Quantifying climate feedbacks in polar regions

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

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Quantifying climate feedbacks in polar regions

DOE PAGES

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.; ...

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

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.

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

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.

Uncertainties associated with quantifying climate change impacts on human health: a case study for diarrhea.

PubMed

Kolstad, Erik W; Johansson, Kjell Arne

2011-03-01

Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase. 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. 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. 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. 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.

Quantifying historical carbon and climate debts among nations

NASA Astrophysics Data System (ADS)

Matthews, H. Damon

2016-01-01

Contributions to historical climate change have varied substantially among nations. These differences reflect underlying inequalities in wealth and development, and pose a fundamental challenge to the implementation of a globally equitable climate mitigation strategy. This Letter presents a new way to quantify historical inequalities among nations using carbon and climate debts, defined as the amount by which national climate contributions have exceeded a hypothetical equal per-capita share over time. Considering only national CO2 emissions from fossil fuel combustion, accumulated carbon debts across all nations from 1990 to 2013 total 250 billion tonnes of CO2, representing 40% of cumulative world emissions since 1990. Expanding this to reflect the temperature response to a range of emissions, historical climate debts accrued between 1990 and 2010 total 0.11 °C, close to a third of observed warming over that period. Large fractions of this debt are carried by industrialized countries, but also by countries with high levels of deforestation and agriculture. These calculations could contribute to discussions of climate responsibility by providing a tangible way to quantify historical inequalities, which could then inform the funding of mitigation, adaptation and the costs of loss and damages in those countries that have contributed less to historical warming.

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

Development and Application of Future Climate Scenarios for Natural Resource Management in Southwestern Colorado

NASA Astrophysics Data System (ADS)

Rangwala, I.; Rondeau, R.; Wyborn, C.; Clifford, K. R.; Travis, W.

2015-12-01

Locally relevant projections of climate change provide critical insights for natural resource managers seeking to adapt their management activities to climate change in the context of uncertainty. To provide such information, we developed climate scenarios, in form of narratives and quantitative information, of future climate change and its impacts in southwestern Colorado. This information was intended to provide detailed insights into the range of changes that natural resource managers may face in the future. The scenarios were developed in an iterative process through interactions among the ecologists, social and climate scientists. In our scenario development process, climate uncertainty is acknowledged by having multiple scenarios, where each scenario is regarded as a storyline with equal likelihood as another scenario. We quantified changes in several decision relevant climate and ecological responses based on our best available understanding and provided a tight storyline for each scenario to facilitate (a) a more augmented use of scientific information in a decision-making process, (b) differential responses from stakeholders across the different scenarios, and (c) identification of strategies that could work across these multiple scenarios. Here, we discuss the process of selecting the scenarios, quantifying climate and ecological responses, and the criteria for building the narrative for each scenario. We also discuss the process by which these scenarios get used, and provide an assessment of their effectiveness and users' feedbacks that could inform the future development of these tools and processes. This research involvement and collaboration occurred, in part, as a result of the PACE Fellowship Program that is associated with NOAA Climate Program Office and the U.S. CLIVAR community.

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.

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.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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

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.

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

Quantifying the intra-annual uncertainties in climate change assessment over 10 sub-basins across the Pacific Northwest US

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

2017-04-01

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

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

Connecting today's climates to future climate analogs to facilitate movement of species under climate change.

PubMed

Littlefield, Caitlin E; McRae, Brad H; Michalak, Julia L; Lawler, Joshua J; Carroll, Carlos

2017-12-01

Increasing connectivity is an important strategy for facilitating species range shifts and maintaining biodiversity in the face of climate change. To date, however, few researchers have included future climate projections in efforts to prioritize areas for increasing connectivity. We identified key areas likely to facilitate climate-induced species' movement across western North America. Using historical climate data sets and future climate projections, we mapped potential species' movement routes that link current climate conditions to analogous climate conditions in the future (i.e., future climate analogs) with a novel moving-window analysis based on electrical circuit theory. In addition to tracing shifting climates, the approach accounted for landscape permeability and empirically derived species' dispersal capabilities. We compared connectivity maps generated with our climate-change-informed approach with maps of connectivity based solely on the degree of human modification of the landscape. Including future climate projections in connectivity models substantially shifted and constrained priority areas for movement to a smaller proportion of the landscape than when climate projections were not considered. Potential movement, measured as current flow, decreased in all ecoregions when climate projections were included, particularly when dispersal was limited, which made climate analogs inaccessible. Many areas emerged as important for connectivity only when climate change was modeled in 2 time steps rather than in a single time step. Our results illustrate that movement routes needed to track changing climatic conditions may differ from those that connect present-day landscapes. Incorporating future climate projections into connectivity modeling is an important step toward facilitating successful species movement and population persistence in a changing climate. © 2017 Society for Conservation Biology.

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.

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.

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.

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.

Quantifying uncertainty in future floods and drought conditions in the Northeastern United States using regionally downscaled climate projections

NASA Astrophysics Data System (ADS)

Siddique, R.; Wu, C.; Karmalkar, A.; Bradley, R. S.; Palmer, R. N.

2017-12-01

Northeastern region (NER) of the United States (US) has been projected to be a place where climate change can have the most severe impacts. These impacts include, but are not limited to, increases in the following: extreme precipitation events, temperature, flood magnitudes, flood frequencies, droughts, and sea level rise. In this study, we estimate the frequency of hydrological extremes under different climate change scenarios using regionally downscaled climate projections from a limited number of selected models from the fifth phase of Coupled Model Intercomparison Project (CMIP5). The models are chosen to minimize the loss of key climate information relevant to the NER. Precipitation and temperature from the selected models are forced into a distributed hydrological model called Hydrology Laboratory - Research Distributed Hydrological Model (HL-RDHM) to obtain streamflows for two different time regimes, near-term (20-50 years out) and long-term (50-80 years out). For this, two climate emission scenarios will be considered: RCP 4.5 and RCP 8.5. The impacts of the climate projections on the streamflows are then evaluated across different watershed scales in the NER. Among different metrics, we employ: 1) Flood Events - return period of 1 year, 10 year, 20 year, 50 year, and 100 year flood events and 2) Drought Events -low flow events associated with the 7-day 10 year low flow, number of days per month that will be below the historic monthly average, number of days per month that will be below the 25 percentile monthly historic average, changes in the 30-day and 60-day cumulative summer flows, and the timing and magnitude of spring run-off. For estimates of the climate impacts on low and high flows, only the unregulated watersheds are taken into consideration. Ensembles of streamflows obtained by forcing different climate projections are used to quantify and account for the associated uncertainties. Thus, the outcomes of this study are expected to guide regional

The impact of past and future climate change on global human mortality due to ozone and PM2.5 outdoor air pollution

NASA Astrophysics Data System (ADS)

Silva, R.; West, J.; Anenberg, S.; Lamarque, J.; Shindell, D. T.; Bergmann, D. J.; Berntsen, T.; Cameron-Smith, P. J.; Collins, B.; Ghan, S. J.; Josse, B.; Nagashima, T.; Naik, V.; Plummer, D.; Rodriguez, J. M.; Szopa, S.; Zeng, G.

2012-12-01

Climate change can adversely affect air quality, through changes in meteorology, atmospheric chemistry, and emissions. Future changes in air pollutant emissions will also profoundly influence air quality. These changes in air quality can affect human health, as exposure to ground-level ozone and fine particulate matter (PM2.5) has been associated with premature human mortality. Here we will quantify the global mortality impacts of past and future climate change, considering the effects of climate change on air quality isolated from emission changes. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has simulated the past and future surface concentrations of ozone and PM2.5 from each of several GCMs, for emissions from 1850 ("preindustrial") to 2000 ("present-day"), and for the IPCC AR5 Representative Concentration Pathways (RCPs) scenarios to 2100. We will use ozone and PM2.5 concentrations from simulations from five or more global models of atmospheric dynamics and chemistry, for a base year (present-day), pre-industrial conditions, and future scenarios, considering changes in climate and emissions. We will assess the mortality impacts of past climate change by using one simulation ensemble with present emissions and climate and one with present emissions but 1850 climate. We will similarly quantify the potential impacts of future climate change under the four RCP scenarios in 2030, 2050 and 2100. All model outputs will be regridded to the same resolution to estimate multi-model medians and range in each grid cell. Resulting premature deaths will be calculated using these medians along with epidemiologically-derived concentration-response functions, and present-day or future projections of population and baseline mortality rates, considering aging and transitioning disease rates over time. The spatial distributions of current and future global premature mortalities due to ozone and PM2.5 outdoor air pollution will be presented separately

The futures of climate engineering

NASA Astrophysics Data System (ADS)

Low, Sean

2017-01-01

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

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 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

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

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.

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

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.

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.

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.

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

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

Serious Simulation Role-Playing Games for Transformative Climate Change Education: "World Climate" and "Future Climate"

NASA Astrophysics Data System (ADS)

Rooney-Varga, J. N.; Sterman, J.; Sawin, E.; Jones, A.; Merhi, H.; Hunt, C.

2012-12-01

Climate change, its mitigation, and adaption to its impacts are among the greatest challenges of our times. Despite the importance of societal decisions in determining climate change outcomes, flawed mental models about climate change remain widespread, are often deeply entrenched, and present significant barriers to understanding and decision-making around climate change. Here, we describe two simulation role-playing games that combine active, affective, and analytical learning to enable shifts of deeply held conceptions about climate change. The games, World Climate and Future Climate, use a state-of-the-art decision support simulation, C-ROADS (Climate Rapid Overview and Decision Support) to provide users with immediate feedback on the outcomes of their mitigation strategies at the national level, including global greenhouse gas (GHG) emissions and concentrations, mean temperature changes, sea level rise, and ocean acidification. C-ROADS outcomes are consistent with the atmosphere-ocean general circulation models (AOGCMS), such as those used by the IPCC, but runs in less than one second on ordinary laptops, providing immediate feedback to participants on the consequences of their proposed policies. Both World Climate and Future Climate role-playing games provide immersive, situated learning experiences that motivate active engagement with climate science and policy. In World Climate, participants play the role of United Nations climate treaty negotiators. Participant emissions reductions proposals are continually assessed through interactive exploration of the best available science through C-ROADS. Future Climate focuses on time delays in the climate and energy systems. Participants play the roles of three generations: today's policymakers, today's youth, and 'just born.' The game unfolds in three rounds 25 simulated years apart. In the first round, only today's policymakers make decisions; In the next round, the young become the policymakers and inherit the

Future Warming Patterns Linked to Today's Climate Variability.

PubMed

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models' ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today's climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges

PubMed Central

Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map’s coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions. PMID:27618445

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges.

PubMed

Zanin, Marina; Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map's coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions.

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.

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

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

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

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.

An observationally centred method to quantify local climate change as a distribution

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2013-04-01

For planning and adaptation, guidance on trends in local climate is needed at the specific thresholds relevant to particular impact or policy endeavours. This requires quantifying trends at specific quantiles in distributions of variables such as daily temperature or precipitation. These non-normal distributions vary both geographically and in time. The trends in the relevant quantiles may not simply follow the trend in the distribution mean. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs how the trend or sensitivity varies with temperature (or occurrence likelihood), and with geographical location. These sensitivities are found to be geographically varying across Europe; as one would expect given the different influences on local climate between, say, Western Scotland and central Italy. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C

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

Design Life Level: Quantifying risk in a changing climate

NASA Astrophysics Data System (ADS)

Rootzén, Holger; Katz, Richard W.

2013-09-01

In the past, the concepts of return levels and return periods have been standard and important tools for engineering design. However, these concepts are based on the assumption of a stationary climate and do not apply to a changing climate, whether local or global. In this paper, we propose a refined concept, Design Life Level, which quantifies risk in a nonstationary climate and can serve as the basis for communication. In current practice, typical hydrologic risk management focuses on a standard (e.g., in terms of a high quantile corresponding to the specified probability of failure for a single year). Nevertheless, the basic information needed for engineering design should consist of (i) the design life period (e.g., the next 50 years, say 2015-2064); and (ii) the probability (e.g., 5% chance) of a hazardous event (typically, in the form of the hydrologic variable exceeding a high level) occurring during the design life period. Capturing both of these design characteristics, the Design Life Level is defined as an upper quantile (e.g., 5%) of the distribution of the maximum value of the hydrologic variable (e.g., water level) over the design life period. We relate this concept and variants of it to existing literature and illustrate how they, and some useful complementary plots, may be computed and used. One practically important consideration concerns quantifying the statistical uncertainty in estimating a high quantile under nonstationarity.

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

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

Determing Credibility of Regional Simulations of Future Climate

NASA Astrophysics Data System (ADS)

Mearns, L. O.

2009-12-01

Climate models have been evaluated or validated ever since they were first developed. Establishing that a climate model can reproduce (some) aspects of the current climate of the earth on various spatial and temporal scales has long been a standard procedure for providing confidence in the model's ability to simulate future climate. However, direct links between the successes and failures of models in reproducing the current climate with regard to what future climates the models simulate has been largely lacking. This is to say that the model evaluation process has been largely divorced from the projections of future climate that the models produce. This is evidenced in the separation in the Intergovernmental Panel on Climate Change (IPCC) WG1 report of the chapter on evaluation of models from the chapter on future climate projections. There has also been the assumption of 'one model, one vote, that is, that each model projection is given equal weight in any multi-model ensemble presentation of the projections of future climate. There have been various attempts at determing measures of credibility that would avoid the 'ultrademocratic' assumption of the IPCC. Simple distinctions between models were made by research such as in Giorgi and Mearns (2002), Tebaldi et al., (2005), and Greene et al., (2006). But the metrics used were rather simplistic. More ambitous means of discriminating among the quality of model simulations have been made through the production of complex multivariate metrics, but insufficent work has been produced to verify that the metrics successfully discriminate in meaningful ways. Indeed it has been suggested that we really don't know what a model must successfully model to establish confidence in its regional-scale projections (Gleckler et al., 2008). Perhaps a more process oriented regional expert judgment approach is needed to understand which errors in climate models really matter for the model's response to future forcing. Such an approach

Development of key indicators to quantify the health impacts of climate change on Canadians.

PubMed

Cheng, June J; Berry, Peter

2013-10-01

This study aimed at developing a list of key human health indicators for quantifying the health impacts of climate change in Canada. A literature review was conducted in OVID Medline to identify health morbidity and mortality indicators currently used to quantify climate change impacts. Public health frameworks and other studies of climate change indicators were reviewed to identify criteria with which to evaluate the list of proposed key indicators and a rating scale was developed. Total scores for each indicator were calculated based on the rating scale. A total of 77 health indicators were identified from the literature. After evaluation using the chosen criteria, 8 indicators were identified as the best for use. They include excess daily all-cause mortality due to heat, premature deaths due to air pollution (ozone and particulate matter 2.5), preventable deaths from climate change, disability-adjusted life years lost from climate change, daily all-cause mortality, daily non-accidental mortality, West Nile Disease incidence, and Lyme borreliosis incidence. There is need for further data and research related to health effect quantification in the area of climate change.

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

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

Patterns of crop cover under future climates.

PubMed

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

2017-04-01

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

The impact of future climate on historic interiors.

PubMed

Lankester, Paul; Brimblecombe, Peter

2012-02-15

The socio-economic significance of climate change is widely recognised. However, its potential to affect our cultural heritage has not been discussed in detail (i.e. not explicit in IPCC 4) even though the cultural impacts of future outdoor climate have been the focus of some European Commission projects (e.g. NOAH'S ARK) and World Heritage Centre reports. Recently there have been a few projects that have examined the changing environmental threats to tangible heritage indoors (e.g. Preparing Historic Collections for Climate Change and Climate for Culture). Here we predict future indoor temperature and humidity, and damage arising from changes to climate in historic rooms in Southern England with little climate control, using simple building simulations coupled with high resolution (~5 km) climate predictions. The calculations suggest an increase in indoor temperature over the next century that is slightly less than that outdoors. Annual relative humidity shows little change, but the seasonal cycles suggest drier summers and slightly damper winters indoors. Damage from mould growth and pests is likely to increase in the future, while humidity driven dimensional change to materials (e.g. wood) should decrease somewhat. The results allow collection managers to prepare for the impact of long-term climate change, putting strategic measures in place to prevent increased damage, and thus preserve our heritage for future generations. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

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

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.

Future warming patterns linked to today’s climate variability

DOE PAGES

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future warming patterns linked to today’s climate variability

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

Dai, Aiguo

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

QUANTIFYING AN UNCERTAIN FUTURE: HYDROLOGIC MODEL PERFORMANCE FOR A SERIES OF REALIZED "/FUTURE" CONDITIONS

EPA Science Inventory

A systematic analysis of model performance during simulations based on observed landcover/use change is used to quantify errors associated with simulations of known "future" conditions. Calibrated and uncalibrated assessments of relative change over different lengths of...

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.

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

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

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

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.

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.

Quantifying Livestock Heat Stress Impacts in the Sahel

NASA Astrophysics Data System (ADS)

Broman, D.; Rajagopalan, B.; Hopson, T. M.

2014-12-01

Livestock heat stress, especially in regions of the developing world with limited adaptive capacity, has a largely unquantified impact on food supply. Though dominated by ambient air temperature, relative humidity, wind speed, and solar radiation all affect heat stress, which can decrease livestock growth, milk production, reproduction rates, and mortality. Indices like the thermal-humidity index (THI) are used to quantify the heat stress experienced from climate variables. Livestock experience differing impacts at different index critical thresholds that are empirically determined and specific to species and breed. This lack of understanding has been highlighted in several studies with a limited knowledge of the critical thresholds of heat stress in native livestock breeds, as well as the current and future impact of heat stress,. As adaptation and mitigation strategies to climate change depend on a solid quantitative foundation, this knowledge gap has limited such efforts. To address the lack of study, we have investigated heat stress impacts in the pastoral system of Sub-Saharan West Africa. We used a stochastic weather generator to quantify both the historic and future variability of heat stress. This approach models temperature, relative humidity, and precipitation, the climate variables controlling heat stress. Incorporating large-scale climate as covariates into this framework provides a better historical fit and allows us to include future CMIP5 GCM projections to examine the climate change impacts on heat stress. Health and production data allow us to examine the influence of this variability on livestock directly, and are considered in conjunction with the confounding impacts of fodder and water access. This understanding provides useful information to decision makers looking to mitigate the impacts of climate change and can provide useful seasonal forecasts of heat stress risk. A comparison of the current and future heat stress conditions based on

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.

Climatic Change--Past, Present & Future

ERIC Educational Resources Information Center

Lindholm, Roy C.

1976-01-01

Presented is a review of studies investigating factors affecting climatic changes in the Earth's atmosphere--past, present, and future. Dating methods, particularly the Oxygen 18/16 method, are discussed. (SL)

Quantifying the Climate-Scale Accuracy of Satellite Cloud Retrievals

NASA Astrophysics Data System (ADS)

Roberts, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Liang, L.; Di Girolamo, L.

2014-12-01

Instrument calibration and cloud retrieval algorithms have been developed to minimize retrieval errors on small scales. However, measurement uncertainties and assumptions within retrieval algorithms at the pixel level may alias into decadal-scale trends of cloud properties. We first, therefore, quantify how instrument calibration changes could alias into cloud property trends. For a perfect observing system the climate trend accuracy is limited only by the natural variability of the climate variable. Alternatively, for an actual observing system, the climate trend accuracy is additionally limited by the measurement uncertainty. Drifts in calibration over time may therefore be disguised as a true climate trend. We impose absolute calibration changes to MODIS spectral reflectance used as input to the CERES Cloud Property Retrieval System (CPRS) and run the modified MODIS reflectance through the CPRS to determine the sensitivity of cloud properties to calibration changes. We then use these changes to determine the impact of instrument calibration changes on trend uncertainty in reflected solar cloud properties. Secondly, we quantify how much cloud retrieval algorithm assumptions alias into cloud optical retrieval trends by starting with the largest of these biases: the plane-parallel assumption in cloud optical thickness (τC) retrievals. First, we collect liquid water cloud fields obtained from Multi-angle Imaging Spectroradiometer (MISR) measurements to construct realistic probability distribution functions (PDFs) of 3D cloud anisotropy (a measure of the degree to which clouds depart from plane-parallel) for different ISCCP cloud types. Next, we will conduct a theoretical study with dynamically simulated cloud fields and a 3D radiative transfer model to determine the relationship between 3D cloud anisotropy and 3D τC bias for each cloud type. Combining these results provides distributions of 3D τC bias by cloud type. Finally, we will estimate the change in

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

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.

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.

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.

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.

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.

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.

State-dependent climate sensitivity in past warm climates and its implications for future climate projections.

PubMed

Caballero, Rodrigo; Huber, Matthew

2013-08-27

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow "Earth system" feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or "Charney" climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature.

Climate Change: Past, Present, and Future

NASA Astrophysics Data System (ADS)

Chapman, David S.; Davis, Michael G.

2010-09-01

Questions about global warming concern climate scientists and the general public alike. Specifically, what are the reliable surface temperature reconstructions over the past few centuries? And what are the best predictions of global temperature change the Earth might expect for the next century? Recent publications [National Research Council (NRC), 2006; Intergovernmental Panel on Climate Change (IPCC), 2007] permit these questions to be answered in a single informative illustration by assembling temperature reconstructions of the past thousand years with predictions for the next century. The result, shown in Figure 1, illustrates present and future warming in the context of natural variations in the past [see also Oldfield and Alverson, 2003]. To quote a Chinese proverb, “A picture's meaning can express ten thousand words.” Because it succinctly captures past inferences and future projections of climate, the illustration should be of interest to scientists, educators, policy makers, and the public.

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.

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

Warm climates of the past—a lesson for the future?

PubMed Central

Lunt, D. J.; Elderfield, H.; Pancost, R.; Ridgwell, A.; Foster, G. L.; Haywood, A.; Kiehl, J.; Sagoo, N.; Shields, C.; Stone, E. J.; Valdes, P.

2013-01-01

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10–11 October 2011. The Discussion Meeting, entitled ‘Warm climates of the past: a lesson for the future?’, brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change. PMID:24043873

Warm climates of the past--a lesson for the future?

PubMed

Lunt, D J; Elderfield, H; Pancost, R; Ridgwell, A; Foster, G L; Haywood, A; Kiehl, J; Sagoo, N; Shields, C; Stone, E J; Valdes, P

2013-10-28

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10-11 October 2011. The Discussion Meeting, entitled 'Warm climates of the past: a lesson for the future?', brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.

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.

Future local climate unlike currently observed anywhere

NASA Astrophysics Data System (ADS)

Dahinden, Fabienne; Fischer, Erich M.; Knutti, Reto

2017-08-01

The concept of spatial climate analogs, that is identifying a place with a present-day climate similar to the projections of a place of interest, is a promising method for visualizing and communicating possible effects of climate change. We show that when accounting for seasonal cycles of both temperature and precipitation, it is impossible to find good analogs for projections at many places across the world. For substantial land fractions, primarily in the tropics and subtropics, there are no analogs anywhere with current seasonal cycles of temperature and precipitation matching their projected future conditions. This implies that these places experience the emergence of novel climates. For 1.5 °C global warming about 15% and for 2 °C warming about 21% of the global land is projected to experience novel climates, whereas for a 4 °C warming the corresponding novel climates may emerge on more than a third of the global land fraction. Similar fractions of today’s climates, mainly found in the tropics, subtropics and polar north, are anticipated to disappear in the future. Note that the exact quantification of the land fraction is sensitive to the threshold selection. Novel and disappearing climates may have serious consequences for impacts that are sensitive to the full seasonal cycle of temperature and precipitation. For individual seasons, however, spatial analogs may still be a powerful tool for climate change communication.

Climate change and future fire regimes: Examples from California

USGS Publications Warehouse

Keeley, Jon E.; Syphard, Alexandra D.

2016-01-01

Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as

Genetic maladaptation of coastal Douglas-fir seedlings to future climates

Treesearch

Brad St. Clair;  Glenn T. Howe

2007-01-01

Climates are expected to warm considerably over the next century, resulting in expectations that plant populations will not be adapted to future climates.We estimated the risk of maladaptation of current populations of coastal Douglas-fir (Pseudotsuga menziesii var. menziesii) to future climates as the proportion of nonoverlap between two normal...

State-dependent climate sensitivity in past warm climates and its implications for future climate projections

PubMed Central

Caballero, Rodrigo; Huber, Matthew

2013-01-01

Projections of future climate depend critically on refined estimates of climate sensitivity. Recent progress in temperature proxies dramatically increases the magnitude of warming reconstructed from early Paleogene greenhouse climates and demands a close examination of the forcing and feedback mechanisms that maintained this warmth and the broad dynamic range that these paleoclimate records attest to. Here, we show that several complementary resolutions to these questions are possible in the context of model simulations using modern and early Paleogene configurations. We find that (i) changes in boundary conditions representative of slow “Earth system” feedbacks play an important role in maintaining elevated early Paleogene temperatures, (ii) radiative forcing by carbon dioxide deviates significantly from pure logarithmic behavior at concentrations relevant for simulation of the early Paleogene, and (iii) fast or “Charney” climate sensitivity in this model increases sharply as the climate warms. Thus, increased forcing and increased slow and fast sensitivity can all play a substantial role in maintaining early Paleogene warmth. This poses an equifinality problem: The same climate can be maintained by a different mix of these ingredients; however, at present, the mix cannot be constrained directly from climate proxy data. The implications of strongly state-dependent fast sensitivity reach far beyond the early Paleogene. The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state-dependent, but proxies and models are both consistent with significant increases in fast sensitivity with increasing temperature. PMID:23918397

Quantifying the effects of land use and climate on Holocene vegetation in Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph M.; Jönsson, Anna Maria; Smith, Benjamin; Kaplan, Jed O.; Alenius, Teija; Birks, H. John B.; Bjune, Anne E.; Christiansen, Jörg; Dodson, John; Edwards, Kevin J.; Giesecke, Thomas; Herzschuh, Ulrike; Kangur, Mihkel; Koff, Tiiu; Latałowa, Małgorzata; Lechterbeck, Jutta; Olofsson, Jörgen; Seppä, Heikki

2017-09-01

Early agriculture can be detected in palaeovegetation records, but quantification of the relative importance of climate and land use in influencing regional vegetation composition since the onset of agriculture is a topic that is rarely addressed. We present a novel approach that combines pollen-based REVEALS estimates of plant cover with climate, anthropogenic land-cover and dynamic vegetation modelling results. This is used to quantify the relative impacts of land use and climate on Holocene vegetation at a sub-continental scale, i.e. northern and western Europe north of the Alps. We use redundancy analysis and variation partitioning to quantify the percentage of variation in vegetation composition explained by the climate and land-use variables, and Monte Carlo permutation tests to assess the statistical significance of each variable. We further use a similarity index to combine pollen-based REVEALS estimates with climate-driven dynamic vegetation modelling results. The overall results indicate that climate is the major driver of vegetation when the Holocene is considered as a whole and at the sub-continental scale, although land use is important regionally. Four critical phases of land-use effects on vegetation are identified. The first phase (from 7000 to 6500 BP) corresponds to the early impacts on vegetation of farming and Neolithic forest clearance and to the dominance of climate as a driver of vegetation change. During the second phase (from 4500 to 4000 BP), land use becomes a major control of vegetation. Climate is still the principal driver, although its influence decreases gradually. The third phase (from 2000 to 1500 BP) is characterised by the continued role of climate on vegetation as a consequence of late-Holocene climate shifts and specific climate events that influence vegetation as well as land use. The last phase (from 500 to 350 BP) shows an acceleration of vegetation changes, in particular during the last century, caused by new farming

Potential economic benefits of adapting agricultural production systems to future climate change

USGS Publications Warehouse

Fagre, Daniel B.; Pederson, Gregory; Bengtson, Lindsey E.; Prato, Tony; Qui, Zeyuan; Williams, Jimmie R.

2010-01-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting

Potential economic benefits of adapting agricultural production systems to future climate change.

PubMed

Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E; Williams, Jimmy R

2010-03-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO(2) emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs

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.

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.

Global Agriculture Yields and Conflict under Future Climate

NASA Astrophysics Data System (ADS)

Rising, J.; Cane, M. A.

2013-12-01

Aspects of climate have been shown to correlate significantly with conflict. We investigate a possible pathway for these effects through changes in agriculture yields, as predicted by field crop models (FAO's AquaCrop and DSSAT). Using satellite and station weather data, and surveyed data for soil and management, we simulate major crop yields across all countries between 1961 and 2008, and compare these to FAO and USDA reported yields. Correlations vary by country and by crop, from approximately .8 to -.5. Some of this range in crop model performance is explained by crop varieties, data quality, and other natural, economic, and political features. We also quantify the ability of AquaCrop and DSSAT to simulate yields under past cycles of ENSO as a proxy for their performance under changes in climate. We then describe two statistical models which relate crop yields to conflict events from the UCDP/PRIO Armed Conflict dataset. The first relates several preceding years of predicted yields of the major grain in each country to any conflict involving that country. The second uses the GREG ethnic group maps to identify differences in predicted yields between neighboring regions. By using variation in predicted yields to explain conflict, rather than actual yields, we can identify the exogenous effects of weather on conflict. Finally, we apply precipitation and temperature time-series under IPCC's A1B scenario to the statistical models. This allows us to estimate the scale of the impact of future yields on future conflict. Centroids of the major growing regions for each country's primary crop, based on USDA FAS consumption. Correlations between simulated yields and reported yields, for AquaCrop and DSSAT, under the assumption that no irrigation, fertilization, or pest control is used. Reported yields are the average of FAO yields and USDA FAS yields, where both are available.

Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

NASA Astrophysics Data System (ADS)

Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

2012-04-01

Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

Quantifying climate change impacts on runoff of zoonotic pathogens from land

NASA Astrophysics Data System (ADS)

Sterk, Ankie; de Roda Husman, Ana Maria; Stergiadi, Maria; de Nijs, Ton; Schijven, Jack

2013-04-01

Several studies have shown a correlation between rainfall and waterborne disease outbreaks. One of the mechanisms whereby rainfall may cause outbreaks is through an increase in runoff of animal faeces from fields to surface waters. Faeces originating from wildlife, domestic animals or manure-fertilized fields, is considered an important source of zoonotic pathogens to which people may be exposed by water recreation or drinking-water consumption. Climate changes affect runoff because of increasing winter precipitation and more extreme precipitation events, as well as changes in evaporation. Furthermore, drier summers are leading to longer periods of high soil moisture deficits, increasing the hydrophobicity of soil and consequently changing infiltration capacities. A conceptual model is designed to describe the impacts of climate changes on the terrestrial and aquatic ecosystems, which are both directly and indirectly affecting pathogen loads in the environment and subsequent public health risks. One of the major outcomes was the lack of quantitative data and limited qualitative analyses of impacts of climate changes on pathogen runoff. Quantifying the processes by which micro-organisms are transported from fields to waters is important to be able to estimate such impacts to enable targeted implementation of effective intervention measures. A quantitative model using Mathematica software will be developed to estimate concentrations of pathogens originating from overland flow during runoff events. Different input sources will be included by applying different land-use scenarios, including point source faecal pollution from dairy cows and geese and diffuse source pollution by fertilization. Zoonotic pathogens, i.e. Cryptosporidium and Campylobacter, were selected based on transport properties, faecal loads and disease burden. Transport and survival rates of these pathogens are determined including effects of changes in precipitation but also temperature induced

Webinar Presentation: Particle-Resolved Simulations for Quantifying Black Carbon Climate Impact and Model Uncertainty

EPA Pesticide Factsheets

This presentation, Particle-Resolved Simulations for Quantifying Black Carbon Climate Impact and Model Uncertainty, was given at the STAR Black Carbon 2016 Webinar Series: Changing Chemistry over Time held on Oct. 31, 2016.

Climate Simulations of Past, Present and Future

NASA Technical Reports Server (NTRS)

Hansen, James E.

1999-01-01

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

DOE PAGES

Calvin, Kate; Fisher-Vanden, Karen

2017-10-27

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

NASA Astrophysics Data System (ADS)

Calvin, Kate; Fisher-Vanden, Karen

2017-11-01

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparison between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between -12% and +15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

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

Calvin, Kate; Fisher-Vanden, Karen

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

Quantifying Climate Feedbacks from Abrupt Changes in High-Latitude Trace-Gas Emissions

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

Schlosser, Courtney Adam; Walter-Anthony, Katey; Zhuang, Qianlai

2013-04-26

Our overall goal 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 extent to which these emissions provide a strong feedback mechanism to global climate warming. This goal is 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 in the extent of wetlands and lakes, especially thermokarst (thaw) lakes, over the Arctic. Through a coordinated effort of fieldmore » measurements, model development, and numerical experimentation with an integrated assessment model framework, we have investigated the following hypothesis: There exists a climate-warming threshold beyond which permafrost degradation becomes widespread and thus instigates strong and/or sharp increases in methane emissions (via thermokarst lakes and wetland expansion). These would outweigh any increased uptake of carbon (e.g. from peatlands) and would result in a strong, positive feedback to global climate warming.« less

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

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

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.

Understanding the Association Between School Climate and Future Orientation.

PubMed

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

2016-08-01

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

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.

Terrestrial Biosphere Dynamics in the Climate System: Past and Future

NASA Astrophysics Data System (ADS)

Overpeck, J.; Whitlock, C.; Huntley, B.

2002-12-01

The paleoenvironmental record makes it clear that climate change as large as is likely to occur in the next two centuries will drive change in the terrestrial biosphere that is both large and difficult to predict, or plan for. Many species, communities and ecosystems could experience rates of climate change, and "destination climates" that are unprecedented in their time on earth. The paleorecord also makes it clear that a wide range of possible climate system behavior, such as decades-long droughts, increases in large storm and flood frequency, and rapid sea level rise, all occurred repeatedly in the past, and for poorly understood reasons. These types of events, if they were to reoccur in the future, could have especially devastating impacts on biodiversity, both because their timing and spatial extent cannot be anticipated, and because the biota's natural defenses have been compromised by land-use, reductions in genetic flexibility, pollution, excess water utilization, invasive species, and other human influences. Vegetation disturbance (e.g., by disease, pests and fire) will undoubtedly be exacerbated by climate change (stress), but could also speed the rate at which terrestrial biosphere change takes place in the future. The paleoenvironmental record makes it clear that major scientific challenges include an improved ability to model regional biospheric change, both past and future. This in turn will be a prerequisite to obtaining realistic estimates of future biogeochemical and biophysical feedbacks, and thus to obtaining better assessments of future climate change. These steps will help generate the improved understanding of climate variability that is needed to manage global biodiversity. However, the most troubling message from the paleoenvironmental record is that unchecked anthropogenic climate change could make the Earth's 6th major mass extinction unavoidable.

Palaeoclimatic insights into future climate challenges.

PubMed

Alley, Richard B

2003-09-15

Palaeoclimatic data document a sensitive climate system subject to large and perhaps difficult-to-predict abrupt changes. These data suggest that neither the sensitivity nor the variability of the climate are fully captured in some climate-change projections, such as the Intergovernmental Panel on Climate Change (IPCC) Summary for Policymakers. Because larger, faster and less-expected climate changes can cause more problems for economies and ecosystems, the palaeoclimatic data suggest the hypothesis that the future may be more challenging than anticipated in ongoing policy making. Large changes have occurred repeatedly with little net forcing. Increasing carbon dioxide concentration appears to have globalized deglacial warming, with climate sensitivity near the upper end of values from general circulation models (GCMs) used to project human-enhanced greenhouse warming; data from the warm Cretaceous period suggest a similarly high climate sensitivity to CO(2). Abrupt climate changes of the most recent glacial-interglacial cycle occurred during warm as well as cold times, linked especially to changing North Atlantic freshwater fluxes. GCMs typically project greenhouse-gas-induced North Atlantic freshening and circulation changes with notable but not extreme consequences; however, such models often underestimate the magnitude, speed or extent of past changes. Targeted research to assess model uncertainties would help to test these hypotheses.

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.

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

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.

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.

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.

Quantifying Hydro-biogeochemical Model Sensitivity in Assessment of Climate Change Effect on Hyporheic Zone Processes

NASA Astrophysics Data System (ADS)

Song, X.; Chen, X.; Dai, H.; Hammond, G. E.; Song, H. S.; Stegen, J.

2016-12-01

The hyporheic zone is an active region for biogeochemical processes such as carbon and nitrogen cycling, where the groundwater and surface water mix and interact with each other with distinct biogeochemical and thermal properties. The biogeochemical dynamics within the hyporheic zone are driven by both river water and groundwater hydraulic dynamics, which are directly affected by climate change scenarios. Besides that, the hydraulic and thermal properties of local sediments and microbial and chemical processes also play important roles in biogeochemical dynamics. Thus for a comprehensive understanding of the biogeochemical processes in the hyporheic zone, a coupled thermo-hydro-biogeochemical model is needed. As multiple uncertainty sources are involved in the integrated model, it is important to identify its key modules/parameters through sensitivity analysis. In this study, we develop a 2D cross-section model in the hyporheic zone at the DOE Hanford site adjacent to Columbia River and use this model to quantify module and parametric sensitivity on assessment of climate change. To achieve this purpose, We 1) develop a facies-based groundwater flow and heat transfer model that incorporates facies geometry and heterogeneity characterized from a field data set, 2) derive multiple reaction networks/pathways from batch experiments with in-situ samples and integrate temperate dependent reactive transport modules to the flow model, 3) assign multiple climate change scenarios to the coupled model by analyzing historical river stage data, 4) apply a variance-based global sensitivity analysis to quantify scenario/module/parameter uncertainty in hierarchy level. The objectives of the research include: 1) identifing the key control factors of the coupled thermo-hydro-biogeochemical model in the assessment of climate change, and 2) quantify the carbon consumption in different climate change scenarios in the hyporheic zone.

Modeling of Greenland outlet glaciers response to future climate change

NASA Astrophysics Data System (ADS)

Beckmann, J.

2017-12-01

Over the past two decades net mass loss from the Greenland ice sheet (GIS) quadrupled, resulting in 25% of the global mean sea level (GMSL) rise. Increased mass loss of the GIS is caused by enhanced surface melting and speedup of the marine-terminating outlet glaciers. This speedup has been related, among other factors, to enhanced submarine melting, which in turn is caused by warming of the surrounding ocean and by increased subglacial, meltwater discharge. Yet, ice-ocean processes are not properly represented in contemporary Greenland Ice Sheet models used to project future changes in the GIS. In this work, we performed numerical experiments with a one-dimensional plume model coupled to a one-dimensional (depth- and width- integrated) ice flow model for several representative outlet glaciers in Greenland. We investigate the dynamic response of the coupled ice-flow plume model to scenarios of future climate change. In particular, we examine the transient response of the outlet glaciers to projected changes in surface melting, ocean temperature and subglacial discharge. With our modeling approach we quantify the amount of the surface and submarine melting and the resulting retreat and mass loss for each individual glacier for the next 100 years.

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.

Future climate stimulates population out-breaks by relaxing constraints on reproduction.

PubMed

Heldt, Katherine A; Connell, Sean D; Anderson, Kathryn; Russell, Bayden D; Munguia, Pablo

2016-09-14

When conditions are stressful, reproduction and population growth are reduced, but when favourable, reproduction and population size can boom. Theory suggests climate change is an increasingly stressful environment, predicting extinctions or decreased abundances. However, if favourable conditions align, such as an increase in resources or release from competition and predation, future climate can fuel population growth. Tests of such population growth models and the mechanisms by which they are enabled are rare. We tested whether intergenerational increases in population size might be facilitated by adjustments in reproductive success to favourable environmental conditions in a large-scale mesocosm experiment. Herbivorous amphipod populations responded to future climate by increasing 20 fold, suggesting that future climate might relax environmental constraints on fecundity. We then assessed whether future climate reduces variation in mating success, boosting population fecundity and size. The proportion of gravid females doubled, and variance in phenotypic variation of male secondary sexual characters (i.e. gnathopods) was significantly reduced. While future climate can enhance individual growth and survival, it may also reduce constraints on mechanisms of reproduction such that enhanced intra-generational productivity and reproductive success transfers to subsequent generations. Where both intra and intergenerational production is enhanced, population sizes might boom.

Adaptation to floods in future climate: a practical approach

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Impacts of climate change on the future of biodiversity.

PubMed

Bellard, Céline; Bertelsmeier, Cleo; Leadley, Paul; Thuiller, Wilfried; Courchamp, Franck

2012-04-01

Many studies in recent years have investigated the effects of climate change on the future of biodiversity. In this review, we first examine the different possible effects of climate change that can operate at individual, population, species, community, ecosystem and biome scales, notably showing that species can respond to climate change challenges by shifting their climatic niche along three non-exclusive axes: time (e.g. phenology), space (e.g. range) and self (e.g. physiology). Then, we present the principal specificities and caveats of the most common approaches used to estimate future biodiversity at global and sub-continental scales and we synthesise their results. Finally, we highlight several challenges for future research both in theoretical and applied realms. Overall, our review shows that current estimates are very variable, depending on the method, taxonomic group, biodiversity loss metrics, spatial scales and time periods considered. Yet, the majority of models indicate alarming consequences for biodiversity, with the worst-case scenarios leading to extinction rates that would qualify as the sixth mass extinction in the history of the earth. © 2012 Blackwell Publishing Ltd/CNRS.

Impacts of climate change on the future of biodiversity

PubMed Central

Leadley, Paul; Thuiller, Wilfried; Courchamp, Franck

2013-01-01

Many studies in recent years have investigated the effects of climate change on the future of biodiversity. In this review, we first examine the different possible effects of climate change that can operate at individual, population, species, community, ecosystem and biome scales, notably showing that species can respond to climate change challenges by shifting their climatic niche along three non-exclusive axes: time (e.g., phenology), space (e.g., range) and self (e.g., physiology). Then, we present the principal specificities and caveats of the most common approaches used to estimate future biodiversity at global and sub-continental scales and we synthesize their results. Finally, we highlight several challenges for future research both in theoretical and applied realms. Overall, our review shows that current estimates are very variable, depending on the method, taxonomic group, biodiversity loss metrics, spatial scales and time periods considered. Yet, the majority of models indicate alarming consequences for biodiversity, with the worst-case scenarios leading to extinction rates that would qualify as the sixth mass extinction in the history of the earth. PMID:22257223

Quantifying the Influence of Dynamics Across Scales on Regional Climate Uncertainty in Western North America

NASA Astrophysics Data System (ADS)

Goldenson, Naomi L.

Uncertainties in climate projections at the regional scale are inevitably larger than those for global mean quantities. Here, focusing on western North American regional climate, several approaches are taken to quantifying uncertainties starting with the output of global climate model projections. Internal variance is found to be an important component of the projection uncertainty up and down the west coast. To quantify internal variance and other projection uncertainties in existing climate models, we evaluate different ensemble configurations. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find internal variability can be quantified consistently using a large ensemble or an ensemble of opportunity that includes small ensembles from multiple models and climate scenarios. The latter offers the advantage of also producing estimates of uncertainty due to model differences. We conclude that climate projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible. We then conduct a small single-model ensemble of simulations using the Model for Prediction Across Scales with physics from the Community Atmosphere Model Version 5 (MPAS-CAM5) and prescribed historical sea surface temperatures. In the global variable resolution domain, the finest resolution (at 30 km) is in our region of interest over western North America and upwind over the northeast Pacific. In the finer-scale region, extreme precipitation from atmospheric rivers (ARs) is connected to tendencies in seasonal snowpack in mountains of the Northwest United States and California. In most of the Cascade Mountains, winters with more AR days are associated with less snowpack, in contrast to the northern Rockies and California's Sierra Nevadas. In snowpack observations and reanalysis of the atmospheric circulation, we find similar relationships between frequency of AR events and winter

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

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...

Quantifying the probability of record-setting heat events in the historical record and at different levels of climate forcing

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2017-12-01

Severe heat provides one of the most direct, acute, and rapidly changing impacts of climate on people and ecostystems. Theory, historical observations, and climate model simulations all suggest that global warming should increase the probability of hot events that fall outside of our historical experience. Given the acutre impacts of extreme heat, quantifying the probability of historically unprecedented hot events at different levels of climate forcing is critical for climate adaptation and mitigation decisions. However, in practice that quantification presents a number of methodological challenges. This presentation will review those methodological challenges, including the limitations of the observational record and of climate model fidelity. The presentation will detail a comprehensive approach to addressing these challenges. It will then demonstrate the application of that approach to quantifying uncertainty in the probability of record-setting hot events in the current climate, as well as periods with lower and higher greenhouse gas concentrations than the present.

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.

Quantifying the relative contribution of climate and human impacts on streamflow at seasonal scale

NASA Astrophysics Data System (ADS)

Xin, Z.; Zhang, L.; Li, Y.; Zhang, C.

2017-12-01

Both climate change and human activities have induced changes to hydrology. The quantification of their impacts on streamflow is a challenge, especially at the seasonal scale due to seasonality of climate and human impacts, i.e., water use for irrigation and water storage and release due to reservoir operation. In this study, the decomposition method based on the Budyko hypothesis is extended to the seasonal scale and is used to quantify the climate and human impacts on annual and seasonal streamflow changes. The results are further compared and verified with those simulated by the hydrological method of abcd model. Data are split into two periods (1953-1974 and 1975-2005) to quantify the change. Three seasons, including wet, dry and irrigation seasons are defined by introducing the monthly aridity index. In general, results showed a satisfactory agreement between the Budyko decomposition method and abcd model. Both climate change and human activities were found to induce a decrease in streamflow at the annual scale, with 67% of the change contributed by human activities. At the seasonal scale, the human-induced contribution to the reduced stream flow was 64% and 73% for dry and wet seasons, respectively; whereas in the irrigation season, the impact of human activities on reducing the streamflow was more pronounced (180%) since the climate contributes to increased streamflow. In addition, the quantification results were analyzed for each month in the wet season to reveal the effects of intense precipitation and reservoir operation rules during flood season.

Quantifying surface albedo and other direct biogeophysical climate forcings of forestry activities.

PubMed

Bright, Ryan M; Zhao, Kaiguang; Jackson, Robert B; Cherubini, Francesco

2015-09-01

By altering fluxes of heat, momentum, and moisture exchanges between the land surface and atmosphere, forestry and other land-use activities affect climate. Although long recognized scientifically as being important, these so-called biogeophysical forcings are rarely included in climate policies for forestry and other land management projects due to the many challenges associated with their quantification. Here, we review the scientific literature in the fields of atmospheric science and terrestrial ecology in light of three main objectives: (i) to elucidate the challenges associated with quantifying biogeophysical climate forcings connected to land use and land management, with a focus on the forestry sector; (ii) to identify and describe scientific approaches and/or metrics facilitating the quantification and interpretation of direct biogeophysical climate forcings; and (iii) to identify and recommend research priorities that can help overcome the challenges of their attribution to specific land-use activities, bridging the knowledge gap between the climate modeling, forest ecology, and resource management communities. We find that ignoring surface biogeophysics may mislead climate mitigation policies, yet existing metrics are unlikely to be sufficient. Successful metrics ought to (i) include both radiative and nonradiative climate forcings; (ii) reconcile disparities between biogeophysical and biogeochemical forcings, and (iii) acknowledge trade-offs between global and local climate benefits. We call for more coordinated research among terrestrial ecologists, resource managers, and coupled climate modelers to harmonize datasets, refine analytical techniques, and corroborate and validate metrics that are more amenable to analyses at the scale of an individual site or region. © 2015 John Wiley & Sons Ltd.

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

Climate mitigation and the future of tropical landscapes.

PubMed

Thomson, Allison M; Calvin, Katherine V; Chini, Louise P; Hurtt, George; Edmonds, James A; Bond-Lamberty, Ben; Frolking, Steve; Wise, Marshall A; Janetos, Anthony C

2010-11-16

Land-use change to meet 21st-century demands for food, fuel, and fiber will depend on many interactive factors, including global policies limiting anthropogenic climate change and realized improvements in agricultural productivity. Climate-change mitigation policies will alter the decision-making environment for land management, and changes in agricultural productivity will influence cultivated land expansion. We explore to what extent future increases in agricultural productivity might offset conversion of tropical forest lands to crop lands under a climate mitigation policy and a contrasting no-policy scenario in a global integrated assessment model. The Global Change Assessment Model is applied here to simulate a mitigation policy that stabilizes radiative forcing at 4.5 W m(-2) (approximately 526 ppm CO(2)) in the year 2100 by introducing a price for all greenhouse gas emissions, including those from land use. These scenarios are simulated with several cases of future agricultural productivity growth rates and the results downscaled to produce gridded maps of potential land-use change. We find that tropical forests are preserved near their present-day extent, and bioenergy crops emerge as an effective mitigation option, only in cases in which a climate mitigation policy that includes an economic price for land-use emissions is in place, and in which agricultural productivity growth continues throughout the century. We find that idealized land-use emissions price assumptions are most effective at limiting deforestation, even when cropland area must increase to meet future food demand. These findings emphasize the importance of accounting for feedbacks from land-use change emissions in global climate change mitigation strategies.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

The Future of Climate Science (Invited)

NASA Astrophysics Data System (ADS)

Bishop, R.

2010-12-01

High Performance Computing is currently deployed in several centers for climate research, but not at the levels needed to achieve substantial success on a global basis, given the complexity of the problem. A quantum leap in capabilities will be necessary to handle next-generation climate models that integrate newly emerging sciences, high-resolution grids, and voluminous observational data from satellites and sophisticated ground devices. Dr. Bishop will discuss efforts to build an International Centre for Earth Simulation (ICES) based in Switzerland that takes an holistic systems approach, and that has the competence and resources to achieve new insights in this new decade, and is capable to globally influence public policy with respect to weather, climate, environment, disaster risk reduction and socio-economic development. On this progressively crowded and fragile planet, such a capability will be invaluable, Bishop believes, if not imperative, for our long-term survival. ICES could serve as a test-bed for large scale public and private development planning. Decision makers could ask ‘what if’ questions for major construction projects (such as China’s Three Gorges Dam), and then interactively evaluate alternative scenarios. Likewise, ICES could help uncover the possible unintended consequences of climate remediation and adaptation strategies, geo-engineering ideas, CO2 sequestration, deep sea drilling, etc. ICES would be a resource for building more resilient societies in an era of rapid climate change and frequent natural disasters (such as flooding, extreme weather events and volcanic ash clouds), and therefore of great consequence to our future well-being. It would ultimately play a major role in the education and training of policy-makers, the public, and future Earth Scientists - in conjunction with the current national and regional centers.

Quantifying Tropical Glacier Mass Balance Sensitivity to Climate Change Through Regional-Scale Modeling and The Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.

2017-12-01

Quantifying mass balance sensitivity to climate change is essential for forecasting glacier evolution and deciphering climate signals embedded in archives of past glacier changes. Ideally, these quantifications result from decades of field measurement, remote sensing, and a hierarchy modeling approach, but in data-sparse regions, such as the Himalayas and tropical Andes, regional-scale modeling rooted in first principles provides a first-order picture. Previous regional-scaling modeling studies have applied a surface energy and mass balance approach in order to quantify equilibrium line altitude sensitivity to climate change. In this study, an expanded regional-scale surface energy and mass balance model is implemented to quantify glacier-wide mass balance sensitivity to climate change for tropical Andean glaciers. Data from the Randolph Glacier Inventory are incorporated, and additional physical processes are included, such as a dynamic albedo and cloud-dependent atmospheric emissivity. The model output agrees well with the limited mass balance records for tropical Andean glaciers. The dominant climate variables driving interannual mass balance variability differ depending on the climate setting. For wet tropical glaciers (annual precipitation >0.75 m y-1), temperature is the dominant climate variable. Different hypotheses for the processes linking wet tropical glacier mass balance variability to temperature are evaluated. The results support the hypothesis that glacier-wide mass balance on wet tropical glaciers is largely dominated by processes at the lowest elevation where temperature plays a leading role in energy exchanges. This research also highlights the transient nature of wet tropical glaciers - the vast majority of tropical glaciers and a vital regional water resource - in an anthropogenic warming world.

Future Climate Change in the Baltic Sea Area

NASA Astrophysics Data System (ADS)

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

2015-04-01

Regional climate models have been used extensively since the first assessment of climate change in the Baltic Sea region published in 2008, not the least for studies of Europe (and including the Baltic Sea catchment area). Therefore, conclusions regarding climate model results have a better foundation than was the case for the first BACC report of 2008. This presentation will report model results regarding future climate. What is the state of understanding about future human-driven climate change? We will cover regional models, statistical downscaling, hydrological modelling, ocean modelling and sea-level change as it is projected for the Baltic Sea region. Collections of regional model simulations from the ENSEMBLES project for example, financed through the European 5th Framework Programme and the World Climate Research Programme Coordinated Regional Climate Downscaling Experiment, have made it possible to obtain an increasingly robust estimation of model uncertainty. While the first Baltic Sea assessment mainly used four simulations from the European 5th Framework Programme PRUDENCE project, an ensemble of 13 transient regional simulations with twice the horizontal resolution reaching the end of the 21st century has been available from the ENSEMBLES project; therefore it has been possible to obtain more quantitative assessments of model uncertainty. The literature about future climate change in the Baltic Sea region is largely built upon the ENSEMBLES project. Also within statistical downscaling, a considerable number of papers have been published, encompassing now the application of non-linear statistical models, projected changes in extremes and correction of climate model biases. The uncertainty of hydrological change has received increasing attention since the previous Baltic Sea assessment. Several studies on the propagation of uncertainties originating in GCMs, RCMs, and emission scenarios are presented. The number of studies on uncertainties related to

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.

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.

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.

Impacts of fine particulate matter on premature mortality under future climate change

NASA Astrophysics Data System (ADS)

Park, S.; Allen, R.; Lim, C. H.

2016-12-01

Climate change modulates concentration of fine particulate matter (PM2.5) via modifying atmospheric circulation and the hydrological cycle. Furthermore, surface PM2.5 is significantly associated with respiratory diseases and premature mortality. In this study, we assess the response of PM2.5 concentration to climate change in the future (end of 21st century) and its effects on year of life lost (YLL) and premature mortality. We use outputs from five models participating in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) to evaluate climate change effects on PM2.5: for present climate with current aerosol emissions and greenhouse gas concentrations, and for future climate, also with present-day aerosol emissions, but with end-of-the century greenhouse gas concentrations, sea surface temperatures and sea-ice. The results show that climate change is associated with an increase in PM2.5 concentration. Combined with global future population data from the United Nation (UN), we also find an increase in premature mortality and YLL.

Using Paleo-climate Comparisons to Constrain Future Projections in CMIP5

NASA Technical Reports Server (NTRS)

Schmidt, G. A.; Annan, J D.; Bartlein, P. J.; Cook, B. I.; Guilyardi, E.; Hargreaves, J. C.; Harrison, S. P.; Kageyama, M.; LeGrande, A. N..; Konecky, B.;

Global climate change: the quantifiable sustainability challenge.

PubMed

Princiotta, Frank T; Loughlin, Daniel H

2014-09-01

Population growth and the pressures spawned by increasing demands for energy and resource-intensive goods, foods, and services are driving unsustainable growth in greenhouse gas (GHG) emissions. Recent GHG emission trends are consistent with worst-case scenarios of the previous decade. Dramatic and near-term emission reductions likely will be needed to ameliorate the potential deleterious impacts of climate change. To achieve such reductions, fundamental changes are required in the way that energy is generated and used. New technologies must be developed and deployed at a rapid rate. Advances in carbon capture and storage, renewable, nuclear and transportation technologies are particularly important; however, global research and development efforts related to these technologies currently appear to fall short relative to needs. Even with a proactive and international mitigation effort, humanity will need to adapt to climate change, but the adaptation needs and damages will be far greater if mitigation activities are not pursued in earnest. In this review, research is highlighted that indicates increasing global and regional temperatures and ties climate changes to increasing GHG emissions. GHG mitigation targets necessary for limiting future global temperature increases are discussed, including how factors such as population growth and the growing energy intensity of the developing world will make these reduction targets more challenging. Potential technological pathways for meeting emission reduction targets are examined, barriers are discussed, and global and US. modeling results are presented that suggest that the necessary pathways will require radically transformed electric and mobile sectors. While geoengineering options have been proposed to allow more time for serious emission reductions, these measures are at the conceptual stage with many unanswered cost, environmental, and political issues. Implications: This paper lays out the case that mitigating the

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Climate mitigation and the future of tropical landscapes

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

Thomson, Allison M.; Calvin, Katherine V.; Chini, Louise Parsons

2010-11-16

Land use change to meet 21st Century demands for food, fuel, and fiber will occur in the context of both a changing climate as well as societal efforts to mitigate climate change. This changing natural and human environment will have large consequences for forest resources, terrestrial carbon storage and emissions, and food and energy crop production over the next century. Any climate change mitigation policies enacted will change the environment under which land-use decisions are made and alter global land use change patterns. Here we use the GCAM integrated assessment model to explore how climate mitigation policies that achieve amore » climate stabilization at 4.5 W m-2 radiative forcing in 2100 and value carbon in terrestrial ecosystems interact with future agricultural productivity and food and energy demands to influence land use in the tropics. The regional land use results are downscaled from GCAM regions to produce gridded maps of tropical land use change. We find that tropical forests are preserved only in cases where a climate mitigation policy that values terrestrial carbon is in place, and crop productivity growth continues throughout the century. Crop productivity growth is also necessary to avoid large scale deforestation globally and enable the production of bioenergy crops. The terrestrial carbon pricing assumptions in GCAM are effective at avoiding deforestation even when cropland must expand to meet future food demand.« less

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.

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.

Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

NASA Technical Reports Server (NTRS)

Karunaratne, A. S.; Walker, S.; Ruane, A. C.

2015-01-01

Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

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

Precipitation forecast verification over Brazilian watersheds on present and future climate

NASA Astrophysics Data System (ADS)

Xavier, L.; Bruyere, C. L.; Rotunno, O.

2016-12-01

Evaluating the quality of precipitation forecast is an essential step for hydrological studies, among other applications, which is particularly relevant when taking into account climate change and the consequent likely modification of precipitation patterns. In this study we analyzed daily precipitation forecasts given by the global model CESM and the regional model WRF on present and future climate. For present runs, CESM data have been considered from 1980 to 2005, and WRF data from 1990 to 2000. CESM future runs were available for 3 RCP scenarios (4.5, 6.0 and 8.5), over 2005-2100 period; for WRF, future runs spanned 4 different 11-year periods (2020-2030, 2030-2040, 2050-2060 and 2080-2090). WRF simulations had been driven by bias-corrected forcings, and had been done on present climate for a 24 members ensemble created by varying the adopted parameterization schemes. On WRF future climate simulations, data from 3 members out of the original ensemble were available. Precipitation data have been spatially averaged over some large Brazilian watersheds (Amazon and subbasins, Tocantins, Sao Francisco, 4 of Parana`s subbasins) and have been evaluated for present climate against a gauge gridded dataset and ERA Interim data both spanning the 1980-2013 period. The evaluation was focused on the analysis of precipitation forecasts probabilities distribution. Taking into account daily and monthly mean precipitation aggregated on 3-month periods (DJF,MAM,JJA,SON), we adopted some skill measures, amongst them, the Perkins Skill Score (PSS). From the results we verified that on present climate WRF ensemble mean led to clearly better results when compared with CESM data for Amazon, Tocantins and Sao Francisco, but model was not as skillful to the other basins, which could be also been observed for future climate. PSS results from future runs showed that few changes would be observed over the different periods for the considered basins.

Future vegetation ecosystem response to warming climate over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Calibrating vascular plant abundance for detecting future climate changes in Oregon and Washington, USA

Treesearch

Timothy J. Brady; Vicente J. Monleon; Andrew N. Gray

2010-01-01

We propose using future vascular plant abundances as indicators of future climate in a way analogous to the reconstruction of past environments by many palaeoecologists. To begin monitoring future short-term climate changes in the forests of Oregon and Washington, USA, we developed a set of transfer functions for a present-day calibration set consisting of climate...

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

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

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

Olive cultivars adaptability in Southern Italy in present and future climate

NASA Astrophysics Data System (ADS)

Riccardi, M.; Alfieri, S.; Bonfante, A.; Basile, A.; Di Tommasi, P.; Menenti, M.; De Lorenzi, F.

2012-04-01

The intra-specific biodiversity of agricultural crops is very significant and likely to provide the single major opportunity to cope with the effects of the changing climate on agricultural ecosystems. Assessment of adaptive capacity must rely on quantitative descriptions of plant responses to environmental factors (e.g. soil water availability, temperature). Moreover climate scenario needs to be downscaled to the spatial scale relevant to crop and farm management. Distributed models of crop response to environmental forcing might be used for this purpose, but severely constrained by the very scarce knowledge on variety-specific values of model parameters, thus limiting the potential exploitation of intra-specific biodiversity towards adaptation. We have developed an approach towards this objective that relies on two complementary elements: a)a distributed model of the soil plant atmosphere system to downscale climate scenarios to landscape units, where generic model parameters for each species are used; b)a data base on climatic requirements of as many varieties as feasible for each species relevant to the agricultural production system of a given region. By means of this approach, the adaptability of some olive cultivars was evaluated in a composite (hills and plains) area of Southern Italy (Valle Telesina, Campania Region, about 20.000 ha). The yearly average temperature is 22.5 °C and rainfall ranges between 600 and 900 mm. Two different climate scenarios were considered: current climate (1961-1990) and future climate (2021-2050). Future climate scenarios at low spatial resolution were generated with general circulation models (AOGCM) and down-scaled by means of a statistical model (Tomozeiu et al., 2007). The climate was represented by daily observations of minimum, maximum temperature and precipitation on a regular grid with a spatial resolution of 35 km; 50 realizations were used for future climate. The soil water regime of 45 soil units was described for

Surface temperatures of the Mid-Pliocene North Atlantic Ocean: Implications for future climate

USGS Publications Warehouse

Dowsett, Harry J.; Chandler, Mark A.; Robinson, Marci M.

2009-01-01

The Mid-Pliocene is the most recent interval in the Earth's history to have experienced warming of the magnitude predicted for the second half of the twenty-first century and is, therefore, a possible analogue for future climate conditions. With continents basically in their current positions and atmospheric CO2 similar to early twenty-first century values, the cause of Mid-Pliocene warmth remains elusive. Understanding the behaviour of the North Atlantic Ocean during the Mid-Pliocene is integral to evaluating future climate scenarios owing to its role in deep water formation and its sensitivity to climate change. Under the framework of the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) sea surface reconstruction, we synthesize Mid-Pliocene North Atlantic studies by PRISM members and others, describing each region of the North Atlantic in terms of palaeoceanography. We then relate Mid-Pliocene sea surface conditions to expectations of future warming. The results of the data and climate model comparisons suggest that the North Atlantic is more sensitive to climate change than is suggested by climate model simulations, raising the concern that estimates of future climate change are conservative.

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

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 influence of global warming on unprecedented extreme climate events

PubMed Central

Singh, Deepti; Horton, Daniel E.; Swain, Daniel L.; Touma, Danielle; Charland, Allison; Liu, Yunjie; Haugen, Matz; Tsiang, Michael; Rajaratnam, Bala

2017-01-01

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent. PMID:28439005

Quantifying the influence of global warming on unprecedented extreme climate events.

PubMed

Diffenbaugh, Noah S; Singh, Deepti; Mankin, Justin S; Horton, Daniel E; Swain, Daniel L; Touma, Danielle; Charland, Allison; Liu, Yunjie; Haugen, Matz; Tsiang, Michael; Rajaratnam, Bala

2017-05-09

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent.

Quantifying the Influence of Global Warming on Unprecedented Extreme Climate Events

NASA Technical Reports Server (NTRS)

Diffenbaugh, Noah S.; Singh, Deepti; Mankin, Justin S.; Horton, Daniel E.; Swain, Daniel L.; Touma, Danielle; Charland, Allison; Liu, Yunjie; Haugen, Matz; Tsiang, Michael;

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Modeling climate and fuel reduction impacts on mixed-conifer forest carbon stocks in the Sierra Nevada, California

Treesearch

Matthew D. Hurteau; Timothy A. Robards; Donald Stevens; David Saah; Malcolm North; George W. Koch

2014-01-01

Quantifying the impacts of changing climatic conditions on forest growth is integral to estimating future forest carbon balance. We used a growth-and-yield model, modified for climate sensitivity, to quantify the effects of altered climate on mixed-conifer forest growth in the Lake Tahoe Basin, California. Estimates of forest growth and live tree carbon stocks were...

Future nutrient load scenarios for the Baltic Sea due to climate and lifestyle changes.

PubMed

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

2014-04-01

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

Next-generation invaders? Hotspots for naturalised sleeper weeds in Australia under future climates.

PubMed

Duursma, Daisy Englert; Gallagher, Rachael V; Roger, Erin; Hughes, Lesley; Downey, Paul O; Leishman, Michelle R

2013-01-01

Naturalised, but not yet invasive plants, pose a nascent threat to biodiversity. As climate regimes continue to change, it is likely that a new suite of invaders will emerge from the established pool of naturalised plants. Pre-emptive management of locations that may be most suitable for a large number of potentially invasive plants will help to target monitoring, and is vital for effective control. We used species distribution models (SDM) and invasion-hotspot analysis to determine where in Australia suitable habitat may occur for 292 naturalised plants. SDMs were built in MaxEnt using both climate and soil variables for current baseline conditions. Modelled relationships were projected onto two Representative Concentration Pathways for future climates (RCP 4.5 and 8.5), based on seven global climate models, for two time periods (2035, 2065). Model outputs for each of the 292 species were then aggregated into single 'hotspot' maps at two scales: continental, and for each of Australia's 37 ecoregions. Across Australia, areas in the south-east and south-west corners of the continent were identified as potential hotspots for naturalised plants under current and future climates. These regions provided suitable habitat for 288 and 239 species respectively under baseline climates. The areal extent of the continental hotspot was projected to decrease by 8.8% under climates for 2035, and by a further 5.2% by 2065. A similar pattern of hotspot contraction under future climates was seen for the majority of ecoregions examined. However, two ecoregions - Tasmanian temperate forests and Australian Alps montane grasslands - showed increases in the areal extent of hotspots of >45% under climate scenarios for 2065. The alpine ecoregion also had an increase in the number of naturalised plant species with abiotically suitable habitat under future climate scenarios, indicating that this area may be particularly vulnerable to future incursions by naturalised plants.

Next-Generation Invaders? Hotspots for Naturalised Sleeper Weeds in Australia under Future Climates

PubMed Central

Roger, Erin; Hughes, Lesley; Downey, Paul O.; Leishman, Michelle R.

2013-01-01

Naturalised, but not yet invasive plants, pose a nascent threat to biodiversity. As climate regimes continue to change, it is likely that a new suite of invaders will emerge from the established pool of naturalised plants. Pre-emptive management of locations that may be most suitable for a large number of potentially invasive plants will help to target monitoring, and is vital for effective control. We used species distribution models (SDM) and invasion-hotspot analysis to determine where in Australia suitable habitat may occur for 292 naturalised plants. SDMs were built in MaxEnt using both climate and soil variables for current baseline conditions. Modelled relationships were projected onto two Representative Concentration Pathways for future climates (RCP 4.5 and 8.5), based on seven global climate models, for two time periods (2035, 2065). Model outputs for each of the 292 species were then aggregated into single ‘hotspot’ maps at two scales: continental, and for each of Australia’s 37 ecoregions. Across Australia, areas in the south-east and south-west corners of the continent were identified as potential hotspots for naturalised plants under current and future climates. These regions provided suitable habitat for 288 and 239 species respectively under baseline climates. The areal extent of the continental hotspot was projected to decrease by 8.8% under climates for 2035, and by a further 5.2% by 2065. A similar pattern of hotspot contraction under future climates was seen for the majority of ecoregions examined. However, two ecoregions - Tasmanian temperate forests and Australian Alps montane grasslands - showed increases in the areal extent of hotspots of >45% under climate scenarios for 2065. The alpine ecoregion also had an increase in the number of naturalised plant species with abiotically suitable habitat under future climate scenarios, indicating that this area may be particularly vulnerable to future incursions by naturalised plants. PMID

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.

Impacts of climate variability and future climate change on harmful algal blooms and human health

Treesearch

Stephanie K. Moore; Vera L. Trainer; Nathan J. Mantua; Micaela S. Parker; Edward A. Laws; Lorraine C. Backer; Lora E. Fleming

2008-01-01

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes...

High-resolution dynamical downscaling of the future Alpine climate

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

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

[Effects of future climate change on climatic suitability of rubber plantation in China].

PubMed

Liu, Shao-jun; Zhou, Guang-sheng; Fang, Shi-bo; Zhang, Jing-hong

2015-07-01

Global warming may seriously affect the climatic suitability distribution of rubber plantation in China. Five main climate factors affecting rubber planting were mean temperature of the coldest month, mean extremely minimum temperature, the number of monthly, mean temperature ≥18 °C, annual mean temperature and annual mean precipitation. Climatic suitability areas of rubber plantation in 1981-2010, 2041-2060, 2061-2080 were analyzed by the maximum entropy model based on the five main climate factors and the climate data of 1981-2010 and RCP4.5 scenario data. The results showed that under the background of the future climate change, the climatic suitability area of rubber plantation would have a trend of expansion to the north in 2041-2060, 2061-2080. The climatic suitability areas of rubber plantation in 2041-2060 and 2061-2080 increased more obviously than in 1981-2010. The suitable area and optimum area would increase, while the less suitable area would decrease. The climatic suitability might change in some areas, such as the total suitable area would decrease in Yunnan Province, and the suitability grade in both Jinghong and Mengna would change from optimum area to suitable area. However, the optimum area of rubber plantation would increase significantly in Hainan Island and Leizhou Peninsula of Guangdong Province, and a new less suitable area of rubber planting would appear in Taiwan Island due to the climate change.

Ecoclimatic indicators to study crop suitability in present and future climatic conditions

NASA Astrophysics Data System (ADS)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been

Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Astrophysics Data System (ADS)

Das, K.; Kodali, A.; Szubert, M.; Ganguly, S.; Bongard, J.

2016-12-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this

Climate Twins - a tool to explore future climate impacts by assessing real world conditions: Exploration principles, underlying data, similarity conditions and uncertainty ranges

NASA Astrophysics Data System (ADS)

Loibl, Wolfgang; Peters-Anders, Jan; Züger, Johann

2010-05-01

To achieve public awareness and thorough understanding about expected climate changes and their future implications, ways have to be found to communicate model outputs to the public in a scientifically sound and easily understandable way. The newly developed Climate Twins tool tries to fulfil these requirements via an intuitively usable web application, which compares spatial patterns of current climate with future climate patterns, derived from regional climate model results. To get a picture of the implications of future climate in an area of interest, users may click on a certain location within an interactive map with underlying future climate information. A second map depicts the matching Climate Twin areas according to current climate conditions. In this way scientific output can be communicated to the public which allows for experiencing climate change through comparison with well-known real world conditions. To identify climatic coincidence seems to be a simple exercise, but the accuracy and applicability of the similarity identification depends very much on the selection of climate indicators, similarity conditions and uncertainty ranges. Too many indicators representing various climate characteristics and too narrow uncertainty ranges will judge little or no area as regions with similar climate, while too little indicators and too wide uncertainty ranges will address too large regions as those with similar climate which may not be correct. Similarity cannot be just explored by comparing mean values or by calculating correlation coefficients. As climate change triggers an alteration of various indicators, like maxima, minima, variation magnitude, frequency of extreme events etc., the identification of appropriate similarity conditions is a crucial question to be solved. For Climate Twins identification, it is necessary to find a right balance of indicators, similarity conditions and uncertainty ranges, unless the results will be too vague conducting a

Floridian heatwaves and extreme precipitation: future climate projections

NASA Astrophysics Data System (ADS)

Raghavendra, Ajay; Dai, Aiguo; Milrad, Shawn M.; Cloutier-Bisbee, Shealynn R.

2018-02-01

Observational analysis and climate modeling efforts concur that the frequency, intensity, and duration of heatwaves will increase as the Earth's mean climate shifts towards warmer temperatures. While the impacts and mechanisms of heatwaves have been well explored, extreme temperatures over Florida are generally understudied. This paper sheds light on Floridian heatwaves by exploring 13 years of daily data from surface observations and high-resolution WRF climate simulations for the same timeframe. The characteristics of the current and future heatwaves under the RCP8.5 high emissions scenario for 2070-2099 were then investigated. Results show a tripling in the frequency, and greater than a sixfold increase in the mean duration of heatwaves over Florida when the current standard of heatwaves was used. The intensity of heatwaves also increased by 4-6 °C due to the combined effects of rising mean temperatures and a 1-2 °C increase attributed to the flattening of the temperature distribution. Since Florida's atmospheric boundary layer is rich in moisture and heatwaves could further increase the moisture content in the lower troposphere, the relationship between heatwaves and extreme precipitation was also explored in both the current and future climate. As expected, rainfall during a heatwave event was anomalously low, but it quickly recovered to normal within 3 days after the passage of a heatwave. Finally, the late 21st-century climate could witness a slight decrease in the mean precipitation over Florida, accompanied by heavier heatwave-associated extreme precipitation events over central and southern Florida.

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

Quantifying the effects of overgrazing on mountainous watershed vegetation dynamics under a changing climate.

PubMed

Hao, Lu; Pan, Cen; Fang, Di; Zhang, Xiaoyu; Zhou, Decheng; Liu, Peilong; Liu, Yongqiang; Sun, Ge

2018-10-15

Grazing is a major ecosystem disturbance in arid regions that are increasingly threatened by climate change. Understanding the long-term impacts of grazing on rangeland vegetation dynamics in a complex terrain in mountainous regions is important for quantifying dry land ecosystem services for integrated watershed management and climate change adaptation. However, data on the detailed long-term spatial distribution of grazing activities are rare, which prevents trend detection and environmental impact assessments of grazing. This study quantified the impacts of grazing on vegetation dynamics for the period of 1983-2010 in the Upper Heihe River basin, a complex multiple-use watershed in northwestern China. We also examined the relative contributions of grazing and climate to vegetation change using a dynamic grazing pressure method. Spatial grazing patterns and temporal dynamics were mapped at a 1 km × 1 km pixel scale using satellite-derived leaf area index (LAI) data. We found that overgrazing was a dominant driver for LAI reduction in alpine grasslands and shrubs, especially for the periods of 1985-1991 and 1997-2004. Although the recent decade-long active grazing management contributed to the improvement of LAI and partially offset the negative effects of increased livestock, overgrazing has posed significant challenges to shrub-grassland ecosystem recovery in the eastern part of the study basin. We conclude that the positive effects of a warming and wetting climate on vegetation could be underestimated if the negative long-term grazing effects are not considered. Findings from the present case study show that assessing long-term climate change impacts on watersheds must include the influences of human activities. Our study provides important guidance for ecological restoration efforts in locating vulnerable areas and designing effective management practices in the study watershed. Such information is essential for natural resource management that aims

Future Effects of Southern Hemisphere Stratospheric Zonal Asymmetries on Climate

NASA Astrophysics Data System (ADS)

Stone, K.; Solomon, S.; Kinnison, D. E.; Fyfe, J. C.

2017-12-01

Stratospheric zonal asymmetries in the Southern Hemisphere have been shown to have significant influences on both stratospheric and tropospheric dynamics and climate. Accurate representation of stratospheric ozone in particular is important for realistic simulation of the polar vortex strength and temperature trends. This is therefore also important for stratospheric ozone change's effect on the troposphere, both through modulation of the Southern Annular Mode (SAM), and more localized climate. Here, we characterization the impact of future changes in Southern Hemisphere zonal asymmetry on tropospheric climate, including changes to future tropospheric temperature, and precipitation. The separate impacts of increasing GHGs and ozone recovery on the zonal asymmetric influence on the surface are also investigated. For this purpose, we use a variety of models, including Chemistry Climate Model Initiative simulations from the Community Earth System Model, version 1, with the Whole Atmosphere Community Climate Model (CESM1(WACCM)) and the Australian Community Climate and Earth System Simulator-Chemistry Climate Model (ACCESS-CCM). These models have interactive chemistry and can therefore more accurately represent the zonally asymmetric nature of the stratosphere. The CESM1(WACCM) and ACCESS-CCM models are also compared to simulations from the Canadian Can2ESM model and CESM-Large Ensemble Project (LENS) that have prescribed ozone to further investigate the importance of simulating stratospheric zonal asymmetry.

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

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.

Future heat stress arising from climate change on Iran's population health.

PubMed

Modarres, Reza; Ghadami, Mohammad; Naderi, Sohrab; Naderi, Mohammad

2018-04-05

Climate change-induced extreme heat events are becoming a major issue in different parts of the world, especially in developing countries. The assessment of regional and temporal past and future change in heat waves is a crucial task for public health strategies and managements. The historical and future heat index (HI) time series are investigated for temporal change across Iran to study the impact of global warming on public health. The heat index is calculated, and the nonparametric trend assessment is carried out for historical time series (1981-2010). The future change in heat index is also projected for 2020-2049 and 2070-2099 periods. A rise in the historical heat index and extreme caution conditions for summer and spring seasons for major parts of Iran are notable for historical (1981-2010) series in this study. Using different climate change scenarios shows that heat index will exceed the critical threshold for human adaptability in the future in the country. The impact of climate change on heat index risk in Iran is significant in the future. To cope with this crucial situation, developing early warning systems and health care strategies to deal with population growth and remarkable socio-economic features in future is essential.

Future heat stress arising from climate change on Iran's population health

NASA Astrophysics Data System (ADS)

Modarres, Reza; Ghadami, Mohammad; Naderi, Sohrab; Naderi, Mohammad

2018-04-01

Climate change-induced extreme heat events are becoming a major issue in different parts of the world, especially in developing countries. The assessment of regional and temporal past and future change in heat waves is a crucial task for public health strategies and managements. The historical and future heat index (HI) time series are investigated for temporal change across Iran to study the impact of global warming on public health. The heat index is calculated, and the nonparametric trend assessment is carried out for historical time series (1981-2010). The future change in heat index is also projected for 2020-2049 and 2070-2099 periods. A rise in the historical heat index and extreme caution conditions for summer and spring seasons for major parts of Iran are notable for historical (1981-2010) series in this study. Using different climate change scenarios shows that heat index will exceed the critical threshold for human adaptability in the future in the country. The impact of climate change on heat index risk in Iran is significant in the future. To cope with this crucial situation, developing early warning systems and health care strategies to deal with population growth and remarkable socio-economic features in future is essential.

Using High Resolution Regional Climate Models to Quantify the Snow Albedo Feedback in a Region of Complex Terrain

NASA Astrophysics Data System (ADS)

Letcher, T.; Minder, J. R.

2015-12-01

High resolution regional climate models are used to characterize and quantify the snow albedo feedback (SAF) over the complex terrain of the Colorado Headwaters region. Three pairs of 7-year control and pseudo global warming simulations (with horizontal grid spacings of 4, 12, and 36 km) are used to study how the SAF modifies the regional climate response to a large-scale thermodynamic perturbation. The SAF substantially enhances warming within the Headwaters domain, locally as much as 5 °C in regions of snow loss. The SAF also increases the inter-annual variability of the springtime warming within Headwaters domain under the perturbed climate. Linear feedback analysis is used quantify the strength of the SAF. The SAF attains a maximum value of 4 W m-2 K-1 during April when snow loss coincides with strong incoming solar radiation. On sub-seasonal timescales, simulations at 4 km and 12 km horizontal grid-spacing show good agreement in the strength and timing of the SAF, whereas a 36km simulation shows greater discrepancies that are tired to differences in snow accumulation and ablation caused by smoother terrain. An analysis of the regional energy budget shows that transport by atmospheric motion acts as a negative feedback to regional warming, damping the effects of the SAF. On the mesoscale, this transport causes non-local warming in locations with no snow. The methods presented here can be used generally to quantify the role of the SAF in other regional climate modeling experiments.

Past and future changes in climate and hydrological indicators in the US Northeast

USGS Publications Warehouse

Hayhoe, K.; Wake, C.P.; Huntington, T.G.; Luo, L.; Schwartz, M.D.; Sheffield, J.; Wood, E.; Anderson, B.; Bradbury, J.; DeGaetano, A.; Troy, T.J.; Wolfe, D.

2007-01-01

To assess the influence of global climate change at the regional scale, we examine past and future changes in key climate, hydrological, and biophysical indicators across the US Northeast (NE). We first consider the extent to which simulations of twentieth century climate from nine atmosphere-ocean general circulation models (AOGCMs) are able to reproduce observed changes in these indicators. We then evaluate projected future trends in primary climate characteristics and indicators of change, including seasonal temperatures, rainfall and drought, snow cover, soil moisture, streamflow, and changes in biometeorological indicators that depend on threshold or accumulated temperatures such as growing season, frost days, and Spring Indices (SI). Changes in indicators for which temperature-related signals have already been observed (seasonal warming patterns, advances in high-spring streamflow, decreases in snow depth, extended growing seasons, earlier bloom dates) are generally reproduced by past model simulations and are projected to continue in the future. Other indicators for which trends have not yet been observed also show projected future changes consistent with a warmer climate (shrinking snow cover, more frequent droughts, and extended low-flow periods in summer). The magnitude of temperature-driven trends in the future are generally projected to be higher under the Special Report on Emission Scenarios (SRES) mid-high (A2) and higher (A1FI) emissions scenarios than under the lower (B1) scenario. These results provide confidence regarding the direction of many regional climate trends, and highlight the fundamental role of future emissions in determining the potential magnitude of changes we can expect over the coming century. ?? Springer-Verlag 2006.

Shifts of regional hydro-climatic regimes in the warmer future

NASA Astrophysics Data System (ADS)

Kim, H.; Morishita, S.

2016-12-01

It is well known that the global climate is projected to be significantly warmer than pre-industrial period, and, in 2015, it was indicated as 1-degreen increase of global mean temperature that was unprecedented previously. Human-induced additional radiative forcing causes global and regional mean temperature increase and alters energy and water partitioning in the heterogeneous pathway. Budyko proposed a conceptual equation to estimate a climate-induced dryness relating available energy and precipitation, and it has been used broadly in hydrology communities to determine regional hydro-climatic characteristics. In this study, a diagnosis framework is proposed to traced how the regional hydro-climatic regimes are shifted under the warming condition with 4 °C increase of global mean temperature. A database for Policy Decision making for Future climate change (d4PDF) based on a super-ensemble AMIP-style experiment (11,400 model years, totally) with sea surface temperature patterns extracted from six CMIP5 models is used to estimate the probability distribution of the regime shifts maximizing signal-to-noise. It was found that the global future hydro-climate condition shifts slightly to more humid condition comparing to the historical condition, since the increase of precipitation is greater and the increate of net radiation, globally. Very humid regions including tropics and semi-arid regions tend to expand, and Semi-humid and arid-regions tend to shrink. Although the change of global mean state between historical and future climate is not considerable, temporal variability under the warming climate is amplified significantly, and it induces more frequent occurrence of once-in-a-century level drought over large terrestrial regions including Africa, South America, East and Central Asia, Australia, and United States. This analysis will be extended up to the availability (expected as October 2016) of a similar database being produced under the Half a degree Additional

Potential impact of future climate change on sugarcane under dryland conditions in Mexico

USDA-ARS?s Scientific Manuscript database

Assessments of impacts of future climate change on widely grown sugarcane varieties can guide decision-making at various levels and help ensure the economic stability of numerous rural households. This study assessed the potential impact of future climatic change on CP 72-2086 the most widely grown...

A simple technique for obtaining future climate data inputs for natural resource models

USDA-ARS?s Scientific Manuscript database

Those conducting impact studies using natural resource models need to be able to quickly and easily obtain downscaled future climate data from multiple models, scenarios, and timescales for multiple locations. This paper describes a method of quickly obtaining future climate data over a wide range o...

Changes of Mediterranean cyclones in the future climate employing high resolution climate simulations

NASA Astrophysics Data System (ADS)

Hatzaki, M.; Flocas, H. A.; Kouroutzoglou, J.; Keay, K.; Simmonds, I.; Giannakopoulos, C. A.; Brikolas, V.

2011-12-01

A number of studies suggest that cyclone activity over both hemispheres has changed over the second half of the 20th century. The assessment of the future changes of the cyclonic activity as imposed by global warming conditions is very important since these cyclones can be associated with extreme precipitation conditions, severe storms and floods. This is more important for the Mediterranean that has been found to be more vulnerable to climate change. The main objective of the current study is to better understand and assess future changes in the main characteristics of Mediterranean cyclones, including temporal and spatial variations of frequency of cyclonic tracks, and dynamic and kinematic parameters, such as intensity, size, propagation velocity, as well as trend analysis. For this purpose, the MPI-HH regional coupled climate model of the Max Planck Institute for Meteorology is employed consisting of the REgional atmosphere MOdel (REMO), the Max-Planck-Institute for Meteorology ocean model (MPI-OM) and the Hydrological Discharge Model (HD Model). A 25 km resolution domain is established on a rotated latitude-longitude coordinate system, while the physical parameterizations are taken from the global climate model ECHAM-4. These model data became available through the EU Project CIRCE which aims to perform, for the first time, climate change projections with a realistic representation of the Mediterranean Sea. The model results for the present climate are evaluated against ERA-40 Reanalysis (available through ECMWF), for the period 1962-2001. The identification and tracking of cyclones is performed with the aid of the Melbourne University algorithm (MS algorithm), according to the Lagrangian perspective. MS algorithm characterizes a cyclone only if a vorticity maximum could be connected with a local pressure minimum. According to the results, a decrease of the storm number and a tendency towards deeper cyclones is expected in the future, in general agreement with

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

PubMed

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

2018-01-01

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

Preserving the world second largest hypersaline lake under future irrigation and climate change.

PubMed

Shadkam, Somayeh; Ludwig, Fulco; van Vliet, Michelle T H; Pastor, Amandine; Kabat, Pavel

2016-07-15

Iran Urmia Lake, the world second largest hypersaline lake, has been largely desiccated over the last two decades resulting in socio-environmental consequences similar or even larger than the Aral Sea disaster. To rescue the lake a new water management plan has been proposed, a rapid 40% decline in irrigation water use replacing a former plan which intended to develop reservoirs and irrigation. However, none of these water management plans, which have large socio-economic impacts, have been assessed under future changes in climate and water availability. By adapting a method of environmental flow requirements (EFRs) for hypersaline lakes, we estimated annually 3.7·10(9)m(3) water is needed to preserve Urmia Lake. Then, the Variable Infiltration Capacity (VIC) hydrological model was forced with bias-corrected climate model outputs for both the lowest (RCP2.6) and highest (RCP8.5) greenhouse-gas concentration scenarios to estimate future water availability and impacts of water management strategies. Results showed a 10% decline in future water availability in the basin under RCP2.6 and 27% under RCP8.5. Our results showed that if future climate change is highly limited (RCP2.6) inflow can be just enough to meet the EFRs by implementing the reduction irrigation plan. However, under more rapid climate change scenario (RCP8.5) reducing irrigation water use will not be enough to save the lake and more drastic measures are needed. Our results showed that future water management plans are not robust under climate change in this region. Therefore, an integrated approach of future land-water use planning and climate change adaptation is therefore needed to improve future water security and to reduce the desiccating of this hypersaline lake. Copyright © 2016 Elsevier B.V. All rights reserved.

Assessment of future extreme climate events over the Porto wine Region

NASA Astrophysics Data System (ADS)

Viceto, Carolina; Cardoso, Susana; Marta-Almeida, Martinho; Gorodetskaya, Irina; Rocha, Alfredo

2017-04-01

The Douro Demarcated Region (DDR) is a wine region, in the northern Portugal, recognized for the Porto wine, which is responsible for more than 60% of the total value of national wine exportations. Since the viticulture is highly dependent on weather/climate patterns, the global warming is expected to affect the areas suitable to the growth of a certain variety of grape, its production and quality. This highlights the need of regional studies that assess the future climate changes effects in the vineyard, which might allow an early adjustment. We explore future climate change in the DDR region using a high-resolution regional climate model for Weather Research and Forecasting (WRF) forced by the Max Planck Institute Earth System Model - low resolution (MPI-ESM-LR). Two future periods have been simulated using the emission scenario RCP8.5 - for the mid- (2046-2065) and late 21st century (2081-2100) - and compared to a reference period (1986-2005). The RCP8.5 is a "baseline" scenario without any climate mitigation and corresponds to the pathway with the highest greenhouse gas emissions compared to other scenarios developed by the Intergovernmental Panel for Climate Change. Our regional WRF implementation uses three online-nested domains with increasing resolution at a downscaling ratio of three. The coarser domain of 81-km resolution covers part of the North Atlantic Ocean and most of the Europe. The innermost 9-km horizontal resolution domain includes the Iberian Peninsula, a portion of Northern Africa and the adjacent part of the Atlantic Ocean and Mediterranean Sea. Our study uses this 9-km resolution domain and focuses on a confined area, which comprises the DDR. Such dynamical downscaling approach gives an advantage to assess climate effects on the DDR region, where the high horizontal resolution allows including effects of the oceanic coastline, local riverbeds and complex topography. The climatology of the DDR region determines the more suitable wine variety

Projecting Future Heat-Related Mortality under Climate Change Scenarios: A Systematic Review

PubMed Central

Barnett, Adrian Gerard; Wang, Xiaoming; Vaneckova, Pavla; FitzGerald, Gerard; Tong, Shilu

2011-01-01

Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality. Objectives: We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios. Data sources and extraction: A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 through July 2010. Data synthesis: Fourteen studies fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding historical temperature–mortality relationships and considering the future changes in climate, population, and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution, and mortality displacement. Conclusions: Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality. PMID:21816703

Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

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.;

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

Quantifying the biophysical climate change mitigation potential of Canada's forest sector

NASA Astrophysics Data System (ADS)

Smyth, C. E.; Stinson, G.; Neilson, E.; Lemprière, T. C.; Hafer, M.; Rampley, G. J.; Kurz, W. A.

2014-01-01

The potential of forests and the forest sector to mitigate greenhouse gas (GHG) emissions is widely recognized, but challenging to quantify at a national scale. Forests and their carbon (C) sequestration potential are affected by management practices, where wood harvesting transfers C out of the forest into products, and subsequent regrowth allows further C sequestration. Here we determine the mitigation potential of the 2.3 × 106 km2 of Canada's managed forests from 2015 to 2050 using the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), a harvested wood products model that estimates emissions based on product half-life decay times, and an account of emission substitution benefits from the use of wood products and bioenergy. We examine several mitigation scenarios with different assumptions about forest management activity levels relative to a base-case scenario, including improved growth from silvicultural activities, increased harvest and residue management for bioenergy, and reduced harvest for conservation. We combine forest management options with two mitigation scenarios for harvested wood product use involving an increase in either long-lived products or bioenergy uses. Results demonstrate large differences among alternative scenarios, and we identify potential mitigation scenarios with increasing benefits to the atmosphere for many decades into the future, as well as scenarios with no net benefit over many decades. The greatest mitigation impact was achieved through a mix of strategies that varied across the country and had cumulative mitigation of 254 Tg CO2e in 2030, and 1180 Tg CO2e in 2050. We conclude that (i) national-scale forest sector mitigation options need to be assessed rigorously from a systems perspective to avoid the development of policies that deliver no net benefits to the atmosphere, (ii) a mix of strategies implemented across the country achieves the greatest mitigation impact, and (iii) because of the time delays in

Future fire probability modeling with climate change data and physical chemistry

Treesearch

Richard P. Guyette; Frank R. Thompson; Jodi Whittier; Michael C. Stambaugh; Daniel C. Dey

2014-01-01

Climate has a primary influence on the occurrence and rate of combustion in ecosystems with carbon-based fuels such as forests and grasslands. Society will be confronted with the effects of climate change on fire in future forests. There are, however, few quantitative appraisals of how climate will affect wildland fire in the United States. We demonstrated a method for...

Assessment of soil organic carbon stocks under future climate and land cover changes in Europe.

PubMed

Yigini, Yusuf; Panagos, Panos

2016-07-01

Soil organic carbon plays an important role in the carbon cycling of terrestrial ecosystems, variations in soil organic carbon stocks are very important for the ecosystem. In this study, a geostatistical model was used for predicting current and future soil organic carbon (SOC) stocks in Europe. The first phase of the study predicts current soil organic carbon content by using stepwise multiple linear regression and ordinary kriging and the second phase of the study projects the soil organic carbon to the near future (2050) by using a set of environmental predictors. We demonstrate here an approach to predict present and future soil organic carbon stocks by using climate, land cover, terrain and soil data and their projections. The covariates were selected for their role in the carbon cycle and their availability for the future model. The regression-kriging as a base model is predicting current SOC stocks in Europe by using a set of covariates and dense SOC measurements coming from LUCAS Soil Database. The base model delivers coefficients for each of the covariates to the future model. The overall model produced soil organic carbon maps which reflect the present and the future predictions (2050) based on climate and land cover projections. The data of the present climate conditions (long-term average (1950-2000)) and the future projections for 2050 were obtained from WorldClim data portal. The future climate projections are the recent climate projections mentioned in the Fifth Assessment IPCC report. These projections were extracted from the global climate models (GCMs) for four representative concentration pathways (RCPs). The results suggest an overall increase in SOC stocks by 2050 in Europe (EU26) under all climate and land cover scenarios, but the extent of the increase varies between the climate model and emissions scenarios. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

The future of terrestrial mammals in the Mediterranean basin under climate change

PubMed Central

Maiorano, Luigi; Falcucci, Alessandra; Zimmermann, Niklaus E.; Psomas, Achilleas; Pottier, Julien; Baisero, Daniele; Rondinini, Carlo; Guisan, Antoine; Boitani, Luigi

2011-01-01

The Mediterranean basin is considered a hotspot of biological diversity with a long history of modification of natural ecosystems by human activities, and is one of the regions that will face extensive changes in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting approach to model the future (approx. 2100) potential distribution under climate change considering five climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean mammals will be severely threatened by future climate change, particularly endemic species. Moreover, we found important changes in potential species richness owing to climate change, with some areas (e.g. montane region in central Italy) gaining species, while most of the region will be losing species (mainly Spain and North Africa). Existing protected areas (PAs) will probably be strongly influenced by climate change, with most PAs in Africa, the Middle East and Spain losing a substantial number of species, and those PAs gaining species (e.g. central Italy and southern France) will experience a substantial shift in species composition. PMID:21844047

Modelling of maize production in Croatia: present and future climate

PubMed Central

VUČETIĆ, V.

2011-01-01

SUMMARY Maize is one of the most important agricultural crops in Croatia, and was selected for research of the effect of climate warming on yields. The Decision Support System for the Agrotechnology Transfer model (DSSAT) is one of the most utilized crop–weather models in the world, and was used in this paper for the investigation of maize growth and production in the present and future climate. The impact of present climate on maize yield was studied using DSSAT 4.0 with meteorological data from the Zagreb–Maksimir station covering the period 1949–2004. Pedological, physiological and genetic data from a 1999 field maize experiment at the same location were added. The location is representative of the continental climate in central Croatia. The linear trends of model outputs and the non-parametric Mann–Kendall test indicate that the beginning of silking has advanced significantly by 1·4 days/decade since the mid-1990s, and maturity by 4·5 days/decade. It also shows a decrease in biomass by 122 kg/ha and in maize yield by 216 kg/ha in 10 years. Estimates of the sensitivity of maize growth and yield in future climates were made by changing the initial weather and CO2 conditions of the DSSAT 4.0 model according to the different climatic scenarios for Croatia at the end of the 21st century. Changed climate suggests increases in global solar radiation, minimal temperature and maximal temperature (×1·07, 2 and 4°C, respectively), but a decrease in the amount of precipitation (×0·92), compared with weather data from the period 1949–2004. The reduction of maize yield was caused by the increase in minimal and maximal temperature and the decrease in precipitation amount, related to the present climate, is 6, 12 and 3%, respectively. A doubling of CO2 concentration stimulates leaf assimilation, but maize yield is only 1% higher, while global solar radiation growth by 7% increases evapotranspiration by 3%. Simultaneous application of all these climate changes

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America

PubMed Central

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data. PMID:27275583

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America.

PubMed

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901-2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011-2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.

Quantifying Florida Bay habitat suitability for fishes and invertebrates under climate change scenarios.

PubMed

Kearney, Kelly A; Butler, Mark; Glazer, Robert; Kelble, Christopher R; Serafy, Joseph E; Stabenau, Erik

2015-04-01

The Florida Bay ecosystem supports a number of economically important ecosystem services, including several recreational fisheries, which may be affected by changing salinity and temperature due to climate change. In this paper, we use a combination of physical models and habitat suitability index models to quantify the effects of potential climate change scenarios on a variety of juvenile fish and lobster species in Florida Bay. The climate scenarios include alterations in sea level, evaporation and precipitation rates, coastal runoff, and water temperature. We find that the changes in habitat suitability vary in both magnitude and direction across the scenarios and species, but are on average small. Only one of the seven species we investigate (Lagodon rhomboides, i.e., pinfish) sees a sizable decrease in optimal habitat under any of the scenarios. This suggests that the estuarine fauna of Florida Bay may not be as vulnerable to climate change as other components of the ecosystem, such as those in the marine/terrestrial ecotone. However, these models are relatively simplistic, looking only at single species effects of physical drivers without considering the many interspecific interactions that may play a key role in the adjustment of the ecosystem as a whole. More complex models that capture the mechanistic links between physics and biology, as well as the complex dynamics of the estuarine food web, may be necessary to further understand the potential effects of climate change on the Florida Bay ecosystem.

Quantifying Florida Bay Habitat Suitability for Fishes and Invertebrates Under Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Kearney, Kelly A.; Butler, Mark; Glazer, Robert; Kelble, Christopher R.; Serafy, Joseph E.; Stabenau, Erik

2015-04-01

The Florida Bay ecosystem supports a number of economically important ecosystem services, including several recreational fisheries, which may be affected by changing salinity and temperature due to climate change. In this paper, we use a combination of physical models and habitat suitability index models to quantify the effects of potential climate change scenarios on a variety of juvenile fish and lobster species in Florida Bay. The climate scenarios include alterations in sea level, evaporation and precipitation rates, coastal runoff, and water temperature. We find that the changes in habitat suitability vary in both magnitude and direction across the scenarios and species, but are on average small. Only one of the seven species we investigate ( Lagodon rhomboides, i.e., pinfish) sees a sizable decrease in optimal habitat under any of the scenarios. This suggests that the estuarine fauna of Florida Bay may not be as vulnerable to climate change as other components of the ecosystem, such as those in the marine/terrestrial ecotone. However, these models are relatively simplistic, looking only at single species effects of physical drivers without considering the many interspecific interactions that may play a key role in the adjustment of the ecosystem as a whole. More complex models that capture the mechanistic links between physics and biology, as well as the complex dynamics of the estuarine food web, may be necessary to further understand the potential effects of climate change on the Florida Bay ecosystem.

Assessment of CORDEX-South Asia experiments for monsoonal precipitation over Himalayan region for future climate

NASA Astrophysics Data System (ADS)

Choudhary, A.; Dimri, A. P.

2018-04-01

Precipitation is one of the important climatic indicators in the global climate system. Probable changes in monsoonal (June, July, August and September; hereafter JJAS) mean precipitation in the Himalayan region for three different greenhouse gas emission scenarios (i.e. representative concentration pathways or RCPs) and two future time slices (near and far) are estimated from a set of regional climate simulations performed under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project. For each of the CORDEX-SA simulations and their ensemble, projections of near future (2020-2049) and far future (2070-2099) precipitation climatology with respect to corresponding present climate (1970-2005) over Himalayan region are presented. The variability existing over each of the future time slices is compared with the present climate variability to determine the future changes in inter annual fluctuations of monsoonal mean precipitation. The long-term (1970-2099) trend (mm/day/year) of monsoonal mean precipitation spatially distributed as well as averaged over Himalayan region is analyzed to detect any change across twenty-first century as well as to assess model uncertainty in simulating the precipitation changes over this period. The altitudinal distribution of difference in trend of future precipitation from present climate existing over each of the time slices is also studied to understand any elevation dependency of change in precipitation pattern. Except for a part of the Hindu-Kush area in western Himalayan region which shows drier condition, the CORDEX-SA experiments project in general wetter/drier conditions in near future for western/eastern Himalayan region, a scenario which gets further intensified in far future. Although, a gradually increasing precipitation trend is seen throughout the twenty-first century in carbon intensive scenarios, the distribution of trend with elevation presents a very complex picture with lower elevations

Impacts of Future Climate and Emission Changes on U.S. Air Quality

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

Penrod, Ashley; Zhang, Yang; Wang, K.

2014-06-01

Changes in climate and emissions will affect future air quality. In this work, simulations of present (2001-2005) and future (2026-2030) regional air quality are conducted with the newly released CMAQ version 5.0 to examine the individual and combined impacts of simulated future climate and anthropogenic emission projections on air quality over the U.S. Current (2001-2005) meteorological and chemical predictions are evaluated against observational data to assess the model’s capability in reproducing the seasonal differences. Overall, WRF and CMAQ perform reasonably well. Increased temperatures (up to 3.18 °C) and decreased ventilation (up to 157 m in planetary boundary layer height) aremore » found in both future winter and summer, with more prominent changes in winter. Increases in future temperatures result in increased isoprene and terpene emissions in winter and summer, driving the increase in maximum 8-h average O3 (up to 5.0 ppb) over the eastern U.S. in winter while decreases in NOx emissions drive the decrease in O3 over most of the U.S. in summer. Future concentrations of PM2.5 in winter and summer and many of its components including organic matter in winter, ammonium and nitrate in summer, and sulfate in winter and summer, decrease due to decreases in primary anthropogenic emissions and the concentrations of secondary anthropogenic pollutants and increased precipitation in winter. Future winter and summer dry and wet deposition fluxes are spatially variable and increase with increasing surface resistance and precipitation (e.g., NH4+ and NO3- dry and wet deposition fluxes increase in winter over much of the U.S.), respectively, and decrease with a decrease in ambient particulate concentrations (e.g., SO42- dry and wet deposition fluxes decrease over the eastern U.S. in summer and winter). Sensitivity simulations show that anthropogenic emission projections dominate over changes in climate in their impacts on the U.S. air quality in the near future

Robust Performance of Marginal Pacific Coral Reef Habitats in Future Climate Scenarios.

PubMed

Freeman, Lauren A

2015-01-01

Coral reef ecosystems are under dual threat from climate change. Increasing sea surface temperatures and thermal stress create environmental limits at low latitudes, and decreasing aragonite saturation state creates environmental limits at high latitudes. This study examines the response of unique coral reef habitats to climate change in the remote Pacific, using the National Center for Atmospheric Research Community Earth System Model version 1 alongside the species distribution algorithm Maxent. Narrow ranges of physico-chemical variables are used to define unique coral habitats and their performance is tested in future climate scenarios. General loss of coral reef habitat is expected in future climate scenarios and has been shown in previous studies. This study found exactly that for most of the predominant physico-chemical environments. However, certain coral reef habitats considered marginal today at high latitude, along the equator and in the eastern tropical Pacific were found to be quite robust in climate change scenarios. Furthermore, an environmental coral reef refuge previously identified in the central south Pacific near French Polynesia was further reinforced. Studying the response of specific habitats showed that the prevailing conditions of this refuge during the 20th century shift to a new set of conditions, more characteristic of higher latitude coral reefs in the 20th century, in future climate scenarios projected to 2100.

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.

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

Development of flood regressions and climate change scenarios to explore estimates of future peak flows

USGS Publications Warehouse

Burns, Douglas A.; Smith, Martyn J.; Freehafer, Douglas A.

2015-12-31

The application uses predictions of future annual precipitation from five climate models and two future greenhouse gas emissions scenarios and provides results that are averaged over three future periods—2025 to 2049, 2050 to 2074, and 2075 to 2099. Results are presented in ensemble form as the mean, median, maximum, and minimum values among the five climate models for each greenhouse gas emissions scenario and period. These predictions of future annual precipitation are substituted into either the precipitation variable or a water balance equation for runoff to calculate potential future peak flows. This application is intended to be used only as an exploratory tool because (1) the regression equations on which the application is based have not been adequately tested outside the range of the current climate and (2) forecasting future precipitation with climate models and downscaling these results to a fine spatial resolution have a high degree of uncertainty. This report includes a discussion of the assumptions, uncertainties, and appropriate use of this exploratory application.

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2013-01-01

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

Impacts of climate variability and future climate change on harmful algal blooms and human health

PubMed Central

Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

2008-01-01

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae. PMID:19025675

Impacts of climate variability and future climate change on harmful algal blooms and human health.

PubMed

Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

2008-11-07

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae.

Nowhere to Invade: Rumex crispus and Typha latifolia Projected to Disappear under Future Climate Scenarios

PubMed Central

Xu, Zhonglin; Feng, Zhaodong; Yang, Jianjun; Zheng, Jianghua; Zhang, Fang

2013-01-01

Future climate change has been predicted to affect the potential distribution of plant species. However, only few studies have addressed how invasive species may respond to future climate change despite the known effects of plant species invasion on nutrient cycles, ecosystem functions, and agricultural yields. In this study, we predicted the potential distributions of two invasive species, Rumex crispus and Typha latifolia, under current and future (2050) climatic conditions. Future climate scenarios considered in our study include A1B, A2, A2A, B1, and B2A. We found that these two species will lose their habitat under the A1B, A2, A2A, and B1 scenarios. Their distributions will be maintained under future climatic conditions related to B2A scenarios, but the total area will be less than 10% of that under the current climatic condition. We also investigated variations of the most influential climatic variables that are likely to cause habitat loss of the two species. Our results demonstrate that rising mean annual temperature, variations of the coldest quarter, and precipitation of the coldest quarter are the main factors contributing to habitat loss of R. crispus. For T. latifolia, the main factors are rising mean annual temperature, variations in temperature of the coldest quarter, mean annual precipitation, and precipitation of the coldest quarter. These results demonstrate that the warmer and wetter climatic conditions of the coldest season (or month) will be mainly responsible for habitat loss of R. crispus and T. latifolia in the future. We also discuss uncertainties related to our study (and similar studies) and suggest that particular attention should be directed toward the manner in which invasive species cope with rapid climate changes because evolutionary change can be rapid for species that invade new areas. PMID:23923020

Future Scenarios for Plant Virus Pathogens as Climate Change Progresses.

PubMed

Jones, R A C

2016-01-01

Knowledge of how climate change is likely to influence future virus disease epidemics in cultivated plants and natural vegetation is of great importance to both global food security and natural ecosystems. However, obtaining such knowledge is hampered by the complex effects of climate alterations on the behavior of diverse types of vectors and the ease by which previously unknown viruses can emerge. A review written in 2011 provided a comprehensive analysis of available data on the effects of climate change on virus disease epidemics worldwide. This review summarizes its findings and those of two earlier climate change reviews and focuses on describing research published on the subject since 2011. It describes the likely effects of the full range of direct and indirect climate change parameters on hosts, viruses and vectors, virus control prospects, and the many information gaps and deficiencies. Recently, there has been encouraging progress in understanding the likely effects of some climate change parameters, especially over the effects of elevated CO2, temperature, and rainfall-related parameters, upon a small number of important plant viruses and several key insect vectors, especially aphids. However, much more research needs to be done to prepare for an era of (i) increasingly severe virus epidemics and (ii) increasing difficulties in controlling them, so as to mitigate their detrimental effects on future global food security and plant biodiversity. © 2016 Elsevier Inc. All rights reserved.

Contrasted demographic responses facing future climate change in Southern Ocean seabirds.

PubMed

Barbraud, Christophe; Rivalan, Philippe; Inchausti, Pablo; Nevoux, Marie; Rolland, Virginie; Weimerskirch, Henri

2011-01-01

1. Recent climate change has affected a wide range of species, but predicting population responses to projected climate change using population dynamics theory and models remains challenging, and very few attempts have been made. The Southern Ocean sea surface temperature and sea ice extent are projected to warm and shrink as concentrations of atmospheric greenhouse gases increase, and several top predator species are affected by fluctuations in these oceanographic variables. 2. We compared and projected the population responses of three seabird species living in sub-tropical, sub-Antarctic and Antarctic biomes to predicted climate change over the next 50 years. Using stochastic population models we combined long-term demographic datasets and projections of sea surface temperature and sea ice extent for three different IPCC emission scenarios (from most to least severe: A1B, A2, B1) from general circulation models of Earth's climate. 3. We found that climate mostly affected the probability to breed successfully, and in one case adult survival. Interestingly, frequent nonlinear relationships in demographic responses to climate were detected. Models forced by future predicted climatic change provided contrasted population responses depending on the species considered. The northernmost distributed species was predicted to be little affected by a future warming of the Southern Ocean, whereas steep declines were projected for the more southerly distributed species due to sea surface temperature warming and decrease in sea ice extent. For the most southerly distributed species, the A1B and B1 emission scenarios were respectively the most and less damaging. For the two other species, population responses were similar for all emission scenarios. 4. This is among the first attempts to study the demographic responses for several populations with contrasted environmental conditions, which illustrates that investigating the effects of climate change on core population dynamics

Climate change and health in Earth's future

NASA Astrophysics Data System (ADS)

Bowles, Devin C.; Butler, Colin D.; Friel, Sharon

2014-02-01

Threats to health from climate change are increasingly recognized, yet little research into the effects upon health systems is published. However, additional demands on health systems are increasingly documented. Pathways include direct weather impacts, such as amplified heat stress, and altered ecological relationships, including alterations to the distribution and activity of pathogens and vectors. The greatest driver of demand on future health systems from climate change may be the alterations to socioeconomic systems; however, these "tertiary effects" have received less attention in the health literature. Increasing demands on health systems from climate change will impede health system capacity. Changing weather patterns and sea-level rise will reduce food production in many developing countries, thus fostering undernutrition and concomitant disease susceptibility. Associated poverty will impede people's ability to access and support health systems. Climate change will increase migration, potentially exposing migrants to endemic diseases for which they have limited resistance, transporting diseases and fostering conditions conducive to disease transmission. Specific predictions of timing and locations of migration remain elusive, hampering planning and misaligning needs and infrastructure. Food shortages, migration, falling economic activity, and failing government legitimacy following climate change are also "risk multipliers" for conflict. Injuries to combatants, undernutrition, and increased infectious disease will result. Modern conflict often sees health personnel and infrastructure deliberately targeted and disease surveillance and eradication programs obstructed. Climate change will substantially impede economic growth, reducing health system funding and limiting health system adaptation. Modern medical care may be snatched away from millions who recently obtained it.

Implications of Climate Mitigation for Future Agricultural Production

NASA Technical Reports Server (NTRS)

Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Deryng, Delphine; Folberth, Christian; Pugh, Thomas A. M.; Schmid, Erwin

2015-01-01

Climate change is projected to negatively impact biophysical agricultural productivity in much of the world. Actions taken to reduce greenhouse gas emissions and mitigate future climate changes, are thus of central importance for agricultural production. Climate impacts are, however, not unidirectional; some crops in some regions (primarily higher latitudes) are projected to benefit, particularly if increased atmospheric carbon dioxide is assumed to strongly increase crop productivity at large spatial and temporal scales. Climate mitigation measures that are implemented by reducing atmospheric carbon dioxide concentrations lead to reductions both in the strength of climate change and in the benefits of carbon dioxide fertilization. Consequently, analysis of the effects of climate mitigation on agricultural productivity must address not only regions for which mitigation is likely to reduce or even reverse climate damages. There are also regions that are likely to see increased crop yields due to climate change, which may lose these added potentials under mitigation action. Comparing data from the most comprehensive archive of crop yield projections publicly available, we find that climate mitigation leads to overall benefits from avoided damages at the global scale and especially in many regions that are already at risk of food insecurity today. Ignoring controversial carbon dioxide fertilization effects on crop productivity, we find that for the median projection aggressive mitigation could eliminate approximately 81% of the negative impacts of climate change on biophysical agricultural productivity globally by the end of the century. In this case, the benefits of mitigation typically extend well into temperate regions, but vary by crop and underlying climate model projections. Should large benefits to crop yields from carbon dioxide fertilization be realized, the effects of mitigation become much more mixed, though still positive globally and beneficial in many

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.

Future southcentral US wildfire probability due to climate change

USGS Publications Warehouse

Stambaugh, Michael C.; Guyette, Richard P.; Stroh, Esther D.; Struckhoff, Matthew A.; Whittier, Joanna B.

2018-01-01

Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160 cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.

Direct and indirect effects of climate change on projected future fire regimes in the western United States.

PubMed

Liu, Zhihua; Wimberly, Michael C

2016-01-15

We asked two research questions: (1) What are the relative effects of climate change and climate-driven vegetation shifts on different components of future fire regimes? (2) How does incorporating climate-driven vegetation change into future fire regime projections alter the results compared to projections based only on direct climate effects? We used the western United States (US) as study area to answer these questions. Future (2071-2100) fire regimes were projected using statistical models to predict spatial patterns of occurrence, size and spread for large fires (>400 ha) and a simulation experiment was conducted to compare the direct climatic effects and the indirect effects of climate-driven vegetation change on fire regimes. Results showed that vegetation change amplified climate-driven increases in fire frequency and size and had a larger overall effect on future total burned area in the western US than direct climate effects. Vegetation shifts, which were highly sensitive to precipitation pattern changes, were also a strong determinant of the future spatial pattern of burn rates and had different effects on fire in currently forested and grass/shrub areas. Our results showed that climate-driven vegetation change can exert strong localized effects on fire occurrence and size, which in turn drive regional changes in fire regimes. The effects of vegetation change for projections of the geographic patterns of future fire regimes may be at least as important as the direct effects of climate change, emphasizing that accounting for changing vegetation patterns in models of future climate-fire relationships is necessary to provide accurate projections at continental to global scales. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluating water quality ecosystem services of wetlands under historic and future climate

NASA Astrophysics Data System (ADS)

Records, R.; Arabi, M.; Fassnacht, S. R.; Duffy, W.; Ahmadi, M.; Hegewisch, K.

2013-12-01

Potential hydrologic effects of climate change have been assessed extensively; however, possible impacts of changing climate on in-stream water quality at the watershed scale have received little study. We assessed potential impacts of climate change on water quantity and quality in the mountainous Sprague River watershed, Oregon, USA, where high total phosphorus (TP) and sediment loads are associated with lake eutrophication and mortality of endangered fish species. Additionally, we analyzed water quality impacts of wetland and riparian zone loss and gain under present-day climate and future climate scenarios. We utilized the hydrologic model Soil and Water Assessment Tool (SWAT) forced with six distinct climate scenarios derived from Coupled Model Intercomparison Project 5 (CMIP5) General Circulation Models to assess magnitude and direction of trends in streamflow, sediment and TP fluxes in the mid-21st century (2030-2059). Model results showed little significant trend in average annual streamflow under most climate scenarios, but trends in annual and monthly streamflow, sediment, and TP fluxes were more pronounced and were generally increasing. Results also suggest that future loss of present-day wetlands and riparian zones under land use or climatic change could result in substantial increases in sediment and TP loads at the Sprague River outlet.

Assessing Lebanon's wildfire potential in association with current and future climatic conditions

Treesearch

George H. Mitri; Mireille G. Jazi; David McWethy

2015-01-01

The increasing occurrence and extent of large-scale wildfires in the Mediterranean have been linked to extended periods of warm and dry weather. We set out to assess Lebanon's wildfire potential in association with current and future climatic conditions. The Keetch-Byram Drought Index (KBDI) was the primary climate variable used in our evaluation of climate/fire...

Web-based access, aggregation, and visualization of future climate projections with emphasis on agricultural assessments

NASA Astrophysics Data System (ADS)

Villoria, Nelson B.; Elliott, Joshua; Müller, Christoph; Shin, Jaewoo; Zhao, Lan; Song, Carol

2018-01-01

Access to climate and spatial datasets by non-specialists is restricted by technical barriers involving hardware, software and data formats. We discuss an open-source online tool that facilitates downloading the climate data from the global circulation models used by the Inter-Sectoral Impacts Model Intercomparison Project. The tool also offers temporal and spatial aggregation capabilities for incorporating future climate scenarios in applications where spatial aggregation is important. We hope that streamlined access to these data facilitates analysis of climate related issues while considering the uncertainties derived from future climate projections and temporal aggregation choices.

Future changes in hydro-climatic extremes in the Upper Indus, Ganges, and Brahmaputra River basins

PubMed Central

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

2017-01-01

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

Using the adaptive cycle in climate-risk insurance to design resilient futures

NASA Astrophysics Data System (ADS)

Cremades, R.; Surminski, S.; Máñez Costa, M.; Hudson, P.; Shrivastava, P.; Gascoigne, J.

2018-01-01

Assessing the dynamics of resilience could help insurers and governments reduce the costs of climate-risk insurance schemes and secure future insurability in the face of an increase in extreme hydro-meteorological events related to climate change.

Future tendencies of climate indicators important for adaptation and mitigation strategies in forestry

NASA Astrophysics Data System (ADS)

Galos, Borbala; Hänsler, Andreas; Gulyas, Krisztina; Bidlo, Andras; Czimber, Kornel

2014-05-01

Climate change is expected to have severe impacts in the forestry sector, especially in low-elevation regions in Southeast Europe, where forests are vulnerable and sensitive to the increasing probability and severity of climatic extremes, especially to droughts. For providing information about the most important regional and local risks and mitigation options for the Carpathian basin, a GIS-supported Decision Support System is under development. This study focuses on the future tendencies of climate indicators that determine the distribution, growth, health status and production of forests as well as the potential pests and diseases. For the analyses the climate database of the Decision Support System has been applied, which contains daily time series for precipitation and temperature means and extremes as well as derived climate indices for 1961-2100. For the future time period, simulation results of 12 regional climate models are included (www.ensembles-eu.org) based on the A1B emission scenario. The main results can be summarized as follows: · The projected change of the climate indices (e.g. total number of hot days, frost days, dry days, consecutive dry periods) and forestry indices (e.g. Ellenberg climate quotient, Forestry aridity index; Tolerance index for beech) indicates the warming and drying of the growing season towards the end of the 21st century. These can have severe consequences on the ecosystem services of forests. · The climatic suitable area of the native tree species is projected to move northwards and upwards in the mountains, respectively. For beech (Fagus sylvatica L.) this shift would mean the drastic shrink of the distribution area in the analyzed region. · The characteristic climate conditions that are expected in the Carpathian basin in the second half of the century, are now located southeastern from the case study region. In this way, the potential future provenance regions can be determined. Results provide input for the climate

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

PubMed Central

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

2013-01-01

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

Conservation Status of North American Birds in the Face of Future Climate Change.

PubMed

Langham, Gary M; Schuetz, Justin G; Distler, Trisha; Soykan, Candan U; Wilsey, Chad

2015-01-01

Human-induced climate change is increasingly recognized as a fundamental driver of biological processes and patterns. Historic climate change is known to have caused shifts in the geographic ranges of many taxa and future climate change is expected to result in even greater redistributions of species. As a result, predicting the impact of climate change on future patterns of biodiversity will greatly aid conservation planning. Using the North American Breeding Bird Survey and Audubon Christmas Bird Count, two of the most comprehensive continental datasets of vertebrates in the world, and correlative distribution modeling, we assessed geographic range shifts for 588 North American bird species during both the breeding and non-breeding seasons under a range of future emission scenarios (SRES A2, A1B, B2) through the end of the century. Here we show that 314 species (53%) are projected to lose more than half of their current geographic range across three scenarios of climate change through the end of the century. For 126 species, loss occurs without concomitant range expansion; whereas for 188 species, loss is coupled with potential to colonize new replacement range. We found no strong associations between projected climate sensitivities and existing conservation prioritizations. Moreover, species responses were not clearly associated with habitat affinities, migration strategies, or climate change scenarios. Our results demonstrate the need to include climate sensitivity into current conservation planning and to develop adaptive management strategies that accommodate shrinking and shifting geographic ranges. The persistence of many North American birds will depend on their ability to colonize climatically suitable areas outside of current ranges and management actions that target climate adaptation.

Conservation Status of North American Birds in the Face of Future Climate Change

PubMed Central

Langham, Gary M.; Schuetz, Justin G.; Distler, Trisha; Soykan, Candan U.; Wilsey, Chad

2015-01-01

Human-induced climate change is increasingly recognized as a fundamental driver of biological processes and patterns. Historic climate change is known to have caused shifts in the geographic ranges of many taxa and future climate change is expected to result in even greater redistributions of species. As a result, predicting the impact of climate change on future patterns of biodiversity will greatly aid conservation planning. Using the North American Breeding Bird Survey and Audubon Christmas Bird Count, two of the most comprehensive continental datasets of vertebrates in the world, and correlative distribution modeling, we assessed geographic range shifts for 588 North American bird species during both the breeding and non-breeding seasons under a range of future emission scenarios (SRES A2, A1B, B2) through the end of the century. Here we show that 314 species (53%) are projected to lose more than half of their current geographic range across three scenarios of climate change through the end of the century. For 126 species, loss occurs without concomitant range expansion; whereas for 188 species, loss is coupled with potential to colonize new replacement range. We found no strong associations between projected climate sensitivities and existing conservation prioritizations. Moreover, species responses were not clearly associated with habitat affinities, migration strategies, or climate change scenarios. Our results demonstrate the need to include climate sensitivity into current conservation planning and to develop adaptive management strategies that accommodate shrinking and shifting geographic ranges. The persistence of many North American birds will depend on their ability to colonize climatically suitable areas outside of current ranges and management actions that target climate adaptation. PMID:26333202

Effects of future climate conditions on terrestrial export from coastal southern California

NASA Astrophysics Data System (ADS)

Feng, D.; Zhao, Y.; Raoufi, R.; Beighley, E.; Melack, J. M.

2015-12-01

The Santa Barbara Coastal - Long Term Ecological Research Project (SBC-LTER) is focused on investigating the relative importance of land and ocean processes in structuring giant kelp forest ecosystems. Understanding how current and future climate conditions influence terrestrial export is a central theme for the project. Here we combine the Hillslope River Routing (HRR) model and daily precipitation and temperature downscaled using statistical downscaling based on localized constructed Analogs (LOCA) to estimate recent streamflow dynamics (2000 to 2014) and future conditions (2015 to 2100). The HRR model covers the SBC-LTER watersheds from just west of the Ventura River to Point Conception; a land area of roughly 800 km2 with 179 watersheds ranging from 0.1 to 123 km2. The downscaled climate conditions have a spatial resolution of 6 km by 6 km. Here, we use the Penman-Monteith method with the Food and Agriculture Organization of the United Nations (FAO) limited climate data approximations and land surface conditions (albedo, leaf area index, land cover) measured from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites to estimate potential evapotranspiration (PET). The HRR model is calibrated for the period 2000 to 2014 using USGS and LTER streamflow. An automated calibration technique is used. For future climate scenarios, we use mean 8-day land cover conditions. Future streamflow, ET and soil moisture statistics are presented and based on downscaled P and T from ten climate model projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5).

Modelling recent and future climatic suitability for fasciolosis in Europe.

PubMed

Caminade, Cyril; van Dijk, Jan; Baylis, Matthew; Williams, Diana

2015-03-19

Fasciola hepatica is a parasitic worm responsible for fasciolosis in grazed ruminants in Europe. The free-living stages of this parasite are sensitive to temperature and soil moisture, as are the intermediate snail hosts the parasite depends on for its life-cycle. We used a climate-driven disease model in order to assess the impact of recent and potential future climate changes on the incidence of fasciolosis and to estimate the related uncertainties at the scale of the European landmass. The current climate appears to be highly suitable for fasciolosis throughout the European Union with the exception of some parts of the Mediterranean region. Simulated climatic suitability for fasciolosis significantly increased during the 2000s in central and northwestern Europe, which is consistent with an observed increased in ruminant infections. The simulation showed that recent trends are likely to continue in the future with the estimated pattern of climate change for northern Europe, possibly extending the season suitable for development of the parasite in the environment by up to four months. For southern Europe, the simulated burden of disease may be lower, but the projected climate change will increase the risk during the winter months, since the simulated changes in temperature and moisture support the development of the free-living and intra-molluscan stages between November and March. In the event of predicted climate change, F. hepatica will present a serious risk to the health, welfare and productivity of all ruminant livestock. Improved, bespoke control programmes, both at farm and region levels, will then become imperative if problems, such as resistance of the parasite associated with increased drug use, are to be mitigated.

Impact of climate change on future concentrated solar power (CSP) production

NASA Astrophysics Data System (ADS)

Wild, Martin; Folini, Doris; Henschel, Florian

2017-02-01

Traditionally, for the planning and assessment of solar power plants, the amount of solar radiation incident on the Earth's surface is assumed to be invariable over the years. However, with changing climate and air pollution levels, solar resources may no longer be stable over time and undergo substantial decadal changes. Observational records covering several decades indeed confirm long-term changes in this quantity. In a previous study (Wild et al. 2015, Solar Energy)1 we examined how the latest generation of climate models (CMIP5) projects potential changes in surface solar radiation over the coming decades, and how this may affect, in combination with the expected greenhouse warming, future power output from photovoltaic (PV) systems. In the present complementary study, we use the CMIP5 model projections to estimate possible future changes in power output from Concentrated Solar Power (CSP) systems due to changing climate and air pollution levels up to the mid-21th century. The results indicate a potential for future increases in CSP production in many parts of the globe, with few exceptions such as the North of India and the irrelevant polar areas. Compared to the changes in PV production, the estimated future production changes by CSP are larger by a factor of 4.

Quantifying climate changes of the Common Era for Finland

NASA Astrophysics Data System (ADS)

Luoto, Tomi P.; Nevalainen, Liisa

2017-10-01

In this study, we aim to quantify summer air temperatures from sediment records from Southern, Central and Northern Finland over the past 2000 years. We use lake sediment archives to estimate paleotemperatures applying fossil Chironomidae assemblages and the transfer function approach. The used enhanced Chironomidae-based temperature calibration set was validated in a 70-year high-resolution sediment record against instrumentally measured temperatures. Since the inferred and observed temperatures showed close correlation, we deduced that the new calibration model is reliable for reconstructions beyond the monitoring records. The 700-year long temperature reconstructions from three sites at multi-decadal temporal resolution showed similar trends, although they had differences in timing of the cold Little Ice Age (LIA) and the initiation of recent warming. The 2000-year multi-centennial reconstructions from three different sites showed resemblance with each other having clear signals of the Medieval Climate Anomaly (MCA) and LIA, but with differences in their timing. The influence of external forcing on climate of the southern and central sites appeared to be complex at the decadal scale, but the North Atlantic Oscillation (NAO) was closely linked to the temperature development of the northern site. Solar activity appears to be synchronous with the temperature fluctuations at the multi-centennial scale in all the sites. The present study provides new insights into centennial and decadal variability in air temperature dynamics in Northern Europe and on the external forcing behind these trends. These results are particularly useful in comparing regional responses and lags of temperature trends between different parts of Scandinavia.

Revealing The Impact Of Climate Variability On The Wind Resource Using Data Mining Techniques

NASA Astrophysics Data System (ADS)

Clifton, A.; Lundquist, J. K.

2011-12-01

Wind turbines harvest energy from the wind. Winds at heights where industrial-scale turbines operate, up to 200 m above ground, experience a complex interaction between the atmosphere and the Earth's surface. Previous studies for a variety of locations have shown that the wind resource varies over time. In some locations, this variability can be related to large-scale climate oscillations as revealed in climate indices such as the El-Nino-Southern Oscillation (ENSO). These indices can be used to quantify climate change in the past, and can also be extracted from models of future climate. Understanding the correlation between climate indices and wind resources therefore allows us to understand how climate change may influence wind energy production. We present a new methodology for assessing relevant climate modes of oscillation at a given site in order to quantify future wind resource variability. We demonstrate the method on a 14-year record of 10-minute averaged wind speed and wind direction data from several levels of an 80m tower at the National Renewable Energy Laboratory (NREL) National Wind Technology Center near Boulder, Colorado. Data mining techniques (based on k-means clustering) identify 4 major groups of wind speed and direction. After removing annual means, each cluster was compared to a series of climate indices, including the Arctic Oscillation (AO) and Multivariate ENSO Index (MEI). Statistically significant relationships emerge between individual clusters and climate indices. At this location, this result is consistent with the MEI's relationship with other meteorological parameters, such as precipitation, in the Rocky Mountain Region. The presentation will illustrate these relationships between wind resource at this location and other relevant climate indices, and suggest how these relationships can provide a foundation for quantifying the potential future variability of wind energy production at this site and others.

"Participatory Cli-Fi": Crowdsourcing Voicemails from the Future to Spark Engagement and Discern Perceptions of Climate Change

NASA Astrophysics Data System (ADS)

Stovall, G.; Eklund, K.; Redsecker, K.; Hernandez, T.; Pfirman, S. L.; Orlove, B. S.

2016-12-01

Communicating climate science alone is not enough to engage the public with climate change: the gap between the abstract science and its impact on their future lives is often too great. We constructed FutureCoast, a collaborative game, to use participatory storymaking as the art that bridges that gap. The FutureCoast game pretended the voicemail system of the future "had a leak in it" and invited people to call and leave voicemail messages that seem to have leaked from the future. These crowdsourced voicemails are short first-person stories that often create complex, visceral experiences of potential climate impacts in listeners. We transcribed and coded this audio for content and affect, finding both a wide array of anticipated climate futures and trends in public sentiment about climate related impacts. Our analysis found the public engages with climate change in both rational and emotional manners which should be considered when motivating them to action. This presentation highlights our methodology and assessment of innovative gameful engagement, and summarizes how the FutureCoast "participatory cli-fi" approach has been employed in community and classroom settings after the close of the active period of the game.

Global Change Impacts on Future Fire Regimes: Distinguishing Between Climate-limited vs Ignition-Limited Landscapes

NASA Astrophysics Data System (ADS)

Keeley, J. E.; Syphard, A. D.

2016-12-01

Global warming is expected to exacerbate fire impacts. Predicting how climates will impact future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned, however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models are needed that predict future seasonal temperature changes if we are to forecast future fire regimes in these forests. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited, and because they are closely juxtaposed with human habitations fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science, it is far more complicated than that. Climate change is not relevant on some landscapes, but where climate is relevant the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.

Quantifying conditional risks for water and energy systems using climate information

NASA Astrophysics Data System (ADS)

Lall, U.

2016-12-01

There has been a growing recognition of the multi-scale spatio-temporal organization of climate dynamics, and its implications for predictable, structured risk exposure to populations and infrastructure systems. At the most base level is an understanding that there are some identifiable climate modes, such as ENSO, that are associated with such outcomes. This has led to the emergence of a small cottage industry of analysts who relate different "climate indices" to specific regional outcomes. Such efforts and the associated media interest in these simplified "stories" have led to an increasing appreciation of the phenomenon, and some formal and informal efforts at decision making using such information. However, as was demonstrated through the 2014-16 El Nino forecasting season, many climate scientists over-emphasized the potential risks, while others cautioned the media as to the caveats and uncertainties associated with assuming that the forecasts of ENSO and the expected teleconnections may pan out. At least in certain sectors and regions, significant efforts or expectations as to outcomes were put in place, and some were beneficial, while others failed to manifest. Climate informed predictions for water and energy systems can be thought of as efforts to infer conditional distributions of specific outcomes given information on climate state. Invariably, the climate state may be presented as a very high dimensional spatial set of variables, with limited temporal sampling, while the water and energy attributes may be regional and constitute a much smaller dimension. One may, of course, be interested in the fact that the same climate state may lead to synchronous positive and negative effects across many locations, as may be expected under mid-latitude stationary and transient wave interaction. In this talk, I will provide examples of a few modern statistical and machine learning tools that allow a decomposition of the high dimensional climate state and its relation

Exploiting satellite earth observation to quantify current global oceanic DMS flux and its future climate sensitivity

NASA Astrophysics Data System (ADS)

Land, P. E.; Shutler, J. D.; Bell, T. G.; Yang, M.

2014-11-01

We used coincident Envisat RA2 and AATSR temperature and wind speed data from 2008/2009 to calculate the global net sea-air flux of dimethyl sulfide (DMS), which we estimate to be 19.6 Tg S a-1. Our monthly flux calculations are compared to open ocean eddy correlation measurements of DMS flux from 10 recent cruises, with a root mean square difference of 3.1 μmol m-2 day-1. In a sensitivity analysis, we varied temperature, salinity, surface wind speed, and aqueous DMS concentration, using fixed global changes as well as CMIP5 model output. The range of DMS flux in future climate scenarios is discussed. The CMIP5 model predicts a reduction in surface wind speed and we estimate that this will decrease the global annual sea-air flux of DMS by 22% over 25 years. Concurrent changes in temperature, salinity, and DMS concentration increase the global flux by much smaller amounts. The net effect of all CMIP5 modelled 25 year predictions was a 19% reduction in global DMS flux. 25 year DMS concentration changes had significant regional effects, some positive (Southern Ocean, North Atlantic, Northwest Pacific) and some negative (isolated regions along the Equator and in the Indian Ocean). Using satellite-detected coverage of coccolithophore blooms, our estimate of their contribution to North Atlantic DMS emissions suggests that the coccolithophores contribute only a small percentage of the North Atlantic annual flux estimate, but may be more important in the summertime and in the northeast Atlantic.

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

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.

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...

Ecoclimatic indicators to study crop suitability in present and future climatic conditionsTIC CONDITIONS

NASA Astrophysics Data System (ADS)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been

The future of energy and climate

ScienceCinema

Steinberger, Jack

2018-04-26

The talk will review some of the basic facts about the history and present status of the use of energy and its climatic consequences. It is clear that the world will have to change its way of energy production, the sooner the better. Because of the difficulty of storing electric energy, by far the best energy source for the future is thermal solar from the deserts, with overnight thermal storage. I will give some description of the present status of the technologies involved and end up with a pilot project for Europe and North Africa.

Future respiratory hospital admissions from wildfire smoke under climate change in the Western US

NASA Astrophysics Data System (ADS)

Coco Liu, Jia; Mickley, Loretta J.; Sulprizio, Melissa P.; Yue, Xu; Peng, Roger D.; Dominici, Francesca; Bell, Michelle L.

2016-12-01

Background. Wildfires are anticipated to be more frequent and intense under climate change. As a result, wildfires may emit more air pollutants that can harm health in communities in the future. The health impacts of wildfire smoke under climate change are largely unknown. Methods. We linked projections of future levels of fine particulate matter (PM2.5) specifically from wildfire smoke under the A1B climate change scenario using the GEOS-Chem model for 2046-2051, present-day estimates of hospital admission impacts from wildfire smoke, and future population projections to estimate the change in respiratory hospital admissions for persons ≥65 years by county (n = 561) from wildfire PM2.5 under climate change in the Western US. Results. The increase in intense wildfire smoke days from climate change would result in an estimated 178 (95% confidence interval: 6.2, 361) additional respiratory hospital admissions in the Western US, accounting for estimated future increase in the elderly population. Climate change is estimated to impose an additional 4990 high-pollution smoke days. Central Colorado, Washington and southern California are estimated to experience the highest percentage increase in respiratory admissions from wildfire smoke under climate change. Conclusion. Although the increase in number of respiratory admissions from wildfire smoke seems modest, these results provide important scientific evidence of an often-ignored aspect of wildfire impact, and information on their anticipated spatial distribution. Wildfires can cause serious social burdens such as property damage and suppression cost, but can also raise health problems. The results provide information that can be incorporated into development of environmental and health policies in response to climate change. Climate change adaptation policies could incorporate scientific evidence on health risks from natural disasters such as wildfires.

Teaching Climate Change to Future Teachers Using 'Real' Data: Challenges and Opportunities (Invited)

NASA Astrophysics Data System (ADS)

Petcovic, H. L.; Barone, S.; Fulford, J.

2013-12-01

A climate-literate public is essential to resolving pressing problems related to global change. Future elementary teachers are a critical audience in climate and climate change education, as they will introduce children in early grades (USA grades K-8, children ages 5-14) to fundamentals of the climate system, natural and anthropogenic drivers of climate change, and impacts of global change on human and natural systems. Here we describe challenges we have encountered in teaching topics of the carbon cycle, greenhouse gases, past climate, recent anthropogenic change, and carbon footprints to future elementary teachers. We also describe how we have met (to varying degrees of success) these challenges in an introductory earth science course that is specifically designed for this audience. Two prominent challenges we have encountered are: the complex nature of the scientific content of climate change, and robust misconceptions held by our students about these topics. To address the first challenge, we attempt to adjust the scientific content to a level appropriate for future K-8 teachers, without sacrificing too much accuracy or critical detail. To address the second challenge, we explicitly discuss alternate conceptions of each topic. The use of authentic data sets can also address both of these challenges. Yet incorporating 'real' climate and paleoclimate data into the classroom poses still an additional challenge of instructional design. We use a variety of teaching approaches in our laboratory-based course including student-designed experiments, computer simulations, physical models, and authentic data sets. We have found that students strongly prefer the physical models and experiments, because these are 'hands-on' and perceived as easily adaptable to the K-8 classroom. Students often express dislike for activities that use authentic data sets (for example, an activity using graphs of CO2 and methane concentrations in Vostok ice cores), in particular because they

Quantifying the biophysical climate change mitigation potential of Canada's forest sector

NASA Astrophysics Data System (ADS)

Smyth, C. E.; Stinson, G.; Neilson, E.; Lemprière, T. C.; Hafer, M.; Rampley, G. J.; Kurz, W. A.

2014-07-01

The potential of forests and the forest sector to mitigate greenhouse gas (GHG) emissions is widely recognized, but challenging to quantify at a national scale. Forests and their carbon (C) sequestration potential are affected by management practices, where wood harvesting transfers C out of the forest into products, and subsequent regrowth allows further C sequestration. Here we determine the mitigation potential of the 2.3 × 106 km2 of Canada's managed forests from 2015 to 2050 using the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), a harvested wood products (HWP) model that estimates emissions based on product half-life decay times, and an account of emission substitution benefits from the use of wood products and bioenergy. We examine several mitigation scenarios with different assumptions about forest management activity levels relative to a base case scenario, including improved growth from silvicultural activities, increased harvest and residue management for bioenergy, and reduced harvest for conservation. We combine forest management options with two mitigation scenarios for harvested wood product use involving an increase in either long-lived products or bioenergy uses. Results demonstrate large differences among alternative scenarios, and we identify potential mitigation scenarios with increasing benefits to the atmosphere for many decades into the future, as well as scenarios with no net benefit over many decades. The greatest mitigation impact was achieved through a mix of strategies that varied across the country and had cumulative mitigation of 254 Tg CO2e in 2030, and 1180 Tg CO2e in 2050. There was a trade-off between short-term and long-term goals, in that maximizing short-term emissions reduction could reduce the forest sector's ability to contribute to longer-term objectives. We conclude that (i) national-scale forest sector mitigation options need to be assessed rigorously from a systems perspective to avoid the development of

Implications of plant acclimation for future climate-carbon cycle feedbacks

NASA Astrophysics Data System (ADS)

Mercado, Lina; Kattge, Jens; Cox, Peter; Sitch, Stephen; Knorr, Wolfgang; Lloyd, Jon; Huntingford, Chris

2010-05-01

The response of land ecosystems to climate change and associated feedbacks are a key uncertainty in future climate prediction (Friedlingstein et al. 2006). However global models generally do not account for the acclimation of plant physiological processes to increased temperatures. Here we conduct a first global sensitivity study whereby we modify the Joint UK land Environment Simulator (JULES) to account for temperature acclimation of two main photosynthetic parameters, Vcmax and Jmax (Kattge and Knorr 2007) and plant respiration (Atkin and Tjoelker 2003). The model is then applied over the 21st Century within the IMOGEN framework (Huntingford et al. 2004). Model simulations will provide new and improved projections of biogeochemical cycling, forest resilience, and thus more accurate projections of climate-carbon cycle feedbacks and the future evolution of the Earth System. Friedlingstein P, Cox PM, Betts R et al. (2006) Climate-carbon cycle feedback analysis, results from the C4MIP model intercomparison. Journal of Climate, 19, 3337-3353. Kattge J and Knorr W (2007): Temperature acclimation in a biochemical model of photosynthesis: a reanalysis of data from 36 species. Plant, Cell and Environment 30, 1176-1190 Atkin O.K and Tjoelker, M. G. (2003): Thermal acclimation and the dynamic response of plant respiration to temperature. Trends in Plant Science 8 (7), 343-351 Huntingford C, et al. (2004) Using a GCM analogue model to investigate the potential for Amazonian forest dieback. Theoretical and Applied Climatology, 78, 177-185.

When, not if: the inescapability of an uncertain climate future.

PubMed

Ballard, Timothy; Lewandowsky, Stephan

2015-11-28

Climate change projections necessarily involve uncertainty. Analysis of the physics and mathematics of the climate system reveals that greater uncertainty about future temperature increases is nearly always associated with greater expected damages from climate change. In contrast to those normative constraints, uncertainty is frequently cited in public discourse as a reason to delay mitigative action. This failure to understand the actual implications of uncertainty may incur notable future costs. It is therefore important to communicate uncertainty in a way that improves people's understanding of climate change risks. We examined whether responses to projections were influenced by whether the projection emphasized uncertainty in the outcome or in its time of arrival. We presented participants with statements and graphs indicating projected increases in temperature, sea levels, ocean acidification and a decrease in arctic sea ice. In the uncertain-outcome condition, statements reported the upper and lower confidence bounds of the projected outcome at a fixed time point. In the uncertain time-of-arrival condition, statements reported the upper and lower confidence bounds of the projected time of arrival for a fixed outcome. Results suggested that people perceived the threat as more serious and were more likely to encourage mitigative action in the time-uncertain condition than in the outcome-uncertain condition. This finding has implications for effectively communicating the climate change risks to policy-makers and the general public. © 2015 The Author(s).

Climate change and the future of seed zones

Treesearch

Francis Kilkenny; Brad St. Clair; Matt Horning

2013-01-01

The use of native plants in wildland restoration is critical to the recovery and health of ecosystems. Information from genecological and reciprocal transplant common garden studies can be used to develop seed transfer guidelines and to predict how plants will respond to future climate change. Tools developed from these data, such as universal response functions and...

[Effects of future climate change on climatic suitability of flue-cured tobacco plantation in Yunnan, China.

PubMed

Hu, Xue Qiong; Xu, Meng Ying; He, Yu Qin; Zhang, Ming da; Ji, Wen Juan; Zhu, Yong

2016-04-22

The climatic suitability distribution of flue-cured tobacco planting in Yunnan will be profoundly affected by climate change. According to three key factors influencing climatic suitability of flue-cured tobacco planting in Yunnan, namely, average temperature in July, sunshine duration from July to August, precipitation from April to September, the variations of climatic suitability distribution of flue-cured tobacco planting in Yunnan respectively in 1986-2005, 2021-2040 and 2041-2060 under RCP4.5 and RCP8.5 climate scenarios were investigated by using the climatic simulation data in 1981-2060 and the meteorological observation data during 1986-2005. The results showed that climatic suitability region would expand northward and eastward and plantable area of flue-cured tobacco would gradually increase. The increment of plantable area was more in 2041-2060 than in 2021-2040, and under RCP8.5 scenario than under RCP4.5 scenario. The optimum climatic area and sub-suitable climatic area were expanded considerably, while the suitable climatic area was not much changed. In the future, the north-central Yunnan such as Kunming, Qujing, Dali, Chuxiong, Lijiang would have a big increase in both the optimum climatic area and the cultivable area, meanwhile, the southern Yunnan including Wenshan, Honghe, Puer and Xishuangbanna would have a big decrease in both the optimum climatic area and the cultivable area.

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

Quantifying hydrological responses of small Mediterranean catchments under climate change projections.

PubMed

Sellami, Haykel; Benabdallah, Sihem; La Jeunesse, Isabelle; Vanclooster, Marnik

2016-02-01

Catchment flow regimes alteration is likely to be a prominent consequence of climate change projections in the Mediterranean. Here we explore the potential effects of climatic change on the flow regime of the Thau and the Chiba catchments which are located in Southern France and Northeastern Tunisia, respectively. The Soil and Water Assessment Tool (SWAT) hydrological model is forced with projections from an ensemble of 4 climate model (CM) to assess changes and uncertainty in relevant hydrological indicators related to water balance, magnitude, frequency and timing of the flow between a reference (1971-2000) and future (2041-2071) periods. Results indicate that both catchments are likely to experience a decrease in precipitation and increase in temperature in the future. Consequently, runoff and soil water content are projected to decrease whereas potential evapotranspiration is likely to increase in both catchments. Yet uncertain, the projected magnitudes of these changes are higher in the wet period than in the dry period. Analyses of extreme flow show similar trend in both catchments, projecting a decrease in both high flow and low flow magnitudes for various time durations. Further, significant increase in low flow frequency as a proxy for hydrological droughts is projected for both catchments but with higher uncertainty in the wet period than in the dry period. Although no changes in the average timing of maximum and minimum flow events for different flow durations are projected, substantial uncertainty remains in the hydrological projections. While the results in both catchments show consistent trend of change for most of the hydrologic indicators, the overall degree of alteration on the flow regime of the Chiba catchment is projected to be higher than that of the Thau catchment. The projected magnitudes of alteration as well as their associated uncertainty vary depending on the catchment characteristics and flow seasonality. Copyright © 2015 Elsevier B

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.

Predicting the Distribution of Commercially Important Invertebrate Stocks under Future Climate

PubMed Central

Russell, Bayden D.; Connell, Sean D.; Mellin, Camille; Brook, Barry W.; Burnell, Owen W.; Fordham, Damien A.

2012-01-01

The future management of commercially exploited species is challenging because techniques used to predict the future distribution of stocks under climate change are currently inadequate. We projected the future distribution and abundance of two commercially harvested abalone species (blacklip abalone, Haliotis rubra and greenlip abalone, H. laevigata) inhabiting coastal South Australia, using multiple species distribution models (SDM) and for decadal time slices through to 2100. Projections are based on two contrasting global greenhouse gas emissions scenarios. The SDMs identified August (winter) Sea Surface Temperature (SST) as the best descriptor of abundance and forecast that warming of winter temperatures under both scenarios may be beneficial to both species by allowing increased abundance and expansion into previously uninhabited coasts. This range expansion is unlikely to be realised, however, as projected warming of March SST is projected to exceed temperatures which cause up to 10-fold increases in juvenile mortality. By linking fine-resolution forecasts of sea surface temperature under different climate change scenarios to SDMs and physiological experiments, we provide a practical first approximation of the potential impact of climate-induced change on two species of marine invertebrates in the same fishery. PMID:23251326

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

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

NASA Astrophysics Data System (ADS)

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-01

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

Abrupt Climate Change: the View from the Past, the Present and the Future

NASA Astrophysics Data System (ADS)

White, J. W. C.

2014-12-01

Climate is changing as humans put more and more greenhouse gases into the atmosphere. With CO2 levels today around 400ppm, we are clearly committed to far more climate change, both in the near term, and well beyond our children's future. A key question is how that change will occur. Abrupt climate changes are those that exceed our expectations, preparedness, and ability to adapt. Such changes challenge us economically, physically, and socially. This talk will draw upon results from ice core research over the past twenty years, as well as a new NRC report on abrupt climate change in order to address abrupt change, as seen in the past in ice cores, as seen today in key environmental systems upon which humans depend, and what is may be coming in the future.

Radiative Forcing in the ACCMIP Historical and Future Climate Simulations

NASA Technical Reports Server (NTRS)

Shindell, Drew Todd; Lamarque, J.-F.; Schulz, M.; Flanner, M.; Jiao, C.; Chin, M.; Young, P. J.; Lee, Y. H.; Rotstayn, L.; Mahowald, N.;

Future climate change scenarios in Central America at high spatial resolution.

PubMed

Imbach, Pablo; Chou, Sin Chan; Lyra, André; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961-1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021-2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021-2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water

Potential distribution of pine wilt disease under future climate change scenarios

PubMed Central

Nakamura, Katsunori; Nakao, Katsuhiro; Kominami, Yuji; Tanaka, Nobuyuki; Ohashi, Haruka; Takano, Kohei Takenaka; Takeuchi, Wataru; Matsui, Tetsuya

2017-01-01

Pine wilt disease (PWD) constitutes a serious threat to pine forests. Since development depends on temperature and drought, there is a concern that future climate change could lead to the spread of PWD infections. We evaluated the risk of PWD in 21 susceptible Pinus species on a global scale. The MB index, which represents the sum of the difference between the mean monthly temperature and 15 when the mean monthly temperatures exceeds 15°C, was used to determine current and future regions vulnerable to PWD (MB ≥ 22). For future climate conditions, we compared the difference in PWD risks among four different representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5) and two time periods (2050s and 2070s). We also evaluated the impact of climate change on habitat suitability for each Pinus species using species distribution models. The findings were then integrated and the potential risk of PWD spread under climate change was discussed. Within the natural Pinus distribution area, southern parts of North America, Europe, and Asia were categorized as vulnerable regions (MB ≥ 22; 16% of the total Pinus distribution area). Representative provinces in which PWD has been reported at least once overlapped with the vulnerable regions. All RCP scenarios showed expansion of vulnerable regions in northern parts of Europe, Asia, and North America under future climate conditions. By the 2070s, under RCP 8.5, an estimated increase in the area of vulnerable regions to approximately 50% of the total Pinus distribution area was revealed. In addition, the habitat conditions of a large portion of the Pinus distribution areas in Europe and Asia were deemed unsuitable by the 2070s under RCP 8.5. Approximately 40% of these regions overlapped with regions deemed vulnerable to PWD, suggesting that Pinus forests in these areas are at risk of serious damage due to habitat shifts and spread of PWD. PMID:28797067

Potential distribution of pine wilt disease under future climate change scenarios.

PubMed

Hirata, Akiko; Nakamura, Katsunori; Nakao, Katsuhiro; Kominami, Yuji; Tanaka, Nobuyuki; Ohashi, Haruka; Takano, Kohei Takenaka; Takeuchi, Wataru; Matsui, Tetsuya

2017-01-01

Pine wilt disease (PWD) constitutes a serious threat to pine forests. Since development depends on temperature and drought, there is a concern that future climate change could lead to the spread of PWD infections. We evaluated the risk of PWD in 21 susceptible Pinus species on a global scale. The MB index, which represents the sum of the difference between the mean monthly temperature and 15 when the mean monthly temperatures exceeds 15°C, was used to determine current and future regions vulnerable to PWD (MB ≥ 22). For future climate conditions, we compared the difference in PWD risks among four different representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5) and two time periods (2050s and 2070s). We also evaluated the impact of climate change on habitat suitability for each Pinus species using species distribution models. The findings were then integrated and the potential risk of PWD spread under climate change was discussed. Within the natural Pinus distribution area, southern parts of North America, Europe, and Asia were categorized as vulnerable regions (MB ≥ 22; 16% of the total Pinus distribution area). Representative provinces in which PWD has been reported at least once overlapped with the vulnerable regions. All RCP scenarios showed expansion of vulnerable regions in northern parts of Europe, Asia, and North America under future climate conditions. By the 2070s, under RCP 8.5, an estimated increase in the area of vulnerable regions to approximately 50% of the total Pinus distribution area was revealed. In addition, the habitat conditions of a large portion of the Pinus distribution areas in Europe and Asia were deemed unsuitable by the 2070s under RCP 8.5. Approximately 40% of these regions overlapped with regions deemed vulnerable to PWD, suggesting that Pinus forests in these areas are at risk of serious damage due to habitat shifts and spread of PWD.

Future change in seasonal march of snow water equivalent due to global climate change

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Ma, X.; Wakazuki, Y.; Fujita, M.; Kimura, F.

2012-04-01

Western side of Honshu Island in Japan is one of the heaviest snowfall areas in the world, although the location is relatively lower latitude than other heavy snowfall areas. Snowfall is one of major source for agriculture, industrial, and house-use in Japan. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities (ex. Ma et al., 2011). We performed the four numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. NCEP/NCAR reanalysis is used for initial and boundary conditions in present climate simulation and PGW method. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. In much-snow cases, Maximum total snow water equivalent over Japan, which is mostly observed in early February, is 49 G ton in the present simulation, the one decreased 26 G ton in the future simulation. The decreasing rate of snow water equivalent due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is strongly affected by the air temperature rise due to global climate change. The difference in present and future precipitation amount is little.

Langley Research Center Utility Risk from Future Climate Change

NASA Technical Reports Server (NTRS)

De Young, Russell J.; Ganoe, Rene

2015-01-01

The successful operation of NASA Langley Research Center (LaRC) depends on services provided by several public utility companies. These include Newport News Waterworks, Dominion Virginia Power, Virginia Natural Gas and Hampton Roads Sanitation District. LaRC's plan to respond to future climate change should take into account how these companies plan to avoid interruption of services while minimizing cost to the customers. This report summarizes our findings from publicly available documents on how each company plans to respond. This will form the basis for future planning for the Center. Our preliminary findings show that flooding and severe storms could interrupt service from the Waterworks and Sanitation District but the potential is low due to plans in place to address climate change on their system. Virginia Natural Gas supplies energy to produce steam but most current steam comes from the Hampton trash burning plant, thus interruption risk is low. Dominion Virginia Power does not address climate change impacts on their system in their public reports. The potential interruption risk is considered to be medium. The Hampton Roads Sanitation District is projecting a major upgrade of their system to mitigate clean water inflow and infiltration. This will reduce infiltration and avoid overloading the pump stations and treatment plants.

Carbon Pools in a Temperate Heathland Resist Changes in a Future Climate

NASA Astrophysics Data System (ADS)

Ambus, P.; Reinsch, S.; Nielsen, P. L.; Michelsen, A.; Schmidt, I. K.; Mikkelsen, T. N.

2014-12-01

The fate of recently plant assimilated carbon was followed into ecosystem carbon pools and fluxes in a temperate heathland after a 13CO2 pulse in the early growing season in a 6-year long multi-factorial climate change experiment. Eight days after the pulse, recently assimilated carbon was significantly higher in storage organs (rhizomes) of the grass Deschampsia flexuosa under elevated atmospheric CO2 concentration. Experimental drought induced a pronounced utilization of recently assimilated carbon belowground (roots, microbes, dissolved organic carbon) potentially counterbalancing limited nutrient availability. The fate of recently assimilated carbon was not affected by moderate warming. The full factorial combination of elevated CO2, warming and drought simulating future climatic conditions as expected for Denmark in 2075 did not change short-term carbon turnover significantly compared to ambient conditions. Overall, climate factors interacted in an unexpected way resulting in strong resilience of the heathland in terms of short-term carbon turnover in a future climate.

NASA's Sentinels Monitoring Weather and Climate: Past, Present, and Future

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Herring, David; Gutro, Rob; Huffman, George; Halverson, Jeff

2002-01-01

Weatherwise is probably the most popular newstand magazine focusing on the subject of weather. It is published six times per year and includes features on weather, climate, and technology. This article (to appear in the January/February Issue) provides a comprehensive review of NASA s past, present, and future contributions in satellite remote sensing for weather and climate processes. The article spans the historical strides of the TIROS program through the scientific and technological innovation of Earth Observer-3 and Global Precipitation Measurement (GPM). It is one of the most thorough reviews of NASA s weather and climate satellite efforts to appear in the popular literature.

Costa Rica Rainfall in Future Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Castillo Rodriguez, R. A., Sr.; Amador, J. A.; Duran-Quesada, A. M.

2017-12-01

Studies of intraseasonal and annual cycles of meteorological variables, using projections of climate change, are nowadays extremely important to improve regional socio-economic planning for countries. This is particularly true in Costa Rica, as Central America has been identified as a climate change hot spot. Today many of the economic activities in the region, especially those related to agriculture, tourism and hydroelectric power generation are linked to the seasonal cycle of precipitation. Changes in rainfall (mm/day) and in the diurnal temperature range (°C) for the periods 1950-2005 and 2006-2100 were investigated using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) constructed using the CMIP5 (Coupled Model Intercomparison Project version 5) data. Differences between the multi-model ensembles of the two prospective scenarios (RCP 4.5 and RCP 8.5) and the retrospective baseline scenario were computed. This study highlights Costa Rica as an inflexion point of the climate change in the region and also suggests future drying conditions.

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.

Future global mortality from changes in air pollution attributable to climate change

DOE PAGES

Silva, Raquel A.; West, J. Jason; Lamarque, Jean-François; ...

2017-07-31

Ground-level ozone and fine particulate matter (PM2.5) are associated with premature human mortality(1-4); their future concentrations depend on changes in emissions, which dominate the near-term(5), and on climate change(6,7). Previous global studies of the air-quality-related health effects of future climate change(8,9) used single atmospheric models. But, in related studies, mortality results differ among models(10-12). Here we use an ensemble of global chemistry-climate models(13) to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.5 (ref. 14), is probably positive. We estimate 3,340 (-30,300 to 47,100) ozone-related deaths in 2030, relativemore » to 2000 climate, and 43,600 (-195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM2.5, we estimate 55,600 (-34,300 to 164,000) deaths in 2030 and 215,000 (-76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Finally, most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.« less

Future Global Mortality from Changes in Air Pollution Attributable to Climate Change

NASA Technical Reports Server (NTRS)

Silva, Raquel A.; West, J. Jason; Lamarque, Jean-Francois; Shindell, Drew T.; Collins, William J.; Faluvegi, Greg; Folberth, Gerd A.; Horowitz, Larry W.; Nagashima, Tatsuya; Naik, Vaishali;

Future global mortality from changes in air pollution attributable to climate change

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

Silva, Raquel A.; West, J. Jason; Lamarque, Jean-François

Ground-level ozone and fine particulate matter (PM2.5) are associated with premature human mortality(1-4); their future concentrations depend on changes in emissions, which dominate the near-term(5), and on climate change(6,7). Previous global studies of the air-quality-related health effects of future climate change(8,9) used single atmospheric models. But, in related studies, mortality results differ among models(10-12). Here we use an ensemble of global chemistry-climate models(13) to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.5 (ref. 14), is probably positive. We estimate 3,340 (-30,300 to 47,100) ozone-related deaths in 2030, relativemore » to 2000 climate, and 43,600 (-195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM2.5, we estimate 55,600 (-34,300 to 164,000) deaths in 2030 and 215,000 (-76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Finally, most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.« less

Holocene climate in the western Great Lakes national parks and lakeshores: Implications for future climate change

USGS Publications Warehouse

Davis, Margaret; Douglas, Christine; Cole, K.L.; Winkler, Marge; Flaknes, Robyn

2000-01-01

We reconstruct Holocene climate history (last 10,000 years) for each of the U.S. National Park Service units in the western Great Lakes region in order to evaluate their sensitivity to global warming. Annual precipitation, annual temperature, and July and January temperatures were reconstructed by comparing fossil pollen in lake sediment with pollen in surface samples, assuming that ancient climates were similar to modern climate near analogous surface samples. In the early Holocene, most of the parks experienced colder winters, warmer summers, and lower precipitation than today. An exception is Voyageurs National Park in northern Minnesota where, by 8000 years ago, January temperatures were higher than today. The combination of high mean annual temperature and lower precipitation at Voyageurs resulted in a dry period between 8000 and 5000 years ago, similar to the Prairie Period in regions to the south and west. A mid-Holocene warm-dry period also occurred at other northern and central parks but was much less strongly developed. In southern parks there was no clear evidence of a mid-Holocene warm-dry period. These differences suggest that global model predictions of a warm, dry climate in the northern Great Plains under doubled atmospheric CO2 may be more applicable to Voyageurs than to the other parks. The contrast in reconstructed temperatures at Voyageurs and Isle Royale indicates that the ameliorating effect of the Great Lakes on temperatures has been in effect throughout the Holocene and presumably will continue in the future, thus reducing the potential for species loss caused by future temperature extremes. Increased numbers of mesic trees at all of the parks in the late Holocene reflect increasing annual precipitation. This trend toward more mesic conditions began 6000 years ago in the south and 4000 years ago in the north and increased sharply in recent millennia at parks located today in lake-effect snow belts. This suggests that lake-effect snowfall is

Impacts of Present and Future Climate Variability on Forest Ecosystem in Mediterranean Region

NASA Astrophysics Data System (ADS)

Ozcan, O.; Musaoglu, N.; Türkeş, M.

2017-12-01

The concept of `climate change vulnerability' helps us to better comprehend the cause/effect relationships behind climate change and its impact on human societies, socioeconomic sectors, physiographical and ecological systems. Herein, multifactorial spatial modeling was applied to evaluate the vulnerability of a Mediterranean forest ecosystem to climate change. Thus, the geographical distribution of the final Environmental Vulnerability Areas (EVAs) of the forest ecosystem are based on the estimated final Environmental Vulnerability Index (EVI) values. This revealed that at current levels of environmental degradation, physical, geographical, policy enforcement and socioeconomic conditions, the area with a "very low" vulnerability degree covered mainly the town, its surrounding settlements and the agricultural lands found mainly over the low and flat travertine plateau and the plains at the east and southeast of the district. The spatial magnitude of the EVAs over the forest ecosystem under the current environmental degradation was also determined. This revealed that the EVAs classed as "very low" account for 21% of the total area of the forest ecosystem, those classed as "low" account for 36%, those classed as "medium" account for 20%, and those classed as "high" account for 24%. Based on regionally averaged future climate assessments and projected future climate indicators, both the study site and the western Mediterranean sub-region of Turkey will probably become associated with a drier, hotter, more continental and more water-deficient climate. This analysis holds true for all future scenarios, with the exception of RCP4.5 for the period from 2015 to 2030. However, the present dry-sub humid climate dominating this sub-region and the study area shows a potential for change towards more dry climatology and for it to become a semiarid climate in the period between 2031 and 2050 according to the RCP8.5 high emission scenario. All the observed and estimated results

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

Simulating malaria transmission in the current and future climate of West Africa

NASA Astrophysics Data System (ADS)

Yamana, T. K.; Bomblies, A.; Eltahir, E. A. B.

2015-12-01

Malaria transmission in West Africa is closely tied to climate, as rain fed water pools provide breeding habitat for the anopheles mosquito vector, and temperature affects the mosquito's ability to spread disease. We present results of a highly detailed, spatially explicit mechanistic modelling study exploring the relationships between the environment and malaria in the current and future climate of West Africa. A mechanistic model of human immunity was incorporated into an existing agent-based model of malaria transmission, allowing us to move beyond entomological measures such as mosquito density and vectorial capacity to analyzing the prevalence of the malaria parasite within human populations. The result is a novel modelling tool that mechanistically simulates all of the key processes linking environment to malaria transmission. Simulations were conducted across climate zones in West Africa, linking temperature and rainfall to entomological and epidemiological variables with a focus on nonlinearities due to threshold effects and interannual variability. Comparisons to observations from the region confirmed that the model provides a reasonable representation of the entomological and epidemiological conditions in this region. We used the predictions of future climate from the most credible CMIP5 climate models to predict the change in frequency and severity of malaria epidemics in West Africa as a result of climate change.

The shaping of genetic variation in edge-of-range populations under past and future climate change

PubMed Central

Razgour, Orly; Juste, Javier; Ibáñez, Carlos; Kiefer, Andreas; Rebelo, Hugo; Puechmaille, Sébastien J; Arlettaz, Raphael; Burke, Terry; Dawson, Deborah A; Beaumont, Mark; Jones, Gareth; Wiens, John

2013-01-01

With rates of climate change exceeding the rate at which many species are able to shift their range or adapt, it is important to understand how future changes are likely to affect biodiversity at all levels of organisation. Understanding past responses and extent of niche conservatism in climatic tolerance can help predict future consequences. We use an integrated approach to determine the genetic consequences of past and future climate changes on a bat species, Plecotus austriacus. Glacial refugia predicted by palaeo-modelling match those identified from analyses of extant genetic diversity and model-based inference of demographic history. Former refugial populations currently contain disproportionately high genetic diversity, but niche conservatism, shifts in suitable areas and barriers to migration mean that these hotspots of genetic diversity are under threat from future climate change. Evidence of population decline despite recent northward migration highlights the need to conserve leading-edge populations for spearheading future range shifts. PMID:23890483

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.

The Contribution of Soils to North America's Current and Future Climate

NASA Astrophysics Data System (ADS)

Mayes, M. A.; Reed, S.; Thornton, P. E.; Lajtha, K.; Bailey, V. L.; Shrestha, G.; Jastrow, J. D.; Torn, M. S.

2015-12-01

This presentation will cover key aspects of the terrestrial soil carbon cycle in North America and the US for the upcoming State of the Carbon Cycle Report (SOCCRII). SOCCRII seeks to summarize how natural processes and human interactions affect the global carbon cycle, how socio-economic trends affect greenhouse gas concentrations in the atmosphere, and how ecosystems are influenced by and respond to greenhouse gas emissions, management decisions, and concomitant climate effects. Here, we will summarize the contemporary understanding of carbon stocks, fluxes, and drivers in the soil ecosystem compartment. We will highlight recent advances in modeling the magnitude of soil carbon stocks and fluxes, as well as the importance of remaining uncertainties in predicting soil carbon cycling and its relationship with climate. Attention will be given to the role of uncertainties in predicting future fluxes from soils, and how those uncertainties vary by region and ecosystem. We will also address how climate feedbacks and management decisions can enhance or minimize future climatic effects based on current understanding and observations, and will highlight select research needs to improve our understanding of the balance of carbon in soils in North America.

Climate induced changes on the hydrology of Mediterranean basins - assessing uncertainties and quantifying risks

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2014-05-01

According to current climate projections, the Mediterranean area is at high risk for severe changes in the hydrological budget and extremes. With innovative scientific measures, integrated hydrological modeling and novel field geophysical field monitoring techniques, the FP7 project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins; GA: 244151) assessed the impacts of climate change on the hydrology in seven basins in the Mediterranean area, in Italy, France, Turkey, Tunisia, Egypt and the Gaza Strip, and quantified uncertainties and risks for the main stakeholders of each test site. Intensive climate model auditing selected four regional climate models, whose data was bias corrected and downscaled to serve as climate forcing for a set of hydrological models in each site. The results of the multi-model hydro-climatic ensemble and socio-economic factor analysis were applied to develop a risk model building upon spatial vulnerability and risk assessment. Findings generally reveal an increasing risk for water resources management in the test sites, yet at different rates and severity in the investigated sectors, with highest impacts likely to occur in the transition months. Most important elements of this research include the following aspects: • Climate change contributes, yet in strong regional variation, to water scarcity in the Mediterranean; other factors, e.g. pollution or poor management practices, are regionally still dominant pressures on water resources. • Rain-fed agriculture needs to adapt to seasonal changes; stable or increasing productivity likely depends on additional irrigation. • Tourism could benefit in shoulder seasons, but may expect income losses in the summer peak season due to increasing heat stress. • Local & regional water managers and water users, lack, as yet, awareness of climate change induced risks; emerging focus areas are supplies of domestic drinking water, irrigation, hydropower and livestock. • Data

Quantifying and Monetizing Potential Climate Change Policy Impacts on Terrestrial Ecosystem Carbon Storage and Wildfires in the United States

EPA Science Inventory

This paper quantifies and monetizes climate change impacts on carbon stored in terrestrial vegetation and wildfire incidence in the contiguous United States to assess the benefits of alternative mitigation policies. The MC-1 dynamic global vegetation model was used to develop int...

The Mediterranean surface wave climate inferred from future scenario simulations

NASA Astrophysics Data System (ADS)

Lionello, P.; Cogo, S.; Galati, M. B.; Sanna, A.

2008-09-01

This study is based on 30-year long simulations of the wind-wave field in the Mediterranean Sea carried out with the WAM model. Wave fields have been computed for the 2071-2100 period of the A2, B2 emission scenarios and for the 1961-1990 period of the present climate (REF). The wave model has been forced by the wind field computed by a regional climate model with 50 km resolution. The mean SWH (Significant Wave Height) field over large fraction of the Mediterranean sea is lower for the A2 scenario than for the present climate during winter, spring and autumn. During summer the A2 mean SWH field is also lower everywhere, except for two areas, those between Greece and Northern Africa and between Spain and Algeria, where it is significantly higher. All these changes are similar, though smaller and less significant, in the B2 scenario, except during winter in the north-western Mediterranean Sea, when the B2 mean SWH field is higher than in the REF simulation. Also extreme SWH values are smaller in future scenarios than in the present climate and such SWH change is larger for the A2 than for the B2 scenario. The only exception is the presence of higher SWH extremes in the central Mediterranean during summer for the A2 scenario. In general, changes of SWH, wind speed and atmospheric circulation are consistent, and results show milder marine storms in future scenarios than in the present climate.

Recent and projected future climatic suitability of North America for the Asian tiger mosquito Aedes albopictus.

PubMed

Ogden, Nicholas H; Milka, Radojević; Caminade, Cyril; Gachon, Philippe

2014-12-02

Since the 1980s, populations of the Asian tiger mosquito Aedes albopictus have become established in south-eastern, eastern and central United States, extending to approximately 40°N. Ae. albopictus is a vector of a wide range of human pathogens including dengue and chikungunya viruses, which are currently emerging in the Caribbean and Central America and posing a threat to North America. The risk of Ae. albopictus expanding its geographic range in North America under current and future climate was assessed using three climatic indicators of Ae. albopictus survival: overwintering conditions (OW), OW combined with annual air temperature (OWAT), and a linear index of precipitation and air temperature suitability expressed through a sigmoidal function (SIG). The capacity of these indicators to predict Ae. albopictus occurrence was evaluated using surveillance data from the United States. Projected future climatic suitability for Ae. albopictus was obtained using output of nine Regional Climate Model experiments (RCMs). OW and OWAT showed >90% specificity and sensitivity in predicting observed Ae. albopictus occurrence and also predicted moderate to high risk of Ae. albopictus invasion in Pacific coastal areas of the Unites States and Canada under current climate. SIG also well predicted observed Ae. albopictus occurrence (ROC area under the curve was 0.92) but predicted wider current climatic suitability in the north-central and north-eastern United States and south-eastern Canada. RCM output projected modest (circa 500 km) future northward range expansion of Ae. albopictus by the 2050s when using OW and OWAT indicators, but greater (600-1000 km) range expansion, particularly in eastern and central Canada, when using the SIG indicator. Variation in future possible distributions of Ae. albopictus was greater amongst the climatic indicators used than amongst the RCM experiments. Current Ae. albopictus distributions were well predicted by simple climatic indicators

Quantifying renewable groundwater stress with GRACE

NASA Astrophysics Data System (ADS)

Richey, Alexandra S.; Thomas, Brian F.; Lo, Min-Hui; Reager, John T.; Famiglietti, James S.; Voss, Katalyn; Swenson, Sean; Rodell, Matthew

2015-07-01

Groundwater is an increasingly important water supply source globally. Understanding the amount of groundwater used versus the volume available is crucial to evaluate future water availability. We present a groundwater stress assessment to quantify the relationship between groundwater use and availability in the world's 37 largest aquifer systems. We quantify stress according to a ratio of groundwater use to availability, which we call the Renewable Groundwater Stress ratio. The impact of quantifying groundwater use based on nationally reported groundwater withdrawal statistics is compared to a novel approach to quantify use based on remote sensing observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. Four characteristic stress regimes are defined: Overstressed, Variable Stress, Human-dominated Stress, and Unstressed. The regimes are a function of the sign of use (positive or negative) and the sign of groundwater availability, defined as mean annual recharge. The ability to mitigate and adapt to stressed conditions, where use exceeds sustainable water availability, is a function of economic capacity and land use patterns. Therefore, we qualitatively explore the relationship between stress and anthropogenic biomes. We find that estimates of groundwater stress based on withdrawal statistics are unable to capture the range of characteristic stress regimes, especially in regions dominated by sparsely populated biome types with limited cropland. GRACE-based estimates of use and stress can holistically quantify the impact of groundwater use on stress, resulting in both greater magnitudes of stress and more variability of stress between regions.

Quantifying renewable groundwater stress with GRACE

PubMed Central

Richey, Alexandra S.; Thomas, Brian F.; Lo, Min‐Hui; Reager, John T.; Voss, Katalyn; Swenson, Sean; Rodell, Matthew

2015-01-01

Abstract Groundwater is an increasingly important water supply source globally. Understanding the amount of groundwater used versus the volume available is crucial to evaluate future water availability. We present a groundwater stress assessment to quantify the relationship between groundwater use and availability in the world's 37 largest aquifer systems. We quantify stress according to a ratio of groundwater use to availability, which we call the Renewable Groundwater Stress ratio. The impact of quantifying groundwater use based on nationally reported groundwater withdrawal statistics is compared to a novel approach to quantify use based on remote sensing observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. Four characteristic stress regimes are defined: Overstressed, Variable Stress, Human‐dominated Stress, and Unstressed. The regimes are a function of the sign of use (positive or negative) and the sign of groundwater availability, defined as mean annual recharge. The ability to mitigate and adapt to stressed conditions, where use exceeds sustainable water availability, is a function of economic capacity and land use patterns. Therefore, we qualitatively explore the relationship between stress and anthropogenic biomes. We find that estimates of groundwater stress based on withdrawal statistics are unable to capture the range of characteristic stress regimes, especially in regions dominated by sparsely populated biome types with limited cropland. GRACE‐based estimates of use and stress can holistically quantify the impact of groundwater use on stress, resulting in both greater magnitudes of stress and more variability of stress between regions. PMID:26900185

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Disaggregating from daily to sub-daily rainfall under a future climate

NASA Astrophysics Data System (ADS)

Westra, S.; Evans, J.; Mehrotra, R.; Sharma, A.

2012-04-01

We describe an algorithm for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous fine-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of atmospheric predictors representative of the future climate. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric profile more reflective of expected future conditions. When looking at the scaling from daily to sub-daily rainfall over the historical record, it was found that the relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically showing more intense rain falling over shorter periods compared with cooler seasons and stations. Importantly, by regressing against atmospheric covariates such as temperature this effect was almost entirely eliminated, providing a basis for suggesting the approach may be valid when extrapolating sub-daily sequences to a future climate. The method of fragments algorithm was then applied to nine stations around Australia, and showed that when holding the total daily rainfall constant, the maximum intensity of a short duration (6 minute) rainfall increased by between 4.1% and 13.4% per degree change in temperature for the maximum six minute burst, between 3.1% and 6.8% for the maximum one hour burst, and between 1.5% and 3.5% for the fraction of the day with no rainfall. This highlights that a large proportion of the change to the distribution of precipitation in the future is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

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.;

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.

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

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.

Quantifying climate change mitigation potential in Great Plains wetlands for three greenhouse gas emission scenarios

USGS Publications Warehouse

Byrd, Kristin B.; Ratliff, Jamie L.; Wein, Anne; Bliss, Norman B.; Sleeter, Benjamin M.; Sohl, Terry L.; Li, Zhengpeng

2015-01-01

We examined opportunities for avoided loss of wetland carbon stocks in the Great Plains of the United States in the context of future agricultural expansion through analysis of land-use land-cover (LULC) change scenarios, baseline carbon datasets and biogeochemical model outputs. A wetland map that classifies wetlands according to carbon pools was created to describe future patterns of carbon loss and potential carbon savings. Wetland avoided loss scenarios, superimposed upon LULC change scenarios, quantified carbon stocks preserved under criteria of carbon densities or land value plus cropland suitability. Up to 3420 km2 of wetlands may be lost in the region by 2050, mainly due to conversion of herbaceous wetlands in the Temperate Prairies where soil organic carbon (SOC) is highest. SOC loss would be approximately 0.20 ± 0.15 megagrams of carbon per hectare per year (MgC ha−1 yr−1), depending upon tillage practices on converted wetlands, and total ecosystem carbon loss in woody wetlands would be approximately 0.81 ± 0.41 MgC ha−1 yr−1, based on biogeochemical model results. Among wetlands vulnerable to conversion, wetlands in the Northern Glaciated Plains and Lake Agassiz Plains ecoregions exhibit very high mean SOC and on average, relatively low land values, potentially creating economically competitive opportunities for avoided carbon loss. This mitigation scenarios approach may be adapted by managers using their own preferred criteria to select sites that best meet their objectives. Results can help prioritize field-based assessments, where site-level investigations of carbon stocks, land value, and consideration of local priorities for climate change mitigation programs are needed.

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

Impacts of climate change on water quantity and quality in Rhineland-Palatinate/Germany

NASA Astrophysics Data System (ADS)

Casper, M. C.; Grigoryan, G. V.

2009-04-01

The Ministry of the Environment of Rhineland-Palatinate, Germany, launched an interdisciplinary research project dealing with "climate and land use change in Rhineland-Palatinate" (KlimLandRP). The aim of KlimLandRP is to specify adaptation strategies and to find current research gaps. The University of Trier/Germany undertakes the task of quantifying the impact of climate change on hydrological cycle and on water quality. In the first phase of the project (2008/2009) the models STOFFBILANZ and WaSiM-ETH are applied. WETTREG projections (2050/2100) and newly high resolution CCLM (2015-2024) projections for Rhineland-Palatinate are used to indicate the spectrum of climate change. Possible land use scenarios for agricultural regions are furthermore adopted. Using STOFFBILANZ it is possible to get approximate spatial information about present and future distribution of water, nitrate and phosphor balance in Rhineland-Palatinate and to identify sensitive regions. Based on achieved results, regions which are vulnerable to water economy are identified and adaptations proposed. With the application of WaSiM-ETH the impact of climate change on water balance of forest sites is quantified. The relation between climate parameters and tree growth indices is applied in forest management planning, particularly for forest site mapping. In the future, also the rainfall-runoff model LARSIM will be applied to quantify the impacts of climate change on the hydrological cycle of mesoscale catchment basins.

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.

Nonlinear climate sensitivity and its implications for future greenhouse warming.

PubMed

Friedrich, Tobias; Timmermann, Axel; Tigchelaar, Michelle; Elison Timm, Oliver; Ganopolski, Andrey

2016-11-01

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing-referred to as specific equilibrium climate sensitivity ( S )-is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth's future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections.

Nonlinear climate sensitivity and its implications for future greenhouse warming

PubMed Central

Friedrich, Tobias; Timmermann, Axel; Tigchelaar, Michelle; Elison Timm, Oliver; Ganopolski, Andrey

2016-01-01

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing—referred to as specific equilibrium climate sensitivity (S)—is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth’s future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections. PMID:28861462

Application of the new scenario framework for climate change research: Future social vulnerability in large urban areas

NASA Astrophysics Data System (ADS)

Rohat, Guillaume; Flacke, Johannes; Dao, Hy

2016-04-01

It is by now widely acknowledged that future social vulnerability to climate change depends on both future climate state and future socio-economic conditions. Nevertheless, while most of the vulnerability assessments are using climate projections, the integration of socio-economic projections into the assessment of vulnerabilities has been very limited. Up to now, the vast majority of vulnerability assessments has been using current socio-economic conditions, hence has failed to consider the influence of socio-economic developments in the construction of vulnerability. To enhance the use of socio-economic projections into climate change impacts, adaptation and vulnerability assessments, the climate change research community has been recently involved in the development of a new model for creating scenarios that integrate future changes in climate as well as in society, known under the name of the new scenario framework for climate change research. This theoretical framework is made of a set of alternative futures of socio-economic developments (known as shared socio-economic pathways - SSPs), a set of hypothesis about future climate policies (known as shared policy assumptions - SPAs) and a set of greenhouse gas concentration trajectories (known as representative concentration pathways - RCPs), which are all combined into a scenario matrix architecture (SMA) whose aim is to facilitate the use of this framework. Despite calls by the climate change research community for the use of this conceptual framework in impacts, adaptation and vulnerability research, its use and its assessment has been very limited. Focusing on case-studies (i.e. specific cities as well as specific climate impacts and their associated human exposures and vulnerabilities), the study presented here will attempt to operationalize this theoretical framework for the assessment of future social vulnerability in large urban areas. A particular attention will be paid to less advanced and more

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

DOE PAGES

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

2018-01-15

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

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

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

Zhou, Qianqian; Leng, Guoyong; Huang, Maoyi

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

Future climate impact on unfavorable meteorological conditions for the dispersion of air pollution in Brussels

NASA Astrophysics Data System (ADS)

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

2015-04-01

Belgium is one of the several countries in Europe where air quality levels of different pollutants such as ozone, NOx, and Particulate Matter (PM) still exceed the prescribed European norms multiple times a year (EEA, 2014). These pollution peaks have a great impact on health and environment, in particular in large cities and urban environments. It is well known that observed concentrations of air pollutants are strongly influenced by emissions and meteorological conditions and therefore is sensitive to climate change. As the effects of global climate change are increasingly felt in Belgium, policy makers express growing interest in quantifying its effect on air pollution and the effort required to meet the air quality targets in the next years and decennia (Lauwaet et al., 2014). In this study, two different stability indices are calculated for a 9-year period using present (1991-1999) and future (2047-2055) climate data that has been obtained from a dynamically downscaling of Global Climate Model data from the Arpège model using the ALARO model at 4 km spatial resolution. The ALARO model is described in detail in previous validation studies from De Troch et al. (2013) and Hamdi et al. (2013). The first index gives a measure of the horizontal and vertical transport of nonreactive pollutants in stable atmospheric conditions and has been proposed and tested by Termonia and Quinet (2004). It gives a characteristic length scale l which is the ratio of the mean horizontal wind speed and the Brunt-Väisälä frequency. In this way low values for l in the lower part of the boundary layer during an extended time span of 12 hours, correspond to calm situations and a stable atmosphere and thus indicate unfavorable conditions for the dispersion of air pollution. This transport index is similar to an index used in an old Pasquill-type scheme but is more convenient to use to detect the strongest pollution peaks. The well known Pasquill classes are also calculated in order to

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

Quantifying climate change impacts emphasises the importance of managing regional threats in the endangered Yellow-eyed penguin.

PubMed

Mattern, Thomas; Meyer, Stefan; Ellenberg, Ursula; Houston, David M; Darby, John T; Young, Melanie; van Heezik, Yolanda; Seddon, Philip J

2017-01-01

Climate change is a global issue with effects that are difficult to manage at a regional scale. Yet more often than not climate factors are just some of multiple stressors affecting species on a population level. Non-climatic factors-especially those of anthropogenic origins-may play equally important roles with regard to impacts on species and are often more feasible to address. Here we assess the influence of climate change on population trends of the endangered Yellow-eyed penguin ( Megadyptes antipodes ) over the last 30 years, using a Bayesian model. Sea surface temperature (SST) proved to be the dominating factor influencing survival of both adult birds and fledglings. Increasing SST since the mid-1990s was accompanied by a reduction in survival rates and population decline. The population model showed that 33% of the variation in population numbers could be explained by SST alone, significantly increasing pressure on the penguin population. Consequently, the population becomes less resilient to non-climate related impacts, such as fisheries interactions, habitat degradation and human disturbance. However, the extent of the contribution of these factors to declining population trends is extremely difficult to assess principally due to the absence of quantifiable data, creating a discussion bias towards climate variables, and effectively distracting from non-climate factors that can be managed on a regional scale to ensure the viability of the population.

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.

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

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.

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

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-10-01

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

DBP formation and disinfection under current and future climates - slides

EPA Science Inventory

How to predict and monitoring DBP formation under current and future climate is a challenge and important to water plant operations and water supply security. This presentation summarizes a system approach being developed at the EPA Water Resources Adaptation Program (WRAP).

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.

Future Evolution of Marine Heat Waves in the Mediterranean: Coupled Regional Climate Projections

NASA Astrophysics Data System (ADS)

Darmaraki, Sofia; Somot, Samuel; Sevault, Florence; Nabat, Pierre; Cavicchia, Leone; Djurdjevic, Vladimir; Cabos, William; Sein, Dmitry

2017-04-01

FUTURE EVOLUTION OF MARINE HEAT WAVES IN THE MEDITERRANEAN : COUPLED REGIONAL CLIMATE PROJECTIONS The Mediterranean area is identified as a « Hot Spot » region, vulnerable to future climate change with potentially strong impacts over the sea. By 2100, climate models predict increased warming over the sea surface, with possible implications on the Mediterranean thermohaline and surface circulation,associated also with severe impacts on the ecosystems (e.g. fish habitat loss, species extinction and migration, invasive species). However, a robust assesment of the future evolution of the extreme marine temperatures remains still an open issue of primary importance, under the anthropogenic pressure. In this context, we study here the probability and characteristics of marine heat wave (MHW) occurrence in the Mediterranean Sea in future climate projections. To this end, we use an ensemble of fully coupled regional climate system models (RCSM) from the Med- CORDEX initiative. This multi-model approach includes a high-resolution representation of the atmospheric, land and ocean component, with a free air-sea interface.Specifically, dedicated simulations for the 20th and the 21st century are carried out with respect to the different IPCC-AR5 socioeconomic scenarios (1950-2100, RCP8.5, RCP4.5, RCP2.6). Model evaluation for the historical period is performed using satellite and in situ data. Then, the variety of factors that can cause the MHW (e.g. direct radiative forcing, ocean advection, stratification change) are examined to disentangle the dominant driving force. Finally, the spatial variability and temporal evolution of MHW are analyzed on an annual basis, along with additional integrated indicators, useful for marine ecosystems.

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.

Climate: Is the past the key to the future?

NASA Astrophysics Data System (ADS)

Hay, W. W.; DeConto, R. M.; Wold, C. N.

maximum. Anthropogenic activity has increased the CO2 content of the atmosphere to 130% of its previous Holocene level, probably higher than at any time during the past few million years. During the Late Cretaceous the atmospheric CO2 content was probably about four times that of the present, the level to which it may rise at the end of the next century. The results of a Campanian (80 Ma) climate simulation suggest that the positive feedback between CO2 and another important greenhouse gas, H2O, raised the earth's temperature to a level where latent heat transport became much more significant than it is presently, and operated efficiently at all latitudes. Atmospheric high- and low-pressure systems were as much the result of variations in the vapor content of the air as of temperature differences. In our present state of knowledge, future climate change is unpredictable because by adding CO2 to the atmosphere we are forcing the climate toward a ``greenhouse'' mode when it is accustomed to moving between the glacial-interglacial ``icehouse'' states that reflect the waxing and waning of ice sheets. At the same time we are replacing freely transpiring C3 plants with water-conserving C4 plants, producing a global vegetation complex that has no past analog. The past climates of the earth cannot be used as a direct guide to what may occur in the future. To understand what may happen in the future we must learn about the first principles of physics and chemistry related to the earth's system. The fundamental mechanisms of the climate system are best explored in simulations of the earth's ancient extreme climates.

Future climate change scenarios in Central America at high spatial resolution

PubMed Central

Imbach, Pablo; Chou, Sin Chan; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961–1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021–2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021–2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean

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.

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.

Development of a database system for near-future climate change projections under the Japanese National Project SI-CAT

NASA Astrophysics Data System (ADS)

Nakagawa, Y.; Kawahara, S.; Araki, F.; Matsuoka, D.; Ishikawa, Y.; Fujita, M.; Sugimoto, S.; Okada, Y.; Kawazoe, S.; Watanabe, S.; Ishii, M.; Mizuta, R.; Murata, A.; Kawase, H.

2017-12-01

Analyses of large ensemble data are quite useful in order to produce probabilistic effect projection of climate change. Ensemble data of "+2K future climate simulations" are currently produced by Japanese national project "Social Implementation Program on Climate Change Adaptation Technology (SI-CAT)" as a part of a database for Policy Decision making for Future climate change (d4PDF; Mizuta et al. 2016) produced by Program for Risk Information on Climate Change. Those data consist of global warming simulations and regional downscaling simulations. Considering that those data volumes are too large (a few petabyte) to download to a local computer of users, a user-friendly system is required to search and download data which satisfy requests of the users. We develop "a database system for near-future climate change projections" for providing functions to find necessary data for the users under SI-CAT. The database system for near-future climate change projections mainly consists of a relational database, a data download function and user interface. The relational database using PostgreSQL is a key function among them. Temporally and spatially compressed data are registered on the relational database. As a first step, we develop the relational database for precipitation, temperature and track data of typhoon according to requests by SI-CAT members. The data download function using Open-source Project for a Network Data Access Protocol (OPeNDAP) provides a function to download temporally and spatially extracted data based on search results obtained by the relational database. We also develop the web-based user interface for using the relational database and the data download function. A prototype of the database system for near-future climate change projections are currently in operational test on our local server. The database system for near-future climate change projections will be released on Data Integration and Analysis System Program (DIAS) in fiscal year 2017

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)

Zhuang, Qianlai; Schlosser, Courtney; Melillo, Jerry

2015-09-15

Our overall goal is 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 is 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 of numerical experiments thatmore » encapsulate the fundamental processes governing methane emissions and carbon exchanges – as well as their coupling to the global climate system - we intend to test 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.« less