, climate change has an impact on human capital because of more severe stunting in some places. Third, climate change has an impact on physical capital via more frequent natural disasters. Fourth, climate change has an impact on consumption because of changes in food prices. Impacts are very heterogeneous across countries and are mostly concentrated in African and South-East Asian countries. For high radiative forcing (RCP8.5), the impact of climate change on poverty is 6 times larger in the pessimistic scenario than in the optimistic scenario, illustrating how development and poverty reduction are powerful adaptation tools. Our results stress the urgency of achieving poverty eradication by 2030 in order to limit the negative impacts of climate change on the poor.

Event coincidence analysis for quantifying statistical interrelationships between event time series. On the role of flood events as triggers of epidemic outbreaks

NASA Astrophysics Data System (ADS)

Donges, J. F.; Schleussner, C.-F.; Siegmund, J. F.; Donner, R. V.

2016-05-01

Studying event time series is a powerful approach for analyzing the dynamics of complex dynamical systems in many fields of science. In this paper, we describe the method of event coincidence analysis to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. Event coincidence analysis allows to formulate and test null hypotheses on the origin of the observed interrelationships including tests based on Poisson processes or, more generally, stochastic point processes with a prescribed inter-event time distribution and other higher-order properties. Applying the framework to country-level observational data yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Facing projected future changes in the statistics of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide.

Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Crop productivity changes in 1.5 °C and 2 °C worlds under climate sensitivity uncertainty

NASA Astrophysics Data System (ADS)

Schleussner, Carl-Friedrich; Deryng, Delphine; Müller, Christoph; Elliott, Joshua; Saeed, Fahad; Folberth, Christian; Liu, Wenfeng; Wang, Xuhui; Pugh, Thomas A. M.; Thiery, Wim; Seneviratne, Sonia I.; Rogelj, Joeri

2018-06-01

Following the adoption of the Paris Agreement, there has been an increasing interest in quantifying impacts at discrete levels of global mean temperature (GMT) increase such as 1.5 °C and 2 °C above pre-industrial levels. Consequences of anthropogenic greenhouse gas emissions on agricultural productivity have direct and immediate relevance for human societies. Future crop yields will be affected by anthropogenic climate change as well as direct effects of emissions such as CO2 fertilization. At the same time, the climate sensitivity to future emissions is uncertain. Here we investigate the sensitivity of future crop yield projections with a set of global gridded crop models for four major staple crops at 1.5 °C and 2 °C warming above pre-industrial levels, as well as at different CO2 levels determined by similar probabilities to lead to 1.5 °C and 2 °C, using climate forcing data from the Half a degree Additional warming, Prognosis and Projected Impacts project. For the same CO2 forcing, we find consistent negative effects of half a degree warming on productivity in most world regions. Increasing CO2 concentrations consistent with these warming levels have potentially stronger but highly uncertain effects than 0.5 °C warming increments. Half a degree warming will also lead to more extreme low yields, in particular over tropical regions. Our results indicate that GMT change alone is insufficient to determine future impacts on crop productivity.

Urban adaptation can roll back warming of emerging megapolitan regions

PubMed Central

Georgescu, Matei; Morefield, Philip E.; Bierwagen, Britta G.; Weaver, Christopher P.

2014-01-01

Modeling results incorporating several distinct urban expansion futures for the United States in 2100 show that, in the absence of any adaptive urban design, megapolitan expansion, alone and separate from greenhouse gas-induced forcing, can be expected to raise near-surface temperatures 1–2 °C not just at the scale of individual cities but over large regional swaths of the country. This warming is a significant fraction of the 21st century greenhouse gas-induced climate change simulated by global climate models. Using a suite of regional climate simulations, we assessed the efficacy of commonly proposed urban adaptation strategies, such as green, cool roof, and hybrid approaches, to ameliorate the warming. Our results quantify how judicious choices in urban planning and design cannot only counteract the climatological impacts of the urban expansion itself but also, can, in fact, even offset a significant percentage of future greenhouse warming over large scales. Our results also reveal tradeoffs among different adaptation options for some regions, showing the need for geographically appropriate strategies rather than one size fits all solutions. PMID:24516126

Limited influence of climate change mitigation on short-term glacier mass loss

NASA Astrophysics Data System (ADS)

Marzeion, Ben; Kaser, Georg; Maussion, Fabien; Champollion, Nicolas

2018-04-01

Glacier mass loss is a key contributor to sea-level change1,2, slope instability in high-mountain regions3,4 and the changing seasonality and volume of river flow5-7. Understanding the causes, mechanisms and time scales of glacier change is therefore paramount to identifying successful strategies for mitigation and adaptation. Here, we use temperature and precipitation fields from the Coupled Model Intercomparison Project Phase 5 output to force a glacier evolution model, quantifying mass responses to future climatic change. We find that contemporary glacier mass is in disequilibrium with the current climate, and 36 ± 8% mass loss is already committed in response to past greenhouse gas emissions. Consequently, mitigating future emissions will have only very limited influence on glacier mass change in the twenty-first century. No significant differences between 1.5 and 2 K warming scenarios are detectable in the sea-level contribution of glaciers accumulated within the twenty-first century. In the long-term, however, mitigation will exert strong control, suggesting that ambitious measures are necessary for the long-term preservation of glaciers.

Quantifying present and future glacier melt-water contribution to runoff in a Central Himalayan river basin

NASA Astrophysics Data System (ADS)

Prasch, M.; Mauser, W.; Weber, M.

2012-10-01

Water supply of most lowland cultures heavily depends on rain and melt-water from the upstream mountains. Especially melt-water release of alpine mountain ranges is usually attributed a pivotal role for the water supply of large downstream regions. Water scarcity is assumed as consequence of glacier shrinkage and possible disappearance due to Global Climate Change, particular for large parts of Central and South East Asia. In this paper, the application and validation of a coupled modeling approach with Regional Climate Model outputs and a process-oriented glacier and hydrological model is presented for a Central Himalayan river basin despite scarce data availability. Current and possible future contributions of ice-melt to runoff along the river network are spatially explicitly shown. Its role among the other water balance components is presented. Although glaciers have retreated and will continue to retreat according to the chosen climate scenarios, water availability is and will be primarily determined by monsoon precipitation and snow-melt. Ice-melt from glaciers is and will be a minor runoff component in summer monsoon-dominated Himalayan river basins.

Regional vegetation die-off in response to global-change-type drought

USGS Publications Warehouse

Breshears, D.D.; Cobb, N.S.; Rich, P.M.; Price, K.P.; Allen, Craig D.; Balice, R.G.; Romme, W.H.; Kastens, J.H.; Floyd, M. Lisa; Belnap, J.; Anderson, J.J.; Myers, O.B.; Meyer, Clifton W.

2005-01-01

Future drought is projected to occur under warmer temperature conditions as climate change progresses, referred to here as global-change-type drought, yet quantitative assessments of the triggers and potential extent of drought-induced vegetation die-off remain pivotal uncertainties in assessing climate-change impacts. Of particular concern is regional-scale mortality of overstory trees, which rapidly alters ecosystem type, associated ecosystem properties, and land surface conditions for decades. Here, we quantify regional-scale vegetation die-off across southwestern North American woodlands in 2002-2003 in response to drought and associated bark beetle infestations. At an intensively studied site within the region, we quantified that after 15 months of depleted soil water content, >90% of the dominant, overstory tree species (Pinus edulis, a piñon) died. The die-off was reflected in changes in a remotely sensed index of vegetation greenness (Normalized Difference Vegetation Index), not only at the intensively studied site but also across the region, extending over 12,000 km2 or more; aerial and field surveys confirmed the general extent of the die-off. Notably, the recent drought was warmer than the previous subcontinental drought of the 1950s. The limited, available observations suggest that die-off from the recent drought was more extensive than that from the previous drought, extending into wetter sites within the tree species' distribution. Our results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-off to be more severe and extensive for future global-change-type drought under warmer conditions.

Regional vegetation die-off in response to global-change-type drought

PubMed Central

Breshears, David D.; Cobb, Neil S.; Rich, Paul M.; Price, Kevin P.; Allen, Craig D.; Balice, Randy G.; Romme, William H.; Kastens, Jude H.; Floyd, M. Lisa; Belnap, Jayne; Anderson, Jesse J.; Myers, Orrin B.; Meyer, Clifton W.

2005-01-01

Future drought is projected to occur under warmer temperature conditions as climate change progresses, referred to here as global-change-type drought, yet quantitative assessments of the triggers and potential extent of drought-induced vegetation die-off remain pivotal uncertainties in assessing climate-change impacts. Of particular concern is regional-scale mortality of overstory trees, which rapidly alters ecosystem type, associated ecosystem properties, and land surface conditions for decades. Here, we quantify regional-scale vegetation die-off across southwestern North American woodlands in 2002-2003 in response to drought and associated bark beetle infestations. At an intensively studied site within the region, we quantified that after 15 months of depleted soil water content, >90% of the dominant, overstory tree species (Pinus edulis, a piñon) died. The die-off was reflected in changes in a remotely sensed index of vegetation greenness (Normalized Difference Vegetation Index), not only at the intensively studied site but also across the region, extending over 12,000 km2 or more; aerial and field surveys confirmed the general extent of the die-off. Notably, the recent drought was warmer than the previous subcontinental drought of the 1950s. The limited, available observations suggest that die-off from the recent drought was more extensive than that from the previous drought, extending into wetter sites within the tree species' distribution. Our results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-off to be more severe and extensive for future global-change-type drought under warmer conditions. PMID:16217022

Future soil moisture and temperature extremes imply expanding suitability for rainfed agriculture in temperate drylands

USGS Publications Warehouse

Bradford, John B.; Schlaepfer, Daniel R.; Lauenroth, William K.; Yackulic, Charles B.; Duniway, Michael C.; Hall, Sonia A.; Jia, Gensuo; Jamiyansharav, Khishigbayar; Munson, Seth M.; Wilson, Scott D.; Tietjen, Britta

2017-01-01

The distribution of rainfed agriculture is expected to respond to climate change and human population growth. However, conditions that support rainfed agriculture are driven by interactions among climate, including climate extremes, and soil moisture availability that have not been well defined. In the temperate regions that support much of the world’s agriculture, these interactions are complicated by seasonal temperature fluctuations that can decouple climate and soil moisture. Here, we show that suitability to support rainfed agriculture can be effectively represented by the interactive effects of just two variables: suitability increases where warm conditions occur with wet soil, and suitability decreases with extreme high temperatures. 21st century projections based on ecohydrological modeling of downscaled climate forecasts imply geographic shifts and overall increases in the area suitable for rainfed agriculture in temperate regions, especially at high latitudes, and pronounced, albeit less widespread, declines in suitable areas in low latitude drylands, especially in Europe. These results quantify the integrative direct and indirect impact of rising temperatures on rainfed agriculture.

Disentangling the effects of feedback structure and climate on Poaceae annual airborne pollen fluctuations and the possible consequences of climate change.

PubMed

García de León, David; García-Mozo, Herminia; Galán, Carmen; Alcázar, Purificación; Lima, Mauricio; González-Andújar, José L

2015-10-15

Pollen allergies are the most common form of respiratory allergic disease in Europe. Most studies have emphasized the role of environmental processes, as the drivers of airborne pollen fluctuations, implicitly considering pollen production as a random walk. This work shows that internal self-regulating processes of the plants (negative feedback) should be included in pollen dynamic systems in order to give a better explanation of the observed pollen temporal patterns. This article proposes a novel methodological approach based on dynamic systems to investigate the interaction between feedback structure of plant populations and climate in shaping long-term airborne Poaceae pollen fluctuations and to quantify the effects of climate change on future airborne pollen concentrations. Long-term historical airborne Poaceae pollen data (30 years) from Cordoba city (Southern Spain) were analyzed. A set of models, combining feedback structure, temperature and actual evapotranspiration effects on airborne Poaceae pollen were built and compared, using a model selection approach. Our results highlight the importance of first-order negative feedback and mean annual maximum temperature in driving airborne Poaceae pollen dynamics. The best model was used to predict the effects of climate change under two standardized scenarios representing contrasting temporal patterns of economic development and CO2 emissions. Our results predict an increase in pollen levels in southern Spain by 2070 ranging from 28.5% to 44.3%. The findings from this study provide a greater understanding of airborne pollen dynamics and how climate change might impact the future evolution of airborne Poaceae pollen concentrations and thus the future evolution of related pollen allergies. Copyright © 2015 Elsevier B.V. All rights reserved.

Storylines of combined land use and climatic drivers and their hydrological impacts in an alpine catchment (Brixental/Austria)

NASA Astrophysics Data System (ADS)

Strasser, Ulrich; Förster, Kristian; Meissl, Gertraud; Marke, Thomas; Schermer, Markus; Stotten, Rike; Formayer, Herbert; Themessl, Matthias

2017-04-01

We present a numerical modelling experiment with storylines of coupled land use and climate evolution as input in the physically-based, distributed water balance model WaSiM. The aim is to quantify the effects of these two framing components on the future water cycle. The test site for the simulations is the catchment of the Brixentaler Ache in Tyrol/Austria (47.5°N, 322 km2). The climatic background is defined by simulations for the A1B and RCP 8.5 emission scenarios until 2050. These two climate projections were combined with three future land use developments for forest management, developed in an inter- and transdisciplinary assessment with local actors using plausible and consisent projections for forest management, policy, social cooperation, tourism and economy: (i) Ecological adaptation: The forest management consequently applies the political guidelines, and the forest cover is dominated by an ecological, place-adapted mixed cultivation with a harmonious age structure. (ii) Economical overexploitation and wildness: The increase in efficiency, cost reduction and short term results are in focus of the forest management. (iii) Withdrawal and wildness: Cultivation in general is decreasing, and the forest becomes vulnerable against natural hazards. A new module for snow-canopy interaction simulation, providing explicit rates of intercepted and sublimated snow from the trees and stems of the different forest stands, has been implemented in WaSiM. The new version of the model is used to model the coupled future climate/land use storylines for the Brixental. Results show the effects of climate change and land use on the water balance and streamflow in the catchment.

Modeling and dynamic monitoring of ecosystem performance in the Yukon River Basin

USGS Publications Warehouse

Wylie, Bruce K.; Zhang, L.; Ji, Lei; Tieszen, Larry L.; Bliss, N.B.

2008-01-01

Central Alaska is ecologically sensitive and experiencing stress in response to marked regional warming. Resource managers would benefit from an improved ability to monitor ecosystem processes in response to climate change, fire, insect damage, and management policies and to predict responses to future climate scenarios. We have developed a method for analyzing ecosystem performance as represented by the growing season integral of normalized difference vegetation index (NDVI), which is a measure of greenness that can be interpreted in terms of plant growth or photosynthetic activity (gross primary productivity). The approach illustrates the status and trends of ecosystem changes and separates the influences of climate and local site conditions from the influences of disturbances and land management.We emphasize the ability to quantify ecosystem processes, not simply changes in land cover, across the entire period of the remote sensing archive (Wylie and others, 2008). The method builds upon remotely sensed measures of vegetation greenness for each growing season. By itself, however, a time series of greenness often reflects annual climate variations in temperature and precipitation. Our method seeks to remove the influence of climate so that changes in underlying ecological conditions are identified and quantified. We define an "expected ecosystem performance" to represent the greenness response expected in a particular year given the climate of that year. We distinguish "performance anomalies" as cases where the ecosystem response is significantly different from the expected ecosystem performance. Maps of the performance anomalies (fig. 1) and trends in the anomalies give valuable information on the ecosystems for land managers and policy makers at a resolution of 1 km to 250 m.

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

2014-12-01

Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Impacts of Climate Change on Surface Ozone and Intercontinental Ozone Pollution: A Multi-Model Study

NASA Technical Reports Server (NTRS)

Doherty, R. M.; Wild, O.; Shindell, D. T.; Zeng, G.; MacKenzie, I. A.; Collins, W. J.; Fiore, A. M.; Stevenson, D. S.; Dentener, F. J.; Schultz, M. G.;

Effects of climate change on aerosol concentrations in Europe

NASA Astrophysics Data System (ADS)

Megaritis, Athanasios G.; Fountoukis, Christos; Pandis, Spyros N.

2013-04-01

High concentrations of particulate matter less than 2.5 μm in size (PM2.5), ozone and other major constituents of air pollution, have adverse effects on human health, visibility and ecosystems (Seinfeld and Pandis, 2006), and are strongly influenced by meteorology. Emissions control policy is currently made assuming that climate will remain constant in the future. However, climate change over the next decades is expected to be significant (IPCC, 2007) and may impact local and regional air quality. Determining the sensitivity of the concentrations of air pollutants to climate change is an important step toward estimating future air quality. In this study we applied PMCAMx (Fountoukis et al., 2011), a three dimensional chemical transport model, over Europe, in order to quantify the individual effects of various meteorological parameters on fine particulate matter (PM2.5) concentrations. A suite of perturbations in various meteorological factors, such as temperature, wind speed, absolute humidity and precipitation were imposed separately on base case conditions to determine the sensitivities of PM2.5 concentrations and composition to these parameters. Different simulation periods (summer, autumn 2008 and winter 2009) are used to examine also the seasonal dependence of the air quality - climate interactions. The results of these sensitivity simulations suggest that there is an important link between changes in meteorology and PM2.5 levels. We quantify through separate sensitivity simulations the processes which are mainly responsible for the final predicted changes in PM2.5 concentration and composition. The predicted PM2.5 response to those meteorology perturbations was found to be quite variable in space and time. These results suggest that, the changes in concentrations caused by changes in climate should be taken into account in long-term air quality planning. References Fountoukis C., Racherla P. N., Denier van der Gon H. A. C., Polymeneas P., Charalampidis P. E., Pilinis C., Wiedensohler A., Dall'Osto M., O'Dowd C., and S. N. Pandis: Evaluation of a three-dimensional chemical transport model (PMCAMx) in the European domain during the EUCAARI May 2008 campaign, Atmos. Chem. Phys., 11, 10331-10347, 2011. Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report: Summary for Policymakers, 2007. Seinfeld, J. H., and Pandis, S. N.: Atmospheric chemistry and physics: From air pollution to climate change, 2nd ed.; John Wiley and Sons, Hoboken, NJ, 2006.

Historical trends and high-resolution future climate projections in northern Tuscany (Italy)

NASA Astrophysics Data System (ADS)

D'Oria, Marco; Ferraresi, Massimo; Tanda, Maria Giovanna

2017-12-01

This paper analyzes the historical precipitation and temperature trends and the future climate projections with reference to the northern part of Tuscany (Italy). The trends are identified and quantified at monthly and annual scale at gauging stations with data collected for long periods (60-90 years). An ensemble of 13 Regional Climate Models (RCMs), based on two Representative Concentration Pathways (RCP4.5 and RCP8.5), was then used to assess local scale future precipitation and temperature projections and to represent the uncertainty in the results. The historical data highlight a general decrease of the annual rainfall at a mean rate of 22 mm per decade but, in many cases, the tendencies are not statistically significant. Conversely, the annual mean temperature exhibits an upward trend, statistically significant in the majority of cases, with a warming rate of about 0.1 °C per decade. With reference to the model projections and the annual precipitation, the results are not concordant; the deviations between models in the same period are higher than the future changes at medium- (2031-2040) and long-term (2051-2060) and highlight that the model uncertainty and variability is high. According to the climate model projections, the warming of the study area is unequivocal; a mean positive increment of 0.8 °C at medium-term and 1.1 °C at long-term is expected with respect to the reference period (2003-2012) and the scenario RCP4.5; the increments grow to 0.9 °C and 1.9 °C for the RCP8.5. Finally, in order to check the observed climate change signals, the climate model projections were compared with the trends based on the historical data. A satisfactory agreement is obtained with reference to the precipitation; a systematic underestimation of the trend values with respect to the models, at medium- and long-term, is observed for the temperature data.

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages.

PubMed

Radinger, Johannes; Hölker, Franz; Horký, Pavel; Slavík, Ondřej; Dendoncker, Nicolas; Wolter, Christian

2016-04-01

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts. © 2015 John Wiley & Sons Ltd.

Evaluation of potential impacts of climate change and water management on streamflow in the Rovuma River, Mozambique and Tanzania

NASA Astrophysics Data System (ADS)

Minihane, M.; Lettenmaier, D. P.

2012-12-01

Economic development and public health are tied to water resources development in many parts of the world. Effective use of water management infrastructure investments requires projections of future climatic and water use conditions. This is particularly true in developing countries. We explore in this work water resource availability in the Rovuma River, which lies in a sparsely-populated region of southeastern Africa, on the border of Mozambique and Tanzania. While there are only limited documented observations of flow of the Rovuma River and it's tributaries, particularly in recent years, there is widespread interest in development of the water resources of the region. The national governments are interested in hydropower potential while private companies, many of them large multinational organizations, have started irrigation programs to increase agricultural output. While the Mozambique and Tanzania governments have a joint agreement over the river development, there is a need to assess both current and potential future water resource conditions in the basin. The sustainability of these developments, however, may be affected by climate change. Here we quantify potential changes in streamflow in the Rovuma River under dry and wet climate projection scenarios using the delta method and the Variable Infiltration Capacity (VIC) macro-scale hydrology model. We then evaluate streamflow changes relative to water withdrawals required for a range of irrigated agriculture scenarios. Our analysis is intended to be a starting point for planners to consider potential impacts of both streamflow withdrawal permits (for irrigated agriculture) and future uncertain climate conditions.

Integrating Plant Science and Crop Modeling: Assessment of the Impact of Climate Change on Soybean and Maize Production.

PubMed

Fodor, Nándor; Challinor, Andrew; Droutsas, Ioannis; Ramirez-Villegas, Julian; Zabel, Florian; Koehler, Ann-Kristin; Foyer, Christine H

2017-11-01

Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world. Crop model inter-comparison studies have identified large uncertainties and biases associated with climate change. The need to quantify uncertainty has drawn the fields of plant molecular physiology, crop breeding and biology, and climate change modeling closer together. Comparing data from different models that have been used to assess the potential climate change impacts on soybean and maize production, future yield losses have been predicted for both major crops. When CO2 fertilization effects are taken into account significant yield gains are predicted for soybean, together with a shift in global production from the Southern to the Northern hemisphere. Maize production is also forecast to shift northwards. However, unless plant breeders are able to produce new hybrids with improved traits, the forecasted yield losses for maize will only be mitigated by agro-management adaptations. In addition, the increasing demands of a growing world population will require larger areas of marginal land to be used for maize and soybean production. We summarize the outputs of crop models, together with mitigation options for decreasing the negative impacts of climate on the global maize and soybean production, providing an overview of projected land-use change as a major determining factor for future global crop production. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

The Millennium Drought in southeast Australia (2001-2009): Natural and human causes and implications for water resources, ecosystems, economy, and society

NASA Astrophysics Data System (ADS)

van Dijk, Albert I. J. M.; Beck, Hylke E.; Crosbie, Russell S.; de Jeu, Richard A. M.; Liu, Yi Y.; Podger, Geoff M.; Timbal, Bertrand; Viney, Neil R.

2013-02-01

The "Millennium Drought" (2001-2009) can be described as the worst drought on record for southeast Australia. Adaptation to future severe droughts requires insight into the drivers of the drought and its impacts. These were analyzed using climate, water, economic, and remote sensing data combined with biophysical modeling. Prevailing El Niño conditions explained about two thirds of rainfall deficit in east Australia. Results for south Australia were inconclusive; a contribution from global climate change remains plausible but unproven. Natural processes changed the timing and magnitude of soil moisture, streamflow, and groundwater deficits by up to several years, and caused the amplification of rainfall declines in streamflow to be greater than in normal dry years. By design, river management avoided impacts on some categories of water users, but did so by exacerbating the impacts on annual irrigation agriculture and, in particular, river ecosystems. Relative rainfall reductions were amplified 1.5-1.7 times in dryland wheat yields, but the impact was offset by steady increases in cropping area and crop water use efficiency (perhaps partly due to CO2 fertilization). Impacts beyond the agricultural sector occurred (e.g., forestry, tourism, utilities) but were often diffuse and not well quantified. Key causative pathways from physical drought to the degradation of ecological, economic, and social health remain poorly understood and quantified. Combined with the multiple dimensions of multiyear droughts and the specter of climate change, this means future droughts may well break records in ever new ways and not necessarily be managed better than past ones.

Influence of climate change on flood magnitude and seasonality in the Arga River catchment in Spain

NASA Astrophysics Data System (ADS)

Garijo, Carlos; Mediero, Luis

2018-04-01

Climate change projections suggest that extremes, such as floods, will modify their behaviour in the future. Detailed catchment-scale studies are needed to implement the European Union Floods Directive and give recommendations for flood management and design of hydraulic infrastructure. In this study, a methodology to quantify changes in future flood magnitude and seasonality due to climate change at a catchment scale is proposed. Projections of 24 global climate models are used, with 10 being downscaled by the Spanish Meteorological Agency (Agencia Estatal de Meteorología, AEMET) and 14 from the EURO-CORDEX project, under two representative concentration pathways (RCPs) 4.5 and 8.5, from the Fifth Assessment Report provided by the Intergovernmental Panel on Climate Change. Downscaled climate models provided by the AEMET were corrected in terms of bias. The HBV rainfall-runoff model was selected to simulate the catchment hydrological behaviour. Simulations were analysed through both annual maximum and peaks-over-threshold (POT) series. The results show a decrease in the magnitude of extreme floods for the climate model projections downscaled by the AEMET. However, results for the climate model projections downscaled by EURO-CORDEX show differing trends, depending on the RCP. A small decrease in the flood magnitude was noticed for the RCP 4.5, while an increase was found for the RCP 8.5. Regarding the monthly seasonality analysis performed by using the POT series, a delay in the flood timing from late-autumn to late-winter is identified supporting the findings of recent studies performed with observed data in recent decades.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Thermal erosion of a permafrost coastline: Improving process-based models using time-lapse photography

USGS Publications Warehouse

Wobus, C.; Anderson, R.; Overeem, I.; Matell, N.; Clow, G.; Urban, F.

2011-01-01

Coastal erosion rates locally exceeding 30 m y-1 have been documented along Alaska's Beaufort Sea coastline, and a number of studies suggest that these erosion rates have accelerated as a result of climate change. However, a lack of direct observational evidence has limited our progress in quantifying the specific processes that connect climate change to coastal erosion rates in the Arctic. In particular, while longer ice-free periods are likely to lead to both warmer surface waters and longer fetch, the relative roles of thermal and mechanical (wave) erosion in driving coastal retreat have not been comprehensively quantified. We focus on a permafrost coastline in the northern National Petroleum Reserve-Alaska (NPR-A), where coastal erosion rates have averaged 10-15 m y-1 over two years of direct monitoring. We take advantage of these extraordinary rates of coastal erosion to observe and quantify coastal erosion directly via time-lapse photography in combination with meteorological observations. Our observations indicate that the erosion of these bluffs is largely thermally driven, but that surface winds play a crucial role in exposing the frozen bluffs to the radiatively warmed seawater that drives melting of interstitial ice. To first order, erosion in this setting can be modeled using formulations developed to describe iceberg deterioration in the open ocean. These simple models provide a conceptual framework for evaluating how climate-induced changes in thermal and wave energy might influence future erosion rates in this setting.

The impacts of climate change on poverty in 2030, and the potential from rapid, inclusive and climate-informed development

NASA Astrophysics Data System (ADS)

Rozenberg, J.; Hallegatte, S.

2016-12-01

There is a consensus on the fact that poor people are more vulnerable to climate change than the rest of the population, but, until recently, few quantified estimates had been proposed and few frameworks existed to design policies for addressing the issue. In this paper, we analyze the impacts of climate change on poverty using micro-simulation approaches. We start from household surveys that describe the current distribution of income and occupations, we project these households into the future and we look at the impacts of climate change on people's income. To project households into the future, we explore a large range of assumptions on future demographic changes (including on education), technological changes, and socio-economic trends (including redistribution policies). This approach allows us to identify the main combination of factors that lead to fast poverty reduction, and the ones that lead to high climate change impacts on the poor. Identifying these factors is critical for designing efficient policies to protect the poorest from climate change impacts and making economic growth more inclusive. Conclusions are twofold. First, by 2030 climate change can have a large impact on poverty, with between 3 and 122 million more people in poverty, but climate change remains a secondary driver of poverty trends within this time horizon. Climate change impacts do not only affect the poorest: in 2030, the bottom 40 percent lose more than 4 percent of income in many countries. The regional hotspots are Sub-Saharan Africa and - to a lesser extent - India and the rest of South Asia. The most important channel through which climate change increases poverty is through agricultural income and food prices. Second, by 2030 and in the absence of surprises on climate impacts, inclusive climate-informed development can prevent most of (but not all) the impacts on poverty. In a scenario with rapid, inclusive and climate-proof development, climate change impact on poverty is between 3 and 16 million, vs. between 35 and 122 million if development is delayed and less inclusive. Development and inclusive policies appears to reduce the impact of climate change on poverty much more than it reduces aggregated losses expressed in percentage of GDP.

Climate and soil attributes determine plant species turnover in global drylands.

PubMed

Ulrich, Werner; Soliveres, Santiago; Maestre, Fernando T; Gotelli, Nicholas J; Quero, José L; Delgado-Baquerizo, Manuel; Bowker, Matthew A; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R; Hernández, Rosa M; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A; Raveh, Eran; Romão, Roberto L; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2014-12-01

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

Robustness for slope stability modelling under deep uncertainty

NASA Astrophysics Data System (ADS)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2015-04-01

Landslides can have large negative societal and economic impacts, such as loss of life and damage to infrastructure. However, the ability of slope stability assessment to guide management is limited by high levels of uncertainty in model predictions. Many of these uncertainties cannot be easily quantified, such as those linked to climate change and other future socio-economic conditions, restricting the usefulness of traditional decision analysis tools. Deep uncertainty can be managed more effectively by developing robust, but not necessarily optimal, policies that are expected to perform adequately under a wide range of future conditions. Robust strategies are particularly valuable when the consequences of taking a wrong decision are high as is often the case of when managing natural hazard risks such as landslides. In our work a physically based numerical model of hydrologically induced slope instability (the Combined Hydrology and Stability Model - CHASM) is applied together with robust decision making to evaluate the most important uncertainties (storm events, groundwater conditions, surface cover, slope geometry, material strata and geotechnical properties) affecting slope stability. Specifically, impacts of climate change on long-term slope stability are incorporated, accounting for the deep uncertainty in future climate projections. Our findings highlight the potential of robust decision making to aid decision support for landslide hazard reduction and risk management under conditions of deep uncertainty.

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.

Stochastic Hourly Weather Generator HOWGH: Validation and its Use in Pest Modelling under Present and Future Climates

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Hirschi, M.; Spirig, C.

2014-12-01

To quantify impact of the climate change on a specific pest (or any weather-dependent process) in a specific site, we may use a site-calibrated pest (or other) model and compare its outputs obtained with site-specific weather data representing present vs. perturbed climates. The input weather data may be produced by the stochastic weather generator. Apart from the quality of the pest model, the reliability of the results obtained in such experiment depend on an ability of the generator to represent the statistical structure of the real world weather series, and on the sensitivity of the pest model to possible imperfections of the generator. This contribution deals with the multivariate HOWGH weather generator, which is based on a combination of parametric and non-parametric statistical methods. Here, HOWGH is used to generate synthetic hourly series of three weather variables (solar radiation, temperature and precipitation) required by a dynamic pest model SOPRA to simulate the development of codling moth. The contribution presents results of the direct and indirect validation of HOWGH. In the direct validation, the synthetic series generated by HOWGH (various settings of its underlying model are assumed) are validated in terms of multiple climatic characteristics, focusing on the subdaily wet/dry and hot/cold spells. In the indirect validation, we assess the generator in terms of characteristics derived from the outputs of SOPRA model fed by the observed vs. synthetic series. The weather generator may be used to produce weather series representing present and future climates. In the latter case, the parameters of the generator may be modified by the climate change scenarios based on Global or Regional Climate Models. To demonstrate this feature, the results of codling moth simulations for future climate will be shown. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Climate influences on whitebark pine mortality from mountain pine beetle in the Greater Yellowstone Ecosystem.

PubMed

Buotte, Polly C; Hicke, Jeffrey A; Preisler, Haiganoush K; Abatzoglou, John T; Raffa, Kenneth F; Logan, Jesse A

2016-12-01

Extensive mortality of whitebark pine, beginning in the early to mid-2000s, occurred in the Greater Yellowstone Ecosystem (GYE) of the western USA, primarily from mountain pine beetle but also from other threats such as white pine blister rust. The climatic drivers of this recent mortality and the potential for future whitebark pine mortality from mountain pine beetle are not well understood, yet are important considerations in whether to list whitebark pine as a threatened or endangered species. We sought to increase the understanding of climate influences on mountain pine beetle outbreaks in whitebark pine forests, which are less well understood than in lodgepole pine, by quantifying climate-beetle relationships, analyzing climate influences during the recent outbreak, and estimating the suitability of future climate for beetle outbreaks. We developed a statistical model of the probability of whitebark pine mortality in the GYE that included temperature effects on beetle development and survival, precipitation effects on host tree condition, beetle population size, and stand characteristics. Estimated probability of whitebark pine mortality increased with higher winter minimum temperature, indicating greater beetle winter survival; higher fall temperature, indicating synchronous beetle emergence; lower two-year summer precipitation, indicating increased potential for host tree stress; increasing beetle populations; stand age; and increasing percent composition of whitebark pine within a stand. The recent outbreak occurred during a period of higher-than-normal regional winter temperatures, suitable fall temperatures, and low summer precipitation. In contrast to lodgepole pine systems, area with mortality was linked to precipitation variability even at high beetle populations. Projections from climate models indicate future climate conditions will likely provide favorable conditions for beetle outbreaks within nearly all current whitebark pine habitat in the GYE by the middle of this century. Therefore, when surviving and regenerating trees reach ages suitable for beetle attack, there is strong potential for continued whitebark pine mortality due to mountain pine beetle. © 2016 by the Ecological Society of America.

Multi-criteria objective based climate change impact assessment for multi-purpose multi-reservoir systems

NASA Astrophysics Data System (ADS)

Müller, Ruben; Schütze, Niels

2014-05-01

Water resources systems with reservoirs are expected to be sensitive to climate change. Assessment studies that analyze the impact of climate change on the performance of reservoirs can be divided in two groups: (1) Studies that simulate the operation under projected inflows with the current set of operational rules. Due to non adapted operational rules the future performance of these reservoirs can be underestimated and the impact overestimated. (2) Studies that optimize the operational rules for best adaption of the system to the projected conditions before the assessment of the impact. The latter allows for estimating more realistically future performance and adaption strategies based on new operation rules are available if required. Multi-purpose reservoirs serve various, often conflicting functions. If all functions cannot be served simultaneously at a maximum level, an effective compromise between multiple objectives of the reservoir operation has to be provided. Yet under climate change the historically preferenced compromise may no longer be the most suitable compromise in the future. Therefore a multi-objective based climate change impact assessment approach for multi-purpose multi-reservoir systems is proposed in the study. Projected inflows are provided in a first step using a physically based rainfall-runoff model. In a second step, a time series model is applied to generate long-term inflow time series. Finally, the long-term inflow series are used as driving variables for a simulation-based multi-objective optimization of the reservoir system in order to derive optimal operation rules. As a result, the adapted Pareto-optimal set of diverse best compromise solutions can be presented to the decision maker in order to assist him in assessing climate change adaption measures with respect to the future performance of the multi-purpose reservoir system. The approach is tested on a multi-purpose multi-reservoir system in a mountainous catchment in Germany. A climate change assessment is performed for climate change scenarios based on the SRES emission scenarios A1B, B1 and A2 for a set of statistically downscaled meteorological data. The future performance of the multi-purpose multi-reservoir system is quantified and possible intensifications of trade-offs between management goals or reservoir utilizations are shown.

Quantifying uncertainty in climate change science through empirical information theory.

PubMed

Majda, Andrew J; Gershgorin, Boris

2010-08-24

Quantifying the uncertainty for the present climate and the predictions of climate change in the suite of imperfect Atmosphere Ocean Science (AOS) computer models is a central issue in climate change science. Here, a systematic approach to these issues with firm mathematical underpinning is developed through empirical information theory. An information metric to quantify AOS model errors in the climate is proposed here which incorporates both coarse-grained mean model errors as well as covariance ratios in a transformation invariant fashion. The subtle behavior of model errors with this information metric is quantified in an instructive statistically exactly solvable test model with direct relevance to climate change science including the prototype behavior of tracer gases such as CO(2). Formulas for identifying the most sensitive climate change directions using statistics of the present climate or an AOS model approximation are developed here; these formulas just involve finding the eigenvector associated with the largest eigenvalue of a quadratic form computed through suitable unperturbed climate statistics. These climate change concepts are illustrated on a statistically exactly solvable one-dimensional stochastic model with relevance for low frequency variability of the atmosphere. Viable algorithms for implementation of these concepts are discussed throughout the paper.

Climate and Cryosphere (CliC) Project and its Interest in Arctic Hydrology Research

NASA Astrophysics Data System (ADS)

Yang, D.; Prowse, T. D.; Steffen, K.; Ryabinin, V.

2009-12-01

The cryosphere is an important and dynamic component of the global climate system. The global cryosphere is changing rapidly, with changes in the Polar Regions receiving particular attention during the International Polar Year 2007-2008. The Climate and Cryosphere (CliC) Project is a core project of the World Climate Research Programme (WCRP) and is co-sponsored by WCRP, SCAR (Scientific Committee for Antarctic Research) and IASC (International Committee for Antarctic Research). The principal goal of CliC is to assess and quantify the impacts that climatic variability and change have on components of the cryosphere and the consequences of these impacts for the climate system. To achieve its objectives, CliC coordinates international and regional projects, partners with other organizations in joint initiatives, and organizes panels and working groups to lead and coordinate advanced research aimed at closing identified gaps in scientific knowledge about climate and cryosphere. The terrestrial cryosphere includes land areas where snow cover, lake- and river-ice, glaciers and ice caps, permafrost and seasonally frozen ground and solid precipitation occur. The main task of this theme is to improve estimates and quantify the uncertainty of water balance and related energy flux components in cold climate regions. This includes precipitation (both solid and liquid) distribution, properties of snow, snow melt, evapotranspiration, sublimation, water movement through frozen and unfrozen ground, water storage in watersheds, river- and lake-ice properties and processes, and river runoff. The focus of this theme includes two specific issues: the role of permafrost and frozen ground in the carbon balance, and precipitation in cold climates. Hydrological studies of cold regions will provide a key contribution to the new theme crosscut, which focuses on the cryospheric input to the freshwater balance of the Arctic. This presentation will provide an overview and update of recent developments of cold region hydrometeorology research activities and future challenges in arctic hydrology and climate change investigations.

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.

Integrated climate/land use/hydrological change scenarios for assessing threats to ecosystem services on California rangelands

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Flint, L. E.; Casey, C. F.; Alvarez, P.; Sleeter, B. M.; Sohl, T.

2013-12-01

In California there are over 18 million acres of rangelands in the Central Valley and the interior Coast Range, most of which are privately owned and managed for livestock production. Ranches provide extensive wildlife habitat and generate multiple ecosystem services that carry considerable market and non-market values. These rangelands are under pressure from urbanization and conversion to intensive agriculture, as well as from climate change that can alter the flow of these services. To understand the coupled and isolated impacts of land use and climate change on rangeland ecosystem services, we developed six spatially explicit (250 m) coupled climate/land use/hydrological change scenarios for the Central Valley and oak woodland regions of California consistent with three IPCC emission scenarios - A2, A1B and B1. Three land use land cover (LULC) change scenarios were each integrated with two downscaled global climate models (GCMs) (a warm, wet future and a hot, dry future) and related hydrologic data. We used these scenarios to quantify wildlife habitat, water supply (recharge potential and streamflow) and carbon sequestration on rangelands and to conduct an economic analysis associated with changes in these benefits. The USGS FOREcasting SCEnarios of land-use change model (FORE-SCE), which runs dynamically with downscaled GCM outputs, was used to generate maps of yearly LULC change for each scenario from 2006 to 2100. We used the USGS Basin Characterization Model (BCM), a regional water balance model, to generate change in runoff, recharge, and stream discharge based on land use change and climate change. Metrics derived from model outputs were generated at the landscape scale and for six case-study watersheds. At the landscape scale, over a quarter of the million acres set aside for conservation in the B1 scenario would otherwise be converted to agriculture in the A2 scenario, where temperatures increase by up to 4.5 °C compared to 1.3 °C in the B1 scenario. A comparison of two watersheds - Alameda Creek, an urbanized watershed, and Upper Stony Creek, impacted by intensified agriculture, demonstrates the relative contribution of urbanization and climate change to water supply. In Upper Stony Creek, where 24% of grassland is converted to agriculture in the A1B scenario, a hotter, dryer 4-year time period could lead to a 40% reduction in streamflow compared to present day. In Alameda Creek, for the same scenario, 47% of grassland is converted to urbanized lands and streamflow may increase by 11%, resulting in a recharge:runoff ratio of 0.26; though if urbanization does not take place, streamflow could decrease by 64% and the recharge:runoff ratio would be 1.2. Model outputs quantify the impact of urbanization on water supply and show the importance of soil storage capacity. Scenarios have applications for climate-smart conservation and land use planning by identifying outcomes associated with coupled future land use scenarios and more variable and extreme potential future climates.

One carbon cycle: Impacts of model integration, ecosystem process detail, model resolution, and initialization data, on projections of future climate mitigation strategies

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; le page, Y.; Patel, P. L.; Chini, L. P.; Sahajpal, R.; Dubayah, R.; Thomson, A. M.; Edmonds, J.; Janetos, A. C.

2013-12-01

Integrated assessment models (IAMs) simulate the interactions between human and natural systems at a global scale, representing a broad suite of phenomena across the global economy, energy system, land-use, and carbon cycling. Most proposed climate mitigation strategies rely on maintaining or enhancing the terrestrial carbon sink as a substantial contribution to restrain the concentration of greenhouse gases in the atmosphere, however most IAMs rely on simplified regional representations of terrestrial carbon dynamics. Our research aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. We developed the new Integrated Ecosystem Demography (iED) to increase terrestrial ecosystem process detail, resolution, and the utilization of remote sensing in integrated assessments. iED brings together state-of-the-art models of human society (GCAM), spatial land-use patterns (GLM) and terrestrial ecosystems (ED) in a fully coupled framework. The major innovative feature of iED is a consistent, process-based representation of ecosystem dynamics and carbon cycle throughout the human, terrestrial, land-use, and atmospheric components. One of the most challenging aspects of ecosystem modeling is to provide accurate initialization of land surface conditions to reflect non-equilibrium conditions, i.e., the actual successional state of the forest. As all plants in ED have an explicit height, it is one of the few ecosystem models that can be initialized directly with vegetation height data. Previous work has demonstrated that ecosystem model resolution and initialization data quality have a large effect on flux predictions at continental scales. Here we use a factorial modeling experiment to quantify the impacts of model integration, process detail, model resolution, and initialization data on projections of future climate mitigation strategies. We find substantial effects on key integrated assessment projections including the magnitude of emissions to mitigate, the economic value of ecosystem carbon storage, future land-use patterns, food prices and energy technology.

Classification and Feature Selection Algorithms for Modeling Ice Storm Climatology

NASA Astrophysics Data System (ADS)

Swaminathan, R.; Sridharan, M.; Hayhoe, K.; Dobbie, G.

2015-12-01

Ice storms account for billions of dollars of winter storm loss across the continental US and Canada. In the future, increasing concentration of human populations in areas vulnerable to ice storms such as the northeastern US will only exacerbate the impacts of these extreme events on infrastructure and society. Quantifying the potential impacts of global climate change on ice storm prevalence and frequency is challenging, as ice storm climatology is driven by complex and incompletely defined atmospheric processes, processes that are in turn influenced by a changing climate. This makes the underlying atmospheric and computational modeling of ice storm climatology a formidable task. We propose a novel computational framework that uses sophisticated stochastic classification and feature selection algorithms to model ice storm climatology and quantify storm occurrences from both reanalysis and global climate model outputs. The framework is based on an objective identification of ice storm events by key variables derived from vertical profiles of temperature, humidity and geopotential height. Historical ice storm records are used to identify days with synoptic-scale upper air and surface conditions associated with ice storms. Evaluation using NARR reanalysis and historical ice storm records corresponding to the northeastern US demonstrates that an objective computational model with standard performance measures, with a relatively high degree of accuracy, identify ice storm events based on upper-air circulation patterns and provide insights into the relationships between key climate variables associated with ice storms.

Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data

Treesearch

K. Barrett; E.S. Kasischke; A.D. McGuire; M.R. Turetsky; E.S. Kane

2010-01-01

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to...

From the Last Interglacial to the Anthropocene: Modelling a Complete Glacial Cycle (PalMod)

NASA Astrophysics Data System (ADS)

Brücher, Tim; Latif, Mojib

2017-04-01

We will give a short overview and update on the current status of the national climate modelling initiative PalMod (Paleo Modelling, www.palmod.de). PalMod focuses on the understanding of the climate system dynamics and its variability during the last glacial cycle. The initiative is funded by the German Federal Ministry of Education and Research (BMBF) and its specific topics are: (i) to identify and quantify the relative contributions of the fundamental processes which determined the Earth's climate trajectory and variability during the last glacial cycle, (ii) to simulate with comprehensive Earth System Models (ESMs) the climate from the peak of the last interglacial - the Eemian warm period - up to the present, including the changes in the spectrum of variability, and (iii) to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs tested in such a way. The research is intended to be conducted over a period of 10 years, but with shorter funding cycles. PalMod kicked off in February 2016. The first phase focuses on the last deglaciation (app. the last 23.000 years). From the ESM perspective PalMod pushes forward model development by coupling ESM with dynamical ice sheet models. Computer scientists work on speeding up climate models using different concepts (like parallelisation in time) and one working group is dedicated to perform a comprehensive data synthesis to validate model performance. The envisioned approach is innovative in three respects. First, the consortium aims at simulating a full glacial cycle in transient mode and with comprehensive ESMs which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. Second, we shall address climate variability during the last glacial cycle on a large range of time scales, from interannual to multi-millennial, and attempt to quantify the relative contributions of external forcing and processes internal to the Earth system to climate variability at different time scales. Third, in order to achieve a higher level of understanding of natural climate variability at time scales of millennia, its governing processes and implications for the future climate, we bring together three different research communities: the Earth system modeling community, the proxy data community and the computational science community. The consortium consists of 18 partners including all major modelling centers within Germany. The funding comprises approximately 65 PostDoc positions and more than 120 scientists are involved. PalMod is coordinated at the Helmholtz Centre for Ocean Research Kiel (GEOMAR).

Quantifying carbon budget and nitrous oxide emissions of terrestrial ecosystems in the Eurasian Arctic and the Dry Latitudinal Belt of Northern Eurasia

NASA Astrophysics Data System (ADS)

Zhuang, Q.; Yu, T.; Qu, Y.; Kicklighter, D. W.; Melillo, J. M.; Sokolov, A. P.; Reilly, J. M.; Monier, E.

2017-12-01

The largest increase of surface air temperature and related climate extremes has occurred in Northern Eurasia in recent decades, and is projected to continue during the 21st century. The changing climate will affect the fate of the large reservoir of organic matter stored in the region. Given a large amount of carbon-based gases CO2 and CH4 is exchanged between the atmosphere and land ecosystems, we hypothesize that the emissions of another potent greenhouse gas N2O are not small. This study used a process-based biogeochemistry model to estimate soil N2O emissions in Northern Eurasia for the latter half of the 20th century and the 21st century. We find that, in the latter half of the 20th century, there was a slight decreasing trend for the regional N2O emissions from 1.4 Tg N yr-1 to 1.17 Tg N yr-1. Boreal forests are the largest source due to their large area and high flux density. Two contrasting climate scenarios with no-policy and policy for future greenhouse gas emissions and with different climate sensitivities (high, medium and low) of a global climate model are used to drive the biogeochemistry model for the 21st century. Simulations indicate that there will be an increasing trend of N2O emissions under the no-policy climate scenario. By 2100, the emissions are 1.28, 1.40 and 1.73 Tg N yr-1 under climate conditions projected considering low, intermediate, and high level of climate sensitivity, respectively. In contrast, under the policy climate scenarios, there will be a decreasing trend and the emissions are 0.89, 1.02, and 1.06 Tg N yr-1 by 2100, respectively. This study suggests that the large increase of air temperature will enhance regional N2O emissions. Future changes in precipitation and depleting organic nitrogen pools also play a role in affecting future emission strengths in Northern Eurasia. In this presentation, we will also present ensemble simulations of carbon budget for the Dry Latitudinal Belt of Northern Eurasia under various future climate conditions.

The economics (or lack thereof) of aerosol geoengineering

NASA Astrophysics Data System (ADS)

Goes, M.; Keller, K.; Tuana, N.

2009-04-01

Anthropogenic greenhouse gas emissions are changing the Earth's climate and impose substantial risks for current and future generations. What are scientifically sound, economically viable, and ethically defendable strategies to manage these climate risks? Ratified international agreements call for a reduction of greenhouse gas emissions to avoid dangerous anthropogenic interference with the climate system. Recent proposals, however, call for the deployment of a different approach: to geoengineer climate by injecting aerosol precursors into the stratosphere. Published economic studies typically suggest that substituting aerosol geoengineering for abatement of carbon dioxide emissions results in large net monetary benefits. However, these studies neglect the risks of aerosol geoengineering due to (i) the potential for future geoengineering failures and (ii) the negative impacts associated with the aerosol forcing. Here we use a simple integrated assessment model of climate change to analyze potential economic impacts of aerosol geoengineering strategies over a wide range of uncertain parameters such as climate sensitivity, the economic damages due to climate change, and the economic damages due to aerosol geoengineering forcing. The simplicity of the model provides the advantages of parsimony and transparency, but it also imposes severe caveats on the interpretation of the results. For example, the analysis is based on a globally aggregated model and is hence silent on the question of intragenerational distribution of costs and benefits. In addition, the analysis neglects the effects of endogenous learning about the climate system. We show that the risks associated with a future geoengineering failure and negative impacts of aerosol forcings can cause geoenginering strategies to fail an economic cost-benefit test. One key to this finding is that a geoengineering failure would lead to dramatic and abrupt climatic changes. The monetary damages due to this failure can dominate the cost-benefit analysis because the monetary damages of climate change are expected to increase with the rate of change. Substituting aerosol geoengineering for greenhouse gas emission abatement might fail not only an economic cost-benefit test but also an ethical test of distributional justice. Substituting aerosol geoengineering for greenhouse gas emissions abatements constitutes a conscious risk transfer to future generations. Intergenerational justice demands distributional justice, namely that present generations may not create benefits for themselves in exchange for burdens on future generations. We use the economic model to quantify this risk transfer to better inform the judgment of whether substituting aerosol geoengineering for carbon dioxide emission abatement fails this ethical test.

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

Northern Winter Climate Change: Assessment of Uncertainty in CMIP5 Projections Related to Stratosphere-Troposphere Coupling

NASA Technical Reports Server (NTRS)

Manzini, E.; Karpechko, A.Yu.; Anstey, J.; Shindell, Drew Todd; Baldwin, M.P.; Black, R.X.; Cagnazzo, C.; Calvo, N.; Charlton-Perez, A.; Christiansen, B.;

A Water Grid for the UK

NASA Astrophysics Data System (ADS)

Leathard, A.; Fowler, H. J.; Kilsby, C. G.

2009-12-01

Anthropogenically aggravated climate change associated with intensive expansion of the global economy has increased the demand for water whilst simultaneously altering natural variability in its distribution, straining water resources unsustainably and inequitably in many parts of the world, increasing drought risk, and encouraging decision-makers to reconsider the security of water supply. Indeed, in the absence of additional resource development, contemporary planning forecasts imply increased water stress across much of the United Kingdom. Until recently the regulatory authorities of the UK promoted increased efficiency of water delivery and consumption combined with a portfolio of financial instruments as a means of reducing water stress, maintaining present levels of consumer service without significant further exploitation of the environment. However, despite an increasingly sophisticated understanding of climate change and its effects, significant uncertainty remains in the quantification of its impacts on the water sector, and questions persist as to the effectiveness of such demand management measures compared to that of more traditional infrastructure improvements. Faced with possible futures provided for by detrimentally over-stressed resources, what opportunities remain for future strategic development in the UK? Is there a single national strategy that is both politically and socially acceptable? Do the benefits of national water infrastructure projects outweigh their costs? This ongoing study aims to evolve robust national adaptation strategies by quantifying the projected impacts of climate change across mainland UK using multi-model and perturbed-physics ensembles of projected future climate, encapsulating uncertainties in a scenario-driven integrated water resources model incorporating socio-economic elements.

Future Climate Impacts on Crop Water Demand and Groundwater Longevity in Agricultural Regions

NASA Astrophysics Data System (ADS)

Russo, T. A.; Sahoo, S.; Elliott, J. W.; Foster, I.

2016-12-01

Improving groundwater management practices under future drought conditions in agricultural regions requires three steps: 1) estimating the impacts of climate and drought on crop water demand, 2) projecting groundwater availability given climate and demand forcing, and 3) using this information to develop climate-smart policy and water use practices. We present an innovative combination of models to address the first two steps, and inform the third. Crop water demand was simulated using biophysical crop models forced by multiple climate models and climate scenarios, with one case simulating climate adaptation (e.g. modify planting or harvest time) and another without adaptation. These scenarios were intended to represent a range of drought projections and farm management responses. Nexty, we used projected climate conditions and simulated water demand across the United States as inputs to a novel machine learning-based groundwater model. The model was applied to major agricultural regions relying on the High Plains and Mississippi Alluvial aquifer systems in the US. The groundwater model integrates input data preprocessed using single spectrum analysis, mutual information, and a genetic algorithm, with an artificial neural network model. Model calibration and test results indicate low errors over the 33 year model run, and strong correlations to groundwater levels in hundreds of wells across each aquifer. Model results include a range of projected groundwater level changes from the present to 2050, and in some regions, identification and timeframe of aquifer depletion. These results quantify aquifer longevity under climate and crop scenarios, and provide decision makers with the data needed to compare scenarios of crop water demand, crop yield, and groundwater response, as they aim to balance water sustainability with food security.

USGCRP's Sustained Assessment Process: Progress to date and future plans

NASA Astrophysics Data System (ADS)

DeAngelo, B. J.; Reidmiller, D.; Lipschultz, F.; Cloyd, E. T.

2016-12-01

One of the four main objectives of the U.S. Global Change Research Program's (USGCRP's) Strategic Plan is to "Conduct Sustained Assessments", which seeks to build a process that synthesizes and advances the state of scientific knowledge on global change, develops future scenarios and potential impacts, and evaluates how effectively science is being and can be used to inform and support the Nation's response to climate change. To do so, USGCRP strives to establish a standing capacity to conduct national climate assessments with sectoral and regional information to evaluate climate risks and opportunities, and to inform decision-making, especially with regard to resiliency planning and adaptation measures. Building on the success of the 3rd National Climate Assessment (NCA) (2014), we discuss the range of USGCRP activities that embody the sustained assessment concept. Special reports, such as the recent Climate and Human Health Assessment and upcoming Climate Science Special Report, fill gaps in our understanding and provide crucial building blocks for next NCA report (NCA4). To facilitate the use of consistent assumptions across NCA4, new scenario products for climate, population, and land use will be made available through initiatives such as NOAA's Climate Resilience Toolkit. NCA4 will be informed by user engagement to advance the customization of knowledge. The report will strive to advance our ability to quantify various risks, monetize certain impacts, and communicate the benefits (i.e., avoided impacts) of various mitigation pathways. NCAnet (a national network of climate-interested stakeholders) continues to grow and foster collaborations across levels of governance and within civil society. Finally, USGCRP continues to actively engage with other assessment processes, at international, state, city, and tribal levels, to exchange ideas and to facilitate the potential for "linked" assessments across spatial scales.

Uncertainty in Climate Change Research: An Integrated Approach

NASA Astrophysics Data System (ADS)

Mearns, L.

2017-12-01

Uncertainty has been a major theme in research regarding climate change from virtually the very beginning. And appropriately characterizing and quantifying uncertainty has been an important aspect of this work. Initially, uncertainties were explored regarding the climate system and how it would react to future forcing. A concomitant area of concern was viewed in the future emissions and concentrations of important forcing agents such as greenhouse gases and aerosols. But, of course we know there are important uncertainties in all aspects of climate change research, not just that of the climate system and emissions. And as climate change research has become more important and of pragmatic concern as possible solutions to the climate change problem are addressed, exploring all the relevant uncertainties has become more relevant and urgent. More recently, over the past five years or so, uncertainties in impacts models, such as agricultural and hydrological models, have received much more attention, through programs such as AgMIP, and some research in this arena has indicated that the uncertainty in the impacts models can be as great or greater than that in the climate system. Still there remains other areas of uncertainty that remain underexplored and/or undervalued. This includes uncertainty in vulnerability and governance. Without more thoroughly exploring these last uncertainties, we likely will underestimate important uncertainties particularly regarding how different systems can successfully adapt to climate change . In this talk I will discuss these different uncertainties and how to combine them to give a complete picture of the total uncertainty individual systems are facing. And as part of this, I will discuss how the uncertainty can be successfully managed even if it is fairly large and deep. Part of my argument will be that large uncertainty is not the enemy, but rather false certainty is the true danger.

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

An integrated modeling approach for estimating hydrologic responses to future urbanization and climate changes in a mixed-use midwestern watershed.

PubMed

Sunde, Michael G; He, Hong S; Hubbart, Jason A; Urban, Michael A

2018-08-15

Future urban development and climatic changes are likely to affect hydrologic regimes in many watersheds. Quantifying potential water regime changes caused by these stressors is therefore crucial for enabling decision makers to develop viable environmental management strategies. This study presents an approach that integrates mid-21st century impervious surface growth estimates derived from the Imperviousness Change Analysis Tool with downscaled climate model projections and a hydrologic model Soil and Water Assessment Tool to characterize potential water regime changes in a mixed-use watershed in central Missouri, USA. Results for the climate change only scenario showed annual streamflow and runoff decreases (-10.7% and -9.2%) and evapotranspiration increases (+6.8%), while results from the urbanization only scenario showed streamflow and runoff increases (+3.8% and +9.3%) and evapotranspiration decreases (-2.4%). Results for the combined impacts scenario suggested that climatic changes could have a larger impact than urbanization on annual streamflow, (overall decrease of -6.1%), and could largely negate surface runoff increases caused by urbanization. For the same scenario, climatic changes exerted a stronger influence on annual evapotranspiration than urbanization (+3.9%). Seasonal results indicated that the relative influences of urbanization and climatic changes vary seasonally. Climatic changes most greatly influenced streamflow and runoff during winter and summer, and evapotranspiration during summer. During some seasons the directional change for hydrologic processes matched for both stressors. This work presented a practicable approach for investigating the relative influences of mid-21st century urbanization and climatic changes on the hydrology of a representative mixed-use watershed, adding to a limited body of research on this topic. This was done using a transferrable approach that can be adapted for watersheds in other regions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative risk assessment of the burden of disease from climate change.

PubMed

Campbell-Lendrum, Diarmid; Woodruff, Rosalie

2006-12-01

The World Health Organization has developed standardized comparative risk assessment methods for estimating aggregate disease burdens attributable to different risk factors. These have been applied to existing and new models for a range of climate-sensitive diseases in order to estimate the effect of global climate change on current disease burdens and likely proportional changes in the future. The comparative risk assessment approach has been used to assess the health consequences of climate change worldwide, to inform decisions on mitigating greenhouse gas emissions, and in a regional assessment of the Oceania region in the Pacific Ocean to provide more location-specific information relevant to local mitigation and adaptation decisions. The approach places climate change within the same criteria for epidemiologic assessment as other health risks and accounts for the size of the burden of climate-sensitive diseases rather than just proportional change, which highlights the importance of small proportional changes in diseases such as diarrhea and malnutrition that cause a large burden. These exercises help clarify important knowledge gaps such as a relatively poor understanding of the role of nonclimatic factors (socioeconomic and other) that may modify future climatic influences and a lack of empiric evidence and methods for quantifying more complex climate-health relationships, which consequently are often excluded from consideration. These exercises highlight the need for risk assessment frameworks that make the best use of traditional epidemiologic methods and that also fully consider the specific characteristics of climate change. These include the longterm and uncertain nature of the exposure and the effects on multiple physical and biotic systems that have the potential for diverse and widespread effects, including high-impact events.

Projected impacts of climate change on habitat availability for an endangered parakeet.

PubMed

Hermes, Claudia; Keller, Klaus; Nicholas, Robert E; Segelbacher, Gernot; Schaefer, H Martin

2018-01-01

In tropical montane cloud forests, climate change can cause upslope shifts in the distribution ranges of species, leading to reductions in distributional range. Endemic species with small ranges are particularly vulnerable to such decreases in range size, as the population size may be reduced significantly. To ensure the survival of cloud forest species in the long term, it is crucial to quantify potential future shifts in their distribution ranges and the related changes in habitat availability in order to assure the long-term effectiveness of conservation measures. In this study, we assessed the influence of climate change on the availability of forested habitat for the endemic El Oro parakeet. We investigated the future range shift by modelling the climatic niche of the El Oro parakeets and projecting it to four different climate change scenarios. Depending on the intensity of climate change, the El Oro parakeets shift their range between 500 and 1700 m uphill by the year 2100. On average, the shift is accompanied by a reduction in range size to 15% and a reduction in forested habitat to only 10% of the original extent. Additionally, the connectivity between populations in different areas is decreasing in higher altitudes. To prevent a population decline due to habitat loss following an upslope range shift, it will be necessary to restore habitat across a large elevational span in order to allow for movement of El Oro parakeets into higher altitudes.

Projected increases in the annual flood pulse of the Western Amazon

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Manz, Bastian; Véliz Rosas, Claudia; Willems, Patrick; Lavado-Casimiro, Waldo; Guyot, Jean-Loup; Santini, William

2016-01-01

The impact of a changing climate on the Amazon basin is a subject of intensive research because of its rich biodiversity and the significant role of rainforests in carbon cycling. Climate change has also a direct hydrological impact, and increasing efforts have focused on understanding the hydrological dynamics at continental and subregional scales, such as the Western Amazon. New projections from the Coupled Model Inter-comparison Project Phase 5 ensemble indicate consistent climatic warming and increasing seasonality of precipitation in the Peruvian Amazon basin. Here we use a distributed land surface model to quantify the potential impact of this change in the climate on the hydrological regime of the upper Amazon river. Using extreme value analysis, historical and future projections of the annual minimum, mean, and maximum river flows are produced for a range of return periods between 1 and 100 yr. We show that the RCP 4.5 and 8.5 scenarios of climate change project an increased severity of the wet season flood pulse (7.5% and 12% increases respectively for the 100 yr return floods). These findings agree with previously projected increases in high extremes under the Special Report on Emissions Scenarios climate projections, and are important to highlight due to the potential consequences on reproductive processes of in-stream species, swamp forest ecology, and socio-economy in the floodplain, amidst a growing literature that more strongly emphasises future droughts and their impact on the viability of the rainforest system over greater Amazonia.

Projected impacts of climate change on habitat availability for an endangered parakeet

PubMed Central

Keller, Klaus; Nicholas, Robert E.; Segelbacher, Gernot; Schaefer, H. Martin

2018-01-01

In tropical montane cloud forests, climate change can cause upslope shifts in the distribution ranges of species, leading to reductions in distributional range. Endemic species with small ranges are particularly vulnerable to such decreases in range size, as the population size may be reduced significantly. To ensure the survival of cloud forest species in the long term, it is crucial to quantify potential future shifts in their distribution ranges and the related changes in habitat availability in order to assure the long-term effectiveness of conservation measures. In this study, we assessed the influence of climate change on the availability of forested habitat for the endemic El Oro parakeet. We investigated the future range shift by modelling the climatic niche of the El Oro parakeets and projecting it to four different climate change scenarios. Depending on the intensity of climate change, the El Oro parakeets shift their range between 500 and 1700 m uphill by the year 2100. On average, the shift is accompanied by a reduction in range size to 15% and a reduction in forested habitat to only 10% of the original extent. Additionally, the connectivity between populations in different areas is decreasing in higher altitudes. To prevent a population decline due to habitat loss following an upslope range shift, it will be necessary to restore habitat across a large elevational span in order to allow for movement of El Oro parakeets into higher altitudes. PMID:29364949

Future Flood Inundation and Damages from Storm Surge in the Coast of Virginia and Maryland with Projected Climate Change and Sea Level Rise Scenarios

NASA Astrophysics Data System (ADS)

Rezaie, A. M.; Ferreira, C.; Walls, M. A.

2016-12-01

The recurrent flood risks on coastal areas in the United States (US) due to hurricane wind and storm surge are likely to rise with warmer climate, frequent storms, and increasing coastal population. Recent studies suggested that the global financial losses from hurricanes will be doubled by 2100 due to combined impact of climate change, sea level rise (SLR) and intensified hurricanes. While the predicted average SLR for the Mid-Atlantic region of the US is 2.2 meter, some coastal areas in Virginia (VA) and Maryland (MD) are expected to experience a 0.7 to 1.6m and 0.6 to 1.7m SLR respectively. Nearly 80 percent of the total $5.3 billion property damage by Hurricane Isabel in 2003 was within VA and MD. In order to provide a quantitative assessment of the future flooding and associated damages for projected climate change and SLR scenarios, this study integrated state-of-the-art coastal numerical model ADCIRC with a careful economic valuation exercise of flood damages. The study area covers the entire coastal zone of VA and MD focusing on regions that are in the vicinity of the Chesapeake Bay and the Atlantic Ocean with high susceptibility to storm surge and flooding. Multiple climate change land cover scenarios generated by the United States Geological Survey (USGS) under a series of the IPCC's Emissions Scenarios are incorporated in the modeling approach to integrate climate change whereas local SLR projections are included to provide the regional aspects of future risks. Preliminary results for hurricane Isabel (2003) shows that a 2.3m rise in sea level can cause storm surges rising up to 3-4m in the coastal areas. While a 0.5m SLR makes the range 1-2.5m in the affected areas. It is also seen that higher increase in the sea level not only causes higher range of inundation but a greater extent of flood as well. The projected inland flooding extents are highest for the SRES A2 Scenario. Alongside an estimate of future loss and damage will be prepared to assist in future planning for the coastal areas near the Chesapeake Bay regions and finally progressing in developing a climate resilient coast. Furthermore the estimated damages will be applied to quantify the functionality and benefits of natural and nature-based features for coastal defense for future changes in climate and development.

Global Carbon Project: the Global Carbon Budget 2015 (V.1.0., issued Nov. 2015 and V.1.1, issued Dec. 2015)

DOE Data Explorer

Le Quere, C. [University of East Anglia, Norwich UK; Moriarty, R. [University of East Anglia, Norwich UK; Andrew, R. M. [Univ. of Oslo (Norway); Canadell, J. G. [Commonwealth Scientific and Industrial Research Organization (CSIRO) Oceans and Atmosphere, Canberra ACT (Australia); Sitch, S. [University of Exeter, Exter UK; Boden, T. A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States) Carbon Dioxide Information Analysis Center (CDIAC); al., et

2015-01-01

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations.

Future scenarios of impacts to ecosystem services on California rangelands

USGS Publications Warehouse

Byrd, Kristin; Alvarez, Pelayo; Flint, Lorraine; Flint, Alan

2014-01-01

The 18 million acres of rangelands in the Central Valley of California provide multiple benefits or “ecosystem services” to people—including wildlife habitat, water supply, open space, recreation, and cultural resources. Most of this land is privately owned and managed for livestock production. These rangelands are vulnerable to land-use conversion and climate change. To help resource managers assess the impacts of land-use change and climate change, U.S. Geological Survey scientists and their cooperators developed scenarios to quantify and map changes to three main rangeland ecosystem services—wildlife habitat, water supply, and carbon sequestration. Project results will help prioritize strategies to conserve these rangelands and the ecosystem services that they provide.

Impact of climate change on irrigation management for olive orchards at southern Spain

NASA Astrophysics Data System (ADS)

Lorite, Ignacio; Gabaldón-Leal, Clara; Santos, Cristina; Belaj, Angjelina; de la Rosa, Raul; Leon, Lorenzo; Ruiz-Ramos, Margarita

2017-04-01

The irrigation management for olive orchards under future weather conditions requires the development of advanced tools for considering specific physiological and phenological components affected by the foreseen changes in climate and atmospheric [CO2]. In this study a new simulation model named AdaptaOlive has been considered to develop controlled deficit irrigation and full irrigation scheduling for the traditional olive orchards located in Andalusia region (southern Spain) under the projected climate generated by an ensemble of 11 climate models from the ENSEMBLES European project corresponding to the SRES A1B scenario. Irrigation requirements, irrigation water productivity (IWP) and net margin (NM) were evaluated for three periods (baseline, near future and far future) and three irrigation strategies (rainfed, RF, controlled deficit irrigation, CDI, and full irrigation, FI). For irrigation requirements, a very limited average increase for far future compared with baseline period was found (2.6 and 1.3%, for CDI and FI, respectively). Equally, when IWP was analyzed, significant increases were identified for both irrigation strategies (77.4 and 72.2%, for CDI and FI, respectively) due to the high simulated increase in yield. Finally, when net margin was analyzed, the irrigation water cost had a key significance. For low water costs FI provided higher net margin values than for CDI. However, for high water costs (expected in the future due to the foreseen reduction in rainfall and the increase of the competence for the available water resources), net margin is reduced significantly, generating a very elevated number of years with negative net margin. All the described results are affected by a high level of uncertainty as the projections from the ensemble of 11 climate models show large spread. Thus, for a representative location within Andalusia region as Baeza, a reduction of irrigation requirements under full irrigation strategy was found for the ensemble mean (equal to 0.5%). However, when the individual projections from the 11 climate models were considered the variation of irrigation requirements for far future compared with baseline period ranged from increases of 8.5% to reductions of 10.7%. This fact demonstrates the necessity to consider ensembles of climate models for identifying averaged impacts and the range of variability of these impacts, quantifying the uncertainty in the estimates related with water management in the future. The study concludes that the promotion of controlled deficit irrigation strategies is an excellent adaptation strategy. However, this strategy must be supported with the enhance of farmers' training by the implementation of local or regional irrigation advisory services.

Quantifying the potential for reservoirs to secure future surface water yields in the world’s largest river basins

NASA Astrophysics Data System (ADS)

Liu, Lu; Parkinson, Simon; Gidden, Matthew; Byers, Edward; Satoh, Yusuke; Riahi, Keywan; Forman, Barton

2018-04-01

Surface water reservoirs provide us with reliable water supply, hydropower generation, flood control and recreation services. Yet reservoirs also cause flow fragmentation in rivers and lead to flooding of upstream areas, thereby displacing existing land-use activities and ecosystems. Anticipated population growth and development coupled with climate change in many regions of the globe suggests a critical need to assess the potential for future reservoir capacity to help balance rising water demands with long-term water availability. Here, we assess the potential of large-scale reservoirs to provide reliable surface water yields while also considering environmental flows within 235 of the world’s largest river basins. Maps of existing cropland and habitat conservation zones are integrated with spatially-explicit population and urbanization projections from the Shared Socioeconomic Pathways to identify regions unsuitable for increasing water supply by exploiting new reservoir storage. Results show that even when maximizing the global reservoir storage to its potential limit (∼4.3–4.8 times the current capacity), firm yields would only increase by about 50% over current levels. However, there exist large disparities across different basins. The majority of river basins in North America are found to gain relatively little firm yield by increasing storage capacity, whereas basins in Southeast Asia display greater potential for expansion as well as proportional gains in firm yield under multiple uncertainties. Parts of Europe, the United States and South America show relatively low reliability of maintaining current firm yields under future climate change, whereas most of Asia and higher latitude regions display comparatively high reliability. Findings from this study highlight the importance of incorporating different factors, including human development, land-use activities, and climate change, over a time span of multiple decades and across a range of different scenarios when quantifying available surface water yields and the potential for reservoir expansion.

Mapping the impact of climate change on surface recession of carbonate buildings in Europe.

PubMed

Bonazza, Alessandra; Messina, Palmira; Sabbioni, Cristina; Grossi, Carlota M; Brimblecombe, Peter

2009-03-01

Climate change is currently attracting interest at both research and policy levels. However, it is usually explored in terms of its effect on agriculture, water, industry, energy, transport and health and as yet has been insufficiently addressed as a factor threatening cultural heritage. Among the climate parameters critical to heritage conservation and expected to change in the future, precipitation plays an important role in surface recession of stone. The Lipfert function has been taken under consideration to quantify the annual surface recession of carbonate stone, due to the effects of clean rain, acid rain and dry deposition of pollutants. The present paper provides Europe-wide maps showing quantitative predictions of surface recession on carbonate stones for the 21st century, combining a modified Lipfert function with output from the Hadley global climate model. Chemical dissolution of carbonate stones, via the karst effect, will increase with future CO(2) concentrations, and will come to dominate over sulfur deposition and acid rain effects on monuments and buildings in both urban and rural areas. During the present century the rainfall contribution to surface recession is likely to have a small effect, while the increase in atmospheric CO(2) concentration is shown to be the main factor in increasing weathering via the karst effect.

Quantifying the effects of climate and post-fire landscape change on hydrologic processes

NASA Astrophysics Data System (ADS)

Steimke, A.; Han, B.; Brandt, J.; Som Castellano, R.; Leonard, A.; Flores, A. N.

2016-12-01

Seasonally snow-dominated, forested mountain watersheds supply water to many human populations globally. However, the timing and magnitude of water delivery from these watersheds has already and will continue to change as the climate warms. Changes in vegetation also affect the runoff response of watersheds. The largest driver of vegetation change in many mountainous regions is wildfire, whose occurrence is affected by both climate and land management decisions. Here, we quantify how direct (i.e. changes in precipitation and temperature) and indirect (i.e. changing fire regimes) effects of climate change influence hydrologic parameters such as dates of peak streamflow, annual discharge, and snowpack levels. We used the Boise River Basin, ID as a model laboratory to calculate the relative magnitude of change stemming from direct and indirect effects of climate change. This basin is relevant to study as it is well-instrumented and major drainages have experienced burning at different spatial and temporal intervals, aiding in model calibration. We built a hydrology-based integrated model of the region using a multiagent simulation framework, Envision. We used a modified HBV (Hydrologiska Byråns Vattenbalansavdelning) rainfall-runoff model and calibrated it to historic streamflow and snowpack observations. We combined a diverse set of climate projections with wildfire scenarios (low vs. high) representing two distinct intervals in the regional historic fire record. In fire simulations, we altered land cover coefficients to reflect a burned state post-fire, which decreased overall evapotranspiration rates and increased water yields. However, direct climate effects had a larger signal on annual variations of hydrologic parameters. By comparing and analyzing scenario outputs, we identified links and sensitivities between land cover and regional hydrology in the context of a changing climate, with potential implications for local land and water managers. In future research, this framework will support investigations of climate-aware land management actions on basin hydrologic response.

An integrated framework for assessing vulnerability to climate change and developing adaptation strategies for coffee growing families in Mesoamerica.

PubMed

Baca, María; Läderach, Peter; Haggar, Jeremy; Schroth, Götz; Ovalle, Oriana

2014-01-01

The Mesoamerican region is considered to be one of the areas in the world most vulnerable to climate change. We developed a framework for quantifying the vulnerability of the livelihoods of coffee growers in Mesoamerica at regional and local levels and identify adaptation strategies. Following the Intergovernmental Panel on Climate Change (IPCC) concepts, vulnerability was defined as the combination of exposure, sensitivity and adaptive capacity. To quantify exposure, changes in the climatic suitability for coffee and other crops were predicted through niche modelling based on historical climate data and locations of coffee growing areas from Mexico, Guatemala, El Salvador and Nicaragua. Future climate projections were generated from 19 Global Circulation Models. Focus groups were used to identify nine indicators of sensitivity and eleven indicators of adaptive capacity, which were evaluated through semi-structured interviews with 558 coffee producers. Exposure, sensitivity and adaptive capacity were then condensed into an index of vulnerability, and adaptation strategies were identified in participatory workshops. Models predict that all target countries will experience a decrease in climatic suitability for growing Arabica coffee, with highest suitability loss for El Salvador and lowest loss for Mexico. High vulnerability resulted from loss in climatic suitability for coffee production and high sensitivity through variability of yields and out-migration of the work force. This was combined with low adaptation capacity as evidenced by poor post harvest infrastructure and in some cases poor access to credit and low levels of social organization. Nevertheless, the specific contributors to vulnerability varied strongly among countries, municipalities and families making general trends difficult to identify. Flexible strategies for adaption are therefore needed. Families need the support of government and institutions specialized in impacts of climate change and strengthening of farmer organizations to enable the adjustment of adaptation strategies to local needs and conditions.

An Integrated Framework for Assessing Vulnerability to Climate Change and Developing Adaptation Strategies for Coffee Growing Families in Mesoamerica

PubMed Central

Baca, María; Läderach, Peter; Haggar, Jeremy; Schroth, Götz; Ovalle, Oriana

2014-01-01

The Mesoamerican region is considered to be one of the areas in the world most vulnerable to climate change. We developed a framework for quantifying the vulnerability of the livelihoods of coffee growers in Mesoamerica at regional and local levels and identify adaptation strategies. Following the Intergovernmental Panel on Climate Change (IPCC) concepts, vulnerability was defined as the combination of exposure, sensitivity and adaptive capacity. To quantify exposure, changes in the climatic suitability for coffee and other crops were predicted through niche modelling based on historical climate data and locations of coffee growing areas from Mexico, Guatemala, El Salvador and Nicaragua. Future climate projections were generated from 19 Global Circulation Models. Focus groups were used to identify nine indicators of sensitivity and eleven indicators of adaptive capacity, which were evaluated through semi-structured interviews with 558 coffee producers. Exposure, sensitivity and adaptive capacity were then condensed into an index of vulnerability, and adaptation strategies were identified in participatory workshops. Models predict that all target countries will experience a decrease in climatic suitability for growing Arabica coffee, with highest suitability loss for El Salvador and lowest loss for Mexico. High vulnerability resulted from loss in climatic suitability for coffee production and high sensitivity through variability of yields and out-migration of the work force. This was combined with low adaptation capacity as evidenced by poor post harvest infrastructure and in some cases poor access to credit and low levels of social organization. Nevertheless, the specific contributors to vulnerability varied strongly among countries, municipalities and families making general trends difficult to identify. Flexible strategies for adaption are therefore needed. Families need the support of government and institutions specialized in impacts of climate change and strengthening of farmer organizations to enable the adjustment of adaptation strategies to local needs and conditions. PMID:24586328

Climate Sensitivity in the Anthropocene

NASA Technical Reports Server (NTRS)

Previdi, M.; Liepert, B. G.; Peteet, Dorothy M.; Hansen, J.; Beerling, D. J.; Broccoli, A. J.; Frolking, S.; Galloway, J. N.; Heimann, M.; LeQuere, C.;

Quantifying Vulnerability to Extreme Heat in Time Series Analyses: A Novel Approach Applied to Neighborhood Social Disparities under Climate Change

PubMed Central

Benmarhnia, Tarik; Grenier, Patrick; Brand, Allan; Fournier, Michel; Deguen, Séverine; Smargiassi, Audrey

2015-01-01

Objectives: We propose a novel approach to examine vulnerability in the relationship between heat and years of life lost and apply to neighborhood social disparities in Montreal and Paris. Methods: We used historical data from the summers of 1990 through 2007 for Montreal and from 2004 through 2009 for Paris to estimate daily years of life lost social disparities (DYLLD), summarizing social inequalities across groups. We used Generalized Linear Models to separately estimate relative risks (RR) for DYLLD in association with daily mean temperatures in both cities. We used 30 climate scenarios of daily mean temperature to estimate future temperature distributions (2021–2050). We performed random effect meta-analyses to assess the impact of climate change by climate scenario for each city and compared the impact of climate change for the two cities using a meta-regression analysis. Results: We show that an increase in ambient temperature leads to an increase in social disparities in daily years of life lost. The impact of climate change on DYLLD attributable to temperature was of 2.06 (95% CI: 1.90, 2.25) in Montreal and 1.77 (95% CI: 1.61, 1.94) in Paris. The city explained a difference of 0.31 (95% CI: 0.14, 0.49) on the impact of climate change. Conclusion: We propose a new analytical approach for estimating vulnerability in the relationship between heat and health. Our results suggest that in Paris and Montreal, health disparities related to heat impacts exist today and will increase in the future. PMID:26402690

Representing agriculture in Earth System Models: Approaches and priorities for development

NASA Astrophysics Data System (ADS)

McDermid, S. S.; Mearns, L. O.; Ruane, A. C.

2017-09-01

Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Last, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

Climate-change-induced range shifts of three allergenic ragweeds (Ambrosia L.) in Europe and their potential impact on human health.

PubMed

Rasmussen, Karen; Thyrring, Jakob; Muscarella, Robert; Borchsenius, Finn

2017-01-01

Invasive allergenic plant species may have severe health-related impacts. In this study we aim to predict the effects of climate change on the distribution of three allergenic ragweed species ( Ambrosia spp.) in Europe and discuss the potential associated health impact. We built species distribution models based on presence-only data for three ragweed species, using MAXENT software. Future climatic habitat suitability was modeled under two IPCC climate change scenarios (RCP 6.0 and RCP 8.5). We quantify the extent of the increase in 'high allergy risk' (HAR) areas, i.e., parts of Europe with climatic conditions corresponding to the highest quartile (25%) of present day habitat suitability for each of the three species. We estimate that by year 2100, the distribution range of all three ragweed species increases towards Northern and Eastern Europe under all climate scenarios. HAR areas will expand in Europe by 27-100%, depending on species and climate scenario. Novel HAR areas will occur mostly in Denmark, France, Germany, Russia and the Baltic countries, and overlap with densely populated cities such as Paris and St. Petersburg. We conclude that areas in Europe affected by severe ragweed associated allergy problems are likely to increase substantially by year 2100, affecting millions of people. To avoid this, management strategies must be developed that restrict ragweed dispersal and establishment of new populations. Precautionary efforts should limit the spread of ragweed seeds and reduce existing populations. Only by applying cross-countries management plans can managers mitigate future health risks and economical consequences of a ragweed expansion in Europe.

Quantifying Vulnerability to Extreme Heat in Time Series Analyses: A Novel Approach Applied to Neighborhood Social Disparities under Climate Change.

PubMed

Benmarhnia, Tarik; Grenier, Patrick; Brand, Allan; Fournier, Michel; Deguen, Séverine; Smargiassi, Audrey

2015-09-22

We propose a novel approach to examine vulnerability in the relationship between heat and years of life lost and apply to neighborhood social disparities in Montreal and Paris. We used historical data from the summers of 1990 through 2007 for Montreal and from 2004 through 2009 for Paris to estimate daily years of life lost social disparities (DYLLD), summarizing social inequalities across groups. We used Generalized Linear Models to separately estimate relative risks (RR) for DYLLD in association with daily mean temperatures in both cities. We used 30 climate scenarios of daily mean temperature to estimate future temperature distributions (2021-2050). We performed random effect meta-analyses to assess the impact of climate change by climate scenario for each city and compared the impact of climate change for the two cities using a meta-regression analysis. We show that an increase in ambient temperature leads to an increase in social disparities in daily years of life lost. The impact of climate change on DYLLD attributable to temperature was of 2.06 (95% CI: 1.90, 2.25) in Montreal and 1.77 (95% CI: 1.61, 1.94) in Paris. The city explained a difference of 0.31 (95% CI: 0.14, 0.49) on the impact of climate change. We propose a new analytical approach for estimating vulnerability in the relationship between heat and health. Our results suggest that in Paris and Montreal, health disparities related to heat impacts exist today and will increase in the future.

The Use of Cover Crops as Climate-Smart Management in Midwest Cropping Systems

NASA Astrophysics Data System (ADS)

Basche, A.; Miguez, F.; Archontoulis, S.; Kaspar, T.

2014-12-01

The observed trends in the Midwestern United States of increasing rainfall variability will likely continue into the future. Events such as individual days of heavy rain as well as seasons of floods and droughts have large impacts on agricultural productivity and the natural resource base that underpins it. Such events lead to increased soil erosion, decreased water quality and reduced corn and soybean yields. Winter cover crops offer the potential to buffer many of these impacts because they essentially double the time for a living plant to protect and improve the soil. However, at present, cover crops are infrequently utilized in the Midwest (representing 1-2% of row cropped land cover) in particular due to producer concerns over higher costs and management, limited time and winter growing conditions as well as the potential harm to corn yields. In order to expand their use, there is a need to quantify how cover crops impact Midwest cropping systems in the long term and namely to understand how to optimize the benefits of cover crops while minimizing their impacts on cash crops. We are working with APSIM, a cropping systems platform, to specifically quantify the long term future impacts of cover crop incorporation in corn-based cropping systems. In general, our regional analysis showed only minor changes to corn and soybean yields (<1% differences) when a cover crop was or was not included in the simulation. Further, a "bad spring" scenario (where every third year had an abnormally wet/cold spring and cover crop termination and planting cash crop were within one day) did not result in any major changes to cash crop yields. Through simulations we estimate an average increase of 4-9% organic matter improvement in the topsoil and an average decrease in soil erosion of 14-32% depending on cover crop planting date and growth. Our work is part of the Climate and Corn-based Cropping Systems Coordinated Agriculture Project (CSCAP), a collaboration of eleven Midwestern institutions established to evaluate how conservation practices, including cover crops, improve the resilience of Midwest agriculture to future change. Such collaborations can help better quantify long term impacts of conservation practices on the landscape that ultimately lead to more climate-smart management of such agricultural systems.

Validation and quantification of uncertainty in coupled climate models using network analysis

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

Bracco, Annalisa

We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies.more » At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) have then been determined. The network of models capable of reproducing well major climate modes in the recent past, changes little during this century. In contrast, among those models the uncertainties in the projections after 2100 remain substantial, and primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation (ENSO), and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. Additionally, we evaluated the relation between the size and the ‘strength’ of the area identified by the network analysis as corresponding to ENSO noting that only a small subset of models can reproduce realistically the observations.« less

Possible future changes in extreme events over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Scott, Jeffery

2013-04-01

In this study, we investigate possible future climate change over Northern Eurasia and its impact on extreme events. Northern Eurasia is a major player in the global carbon budget because of boreal forests and peatlands. Circumpolar boreal forests alone contain more than five times the amount of carbon of temperate forests and almost double the amount of carbon of the world's tropical forests. Furthermore, severe permafrost degradation associated with climate change could result in peatlands releasing large amounts of carbon dioxide and methane. Meanwhile, changes in the frequency and magnitude of extreme events, such as extreme precipitation, heat waves or frost days are likely to have substantial impacts on Northern Eurasia ecosystems. For this reason, it is very important to quantify the possible climate change over Northern Eurasia under different emissions scenarios, while accounting for the uncertainty in the climate response and changes in extreme events. For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. In this study, regional change is investigated using the MIT IGSM-CAM framework that links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). New modules were developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM. The simulations presented in this paper were carried out for two emission scenarios, a "business as usual" scenario and a 660 ppm of CO2-equivalent stabilization, which are similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios. Values of climate sensitivity and net aerosol forcing used in the simulations within the IGSM-CAM framework provide a good approximation for the median, and the lower and upper bound of 90% probability distribution of 21st century climate change. Five member ensembles were carried out for each choice of parameters using different initial conditions. With these simulations, we investigate the role of emissions scenarios (climate policies), the global climate response (climate sensitivity) and natural variability (initial conditions) on the uncertainty in future climate changes over Northern Eurasia. A particular emphasis is made on future changes in extreme events, including frost days, extreme summer temperature and extreme summer and winter precipitation.

Assessing coastal flood risk and sea level rise impacts at New York City area airports

NASA Astrophysics Data System (ADS)

Ohman, K. A.; Kimball, N.; Osler, M.; Eberbach, S.

2014-12-01

Flood risk and sea level rise impacts were assessed for the Port Authority of New York and New Jersey (PANYNJ) at four airports in the New York City area. These airports included John F. Kennedy International, LaGuardia, Newark International, and Teterboro Airports. Quantifying both present day and future flood risk due to climate change and developing flood mitigation alternatives is crucial for the continued operation of these airports. During Hurricane Sandy in October 2012 all four airports were forced to shut down, in part due to coastal flooding. Future climate change and sea level rise effects may result in more frequent shutdowns and disruptions in travel to and from these busy airports. The study examined the effects of the 1%-annual-chance coastal flooding event for present day existing conditions and six different sea level rise scenarios at each airport. Storm surge model outputs from the Federal Emergency Management Agency (FEMA) provided the present day storm surge conditions. 50th and 90thpercentile sea level rise projections from the New York Panel on Climate Change (NPCC) 2013 report were incorporated into storm surge results using linear superposition methods. These projections were evaluated for future years 2025, 2035, and 2055. In addition to the linear superposition approach for storm surge at airports where waves are a potential hazard, one dimensional wave modeling was performed to get the total water level results. Flood hazard and flood depth maps were created based on these results. In addition to assessing overall flooding at each airport, major at-risk infrastructure critical to the continued operation of the airport was identified and a detailed flood vulnerability assessment was performed. This assessment quantified flood impacts in terms of potential critical infrastructure inundation and developed mitigation alternatives to adapt to coastal flooding and future sea level changes. Results from this project are advancing the PANYNJ's understanding of the effects of sea level rise on coastal flooding at the airports and guiding decision-making in the selection of effective adaptation actions. Given the importance of these airports to transportation, this project is advancing security and continuity of national and international commerce well into the 21st century.

Synergistic effects of drought and fire on the carbon carrying capacity of tropical forests and woodlands

NASA Astrophysics Data System (ADS)

Boer, Matthias; Bradstock, Ross

2014-05-01

More than half of the global forest carbon stock is held in tropical forests. A relatively large proportion of the tropical forest carbon is stored in plant biomass rather than in the soil, making these stocks particularly vulnerable to disturbances such as droughts, fires and cyclones. The frequencies, duration and intensities of such disturbances may change under future climates with poorly resolved but potentially significant (synergistic) effects on the carbon carrying capacity of tropical forests and thereby on global geochemical cycles. In this study we analyse high-resolution global data sets for tropical forest biomass (Saatchi et al., 2011. PNAS) and fire affected areas (GFED4, Giglio et al.,2013. JGR 118), together with climate data (WorldClim, Hijmans et al., 2005. Int. J. Clim. 25), to quantify the sensitivity of tropical forest carbon stocks in South America, Africa and Asia/Australia to seasonal water deficits and fire. Here, the climatic water deficit (D), calculated as the difference between mean annual potential evapotranspiration and actual evapotranspiration, is used as a measure of seasonal water stress (i.e., evaporative demand not met by available water), while the mean annual burned area fraction (1995-2013) of grid cells is used as a measure of average fire activity. Tropical forest carbon stocks are maximal, as expected, where water deficits are negligible. In those densely forested environments fire tends to be extremely rare as fuels are too wet to burn for most of the time. In all three continents, potential tropical forest carbon stocks are well predicted by a non-linear decreasing function of the mean annual climatic water deficit, with a steep drop in carbon stocks at D of 700-800 mm per year. At this threshold in the climatic water deficit we observe a strong increase in fire activity that is indicative of a critical change in vegetation structure (i.e., tree/grass ratio) and associated shift in the dominant climatic constraint on fire activity from fuel dryness to fuel productivity. By comparing predictions of potential forest carbon stocks (i.e., as a function of D only) with actual carbon stocks, we quantify the sensitivity of those stocks to increasing fire activity. Finally, we map the risk of losses in carbon carrying capacity of tropical forests under scenarios of future climate.

Contrasting Climate Change Impact on River Flow from Glacierised Catchments in the Himalayan and Andes Mountains

NASA Astrophysics Data System (ADS)

Pellicciotti, F.; Ragettli, S.; Immerzeel, W. W. W.

2016-12-01

Glaciers and glacierised catchments in mountainous regions react to a changing climate in different manners depending on climate and glacier characteristics. Despite the key role of mountain ranges as natural water towers, their hydrological balance and future changes in glacier runoff associated with climate warming remain poorly understood because of high meteorological variability, physical inaccessibility and the complex interplay between climate, cryosphere and hydrological processes. We use a state-of-the art glacio-hydrological model informed by data from high altitude observations and the latest CMIP5 climate change scenarios to quantify the climate change impact on glaciers and runoff for two contrasting catchments vulnerable to changes in the cryosphere. The two catchments are located in the Central Andes of Chile and in the Nepalese Himalaya in close vicinity of densely populated areas. Although both sites are projected to experience a strong decrease in glacier area, they show remarkably different hydrological responses. Icemelt is on a rising limb in Langtang at least until 2041-2050 and starts to decrease afterwards, while in Juncal icemelt was already beyond its tipping point at the beginning of the 21st century. This contrasting response can be explained by differences in the elevation distribution of the glaciers in the two regions. In Juncal, many glaciers are melting up to the highest elevations already during the reference period (2000-2010) and increasing melt rates due to higher air temperatures cannot compensate the loss of glacier area. In Langtang, large sections of the glaciers at high elevations are currently not exposed to melt, but will be in the future, thus compensating for the loss of glacier area at lower elevations. As a result of these changes and projected changes in precipitation, in Juncal runoff will sharply decrease in the future and the runoff seasonality is sensitive to projected climatic changes. In Langtang, future water availability is on the rise for decades to come with limited shifts between seasons but increases in extreme events. Climate change adaptation in the Andes of Central Chile should thus focus on dealing with a reduction in water availability from the glacierised catchments, whereas in Nepal preparedness for flood extremes should be the policy priority.

Future productivity and phenology changes in European grasslands for different warming levels: implications for grassland management and carbon balance.

PubMed

Chang, Jinfeng; Ciais, Philippe; Viovy, Nicolas; Soussana, Jean-François; Klumpp, Katja; Sultan, Benjamin

2017-12-01

Europe has warmed more than the global average (land and ocean) since pre-industrial times, and is also projected to continue to warm faster than the global average in the twenty-first century. According to the climate models ensemble projections for various climate scenarios, annual mean temperature of Europe for 2071-2100 is predicted to be 1-5.5 °C higher than that for 1971-2000. Climate change and elevated CO 2 concentration are anticipated to affect grassland management and livestock production in Europe. However, there has been little work done to quantify the European-wide response of grassland to future climate change. Here we applied ORCHIDEE-GM v2.2, a grid-based model for managed grassland, over European grassland to estimate the impacts of future global change. Increases in grassland productivity are simulated in response to future global change, which are mainly attributed to the simulated fertilization effect of rising CO 2 . The results show significant phenology shifts, in particular an earlier winter-spring onset of grass growth over Europe. A longer growing season is projected over southern and southeastern Europe. In other regions, summer drought causes an earlier end to the growing season, overall reducing growing season length. Future global change allows an increase of management intensity with higher than current potential annual grass forage yield, grazing capacity and livestock density, and a shift in seasonal grazing capacity. We found a continual grassland soil carbon sink in Mediterranean, Alpine, North eastern, South eastern and Eastern regions under specific warming level (SWL) of 1.5 and 2 °C relative to pre-industrial climate. However, this carbon sink is found to saturate, and gradually turn to a carbon source at warming level reaching 3.5 °C. This study provides a European-wide assessment of the future changes in productivity and phenology of grassland, and their consequences for the management intensity and the carbon balance. The simulated productivity increase in response to future global change enables an intensification of grassland management over Europe. However, the simulated increase in the interannual variability of grassland productivity over some regions may reduce the farmers' ability to take advantage of the increased long-term mean productivity in the face of more frequent, and more severe drops of productivity in the future.

Scaling future tropical cyclone damage with global mean temperature

NASA Astrophysics Data System (ADS)

Geiger, T.; Bresch, D.; Frieler, K.

2017-12-01

Tropical cyclones (TC) are one of the most damaging natural hazards and severely affectmany countries around the globe each year. Their nominal impact is projected to increasesubstantially as the exposed coastal population grows, per capita income increases, andanthropogenic climate change manifests. The magnitude of this increase, however, variesacross regions and is obscured by the stochastic behaviour of TCs, so far impeding arigorous quantification of trends in TC damage with global mean temperature (GMT) rise. Here, we build on the large sample of spatially explicit TCs simulations generated withinISIMIP(2b) for 1) pre-industrial conditions, 2) the historical period, and 3) future projectionsunder RCP2.6 and RCP6.0 to estimate future TC damage assuming fixed present-daysocio-economic conditions or SSP-based future projections of population patterns andincome. Damage estimates will be based on region-specific empirical damage modelsderived from reported damages and accounting for regional characteristics of vulnerability.Different combinations of 1) socio-economic drivers with pre-industrial climate or 2) changingclimate with fixed socio-economic conditions will be used to derive functional relationshipsbetween regionally aggregated changes in damages on one hand and global meantemperature and socio-economic predictors on the other hand. The obtained region-specific scaling of future TC damage with GMT provides valuable inputfor IPCC's special report on the impacts of global warming of 1.5°C by quantifying theincremental changes in impact with global warming. The approach allows for an update ofdamage functions used in integrated assessment models, and contributes to assessing theadequateness of climate mitigation and adaptation strategies.

Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative

NASA Astrophysics Data System (ADS)

Frank, Dorothea; Reichstein, Markus

2017-04-01

The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.

The pace of past climate change vs. potential bird distributions and land use in the United States

USGS Publications Warehouse

Bateman, Brooke L.; Pidgeon, Anna M.; Radeloff, Volker C.; VanDerWal, Jeremy; Thogmartin, Wayne E.; Vavrus, Stephen J.; Heglund, Patricia J.

2016-01-01

Climate change may drastically alter patterns of species distributions and richness, but predicting future species patterns in occurrence is challenging. Significant shifts in distributions have already been observed, and understanding these recent changes can improve our understanding of potential future changes. We assessed how past climate change affected potential breeding distributions for landbird species in the conterminous United States. We quantified the bioclimatic velocity of potential breeding distributions, that is, the pace and direction of change for each species’ suitable climate space over the past 60 years. We found that potential breeding distributions for landbirds have shifted substantially with an average velocity of 1.27 km yr−1, about double the pace of prior distribution shift estimates across terrestrial systems globally (0.61 km yr−1). The direction of shifts was not uniform. The majority of species’ distributions shifted west, northwest, and north. Multidirectional shifts suggest that changes in climate conditions beyond mean temperature were influencing distributional changes. Indeed, precipitation variables that were proxies for extreme conditions were important variables across all models. There were winners and losers in terms of the area of distributions; many species experienced contractions along west and east distribution edges, and expansions along northern distribution edges. Changes were also reflected in the potential species richness, with some regions potentially gaining species (Midwest, East) and other areas potentially losing species (Southwest). However, the degree to which changes in potential breeding distributions are manifested in actual species richness depends on landcover. Areas that have become increasingly suitable for breeding birds due to changing climate are often those attractive to humans for agriculture and development. This suggests that many areas might have supported more breeding bird species had the landscape not been altered. Our study illustrates that climate change is not only a future threat, but something birds are already experiencing.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2.

PubMed

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali; Archontoulis, Sotirios V; Zobel, Zachary; Kotamarthi, Veerabhadra R

2017-07-01

Heat and drought are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO 2 concentrations. This study quantifies the combined and separate impacts of high temperature, heat and drought stresses on the current and future US rainfed maize and soybean production and for the first time characterizes spatial shifts in the relative importance of individual stress. Crop yields are simulated using the Agricultural Production Systems Simulator (APSIM), driven by high-resolution (12 km) dynamically downscaled climate projections for 1995-2004 and 2085-2094. Results show that maize and soybean yield losses are prominent in the US Midwest by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of loss highly depends on the current vulnerability and changes in climate extremes. Elevated atmospheric CO 2 partially but not completely offsets the yield gaps caused by climate extremes, and the effect is greater in soybean than in maize. Our simulations suggest that drought will continue to be the largest threat to US rainfed maize production under RCP4.5 and soybean production under both RCP scenarios, whereas high temperature and heat stress take over the dominant stress of drought on maize under RCP8.5. We also reveal that shifts in the geographic distributions of dominant stresses are characterized by the increase in concurrent stresses, especially for the US Midwest. These findings imply the importance of considering heat and drought stresses simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management. The modeling framework of partitioning the total effects of climate change into individual stress impacts can be applied to the study of other crops and agriculture systems. © 2017 John Wiley & Sons Ltd.

The pace of past climate change vs. potential bird distributions and land use in the United States.

PubMed

Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; VanDerWal, Jeremy; Thogmartin, Wayne E; Vavrus, Stephen J; Heglund, Patricia J

2016-03-01

Climate change may drastically alter patterns of species distributions and richness, but predicting future species patterns in occurrence is challenging. Significant shifts in distributions have already been observed, and understanding these recent changes can improve our understanding of potential future changes. We assessed how past climate change affected potential breeding distributions for landbird species in the conterminous United States. We quantified the bioclimatic velocity of potential breeding distributions, that is, the pace and direction of change for each species' suitable climate space over the past 60 years. We found that potential breeding distributions for landbirds have shifted substantially with an average velocity of 1.27 km yr(-1) , about double the pace of prior distribution shift estimates across terrestrial systems globally (0.61 km yr(-1) ). The direction of shifts was not uniform. The majority of species' distributions shifted west, northwest, and north. Multidirectional shifts suggest that changes in climate conditions beyond mean temperature were influencing distributional changes. Indeed, precipitation variables that were proxies for extreme conditions were important variables across all models. There were winners and losers in terms of the area of distributions; many species experienced contractions along west and east distribution edges, and expansions along northern distribution edges. Changes were also reflected in the potential species richness, with some regions potentially gaining species (Midwest, East) and other areas potentially losing species (Southwest). However, the degree to which changes in potential breeding distributions are manifested in actual species richness depends on landcover. Areas that have become increasingly suitable for breeding birds due to changing climate are often those attractive to humans for agriculture and development. This suggests that many areas might have supported more breeding bird species had the landscape not been altered. Our study illustrates that climate change is not only a future threat, but something birds are already experiencing. © 2015 John Wiley & Sons Ltd.

Estuarine Response to River Flow and Sea-Level Rise under Future Climate Change and Human Development

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

Yang, Zhaoqing; Wang, Taiping; Voisin, Nathalie

Understanding the response of river flow and estuarine hydrodynamics to climate change, land-use/land-cover change (LULC), and sea-level rise is essential to managing water resources and stress on living organisms under these changing conditions. This paper presents a modeling study using a watershed hydrology model and an estuarine hydrodynamic model, in a one-way coupling, to investigate the estuarine hydrodynamic response to sea-level rise and change in river flow due to the effect of future climate and LULC changes in the Snohomish River estuary, Washington, USA. A set of hydrodynamic variables, including salinity intrusion points, average water depth, and salinity of themore » inundated area, were used to quantify the estuarine response to river flow and sea-level rise. Model results suggest that salinity intrusion points in the Snohomish River estuary and the average salinity of the inundated areas are a nonlinear function of river flow, although the average water depth in the inundated area is approximately linear with river flow. Future climate changes will shift salinity intrusion points further upstream under low flow conditions and further downstream under high flow conditions. In contrast, under the future LULC change scenario, the salinity intrusion point will shift downstream under both low and high flow conditions, compared to present conditions. The model results also suggest that the average water depth in the inundated areas increases linearly with sea-level rise but at a slower rate, and the average salinity in the inundated areas increases linearly with sea-level rise; however, the response of salinity intrusion points in the river to sea-level rise is strongly nonlinear.« less

Developing a phenological model for grapevine to assess future frost risk in Luxembourg

NASA Astrophysics Data System (ADS)

Caffarra, A.; Molitor, D.; Pertot, I.; Sinigoy, P.; Junk, J.

2012-04-01

Late frost damage represents a significant hazard to grape production in cool climate viticulture regions such as Luxembourg. The main aim of our study is to analyze the frequency of these events for the Luxembourg's winegrowing region in the future. Spring frost injuries on grape may occur when young green parts are exposed to air temperature below 0°C. The potential risk is determined by: (i) minimum air temperature conditions and the (ii) the timing of bud burst. Therefore, we developed and validated a model for budburst of the grapevine (*Vitis vinifera)* cultivar Rivaner, the most grown local variety, based on multi-annual data from 7 different sites across Europe and the US. An advantage of this approach is, that it could be applied to a wide range of climate conditions. Higher spring temperatures were projected for the future and could lead to earlier dates of budburst as well as earlier dates of last frost events in the season. However, so far it is unknown if this will increase or decrease the risk of severe late frost damages for Luxembourg's winegrowing region. To address this question results of 10 regional climate change projections from the FP6 ENSEMBLES project (spatial resolution = 25km; A1B emission scenario) were combined with the new bud burst model. The use of a multi model ensemble of climate change projections allows for a better quantification of the uncertainties. A bias corrections scheme, based on local observations, was applied to the model output. Projected daily minimum air temperatures, up to 2098, were compared to the projected date of bud burst in order to quantify the future frost risk for Luxembourg.

Historical Pattern and Future Trajectories of Terrestrial N2O Emission driven by Multi-factor Global Changes

NASA Astrophysics Data System (ADS)

Lu, C.; Tian, H.; Yang, J.; Zhang, B.; Xu, R.

2015-12-01

Nitrous oxide (N2O) is among the most important greenhouse gases only next to carbon dioxide (CO2) and methane (CH4) due to its long life time and high radiative forcing (with a global warming potential 265 times as much as CO2 at 100-year time horizon). The Atmospheric concentration of N2O has increased by 20% since pre-industrial era, and this increase plays a significant role in shaping anthropogenic climate change. However, compared to CO2- and CH4-related research, fewer studies have been performed in assessing and predicting the spatiotemporal patterns of N2O emission from natural and agricultural soils. Here we used a coupled biogeochemical model, DLEM, to quantify the historical and future changes in global terrestrial N2O emissions resulting from natural and anthropogenic perturbations including climate variability, atmospheric CO2 concentration, nitrogen deposition, land use and land cover changes, and agricultural land management practices (i.e., synthetic nitrogen fertilizer use, manure application, and irrigation etc.) over the period 1900-2099. We focused on inter-annual variation and long-term trend of terrestrial N2O emission driven by individual and combined environmental changes during historical and future periods. The sensitivity of N2O emission to climate, atmospheric composition, and human activities has been examined at biome-, latitudinal, continental and global scales. Future projections were conducted to identify the hot spots and hot time periods of global N2O emission under two emission scenarios (RCP2.6 and RCP8.5). It provides a modeling perspective for understanding human-induced N2O emission growth and developing potential management strategies to mitigate further atmospheric N2O increase and climate warming.

The Mekong's future flows under multiple driving factors: How future climate change, hydropower developments and irrigation expansion drive hydrological changes?

NASA Astrophysics Data System (ADS)

Hoang, L. P.; van Vliet, M. T. H.; Lauri, H.; Kummu, M.; Koponen, J.; Supit, I.; Leemans, R.; Kabat, P.; Ludwig, F.

2016-12-01

The Mekong River's flows and water resources are in many ways essential for sustaining economic growths, flood security of about 70 million people and biodiversity in one of the world's most ecologically productive wetland systems. The river's hydrological cycle, however, are increasingly perturbed by climate change, large-scale hydropower developments and rapid irrigated land expansions. This study presents an integrated impact assessment to characterize and quantify future hydrological changes induced by these driving factors, both separately and combined. We have integrated a crop simulation module and a hydropower dam module into a distributed hydrological model (VMod) and simulated the Mekong's hydrology under multiple climate change and development scenarios. Our results show that the Mekong's hydrological regime will experience substantial changes caused by the considered factors. Magnitude-wise, hydropower dam developments exhibit the largest impacts on river flows, with projected higher flows (up to +35%) during the dry season and lower flows (up to -44%) during the wet season. Annual flow changes caused by the dams, however, are relatively marginal. In contrast to this, climate change is projected to increase the Mekong's annual flows (up to +16%) while irrigated land expansions result in annual flow reductions (-1% to -3%). Combining the impacts of these three drivers, we found that river flow changes, especially those at the monthly scale, largely differ from changes under the individual driving factors. This is explained by large differences in impacts' magnitudes and contrasting impacts' directions for the individual drivers. We argue that the Mekong's future flows are likely driven by multiple factors and thus advocate for integrated assessment approaches and tools that support proper considerations of these factors and their interplays.

Climate Variability: Adaptation Strategies for Colorado River Management

NASA Astrophysics Data System (ADS)

Fulp, T. J.; Prairie, J. R.

2008-12-01

The importance of the Colorado River system to the western United States and the Republic of Mexico is well documented. Much has been written recently in response to the lingering drought and increasing demands on the system. Questions such as "has the river run out of water?", "how low can it go?", and "will Lake Mead go dry?" express the concern that the river system will be hard-pressed to continue to meet future demands, particularly if droughts tend toward increased magnitudes and longer durations. Reservoirs on the main stream of the Colorado River are managed by the Bureau of Reclamation (Reclamation), on behalf of the Secretary of the U.S. Department of the Interior (Secretary). Over 80% of the 60 million acre-feet of storage capacity is contained in Lake Powell and Lake Mead, large reservoirs that are located in each of the sub-basins (Upper Basin and Lower Basin) defined in the 1922 Colorado River Compact. In response to the worst drought conditions in approximately one hundred years of recorded history and the lack of specific operational guidelines for operation of Lake Powell and Lake Mead for drought and low reservoir conditions, the Secretary adopted new operational guidelines in December 2007 that will be used for an interim period (through 2026). The Interim Guidelines were the result of an intense, three-year effort in accordance with the National Environmental Policy Act of 1969 (NEPA). Several alternative operational rules were compared with respect to future potential impacts to Colorado River resources, including lake levels, water delivery, hydropower production, water quality, recreation, and fish and wildlife and published in an Environmental Impact Statement (EIS). Due to the large uncertainty regarding future inflows into the system, particularly in a changing climate, these comparisons were presented in probabilistic terms in order to assess the risk of key events (e.g., the timing and magnitude of water shortages). Because it is impossible to precisely predict future inflows, a range of possible inflows were analyzed and used to quantify the uncertainty with respect to inflows, which by far dominates the overall uncertainty. Although Reclamation had typically used a technique that resamples the historical record to generate future hydrologic inflow scenarios, new techniques were used in this EIS in order to better quantify the uncertainties. These techniques were the outcome of a multi-faceted research and development program begun in 2004 to enable the use of other methods for projecting possible future inflow sequences for Colorado River planning studies. The techniques employed in this EIS included resampling from a new paleo-reconstruction of Colorado River flows dating back to 762 A.D. and a hybrid technique that couples the state information derived from the paleo-record (i.e., wet, dry) with the historical record to generate future sequences that have not been seen in the past. Additional research is both needed and warranted to better quantify the uncertainties and the risks of current and future water resource management decisions and Reclamation is continuing its research effort, working with other governmental agencies and universities, to further its ability to use climate information in its decision-making.

FUPSOL: Modelling the Future and Past Solar Influence on Earth Climate

NASA Astrophysics Data System (ADS)

Anet, J. G.; Rozanov, E.; Peter, T.

2012-04-01

Global warming is becoming one of the main threats to mankind. There is growing evidence that anthropogenic greenhouse gases have become the dominant factor since about 1970. At the same time natural factors of climate change such as solar and volcanic forcings cannot be neglected on longer time scales. Despite growing scientific efforts over the last decades in both, observations and simulations, the uncertainty of the solar contribution to the past climate change remained unacceptably high (IPCC, 2007), the reasons being on one hand missing observations of solar irradiance prior to the satellite era, and on the other hand a majority of models so far not including all processes relevant for solar-climate interactions. This project aims at elucidating the processes governing the effects of solar activity variations on Earth's climate. We use the state-of-the-art coupled atmosphere-ocean-chemistry-climate model (AOCCM) SOCOL (Schraner et al, 2008) developed in Switzerland by coupling the community Earth System Model (ESM) COSMOS distributed by MPI for Meteorology (Hamburg, Germany) with a comprehensive atmospheric chemistry module. The model solves an extensive set of equations describing the dynamics of the atmosphere and ocean, radiative transfer, transport of species, their chemical transformations, cloud formation and the hydrological cycle. The intention is to show how past solar variations affected climate and how the decrease in solar forcing expected for the next decades will affect climate on global and regional scales. We will simulate the global climate system behavior during Dalton minimum (1790 and 1830) and first half of 21st century with a series of multiyear ensemble experiments and perform these experiments using all known anthropogenic and natural climate forcing taken in different combinations to understand the effects of solar irradiance in different spectral regions and particle precipitation variability. Further on, we will quantify the solar influence on global climate in the future by evaluating the simulations and using information from past analogs such as the Dalton minimum. In the end, the project aims at reducing the uncertainty of the solar contribution to past and future climate change, which so far remained high despite many years of analyses of observational records and theoretical investigations with climate models of different complexity.

Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA

USGS Publications Warehouse

Lauffenburger, Zachary H.; Gurdak, Jason J.; Hobza, Christopher M.; Woodward, Duane; Wolf, Cassandra

2018-01-01

Understanding the controls of agriculture and climate change on recharge rates is critically important to develop appropriate sustainable management plans for groundwater resources and coupled irrigated agricultural systems. In this study, several physical (total potential (ψT) time series) and chemical tracer and dating (3H, Cl−, Br−, CFCs, SF6, and 3H/3He) methods were used to quantify diffuse recharge rates beneath two rangeland sites and irrigation recharge rates beneath two irrigated corn sites along an east-west (wet-dry) transect of the northern High Plains aquifer, Platte River Basin, central Nebraska. The field-based recharge estimates and historical climate were used to calibrate site-specific Hydrus-1D models, and irrigation requirements were estimated using the Crops Simulation Model (CROPSIM). Future model simulations were driven by an ensemble of 16 global climate models and two global warming scenarios to project a 2050 climate relative to the historical baseline 1990 climate, and simulate changes in precipitation, irrigation, evapotranspiration, and diffuse and irrigation recharge rates. Although results indicate statistical differences between the historical variables at the eastern and western sites and rangeland and irrigated sites, the low warming scenario (+1.0 °C) simulations indicate no statistical differences between 2050 and 1990. However, the high warming scenarios (+2.4 °C) indicate a 25% and 15% increase in median annual evapotranspiration and irrigation demand, and decreases in future diffuse recharge by 53% and 98% and irrigation recharge by 47% and 29% at the eastern and western sites, respectively. These results indicate an important threshold between the low and high warming scenarios that if exceeded could trigger a significant bidirectional shift in 2050 hydroclimatology and recharge gradients. The bidirectional shift is that future northern High Plains temperatures will resemble present central High Plains temperatures and future recharge rates in the east will resemble present recharge rates in the western part of the northern High Plains aquifer. The reductions in recharge rates could accelerate declining water levels if irrigation demand and other management strategies are not implemented. Findings here have important implications for future management of irrigation practices and to slow groundwater depletion in this important agricultural region.

Airborne Particles: What We Have Learned About Their Role in Climate from Remote Sensing, and Prospects for Future Advances

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

Desert dust, wildfire smoke, volcanic ash, biogenic and urban pollution particles, all affect the regional-scale climate of Earth in places and at times; some have global-scale impacts on the column radiation balance, cloud properties, atmospheric stability structure, and circulation patterns. Remote sensing has played a central role in identifying the sources and transports of airborne particles, mapping their three-dimensional distribution and variability, quantifying their amount, and constraining aerosol air mass type. The measurements obtained from remote sensing have strengths and limitations, and their value for characterizing Earths environment is enhanced immensely when they are combined with direct, in situ observations, and used to constrain aerosol transport and climate models. A similar approach has been taken to study the role particles play in determining the climate of Mars, though based on far fewer observations. This presentation will focus what we have learned from remote sensing about the impacts aerosol have on Earths climate; a few points about how aerosols affect the climate of Mars will also be introduced, in the context of how we might assess aerosol-climate impacts more generally on other worlds.

Incorporating climate change and morphological uncertainty into coastal change hazard assessments

USGS Publications Warehouse

Baron, Heather M.; Ruggiero, Peter; Wood, Nathan J.; Harris, Erica L.; Allan, Jonathan; Komar, Paul D.; Corcoran, Patrick

2015-01-01

Documented and forecasted trends in rising sea levels and changes in storminess patterns have the potential to increase the frequency, magnitude, and spatial extent of coastal change hazards. To develop realistic adaptation strategies, coastal planners need information about coastal change hazards that recognizes the dynamic temporal and spatial scales of beach morphology, the climate controls on coastal change hazards, and the uncertainties surrounding the drivers and impacts of climate change. We present a probabilistic approach for quantifying and mapping coastal change hazards that incorporates the uncertainty associated with both climate change and morphological variability. To demonstrate the approach, coastal change hazard zones of arbitrary confidence levels are developed for the Tillamook County (State of Oregon, USA) coastline using a suite of simple models and a range of possible climate futures related to wave climate, sea-level rise projections, and the frequency of major El Niño events. Extreme total water levels are more influenced by wave height variability, whereas the magnitude of erosion is more influenced by sea-level rise scenarios. Morphological variability has a stronger influence on the width of coastal hazard zones than the uncertainty associated with the range of climate change scenarios.

The 2 °C global warming effect on summer European tourism through different indices.

PubMed

Grillakis, Manolis G; Koutroulis, Aristeidis G; Tsanis, Ioannis K

2016-08-01

Climate and weather patterns are an essential resource for outdoor tourism activities. The projected changes in climate and weather patterns are expected to affect the future state of tourism. The present study aims to quantify the positive or negative effect of a 2 °C global warming on summertime climate comfort in the sense of exercising activities that involve light body activity. The well-established Climate Index for Tourism (CIT) and three variants of the widely used Tourism Climatic Index (TCI) were analyzed. Additionally, a new index based on TCI and CIT was tested and compared against the precious indices. Past and future climate data of five high-resolution regional climate models (RCMs) from different Representative Concentration Pathways (RCP4.5 and RCP8.5) of the European Coordinated Regional Climate Downscaling Experiment (Euro-CORDEX) for a +2 °C period were used. The results indicate improvement in the climate comfort for the majority of European areas for the May to October period. For the June to August period, central and northern European areas are projected to improve, while marginal improvement is found for Mediterranean countries. Furthermore, in specific cases of adjacent Mediterranean areas such as the southern Iberian Peninsula, the June to August climate favorability is projected to reduce as a result of the increase to daytime temperature. The use of a set of different indices and different RCMs and RCPs samples a large fraction of the uncertainty that is crucial for providing robust regional impact information due to climate change. The analysis revealed the similarities and the differences in the magnitude of change across the different indices. Moreover, discrepancies were found in the results of different concentration pathways to the +2 °C global warming, with the RCP8.5 projecting more significant changes for some of the analyzed indices. The estimation of the TCI using different timescale climate data did not change the results on tourism significantly.

Uncertainties in climate change projections for viticulture in Portugal

NASA Astrophysics Data System (ADS)

Fraga, Helder; Malheiro, Aureliano C.; Moutinho-Pereira, José; Pinto, Joaquim G.; Santos, João A.

2013-04-01

The assessment of climate change impacts on viticulture is often carried out using regional climate model (RCM) outputs. These studies rely on either multi-model ensembles or on single-model approaches. The RCM-ensembles account for uncertainties inherent to the different models. In this study, using a 16-RCM ensemble under the IPCC A1B scenario, the climate change signal (future minus recent-past, 2041-2070 - 1961-2000) of 4 bioclimatic indices (Huglin Index - HI, Dryness Index - DI, Hydrothermal Index - HyI and CompI - Composite Index) over mainland Portugal is analysed. A normalized interquartile range (NIQR) of the 16-member ensemble for each bioclimatic index is assessed in order to quantify the ensemble uncertainty. The results show significant increases in the HI index over most of Portugal, with higher values in Alentejo, Trás-os-Montes and Douro/Porto wine regions, also depicting very low uncertainty. Conversely, the decreases in the DI pattern throughout the country show large uncertainties, except in Minho (northwestern Portugal), where precipitation reaches the highest amounts in Portugal. The HyI shows significant decreases in northwestern Portugal, with relatively low uncertainty all across the country. The CompI depicts significant decreases over Alentejo and increases over Minho, though decreases over Alentejo reveal high uncertainty, while increases over Minho show low uncertainty. The assessment of the uncertainty in climate change projections is of great relevance for the wine industry. Quantifying this uncertainty is crucial, since different models may lead to quite different outcomes and may thereby be as crucial as climate change itself to the winemaking sector. This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692.

Climate change impacts on thermoelectric-power generation in the United States

NASA Astrophysics Data System (ADS)

Liu, L.

2015-12-01

Thermoelectric-power generation accounts for more than 70% of the total electricity generation in the United States, which requires large amounts of water for cooling purposes. Water withdrawals for thermoelectric-power generation accounted for 45% of total water use in the United States in 2010. Across the country, water demand from power plants is increasing due to pressures from growing populations and other needs, and is straining existing water resources. Moreover, temperature exceedance in receiving waters has increasingly caused power plants shut downs across parts of the country. Thermoelectric power is vulnerable to climate change owing to the combined effects of lower summer river flows and higher receiving water temperatures. In addition, the efficiency of production is reduced as air temperature rises, which propagates to more unfulfilled power demand during peak seasons. Therefore, a holistic modeling framework of water-energy-climate for the contiguous U.S. is presented here to quantify thermal output from power plants and estimate water use and energy production fluctuations due to ambient climate as well as environmental regulations. The model is calibrated on a plant-by-plant basis for year 2010 and 2011 using the available power plant inventory from the Energy Information Administration (EIA). Simulations were carried out for years 2012 and 2013, and results show moderate improvements in capturing thermal output variabilities after calibration. Future power plant operations under scenarios featuring different climate and regulatory settings were investigated. Results demonstrate the interplay among water, energy and climate, and that future changes in climate and socioeconomics significantly affect power plant operations, which may provide insights to climate change mitigation considerations and energy decisions.

Climate Change and Food Security: Health Impacts in Developed Countries

PubMed Central

Hooper, Lee; Abdelhamid, Asmaa; Bentham, Graham; Boxall, Alistair B.A.; Draper, Alizon; Fairweather-Tait, Susan; Hulme, Mike; Hunter, Paul R.; Nichols, Gordon; Waldron, Keith W.

2012-01-01

Background: Anthropogenic climate change will affect global food production, with uncertain consequences for human health in developed countries. Objectives: We investigated the potential impact of climate change on food security (nutrition and food safety) and the implications for human health in developed countries. Methods: Expert input and structured literature searches were conducted and synthesized to produce overall assessments of the likely impacts of climate change on global food production and recommendations for future research and policy changes. Results: Increasing food prices may lower the nutritional quality of dietary intakes, exacerbate obesity, and amplify health inequalities. Altered conditions for food production may result in emerging pathogens, new crop and livestock species, and altered use of pesticides and veterinary medicines, and affect the main transfer mechanisms through which contaminants move from the environment into food. All these have implications for food safety and the nutritional content of food. Climate change mitigation may increase consumption of foods whose production reduces greenhouse gas emissions. Impacts may include reduced red meat consumption (with positive effects on saturated fat, but negative impacts on zinc and iron intake) and reduced winter fruit and vegetable consumption. Developed countries have complex structures in place that may be used to adapt to the food safety consequences of climate change, although their effectiveness will vary between countries, and the ability to respond to nutritional challenges is less certain. Conclusions: Climate change will have notable impacts upon nutrition and food safety in developed countries, but further research is necessary to accurately quantify these impacts. Uncertainty about future impacts, coupled with evidence that climate change may lead to more variable food quality, emphasizes the need to maintain and strengthen existing structures and policies to regulate food production, monitor food quality and safety, and respond to nutritional and safety issues that arise. PMID:23124134

Climate change and food security: health impacts in developed countries.

PubMed

Lake, Iain R; Hooper, Lee; Abdelhamid, Asmaa; Bentham, Graham; Boxall, Alistair B A; Draper, Alizon; Fairweather-Tait, Susan; Hulme, Mike; Hunter, Paul R; Nichols, Gordon; Waldron, Keith W

2012-11-01

Anthropogenic climate change will affect global food production, with uncertain consequences for human health in developed countries. We investigated the potential impact of climate change on food security (nutrition and food safety) and the implications for human health in developed countries. Expert input and structured literature searches were conducted and synthesized to produce overall assessments of the likely impacts of climate change on global food production and recommendations for future research and policy changes. Increasing food prices may lower the nutritional quality of dietary intakes, exacerbate obesity, and amplify health inequalities. Altered conditions for food production may result in emerging pathogens, new crop and livestock species, and altered use of pesticides and veterinary medicines, and affect the main transfer mechanisms through which contaminants move from the environment into food. All these have implications for food safety and the nutritional content of food. Climate change mitigation may increase consumption of foods whose production reduces greenhouse gas emissions. Impacts may include reduced red meat consumption (with positive effects on saturated fat, but negative impacts on zinc and iron intake) and reduced winter fruit and vegetable consumption. Developed countries have complex structures in place that may be used to adapt to the food safety consequences of climate change, although their effectiveness will vary between countries, and the ability to respond to nutritional challenges is less certain. Climate change will have notable impacts upon nutrition and food safety in developed countries, but further research is necessary to accurately quantify these impacts. Uncertainty about future impacts, coupled with evidence that climate change may lead to more variable food quality, emphasizes the need to maintain and strengthen existing structures and policies to regulate food production, monitor food quality and safety, and respond to nutritional and safety issues that arise.

Quantifying CO2 Emissions from Individual Power Plants using OCO-2 Observations

NASA Astrophysics Data System (ADS)

Nassar, R.; Hill, T. G.; McLinden, C. A.; Wunch, D.; Jones, D. B. A.; Crisp, D.

2017-12-01

In order to better manage anthropogenic CO2 emissions, improved methods of quantifying emissions are needed at all spatial scales from the national level down to the facility level. Although the Orbiting Carbon Observatory 2 (OCO-2) satellite was not designed for monitoring power plant emissions, we show that in select cases, CO2 observations from OCO-2 can be used to quantify daily CO2 emissions from individual mid- to large-sized coal power plants by fitting the data to plume model simulations. Emission estimates for US power plants are within 1-13% of reported daily emission values enabling application of the approach to international sites that lack detailed emission information. These results affirm that a constellation of future CO2 imaging satellites, optimized for point sources, could be used for the Monitoring, Reporting and Verification (MRV) of CO2 emissions from individual power plants to support the implementation of climate policies.

Quantifying CO2 Emissions From Individual Power Plants From Space

NASA Astrophysics Data System (ADS)

Nassar, Ray; Hill, Timothy G.; McLinden, Chris A.; Wunch, Debra; Jones, Dylan B. A.; Crisp, David

2017-10-01

In order to better manage anthropogenic CO2 emissions, improved methods of quantifying emissions are needed at all spatial scales from the national level down to the facility level. Although the Orbiting Carbon Observatory 2 (OCO-2) satellite was not designed for monitoring power plant emissions, we show that in some cases, CO2 observations from OCO-2 can be used to quantify daily CO2 emissions from individual middle- to large-sized coal power plants by fitting the data to plume model simulations. Emission estimates for U.S. power plants are within 1-17% of reported daily emission values, enabling application of the approach to international sites that lack detailed emission information. This affirms that a constellation of future CO2 imaging satellites, optimized for point sources, could monitor emissions from individual power plants to support the implementation of climate policies.

Measuring and modelling ecosystem productivity: a PhenoCam-based approach.

NASA Astrophysics Data System (ADS)

Hufkens, K.; Keenan, T. F.; Flanagan, L. B.; Richardson, A. D.

2015-12-01

Phenology controls feedbacks to the climate system through abiotic and biotic forces such as albedo or fluxes of water, energy and CO2. Understanding and modelling these vegetation-climate feedbacks is key to accurately predicting a future climate. For the past 6 years the PhenoCam network, a network of near-surface remote sensing cameras, has consistently monitored vegetation phenology in a wide range of ecoregions, climate zones, and plant functional types. Here we explore the tight coupling between canopy greenness and rates of photosynthesis using two studies. A first study highlights how PhenoCam data can be used to quantify the effect of a late spring frost event on ecosystem productivity, introducing a 7-14% loss in annual gross productivity across 8753 km2 in the northeastern United States. This case study emphasizes the use of the PhenoCam data in estimating productivity loss / the opportunity cost of ecosystem disturbance in areas not covered by ecosystem flux measurement equipment. In a more recent, second, study we developed a PhenoCam data-informed pulse-response model of grassland growth to explore potential responses of grasslands to future climate change across North America. Our findings projected widespread and consistent increase in grassland productivity (for the current range of grassland ecosystems of North American) over the coming century, despite a general increase in aridity projected across most of our study area. Once more PhenoCam data allowed us to inform our modelling efforts with data of a high temporal and spatial resolution. In conclusion, both studies illustrate direct applications of the ever growing PhenoCam network (http://phenocam.sr.unh.edu/webcam/) in scaling the effects of ecosystem disturbances, predicting future ecosystem productivity and underscore the complementary nature of PhenoCam data with ecosystem exchange measurements.

Future battlegrounds for conservation under global change

PubMed Central

Lee, Tien Ming; Jetz, Walter

2008-01-01

Global biodiversity is under significant threat from the combined effects of human-induced climate and land-use change. Covering 12% of the Earth's terrestrial surface, protected areas are crucial for conserving biodiversity and supporting ecological processes beneficial to human well-being, but their selection and design are usually uninformed about future global change. Here, we quantify the exposure of the global reserve network to projected climate and land-use change according to the Millennium Ecosystem Assessment and set these threats in relation to the conservation value and capacity of biogeographic and geopolitical regions. We find that geographical patterns of past human impact on the land cover only poorly predict those of forecasted change, thus revealing the inadequacy of existing global conservation prioritization templates. Projected conservation risk, measured as regional levels of land-cover change in relation to area protected, is the greatest at high latitudes (due to climate change) and tropics/subtropics (due to land-use change). Only some high-latitude nations prone to high conservation risk are also of high conservation value, but their high relative wealth may facilitate additional conservation efforts. In contrast, most low-latitude nations tend to be of high conservation value, but they often have limited capacity for conservation which may exacerbate the global biodiversity extinction crisis. While our approach will clearly benefit from improved land-cover projections and a thorough understanding of how species range will shift under climate change, our results provide a first global quantitative demonstration of the urgent need to consider future environmental change in reserve-based conservation planning. They further highlight the pressing need for new reserves in target regions and support a much extended ‘north–south’ transfer of conservation resources that maximizes biodiversity conservation while mitigating global climate change. PMID:18302999

Estimating Ecosystem Carbon Stock Change in the Conterminous United States from 1971 to 2010

NASA Astrophysics Data System (ADS)

Liu, J.; Sleeter, B. M.; Zhu, Z.; Loveland, T. R.; Sohl, T.; Howard, S. M.; Hawbaker, T. J.; Liu, S.; Heath, L. S.; Cochrane, M. A.; Key, C. H.; Jiang, H.; Price, D. T.; Chen, J. M.

2015-12-01

There is significant geographic variability in U.S. ecosystem carbon sequestration due to natural and human environmental conditions. Climate change, natural disturbance and human land use are the major driving forces that can alter local and regional carbon sequestration rates. In this study, a comprehensive environmental input dataset (1-km resolution) was developed and used in the process-based Integrated Biosphere Simulator (IBIS) to quantify the U.S. carbon stock changes from 1971-2010, which potentially forms a baseline for future U.S. carbon scenarios. The key environmental data sources include land cover change information from more than 2,600 sample blocks across U.S. (10-km by 10-km in size, 60-m resolution, 1973-2000), wildland fire scar and burn severity information (30-m resolution, 1984-2010), vegetation canopy percentage and live biomass level (30-m resolution, ~2000), spatially heterogeneous atmospheric carbon dioxide and nitrogen deposition (~50-km resolution, 2003-2009), and newly available climate (4-km resolution, 1895-2010) and soil variables (1-km resolution, ~2000). The IBIS simulated the effects of atmospheric CO2 fertilization, nitrogen deposition, climate change, fire, logging, and deforestation/devegetation on ecosystem carbon changes. Multiple comparable simulations were implemented to quantify the contributions of key environmental drivers.

Quantifying effects of humans and climate on groundwater resources through modeling of volcanic-rock aquifers of Hawaii

NASA Astrophysics Data System (ADS)

Rotzoll, K.; Izuka, S. K.; Nishikawa, T.; Fienen, M. N.; El-Kadi, A. I.

2015-12-01

The volcanic-rock aquifers of Kauai, Oahu, and Maui are heavily developed, leading to concerns related to the effects of groundwater withdrawals on saltwater intrusion and streamflow. A numerical modeling analysis using the most recently available data (e.g., information on recharge, withdrawals, hydrogeologic framework, and conceptual models of groundwater flow) will substantially advance current understanding of groundwater flow and provide insight into the effects of human activity and climate change on Hawaii's water resources. Three island-wide groundwater-flow models were constructed using MODFLOW 2005 coupled with the Seawater-Intrusion Package (SWI2), which simulates the transition between saltwater and freshwater in the aquifer as a sharp interface. This approach allowed relatively fast model run times without ignoring the freshwater-saltwater system at the regional scale. Model construction (FloPy3), automated-parameter estimation (PEST), and analysis of results were streamlined using Python scripts. Model simulations included pre-development (1870) and current (average of 2001-10) scenarios for each island. Additionally, scenarios for future withdrawals and climate change were simulated for Oahu. We present our streamlined approach and preliminary results showing estimated effects of human activity on the groundwater resource by quantifying decline in water levels, reduction in stream base flow, and rise of the freshwater-saltwater interface.

Quantifying the effect of autonomous adaptation to global river flood projections: application to future flood risk assessments

NASA Astrophysics Data System (ADS)

Kinoshita, Youhei; Tanoue, Masahiro; Watanabe, Satoshi; Hirabayashi, Yukiko

2018-01-01

This study represents the first attempt to quantify the effects of autonomous adaptation on the projection of global flood hazards and to assess future flood risk by including this effect. A vulnerability scenario, which varies according to the autonomous adaptation effect for conventional disaster mitigation efforts, was developed based on historical vulnerability values derived from flood damage records and a river inundation simulation. Coupled with general circulation model outputs and future socioeconomic scenarios, potential future flood fatalities and economic loss were estimated. By including the effect of autonomous adaptation, our multimodel ensemble estimates projected a 2.0% decrease in potential flood fatalities and an 821% increase in potential economic losses by 2100 under the highest emission scenario together with a large population increase. Vulnerability changes reduced potential flood consequences by 64%-72% in terms of potential fatalities and 28%-42% in terms of potential economic losses by 2100. Although socioeconomic changes made the greatest contribution to the potential increased consequences of future floods, about a half of the increase of potential economic losses was mitigated by autonomous adaptation. There is a clear and positive relationship between the global temperature increase from the pre-industrial level and the estimated mean potential flood economic loss, while there is a negative relationship with potential fatalities due to the autonomous adaptation effect. A bootstrapping analysis suggests a significant increase in potential flood fatalities (+5.7%) without any adaptation if the temperature increases by 1.5 °C-2.0 °C, whereas the increase in potential economic loss (+0.9%) was not significant. Our method enables the effects of autonomous adaptation and additional adaptation efforts on climate-induced hazards to be distinguished, which would be essential for the accurate estimation of the cost of adaptation to climate change.

How to deal with climate change uncertainty in the planning of engineering systems

NASA Astrophysics Data System (ADS)

Spackova, Olga; Dittes, Beatrice; Straub, Daniel

2016-04-01

The effect of extreme events such as floods on the infrastructure and built environment is associated with significant uncertainties: These include the uncertain effect of climate change, uncertainty on extreme event frequency estimation due to limited historic data and imperfect models, and, not least, uncertainty on future socio-economic developments, which determine the damage potential. One option for dealing with these uncertainties is the use of adaptable (flexible) infrastructure that can easily be adjusted in the future without excessive costs. The challenge is in quantifying the value of adaptability and in finding the optimal sequence of decision. Is it worth to build a (potentially more expensive) adaptable system that can be adjusted in the future depending on the future conditions? Or is it more cost-effective to make a conservative design without counting with the possible future changes to the system? What is the optimal timing of the decision to build/adjust the system? We develop a quantitative decision-support framework for evaluation of alternative infrastructure designs under uncertainties, which: • probabilistically models the uncertain future (trough a Bayesian approach) • includes the adaptability of the systems (the costs of future changes) • takes into account the fact that future decisions will be made under uncertainty as well (using pre-posterior decision analysis) • allows to identify the optimal capacity and optimal timing to build/adjust the infrastructure. Application of the decision framework will be demonstrated on an example of flood mitigation planning in Bavaria.

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

PubMed

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

2018-03-01

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

Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models

DOE PAGES

Andrews, Timothy; Gregory, Jonathan M.; Webb, Mark J.; ...

2012-05-15

We quantify forcing and feedbacks across available CMIP5 coupled atmosphere-ocean general circulation models (AOGCMs) by analysing simulations forced by an abrupt quadrupling of atmospheric carbon dioxide concentration. This is the first application of the linear forcing-feedback regression analysis of Gregory et al. (2004) to an ensemble of AOGCMs. The range of equilibrium climate sensitivity is 2.1–4.7 K. Differences in cloud feedbacks continue to be important contributors to this range. Some models show small deviations from a linear dependence of top-of-atmosphere radiative fluxes on global surface temperature change. We show that this phenomenon largely arises from shortwave cloud radiative effects overmore » the ocean and is consistent with independent estimates of forcing using fixed sea-surface temperature methods. Moreover, we suggest that future research should focus more on understanding transient climate change, including any time-scale dependence of the forcing and/or feedback, rather than on the equilibrium response to large instantaneous forcing.« less

The Arctic-Subarctic Sea Ice System is Entering a Seasonal Regime: Implications for Future Arctic Amplication

NASA Astrophysics Data System (ADS)

Haine, T. W. N.; Martin, T.

2017-12-01

The loss of Arctic sea ice is a conspicuous example of climate change. Climate models project ice-free conditions during summer this century under realistic emission scenarios, reflecting the increase in seasonality in ice cover. To quantify the increased seasonality in the Arctic-Subarctic sea ice system, we define a non-dimensional seasonality number for sea ice extent, area, and volume from satellite data and realistic coupled climate models. We show that the Arctic-Subarctic, i.e. the northern hemisphere, sea ice now exhibits similar levels of seasonality to the Antarctic, which is in a seasonal regime without significant change since satellite observations began in 1979. Realistic climate models suggest that this transition to the seasonal regime is being accompanied by a maximum in Arctic amplification, which is the faster warming of Arctic latitudes compared to the global mean, in the 2010s. The strong link points to a peak in sea-ice-related feedbacks that occurs long before the Arctic becomes ice-free in summer.

The influence of climate change on Tanzania's hydropower sustainability

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek; Boehlert, Brent; Meijer, Karen; Schellekens, Jaap; Magnell, Jan-Petter; Helbrink, Jakob; Kassana, Leonard; Liden, Rikard

2015-04-01

Economic costs induced by current climate variability are large for Tanzania and may further increase due to future climate change. The Tanzanian National Climate Change Strategy addressed the need for stabilization of hydropower generation and strengthening of water resources management. Increased hydropower generation can contribute to sustainable use of energy resources and stabilization of the national electricity grid. To support Tanzania the World Bank financed this study in which the impact of climate change on the water resources and related hydropower generation capacity of Tanzania is assessed. To this end an ensemble of 78 GCM projections from both the CMIP3 and CMIP5 datasets was bias-corrected and down-scaled to 0.5 degrees resolution following the BCSD technique using the Princeton Global Meteorological Forcing Dataset as a reference. To quantify the hydrological impacts of climate change by 2035 the global hydrological model PCR-GLOBWB was set-up for Tanzania at a resolution of 3 minutes and run with all 78 GCM datasets. From the full set of projections a probable (median) and worst case scenario (95th percentile) were selected based upon (1) the country average Climate Moisture Index and (2) discharge statistics of relevance to hydropower generation. Although precipitation from the Princeton dataset shows deviations from local station measurements and the global hydrological model does not perfectly reproduce local scale hydrographs, the main discharge characteristics and precipitation patterns are represented well. The modeled natural river flows were adjusted for water demand and irrigation within the water resources model RIBASIM (both historical values and future scenarios). Potential hydropower capacity was assessed with the power market simulation model PoMo-C that considers both reservoir inflows obtained from RIBASIM and overall electricity generation costs. Results of the study show that climate change is unlikely to negatively affect the average potential of future hydropower production; it will likely make hydropower more profitable. Yet, the uncertainty in climate change projections remains large and risks are significant, adaptation strategies should ideally consider a worst case scenario to ensure robust power generation. Overall a diversified power generation portfolio, anchored in hydropower and supported by other renewables and fossil fuel-based energy sources, is the best solution for Tanzania

Implementation of an acoustic-based methane flux estimation methodology in the Eastern Siberian Arctic Sea

NASA Astrophysics Data System (ADS)

Weidner, E. F.; Weber, T. C.; Mayer, L. A.

2017-12-01

Quantifying methane flux originating from marine seep systems in climatically sensitive regions is of critically importance for current and future climate studies. Yet, the methane contribution from these systems has been difficult to estimate given the broad spatial scale of the ocean and the heterogeneity of seep activity. One such region is the Eastern Siberian Arctic Sea (ESAS), where bubble release into the shallow water column (<40 meters average depth) facilitates transport of methane to the atmosphere without oxidation. Quantifying the current seep methane flux from the ESAS is necessary to understand not only the total ocean methane budget, but also to provide baseline estimates against which future climate-induced changes can be measured. At the 2016 AGU fall meeting, we presented a new acoustic-based flux methodology using a calibrated broadband split-beam echosounder. The broad (14-24 kHz) bandwidth provides a vertical resolution of 10 cm, making possible the identification of single bubbles. After calibration using 64 mm copper sphere of known backscatter, the acoustic backscatter of individual bubbles is measured and compared to analytical models to estimate bubble radius. Additionally, bubbles are precisely located and traced upwards through the water column to estimate rise velocity. The combination of radius and rise velocity allows for gas flux estimation. Here, we follow up with the completed implementation of this methodology applied to the Herald Canyon region of the western ESAS. From the 68 recognized seeps, bubble radii and rise velocity were computed for more than 550 individual bubbles. The range of bubble radii, 1-6 mm, is comparable to those published by other investigators, while the radius dependent rise velocities are consistent with published models. Methane flux for the Herald Canyon region was estimated by extrapolation from individual seep flux values.

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

PubMed

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

2018-01-15

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

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

Arctic shipping emissions inventories and future scenarios

NASA Astrophysics Data System (ADS)

Corbett, J. J.; Lack, D. A.; Winebrake, J. J.; Harder, S.; Silberman, J. A.; Gold, M.

2010-10-01

This paper presents 5 km×5 km Arctic emissions inventories of important greenhouse gases, black carbon and other pollutants under existing and future (2050) scenarios that account for growth of shipping in the region, potential diversion traffic through emerging routes, and possible emissions control measures. These high-resolution, geospatial emissions inventories for shipping can be used to evaluate Arctic climate sensitivity to black carbon (a short-lived climate forcing pollutant especially effective in accelerating the melting of ice and snow), aerosols, and gaseous emissions including carbon dioxide. We quantify ship emissions scenarios which are expected to increase as declining sea ice coverage due to climate change allows for increased shipping activity in the Arctic. A first-order calculation of global warming potential due to 2030 emissions in the high-growth scenario suggests that short-lived forcing of ~4.5 gigagrams of black carbon from Arctic shipping may increase global warming potential due to Arctic ships' CO2 emissions (~42 000 gigagrams) by some 17% to 78%. The paper also presents maximum feasible reduction scenarios for black carbon in particular. These emissions reduction scenarios will enable scientists and policymakers to evaluate the efficacy and benefits of technological controls for black carbon, and other pollutants from ships.

Adapting wheat in Europe for climate change.

PubMed

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

2014-05-01

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

Unrealized Global Temperature Increase: Implications of Current Uncertainties

NASA Astrophysics Data System (ADS)

Schwartz, Stephen E.

2018-04-01

Unrealized increase in global mean surface air temperature (GMST) may result from the climate system not being in steady state with forcings and/or from cessation of negative aerosol forcing that would result from decreases in emissions. An observation-constrained method is applied to infer the dependence of Earth's climate sensitivity on forcing by anthropogenic aerosols within the uncertainty on that forcing given by the Fifth (2013) Assessment Report of the Intergovernmental Panel on Climate Change. Within these uncertainty ranges the increase in GMST due to temperature lag for future forcings held constant is slight (0.09-0.19 K over 20 years; 0.12-0.26 K over 100 years). However, the incremental increase in GMST that would result from a hypothetical abrupt cessation of sources of aerosols could be quite large but is highly uncertain, 0.1-1.3 K over 20 years. Decrease in CO2 abundance and forcing following abrupt cessation of emissions would offset these increases in GMST over 100 years by as little as 0.09 K to as much as 0.8 K. The uncertainties quantified here greatly limit confidence in projections of change in GMST that would result from any strategy for future reduction of emissions.

Quantifying the Terrestrial Surface Energy Fluxes Using Remotely-Sensed Satellite Data

NASA Astrophysics Data System (ADS)

Siemann, Amanda Lynn

The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the decrease in the available energy balances the decrease in the sensible heat flux. These datasets are useful for benchmarking climate models and LSM output at the global annual scale and the regional scale subject to the regional uncertainties and performance. Future work should improve the input data, particularly the temperature gradient and Zilitinkevich empirical constant, to reduce uncertainties.

Assessment of impact of climate change and adaptation strategies on maize production in Uganda

NASA Astrophysics Data System (ADS)

Kikoyo, Duncan A.; Nobert, Joel

2016-06-01

Globally, various climatic studies have estimated a reduction of crop yields due to changes in surface temperature and precipitation especially for the developing countries which is heavily dependent on agriculture and lacks resources to counter the negative effects of climate change. Uganda's economy and the wellbeing of its populace depend on rain-fed agriculture which is susceptible to climate change. This study quantified the impacts of climate change and variability in Uganda and how coping strategies can enhance crop production against climate change and/or variability. The study used statistical methods to establish various climate change and variability indicators across the country, and uses the FAO AquaCrop model to simulate yields under possible future climate scenarios with and without adaptation strategies. Maize, the most widely grown crop was used for the study. Meteorological, soil and crop data were collected for various districts representing the maize growing ecological zones in the country. Based on this study, it was found that temperatures have increased by up to 1 °C across much of Uganda since the 1970s, with rates of warming around 0.3 °C per decade across the country. High altitude, low rainfall regions experience the highest level of warming, with over 0.5 °C/decade recorded in Kasese. Rainfall is variable and does not follow a specific significant increasing or decreasing trend. For both future climate scenarios, Maize yields will reduce in excess of 4.7% for the fast warming-low rainfall climates but increase on average by 3.5% for slow warming-high rainfall regions, by 2050. Improved soil fertility can improve yields by over 50% while mulching and use of surface water management practices improve yields by single digit percentages. The use of fertilizer application needs to go hand in hand with other water management strategies since more yields as a result of the improved soil fertility leads to increased water stress, especially for the dry climates.

Quantifying the Global Fresh Water Budget: Capabilities from Current and Future Satellite Sensors

NASA Technical Reports Server (NTRS)

Hildebrand, Peter; Zaitchik, Benjamin

2007-01-01

The global water cycle is complex and its components are difficult to measure, particularly at the global scales and with the precision needed for assessing climate impacts. Recent advances in satellite observational capabilities, however, are greatly improving our knowledge of the key terms in the fresh water flux budget. Many components of the of the global water budget, e.g. precipitation, atmospheric moisture profiles, soil moisture, snow cover, sea ice are now routinely measured globally using instruments on satellites such as TRMM, AQUA, TERRA, GRACE, and ICESat, as well as on operational satellites. New techniques, many using data assimilation approaches, are providing pathways toward measuring snow water equivalent, evapotranspiration, ground water, ice mass, as well as improving the measurement quality for other components of the global water budget. This paper evaluates these current and developing satellite capabilities to observe the global fresh water budget, then looks forward to evaluate the potential for improvements that may result from future space missions as detailed by the US Decadal Survey, and operational plans. Based on these analyses, and on the goal of improved knowledge of the global fresh water budget under the effects of climate change, we suggest some priorities for the future, based on new approaches that may provide the improved measurements and the analyses needed to understand and observe the potential speed-up of the global water cycle under the effects of climate change.

The Future of Hydropower: Assessing the Impacts of Climate Change, Energy Prices and New Storage Technologies

NASA Astrophysics Data System (ADS)

Gaudard, Ludovic; Madani, Kaveh; Romerio, Franco

2016-04-01

The future of hydropower depends on various drivers, and in particular on climate change, electricity market evolution and innovation in new storage technologies. Their impacts on the power plants' profitability can widely differ in regards of scale, timing, and probability of occurrence. In this respect, the risk should not be expressed only in terms of expected revenue, but also of uncertainty. These two aspects must be considered to assess the future of hydropower. This presentation discusses the impacts of climate change, electricity market volatility and competing energy storage's technologies and quantifies them in terms of annual revenue. Our simulations integrate a glacio-hydrological model (GERM) with various electricity market data and models (mean reversion and jump diffusion). The medium (2020-50) and long-term (2070-2100) are considered thanks to various greenhouse gas scenarios (A1B, A2 and RCP3PD) and the stochastic approach for the electricity prices. An algorithm named "threshold acceptance" is used to optimize the reservoir operations. The impacts' scale, and the related uncertainties are presented for Mauvoisin, which is a storage-hydropower plant situated in the Swiss Alps, and two generic pure pumped-storage installations, which are assessed with the prices of 17 European electricity markets. The discussion will highlight the key differences between the impacts brought about by the drivers.

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

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2017-12-01

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

Drought impacts on children's respiratory health in the Brazilian Amazon

PubMed Central

Smith, Lauren T.; Aragão, Luiz E. O. C.; Sabel, Clive E.; Nakaya, Tomoki

2014-01-01

Drought conditions in Amazonia are associated with increased fire incidence, enhancing aerosol emissions with degradation in air quality. Quantifying the synergic influence of climate and human-driven environmental changes on human health is, therefore, critical for identifying climate change adaptation pathways for this vulnerable region. Here we show a significant increase (1.2%–267%) in hospitalisations for respiratory diseases in children under-five in municipalities highly exposed to drought. Aerosol was the primary driver of hospitalisations in drought affected municipalities during 2005, while human development conditions mitigated the impacts in 2010. Our results demonstrated that drought events deteriorated children's respiratory health particularly during 2005 when the drought was more geographically concentrated. This indicates that if governments act on curbing fire usage and effectively plan public health provision, as a climate change adaptation procedure, health quality would improve and public expenditure for treatment would decrease in the region during future drought events. PMID:24430803

The Role of Health Co-Benefits in the Development of Australian Climate Change Mitigation Policies

PubMed Central

Workman, Annabelle; Blashki, Grant; Karoly, David; Wiseman, John

2016-01-01

Reducing domestic carbon dioxide and other associated emissions can lead to short-term, localized health benefits. Quantifying and incorporating these health co-benefits into the development of national climate change mitigation policies may facilitate the adoption of stronger policies. There is, however, a dearth of research exploring the role of health co-benefits on the development of such policies. To address this knowledge gap, research was conducted in Australia involving the analysis of several data sources, including interviews carried out with Australian federal government employees directly involved in the development of mitigation policies. The resulting case study determined that, in Australia, health co-benefits play a minimal role in the development of climate change mitigation policies. Several factors influence the extent to which health co-benefits inform the development of mitigation policies. Understanding these factors may help to increase the political utility of future health co-benefits studies. PMID:27657098

Drought impacts on children's respiratory health in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Smith, Lauren T.; Aragão, Luiz E. O. C.; Sabel, Clive E.; Nakaya, Tomoki

2014-01-01

Drought conditions in Amazonia are associated with increased fire incidence, enhancing aerosol emissions with degradation in air quality. Quantifying the synergic influence of climate and human-driven environmental changes on human health is, therefore, critical for identifying climate change adaptation pathways for this vulnerable region. Here we show a significant increase (1.2%-267%) in hospitalisations for respiratory diseases in children under-five in municipalities highly exposed to drought. Aerosol was the primary driver of hospitalisations in drought affected municipalities during 2005, while human development conditions mitigated the impacts in 2010. Our results demonstrated that drought events deteriorated children's respiratory health particularly during 2005 when the drought was more geographically concentrated. This indicates that if governments act on curbing fire usage and effectively plan public health provision, as a climate change adaptation procedure, health quality would improve and public expenditure for treatment would decrease in the region during future drought events.

Vulnerability of two European lakes in response to future climatic changes

NASA Astrophysics Data System (ADS)

Danis, Pierre-Alain; von Grafenstein, Ulrich; Masson-Delmotte, Valérie; Planton, S.; Gerdeaux, D.; Moisselin, J.-M.

2004-11-01

Temperate deep freshwater lakes are important resources of drinking water and fishing, and regional key recreation areas. Their deep water often hosts highly specialised fauna surviving since glacial times. Theoretical and observational studies suggest a vulnerability of these hydro-ecosystems to reduced mixing and ventilation within the ongoing climatic change. Here we use a numerical thermal lake model, verified over the 20th century, to quantify the transient thermal behaviour of two European lakes in response to the observed 20th-century and predicted 21th-century climate changes. In contrast to Lac d'Annecy (France) which, after adaptation, maintains its modern mixing behaviour, Ammersee (Germany) is expected to undergo a dramatic and persistent lack of mixing starting from ~2020, when European air temperatures should be ~1°C warmer. The resulting lack of oxygenation will irreversibly destroy the deepwater fauna prevailing since 15 kyrs.

The Role of Health Co-Benefits in the Development of Australian Climate Change Mitigation Policies.

PubMed

Workman, Annabelle; Blashki, Grant; Karoly, David; Wiseman, John

2016-09-20

Reducing domestic carbon dioxide and other associated emissions can lead to short-term, localized health benefits. Quantifying and incorporating these health co-benefits into the development of national climate change mitigation policies may facilitate the adoption of stronger policies. There is, however, a dearth of research exploring the role of health co-benefits on the development of such policies. To address this knowledge gap, research was conducted in Australia involving the analysis of several data sources, including interviews carried out with Australian federal government employees directly involved in the development of mitigation policies. The resulting case study determined that, in Australia, health co-benefits play a minimal role in the development of climate change mitigation policies. Several factors influence the extent to which health co-benefits inform the development of mitigation policies. Understanding these factors may help to increase the political utility of future health co-benefits studies.

Science Overview: The LTTG Technology Review Meeting March 2006 Summary Report

NASA Technical Reports Server (NTRS)

Bruning, Claus; Ko, Malcolm; Lee, David; Miake-Lye, Richard

2006-01-01

This report presents an overview of the latest scientific consensus understanding of the effect of aviation emissions on the atmosphere for both local air quality and climate change in order to provide a contextual framework for raising future questions to help assess the environmental benefits of technology goals. Although studies of the two issues share a common framework (of quantifying the emissions, the change in concentrations in the atmosphere, and the environmental impacts), the communities of practitioners are distinctly different. The scientific community will continue to provide guidelines on trade-off among different contributors to a specific environmental impact, such as global climate, or local air quality. Ultimately, monetization of the costs and benefits of mitigation actions is the proper tool for quantifying and analyzing trade-offs between the two issues. Scientific assessment of the impacts and their uncertainties are critical inputs to these analyses. Until environmental effects of aviation emerge as a policy driven issue, there is little incentive within the scientific community to focus on research efforts specific to trade-off studies between local and global impacts.

A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.

PubMed

Nojavan A, Farnaz; Qian, Song S; Paerl, Hans W; Reckhow, Kenneth H; Albright, Elizabeth A

2014-06-15

The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nudging the Arctic Ocean to quantify Arctic sea ice feedbacks

NASA Astrophysics Data System (ADS)

Dekker, Evelien; Severijns, Camiel; Bintanja, Richard

2017-04-01

It is well-established that the Arctic is warming 2 to 3 time faster than rest of the planet. One of the great uncertainties in climate research is related to what extent sea ice feedbacks amplify this (seasonally varying) Arctic warming. Earlier studies have analyzed existing climate model output using correlations and energy budget considerations in order to quantify sea ice feedbacks through indirect methods. From these analyses it is regularly inferred that sea ice likely plays an important role, but details remain obscure. Here we will take a different and a more direct approach: we will keep the sea ice constant in a sensitivity simulation, using a state-of -the-art climate model (EC-Earth), applying a technique that has never been attempted before. This experimental technique involves nudging the temperature and salinity of the ocean surface (and possibly some layers below to maintain the vertical structure and mixing) to a predefined prescribed state. When strongly nudged to existing (seasonally-varying) sea surface temperatures, ocean salinity and temperature, we force the sea ice to remain in regions/seasons where it is located in the prescribed state, despite the changing climate. Once we obtain fixed' sea ice, we will run a future scenario, for instance 2 x CO2 with and without prescribed sea ice, with the difference between these runs providing a measure as to what extent sea ice contributes to Arctic warming, including the seasonal and geographical imprint of the effects.

The Land Use Model Intercomparison Project (LUMIP) Contribution to CMIP6: Rationale and Experimental Design

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Hurtt, G. C.; Arneth, A.; Brovkin, V.; Calvin, K. V.; Jones, A. D.; Jones, C.; Lawrence, P.; De Noblet-Ducoudré, N.; Pongratz, J.; Seneviratne, S. I.; Shevliakova, E.

2016-12-01

Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the questions: (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy and (3) Are there regional land-management strategies with promise to help mitigate against climate change? LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. Foci will include separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land-use, the unique impacts of land-cover change versus land management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent that CO2 fertilization is modulated by past and future land use. LUMIP involves three sets of activities: (1) development of an updated and expanded historical and future land-use dataset, (2) an experimental protocol for LUMIP experiments, and (3) definition of metrics that quantify model performance with respect to LULCC. LUMIP experiments are designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate. LUMIP also includes simulations that allow quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. We will present the experimental protocol in detail, explain the rationale, outlines plans for analysis, and describe a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types).

Applying Metrological Techniques to Satellite Fundamental Climate Data Records

NASA Astrophysics Data System (ADS)

Woolliams, Emma R.; Mittaz, Jonathan PD; Merchant, Christopher J.; Hunt, Samuel E.; Harris, Peter M.

2018-02-01

Quantifying long-term environmental variability, including climatic trends, requires decadal-scale time series of observations. The reliability of such trend analysis depends on the long-term stability of the data record, and understanding the sources of uncertainty in historic, current and future sensors. We give a brief overview on how metrological techniques can be applied to historical satellite data sets. In particular we discuss the implications of error correlation at different spatial and temporal scales and the forms of such correlation and consider how uncertainty is propagated with partial correlation. We give a form of the Law of Propagation of Uncertainties that considers the propagation of uncertainties associated with common errors to give the covariance associated with Earth observations in different spectral channels.

Tracking an atmospheric river in a warmer climate: from water vapor to economic impacts

NASA Astrophysics Data System (ADS)

Dominguez, Francina; Dall'erba, Sandy; Huang, Shuyi; Avelino, Andre; Mehran, Ali; Hu, Huancui; Schmidt, Arthur; Schick, Lawrence; Lettenmaier, Dennis

2018-03-01

Atmospheric rivers (ARs) account for more than 75 % of heavy precipitation events and nearly all of the extreme flooding events along the Olympic Mountains and western Cascade Mountains of western Washington state. In a warmer climate, ARs in this region are projected to become more frequent and intense, primarily due to increases in atmospheric water vapor. However, it is unclear how the changes in water vapor transport will affect regional flooding and associated economic impacts. In this work we present an integrated modeling system to quantify the atmospheric-hydrologic-hydraulic and economic impacts of the December 2007 AR event that impacted the Chehalis River basin in western Washington. We use the modeling system to project impacts under a hypothetical scenario in which the same December 2007 event occurs in a warmer climate. This method allows us to incorporate different types of uncertainty, including (a) alternative future radiative forcings, (b) different responses of the climate system to future radiative forcings and (c) different responses of the surface hydrologic system. In the warming scenario, AR integrated vapor transport increases; however, these changes do not translate into generalized increases in precipitation throughout the basin. The changes in precipitation translate into spatially heterogeneous changes in sub-basin runoff and increased streamflow along the entire Chehalis main stem. Economic losses due to stock damages increase moderately, but losses in terms of business interruption are significant. Our integrated modeling tool provides communities in the Chehalis region with a range of possible future physical and economic impacts associated with AR flooding.

Japanese and Taiwanese pelagic longline fleet dynamics and the impacts of climate change in the southern Indian Ocean

NASA Astrophysics Data System (ADS)

Michael, P. E.; Wilcox, C.; Tuck, G. N.; Hobday, A. J.; Strutton, P. G.

2017-06-01

Climate change is projected to continue shifting the distribution of marine species, leading to changes in local assemblages and different interactions with human activities. With regard to fisheries, understanding the relationship between fishing fleets, target species catch per unit effort (CPUE), and the environment enhances our ability to anticipate fisher response and is an essential step towards proactive management. Here, we explore the potential impact of climate change in the southern Indian Ocean by modelling Japanese and Taiwanese pelagic longline fleet dynamics. We quantify the mean and variability of target species CPUE and the relative value and cost of fishing in different areas. Using linear mixed models, we identify fleet-specific effort allocation strategies most related to observed effort and predict the future distribution of effort and tuna catch under climate change for 2063-2068. The Japanese fleet's strategy targets high-value species and minimizes the variability in CPUE of the primary target species. Conversely, the Taiwanese strategy indicated flexible targeting of a broad range of species, fishing in areas of high and low variability in catch, and minimizing costs. The projected future mean and variability in CPUE across species suggest a slight increase in CPUE in currently high CPUE areas for most species. The corresponding effort projections suggest a slight increase in Japanese effort in the western and eastern study area, and Taiwanese effort increasing east of Madagascar. This approach provides a useful method for managers to explore the impacts of different fishing and fleet management strategies for the future.

Climate impacts of shipping and petroleum extraction in an unlocked Arctic ocean

NASA Astrophysics Data System (ADS)

Samset, B. H.; Berntsen, T.; Dahlsøren, S. B.; Eide, L. I.; Eide, M. S.; Fuglestvedt, J.; Glomsrød, S.; Lindholt, L.; Myhre, G.; Nilssen, T. B.; Peters, G. P.; Ødemark, K.

2012-04-01

Reductions in sea ice extent are expected to open up the Arctic region to increased volumes of ship traffic and petroleum extraction activities. Both of these potentially entail changes in concentrations of short-lived climate forcers (SLCFs) such as aerosols and ozone, which may impact the future climate. The response of the Arctic to SLCF emissions is however not well constrained, as the annual cycle, solar irradiation, surface albedo and ambient temperature are special to this region. The present study investigates the effects of SLCF emissions in the Arctic in 2004, as well as in 2030 and 2050. An emission inventory is used for present day activities, while future emissions are taken from models of the global energy market and shipping fleet. Atmospheric concentrations are input to the OsloCTM2 chemical transport model, and radiative forcings (RFs) are calculated using a multi-stream radiation transport code. Climate impacts are quantified via RFs and Global Warming Potentials of the various emitted components, in addition to estimates of the first indirect aerosol effect and the snow albedo effect from black carbon (BC). For present day emissions we calculate a net negative RF from shipping, mainly driven by the indirect aerosol effect, and a net positive RF from petroleum extraction, mainly due to the BC snow albedo effect. For future emissions the general results remain similar, but the total RFs develop with changes in emission volume and composition. We discuss the sensitivity of the Arctic region to emissions in terms of normalized RFs as function of season and geographical location.

Climate change increases deoxynivalenol contamination of wheat in north-western Europe.

PubMed

van der Fels-Klerx, H J; Olesen, J E; Madsen, M S; Goedhart, P W

2012-01-01

Climate change will affect the development of cereal crops and the occurrence of mycotoxins in these crops, but so far little research has been done on quantifying the expected effects. The aim of this study was to assess climate change impacts on the occurrence of deoxynivalenol in wheat grown in north-western Europe by 2040, considering the combined effects of shifts in wheat phenology and climate. The study used climate model data for the future period of 2031-2050 relative to the baseline period of 1975-1994. A weather generator was used for generating synthetic series of daily weather data for both the baseline and the future periods. Available models for wheat phenology and prediction of deoxynivalenol concentrations in north-western Europe were used. Both models were run for winter wheat and spring wheat, separately. The results showed that both flowering and full maturation of wheat will be earlier in the season because of climate change effects, about 1 to 2 weeks. Deoxynivalenol contamination was found to increase in most of the study region, with an increase of the original concentrations by up to 3 times. The study results may inform governmental and industrial risk managers to underpin decision-making and planning processes in north-western Europe. On the local level, deoxynivalenol contamination should be closely monitored to pick out wheat batches with excess levels at the right time. Using predictive models on a more local scale could be helpful to assist other monitoring measures to safeguard food safety in the wheat supply chain.

Projected increases in the annual flood pulse of the western Amazon

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Manz, Bastian; Veliz Rosas, Claudia; Willems, Patrick; Lavado-Casimiro, Waldo; Guyot, Jean-Loup; Santini, William

2016-04-01

The impact of a changing climate on the Amazon basin is a subject of intensive research due to its rich biodiversity and the significant role of rain forest in carbon cycling. Climate change has also direct hydrological impact, and there have been increasing efforts to understand such dynamics at continental and subregional scales such as the scale of the western Amazon. New projections from the Coupled Model Inter- comparison Project Phase 5 (CMIP5) ensemble indicate consistent climatic warming and increasing seasonality of precipitation in the Peruvian Amazon basin. Here we use a distributed land surface model to quantify the potential impact of this change in the climate on the hydrological regime of the river. Using extremes value analysis, historical and future projections of the annual minimum, mean, and maximum river flows are produced for a range of return periods between 1 and 100 years. We show that the RCP 4.5 and 8.5 scenarios of climate change project an increased severity of the wet season flood pulse (7.5% and 12% increases respectively for the 100- year return floods). These findings are in agreement with previously projected increases in high extremes under the Special Report on Emissions Scenarios (SRES) climate projections, and are important to highlight due to the potential consequences on reproductive processes of in-stream species, swamp forest ecology, and socio-economy in the floodplain, amid a growing literature that more strongly emphasises future droughts and their impact on the viability of the rain forest system over the greater Amazonia.

Perspectives on Hydro-Climatic Change in Rivers Sourced From the Khangai Mountains, Mongolia

NASA Astrophysics Data System (ADS)

Venable, N. B.; Fassnacht, S. R.; Tumenjargal, S.; Batbuyan, B.; Odgarav, J.; Sukhbataar, J.; Fernandez-Gimenez, M.; Adyabadam, G.

2012-12-01

Patterns of pastoralism have shaped the Mongolian countryside throughout history. These patterns are largely dictated by seasonal and extreme climate and water conditions. While change has always been a part of the traditional herder lifestyle, the magnitude and variety of impacts imposed by natural and human-induced changes in the last few decades has increased, negatively affecting the coupled natural-human systems of Mongolia. Regional hydrologic impacts from increased mining, irrigation, urbanization, and climate change are challenging to measure and model due to sparse and relatively short meteorological and hydrological records. Characterization of the variability inherent in Mongolian hydrological systems in the international literature remains limited. To quantify recent changes to these systems, several river basins near the Khangai Mountains were analyzed. These basins adjoin and include community-based managed and non-managed grazing lands under study as part of an ongoing National Science Foundation Coupled Natural and Human Systems (NSF-CNH) project. Statistically significant increasing temperatures and decreasing streamflows in the study areas support herder's perceptions of hydro-climatic changes and variability. The results of basin characterization combined with water balance modeling and trend analyses illustrate the future potential for further change in these hydro-climatic systems. Alternate land-uses and herder lifestyle modifications may amplify impacts from climatic change. Recent fieldwork also revealed complex surface-groundwater interactions in some areas that may affect model outcomes. Future explorations of longer-term variability through the use of proxies and the development of hydrologic scenarios will place the current basin analyses in context to more fully assess possible impacts to the hydrologic-human systems of Mongolia.

Quantifying Projected Heat Mortality Impacts under 21st-Century Warming Conditions for Selected European Countries

PubMed Central

Baccini, Michela; Wolf, Tanja; Paunovic, Elizabet; Menne, Bettina

2017-01-01

Under future warming conditions, high ambient temperatures will have a significant impact on population health in Europe. The aim of this paper is to quantify the possible future impact of heat on population mortality in European countries, under different climate change scenarios. We combined the heat-mortality function estimated from historical data with meteorological projections for the future time laps 2035–2064 and 2071–2099, developed under the Representative Concentration Pathways (RCP) 4.5 and 8.5. We calculated attributable deaths (AD) at the country level. Overall, the expected impacts will be much larger than the impacts we would observe if apparent temperatures would remain in the future at the observed historical levels. During the period 2071–2099, an overall excess of 46,690 and 117,333 AD per year is expected under the RCP 4.5 and RCP 8.5 scenarios respectively, in addition to the 16,303 AD estimated under the historical scenario. Mediterranean and Eastern European countries will be the most affected by heat, but a non-negligible impact will be still registered in North-continental countries. Policies and plans for heat mitigation and adaptation are needed and urgent in European countries in order to prevent the expected increase of heat-related deaths in the coming decades. PMID:28678192

Quantifying Projected Heat Mortality Impacts under 21st-Century Warming Conditions for Selected European Countries.

PubMed

Kendrovski, Vladimir; Baccini, Michela; Martinez, Gerardo Sanchez; Wolf, Tanja; Paunovic, Elizabet; Menne, Bettina

2017-07-05

Under future warming conditions, high ambient temperatures will have a significant impact on population health in Europe. The aim of this paper is to quantify the possible future impact of heat on population mortality in European countries, under different climate change scenarios. We combined the heat-mortality function estimated from historical data with meteorological projections for the future time laps 2035-2064 and 2071-2099, developed under the Representative Concentration Pathways (RCP) 4.5 and 8.5. We calculated attributable deaths (AD) at the country level. Overall, the expected impacts will be much larger than the impacts we would observe if apparent temperatures would remain in the future at the observed historical levels. During the period 2071-2099, an overall excess of 46,690 and 117,333 AD per year is expected under the RCP 4.5 and RCP 8.5 scenarios respectively, in addition to the 16,303 AD estimated under the historical scenario. Mediterranean and Eastern European countries will be the most affected by heat, but a non-negligible impact will be still registered in North-continental countries. Policies and plans for heat mitigation and adaptation are needed and urgent in European countries in order to prevent the expected increase of heat-related deaths in the coming decades.

Quantifying Future PM2.5 and Associated Health Effects Due to Changes in US Wildfires

NASA Astrophysics Data System (ADS)

Pierce, J. R.; Val Martin, M.; Ford, B.; Zelasky, S.; Heald, C. L.; Li, F.; Lawrence, D. M.; Fischer, E. V.

2017-12-01

Fine particulate matter (PM2.5) from landscape fires has been shown to adversely affect visibility, air quality and and health across the US. Fire activity is strongly related to climate and human activities. Predictions based on climate scenarios and future land cover projections that consider socioeconomic development suggest that fire activity will rise dramatically over the next decades. As PM2.5 is associated with increased mortality and morbidity rates, increases in emissions from landscape fires may alter the health burden on the US population. Here we present an analysis of the changes in future wildfire activity and consequences for PM2.5 and health over the US from 2000 to 2100. We employ the global Community Earth System Model (CESM) with the IPCC RCP projections. Within CESM, we use a process-based global fire parameterization to project future climate-driven and human-caused fire emissions. From these simulations, we determine the current and future impact on PM2.5 concentrations and visibility for different regions of the US, and we also calculate the mortality attributable to PM2.5 and wildfire-specific PM2.5 using existing concentration-response functions. Results show that although total PM2.5 concentrations in the US are projected to be similar in 2100 as in 2000, the dominant source of PM2.5 will change. Under the RCP8.5 climate projection and SSP3 population projection, non-fire emissions (mostly anthropogenic) are projected to decrease, but PM2.5 from CONUS and non-US wildfires is projected to increase from approximately 20% of all PM2.5 in 2000 to 80% of all PM2.5 in 2100. Furthermore, although the US population is expected to decline between 2000 and 2100, the mortality attributable to wildfire smoke is expected to increase from 25,000 deaths per year in 2000 to 75,000 deaths per year in 2100.

Flexibility in Flood Management Design: Proactive Planning Under Climate Change Uncertainty

NASA Astrophysics Data System (ADS)

Smet, K.; de Neufville, R.; van der Vlist, M.

2015-12-01

This paper presents an innovative, value-enhancing procedure for effective planning and design of long-lived flood management infrastructure given uncertain future flooding threats due to climate change. Designing infrastructure that can be adapted over time is a method to safeguard the efficacy of current design decisions given uncertainty about rates and future impacts of climate change. This paper explores the value of embedding "options" in a physical structure, where an option is the right but not the obligation to do something at a later date (e.g. over-dimensioning a floodwall foundation now facilitates a future height addition in response to observed increases in sea level; building of extra pump bays in a pumping station now enables the addition of pumping capacity whenever increased precipitation warrants an expansion.) The proposed procedure couples a simulation model that captures future climate induced changes to the hydrologic operating environment of a structure, with an economic model that estimates the lifetime economic performance of alternative investments. The economic model uses Real "In" Options analysis, a type of cash flow analysis that quantifies the implicit value of options and the flexibility they provide. This procedure is demonstrated using replacement planning for the multi-functional pumping station IJmuiden on the North Sea Canal in the Netherlands. Flexibility in design decisions is modelled, varying the size and specific options included in the new structure. Results indicate that the incorporation of options within the structural design has the potential to improve its economic performance, as compared to more traditional, "build it once and build it big" designs where flexibility is not an explicit design criterion. The added value resulting from the incorporation of flexibility varies with the range of future conditions considered, as well as the options examined. This procedure could be applied more broadly to explore investment strategies for the design of other flood management structures.

Observational determination of the greenhouse effect

NASA Technical Reports Server (NTRS)

Raval, A.; Ramanathan, V.

1989-01-01

Satellite measurements are used to quantify the atmospheric greenhouse effect, defined here as the infrared radiation energy trapped by atmospheric gases and clouds. The greenhouse effect is found to increase significantly with sea surface temperature. The rate of increase gives compelling evidence for the positive feedback between surface temperature, water vapor and the greenhouse effect; the magnitude of the feedback is consistent with that predicted by climate models. This study demonstrates an effective method for directly monitoring, from space, future changes in the greenhouse effect.

Vulnerability of the global terrestrial ecosystems to climate change.

PubMed

Li, Delong; Wu, Shuyao; Liu, Laibao; Zhang, Yatong; Li, Shuangcheng

2018-05-27

Climate change has far-reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short-term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems. © 2018 John Wiley & Sons Ltd.

Effects of climate change on the persistence and dispersal of foodborne bacterial pathogens in the outdoor environment: A review.

PubMed

Hellberg, Rosalee S; Chu, Eric

2016-08-01

According to the Intergovernmental Panel on Climate Change (IPCC), warming of the climate system is unequivocal. Over the coming century, warming trends such as increased duration and frequency of heat waves and hot extremes are expected in some areas, as well as increased intensity of some storm systems. Climate-induced trends will impact the persistence and dispersal of foodborne pathogens in myriad ways, especially for environmentally ubiquitous and/or zoonotic microorganisms. Animal hosts of foodborne pathogens are also expected to be impacted by climate change through the introduction of increased physiological stress and, in some cases, altered geographic ranges and seasonality. This review article examines the effects of climatic factors, such as temperature, rainfall, drought and wind, on the environmental dispersal and persistence of bacterial foodborne pathogens, namely, Bacillus cereus, Brucella, Campylobacter, Clostridium, Escherichia coli, Listeria monocytogenes, Salmonella, Staphylococcus aureus, Vibrio and Yersinia enterocolitica. These relationships are then used to predict how future climatic changes will impact the activity of these microorganisms in the outdoor environment and associated food safety issues. The development of predictive models that quantify these complex relationships will also be discussed, as well as the potential impacts of climate change on transmission of foodborne disease from animal hosts.

Unravelling connections between river flow and large-scale climate: experiences from Europe

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Kingston, D. G.; Lavers, D.; Stagge, J. H.; Tallaksen, L. M.

2016-12-01

The United Nations has identified better knowledge of large-scale water cycle processes as essential for socio-economic development and global water-food-energy security. In this context, and given the ever-growing concerns about climate change/ variability and human impacts on hydrology, there is an urgent research need: (a) to quantify space-time variability in regional river flow, and (b) to improve hydroclimatological understanding of climate-flow connections as a basis for identifying current and future water-related issues. In this paper, we draw together studies undertaken at the pan-European scale: (1) to evaluate current methods for assessing space-time dynamics for different streamflow metrics (annual regimes, low flows and high flows) and for linking flow variability to atmospheric drivers (circulation indices, air-masses, gridded climate fields and vapour flux); and (2) to propose a plan for future research connecting streamflow and the atmospheric conditions in Europe and elsewhere. We believe this research makes a useful, unique contribution to the literature through a systematic inter-comparison of different streamflow metrics and atmospheric descriptors. In our findings, we highlight the need to consider appropriate atmospheric descriptors (dependent on the target flow metric and region of interest) and to develop analytical techniques that best characterise connections in the ocean-atmosphere-land surface process chain. We call for the need to consider not only atmospheric interactions, but also the role of the river basin-scale terrestrial hydrological processes in modifying the climate signal response of river flows.

Climate change risk analysis framework (CCRAF) a probabilistic tool for analyzing climate change uncertainties

NASA Astrophysics Data System (ADS)

Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.

2003-04-01

Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000 variants per set of fixed input parameters. The shape and coefficients of CCRAF equations are derived from regression analyses of historic data and expert assessments. There are two types of random components in CCRAF - one reflects a year-to-year fluctuations around the expected value of a given variable (e.g., standard error of the annual GDP growth) and another is fixed within each CCRAF variant and represents some essential constants within a "world" represented by that variant (e.g., the value of climate sensitivity). Both types of random components are drawn from pre-defined probability distributions functions developed based on historic data or expert assessments. Preliminary CCRAF results emphasize the relative importance of uncertainties associated with the conversion of GHG and particulate emissions into radiative forcing and quantifying climate change effects at the regional level. A separates analysis involves an "adaptive decision-making", which optimizes the expected future policy effects given the estimated probabilistic uncertainties. As uncertainty for some variables evolve over the time steps, the decisions also adapt. This modeling approach is feasible only with explicit modeling of uncertainties.

Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity

NASA Astrophysics Data System (ADS)

Holmes, Keith Richard

Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity.

Determining the Current and Future Health of Low-Latitude Andean Glaciers Using an Equilibrium Line Altitude Model and Hypsometric Data from the Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.; MacAyeal, D. R.

2015-12-01

Mountain glaciers have been described as the water towers of world, and for many populations in the low-latitude South American Andes, glacial runoff is vital for agricultural, industrial, and basic water needs. Previous studies of low-latitude Andean glaciers suggest a precarious future due to contemporary warming. These studies have looked at trends in freezing level heights or observations of contemporary retreat. However, regional-scale understanding of low-latitude glacial responses to present and future climate change is limited, in part due to incomplete information about the extent and elevation distribution of low-latitude glaciers. The recently published Randolph Glacier Inventory (RGI) (5.0) provides the necessary information about the size and elevation distribution of low-latitude glaciers to begin such studies. We determine the contemporary equilibrium line altitudes (ELAs) for low-latitude Andean glaciers in the RGI, using a numerical energy balance ablation model driven with reanalysis and gridded data products. Contemporary ELAs tend to fall around the peak of the elevation histogram, with an exception being the southern-most outer tropical glaciers whose modeled ELAs tend to be higher than the elevation histogram for that region (see below figure). Also, we use the linear tends in temperature and precipitation from the contemporary climatology to extrapolate 21stcentury climate forcings. Modeled ELAs by the middle on the century are universally predicted to rise, with outer tropical ELAs rising more than the inner tropical glaciers. These trends continue through the end of the century. Finally, we explore how climate variables and parameters in our numerical model may vary for different warming scenarios from United Nation's IPCC AR5 report. We quantify the impacts of these changes on ELAs for various climate change trajectories. These results support previous work on the precarious future of low latitude Andean glaciers, while providing a richer understanding of the glacial impacts of contemporary and future warming. Also, this work provides analysis of processes and feedbacks between different climate variables important to glacier mass balances in a warming world, improving predictions for the fate of low-latitude Andean glaciers.

Collaborative Project. Understanding the effects of tides and eddies on the ocean dynamics, sea ice cover and decadal/centennial climate prediction using the Regional Arctic Climate Model (RACM)

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

Hutchings, Jennifer; Joseph, Renu

2013-09-14

The goal of this project is to develop an eddy resolving ocean model (POP) with tides coupled to a sea ice model (CICE) within the Regional Arctic System Model (RASM) to investigate the importance of ocean tides and mesoscale eddies in arctic climate simulations and quantify biases associated with these processes and how their relative contribution may improve decadal to centennial arctic climate predictions. Ocean, sea ice and coupled arctic climate response to these small scale processes will be evaluated with regard to their influence on mass, momentum and property exchange between oceans, shelf-basin, ice-ocean, and ocean-atmosphere. The project willmore » facilitate the future routine inclusion of polar tides and eddies in Earth System Models when computing power allows. As such, the proposed research addresses the science in support of the BER’s Climate and Environmental Sciences Division Long Term Measure as it will improve the ocean and sea ice model components as well as the fully coupled RASM and Community Earth System Model (CESM) and it will make them more accurate and computationally efficient.« less

Mid-Piacensian mean annual sea surface temperature: an analysis for data-model comparisons

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Foley, Kevin M.; Stoll, Danielle K.

2010-01-01

Numerical models of the global climate system are the primary tools used to understand and project climate disruptions in the form of future global warming. The Pliocene has been identified as the closest, albeit imperfect, analog to climate conditions expected for the end of this century, making an independent data set of Pliocene conditions necessary for ground truthing model results. Because most climate model output is produced in the form ofmean annual conditions, we present a derivative of the USGS PRISM3 Global Climate Reconstruction which integrates multiple proxies of sea surface temperature (SST) into single surface temperature anomalies. We analyze temperature estimates from faunal and floral assemblage data,Mg/Ca values and alkenone unsaturation indices to arrive at a single mean annual SST anomaly (Pliocene minus modern) best describing each PRISM site, understanding that multiple proxies should not necessarily show concordance. The power of themultiple proxy approach lies within its diversity, as no two proxies measure the same environmental variable. This data set can be used to verify climate model output, to serve as a starting point for model inter-comparisons, and for quantifying uncertainty in Pliocene model prediction in perturbed physics ensembles.

Challenges in Quantifying Pliocene Terrestrial Warming Revealed by Data-Model Discord

NASA Technical Reports Server (NTRS)

Salzmann, Ulrich; Dolan, Aisling M.; Haywood, Alan M.; Chan, Wing-Le; Voss, Jochen; Hill, Daniel J.; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Bragg, Frances J.; Chandler, Mark A.;

Projected effects of climate and development on California wildfire emissions through 2100.

PubMed

Hurteau, Matthew D; Westerling, Anthony L; Wiedinmyer, Christine; Bryant, Benjamin P

2014-02-18

Changing climatic conditions are influencing large wildfire frequency, a globally widespread disturbance that affects both human and natural systems. Understanding how climate change, population growth, and development patterns will affect the area burned by and emissions from wildfires and how populations will in turn be exposed to emissions is critical for climate change adaptation and mitigation planning. We quantified the effects of a range of population growth and development patterns in California on emission projections from large wildfires under six future climate scenarios. Here we show that end-of-century wildfire emissions are projected to increase by 19-101% (median increase 56%) above the baseline period (1961-1990) in California for a medium-high temperature scenario, with the largest emissions increases concentrated in northern California. In contrast to other measures of wildfire impacts previously studied (e.g., structural loss), projected population growth and development patterns are unlikely to substantially influence the amount of projected statewide wildfire emissions. However, increases in wildfire emissions due to climate change may have detrimental impacts on air quality and, combined with a growing population, may result in increased population exposure to unhealthy air pollutants.

Predicting shifting sustainability trade-offs in marine finfish aquaculture under climate change.

PubMed

Sarà, Gianluca; Gouhier, Tarik C; Brigolin, Daniele; Porporato, Erika M D; Mangano, Maria Cristina; Mirto, Simone; Mazzola, Antonio; Pastres, Roberto

2018-05-03

Defining sustainability goals is a crucial but difficult task because it often involves the quantification of multiple interrelated and sometimes conflicting components. This complexity may be exacerbated by climate change, which will increase environmental vulnerability in aquaculture and potentially compromise the ability to meet the needs of a growing human population. Here, we developed an approach to inform sustainable aquaculture by quantifying spatio-temporal shifts in critical trade-offs between environmental costs and benefits using the time to reach the commercial size as a possible proxy of economic implications of aquaculture under climate change. Our results indicate that optimizing aquaculture practices by minimizing impact (this study considers as impact a benthic carbon deposition ≥ 1 g C m -2  day -1 ) will become increasingly difficult under climate change. Moreover, an increasing temperature will produce a poleward shift in sustainability trade-offs. These findings suggest that future sustainable management strategies and plans will need to account for the effects of climate change across scales. Overall, our results highlight the importance of integrating environmental factors in order to sustainably manage critical natural resources under shifting climatic conditions. © 2018 John Wiley & Sons Ltd.

Climate-change-induced range shifts of three allergenic ragweeds (Ambrosia L.) in Europe and their potential impact on human health

PubMed Central

Muscarella, Robert; Borchsenius, Finn

2017-01-01

Invasive allergenic plant species may have severe health-related impacts. In this study we aim to predict the effects of climate change on the distribution of three allergenic ragweed species (Ambrosia spp.) in Europe and discuss the potential associated health impact. We built species distribution models based on presence-only data for three ragweed species, using MAXENT software. Future climatic habitat suitability was modeled under two IPCC climate change scenarios (RCP 6.0 and RCP 8.5). We quantify the extent of the increase in ‘high allergy risk’ (HAR) areas, i.e., parts of Europe with climatic conditions corresponding to the highest quartile (25%) of present day habitat suitability for each of the three species. We estimate that by year 2100, the distribution range of all three ragweed species increases towards Northern and Eastern Europe under all climate scenarios. HAR areas will expand in Europe by 27–100%, depending on species and climate scenario. Novel HAR areas will occur mostly in Denmark, France, Germany, Russia and the Baltic countries, and overlap with densely populated cities such as Paris and St. Petersburg. We conclude that areas in Europe affected by severe ragweed associated allergy problems are likely to increase substantially by year 2100, affecting millions of people. To avoid this, management strategies must be developed that restrict ragweed dispersal and establishment of new populations. Precautionary efforts should limit the spread of ragweed seeds and reduce existing populations. Only by applying cross-countries management plans can managers mitigate future health risks and economical consequences of a ragweed expansion in Europe. PMID:28321366

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.

Hydroclimatic Change in the Congo River Basin: Past, Present and Future169

NASA Astrophysics Data System (ADS)

Aloysius, N. R.

2016-12-01

Tropical regions provide habitat for the world's most diverse fauna and flora, sequester more atmospheric carbon and provide livelihood for millions of people. The hydrological cycle provides vital linkages for maintaining these ecosystem functions, yet, the understanding of its spatiotemporal variability is limited. Research on the hydrological cycle of the Congo River Basin (CRB), which encompasses the second largest rainforests, has been largely ignored. Global Climate Models (GCM) show limited skills in simulating CRB's climate and their future projections vary widely. Yet, GCMs provide the most plausible scenarios of future climate, based upon which changes in hydrologic fluxes can be predicted with the aid hydrological models. In order to address the gaps in knowledge and to highlight the research needs, we i) developed a spatially explicit hydrological model suitable for describing key hydrological processes, ii) evaluated the performance of GCMs in simulating precipitation and temperature in the region, iii) developed a set of climate change scenarios for the CRB and iv) developed a simplified modeling framework to quantify water management options for rain-fed agriculture with the objective of achieving the triple goals of sustainable development: food security, poverty alleviation and ecosystem conservation. The hydrology model, which was validated with observed stream flows at 50 locations, satisfactorily characterizes spatiotemporal variability of key fluxes. Our evaluation of 25 GCM outputs reveal that many GCMs poorly simulate regional precipitation. We implemented a statistical bias-correction method to develop precipitation and temperature projections for two future greenhouse gas emission scenarios. These climate forcings were, then, used to drive the hydrology model. Our results show that the near-term projections are not affected by emission scenarios. However, towards the mid-21st century, projections are emission scenario dependent. Available freshwater resources are projected to increase in the CRB, except in the semiarid southeast. Our findings have wider implications for climate change assessment and water resource management, because the region, with high population growth and limited capacity to adapt, are primary targets of land and water grabs. 155

Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C earth system model

NASA Astrophysics Data System (ADS)

Falloon, P. D.; Dankers, R.; Betts, R. A.; Jones, C. D.; Booth, B. B. B.; Lambert, F. H.

2012-06-01

The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios - the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20), allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario - one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C. In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in scrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during winter and spring); small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively) and increased global precipitation, with reductions in precipitation over the Amazon and increases over high latitudes. In general, changes were stronger over land - for example, global temperature changes due to interactive vegetation of 0.43 and 0.28 K under A1B and 2C20, respectively. Regionally, the warming influence of future vegetation change in our simulations was driven by the balance between driving factors. For instance, reduced tree cover over the Amazon reduced evaporation (particularly during summer), outweighing the cooling influence of any small albedo changes. In contrast, at high latitudes the warming impact of reduced albedo (particularly during winter and spring) due to increased vegetation cover appears to have offset any cooling due to small evaporation increases. Climate mitigation generally reduced the impact of vegetation change on future global and regional climate in our simulations. Our study therefore suggests that there is a need to consider both biogeochemical and biophysical effects in climate adaptation and mitigation decision making.

Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C Earth system model

NASA Astrophysics Data System (ADS)

Falloon, P. D.; Dankers, R.; Betts, R. A.; Jones, C. D.; Booth, B. B. B.; Lambert, F. H.

2012-11-01

The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios - the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20), allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario - one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C. In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in shrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during December-January and March-May); small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively) and increased global precipitation, with reductions in precipitation over the Amazon and increases over high latitudes. In general, changes were stronger over land - for example, global temperature changes due to interactive vegetation of 0.43 and 0.28 K under A1B and 2C20, respectively. Regionally, the warming influence of future vegetation change in our simulations was driven by the balance between driving factors. For instance, reduced tree cover over the Amazon reduced evaporation (particularly during June-August), outweighing the cooling influence of any small albedo changes. In contrast, at high latitudes the warming impact of reduced albedo (particularly during December-February and March-May) due to increased vegetation cover appears to have offset any cooling due to small evaporation increases. Climate mitigation generally reduced the impact of vegetation change on future global and regional climate in our simulations. Our study therefore suggests that there is a need to consider both biogeochemical and biophysical effects in climate adaptation and mitigation decision making.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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.

Quantifying the combined effects of land use and climate changes on stream flow and nutrient loads: A modelling approach in the Odense Fjord catchment (Denmark).

PubMed

Molina-Navarro, Eugenio; Andersen, Hans E; Nielsen, Anders; Thodsen, Hans; Trolle, Dennis

2018-04-15

Water pollution and water scarcity are among the main environmental challenges faced by the European Union, and multiple stressors compromise the integrity of water resources and ecosystems. Particularly in lowland areas of northern Europe, high population density, flood protection and, especially, intensive agriculture, are important drivers of water quality degradation. In addition, future climate and land use changes may interact, with uncertain consequences for water resources. Modelling approaches have become essential to address water issues and to evaluate ecosystem management. In this work, three multi-stressor future storylines combining climatic and socio-economic changes, defined at European level, have been downscaled for the Odense Fjord catchment (Denmark), giving three scenarios: High-Tech agriculture (HT), Agriculture for Nature (AN) and Market-Driven agriculture (MD). The impacts of these scenarios on water discharge and inorganic and organic nutrient loads to the streams have been simulated using the Soil and Water Assessment Tool (SWAT). The results revealed that the scenario-specific climate inputs were most important when simulating hydrology, increasing river discharge in the HT and MD scenarios (which followed the high emission 8.5 representative concentration pathway, RCP), while remaining stable in the AN scenario (RCP 4.5). Moreover, discharge was the main driver of changes in organic nutrients and inorganic phosphorus loads that consequently increased in a high emission scenario. Nevertheless, both land use (via inputs of fertilizer) and climate changes affected the nitrate transport. Different levels of fertilization yielded a decrease in the nitrate load in AN and an increase in MD. In HT, however, nitrate losses remained stable because the fertilization decrease was counteracted by a flow increase. Thus, our results suggest that N loads will ultimately depend on future land use and management in an interaction with climate changes, and this knowledge is of utmost importance for the achievement of European environmental policy goals. Copyright © 2017 Elsevier B.V. All rights reserved.

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

NASA Astrophysics Data System (ADS)

Sun, Shanlei; Sun, Ge; Cohen, Erika; McNulty, Steven G.; Caldwell, Peter V.; Duan, Kai; Zhang, Yang

2016-03-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8° C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 gC m-2 yr-1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr-1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

MIDWESTERN REGIONAL CENTER OF THE DOE NATIONAL INSTITUTE FOR CLIMATIC CHANGE RESEARCH

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

Burton, Andrew J.

2014-02-28

The goal of NICCR (National Institute for Climatic Change Research) was to mobilize university researchers, from all regions of the country, in support of the climatic change research objectives of DOE/BER. The NICCR Midwestern Regional Center (MRC) supported work in the following states: North Dakota, South Dakota, Nebraska, Kansas, Oklahoma, Minnesota, Iowa, Missouri, Wisconsin, Illinois, Michigan, Indiana, and Ohio. The MRC of NICCR was able to support nearly $8 million in climatic change research, including $6,671,303 for twenty projects solicited and selected by the MRC over five requests for proposals (RFPs) and $1,051,666 for the final year of ten projectsmore » from the discontinued DOE NIGEC (National Institute for Global Environmental Change) program. The projects selected and funded by the MRC resulted in 135 peer-reviewed publications and supported the training of 25 PhD students and 23 Masters students. Another 36 publications were generated by the final year of continuing NIGEC projects supported by the MRC. The projects funded by the MRC used a variety of approaches to answer questions relevant to the DOE’s climate change research program. These included experiments that manipulated temperature, moisture and other global change factors; studies that sought to understand how the distribution of species and ecosystems might change under future climates; studies that used measurements and modeling to examine current ecosystem fluxes of energy and mass and those that would exist under future conditions; and studies that synthesized existing data sets to improve our understanding of the effects of climatic change on terrestrial ecosystems. In all of these efforts, the MRC specifically sought to identify and quantify responses of terrestrial ecosystems that were not well understood or not well modeled by current efforts. The MRC also sought to better understand and model important feedbacks between terrestrial ecosystems, atmospheric chemistry, and regional and global climate systems. The broad variety of projects the MRC has supported gave us a unique opportunity to greatly improve our ability to predict the future health, composition and function of important agricultural and natural terrestrial ecosystems within the Midwestern Region.« less