Climate risks on potato yield in Europe

NASA Astrophysics Data System (ADS)

Sun, Xun; Lall, Upmanu

2016-04-01

The yield of potatoes is affected by water and temperature during the growing season. We study the impact of a suite of climate variables on potato yield at country level. More than ten climate variables related to the growth of potato are considered, including the seasonal rainfall and temperature, but also extreme conditions at different averaging periods from daily to monthly. A Bayesian hierarchical model is developed to jointly consider the risk of heat stress, cold stress, wet and drought. Future climate risks are investigated through the projection of future climate data. This study contributes to assess the risks of present and future climate risks on potatoes yield, especially the risks of extreme events, which could be used to guide better sourcing strategy and ensure food security in the future.

Changes in extreme events and the potential impacts on human health.

PubMed

Bell, Jesse E; Brown, Claudia Langford; Conlon, Kathryn; Herring, Stephanie; Kunkel, Kenneth E; Lawrimore, Jay; Luber, George; Schreck, Carl; Smith, Adam; Uejio, Christopher

2018-04-01

Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future. Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

PubMed

Kara, Fatih; Yucel, Ismail

2015-09-01

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

Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

NASA Astrophysics Data System (ADS)

Samaras, C.; Cook, L.

2015-12-01

Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.

Precipitation extremes and their relation to climatic indices in the Pacific Northwest USA

NASA Astrophysics Data System (ADS)

Zarekarizi, Mahkameh; Rana, Arun; Moradkhani, Hamid

2018-06-01

There has been focus on the influence of climate indices on precipitation extremes in the literature. Current study presents the evaluation of the precipitation-based extremes in Columbia River Basin (CRB) in the Pacific Northwest USA. We first analyzed the precipitation-based extremes using statistically (ten GCMs) and dynamically downscaled (three GCMs) past and future climate projections. Seven precipitation-based indices that help inform about the flood duration/intensity are used. These indices help in attaining first-hand information on spatial and temporal scales for different service sectors including energy, agriculture, forestry etc. Evaluation of these indices is first performed in historical period (1971-2000) followed by analysis of their relation to large scale tele-connections. Further we mapped these indices over the area to evaluate the spatial variation of past and future extremes in downscaled and observational data. The analysis shows that high values of extreme indices are clustered in either western or northern parts of the basin for historical period whereas the northern part is experiencing higher degree of change in the indices for future scenario. The focus is also on evaluating the relation of these extreme indices to climate tele-connections in historical period to understand their relationship with extremes over CRB. Various climate indices are evaluated for their relationship using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD). Results indicated that, out of 13 climate tele-connections used in the study, CRB is being most affected inversely by East Pacific (EP), Western Pacific (WP), East Atlantic (EA) and North Atlaentic Oscillation (NAO).

Characterization of extreme precipitation within atmospheric river events over California

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

Jeon, S.; Prabhat,; Byna, S.

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

Characterization of extreme precipitation within atmospheric river events over California

DOE PAGES

Jeon, S.; Prabhat,; Byna, S.; ...

2015-11-17

Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climatemore » Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.« less

Research progress of extreme climate and its vegetation response

NASA Astrophysics Data System (ADS)

Cui, Xiaolin; Wei, Xiaoqing; Wang, Tao

2017-08-01

The IPCC’s fifth assessment report indicates that climate warming is unquestionable, the frequency and intensity of extreme weather events may increase, and extreme weather events can destroy the growth conditions of vegetation that is otherwise in a stable condition. Therefore, it is essential to research the formation of extreme weather events and its ecological response, both in terms scientific development and the needs of societal development. This paper mainly examines these issues from the following aspects: (1) the definition of extreme climate events and the methods of studying the associated response of vegetation; (2) the research progress on extreme climate events and their vegetation response; and (3) the future direction of research on extreme climate and its vegetation response.

Changes in the probability of co-occurring extreme climate events

NASA Astrophysics Data System (ADS)

Diffenbaugh, N. S.

2017-12-01

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

Hazardous thunderstorm intensification over Lake Victoria

PubMed Central

Thiery, Wim; Davin, Edouard L.; Seneviratne, Sonia I.; Bedka, Kristopher; Lhermitte, Stef; van Lipzig, Nicole P. M.

2016-01-01

Weather extremes have harmful impacts on communities around Lake Victoria, where thousands of fishermen die every year because of intense night-time thunderstorms. Yet how these thunderstorms will evolve in a future warmer climate is still unknown. Here we show that Lake Victoria is projected to be a hotspot of future extreme precipitation intensification by using new satellite-based observations, a high-resolution climate projection for the African Great Lakes and coarser-scale ensemble projections. Land precipitation on the previous day exerts a control on night-time occurrence of extremes on the lake by enhancing atmospheric convergence (74%) and moisture availability (26%). The future increase in extremes over Lake Victoria is about twice as large relative to surrounding land under a high-emission scenario, as only over-lake moisture advection is high enough to sustain Clausius–Clapeyron scaling. Our results highlight a major hazard associated with climate change over East Africa and underline the need for high-resolution projections to assess local climate change. PMID:27658848

Updated Intensity - Duration - Frequency Curves Under Different Future Climate Scenarios

NASA Astrophysics Data System (ADS)

Ragno, E.; AghaKouchak, A.

2016-12-01

Current infrastructure design procedures rely on the use of Intensity - Duration - Frequency (IDF) curves retrieved under the assumption of temporal stationarity, meaning that occurrences of extreme events are expected to be time invariant. However, numerous studies have observed more severe extreme events over time. Hence, the stationarity assumption for extreme analysis may not be appropriate in a warming climate. This issue raises concerns regarding the safety and resilience of the existing and future infrastructures. Here we employ historical and projected (RCP 8.5) CMIP5 runs to investigate IDF curves of 14 urban areas across the United States. We first statistically assess changes in precipitation extremes using an energy-based test for equal distributions. Then, through a Bayesian inference approach for stationary and non-stationary extreme value analysis, we provide updated IDF curves based on climatic model projections. This presentation summarizes the projected changes in statistics of extremes. We show that, based on CMIP5 simulations, extreme precipitation events in some urban areas can be 20% more severe in the future, even when projected annual mean precipitation is expected to remain similar to the ground-based climatology.

Projected changes in climate extremes over Qatar and the Arabian Gulf region

NASA Astrophysics Data System (ADS)

Kundeti, K.; Kanikicharla, K. K.; Al sulaiti, M.; Khulaifi, M.; Alboinin, N.; Kito, A.

2015-12-01

The climate of the State of Qatar and the adjacent region is dominated by subtropical dry, hot desert climate with low annual rainfall, very high temperatures in summer and a big difference between maximum and minimum temperatures, especially in the inland areas. The coastal areas are influenced by the Arabian Gulf, and have lower maximum, but higher minimum temperatures and a higher moisture percentage in the air. The global warming can have profound impact on the mean climate as well as extreme weather events over the Arabian Peninsula that may affect both natural and human systems significantly. Therefore, it is important to assess the future changes in the seasonal/annual mean of temperature and precipitation and also the extremes in temperature and wind events for a country like Qatar. This study assesses the performance of the Coupled Model Inter comparison Project Phase 5 (CMIP5) simulations in present and develops future climate scenarios. The changes in climate extremes are assessed for three future periods 2016-2035, 2046-2065 and 2080-2099 with respect to 1986-2005 (base line) under two RCPs (Representative Concentrate Pathways) - RCP4.5 and RCP8.5. We analyzed the projected changes in temperature and precipitation extremes using several indices including those that capture heat stress. The observations show an increase in warm extremes over many parts in this region that are generally well captured by the models. The results indicate a significant change in frequency and intensity of both temperature and precipitation extremes over many parts of this region which may have serious implications on human health, water resources and the onshore/offshore infrastructure in this region. Data from a high-resolution (20km) AGCM simulation from Meteorological Research Institute of Japan Meteorological Agency for the present (1979-2003) and a future time slice (2075-2099) corresponding to RCP8.5 have also been utilized to assess the impact of climate change on regional climate extremes as well. The scenarios generated with the high-resolution model simulation were compared with the coarse resolution CMIP5 model scenarios to identify region specific features that might be better resolved in the former simulation.

Climate extremes and the carbon cycle.

PubMed

Reichstein, Markus; Bahn, Michael; Ciais, Philippe; Frank, Dorothea; Mahecha, Miguel D; Seneviratne, Sonia I; Zscheischler, Jakob; Beer, Christian; Buchmann, Nina; Frank, David C; Papale, Dario; Rammig, Anja; Smith, Pete; Thonicke, Kirsten; van der Velde, Marijn; Vicca, Sara; Walz, Ariane; Wattenbach, Martin

2013-08-15

The terrestrial biosphere is a key component of the global carbon cycle and its carbon balance is strongly influenced by climate. Continuing environmental changes are thought to increase global terrestrial carbon uptake. But evidence is mounting that climate extremes such as droughts or storms can lead to a decrease in regional ecosystem carbon stocks and therefore have the potential to negate an expected increase in terrestrial carbon uptake. Here we explore the mechanisms and impacts of climate extremes on the terrestrial carbon cycle, and propose a pathway to improve our understanding of present and future impacts of climate extremes on the terrestrial carbon budget.

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.

Extreme Events in China under Climate Change: Uncertainty and related impacts (CSSP-FOREX)

NASA Astrophysics Data System (ADS)

Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.

2016-04-01

Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.

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.

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.

Possible future changes in extreme events over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Scott, Jeffery

2013-04-01

In this study, we investigate possible future climate change over Northern Eurasia and its impact on extreme events. Northern Eurasia is a major player in the global carbon budget because of boreal forests and peatlands. Circumpolar boreal forests alone contain more than five times the amount of carbon of temperate forests and almost double the amount of carbon of the world's tropical forests. Furthermore, severe permafrost degradation associated with climate change could result in peatlands releasing large amounts of carbon dioxide and methane. Meanwhile, changes in the frequency and magnitude of extreme events, such as extreme precipitation, heat waves or frost days are likely to have substantial impacts on Northern Eurasia ecosystems. For this reason, it is very important to quantify the possible climate change over Northern Eurasia under different emissions scenarios, while accounting for the uncertainty in the climate response and changes in extreme events. For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. In this study, regional change is investigated using the MIT IGSM-CAM framework that links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). New modules were developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM. The simulations presented in this paper were carried out for two emission scenarios, a "business as usual" scenario and a 660 ppm of CO2-equivalent stabilization, which are similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios. Values of climate sensitivity and net aerosol forcing used in the simulations within the IGSM-CAM framework provide a good approximation for the median, and the lower and upper bound of 90% probability distribution of 21st century climate change. Five member ensembles were carried out for each choice of parameters using different initial conditions. With these simulations, we investigate the role of emissions scenarios (climate policies), the global climate response (climate sensitivity) and natural variability (initial conditions) on the uncertainty in future climate changes over Northern Eurasia. A particular emphasis is made on future changes in extreme events, including frost days, extreme summer temperature and extreme summer and winter precipitation.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Attribution of Extreme Rainfall from Landfalling Tropical Cyclones to Climate Change for the Eastern United States

NASA Astrophysics Data System (ADS)

Liu, M.; Yang, L.; Smith, J. A.; Vecchi, G. A.

2017-12-01

Extreme rainfall and flooding associated with landfalling tropical cyclones (TC) is responsible for vast socioeconomic losses and fatalities. Landfalling tropical cyclones are an important element of extreme rainfall and flood peak distributions in the eastern United States. Record floods for USGS stream gauging stations over the eastern US are closely tied to landfalling hurricanes. A small number of storms account for the largest record floods, most notably Hurricanes Diane (1955) and Agnes (1972). The question we address is: if the synoptic conditions accompanying those hurricanes were to be repeated in the future, how would the thermodynamic and dynamic storm properties and associated extreme rainfall differ in response to climate change? We examine three hurricanes: Diane (1955), Agnes (1972) and Irene (2011), due to the contrasts in structure/evolution properties and their important roles in dictating the upper tail properties of extreme rainfall and flood frequency over eastern US. Extreme rainfall from Diane is more localized as the storm maintains tropical characteristics, while synoptic-scale vertical motion associated with extratropical transition is a central feature for extreme rainfall induced by Agnes. Our analyses are based on ensemble simulations using the Weather Research and Forecasting (WRF) model, considering combinations of different physics options (i.e., microphysics, boundary layer schemes). The initial and boundary conditions of WRF simulations for the present-day climate are using the Twentieth Century Reanalysis (20thCR). A sub-selection of GCMs is used, as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5), to provide future climate projections. For future simulations, changes in model fields (i.e., temperature, humidity, geopotential height) between present-day and future climate are first derived and then added to the same 20thCR initial and boundary data used for the present-day simulations, and the ensemble is rerun using identical model configurations. Response of extreme rainfall as well as changes in thermodynamic and dynamic storm properties will be presented and analyzed. Contrasting responses across the three storm events to climate change will shed light on critical environmental factors for TC-related extreme rainfall over eastern US.

Losing your edge: climate change and the conservation value of range-edge populations.

PubMed

Rehm, Evan M; Olivas, Paulo; Stroud, James; Feeley, Kenneth J

2015-10-01

Populations occurring at species' range edges can be locally adapted to unique environmental conditions. From a species' perspective, range-edge environments generally have higher severity and frequency of extreme climatic events relative to the range core. Under future climates, extreme climatic events are predicted to become increasingly important in defining species' distributions. Therefore, range-edge genotypes that are better adapted to extreme climates relative to core populations may be essential to species' persistence during periods of rapid climate change. We use relatively simple conceptual models to highlight the importance of locally adapted range-edge populations (leading and trailing edges) for determining the ability of species to persist under future climates. Using trees as an example, we show how locally adapted populations at species' range edges may expand under future climate change and become more common relative to range-core populations. We also highlight how large-scale habitat destruction occurring in some geographic areas where many species range edge converge, such as biome boundaries and ecotones (e.g., the arc of deforestation along the rainforest-cerrado ecotone in the southern Amazonia), can have major implications for global biodiversity. As climate changes, range-edge populations will play key roles in helping species to maintain or expand their geographic distributions. The loss of these locally adapted range-edge populations through anthropogenic disturbance is therefore hypothesized to reduce the ability of species to persist in the face of rapid future climate change.

Extreme Temperature Exceedances Change more Rapidly Under Future Warming in Regions of non-Gaussian Short Temperature Distribution Tails

NASA Astrophysics Data System (ADS)

Loikith, P. C.; Neelin, J. D.; Meyerson, J.

2017-12-01

Regions of shorter-than-Gaussian warm and cold side temperature distribution tails are shown to occur in spatially coherent patterns in the current climate. Under such conditions, warming may be manifested in more complex ways than if the underlying distribution were close to Gaussian. For example, under a uniform warm shift, the simplest prototype for future warming, a location with a short warm side tail would experience a greater increase in extreme warm exceedances compared to if the distribution were Gaussian. Similarly, for a location with a short cold side tail, a uniform warm shift would result in a rapid decrease in extreme cold exceedances. Both scenarios carry major societal and environmental implications including but not limited to negative impacts on human and ecosystem health, agriculture, and the economy. It is therefore important for climate models to be able to realistically reproduce short tails in simulations of historical climate in order to boost confidence in projections of future temperature extremes. Overall, climate models contributing to the fifth phase of the Coupled Model Intercomparison Project capture many of the principal observed regions of short tails. This suggests the underlying dynamics and physics occur on scales resolved by the models, and helps build confidence in model projections of extremes. Furthermore, most GCMs show more rapid changes in exceedances of extreme temperature thresholds in regions of short tails. Results therefore suggest that the shape of the tails of the underlying temperature distribution is an indicator of how rapidly a location will experience changes to extreme temperature occurrence under future warming.

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

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.

Developing future precipitation events from historic events: An Amsterdam case study.

NASA Astrophysics Data System (ADS)

Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen

2016-04-01

Due to climate change, the frequency and intensity of extreme precipitation events is expected to increase. It is therefore of high importance to develop climate change scenarios tailored towards the local and regional needs of policy makers in order to develop efficient adaptation strategies to reduce the risks from extreme weather events. Current approaches to tailor climate scenarios are often not well adopted in hazard management, since average changes in climate are not a main concern to policy makers, and tailoring climate scenarios to simulate future extremes can be complex. Therefore, a new concept has been introduced recently that uses known historic extreme events as a basis, and modifies the observed data for these events so that the outcome shows how the same event would occur in a warmer climate. This concept is introduced as 'Future Weather', and appeals to the experience of stakeholders and users. This research presents a novel method of projecting a future extreme precipitation event, based on a historic event. The selected precipitation event took place over the broader area of Amsterdam, the Netherlands in the summer of 2014, which resulted in blocked highways, disruption of air transportation, flooded buildings and public facilities. An analysis of rain monitoring stations showed that an event of such intensity has a 5 to 15 years return period. The method of projecting a future event follows a non-linear delta transformation that is applied directly on the observed event assuming a warmer climate to produce an "up-scaled" future precipitation event. The delta transformation is based on the observed behaviour of the precipitation intensity as a function of the dew point temperature during summers. The outcome is then compared to a benchmark method using the HARMONIE numerical weather prediction model, where the boundary conditions of the event from the Ensemble Prediction System of ECMWF (ENS) are perturbed to indicate a warmer climate. The two methodologies are statistically compared and evaluated. The comparison between the historic event generated by the model and the observed event will give information on the realism of the model for this event. The comparison between the delta transformation method and the future simulation will provide information on how the dynamics would affect the precipitation field, as compared to the statistical method.

Characteristic changes in heat extremes over India in response to global warming using CMIP5 model simulations

NASA Astrophysics Data System (ADS)

Kundeti, K.; Chang, H. H.; T V, L. K.; Desamsetti, S.; Dandi, A. R.

2017-12-01

A critical aspect of human-induced climate change is how it will affect climatological mean and extremes around the world. Summer season surface climate of the Indian sub continent is characterized by hot and humid conditions. The global warming can have profound impact on the mean climate as well as extreme weather events over India that may affect both natural and human systems significantly. In this study we examine very direct measure of the impact of climate change on human health and comfort. The Heat stress Index is the measure of combined effects of temperature and atmospheric moisture on the ability of the human body to dissipate heat. It is important to assess the future changes in the seasonal mean of heat stress index, it is also desirable to know how the future holds when it comes to extremes in temperature for a country like India where so much of outdoor activities happen both in the onshore/offshore energy sectors, extensive construction activities. This study assesses the performance of the Coupled Model Inter comparison Project Phase 5 (CMIP5) simulations in the present and develops future climate scenarios. The changes in heat extremes are assessed for three future periods 2016-2035, 2046-2065 and 2080-2099 with respect to 1986-2005 (base line) under two RCP's (Representative Concentrate Pathways) - RCP4.5 and RCP8.5. In view of this, we provide the expected future changes in the seasonal mean heat stress indices and also the frequency of heat stress exceeding a certain threshold relevant to Inida. Besides, we provide spatial maps of expected future changes in the heat stress index derived as a function of daily mean temperature and relative humidity and representative of human comfort having a direct bearing on the human activities. The observations show an increase in heat extremes over many parts in this region that are generally well captured by the models. The results indicate a significant change in frequency and intensity of heat extremes over many parts of this region which may have serious implications on agriculture,human health, management of urban infrastructure and water resources.

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.

From climate-change spaghetti to climate-change distributions for 21st Century California

USGS Publications Warehouse

Dettinger, M.D.

2005-01-01

The uncertainties associated with climate-change projections for California are unlikely to disappear any time soon, and yet important long-term decisions will be needed to accommodate those potential changes. Projection uncertainties have typically been addressed by analysis of a few scenarios, chosen based on availability or to capture the extreme cases among available projections. However, by focusing on more common projections rather than the most extreme projections (using a new resampling method), new insights into current projections emerge: (1) uncertainties associated with future greenhouse-gas emissions are comparable with the differences among climate models, so that neither source of uncertainties should be neglected or underrepresented; (2) twenty-first century temperature projections spread more, overall, than do precipitation scenarios; (3) projections of extremely wet futures for California are true outliers among current projections; and (4) current projections that are warmest tend, overall, to yield a moderately drier California, while the cooler projections yield a somewhat wetter future. The resampling approach applied in this paper also provides a natural opportunity to objectively incorporate measures of model skill and the likelihoods of various emission scenarios into future assessments.

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.

Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

NASA Astrophysics Data System (ADS)

Oni, Stephen; Futter, Martyn; Ledesma, Jose; Teutschbein, Claudia; Buttle, Jim; Laudon, Hjalmar

2016-07-01

There are growing numbers of studies on climate change impacts on forest hydrology, but limited attempts have been made to use current hydroclimatic variabilities to constrain projections of future climatic conditions. Here we used historical wet and dry years as a proxy for expected future extreme conditions in a boreal catchment. We showed that runoff could be underestimated by at least 35 % when dry year parameterizations were used for wet year conditions. Uncertainty analysis showed that behavioural parameter sets from wet and dry years separated mainly on precipitation-related parameters and to a lesser extent on parameters related to landscape processes, while uncertainties inherent in climate models (as opposed to differences in calibration or performance metrics) appeared to drive the overall uncertainty in runoff projections under dry and wet hydroclimatic conditions. Hydrologic model calibration for climate impact studies could be based on years that closely approximate anticipated conditions to better constrain uncertainty in projecting extreme conditions in boreal and temperate regions.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

NASA Astrophysics Data System (ADS)

Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

2018-06-01

The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

The Peak Structure and Future Changes of the Relationships Between Extreme Precipitation and Temperature

NASA Technical Reports Server (NTRS)

Wang, Guiling; Wang, Dagang; Trenberth, Kevin E.; Erfanian, Amir; Yu, Miao; Bosilovich, Michael G.; Parr, Dana T.

2017-01-01

Theoretical models predict that, in the absence of moisture limitation, extreme precipitation intensity could exponentially increase with temperatures at a rate determined by the Clausius-Clapeyron (C-C) relationship. Climate models project a continuous increase of precipitation extremes for the twenty-first century over most of the globe. However, some station observations suggest a negative scaling of extreme precipitation with very high temperatures, raising doubts about future increase of precipitation extremes. Here we show for the present-day climate over most of the globe,the curve relating daily precipitation extremes with local temperatures has a peak structure, increasing as expected at the low medium range of temperature variations but decreasing at high temperatures. However, this peak-shaped relationship does not imply a potential upper limit for future precipitation extremes. Climate models project both the peak of extreme precipitation and the temperature at which it peaks (T(sub peak)) will increase with warming; the two increases generally conform to the C-C scaling rate in mid- and high-latitudes,and to a super C-C scaling in most of the tropics. Because projected increases of local mean temperature (T(sub mean)) far exceed projected increases of T(sub peak) over land, the conventional approach of relating extreme precipitation to T(sub mean) produces a misleading sub-C-C scaling rate.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

Tropical cyclones generate extreme waves that represent a risk to infrastructure and maritime activities. The projection of the tropical cyclones derived wave climate are challenged by the short historical record of tropical cyclones, their low occurrence, and the poor wind field resolution in General Circulation Models. In this study we use synthetic tropical cyclones to overcome such limitations and be able to characterize present and future wave climate associated with tropical cyclones in the Gulf of Mexico. Synthetic events derived from the NCEP/NCAR atmospheric reanalysis and the Coupled Model Intercomparison Project Phase 5 models NOAA/GFDL CM3 and UK Met Office HADGEM2-ES, were used to force a third generation wave model to characterize the present and future wave climate under RCP 4.5 and 8.5 escenarios. An increase in wave activity is projected for the future climate, particularly for the GFDL model that shows less bias in the present climate, although some areas are expected to decrease the wave energy. The practical implications of determining the future wave climate is exemplified by means of the 100-year design wave, where the use of the present climate may result in under/over design of structures, since the lifespan of a structure includes the future wave climate period.

Projections of West African summer monsoon rainfall extremes from two CORDEX models

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Zhou, Wen

2018-05-01

Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

Improving Predictions and Management of Hydrological Extremes through Climate Services

NASA Astrophysics Data System (ADS)

van den Hurk, Bart; Wijngaard, Janet; Pappenberger, Florian; Bouwer, Laurens; Weerts, Albrecht; Buontempo, Carlo; Doescher, Ralf; Manez, Maria; Ramos, Maria-Helena; Hananel, Cedric; Ercin, Ertug; Hunink, Johannes; Klein, Bastian; Pouget, Laurent; Ward, Philip

2016-04-01

The EU Roadmap on Climate Services can be seen as a result of convergence between the society's call for "actionable research", and the climate research community providing tailored data, information and knowledge. However, although weather and climate have clearly distinct definitions, a strong link between weather and climate services exists that is not explored extensively. Stakeholders being interviewed in the context of the Roadmap consider climate as a far distant long term feature that is difficult to consider in present-day decision taking, which is dominated by daily experience with handling extreme events. It is argued that this experience is a rich source of inspiration to increase society's resilience to an unknown future. A newly started European research project, IMPREX, is built on the notion that "experience in managing current day weather extremes is the best learning school to anticipate consequences of future climate". This paper illustrates possible ways to increase the link between information and services addressing weather and climate time scales by discussing the underlying concepts of IMPREX and its expected outcome.

TECA: Petascale pattern recognition for climate science

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

Prabhat, .; Byna, Surendra; Vishwanath, Venkatram

Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 5PB in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA (Toolkit for Extreme Climate Analysis) framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBMmore » BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.« less

Public perceptions of climate change and extreme weather events

NASA Astrophysics Data System (ADS)

Bruine de Bruin, W.; Dessai, S.; Morgan, G.; Taylor, A.; Wong-Parodi, G.

2013-12-01

Climate experts face a serious communication challenge. Public debate about climate change continues, even though at the same time people seem to complain about extreme weather events becoming increasingly common. As compared to the abstract concept of ';climate change,' (changes in) extreme weather events are indeed easier to perceive, more vivid, and personally relevant. Public perception research in different countries has suggested that people commonly expect that climate change will lead to increases in temperature, and that unseasonably warm weather is likely to be interpreted as evidence of climate change. However, relatively little is known about whether public concerns about climate change may also be driven by changes in other types of extreme weather events, such as exceptional amounts of precipitation or flooding. We therefore examined how perceptions of and personal experiences with changes in these specific weather events are related to public concerns about climate change. In this presentation, we will discuss findings from two large public perception surveys conducted in flood-prone Pittsburgh, Pennsylvania (US) and with a national sample in the UK, where extreme flooding has recently occurred across the country. Participants completed questions about their perceptions of and experiences with specific extreme weather events, and their beliefs about climate change. We then conducted linear regressions to predict individual differences in climate-change beliefs, using perceptions of and experiences with specific extreme weather events as predictors, while controlling for demographic characteristics. The US study found that people (a) perceive flood chances to be increasing over the decades, (b) believe climate change to play a role in increases in future flood chances, and (c) would interpret future increases in flooding as evidence for climate change. The UK study found that (a) UK residents are more likely to perceive increases in ';wet' events such as flooding and heavy rainfall than in ';hot' events such as heatwaves, (b) perceptions of these ';wet' weather events are more strongly associated with climate-change beliefs than were extremely ';hot' weather events, and (c) personal experiences with the negative consequences of specific extreme weather events are associated with stronger climate-change beliefs. Hence, which specific weather events people interpret as evidence of climate change may depend on their personal perceptions and experiences - which may not involve the temperature increases that are commonly the focus of climate-change communications. Overall, these findings suggest that climate experts should consider focusing their public communications on extreme weather events that are relevant to their intended audience. We will discuss strategies for designing and evaluating communications about climate change and adaptation.

IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation

NASA Astrophysics Data System (ADS)

Field, C. B.; Stocker, T. F.; Barros, V. R.; Qin, D.; Ebi, K. L.; Midgley, P. M.

2011-12-01

The Summary for Policy Makers of the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation will be approved by the world governments in November 2011. The focus of the Special Report is on climate change and its role in altering the frequency, severity, and impact of extreme events or disasters, and on the costs of both impacts and the actions taken to prepare for, respond to, and recover from extreme events and disasters. The emphasis is on understanding the factors that make people and infrastructure vulnerable to extreme events, on recent and future changes in the relationship between climate change and extremes, and on managing the risks of disasters over a wide range of spatial and temporal scales. The assessment considers a broad suite of adaptations and explores the limits to adaptation. The assessment was designed to build durable links and foundations for partnerships between the stakeholder communities focused on climate change and those focused on disaster risk reduction. The Special Report begins with material that frames the issues, followed by an assessment of the reasons that communities are vulnerable. Two chapters assess the role of past and future climate change in altering extremes and the impact of these on the physical environment and human systems. Three chapters assess available knowledge on impacts and adaptation, with separate chapters considering the literature, stakeholder relationships, and potential policy tools relevant to the local, national, and international scales. Longer-term components of adaptation to weather and climate extremes and disasters are assessed in the context of moving toward sustainability. The final chapter provides case studies that integrate themes across several chapters or are so unique that they need to be considered separately.

Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative

NASA Astrophysics Data System (ADS)

Frank, Dorothea; Reichstein, Markus

2017-04-01

The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.

Regional warming of hot extremes accelerated by surface energy fluxes consistent with drying soils

NASA Astrophysics Data System (ADS)

Donat, M.; Pitman, A.; Seneviratne, S. I.

2017-12-01

Strong regional differences exist in how hot temperature extremes increase under global warming. Using an ensemble of coupled climate models, we examine the regional warming rates of hot extremes relative to annual average warming rates in the same regions. We identify hotspots of accelerated warming of model-simulated hot extremes in Europe, North America, South America and Southeast China. These hotspots indicate where the warm tail of a distribution of temperatures increases faster than the average and are robust across most CMIP5 models. Exploring the conditions on the specific day the hot extreme occurs demonstrates the hotspots are explained by changes in the surface energy fluxes consistent with drying soils. Furthermore, in these hotspot regions we find a relationship between the temperature - heat flux correlation under current climate conditions and the magnitude of future projected changes in hot extremes, pointing to a potential emergent constraint for simulations of future hot extremes. However, the model-simulated accelerated warming of hot extremes appears inconsistent with observations of the past 60 years, except over Europe. The simulated acceleration of hot extremes may therefore be unreliable, a result that necessitates a re-evaluation of how climate models resolve the relevant terrestrial processes.

Climate variability and vulnerability to climate change: a review

PubMed Central

Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J

2014-01-01

The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802

Assessment of the uncertainty in future projection for summer climate extremes over the East Asia

NASA Astrophysics Data System (ADS)

Park, Changyong; Min, Seung-Ki; Cha, Dong-Hyun

2017-04-01

Future projections of climate extremes in regional and local scales are essential information needed for better adapting to climate changes. However, future projections hold larger uncertainty factors arising from internal and external processes which reduce the projection confidence. Using CMIP5 (Coupled Model Intercomparison Project Phase 5) multi-model simulations, we assess uncertainties in future projections of the East Asian temperature and precipitation extremes focusing on summer. In examining future projection, summer mean and extreme projections of the East Asian temperature and precipitation would be larger as time. Moreover, uncertainty cascades represent wider scenario difference and inter-model ranges with increasing time. A positive mean-extreme relation is found in projections for both temperature and precipitation. For the assessment of uncertainty factors for these projections, dominant uncertainty factors from temperature and precipitation change as time. For uncertainty of mean and extreme temperature, contributions of internal variability and model uncertainty declines after mid-21st century while role of scenario uncertainty grows rapidly. For uncertainty of mean precipitation projections, internal variability is more important than the scenario uncertainty. Unlike mean precipitation, extreme precipitation shows that the scenario uncertainty is expected to be a dominant factor in 2090s. The model uncertainty holds as an important factor for both mean and extreme precipitation until late 21st century. The spatial changes for the uncertainty factors of mean and extreme projections generally are expressed according to temporal changes of the fraction of total variance from uncertainty factors in many grids of the East Asia. ACKNOWLEDGEMENTS The research was supported by the Korea Meteorological Administration Research and Development program under grant KMIPA 2015-2083 and the National Research Foundation of Korea Grant funded by the Ministry of Science, ICT and Future Planning of Korea (NRF-2016M3C4A7952637) for its support and assistant in completion of the study.

Impacts of climate change on rainfall extremes and urban drainage systems: a review.

PubMed

Arnbjerg-Nielsen, K; Willems, P; Olsson, J; Beecham, S; Pathirana, A; Bülow Gregersen, I; Madsen, H; Nguyen, V-T-V

2013-01-01

A review is made of current methods for assessing future changes in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic-induced climate change. The review concludes that in spite of significant advances there are still many limitations in our understanding of how to describe precipitation patterns in a changing climate in order to design and operate urban drainage infrastructure. Climate change may well be the driver that ensures that changes in urban drainage paradigms are identified and suitable solutions implemented. Design and optimization of urban drainage infrastructure considering climate change impacts and co-optimizing these with other objectives will become ever more important to keep our cities habitable into the future.

Multi-index evaluation of future drought and climate extreme occurrence in Goodwater Creek Experimental Watershed

USDA-ARS?s Scientific Manuscript database

Understanding the frequency and occurrence of drought events in historic and projected future climate is essential for managing natural resources and setting policy. This study aims to identify future patterns of meteorological, hydrological and agricultural droughts based on projection from 12 GCM ...

Future changes in precipitation patterns and extremes: a model-based approach

NASA Astrophysics Data System (ADS)

Mitsakis, Evangelos; Stamos, Iraklis; Anastassiadou, Kalliopi; Kammerer, Harald; Kaundinya, Ingo; Kohl, Bernhard; Kapsomenakis, John; Zerefos, Christos; Aifadopoulou, Georfia

2016-04-01

In recent decades, the Earth has experienced abrupt climate changes, including changes of mean precipitation heights as well as precipitation extremes. It is very likely that the abrupt climate changes which are result of the increase of the greenhouse gases (GHG) concentration (IPCC 2007) will continue with an accelerate magnitude in the coming decades. The modern tool used to project the future climate change is General Circulation Models (GCMs). Due to computational resources limitations, the horizontal resolution of present day GCMs is quite low, usually in the order of hundreds of kilometers. In such a crude resolution many local aspects of the climate are unable to be represented. In addition, the topographical input is equally crude, thus excluding important local features of the topographic forcing. For these reasons downscaling methods have been developed, which input the GCM results producing high resolution localized climate information. Dynamical downscaling is achieved using Regional Climate Models (RCMs) that increase the resolution of the GCMs to even less than 10 km. In that direction, future changes in the mean precipitation as well as precipitation extremes due to the anthropogenic climate change over the area of Greece are examined for various emission scenarios in the framework of this paper (e.g. RCP 8.5, SRES A1B, etc.). Regarding Greece, future changes are based on daily precipitation data from 18 Region Climate Models simulations (6 for RCP 8.5 and 12 for SRES A1B). The changes in precipitation extremes are defined by calculating the changes of nine extreme precipitation indices which are divided in three categories: percentile (R75p, R95p, R99p), absolute threshold (Rmax, R10, R20, R50, RX5day) and duration (CDD) indices, as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). Taking into account all the results that are discussed explicitly in the following sections we conclude that the mean precipitation as well as the number of moderate rainy days is projected to decrease over Greece especially in the end of 21th century. Nevertheless the frequency as well as the strength of individual extremely high precipitation events will be increased over the largest part of Greece.

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

Future Simulated Intensification of Precipitation Extremes, CMIP5 Model Uncertainties and Dependencies

NASA Astrophysics Data System (ADS)

Bador, M.; Donat, M.; Geoffroy, O.; Alexander, L. V.

2017-12-01

Precipitation intensity during extreme events is expected to increase with climate change. Throughout the 21st century, CMIP5 climate models project a general increase in annual extreme precipitation in most regions. We investigate how robust this future increase is across different models, regions and seasons. We find that there is strong similarity in extreme precipitation changes between models that share atmospheric physics, reducing the ensemble of 27 models to 14 independent projections. We find that future simulated extreme precipitation increases in most models in the majority of land grid cells located in the dry, intermediate and wet regions according to each model's precipitation climatology. These increases significantly exceed the range of natural variability estimated from long equilibrium control runs. The intensification of extreme precipitation across the entire spectrum of dry to wet regions is particularly robust in the extra-tropics in both wet and dry season, whereas uncertainties are larger in the tropics. The CMIP5 ensemble therefore indicates robust future intensification of annual extreme rainfall in particular in extra-tropical regions. Generally, the CMIP5 robustness is higher during the dry season compared to the wet season and the annual scale, but inter-model uncertainties in the tropics remain important.

Can quantile mapping improve precipitation extremes from regional climate models?

NASA Astrophysics Data System (ADS)

Tani, Satyanarayana; Gobiet, Andreas

2015-04-01

The ability of quantile mapping to accurately bias correct regard to precipitation extremes is investigated in this study. We developed new methods by extending standard quantile mapping (QMα) to improve the quality of bias corrected extreme precipitation events as simulated by regional climate model (RCM) output. The new QM version (QMβ) was developed by combining parametric and nonparametric bias correction methods. The new nonparametric method is tested with and without a controlling shape parameter (Qmβ1 and Qmβ0, respectively). Bias corrections are applied on hindcast simulations for a small ensemble of RCMs at six different locations over Europe. We examined the quality of the extremes through split sample and cross validation approaches of these three bias correction methods. This split-sample approach mimics the application to future climate scenarios. A cross validation framework with particular focus on new extremes was developed. Error characteristics, q-q plots and Mean Absolute Error (MAEx) skill scores are used for evaluation. We demonstrate the unstable behaviour of correction function at higher quantiles with QMα, whereas the correction functions with for QMβ0 and QMβ1 are smoother, with QMβ1 providing the most reasonable correction values. The result from q-q plots demonstrates that, all bias correction methods are capable of producing new extremes but QMβ1 reproduces new extremes with low biases in all seasons compared to QMα, QMβ0. Our results clearly demonstrate the inherent limitations of empirical bias correction methods employed for extremes, particularly new extremes, and our findings reveals that the new bias correction method (Qmß1) produces more reliable climate scenarios for new extremes. These findings present a methodology that can better capture future extreme precipitation events, which is necessary to improve regional climate change impact studies.

Assessing the impact of extreme air temperature on fruit trees by modeling weather dependent phenology with variety-specific thermal requirements

NASA Astrophysics Data System (ADS)

Alfieri, Silvia Maria; De Lorenzi, Francesca; Missere, Daniele; Buscaroli, Claudio; Menenti, Massimo

2013-04-01

Extremely high and extremely low temperature may have a terminal impact on the productivity of fruit tree if occurring at critical phases of development. Notorious examples are frost during flowering or extremely high temperature during fruit setting. The dates of occurrence of such critical phenological stages depend on the weather history from the start of the yearly development cycle in late autumn, thus the impact of climate extremes can only be evaluated correctly if the phenological development is modeled taking into account the weather history of the specific year being evaluated. Climate change impact may lead to a shift in timing of phenological stages and change in the duration of vegetative and reproductive phases. A changing climate can also exhibit a greater climatic variability producing quite large changes in the frequency of extreme climatic events. We propose a two-stage approach to evaluate the impact of predicted future climate on the productivity of fruit trees. The phenological development is modeled using phase - specific thermal times and variety specific thermal requirements for several cultivars of pear, apricot and peach. These requirements were estimated using phenological observations over several years in Emilia Romagna region and scientific literature. We calculated the dates of start and end of rest completion, bud swell, flowering, fruit setting and ripening stages , from late autumn through late summer. Then phase-specific minimum and maximum cardinal temperature were evaluated for present and future climate to estimate how frequently they occur during any critically sensitive phenological phase. This analysis has been done for past climate (1961 - 1990) and fifty realizations of a year representative of future climate (2021 - 2050). A delay in rest completion of about 10-20 days has been predicted for future climate for most of the cultivars. On the other hand the predicted rise in air temperature causes an earlier development of crops thus a reduction in the length of the different phenological stages. Despite the earlier timing of phenological phases may expose the crops to frost hazard, the mean increase of air temperature avoids relevant impacts on crops. The frequency of air temperatures higher than the cardinal temperatures is expected to increase by 5% compared with the reference 1961 - 1990 climate. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Beyond Prediction: the Many Ways in which Climate Science can Inform Adaptation Decisions

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2017-12-01

Climate science provides an increasingly rich understanding of current and future climate, but this understanding is often not fully incorporated into climate adaptation decisions. In particular, the provision of climate information is still trapped in a narrow prediction-based framework, which envisions a sequential process that begins with model-based forecasts of future climate and decision makers then acting on those forecasts. Among its challenges, this framework can discourage action when climate predictions are deemed too uncertain, encourage overconfidence when climate scientists and decision makers fail to focus on decision-relevant but poorly understood extreme events, and offers a too-narrow communication path among climate scientists and decision makers. This talk will describe how robust decision approaches, organized around the idea of stress testing proposed adaptation decisions over a wide range of futures, can enable a richer flow information among climate scientists and decision makers. The talk illustrates these themes with two examples: 1) conservation management that explores the tradeoffs among alternative climate information products with different combinations of ensemble size and spatial resolution and 2) water quality implementation planning that focuses on the handling of extremes.

Future projections of total snowfall and heavy snowfall in Japan simulated by large ensemble regional climate simulations.

NASA Astrophysics Data System (ADS)

Kawase, H.; Sasaki, H.; Murata, A.; Nosaka, M.; Ito, R.; Dairaku, K.; Sasai, T.; Yamazaki, T.; Sugimoto, S.; Watanabe, S.; Fujita, M.; Kawazoe, S.; Okada, Y.; Ishii, M.; Mizuta, R.; Takayabu, I.

2017-12-01

We performed large ensemble climate experiments to investigate future changes in extreme weather events using Meteorological Research Institute-Atmospheric General Circulation Model (MRI-AGCM) with about 60 km grid spacing and Non-Hydrostatic Regional Climate Model with 20 km grid spacing (NHRCM20). The global climate simulations are prescribed by the past and future sea surface temperature (SST). Two future climate simulations are conducted so that the global-mean surface air temperature rise 2 K and 4 K from the pre-industrial period. The non-warming simulations are also conducted by MRI-AGCM and NHRCM20. We focus on the future changes in snowfall in Japan. In winter, the Sea of Japan coast experiences heavy snowfall due to East Asian winter monsoon. The cold and dry air from the continent obtains abundant moisture from the warm Sea of Japan, causing enormous amount of snowfall especially in the mountainous area. The NHRCM20 showed winter total snowfall decreases in the most parts of Japan. In contrast, extremely heavy daily snowfall could increase at mountainous areas in the Central Japan and Northern parts of Japan when strong cold air outbreak occurs and the convergence zone appears over the Sea of Japan. The warmer Sea of Japan in the future climate could supply more moisture than that in the present climate, indicating that the cumulus convections could be enhanced around the convergence zone in the Sea of Japan. However, the horizontal resolution of 20 km is not enough to resolve Japan`s complex topography. Therefore, dynamical downscaling with 5 km grid spacing (NHRCM05) is also conducted using NHRCM20. The NHRCM05 does a better job simulating the regional boundary of snowfall and shows more detailed changes in future snowfall characteristics. The future changes in total and extremely heavy snowfall depend on the regions, elevations, and synoptic conditions around Japan.

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.

Assessing changes in failure probability of dams in a changing climate

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Hydrological extremes and their agricultural impacts under a changing climate in Texas

NASA Astrophysics Data System (ADS)

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

2015-12-01

With the changing climate, hydrologic extremes (such as floods, droughts, and heat waves) are becoming more frequent and intensified. Such changes in extreme events are expected to affect agricultural production and food supplies. This study focuses on the State of Texas, which has the largest farm area and the highest value of livestock production in the U.S. The objectives are two-fold: First, to investigate the climatic impact on the occurrence of future hydrologic extreme events; and second, to evaluate the effects of the future extremes on agricultural production. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over Texas river basins during the historical period, is employed for this study. The VIC model is forced by the statistically downscaled climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles 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). To carry out the analysis, VIC outputs forced by the CMIP5 model scenarios over three 30-year periods (1970-1999, 2020-2049 and 2070-2099) are first evaluated to identify how the frequency and the extent of the extreme events will be altered in the ten Texas major river basins. The results suggest that a significant increase in the number of extreme events will occur starting in the first half of the 21st century in Texas. Then, the effects of the predicted hydrologic extreme events on the irrigation water demand are investigated. It is found that future changes in water demand vary by crop type and location, with an east-to-west gradient. The results are expected to contribute to future water management and planning in Texas.

Future changes in Asian summer monsoon precipitation extremes as inferred from 20-km AGCM simulations

NASA Astrophysics Data System (ADS)

Lui, Yuk Sing; Tam, Chi-Yung; Lau, Ngar-Cheung

2018-04-01

This study examines the impacts of climate change on precipitation extremes in the Asian monsoon region during boreal summer, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model. The model can capture the summertime monsoon rainfall, with characteristics similar to those from Tropical Rainfall Measuring Mission and Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation. By comparing the 2075-2099 with the present-day climate simulations, there is a robust increase of the mean rainfall in many locations due to a warmer climate. Over southeastern China, the Baiu rainband, Bay of Bengal and central India, extreme precipitation rates are also enhanced in the future, which can be inferred from increases of the 95th percentile of daily precipitation, the maximum accumulated precipitation in 5 consecutive days, the simple daily precipitation intensity index, and the scale parameter of the fitted gamma distribution. In these regions, with the exception of the Baiu rainband, most of these metrics give a fractional change of extreme rainfall per degree increase of the lower-tropospheric temperature of 5 to 8.5% K-1, roughly consistent with the Clausius-Clapeyron relation. However, over the Baiu area extreme precipitation change scales as 3.5% K-1 only. We have also stratified the rainfall data into those associated with tropical cyclones (TC) and those with other weather systems. The AGCM gives an increase of the accumulated TC rainfall over southeastern China, and a decrease in southern Japan in the future climate. The latter can be attributed to suppressed TC occurrence in southern Japan, whereas increased accumulated rainfall over southeastern China is due to more intense TC rain rate under global warming. Overall, non-TC weather systems are the main contributor to enhanced precipitation extremes in various locations. In the future, TC activities over southeastern China tend to further exacerbate the precipitation extremes, whereas those in the Baiu region lead to weaker changes of these extremes.

Nonstationarity RC Workshop Report: Nonstationary Weather Patterns and Extreme Events Informing Design and Planning for Long-Lived Infrastructure

DTIC Science & Technology

2017-11-01

magnitude, intensity, and seasonality of climate. For infrastructure projects, relevant design life often exceeds 30 years—a period of time of...uncertainty about future statistical properties of climate at time and spatial scales required for planning and design purposes. Information...about future statistical properties of climate at time and spatial scales required for planning and design , and for assessing future operational

Excessive heat and respiratory hospitalizations in New York State: estimating current and future public health burden related to climate change.

PubMed

Lin, Shao; Hsu, Wan-Hsiang; Van Zutphen, Alissa R; Saha, Shubhayu; Luber, George; Hwang, Syni-An

2012-11-01

Although many climate-sensitive environmental exposures are related to mortality and morbidity, there is a paucity of estimates of the public health burden attributable to climate change. We estimated the excess current and future public health impacts related to respiratory hospitalizations attributable to extreme heat in summer in New York State (NYS) overall, its geographic regions, and across different demographic strata. On the basis of threshold temperature and percent risk changes identified from our study in NYS, we estimated recent and future attributable risks related to extreme heat due to climate change using the global climate model with various climate scenarios. We estimated effects of extreme high apparent temperature in summer on respiratory admissions, days hospitalized, direct hospitalization costs, and lost productivity from days hospitalized after adjusting for inflation. The estimated respiratory disease burden attributable to extreme heat at baseline (1991-2004) in NYS was 100 hospital admissions, US$644,069 in direct hospitalization costs, and 616 days of hospitalization per year. Projections for 2080-2099 based on three different climate scenarios ranged from 206-607 excess hospital admissions, US$26-$76 million in hospitalization costs, and 1,299-3,744 days of hospitalization per year. Estimated impacts varied by geographic region and population demographics. We estimated that excess respiratory admissions in NYS due to excessive heat would be 2 to 6 times higher in 2080-2099 than in 1991-2004. When combined with other heat-associated diseases and mortality, the potential public health burden associated with global warming could be substantial.

Flood Risk in the Danube basin under climate change

NASA Astrophysics Data System (ADS)

Schröter, Kai; Wortmann, Michel; del Rocio Rivas Lopez, Maria; Liersch, Stefan; Viet Nguyen, Dung; Hardwick, Stephen; Hattermann, Fred

2017-04-01

The projected increase in temperature is expected to intensify the hydrological cycle, and thus more intense precipitation is likely to increase hydro-meteorological extremes and flood hazard. However to assess the future dynamics of hazard and impact induced by these changes it is necessary to consider extreme events and to take a spatially differentiated perspective. The Future Danube Model is a multi-hazard and risk model suite for the Danube region which has been developed in the OASIS project. The model comprises modules for estimating potential perils from heavy precipitation, heat-waves, floods, droughts, and damage risk considering hydro-climatic extremes under current and climate change conditions. Web-based open Geographic Information Systems (GIS) technology allows customers to graphically analyze and overlay perils and other spatial information such as population density or assets exposed. The Future Danube Model combines modules for weather generation, hydrological and hydrodynamic processes, and supports risk assessment and adaptation planning support. This contribution analyses changes in flood hazard in the Danube basin and in flood risk for the German part of the Danube basin. As climate change input, different regionalized climate ensemble runs of the newest IPCC generation are used, the so-called Representative Concentration Pathways (RCPs). They are delivered by the CORDEX initiative (Coordinated Downscaling Experiments). The CORDEX data sample is extended using the statistical weather generator (IMAGE) in order to also consider extreme events. Two time slices are considered: near future 2020-2049 and far future 2050-2079. This data provides the input for the hydrological, hydraulic and flood loss model chain. Results for RCP4.5 and RCP8.5 indicate an increase in intensity and frequency of peak discharges and thus in flood hazard for many parts of the Danube basin.

Perspectives on Extremes as a Climate Scientist and Farmer

NASA Astrophysics Data System (ADS)

Grotjahn, R.

2016-12-01

The speaker is both a climate scientist whose research emphasizes climate extremes and a small farmer in the most agriculturally productive region in the world. He will share some perspectives about the future of extremes over the United States as they relate to farming. General information will be drawn from the National Climate Assessment (NCA) published in 2014. Different weather-related quantities are useful for different commodities. While plant and animal production are time-integrative, extreme events can cause lasting harm long after the event is over. Animal production, including dairy, is sensitive to combinations of high heat and humidity; lasting impacts include suspended milk production, aborted fetuses, and increased mortality. The rice crop can be devastated by the wrong combination of wind and humidity just before harvest time. Extremes at the bud break, flowering, and nascent fruit stage and greatly reduce the fruit production for the year in tree crops. Saturated soils from heavy rainfall cause major losses to some crops (for example, by fostering pathogen growth), harm water delivery systems, and disrupt timing of field activities (primarily harvest).After an overview of some general issues relating to Agriculture, some extreme weather impacts on specific commodities (primarily dairy and specialty crops, some grains) will be highlighted including quantities relevant to agriculture. Example extreme events economic impacts will be summarized. If there is interest, issues related to water availability and management will be described. Projected extreme event changes over the US will be discussed. Some conclusions will be drawn about: future impacts and possible changes to farming (some are already occurring). Perspectives will be given on including the diverse range of quantities useful to agriculture when developing climate models. As time permits, some personal experiences with climate change and discussing it with fellow farmers will be shared.

Enhancing the Extreme Climate Index (ECI) to monitor climate extremes for an index-based insurance scheme across Africa

NASA Astrophysics Data System (ADS)

Helmschrot, J.; Malherbe, J.; Chamunorwa, M.; Muthige, M.; Petitta, M.; Calmanti, S.; Cucchi, M.; Syroka, J.; Iyahen, E.; Engelbrecht, F.

2017-12-01

Climate services are a key component of National Adaptation Plan (NAP) processes, which require the analysis of current climate conditions, future climate change scenarios and the identification of adaptation strategies, including the capacity to finance and implement effective adaptation options. The Extreme Climate Facility (XCF) proposed by the African Risk Capacity (ARC) developed a climate index insurance scheme, which is based on the Extreme Climate Index (ECI): an objective, multi-hazard index capable of tracking changes in the frequency or magnitude of extreme weather events, thus indicating possible shifts to a new climate regime in various regions. The main hazards covered by ECI are extreme dry, wet and heat events, with the possibility of adding other region-specific risk events. The ECI is standardized across broad geographical regions, so that extreme events occurring under different climatic regimes in Africa can be compared. Initially developed by an Italian company specialized in Climate Services, research is now conducted at the CSIR and SASSCAL, to verify and further develop the ECI for application in southern African countries, through a project initiated by the World Food Programme (WFP) and ARC. The paper will present findings on the most appropriate definitions of extremely wet and dry conditions in Africa, in terms of their impact across a multitude of sub-regional climates of the African continent. Findings of a verification analysis of the ECI, as determined through vegetation monitoring data and the SASSCAL weather station network will be discussed. Changes in the ECI under climate change will subsequently be projected, using detailed regional projections generated by the CSIR and through the Coordinated Regional Downscaling Experiment (CORDEX). This work will be concluded by the development of a web-based climate service informing African Stakeholders on climate extremes.

Adapting Infrastructure and Civil Engineering Practice to a Changing Climate: Developing a Manual of Practice

NASA Astrophysics Data System (ADS)

Walker, D.; Ayyub, B. M.

2017-12-01

According to U.S. Census, new construction spending in the U.S. for 2014 was $993 Billion (roughly 6 percent of U.S. GDP). Informing the development of standards of engineering practice related to design and maintenance thus represents a significant opportunity to promote climate adaptation and mitigation, as well as community resilience. The climate science community informs us that extremes of climate and weather are changing from historical values and that the changes are driven substantially by emissions of greenhouse gases caused by human activities. Civil infrastructure systems traditionally have been designed, constructed, operated and maintained for appropriate probabilities of functionality, durability and safety while exposed to climate and weather extremes during their full service lives. Because of uncertainties in future greenhouse gas emissions and in the models for future climate and weather extremes, neither the climate science community nor the engineering community presently can define the statistics of future climate and weather extremes. The American Society for Civil Engineering's (ASCE) Committee on Adapting to a Changing Climate is actively involved in efforts internal and external to ASCE to promote understanding of the challenges climate change represents in engineering practice and to promote a re-examination of those practices that may need to change in light of changing climate. In addition to producing an ASCE e-book, as well as number of ASCE webinars, the Committee is currently developing a Manual of Practice intended to provide guidance for the development or enhancement of standards for infrastructure analysis and design in a world in which risk profiles are changing (non-stationarity) and climate change is a reality, but cannot be projected with a high degree of certainty. This presentation will explore both the need for such guidance as well as some of the challenges and opportunities facing its implementation.

Precipitation extremes in the Iberian Peninsula: an overview of the CLIPE project

NASA Astrophysics Data System (ADS)

Santos, João A.; Gonçalves, Paulo M.; Rodrigues, Tiago; Carvalho, Maria J.; Rocha, Alfredo

2014-05-01

The main aims of the project "Climate change of precipitation extreme episodes in the Iberian Peninsula and its forcing mechanisms - CLIPE" are 1) to diagnose the climate change signal in the precipitation extremes over the Iberian Peninsula (IP) and 2) to identify the underlying physical mechanisms. For the first purpose, a multi-model ensemble of 25 Regional Climate Model (RCM) simulations, from the ENSEMBLES project, is used. These experiments were generated by 15 RCMs, driven by five General Circulation Models (GCMs) under both historic conditions (1951-2000) and SRES A1B scenario (2001-2100). In this project, daily precipitation and mean sea level pressure, for the periods 1961-1990 (recent past) and 2021-2100 (future), are used. Using the Standardised Precipitation Index (SPI) on a daily basis, a precipitation extreme is defined by the pair of threshold values (Dmin, Imin), where Dmin is the minimum number of consecutive days with daily SPI above the Imin value. For both past and future climates, a precipitation extreme of a specific type is then characterised by two variables: the number of episodes with a specific duration in days and the number of episodes with a specific mean intensity (SPI/duration). Climate change is also assessed by changes in their Probability Density Functions (PDFs), estimated at sectors representative of different precipitation regimes. Lastly, for the second objective of this project, links between precipitation and Circulation Weather Regimes (CWRs) are explored for both past and future climates. Acknowledgments: this work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project CLIPE (PTDC/AAC-CLI/111733/2009).

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

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

Future changes in summer mean and extreme precipitation frequency in Japan by d4PDF regional climate simulations

NASA Astrophysics Data System (ADS)

Okada, Y.; Ishii, M.; Endo, H.; Kawase, H.; Sasaki, H.; Takayabu, I.; Watanabe, S.; Fujita, M.; Sugimoto, S.; Kawazoe, S.

2017-12-01

Precipitation in summer plays a vital role in sustaining life across East Asia, but the heavy rain that is often generated during this period can also cause serious damage. Developing a better understanding of the features and occurrence frequency of this heavy rain is an important element of disaster prevention. We investigated future changes in summer mean and extreme precipitation frequency in Japan using large ensemble dataset which simulated by the Non-Hydrostatic Regional Climate Model with a horizontal resolution of 20km (NHRCM20). This dataset called database for Policy Decision making for Future climate changes (d4PDF), which is intended to be utilized for the impact assessment studies and adaptation planning to global warming. The future climate experiments assume the global mean surface air temperature rise 2K and 4K from the pre-industrial period. We investigated using this dataset future changes of precipitation in summer over the Japanese archipelago based on observational locations. For mean precipitation in the present-day climate, the bias of the rainfall for each month is within 25% even considering all members (30 members). The bias at each location is found to increase by over 50% on the Pacific Ocean side of eastern part of Japan and interior locations of western part of Japan. The result in western part of Japan depends on the effect of the elevations in this model. The future changes in mean precipitation show a contrast between northern and southern Japan, with the north showing a slight increase but the south a decrease. The future changes in the frequency of extreme precipitation in the national average of Japan increase at 2K and 4K simulations compared with the present-day climate, respectively. The authors were supported by the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

Past and future weather-induced risk in crop production

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Crosson, W. L.; Al-Hamdan, M. Z.; Estes, M. G., Jr.

2013-12-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981-2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a ';heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.

2013-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Climate change impacts on tropical cyclones and extreme sea levels in the South Pacific — A regional assessment

NASA Astrophysics Data System (ADS)

Walsh, Kevin J. E.; McInnes, Kathleen L.; McBride, John L.

2012-01-01

This paper reviews the current understanding of the effect of climate change on extreme sea levels in the South Pacific region. This region contains many locations that are vulnerable to extreme sea levels in the current climate, and projections indicate that this vulnerability will increase in the future. The recent publication of authoritative statements on the relationship between global warming and global sea level rise, tropical cyclones and the El Niño-Southern Oscillation phenomenon has motivated this review. Confident predictions of global mean sea level rise are modified by regional differences in the steric (density-related) component of sea level rise and changing gravitational interactions between the ocean and the ice sheets which affect the regional distribution of the eustatic (mass-related) contribution to sea level rise. The most extreme sea levels in this region are generated by tropical cyclones. The intensity of the strongest tropical cyclones is likely to increase, but many climate models project a substantial decrease in tropical cyclone numbers in this region, which may lead to an overall decrease in the total number of intense tropical cyclones. This projection, however, needs to be better quantified using improved high-resolution climate model simulations of tropical cyclones. Future changes in ENSO may lead to large regional variations in tropical cyclone incidence and sea level rise, but these impacts are also not well constrained. While storm surges from tropical cyclones give the largest sea level extremes in the parts of this region where they occur, other more frequent high sea level events can arise from swell generated by distant storms. Changes in wave climate are projected for the tropical Pacific due to anthropogenically-forced changes in atmospheric circulation. Future changes in sea level extremes will be caused by a combination of changes in mean sea level, regional sea level trends, tropical cyclone incidence and wave climate. Recommendations are given for research to increase understanding of the response of these factors to climate change. Implications of the results for adaptation research are also discussed.

The potential impacts of climate variability and change on health impacts of extreme weather events in the United States.

PubMed

Greenough, G; McGeehin, M; Bernard, S M; Trtanj, J; Riad, J; Engelberg, D

2001-05-01

Extreme weather events such as precipitation extremes and severe storms cause hundreds of deaths and injuries annually in the United States. Climate change may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation.

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.

Application of data on climate extremes for the southwestern United States

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Means and extremes: building variability into community-level climate change experiments.

PubMed

Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

2013-06-01

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.

Projected Changes to Streamflow Characteristics in Quebec Basins as Simulated by the Canadian Regional Climate Model (CRCM4)

NASA Astrophysics Data System (ADS)

Huziy, O.; Sushama, L.; Khaliq, M.; Lehner, B.; Laprise, R.; Roy, R.

2011-12-01

According to the Intergovernmental Panel on Climate Change (IPCC, 2007), an intensification of the global hydrological cycle and increase in precipitation for some regions around the world, including the northern mid- to high-latitudes, is expected in future climate. This will have an impact on mean and extreme flow characteristics, which need to be assessed for better development of adaptation strategies. Analysis of the mean and extreme streamflow characteristics for Quebec (North-eastern Canada) basins in current climate and their projected changes in future climate are assessed using a 10 member ensemble of current (1970 - 1999) and future (2041 - 2070) Canadian RCM (CRCM4) simulations. Validation of streamflow characteristics, performed by comparing modeled values with those observed, available from the Centre d'expertise hydrique du Quebec (CEHQ) shows that the model captures reasonably well the high flows. Results suggest increase in mean and 10 year return levels of 1 day high flows, which appear significant for most of the northern basins.

The critical role of uncertainty in projections of hydrological extremes

NASA Astrophysics Data System (ADS)

Meresa, Hadush K.; Romanowicz, Renata J.

2017-08-01

This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high- and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management.

Evaluating the ClimEx Single Model Large Ensemble in Comparison with EURO-CORDEX Results of Seasonal Means and Extreme Precipitation Indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Brisette, F.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several extreme indicators like R95pTOT, RX5day and others are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

WRF-Cordex simulations for Europe: mean and extreme precipitation for present and future climates

NASA Astrophysics Data System (ADS)

Cardoso, Rita M.; Soares, Pedro M. M.; Miranda, Pedro M. A.

2013-04-01

The Weather Research and Forecast (WRF-ARW) model, version 3.3.1, was used to perform the European domain Cordex simulations, at 50km resolution. A first simulation, forced by ERA-Interim (1989-2009), was carried out to evaluate the models performance to represent the mean and extreme precipitation in present European climate. This evaluation is based in the comparison of WRF results against the ECAD regular gridded dataset of daily precipitation. Results are comparable to recent studies with other models for the European region, at this resolution. For the same domain a control and a future scenario (RCP8.5) simulation was performed to assess the climate change impact on the mean and extreme precipitation. These regional simulations were forced by EC-EARTH model results, and, encompass the periods from 1960-2006 and 2006-2100, respectively.

Predicting the Impacts of Climate Change on Central American Agriculture

NASA Astrophysics Data System (ADS)

Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

2011-12-01

Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

Trends and Projections of Climatic Extremes in the Black Volta Basin, West Africa: Towards Climate Change Adaptation.

NASA Astrophysics Data System (ADS)

Aziz, F.

2015-12-01

The water resources of the Black Volta Basin in West Africa constitute a major resource for the four countries (Burkina Faso, Ghana, Côte d'Ivoire, Mali) that share it. For Burkina Faso and Ghana, the river is the main natural resource around which the development of the diverse sectors of the two economies is built. Whereas Ghana relies heavily on the river for energy, land-locked Burkina Faso continuously develops the water for agricultural purposes. Such important role of the river makes it an element around which there are potential conflicts: either among riparian countries or within the individual countries themselves. This study documents the changes in temperature and precipitation extremes in the Black Volta Basin region for the past (1981-2010) and makes projections for the mid-late 21st century (2051-2080) under two emission scenarios; RCP 2.6 and RCP 8.5. The Expert Team on Climate Change Detection and Indices (ETCCDI) temperature- and precipitation-based indices are computed with the RClimdex software. Observed daily records and downscaled CORDEX data of precipitation and maximum and minimum temperatures are used for historical and future trend analysis respectively. In general low emission scenarios show increases in the cold extremes. The region shows a consistent pattern of trends in hot extremes for the 1990's. An increasing trend in hot extremes is expected in the future under RCP 8.5 while RCP 2.5 shows reductions in hot extremes. Regardless of the emission scenario, projections show more frequent hot nights in the 21st century. Generally, the region shows variability in trends for future extreme precipitation indices with only a few of the trends being statistically significant (5% level). Results obtained provide a basic and first step to understanding how climatic extremes have been changing in the Volta Basin region and gives an idea of what to expect in the future. Such studies will also help in making informed decisions on water management in the basin. The various water users; agriculture, household, industries will be able to prepare adequately and adapt to changes when they have information of the trends of extreme events well ahead of time.

Excessive Heat and Respiratory Hospitalizations in New York State: Estimating Current and Future Public Health Burden Related to Climate Change

PubMed Central

Hsu, Wan-Hsiang; Van Zutphen, Alissa R.; Saha, Shubhayu; Luber, George; Hwang, Syni-An

2012-01-01

Background: Although many climate-sensitive environmental exposures are related to mortality and morbidity, there is a paucity of estimates of the public health burden attributable to climate change. Objective: We estimated the excess current and future public health impacts related to respiratory hospitalizations attributable to extreme heat in summer in New York State (NYS) overall, its geographic regions, and across different demographic strata. Methods: On the basis of threshold temperature and percent risk changes identified from our study in NYS, we estimated recent and future attributable risks related to extreme heat due to climate change using the global climate model with various climate scenarios. We estimated effects of extreme high apparent temperature in summer on respiratory admissions, days hospitalized, direct hospitalization costs, and lost productivity from days hospitalized after adjusting for inflation. Results: The estimated respiratory disease burden attributable to extreme heat at baseline (1991–2004) in NYS was 100 hospital admissions, US$644,069 in direct hospitalization costs, and 616 days of hospitalization per year. Projections for 2080–2099 based on three different climate scenarios ranged from 206–607 excess hospital admissions, US$26–$76 million in hospitalization costs, and 1,299–3,744 days of hospitalization per year. Estimated impacts varied by geographic region and population demographics. Conclusions: We estimated that excess respiratory admissions in NYS due to excessive heat would be 2 to 6 times higher in 2080–2099 than in 1991–2004. When combined with other heat-associated diseases and mortality, the potential public health burden associated with global warming could be substantial. PMID:22922791

Influence of Climate Oscillations on Extreme Precipitation in Texas

NASA Astrophysics Data System (ADS)

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

2016-12-01

Much research in the field of hydroclimatology is focusing on the impact of climate variability on hydrologic extremes. Recent studies show that the unique geographical location and the enormous areal extent, coupled with extensive variations in climate oscillations, have intensified the regional hydrologic cycle of Texas. The state-wide extreme precipitation events can actually be attributed to sea-surface pressure and temperature anomalies, such as Bermuda High and Jet Streams, which are further triggered by such climate oscillations. This study aims to quantify the impact of five major Atlantic and Pacific Ocean related climate oscillations: (i) Atlantic Multidecadal Oscillation (AMO), (ii) North Atlantic Oscillation (NAO), (iii) Pacific Decadal Oscillation (PDO), (iv) Pacific North American Pattern (PNA), and (v) Southern Oscillation Index (SOI), on extreme precipitation in Texas. Their respective effects will be determined for both climate divisions delineated by the National Climatic Data Centre (NCDC) and climate regions defined by the Köppen Climate Classification System. This study will adopt a weighted correlation approach to attain the robust correlation coefficients while addressing the regionally variable data outliers for extreme precipitation. Further, the variation of robust correlation coefficients across Texas is found to be related to the station elevation, historical average temperature, and total precipitation in the months of extremes. The research will shed light on the relationship between precipitation extremes and climate variability, thus aiding regional water boards in planning, designing, and managing the respective systems as per the future climate change.

Climate volatility deepens poverty vulnerability in developing countries

NASA Astrophysics Data System (ADS)

Ahmed, Syud A.; Diffenbaugh, Noah S.; Hertel, Thomas W.

2009-07-01

Extreme climate events could influence poverty by affecting agricultural productivity and raising prices of staple foods that are important to poor households in developing countries. With the frequency and intensity of extreme climate events predicted to change in the future, informed policy design and analysis requires an understanding of which countries and groups are going to be most vulnerable to increasing poverty. Using a novel economic-climate analysis framework, we assess the poverty impacts of climate volatility for seven socio-economic groups in 16 developing countries. We find that extremes under present climate volatility increase poverty across our developing country sample—particularly in Bangladesh, Mexico, Indonesia, and Africa—with urban wage earners the most vulnerable group. We also find that global warming exacerbates poverty vulnerability in many nations.

Simulated trends of extreme climate indices for the Carpathian basin using outputs of different regional climate models

NASA Astrophysics Data System (ADS)

Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.

2009-04-01

Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model RegCM3 (run at 10 km horizontal resolution) was developed by Giorgi et al. and it is available from the ICTP (International Centre for Theoretical Physics). Analysis of the simulated daily temperature datasets suggests that the detected regional warming is expected to continue in the 21st century. Cold temperature extremes are projected to decrease while warm extremes tend to increase significantly. Expected changes of annual precipitation indices are small, but generally consistent with the detected trends of the 20th century. Based on the simulations, extreme precipitation events are expected to become more intense and more frequent in winter, while a general decrease of extreme precipitation indices is expected in summer.

Future summer mega-heatwave and record-breaking temperatures in a warmer France climate

NASA Astrophysics Data System (ADS)

Bador, Margot; Terray, Laurent; Boé, Julien; Somot, Samuel; Alias, Antoinette; Gibelin, Anne-Laure; Dubuisson, Brigitte

2017-07-01

This study focuses on future very hot summers associated with severe heatwaves and record-breaking temperatures in France. Daily temperature observations and a pair of historical and scenario (greenhouse gas radiative concentration pathway 8.5) simulations with the high-resolution (∼12.5 km) ALADIN regional climate model provide a robust framework to examine the spatial distribution of these extreme events and their 21st century evolution. Five regions are identified with an extreme event spatial clustering algorithm applied to observed temperatures. They are used to diagnose the 21st century heatwave spatial patterns. In the 2070s, we find a simulated mega-heatwave as severe as the 2003 observed heatwave relative to its contemporaneous climate. A 20-member initial condition ensemble is used to assess the sensitivity of this future heatwave to the internal variability in the regional climate model and to pre-existing land surface conditions. Even in a much warmer and drier climate in France, late spring dry land conditions may lead to a significant amplification of summer extreme temperatures and heatwave intensity through limitations in evapotranspiration. By 2100, the increase in summer temperature maxima exhibits a range from 6 °C to almost 13 °C in the five regions in France, relative to historical maxima. These projections are comparable with the estimates given by a large number of global climate models.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Extreme Weather and Climate: Workshop Report

NASA Technical Reports Server (NTRS)

Sobel, Adam; Camargo, Suzana; Debucquoy, Wim; Deodatis, George; Gerrard, Michael; Hall, Timothy; Hallman, Robert; Keenan, Jesse; Lall, Upmanu; Levy, Marc;

Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

NASA Astrophysics Data System (ADS)

Colmet-Daage, Antoine; Sanchez-Gomez, Emilia; Ricci, Sophie; Llovel, Cécile; Borrell Estupina, Valérie; Quintana-Seguí, Pere; Llasat, Maria Carmen; Servat, Eric

2018-01-01

The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981-2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

Asymmetrical Responses of Ecosystem Processes to Positive Versus Negative Precipitation Extremes: a Replicated Regression Experimental Approach

NASA Astrophysics Data System (ADS)

Felton, A. J.; Smith, M. D.

2016-12-01

Heightened climatic variability due to atmospheric warming is forecast to increase the frequency and severity of climate extremes. In particular, changes to interannual variability in precipitation, characterized by increases in extreme wet and dry years, are likely to impact virtually all terrestrial ecosystem processes. However, to date experimental approaches have yet to explicitly test how ecosystem processes respond to multiple levels of climatic extremity, limiting our understanding of how ecosystems will respond to forecast increases in the magnitude of climate extremes. Here we report the results of a replicated regression experimental approach, in which we imposed 9 and 11 levels of growing season precipitation amount and extremity in mesic grassland during 2015 and 2016, respectively. Each level corresponded to a specific percentile of the long-term record, which produced a large gradient of soil moisture conditions that ranged from extreme wet to extreme dry. In both 2015 and 2016, asymptotic responses to water availability were observed for soil respiration. This asymmetry was driven in part by transitions between soil moisture versus temperature constraints on respiration as conditions became increasingly dry versus increasingly wet. In 2015, aboveground net primary production (ANPP) exhibited asymmetric responses to precipitation that largely mirrored those of soil respiration. In total, our results suggest that in this mesic ecosystem, these two carbon cycle processes were more sensitive to extreme drought than to extreme wet years. Future work will assess ANPP responses for 2016, soil nutrient supply and physiological responses of the dominant plant species. Future efforts are needed to compare our findings across a diverse array of ecosystem types, and in particular how the timing and magnitude of precipitation events may modify the response of ecosystem processes to increasing magnitudes of precipitation extremes.

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Abrupt shifts in phenology and vegetation productivity under climate extremes

USDA-ARS?s Scientific Manuscript database

Amplification of the hydrologic cycle as a consequence of global warming is predicted to increase climate variability and the frequency and severity of droughts. Predicting how ecosystems will be affected by climate change requires not only reliable forecasts of future climate, but also observationa...

Evaluation and projected changes of precipitation statistics in convection-permitting WRF climate simulations over Central Europe

NASA Astrophysics Data System (ADS)

Knist, Sebastian; Goergen, Klaus; Simmer, Clemens

2018-02-01

We perform simulations with the WRF regional climate model at 12 and 3 km grid resolution for the current and future climates over Central Europe and evaluate their added value with a focus on the daily cycle and frequency distribution of rainfall and the relation between extreme precipitation and air temperature. First, a 9 year period of ERA-Interim driven simulations is evaluated against observations; then global climate model runs (MPI-ESM-LR RCP4.5 scenario) are downscaled and analyzed for three 12-year periods: a control, a mid-of-century and an end-of-century projection. The higher resolution simulations reproduce both the diurnal cycle and the hourly intensity distribution of precipitation more realistically compared to the 12 km simulation. Moreover, the observed increase of the temperature-extreme precipitation scaling from the Clausius-Clapeyron (C-C) scaling rate of 7% K-1 to a super-adiabatic scaling rate for temperatures above 11 °C is reproduced only by the 3 km simulation. The drop of the scaling rates at high temperatures under moisture limited conditions differs between sub-regions. For both future scenario time spans both simulations suggest a slight decrease in mean summer precipitation and an increase in hourly heavy and extreme precipitation. This increase is stronger in the 3 km runs. Temperature-extreme precipitation scaling curves in the future climate are projected to shift along the 7% K-1 trajectory to higher peak extreme precipitation values at higher temperatures. The curves keep their typical shape of C-C scaling followed by super-adiabatic scaling and a drop-off at higher temperatures due to moisture limitation.

Projected changes in the future distribution and production of sessile oak forests near the xeric limit

NASA Astrophysics Data System (ADS)

Gulyás, Krisztina; Berki, Imre; Veperdi, Gábor

2017-04-01

As a result of regional climate change, most European countries are experiencing an increase in mean annual temperature and CO2 concentration and a decrease in mean annual precipitation. In low-elevation areas in Southeast Europe, where precipitation is a limiting factor, the projected climate change threatens the health, production, and potential distribution of forest ecosystems. The intensive summer droughts and commonly occurring extreme weather events create negative influences that cause health declines, changes in yield potential, and tree mortality. Due to the observed damages, attention has been focused on these problems. The impacts of climatic extremes cause difficulties in forest management; these difficulties occur more frequently in Hungary, which is a region that is the most sensitive to climatic extremes. Regional climate model simulations project that the frequency of extremely high temperatures and long-term dry periods will increase; both of these factors have negative effects on future tree species distribution and production. Thus, the aim of our study is to utilize the sessile oak (Quercus petraea) as a climate indicator tree species to investigate potential future distribution and estimate changes in growth trends. For future spatial distribution, we used the Fuzzy membership distribution model in a new Decision Support System (DSS) which was developed for the Hungarian forestry and agricultural sectors. Through study techniques we can employ DSS, which contains various environmental layers (topography, vegetation, past and projected future climate, soils, and hydrology), to create probability distribution maps. The results, based on 12 regional climate model simulations (www.ensembles-eu.org), show that the area of sessile oak forests is shrinking continuously and will continue to do so to the end of the 21st century. For future production estimations, we analysed intensive long-term growth monitoring network plots that were established in 1993. We calculated production capacity on the basis of age and height; we then compared these to past climate conditions to discover connections between climate, site conditions, and production. We estimated future growth tendencies for three different time periods (2011-2040; 2041-2070; 2071-2100). Results show that the most vulnerable region is the south-western part of Hungary where the projected production capacity may decrease by 26% for the time period 2071-2100. The impacts of climate change may be milder in the north-eastern part of Hungary where a 19% decrease in the production capacity of sessile oak forests is estimated. These investigations and results are important for sustainable forest management and help define climate change adaptation strategies in forestry. Keywords: climate change impacts, distribution modelling, production capacity Acknowledgements: Research is supported by the ÚNKP-16-3-3 New National Excellence Program of the Ministry of Human Capacities and the "Agroclimate.2" (VKSZ_12-1-2013-0034) EU-national joint funded research project.

Extreme climatic events change the dynamics and invasibility of semi-arid annual plant communities.

PubMed

Jiménez, Milagros A; Jaksic, Fabian M; Armesto, Juan J; Gaxiola, Aurora; Meserve, Peter L; Kelt, Douglas A; Gutiérrez, Julio R

2011-12-01

Extreme climatic events represent disturbances that change the availability of resources. We studied their effects on annual plant assemblages in a semi-arid ecosystem in north-central Chile. We analysed 130 years of precipitation data using generalised extreme-value distribution to determine extreme events, and multivariate techniques to analyse 20 years of plant cover data of 34 native and 11 exotic species. Extreme drought resets the dynamics of the system and renders it susceptible to invasion. On the other hand, by favouring native annuals, moderately wet events change species composition and allow the community to be resilient to extreme drought. The probability of extreme drought has doubled over the last 50 years. Therefore, investigations on the interaction of climate change and biological invasions are relevant to determine the potential for future effects on the dynamics of semi-arid annual plant communities. 2011 Blackwell Publishing Ltd/CNRS.

A European Flagship Programme on Extreme Computing and Climate

NASA Astrophysics Data System (ADS)

Palmer, Tim

2017-04-01

In 2016, an outline proposal co-authored by a number of leading climate modelling scientists from around Europe for a (c. 1 billion euro) flagship project on exascale computing and high-resolution global climate modelling was sent to the EU via its Future and Emerging Flagship Technologies Programme. The project is formally entitled "A Flagship European Programme on Extreme Computing and Climate (EPECC)"? In this talk I will outline the reasons why I believe such a project is needed and describe the current status of the project. I will leave time for some discussion.

A vulnerability tool for adapting water and aquatic resources to climate change and extremes on the Shoshone National Forest, Wyoming

NASA Astrophysics Data System (ADS)

Rice, J.; Joyce, L. A.; Armel, B.; Bevenger, G.; Zubic, R.

2011-12-01

Climate change introduces a significant challenge for land managers and decision makers managing the natural resources that provide many benefits from forests. These benefits include water for urban and agricultural uses, wildlife habitat, erosion and climate control, aquifer recharge, stream flows regulation, water temperature regulation, and cultural services such as outdoor recreation and aesthetic enjoyment. The Forest Service has responded to this challenge by developing a national strategy for responding to climate change (the National Roadmap for Responding to Climate Change, July 2010). In concert with this national strategy, the Forest Service's Westwide Climate Initiative has conducted 4 case studies on individual Forests in the western U.S to develop climate adaptation tools. Western National Forests are particularly vulnerable to climate change as they have high-mountain topography, diversity in climate and vegetation, large areas of water limited ecosystems, and increasing urbanization. Information about the vulnerability and capacity of resources to adapt to climate change and extremes is lacking. There is an urgent need to provide customized tools and synthesized local scale information about the impacts to resources from future climate change and extremes, as well as develop science based adaptation options and strategies in National Forest management and planning. The case study on the Shoshone National Forest has aligned its objectives with management needs by developing a climate extreme vulnerability tool that guides adaptation options development. The vulnerability tool determines the likely degree to which native Yellowstone cutthroat trout and water availability are susceptible to, or unable to cope with adverse effects of climate change extremes. We spatially categorize vulnerability for water and native trout resources using exposure, sensitivity, and adaptive capacity indicators that use minimum and maximum climate and GIS data. Results show that the vulnerability of water availability may increase in areas that have less storage and become more dominated by rain instead of snow. Native trout habitat was found to improve in some areas from warmer temperatures suggesting future refugia habitat may need to be a focus of conservation efforts. The climate extreme vulnerability tool provides Forest Service resource managers science based information that guides adaptation strategy development; prioritize conservation projects; guides monitoring efforts, and helps promote more resilient ecosystems undergoing the effects of climate change.

The potential impacts of climate variability and change on health impacts of extreme weather events in the United States.

PubMed Central

Greenough, G; McGeehin, M; Bernard, S M; Trtanj, J; Riad, J; Engelberg, D

2001-01-01

Extreme weather events such as precipitation extremes and severe storms cause hundreds of deaths and injuries annually in the United States. Climate change may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation. PMID:11359686

Adaptation potential of naturally ventilated barns to high temperature extremes: The OptiBarn project

NASA Astrophysics Data System (ADS)

Menz, Christoph

2016-04-01

Climate change interferes with various aspects of the socio-economic system. One important aspect is its influence on animal husbandry, especially dairy faming. Dairy cows are usually kept in naturally ventilated barns (NVBs) which are particular vulnerable to extreme events due to their low adaptation capabilities. An effective adaptation to high outdoor temperatures for example, is only possible under certain wind and humidity conditions. High temperature extremes are expected to increase in number and strength under climate change. To assess the impact of this change on NVBs and dairy cows also the changes in wind and humidity needs to be considered. Hence we need to consider the multivariate structure of future temperature extremes. The OptiBarn project aims to develop sustainable adaptation strategies for dairy housings under climate change for Europe, by considering the multivariate structure of high temperature extremes. In a first step we identify various multivariate high temperature extremes for three core regions in Europe. With respect to dairy cows in NVBs we will focus on the wind and humidity field during high temperature events. In a second step we will use the CORDEX-EUR-11 ensemble to evaluate the capability of the RCMs to model such events and assess their future change potential. By transferring the outdoor conditions to indoor climate and animal wellbeing the results of this assessment can be used to develop technical, architectural and animal specific adaptation strategies for high temperature extremes.

Using Four Downscaling Techniques to Characterize Uncertainty in Updating Intensity-Duration-Frequency Curves Under Climate Change

NASA Astrophysics Data System (ADS)

Cook, L. M.; Samaras, C.; McGinnis, S. A.

2017-12-01

Intensity-duration-frequency (IDF) curves are a common input to urban drainage design, and are used to represent extreme rainfall in a region. As rainfall patterns shift into a non-stationary regime as a result of climate change, these curves will need to be updated with future projections of extreme precipitation. Many regions have begun to update these curves to reflect the trends from downscaled climate models; however, few studies have compared the methods for doing so, as well as the uncertainty that results from the selection of the native grid scale and temporal resolution of the climate model. This study examines the variability in updated IDF curves for Pittsburgh using four different methods for adjusting gridded regional climate model (RCM) outputs into station scale precipitation extremes: (1) a simple change factor applied to observed return levels, (2) a naïve adjustment of stationary and non-stationary Generalized Extreme Value (GEV) distribution parameters, (3) a transfer function of the GEV parameters from the annual maximum series, and (4) kernel density distribution mapping bias correction of the RCM time series. Return level estimates (rainfall intensities) and confidence intervals from these methods for the 1-hour to 48-hour duration are tested for sensitivity to the underlying spatial and temporal resolution of the climate ensemble from the NA-CORDEX project, as well as, the future time period for updating. The first goal is to determine if uncertainty is highest for: (i) the downscaling method, (ii) the climate model resolution, (iii) the climate model simulation, (iv) the GEV parameters, or (v) the future time period examined. Initial results of the 6-hour, 10-year return level adjusted with the simple change factor method using four climate model simulations of two different spatial resolutions show that uncertainty is highest in the estimation of the GEV parameters. The second goal is to determine if complex downscaling methods and high-resolution climate models are necessary for updating, or if simpler methods and lower resolution climate models will suffice. The final results can be used to inform the most appropriate method and climate model resolutions to use for updating IDF curves for urban drainage design.

Climate Change Impacts on Sediment Transport In a Lowland Watershed System: Controlling Processes and Projection

NASA Astrophysics Data System (ADS)

al Aamery, N. M. H.; Mahoney, D. T.; Fox, J.

2017-12-01

Future climate change projections suggest extreme impacts on watershed hydrologic systems for some regions of the world including pronounced increases in surface runoff and instream flows. Yet, there remains a lack of research focused on how future changes in hydrologic extremes, as well as relative hydrologic mean changes, impact sediment redistribution within a watershed and sediment flux from a watershed. The authors hypothesized that variations in mean and extreme changes in turn may impact sediments in depositional and erosional dominance in a manner that may not be obvious to the watershed manager. Therefore, the objectives of this study were to investigate the inner processes connecting the combined effect of extreme climate change projections on the vegetation, upland erosion, and instream processes to produce changes in sediment redistribution within watersheds. To do so, research methods were carried out by the authors including simulating sediment processes in forecast and hindcast periods for a lowland watershed system. Publically available climate realizations from several climate factors and the Soil Water Assessment Tool (SWAT) were used to predict hydrologic conditions for the South Elkhorn Watershed in central Kentucky, USA to 2050. The results of the simulated extreme and mean hydrological components were used in simulating upland erosion with the connectivity processes consideration and thereafter used in building and simulating the instream erosion and deposition of sediment processes with the consideration of surface fine grain lamina (SFGL) layer controlling the benthic ecosystem. Results are used to suggest the dominance of erosional and depositional redistribution of sediments under different scenarios associated with extreme and mean hydrologic forecasting. The results are discussed in reference to the benthic ecology of the stream system providing insight on how water managers might consider sediment redistribution in a changing climate.

Reduced CO2 fertilization effect in temperate C3 grasslands under more extreme weather conditions

NASA Astrophysics Data System (ADS)

Obermeier, W. A.; Lehnert, L. W.; Kammann, C. I.; Müller, C.; Grünhage, L.; Luterbacher, J.; Erbs, M.; Moser, G.; Seibert, R.; Yuan, N.; Bendix, J.

2017-02-01

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of recent global climate change. The stimulation of plant photosynthesis due to rising atmospheric carbon dioxide concentrations ([CO2]) is widely assumed to increase the net primary productivity (NPP) of C3 plants--the CO2 fertilization effect (CFE). However, the magnitude and persistence of the CFE under future climates, including more frequent weather extremes, are controversial. Here we use data from 16 years of temperate grassland grown under `free-air carbon dioxide enrichment’ conditions to show that the CFE on above-ground biomass is strongest under local average environmental conditions. The observed CFE was reduced or disappeared under wetter, drier and/or hotter conditions when the forcing variable exceeded its intermediate regime. This is in contrast to predictions of an increased CO2 fertilization effect under drier and warmer conditions. Such extreme weather conditions are projected to occur more intensely and frequently under future climate scenarios. Consequently, current biogeochemical models might overestimate the future NPP sink capacity of temperate C3 grasslands and hence underestimate future atmospheric [CO2] increase.

Future Extreme Event Vulnerability in the Rural Northeastern United States

NASA Astrophysics Data System (ADS)

Winter, J.; Bowen, F. L.; Partridge, T.; Chipman, J. W.

2017-12-01

Future climate change impacts on humans will be determined by the convergence of evolving physical climate and socioeconomic systems. Of particular concern is the intersection of extreme events and vulnerable populations. Rural areas of the Northeastern United States have experienced increased temperature and precipitation extremes, especially over the past three decades, and face unique challenges due to their physical isolation, natural resources dependent economies, and high poverty rates. To explore the impacts of future extreme events on vulnerable, rural populations in the Northeast, we project extreme events and vulnerability indicators to identify where changes in extreme events and vulnerable populations coincide. Specifically, we analyze future (2046-2075) maximum annual daily temperature, minimum annual daily temperature, maximum annual daily precipitation, and maximum consecutive dry day length for Representative Concentration Pathways (RCP) 4.5 and 8.5 using four global climate models (GCM) and a gridded observational dataset. We then overlay those projections with estimates of county-level population and relative income for 2060 to calculate changes in person-events from historical (1976-2005), with a focus on Northeast counties that have less than 250,000 people and are in the bottom income quartile. We find that across the rural Northeast for RCP4.5, heat person-events per year increase tenfold, far exceeding decreases in cold person-events and relatively small changes in precipitation and drought person-events. Counties in the bottom income quartile have historically (1976-2005) experienced a disproportionate number of heat events, and counties in the bottom two income quartiles are projected to experience a greater heat event increase by 2046-2075 than counties in the top two income quartiles. We further explore the relative contributions of event frequency, population, and income changes to the total and geographic distribution of climate change impacts on rural, vulnerable areas of the Northeast.

Seasonally varying footprint of climate change on precipitation in the Middle East.

PubMed

Tabari, Hossein; Willems, Patrick

2018-03-13

Climate change is expected to alter precipitation patterns; however, the amplitude of the change may broadly differ across seasons. Combining different seasons may mask contrasting climate change signals in individual seasons, leading to weakened signals and misleading impact results. A realistic assessment of future climate change is of great importance for arid regions, which are more vulnerable to any change in extreme events as their infrastructure is less experienced or not well adapted for extreme conditions. Our results show that climate change signals and associated uncertainties over the Middle East region remarkably vary with seasons. The region is identified as a climate change hotspot where rare extreme precipitation events are expected to intensify for all seasons, with a "highest increase in autumn, lowest increase in spring" pattern which switches to the "increase in autumn, decrease in spring" pattern for less extreme precipitation. This pattern is also held for mean precipitation, violating the "wet gets wetter, dry gets drier" paradigm.

Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments

USGS Publications Warehouse

Littell, Jeremy S.; Mauger, Guillaume S.; Salathe, Eric P.; Hamlet, Alan F.; Lee, Se-Yeun; Stumbaugh, Matt R.; Elsner, Marketa; Norheim, Robert; Lutz, Eric R.; Mantua, Nathan J.

2014-01-01

The purpose of this project was to (1) provide an internally-consistent set of downscaled projections across the Western U.S., (2) include information about projection uncertainty, and (3) assess projected changes of hydrologic extremes. These objectives were designed to address decision support needs for climate adaptation and resource management actions. Specifically, understanding of uncertainty in climate projections – in particular for extreme events – is currently a key scientific and management barrier to adaptation planning and vulnerability assessment. The new dataset fills in the Northwest domain to cover a key gap in the previous dataset, adds additional projections (both from other global climate models and a comparison with dynamical downscaling) and includes an assessment of changes to flow and soil moisture extremes. This new information can be used to assess variations in impacts across the landscape, uncertainty in projections, and how these differ as a function of region, variable, and time period. In this project, existing University of Washington Climate Impacts Group (UW CIG) products were extended to develop a comprehensive data archive that accounts (in a reigorous and physically based way) for climate model uncertainty in future climate and hydrologic scenarios. These products can be used to determine likely impacts on vegetation and aquatic habitat in the Pacific Northwest (PNW) region, including WA, OR, ID, northwest MT to the continental divide, northern CA, NV, UT, and the Columbia Basin portion of western WY New data series and summaries produced for this project include: 1) extreme statistics for surface hydrology (e.g. frequency of soil moisture and summer water deficit) and streamflow (e.g. the 100-year flood, extreme 7-day low flows with a 10-year recurrence interval); 2) snowpack vulnerability as indicated by the ratio of April 1 snow water to cool-season precipitation; and, 3) uncertainty analyses for multiple climate scenarios.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Evolution of Precipitation Extremes in Three Large Ensembles of Climate Simulations - Impact of Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Martel, J. L.; Brissette, F.; Mailhot, A.; Wood, R. R.; Ludwig, R.; Frigon, A.; Leduc, M.; Turcotte, R.

2017-12-01

Recent studies indicate that the frequency and intensity of extreme precipitation will increase in future climate due to global warming. In this study, we compare annual maxima precipitation series from three large ensembles of climate simulations at various spatial and temporal resolutions. The first two are at the global scale: the Canadian Earth System Model (CanESM2) 50-member large ensemble (CanESM2-LE) at a 2.8° resolution and the Community Earth System Model (CESM1) 40-member large ensemble (CESM1-LE) at a 1° resolution. The third ensemble is at the regional scale over both Eastern North America and Europe: the Canadian Regional Climate Model (CRCM5) 50-member large ensemble (CRCM5-LE) at a 0.11° resolution, driven at its boundaries by the CanESM-LE. The CRCM5-LE is a new ensemble issued from the ClimEx project (http://www.climex-project.org), a Québec-Bavaria collaboration. Using these three large ensembles, change in extreme precipitations over the historical (1980-2010) and future (2070-2100) periods are investigated. This results in 1 500 (30 years x 50 members for CanESM2-LE and CRCM5-LE) and 1200 (30 years x 40 members for CESM1-LE) simulated years over both the historical and future periods. Using these large datasets, the empirical daily (and sub-daily for CRCM5-LE) extreme precipitation quantiles for large return periods ranging from 2 to 100 years are computed. Results indicate that daily extreme precipitations generally will increase over most land grid points of both domains according to the three large ensembles. Regarding the CRCM5-LE, the increase in sub-daily extreme precipitations will be even more important than the one observed for daily extreme precipitations. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety.

Strategies to take into account variations in extreme rainfall events for design storms in urban area: an example over Naples (Southern Italy)

NASA Astrophysics Data System (ADS)

Mercogliano, P.; Rianna, G.

2017-12-01

Eminent works highlighted how available observations display ongoing increases in extreme rainfall events while climate models assess them for future. Although the constraints in rainfall networks observations and uncertainties in climate modelling currently affect in significant way investigations, the huge impacts potentially induced by climate changes (CC) suggest adopting effective adaptation measures in order to take proper precautions. In this regard, design storms are used by engineers to size hydraulic infrastructures potentially affected by direct (e.g. pluvial/urban flooding) and indirect (e.g. river flooding) effects of extreme rainfall events. Usually they are expressed as IDF curves, mathematical relationships between rainfall Intensity, Duration, and the return period (frequency, F). They are estimated interpreting through Extreme Theories Statistical Theories (ETST) past rainfall records under the assumption of steady conditions resulting then unsuitable under climate change. In this work, a methodology to estimate future variations in IDF curves is presented and carried out for the city of Naples (Southern Italy). In this regard, the Equidistance Quantile Matching Approach proposed by Sivrastav et al. (2014) is adopted. According it, daily-subdaily maximum precipitation observations [a] and the analogous daily data provided by climate projections on current [b] and future time spans [c] are interpreted in IDF terms through Generalized Extreme Value (GEV) approach. After, quantile based mapping approach is used to establish a statistical relationship between cumulative distribution functions resulting by GEV of [a] and [b] (spatial downscaling) and [b] and [c] functions (temporal downscaling). Coupling so-obtained relations permits generating IDF curves under CC assumption. To account for uncertainties in future projections, all climate simulations available for the area in Euro-Cordex multimodel ensemble at 0.11° (about 12 km) are considered under three different concentration scenarios (RCP2.6, RCP4.5 and RCP8.5). The results appear largely influenced by models, RCPs and time horizon of interest; nevertheless, clear indications of increases are detectable although with different magnitude on the different precipitation durations.

Stress testing hydrologic models using bottom-up climate change assessment

NASA Astrophysics Data System (ADS)

Stephens, C.; Johnson, F.; Marshall, L. A.

2017-12-01

Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

Mapping the Decadal Spatio-temporal Variation of Social Vulnerability to Hydro-climatic Extremes over India

NASA Astrophysics Data System (ADS)

H, V.; Karmakar, S.; Ghosh, S.

2015-12-01

Human induced global warming is unequivocal and observational studies shows that, this has led to increase in the intensity and frequency of hydro-climatic extremes, most importantly precipitation extreme, heat waves and drought; and also is expected to be increased in the future. The occurrence of these extremes have a devastating effects on nation's economy and on societal well-being. Previous studies on India provided the evidences of significant changes in the precipitation extreme from pre- to post-1950, with huge spatial heterogeneity; and projections of heat waves indicated that significant part of India will experience heat stress conditions in the future. Under these circumstance, it is necessary to develop a nation-wide social vulnerability map to scrutinize the adequacy of existing emergency management. Yet there has been no systematic past efforts on mapping social vulnerability to hydro-climatic extremes at nation-wide for India. Therefore, immediate efforts are required to quantify the social vulnerability, particularly developing country like India, where major transformations in demographic characteristics and development patterns are evident during past decades. In the present study, we perform a comprehensive spatio-temporal social vulnerability analysis by considering multiple sensitive indicators for three decades (1990-2010) which identifies the hot-spots, with higher vulnerability to hydro-climatic extremes. The population datasets are procured from Census of India and the meteorological datasets are obtained from India Meteorological Department (IMD). The study derives interesting results on decadal changes of spatial distribution of risk, considering social vulnerability and hazard to extremes.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Large-Scale Atmospheric Circulation Patterns Associated with Temperature Extremes as a Basis for Model Evaluation: Methodological Overview and Results

NASA Astrophysics Data System (ADS)

Loikith, P. C.; Broccoli, A. J.; Waliser, D. E.; Lintner, B. R.; Neelin, J. D.

2015-12-01

Anomalous large-scale circulation patterns often play a key role in the occurrence of temperature extremes. For example, large-scale circulation can drive horizontal temperature advection or influence local processes that lead to extreme temperatures, such as by inhibiting moderating sea breezes, promoting downslope adiabatic warming, and affecting the development of cloud cover. Additionally, large-scale circulation can influence the shape of temperature distribution tails, with important implications for the magnitude of future changes in extremes. As a result of the prominent role these patterns play in the occurrence and character of extremes, the way in which temperature extremes change in the future will be highly influenced by if and how these patterns change. It is therefore critical to identify and understand the key patterns associated with extremes at local to regional scales in the current climate and to use this foundation as a target for climate model validation. This presentation provides an overview of recent and ongoing work aimed at developing and applying novel approaches to identifying and describing the large-scale circulation patterns associated with temperature extremes in observations and using this foundation to evaluate state-of-the-art global and regional climate models. Emphasis is given to anomalies in sea level pressure and 500 hPa geopotential height over North America using several methods to identify circulation patterns, including self-organizing maps and composite analysis. Overall, evaluation results suggest that models are able to reproduce observed patterns associated with temperature extremes with reasonable fidelity in many cases. Model skill is often highest when and where synoptic-scale processes are the dominant mechanisms for extremes, and lower where sub-grid scale processes (such as those related to topography) are important. Where model skill in reproducing these patterns is high, it can be inferred that extremes are being simulated for plausible physical reasons, boosting confidence in future projections of temperature extremes. Conversely, where model skill is identified to be lower, caution should be exercised in interpreting future projections.

Historical and Future Projected Hydrologic Extremes over the Midwest and Great Lakes Region

NASA Astrophysics Data System (ADS)

Byun, K.; Hamlet, A. F.; Chiu, C. M.

2016-12-01

There is an increasing body of evidence from observed data that climate variability combined with regional climate change has had a significant impact on hydrologic cycles, including both seasonal patterns of runoff and altered hydrologic extremes (e.g. floods and extreme stormwater events). To better understand changing patterns of extreme high flows in Midwest and Great Lakes region, we analyzed long-term historical observations of peak streamflow at different gaging stations. We also conducted hydrologic model experiments using the Variable Infiltration Capacity (VIC) at 1/16 degree resolution in order to explore sensitivity of annual peak streamflow, both historically and under temperature and precipitation changes for several future periods. For future projections, the Hybrid Delta statistical downscaling approach applied to the Coupled Model Inter-comparison, Phase5 (CMIP5) Global Climate Model (GCM) scenarios was used to produce driving data for the VIC hydrologic model. Preliminary results for several test basins in the Midwest support the hypothesis that there are consistent and statistically significant changes in the mean annual flood starting before and after about 1975. Future projections using hydrologic model simulations support the hypothesis of higher peak flows due to warming and increasing precipitation projected for the 21st century. We will extend this preliminary analysis using observed data and simulations from 40 river basins in the Midwest to further test these hypotheses.

Associations between extreme precipitation and acute gastro-intestinal illness due to cryptosporidiosis and giardiasis in an urban Canadian drinking water system (1997-2009).

PubMed

Chhetri, Bimal K; Takaro, Tim K; Balshaw, Robert; Otterstatter, Michael; Mak, Sunny; Lem, Marcus; Zubel, Marc; Lysyshyn, Mark; Clarkson, Len; Edwards, Joanne; Fleury, Manon D; Henderson, Sarah B; Galanis, Eleni

2017-10-01

Drinking water related infections are expected to increase in the future due to climate change. Understanding the current links between these infections and environmental factors is vital to understand and reduce the future burden of illness. We investigated the relationship between weekly reported cryptosporidiosis and giardiasis (n = 7,422), extreme precipitation (>90th percentile), drinking water turbidity, and preceding dry periods in a drinking water system located in greater Vancouver, British Columbia, Canada (1997-2009) using distributed lag non-linear Poisson regression models adjusted for seasonality, secular trend, and the effect of holidays on reporting. We found a significant increase in cryptosporidiosis and giardiasis 4-6 weeks after extreme precipitation. The effect was greater following a dry period. Similarly, extreme precipitation led to significantly increased turbidity only after prolonged dry periods. Our results suggest that the risk of cryptosporidiosis and giardiasis increases with extreme precipitation, and that the effects are more pronounced after a prolonged dry period. Given that extreme precipitation events are expected to increase with climate change, it is important to further understand the risks from these events, develop planning tools, and build resilience to these future risks.

Assessment of hi-resolution multi-ensemble statistical downscaling regional climate scenarios over Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.

2017-12-01

The Asia-Pacific regions are increasingly threatened by large scale natural disasters. Growing concerns that loss and damages of natural disasters are projected to further exacerbate by climate change and socio-economic change. Climate information and services for risk assessments are of great concern. Fundamental regional climate information is indispensable for understanding changing climate and making decisions on when and how to act. To meet with the needs of stakeholders such as National/local governments, spatio-temporal comprehensive and consistent information is necessary and useful for decision making. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 37 GCMs (RCP8.5) and a statistical downscaling (Bias Corrected Spatial Disaggregation (BCSD)) to investigate uncertainty of projected change associated with structural differences of the GCMs for the periods of historical climate (1950-2005) and near future climate (2026-2050). Statistical downscaling regional climate scenarios show good performance for annual and seasonal averages for precipitation and temperature. The regional climate scenarios show systematic underestimate of extreme events such as hot days of over 35 Celsius and annual maximum daily precipitation because of the interpolation processes in the BCSD method. Each model projected different responses in near future climate because of structural differences. The most of CMIP5 37 models show qualitatively consistent increase of average and extreme temperature and precipitation. The added values of statistical/dynamical downscaling methods are also investigated for locally forced nonlinear phenomena, extreme events.

Climate Change Impact on Variability of Rainfall Intensity in Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worku, L. Y.

2015-12-01

Extreme rainfall events are major problems in Ethiopia with the resulting floods that usually could cause significant damage to agriculture, ecology, infrastructure, disruption to human activities, loss of property, loss of lives and disease outbreak. The aim of this study was to explore the likely changes of precipitation extreme changes due to future climate change. The study specifically focuses to understand the future climate change impact on variability of rainfall intensity-duration-frequency in Upper Blue Nile basin. Precipitations data from two Global Climate Models (GCMs) have been used in the study are HadCM3 and CGCM3. Rainfall frequency analysis was carried out to estimate quantile with different return periods. Probability Weighted Method (PWM) selected estimation of parameter distribution and L-Moment Ratio Diagrams (LMRDs) used to find the best parent distribution for each station. Therefore, parent distributions for derived from frequency analysis are Generalized Logistic (GLOG), Generalized Extreme Value (GEV), and Gamma & Pearson III (P3) parent distribution. After analyzing estimated quantile simple disaggregation model was applied in order to find sub daily rainfall data. Finally the disaggregated rainfall is fitted to find IDF curve and the result shows in most parts of the basin rainfall intensity expected to increase in the future. As a result of the two GCM outputs, the study indicates there will be likely increase of precipitation extremes over the Blue Nile basin due to the changing climate. This study should be interpreted with caution as the GCM model outputs in this part of the world have huge uncertainty.

Extreme storm surge and wind wave climate scenario simulations at the Venetian littoral

NASA Astrophysics Data System (ADS)

Lionello, P.; Galati, M. B.; Elvini, E.

Scenario climate projections for extreme marine storms producing storm surges and wind waves are very important for the northern flat coast of the Adriatic Sea, where the area at risk includes a unique cultural and environmental heritage, and important economic activities. This study uses a shallow water model and a spectral wave model for computing the storm surge and the wind wave field, respectively, from the sea level pressure and wind fields that have been computed by the RegCM regional climate model. Simulations cover the period 1961-1990 for the present climate (control simulations) and the period 2071-2100 for the A2 and B2 scenarios. Generalized Extreme Value analysis is used for estimating values for the 10 and 100 year return times. The adequacy of these modeling tools for a reliable estimation of the climate change signal, without needing further downscaling is shown. However, this study has mainly a methodological value, because issues such as interdecadal variability and intermodel variability cannot be addressed, since the analysis is based on single model 30-year long simulations. The control simulation looks reasonably accurate for extreme value analysis, though it overestimates/underestimates the frequency of high/low surge and wind wave events with respect to observations. Scenario simulations suggest higher frequency of intense storms for the B2 scenario, but not for the A2. Likely, these differences are not the effect of climate change, but of climate multidecadal variability. Extreme storms are stronger in future scenarios, but differences are not statistically significant. Therefore this study does not provide convincing evidence for more stormy conditions in future scenarios.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Projected timing of perceivable changes in climate extremes for terrestrial and marine ecosystems.

PubMed

Tan, Xuezhi; Gan, Thian Yew; Horton, Daniel E

2018-05-26

Human and natural systems have adapted to and evolved within historical climatic conditions. Anthropogenic climate change has the potential to alter these conditions such that onset of unprecedented climatic extremes will outpace evolutionary and adaptive capabilities. To assess whether and when future climate extremes exceed their historical windows of variability within impact-relevant socioeconomic, geopolitical, and ecological domains, we investigate the timing of perceivable changes (time of emergence; TOE) for 18 magnitude-, frequency-, and severity-based extreme temperature (10) and precipitation (8) indices using both multimodel and single-model multirealization ensembles. Under a high-emission scenario, we find that the signal of frequency- and severity-based temperature extremes is projected to rise above historical noise earliest in midlatitudes, whereas magnitude-based temperature extremes emerge first in low and high latitudes. Precipitation extremes demonstrate different emergence patterns, with severity-based indices first emerging over midlatitudes, and magnitude- and frequency-based indices emerging earliest in low and high latitudes. Applied to impact-relevant domains, simulated TOE patterns suggest (a) unprecedented consecutive dry day occurrence in >50% of 14 terrestrial biomes and 12 marine realms prior to 2100, (b) earlier perceivable changes in climate extremes in countries with lower per capita GDP, and (c) emergence of severe and frequent heat extremes well-before 2030 for the 590 most populous urban centers. Elucidating extreme-metric and domain-type TOE heterogeneities highlights the challenges adaptation planners face in confronting the consequences of elevated twenty-first century radiative forcing. © 2018 John Wiley & Sons Ltd.

Climate change and viticulture in Mediterranean climates: the complex response of socio-ecosystems. A comparative case study from France and Australia (1955-2040)

NASA Astrophysics Data System (ADS)

Lereboullet, A.-L.; Beltrando, G.; Bardsley, D. K.

2012-04-01

The wine industry is very sensitive to extreme weather events, especially to temperatures above 35°C and drought. In a context of global climate change, Mediterranean climate regions are predicted to experience higher variability in rainfall and temperatures and an increased occurrence of extreme weather events. Some viticultural systems could be particularly at risk in those regions, considering their marginal position in the growth climatic range of Vitis vinifera, the long commercial lifespan of a vineyard, the high added-value of wine and the volatile nature of global markets. The wine industry, like other agricultural systems, is inserted in complex networks of climatic and non-climatic (other physical, economical, social and legislative) components, with constant feedbacks. We use a socio-ecosystem approach to analyse the adaptation of two Mediterranean viticultural systems to recent and future increase of extreme weather events. The present analysis focuses on two wine regions with a hot-summer Mediterranean climate (CSb type in the Köppen classification): Côtes-du-Roussillon in southern France and McLaren Vale in southern Australia. Using climate data from two synoptic weather stations, Perpignan (France) and Adelaide (Australia), with time series running from 1955 to 2010, we highlight changes in rainfall patterns and an increase in the number of days with Tx >35°c since the last three decades in both regions. Climate models (DRIAS project data for France and CSIRO Mk3.5 for Australia) project similar trends in the future. To date, very few projects have focused on an international comparison of the adaptive capacity of viticultural systems to climate change with a holistic approach. Here, the analysis of climate data was complemented by twenty in-depth semi-structured interviews with key actors of the two regional wine industries, in order to analyse adaptation strategies put in place regarding recent climate evolution. This mixed-methods approach allows for a comprehensive assessment of adaptation capacity of the two viticultural systems to future climate change. The strategies of grape growers and wine producers focus on maintaining optimal yields and a constant wine style adapted to markets in a variable and uncertain climate. Their implementation and efficiency depend strongly on non-climatic factors. Thus, adaptation capacity to recent and future climate change depends strongly on adaptation to other non-climatic changes.

Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes

PubMed Central

Immerzeel, W. W.; Kraaijenbrink, P. D. A.; Shrestha, A. B.; Bierkens, M. F. P.

2016-01-01

The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin’s water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members. PMID:27828994

Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes.

PubMed

Lutz, A F; Immerzeel, W W; Kraaijenbrink, P D A; Shrestha, A B; Bierkens, M F P

2016-01-01

The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin's water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members.

North American extreme temperature events and related large scale meteorological patterns: A review of statistical methods, dynamics, modeling, and trends

DOE PAGES

Grotjahn, Richard; Black, Robert; Leung, Ruby; ...

2015-05-22

This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic tomore » planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so more research is needed to understand the limitations of climate models and improve model skill in simulating extreme temperatures and their associated LSMPs. Furthermore, the paper concludes with unresolved issues and research questions.« less

TOWARDS AN IMPROVED UNDERSTANDING OF SIMULATED AND OBSERVED CHANGES IN EXTREME PRECIPITATION

EPA Science Inventory

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

Improving Predictions and Management of Hydrological Extremes

NASA Astrophysics Data System (ADS)

Wijngaard, Janet; Liggins, Felicity; Hurk, Bart vd; Lavers, David; Magnusson, Linus; Bouwer, Laurens; Weerts, Albrecht; Kjellström, Erik; Mañez, Maria; Ramos, Maria-Helena; Hananel, Cedric; Ercin, Ertug; Hunink, Johannes; Klein, Bastian; Pouget, Laurent; de Moel, Hans

2017-04-01

The EU Roadmap on Climate Services can be seen as a result of convergence between society's call for "actionable research" and the climate research community's provision of tailored data, information and knowledge. Although weather and climate have distinct definitions, a strong link between weather and climate services does exist but, to date, this link has not been explored extensively. Stakeholders being interviewed in the context of the Roadmap consider changes in our climate as distant, long-term impacts that are difficult to consider in present-day decision making, a process usually dominated by their daily experience with handling adverse weather and extreme events. However, it could be argued that this experience is a rich source of inspiration to increase society's resilience to an unknown future. The European research project, IMPREX, is built on the notion that "experience in managing present day weather extremes can help us anticipate the consequences of future climate variability and change". This presentation illustrates how IMPREX is building the link between the providers and users of information and services addressing both the weather and climate timescales. For different stakeholders in key economic sectors the needs and vulnerabilities in their daily practice are discussed, followed by an analysis of how weather and climate (W&C) services could contribute to the demands that arise from this. Examples of case studies showing the relevance of the tailored W&C information in users' operations will be included.

Changes in Seasonal and Extreme Hydrologic Conditions of the Georgia Basin/Puget Sound in an Ensemble Regional Climate Simulation for the Mid-Century

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

Leung, Lai R.; Qian, Yun

This study examines an ensemble of climate change projections simulated by a global climate model (GCM) and downscaled with a region climate model (RCM) to 40 km spatial resolution for the western North America. One control and three ensemble future climate simulations were produced by the GCM following a business as usual scenario for greenhouse gases and aerosols emissions from 1995 to 2100. The RCM was used to downscale the GCM control simulation (1995-2015) and each ensemble future GCM climate (2040-2060) simulation. Analyses of the regional climate simulations for the Georgia Basin/Puget Sound showed a warming of 1.5-2oC and statisticallymore » insignificant changes in precipitation by the mid-century. Climate change has large impacts on snowpack (about 50% reduction) but relatively smaller impacts on the total runoff for the basin as a whole. However, climate change can strongly affect small watersheds such as those located in the transient snow zone, causing a higher likelihood of winter flooding as a higher percentage of precipitation falls in the form of rain rather than snow, and reduced streamflow in early summer. In addition, there are large changes in the monthly total runoff above the upper 1% threshold (or flood volume) from October through May, and the December flood volume of the future climate is 60% above the maximum monthly flood volume of the control climate. Uncertainty of the climate change projections, as characterized by the spread among the ensemble future climate simulations, is relatively small for the basin mean snowpack and runoff, but increases in smaller watersheds, especially in the transient snow zone, and associated with extreme events. This emphasizes the importance of characterizing uncertainty through ensemble simulations.« less

Extreme Events and Energy Providers: Science and Innovation

NASA Astrophysics Data System (ADS)

Yiou, P.; Vautard, R.

2012-04-01

Most socio-economic regulations related to the resilience to climate extremes, from infrastructure or network design to insurance premiums, are based on a present-day climate with an assumption of stationarity. Climate extremes (heat waves, cold spells, droughts, storms and wind stilling) affect in particular energy production, supply, demand and security in several ways. While national, European or international projects have generated vast amounts of climate projections for the 21st century, their practical use in long-term planning remains limited. Estimating probabilistic diagnostics of energy user relevant variables from those multi-model projections will help the energy sector to elaborate medium to long-term plans, and will allow the assessment of climate risks associated to those plans. The project "Extreme Events for Energy Providers" (E3P) aims at filling a gap between climate science and its practical use in the energy sector and creating in turn favourable conditions for new business opportunities. The value chain ranges from addressing research questions directly related to energy-significant climate extremes to providing innovative tools of information and decision making (including methodologies, best practices and software) and climate science training for the energy sector, with a focus on extreme events. Those tools will integrate the scientific knowledge that is developed by scientific communities, and translate it into a usable probabilistic framework. The project will deliver projection tools assessing the probabilities of future energy-relevant climate extremes at a range of spatial scales varying from pan-European to local scales. The E3P project is funded by the Knowledge and Innovation Community (KIC Climate). We will present the mechanisms of interactions between academic partners, SMEs and industrial partners for this project. Those mechanisms are elementary bricks of a climate service.

The Weather of the Future: Heat Waves, Extreme Storms, and Other Scenes from a Climate-Changed Planet

NASA Astrophysics Data System (ADS)

Cullen, H. M.

2010-12-01

In The Weather of the Future, Dr. Heidi Cullen puts a vivid face on climate change, offering a new way of seeing this phenomenon not just as an event set to happen in the distant future but as something happening right now in our own backyards. Arguing that we must connect the weather of today with the climate change of tomorrow, Cullen combines the latest research from scientists on the ground with state-of-the-art climate model projections to create climate-change scenarios for seven of the most at-risk locations around the world. From the Central Valley of California, where coming droughts will jeopardize the entire state’s water supply, to Greenland, where warmer temperatures will give access to mineral wealth buried beneath ice sheets for millennia, Cullen illustrates how, if left unabated, climate change will transform every corner of the world by midcentury. What emerges is a mosaic of changing weather patterns that collectively spell out the range of risks posed by global warming—whether it’s New York City, whose infrastructure is extremely vulnerable even to a relatively weak Category 3 hurricane or to Bangladesh, a country so low-lying that millions of people could become climate refugees thanks to rising sea levels. The Weather of the Future makes climate change local, showing how no two regions of the country or the world will be affected in quite the same way and demonstrating that melting ice is just the beginning.

Using Dynamically Downscaled Climate Model Outputs to Inform Projections of Extreme Precipitation Events

NASA Technical Reports Server (NTRS)

Wobus, Cameron; Reynolds, Lara; Jones, Russell; Horton, Radley; Smith, Joel; Fries, J. Stephen; Tryby, Michael; Spero, Tanya; Nolte, Chris

2015-01-01

Many of the storms that generate damaging floods are caused by locally intense, sub-daily precipitation, yet the spatial and temporal resolution of the most widely available climate model outputs are both too coarse to simulate these events. Thus there is often a disconnect between the nature of the events that cause damaging floods and the models used to project how climate change might influence their magnitude. This could be a particular problem when developing scenarios to inform future storm water management options under future climate scenarios. In this study we sought to close this gap, using sub-daily outputs from the Weather Research and Forecasting model (WRF) from each of the nine climate regions in the United States. Specifically, we asked 1) whether WRF outputs projected consistent patterns of change for sub-daily and daily precipitation extremes; and 2) whether this dynamically downscaled model projected different magnitudes of change for 3-hourly vs 24-hourly extreme events. We extracted annual maximum values for 3-hour through 24-hour precipitation totals from an 11-year time series of hindcast (1995-2005) and mid-century (2045-2055) climate, and calculated the direction and magnitude of change for 3-hour and 24-hour extreme events over this timeframe. The model results project that the magnitude of both 3-hour and 24-hour events will increase over most regions of the United States, but there was no clear or consistent difference in the relative magnitudes of change for sub-daily vs daily events.

Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa Under Evolving Climate Conditions to Support Adaptation Strategies

NASA Astrophysics Data System (ADS)

Tadesse, T.; Zaitchik, B. F.; Habib, S.; Funk, C. C.; Senay, G. B.; Dinku, T.; Policelli, F. S.; Block, P.; Baigorria, G. A.; Beyene, S.; Wardlow, B.; Hayes, M. J.

2014-12-01

The development of effective strategies to adapt to changes in the character of droughts and floods in Africa will rely on improved seasonal prediction systems that are robust to an evolving climate baseline and can be integrated into disaster preparedness and response. Many efforts have been made to build models to improve seasonal forecasts in the Greater Horn of Africa region (GHA) using satellite and climate data, but these efforts and models must be improved and translated into future conditions under evolving climate conditions. This has considerable social significance, but is challenged by the nature of climate predictability and the adaptability of coupled natural and human systems facing exposure to climate extremes. To address these issues, work is in progress under a project funded by NASA. The objectives of the project include: 1) Characterize and explain large-scale drivers in the ocean-atmosphere-land system associated with years of extreme flood or drought in the GHA. 2) Evaluate the performance of state-of-the-art seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes. 3) Apply seasonal forecast systems to prediction of socially relevant impacts on crops, flood risk, and economic outcomes, and assess the value of these predictions to decision makers. 4) Evaluate the robustness of seasonal prediction systems to evolving climate conditions. The National Drought Mitigation Center (University of Nebraska-Lincoln, USA) is leading this project in collaboration with the USGS, Johns Hopkins University, University of Wisconsin-Madison, the International Research Institute for Climate and Society, NASA, and GHA local experts. The project is also designed to have active engagement of end users in various sectors, university researchers, and extension agents in GHA through workshops and/or webinars. This project is expected improve and implement new and existing climate- and remote sensing-based agricultural, meteorological, and hydrologic drought and flood monitoring products (or indicators) that can enhance the preparedness for extreme climate events and climate change adaptation and mitigation strategies in the GHA. Even though this project is in its first year, the preliminary results and future plans to carry out the objectives will be presented.

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

NASA Technical Reports Server (NTRS)

Crosson, William L; Al-Hamdan, Mohammad Z.; Economou, Sigrid, A.; Estes, Maurice G.; Estes, Sue M.; Puckett, Mark; Quattrochi, Dale A

2013-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Changes in Hydrological Extremes and its Relation to Climate Variability in Mountainous Watershed: A Case Study from Gandaki River Basin, Nepal

NASA Astrophysics Data System (ADS)

Shrestha, N. S.; Dahal, P.

2016-12-01

Changes in the hydrological extreme are expected due to climate variability and are needed to assess at local and regional scales since these changes are not uniform over the globe. This study analyses the changes in intensity, frequency and persistence hydrological extreme in Gandaki River Basin (GRB) Nepal over past and future and its relation to climate variability. Hydrological data of 12 different hydrological stations covering all the sub basins of Gandaki River Basin were analyzed. At least 1 hydrological station in each sub basin to the maximum of 3 was taken into consideration for this study. Results show that hydrological extreme have increased in intensity, frequency and persistence over recent year and are predicted to increase in future (2030-2060). The time-series analysis revealed an increase in the magnitude, frequency and duration of flood and drought. The instantaneous maximum flow, flood events and duration of flood events are found to have increasing trend. The minimum discharge was observed to be decreasing which entails that the water availability in the driest time is decreasing. Trend analysis of seasonal flow revealed an increase in monsoon flows and decreasing in post monsoon. Changes in climate variability over the same period shows higher anomalies in both temperature and precipitation in recent decades (1990s and 2000s) compared to the baseline period (1970-2000). Model suggests an increasing trend in annual flows with the increase more pronounced in 2060s. Significant increase in extreme flows and subsequent decrease in dependable flows suggest increase in frequency of isolated extreme flows followed by prolonged dry spells. Data also showed that the mean temperature will be increasing from 1.9 0C to 3.1 0C and precipitation will be changing by -8% to +12% in 2031-2060 compared to the baseline period. For long-term planning and management of water resources, current trend and future change in the pattern of water availability should be analysed well in advance. Climate change with intensifying extreme events will likely have serious consequences on the hydrological changes. Therefore, this study would be useful in understanding how the hydrological regime has been changing with climate change in mountainous watershed.

Assessing Australian Rainfall Projections in Two Model Resolutions

NASA Astrophysics Data System (ADS)

Taschetto, A.; Haarsma, R. D.; Sen Gupta, A.

2016-02-01

Australian climate is projected to change with increases in greenhouse gases. The IPCC reports an increase in extreme daily rainfall across the country. At the same time, mean rainfall over southeast Australia is projected to reduce during austral winter, but to increase during austral summer, mainly associated with changes in the surrounding oceans. Climate models agree better on the future reduction of average rainfall over the southern regions of Australia compared to the increase in extreme rainfall events. One of the reasons for this disagreement may be related to climate model limitations in simulating the observed mechanisms associated with the mid-latitude weather systems, in particular due to coarse model resolutions. In this study we investigate how changes in sea surface temperature (SST) affect Australian mean and extreme rainfall under global warming, using a suite of numerical experiments at two model resolutions: about 126km (T159) and 25km (T799). The numerical experiments are performed with the earth system model EC-EARTH. Two 6-member ensembles are produced for the present day conditions and a future scenario. The present day ensemble is forced with the observed daily SST from the NOAA National Climatic Data Center from 2002 to 2006. The future scenario simulation is integrated from 2094 to 2098 using the present day SST field added onto the future SST change created from a 17-member ensemble based on the RCP4.5 scenario. Preliminary results show an increase in extreme rainfall events over Tasmania associated with enhanced convection driven by the Tasman Sea warming. We will further discuss how the projected changes in SST will impact the southern mid-latitude weather systems that ultimately affect Australian rainfall.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

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

Brunsell, Nathaniel; Mechem, David; Ma, Chunsheng

Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive tomore » alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the validity of an innovative multi–resolution information theory approach, and the ability of the RCM modeling framework to represent the low-frequency modulation of extreme climate events. Once the skill of the modeling and analysis methodology has been established, we will apply the same approach for the AR5 (IPCC Fifth Assessment Report) climate change scenarios in order to assess how climate extremes and the the influence of lowfrequency variability on climate extremes might vary under changing climate. The research specifically addresses the DOE focus area 2. Simulation of climate extremes under a changing climate. Specific results will include (1) a better understanding of the spatial and temporal structure of extreme events, (2) a thorough quantification of how extreme values are impacted by low-frequency climate teleconnections, (3) increased knowledge of current regional climate models ability to ascertain these influences, and (4) a detailed examination of the how the distribution of extreme events are likely to change under different climate change scenarios. In addition, this research will assess the ability of the innovative wavelet information theory approach to characterize extreme events. Any and all of these results will greatly enhance society’s ability to understand and mitigate the regional ramifications of future global climate change.« less

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

Impacts of Climate Change and Variability on Water Resources in the Southeast USA

Treesearch

Ge Sun; Peter V. Caldwell; Steven G. McNulty; Aris P. Georgakakos; Sankar Arumugam; James Cruise; Richard T. McNider; Adam Terando; Paul A. Conrads; John Feldt; Vasu Misra; Luigi Romolo; Todd C. Rasmussen; Daniel A. Marion

2013-01-01

Key FindingsClimate change is affecting the southeastern USA, particularly increases in rainfall variability and air temperature, which have resulted in more frequent hydrologic extremes, such as high‐intensity storms (tropical storms and hurricanes), flooding, and drought events.Future climate warming likely will...

Implications of Climate Change for Children in Developing Countries

ERIC Educational Resources Information Center

Hanna, Rema; Oliva, Paulina

2016-01-01

Climate change may be particularly dangerous for children in developing countries. Even today, many developing countries experience a disproportionate share of extreme weather, and they are predicted to suffer disproportionately from the effects of climate change in the future. Moreover, developing countries often have limited social safety nets,…

Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2007-12-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

Advancing the adaptive capacity of social-ecological systems to absorb climate extremes

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; Bahn, Michael; Bardgett, Richard; Bloemen, Jasper; Chabay, Ilan; Erb, Karlheinz; Giamberini, Mariasilvia; Gingrich, Simone; Lavorel, Sandra; Liehr, Stefan; Rammig, Anja

2017-04-01

The recent and projected increases in climate variability and the frequency of climate extremes are posing a profound challenge to society and the biosphere (IPCC 2012, IPCC 2013). Climate extremes can affect natural and managed ecosystems more severely than gradual warming. The ability of ecosystems to resist and recover from climate extremes is therefore of fundamental importance for society, which strongly relies on their ability to supply provisioning, regulating, supporting and cultural services. Society in turn triggers land-use and management decisions that affect ecosystem properties. Thus, ecological and socio-economic conditions are tightly coupled in what has been referred to as the social-ecological system. For ensuring human well-being in the light of climate extremes it is crucial to enhance the resilience of the social-ecological system (SES) across spatial, temporal and institutional scales. Stakeholders, such as resource managers, urban, landscape and conservation planners, decision-makers in agriculture and forestry, as well as natural hazards managers, require an improved knowledge base for better-informed decision making. To date the vulnerability and adaptive capacity of SESs to climate extremes is not well understood and large uncertainties exist as to the legacies of climate extremes on ecosystems and on related societal structures and processes. Moreover, we lack empirical evidence and incorporation of simulated future ecosystem and societal responses to support pro-active management and enhance social-ecological resilience. In our presentation, we outline the major research gaps and challenges to be addressed for understanding and enhancing the adaptive capacity of SES to absorb and adapt to climate extremes, including acquisition and elaboration of long-term monitoring data and improvement of ecological models to better project climate extreme effects and provide model uncertainties. We highlight scientific challenges and discuss conceptual and observational gaps that need to be overcome to advance this inter- and transdisciplinary topic.

The effects of climate-change-induced drought and freshwater wetlands

USGS Publications Warehouse

Middleton, B.A.; Kleinebecker, Till; Middleton, B.A.

2012-01-01

Drought cycles in wetlands may become more frequent and severe in the future, with consequences for wetland distribution and function. According to the Intergovernmental Panel on Climate Change (Intergovernmental Panel on Climate Change [IPCC], Managing the risks of extreme events and disasters to advance climate change adaptation, 2012. Online: http://ipcc-wg2.gov/SREX/images/uploads/SREX-All_FINAL.pdf, climate-change is likely to affect precipitation and evapotranspiration patterns so that the world’s wetlands may have more frequent episodes of extreme flooding and drought. This chapter contributes to a worldwide view of how wetland processes may be affected by these predicted changes in climate. Specifically, the occurrence of drought may increase, and that increase may affect the critical processes that sustain biodiversity in wetlands. We include specific examples that explore the effects of drought and other climate-change factors on wetland function in various parts of the world. In a concluding section we discuss management strategies for climate-change in wetlands. The synthesis of information in this chapter will contribute to a better understanding of how climate-change-induced drought may affect the function and distribution of wetlands in the future.

Climate change and rising heat: population health implications for working people in Australia.

PubMed

Hanna, Elizabeth G; Kjellstrom, Tord; Bennett, Charmian; Dear, Keith

2011-03-01

The rapid rise in extreme heat events in Australia recently is already taking a health toll. Climate change scenarios predict increases in the frequency and intensity of extreme heat events in the future, and population health may be significantly compromised for people who cannot reduce their heat exposure. Exposure to extreme heat presents a health hazard to all who are physically active, particularly outdoor workers and indoor workers with minimal access to cooling systems while working. At air temperatures close to (or beyond) the core body temperature of 37°C, body cooling via sweating is essential, and this mechanism is hampered by high air humidity. Heat exposure among elite athletes and the military has been investigated, whereas the impacts on workers remain largely unexplored, particularly in relation to future climate change. Workers span all age groups and diverse levels of fitness and health status, including people with higher than "normal" sensitivity to heat. In a hotter world, workers are likely to experience more heat stress and find it increasingly difficult to maintain productivity. Modeling of future climate change in Australia shows a substantial increase in the number of very hot days (>35°C) across the country. In this article, the authors characterize the health risks associated with heat exposure on working people and discuss future exposure risks as temperatures rise. Progress toward developing occupational health and safety guidelines for heat in Australia are summarized.

Estimating the effects of extreme weather on transportation infrastructure.

DOT National Transportation Integrated Search

2016-12-01

Climate change, already taking place, is expected to become more pronounced in the future. Current damage assessment models for extreme weather events, such as FEMAs Hazus, do not take the full impact to transportation systems into consideration. ...

Tailored scenarios for streamflow climate change impacts based on the perturbation of precipitation and evapotranspiration

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Willems, Patrick; Baguis, Pierre; Roulin, Emmanuel

2015-04-01

It is advisable to account for a wide range of uncertainty by including the maximum possible number of climate models and scenarios for future impacts. As this is not always feasible, impact assessments are inevitably performed with a limited set of scenarios. The development of tailored scenarios is a challenge that needs more attention as the number of available climate change simulations grows. Whether these scenarios are representative enough for climate change impacts is a question that needs addressing. This study presents a methodology of constructing tailored scenarios for assessing runoff flows including extreme conditions (peak flows) from an ensemble of future climate change signals of precipitation and potential evapotranspiration (ETo) derived from the climate model simulations. The aim of the tailoring process is to formulate scenarios that can optimally represent the uncertainty spectrum of climate scenarios. These tailored scenarios have the advantage of being few in number as well as having a clear description of the seasonal variation of the climate signals, hence allowing easy interpretation of the implications of future changes. The tailoring process requires an analysis of the hydrological impacts from the likely future change signals from all available climate model simulations in a simplified (computationally less expensive) impact model. Historical precipitation and ETo time series are perturbed with the climate change signals based on a quantile perturbation technique that accounts for the changes in extremes. For precipitation, the change in wetday frequency is taken into account using a markov-chain approach. Resulting hydrological impacts from the perturbed time series are then subdivided into high, mean and low hydrological impacts using a quantile change analysis. From this classification, the corresponding precipitation and ETo change factors are back-tracked on a seasonal basis to determine precipitation-ETo covariation. The established precipitation-ETo covariations are used to inform the scenario construction process. Additionally, the back-tracking of extreme flows from driving scenarios allows for a diagnosis of the physical responses to climate change scenarios. The method is demonstrated through the application of scenarios from 10 Regional Climate Models,21 Global Climate Models and selected catchments in central Belgium. Reference Ntegeka, V., Baguis, P., Roulin, E., & Willems, P. (2014). Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508, 307-321.

The Joint Statistics of California Temperature and Precipitation as a Function of the Large-scale State of the Climate

NASA Astrophysics Data System (ADS)

OBrien, J. P.; O'Brien, T. A.

2015-12-01

Single climatic extremes have a strong and disproportionate effect on society and the natural environment. However, the joint occurrence of two or more concurrent extremes has the potential to negatively impact these areas of life in ways far greater than any single event could. California, USA, home to nearly 40 million people and the largest agricultural producer in the United States, is currently experiencing an extreme drought, which has persisted for several years. While drought is commonly thought of in terms of only precipitation deficits, above average temperatures co-occurring with precipitation deficits greatly exacerbate drought conditions. The 2014 calendar year in California was characterized both by extremely low precipitation and extremely high temperatures, which has significantly deepened the already extreme drought conditions leading to severe water shortages and wildfires. While many studies have shown the statistics of 2014 temperature and precipitation anomalies as outliers, none have demonstrated a connection with large-scale, long-term climate trends, which would provide useful relationships for predicting the future trajectory of California climate and water resources. We focus on understanding non-stationarity in the joint distribution of California temperature and precipitation anomalies in terms of large-scale, low-frequency trends in climate such as global mean temperature rise and oscillatory indices such as ENSO and the Pacific Decadal Oscillation among others. We consider temperature and precipitation data from the seven distinct climate divisions in California and employ a novel, high-fidelity kernel density estimation method to directly infer the multivariate distribution of temperature and precipitation anomalies conditioned on the large-scale state of the climate. We show that the joint distributions and associated statistics of temperature and precipitation are non-stationary and vary regionally in California. Further, we show that recurrence intervals of extreme concurrent events vary as a function of time and of teleconnections. This research has implications for predicting and forecasting future temperature and precipitation anomalies, which is critically important for city, water, and agricultural planning in California.

Elevated CO2 maintains grassland net carbon uptake under a future heat and drought extreme

PubMed Central

Roy, Jacques; Picon-Cochard, Catherine; Augusti, Angela; Benot, Marie-Lise; Thiery, Lionel; Darsonville, Olivier; Landais, Damien; Piel, Clément; Defossez, Marc; Devidal, Sébastien; Escape, Christophe; Ravel, Olivier; Fromin, Nathalie; Volaire, Florence; Milcu, Alexandru; Bahn, Michael; Soussana, Jean-François

2016-01-01

Extreme climatic events (ECEs) such as droughts and heat waves are predicted to increase in intensity and frequency and impact the terrestrial carbon balance. However, we lack direct experimental evidence of how the net carbon uptake of ecosystems is affected by ECEs under future elevated atmospheric CO2 concentrations (eCO2). Taking advantage of an advanced controlled environment facility for ecosystem research (Ecotron), we simulated eCO2 and extreme cooccurring heat and drought events as projected for the 2050s and analyzed their effects on the ecosystem-level carbon and water fluxes in a C3 grassland. Our results indicate that eCO2 not only slows down the decline of ecosystem carbon uptake during the ECE but also enhances its recovery after the ECE, as mediated by increases of root growth and plant nitrogen uptake induced by the ECE. These findings indicate that, in the predicted near future climate, eCO2 could mitigate the effects of extreme droughts and heat waves on ecosystem net carbon uptake. PMID:27185934

Managing the Risks of Extreme Events and Disasters in a Changing Climate: Lessons for Adaptation to Climate Change (Invited)

NASA Astrophysics Data System (ADS)

Mastrandrea, M.; Field, C. B.; Mach, K. J.; Barros, V.

2013-12-01

The IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, published in 2012, integrates expertise in climate science, disaster risk reduction, and adaptation to inform discussions on how to reduce and manage the risks of extreme events and disasters in a changing climate. Impacts and the risks of disasters are determined by the interaction of the physical characteristics of weather and climate events with the vulnerability of exposed human society and ecosystems. The Special Report evaluates the factors that make people and infrastructure vulnerable to extreme events, trends in disaster losses, recent and future changes in the relationship between climate change and extremes, and experience with a wide range of options used by institutions, organizations, and communities to reduce exposure and vulnerability, and improve resilience, to climate extremes. Actions ranging from incremental improvements in governance and technology to more transformational changes are assessed. The Special Report provides a knowledge base that is also relevant to the broader context of managing the risks of climate change through mitigation, adaptation, and other responses, assessed in the IPCC's Fifth Assessment Report (AR5), to be completed in 2014. These themes include managing risks through an iterative process involving learning about risks and the effectiveness of responses, employing a portfolio of actions tailored to local circumstances but with links from local to global scales, and considering additional benefits of actions such as improving livelihoods and well-being. The Working Group II contribution to the AR5 also examines the ways that extreme events and their impacts contribute to understanding of vulnerabilities and adaptation deficits in the context of climate change, the extent to which impacts of climate change are experienced through changes in the frequency and severity of extremes as opposed to mean changes, and the emergence of risks that are place-based vs. systemic.

Knowledge discovery and nonlinear modeling can complement climate model simulations for predictive insights about climate extremes and their impacts

NASA Astrophysics Data System (ADS)

Ganguly, A. R.; Steinbach, M.; Kumar, V.

2009-12-01

The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative predictive insights based on a combination of hypothesis-guided data analysis and relatively hypothesis-free but data-guided discovery processes. The analysis and discovery approaches need to be cognizant of climate data characteristics like nonlinear processes, low-frequency variability, long-range spatial dependence and long-memory temporal processes; the value of physically-motivated conceptual understanding and functional associations; as well as possible thresholds and tipping points in the impacted natural, engineered or human systems. Case studies focusing on new methodologies as well as novel climate insights are discussed with a focus on stakeholder requirements.

Compound summer temperature and precipitation extremes over central Europe

NASA Astrophysics Data System (ADS)

Sedlmeier, Katrin; Feldmann, H.; Schädler, G.

2018-02-01

Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes, like heat and drought occurring simultaneously, may have a greater impact on society than their univariate counterparts and have recently become an active field of study. In this paper, we use a 12-member ensemble of high-resolution (7 km) regional climate simulations with the regional climate model COSMO-CLM over central Europe to analyze the climate change signal and its uncertainty for compound heat and drought extremes in summer by two different measures: one describing absolute (i.e., number of exceedances of absolute thresholds like hot days), the other relative (i.e., number of exceedances of time series intrinsic thresholds) compound extreme events. Changes are assessed between a reference period (1971-2000) and a projection period (2021-2050). Our findings show an increase in the number of absolute compound events for the whole investigation area. The change signal of relative extremes is more region-dependent, but there is a strong signal change in the southern and eastern parts of Germany and the neighboring countries. Especially the Czech Republic shows strong change in absolute and relative extreme events.

Dynamically-downscaled projections of changes in temperature extremes over China

NASA Astrophysics Data System (ADS)

Guo, Junhong; Huang, Guohe; Wang, Xiuquan; Li, Yongping; Lin, Qianguo

2018-02-01

In this study, likely changes in extreme temperatures (including 16 indices) over China in response to global warming throughout the twenty-first century are investigated through the PRECIS regional climate modeling system. The PRECIS experiment is conducted at a spatial resolution of 25 km and is driven by a perturbed-physics ensemble to reflect spatial variations and model uncertainties. Simulations of present climate (1961-1990) are compared with observations to validate the model performance in reproducing historical climate over China. Results indicate that the PRECIS demonstrates reasonable skills in reproducing the spatial patterns of observed extreme temperatures over the most regions of China, especially in the east. Nevertheless, the PRECIS shows a relatively poor performance in simulating the spatial patterns of extreme temperatures in the western mountainous regions, where its driving GCM exhibits more uncertainties due to lack of insufficient observations and results in more errors in climate downscaling. Future spatio-temporal changes of extreme temperature indices are then analyzed for three successive periods (i.e., 2020s, 2050s and 2080s). The projected changes in extreme temperatures by PRECIS are well consistent with the results of the major global climate models in both spatial and temporal patterns. Furthermore, the PRECIS demonstrates a distinct superiority in providing more detailed spatial information of extreme indices. In general, all extreme indices show similar changes in spatial pattern: large changes are projected in the north while small changes are projected in the south. In contrast, the temporal patterns for all indices vary differently over future periods: the warm indices, such as SU, TR, WSDI, TX90p, TN90p and GSL are likely to increase, while the cold indices, such as ID, FD, CSDI, TX10p and TN10p, are likely to decrease with time in response to global warming. Nevertheless, the magnitudes of changes in all indices tend to decrease gradually with time, indicating the projected warming will begin to slow down in the late of this century. In addition, the projected range of changes for all indices would become larger with time, suggesting more uncertainties would be involved in long-term climate projections.

Changes in Concurrent Risk of Warm and Dry Years under Impact of Climate Change

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Wiper, M.; Touma, D. E.; Ausín, M. C.; Diffenbaugh, N. S.

2017-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena. The changing concurrence of multiple climatic extremes (warm and dry years) may result in intensification of undesirable consequences for water resources, human and ecosystem health, and environmental equity. The present study assesses how global warming influences the probability that warm and dry years co-occur in a global scale. In the first step of the study a designed multivariate Mann-Kendall trend analysis is used to detect the areas in which the concurrence of warm and dry years has increased in the historical climate records and also climate models in the global scale. The next step investigates the concurrent risk of the extremes under dynamic nonstationary conditions. A fully generalized multivariate risk framework is designed to evolve through time under dynamic nonstationary conditions. In this methodology, Bayesian, dynamic copulas are developed to model the time-varying dependence structure between the two different climate extremes (warm and dry years). The results reveal an increasing trend in the concurrence risk of warm and dry years, which are in agreement with the multivariate trend analysis from historical and climate models. In addition to providing a novel quantification of the changing probability of compound extreme events, the results of this study can help decision makers develop short- and long-term strategies to prepare for climate stresses now and in the future.

Impact of urban WWTP and CSO fluxes on river peak flow extremes under current and future climate conditions.

PubMed

Keupers, Ingrid; Willems, Patrick

2013-01-01

The impact of urban water fluxes on the river system outflow of the Grote Nete catchment (Belgium) was studied. First the impact of the Waste Water Treatment Plant (WWTP) and the Combined Sewer Overflow (CSO) outflows on the river system for the current climatic conditions was determined by simulating the urban fluxes as point sources in a detailed, hydrodynamic river model. Comparison was made of the simulation results on peak flow extremes with and without the urban point sources. In a second step, the impact of climate change scenarios on the urban fluxes and the consequent impacts on the river flow extremes were studied. It is shown that the change in the 10-year return period hourly peak flow discharge due to climate change (-14% to +45%) was in the same order of magnitude as the change due to the urban fluxes (+5%) in current climate conditions. Different climate change scenarios do not change the impact of the urban fluxes much except for the climate scenario that involves a strong increase in rainfall extremes in summer. This scenario leads to a strong increase of the impact of the urban fluxes on the river system.

Increasing water cycle extremes in California and relation to ENSO cycle under global warming

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

Yoon, Jin -Ho; Wang, S. -Y. Simon; Gillies, Robert R.

California has experienced its most severe drought in recorded history since the winter of 2013-2014. The long duration of drought has stressed statewide water resources and the economy, while fueling an extraordinary increase in wildfires. The effects of global warming on the regional climate include a hotter and drier climate, as well as earlier snowmelt, both of which exacerbate drought conditions. However, connections between a changing climate and how climate oscillations modulate regional water cycle extremes are not well understood. Here we analyze large-ensemble simulations of future climate change in California using the Community Earth System Model version 1 (CESM1)more » and multiple climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both intense drought and excessive flooding are projected to increase by at least 50% toward the end of the 21st century. Furthermore, the projected increase in water cycle extremes is associated with tighter relation to El Niño and Southern Oscillation (ENSO), particularly extreme El Niño and La Niña events, which modulates California’s climate not only through its warm and cold phases, but also ENSO’s precursor patterns.« less

Increasing water cycle extremes in California and relation to ENSO cycle under global warming

DOE PAGES

Yoon, Jin -Ho; Wang, S. -Y. Simon; Gillies, Robert R.; ...

2015-10-21

California has experienced its most severe drought in recorded history since the winter of 2013-2014. The long duration of drought has stressed statewide water resources and the economy, while fueling an extraordinary increase in wildfires. The effects of global warming on the regional climate include a hotter and drier climate, as well as earlier snowmelt, both of which exacerbate drought conditions. However, connections between a changing climate and how climate oscillations modulate regional water cycle extremes are not well understood. Here we analyze large-ensemble simulations of future climate change in California using the Community Earth System Model version 1 (CESM1)more » and multiple climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both intense drought and excessive flooding are projected to increase by at least 50% toward the end of the 21st century. Furthermore, the projected increase in water cycle extremes is associated with tighter relation to El Niño and Southern Oscillation (ENSO), particularly extreme El Niño and La Niña events, which modulates California’s climate not only through its warm and cold phases, but also ENSO’s precursor patterns.« less

The role of horizontal thermal advection in regulating wintertime mean and extreme temperatures over the central United States during the past and future

NASA Astrophysics Data System (ADS)

Wang, F.; Vavrus, S. J.

2017-12-01

Horizontal temperature advection plays an especially prominent role in affecting winter climate over continental interiors, where both climatological conditions and extreme weather are strongly regulated by transport of remote air masses. Central North America is one such region, and it experienced a major cold-air outbreak (CAO) a few years ago that some have related to amplified Arctic warming. Despite the known importance of dynamics in shaping the winter climate of this sector and the potential for climate change to modify heat transport, limited attention has been paid to the regional impact of thermal advection. Here, we use a reanalysis product and output from the Community Earth System Model's Large Ensemble to quantify the roles of zonal and meridional temperature advection over the central U. S. during winter, both in the late 20th and 21st centuries. We frame our findings as a "tug of war" between opposing influences of the two advection components and between these dynamical forcings vs. thermodynamic changes under greenhouse warming. For example, Arctic amplification leads to much warmer polar air masses, causing a moderation of cold-air advection into the central U. S., yet the model also simulates a wavier mean circulation and stronger northerly flow during CAOs, favoring lower regional temperatures. We also compare the predominant warming effect of zonal advection and overall cooling effect of meridional temperature advection as an additional tug of war. During both historical and future periods, zonal temperature advection is stronger than meridional advection over the Central U. S. The model simulates a future weakening of both zonal and meridional temperature advection, such that westerly flow provides less warming and northerly flow less cooling. On the most extreme warm days in the past and future, both zonal and meridional temperature advection have positive (warming) contributions. On the most extreme cold days, meridional cold air advection is more important than zonal warm air advection. CAOs in the future feature stronger northerly flow but less extreme temperatures (even relative to the warmer climate), exemplifying the complex competition between thermodynamic and dynamic influences.

Assessing Climate Change Impacts for Military Installations in the Southwest United States During the Warm Season

NASA Astrophysics Data System (ADS)

Castro, C.

2013-05-01

Arid and semi-arid regions are experiencing some of the most adverse impacts of climate change with increased heat waves, droughts, and extreme weather. These events will likely exacerbate socioeconomic and political instabilities in regions where the United States has vital strategic interests and ongoing military operations. The Southwest U.S. is strategically important in that it houses some of the most spatially expansive and important military installations in the country. The majority of severe weather events in the Southwest occur in association with the North American monsoon system (NAMS), and current observational record has shown a 'wet gets wetter and dry gets drier' global monsoon precipitation trend. We seek to evaluate the warm season extreme weather projection in the Southwest U.S., and how the extremes can affect Department of Defense (DoD) military facilities in that region. A baseline methodology is being developed to select extreme warm season weather events based on historical sounding data and moisture surge observations from Gulf of California. Numerical Weather Prediction (NWP)-type high resolution simulations will be performed for the extreme events identified from Weather Research and Forecast (WRF) model simulations initiated from IPCC GCM and NCAR Reanalysis data in both climate control and climate change periods. The magnitude in extreme event changes will be analyzed, and the synoptic forcing patterns of the future severe thunderstorms will provide a guide line to assess if the military installations in the Southwest will become more or less susceptible to severe weather in the future.

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

NASA Astrophysics Data System (ADS)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Regionally dependent summer heat wave response to increased surface temperature in the US

NASA Astrophysics Data System (ADS)

Lopez, H.; Dong, S.; Kirtman, B. P.; Goni, G. J.; Lee, S. K.; Atlas, R. M.; West, R.

2017-12-01

Climate projections for the 21st Century suggest an increase in the occurrence of heat waves. However, the time it takes for the externally forced signal of climate change to emerge against the background of natural variability (i.e., Time of Emergence, ToE) particularly on the regional scale makes reliable future projection of heat waves challenging. Here, we combine observations and model simulations under present and future climate forcing to assess internal variability versus external forcing in modulating US heat waves. We characterized the most common heat wave patterns over the US by the use of clustering of extreme events by their spatial distribution. For each heat wave cluster, we assess changes in the probability density function (PDF) of summer temperature extremes by modeling the PDF as a stochastically generated skewed (SGS) distribution. The probability of necessary causation for each heat wave cluster was also quantified, allowing to make assessments of heat extreme attribution to anthropogenic climate change. The results suggest that internal variability will dominate heat wave occurrence over the Great Plains with ToE occurring in the 2050s (2070s) and of occurrence of ratio of warm-to-cold extremes of 1.7 (1.7) for the Northern (Southern) Plains. In contrast, external forcing will dominate over the Western (Great Lakes) region with ToE occurring as early as in the 2020s (2030s) and warm-to-cold extremes ratio of 6.4 (10.2), suggesting caution in attributing heat extremes to external forcing due to their regional dependence.

Extreme events of perceived temperature over Europe: a projected northward extension of dangerous areas

NASA Astrophysics Data System (ADS)

Scoccimarro, Enrico; Fogli, Pier Giuseppe; Gualdi, Silvio

2017-04-01

It is well known that an increase of temperature over Europe, both in terms of averages and extremes, is expected within the current century. In order to consider health impacts under warm conditions, it is important to take into account the combined effect of temperature and humidity on the human body. To this aim a basic index - the humindex - representative of the perceived temperature, under different scenarios and periods, has been investigated in this study. A very low concomitance of extreme temperature events and extreme humindex events is found over the present climate, reinforcing the importance to investigate not only extreme temperature and relative humidity future projections but also the combination of the two parameters. A set of 10-km resolution regional climate simulations provided within the EUR-11 EURO-CORDEX multi-model effort, demonstrates ability in representing the intense and extreme events of the humindex over the present climate and to be eligible as a tool to quantify future changes in geographical patterns of exposed areas over Europe. An enlargement of the domain subject to dangerous conditions is found since the middle of the current century, reaching 60 degrees North when considering really extreme events. The most significant increase in humindex extreme events is found when comparing the 2066-2095 projections under rcp8.5 scenario, to the 1966-2005 period: bearing in mind that changes in relative humidity may either amplify or offset the health effects of temperature extremes, a less pronounced projected reduction of relative humidity intensity in the Northern part of the European domain, associated to extreme temperature and humindex, makes Northern Europe the most prone region to a local increase of the humindex extremes.

Persistent cold air outbreaks over North America in a warming climate

DOE PAGES

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

2015-03-30

This study examines future changes of cold air outbreaks (CAO) using a multi-model ensemble of global climate simulations from the Coupled Model Intercomparison Project Phase 5 as well as regional high resolution climate simulations. In the future, while robust decrease of CAO duration dominates in most regions, the magnitude of decrease over northwestern U.S. is much smaller than the surrounding regions. We identified statistically significant increases in sea level pressure during CAO events centering over Yukon, Alaska, and Gulf of Alaska that advects continental cold air to northwestern U.S., leading to blocking and CAO events. Changes in large scale circulationmore » contribute to about 50% of the enhanced sea level pressure anomaly conducive to CAO in northwestern U.S. in the future. High resolution regional simulations revealed potential contributions of increased existing snowpack to increased CAO in the near future over the Rocky Mountain, southwestern U.S., and Great Lakes areas through surface albedo effects, despite winter mean snow water equivalent decreases in the future. Overall, the multi-model projections emphasize that cold extremes do not completely disappear in a warming climate. Concomitant with the relatively smaller reduction in CAO events in northwestern U.S., the top 5 most extreme CAO events may still occur in the future, and wind chill warning will continue to have societal impacts in that region.« less

Spatially explicit scenario analysis for hydrologic services in an urbanizing agricultural watershed

NASA Astrophysics Data System (ADS)

Qiu, J.; Booth, E.; Carpenter, S. R.; Turner, M.

2013-12-01

The sustainability of hydrologic services (benefits to people generated by terrestrial ecosystem effects on freshwater) is challenged by changes in climate and land use. Despite the importance of hydrologic services, few studies have investigated how the provision of ecosystem services related to freshwater quantity and quality may vary in magnitude and spatial pattern for alternative future trajectories. Such analyses may provide useful information for sustaining freshwater resources in the face of a complex and uncertain future. We analyzed the supply of multiple hydrologic services from 2010 to 2070 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) What are the potential trajectories for the supply of hydrologic services under contrasting but plausible future scenarios? (ii) Where on the landscape is the delivery of hydrologic services most vulnerable to future changes? The Nested Watershed scenario represents extreme climate change (warmer temperatures and more frequent extreme events) and a concerted response from institutions, whereas in the Investment in Innovation scenario, climate change is less severe and technological innovations play a major role. Despite more extreme climate in the Nested Watershed scenario, all hydrologic services (i.e., freshwater supply, surface water quality, flood regulation) were maintained or enhanced (~30%) compared to the 2010 baseline, by strict government interventions that prioritized freshwater resources. Despite less extreme climate in the Investment in Innovation scenario and advances in green technology, only surface water quality and flood regulation were maintained or increased (~80%); freshwater supply declined by 25%, indicating a potential future tradeoff between water quality and quantity. Spatially, the locations of greatest vulnerability (i.e., decline) differed by service and among scenarios. In the Nested Watershed scenario, although freshwater supply and surface water quality were sustained or enhanced overall, these hydrologic services declined in ~60% and 20% of the landscape, respectively. The greatest improvement for most hydrologic services corresponded to areas of restored wetland, forest and perennial crops, which were less vulnerable to future degradation. In the Investment in Innovation scenario, freshwater supply declined in almost the entire watershed; improvement of surface water quality and flood regulation occurred mainly in urban areas, where highly engineered systems made them less vulnerable. Overall, our results indicated that hydrologic services will respond differently to future climate and land-use change, and sustaining one may involve tradeoffs of another. Technological progress can conserve particular services but might not be the panacea for the future. How society reacts in the face of changes can have an important role in determining the pathways to the future and the provision and spatial patterns of ecosystem services.

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.

2014-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Ensemble climate projections of mean and extreme rainfall over Vietnam

NASA Astrophysics Data System (ADS)

Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

2017-01-01

A systematic ensemble high resolution climate modelling study over Vietnam has been performed using the PRECIS model developed by the Hadley Center in UK. A 5 member subset of the 17-member Perturbed Physics Ensembles (PPE) of the Quantifying Uncertainty in Model Predictions (QUMP) project were simulated and analyzed. The PRECIS model simulations were conducted at a horizontal resolution of 25 km for the baseline period 1961-1990 and a future climate period 2061-2090 under scenario A1B. The results of model simulations show that the model was able to reproduce the mean state of climate over Vietnam when compared to observations. The annual cycles and seasonal averages of precipitation over different sub-regions of Vietnam show the ability of the model in also reproducing the observed peak and magnitude of monthly rainfall. The climate extremes of precipitation were also fairly well captured. Projections of future climate show both increases and decreases in the mean climate over different regions of Vietnam. The analyses of future extreme rainfall using the STARDEX precipitation indices show an increase in 90th percentile precipitation (P90p) over the northern provinces (15-25%) and central highland (5-10%) and over southern Vietnam (up to 5%). The total number of wet days (Prcp) indicates a decrease of about 5-10% all over Vietnam. Consequently, an increase in the wet day rainfall intensity (SDII), is likely inferring that the projected rainfall would be much more severe and intense which have the potential to cause flooding in some regions. Risks due to extreme drought also exist in other regions where the number of wet days decreases. In addition, the maximum 5 day consecutive rainfall (R5d) increases by 20-25% over northern Vietnam but decreases in a similar range over the central and southern Vietnam. These results have strong implications for the management water resources, agriculture, bio diversity and economy and serve as some useful findings to be considered by the policy makers within a wider range of climate uncertainties.

Regional changes in extreme monsoon rainfall deficit and excess in India

NASA Astrophysics Data System (ADS)

Pal, Indrani; Al-Tabbaa, Abir

2010-04-01

With increasing concerns about climate change, the need to understand the nature and variability of monsoon climatic conditions and to evaluate possible future changes becomes increasingly important. This paper deals with the changes in frequency and magnitudes of extreme monsoon rainfall deficiency and excess in India from 1871 to 2005. Five regions across India comprising variable climates were selected for the study. Apart from changes in individual regions, changing tendencies in extreme monsoon rainfall deficit and excess were also determined for the Indian region as a whole. The trends and their significance were assessed using non-parametric Mann-Kendall technique. The results show that intra-region variability for extreme monsoon seasonal precipitation is large and mostly exhibited a negative tendency leading to increasing frequency and magnitude of monsoon rainfall deficit and decreasing frequency and magnitude of monsoon rainfall excess.

The Engineering for Climate Extremes Partnership

NASA Astrophysics Data System (ADS)

Holland, G. J.; Tye, M. R.

2014-12-01

Hurricane Sandy and the recent floods in Thailand have demonstrated not only how sensitive the urban environment is to the impact of severe weather, but also the associated global reach of the ramifications. These, together with other growing extreme weather impacts and the increasing interdependence of global commercial activities point towards a growing vulnerability to weather and climate extremes. The Engineering for Climate Extremes Partnership brings academia, industry and government together with the goals encouraging joint activities aimed at developing new, robust, and well-communicated responses to this increasing vulnerability. Integral to the approach is the concept of 'graceful failure' in which flexible designs are adopted that protect against failure by combining engineering or network strengths with a plan for efficient and rapid recovery if and when they fail. Such an approach enables optimal planning for both known future scenarios and their assessed uncertainty.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Past exposure to climate extremes can inform future projections and guide management: coral reefs as a model system

NASA Astrophysics Data System (ADS)

Donner, S. D.

2016-12-01

Coral reefs are thought to be more sensitive to climate change than any other marine ecosystem. Episodes of mass coral bleaching, due to anomalously warm water temperatures, have led to coral mortality, declines in coral cover and shifts in the population of other reef-dwelling organisms. The onset of mass bleaching is typically predicted using accumulated heat stress, specifically when the SST exceeds a local climatological maximum by 1-2 °C for a month or more. However, recent evidence suggests that the threshold at which bleaching occurs depends on the past thermal experience of the coral reef and the composition of the coral community. This presentation describes the results of a long-term field and modelling research program evaluating the influence of climate experience on the susceptibility of coral reef ecosystems to future climate extremes. Modeling work identified Kiribati's equatorial Gilbert Islands, where the El Niño / Southern Oscillation drives year-to-year shifts in current strength, current direction and consequently ocean temperatures, as an ideal natural laboratory for studying ocean climate extremes. The field program then tracked changes in the coral communities over multiple heat stress events (e.g. 2004-5, 2009-10 El Niño) at a matrix of sites exposed to different levels of historical climate variability and human disturbance. Among the results is evidence that coral bleaching patterns are best predicted by the coefficient of variation of past SST, light exposure, and the presence of particular resilient coral taxa, rather than the standard heat stress metrics. The lessons of this research can be applicable other systems where past experience influences the response to climate extremes

The National Integrated Heat Health Information System (NIHHIS) as a Learning System for Extreme Heat: Evolving Future Resilience from Present Climate Extremes

NASA Astrophysics Data System (ADS)

Jones, H.; Trtanj, J.; Pulwarty, R. S.; Higgins, W.

2016-12-01

There is presently no consensus indicator for the effect of extreme heat on human health. At the early warning timescale, a variety of approaches to setting temperature thresholds (minimum, maximum, time-lagged) or more complex approaches (Heat Index, Thermal Comfort, etc...) for issuing alerts and warnings have been recommended by literature and implemented, leading to much heterogeneity. At longer timescales, efforts have been made to quantify potential future health outcomes using climate projections, but nonstationarity of the climate system, economy, and demography may invalidate many of the assumptions which were necessarily made in these studies. Furthermore, in our pursuit of developing the best models and indicators to represent the impacts of climate extremes, perhaps we have not paid enough attention to what makes them policy-relevant, responsive to changing assumptions, and targeted at elements that can actually be predicted. In response to this concern, a comprehensive approach to improving the impactfulness of these indicators is underway as part of the National Integrated Heat Health Information System (NIHHIS), which was initiated by NOAA and CDC, but has grown to include many other federal agency and non-governmental partners. NIHHIS is a framework that integrates what we know about extreme heat and health outcomes within a learning system - simultaneously informing early warning and long-term risk reduction prior to, during, and while recovering from extreme heat events. NIHHIS develops impactful evolutionary responses to climate extremes. Through ongoing regional engagements, we are applying the lessons of impact modeling studies to create learning systems in the Southwest, Northeast, Midwest, and soon other regions of the U.S. This session will provide a view of this process as it has been carried out in the Southwest region - focused on the transboundary (US-Mexico) region around El Paso, Texas, and the NIHHIS approach to indicators overall.

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.

Effects of Climate Change on Extreme Streamflow Risks in the Olympic National Park

NASA Astrophysics Data System (ADS)

Tohver, I. M.; Lee, S.; Hamlet, A.

2011-12-01

Conventionally, natural resource management practices are designed within the framework that past conditions serve as a baseline for future conditions. However, the warmer future climate projected for the Pacific Northwest will alter the region's flood and low flow risks, posing considerable challenges to resource managers in the Olympic National Forest (ONF) and Olympic National Park (ONP). Shifts in extreme streamflow will influence two key management objectives in the ONF and ONP: the protection of wildlife and the maintenance of road infrastructure. The ONF is charged with managing habitat for species listed under the Endangered Species Act (ESA), and with maintaining the network of forest roads and culverts. Climate-induced increases in flood severity will introduce additional challenges in road and culvert design. Furthermore, the aging road infrastructure and more extreme summer low flows will compromise aquatic habitats, intrinsic to the health of threatened and endangered fish species listed under the ESA. Current practice uses estimates of Q100 (or the peak flow with an estimated 100 year return frequency) as the standard metric for stream crossing design. Simple regression models relating annual precipitation and basin area to Q100 are used in the design process. Low flow estimates are based on historical streamflow data to calculate the 7-day consecutive lowest flow with a 10-year return interval, or 7Q10. Under the projections a changing climate, these methods for estimating extreme flows are ill equipped to capture the complex and spatially varying effects of seasonal changes in temperature, precipitation, and snowpack on extreme flow risk. As an alternative approach, this study applies a physically-based hydrologic model to estimate historical and future flood risk at 1/16th degree (latitude/longitude) resolution (about 32 km2). We downscaled climate data derived from 10 global climate models to use as input for the Variable Infiltration Capacity (VIC) model, a macro-scale hydrologic model, which simulates various hydrologic variables at a daily time step. Using the VIC estimates for baseflow and run-off, we calculated Q100 and 7Q10 for the historical period and under two emission scenarios, A1B and B1, at three future time intervals: the 2020s, the 2040s and the 2080s. We also calculated Q100 and 7Q10 at the spatial scale of the 12-digit hydrologic unit codes (HUCs) as delineated by the United States Geologic Survey. The results demonstrate the sensitivity of snowpack at mid-elevation basins to a warmer climate, resulting in more severe winter flooding and lower streamflows in the summertime. These ensemble estimates of extreme streamflows will serve as a tool for management practices by providing high-resolution maps of changing risk over the ONF and ONP.

Present-day irrigation mitigates heat extremes

NASA Astrophysics Data System (ADS)

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; Hirsch, Annette L.; Hauser, Mathias; Seneviratne, Sonia I.

2017-02-01

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.

Quantifying population exposure to airborne particulate matter during extreme events in California due to climate change

NASA Astrophysics Data System (ADS)

Mahmud, A.; Hixson, M.; Kleeman, M. J.

2012-02-01

The effect of climate change on population-weighted concentrations of particulate matter (PM) during extreme events was studied using the Parallel Climate Model (PCM), the Weather Research and Forecasting (WRF) model and the UCD/CIT 3-D photochemical air quality model. A "business as usual" (B06.44) global emissions scenario was dynamically downscaled for the entire state of California between the years 2000-2006 and 2047-2053. Air quality simulations were carried out for 1008 days in each of the present-day and future climate conditions using year-2000 emissions. Population-weighted concentrations of PM0.1, PM2.5, and PM10 total mass, components species, and primary source contributions were calculated for California and three air basins: the Sacramento Valley air basin (SV), the San Joaquin Valley air basin (SJV) and the South Coast Air Basin (SoCAB). Results over annual-average periods were contrasted with extreme events. Climate change between 2000 vs. 2050 did not cause a statistically significant change in annual-average population-weighted PM2.5 mass concentrations within any major sub-region of California in the current study. Climate change did alter the annual-average composition of the airborne particles in the SoCAB, with notable reductions of elemental carbon (EC; -3%) and organic carbon (OC; -3%) due to increased annual-average wind speeds that diluted primary concentrations from gasoline combustion (-3%) and food cooking (-4%). In contrast, climate change caused significant increases in population-weighted PM2.5 mass concentrations in central California during extreme events. The maximum 24-h average PM2.5 concentration experienced by an average person during a ten-year period in the SJV increased by 21% due to enhanced production of secondary particulate matter (manifested as NH4NO3). In general, climate change caused increased stagnation during future extreme pollution events, leading to higher exposure to diesel engines particles (+32%) and wood combustion particles (+14%) when averaging across the population of the entire state. Enhanced stagnation also isolated populations from distant sources such as shipping (-61%) during extreme events. The combination of these factors altered the statewide population-averaged composition of particles during extreme events, with EC increasing by 23%, nitrate increasing by 58%, and sulfate decreasing by 46%.

Quantifying population exposure to airborne particulate matter during extreme events in California due to climate change

NASA Astrophysics Data System (ADS)

Mahmud, A.; Hixson, M.; Kleeman, M. J.

2012-08-01

The effect of climate change on population-weighted concentrations of particulate matter (PM) during extreme pollution events was studied using the Parallel Climate Model (PCM), the Weather Research and Forecasting (WRF) model and the UCD/CIT 3-D photochemical air quality model. A "business as usual" (B06.44) global emissions scenario was dynamically downscaled for the entire state of California between the years 2000-2006 and 2047-2053. Air quality simulations were carried out for 1008 days in each of the present-day and future climate conditions using year-2000 emissions. Population-weighted concentrations of PM0.1, PM2.5, and PM10 total mass, components species, and primary source contributions were calculated for California and three air basins: the Sacramento Valley air basin (SV), the San Joaquin Valley air basin (SJV) and the South Coast Air Basin (SoCAB). Results over annual-average periods were contrasted with extreme events. The current study found that the change in annual-average population-weighted PM2.5 mass concentrations due to climate change between 2000 vs. 2050 within any major sub-region in California was not statistically significant. However, climate change did alter the annual-average composition of the airborne particles in the SoCAB, with notable reductions of elemental carbon (EC; -3%) and organic carbon (OC; -3%) due to increased annual-average wind speeds that diluted primary concentrations from gasoline combustion (-3%) and food cooking (-4%). In contrast, climate change caused significant increases in population-weighted PM2.5 mass concentrations in central California during extreme events. The maximum 24-h average PM2.5 concentration experienced by an average person during a ten-yr period in the SJV increased by 21% due to enhanced production of secondary particulate matter (manifested as NH4NO3). In general, climate change caused increased stagnation during future extreme pollution events, leading to higher exposure to diesel engines particles (+32%) and wood combustion particles (+14%) when averaging across the population of the entire state. Enhanced stagnation also isolated populations from distant sources such as shipping (-61%) during extreme events. The combination of these factors altered the statewide population-averaged composition of particles during extreme events, with EC increasing by 23 %, nitrate increasing by 58%, and sulfate decreasing by 46%.

An application of a hydraulic model simulator in flood risk assessment under changing climatic conditions

NASA Astrophysics Data System (ADS)

Doroszkiewicz, J. M.; Romanowicz, R. J.

2016-12-01

The standard procedure of climate change impact assessment on future hydrological extremes consists of a chain of consecutive actions, starting from the choice of GCM driven by an assumed CO2 scenario, through downscaling of climatic forcing to a catchment scale, estimation of hydrological extreme indices using hydrological modelling tools and subsequent derivation of flood risk maps with the help of a hydraulic model. Among many possible sources of uncertainty, the main are the uncertainties related to future climate scenarios, climate models, downscaling techniques and hydrological and hydraulic models. Unfortunately, we cannot directly assess the impact of these different sources of uncertainties on flood risk in future due to lack of observations of future climate realizations. The aim of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the processes involved, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-sections. The study shows that the application of a simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the uncertainty of future climate projections, an uncertainty of flow routing model, the propagation of that uncertainty through the hydraulic model, and finally, the uncertainty related to the derivation of flood risk maps.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed

Lowe, J A; Gregory, J M

2005-06-15

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

Planning for Adaptation to Climate Change in the City of Chicago

NASA Astrophysics Data System (ADS)

Wuebbles, D. J.; Hayhoe, K.; Coffee, J.; McGraw, J.; Parzen, J.

2008-12-01

Under Mayor Richard M. Daley's leadership, the City of Chicago initiated the Chicago Climate Action Plan (CCAP) to better understand local implications of global climate change in both higher and lower emissions scenarios, reduce greenhouse gas emissions, and implement programs to build future climate change resilience. The City approached this work not only as a way to make Chicago more adaptable in the future, but also to improve Chicago's quality of life today. The Chicago Climate Action Plan adopted stresses the importance of both reducing greenhouse gas emissions in Chicago and preparing for climate changes that may be unavoidable. Building off of the City's significant environmental programs and projects, and based on our analyses of the climate effects and impacts that improved the scientific understanding of future climate change impacts on Chicago, the City then developed a set of climate change adaptation strategies, resulting in the City of Chicago Climate Change Adaptation Summary. This document includes prioritization of climate change adaptations based on relative risk as well as framework strategies for those tactics categorized as "must do/early action." In early 2008, The Mayor's Office asked five Commissioners from its Green Steering Committee to chair adaptation work groups including: extreme heat; extreme precipitation; buildings, infrastructure and equipment; ecosystems; and leadership, planning and communications. Working with staff from relevant departments, sister agencies and other stakeholders, these work groups developed 39 basic adaptation work plans, including plans for enhancing the City's existing projects and programs that relate to climate change adaptation. Climate change adaptation work will be on-going in City Departments under the Mayor's Office leadership. The City intends to continually monitor and improve its response to climate change, resulting in an improved quality of life for Chicago residents.

Integrated modeling for assessment of energy-water system resilience under changing climate

NASA Astrophysics Data System (ADS)

Yan, E.; Veselka, T.; Zhou, Z.; Koritarov, V.; Mahalik, M.; Qiu, F.; Mahat, V.; Betrie, G.; Clark, C.

2016-12-01

Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. The IWESAF currently includes an extreme climate event generator to predict future extreme weather events, hydrologic and reservoir models, riverine temperature model, power plant water use simulator, and power grid operation and cost optimization model. The IWESAF can facilitate the interaction among the modeling systems and provide insights of the sustainability and resilience of the energy-water system under extreme climate events and economic consequence. The regional case demonstration in the Midwest region will be presented. The detailed information on some of individual modeling components will also be presented in several other abstracts submitted to AGU this year.

Thermodynamic and dynamic contributions to future changes in summer precipitation over Northeast Asia and Korea: a multi-RCM study

NASA Astrophysics Data System (ADS)

Lee, Donghyun; Min, Seung-Ki; Jin, Jonghun; Lee, Ji-Woo; Cha, Dong-Hyun; Suh, Myoung-Seok; Ahn, Joong-Bae; Hong, Song-You; Kang, Hyun-Suk; Joh, Minsu

2017-12-01

This study examines future changes in precipitation over Northeast Asia and Korea using five regional climate model (RCM) simulations driven by single global climate model (GCM) under two representative concentration pathway (RCP) emission scenarios. Focusing on summer season (June-July-August) when heavy rains dominate in this region, future changes in precipitation and associated variables including temperature, moisture, and winds are analyzed by comparing future conditions (2071-2100) with a present climate (1981-2005). Physical mechanisms are examined by analyzing moisture flux convergence at 850 hPa level, which is found to have a close relationship to precipitation and by assessing contribution of thermodynamic effect (TH, moisture increase due to warming) and dynamic effect (DY, atmospheric circulation change) to changes in the moisture flux convergence. Overall background warming and moistening are projected over the Northeast Asia with a good inter-RCM agreement, indicating dominant influence of the driving GCM. Also, RCMs consistently project increases in the frequency of heavy rains and the intensification of extreme precipitation over South Korea. Analysis of moisture flux convergence reveals competing impacts between TH and DY. The TH effect contributes to the overall increases in mean precipitation over Northeast Asia and in extreme precipitation over South Korea, irrespective of models and scenarios. However, DY effect is found to induce local-scale precipitation decreases over the central part of the Korean Peninsula with large inter-RCM and inter-scenario differences. Composite analysis of daily anomaly synoptic patterns indicates that extreme precipitation events are mainly associated with the southwest to northeast evolution of large-scale low-pressure system in both present and future climates.

Impacts of climate change on precipitation and discharge extremes through the use of statistical downscaling approaches in a Mediterranean basin.

PubMed

Piras, Monica; Mascaro, Giuseppe; Deidda, Roberto; Vivoni, Enrique R

2016-02-01

Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5km(2)), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America.

PubMed

Vörösmarty, Charles J; Bravo de Guenni, Lelys; Wollheim, Wilfred M; Pellerin, Brian; Bjerklie, David; Cardoso, Manoel; D'Almeida, Cassiano; Green, Pamela; Colon, Lilybeth

2013-11-13

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960-2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

Uncertainties in hydrological extremes projections and its effects on decision-making processes in an Amazonian sub-basin.

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lazaro Siqueira Junior, Jose

2013-04-01

Uncertainties in Climate Change projections are affected by irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process. Such uncertainties affect the impact studies, complicating the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. Through these kinds of analyses it is possible to identify critical issues, which must be deeper studied. For this study we used several future's projections from General Circulation Models to feed a Hydrological Model, applied to the Amazonian sub-basin of Ji-Paraná. Hydrological Model integrations are performed for present historical time (1970-1990) and for future period (2010-2100). Extreme values analyses are performed to each simulated time series and results are compared with extremes events in present time. A simple approach to identify potential vulnerabilities consists of evaluating the hydrologic system response to climate variability and extreme events observed in the past, comparing them with the conditions projected for the future. Thus it is possible to identify critical issues that need attention and more detailed studies. For the goal of this work, we used socio-economic data from Brazilian Institute of Geography and Statistics, the Operator of the National Electric System, the Brazilian National Water Agency and scientific and press published information. This information is used to characterize impacts associated to extremes hydrological events in the basin during the present historical time and to evaluate potential impacts in the future face to the different hydrological projections. Results show inter-model variability results in a broad dispersion on projected extreme's values. The impact of such dispersion is differentiated for different aspects of socio-economic and natural systems and must be carefully addressed in order to help in decision-making processes.

Development of a Simple Framework to Assess Hydrological Extremes using Solely Climate Data

NASA Astrophysics Data System (ADS)

Foulon, E.; Gagnon, P.; Rousseau, A. N.

2014-12-01

Extreme flow conditions such as droughts and floods are in general the direct consequences of short- to long-term weather/climate anomalies. For example, in southern Quebec, Canada, winter and summer 7-day low flows are due to summer and fall precipitations. Which prompts the question: is it possible to assess future extreme flow conditions from meteorological/climate indices or should we rely on the classical approach of using outputs of climate models as input to a hydrological model? The objective of this study is to assess six hydrological indices describing extreme flows at the watershed scale (Qmax, Qmin;7d, Qmin;30d for two seasons: winter and summer) using local climate indices without relying on the aforementioned classical approach. To establish the relationship between climate and hydrological indices, daily precipitations, minimum and maximum temperatures from 89 climate projections are used as inputs to a distributed hydrological model. River flows are simulated at the outlet of the Yamaska and Bécancour watersheds in Québec for the 1961-2100 periods. To identify the best predictors, hydrological indices are extracted from the flow series, and climate indices are computed for different time intervals (from a day up to four years). The difference between four-month, cumulative, climatic demand (P-ETP) explains 69% of the 7-day summer low flow during the calibration process. For both watersheds, preliminary findings indicate that the selected indices explain, on average, 38 and 60% of the variability of high- and low-flow indices, respectively. Overall, the results clearly illustrate that the change in the hydrological indices can be detected through the concurrent trends in the climate indices. The use of many climate projections ensures the relationships are not simulation-dependent and shows summer events are particularly at risk with increasing high flows and decreasing low flows. The development of a simple predictive tool to assess the impact of climate change on flows represents one of the major spin-off benefits of this study and may prooveto be useful to municipalities concerned with source water and flood management. Future work includes development of additional climate indices and application of the framework to more watersheds.

Climate change impacts on rainfall extremes and urban drainage: state-of-the-art review

NASA Astrophysics Data System (ADS)

Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van

2013-04-01

Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions; adaptive approach that provides inherent flexibility and reversibility and avoids closing off options; importance of active learning. References: Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012). Impacts of climate change on rainfall extremes and urban drainage. IWA Publishing, 252 p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263 Willems, P., Arnbjerg-Nielsen, K., Olsson, J., Nguyen, V.T.V. (2012), 'Climate change impact assessment on urban rainfall extremes and urban drainage: methods and shortcomings', Atmospheric Research, 103, 106-118

The Importance of Studying Past Extreme Floods to Prepare for Uncertain Future Extremes

NASA Astrophysics Data System (ADS)

Burges, S. J.

2016-12-01

Hoyt and Langbein, 1955 in their book `Floods' wrote: " ..meteorologic and hydrologic conditions will combine to produce superfloods of unprecedented magnitude. We have every reason to believe that in most rivers past floods may not be an accurate measure of ultimate flood potentialities. It is this superflood with which we are always most concerned". I provide several examples to offer some historical perspective on assessing extreme floods. In one example, flooding in the Miami Valley, OH in 1913 claimed 350 lives. The engineering and socio-economic challenges facing the Morgan Engineering Co in how to mitigate against future flood damage and loss of life when limited information was available provide guidance about ways to face an uncertain hydroclimate future, particularly one of a changed climate. A second example forces us to examine mixed flood populations and illustrates the huge uncertainty in assigning flood magnitude and exceedance probability to extreme floods in such cases. There is large uncertainty in flood frequency estimates; knowledge of the total flood hydrograph, not the peak flood flow rate alone, is what is needed for hazard mitigation assessment or design. Some challenges in estimating the complete flood hydrograph in an uncertain future climate, including demands on hydrologic models and their inputs, are addressed.

Intercomparison of hydrological model structures and calibration approaches in climate scenario impact projections

NASA Astrophysics Data System (ADS)

Vansteenkiste, Thomas; Tavakoli, Mohsen; Ntegeka, Victor; De Smedt, Florimond; Batelaan, Okke; Pereira, Fernando; Willems, Patrick

2014-11-01

The objective of this paper is to investigate the effects of hydrological model structure and calibration on climate change impact results in hydrology. The uncertainty in the hydrological impact results is assessed by the relative change in runoff volumes and peak and low flow extremes from historical and future climate conditions. The effect of the hydrological model structure is examined through the use of five hydrological models with different spatial resolutions and process descriptions. These were applied to a medium sized catchment in Belgium. The models vary from the lumped conceptual NAM, PDM and VHM models over the intermediate detailed and distributed WetSpa model to the fully distributed MIKE SHE model. The latter model accounts for the 3D groundwater processes and interacts bi-directionally with a full hydrodynamic MIKE 11 river model. After careful and manual calibration of these models, accounting for the accuracy of the peak and low flow extremes and runoff subflows, and the changes in these extremes for changing rainfall conditions, the five models respond in a similar way to the climate scenarios over Belgium. Future projections on peak flows are highly uncertain with expected increases as well as decreases depending on the climate scenario. The projections on future low flows are more uniform; low flows decrease (up to 60%) for all models and for all climate scenarios. However, the uncertainties in the impact projections are high, mainly in the dry season. With respect to the model structural uncertainty, the PDM model simulates significantly higher runoff peak flows under future wet scenarios, which is explained by its specific model structure. For the low flow extremes, the MIKE SHE model projects significantly lower low flows in dry scenario conditions in comparison to the other models, probably due to its large difference in process descriptions for the groundwater component, the groundwater-river interactions. The effect of the model calibration was tested by comparing the manual calibration approach with automatic calibrations of the VHM model based on different objective functions. The calibration approach did not significantly alter the model results for peak flow, but the low flow projections were again highly influenced. Model choice as well as calibration strategy hence have a critical impact on low flows, more than on peak flows. These results highlight the high uncertainty in low flow modelling, especially in a climate change context.

Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Projected changes to precipitation extremes over the Canadian Prairies using multi-RCM ensemble

NASA Astrophysics Data System (ADS)

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

2016-12-01

Information on projected changes to precipitation extremes is needed for future planning of urban drainage infrastructure and storm water management systems and to sustain socio-economic activities and ecosystems at local, regional and other scales of interest. This study explores the projected changes to seasonal (April-October) precipitation extremes at daily, hourly and sub-hourly scales over the Canadian Prairie Provinces of Alberta, Saskatchewan, and Manitoba, based on the North American Regional Climate Change Assessment Program multi-Regional Climate Model (RCM) ensemble and regional frequency analysis. The performance of each RCM is evaluated regarding boundary and performance errors to study various sources of uncertainties and the impact of large-scale driving fields. In the absence of RCM-simulated short-duration extremes, a framework is developed to derive changes to extremes of these durations. Results from this research reveal that the relative changes in sub-hourly extremes are higher than those in the hourly and daily extremes. Overall, projected changes in precipitation extremes are larger for southeastern parts of this region than southern and northern areas, and smaller for southwestern and western parts of the study area. Keywords: climate change, precipitation extremes, regional frequency analysis, NARCCAP, Canadian Prairie provinces

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

NASA Astrophysics Data System (ADS)

Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Uncertainties in observations and climate projections for the North East India

NASA Astrophysics Data System (ADS)

Soraisam, Bidyabati; Karumuri, Ashok; D. S., Pai

2018-01-01

The Northeast-India has undergone many changes in climatic-vegetation related issues in the last few decades due to increased human activities. However, lack of observations makes it difficult to ascertain the climate change. The study involves the mean, seasonal cycle, trend and extreme-month analysis for summer-monsoon and winter seasons of observed climate data from Indian Meteorological Department (1° × 1°) and Aphrodite & CRU-reanalysis (both 0.5° × 0.5°), and five regional-climate-model simulations (LMDZ, MPI, GFDL, CNRM and ACCESS) data from AR5/CORDEX-South-Asia (0.5° × 0.5°). Long-term (1970-2005) observed, minimum and maximum monthly temperature and precipitation, and the corresponding CORDEX-South-Asia data for historical (1970-2005) and future-projections of RCP4.5 (2011-2060) have been analyzed for long-term trends. A large spread is found across the models in spatial distributions of various mean maximum/minimum climate statistics, though models capture a similar trend in the corresponding area-averaged seasonal cycles qualitatively. Our observational analysis broadly suggests that there is no significant trend in rainfall. Significant trends are observed in the area-averaged minimum temperature during winter. All the CORDEX-South-Asia simulations for the future project either a decreasing insignificant trend in seasonal precipitation, but increasing trend for both seasonal maximum and minimum temperature over the northeast India. The frequency of extreme monthly maximum and minimum temperature are projected to increase. It is not clear from future projections how the extreme rainfall months during JJAS may change. The results show the uncertainty exists in the CORDEX-South-Asia model projections over the region in spite of the relatively high resolution.

A large set of potential past, present and future hydro-meteorological time series for the UK

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Dadson, Simon J.; Coxon, Gemma; Bussi, Gianbattista; Freer, James; Kay, Alison L.; Massey, Neil R.; Sparrow, Sarah N.; Wallom, David C. H.; Allen, Myles R.; Hall, Jim W.

2018-01-01

Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900-2006), (ii) five near-future scenarios (2020-2049) and (iii) five far-future scenarios (2070-2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1-30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK.

Future crop production threatened by extreme heat

NASA Astrophysics Data System (ADS)

Siebert, Stefan; Ewert, Frank

2014-04-01

Heat is considered to be a major stress limiting crop growth and yields. While important findings on the impact of heat on crop yield have been made based on experiments in controlled environments, little is known about the effects under field conditions at larger scales. The study of Deryng et al (2014 Global crop yield response to extreme heat stress under multiple climate change futures Environ. Res. Lett. 9 034011), analysing the impact of heat stress on maize, spring wheat and soya bean under climate change, represents an important contribution to this emerging research field. Uncertainties in the occurrence of heat stress under field conditions, plant responses to heat and appropriate adaptation measures still need further investigation.

Irrigation mitigates against heat extremes

NASA Astrophysics Data System (ADS)

Thiery, Wim; Fischer, Erich; Visser, Auke; Hirsch, Annette L.; Davin, Edouard L.; Lawrence, Dave; Hauser, Mathias; Seneviratne, Sonia I.

2017-04-01

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use gridded observations and ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on hot extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Finally we find that present-day irrigation is partly masking GHG-induced warming of extreme temperatures, with particularly strong effects in South Asia. Our results overall underline that irrigation substantially reduces our exposure to hot temperature extremes and highlight the need to account for irrigation in future climate projections.

Using Climate Science to Inform Local Planning: Challenges and Successes from the Field

NASA Astrophysics Data System (ADS)

Hayhoe, K.

2014-12-01

Much of our society, including our agriculture, our dependence on natural resources, and our infrastructure, is built on the assumption that individual weather events and average conditions may vary from year to year, but over the long term the climate of a given region can be predicted based on past climate "normals". This assumption is no longer valid; today, human-induced climate change is altering average conditions as well as the risk of many types of weather extremes. Observed trends and projected future changes in mean climate and in the frequency and severity of temperature extremes, heat waves, heavy precipitation events, coastal flooding, and storms are clearly documented in the Third U.S. National Climate Assessment, as well as by a host of other regional impact assessments. While future projections are inherently uncertain, these assessments make one fact clear: future planning for any sector or region affected by climate change that fails to take into account long-term trends will end up with the wrong answer. This concept of non-stationarity, that future climate will differ from that experienced in the past, challenges regional planners, water managers, city managers and engineers to incorporate future climate change into present-day planning. From the perspective of scientists, translating climate projections into information that can be used by stakeholders and decision-makers presents a challenge of equal magnitude. Here, I draw on my experience working with the agriculture, ecosystem, energy, health, infrastructure, insurance, and water sectors to propose a framework for, and highlight some of the main challenges inherent to, incorporating climate information into practical, on-the-ground planning at the local to regional scale. This approach, which we have developed through working with a range of cities, states, and regions including Austin, Cambridge, California, Chicago, Delaware, the Northeast, and most recently Washington DC, is based on identifying known vulnerabilities within the systems of interest, and developing appropriate information compatible with existing planning mechanisms to ensure the relevance and utility of the climate information for increasing resilience and reducing vulnerability to climate risks.

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

NASA Astrophysics Data System (ADS)

Lenderink, Geert; Attema, Jisk

2015-08-01

Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Interaction between Soil Moisture and Air Temperature in the Mississippi River Basin

EPA Science Inventory

Increasing air temperatures are expected to continue in the future. The relation between soil moisture and near surface air temperature is significant for climate change and climate extremes. Evaluation of the relations between soil moisture and temperature was performed by devel...

Assessment of climate change downscaling and non-stationarity on the spatial pattern of a mangrove ecosystem in an arid coastal region of southern Iran

NASA Astrophysics Data System (ADS)

Etemadi, Halimeh; Samadi, S. Zahra; Sharifikia, Mohammad; Smoak, Joseph M.

2016-10-01

Mangrove wetlands exist in the transition zone between terrestrial and marine environments and have remarkable ecological and socio-economic value. This study uses climate change downscaling to address the question of non-stationarity influences on mangrove variations (expansion and contraction) within an arid coastal region. Our two-step approach includes downscaling models and uncertainty assessment, followed by a non-stationary and trend procedure using the Extreme Value Analysis (extRemes code). The Long Ashton Research Station Weather Generator (LARS-WG) model along with two different general circulation model (GCMs) (MIRH and HadCM3) were used to downscale climatic variables during current (1968-2011) and future (2011-2030, 2045-2065, and 2080-2099) periods. Parametric and non-parametric bootstrapping uncertainty tests demonstrated that the LARS-WGS model skillfully downscaled climatic variables at the 95 % significance level. Downscaling results using MIHR model show that minimum and maximum temperatures will increase in the future (2011-2030, 2045-2065, and 2080-2099) during winter and summer in a range of +4.21 and +4.7 °C, and +3.62 and +3.55 °C, respectively. HadCM3 analysis also revealed an increase in minimum (˜+3.03 °C) and maximum (˜+3.3 °C) temperatures during wet and dry seasons. In addition, we examined how much mangrove area has changed during the past decades and, thus, if climate change non-stationarity impacts mangrove ecosystems. Our results using remote sensing techniques and the non-parametric Mann-Whitney two-sample test indicated a sharp decline in mangrove area during 1972,1987, and 1997 periods ( p value = 0.002). Non-stationary assessment using the generalized extreme value (GEV) distributions by including mangrove area as a covariate further indicated that the null hypothesis of the stationary climate (no trend) should be rejected due to the very low p values for precipitation ( p value = 0.0027), minimum ( p value = 0.000000029) and maximum ( p value = 0.00016) temperatures. Based on non-stationary analysis and an upward trend in downscaled temperature extremes, climate change may control mangrove development in the future.

The nonstationary impact of local temperature changes and ENSO on extreme precipitation at the global scale

NASA Astrophysics Data System (ADS)

Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun

2017-12-01

The El Niño-Southern Oscillation (ENSO) and local temperature are important drivers of extreme precipitation. Understanding the impact of ENSO and temperature on the risk of extreme precipitation over global land will provide a foundation for risk assessment and climate-adaptive design of infrastructure in a changing climate. In this study, nonstationary generalized extreme value distributions were used to model extreme precipitation over global land for the period 1979-2015, with ENSO indicator and temperature as covariates. Risk factors were estimated to quantify the contrast between the influence of different ENSO phases and temperature. The results show that extreme precipitation is dominated by ENSO over 22% of global land and by temperature over 26% of global land. With a warming climate, the risk of high-intensity daily extreme precipitation increases at high latitudes but decreases in tropical regions. For ENSO, large parts of North America, southern South America, and southeastern and northeastern China are shown to suffer greater risk in El Niño years, with more than double the chance of intense extreme precipitation in El Niño years compared with La Niña years. Moreover, regions with more intense precipitation are more sensitive to ENSO. Global climate models were used to investigate the changing relationship between extreme precipitation and the covariates. The risk of extreme, high-intensity precipitation increases across high latitudes of the Northern Hemisphere but decreases in middle and lower latitudes under a warming climate scenario, and will likely trigger increases in severe flooding and droughts across the globe. However, there is some uncertainties associated with the influence of ENSO on predictions of future extreme precipitation, with the spatial extent and risk varying among the different models.

Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

2005-12-01

Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.

Asymmetry of projected increases in extreme temperature distributions

PubMed Central

Kodra, Evan; Ganguly, Auroop R.

2014-01-01

A statistical analysis reveals projections of consistently larger increases in the highest percentiles of summer and winter temperature maxima and minima versus the respective lowest percentiles, resulting in a wider range of temperature extremes in the future. These asymmetric changes in tail distributions of temperature appear robust when explored through 14 CMIP5 climate models and three reanalysis datasets. Asymmetry of projected increases in temperature extremes generalizes widely. Magnitude of the projected asymmetry depends significantly on region, season, land-ocean contrast, and climate model variability as well as whether the extremes of consideration are seasonal minima or maxima events. An assessment of potential physical mechanisms provides support for asymmetric tail increases and hence wider temperature extremes ranges, especially for northern winter extremes. These results offer statistically grounded perspectives on projected changes in the IPCC-recommended extremes indices relevant for impacts and adaptation studies. PMID:25073751

Trees tolerate an extreme heatwave via sustained transpirational cooling and increased leaf thermal tolerance.

PubMed

Drake, John E; Tjoelker, Mark G; Vårhammar, Angelica; Medlyn, Belinda E; Reich, Peter B; Leigh, Andrea; Pfautsch, Sebastian; Blackman, Chris J; López, Rosana; Aspinwall, Michael J; Crous, Kristine Y; Duursma, Remko A; Kumarathunge, Dushan; De Kauwe, Martin G; Jiang, Mingkai; Nicotra, Adrienne B; Tissue, David T; Choat, Brendan; Atkin, Owen K; Barton, Craig V M

2018-06-01

Heatwaves are likely to increase in frequency and intensity with climate change, which may impair tree function and forest C uptake. However, we have little information regarding the impact of extreme heatwaves on the physiological performance of large trees in the field. Here, we grew Eucalyptus parramattensis trees for 1 year with experimental warming (+3°C) in a field setting, until they were greater than 6 m tall. We withheld irrigation for 1 month to dry the surface soils and then implemented an extreme heatwave treatment of 4 consecutive days with air temperatures exceeding 43°C, while monitoring whole-canopy exchange of CO 2 and H 2 O, leaf temperatures, leaf thermal tolerance, and leaf and branch hydraulic status. The heatwave reduced midday canopy photosynthesis to near zero but transpiration persisted, maintaining canopy cooling. A standard photosynthetic model was unable to capture the observed decoupling between photosynthesis and transpiration at high temperatures, suggesting that climate models may underestimate a moderating feedback of vegetation on heatwave intensity. The heatwave also triggered a rapid increase in leaf thermal tolerance, such that leaf temperatures observed during the heatwave were maintained within the thermal limits of leaf function. All responses were equivalent for trees with a prior history of ambient and warmed (+3°C) temperatures, indicating that climate warming conferred no added tolerance of heatwaves expected in the future. This coordinated physiological response utilizing latent cooling and adjustment of thermal thresholds has implications for tree tolerance of future climate extremes as well as model predictions of future heatwave intensity at landscape and global scales. © 2018 John Wiley & Sons Ltd.

Aerosol effect on climate extremes in Europe under different future scenarios

NASA Astrophysics Data System (ADS)

Sillmann, J.; Pozzoli, L.; Vignati, E.; Kloster, S.; Feichter, J.

2013-05-01

This study investigates changes in extreme temperature and precipitation events under different future scenarios of anthropogenic aerosol emissions (i.e., SO2 and black and organic carbon) simulated with an aerosol-climate model (ECHAM5-HAM) with focus on Europe. The simulations include a maximum feasible aerosol reduction (MFR) scenario and a current legislation emission (CLEmod) scenario where Europe implements the MFR scenario, but the rest of the world follows the current legislation scenario and a greenhouse gas scenario. The strongest changes relative to the year 2000 are projected for the MFR scenario, in which the global aerosol reduction greatly enforces the general warming effect due to greenhouse gases and results in significant increases of temperature and precipitation extremes in Europe. Regional warming effects can also be identified from aerosol reductions under the CLEmodscenario. This becomes most obvious in the increase of the hottest summer daytime temperatures in Northern Europe.

Future soil moisture and temperature extremes imply expanding suitability for rainfed agriculture in temperate drylands

USGS Publications Warehouse

Bradford, John B.; Schlaepfer, Daniel R.; Lauenroth, William K.; Yackulic, Charles B.; Duniway, Michael C.; Hall, Sonia A.; Jia, Gensuo; Jamiyansharav, Khishigbayar; Munson, Seth M.; Wilson, Scott D.; Tietjen, Britta

2017-01-01

The distribution of rainfed agriculture is expected to respond to climate change and human population growth. However, conditions that support rainfed agriculture are driven by interactions among climate, including climate extremes, and soil moisture availability that have not been well defined. In the temperate regions that support much of the world’s agriculture, these interactions are complicated by seasonal temperature fluctuations that can decouple climate and soil moisture. Here, we show that suitability to support rainfed agriculture can be effectively represented by the interactive effects of just two variables: suitability increases where warm conditions occur with wet soil, and suitability decreases with extreme high temperatures. 21st century projections based on ecohydrological modeling of downscaled climate forecasts imply geographic shifts and overall increases in the area suitable for rainfed agriculture in temperate regions, especially at high latitudes, and pronounced, albeit less widespread, declines in suitable areas in low latitude drylands, especially in Europe. These results quantify the integrative direct and indirect impact of rising temperatures on rainfed agriculture.

Extreme temperature events on Greenland in observations and the MAR regional climate model

NASA Astrophysics Data System (ADS)

Leeson, Amber A.; Eastoe, Emma; Fettweis, Xavier

2018-03-01

Meltwater from the Greenland Ice Sheet contributed 1.7-6.12 mm to global sea level between 1993 and 2010 and is expected to contribute 20-110 mm to future sea level rise by 2100. These estimates were produced by regional climate models (RCMs) which are known to be robust at the ice sheet scale but occasionally miss regional- and local-scale climate variability (e.g. Leeson et al., 2017; Medley et al., 2013). To date, the fidelity of these models in the context of short-period variability in time (i.e. intra-seasonal) has not been fully assessed, for example their ability to simulate extreme temperature events. We use an event identification algorithm commonly used in extreme value analysis, together with observations from the Greenland Climate Network (GC-Net), to assess the ability of the MAR (Modèle Atmosphérique Régional) RCM to reproduce observed extreme positive-temperature events at 14 sites around Greenland. We find that MAR is able to accurately simulate the frequency and duration of these events but underestimates their magnitude by more than half a degree Celsius/kelvin, although this bias is much smaller than that exhibited by coarse-scale Era-Interim reanalysis data. As a result, melt energy in MAR output is underestimated by between 16 and 41 % depending on global forcing applied. Further work is needed to precisely determine the drivers of extreme temperature events, and why the model underperforms in this area, but our findings suggest that biases are passed into MAR from boundary forcing data. This is important because these forcings are common between RCMs and their range of predictions of past and future ice sheet melting. We propose that examining extreme events should become a routine part of global and regional climate model evaluation and that addressing shortcomings in this area should be a priority for model development.

Atmospheric Rivers, Climate Change, and the Howard Hanson Dam

NASA Astrophysics Data System (ADS)

Warner, M.; Mass, C.; Shaffer, K.; Brettman, K.

2017-12-01

All wintertime extreme precipitation and major flooding events in Western Washington are associated with Atmospheric Rivers (ARs), narrow bands of elevated integrated water vapor transport (IVT) stretching from the tropical Pacific Ocean to the Pacific Northwest coast. Several studies over the last decade have suggested that climate change could impact the intensity, frequency, timing, and structure of Pacific Northwest extreme precipitation. The Howard Hanson Dam is situated on the Green River in the central Cascade Mountains in Western Washington and is operated by the US Army Corps of Engineers (USACE) in Seattle. The reservoir behind the dam has two functions: It is the main water supply for the city of Tacoma and is filled during the summer months, and it is empty during winter months when it is used for flood risk management during AR events, protecting billions of dollars of infrastructure downstream. The reservoir is maintained by the Cascade Mountains' abundant winter snowpack and precipitation. Since the reservoir behind Howard Hanson Dam must be empty before the flood season starts and is reliant on snowpack and precipitation to fill in late spring, impacts due to climate change are important for how the USACE operates and manages flood risk and water supply in the future. This work describes changes in the structure, climatology, and seasonality of cool-season atmospheric rivers influencing the west coast of North America by examining the projections of Coupled Model Intercomparison Project 5 (CMIP5) climate simulations forced by the Representative Concentration Pathway (RCP) 8.5 scenario. There are only slight changes in AR frequency and seasonality between historical (1970-1999) and future (2070-2099) periods considering the most extreme days (99th percentile) in integrated water vapor transport (IVT) along the West Coast, particularly along the southern part of the U.S. west coast, where some changes in the most extreme events are statistically significant. In contrast, using the number of future days exceeding the historical 99th percentile IVT threshold produces statistically significant increases in the frequency of extreme IVT events for all winter months. The peak in future AR days appears to occur approximately one month earlier.

Deadly heat waves projected in the densely populated agricultural regions of South Asia.

PubMed

Im, Eun-Soon; Pal, Jeremy S; Eltahir, Elfatih A B

2017-08-01

The risk associated with any climate change impact reflects intensity of natural hazard and level of human vulnerability. Previous work has shown that a wet-bulb temperature of 35°C can be considered an upper limit on human survivability. On the basis of an ensemble of high-resolution climate change simulations, we project that extremes of wet-bulb temperature in South Asia are likely to approach and, in a few locations, exceed this critical threshold by the late 21st century under the business-as-usual scenario of future greenhouse gas emissions. The most intense hazard from extreme future heat waves is concentrated around densely populated agricultural regions of the Ganges and Indus river basins. Climate change, without mitigation, presents a serious and unique risk in South Asia, a region inhabited by about one-fifth of the global human population, due to an unprecedented combination of severe natural hazard and acute vulnerability.

Increasing potential for intense tropical and subtropical thunderstorms under global warming.

PubMed

Singh, Martin S; Kuang, Zhiming; Maloney, Eric D; Hannah, Walter M; Wolding, Brandon O

2017-10-31

Intense thunderstorms produce rapid cloud updrafts and may be associated with a range of destructive weather events. An important ingredient in measures of the potential for intense thunderstorms is the convective available potential energy (CAPE). Climate models project increases in summertime mean CAPE in the tropics and subtropics in response to global warming, but the physical mechanisms responsible for such increases and the implications for future thunderstorm activity remain uncertain. Here, we show that high percentiles of the CAPE distribution (CAPE extremes) also increase robustly with warming across the tropics and subtropics in an ensemble of state-of-the-art climate models, implying strong increases in the frequency of occurrence of environments conducive to intense thunderstorms in future climate projections. The increase in CAPE extremes is consistent with a recently proposed theoretical model in which CAPE depends on the influence of convective entrainment on the tropospheric lapse rate, and we demonstrate the importance of this influence for simulated CAPE extremes using a climate model in which the convective entrainment rate is varied. We further show that the theoretical model is able to account for the climatological relationship between CAPE and a measure of lower-tropospheric humidity in simulations and in observations. Our results provide a physical basis on which to understand projected future increases in intense thunderstorm potential, and they suggest that an important mechanism that contributes to such increases may be present in Earth's atmosphere. Published under the PNAS license.

Increasing potential for intense tropical and subtropical thunderstorms under global warming

PubMed Central

Kuang, Zhiming; Maloney, Eric D.; Hannah, Walter M.; Wolding, Brandon O.

2017-01-01

Intense thunderstorms produce rapid cloud updrafts and may be associated with a range of destructive weather events. An important ingredient in measures of the potential for intense thunderstorms is the convective available potential energy (CAPE). Climate models project increases in summertime mean CAPE in the tropics and subtropics in response to global warming, but the physical mechanisms responsible for such increases and the implications for future thunderstorm activity remain uncertain. Here, we show that high percentiles of the CAPE distribution (CAPE extremes) also increase robustly with warming across the tropics and subtropics in an ensemble of state-of-the-art climate models, implying strong increases in the frequency of occurrence of environments conducive to intense thunderstorms in future climate projections. The increase in CAPE extremes is consistent with a recently proposed theoretical model in which CAPE depends on the influence of convective entrainment on the tropospheric lapse rate, and we demonstrate the importance of this influence for simulated CAPE extremes using a climate model in which the convective entrainment rate is varied. We further show that the theoretical model is able to account for the climatological relationship between CAPE and a measure of lower-tropospheric humidity in simulations and in observations. Our results provide a physical basis on which to understand projected future increases in intense thunderstorm potential, and they suggest that an important mechanism that contributes to such increases may be present in Earth’s atmosphere. PMID:29078312

Present-day irrigation mitigates heat extremes

DOE PAGES

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; ...

2017-02-16

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less

MODIS EVI as a Surrogate for Net Primary Production across Precipitation Regimes

USDA-ARS?s Scientific Manuscript database

According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patte...

Characterizing the impact of projected changes in climate and air quality on human exposures to ozone.

PubMed

Dionisio, Kathie L; Nolte, Christopher G; Spero, Tanya L; Graham, Stephen; Caraway, Nina; Foley, Kristen M; Isaacs, Kristin K

2017-05-01

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O 3 ) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O 3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O 3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O 3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O 3 are much larger than the impacts of changing demographics. These results indicate the potential for future changes in O 3 exposure as a result of changes in climate that could impact human health.

Integrating plant ecological responses to climate extremes from individual to ecosystem levels.

PubMed

Felton, Andrew J; Smith, Melinda D

2017-06-19

Climate extremes will elicit responses from the individual to the ecosystem level. However, only recently have ecologists begun to synthetically assess responses to climate extremes across multiple levels of ecological organization. We review the literature to examine how plant responses vary and interact across levels of organization, focusing on how individual, population and community responses may inform ecosystem-level responses in herbaceous and forest plant communities. We report a high degree of variability at the individual level, and a consequential inconsistency in the translation of individual or population responses to directional changes in community- or ecosystem-level processes. The scaling of individual or population responses to community or ecosystem responses is often predicated upon the functional identity of the species in the community, in particular, the dominant species. Furthermore, the reported stability in plant community composition and functioning with respect to extremes is often driven by processes that operate at the community level, such as species niche partitioning and compensatory responses during or after the event. Future research efforts would benefit from assessing ecological responses across multiple levels of organization, as this will provide both a holistic and mechanistic understanding of ecosystem responses to increasing climatic variability.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

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

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less

Intensity - Duration - Frequency Curves for U.S. Cities in a Warming Climate

NASA Astrophysics Data System (ADS)

Ragno, Elisa; AghaKouchak, Amir; Love, Charlotte; Vahedifard, Farshid; Cheng, Linyin; Lima, Carlos

2017-04-01

Current infrastructure design procedures rely on the use of Intensity - Duration - Frequency (IDF) curves retrieved under the assumption of temporal stationarity, meaning that occurrences of extreme events are expected to be time invariant. However, numerous studies have observed more severe extreme events over time. Hence, the stationarity assumption for extreme analysis may not be appropriate in a warming climate. This issue raises concerns regarding the safety and resilience of infrastructures and natural slopes. Here we employ daily precipitation data from historical and projected (RCP 8.5) CMIP5 runs to investigate IDF curves of 14 urban areas across the United States. We first statistically assess changes in precipitation extremes using an energy-based test for equal distributions. Then, through a Bayesian inference approach for stationary and non-stationary extreme value analysis, we provide updated IDF curves based on future climatic model projections. We show that, based on CMIP5 simulations, U.S cities may experience extreme precipitation events up to 20% more intense and twice as frequently, relative to historical records, despite the expectation of unchanged annual mean precipitation.

Simulated Extreme Prepitation Indices over Northeast Brasil in Current Climate and Future Scenarios RCP4.5 and RCP8.5

NASA Astrophysics Data System (ADS)

Wender Santiago Marinho, Marcos; Araújo Costa, Alexandre; Cassain Sales, Domingo; Oliveira Guimarães, Sullyandro; Mariano da Silva, Emerson; das Chagas Vasconcelos Júnior, Francisco

2013-04-01

In this study, we analyzed extreme precipitation indices, for present and future modeled climates over Northeast of Brazil (NEB), from CORDEX simulations over the domain of Tropical Americas. The period for the model validation was from 1989-2007, using data from the European Center (ECWMF) Reanalysis, ERA-INTERIM, as input to drive the regional model (RAMS 6.0). Reanalysis data were assimilated via both lateral boundaries and the entire domain (a much weaker "central nudging"). Six indices of extreme precipitation were calculated over NEB: the average number of days above 10, 20 and 30 mm in one year (R10, R20, R30), the number of consecutive dry days (CDD), the number of consecutive wet days (CWD) and the maximum rainfall in five consecutive days (RX5). Those indices were compared against two independent databases: MERRA (Modern Era Retrospective analysis for Research and Applications) and TRMM (Tropical Rainfall Measuring Mission). After validation, climate simulations were performed for the present climate (1985-2005) and short-term (2015-2035), mid-term (2045-2065) and long-term (2079 to 2099) future climates for two scenarios: RCP 4.5 and RCP 8.5, nesting RAMS into HadGEM2-ES global model (a participant of CMIP5). Along with the indices, we also calculated Probability Distribution Functions (PDFs) to study the behavior of daily precipitation in the present and by the end of the 21st century (2079 to 2099) to assess possible changes under RCPs 4.5 and 8.5. The regional model is capable of representing relatively well the extreme precipitation indices for current climate, but there is some difficulties in performing a proper validation since the observed databases disagree significantly. Future projections show significant changes in most extreme indices. Rnn generally tend to increase, especially under RCP8.5. More significant changes are projected for the long-term period, under RCP8.5, which shows a pronounced R30 enhancement over northern states. CDD tends to decrease over most of NEB in the short but this trend is reverted toward the end of the century in both scenarios with a significant increase in the duration of the dry season over Northwestern and Eastern NEB (exceeding 50 days over certain areas), whereas projected CWD changes are smaller. Rx5 shows a general increasing trend especially in the long term period,under RCP8.5.

Using Risk Assessment and Habitat Suitability Models to Prioritise Invasive Species for Management in a Changing Climate.

PubMed

Chai, Shauna-Lee; Zhang, Jian; Nixon, Amy; Nielsen, Scott

2016-01-01

Accounting for climate change in invasive species risk assessments improves our understanding of potential future impacts and enhances our preparedness for the arrival of new non-native species. We combined traditional risk assessment for invasive species with habitat suitability modeling to assess risk to biodiversity based on climate change. We demonstrate our method by assessing the risk for 15 potentially new invasive plant species to Alberta, Canada, an area where climate change is expected to facilitate the poleward expansion of invasive species ranges. Of the 15 species assessed, the three terrestrial invasive plant species that could pose the greatest threat to Alberta's biodiversity are giant knotweed (Fallopia sachalinensis), tamarisk (Tamarix chinensis), and alkali swainsonpea (Sphaerophysa salsula). We characterise giant knotweed as 'extremely invasive', with 21 times the suitable habitat between baseline and future projected climate. Tamarisk is 'extremely invasive' with a 64% increase in suitable habitat, and alkali swainsonpea is 'highly invasive' with a 21% increase in suitable habitat. Our methodology can be used to predict and prioritise potentially new invasive species for their impact on biodiversity in the context of climate change.

Using Risk Assessment and Habitat Suitability Models to Prioritise Invasive Species for Management in a Changing Climate

PubMed Central

Chai, Shauna-Lee; Zhang, Jian; Nixon, Amy; Nielsen, Scott

2016-01-01

Accounting for climate change in invasive species risk assessments improves our understanding of potential future impacts and enhances our preparedness for the arrival of new non-native species. We combined traditional risk assessment for invasive species with habitat suitability modeling to assess risk to biodiversity based on climate change. We demonstrate our method by assessing the risk for 15 potentially new invasive plant species to Alberta, Canada, an area where climate change is expected to facilitate the poleward expansion of invasive species ranges. Of the 15 species assessed, the three terrestrial invasive plant species that could pose the greatest threat to Alberta’s biodiversity are giant knotweed (Fallopia sachalinensis), tamarisk (Tamarix chinensis), and alkali swainsonpea (Sphaerophysa salsula). We characterise giant knotweed as ‘extremely invasive’, with 21 times the suitable habitat between baseline and future projected climate. Tamarisk is ‘extremely invasive’ with a 64% increase in suitable habitat, and alkali swainsonpea is ‘highly invasive’ with a 21% increase in suitable habitat. Our methodology can be used to predict and prioritise potentially new invasive species for their impact on biodiversity in the context of climate change. PMID:27768758

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

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

2005-12-01

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

Life stage influences the resistance and resilience of black mangrove forests to winter climate extremes

USGS Publications Warehouse

Osland, Michael J.; Day, Richard H.; From, Andrew S.; McCoy, Megan L.; McLeod, Jennie L.; Kelleway, Jeffrey

2015-01-01

In subtropical coastal wetlands on multiple continents, climate change-induced reductions in the frequency and intensity of freezing temperatures are expected to lead to the expansion of woody plants (i.e., mangrove forests) at the expense of tidal grasslands (i.e., salt marshes). Since some ecosystem goods and services would be affected by mangrove range expansion, there is a need to better understand mangrove sensitivity to freezing temperatures as well as the implications of changing winter climate extremes for mangrove-salt marsh interactions. In this study, we investigated the following questions: (1) how does plant life stage (i.e., ontogeny) influence the resistance and resilience of black mangrove (Avicennia germinans) forests to freezing temperatures; and (2) how might differential life stage responses to freeze events affect the rate of mangrove expansion and salt marsh displacement due to climate change? To address these questions, we quantified freeze damage and recovery for different life stages (seedling, short tree, and tall tree) following extreme winter air temperature events that occurred near the northern range limit of A. germinans in North America. We found that life stage affects black mangrove forest resistance and resilience to winter climate extremes in a nonlinear fashion. Resistance to winter climate extremes was high for tall A. germinans trees and seedlings, but lowest for short trees. Resilience was highest for tall A. germinans trees. These results suggest the presence of positive feedbacks and indicate that climate-change induced decreases in the frequency and intensity of extreme minimum air temperatures could lead to a nonlinear increase in mangrove forest resistance and resilience. This feedback could accelerate future mangrove expansion and salt marsh loss at rates beyond what would be predicted from climate change alone. In general terms, our study highlights the importance of accounting for differential life stage responses and positive feedbacks when evaluating the ecological effects of changes in the frequency and magnitude of climate extremes.

Are implicit policy assumptions about climate adaptation trying to push drinking water utilities down an impossible path?

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The Great Plains low-level jet in 1.5C and 2C HAPPI simulations: Implications for changes in extreme climate events

NASA Astrophysics Data System (ADS)

Weaver, S. J.; Barcikowska, M. J.

2017-12-01

Global temperature targets have become the cornerstone for global climate policy discussions. Given the goal of the Paris Accord to limit the rise in global mean temperature to well below 2.0oC above pre-industrial levels, and pursue efforts toward the more ambitious 1.5oC goal, there is increasing focus in the climate science community on what the relative changes in regional climate extremes may be for these two scenarios. Despite the successes of major climate science modeling efforts, there is still a significant information gap regarding the regional and seasonal changes in some climate extremes over the U.S. as a function of these global mean temperature targets.During the spring and summer, large amounts of heat and moisture are transported northward into the central and eastern U.S. by the Great Plains Low-Level Jet (GPLLJ) - an atmospheric river which dominates the subcontinental scale climate variability during the warm half of the year. Accordingly, the GPLLJ and its vast spatiotemporal variability is highly influential over several types of extreme climate anomalies east of the Rocky Mountains, including, drought and pluvial events, tornadic activity, and the evolution of central U.S warming hole. Changes in the GPLLJ and its variability are probed from the perspective of several hundred climate realizations afforded by the availability of climate model experiments from the Half a degree additional warming, Prognosis, and Projected Impacts (HAPPI) effort - a suite of multi-model ensemble AMIP simulations forced by 1.5oC and 2oC levels of global warming. The multimodel analysis focuses on the variable magnitude of the seasonal changes in the mean GPLLJ and shifts in the extremes of the prominent modes of GPLLJ variability - both of which have implications for the future shifts in extreme climate events over the Great Plains, Midwest, and southeast regions of the U.S.

Convergence of Dynamic Vegetation Net Productivity Responses to Precipitation Variability from 10 Years of MODIS EVI

USDA-ARS?s Scientific Manuscript database

According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patte...

Adaptation Resources for Agriculture: Responding to climate variability and change in the midwest and northeast

USDA-ARS?s Scientific Manuscript database

Changes in climate and extreme weather have already occurred and are increasing challenges for agriculture nationally and globally, and many of these impacts will continue into the future. This technical bulletin contains information and resources designed to help agricultural producers, service pro...

Potential climate change impacts on fire weather in the United States

Treesearch

Warren E. Heilman; Ying Tang; Lifeng Luo; Shiyuan Zhong; Julie Winkler; Xindi. Bian

2015-01-01

Researchers at Michigan State University and the Forest Service's Northern Research Station worked on a joint study to examine the possible effects of future global and regional climate change on the occurrence of fire-weather patterns often associated with extreme and erratic wildfire behavior in the United States.

Evaluation of climate variability on drought occurrence in an agricultural watershed

USDA-ARS?s Scientific Manuscript database

Changes in the future hydrologic cycle due to changes in precipitation and temperature are likely to be associated with increases in hydrologic extremes. This study evaluates the impacts of climate variability on drought using the Soil and Water Assessment Tool (SWAT) in the Goodwater Creek Experim...

Predicting drought in an agricultural watershed given climate variability

USDA-ARS?s Scientific Manuscript database

Changes in the future hydrologic cycle due to changes in temperature (T) and precipitation (P) are likely to be associated with increases in hydrologic extremes. This study evaluates the impacts of climate variability on drought using the Soil and Water Assessment Tool (SWAT) in Goodwater Creek Expe...

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

USGS Publications Warehouse

Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2.

PubMed

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali; Archontoulis, Sotirios V; Zobel, Zachary; Kotamarthi, Veerabhadra R

2017-07-01

Heat and drought are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO 2 concentrations. This study quantifies the combined and separate impacts of high temperature, heat and drought stresses on the current and future US rainfed maize and soybean production and for the first time characterizes spatial shifts in the relative importance of individual stress. Crop yields are simulated using the Agricultural Production Systems Simulator (APSIM), driven by high-resolution (12 km) dynamically downscaled climate projections for 1995-2004 and 2085-2094. Results show that maize and soybean yield losses are prominent in the US Midwest by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of loss highly depends on the current vulnerability and changes in climate extremes. Elevated atmospheric CO 2 partially but not completely offsets the yield gaps caused by climate extremes, and the effect is greater in soybean than in maize. Our simulations suggest that drought will continue to be the largest threat to US rainfed maize production under RCP4.5 and soybean production under both RCP scenarios, whereas high temperature and heat stress take over the dominant stress of drought on maize under RCP8.5. We also reveal that shifts in the geographic distributions of dominant stresses are characterized by the increase in concurrent stresses, especially for the US Midwest. These findings imply the importance of considering heat and drought stresses simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management. The modeling framework of partitioning the total effects of climate change into individual stress impacts can be applied to the study of other crops and agriculture systems. © 2017 John Wiley & Sons Ltd.

Integration of modern statistical tools for the analysis of climate extremes into the web-GIS “CLIMATE”

NASA Astrophysics Data System (ADS)

Ryazanova, A. A.; Okladnikov, I. G.; Gordov, E. P.

2017-11-01

The frequency of occurrence and magnitude of precipitation and temperature extreme events show positive trends in several geographical regions. These events must be analyzed and studied in order to better understand their impact on the environment, predict their occurrences, and mitigate their effects. For this purpose, we augmented web-GIS called “CLIMATE” to include a dedicated statistical package developed in the R language. The web-GIS “CLIMATE” is a software platform for cloud storage processing and visualization of distributed archives of spatial datasets. It is based on a combined use of web and GIS technologies with reliable procedures for searching, extracting, processing, and visualizing the spatial data archives. The system provides a set of thematic online tools for the complex analysis of current and future climate changes and their effects on the environment. The package includes new powerful methods of time-dependent statistics of extremes, quantile regression and copula approach for the detailed analysis of various climate extreme events. Specifically, the very promising copula approach allows obtaining the structural connections between the extremes and the various environmental characteristics. The new statistical methods integrated into the web-GIS “CLIMATE” can significantly facilitate and accelerate the complex analysis of climate extremes using only a desktop PC connected to the Internet.

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

USGS Publications Warehouse

Vorosmarty, Charles J.; de Guenni, Lelys Bravo; Wollheim, Wilfred M.; Pellerin, Brian A.; Bjerklie, David M.; Cardoso, Manoel; D'Almeida, Cassiano; Colon, Lilybeth

2013-01-01

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

Investigating Differences between Modeled Historical and Station Calculated Drought

EPA Science Inventory

With growing concern over increased frequency and intensity of extreme climate events, there is an imperative need to investigate drought under different future scenarios for the contiguous U.S. To assess future drought relative to a historical baseline, drought occurrence (numbe...

Relationship between extreme Precipitation and Temperature over Japan: An analysis from Multi-GCMs and Multi-RCMs products

NASA Astrophysics Data System (ADS)

Nayak, S.; Dairaku, K.; Takayabu, I.

2014-12-01

According to the IPCC reports, the concentration of CO­2 has been increasing and projected to be increased significantly in future (IPCC, 2012). This can have significant impacts on climate. For instance, Dairaku and Emori (2006) examined over south Asia by doubling CO2 and documented an increase in precipitation intensities during Indian summer monsoon. This would increase natural disasters such as floods, landslide, coastal disaster, erosion etc. Recent studies investigated whether the rate of increase of extreme precipitation is related with the rate expected by Clausius-Clapeyron (CC) relationship (approximately 7% per degree temperature rise). In our study, we examine whether this rate can increase or decrease in the future regional climate scenarios over Japan. We have analysed the ensemble experiments by three RCMs(NHRCM, NRAMS, WRF) forced by JRA25 as well as three GCMs (CCSM4, MIROC5, MRI-GCM3) for the current climate (1981-2000) and future scenario (2081-2100, RCP4.5) over Japan. We have stratified the extreme (99th, 95th, 90th, 75th percentile) precipitation of daily sum and daily maximum of hourly precipitation intensities of wet events based on daily mean temperature in bins of 1°C width for annual as well as for each season (DJF, MAM, JJA, SON). The results indicate that precipitation intensity increases when temperature increases roughly up to 22 °C and further increase of temperature decreases the precipitation intensities. The obtained results are consistent and match with the observation (APHRODITE dataset) over Japan. The decrease of precipitation at higher temperature mainly can be found in JJA. It is also noticed that the rate of specific humidity is estimated higher during JJA than other seasons. The rate of increase of extreme precipitation is similar to the rate expected by CC relation except DJF (nearly twice of CC relation) in current climate. This rate becomes to be significantly larger in future scenario for higher temperatures than in current climate.Acknowledgement: This study is conducted as part of a research at NIED, Japan (PI: Koji Dairaku) of Research Program on Climate Change Adaptation (RECCA) and was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

Future precipitation changes over China under 1.5 °C and 2.0 °C global warming targets by using CORDEX regional climate models.

PubMed

Li, Huixin; Chen, Huopo; Wang, Huijun; Yu, Entao

2018-06-01

This study aims to characterize future changes in precipitation extremes over China based on regional climate models (RCMs) participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX)-East Asia project. The results of five RCMs involved in CORDEX-East Asia project that driven by HadGEM2-AO are compared with the simulation of CMA-RegCM driven by BCC-CSM1.1. Eleven precipitation extreme indices that developed by the Expert Team on Climate Change Detection and Indices are employed to evaluate precipitation extreme changes over China. Generally, RCMs can reproduce their spatiotemporal characteristics over China in comparison with observations. For future climate projections, RCMs indicate that both the occurrence and intensity of precipitation extremes in most regions of China will increase when the global temperature increases by 1.5/2.0 °C. The yearly maximum five-day precipitation (RX5D) averaged over China is reported to increase by 4.4% via the CMA-RegCM under the 1.5 °C warming in comparison with the baseline period (1986-2005); however, a relatively large increase of 11.1% is reported by the multi-model ensemble median (MME) when using the other five models. Furthermore, the reoccurring risks of precipitation extremes over most regions of China will further increase due to the additional 0.5 °C warming. For example, RX5D will further increase by approximately 8.9% over NWC, 3.8% over NC, 2.3% over SC, and approximately 1.0% over China. Extremes, such as the historical 20-year return period event of yearly maximum one-day precipitation (RX1D) and RX5D, will become more frequent, with occurrences happening once every 8.8 years (RX1D) and 11.5 years (RX5D) under the 1.5 °C warming target, and there will be two fewer years due to the additional 0.5 °C warming. In addition, the intensity of these events will increase by approximately 9.2% (8.5%) under the 1.5 °C warming target and 12.6% (11.0%) under the 2.0 °C warming target for RX1D (RX5D). Copyright © 2018 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Quantifying the health impacts of air pollution under a changing climate-a review of approaches and methodology.

PubMed

Sujaritpong, Sarunya; Dear, Keith; Cope, Martin; Walsh, Sean; Kjellstrom, Tord

2014-03-01

Climate change has been predicted to affect future air quality, with inevitable consequences for health. Quantifying the health effects of air pollution under a changing climate is crucial to provide evidence for actions to safeguard future populations. In this paper, we review published methods for quantifying health impacts to identify optimal approaches and ways in which existing challenges facing this line of research can be addressed. Most studies have employed a simplified methodology, while only a few have reported sensitivity analyses to assess sources of uncertainty. The limited investigations that do exist suggest that examining the health risk estimates should particularly take into account the uncertainty associated with future air pollution emissions scenarios, concentration-response functions, and future population growth and age structures. Knowledge gaps identified for future research include future health impacts from extreme air pollution events, interactions between temperature and air pollution effects on public health under a changing climate, and how population adaptation and behavioural changes in a warmer climate may modify exposure to air pollution and health consequences.

States at Risk: America's Preparedness Report Card

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Early benefits of mitigation in risk of regional climate extremes

NASA Astrophysics Data System (ADS)

Ciavarella, Andrew; Stott, Peter; Lowe, Jason

2017-04-01

Large differences in climate outcomes are projected by the end of this century depending on whether greenhouse gas emissions continue to increase or are reduced sufficiently to limit total warming to below 2 °C (ref. ). However, it is generally thought that benefits of mitigation are hidden by internal climate variability until later in the century. Here we show that if the likelihood of extremely hot seasons is considered, the benefits of mitigation emerge more quickly than previously thought. It takes less than 20 years of emissions reductions in many regions for the likelihood of extreme seasonal warmth to reduce by more than half following initiation of mitigation. Additionally we show that the latest possible date at which the probability of extreme seasonal temperatures will be halved through emissions reductions consistent with the 2 °C target is in the 2040s. Exposure to climate risk is therefore reduced markedly and rapidly with substantial reductions of greenhouse gas emissions, demonstrating that the early mitigation needed to limit eventual warming below potentially dangerous levels benefits societies in the nearer term not just in the longer-term future.

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.

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 impact analyses and build an important basis of the future adaptation strategies in forestry, agriculture and water management. Funding: The research is supported by the TÁMOP-4.2.2.A-11/1/KONV-2012-0013 and TÁMOP-4.1.1.C-12/1/KONV-2012-0012 (ZENFE) joint EU-national research projects. Keywords: climate indices, climate change impacts, forestry, regional climate modelling

Uncertainty in projected point precipitation extremes for hydrological impact analysis of climate change

NASA Astrophysics Data System (ADS)

Van Uytven, Els; Willems, Patrick

2017-04-01

Current trends in the hydro-meteorological variables indicate the potential impact of climate change on hydrological extremes. Therefore, they trigger an increased importance climate adaptation strategies in water management. The impact of climate change on hydro-meteorological and hydrological extremes is, however, highly uncertain. This is due to uncertainties introduced by the climate models, the internal variability inherent to the climate system, the greenhouse gas scenarios and the statistical downscaling methods. In view of the need to define sustainable climate adaptation strategies, there is a need to assess these uncertainties. This is commonly done by means of ensemble approaches. Because more and more climate models and statistical downscaling methods become available, there is a need to facilitate the climate impact and uncertainty analysis. A Climate Perturbation Tool has been developed for that purpose, which combines a set of statistical downscaling methods including weather typing, weather generator, transfer function and advanced perturbation based approaches. By use of an interactive interface, climate impact modelers can apply these statistical downscaling methods in a semi-automatic way to an ensemble of climate model runs. The tool is applicable to any region, but has been demonstrated so far to cases in Belgium, Suriname, Vietnam and Bangladesh. Time series representing future local-scale precipitation, temperature and potential evapotranspiration (PET) conditions were obtained, starting from time series of historical observations. Uncertainties on the future meteorological conditions are represented in two different ways: through an ensemble of time series, and a reduced set of synthetic scenarios. The both aim to span the full uncertainty range as assessed from the ensemble of climate model runs and downscaling methods. For Belgium, for instance, use was made of 100-year time series of 10-minutes precipitation observations and daily temperature and PET observations at Uccle and a large ensemble of 160 global climate model runs (CMIP5). They cover all four representative concentration pathway based greenhouse gas scenarios. While evaluating the downscaled meteorological series, particular attention was given to the performance of extreme value metrics (e.g. for precipitation, by means of intensity-duration-frequency statistics). Moreover, the total uncertainty was decomposed in the fractional uncertainties for each of the uncertainty sources considered. Research assessing the additional uncertainty due to parameter and structural uncertainties of the hydrological impact model is ongoing.

Implications of climate change predictions for UK cropping and prospects for possible mitigation: a review of challenges and potential responses.

PubMed

Rial-Lovera, Karen; Davies, W Paul; Cannon, Nicola D

2017-01-01

The UK, like the rest of the world, is confronting the impacts of climate change. Further changes are expected and they will have a profound effect on agriculture. Future crop production will take place against increasing CO 2 levels and temperatures, decreasing water availability, and increasing frequency of extreme weather events. This review contributes to research on agricultural practices for climate change, but with a more regional perspective. The present study explores climate change impacts on UK agriculture, particularly food crop production, and how to mitigate and build resilience to climate change by adopting and/or changing soil management practices, including fertilisation and tillage systems, new crop adoption and variety choice. Some mitigation can be adopted in the shorter term, such as changes in crop type and reduction in fertiliser use, but in other cases the options will need greater investment and longer adaptation period. This is the case for new crop variety development and deployment, and possible changes to soil cultivations. Uncertainty of future weather conditions, particularly extreme weather, also affect decision-making for adoption of practices by farmers to ensure more stable and sustainable production. Even when there is real potential for climate change mitigation, it can sometimes be more difficult to accomplish with certainty on-farm. Better future climate projections and long-term investments will be required to create more resilient agricultural systems in the UK in the face of climate change challenges. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Future Changes to ENSO Temperature and Precipitation Teleconnections Under Warming

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The end of trend-estimation for extreme floods under climate change?

NASA Astrophysics Data System (ADS)

Schulz, Karsten; Bernhardt, Matthias

2016-04-01

An increased risk of flood events is one of the major threats under future climate change conditions. Therefore, many recent studies have investigated trends in flood extreme occurences using historic long-term river discharge data as well as simulations from combined global/regional climate and hydrological models. Severe floods are relatively rare events and the robust estimation of their probability of occurrence requires long time series of data (6). Following a method outlined by the IPCC research community, trends in extreme floods are calculated based on the difference of discharge values exceeding e.g. a 100-year level (Q100) between two 30-year windows, which represents prevailing conditions in a reference and a future time period, respectively. Following this approach, we analysed multiple, synthetically derived 2,000-year trend-free, yearly maximum runoff data generated using three different extreme value distributions (EDV). The parameters were estimated from long term runoff data of four large European watersheds (Danube, Elbe, Rhine, Thames). Both, Q100-values estimated from 30-year moving windows, as well as the subsequently derived trends showed enormous variations with time: for example, estimating the Extreme Value (Gumbel) - distribution for the Danube data, trends of Q100 in the synthetic time-series range from -4,480 to 4,028 m³/s per 100 years (Q100 =10,071m³/s, for reference). Similar results were found when applying other extreme value distributions (Weibull, and log-Normal) to all of the watersheds considered. This variability or "background noise" of estimating trends in flood extremes makes it almost impossible to significantly distinguish any real trend in observed as well as modelled data when such an approach is applied. These uncertainties, even though known in principle are hardly addressed and discussed by the climate change impact community. Any decision making and flood risk management, including the dimensioning of flood protection measures, that is based on such studies might therefore be fundamentally flawed.

Changes in Extreme Events and the Potential Impacts on National Security

NASA Astrophysics Data System (ADS)

Bell, J.

2017-12-01

Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socio-economic impacts. Climate change has caused changes in extreme event frequency, intensity and geographic distribution, and will continue to be a driver for changes in the future. Some of the extreme events that have already changed are heat waves, droughts, wildfires, flooding rains, coastal flooding, storm surge, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local intricacies of societal and environmental factors that influences the level of exposure. The goal of this presentation is to discuss the national security implications of changes in extreme weather events and demonstrate how changes in extremes can lead to a host cascading issues. To illustrate this point, this presentation will provide examples of the various pathways that extreme events can increase disease burden and cause economic stress.

Evaluating the ClimEx Single Model large ensemble in comparison with EURO-CORDEX results of heatwave and drought indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several indicators concerning heatwave frequency, duration and mean temperature a well as number and maximum length of dry periods (cons. days <1mm) are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Role of resolution in regional climate change projections over China

NASA Astrophysics Data System (ADS)

Shi, Ying; Wang, Guiling; Gao, Xuejie

2017-11-01

This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

Coastal Hazards and Integration of Impacts in Local Adaptation Planning

NASA Astrophysics Data System (ADS)

Knudsen, P.; Sorensen, C.; Molgaard, M. R.; Broge, N. H.; Andersen, O. B.

2016-12-01

Data on sea and groundwater levels, precipitation, land subsidence, geology, and geotechnical soil properties are combined with information on flood and erosion protection measures to analyze water-related impacts from climate change at an exposed coastal location. Future sea extremes will have a large impact but several coupled effects in the hydrological system need to be considered as well to provide for optimal protection and mitigation efforts. For instance, the investment and maintenance costs of securing functional water and wastewater pipes are significantly reduced by incorporating knowledge about climate change. The translation of regional sea level rise evidence and projections to concrete impact measures should take into account the potentially affected stakeholders who must collaborate on common and shared adaptation solutions. Here, knowledge integration across levels of governance and between research, private and public institutions, and the local communities provides: understanding of the immediate and potential future challenges; appreciation of different stakeholder motives, business agendas, legislative constraints etc., and a common focus on how to cost-efficiently adapt to and manage impacts of climate change. By construction of a common working platform that is updated with additional data and knowledge, e.g. from future regional models or extreme events, advances in sea level research can more readily be translated into concrete and local impact measures in a way that handles uncertainties in the future climate and urban development as well as suiting the varying stakeholder needs.

Using Scenario Development to Encourage Tourism Business Resilience in the Great Lakes

NASA Astrophysics Data System (ADS)

Chin, N.; Day, J.; Sydnor, S.; Cherkauer, K. A.

2015-12-01

Tourism is an economic sector anticipated to be greatly affected by climate change, but the potential impacts of climate change on tourism have rarely been examined in detail in existing research. Past research has shown, however, that the small and medium businesses that dominate the tourism sector could be greatly impacted by climate change. We have presented global climate and hydrologic model research results to pre-selected coastal tourism business owners in the Great Lakes region to determine the best methods for delivering user-friendly future climate scenarios, given that existing research suggests that climate change adaptive behaviors and resilience increase with information (message) clarity. Model output analyses completed for this work have focused on temperature, precipitation, and extreme weather events due to their economic impact on tourism activities. We have also experimented with the development and use of infographics because of their ability to present information quickly and clearly. Initial findings of this work will be presented as well as lessons learned from stakeholder interactions. Two main results include that (1) extreme weather events may have more meaning to tourism business owners than general trends in climate and (2) long-term planning for climate is extremely difficult for tourism business owners because they operate on a much shorter planning timeline than those generally used for climate change analyses.

Final Technical Report for DE-SC0005467

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

Broccoli, Anthony J.

2014-09-14

The objective of this project is to gain a comprehensive understanding of the key atmospheric mechanisms and physical processes associated with temperature extremes in order to better interpret and constrain uncertainty in climate model simulations of future extreme temperatures. To achieve this objective, we first used climate observations and a reanalysis product to identify the key atmospheric circulation patterns associated with extreme temperature days over North America during the late twentieth century. We found that temperature extremes were associated with distinctive signatures in near-surface and mid-tropospheric circulation. The orientations and spatial scales of these circulation anomalies vary with latitude, season,more » and proximity to important geographic features such as mountains and coastlines. We next examined the associations between daily and monthly temperature extremes and large-scale, recurrent modes of climate variability, including the Pacific-North American (PNA) pattern, the northern annular mode (NAM), and the El Niño-Southern Oscillation (ENSO). The strength of the associations are strongest with the PNA and NAM and weaker for ENSO, and also depend upon season, time scale, and location. The associations are stronger in winter than summer, stronger for monthly than daily extremes, and stronger in the vicinity of the centers of action of the PNA and NAM patterns. In the final stage of this project, we compared climate model simulations of the circulation patterns associated with extreme temperature days over North America with those obtained from observations. Using a variety of metrics and self-organizing maps, we found the multi-model ensemble and the majority of individual models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) generally capture the observed patterns well, including their strength and as well as variations with latitude and season. The results from this project indicate that current models are capable of simulating the large-scale meteorological patterns associated with daily temperature extremes and they suggest that such models can be used to evaluate the extent to which changes in atmospheric circulation will influence future changes in temperature extremes.« less

Anticipating Future Extreme Climate Events for Alaska Using Dynamical Downscaling and Quantile Mapping

NASA Astrophysics Data System (ADS)

Lader, R.; Walsh, J. E.

2016-12-01

Alaska is projected to experience major changes in extreme climate during the 21st century, due to greenhouse warming and exacerbated by polar amplification, wherein the Arctic is warming at twice the rate compared to the Northern Hemisphere. Given its complex topography, Alaska displays extreme gradients of temperature and precipitation. However, global climate models (GCMs), which typically have a spatial resolution on the order of 100km, struggle to replicate these extremes. To help resolve this issue, this study employs dynamically downscaled regional climate simulations and quantile-mapping methodologies to provide a full suite of daily model variables at 20 km spatial resolution for Alaska, from 1970 to 2100. These data include downscaled products of the: ERA-Interim reanalysis from 1979 to 2015, GFDL-CM3 historical from 1970 to 2005, and GFDL-CM3 RCP 8.5 from 2006 to 2100. Due to the limited nature of long-term observations and high-resolution modeling in Alaska, these data enable a broad expansion of extremes analysis. This study uses these data to highlight a subset of the 27 climate extremes indices, previously defined by the Expert Team on Climate Change Detection and Indices, as they pertain to climate change in Alaska. These indices are based on the statistical distributions of daily surface temperature and precipitation and focus on threshold exceedance, and percentiles. For example, the annual number of days with a daily maximum temperature greater than 25°C is anticipated to triple in many locations in Alaska by the end of the century. Climate extremes can also refer to long duration events, such as the record-setting warmth that defined the 2015-16 cold season in Alaska. The downscaled climate model simulations indicate that this past winter will be considered normal by as early as the mid-2040s, if we continue to warm according to the business-as-usual RCP 8.5 emissions scenario. This represents an accelerated warming as compared to projections form the coarse scale GCMs, and this greater rate of change in the downscaled products is noted with other extremes indices as well.

Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

NASA Astrophysics Data System (ADS)

Werner, A. T.; Cannon, A. J.

2015-06-01

Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e., correlation tests) and distributional properties (i.e., tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3 day peak flow and 7 day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational datasets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational dataset. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7 day low flow events, regardless of reanalysis or observational dataset. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis datasets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical datasets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.

Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

NASA Astrophysics Data System (ADS)

Werner, Arelia T.; Cannon, Alex J.

2016-04-01

Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis data sets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical data sets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.

Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States

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

Anderson, Bruce T.

2015-12-11

Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantiallymore » from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred through a change in the underlying climate. As such, this method is capable of detecting “hot spot” regions—as well as “flare ups” within the hot spot regions—that have experienced interannual to multi-decadal scale variations and trends in seasonal-mean precipitation and extreme events. Further by applying the same methods to numerical climate models we can discern the fidelity of the current-generation climate models in representing detectability within the observed climate system. In this way, we can objectively determine the utility of these model systems for performing detection studies of historical and future climate change.« less

Simulation of Extreme Arctic Cyclones in IPCC AR5 Experiments

NASA Astrophysics Data System (ADS)

Vavrus, S. J.

2012-12-01

Although impending Arctic climate change is widely recognized, a wild card in its expression is how extreme weather events in this region will respond to greenhouse warming. Intense polar cyclones represent one type of high-latitude phenomena falling into this category, including very deep synoptic-scale cyclones and mesoscale polar lows. These systems inflict damage through high winds, heavy precipitation, and wave action along coastlines, and their impact is expected to expand in the future, when reduced sea ice cover allows enhanced wave energy. The loss of a buffering ice pack could greatly increase the rate of coastal erosion, which has already been increasing in the Arctic. These and related threats may amplify if extreme Arctic cyclones become more frequent and/or intense in a warming climate with much more open water to fuel them. This possibility has merit on the basis of GCM experiments, which project that greenhouse forcing causes lower mean sea level pressure (SLP) in the Arctic and a strengthening of the deepest storms over boreal high latitudes. In this study, the latest Coupled Model Intercomparison Project (CMIP5) climate model output is used to investigate the following questions: (1) What are the spatial and seasonal characteristics of extreme Arctic cyclones? (2) How well do GCMs simulate these phenomena? (3) Are Arctic cyclones already showing the expected response to greenhouse warming in climate models? To address these questions, a retrospective analysis is conducted of the transient 20th century simulations among the CMIP5 GCMs (spanning years 1850-2005). The results demonstrate that GCMs are able to reasonably represent extreme Arctic cyclones and that the simulated characteristics do not depend significantly on model resolution. Consistent with observational evidence, climate models generate these storms primarily during winter and within the climatological Aleutian and Icelandic Low regions. Occasionally the cyclones remain very intense over the Arctic Ocean. The historical tendency in Arctic SLP varies considerably among the GCMs, but the intermodel average trend exhibits a lowering of mean-annual pressure over the Arctic during the past 150 years and an increase in extreme cyclones in the vicinity of the Aleutian and Icelandic Lows. However, only weak trends in extreme cyclones are simulated through 2005 over the Arctic Ocean, where simulations of future climate change produce the largest SLP falls.

Simulation of future global warming scenarios in rice paddies with an open-field ecosystem warming facility

USDA-ARS?s Scientific Manuscript database

Rice (Oryza sativa L.) in Yangtze River Valley (YRV) suffered serious yield losses in 2003 when extreme heatwave (HW), hampered rice reproductive growth phase (RGP). Climate change induced extreme and asymmetrical fluctuations in temperature during heat sensitive stage of rice growth cycle, i.e., RG...

Inter-model variability in hydrological extremes projections for Amazonian sub-basins

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

2014-05-01

Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.

Climate Change and Hydrological Extreme Events - Risks and Perspectives for Water Management in Bavaria and Québec

NASA Astrophysics Data System (ADS)

Ludwig, R.

2017-12-01

There is as yet no confirmed knowledge whether and how climate change contributes to the magnitude and frequency of hydrological extreme events and how regional water management could adapt to the corresponding risks. The ClimEx project (2015-2019) investigates the effects of climate change on the meteorological and hydrological extreme events and their implications for water management in Bavaria and Québec. High Performance Computing is employed to enable the complex simulations in a hydro-climatological model processing chain, resulting in a unique high-resolution and transient (1950-2100) dataset of climatological and meteorological forcing and hydrological response: (1) The climate module has developed a large ensemble of high resolution data (12km) of the CRCM5 RCM for Central Europe and North-Eastern North America, downscaled from 50 members of the CanESM2 GCM. The dataset is complemented by all available data from the Euro-CORDEX project to account for the assessment of both natural climate variability and climate change. The large ensemble with several thousand model years provides the potential to catch rare extreme events and thus improves the process understanding of extreme events with return periods of 1000+ years. (2) The hydrology module comprises process-based and spatially explicit model setups (e.g. WaSiM) for all major catchments in Bavaria and Southern Québec in high temporal (3h) and spatial (500m) resolution. The simulations form the basis for in depth analysis of hydrological extreme events based on the inputs from the large climate model dataset. The specific data situation enables to establish a new method for `virtual perfect prediction', which assesses climate change impacts on flood risk and water resources management by identifying patterns in the data which reveal preferential triggers of hydrological extreme events. The presentation will highlight first results from the analysis of the large scale ClimEx model ensemble, showing the current and future ratio of natural variability and climate change impacts on meteorological extreme events. Selected data from the ensemble is used to drive a hydrological model experiment to illustrate the capacity to better determine the recurrence periods of hydrological extreme events under conditions of climate change.

High Resolution Simulation of a Colorado Rockies Extreme Snow and Rain Event in both a Current and Future Climate

NASA Astrophysics Data System (ADS)

Rasmussen, Roy; Ikeda, Kyoko; Liu, Changhai; Gutmann, Ethan; Gochis, David

2016-04-01

Modeling of extreme weather events often require very finely resolved treatment of atmospheric circulation structures in order to produce and localize the large moisture fluxes that result in extreme precipitation. This is particularly true for cool season orographic precipitation processes where the representation of the landform can significantly impact vertical velocity profiles and cloud moisture entrainment rates. This study presents results for high resolution regional climate modeling study of the Colorado Headwaters region using an updated version of the Weather Research and Forecasting (WRF) model run at 4 km horizontal resolution and a hydrological extension package called WRF-Hydro. Previous work has shown that the WRF modeling system can produce credible depictions of winter orographic precipitation over the Colorado Rockies if run at horizontal resolutions < 6 km. Here we present results from a detailed study of an extreme springtime snowfall event that occurred along the Colorado Front Range in March 2003. Results from the impact of warming on total precipitation, snow-rain partitioning and surface hydrological fluxes (evapotranspiration and runoff) will be discussed in the context of how potential changes in temperature impact the amount of precipitation, the phase of precipitation (rain vs. snow) and the timing and amplitude of streamflow responses. The results show using the Pseudo Global Warming technique that intense precipitation rates significantly increased during the event and a significant fraction of the snowfall converts to rain which significantly amplifies the runoff response from one where runoff is produced gradually to one in which runoff is rapidly translated into streamflow values that approach significant flooding risks. Results from a new, CONUS scale high resolution climate simulation of extreme events in a current and future climate will be presented as time permits.

Assessing present and future climate changes in Siberia and their regional socioeconomic consequences using a web-based big data geoprocessing platform

NASA Astrophysics Data System (ADS)

Alexeev, V. A.; Gordov, E. P.

2016-12-01

Recently initiated collaborative research project is presented. Its main objective is to develop high spatial and temporal resolution datasets for studying the ongoing and future climate changes in Siberia, caused by global and regional processes in the atmosphere and the ocean. This goal will be achieved by using a set of regional and global climate models for the analysis of the mechanisms of climate change and quantitative assessment of changes in key climate variables, including analysis of extreme weather and climate events and their dynamics, evaluation of the frequency, amplitude and the risks caused by the extreme events in the region. The main practical application of the project is to provide experts, stakeholders and the public with quantitative information about the future climate change in Siberia obtained on the base of a computational web- geoinformation platform. The thematic platform will be developed in order to facilitate processing and analysis of high resolution georeferenced datasets that will be delivered and made available to scientific community, policymakes and other end users as a result of the project. Software packages will be developed to implement calculation of various climatological indicators in order to characterize and diagnose climate change and its dynamics, as well as to archive results in digital form of electronic maps (GIS layers). By achieving these goals the project will provide science based tools necessary for developing mitigation measures for adapting to climate change and reducing negative impact on the population and infrastructure of the region. Financial support of the computational web- geoinformation platform prototype development by the RF Ministry of Education and Science under Agreement 14.613.21.0037 (RFMEFI61315X0037) is acknowledged.

Contributions of changes in climatology and perturbation and the resulting nonlinearity to regional climate change.

PubMed

Adachi, Sachiho A; Nishizawa, Seiya; Yoshida, Ryuji; Yamaura, Tsuyoshi; Ando, Kazuto; Yashiro, Hisashi; Kajikawa, Yoshiyuki; Tomita, Hirofumi

2017-12-20

Future changes in large-scale climatology and perturbation may have different impacts on regional climate change. It is important to understand the impacts of climatology and perturbation in terms of both thermodynamic and dynamic changes. Although many studies have investigated the influence of climatology changes on regional climate, the significance of perturbation changes is still debated. The nonlinear effect of these two changes is also unknown. We propose a systematic procedure that extracts the influences of three factors: changes in climatology, changes in perturbation and the resulting nonlinear effect. We then demonstrate the usefulness of the procedure, applying it to future changes in precipitation. All three factors have the same degree of influence, especially for extreme rainfall events. Thus, regional climate assessments should consider not only the climatology change but also the perturbation change and their nonlinearity. This procedure can advance interpretations of future regional climates.

The rogue nature of hiatuses in a global warming climate

NASA Astrophysics Data System (ADS)

Sévellec, F.; Sinha, B.; Skliris, N.

2016-08-01

The nature of rogue events is their unlikelihood and the recent unpredicted decade-long slowdown in surface warming, the so-called hiatus, may be such an event. However, given decadal variability in climate, global surface temperatures were never expected to increase monotonically with increasing radiative forcing. Here surface air temperature from 20 climate models is analyzed to estimate the historical and future likelihood of hiatuses and "surges" (faster than expected warming), showing that the global hiatus of the early 21st century was extremely unlikely. A novel analysis of future climate scenarios suggests that hiatuses will almost vanish and surges will strongly intensify by 2100 under a "business as usual" scenario. For "CO2 stabilisation" scenarios, hiatus, and surge characteristics revert to typical 1940s values. These results suggest to study the hiatus of the early 21st century and future reoccurrences as rogue events, at the limit of the variability of current climate modelling capability.

Making Energy-Water Nexus Scenarios more Fit-for-Purpose through Better Characterization of Extremes

NASA Astrophysics Data System (ADS)

Yetman, G.; Levy, M. A.; Chen, R. S.; Schnarr, E.

2017-12-01

Often quantitative scenarios of future trends exhibit less variability than the historic data upon which the models that generate them are based. The problem of dampened variability, which typically also entails dampened extremes, manifests both temporally and spatially. As a result, risk assessments that rely on such scenarios are in danger of producing misleading results. This danger is pronounced in nexus issues, because of the multiple dimensions of change that are relevant. We illustrate the above problem by developing alternative joint distributions of the probability of drought and of human population totals, across U.S. counties over the period 2010-2030. For the dampened-extremes case we use drought frequencies derived from climate models used in the U.S. National Climate Assessment and the Environmental Protection Agency's population and land use projections contained in its Integrated Climate and Land Use Scenarios (ICLUS). For the elevated extremes case we use an alternative spatial drought frequency estimate based on tree-ring data, covering a 555-year period (Ho et al 2017); and we introduce greater temporal and spatial extremes in the ICLUS socioeconomic projections so that they conform to observed extremes in the historical U.S. spatial census data 1790-present (National Historical Geographic Information System). We use spatial and temporal coincidence of high population and extreme drought as a proxy for energy-water nexus risk. We compare the representation of risk in the dampened-extreme and elevated-extreme scenario analysis. We identify areas of the country where using more realistic portrayals of extremes makes the biggest difference in estimate risk and suggest implications for future risk assessments. References: Michelle Ho, Upmanu Lall, Xun Sun, Edward R. Cook. 2017. Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow. Water Resources Research. . doi: 10.1002/2016WR019632

Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario

NASA Astrophysics Data System (ADS)

Shkolnik, Igor; Pavlova, Tatiana; Efimov, Sergey; Zhuravlev, Sergey

2018-01-01

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security.

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.

Leaf Area Index Drives Soil Water Availability and Extreme Drought-Related Mortality under Elevated CO2 in a Temperate Grassland Model System

PubMed Central

Manea, Anthony; Leishman, Michelle R.

2014-01-01

The magnitude and frequency of climatic extremes, such as drought, are predicted to increase under future climate change conditions. However, little is known about how other factors such as CO2 concentration will modify plant community responses to these extreme climatic events, even though such modifications are highly likely. We asked whether the response of grasslands to repeat extreme drought events is modified by elevated CO2, and if so, what are the underlying mechanisms? We grew grassland mesocosms consisting of 10 co-occurring grass species common to the Cumberland Plain Woodland of western Sydney under ambient and elevated CO2 and subjected them to repeated extreme drought treatments. The 10 species included a mix of C3, C4, native and exotic species. We hypothesized that a reduction in the stomatal conductance of the grasses under elevated CO2 would be offset by increases in the leaf area index thus the retention of soil water and the consequent vulnerability of the grasses to extreme drought would not differ between the CO2 treatments. Our results did not support this hypothesis: soil water content was significantly lower in the mesocosms grown under elevated CO2 and extreme drought-related mortality of the grasses was greater. The C4 and native grasses had significantly higher leaf area index under elevated CO2 levels. This offset the reduction in the stomatal conductance of the exotic grasses as well as increased rainfall interception, resulting in reduced soil water content in the elevated CO2 mesocosms. Our results suggest that projected increases in net primary productivity globally of grasslands in a high CO2 world may be limited by reduced soil water availability in the future. PMID:24632832

Leaf area index drives soil water availability and extreme drought-related mortality under elevated CO2 in a temperate grassland model system.

PubMed

Manea, Anthony; Leishman, Michelle R

2014-01-01

The magnitude and frequency of climatic extremes, such as drought, are predicted to increase under future climate change conditions. However, little is known about how other factors such as CO2 concentration will modify plant community responses to these extreme climatic events, even though such modifications are highly likely. We asked whether the response of grasslands to repeat extreme drought events is modified by elevated CO2, and if so, what are the underlying mechanisms? We grew grassland mesocosms consisting of 10 co-occurring grass species common to the Cumberland Plain Woodland of western Sydney under ambient and elevated CO2 and subjected them to repeated extreme drought treatments. The 10 species included a mix of C3, C4, native and exotic species. We hypothesized that a reduction in the stomatal conductance of the grasses under elevated CO2 would be offset by increases in the leaf area index thus the retention of soil water and the consequent vulnerability of the grasses to extreme drought would not differ between the CO2 treatments. Our results did not support this hypothesis: soil water content was significantly lower in the mesocosms grown under elevated CO2 and extreme drought-related mortality of the grasses was greater. The C4 and native grasses had significantly higher leaf area index under elevated CO2 levels. This offset the reduction in the stomatal conductance of the exotic grasses as well as increased rainfall interception, resulting in reduced soil water content in the elevated CO2 mesocosms. Our results suggest that projected increases in net primary productivity globally of grasslands in a high CO2 world may be limited by reduced soil water availability in the future.

Is extreme climate or moderate climate more conducive to longevity in China?

NASA Astrophysics Data System (ADS)

Huang, Yi; Rosenberg, Mark; Wang, Yingli

2018-02-01

Climate is closely related to human longevity. In China, there are many climate types. According to national population censuses from 1982 to 2000, most provinces with a high ratio of centenarians are located in western and northwestern China far from the sea; these areas are characterized by a dry, cold climate, very high altitude, very high daily temperature range, strong winds, and partial hypoxia. Meanwhile, provinces with a high ratio of nonagenarians from 1982 to 2000 are located in southern China near the sea. Previous studies have attributed the high ratio of centenarians in western and northwestern China to the extreme local climate. However, centenarians in these areas decreased greatly in 2010, whereas residents in southern China frequently reached 90 to 100 years old in 2010. This study aims to explain this strange phenomenon and find whether extreme climate in Tibetan plateau and northwestern China or moderate climate in southern China is more conducive to longevity. The study found that mortality rate in Tibetan plateau is much higher than southern China, then a population evolution experiment was proposed to compare longevity indicators between low mortality rate and high mortality rate and shows that longevity indicators will decrease in the near future and increase above their original levels after several decades when the mortality rate is decreased. Results of this study show individuals in northwestern China do not live as long as those in eastern and southern China. A moderate climate is more conducive to longevity than extreme climate in China. The longevity of a region should be judged by long-term longevity indicators.

Is extreme climate or moderate climate more conducive to longevity in China?

PubMed

Huang, Yi; Rosenberg, Mark; Wang, Yingli

2018-06-01

Climate is closely related to human longevity. In China, there are many climate types. According to national population censuses from 1982 to 2000, most provinces with a high ratio of centenarians are located in western and northwestern China far from the sea; these areas are characterized by a dry, cold climate, very high altitude, very high daily temperature range, strong winds, and partial hypoxia. Meanwhile, provinces with a high ratio of nonagenarians from 1982 to 2000 are located in southern China near the sea. Previous studies have attributed the high ratio of centenarians in western and northwestern China to the extreme local climate. However, centenarians in these areas decreased greatly in 2010, whereas residents in southern China frequently reached 90 to 100 years old in 2010. This study aims to explain this strange phenomenon and find whether extreme climate in Tibetan plateau and northwestern China or moderate climate in southern China is more conducive to longevity. The study found that mortality rate in Tibetan plateau is much higher than southern China, then a population evolution experiment was proposed to compare longevity indicators between low mortality rate and high mortality rate and shows that longevity indicators will decrease in the near future and increase above their original levels after several decades when the mortality rate is decreased. Results of this study show individuals in northwestern China do not live as long as those in eastern and southern China. A moderate climate is more conducive to longevity than extreme climate in China. The longevity of a region should be judged by long-term longevity indicators.

Is extreme climate or moderate climate more conducive to longevity in China?

NASA Astrophysics Data System (ADS)

Huang, Yi; Rosenberg, Mark; Wang, Yingli

2018-06-01

Climate is closely related to human longevity. In China, there are many climate types. According to national population censuses from 1982 to 2000, most provinces with a high ratio of centenarians are located in western and northwestern China far from the sea; these areas are characterized by a dry, cold climate, very high altitude, very high daily temperature range, strong winds, and partial hypoxia. Meanwhile, provinces with a high ratio of nonagenarians from 1982 to 2000 are located in southern China near the sea. Previous studies have attributed the high ratio of centenarians in western and northwestern China to the extreme local climate. However, centenarians in these areas decreased greatly in 2010, whereas residents in southern China frequently reached 90 to 100 years old in 2010. This study aims to explain this strange phenomenon and find whether extreme climate in Tibetan plateau and northwestern China or moderate climate in southern China is more conducive to longevity. The study found that mortality rate in Tibetan plateau is much higher than southern China, then a population evolution experiment was proposed to compare longevity indicators between low mortality rate and high mortality rate and shows that longevity indicators will decrease in the near future and increase above their original levels after several decades when the mortality rate is decreased. Results of this study show individuals in northwestern China do not live as long as those in eastern and southern China. A moderate climate is more conducive to longevity than extreme climate in China. The longevity of a region should be judged by long-term longevity indicators.

Securing the Future of Water, Energy and Food: Can solutions for the currently stressed countries provide the direction for ensuring global water sustainability and food security in the 21st century?

NASA Astrophysics Data System (ADS)

Devineni, N.; Lall, U.

2014-12-01

Where will the food for the 9 billion people we expect on Earth by 2050 come from? The answer to this question depends on where the water and the energy for agriculture will come from. This assumes of course, that our primary food source will continue to be based on production on land, and that irrigation and the use of fertilizers to improve production are needed to address climate shocks and deteriorating soil health. Given this, establishing an economically, environmentally and physically feasible pathway to achieve water, energy and food security in the face of a changing climate is crucial to planetary well-being. A central hypothesis of the proposed paper is that innovation towards agricultural sustainability in countries such as India and China, that have large populations relative to their water, energy and arable land endowment, and yet have opportunity for improvement in productivity metrics such as crop yield per unit water or energy use, can show us the way to achieve global water-food-energy sustainability. These countries experience a monsoonal climate, which has a high frequency of climate extremes (more floods and droughts, and a short rainy season) relative to the developed countries in temperate climates. Global climate change projections indicate that the frequency and severity of extremes may pose a challenge in the future. Thus, strategies that are resilient to such extremes in monsoonal climates may be of global value in a warmer, more variable world. Much of the future population growth is expected to occur in Africa, S. America and S. Asia. Targeting these regions for higher productivity and resilience is consequently important from a national security perspective as well. Through this paper, we propose to (a) layout in detail, the challenges faced by the water, energy and food sectors in emerging countries, with specific focus on India and China and (b) provide the scientific background for an integrated systems analytic approach to formulate solutions at varying scales that can be employed globally. Such coordinated analyses is important for an examination of the future water sustainability in the face of changing climate, agricultural trends, environmental impacts and new energy choices.

Extreme heat reduces and shifts United States premium wine production in the 21st century

PubMed Central

White, M. A.; Diffenbaugh, N. S.; Jones, G. V.; Pal, J. S.; Giorgi, F.

2006-01-01

Premium wine production is limited to regions climatically conducive to growing grapes with balanced composition and varietal typicity. Three central climatic conditions are required: (i) adequate heat accumulation; (ii) low risk of severe frost damage; and (iii) the absence of extreme heat. Although wine production is possible in an extensive climatic range, the highest-quality wines require a delicate balance among these three conditions. Although historical and projected average temperature changes are known to influence global wine quality, the potential future response of wine-producing regions to spatially heterogeneous changes in extreme events is largely unknown. Here, by using a high-resolution regional climate model forced by the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios A2 greenhouse gas emission scenario, we estimate that potential premium winegrape production area in the conterminous United States could decline by up to 81% by the late 21st century. While increases in heat accumulation will shift wine production to warmer climate varieties and/or lower-quality wines, and frost constraints will be reduced, increases in the frequency of extreme hot days (>35°C) in the growing season are projected to eliminate winegrape production in many areas of the United States. Furthermore, grape and wine production will likely be restricted to a narrow West Coast region and the Northwest and Northeast, areas currently facing challenges related to excess moisture. Our results not only imply large changes for the premium wine industry, but also highlight the importance of incorporating fine-scale processes and extreme events in climate-change impact studies. PMID:16840557

Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios

USGS Publications Warehouse

Erikson, Li H.; Hegermiller, Christie; Barnard, Patrick; Ruggiero, Peter; van Ormondt, Martin

2015-01-01

Hindcast and 21st century winds, simulated by General Circulation Models (GCMs), were used to drive global- and regional-scale spectral wind-wave generation models in the Pacific Ocean Basin to assess future wave conditions along the margins of the North American west coast and Hawaiian Islands. Three-hourly winds simulated by four separate GCMs were used to generate an ensemble of wave conditions for a recent historical time-period (1976–2005) and projections for the mid and latter parts of the 21st century under two radiative forcing scenarios (RCP 4.5 and RCP 8.5), as defined by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) experiments. Comparisons of results from historical simulations with wave buoy and ERA-Interim wave reanalysis data indicate acceptable model performance of wave heights, periods, and directions, giving credence to generating projections. Mean and extreme wave heights are projected to decrease along much of the North American west coast. Extreme wave heights are projected to decrease south of ∼50°N and increase to the north, whereas extreme wave periods are projected to mostly increase. Incident wave directions associated with extreme wave heights are projected to rotate clockwise at the eastern end of the Aleutian Islands and counterclockwise offshore of Southern California. Local spatial patterns of the changing wave climate are similar under the RCP 4.5 and RCP 8.5 scenarios, but stronger magnitudes of change are projected under RCP 8.5. Findings of this study are similar to previous work using CMIP3 GCMs that indicates decreasing mean and extreme wave conditions in the Eastern North Pacific, but differ from other studies with respect to magnitude and local patterns of change. This study contributes toward a larger ensemble of global and regional climate projections needed to better assess uncertainty of potential future wave climate change, and provides model boundary conditions for assessing the impacts of climate change on coastal systems.

Characterizing the impact of projected changes in climate and ...

EPA Pesticide Factsheets

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O3) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O3 are much larger than the impacts of changing demographics.

Combined impacts of current and future dust deposition and regional warming on Colorado River Basin snow dynamics and hydrology

USGS Publications Warehouse

Deems, Jeffrey S.; Painter, Thomas H.; Barsugli, Joseph J.; Belnap, Jayne; Udall, Bradley

2013-01-01

The Colorado River provides water to 40 million people in seven western states and two countries and to 5.5 million irrigated acres. The river has long been overallocated. Climate models project runoff losses of 5–20% from the basin by mid-21st century due to human-induced climate change. Recent work has shown that decreased snow albedo from anthropogenic dust loading to the CO mountains shortens the duration of snow cover by several weeks relative to conditions prior to western expansion of the US in the mid-1800s, and advances peak runoff at Lees Ferry, Arizona, by an average of 3 weeks. Increases in evapotranspiration from earlier exposure of soils and germination of plants have been estimated to decrease annual runoff by more than 1.0 billion cubic meters, or ~5% of the annual average. This prior work was based on observed dust loadings during 2005–2008; however, 2009 and 2010 saw unprecedented levels of dust loading on snowpacks in the Upper Colorado River Basin (UCRB), being on the order of 5 times the 2005–2008 loading. Building on our prior work, we developed a new snow albedo decay parameterization based on observations in 2009/10 to mimic the radiative forcing of extreme dust deposition. We convolve low, moderate, and extreme dust/snow albedos with both historic climate forcing and two future climate scenarios via a delta method perturbation of historic records. Compared to moderate dust, extreme dust absorbs 2× to 4× the solar radiation, and shifts peak snowmelt an additional 3 weeks earlier to a total of 6 weeks earlier than pre-disturbance. The extreme dust scenario reduces annual flow volume an additional 1% (6% compared to pre-disturbance), a smaller difference than from low to moderate dust scenarios due to melt season shifting into a season of lower evaporative demand. The sensitivity of flow timing to dust radiative forcing of snow albedo is maintained under future climate scenarios, but the sensitivity of flow volume reductions decreases with increased climate forcing. These results have implications for water management and suggest that dust abatement efforts could be an important component of any climate adaptation strategies in the UCRB.

Addressing extreme precipitation change under future climates in the Upper Yangtze River Basin

NASA Astrophysics Data System (ADS)

Yang, Z.; Yuan, Z.; Gao, X.

2017-12-01

Investigating the impact of climate change on extreme precipitation accurately is of importance for application purposes such as flooding mitigation and urban drainage system design. In this paper, a systematical analysis framework to assess the impact of climate change on extreme precipitation events is developed and practiced in the Upper Yangtze River Basin (UYRB) in China. Firstly, the UYRB is gridded and five extreme precipitation indices (annual maximum 3- 5- 7- 15- and 30-day precipitation) are selected. Secondly, with observed precipitation from China's Ground Precipitation 0.5°×0.5° Gridded Dataset (V2.0) and simulated daily precipitation from ten general circulation models (GCMs) of CMIP5, A regionally efficient GCM is selected for each grid by the skill score (SS) method which maximizes the overlapped area of probability density functions of extreme precipitation indices between observations and simulations during the historical period. Then, simulations of assembled efficient GCMs are bias corrected by Equidistant Cumulative Distribution Function method. Finally, the impact of climate change on extreme precipitation is analyzed. The results show that: (1) the MRI-CGCM3 and MIROC-ESM perform better in the UYRB. There are 19.8 to 20.9% and 14.2 to 18.7% of all grids regard this two GCMs as regionally efficient GCM for the five indices, respectively. Moreover, the regionally efficient GCMs are spatially distributed. (2) The assembled GCM performs much better than any single GCM, with the SS>0.8 and SS>0.6 in more than 65 and 85 percent grids. (3) Under the RCP4.5 scenario, the extreme precipitation of 50-year and 100-year return period is projected to increase in most areas of the UYRB in the future period, with 55.0 to 61.3% of the UYRB increasing larger than 10 percent for the five indices. The changes are spatially and temporal distributed. The upstream region of the UYRB has a relatively significant increase compared to the downstream basin, while the increase for annual maximum 5- and 7-day precipitation are more significant than other indices. The results demonstrate the impact of climate change on extreme precipitation in the UYRB, which provides a support to manage the water resource in this area.

Effect of Climate Change on Surface Ozone over North America, Europe, and East Asia

NASA Technical Reports Server (NTRS)

Schnell, Jordan L.; Prather, Michael J.; Josse, Beatrice; Naik, Vaishali; Horowitz, Larry W.; Zeng, Guang; Shindell, Drew T.; Faluvegi, Greg

2016-01-01

The effect of future climate change on surface ozone over North America, Europe, and East Asia is evaluated using present-day (2000s) and future (2100s) hourly surface ozone simulated by four global models. Future climate follows RCP8.5, while methane and anthropogenic ozone precursors are fixed at year-2000 levels. Climate change shifts the seasonal surface ozone peak to earlier in the year and increases the amplitude of the annual cycle. Increases in mean summertime and high-percentile ozone are generally found in polluted environments, while decreases are found in clean environments. We propose climate change augments the efficiency of precursor emissions to generate surface ozone in polluted regions, thus reducing precursor export to neighboring downwind locations. Even with constant biogenic emissions, climate change causes the largest ozone increases at high percentiles. In most cases, air quality extreme episodes become larger and contain higher ozone levels relative to the rest of the distribution.

Impacts of Climate Change On The Occurrence of Extreme Events: The Mice Project

NASA Astrophysics Data System (ADS)

Palutikof, J. P.; Mice Team

It is widely accepted that climate change due to global warming will have substan- tial impacts on the natural environment, and on human activities. Furthermore, it is increasingly recognized that changes in the severity and frequency of extreme events, such as windstorm and flood, are likely to be more important than changes in the average climate. The EU-funded project MICE (Modelling the Impacts of Climate Extremes) commenced in January 2002. It seeks to identify the likely changes in the occurrence of extremes of rainfall, temperature and windstorm due to global warm- ing, using information from climate models as a basis, and to study the impacts of these changes in selected European environments. The objectives are: a) to evaluate, by comparison with gridded and station observations, the ability of climate models to successfully reproduce the occurrence of extremes at the required spatial and temporal scales. b) to analyse model output with respect to future changes in the occurrence of extremes. Statistical analyses will determine changes in (i) the return periods of ex- tremes, (ii) the joint probability of extremes (combinations of damaging events such as windstorm followed by heavy rain), (iii) the sequential behaviour of extremes (whether events are well-separated or clustered) and (iv) the spatial patterns of extreme event occurrence across Europe. The range of uncertainty in model predictions will be ex- plored by analysing changes in model experiments with different spatial resolutions and forcing scenarios. c) to determine the impacts of the predicted changes in extremes occurrence on selected activity sectors: agriculture (Mediterranean drought), commer- cial forestry and natural forest ecosystems (windstorm and flood in northern Europe, fire in the Mediterranean), energy use (temperature extremes), tourism (heat stress and Mediterranean beach holidays, changes in the snow pack and winter sports ) and civil protection/insurance (windstorm and flood). Impacts will be evaluated through a combination of techniques ranging from quantitative analyses through to expert judge- ment. Throughout the project, a continuing dialogue with stakeholders and end-users will be maintained.

Can Regional Climate Modeling Capture the Observed Changes in Spatial Organization of Extreme Storms at Higher Temperatures?

NASA Astrophysics Data System (ADS)

Li, J.; Wasko, C.; Johnson, F.; Evans, J. P.; Sharma, A.

2018-05-01

The spatial extent and organization of extreme storm events has important practical implications for flood forecasting. Recently, conflicting evidence has been found on the observed changes of storm spatial extent with increasing temperatures. To further investigate this question, a regional climate model assessment is presented for the Greater Sydney region, in Australia. Two regional climate models were considered: the first a convection-resolving simulation at 2-km resolution, the second a resolution of 10 km with three different convection parameterizations. Both the 2- and the 10-km resolutions that used the Betts-Miller-Janjic convective scheme simulate decreasing storm spatial extent with increasing temperatures for 1-hr duration precipitation events, consistent with the observation-based study in Australia. However, other observed relationships of extreme rainfall with increasing temperature were not well represented by the models. Improved methods for considering storm organization are required to better understand potential future changes.

Know your limits? Climate extremes impact the range of Scots pine in unexpected places

PubMed Central

Julio Camarero, J.; Gazol, Antonio; Sancho-Benages, Santiago; Sangüesa-Barreda, Gabriel

2015-01-01

Background and Aims Although extreme climatic events such as drought are known to modify forest dynamics by triggering tree dieback, the impact of extreme cold events, especially at the low-latitude margin (‘rear edge’) of species distributional ranges, has received little attention. The aim of this study was to examine the impact of one such extreme cold event on a population of Scots pine (Pinus sylvestris) along the species’ European southern rear-edge range limit and to determine how such events can be incorporated into species distribution models (SDMs). Methods A combination of dendrochronology and field observation was used to quantify how an extreme cold event in 2001 in eastern Spain affected growth, needle loss and mortality of Scots pine. Long-term European climatic data sets were used to contextualize the severity of the 2001 event, and an SDM for Scots pine in Europe was used to predict climatic range limits. Key Results The 2001 winter reached record minimum temperatures (equivalent to the maximum European-wide diurnal ranges) and, for trees already stressed by a preceding dry summer and autumn, this caused dieback and large-scale mortality. Needle loss and mortality were particularly evident in south-facing sites, where post-event recovery was greatly reduced. The SDM predicted European Scots pine distribution mainly on the basis of responses to maximum and minimum monthly temperatures, but in comparison with this the observed effects of the 2001 cold event at the southerly edge of the range limit were unforeseen. Conclusions The results suggest that in order to better forecast how anthropogenic climate change might affect future forest distributions, distribution modelling techniques such as SDMs must incorporate climatic extremes. For Scots pine, this study shows that the effects of cold extremes should be included across the entire distribution margin, including the southern ‘rear edge’, in order to avoid biased predictions based solely on warmer climatic scenarios. PMID:26292992

Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes remote SST anomalies.

The analyses of extreme climate events over China based on CMIP5 historical and future simulations

NASA Astrophysics Data System (ADS)

Yang, S.; Dong, W.; Feng, J.; Chou, J.

2013-12-01

The extreme climate events have a serious influence on human society. Based on observations and 12 simulations from Coupled Model Intercomparison Project Phase 5 (CMIP5), Climatic extremes and their changes over china in history and future scenarios of three Representative Concentration Pathways (RCPs) are analyzed. Because of the background of global warming, in observations, the frost days (FD) and low-temperature threshold days (TN10P) have decreasing trend, and summer days (SU), high-temperature threshold days (TX90P), the heavy precipitation days (R20) and contribution of heavy precipitation days (P95T) show an increasing trend. Most coupled models can basically simulate main characteristics of most extreme indexes. The models reproduce the mean FD and TX90P value best and can give basic trends of the FD, TN10P, SU and TX90P. High correlation coefficients between simulated results and observation are found in FD, SU and P95T. For FD and SU index, most of the models have good ability to capture the spatial differences between the mean state of the 1986-2005 and 1961-1980 periods, but for other indexes, most of models' simulation ability for spatial disparity are not so satisfactory and have to be promoted. Under the high emission scenario of RCP8.5, the century-scale linear changes of Multi-Model Ensembles (MME) for FD, SU, TN10P, TX90P, R20 and P95T are -46.9, 46.0, -27.1, 175.4, 2.9 days and 9.9%, respectively. Due to the complexities of physical process parameterizations and the limitation of forcing data, a large uncertainty still exists in the simulations of climatic extremes. Fig.1 Observed and modeled multi-year average for each index (Dotted line: observation) Table1. Extreme index definition

Deadly heat waves projected in the densely populated agricultural regions of South Asia

PubMed Central

Im, Eun-Soon; Pal, Jeremy S.; Eltahir, Elfatih A. B.

2017-01-01

The risk associated with any climate change impact reflects intensity of natural hazard and level of human vulnerability. Previous work has shown that a wet-bulb temperature of 35°C can be considered an upper limit on human survivability. On the basis of an ensemble of high-resolution climate change simulations, we project that extremes of wet-bulb temperature in South Asia are likely to approach and, in a few locations, exceed this critical threshold by the late 21st century under the business-as-usual scenario of future greenhouse gas emissions. The most intense hazard from extreme future heat waves is concentrated around densely populated agricultural regions of the Ganges and Indus river basins. Climate change, without mitigation, presents a serious and unique risk in South Asia, a region inhabited by about one-fifth of the global human population, due to an unprecedented combination of severe natural hazard and acute vulnerability. PMID:28782036

Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

NASA Astrophysics Data System (ADS)

El-Samra, R.; Bou-Zeid, E.; Bangalath, H. K.; Stenchikov, G.; El-Fadel, M.

2017-12-01

A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model's ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

Regaining momentum for international climate policy beyond Copenhagen

PubMed Central

2010-01-01

The 'Copenhagen Accord' fails to deliver the political framework for a fair, ambitious and legally-binding international climate agreement beyond 2012. The current climate policy regime dynamics are insufficient to reflect the realities of topical complexity, actor coalitions, as well as financial, legal and institutional challenges in the light of extreme time constraints to avoid 'dangerous' climate change of more than 2°C. In this paper we analyze these stumbling blocks for international climate policy and discuss alternatives in order to regain momentum for future negotiations. PMID:20525341

Potential effects of climate change on aquatic ecosystems of the Great Plains of North America

USGS Publications Warehouse

Covich, A.P.; Fritz, S.C.; Lamb, P.J.; Marzolf, R.D.; Matthews, W.J.; Poiani, K.A.; Prepas, E.E.; Richman, M.B.; Winter, T.C.

1997-01-01

The Great Plains landscape is less topographically complex than most other regions within North America, but diverse aquatic ecosystems, such as playas, pothole lakes, ox-bow lakes, springs, groundwater aquifers, intermittent and ephemeral streams, as well as large rivers and wetlands, are highly dynamic and responsive to extreme climatic fluctuations. We review the evidence for climatic change that demonstrates the historical importance of extremes in north-south differences in summer temperatures and east-west differences in aridity across four large subregions. These physical driving forces alter density stratification, deoxygenation, decomposition and salinity. Biotic community composition and associated ecosystem processes of productivity and nutrient cycling respond rapidly to these climatically driven dynamics. Ecosystem processes also respond to cultural effects such as dams and diversions of water for irrigation, waste dilution and urban demands for drinking water and industrial uses. Distinguishing climatic from cultural effects in future models of aquatic ecosystem functioning will require more refinement in both climatic and economic forecasting. There is a need, for example, to predict how long-term climatic forecasts (based on both ENSO and global warming simulations) relate to the permanence and productivity of shallow water ecosystems. Aquatic ecologists, hydrologists, climatologists and geographers have much to discuss regarding the synthesis of available data and the design of future interdisciplinary research. ?? 1997 by John Wiley & Sons, Ltd.

Opportunities and constraints for improved water resources management under increasing hydrological extremes

NASA Astrophysics Data System (ADS)

Wada, Y.

2017-12-01

Increased occurrence of extreme climate events is one of the most damaging consequences of global climate change today and in the future. Estimating the impacts of such extreme events on global and regional water resources is therefore crucial for quantifying increasing risks from climate change. The quest for water security has been a struggle throughout human history. Only in recent years has the scale of this quest moved beyond the local, to the national and regional scales and to the planet itself. Absent or unreliable water supply, sanitation and irrigation services, unmitigated floods and droughts, and degraded water environments severely impact half of the planet's population. The scale and complexity of the water challenges faced by society, particularly but not only in the world's poorest regions, are now recognized, as is the imperative of overcoming these challenges for a stable and equitable world. IIASA's Water Futures and Solutions Initiative (WFAS) is an unprecedented inter-disciplinary scientific initiative to identify robust and adaptive portfolios of optional solutions across different economic sectors, including agriculture, energy and industry, and to test these solution-portfolios with multi-model ensembles of hydrologic and sector models to obtain a clearer picture of the trade-offs, risks, and opportunities. The results of WFaS scenarios and models provide a basis for long-term strategic planning of water resource development under changing environments and increasing climate extremes. And given the complexity of the water system, WFaS uniquely provides policy makers with optional sets of solutions that work together and that can be easily adapted as circumstances change in the future. As WFaS progresses, it will establish a network involving information exchange, mutual learning and horizontal cooperation across teams of researchers, public and private decision makers and practitioners exploring solutions at regional, national and local scales. The initiative includes a major stakeholder consultation component, to inform and guide the science and to test and refine policy and business outcome.

Tick exposure and extreme climate events impact survival and threaten the persistence of a long-lived lizard.

PubMed

Jones, Alice R; Bull, C Michael; Brook, Barry W; Wells, Konstans; Pollock, Kenneth H; Fordham, Damien A

2016-03-01

Assessing the impacts of multiple, often synergistic, stressors on the population dynamics of long-lived species is becoming increasingly important due to recent and future global change. Tiliqua rugosa (sleepy lizard) is a long-lived skink (>30 years) that is adapted to survive in semi-arid environments with varying levels of parasite exposure and highly seasonal food availability. We used an exhaustive database of 30 years of capture-mark-recapture records to quantify the impacts of both parasite exposure and environmental conditions on the lizard's survival rates and long-term population dynamics. Lizard abundance was relatively stable throughout the study period; however, there were changing patterns in adult and juvenile apparent survival rates, driven by spatial and temporal variation in levels of tick exposure and temporal variation in environmental conditions. Extreme weather events during the winter and spring seasons were identified as important environmental drivers of survival. Climate models predict a dramatic increase in the frequency of extreme hot and dry winter and spring seasons in our South Australian study region; from a contemporary probability of 0.17 up to 0.47-0.83 in 2080 depending on the emissions scenario. Our stochastic population model projections showed that these future climatic conditions will induce a decline in the abundance of this long-lived reptile of up to 67% within 30 years from 2080, under worst case scenario modelling. The results have broad implications for future work investigating the drivers of population dynamics and persistence. We highlight the importance of long-term data sets and accounting for synergistic impacts between multiple stressors. We show that predicted increases in the frequency of extreme climate events have the potential to considerably and negatively influence a long-lived species, which might previously have been assumed to be resilient to environmental perturbations. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Adaptation resources for agriculture: Responding to climate variability and change in the midwest and northeast

Treesearch

Maria K. Janowiak; Daniel D. Dostie; Michael A. Wilson; Michael J. Kucera; R. Howard Skinner; Jerry L. Hatfield; David Hollinger; Christopher W. Swanston

2016-01-01

Changes in climate and extreme weather are already increasing challenges for agriculture nationally and globally, and many of these impacts will continue into the future. This technical bulletin contains information and resources designed to help agricultural producers, service providers, and educators in the Midwest and Northeast regions of the United States integrate...

Comparison Of Downscaled CMIP5 Precipitation Datasets For Projecting Changes In Extreme Precipitation In The San Francisco Bay Area.

NASA Technical Reports Server (NTRS)

Milesi, Cristina; Costa-Cabral, Mariza; Rath, John; Mills, William; Roy, Sujoy; Thrasher, Bridget; Wang, Weile; Chiang, Felicia; Loewenstein, Max; Podolske, James

2014-01-01

Water resource managers planning for the adaptation to future events of extreme precipitation now have access to high resolution downscaled daily projections derived from statistical bias correction and constructed analogs. We also show that along the Pacific Coast the Northern Oscillation Index (NOI) is a reliable predictor of storm likelihood, and therefore a predictor of seasonal precipitation totals and likelihood of extremely intense precipitation. Such time series can be used to project intensity duration curves into the future or input into stormwater models. However, few climate projection studies have explored the impact of the type of downscaling method used on the range and uncertainty of predictions for local flood protection studies. Here we present a study of the future climate flood risk at NASA Ames Research Center, located in South Bay Area, by comparing the range of predictions in extreme precipitation events calculated from three sets of time series downscaled from CMIP5 data: 1) the Bias Correction Constructed Analogs method dataset downscaled to a 1/8 degree grid (12km); 2) the Bias Correction Spatial Disaggregation method downscaled to a 1km grid; 3) a statistical model of extreme daily precipitation events and projected NOI from CMIP5 models. In addition, predicted years of extreme precipitation are used to estimate the risk of overtopping of the retention pond located on the site through simulations of the EPA SWMM hydrologic model. Preliminary results indicate that the intensity of extreme precipitation events is expected to increase and flood the NASA Ames retention pond. The results from these estimations will assist flood protection managers in planning for infrastructure adaptations.

Sea Extremes: Integrated impact assessment in coastal climate adaptation

NASA Astrophysics Data System (ADS)

Sorensen, Carlo; Knudsen, Per; Broge, Niels; Molgaard, Mads; Andersen, Ole

2016-04-01

We investigate effects of sea level rise and a change in precipitation pattern on coastal flooding hazards. Historic and present in situ and satellite data of water and groundwater levels, precipitation, vertical ground motion, geology, and geotechnical soil properties are combined with flood protection measures, topography, and infrastructure to provide a more complete picture of the water-related impact from climate change at an exposed coastal location. Results show that future sea extremes evaluated from extreme value statistics may, indeed, have a large impact. The integrated effects from future storm surges and other geo- and hydro-parameters need to be considered in order to provide for the best protection and mitigation efforts, however. Based on the results we present and discuss a simple conceptual model setup that can e.g. be used for 'translation' of regional sea level rise evidence and projections to concrete impact measures. This may be used by potentially affected stakeholders -often working in different sectors and across levels of governance, in a common appraisal of the challenges faced ahead. The model may also enter dynamic tools to evaluate local impact as sea level research advances and projections for the future are updated.

A Dynamic Flood Inundation Model Framework to Assess Coastal Flood Risk in a Changing Climate

NASA Astrophysics Data System (ADS)

Bilskie, M. V.; Hagen, S. C.; Passeri, D. L.; Alizad, K.; Medeiros, S. C.; Irish, J. L.

2015-12-01

Coastal regions around the world are susceptible to a variety of natural disasters causing extreme inundation. It is anticipated that the vulnerability of coastal cities will increase due to the effects of climate change, and in particular sea level rise (SLR). A novel framework was developed to generate a suite of physics-based storm surge models that include projections of coastal floodplain dynamics under climate change scenarios: shoreline erosion/accretion, dune morphology, salt marsh migration, and population dynamics. First, the storm surge inundation model was extensively validated for present day conditions with respect to astronomic tides and hindcasts of Hurricane Ivan (2004), Dennis (2005), Katrina (2005), and Isaac (2012). The model was then modified to characterize the future outlook of the landscape for four climate change scenarios for the year 2100 (B1, B2, A1B, and A2), and each climate change scenario was linked to a sea level rise of 0.2 m, 0.5 m, 1.2 m, and 2.0 m. The adapted model was then used to simulate hurricane storm surge conditions for each climate scenario using a variety of tropical cyclones as the forcing mechanism. The collection of results shows the intensification of inundation area and the vulnerability of the coast to potential future climate conditions. The methodology developed herein to assess coastal flooding under climate change can be performed across any coastal region worldwide, and results provide awareness of regions vulnerable to extreme flooding in the future. Note: The main theme behind this work is to appear in a future Earth's Future publication. Bilskie, M. V., S. C. Hagen, S. C. Medeiros, and D. L. Passeri (2014), Dynamics of sea level rise and coastal flooding on a changing landscape, Geophysical Research Letters, 41(3), 927-934. Parris, A., et al. (2012), Global Sea Level Rise Scenarios for the United States National Climate AssessmentRep., 37 pp. Passeri, D. L., S. C. Hagen, M. V. Bilskie, and S. C. Medeiros (2014), On the significance of incorporating shoreline changes for evaluating coastal hydrodynamics under sea level rise scenarios, Natural Hazards, 1599-1617. Passeri, D. L., S. C. Hagen, S. C. Medeiros, M. V. Bilskie, K. Alizad, and D. Wang (2015), The dynamic effects of sea level rise on low gradient coastal landscapes: a review, Earth's Future, 3.

Extreme Water Levels in Bangladesh: Past Trends, Future Projections and their Impact on Mortality

NASA Astrophysics Data System (ADS)

Thiele-Eich, I.; Burkart, K.; Hopson, T. M.; Simmer, C.

2014-12-01

Climate change is expected to have an impact on meteorological and therefore hydrological extremes, thereby possibly altering the vulnerability of exposed populations. Our study focuses on Bangladesh, which is particularly vulnerable to changes in extremes due to both the large population at risk, as well as geographical characteristics such as the low-rising slope of the country through which the outflow of the combined catchments of the Ganges, Brahmaputra and Meghna rivers (GBM, ~1.75 million km2) is channeled.Time series of daily discharge and water level data for the past 100 years were analyzed with respect to trends in frequency, magnitude and duration, focusing on rare but particularly high-risk events using extreme-value theory. Mortality data is available for a five-year period (2003-2007), with a distributed lag non-linear model used to examine possible connections between extreme water levels and mortality. Then, using output from the Community Climate System Model CCSM4, projections were made regarding future flooding due to changes in precipitation intensity and frequency, while also accounting for the backwater effect of sea-level rise. For this, the upper catchment precipitation as well as monthly mean thermosteric sea-level rise at the river mouth outflow were taken from the four CCSM4 1° 20th Century ensemble members as well as from six CCSM4 1° ensemble members for the RCP scenarios RCP 2.6, 4.5, 6.0 and 8.5.Results show that while e.g. the mean water level did not significantly rise during the past 100 years, a change in extreme water levels can be detected. In addition, annual minimum water levels have decreased, which is of particular importance as there is a significant connection to an increase in mortality for low water levels. While mortality does not seem to increase significantly due to extreme floods, our results indicate that return levels projected for the future shift progressively, with the effect being strongest for RCP 8.5. Further measures to strengthen the resilience of the exposed population are therefore required to ensure that climate change effects do not overwhelm the population's coping capacities.

Post-Fire Recovery of Eco-Hydrologic Behavior Given Historic and Projected Climate Variability in California Mediterranean Type Environments

NASA Astrophysics Data System (ADS)

Seaby, L. P.; Tague, C. L.; Hope, A. S.

2006-12-01

The Mediterranean type environments (MTEs) of California are characterized by a distinct wet and dry season and high variability in inter-annual climate. Water limitation in MTEs makes eco-hydrological processes highly sensitive to both climate variability and frequent fire disturbance. This research modeled post-fire eco- hydrologic behavior under historical and moderate and extreme scenarios of future climate in a semi-arid chaparral dominated southern California MTE. We used a physically-based, spatially-distributed, eco- hydrological model (RHESSys - Regional Hydro-Ecologic Simulation System), to capture linkages between water and vegetation response to the combined effects of fire and historic and future climate variability. We found post-fire eco-hydrologic behavior to be strongly influenced by the episodic nature of MTE climate, which intensifies under projected climate change. Higher rates of post-fire net primary productivity were found under moderate climate change, while more extreme climate change produced water stressed conditions which were less favorable for vegetation productivity. Precipitation variability in the historic record follows the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), and these inter-annual climate characteristics intensify under climate change. Inter-annual variation in streamflow follows these precipitation patterns. Post-fire streamflow and carbon cycling trajectories are strongly dependent on climate characteristics during the first 5 years following fire, and historic intra-climate variability during this period tends to overwhelm longer term trends and variation that might be attributable to climate change. Results have implications for water resource availability, vegetation type conversion from shrubs to grassland, and changes in ecosystem structure and function.

Characterization of extreme sea level at the European coast

NASA Astrophysics Data System (ADS)

Elizalde, Alberto; Jorda, Gabriel; Mathis, Moritz; Mikolajewicz, Uwe

2015-04-01

Extreme high sea levels arise as a combination of storm surges and particular high tides events. Future climate simulations not only project changes in the atmospheric circulation, which induces changes in the wind conditions, but also an increase in the global mean sea level by thermal expansion and ice melting. Such changes increase the risk of coastal flooding, which represents a possible hazard for human activities. Therefore, it is important to investigate the pattern of sea level variability and long-term trends at coastal areas. In order to analyze further extreme sea level events at the European coast in the future climate projections, a new setup for the global ocean model MPIOM coupled with the regional atmosphere model REMO is prepared. The MPIOM irregular grid has enhanced resolution in the European region to resolve the North and the Mediterranean Seas (up to 11 x 11 km at the North Sea). The ocean model includes as well the full luni-solar ephemeridic tidal potential for tides simulation. To simulate the air-sea interaction, the regional atmospheric model REMO is interactively coupled to the ocean model over Europe. Such region corresponds to the EuroCORDEX domain with a 50 x 50 km resolution. Besides the standard fluxes of heat, mass (freshwater), momentum and turbulent energy input, the ocean model is also forced with sea level pressure, in order to be able to capture the full variation of sea level. The hydrological budget within the study domain is closed using a hydrological discharge model. With this model, simulations for present climate and future climate scenarios are carried out to study transient changes on the sea level and extreme events. As a first step, two simulations (coupled and uncoupled ocean) driven by reanalysis data (ERA40) have been conducted. They are used as reference runs to evaluate the climate projection simulations. For selected locations at the coast side, time series of sea level are separated on its different components: tides, short time atmospheric process influence (1-30 days), seasonal cycle and interannual variability. Every sea level component is statistically compared with data from local tide gauges.

Current and future pluvial flood hazard analysis for the city of Antwerp

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099

USGS Publications Warehouse

Wood, Tamara M.; Wherry, Susan A.; Piccolroaz, Sebastiano; Girdner, Scott F

2016-05-04

The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.

Australia's Unprecedented Future Temperature Extremes Under Paris Limits to Warming

NASA Astrophysics Data System (ADS)

Lewis, Sophie C.; King, Andrew D.; Mitchell, Daniel M.

2017-10-01

Record-breaking temperatures can detrimentally impact ecosystems, infrastructure, and human health. Previous studies show that climate change has influenced some observed extremes, which are expected to become more frequent under enhanced future warming. Understanding the magnitude, as a well as frequency, of such future extremes is critical for limiting detrimental impacts. We focus on temperature changes in Australian regions, including over a major coral reef-building area, and assess the potential magnitude of future extreme temperatures under Paris Agreement global warming targets (1.5°C and 2°C). Under these limits to global mean warming, we determine a set of projected high-magnitude unprecedented Australian temperature extremes. These include extremes unexpected based on observational temperatures, including current record-breaking events. For example, while the difference in global-average warming during the hottest Australian summer and the 2°C Paris target is 1.1°C, extremes of 2.4°C above the observed summer record are simulated. This example represents a more than doubling of the magnitude of extremes, compared with global mean change, and such temperatures are unexpected based on the observed record alone. Projected extremes do not necessarily scale linearly with mean global warming, and this effect demonstrates the significant potential benefits of limiting warming to 1.5°C, compared to 2°C or warmer.

Facing the Future: Effects of Short-Term Climate Extremes on Isoprene-Emitting and Nonemitting Poplar1

PubMed Central

Vanzo, Elisa; Jud, Werner; Li, Ziru; Albert, Andreas; Domagalska, Malgorzata A.; Ghirardo, Andrea; Niederbacher, Bishu; Frenzel, Juliane; Beemster, Gerrit T.S.; Asard, Han; Rennenberg, Heinz; Sharkey, Thomas D.; Hansel, Armin; Schnitzler, Jörg-Peter

2015-01-01

Isoprene emissions from poplar (Populus spp.) plantations can influence atmospheric chemistry and regional climate. These emissions respond strongly to temperature, [CO2], and drought, but the superimposed effect of these three climate change factors are, for the most part, unknown. Performing predicted climate change scenario simulations (periodic and chronic heat and drought spells [HDSs] applied under elevated [CO2]), we analyzed volatile organic compound emissions, photosynthetic performance, leaf growth, and overall carbon (C) gain of poplar genotypes emitting (IE) and nonemitting (NE) isoprene. We aimed (1) to evaluate the proposed beneficial effect of isoprene emission on plant stress mitigation and recovery capacity and (2) to estimate the cumulative net C gain under the projected future climate. During HDSs, the chloroplastidic electron transport rate of NE plants became impaired, while IE plants maintained high values similar to unstressed controls. During recovery from HDS episodes, IE plants reached higher daily net CO2 assimilation rates compared with NE genotypes. Irrespective of the genotype, plants undergoing chronic HDSs showed the lowest cumulative C gain. Under control conditions simulating ambient [CO2], the C gain was lower in the IE plants than in the NE plants. In summary, the data on the overall C gain and plant growth suggest that the beneficial function of isoprene emission in poplar might be of minor importance to mitigate predicted short-term climate extremes under elevated [CO2]. Moreover, we demonstrate that an analysis of the canopy-scale dynamics of isoprene emission and photosynthetic performance under multiple stresses is essential to understand the overall performance under proposed future conditions. PMID:26162427

Modelling the potential impacts of afforestation on extreme precipitation over West Africa

NASA Astrophysics Data System (ADS)

Odoulami, Romaric C.; Abiodun, Babatunde J.; Ajayi, Ayodele E.

2018-05-01

This study examines how afforestation in West Africa could influence extreme precipitation over the region, with a focus on widespread extreme rainfall events (WEREs) over the afforestation area. Two regional climate models (RegCM and WRF) were applied to simulate the present-day climate (1971-2000) and future climate (2031-2060, under IPCC RCP 4.5 emission scenario) with and without afforestation of the Savannah zone in West Africa. The models give a realistic simulation of precipitation indices and WEREs over the subcontinent. On average, the regional models projected future decreases in total annual wet day precipitation (PRCPTOT) and total annual daily precipitation greater than or equal to the 95th percentile of daily precipitation threshold (R95pTOT) and increases in maximum number of consecutive dry days (CDD) over Sahel. Over Savannah, the models projected decreases in PRCPTOT but increases in R95pTOT and CDD. Also, an increase in WEREs frequency is projected over west, central and east Savannah, except that RegCM simulated a decrease in WEREs over east Savannah. In general, afforestation increases PRCPTOT and R95pTOT but decreases CDD over the afforestation area. The forest-induced increases in PRCPTOT and decreases in CDD affect all ecological zones in West Africa. However, the simulations show that afforestation of Savannah also decreases R95pTOT over the Guinea Coast. It further increases WEREs over west and central Savannah and decreases them over east Savannah because of the local decrease in R95pTOT. Results of this study suggest that the future changes in characteristics of extreme precipitation events over West Africa are sensitive to the ongoing land modification.

A comparison of methods to estimate future sub-daily design rainfall

NASA Astrophysics Data System (ADS)

Li, J.; Johnson, F.; Evans, J.; Sharma, A.

2017-12-01

Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

Using Extreme Tropical Precipitation Statistics to Constrain Future Climate States

NASA Astrophysics Data System (ADS)

Igel, M.; Biello, J. A.

2017-12-01

Tropical precipitation is characterized by a rapid growth in mean intensity as the column humidity increases. This behavior is examined in both a cloud resolving model and with high-resolution observations of precipitation and column humidity from CloudSat and AIRS, respectively. The model and the observations exhibit remarkable consistency and suggest a new paradigm for extreme precipitation. We show that the total precipitation can be decomposed into a product of contributions from a mean intensity, a probability of precipitation, and a global PDF of column humidity values. We use the modeling and observational results to suggest simple, analytic forms for each of these functions. The analytic representations are then used to construct a simple expression for the global accumulated precipitation as a function of the parameters of each of the component functions. As the climate warms, extreme precipitation intensity and global precipitation are expected to increase, though at different rates. When these predictions are incorporated into the new analytic expression for total precipitation, predictions for changes due to global warming to the probability of precipitation and the PDF of column humidity can be made. We show that strong constraints can be imposed on the future shape of the PDF of column humidity but that only weak constraints can be set on the probability of precipitation. These are largely imposed by the intensification of extreme precipitation. This result suggests that understanding precisely how extreme precipitation responds to climate warming is critical to predicting other impactful properties of global hydrology. The new framework can also be used to confirm and discount existing theories for shifting precipitation.

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.

Riparian responses to extreme climate and land-use change scenarios.

PubMed

Fernandes, Maria Rosário; Segurado, Pedro; Jauch, Eduardo; Ferreira, Maria Teresa

2016-11-01

Climate change will induce alterations in the hydrological and landscape patterns with effects on riparian ecotones. In this study we assess the combined effect of an extreme climate and land-use change scenario on riparian woody structure and how this will translate into a future risk of riparian functionality loss. The study was conducted in the Tâmega catchment of the Douro basin. Boosted Regression Trees (BRTs) were used to model two riparian landscape indicators related with the degree of connectivity (Mean Width) and complexity (Area Weighted Mean Patch Fractal Dimension). Riparian data were extracted by planimetric analysis of high spatial-resolution Word Imagery Layer (ESRI). Hydrological, climatic and land-use variables were obtained from available datasets and generated with process-based modeling using current climate data (2008-2014), while also considering the high-end RCP8.5 climate-change and "Icarus" socio-economic scenarios for the 2046-2065 time slice. Our results show that hydrological and land-use changes strongly influence future projections of riparian connectivity and complexity, albeit to diverse degrees and with differing effects. A harsh reduction in average flows may impair riparian zones while an increase in extreme rain events may benefit connectivity by promoting hydrologic dynamics with the surrounding floodplains. The expected increase in broad-leaved woodlands and mixed forests may enhance the riparian galleries by reducing the agricultural pressure on the area in the vicinity of the river. According to our results, 63% of river segments in the Tâmega basin exhibited a moderate risk of functionality loss, 16% a high risk, and 21% no risk. Weaknesses and strengths of the method are highlighted and results are discussed based on a resilience perspective with regard to riparian ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

High-resolution ensemble projections of near-term regional climate over the continental United States

DOE PAGES

Ashfaq, Moetasim; Rastogi, Deeksha; Mei, Rui; ...

2016-09-01

We present high-resolution near-term ensemble projections of hydro-climatic changes over the contiguous U.S. using a regional climate model (RegCM4) that dynamically downscales 11 Global Climate Models from the 5th phase of Coupled Model Inter-comparison Project at 18km horizontal grid spacing. All model integrations span 41 years in the historical period (1965 – 2005) and 41 years in the near-term future period (2010 – 2050) under Representative Concentration Pathway 8.5 and cover a domain that includes the contiguous U.S. and parts of Canada and Mexico. Should emissions continue to rise, surface temperatures in every region within the U.S. will reach amore » new climate norm well before mid 21st century regardless of the magnitudes of regional warming. Significant warming will likely intensify the regional hydrological cycle through the acceleration of the historical trends in cold, warm and wet extremes. The future temperature response will be partly regulated by changes in snow hydrology over the regions that historically receive a major portion of cold season precipitation in the form of snow. Our results indicate the existence of the Clausius-Clapeyron scaling at regional scales where per degree centigrade rise in surface temperature will lead to a 7.4% increase in precipitation from extremes. More importantly, both winter (snow) and summer (liquid) extremes are projected to increase across the U.S. These changes in precipitation characteristics will be driven by a shift towards shorter and wetter seasons. Altogether, projected changes in the regional hydro-climate can have substantial impacts on the natural and human systems across the U.S.« less

Scenario dependence of future changes in climate extremes under 1.5 °C and 2 °C global warming

NASA Astrophysics Data System (ADS)

Wang, Zhili; Lin, Lei; Zhang, Xiaoye; Zhang, Hua; Liu, Liangke; Xu, Yangyang

2017-04-01

The 2015 Paris Agreement aims to limit global warming below 2 °C and pursue efforts to even limit it to 1.5 °C relative to pre-industrial levels. Decision makers need reliable information on the impacts caused by these warming levels for climate mitigation and adaptation measures. We explore the changes in climate extremes, which are closely tied to economic losses and casualties, under 1.5 °C and 2 °C global warming and their scenario dependence using three sets of ensemble global climate model simulations. A warming of 0.5 °C (from 1.5 °C to 2 °C) leads to significant increases in temperature and precipitation extremes in most regions. However, the projected changes in climate extremes under both warming levels highly depend on the pathways of emissions scenarios, with different greenhouse gas (GHG)/aerosol forcing ratio and GHG levels. Moreover, there are multifold differences in several heavily polluted regions, among the scenarios, in the changes in precipitation extremes due to an additional 0.5 °C warming from 1.5 °C to 2 °C. Our results demonstrate that the chemical compositions of emissions scenarios, not just the total radiative forcing and resultant warming level, must be considered when assessing the impacts of global 1.5/2 °C warming.

Scenario dependence of future changes in climate extremes under 1.5 °C and 2 °C global warming.

PubMed

Wang, Zhili; Lin, Lei; Zhang, Xiaoye; Zhang, Hua; Liu, Liangke; Xu, Yangyang

2017-04-20

The 2015 Paris Agreement aims to limit global warming below 2 °C and pursue efforts to even limit it to 1.5 °C relative to pre-industrial levels. Decision makers need reliable information on the impacts caused by these warming levels for climate mitigation and adaptation measures. We explore the changes in climate extremes, which are closely tied to economic losses and casualties, under 1.5 °C and 2 °C global warming and their scenario dependence using three sets of ensemble global climate model simulations. A warming of 0.5 °C (from 1.5 °C to 2 °C) leads to significant increases in temperature and precipitation extremes in most regions. However, the projected changes in climate extremes under both warming levels highly depend on the pathways of emissions scenarios, with different greenhouse gas (GHG)/aerosol forcing ratio and GHG levels. Moreover, there are multifold differences in several heavily polluted regions, among the scenarios, in the changes in precipitation extremes due to an additional 0.5 °C warming from 1.5 °C to 2 °C. Our results demonstrate that the chemical compositions of emissions scenarios, not just the total radiative forcing and resultant warming level, must be considered when assessing the impacts of global 1.5/2 °C warming.

Scenario dependence of future changes in climate extremes under 1.5 °C and 2 °C global warming

PubMed Central

Wang, Zhili; Lin, Lei; Zhang, Xiaoye; Zhang, Hua; Liu, Liangke; Xu, Yangyang

2017-01-01

The 2015 Paris Agreement aims to limit global warming below 2 °C and pursue efforts to even limit it to 1.5 °C relative to pre-industrial levels. Decision makers need reliable information on the impacts caused by these warming levels for climate mitigation and adaptation measures. We explore the changes in climate extremes, which are closely tied to economic losses and casualties, under 1.5 °C and 2 °C global warming and their scenario dependence using three sets of ensemble global climate model simulations. A warming of 0.5 °C (from 1.5 °C to 2 °C) leads to significant increases in temperature and precipitation extremes in most regions. However, the projected changes in climate extremes under both warming levels highly depend on the pathways of emissions scenarios, with different greenhouse gas (GHG)/aerosol forcing ratio and GHG levels. Moreover, there are multifold differences in several heavily polluted regions, among the scenarios, in the changes in precipitation extremes due to an additional 0.5 °C warming from 1.5 °C to 2 °C. Our results demonstrate that the chemical compositions of emissions scenarios, not just the total radiative forcing and resultant warming level, must be considered when assessing the impacts of global 1.5/2 °C warming. PMID:28425445

The future of our National Forests: Enhancing adaptive capacity

Treesearch

Linda A. Joyce

2012-01-01

Ecosystems are changing in response to observed changes in climate, extreme events, and disturbances such as fire and insects. We read not only that these changes are occurring but that we should expect them to continue - changes in temperature; more extreme events; and more disturbances such as fire and insects that are not like the past. Key point: these changes in...

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Increasing impacts of climate extremes on critical infrastructures in Europe

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Climate, icing, and wild arctic reindeer: past relationships and future prospects.

PubMed

Hansen, Brage Bremset; Aanes, Ronny; Herfindal, Ivar; Kohler, Jack; Saether, Bernt-Erik

2011-10-01

Across the Arctic, heavy rain-on-snow (ROS) is an "extreme" climatic event that is expected to become increasingly frequent with global warming. This has potentially large ecosystem implications through changes in snowpack properties and ground-icing, which can block the access to herbivores' winter food and thereby suppress their population growth rates. However, the supporting empirical evidence for this is still limited. We monitored late winter snowpack properties to examine the causes and consequences of ground-icing in a Svalbard reindeer (Rangifer tarandus platyrhynchus) metapopulation. In this high-arctic area, heavy ROS occurred annually, and ground-ice covered from 25% to 96% of low-altitude habitat in the sampling period (2000-2010). The extent of ground-icing increased with the annual number of days with heavy ROS (> or = 10 mm) and had a strong negative effect on reindeer population growth rates. Our results have important implications as a downscaled climate projection (2021-2050) suggests a substantial future increase in ROS and icing. The present study is the first to demonstrate empirically that warmer and wetter winter climate influences large herbivore population dynamics by generating ice-locked pastures. This may serve as an early warning of the importance of changes in winter climate and extreme weather events in arctic ecosystems.

Managing Expectations: Results from Case Studies of US Water Utilities on Preparing for, Coping with, and Adapting to Extreme Events

NASA Astrophysics Data System (ADS)

Beller-Simms, N.; Metchis, K.

2014-12-01

Water utilities, reeling from increased impacts of successive extreme events such as floods, droughts, and derechos, are taking a more proactive role in preparing for future incursions. A recent study by Federal and water foundation investigators, reveals how six US water utilities and their regions prepared for, responded to, and coped with recent extreme weather and climate events and the lessons they are using to plan future adaptation and resilience activities. Two case studies will be highlighted. (1) Sonoma County, CA, has had alternating floods and severe droughts. In 2009, this area, home to competing water users, namely, agricultural crops, wineries, tourism, and fisheries faced a three-year drought, accompanied at the end by intense frosts. Competing uses of water threatened the grape harvest, endangered the fish industry and resulted in a series of regulations, and court cases. Five years later, new efforts by partners in the entire watershed have identified mutual opportunities for increased basin sustainability in the face of a changing climate. (2) Washington DC had a derecho in late June 2012, which curtailed water, communications, and power delivery during a record heat spell that impacted hundreds of thousands of residents and lasted over the height of the tourist-intensive July 4th holiday. Lessons from this event were applied three months later in anticipation of an approaching Superstorm Sandy. This study will help other communities in improving their resiliency in the face of future climate extremes. For example, this study revealed that (1) communities are planning with multiple types and occurrences of extreme events which are becoming more severe and frequent and are impacting communities that are expanding into more vulnerable areas and (2) decisions by one sector can not be made in a vacuum and require the scientific, sectoral and citizen communities to work towards sustainable solutions.

Can Dynamic Global Vegetation Models Reproduce Satellite Observed Extreme Browning and Greening Events in Vegetation Productivity?

NASA Astrophysics Data System (ADS)

van Eck, C. M.; Morfopoulos, C.; Betts, R. A.; Chang, J.; Ciais, P.; Friedlingstein, P.; Regnier, P. A. G.

2016-12-01

The frequency and severity of extreme climate events such as droughts, extreme precipitation and heatwaves are expected to increase in our changing climate. These extreme climate events will have an effect on vegetation either by enhanced or reduced productivity. Subsequently, this can have a substantial impact on the terrestrial carbon sink and thus the global carbon cycle, especially as extreme climate events are expected to increase in frequency and severity. Connecting observational datasets with modelling studies provides new insights into these climate-vegetation interactions. This study aims to compare extremes in vegetation productivity as derived from observations with that of Dynamic Global Vegetation Models (DGVMs). In this case GIMMS-NDVI 3g is selected as the observational dataset and both JULES (Joint UK Land Environment Simulator) and ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) as the DGVMs. Both models are forced with PGFv2 Global Meteorological Forcing Dataset according to the ISI-MIP2 protocol for historical runs. Extremes in vegetation productivity are the focal point, which are identified as NDVI anomalies below the 10th percentile or above the 90th percentile during the growing season, referred to as browning or greening events respectively. The monthly NDVI dataset GIMMS-NDVI 3g is used to obtain the location in time and space of the vegetation extremes. The global GIMMS-NDVI 3g dataset has been subdivided into IPCC's SREX-regions for which the NDVI anomalies are calculated and the extreme thresholds are determined. With this information we can identify the location in time and space of the browning and greening events in remotely-sensed vegetation productivity. The same procedure is applied to the modelled Gross Primary Productivity (GPP) allowing a comparison between the spatial and temporal occurrence of the browning and greening events in the observational dataset and the models' output. The capacity of the models to catch observed extremes in vegetation productivity is assessed and compared. Factors contributing to observed and modelled vegetation browning/greening extremes are analysed. The results of this study provide a stepping stone to modelling future extremes in vegetation productivity.

Future potential distribution of the emerging amphibian chytrid fungus under anthropogenic climate change.

PubMed

Rödder, Dennis; Kielgast, Jos; Lötters, Stefan

2010-11-01

Anthropogenic climate change poses a major threat to global biodiversity with a potential to alter biological interactions at all spatial scales. Amphibians are the most threatened vertebrates and have been subject to increasing conservation attention over the past decade. A particular concern is the pandemic emergence of the parasitic chytrid fungus Batrachochytrium dendrobatidis, which has been identified as the cause of extremely rapid large-scale declines and species extinctions. Experimental and observational studies have demonstrated that the host-pathogen system is strongly influenced by climatic parameters and thereby potentially affected by climate change. Herein we project a species distribution model of the pathogen onto future climatic scenarios generated by the IPCC to examine their potential implications on the pandemic. Results suggest that predicted anthropogenic climate change may reduce the geographic range of B. dendrobatidis and its potential influence on amphibian biodiversity.

Climate Exposure of US National Parks in a New Era of Change

PubMed Central

Monahan, William B.; Fisichelli, Nicholas A.

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901–2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change. PMID:24988483

Managing air and water quality in the face of uncertain futures: perspectives, perceptions, reported action, and needs for climate adaptation at the local level

NASA Astrophysics Data System (ADS)

Bedsworth, L. W.; Ekstrom, J.

2017-12-01

As the climate continues to shift, projections show amplified and more frequent extreme events, including coastal and inland flooding, wildfires, prolonged droughts, and heatwaves. Vital public goods, both air quality and water quality, can be critically affected by such extreme events. Climate change will make it increasingly difficult for managers to achieve public health targets for air and water quality. Successfully preparing governance structures developed to maintain and improve air and water quality may benefit from preventative strategies to avoid public health impacts and costs of climate change locally. Perceptions of climate change and its risks, actions taken so far, and perceived barriers to adaptation give insight into the needs of managers for preparing for climate change impacts. This paper compares results of two surveys that looked at local level management of air quality and water quality in California. Air quality managers consistently reported to recognize the risks of climate change on their sector, where water quality managers' perceptions varied between no concern to high concern. We explore the differences in governance, capacity influence the ill-defined responsibility and assumed roles of water and air districts in adaptation to extreme events increasing with climate change. The chain and network of managing air quality is compared with that of water quality - laying out similarities and differences. Then we compare how the survey respondents differed in terms of extreme weather-influenced threats to environmental quality. We end with a discussion of responsibility - where in the chain of managing these life-critical ecosystem services, is the need greatest for adapting to climate change and what does this mean for the other levels in the chain beyond the local management.

Climate exposure of US national parks in a new era of change.

PubMed

Monahan, William B; Fisichelli, Nicholas A

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901-2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change.

Assessing the Impact of Climate Change on Extreme Streamflow and Reservoir Operation for Nuuanu Watershed, Oahu, Hawaii

NASA Astrophysics Data System (ADS)

Leta, O. T.; El-Kadi, A. I.; Dulaiova, H.

2016-12-01

Extreme events, such as flooding and drought, are expected to occur at increased frequencies worldwide due to climate change influencing the water cycle. This is particularly critical for tropical islands where the local freshwater resources are very sensitive to climate. This study examined the impact of climate change on extreme streamflow, reservoir water volume and outflow for the Nuuanu watershed, using the Soil and Water Assessment Tool (SWAT) model. Based on the sensitive parameters screened by the Latin Hypercube-One-factor-At-a-Time (LH-OAT) method, SWAT was calibrated and validated to daily streamflow using the SWAT Calibration and Uncertainty Program (SWAT-CUP) at three streamflow gauging stations. Results showed that SWAT adequately reproduced the observed daily streamflow hydrographs at all stations. This was verified with Nash-Sutcliffe Efficiency that resulted in acceptable values of 0.58 to 0.88, whereby more than 90% of observations were bracketed within 95% model prediction uncertainty interval for both calibration and validation periods, signifying the potential applicability of SWAT for future prediction. The climate change impact on extreme flows, reservoir water volume and outflow was assessed under the Representative Concentration Pathways of 4.5 and 8.5 scenarios. We found wide changes in extreme peak and low flows ranging from -44% to 20% and -50% to -2%, respectively, compared to baseline. Consequently, the amount of water stored in Nuuanu reservoir will be decreased up to 27% while the corresponding outflow rates are expected to decrease up to 37% relative to the baseline. In addition, the stored water and extreme flows are highly sensitive to rainfall change when compared to temperature and solar radiation changes. It is concluded that the decrease in extreme low and peak flows can have serious consequences, such as flooding, drought, with detrimental effects on riparian ecological functioning. This study's results are expected to aid in reservoir operation as well as in identifying appropriate climate change adaptation strategies.

Development of National Future Extreme Heat Scenario to Enable the Assessment of Climate Impacts on Public Health

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Cresson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G.

2013-01-01

The project's emphasis is on providing assessments of the magnitude, frequency and geographic distribution of EHEs to facilitate public health studies. We focus on the daily to weekly time scales on which EHEs occur, not on decadal-scale climate changes. There is, however, a very strong connection between air temperature patterns at the two time scales and long-term climatic changes will certainly alter the frequency of EHEs.

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.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

Extreme Precipitation and Runoff under Changing Climate in Southern Maine

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

Yan, Eugene; Jared, Alissa; Mahat, Vinod

The quantification of extreme precipitation events is vitally important for designing and engineering water and flood sensitive infrastructure. Since this kind of infrastructure is usually built to last much longer than 10, 50, or even 100 years, there is great need for statistically sound estimates of the intensity of 10-, 50-, 100-, and 500-year rainstorms and associated floods. The recent assessment indicated that the intensity of the most extreme precipitation events (or the heaviest 1% of all daily events) have increased in every region of the contiguous states since the 1950s (Melillo et al. 2014). The maximum change in precipitationmore » intensity of extreme events occurred in the northeast region reaching 71%. The precipitation extremes can be characterized using intensity-duration-frequency analysis (IDF). However, the current IDFs in this region were developed around the assumption that climate condition remains stationary over the next 50 or 100 years. To better characterize the potential flood risk, this project will (1) develop precipitation IDFs on the basis of both historical observations and future climate projections from dynamic downscaling with Argonne National Laboratory’s (Argonne’s) regional climate model and (2) develop runoff IDFs using precipitation IDFs for the Casco Bay Watershed. IDF development also considers non-stationary distribution models and snowmelt effects that are not incorporated in the current IDFs.« less

ClimEx - Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec

NASA Astrophysics Data System (ADS)

Ludwig, Ralf; Baese, Frank; Braun, Marco; Brietzke, Gilbert; Brissette, Francois; Frigon, Anne; Giguère, Michel; Komischke, Holger; Kranzlmueller, Dieter; Leduc, Martin; Martel, Jean-Luc; Ricard, Simon; Schmid, Josef; von Trentini, Fabian; Turcotte, Richard; Weismueller, Jens; Willkofer, Florian; Wood, Raul

2017-04-01

The recent accumulation of extreme hydrological events in Bavaria and Québec has stimulated scientific and also societal interest. In addition to the challenges of an improved prediction of such situations and the implications for the associated risk management, there is, as yet, no confirmed knowledge whether and how climate change contributes to the magnitude and frequency of hydrological extreme events and how regional water management could adapt to the corresponding risks. The ClimEx project (2015-2019) investigates the effects of climate change on the meteorological and hydrological extreme events and their implications for water management in Bavaria and Québec. High Performance Computing is employed to enable the complex simulations in a hydro-climatological model processing chain, resulting in a unique high-resolution and transient (1950-2100) dataset of climatological and meteorological forcing and hydrological response: (1) The climate module has developed a large ensemble of high resolution data (12km) of the CRCM5 RCM for Central Europe and North-Eastern North America, downscaled from 50 members of the CanESM2 GCM. The dataset is complemented by all available data from the Euro-CORDEX project to account for the assessment of both natural climate variability and climate change. The large ensemble with several thousand model years provides the potential to catch rare extreme events and thus improves the process understanding of extreme events with return periods of 1000+ years. (2) The hydrology module comprises process-based and spatially explicit model setups (e.g. WaSiM) for all major catchments in Bavaria and Southern Québec in high temporal (3h) and spatial (500m) resolution. The simulations form the basis for in depth analysis of hydrological extreme events based on the inputs from the large climate model dataset. The specific data situation enables to establish a new method for 'virtual perfect prediction', which assesses climate change impacts on flood risk and water resources management by identifying patterns in the data which reveal preferential triggers of hydrological extreme events. The presentation will highlight first results from the analysis of the large scale ClimEx model ensemble, showing the current and future ratio of natural variability and climate change impacts on meteorological extreme events. Selected data from the ensemble is used to drive a hydrological model experiment to illustrate the capacity to better determine the recurrence periods of hydrological extreme events under conditions of climate change. [The authors acknowledge funding for the project from the Bavarian State Ministry for the Environment and Consumer Protection].

Investigation of temperature and its indices under climate change scenarios over different regions of Rajasthan state in India

NASA Astrophysics Data System (ADS)

Sharma, Aditya; Sharma, Devesh; Panda, S. K.; Dubey, Swatantra Kumar; Pradhan, Rajani K.

2018-02-01

The ongoing increases in concentrations of atmospheric greenhouse gas will most likely affect global climate for the rest of this century. Global warming brings a huge provocation to society and human beings. Single extreme events and increased climate variability have a greater impact than long-term changes in the mean of climatic variables. This study analyzed the temperature projections for Rajasthan state, India using data obtain from two General Circulation Models (GFCM21 and HadCM3) for three Intergovernmental Panel on Climate Change (IPCC) Special Range of Emission Scenarios (SRES) A1B, A2, and B1. A 30 years of maximum (Tmax) and minimum (Tmin) temperature for the period 1976-2005 has been obtained from India Meteorological Department (IMD) and by using LARS-WG5 to generate the long-term weather series for three different periods i.e. 2011-2040 (2025s), 2041-2070 (2055s), and 2071-2100 (2085s). Further to determine the changes in extreme temperature events, the data for the baseline period and the future periods was represented by eight extreme temperature indices. Results illustrate that an increase in minimum and the maximum temperature are observed in all the three future periods. The average mean temperature for base period and three future periods over four regions of Rajasthan was observed highest in region 3 which shows an incessantly increased in mean temperature about 2.6 °C i.e. north-east and north-west part of Rajasthan. Two GCMs depicts that the incessant temperatures may be increase in the future and future maximum temperature in all the seasons varies from 2.43 °C to 4.27 °C in the direction from south to north of Rajasthan during 2071-2100. While for minimum temperature, the range of temperature changes varies from 0.23 °C to 1.42 °C from south-east to north-west of Rajasthan during 2011-2040. In the temperature indices, the number of tropical nights (TR20), warmest day (TX90p), warmest night (TN90p) and summer days (SU25) is expected to increase during all three future periods. The maximum changes was found in region 2 (39.4 days) and region 1 (38.8 days) during the 2071-2100 periods, followed by 2041-2070 and 2011-2040. In all the four regions, the annual occurrence of Cold Spells Duration Indicator (CSDI) decreased and Warm Spells Duration Indicator (WSDI) increased for all three future periods.

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

Chen, Gang

Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very widemore » range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.« less

A Regional-Scale Evaluation on Environmental Stability Conditions for Convective Rain under Climate Change from Super-High-Resolution GCM Simulations

NASA Astrophysics Data System (ADS)

Takemi, T.; Nomura, S.; Oku, Y.; Ishikawa, H.

2011-12-01

Understanding and forecasting of convective rain due to intense thunderstorms, which develop under conditions both with and without significant synoptic-scale and/or mesoscale forcings, are critical in dealing with disaster prevention/mitigation and developing urban planning appropriate for disaster management. Thunderstorms rapidly develop even during the daytimes of fair weather conditions without any external forcings, and sometimes become strong enough to induce local-scale meteorological disasters such as torrential rain, flush flooding, high winds, and tornadoes/gusts. With the growing interests in climate change, future changes in the behavior of such convectively generated extreme events have gained scientific and societal interests. This study conducted the regional-scale evaluations on the environmental stability conditions for convective rain that develops under synoptically undisturbed, summertime conditions by using the outputs of super-high-resolution AGCM simulations, at a 20-km resolution, for the present, the near-future, and the future climates under global warming with IPCC A1B emission scenario. The GCM, MRI-AGCM3.2S, was developed by Meteorological Research Institute of Japan Meteorological Agency under the KAKUSHIN program funded by the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The climate simulation outputs that were used in this study corresponded to three 25-year periods: 1980-2004 for the present climate; 2020-2044 for the near-future climate; and 2075-2099 for the future climate. The Kanto Plain that includes the Tokyo metropolitan area was chosen as the study area, since the Tokyo metropolitan area is one of the largest metropolises in the world and is vulnerable to extreme weather events. Therefore, one of the purposes of this study was to examine how regional-scale evaluations are performed from the super-high-resolution GCM outputs. After verifying the usefulness of the GCM present-climate outputs with observations and operational mesoscale analyses, we examined, as another purpose of this study, the future changes in the environmental stability for convective rain. To diagnose the environmental conditions, some of the commonly used stability parameters and indices were examined. In the future climates, temperature lapse rate decreased in the lower troposphere, while water vapor mixing ratio increased throughout the deep troposphere. The changes in the temperature and moisture profiles resulted in the increase in both precipitable water vapor and convective available potential energy. These projected changes will be enhanced with the future period. Furthermore, the statistical analyses for the differences of the stability parameters between no-rain and rain days under the synoptically undisturbed condition in each simulated climate period indicated that the environmental conditions in terms of the stability parameters that distinguish no-rain and rain events are basically unchanged between the present and the future climates. This result suggests that the environmental characteristics favorable for afternoon rain events in the synoptically undisturbed environments will not change under global warming.

Increasing precipitation volatility in twenty-first-century California

NASA Astrophysics Data System (ADS)

Swain, Daniel L.; Langenbrunner, Baird; Neelin, J. David; Hall, Alex

2018-05-01

Mediterranean climate regimes are particularly susceptible to rapid shifts between drought and flood—of which, California's rapid transition from record multi-year dryness between 2012 and 2016 to extreme wetness during the 2016-2017 winter provides a dramatic example. Projected future changes in such dry-to-wet events, however, remain inadequately quantified, which we investigate here using the Community Earth System Model Large Ensemble of climate model simulations. Anthropogenic forcing is found to yield large twenty-first-century increases in the frequency of wet extremes, including a more than threefold increase in sub-seasonal events comparable to California's `Great Flood of 1862'. Smaller but statistically robust increases in dry extremes are also apparent. As a consequence, a 25% to 100% increase in extreme dry-to-wet precipitation events is projected, despite only modest changes in mean precipitation. Such hydrological cycle intensification would seriously challenge California's existing water storage, conveyance and flood control infrastructure.

Projections of Future Summer Weather in Seoul and Their Impacts on Urban Agriculture

NASA Astrophysics Data System (ADS)

Kim, S. O.; Kim, J. H.; Yun, J. I.

2015-12-01

Climate departure from the past variability was projected to start in 2042 for Seoul. In order to understand the implication of climate departure in Seoul for urban agriculture, we evaluated the daily temperature for the June-September period from 2041 to 2070, which were projected by the RCP8.5 climate scenario. These data were analyzed with respect to climate extremes and their effects on growth of hot pepper (Capsicum annuum), one of the major crops in urban farming. The mean daily maximum and minimum temperatures in 2041-2070 approached to the 90th percentile in the past 30 years (1951- 1980). However, the frequency of extreme events such as heat waves and tropical nights appeared to exceed the past variability. While the departure of mean temperature might begin in or after 2040, the climate departure in the sense of extreme weather events seems already in progress. When the climate scenario data were applied to the growth and development of hot pepper, the departures of both planting date and harvest date are expected to follow those of temperature. However, the maximum duration for hot pepper cultivation, which is the number of days between the first planting and the last harvest, seems to have already deviated from the past variability.

Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability

NASA Technical Reports Server (NTRS)

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid; Stewardson, Michael J.; Peel, Murray C.; Phillips, Thomas J.; Wada, Yoshihide; Ravalico, Jakin K.

2017-01-01

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the region could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.

Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability.

PubMed

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid; Stewardson, Michael J; Peel, Murray C; Phillips, Thomas J; Wada, Yoshihide; Ravalico, Jakin K

2017-07-24

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the region could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.

Analysis of regional natural flow for evaluation of flood risk according to RCP climate change scenarios

NASA Astrophysics Data System (ADS)

Lee, J. Y.; Chae, B. S.; Wi, S.; KIm, T. W.

2017-12-01

Various climate change scenarios expect the rainfall in South Korea to increase by 3-10% in the future. The future increased rainfall has significant effect on the frequency of flood in future as well. This study analyzed the probability of future flood to investigate the stability of existing and new installed hydraulic structures and the possibility of increasing flood damage in mid-sized watersheds in South Korea. To achieve this goal, we first clarified the relationship between flood quantiles acquired from the flood-frequency analysis (FFA) and design rainfall-runoff analysis (DRRA) in gauged watersheds. Then, after synthetically generating the regional natural flow data according to RCP climate change scenarios, we developed mathematical formulas to estimate future flood quantiles based on the regression between DRRA and FFA incorporated with regional natural flows in unguaged watersheds. Finally, we developed a flood risk map to investigate the change of flood risk in terms of the return period for the past, present, and future. The results identified that the future flood quantiles and risks would increase in accordance with the RCP climate change scenarios. Because the regional flood risk was identified to increase in future comparing with the present status, comprehensive flood control will be needed to cope with extreme floods in future.

Loss of ecosystem productivity with repeated drought: a multi-year experiment to assess the role of drought legacy effects

NASA Astrophysics Data System (ADS)

Smith, M. D.; Knapp, A.; Hoover, D. L.; Avolio, M. L.; Felton, A. J.; Slette, I.; Wilcox, K.

2017-12-01

Climate extremes, such as drought, are increasing in frequency and intensity, and the ecological consequences of these extreme events can be substantial and widespread. Yet, little is known about the factors that determine recovery of ecosystem function post-drought. Such knowledge is particularly important because post-drought recovery periods can be protracted depending on drought legacy effects (e.g., loss key plant populations, altered community structure and/or biogeochemical processes). These drought legacies may alter ecosystem function for many years post-drought and may impact future sensitivity to climate extremes. With forecasts of more frequent drought, there is an imperative to understand whether and how post-drought legacies will affect ecosystem response to future drought events. To address this knowledge gap, we experimentally imposed over an eight year period two extreme growing season droughts, each two years in duration followed by a two-year recovery period, in a central US grassland. We found that aboveground net primary productivity (ANPP) declined dramatically with the first drought and was accompanied by a large shift in plant species composition (loss of C3 forb and increase in C4 grasses). This drought legacy - shift in plant composition - persisted two years post-drought. Yet, despite this legacy, ANPP recovered fully. However, we expected that previously-droughted grassland would be less sensitive to a second extreme drought due to the shift in plant composition. Contrary to this expectation, previously droughted grassland experienced a greater loss in ANPP than grassland that had not experienced drought. Furthermore, previously droughted grassland did not fully recover after the second drought. Thus, the legacy of drought - a shift in plant community composition - increased ecosystem sensitivity to a future extreme drought event.

Climate change impacts on human health over Europe through its effect on air quality.

PubMed

Doherty, Ruth M; Heal, Mathew R; O'Connor, Fiona M

2017-12-05

This review examines the current literature on the effects of future emissions and climate change on particulate matter (PM) and O 3 air quality and on the consequent health impacts, with a focus on Europe. There is considerable literature on the effects of climate change on O 3 but fewer studies on the effects of climate change on PM concentrations. Under the latest Intergovernmental Panel on Climate Change (IPCC) 5th assessment report (AR5) Representative Concentration Pathways (RCPs), background O 3 entering Europe is expected to decrease under most scenarios due to higher water vapour concentrations in a warmer climate. However, under the extreme pathway RCP8.5 higher (more than double) methane (CH 4 ) abundances lead to increases in background O 3 that offset the O 3 decrease due to climate change especially for the 2100 period. Regionally, in polluted areas with high levels of nitrogen oxides (NO x ), elevated surface temperatures and humidities yield increases in surface O 3 - termed the O 3 climate penalty - especially in southern Europe. The O 3 response is larger for metrics that represent the higher end of the O 3 distribution, such as daily maximum O 3 . Future changes in PM concentrations due to climate change are much less certain, although several recent studies also suggest a PM climate penalty due to high temperatures and humidity and reduced precipitation in northern mid-latitude land regions in 2100.A larger number of studies have examined both future climate and emissions changes under the RCP scenarios. Under these pathways the impact of emission changes on air quality out to the 2050s will be larger than that due to climate change, because of large reductions in emissions of O 3 and PM pollutant precursor emissions and the more limited climate change response itself. Climate change will also affect climate extreme events such as heatwaves. Air pollution episodes are associated with stagnation events and sometimes heat waves. Air quality during the 2003 heatwave over Europe has been examined in numerous studies and mechanisms for enhancing O 3 have been identified.There are few studies on health effects associated with climate change impacts alone on air quality, but these report higher O 3 -related health burdens in polluted populated regions and greater PM 2.5 health burdens in these emission regions. Studies that examine the combined impacts of climate change and anthropogenic emissions change under the RCP scenarios report reductions in global and European premature O 3 -respiratory related and PM mortalities arising from the large decreases in precursor emissions. Under RCP 8.5 the large increase in CH 4 leads to global and European excess O 3 -respiratory related mortalities in 2100. For future health effects, besides uncertainty in future O 3 and particularly PM concentrations, there is also uncertainty in risk estimates such as effect modification by temperature on pollutant-response relationships and potential future adaptation that would alter exposure risk.

Future equivalent of 2010 Russian heatwave intensified by weakening soil moisture constraints

NASA Astrophysics Data System (ADS)

Rasmijn, L. M.; van der Schrier, G.; Bintanja, R.; Barkmeijer, J.; Sterl, A.; Hazeleger, W.

2018-05-01

The 2010 heatwave in eastern Europe and Russia ranks among the hottest events ever recorded in the region1,2. The excessive summer warmth was related to an anomalously widespread and intense quasi-stationary anticyclonic circulation anomaly over western Russia, reinforced by depletion of spring soil moisture1,3-5. At present, high soil moisture levels and strong surface evaporation generally tend to cap maximum summer temperatures6-8, but these constraints may weaken under future warming9,10. Here, we use a data assimilation technique in which future climate model simulations are nudged to realistically represent the persistence and strength of the 2010 blocked atmospheric flow. In the future, synoptically driven extreme warming under favourable large-scale atmospheric conditions will no longer be suppressed by abundant soil moisture, leading to a disproportional intensification of future heatwaves. This implies that future mid-latitude heatwaves analogous to the 2010 event will become even more extreme than previously thought, with temperature extremes increasing by 8.4 °C over western Russia. Thus, the socioeconomic impacts of future heatwaves will probably be amplified beyond current estimates.

Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes

NASA Astrophysics Data System (ADS)

Iizumi, Toshichika; Takikawa, Hiroki; Hirabayashi, Yukiko; Hanasaki, Naota; Nishimori, Motoki

2017-08-01

The use of different bias-correction methods and global retrospective meteorological forcing data sets as the reference climatology in the bias correction of general circulation model (GCM) daily data is a known source of uncertainty in projected climate extremes and their impacts. Despite their importance, limited attention has been given to these uncertainty sources. We compare 27 projected temperature and precipitation indices over 22 regions of the world (including the global land area) in the near (2021-2060) and distant future (2061-2100), calculated using four Representative Concentration Pathways (RCPs), five GCMs, two bias-correction methods, and three reference forcing data sets. To widen the variety of forcing data sets, we developed a new forcing data set, S14FD, and incorporated it into this study. The results show that S14FD is more accurate than other forcing data sets in representing the observed temperature and precipitation extremes in recent decades (1961-2000 and 1979-2008). The use of different bias-correction methods and forcing data sets contributes more to the total uncertainty in the projected precipitation index values in both the near and distant future than the use of different GCMs and RCPs. However, GCM appears to be the most dominant uncertainty source for projected temperature index values in the near future, and RCP is the most dominant source in the distant future. Our findings encourage climate risk assessments, especially those related to precipitation extremes, to employ multiple bias-correction methods and forcing data sets in addition to using different GCMs and RCPs.

The interplay of climate and land use change affects the distribution of EU bumblebees.

PubMed

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

2018-01-01

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

Escalating impacts of climate extremes on critical infrastructures in Europe.

PubMed

Forzieri, Giovanni; Bianchi, Alessandra; Silva, Filipe Batista E; Marin Herrera, Mario A; Leblois, Antoine; Lavalle, Carlo; Aerts, Jeroen C J H; Feyen, Luc

2018-01-01

Extreme climatic events are likely to become more frequent owing to global warming. This may put additional stress on critical infrastructures with typically long life spans. However, little is known about the risks of multiple climate extremes on critical infrastructures at regional to continental scales. Here we show how single- and multi-hazard damage to energy, transport, industrial, and social critical infrastructures in Europe are likely to develop until the year 2100 under the influence of climate change. We combine a set of high-resolution climate hazard projections, a detailed representation of physical assets in various sectors and their sensitivity to the hazards, and more than 1100 records of losses from climate extremes in a prognostic modelling framework. We find that damages could triple by the 2020s, multiply six-fold by mid-century, and amount to more than 10 times present damage of €3.4 billion per year by the end of the century due only to climate change. Damage from heatwaves, droughts in southern Europe, and coastal floods shows the most dramatic rise, but the risks of inland flooding, windstorms, and forest fires will also increase in Europe, with varying degrees of change across regions. Economic losses are highest for the industry, transport, and energy sectors. Future losses will not be incurred equally across Europe. Southern and south-eastern European countries will be most affected and, as a result, will probably require higher costs of adaptation. The findings of this study could aid in prioritizing regional investments to address the unequal burden of impacts and differences in adaptation capacities across Europe.

Cold-related mortality vs heat-related mortality in a changing climate: A case study in Vilnius (Lithuania).

PubMed

Martinez, Gerardo Sanchez; Diaz, Julio; Hooyberghs, Hans; Lauwaet, Dirk; De Ridder, Koen; Linares, Cristina; Carmona, Rocio; Ortiz, Cristina; Kendrovski, Vladimir; Adamonyte, Dovile

2018-06-21

Direct health effects of extreme temperatures are a significant environmental health problem in Lithuania, and could worsen further under climate change. This paper attempts to describe the change in environmental temperature conditions that the urban population of Vilnius could experience under climate change, and the effects such change could have on excess heat-related and cold-related mortality in two future periods within the 21st century. We modelled the urban climate of Vilnius for the summer and winter seasons during a sample period (2009-2015) and projected summertime and wintertime daily temperatures for two prospective periods, one in the near (2030-2045) and one in the far future (2085-2100), under the Representative Concentration Pathway (RCP) 8.5. We then analysed the historical relationship between temperature and mortality for the period 2009-2015, and estimated the projected mortality in the near future and far future periods under a changing climate and population, assuming alternatively no acclimatisation and acclimatisation to heat and cold based on a constant-percentile threshold temperature. During the sample period 2009-2015 in summertime we observed an increase in daily mortality from a maximum daily temperature of 30 °C (the 96th percentile of the series), with an average of around 7 deaths per year. Under a no acclimatisation scenario, annual average heat-related mortality would rise to 24 deaths/year (95% CI: 8.4-38.4) in the near future and to 46 deaths/year (95% CI: 16.4-74.4) in the far future. Under a heat acclimatisation scenario, mortality would not increase significantly in the near or in the far future. Regarding wintertime cold-related mortality in the sample period 2009-2015, we observed increased mortality on days on which the minimum daily temperature fell below - 12 °C (the 7th percentile of the series), with an average of around 10 deaths a year. Keeping the threshold temperature constant, annual average cold-related mortality would decrease markedly in the near future, to 5 deaths/year (95% CI: 0.8-7.9) and even more in the far future, down to 0.44 deaths/year (95% C: 0.1-0.8). Assuming a "middle ground" between the acclimatisation and non-acclimatisation scenarios, the decrease in cold-related mortality will not compensate the increase in heat-related mortality. Thermal extremes, both heat and cold, constitute a serious public health threat in Vilnius, and in a changing climate the decrease in mortality attributable to cold will not compensate for the increase in mortality attributable to heat. Study results reinforce the notion that public health prevention against thermal extremes should be designed as a dynamic, adaptive process from the inception. Copyright © 2018 Elsevier Inc. All rights reserved.

Quantitative assessment of current and future risks related rainfall in processing tomato in the Guadiana river basin (SW Spain)

NASA Astrophysics Data System (ADS)

Castañeda-Vera, Alba; Garrido, Alberto; Ruiz-Ramos, Margarita; Sánchez-Sánchez, Enrique; Inés Mínguez, M.

2013-04-01

An extension of risk coverages in the insurance policies for processing tomato, mainly related to rainfall events, has resulted in an important increase in claims. This suggests that damages related to extreme or ill-timed showers have been underestimated in previous years. An estimation of damages related to rainfall in the last thirty years and the impact of climate change in the risk related to rainfall in processing tomato crops in the Guadiana river basin (SW Spain) were studied through a risk index. First, the risk index was defined with temperature and relative humidity thresholds related to different damage magnitudes. Then, this index was applied to current climate and to future climate scenarios in nine weather stations representative of the studied area to determine the trends in losses related to extreme or inopportune rainfall events. Thresholds of temperature and relative humidity were obtained from cross-checking agricultural insurance records and meteorological data from local weather stations (REDAREX, http://sw-aperos.juntaex.es/redarex). To consider longer time series, the reanalysis database ERA-INTERIM (Dee et al., 2011) was used. Simulated climate was obtained from the European Project ENSEMBLES (http://www.ensembles-eu.org/). Trends in climatic risk were analysed by applying the risk index to three sets of data defining current climate (1980-2010), mid-future climate (2010-2040) and long-term future climate (2040-2070). An algorithm to choose the surrounding cell that minimizes the temperature and precipitation climatic biases and maximizes seasonal correlation when comparing ENSEMBLES regional climate model simulations and observed climate was applied before index calculation. The results show the trends in frequency and magnitude of the risk of suffering damages related to rainfall events. The methodology decreased the uncertainty on risk levels. Results contribute to detect the periods during the growing season with larger risk of damage in order to provide information to assist research on risk management practices and to support insurance policy makers to extend guaranties and to adapt the insurance conditions and costs to real crop risks. This research is being financed by MULCLIVAR project (CGL2012-38923-C02-02), MINECO, Spain Keywords: climate change, risk, rainfall, processing tomato. References Dee, D. P., with 35 co-authors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. R. Meteorol. Soc., 137, 553-597.

A socioeconomic assessment of climate change-enhanced coastal storm hazards in the U.S. Pacific Northwest

NASA Astrophysics Data System (ADS)

Baron, H. M.; Ruggiero, P.; Harris, E.

2010-12-01

Every winter, coastal communities in the U.S. Pacific Northwest are at risk to coastal change hazards caused by extreme storm events. These storms have the potential to erode large portions of the primary foredune that may be a community’s only barrier from the ocean. Furthermore, the frequency and magnitude of significant erosion events appears to be increasing, likely due to climate-related processes such as sea level rise and increases in storm wave heights. To reduce risks posed by winter storms, it is not only important to determine the impending physical impacts but it is also necessary to explore the vulnerability of the social-ecological system in the context of these hazards. Here we assess the exposure to both annually occurring and extreme storm events at various planning timelines using a methodology that incorporates the effect of a variable and changing climate on future total water levels. To do this, we have developed a suite of climate change scenarios involving a range of projections for the wave climate, global sea level rise, and the occurrence of El Niño events through 2100. Simple geometric models are then used to conservatively determine the extent of erosion that may occur for a given combination of these climatic factors. We integrate the physical hazards with socioeconomic data using a geographic information system (GIS) in order to quantify societal vulnerability, characterized by the exposure and sensitivity of a community, which is based on the distribution of people, property, and resources. Here we focus on a 14 km stretch of dune-backed coast in northwest Oregon, from Cascade Head to Cape Kiwanda—the location of two communities that, historically, have experienced problematic storm-induced coastal change, Pacific City and Neskowin. Although both of these communities have similar exposure to coastal change hazards at the present, Neskowin is more than twice as sensitive to erosion because almost all of its residents and community assets are located within ~230 m of a narrow beach behind a rip rap revetment. Clearly, any significant losses sustained during an extreme storm could be devastating to the community, and these impacts will likely be amplified in the future. This information is being used to inform land-use planners as well as coastal community residents and visitors about potential coastal change hazards in order to make communities more resistant to future extreme storm events as they are influenced by a changing climate.

Population exposure to heat-related extremes: Demographic change vs climate change

NASA Astrophysics Data System (ADS)

Jones, B.; O'Neill, B. C.; Tebaldi, C.; Oleson, K. W.

2014-12-01

Extreme heat events are projected to increase in frequency and intensity in the coming decades [1]. The physical effects of extreme heat on human populations are well-documented, and anticipating changes in future exposure to extreme heat is a key component of adequate planning/mitigation [2, 3]. Exposure to extreme heat depends not only on changing climate, but also on changes in the size and spatial distribution of the human population. Here we focus on systematically quantifying exposure to extreme heat as a function of both climate and population change. We compare exposure outcomes across multiple global climate and spatial population scenarios, and characterize the relative contributions of each to population exposure to extreme heat. We consider a 2 x 2 matrix of climate and population output, using projections of heat extremes corresponding to RCP 4.5 and RCP 8.5 from the NCAR community land model, and spatial population projections for SSP 3 and SSP 5 from the NCAR spatial population downscaling model. Our primary comparison is across RCPs - exposure outcomes from RCP 4.5 versus RCP 8.5 - paying particular attention to how variation depends on the choice of SSP in terms of aggregate global and regional exposure, as well as the spatial distribution of exposure. We assess how aggregate exposure changes based on the choice of SSP, and which driver is more important, population or climate change (i.e. does that outcome vary more as a result of RCP or SSP). We further decompose the population component to analyze the contributions of total population change, migration, and changes in local spatial structure. Preliminary results from a similar study of the US suggests a four-to-six fold increase in total exposure by the latter half of the 21st century. Changes in population are as important as changes in climate in driving this outcome, and there is regional variation in the relative importance of each. Aggregate population growth, as well as redistribution of the population across larger US regions, strongly affects outcomes while smaller-scale spatial patterns of population change have smaller effects. [1] Collins, M. et al. (2013) Contribution of WG I to the 5th AR of the IPCC[2] Romero-Lankao, P. et al (2014) Contribution of WG II to the 5th AR of the IPCC[3] Walsh, J. et al. (2014) The 3rd National Climate Assessment

Importance of anthropogenic climate impact, sampling error and urban development in sewer system design.

PubMed

Egger, C; Maurer, M

2015-04-15

Urban drainage design relying on observed precipitation series neglects the uncertainties associated with current and indeed future climate variability. Urban drainage design is further affected by the large stochastic variability of precipitation extremes and sampling errors arising from the short observation periods of extreme precipitation. Stochastic downscaling addresses anthropogenic climate impact by allowing relevant precipitation characteristics to be derived from local observations and an ensemble of climate models. This multi-climate model approach seeks to reflect the uncertainties in the data due to structural errors of the climate models. An ensemble of outcomes from stochastic downscaling allows for addressing the sampling uncertainty. These uncertainties are clearly reflected in the precipitation-runoff predictions of three urban drainage systems. They were mostly due to the sampling uncertainty. The contribution of climate model uncertainty was found to be of minor importance. Under the applied greenhouse gas emission scenario (A1B) and within the period 2036-2065, the potential for urban flooding in our Swiss case study is slightly reduced on average compared to the reference period 1981-2010. Scenario planning was applied to consider urban development associated with future socio-economic factors affecting urban drainage. The impact of scenario uncertainty was to a large extent found to be case-specific, thus emphasizing the need for scenario planning in every individual case. The results represent a valuable basis for discussions of new drainage design standards aiming specifically to include considerations of uncertainty. Copyright © 2015 Elsevier Ltd. All rights reserved.

Increasing water cycle extremes in California and in relation to ENSO cycle under global warming

NASA Astrophysics Data System (ADS)

Yoon, Jin-Ho; Wang, S.-Y. Simon; Gillies, Robert R.; Kravitz, Ben; Hipps, Lawrence; Rasch, Philip J.

2015-10-01

Since the winter of 2013-2014, California has experienced its most severe drought in recorded history, causing statewide water stress, severe economic loss and an extraordinary increase in wildfires. Identifying the effects of global warming on regional water cycle extremes, such as the ongoing drought in California, remains a challenge. Here we analyse large-ensemble and multi-model simulations that project the future of water cycle extremes in California as well as to understand those associations that pertain to changing climate oscillations under global warming. Both intense drought and excessive flooding are projected to increase by at least 50% towards the end of the twenty-first century; this projected increase in water cycle extremes is associated with a strengthened relation to El Niño and the Southern Oscillation (ENSO)--in particular, extreme El Niño and La Niña events that modulate California's climate not only through its warm and cold phases but also its precursor patterns.

Increasing water cycle extremes in California and in relation to ENSO cycle under global warming.

PubMed

Yoon, Jin-Ho; Wang, S-Y Simon; Gillies, Robert R; Kravitz, Ben; Hipps, Lawrence; Rasch, Philip J

2015-10-21

Since the winter of 2013-2014, California has experienced its most severe drought in recorded history, causing statewide water stress, severe economic loss and an extraordinary increase in wildfires. Identifying the effects of global warming on regional water cycle extremes, such as the ongoing drought in California, remains a challenge. Here we analyse large-ensemble and multi-model simulations that project the future of water cycle extremes in California as well as to understand those associations that pertain to changing climate oscillations under global warming. Both intense drought and excessive flooding are projected to increase by at least 50% towards the end of the twenty-first century; this projected increase in water cycle extremes is associated with a strengthened relation to El Niño and the Southern Oscillation (ENSO)--in particular, extreme El Niño and La Niña events that modulate California's climate not only through its warm and cold phases but also its precursor patterns.

Increasing water cycle extremes in California and in relation to ENSO cycle under global warming

PubMed Central

Yoon, Jin-Ho; Wang, S-Y Simon; Gillies, Robert R.; Kravitz, Ben; Hipps, Lawrence; Rasch, Philip J.

2015-01-01

Since the winter of 2013–2014, California has experienced its most severe drought in recorded history, causing statewide water stress, severe economic loss and an extraordinary increase in wildfires. Identifying the effects of global warming on regional water cycle extremes, such as the ongoing drought in California, remains a challenge. Here we analyse large-ensemble and multi-model simulations that project the future of water cycle extremes in California as well as to understand those associations that pertain to changing climate oscillations under global warming. Both intense drought and excessive flooding are projected to increase by at least 50% towards the end of the twenty-first century; this projected increase in water cycle extremes is associated with a strengthened relation to El Niño and the Southern Oscillation (ENSO)—in particular, extreme El Niño and La Niña events that modulate California's climate not only through its warm and cold phases but also its precursor patterns. PMID:26487088

Assessing, Modeling, and Monitoring the Impacts of Extreme Climate Events

NASA Astrophysics Data System (ADS)

Murnane, Richard J.; Diaz, Henry F.

2006-01-01

Extreme weather and climate events provide dramatic content for the news media, and the past few years have supplied plenty of material. The 2004 and 2005 Atlantic hurricane seasons were very active; the United States was struck repeatedly by landfalling major hurricanes. A five-year drought in the southwestern United States was punctuated in 2003 by wildfires in southern California that caused billions of dollars in losses. Ten cyclones of at least tropical storm strength struck Japan in 2004, easily breaking the 1990 and 1993 records of six cyclones each year. Hurricane Catarina was the first recorded hurricane in the South Atlantic. Europe's summer of 2003 saw record-breaking heat that caused tens of thousands of deaths. These events have all been widely publicized, and they naturally raise several questions: Is climate changing, and if so, why? What can we expect in the future? How can we better respond to climate variability regardless of its source?

Financial market response to extreme events indicating climatic change

NASA Astrophysics Data System (ADS)

Anttila-Hughes, J. K.

2016-05-01

A variety of recent extreme climatic events are considered to be strong evidence that the climate is warming, but these incremental advances in certainty often seem ignored by non-scientists. I identify two unusual types of events that are considered to be evidence of climate change, announcements by NASA that the global annual average temperature has set a new record, and the sudden collapse of major polar ice shelves, and then conduct an event study to test whether news of these events changes investors' valuation of energy companies, a subset of firms whose future performance is closely tied to climate change. I find evidence that both classes of events have influenced energy stock prices since the 1990s, with record temperature announcements on average associated with negative returns and ice shelf collapses associated with positive returns. I identify a variety of plausible mechanisms that may be driving these differential responses, discuss implications for energy markets' views on long-term regulatory risk, and conclude that investors not only pay attention to scientifically significant climate events, but discriminate between signals carrying different information about the nature of climatic change.

The interplay between climate change, forests, and disturbances.

PubMed

Dale, V H; Joyce, L A; McNulty, S; Neilson, R P

2000-11-15

Climate change affects forests both directly and indirectly through disturbances. Disturbances are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. When disturbances exceed their natural range of variation, the change in forest structure and function may be extreme. Each disturbance affects forests differently. Some disturbances have tight interactions with the species and forest communities which can be disrupted by climate change. Impacts of disturbances and thus of climate change are seen over a board spectrum of spatial and temporal scales. Future observations, research, and tool development are needed to further understand the interactions between climate change and forest disturbances.

Modelling the occurrence of heat waves in maximum and minimum temperatures over Spain and projections for the period 2031-60

NASA Astrophysics Data System (ADS)

Abaurrea, J.; Asín, J.; Cebrián, A. C.

2018-02-01

The occurrence of extreme heat events in maximum and minimum daily temperatures is modelled using a non-homogeneous common Poisson shock process. It is applied to five Spanish locations, representative of the most common climates over the Iberian Peninsula. The model is based on an excess over threshold approach and distinguishes three types of extreme events: only in maximum temperature, only in minimum temperature and in both of them (simultaneous events). It takes into account the dependence between the occurrence of extreme events in both temperatures and its parameters are expressed as functions of time and temperature related covariates. The fitted models allow us to characterize the occurrence of extreme heat events and to compare their evolution in the different climates during the observed period. This model is also a useful tool for obtaining local projections of the occurrence rate of extreme heat events under climate change conditions, using the future downscaled temperature trajectories generated by Earth System Models. The projections for 2031-60 under scenarios RCP4.5, RCP6.0 and RCP8.5 are obtained and analysed using the trajectories from four earth system models which have successfully passed a preliminary control analysis. Different graphical tools and summary measures of the projected daily intensities are used to quantify the climate change on a local scale. A high increase in the occurrence of extreme heat events, mainly in July and August, is projected in all the locations, all types of event and in the three scenarios, although in 2051-60 the increase is higher under RCP8.5. However, relevant differences are found between the evolution in the different climates and the types of event, with a specially high increase in the simultaneous ones.

Extreme Weather Risk Assessment: The Case of Jiquilisco, El Salvador

NASA Astrophysics Data System (ADS)

Melendez, Karla; Ceppi, Claudia; Molero, Juanjo; Rios Insua, David

2014-05-01

All major climate models predict increases in both global and regional mean temperatures throughout this century, under different scenarios concerning future trends in population growth or economic and technological development. This consistency of results across models has strengthened the evidence about global warming. Despite the convincing facts and findings of climate researchers, there is still a great deal of skepticism around climate change. There is somewhat less consensus about some of the consequences of climate change, for example in reference to extreme weather changes, in particular as regards more local scales. However, such changes seem to have already considerable impact in many regions across the world in terms of lives, economic losses, and required changes in lifestyles. This may demand appropriate policy responses both at national and local levels. Our work provides a framework for extreme weather multithreat risk management, based on probabilistic risk assessment (PRA). This may be useful in comparing the effectiveness of different actions to manage risks and inform judgment concerning the appropriate resource allocation to mitigate the risks. The methodology has been applied to the case study of the "El Marillo II" community, located in the municipality of Jiquilisco in El Salvador. There, the main problem related with extreme weather conditions are the frequent floods caused by rainfall, hurricanes , and water increases in the Lempa river nearby located. However, droughts are also very relevant. Based on several sources like SNET, newspapers, field visits to the region and interviews, we have built a detailed database that comprises extreme weather daily data from January 1971 until December 2011. Forecasting models for floods and droughts were built suggesting the need to properly manage the risks. We subsequently obtained the optimal portfolio of countermeasures, given the budget constraints. KEYWORDS: CLIMATE CHANGE, EXTREME WEATHER, RISK ANALYSIS, DECISION ANALYSIS, EL SALVADOR.

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

PubMed

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

2018-02-15

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

Extreme European heat waves since 1950 with Heat Wave Magnitude Index and their occurrence in the future

NASA Astrophysics Data System (ADS)

Russo, Simone; Dosio, Alessandro; Sillmann, Jana

2015-04-01

Heat waves are defined as prolonged periods of extremely hot weather and their magnitude and frequency are expected to increase in the future under climate change. Here we grade the heat waves occurred in Europe since 1950, by means of the Heat Wave Magnitude Index (HWMI) applied to daily maximum temperature from European Observation dataset (E-OBS). As shown in many studies the worst event in the last decades occurred in Russia in 2010. However many other heat waves, as shown here and documented in literature and also in newspapers, occurred in different European regions in the past 64 years. In addition, predictions from ten models from the COordinated Regional climate Downscaling EXperiment (CORDEX) under different IPCC AR5 scenarios, suggest an increased probability of occurrence of extreme heat waves by the end of the century. In particular, under the most severe scenario, events of the same severity, as the 2010 Russian heat wave, will become the norm and are projected to occur as often as every two years in the studied region.

Climate change impacts in Zhuoshui watershed, Taiwan

NASA Astrophysics Data System (ADS)

Chao, Yi-Chiung; Liu, Pei-Ling; Cheng, Chao-Tzuen; Li, Hsin-Chi; Wu, Tingyeh; Chen, Wei-Bo; Shih, Hung-Ju

2017-04-01

There are 5.3 typhoons hit Taiwan per year on average in last decade. Typhoon Morakot in 2009, the most severe typhoon, causes huge damage in Taiwan, including 677 casualty and roughly NT 110 billion (3.3 billion USD) in economic loss. Some researches documented that typhoon frequency will decrease but increase in intensity in western North Pacific region. It is usually preferred to use high resolution dynamical model to get better projection of extreme events; because coarse resolution models cannot simulate intense extreme events. Under that consideration, dynamical downscaling climate data was chosen to describe typhoon satisfactorily. One of the aims for Taiwan Climate Change Projection and Information Platform (TCCIP) is to demonstrate the linkage between climate change data and watershed impact models. The purpose is to understand relative disasters induced by extreme rainfall (typhoons) under climate change in watersheds including landslides, debris flows, channel erosion and deposition, floods, and economic loss. The study applied dynamic downscaling approach to release climate change projected typhoon events under RCP 8.5, the worst-case scenario. The Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) and FLO-2D models, then, were used to simulate hillslope disaster impacts in the upstream of Zhuoshui River. CCHE1D model was used to elevate the sediment erosion or deposition in channel. FVCOM model was used to asses a flood impact in urban area in the downstream. Finally, whole potential loss associate with these typhoon events was evaluated by the Taiwan Typhoon Loss Assessment System (TLAS) under climate change scenario. Results showed that the total loss will increase roughly by NT 49.7 billion (1.6 billion USD) in future in Zhuoshui watershed in Taiwan. The results of this research could help to understand future impact; however model bias still exists. Because typhoon track is a critical factor to consider regional disaster risk and the projection of typhoon is still highly uncertain and typhoon number is very limited in a single model simulation. Since Taiwan is a small island, different typhoon tracks induce different level of disaster impacts in watersheds. Therefore, more samples dynamic downscaled typhoon events are needed for analysis to improve and increase reliability in future. Considering dynamical downscaling methods consume massive computing power, developing a new statistical downscaling approach and new method to release daily climate change data to hourly data could be a short-term solution.

weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Projections of future meteorological drought and wet periods in the Amazon

PubMed Central

Duffy, Philip B.; Brando, Paulo; Asner, Gregory P.; Field, Christopher B.

2015-01-01

Future intensification of Amazon drought resulting from climate change may cause increased fire activity, tree mortality, and emissions of carbon to the atmosphere across large areas of Amazonia. To provide a basis for addressing these issues, we examine properties of recent and future meteorological droughts in the Amazon in 35 climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that the CMIP5 climate models, as a group, simulate important properties of historical meteorological droughts in the Amazon. In addition, this group of models reproduces observed relationships between Amazon precipitation and regional sea surface temperature anomalies in the tropical Pacific and the North Atlantic oceans. Assuming the Representative Concentration Pathway 8.5 scenario for future drivers of climate change, the models project increases in the frequency and geographic extent of meteorological drought in the eastern Amazon, and the opposite in the West. For the region as a whole, the CMIP5 models suggest that the area affected by mild and severe meteorological drought will nearly double and triple, respectively, by 2100. Extremes of wetness are also projected to increase after 2040. Specifically, the frequency of periods of unusual wetness and the area affected by unusual wetness are projected to increase after 2040 in the Amazon as a whole, including in locations where annual mean precipitation is projected to decrease. Our analyses suggest that continued emissions of greenhouse gases will increase the likelihood of extreme events that have been shown to alter and degrade Amazonian forests. PMID:26460046

Norway and Cuba Continue Collaborating to Build Capacity to Improve Weather Forecasting

NASA Astrophysics Data System (ADS)

Antuña, Juan Carlos; Kalnay, Eugenia; Mesquita, Michel D. S.

2014-06-01

The Future of Climate Extremes in the Caribbean Extreme Cuban Climate (XCUBE) project, which is funded by the Norwegian Directorate for Civil Protection as part of an assignment for the Norwegian Ministry of Foreign Affairs to support scientific cooperation between Norway and Cuba, carried out a training workshop on seasonal forecasting, reanalysis data, and weather research and forecasting (WRF). The workshop was a follow-up to the XCUBE workshop conducted in Havana in 2013 and provided Cuban scientists with access to expertise on seasonal forecasting, the WRF model developed by the National Center for Atmospheric Research (NCAR) and the community, data assimilation, and reanalysis.

Decision strategies for handling the uncertainty of future extreme rainfall under the influence of climate change.

PubMed

Gregersen, I B; Arnbjerg-Nielsen, K

2012-01-01

Several extraordinary rainfall events have occurred in Denmark within the last few years. For each event, problems in urban areas occurred as the capacity of the existing drainage systems were exceeded. Adaptation to climate change is necessary but also very challenging as urban drainage systems are characterized by long technical lifetimes and high, unrecoverable construction costs. One of the most important barriers for the initiation and implementation of the adaptation strategies is therefore the uncertainty when predicting the magnitude of the extreme rainfall in the future. This challenge is explored through the application and discussion of three different theoretical decision support strategies: the precautionary principle, the minimax strategy and Bayesian decision support. The reviewed decision support strategies all proved valuable for addressing the identified uncertainties, at best applied together as they all yield information that improved decision making and thus enabled more robust decisions.

Mangrove expansion and contraction at a poleward range limit: Climate extremes and land-ocean temperature gradients

USGS Publications Warehouse

Osland, Michael J.; Day, Richard H.; Hall, Courtney T.; Brumfield, Marisa D; Dugas, Jason; Jones, William R.

2017-01-01

Within the context of climate change, there is a pressing need to better understand the ecological implications of changes in the frequency and intensity of climate extremes. Along subtropical coasts, less frequent and warmer freeze events are expected to permit freeze-sensitive mangrove forests to expand poleward and displace freeze-tolerant salt marshes. Here, our aim was to better understand the drivers of poleward mangrove migration by quantifying spatiotemporal patterns in mangrove range expansion and contraction across land-ocean temperature gradients. Our work was conducted in a freeze-sensitive mangrove-marsh transition zone that spans a land-ocean temperature gradient in one of the world's most wetland-rich regions (Mississippi River Deltaic Plain; Louisiana, USA). We used historical air temperature data (1893-2014), alternative future climate scenarios, and coastal wetland coverage data (1978-2011) to investigate spatiotemporal fluctuations and climate-wetland linkages. Our analyses indicate that changes in mangrove coverage have been controlled primarily by extreme freeze events (i.e., air temperatures below a threshold zone of -6.3 to -7.6 °C). We expect that in the past 121 years, mangrove range expansion and contraction has occurred across land-ocean temperature gradients. Mangrove resistance, resilience, and dominance were all highest in areas closer to the ocean where temperature extremes were buffered by large expanses of water and saturated soil. Under climate change, these areas will likely serve as local hotspots for mangrove dispersal, growth, range expansion, and displacement of salt marsh. Collectively, our results show that the frequency and intensity of freeze events across land-ocean temperature gradients greatly influences spatiotemporal patterns of range expansion and contraction of freeze-sensitive mangroves. We expect that, along subtropical coasts, similar processes govern the distribution and abundance of other freeze-sensitive organisms. In broad terms, our findings can be used to better understand and anticipate the ecological effects of changing winter climate extremes, especially within the transition zone between tropical and temperate climates.

Sensitivity of UK butterflies to local climatic extremes: which life stages are most at risk?

PubMed

McDermott Long, Osgur; Warren, Rachel; Price, Jeff; Brereton, Tom M; Botham, Marc S; Franco, Aldina M A

2017-01-01

There is growing recognition as to the importance of extreme climatic events (ECEs) in determining changes in species populations. In fact, it is often the extent of climate variability that determines a population's ability to persist at a given site. This study examined the impact of ECEs on the resident UK butterfly species (n = 41) over a 37-year period. The study investigated the sensitivity of butterflies to four extremes (drought, extreme precipitation, extreme heat and extreme cold), identified at the site level, across each species' life stages. Variations in the vulnerability of butterflies at the site level were also compared based on three life-history traits (voltinism, habitat requirement and range). This is the first study to examine the effects of ECEs at the site level across all life stages of a butterfly, identifying sensitive life stages and unravelling the role life-history traits play in species sensitivity to ECEs. Butterfly population changes were found to be primarily driven by temperature extremes. Extreme heat was detrimental during overwintering periods and beneficial during adult periods and extreme cold had opposite impacts on both of these life stages. Previously undocumented detrimental effects were identified for extreme precipitation during the pupal life stage for univoltine species. Generalists were found to have significantly more negative associations with ECEs than specialists. With future projections of warmer, wetter winters and more severe weather events, UK butterflies could come under severe pressure given the findings of this study. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Know your limits? Climate extremes impact the range of Scots pine in unexpected places.

PubMed

Julio Camarero, J; Gazol, Antonio; Sancho-Benages, Santiago; Sangüesa-Barreda, Gabriel

2015-11-01

Although extreme climatic events such as drought are known to modify forest dynamics by triggering tree dieback, the impact of extreme cold events, especially at the low-latitude margin ('rear edge') of species distributional ranges, has received little attention. The aim of this study was to examine the impact of one such extreme cold event on a population of Scots pine (Pinus sylvestris) along the species' European southern rear-edge range limit and to determine how such events can be incorporated into species distribution models (SDMs). A combination of dendrochronology and field observation was used to quantify how an extreme cold event in 2001 in eastern Spain affected growth, needle loss and mortality of Scots pine. Long-term European climatic data sets were used to contextualize the severity of the 2001 event, and an SDM for Scots pine in Europe was used to predict climatic range limits. The 2001 winter reached record minimum temperatures (equivalent to the maximum European-wide diurnal ranges) and, for trees already stressed by a preceding dry summer and autumn, this caused dieback and large-scale mortality. Needle loss and mortality were particularly evident in south-facing sites, where post-event recovery was greatly reduced. The SDM predicted European Scots pine distribution mainly on the basis of responses to maximum and minimum monthly temperatures, but in comparison with this the observed effects of the 2001 cold event at the southerly edge of the range limit were unforeseen. The results suggest that in order to better forecast how anthropogenic climate change might affect future forest distributions, distribution modelling techniques such as SDMs must incorporate climatic extremes. For Scots pine, this study shows that the effects of cold extremes should be included across the entire distribution margin, including the southern 'rear edge', in order to avoid biased predictions based solely on warmer climatic scenarios. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Facing the Future: Effects of Short-Term Climate Extremes on Isoprene-Emitting and Nonemitting Poplar.

PubMed

Vanzo, Elisa; Jud, Werner; Li, Ziru; Albert, Andreas; Domagalska, Malgorzata A; Ghirardo, Andrea; Niederbacher, Bishu; Frenzel, Juliane; Beemster, Gerrit T S; Asard, Han; Rennenberg, Heinz; Sharkey, Thomas D; Hansel, Armin; Schnitzler, Jörg-Peter

2015-09-01

Isoprene emissions from poplar (Populus spp.) plantations can influence atmospheric chemistry and regional climate. These emissions respond strongly to temperature, [CO2], and drought, but the superimposed effect of these three climate change factors are, for the most part, unknown. Performing predicted climate change scenario simulations (periodic and chronic heat and drought spells [HDSs] applied under elevated [CO2]), we analyzed volatile organic compound emissions, photosynthetic performance, leaf growth, and overall carbon (C) gain of poplar genotypes emitting (IE) and nonemitting (NE) isoprene. We aimed (1) to evaluate the proposed beneficial effect of isoprene emission on plant stress mitigation and recovery capacity and (2) to estimate the cumulative net C gain under the projected future climate. During HDSs, the chloroplastidic electron transport rate of NE plants became impaired, while IE plants maintained high values similar to unstressed controls. During recovery from HDS episodes, IE plants reached higher daily net CO2 assimilation rates compared with NE genotypes. Irrespective of the genotype, plants undergoing chronic HDSs showed the lowest cumulative C gain. Under control conditions simulating ambient [CO2], the C gain was lower in the IE plants than in the NE plants. In summary, the data on the overall C gain and plant growth suggest that the beneficial function of isoprene emission in poplar might be of minor importance to mitigate predicted short-term climate extremes under elevated [CO2]. Moreover, we demonstrate that an analysis of the canopy-scale dynamics of isoprene emission and photosynthetic performance under multiple stresses is essential to understand the overall performance under proposed future conditions. © 2015 American Society of Plant Biologists. All Rights Reserved.

A new large initial condition ensemble to assess avoided impacts in a climate mitigation scenario

NASA Astrophysics Data System (ADS)

Sanderson, B. M.; Tebaldi, C.; Knutti, R.; Oleson, K. W.

2014-12-01

It has recently been demonstrated that when considering timescales of up to 50 years, natural variability may play an equal role to anthropogenic forcing on subcontinental trends for a variety of climate indicators. Thus, for many questions assessing climate impacts on such time and spatial scales, it has become clear that a significant number of ensemble members may be required to produce robust statistics (and especially so for extreme events). However, large ensemble experiments to date have considered the role of variability in a single scenario, leaving uncertain the relationship between the forced climate trajectory and the variability about that path. To address this issue, we present a new, publicly available, 15 member initial condition ensemble of 21st century climate projections for the RCP 4.5 scenario using the CESM1.1 Earth System Model, which we propose as a companion project to the existing 40 member CESM large ensemble which uses the higher greenhouse gas emission future of RCP8.5. This provides a valuable data set for assessing what societal and ecological impacts might be avoided through a moderate mitigation strategy in contrast to a fossil fuel intensive future. We present some early analyses of these combined ensembles to assess to what degree the climate variability can be considered to combine linearly with the underlying forced response. In regions where there is no detectable relationship between the mean state and the variability about the mean trajectory, then linear assumptions can be trivially exploited to utilize a single ensemble or control simulation to characterize the variability in any scenario of interest. We highlight regions where there is a detectable nonlinearity in extreme event frequency, how far in the future they will be manifested and propose mechanisms to account for these effects.

The relative importance among anthropogenic forcings of land use/land cover change in affecting temperature extremes

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.

2018-05-01

Land use/land cover change (LULCC) exerts significant influence on regional climate extremes, but its relative importance compared with other anthropogenic climate forcings has not been thoroughly investigated. This study compares land use forcing with other forcing agents in explaining the simulated historical temperature extreme changes since preindustrial times in the CESM-Last Millennium Ensemble (LME) project. CESM-LME suggests that the land use forcing has caused an overall cooling in both warm and cold extremes, and has significantly decreased diurnal temperature range (DTR). Due to the competing effects of the GHG and aerosol forcings, the spatial pattern of changes in 1850-2005 climatology of temperature extremes in CESM-LME can be largely explained by the land use forcing, especially for hot extremes and DTR. The dominance of land use forcing is particularly evident over Europe, eastern China, and the central and eastern US. Temporally, the land-use cooling is relatively stable throughout the historical period, while the warming of temperature extremes is mainly influenced by the enhanced GHG forcing, which has gradually dampened the local dominance of the land use effects. Results from the suite of CMIP5 experiments partially agree with the local dominance of the land use forcing in CESM-LME, but inter-model discrepancies exist in the distribution and sign of the LULCC-induced temperature changes. Our results underline the overall importance of LULCC in historical temperature extreme changes, implying land use forcing should be highlighted in future climate projections.

Climate Change and Your National Forest: Assessing the potential effects of climate change on the El Yunque National Forest

Treesearch

L.N. Jennings; E.A. Treasure; S.G. McNulty

2013-01-01

Forestlands across the world are experiencing increased threats from fire, insect and plant invasions, disease, extreme weather, and drought. Scientists project increases in temperature and changes in rainfall patterns that can make these threats occur more often, with more intensity, and/or for longer durations. Although many of the effects of future changes are...

The cold-water climate shield: Delineating refugia for preserving salmonid fishes through the 21st century

Treesearch

Daniel J. Isaak; Michael K. Young; David E. Nagel; Dona L. Horan; Matthew C. Groce

2015-01-01

The distribution and future fate of ectothermic organisms in a warming world will be dictated by thermalscapes across landscapes. That is particularly true for stream fishes and cold-water species like trout, salmon, and char that are already constrained to high elevations and latitudes. The extreme climates in those environments also preclude invasions by most non-...

DCERP Annual Technical Report 4: March 2010 - February 2011

DTIC Science & Technology

2011-05-01

of monitoring may be necessary to fully characterize and model the impact of major climatic events (e.g., tropical cyclones, major droughts ) and...stressors (past, present, and future) at local and regional scales; take account of extreme climatic events (e.g., hurricanes, droughts ); and integrate...the longleaf pine ( Pinus palustris), savannas, and pocosins (shrub bog) that dominate MCBCL’s terrestrial environments. Variation in the biota and

Effects of changes in climate variability and extremes on the exceedance of critical algal bloom thresholds

NASA Astrophysics Data System (ADS)

Hecht, J. S.; Zia, A.; Beckage, B.; Winter, J.; Schroth, A. W.; Bomblies, A.; Clemins, P. J.; Rizzo, D. M.

2017-12-01

Identifying critical thresholds associated with algal blooms in freshwater lakes is important for avoiding persistent eutrophic conditions and their undesirable ecological, recreational and drinking water impacts. Recent Integrated Assessment Model (IAM) and Bayesian network studies have demonstrated that future climatic changes could increase the duration and intensity of these blooms. Yet, few studies have systematically examined the sensitivity of algal blooms to projected changes in precipitation and temperature variability and extremes at storm-event to seasonal timescales. We employ an IAM, which couples downscaled Global Climate Model (GCM) output with hydrologic and water quality models, to examine the sensitivity of algal blooms in Lake Champlain's shallow Missisquoi Bay to potential future climate changes. We first identify a set of statistically downscaled GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) that reproduce recent historical daily temperature and precipitation observations well in the Lake Champlain basin. Then, we identify plausible covarying changes in the (i) mean and variance of seasonal precipitation and temperature distributions and (ii) frequency and magnitude of individual storm events. We assess the response of water quality indicators (e.g. chlorophyll a concentrations, Trophic State Index) and societal impacts to sequences of daily meteorological series generated from distributions that account for these covarying changes. We also discuss strategies for examining the sensitivity of bloom impacts to different weather sequences generated from a single set of precipitation and temperature distributions with a limited number of computationally intensive IAM simulations. We then evaluate the implications of modeling these changes in climate variability and extreme precipitation events for nutrient management. Finally, we consider the generalizability of our findings for water bodies with different physical and climatic characteristics and address the extent to which climate-driven alterations to terrestrial hydrologic processes, such as evapotranspiration and soil moisture storage, mediate changes to lake water quality.

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed Central

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-01-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change. PMID:10753097

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-04-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change.

Impact assessment of climate change on tourism in the Pacific small islands based on the database of long-term high-resolution climate ensemble experiments

NASA Astrophysics Data System (ADS)

Watanabe, S.; Utsumi, N.; Take, M.; Iida, A.

2016-12-01

This study aims to develop a new approach to assess the impact of climate change on the small oceanic islands in the Pacific. In the new approach, the change of the probabilities of various situations was projected with considering the spread of projection derived from ensemble simulations, instead of projecting the most probable situation. The database for Policy Decision making for Future climate change (d4PDF) is a database of long-term high-resolution climate ensemble experiments, which has the results of 100 ensemble simulations. We utilized the database for Policy Decision making for Future climate change (d4PDF), which was (a long-term and high-resolution database) composed of results of 100 ensemble experiments. A new methodology, Multi Threshold Ensemble Assessment (MTEA), was developed using the d4PDF in order to assess the impact of climate change. We focused on the impact of climate change on tourism because it has played an important role in the economy of the Pacific Islands. The Yaeyama Region, one of the tourist destinations in Okinawa, Japan, was selected as the case study site. Two kinds of impact were assessed: change in probability of extreme climate phenomena and tourist satisfaction associated with weather. The database of long-term high-resolution climate ensemble experiments and the questionnaire survey conducted by a local government were used for the assessment. The result indicated that the strength of extreme events would be increased, whereas the probability of occurrence would be decreased. This change should result in increase of the number of clear days and it could contribute to improve the tourist satisfaction.

A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation

NASA Astrophysics Data System (ADS)

Byun, K.; Hamlet, A. F.

2017-12-01

There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.

Ecological genomics predicts climate vulnerability in an endangered southwestern songbird.

PubMed

Ruegg, Kristen; Bay, Rachael A; Anderson, Eric C; Saracco, James F; Harrigan, Ryan J; Whitfield, Mary; Paxton, Eben H; Smith, Thomas B

2018-05-09

Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher (Empidonax traillii), and find the endangered desert southwestern subspecies (E. t. extimus) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability - the mismatch between current and predicted future genotype-environment relationships - indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate-associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype-environment relationships into landscape-scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups. © 2018 John Wiley & Sons Ltd/CNRS.

Influence of climate change on flood magnitude and seasonality in the Arga River catchment in Spain

NASA Astrophysics Data System (ADS)

Garijo, Carlos; Mediero, Luis

2018-04-01

Climate change projections suggest that extremes, such as floods, will modify their behaviour in the future. Detailed catchment-scale studies are needed to implement the European Union Floods Directive and give recommendations for flood management and design of hydraulic infrastructure. In this study, a methodology to quantify changes in future flood magnitude and seasonality due to climate change at a catchment scale is proposed. Projections of 24 global climate models are used, with 10 being downscaled by the Spanish Meteorological Agency (Agencia Estatal de Meteorología, AEMET) and 14 from the EURO-CORDEX project, under two representative concentration pathways (RCPs) 4.5 and 8.5, from the Fifth Assessment Report provided by the Intergovernmental Panel on Climate Change. Downscaled climate models provided by the AEMET were corrected in terms of bias. The HBV rainfall-runoff model was selected to simulate the catchment hydrological behaviour. Simulations were analysed through both annual maximum and peaks-over-threshold (POT) series. The results show a decrease in the magnitude of extreme floods for the climate model projections downscaled by the AEMET. However, results for the climate model projections downscaled by EURO-CORDEX show differing trends, depending on the RCP. A small decrease in the flood magnitude was noticed for the RCP 4.5, while an increase was found for the RCP 8.5. Regarding the monthly seasonality analysis performed by using the POT series, a delay in the flood timing from late-autumn to late-winter is identified supporting the findings of recent studies performed with observed data in recent decades.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations.

PubMed

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; Xie, Yangyang; Liu, Saiyan; Meng, Erhao; Li, Pei

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating the potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. This study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.

Examining the Stationarity Assumption for Statistically Downscaled Climate Projections of Precipitation

NASA Astrophysics Data System (ADS)

Wootten, A.; Dixon, K. W.; Lanzante, J. R.; Mcpherson, R. A.

2017-12-01

Empirical statistical downscaling (ESD) approaches attempt to refine global climate model (GCM) information via statistical relationships between observations and GCM simulations. The aim of such downscaling efforts is to create added-value climate projections by adding finer spatial detail and reducing biases. The results of statistical downscaling exercises are often used in impact assessments under the assumption that past performance provides an indicator of future results. Given prior research describing the danger of this assumption with regards to temperature, this study expands the perfect model experimental design from previous case studies to test the stationarity assumption with respect to precipitation. Assuming stationarity implies the performance of ESD methods are similar between the future projections and historical training. Case study results from four quantile-mapping based ESD methods demonstrate violations of the stationarity assumption for both central tendency and extremes of precipitation. These violations vary geographically and seasonally. For the four ESD methods tested the greatest challenges for downscaling of daily total precipitation projections occur in regions with limited precipitation and for extremes of precipitation along Southeast coastal regions. We conclude with a discussion of future expansion of the perfect model experimental design and the implications for improving ESD methods and providing guidance on the use of ESD techniques for impact assessments and decision-support.

Sensitivity of Hydrologic Extremes to Spatial Resolution of Meteorological Forcings: A Case Study of the Conterminous United States

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.; Ashfaq, M.; Rastogi, D.

2016-12-01

The magnitude and frequency of hydroclimate extremes are projected to increase in the conterminous United States (CONUS) with significant implications for future water resource planning and flood risk management. Nevertheless, apart from the change of natural environment, the choice of model spatial resolution could also artificially influence the features of simulated extremes. To better understand how the spatial resolution of meteorological forcings may affect hydroclimate projections, we test the runoff sensitivity using the Variable Infiltration Capacity (VIC) model that was calibrated for each CONUS 8-digit hydrologic unit (HUC8) at 1/24° ( 4km) grid resolution. The 1980-2012 gridded Daymet and PRISM meteorological observations are used to conduct the 1/24° resolution control simulation. Comparative simulations are achieved by smoothing the 1/24° forcing into 1/12° and 1/8° resolutions which are then used to drive the VIC model for the CONUS. In addition, we also test how the simulated high and low runoff conditions would react to change in precipitation (±10%) and temperature (+1°C). The results are further analyzed for various types of hydroclimate extremes across different watersheds in the CONUS. This work helps us understand the sensitivity of simulated runoff to different spatial resolutions of climate forcings and also its sensitivity to different watershed sizes and characteristics of extreme events in the future climate conditions.

Impacts of Anthropogenic Aerosols on Regional Climate: Extreme Events, Stagnation, and the United States Warming Hole

NASA Astrophysics Data System (ADS)

Mascioli, Nora R.

Extreme temperatures, heat waves, heavy rainfall events, drought, and extreme air pollution events have adverse effects on human health, infrastructure, agriculture and economies. The frequency, magnitude and duration of these events are expected to change in the future in response to increasing greenhouse gases and decreasing aerosols, but future climate projections are uncertain. A significant portion of this uncertainty arises from uncertainty in the effects of aerosol forcing: to what extent were the effects from greenhouse gases masked by aerosol forcing over the historical observational period, and how much will decreases in aerosol forcing influence regional and global climate over the remainder of the 21st century? The observed frequency and intensity of extreme heat and precipitation events have increased in the U.S. over the latter half of the 20th century. Using aerosol only (AER) and greenhouse gas only (GHG) simulations from 1860 to 2005 in the GFDL CM3 chemistry-climate model, I parse apart the competing influences of aerosols and greenhouse gases on these extreme events. I find that small changes in extremes in the "all forcing" simulations reflect cancellations between the effects of increasing anthropogenic aerosols and greenhouse gases. In AER, extreme high temperatures and the number of days with temperatures above the 90th percentile decline over most of the U.S., while in GHG high temperature extremes increase over most of the U.S. The spatial response patterns in AER and GHG are significantly anti-correlated, suggesting a preferred regional mode of response that is largely independent of the type of forcing. Extreme precipitation over the eastern U.S. decreases in AER, particularly in winter, and increases over the eastern and central U.S. in GHG, particularly in spring. Over the 21 st century under the RCP8.5 emissions scenario, the patterns of extreme temperature and precipitation change associated with greenhouse gas forcing dominate. The temperature response pattern in AER and GHG is characterized by strong responses over the western U.S. and weak or opposite signed responses over the southeast U.S., raising the question of whether the observed U.S. "warming hole" could have a forced component. To address this question, I systematically examine observed seasonal temperature trends over all time periods of at least 10 years during 1901-2015. In the northeast and southern U.S., significant summertime cooling occurs from the early 1950s to the mid 1970s, which I partially attribute to increasing anthropogenic aerosol emissions (median fraction of the observed temperature trends explained is 0.69 and 0.17, respectively). In winter, the northeast and southern U.S. cool significantly from the early 1950s to the early 1990s, which I attribute to long-term phase changes in the North Atlantic Oscillation and the Pacific Decadal Oscillation. Rather than being a single phenomenon stemming from a single cause, both the warming hole and its dominant drivers vary by season, region, and time period. Finally, I examine historical and projected future changes in atmospheric stagnation. Stagnation, which is characterized by weak winds and an absence of precipitation, is a meteorological contributor to heat waves, extreme pollution, and drought. Using CM3, I show that regional stagnation trends over the historical period (1860-2005) are driven by changes in anthropogenic aerosol emissions, rather than rising greenhouse gases. In the northeastern and central United States, aerosol-induced changes in surface and upper level winds produce significant decreases in the number of stagnant summer days, while decreasing precipitation in the southeast US increases the number of stagnant summer days. Outside of the U.S., significant drying over eastern China in response to rising aerosol emissions contributed to increased stagnation during 1860-2005. Additionally, this region was found to be particularly sensitive to changes in local aerosol emissions, indicating that decreasing Chinese emissions in efforts to improve air quality will also decrease stagnation. In Europe, I find a dipole response pattern during the historical period wherein stagnation decreases over southern Europe and increases over northern Europe in response to global increases in aerosol emissions. In the future, declining aerosol emissions will likely lead to a reversal of the historical stagnation trends, with increasing greenhouse gases again playing a secondary role. Aerosols have a significant effect on a number of societally important extreme events, including heat waves, intense rainfall events, drought, and stagnation. Further, uncertainty in the strength of aerosol masking of historical greenhouse gas forcing is a significant source of spread in future climate projections. Quantifying these aerosol effects is therefore critical for our ability to accurately project and prepare for future changes in extreme events.

Simulation of Deep Water Renewal in Crater Lake, Oregon, USA under Current and Future Climate Conditions

NASA Astrophysics Data System (ADS)

Piccolroaz, S.; Wood, T. M.; Wherry, S.; Girdner, S.

2015-12-01

We applied a 1-dimensional lake model developed to simulate deep mixing related to thermobaric instabilities in temperate lakes to Crater Lake, a 590-m deep caldera lake in Oregon's Cascade Range known for its stunning deep blue color and extremely clear water, in order to determine the frequency of deep water renewal in future climate conditions. The lake model was calibrated with 6 years of water temperature profiles, and then simulated 10 years of validation data with an RMSE ranging from 0.81°C at 50 m depth to 0.04°C at 350-460 m depth. The simulated time series of heat content in the deep lake accurately captured extreme years characterized by weak and strong deep water renewal. The lake model uses wind speed and lake surface temperature (LST) as boundary conditions. LST projections under six climate scenarios from the CMIP5 intermodel comparison project (2 representative concentration pathways X 3 general circulation models) were evaluated with air2water, a simple lumped model that only requires daily values of downscaled air temperature. air2water was calibrated with data from 1993-2011, resulting in a RMSE between simulated and observed daily LST values of 0.68°C. All future climate scenarios project increased water temperature throughout the water column and a substantive reduction in the frequency of deepwater renewal events. The least extreme scenario (CNRM-CM5, RCP4.5) projects the frequency of deepwater renewal events to decrease from about 1 in 2 years in the present to about 1 in 3 years by 2100. The most extreme scenario (HadGEM2-ES, RCP8.5) projects the frequency of deepwater renewal events to be less than 1 in 7 years by 2100 and lake surface temperatures never cooling to less than 4°C after 2050. In all RCP4.5 simulations the temperature of the entire water column is greater than 4°C for increasing periods of time. In the RCP8.5 simulations, the temperature of the entire water column is greater than 4°C year round by the year 2060 (HadGEM2) or 2080 (CNRM-CM5); thus, the conditions required for thermobaric instability induced mixing become rare or non-existent in these projections. The results indicate that the frequency of deep water renewal events could change substantially in a warmer future climate, potentially altering the lake ecosystem and water clarity.

Evaluation on uncertainty sources in projecting hydrological changes over the Xijiang River basin in South China

NASA Astrophysics Data System (ADS)

Yuan, Fei; Zhao, Chongxu; Jiang, Yong; Ren, Liliang; Shan, Hongcui; Zhang, Limin; Zhu, Yonghua; Chen, Tao; Jiang, Shanhu; Yang, Xiaoli; Shen, Hongren

2017-11-01

Projections of hydrological changes are associated with large uncertainties from different sources, which should be quantified for an effective implementation of water management policies adaptive to future climate change. In this study, a modeling chain framework to project future hydrological changes and the associated uncertainties in the Xijiang River basin, South China, was established. The framework consists of three emission scenarios (ESs), four climate models (CMs), four statistical downscaling (SD) methods, four hydrological modeling (HM) schemes, and four probability distributions (PDs) for extreme flow frequency analyses. Direct variance method was adopted to analyze the manner by which uncertainty sources such as ES, CM, SD, and HM affect the estimates of future evapotranspiration (ET) and streamflow, and to quantify the uncertainties of PDs in future flood and drought risk assessment. Results show that ES is one of the least important uncertainty sources in most situations. CM, in general, is the dominant uncertainty source for the projections of monthly ET and monthly streamflow during most of the annual cycle, daily streamflow below the 99.6% quantile level, and extreme low flow. SD is the most predominant uncertainty source in the projections of extreme high flow, and has a considerable percentage of uncertainty contribution in monthly streamflow projections in July-September. The effects of SD in other cases are negligible. HM is a non-ignorable uncertainty source that has the potential to produce much larger uncertainties for the projections of low flow and ET in warm and wet seasons than for the projections of high flow. PD contributes a larger percentage of uncertainty in extreme flood projections than it does in extreme low flow estimates. Despite the large uncertainties in hydrological projections, this work found that future extreme low flow would undergo a considerable reduction, and a noticeable increase in drought risk in the Xijiang River basin would be expected. Thus, the necessity of employing effective water-saving techniques and adaptive water resources management strategies for drought disaster mitigation should be addressed.

Extreme weather: Subtropical floods and tropical cyclones

NASA Astrophysics Data System (ADS)

Shaevitz, Daniel A.

Extreme weather events have a large effect on society. As such, it is important to understand these events and to project how they may change in a future, warmer climate. The aim of this thesis is to develop a deeper understanding of two types of extreme weather events: subtropical floods and tropical cyclones (TCs). In the subtropics, the latitude is high enough that quasi-geostrophic dynamics are at least qualitatively relevant, while low enough that moisture may be abundant and convection strong. Extratropical extreme precipitation events are usually associated with large-scale flow disturbances, strong ascent, and large latent heat release. In the first part of this thesis, I examine the possible triggering of convection by the large-scale dynamics and investigate the coupling between the two. Specifically two examples of extreme precipitation events in the subtropics are analyzed, the 2010 and 2014 floods of India and Pakistan and the 2015 flood of Texas and Oklahoma. I invert the quasi-geostrophic omega equation to decompose the large-scale vertical motion profile to components due to synoptic forcing and diabatic heating. Additionally, I present model results from within the Column Quasi-Geostrophic framework. A single column model and cloud-revolving model are forced with the large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation with input data from a reanalysis data set, and the large-scale vertical motion is diagnosed interactively with the simulated convection. It is found that convection was triggered primarily by mechanically forced orographic ascent over the Himalayas during the India/Pakistan flood and by upper-level Potential Vorticity disturbances during the Texas/Oklahoma flood. Furthermore, a climate attribution analysis was conducted for the Texas/Oklahoma flood and it is found that anthropogenic climate change was responsible for a small amount of rainfall during the event but the intensity of this event may be greatly increased if it occurs in a future climate. In the second part of this thesis, I examine the ability of high-resolution global atmospheric models to simulate TCs. Specifically, I present an intercomparison of several models' ability to simulate the global characteristics of TCs in the current climate. This is a necessary first step before using these models to project future changes in TCs. Overall, the models were able to reproduce the geographic distribution of TCs reasonably well, with some of the models performing remarkably well. The intensity of TCs varied widely between the models, with some of this difference being due to model resolution.

Ensemble of regional climate model projections for Ireland

NASA Astrophysics Data System (ADS)

Nolan, Paul; McGrath, Ray

2016-04-01

The method of Regional Climate Modelling (RCM) was employed to assess the impacts of a warming climate on the mid-21st-century climate of Ireland. The RCM simulations were run at high spatial resolution, up to 4 km, thus allowing a better evaluation of the local effects of climate change. Simulations were run for a reference period 1981-2000 and future period 2041-2060. Differences between the two periods provide a measure of climate change. To address the issue of uncertainty, a multi-model ensemble approach was employed. Specifically, the future climate of Ireland was simulated using three different RCMs, driven by four Global Climate Models (GCMs). To account for the uncertainty in future emissions, a number of SRES (B1, A1B, A2) and RCP (4.5, 8.5) emission scenarios were used to simulate the future climate. Through the ensemble approach, the uncertainty in the RCM projections can be partially quantified, thus providing a measure of confidence in the predictions. In addition, likelihood values can be assigned to the projections. The RCMs used in this work are the COnsortium for Small-scale MOdeling-Climate Limited-area Modelling (COSMO-CLM, versions 3 and 4) model and the Weather Research and Forecasting (WRF) model. The GCMs used are the Max Planck Institute's ECHAM5, the UK Met Office's HadGEM2-ES, the CGCM3.1 model from the Canadian Centre for Climate Modelling and the EC-Earth consortium GCM. The projections for mid-century indicate an increase of 1-1.6°C in mean annual temperatures, with the largest increases seen in the east of the country. Warming is enhanced for the extremes (i.e. hot or cold days), with the warmest 5% of daily maximum summer temperatures projected to increase by 0.7-2.6°C. The coldest 5% of night-time temperatures in winter are projected to rise by 1.1-3.1°C. Averaged over the whole country, the number of frost days is projected to decrease by over 50%. The projections indicate an average increase in the length of the growing season of over 35 days per year. Results show significant projected decreases in mean annual, spring and summer precipitation amounts by mid-century. The projected decreases are largest for summer, with "likely" reductions ranging from 0% to 20%. The frequencies of heavy precipitation events show notable increases (approximately 20%) during the winter and autumn months. The number of extended dry periods is projected to increase substantially during autumn and summer. Regional variations of projected precipitation change remain statistically elusive. The energy content of the wind is projected to significantly decrease for the future spring, summer and autumn months. Projected increases for winter were found to be statistically insignificant. The projected decreases were largest for summer, with "likely" values ranging from 3% to 15%. Results suggest that the tracks of intense storms are projected to extend further south over Ireland relative to those in the reference simulation. As extreme storm events are rare, the storm-tracking research needs to be extended. Future work will focus on analysing a larger ensemble, thus allowing a robust statistical analysis of extreme storm track projections.

Current and Potential Future Seasonal Trends of Indoor Dwelling Temperature and Likely Health Risks in Rural Southern Africa.

PubMed

Kapwata, Thandi; Gebreslasie, Michael T; Mathee, Angela; Wright, Caradee Yael

2018-05-10

Climate change has resulted in rising temperature trends which have been associated with changes in temperature extremes globally. Attendees of Conference of the Parties (COP) 21 agreed to strive to limit the rise in global average temperatures to below 2 °C compared to industrial conditions, the target being 1.5 °C. However, current research suggests that the African region will be subjected to more intense heat extremes over a shorter time period, with projections predicting increases of 4⁻6 °C for the period 2071⁻2100, in annual average maximum temperatures for southern Africa. Increased temperatures may exacerbate existing chronic ill health conditions such as cardiovascular disease, respiratory disease, cerebrovascular disease, and diabetes-related conditions. Exposure to extreme temperatures has also been associated with mortality. This study aimed to consider the relationship between temperatures in indoor and outdoor environments in a rural residential setting in a current climate and warmer predicted future climate. Temperature and humidity measurements were collected hourly in 406 homes in summer and spring and at two-hour intervals in 98 homes in winter. Ambient temperature, humidity and windspeed were obtained from the nearest weather station. Regression models were used to identify predictors of indoor apparent temperature (AT) and to estimate future indoor AT using projected ambient temperatures. Ambient temperatures will increase by a mean of 4.6 °C for the period 2088⁻2099. Warming in winter was projected to be greater than warming in summer and spring. The number of days during which indoor AT will be categorized as potentially harmful will increase in the future. Understanding current and future heat-related health effects is key in developing an effective surveillance system. The observations of this study can be used to inform the development and implementation of policies and practices around heat and health especially in rural areas of South Africa.

Effects of ice storm on forest ecosystem of southern China in 2008 Shaoqiang Wang1, Lei Zhou1, Weimin Ju2, Kun Huang1 1Key Lab of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Beijing, 10010

NASA Astrophysics Data System (ADS)

Wang, Shaoqiang

2014-05-01

Evidence is mounting that an increase in extreme climate events has begun to occur worldwide during the recent decades, which affect biosphere function and biodiversity. Ecosystems returned to its original structures and functions to maintain its sustainability, which was closely dependent on ecosystem resilience. Understanding the resilience and recovery capacity of ecosystem to extreme climate events is essential to predicting future ecosystem responses to climate change. Given the overwhelming importance of this region in the overall carbon cycle of forest ecosystems in China, south China suffered a destructive ice storm in 2008. In this study, we used the number of freezing day and a process-based model (Boreal Ecosystem Productivity Simulator, BEPS) to characterize the spatial distribution of ice storm region in southeastern China and explore the impacts on carbon cycle of forest ecosystem over the past decade. The ecosystem variables, i.e. Net primary productivity (NPP), Evapotranspiration (ET), and Water use efficiency (WUE, the ratio of NPP to ET) from the outputs of BEPS models were used to detect the resistance and resilience of forest ecosystem in southern China. The pattern of ice storm-induced forest productivity widespread decline was closely related to the number of freezing day during the ice storm period. The NPP of forest area suffered heavy ice storm returned to normal status after five months with high temperature and ample moisture, indicated a high resilience of subtropical forest in China. The long-term changes of forest WUE remain stable, behaving an inherent sensitivity of ecosystem to extreme climate events. In addition, ground visits suggested that the recovery of forest productivity was attributed to rapid growth of understory. Understanding the variability and recovery threshold of ecosystem following extreme climate events help us to better simulate and predict the variability of ecosystem structure and function under current and future climate change.

Crop insurance evaluation in response to extreme events

NASA Astrophysics Data System (ADS)

Moriondo, Marco; Ferrise, Roberto; Bindi, Marco

2013-04-01

Crop yield insurance has been indicated as a tool to manage the uncertainties of crop yields (Sherrick et al., 2004) but the changes in crop yield variability as expected in the near future should be carefully considered for a better quantitative assessment of farmer's revenue risk and insurance values in a climatic change regime (Moriondo et al., 2011). Under this point of view, mechanistic crop growth models coupled to the output of General/Regional Circulation Models (GCMs, RCMs) offer a valuable tool to evaluate crop responses to climatic change and this approach has been extensively used to describe crop yield distribution in response to climatic change considering changes in both mean climate and variability. In this work, we studied the effect of a warmer climate on crop yield distribution of durum wheat (Triticum turgidum L. subsp durum) in order to assess the economic significance of climatic change in a risk decision context. Specifically, the outputs of 6 RCMs (Tmin, Tmax, Rainfall, Global Radiation) (van der Linden and Mitchell 2009) have been statistically downscaled by a stochastic weather generator over eight sites across the Mediterranean basin and used to feed the crop growth model Sirius Quality. Three time slices were considered i) the present period PP (average of the period 1975-1990, [CO2]=350 ppm), 2020 (average of the period 2010-2030, SRES scenario A1b, [CO2]=415 ppm) and 2040 (average of the period 2030-2050, SRES scenario A1b, [CO2]=480 ppm). The effect of extreme climate events (i.e. heat stress at anthesis stage) was also considered. The outputs of these simulations were used to estimate the expected payout per hectare from insurance triggered when yields fall below a specific threshold defined as "the insured yield". For each site, the threshold was calculated as a fraction (70%) of the median of yield distribution under PP that represents the percentage of median yield above which indemnity payments are triggered. The results indicated that when the effect of extreme events was not considered, climate change had a low or no impact on crop yield distribution in 2020 and 2040. This resulted into an expected payout close to what observed in the present period. Conversely, the simulation of the effect of extreme events highly affected the PDFs by reducing the expected yield. This highlights that insured yield in future projections may be overestimated when not considering the impact of extremes, leading to distortions in the risk management of crop insurance companies. References Moriondo M, Giannakopoulos C, Bindi M (2011) Climate ch'ange impact assessment: the role of climate extremes in crop yield simulation. Clim Change 104:679-701 Sherrick BJ, Zanini FC, Schnitkey GD, Irwin SH (2004) Crop Insurance Valuation under Alternative Yield Distributions. American Journal of Agricultural Economics, 86:406-419. van der Linden P, Mitchell JFB (eds) (2009) ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3 PB, UK. 160 pp

Global crop yield response to extreme heat stress under multiple climate change futures

NASA Astrophysics Data System (ADS)

Deryng, D.; Conway, D.; Ramankutty, N.; Price, J.; Warren, R.

2014-12-01

Extreme heat stress during the crop reproductive period can be critical for crop productivity. Projected changes in the frequency and severity of extreme climatic events are expected to negatively impact crop yields and global food production. This study applies the global crop model PEGASUS to quantify, for the first time at the global scale, impacts of extreme heat stress on maize, spring wheat and soybean yields resulting from 72 climate change scenarios for the 21st century. Our results project maize to face progressively worse impacts under a range of RCPs but spring wheat and soybean to improve globally through to the 2080s due to CO2 fertilization effects, even though parts of the tropic and sub-tropic regions could face substantial yield declines. We find extreme heat stress at anthesis (HSA) by the 2080s (relative to the 1980s) under RCP 8.5, taking into account CO2 fertilization effects, could double global losses of maize yield (dY = -12.8 ± 6.7% versus -7.0 ± 5.3% without HSA), reduce projected gains in spring wheat yield by half (dY = 34.3 ± 13.5% versus 72.0 ± 10.9% without HSA) and in soybean yield by a quarter (dY = 15.3 ± 26.5% versus 20.4 ± 22.1% without HSA). The range reflects uncertainty due to differences between climate model scenarios; soybean exhibits both positive and negative impacts, maize is generally negative and spring wheat generally positive. Furthermore, when assuming CO2 fertilization effects to be negligible, we observe drastic climate mitigation policy as in RCP 2.6 could avoid more than 80% of the global average yield losses otherwise expected by the 2080s under RCP 8.5. We show large disparities in climate impacts across regions and find extreme heat stress adversely affects major producing regions and lower income countries.

Global crop yield response to extreme heat stress under multiple climate change futures

NASA Astrophysics Data System (ADS)

Deryng, Delphine; Conway, Declan; Ramankutty, Navin; Price, Jeff; Warren, Rachel

2014-03-01

Extreme heat stress during the crop reproductive period can be critical for crop productivity. Projected changes in the frequency and severity of extreme climatic events are expected to negatively impact crop yields and global food production. This study applies the global crop model PEGASUS to quantify, for the first time at the global scale, impacts of extreme heat stress on maize, spring wheat and soybean yields resulting from 72 climate change scenarios for the 21st century. Our results project maize to face progressively worse impacts under a range of RCPs but spring wheat and soybean to improve globally through to the 2080s due to CO2 fertilization effects, even though parts of the tropic and sub-tropic regions could face substantial yield declines. We find extreme heat stress at anthesis (HSA) by the 2080s (relative to the 1980s) under RCP 8.5, taking into account CO2 fertilization effects, could double global losses of maize yield (ΔY = -12.8 ± 6.7% versus - 7.0 ± 5.3% without HSA), reduce projected gains in spring wheat yield by half (ΔY = 34.3 ± 13.5% versus 72.0 ± 10.9% without HSA) and in soybean yield by a quarter (ΔY = 15.3 ± 26.5% versus 20.4 ± 22.1% without HSA). The range reflects uncertainty due to differences between climate model scenarios; soybean exhibits both positive and negative impacts, maize is generally negative and spring wheat generally positive. Furthermore, when assuming CO2 fertilization effects to be negligible, we observe drastic climate mitigation policy as in RCP 2.6 could avoid more than 80% of the global average yield losses otherwise expected by the 2080s under RCP 8.5. We show large disparities in climate impacts across regions and find extreme heat stress adversely affects major producing regions and lower income countries.

Assessing Climate Change Perceptions, Management Strategies, and Information Needs for Indiana Agricultural and Forestry Sectors

NASA Astrophysics Data System (ADS)

Cherkauer, K. A.; Chin, N.

2016-12-01

The agricultural and forestry sectors in the state of Indiana are highly dependent on climate and, subsequently, highly vulnerable to the impacts of climate change. Higher temperatures, shifts in precipitation patterns, more widespread prevalence of pests and pathogens, and increased frequency and severity of extreme weather events could all have negative effects on these two sectors in the future. Agricultural and forest producers are already modifying their management strategies in response to perceptions of changes in climate risk, but such responses have been primarily reactive in nature and, in many cases, demonstrate a disconnect between scientific findings and stakeholder perceptions of the greatest climate risks. This research has been conducted to help improve understanding of climate change risks to agriculture and forestry in Indiana; stakeholder perceptions of climate risks and their current management strategies; and the effectiveness of these management strategies for dealing with current and future climate risk. Sector-specific focus groups, expert panel assessments and surveys have all been utilized in this work, which will also contribute to the new Indiana Climate Change Impacts Assessment report.

21st Century Changes in Precipitation Extremes Over the United States: Can Climate Analogues Help or Hinder?

NASA Astrophysics Data System (ADS)

Gao, X.; Schlosser, C. A.

2013-12-01

Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency and intensity distribution of precipitation, especially at the regional scale. In this study, gridded data from a dense network of surface precipitation gauges and a global atmospheric analysis at a coarser scale are combined to develop a diagnostic framework for the large-scale meteorological conditions (i.e. flow features, moisture supply) that dominate during extreme precipitation. Such diagnostic framework is first evaluated with the late 20th century simulations from an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and is found to produce more consistent (and less uncertain) total and interannaul number of extreme days with the observations than the model-based precipitation over the south-central United States and the Western United States examined in this study. The framework is then applied to the CMIP5 multi-model projections for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5) to assess the potential future changes in the probability of precipitation extremes over the same study regions. We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.

Discounting the distant future-Data on Australian discount rates estimated by a stochastic interest rate model.

PubMed

Truong, Chi; Trück, Stefan

2017-04-01

Data on certainty equivalent discount factors and discount rates for stochastic interest rates in Australia are provided in this paper. The data has been used for the analysis of investments into climate adaptation projects in ׳It׳s not now or never: Implications of investment timing and risk aversion on climate adaptation to extreme events ׳ (Truong and Trück, 2016) [3] and can be used for other cost-benefit analysis studies in Australia. The data is of particular interest for the discounting of projects that create monetary costs and benefits in the distant future.

Simulating US Agriculture in a Modern Dust Bowl Drought

NASA Technical Reports Server (NTRS)

Glotter, Michael; Elliott, Joshua

2016-01-01

Drought-induced agricultural loss is one of the most costly impacts of extreme weather, and without mitigation, climate change is likely to increase the severity and frequency of future droughts. The Dust Bowl of the 1930s was the driest and hottest for agriculture in modern US history. Improvements in farming practices have increased productivity, but yields today are still tightly linked to climate variation and the impacts of a 1930s-type drought on current and future agricultural systems remain unclear. Simulations of biophysical process and empirical models suggest that Dust-Bowl-type droughts today would have unprecedented consequences, with yield losses approx.50% larger than the severe drought of 2012. Damages at these extremes are highly sensitive to temperature, worsening by approx.25% with each degree centigrade of warming. We find that high temperatures can be more damaging than rainfall deficit, and, without adaptation, warmer mid-century temperatures with even average precipitation could lead to maize losses equivalent to the Dust Bowl drought. Warmer temperatures alongside consecutive droughts could make up to 85% of rain-fed maize at risk of changes that may persist for decades. Understanding the interactions of weather extremes and a changing agricultural system is therefore critical to effectively respond to, and minimize, the impacts of the next extreme drought event.

Simulating US agriculture in a modern Dust Bowl drought.

PubMed

Glotter, Michael; Elliott, Joshua

2016-12-12

Drought-induced agricultural loss is one of the most costly impacts of extreme weather 1-3 , and without mitigation, climate change is likely to increase the severity and frequency of future droughts 4,5 . The Dust Bowl of the 1930s was the driest and hottest for agriculture in modern US history. Improvements in farming practices have increased productivity, but yields today are still tightly linked to climate variation 6 and the impacts of a 1930s-type drought on current and future agricultural systems remain unclear. Simulations of biophysical process and empirical models suggest that Dust-Bowl-type droughts today would have unprecedented consequences, with yield losses ∼50% larger than the severe drought of 2012. Damages at these extremes are highly sensitive to temperature, worsening by ∼25% with each degree centigrade of warming. We find that high temperatures can be more damaging than rainfall deficit, and, without adaptation, warmer mid-century temperatures with even average precipitation could lead to maize losses equivalent to the Dust Bowl drought. Warmer temperatures alongside consecutive droughts could make up to 85% of rain-fed maize at risk of changes that may persist for decades. Understanding the interactions of weather extremes and a changing agricultural system is therefore critical to effectively respond to, and minimize, the impacts of the next extreme drought event.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Are extreme hydro-meteorological events a prerequisite for extreme water quality impacts? Exploring climate impacts on inland and coastal waters

NASA Astrophysics Data System (ADS)

Michalak, A. M.; Balaji, V.; Del Giudice, D.; Sinha, E.; Zhou, Y.; Ho, J. C.

2017-12-01

Questions surrounding water sustainability, climate change, and extreme events are often framed around water quantity - whether too much or too little. The massive impacts of extreme water quality impairments are equally compelling, however. Recent years have provided a host of compelling examples, with unprecedented harmful algal blooms developing along the West coast, in Utah Lake, in Lake Erie, and off the Florida coast, and huge hypoxic dead zones continuing to form in regions such as Lake Erie, the Chesapeake Bay, and the Gulf of Mexico. Linkages between climate change, extreme events, and water quality impacts are not well understood, however. Several factors explain this lack of understanding, including the relative complexity of underlying processes, the spatial and temporal scale mismatch between hydrologists and climatologists, and observational uncertainty leading to ambiguities in the historical record. Here, we draw on a number of recent studies that aim to quantitatively link meteorological variability and water quality impacts to test the hypothesis that extreme water quality impairments are the result of extreme hydro-meteorological events. We find that extreme hydro-meteorological events are neither always a necessary nor a sufficient condition for the occurrence of extreme water quality impacts. Rather, extreme water quality impairments often occur in situations where multiple contributing factors compound, which complicates both attribution of historical events and the ability to predict the future incidence of such events. Given the critical societal importance of water quality projections, a concerted program of uncertainty reduction encompassing observational and modeling components will be needed to examine situations where extreme weather plays an important, but not solitary, role in the chain of cause and effect.

An approach toward incorporation of global warming effects into Intensity-Duration-Frequency values

NASA Astrophysics Data System (ADS)

Kunkel, K.; Easterling, D. R.

2017-12-01

Rising global temperatures from increasing greenhouse gas concentrations will increase overall atmospheric water vapor concentrations. There is a high level of scientific confidence that this will increase the future intensity and frequency of extreme precipitation events, even in regions where overall precipitation may decrease. For control of runoff from extreme rainfall, infrastructure engineering utilizes design values of rainfall known as Intensity-Duration-Frequency (IDF) values. Use of the existing IDF values, which are based solely on historical climate records, is likely to lead to under-design of runoff control structures, and associated increased flood damages. However, future changes in IDF values are uncertain and probably regionally variable. Our paradigm is that changes in IDF values will result from changes in atmospheric capacity (water vapor concentrations) and opportunity (the number and intensity of heavy precipitation-producing storm systems). Relevant storm systems being investigated include extratropical cyclones and their associated fronts, tropical cyclones, and the North American Monsoon system. The overall approach involves developing IDF adjustment factors for changes in these components of the climate system. The adjustment factors have associated uncertainties, primarily from (1) uncertainties in the future pathway of greenhouse gas emissions and (2) variations among climate models in the sensitivity of the climate system to greenhouse gas concentration changes. In addition to meteorological considerations, the lifetime of projects designed using IDF values is an essential consideration because the IDF values may change substantially during that time. The initial results of this project will be discussed.

An Investigation of Bomb Cyclogenesis in NCEP's CFS Model

NASA Astrophysics Data System (ADS)

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

2008-12-01

With the concerns, impacts and consequences of climate change increasing, the need for climate models to simulate daily weather is very important. Given the improvements in resolution and physical parameterizations, climate models are becoming capable of resolving extreme weather events. A particular type of extreme event which has large impacts on transportation, industry and the general public is a rapidly intensifying cyclone referred to as a "bomb." In this study, bombs are investigated using the National Center for Environmental Prediction's (NCEP) Climate Forecast System (CFS) model. We generate storm tracks based on 6-hourly sea-level pressure (SLP) from long-term climate runs of the CFS model. Investigation of this dataset has revealed that the CFS model is capable of producing bombs. We show a case study of a bomb in the CFS model and demonstrate that it has characteristics similar to the observed. Since the CFS model is capable of producing bombs, future work will focus on trends in their frequency and intensity so that an assessment of the potential role of the bomb in climate change can be assessed.

Coastal vulnerability across the Pacific dominated by El Niño-Southern Oscillation

USGS Publications Warehouse

Barnard, Patrick L.; Short, Andrew D.; Harley, Mitchell D.; Splinter, Kristen D.; Vitousek, Sean; Turner, Ian L.; Allan, Jonathan; Banno, Masayuki; Bryan, Karin R.; Doria, André; Hansen, Jeff E.; Kato, Shigeru; Kuriyama, Yoshiaki; Randall-Goodwin, Evan; Ruggiero, Peter; Walker, Ian J.; Heathfield, Derek K.

2015-01-01

To predict future coastal hazards, it is important to quantify any links between climate drivers and spatial patterns of coastal change. However, most studies of future coastal vulnerability do not account for the dynamic components of coastal water levels during storms, notably wave-driven processes, storm surges and seasonal water level anomalies, although these components can add metres to water levels during extreme events. Here we synthesize multi-decadal, co-located data assimilated between 1979 and 2012 that describe wave climate, local water levels and coastal change for 48 beaches throughout the Pacific Ocean basin. We find that observed coastal erosion across the Pacific varies most closely with El Niño/Southern Oscillation, with a smaller influence from the Southern Annular Mode and the Pacific North American pattern. In the northern and southern Pacific Ocean, regional wave and water level anomalies are significantly correlated to a suite of climate indices, particularly during boreal winter; conditions in the northeast Pacific Ocean are often opposite to those in the western and southern Pacific. We conclude that, if projections for an increasing frequency of extreme El Niño and La Niña events over the twenty-first century are confirmed, then populated regions on opposite sides of the Pacific Ocean basin could be alternately exposed to extreme coastal erosion and flooding, independent of sea-level rise.

Robust changes in the socio-climate risk over CONUS by mid 21st century

NASA Astrophysics Data System (ADS)

Ashfaq, M.; Rastogi, D.; Batibeniz, F.; Alifa, M.; Pagán, B. R.; Bonds, B. W.; Pal, J. S.; Diffenbaugh, N. S.; Preston, B. L.

2017-12-01

Using high-resolution near-term ensemble projections of hydro-climatic changes, we investigate impacts of climate change on natural and human systems across the CONUS. Climate projections are based a hybrid downscaling approach where a combination of regional and hydrological models are used to downscales 11 Global Climate Models from the 5th phase of Coupled Model Inter-comparison Project to 4km horizontal grid spacing for 41 years in the historical period (1965-2005) and 41 years in the near-term future period (2010-2050) under Representative Concentration Pathway 8.5. Should emissions continue to rise, climatic changes will likely intensify the regional hydrological cycle over CONUS through the acceleration of the historical trends in cold, warm and wet extremes. Our results show robust changes in the occurrence of severe weather conditions and in the likelihood of ice, freezing rain and snowstorms that may have disruptive impact on large human population across the U.S. More summer like conditions will also drive increase in cooling demands and a net increase in the energy consumption over many regions. We further use an integrated vulnerability index that combines human exposure to different climate extremes (hot, cold, wet and dry) and changes in socioeconomic pathways (due to changes in population and income levels), to reveal that future exposure to potentially damaging climatic conditions will likely increase manifold for population living in major urban centers in California, Texas, Florida, Michigan, Illinois and Northeast. With the current trajectory of emissions, these results warrant that a large human population across the U.S. may feel the impacts of climate change within its lifespan.

Projected increases in the annual flood pulse of the Western Amazon

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Manz, Bastian; Véliz Rosas, Claudia; Willems, Patrick; Lavado-Casimiro, Waldo; Guyot, Jean-Loup; Santini, William

2016-01-01

The impact of a changing climate on the Amazon basin is a subject of intensive research because of its rich biodiversity and the significant role of rainforests in carbon cycling. Climate change has also a direct hydrological impact, and increasing efforts have focused on understanding the hydrological dynamics at continental and subregional scales, such as the Western Amazon. New projections from the Coupled Model Inter-comparison Project Phase 5 ensemble indicate consistent climatic warming and increasing seasonality of precipitation in the Peruvian Amazon basin. Here we use a distributed land surface model to quantify the potential impact of this change in the climate on the hydrological regime of the upper Amazon river. Using extreme value analysis, historical and future projections of the annual minimum, mean, and maximum river flows are produced for a range of return periods between 1 and 100 yr. We show that the RCP 4.5 and 8.5 scenarios of climate change project an increased severity of the wet season flood pulse (7.5% and 12% increases respectively for the 100 yr return floods). These findings agree with previously projected increases in high extremes under the Special Report on Emissions Scenarios climate projections, and are important to highlight due to the potential consequences on reproductive processes of in-stream species, swamp forest ecology, and socio-economy in the floodplain, amidst a growing literature that more strongly emphasises future droughts and their impact on the viability of the rainforest system over greater Amazonia.

Will climate change increase the risk for critical infrastructure failures in Europe due to extreme precipitation?

NASA Astrophysics Data System (ADS)

Nissen, Katrin; Ulbrich, Uwe

2016-04-01

An event based detection algorithm for extreme precipitation is applied to a multi-model ensemble of regional climate model simulations. The algorithm determines extent, location, duration and severity of extreme precipitation events. We assume that precipitation in excess of the local present-day 10-year return value will potentially exceed the capacity of the drainage systems that protect critical infrastructure elements. This assumption is based on legislation for the design of drainage systems which is in place in many European countries. Thus, events exceeding the local 10-year return value are detected. In this study we distinguish between sub-daily events (3 hourly) with high precipitation intensities and long-duration events (1-3 days) with high precipitation amounts. The climate change simulations investigated here were conducted within the EURO-CORDEX framework and exhibit a horizontal resolution of approximately 12.5 km. The period between 1971-2100 forced with observed and scenario (RCP 8.5 and RCP 4.5) greenhouse gas concentrations was analysed. Examined are changes in event frequency, event duration and size. The simulations show an increase in the number of extreme precipitation events for the future climate period over most of the area, which is strongest in Northern Europe. Strength and statistical significance of the signal increase with increasing greenhouse gas concentrations. This work has been conducted within the EU project RAIN (Risk Analysis of Infrastructure Networks in response to extreme weather).

Simulating the Response of Urban Water Quality to Climate and Land Use Change in Partially Urbanized Basins

NASA Astrophysics Data System (ADS)

Sun, N.; Yearsley, J. R.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

Urban stream quality is particularly susceptible to extreme precipitation events and land use change. Although the projected effects of extreme events and land use change on hydrology have been resonably well studied, the impacts on urban water quality have not been widely examined due in part to the scale mismatch between global climate models and the spatial scales required to represent urban hydrology and water quality signals. Here we describe a grid-based modeling system that integrates the Distributed Hydrology Soil Vegetation Model (DHSVM) and urban water quality module adpated from EPA's Storm Water Management Model (SWMM) and Soil and water assessment tool (SWAT). Using the model system, we evaluate, for four partially urbanized catchments within the Puget Sound basin, urban water quality under current climate conditions, and projected potential changes in urban water quality associated with future changes in climate and land use. We examine in particular total suspended solids, toal nitrogen, total phosphorous, and coliform bacteria, with catchment representations at the 150-meter spatial resolution and the sub-daily timestep. We report long-term streamflow and water quality predictions in response to extreme precipitation events of varying magnitudes in the four partially urbanized catchments. Our simulations show that urban water quality is highly sensitive to both climatic and land use change.

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 excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.

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 water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario. PMID:29694355

Change of niche in guanaco (Lama guanicoe): the effects of climate change on habitat suitability and lineage conservatism in Chile.

PubMed

Castillo, Andrea G; Alò, Dominique; González, Benito A; Samaniego, Horacio

2018-01-01

The main goal of this contribution was to define the ecological niche of the guanaco ( Lama guanicoe ), to describe potential distributional changes, and to assess the relative importance of niche conservatism and divergence processes between the two lineages described for the species ( L.g. cacsilensis and L.g. guanicoe ). We used maximum entropy to model lineage's climate niche from 3,321 locations throughout continental Chile, and developed future niche models under climate change for two extreme greenhouse gas emission scenarios (RCP2.6 and RCP8.5). We evaluated changes of the environmental niche and future distribution of the largest mammal in the Southern Cone of South America. Evaluation of niche conservatism and divergence were based on identity and background similarity tests. We show that: (a) the current geographic distribution of lineages is associated with different climatic requirements that are related to the geographic areas where these lineages are located; (b) future distribution models predict a decrease in the distribution surface under both scenarios; (c) a 3% decrease of areal protection is expected if the current distribution of protected areas is maintained, and this is expected to occur at the expense of a large reduction of high quality habitats under the best scenario; (d) current and future distribution ranges of guanaco mostly adhere to phylogenetic niche divergence hypotheses between lineages. Associating environmental variables with species ecological niche seems to be an important aspect of unveiling the particularities of, both evolutionary patterns and ecological features that species face in a changing environment. We report specific descriptions of how these patterns may play out under the most extreme climate change predictions and provide a grim outlook of the future potential distribution of guanaco in Chile. From an ecological perspective, while a slightly smaller distribution area is expected, this may come with an important reduction of available quality habitats. From the evolutionary perspective, we describe the limitations of this taxon as it experiences forces imposed by climate change dynamics.

Change of niche in guanaco (Lama guanicoe): the effects of climate change on habitat suitability and lineage conservatism in Chile

PubMed Central

Castillo, Andrea G.; González, Benito A.

2018-01-01

Background The main goal of this contribution was to define the ecological niche of the guanaco (Lama guanicoe), to describe potential distributional changes, and to assess the relative importance of niche conservatism and divergence processes between the two lineages described for the species (L.g. cacsilensis and L.g. guanicoe). Methods We used maximum entropy to model lineage’s climate niche from 3,321 locations throughout continental Chile, and developed future niche models under climate change for two extreme greenhouse gas emission scenarios (RCP2.6 and RCP8.5). We evaluated changes of the environmental niche and future distribution of the largest mammal in the Southern Cone of South America. Evaluation of niche conservatism and divergence were based on identity and background similarity tests. Results We show that: (a) the current geographic distribution of lineages is associated with different climatic requirements that are related to the geographic areas where these lineages are located; (b) future distribution models predict a decrease in the distribution surface under both scenarios; (c) a 3% decrease of areal protection is expected if the current distribution of protected areas is maintained, and this is expected to occur at the expense of a large reduction of high quality habitats under the best scenario; (d) current and future distribution ranges of guanaco mostly adhere to phylogenetic niche divergence hypotheses between lineages. Discussion Associating environmental variables with species ecological niche seems to be an important aspect of unveiling the particularities of, both evolutionary patterns and ecological features that species face in a changing environment. We report specific descriptions of how these patterns may play out under the most extreme climate change predictions and provide a grim outlook of the future potential distribution of guanaco in Chile. From an ecological perspective, while a slightly smaller distribution area is expected, this may come with an important reduction of available quality habitats. From the evolutionary perspective, we describe the limitations of this taxon as it experiences forces imposed by climate change dynamics. PMID:29868293

Overwintering of herbaceous plants in a changing climate. Still more questions than answers.

PubMed

Rapacz, Marcin; Ergon, Ashild; Höglind, Mats; Jørgensen, Marit; Jurczyk, Barbara; Ostrem, Liv; Rognli, Odd Arne; Tronsmo, Anne Marte

2014-08-01

The increase in surface temperature of the Earth indicates a lower risk of exposure for temperate grassland and crop to extremely low temperatures. However, the risk of low winter survival rate, especially in higher latitudes may not be smaller, due to complex interactions among different environmental factors. For example, the frequency, degree and length of extreme winter warming events, leading to snowmelt during winter increased, affecting the risks of anoxia, ice encasement and freezing of plants not covered with snow. Future climate projections suggest that cold acclimation will occur later in autumn, under shorter photoperiod and lower light intensity, which may affect the energy partitioning between the elongation growth, accumulation of organic reserves and cold acclimation. Rising CO2 levels may also disturb the cold acclimation process. Predicting problems with winter pathogens is also very complex, because climate change may greatly influence the pathogen population and because the plant resistance to these pathogens is increased by cold acclimation. All these factors, often with contradictory effects on winter survival, make plant overwintering viability under future climates an open question. Close cooperation between climatologists, ecologists, plant physiologists, geneticists and plant breeders is strongly required to predict and prevent possible problems. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Developing research about extreme events and impacts to support international climate policy

NASA Astrophysics Data System (ADS)

Otto, Friederike; James, Rachel; Parker, Hannah; Boyd, Emily; Jones, Richard; Allen, Myles; Mitchell, Daniel; Cornforth, Rosalind

2015-04-01

Climate change is expected to have some of its most significant impacts through changes in the frequency and severity of extreme events. There is a pressing need for policy to support adaptation to changing climate risks, and to deal with residual loss and damage from climate change. In 2013, the Warsaw International Mechanism was established by the United Nations Framework Convention on Climate Change (UNFCCC) to address loss and damage in developing countries. Strategies to help vulnerable regions cope with losses from extreme events will presumably require information about the influence of anthropogenic forcing on extreme weather. But what kind of scientific evidence will be most useful for the Warsaw Mechanism? And how can the scientific communities working on extreme events and impacts develop their research to support the advance of this important policy? As climate scientists conducting probabilistic event attribution studies, we have been working with social scientists to investigate these questions. Our own research seeks to examine the role of external drivers, including greenhouse gas emissions, on the risk of extreme weather events such as heatwaves, flooding, and drought. We use large ensembles of climate models to compute the probability of occurrence of extreme events under current conditions and in a world which might have been without anthropogenic interference. In cases where the models are able to simulate extreme weather, the analysis allows for conclusions about the extent to which climate change may have increased, decreased, or made no change to the risk of the event occurring. These results could thus have relevance for the UNFCCC negotiations on loss and damage, and we have been communicating with policymakers and observers to the policy process to better understand how we can develop our research to support their work; by attending policy meetings, conducting interviews, and using a participatory game developed with the Red Cross/Red Crescent Climate Centre. This presentation is an opportunity to share some of our findings from this stakeholder engagement with a wider community of scientists working on extreme events. Discussing the use of scientific evidence in UNFCCC loss and damage policy has not been straightforward, since this is a very controversial topic. However, the UNFCCC has now approved a workplan for the next two years and there will be windows of opportunity for interaction between scientists and policymakers. Currently it is not clear what kind of evidence of loss and damage will be required for the Warsaw Mechanism, and in fact, there has been no official discussion under the UNFCCC about what defines loss and damage. One possibility would be to attempt to define loss and damage from climate change from a scientific perspective, and to identify the research gaps which might be addressed to support this. In the presentation we will make a proposal for future research directions, including the development of an inventory of impacts from climate change.

Impacts of future changes in weather condition on U.S. transportation

NASA Astrophysics Data System (ADS)

Ashfaq, M.; Pagan, B. R.; Bonds, B. W.; Rastogi, D.

2016-12-01

High-resolution near-term climate projections suggest an intensification of the regional hydrological cycle over the U.S., leading to stronger and more frequent precipitation events. Increase in precipitation extremes is driven by both warm season convection driven rainstorms and frontal based cold season snowstorms. Results also indicate that future warming is driven more by hot extremes, as decrease in cold extremes is three times less than increase in hot extremes. While projected changes may likely impact the transportation system across the U.S., accurate estimation of such impacts requires knowledge of changes in precipitation types (rain, snow, ice, freezing rain). Here we apply four commonly used precipitation typing algorithms to determine different types of precipitation in an 11-memebr high-resolution (18 km) climate projections dataset that covers 40 years (1966-2005) in the baseline and 40 years (2011-2050) in the future period under Representative Concentration Pathway 8.5. The results are compared with the NARR-based precipitation classification in the historical period at the county level. Documented weather related county level fatal crash data for the CONUS and non-fatal crash data for selected states in the eastern half of the U.S. is compiled to develop the historical baseline for the impact of weather conditions on transportation. Further analysis is carried out to understand the ability of an ensemble of high-resolution simulations to produce different precipitation types in the baseline period, potential changes in the occurrence of each type of weather condition in the future period and that how such changes may impact road conditions, vehicle crashes and human fatalities. Additional analysis will also be explored to understand the impact of changes in winter weather conditions on the cost associated with road maintenance.

Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability

DOE PAGES

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid; ...

2017-07-24

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the regionmore » could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.« less

Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability

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

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the regionmore » could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.« less

Projected changes to rain-on-snow events over North America

NASA Astrophysics Data System (ADS)

Jeong, Dae Il; Sushama, Laxmi

2016-04-01

Rain-on-snow (ROS) events have significant impacts on cold region ecosystems and water-related natural hazards, and therefore it is very important to assess how this hydro-meteorological phenomenon will evolve in a changing climate. This study evaluates the changes in ROS characteristics (i.e., frequency, amounts, and runoff) for the future 2041-2070 period with respect to the current 1976-2005 period over North America using six simulations, based on two Canadian RCMs, driven by two driving GCMs for RCP4.5 and 8.5 emission pathways. Projected changes to extreme runoff caused by the changes of the ROS characteristics are also evaluated. All simulations suggest general increases in ROS days in late autumn, winter, and early spring periods for most Canadian regions and northwestern USA for the future period, due to an increase in rain days in a warmer climate. Increases in the future ROS amounts are projected mainly due to an increase in ROS days, although increases in precipitation intensity also contributes to the future increases. Future ROS runoff is expected to increase more than future ROS amounts during snowmelt months as ROS events usually enhance runoff, given the land state and asociated reduced soil infiltration rate and also due to the faster snowmelt rate occuring during these events. The simulations also show that ROS events usually lead to extreme runoff over most of Canada and north-western and -central USA in the January-May snowmelt months for the current period and these show no significant changes in the future climate. However, the future ROS to total runoff ratio will significantly decrease for western and eastern Canada as well as north-western USA for these months, due to an overall increase of the fraction of direct snowmelt and rainfall generated runoff in a warmer climate. These results indicate the difficulties of flood risk and water resource managements in the future, particularly in Canada and north-western and -central USA, requiring more in depth studies for these regions to facilitate appropriate adaptation measures.

The relative contribution of climate to changes in lesser prairie-chicken abundance

USGS Publications Warehouse

Ross, Beth E.; Haukos, David A.; Hagen, Christian A.; Pitman, James

2016-01-01

Managing for species using current weather patterns fails to incorporate the uncertainty associated with future climatic conditions; without incorporating potential changes in climate into conservation strategies, management and conservation efforts may fall short or waste valuable resources. Understanding the effects of climate change on species in the Great Plains of North America is especially important, as this region is projected to experience an increased magnitude of climate change. Of particular ecological and conservation interest is the lesser prairie-chicken (Tympanuchus pallidicinctus), which was listed as “threatened” under the U.S. Endangered Species Act in May 2014. We used Bayesian hierarchical models to quantify the effects of extreme climatic events (extreme values of the Palmer Drought Severity Index [PDSI]) relative to intermediate (changes in El Niño Southern Oscillation) and long-term climate variability (changes in the Pacific Decadal Oscillation) on trends in lesser prairie-chicken abundance from 1981 to 2014. Our results indicate that lesser prairie-chicken abundance on leks responded to environmental conditions of the year previous by positively responding to wet springs (high PDSI) and negatively to years with hot, dry summers (low PDSI), but had little response to variation in the El Niño Southern Oscillation and the Pacific Decadal Oscillation. Additionally, greater variation in abundance on leks was explained by variation in site relative to broad-scale climatic indices. Consequently, lesser prairie-chicken abundance on leks in Kansas is more strongly influenced by extreme drought events during summer than other climatic conditions, which may have negative consequences for the population as drought conditions intensify throughout the Great Plains.

Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?

NASA Astrophysics Data System (ADS)

Ban, Nikolina; Schmidli, Juerg; Schär, Christoph

2015-02-01

Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6-7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that subdaily (e.g., hourly) precipitation extremes may increase at about twice this rate. Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parametrize convective precipitation (i.e., thunderstorms and rain showers). Here we employ a convection-resolving model using a horizontal grid spacing of 2.2 km across an extended region covering the Alps and its larger-scale surrounding from northern Italy to northern Germany. Consistent with previous results, projections using a Representative Concentration Pathways version 8.5 greenhouse gas scenario reveal a significant decrease of mean summer precipitation. However, unlike previous studies, we find that both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation. Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day precipitation scaling into the future.

Freight economic vulnerabilities due to flooding events.

DOT National Transportation Integrated Search

2016-12-01

Extreme weather events, and flooding in particular, have been occurring more often and with increased severity over the past decade, and there is reason to expect this trend will continue in the future due to a changing climate. Flooding events can u...

Progress Toward Meeting the Challenges of our Coastal Urban Future

EPA Science Inventory

Coastal urban regions are a nexus for climate change effects, extreme weather impacts, chemical/biological threats, and air quality issues as the global population increasingly concentrates in cities and megacities at the land/water interface. Sophisticated observational and mode...

Climate change. Six centuries of variability and extremes in a coupled marine-terrestrial ecosystem.

PubMed

Black, Bryan A; Sydeman, William J; Frank, David C; Griffin, Daniel; Stahle, David W; García-Reyes, Marisol; Rykaczewski, Ryan R; Bograd, Steven J; Peterson, William T

2014-09-19

Reported trends in the mean and variability of coastal upwelling in eastern boundary currents have raised concerns about the future of these highly productive and biodiverse marine ecosystems. However, the instrumental records on which these estimates are based are insufficiently long to determine whether such trends exceed preindustrial limits. In the California Current, a 576-year reconstruction of climate variables associated with winter upwelling indicates that variability increased over the latter 20th century to levels equaled only twice during the past 600 years. This modern trend in variance may be unique, because it appears to be driven by an unprecedented succession of extreme, downwelling-favorable, winter climate conditions that profoundly reduce productivity for marine predators of commercial and conservation interest. Copyright © 2014, American Association for the Advancement of Science.

Spatial analysis of extreme precipitation deficit as an index for atmospheric drought in Belgium

NASA Astrophysics Data System (ADS)

Zamani, Sepideh; Van De Vyver, Hans; Gobin, Anne

2014-05-01

The growing concern among the climate scientists is that the frequency of weather extremes will increase as a result of climate change. European society, for example, is particularly vulnerable to changes in the frequency and intensity of extreme events such as heat waves, heavy precipitation, droughts, and wind storms, as seen in recent years [1,2]. A more than 50% of the land is occupied by managed ecosystem (agriculture, forestry) in Belgium. Moreover, among the many extreme weather conditions, drought counts to have a substantial impact on the agriculture and ecosystem of the affected region, because its most immediate consequence is a fall in crop production. Besides the technological advances, a reliable estimation of weather conditions plays a crucial role in improving the agricultural productivity. The above mentioned reasons provide a strong motivation for a research on the drought and its impacts on the economical and agricultural aspects in Belgium. The main purpose of the presented work is to map atmospheric drought Return-Levels (RL), as first insight for agricultural drought, employing spatial modelling approaches. The likelihood of future drought is studied on the basis of precipitation deficit indices for four vegetation types: water (W), grass (G), deciduous (D) and coniferous forests (C) is considered. Extreme Value Theory (EVT) [3,4,5] as a branch of probability and statistics, is dedicated to characterize the behaviour of extreme observations. The tail behaviour of the EVT distributions provide important features about return levels. EVT distributions are applicable in many study areas such as: hydrology, environmental research and meteorology, insurance and finance. Spatial Generalized Extreme Value (GEV) distributions, as a branch of EVT, are applied to annual maxima of drought at 13 hydro-meteorological stations across Belgium. Superiority of the spatial GEV model is that a region can be modelled merging the individual time series of observations from isolated sites and using a common regression model based on climatological/geographical covariates. The behaviour of the fitted spatial GEV-distribution is heavy-tailed with γ ≡ 0.3 over Belgium. A comparison between the RL-maps using GEV model and the ones obtained from Universal Kriging (UK) confirms the reliability of the spatial GEV model in explaining atmospheric drought in Belgium. References [1] Beniston, M., Stephenson, D. B., Christensen, O. B., Ferro, C. A. T., Frei, C., Goyette, S., Halsnaes, K., Holt, T., Jylhü, K., Koffi, B., Palutikoff, J., Schöll, R., Semmler, T., and Woth, K. (2007), Future extreme events in European climate; an exploration of Regional Climate Model projections. Climatic Change, 81, 71-95. [2] Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (Eds.)] (2007), king Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp. [3] Coles, S. (2001), An Introduction to Statistical Modeling of Extreme Values, Springer-Verlag Heidelberg, Germany. [4] Embrechts, P., C. Klüppelberg, and T. Mikosch (1997), Modelling Extremal Events for Insurance and Finance, Springer-Verlag, Berlin. [5] Smith, R., (2004), Statistics of extremes, with application in environment, insurance and finance, in : Extreme Values in Finance, Telecommunications and the Environment, edited by: Finkenstadt, B. and Rootzen, H., 373-388, Chapman and Hall CRC Press, London.

Future Scenarios as a Research Tool: Investigating Climate Change Impacts, Adaptation Options and Outcomes for the Great Barrier Reef, Australia.

PubMed

Evans, Louisa S; Hicks, Christina C; Fidelman, Pedro; Tobin, Renae C; Perry, Allison L

2013-01-01

Climate change is a significant future driver of change in coastal social-ecological systems. Our knowledge of impacts, adaptation options, and possible outcomes for marine environments and coastal industries is expanding, but remains limited and uncertain. Alternative scenarios are a way to explore potential futures under a range of conditions. We developed four alternative future scenarios for the Great Barrier Reef and its fishing and tourism industries positing moderate and more extreme (2-3 °C above pre-industrial temperatures) warming for 2050 and contrasting 'limited' and 'ideal' ecological and social adaptation. We presented these scenarios to representatives of key stakeholder groups to assess the perceived viability of different social adaptation options to deliver desirable outcomes under varied contexts.

Ranking of European Capitals According to the Impact of Future Heat Waves

NASA Astrophysics Data System (ADS)

Smid, M.; Costa, A. C.; Russo, S.; Pebesma, E. J.; Canut, C. G.

2017-12-01

In warming Europe, we are witnessing a growth in urban population with aging trend, which will make the society more vulnerable to extreme heat waves. In the period 1950-2015 the occurrence of extreme heat waves increased across European capitals. As an example, Moscow was hit by the strongest heat wave of the present era, killing more than ten thousand people. Here we focus on larger metropolitan areas of European capitals. By using observations and an ensemble of eight EURO-CORDEX models under the RCP8.5 scenario, we calculate a suite of temperature based climate indices. We introduce a simple ranking procedure based on ensemble predictions using the mean of metropolitan grid cells for each capital, and population density as a proxy to quantify the future impact. Results show that the selected ensemble provides solid simulation of climate characteristics over most of the targeted metropolitan areas. All the investigated European metropolitan areas will be more vulnerable to extreme heat in the coming decades. Based on the impact ranking, the results reveal that in near, but mainly in distant future, the extreme heat events in European capitals will be not exclusive to traditionally exposed areas such as the Mediterranean and the Iberian Peninsula. The ranking of European capitals based on their vulnerability to the extreme heat could be of paramount importance to the decision makers in order to mitigate the heat related mortality, especially with the foreseen increase of global mean temperature. Acknowledgments: The authors gratefully acknowledge the support of Geoinformatics: Enabling Open Cities (GEO-C), the project funded by the European Commission within the Marie Skłodowska-Curie Actions, International Training Networks (ITN), European Joint Doctorates (EJD). Grant Agreement number 642332 — GEO-C — H2020-MSCA-ITN-2014.

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 to be produced (Porto and Douro wine), while climate variability affects the annual productivity and quality of the grape harvest. Our study investigates changes in the extreme climate events in the future model runs, through a set of climate change indicators defined by the WRCP's Expert Team in Climate Change Detection and Indices, which uses variables such as daily maximum and minimum temperatures and precipitation amounts. Furthermore, we explore heat waves and their properties (duration, intensity and recovery factor). The analysis shows an increase of the mean temperature in the DDR higher than 2°C by the mid-21st century and 4.5°C by the end of the century, relatively to the reference period. Moreover, we found a major predisposition towards higher values of minimum and maximum daily temperatures and a decrease in the total precipitation during both future periods. These preliminary results indicate increased climatic stress on the DDR wine production and increased vulnerability of the wine varieties in this region.

Impact of climate change and seasonal trends on the fate of Arctic oil spills.

PubMed

Nordam, Tor; Dunnebier, Dorien A E; Beegle-Krause, C J; Reed, Mark; Slagstad, Dag

2017-12-01

We investigated the effects of a warmer climate, and seasonal trends, on the fate of oil spilled in the Arctic. Three well blowout scenarios, two shipping accidents and a pipeline rupture were considered. We used ensembles of numerical simulations, using the OSCAR oil spill model, with environmental data for the periods 2009-2012 and 2050-2053 (representing a warmer future) as inputs to the model. Future atmospheric forcing was based on the IPCC's A1B scenario, with the ocean data generated by the hydrodynamic model SINMOD. We found differences in "typical" outcome of a spill in a warmer future compared to the present, mainly due to a longer season of open water. We have demonstrated that ice cover is extremely important for predicting the fate of an Arctic oil spill, and find that oil spills in a warming climate will in some cases result in greater areal coverage and shoreline exposure.

Climate change impacts on forest fires: the stakeholders' perspective

NASA Astrophysics Data System (ADS)

Giannakopoulos, C.; Roussos, A.; Karali, A.; Hatzaki, M.; Xanthopoulos, G.; Chatzinikos, E.; Fyllas, N.; Georgiades, N.; Karetsos, G.; Maheras, G.; Nikolaou, I.; Proutsos, N.; Sbarounis, T.; Tsaggari, K.; Tzamtzis, I.; Goodess, C.

2012-04-01

In this work, we present a synthesis of the presentations and discussions which arose during a workshop on 'Impacts of climate change on forest fires' held in September 2011 at the National Observatory of Athens, Greece in the framework of EU project CLIMRUN. At first, a general presentation about climate change and extremes in the Greek territory provided the necessary background to the audience and highlighted the need for data and information exchange between scientists and stakeholders through climate services within CLIMRUN. Discussions and presentations that followed linked climate with forest science through the use of a meteorological index for fire risk and future projections of fire danger using regional climate models. The current situation on Greek forests was also presented, as well as future steps that should be taken to ameliorate the situation under a climate change world. A time series analysis of changes in forest fires using available historical data on forest ecosystems in Greece was given in this session. This led to the topic of forest fire risk assessment and fire prevention, stating all actions towards sustainable management of forests and effective mechanisms to control fires under climate change. Options for a smooth adaptation of forests to climate change were discussed together with the lessons learned on practical level on prevention, repression and rehabilitation of forest fires. In between there were useful interventions on sustainable hunting and biodiversity protection and on climate change impacts on forest ecosystems dynamics. The importance of developing an educational program for primary/secondary school students on forest fire management was also highlighted. The perspective of forest stakeholders on climate change and how this change can affect their current or future activities was addressed through a questionnaire they were asked to complete. Results showed that the majority of the participants consider climate variability to be important or very important and to influence their activities. Extreme climate events, desertification and drought were regarded as the most important environmental problems along with loss of biodiversity. Most of the participants answered that they use historical data for research, and would welcome climate data and services targeted to their sector if offered. Acknowledgement: This work was supported by the EU project CLIMRUN under contract FP7-ENV-2010- 265192.

Projecting future climate change impacts on heat-related mortality in large urban areas in China.

PubMed

Li, Ying; Ren, Ting; Kinney, Patrick L; Joyner, Andrew; Zhang, Wei

2018-05-01

Global climate change is anticipated to raise overall temperatures and has the potential to increase future mortality attributable to heat. Urban areas are particularly vulnerable to heat because of high concentrations of susceptible people. As the world's largest developing country, China has experienced noticeable changes in climate, partially evidenced by frequent occurrence of extreme heat in urban areas, which could expose millions of residents to summer heat stress that may result in increased health risk, including mortality. While there is a growing literature on future impacts of extreme temperatures on public health, projecting changes in future health outcomes associated with climate warming remains challenging and underexplored, particularly in developing countries. This is an exploratory study aimed at projecting future heat-related mortality risk in major urban areas in China. We focus on the 51 largest Chinese cities that include about one third of the total population in China, and project the potential changes in heat-related mortality based on 19 different global-scale climate models and three Representative Concentration Pathways (RCPs). City-specific risk estimates for high temperature and all-cause mortality were used to estimate annual heat-related mortality over two future twenty-year time periods. We estimated that for the 20-year period in Mid-21st century (2041-2060) relative to 1970-2000, incidence of excess heat-related mortality in the 51 cities to be approximately 37,800 (95% CI: 31,300-43,500), 31,700 (95% CI: 26,200-36,600) and 25,800 (95% CI: 21,300-29,800) deaths per year under RCP8.5, RCP4.5 and RCP2.6, respectively. Slowing climate change through the most stringent emission control scenario RCP2.6, relative to RCP8.5, was estimated to avoid 12,900 (95% CI: 10,800-14,800) deaths per year in the 51 cities in the 2050s, and 35,100 (95% CI: 29,200-40,100) deaths per year in the 2070s. The highest mortality risk is primarily in cities located in the North, East and Central regions of China. Population adaptation to heat is likely to reduce excess heat mortality, but the extent of adaptation is still unclear. Future heat mortality risk attributable to exposure to elevated warm season temperature is likely to be considerable in China's urban centers, with substantial geographic variations. Climate mitigation and heat risk management are needed to reduce such risk and produce substantial public health benefits. Copyright © 2018 Elsevier Inc. All rights reserved.

The response of tropical rainforests to drought-lessons from recent research and future prospects.

PubMed

Bonal, Damien; Burban, Benoit; Stahl, Clément; Wagner, Fabien; Hérault, Bruno

We review the recent findings on the influence of drought on tree mortality, growth or ecosystem functioning in tropical rainforests. Drought plays a major role in shaping tropical rainforests and the response mechanisms are highly diverse and complex. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical rainforests on the three continents. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance. Tropical rainforest ecosystems are characterized by high annual rainfall. Nevertheless, rainfall regularly fluctuates during the year and seasonal soil droughts do occur. Over the past decades, a number of extreme droughts have hit tropical rainforests, not only in Amazonia but also in Asia and Africa. The influence of drought events on tree mortality and growth or on ecosystem functioning (carbon and water fluxes) in tropical rainforest ecosystems has been studied intensively, but the response mechanisms are complex. Herein, we review the recent findings related to the response of tropical forest ecosystems to seasonal and extreme droughts and the current knowledge about the future of these ecosystems. This review emphasizes the progress made over recent years and the importance of the studies conducted under extreme drought conditions or in through-fall exclusion experiments in understanding the response of these ecosystems. It also points to the great diversity and complexity of the response of tropical rainforest ecosystems to drought. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical forest regions. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance.

Global hotspots of river erosion under global warming

NASA Astrophysics Data System (ADS)

Plink-Bjorklund, P.; Reichler, T.

2017-12-01

Extreme precipitation plays a significant role for river hydrology, flood hazards and landscape response. For example, the September 2013 rainstorm in the Colorado Front Range evacuated the equivalent of hundreds to thousands of years of hillslope weathering products. Although promoted by steep topography, the Colorado event is clearly linked to rainfall intensity, since most of the 1100 debris flows occurred within the highest rainfall contour. Additional evidence for a strong link between extreme precipitation and river erosion comes from the sedimentary record, and especially from that of past greenhouse climates. The existence of such a link suggests that information about global rainfall patterns can be used to define regions of increased erosion potential. However, the question arises what rainfall criteria to use and how well the method works. A related question is how ongoing climate change and the corresponding shifts in rainfall might impact the results. Here, we use atmospheric reanalysis and output from a climate model to identify regions that are particularly susceptible to landscape change in response to extreme precipitation. In order to define the regions, we combine several hydroclimatological and geomorphological criteria into a single index of erosion potential. We show that for current climate, our criteria applied to atmospheric reanalysis or to climate model data successfully localize known areas of increased erosion potential, such as the Colorado region. We then apply our criteria to climate model data for future climate to document how the location, extent, and intensity of erosion hotspots are likely to change under global warming.

The Impact of Climate Change in Rainfall Erosivity Index on Humid Mudstone Area

NASA Astrophysics Data System (ADS)

Yang, Ci-Jian; Lin, Jiun-Chuan

2017-04-01

It has been quite often pointed out in many relevant studies that climate change may result in negative impacts on soil erosion. Then, humid mudstone area is highly susceptible to climate change. Taiwan has extreme erosion in badland area, with annual precipitation over 2000 mm/y which is a considerably 3 times higher than other badland areas around the world, and with around 9-13 cm/y in denudation rate. This is the reason why the Erren River, a badland dominated basin has the highest mean sediment yield in the world, over 105 t km2 y. This study aims to know how the climate change would affect soil erosion from the source in the Erren River catchment. Firstly, the data of hourly precipitation from 1992 to 2016 are used to establish the regression between rainfall erosivity index (R, one of component for USLE) and precipitation. Secondly, using the 10 climate change models (provide form IPCC AR5) simulates the changes of monthly precipitation in different scenario from 2017 to 2216, and then over 200 years prediction R values can be use to describe the tendency of soil erosion in the future. The results show that (1) the relationship between rainfall erosion index and precipitation has high correction (>0.85) during 1992-2016. (2) From 2017 to 2216, 7 scenarios show that annual rainfall erosion index will increase over 2-18%. In contrast, the others will decrease over 7-14%. Overall, the variations of annual rainfall erosion index fall in the range of -14 to 18%, but it is important to pay attention to the variation of annual rainfall erosion index in extreme years. These fall in the range of -34 to 239%. This explains the extremity of soil erosion will occur easily in the future. Keywords: Climate Change, Mudstone, Rainfall Erosivity Index, IPCC AR5

Effects of climate change on landslide hazard in Europe (Invited)

NASA Astrophysics Data System (ADS)

Nadim, F.; Solheim, A.

2009-12-01

Landslides represent a major threat to human life, property and constructed facilities, infrastructure and natural environment in most mountainous and hilly regions of the world. As a consequence of climatic changes and potential global warming, an increase of landslide activity is expected in some parts of the world in the future. This will be due to increased extreme rainfall events, changes of hydrological cycles, meteorological events followed by sea storms causing coastal erosion and melting of snow and of frozen soils in the high mountains. During the past century, Europe experienced many fatalities and significant economic losses due to landslides. Since in many parts of Europe landslides are the most serious natural hazard, several recent European research projects are looking into the effects of climate change on the risk associated with landslides. Examples are the recently initiated SafeLand project, which looks into this problem across the continent, and GeoExtreme, which focused on Norway. The ongoing project SafeLand (www.safeland-fp7.eu) is a large, integrating project financed by the European Commission. It involves close to 30 organizations from 13 countries in Europe, and it looks into the effects of global change (mainly changes in demography and climate change) on the pattern of landslide risk in Europe. The SafeLand objectives are to (1) provide policy-makers, public administrators, researchers, scientists, educators and other stakeholders with improved harmonized framework and methodology for the assessment and quantification of landslide risk in Europe's regions; (2) evaluate the changes in risk pattern caused by climate change, human activity and policy changes; and (3) provide guidelines for choosing the most appropriate risk management strategies, including risk mitigation and prevention measures. To assess the changes in the landslide risk pattern in Norway over the next 50 years, the four-year integrated research project GeoExtreme (www.geoextreme.no) was executed. Different modules of the project established the database of landslide and avalanche events in Norway, investigated the coupling between climatic parameters and the occurrence of avalanches and landslides, developed regional, down-scaled climate scenarios for the next 50 years, and simulated a picture of possible future geohazards risk in Norway. The socioeconomic implications of geohazards in Norway, both in the past, and under the predicted future climate scenarios were also studied in the project. The latter study considered the costs related to damage by natural disasters and mitigation measures, ability to learn by experience, changes in preparedness, and impact of policy decisions. The main conclusion of the GeoExtreme project was that in a country with large climatic variation like Norway, the effects of climate change on the geohazard situation will vary significantly from location to location. Over a short time interval of 50 years, the largest increase in the direct socio-economic costs will most likely be in the transport sector. However, better adaptation to the present climate and geohazard problems would also require large investments, and this would in fact be the most important step in preparing for the expected changes during the next 50 years.

Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

Using EPA Tools and Data Services to Inform Changes to Design Storm Definitions for Wastewater Utilities based on Climate Model Projections

NASA Astrophysics Data System (ADS)

Tryby, M.; Fries, J. S.; Baranowski, C.

2014-12-01

Extreme precipitation events can cause significant impacts to drinking water and wastewater utilities, including facility damage, water quality impacts, service interruptions and potential risks to human health and the environment due to localized flooding and combined sewer overflows (CSOs). These impacts will become more pronounced with the projected increases in frequency and intensity of extreme precipitation events due to climate change. To model the impacts of extreme precipitation events, wastewater utilities often develop Intensity, Duration, and Frequency (IDF) rainfall curves and "design storms" for use in the U.S. Environmental Protection Agency's (EPA) Storm Water Management Model (SWMM). Wastewater utilities use SWMM for planning, analysis, and facility design related to stormwater runoff, combined and sanitary sewers, and other drainage systems in urban and non-urban areas. SWMM tracks (1) the quantity and quality of runoff made within each sub-catchment; and (2) the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period made up of multiple time steps. In its current format, EPA SWMM does not consider climate change projection data. Climate change may affect the relationship between intensity, duration, and frequency described by past rainfall events. Therefore, EPA is integrating climate projection data available in the Climate Resilience Evaluation and Awareness Tool (CREAT) into SWMM. CREAT is a climate risk assessment tool for utilities that provides downscaled climate change projection data for changes in the amount of rainfall in a 24-hour period for various extreme precipitation events (e.g., from 5-year to 100-year storm events). Incorporating climate change projections into SWMM will provide wastewater utilities with more comprehensive data they can use in planning for future storm events, thereby reducing the impacts to the utility and customers served from flooding and stormwater issues.

Low fidelity of CORDEX and their driving experiments indicates future climatic uncertainty over Himalayan watersheds of Indus basin

NASA Astrophysics Data System (ADS)

Hasson, Shabeh ul; Böhner, Jürgen; Chishtie, Farrukh

2018-03-01

Assessment of future water availability from the Himalayan watersheds of Indus Basin (Jhelum, Kabul and upper Indus basin—UIB) is a growing concern for safeguarding the sustainable socioeconomic wellbeing downstream. This requires, before all, robust climate change information from the present-day state-of-the-art climate models. However, the robustness of climate change projections highly depends upon the fidelity of climate modeling experiments. Hence, this study assesses the fidelity of seven dynamically refined (0.44° ) experiments, performed under the framework of the coordinated regional climate downscaling experiment for South Asia (CX-SA), and additionally, their six coarse-resolution driving datasets participating in the coupled model intercomparison project phase 5 (CMIP5). We assess fidelity in terms of reproducibility of the observed climatology of temperature and precipitation, and the seasonality of the latter for the historical period (1971-2005). Based on the model fidelity results, we further assess the robustness or uncertainty of the far future climate (2061-2095), as projected under the extreme-end warming scenario of the representative concentration pathway (RCP) 8.5. Our results show that the CX-SA and their driving CMIP5 experiments consistently feature low fidelity in terms of the chosen skill metrics, suggesting substantial cold (6-10 ° C) and wet (up to 80%) biases and underestimation of observed precipitation seasonality. Surprisingly, the CX-SA are unable to outperform their driving datasets. Further, the biases of CX-SA and of their driving CMIP5 datasets are higher in magnitude than their projected changes under RCP8.5—and hence under less extreme RCPs—by the end of 21st century, indicating uncertain future climates for the Indus Basin watersheds. Higher inter-dataset disagreements of both CMIP5 and CX-SA for their simulated historical precipitation and for its projected changes reinforce uncertain future wet/dry conditions whereas the CMIP5 projected warming is less robust owing to higher historical period uncertainty. Interestingly, a better agreement among those CX-SA experiments that have been obtained through downscaling different CMIP5 experiments with the same regional climate model (RCM) indicates the RCMs' ability of modulating the influence of lateral boundary conditions over a large domain. These findings, instead of suggesting the usual skill-based identification of 'reasonable' global or regional low fidelity experiments, rather emphasize on a paradigm shift towards improving their fidelity by exploiting the potential of meso-to-local scale climate models—preferably of those that can solely resolve global-to-local scale climatic processes—in terms of microphysics, resolution and explicitly resolved convections. Additionally, an extensive monitoring of the nival regime within the Himalayan watersheds will reduce the observational uncertainty, allowing for a more robust fidelity assessment of the climate modeling experiments.

Simulations of the Montréal urban heat island

NASA Astrophysics Data System (ADS)

Roberge, François; Sushama, Laxmi; Fanta, Gemechu

2017-04-01

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

Climate change in Brazil: perspective on the biogeochemistry of inland waters.

PubMed

Roland, F; Huszar, V L M; Farjalla, Vf; Enrich-Prast, A; Amado, A M; Ometto, J P H B

2012-08-01

Although only a small amount of the Earth's water exists as continental surface water bodies, this compartment plays an important role in the biogeochemical cycles connecting the land to the atmosphere. The territory of Brazil encompasses a dense river net and enormous number of shallow lakes. Human actions have been heavily influenced by the inland waters across the country. Both biodiversity and processes in the water are strongly driven by seasonal fluvial forces and/or precipitation. These macro drivers are sensitive to climate changes. In addition to their crucial importance to humans, inland waters are extremely rich ecosystems, harboring high biodiversity, promoting landscape equilibrium (connecting ecosystems, maintaining animal and plant flows in the landscape, and transferring mass, nutrients and inocula), and controlling regional climates through hydrological-cycle feedback. In this contribution, we describe the aquatic ecological responses to climate change in a conceptual perspective, and we then analyze the possible climate-change scenarios in different regions in Brazil. We also indentify some potential biogeochemical signals in running waters, natural lakes and man-made impoundments. The possible future changes in climate and aquatic ecosystems in Brazil are highly uncertain. Inland waters are pressured by local environmental changes because of land uses, landscape fragmentation, damming and diversion of water bodies, urbanization, wastewater load, and level of pollutants can alter biogeochemical patterns in inland waters over a shorter term than can climate changes. In fact, many intense environmental changes may enhance the effects of changes in climate. Therefore, the maintenance of key elements within the landscape and avoiding extreme perturbation in the systems are urgent to maintain the sustainability of Brazilian inland waters, in order to prevent more catastrophic future events.

Contrasting Climate Change Impact on River Flow from Glacierised Catchments in the Himalayan and Andes Mountains

NASA Astrophysics Data System (ADS)

Pellicciotti, F.; Ragettli, S.; Immerzeel, W. W. W.

2016-12-01

Glaciers and glacierised catchments in mountainous regions react to a changing climate in different manners depending on climate and glacier characteristics. Despite the key role of mountain ranges as natural water towers, their hydrological balance and future changes in glacier runoff associated with climate warming remain poorly understood because of high meteorological variability, physical inaccessibility and the complex interplay between climate, cryosphere and hydrological processes. We use a state-of-the art glacio-hydrological model informed by data from high altitude observations and the latest CMIP5 climate change scenarios to quantify the climate change impact on glaciers and runoff for two contrasting catchments vulnerable to changes in the cryosphere. The two catchments are located in the Central Andes of Chile and in the Nepalese Himalaya in close vicinity of densely populated areas. Although both sites are projected to experience a strong decrease in glacier area, they show remarkably different hydrological responses. Icemelt is on a rising limb in Langtang at least until 2041-2050 and starts to decrease afterwards, while in Juncal icemelt was already beyond its tipping point at the beginning of the 21st century. This contrasting response can be explained by differences in the elevation distribution of the glaciers in the two regions. In Juncal, many glaciers are melting up to the highest elevations already during the reference period (2000-2010) and increasing melt rates due to higher air temperatures cannot compensate the loss of glacier area. In Langtang, large sections of the glaciers at high elevations are currently not exposed to melt, but will be in the future, thus compensating for the loss of glacier area at lower elevations. As a result of these changes and projected changes in precipitation, in Juncal runoff will sharply decrease in the future and the runoff seasonality is sensitive to projected climatic changes. In Langtang, future water availability is on the rise for decades to come with limited shifts between seasons but increases in extreme events. Climate change adaptation in the Andes of Central Chile should thus focus on dealing with a reduction in water availability from the glacierised catchments, whereas in Nepal preparedness for flood extremes should be the policy priority.

Future projection of design storms using a GCM-informed weather generator

NASA Astrophysics Data System (ADS)

KIm, T. W.; Wi, S.; Valdés-Pineda, R.; Valdés, J. B.

2017-12-01

The rainfall Intensity-Duration-Frequency (IDF) curves are one of the most common tools used to provide planners with a description of the frequency of extreme rainfall events of various intensities and durations. Therefore deriving appropriate IDF estimates is important to avoid malfunctions of water structures that cause huge damage. Evaluating IDF estimates in the context of climate change has become more important because projections from climate models suggest that the frequency of intense rainfall events will increase in the future due to the increase in greenhouse gas emissions. In this study, the Bartlett-Lewis (BL) stochastic rainfall model is employed to generate annual maximum series of various sub-daily durations for test basins of the Model Parameter Estimation Experiment (MOPEX) project, and to derive the IDF curves in the context of climate changes projected by the North American Regional Climate Change (NARCCAP) models. From our results, it has been found that the observed annual rainfall maximum series is reasonably represented by the synthetic annual maximum series generated by the BL model. The observed data is perturbed by change factors to incorporate the NARCCAP climate change scenarios into the IDF estimates. The future IDF curves show a significant difference from the historical IDF curves calculated for the period 1968-2000. Overall, the projected IDF curves show an increasing trend over time. The impacts of changes in extreme rainfall on the hydrologic response of the MOPEX basins are also explored. Acknowledgement: This research was supported by a grant [MPSS-NH-2015-79] through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.

Atmospheric circulation types and extreme areal precipitation in southern central Europe

NASA Astrophysics Data System (ADS)

Jacobeit, Jucundus; Homann, Markus; Philipp, Andreas; Beck, Christoph

2017-04-01

Gridded daily rainfall data for southern central Europe are aggregated to regions of similar precipitation variability by means of S-mode principal component analyses separately for the meteorological seasons. Atmospheric circulation types (CTs) are derived by a particular clustering technique including large-scale fields of SLP, vertical wind and relative humidity at the 700 hPa level as well as the regional rainfall time series. Multiple regression models with monthly CT frequencies as predictors are derived for monthly frequencies and amounts of regional precipitation extremes (beyond the 95 % percentile). Using predictor output from different global climate models (ECHAM6, ECHAM5, EC-EARTH) for different scenarios (RCP4.5, RCP8.5, A1B) and two projection periods (2021-2050, 2071-2100) leads to assessments of future changes in regional precipitation extremes. Most distinctive changes are indicated for the summer season with mainly increasing extremes for the earlier period and widespread decreasing extremes towards the end of the 21st century, mostly for the strong scenario. Considerable uncertainties arise from the predictor use of different global climate models, especially during the winter and spring seasons.

21st Century Changes in Precipitation Extremes Based on Resolved Atmospheric Patterns

NASA Astrophysics Data System (ADS)

Gao, X.; Schlosser, C. A.; O'Gorman, P. A.; Monier, E.

2014-12-01

Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency distribution of precipitation, especially at the regional scale. In this study, a validated analogue method is employed to diagnose the potential future shifts in the probability of extreme precipitation over the United States under global warming. The method is based on the use of the resolved large-scale meteorological conditions (i.e. flow features, moisture supply) to detect the occurrence of extreme precipitation. The CMIP5 multi-model projections have been compiled for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The application of such analogue method to detect other types of hazard events, i.e. landslides is also explored. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.

How to deal with climate change uncertainty in the planning of engineering systems

NASA Astrophysics Data System (ADS)

Spackova, Olga; Dittes, Beatrice; Straub, Daniel

2016-04-01

The effect of extreme events such as floods on the infrastructure and built environment is associated with significant uncertainties: These include the uncertain effect of climate change, uncertainty on extreme event frequency estimation due to limited historic data and imperfect models, and, not least, uncertainty on future socio-economic developments, which determine the damage potential. One option for dealing with these uncertainties is the use of adaptable (flexible) infrastructure that can easily be adjusted in the future without excessive costs. The challenge is in quantifying the value of adaptability and in finding the optimal sequence of decision. Is it worth to build a (potentially more expensive) adaptable system that can be adjusted in the future depending on the future conditions? Or is it more cost-effective to make a conservative design without counting with the possible future changes to the system? What is the optimal timing of the decision to build/adjust the system? We develop a quantitative decision-support framework for evaluation of alternative infrastructure designs under uncertainties, which: • probabilistically models the uncertain future (trough a Bayesian approach) • includes the adaptability of the systems (the costs of future changes) • takes into account the fact that future decisions will be made under uncertainty as well (using pre-posterior decision analysis) • allows to identify the optimal capacity and optimal timing to build/adjust the infrastructure. Application of the decision framework will be demonstrated on an example of flood mitigation planning in Bavaria.

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 useful Climate Twins regions search. The Climate Twins tool works actually comparing future climate conditions of a certain source area in the Greater Alpine Region with current climate conditions of entire Europe and the neighbouring southern as well south-eastern areas as target regions. A next version will integrate web crawling features for searching information about climate-related local adaptations observed today in the target region which may turn out as appropriate solution for the source region under future climate conditions. The contribution will present the current tool functionally and will discuss which indicator sets, similarity conditions and uncertainty ranges work best to deliver scientifically sound climate comparisons and distinct mapping results.

Future flood risk in the tropics as measured by changes in extreme runoff intensity is strongly influenced by plant-physiological responses to rising CO2

NASA Astrophysics Data System (ADS)

Kooperman, G. J.; Hoffman, F. M.; Koven, C.; Lindsay, K. T.; Swann, A. L. S.; Randerson, J. T.

2017-12-01

Climate change is expected to increase the frequency of intense flooding events, and thus the risk of flood-related mortality, infrastructure damage, and economic loss. Assessments of future flooding from global climate models based only on precipitation intensity and temperature neglect important processes that occur within the land-surface, particularly the impacts of plant-physiological responses to rising CO2. Higher CO2 reduces stomatal conductance, leading to less water loss through transpiration and higher soil moisture. For a given precipitation rate, higher soil moisture decreases the amount of rainwater that infiltrates the surface and increases runoff. Here we assess the relative impacts of plant-physiological and radiative-greenhouse effects on changes in extreme runoff intensity over tropical continents using the Community Earth System Model. We find that extreme percentile rates increase significantly more than mean runoff in response to higher CO2. Plant-physiological effects contribute to only a small increase in precipitation intensity, but are a dominant driver of runoff intensification, contributing to one-half of the 99th percentile runoff intensity change and one-third of the 99.9th percentile change. Comprehensive assessments of future flooding risk need to account for the physiological as well as radiative impacts of CO2 in order to better inform flood prediction and mitigation practices.

Defense Coastal/Estuarine Research Program (DCERP) Annual Technical Report IV: March 2010-February 2011

DTIC Science & Technology

2011-05-01

of monitoring may be necessary to fully characterize and model the impact of major climatic events (e.g., tropical cyclones, major droughts ) and...stressors (past, present, and future) at local and regional scales; take account of extreme climatic events (e.g., hurricanes, droughts ); and integrate...the longleaf pine ( Pinus palustris), savannas, and pocosins (shrub bog) that dominate MCBCL’s terrestrial environments. Variation in the biota and

Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk

USGS Publications Warehouse

Lee, Minjin; Shevliakova, Elena; Malyshev, Sergey; Milly, P.C.D.; Jaffe, Peter R.

2016-01-01

Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.

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.

Heat waves in Portugal: Current regime, changes in future climate and impacts on extreme wildfires.

PubMed

Parente, J; Pereira, M G; Amraoui, M; Fischer, E M

2018-08-01

Heat waves (HW) can have devastating social, economic and environmental impacts. Together with long-term drought, they are the main factors contributing to wildfires. Surprisingly, the quantitative and objective analysis leading to the identification and characterization of HW in current and future climate conditions as well as its influence on the occurrence of extreme wildfires (EW) has never been performed for Portugal and are the main objectives of this study. For this reason, we assess HW in recent past and future climate based on a consistent high resolution meteorological database and have compared their occurrence with long and reliable, precise and detailed information about Portuguese fire events. Results include the characterization of HW frequency, duration, seasonality and intensity for current and different future climate conditions and their relationship with EW occurrence. We detected 130 HW between 1981 and 2010, concentrated between May and October and highest values in July and August. The highest HW number and duration is found over the Northeast corner and the south of the country while highest amplitudes are typically located in central area. HW characteristics present high inter-annual variability but are clearly associated to the temporal and spatial distribution of EW: 97% of total number of EW were active during an HW, 90% of total EW days were also HW days; 82% of the EW had duration completely contained in the duration of an HW; and, 83% of EW occurred during and in the area affected by HW. Our results also show that HW should increase in number, duration and amplitude, more significantly for RCP 8.5, and for the 30-year periods near the end of the 21st century. Findings of this study will support the definition of climate change adaptation strategies for fire danger and risk management. Copyright © 2018. Published by Elsevier B.V.

Variability of hydrological extreme events in East Asia and their dynamical control: a comparison between observations and two high-resolution global climate models

NASA Astrophysics Data System (ADS)

Freychet, N.; Duchez, A.; Wu, C.-H.; Chen, C.-A.; Hsu, H.-H.; Hirschi, J.; Forryan, A.; Sinha, B.; New, A. L.; Graham, T.; Andrews, M. B.; Tu, C.-Y.; Lin, S.-J.

2017-02-01

This work investigates the variability of extreme weather events (drought spells, DS15, and daily heavy rainfall, PR99) over East Asia. It particularly focuses on the large scale atmospheric circulation associated with high levels of the occurrence of these extreme events. Two observational datasets (APHRODITE and PERSIANN) are compared with two high-resolution global climate models (HiRAM and HadGEM3-GC2) and an ensemble of other lower resolution climate models from CMIP5. We first evaluate the performance of the high resolution models. They both exhibit good skill in reproducing extreme events, especially when compared with CMIP5 results. Significant differences exist between the two observational datasets, highlighting the difficulty of having a clear estimate of extreme events. The link between the variability of the extremes and the large scale circulation is investigated, on monthly and interannual timescales, using composite and correlation analyses. Both extreme indices DS15 and PR99 are significantly linked to the low level wind intensity over East Asia, i.e. the monsoon circulation. It is also found that DS15 events are strongly linked to the surface temperature over the Siberian region and to the land-sea pressure contrast, while PR99 events are linked to the sea surface temperature anomalies over the West North Pacific. These results illustrate the importance of the monsoon circulation on extremes over East Asia. The dependencies on of the surface temperature over the continent and the sea surface temperature raise the question as to what extent they could affect the occurrence of extremes over tropical regions in future projections.

Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

NASA Astrophysics Data System (ADS)

Ali, H.; Mishra, V.

2017-12-01

Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.

Translating Extreme Precipitation Data from Climate Change Projections into Resilient Engineering Applications

NASA Astrophysics Data System (ADS)

Cook, L. M.; Samaras, C.; Anderson, C.

2016-12-01

Engineers generally use historical precipitation trends to inform assumptions and parameters for long-lived infrastructure designs. However, resilient design calls for the adjustment of current engineering practice to incorporate a range of future climate conditions that are likely to be different than the past. Despite the availability of future projections from downscaled climate models, there remains a considerable mismatch between climate model outputs and the inputs needed in the engineering community to incorporate climate resiliency. These factors include differences in temporal and spatial scales, model uncertainties, and a lack of criteria for selection of an ensemble of models. This research addresses the limitations to working with climate data by providing a framework for the use of publicly available downscaled climate projections to inform engineering resiliency. The framework consists of five steps: 1) selecting the data source based on the engineering application, 2) extracting the data at a specific location, 3) validating for performance against observed data, 4) post-processing for bias or scale, and 5) selecting the ensemble and calculating statistics. The framework is illustrated with an example application to extreme precipitation-frequency statistics, the 25-year daily precipitation depth, using four publically available climate data sources: NARCCAP, USGS, Reclamation, and MACA. The attached figure presents the results for step 5 from the framework, analyzing how the 24H25Y depth changes when the model ensemble is culled based on model performance against observed data, for both post-processing techniques: bias-correction and change factor. Culling the model ensemble increases both the mean and median values for all data sources, and reduces range for NARCCAP and MACA ensembles due to elimination of poorer performing models, and in some cases, those that predict a decrease in future 24H25Y precipitation volumes. This result is especially relevant to engineers who wish to reduce the range of the ensemble and remove contradicting models; however, this result is not generalizable for all cases. Finally, this research highlights the need for the formation of an intermediate entity that is able to translate climate projections into relevant engineering information.

Understanding extreme rainfall events in Australia through historical data

NASA Astrophysics Data System (ADS)

Ashcroft, Linden; Karoly, David John

2016-04-01

Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this relationship has remained stable since the early to mid-19th century. Ashcroft, L., Gergis, J., Karoly, D.J., 2014a. A historical climate dataset for southeastern Australia, 1788-1859. Geosci. Data J. 1, 158-178. doi:10.1002/gdj3.19 Ashcroft, L., Karoly, D.J., Gergis, J., 2014b. Southeastern Australian climate variability 1860-2009: A multivariate analysis. Int. J. Climatol. 34, 1928-1944. doi:10.1002/joc.3812

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

Wilcox, Kevin R.; Shi, Zheng; Gherardi, Laureano A.

Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitationmore » changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. Here, we used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. Finally, this highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change experiments. Additionally, policy and land management decisions related to global change scenarios should consider how ANPP and BNPP responses may differ, and that ecosystem responses to extreme events might not be predicted from relationships found under moderate environmental changes.« less

Shifting patterns of mild weather in response to projected radiative forcing

NASA Astrophysics Data System (ADS)

van der Wiel, Karin; Kapnick, Sarah; Vecchi, Gabriel

2017-04-01

Traditionally, climate change research has focused on changes in mean climate (e.g. global mean temperature, sea level rise, glacier melt) or change in extreme events (e.g. hurricanes, extreme precipitation, droughts, heat waves, wild fires). Though extreme events have the potential to disrupt society, extreme conditions are rare by definition. In contrast, mild weather occurs frequently and many human activities are built around it. Examples of such activities include football games, dog walks, bike rides, and outdoor weddings, but also activities of direct economic impact, e.g. construction work, infrastructure projects, road or rail transportation, air travel, and landscaping projects. Absence of mild weather impacts society in various way, understanding current and future mild weather is therefore of high scientific interest. We present a global analysis of mild weather based on simple and relatable criteria and we explore changes in mild weather occurrence in response to radiative forcing. A high-resolution global climate model, GFDL HiFLOR, is used to allow for investigation of local features and changes. In response to RCP4.5, we find a slight global mean decrease in the annual number of mild days projected both in the near future (-4 d/yr, 2016-2035) and at the end of this century (-10 d/yr, 2081-2100). Projected regional and seasonal redistributions of mild days are substantially greater. Tropical regions are projected to see large decreases, in the mid-latitudes small increases in the number of mild days are projected. Mediterranean climates are projected to see a shift of mild weather away from the local summer to the shoulder seasons. These changes are larger than the interannual variability of mild weather caused by El Niño-Southern Oscillation. Finally, we use reanalysis data to show an observed global decrease in the recent past, and we verify that these observed regional changes in mild weather resemble the projections.

Integrated Framework for an Urban Climate Adaptation Tool

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

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

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

DOE PAGES

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; ...

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

Continental-Scale Estimates of Runoff Using Future Climate ...

EPA Pesticide Factsheets

Recent runoff events have had serious repercussions to both natural ecosystems and human infrastructure. Understanding how shifts in storm event intensities are expected to change runoff responses are valuable for local, regional, and landscape planning. To address this challenge, relative changes in runoff using predicted future climate conditions were estimated over different biophysical areas for the CONterminous U.S. (CONUS). Runoff was estimated using the Curve Number (CN) developed by the USDA Soil Conservation Service (USDA, 1986). A seamless gridded dataset representing a CN for existing land use/land cover (LULC) across the CONUS was used along with two different storm event grids created specifically for this effort. The two storm event grids represent a 2- and a 100-year, 24-hour storm event under current climate conditions. The storm event grids were generated using a compilation of county-scale Texas USGS Intensity-Duration-Frequency (IDF) data (provided by William Asquith, USGS, Lubbock, Texas), and NOAA Atlas-2 and NOAA Atlas-14 gridded data sets. Future CN runoff was predicted using extreme storm events grids created using a method based on Kao and Ganguly (2011) where precipitation extremes reflect changes in saturated water vapor pressure of the atmosphere in response to temperature changes. The Clausius-Clapeyron relationship establishes that the total water vapor mass of fully saturated air increases with increasing temperature, leading to

Effects on Storm-Water Management for Three Major US Cities Using Location Specific Extreme Precipitation Dynamical Downscaling

NASA Astrophysics Data System (ADS)

Pelle, A.; Allen, M.; Fu, J. S.

2013-12-01

With rising population and increasing urban density, it is of pivotal importance for urban planners to plan for increasing extreme precipitation events. Climate models indicate that an increase in global mean temperature will lead to increased frequency and intensity of storms of a variety of types. Analysis of results from the Coupled Model Intercomparison Project, Phase 5 (CMIP5) has demonstrated that global climate models severely underestimate precipitation, however. Preliminary results from dynamical downscaling indicate that Philadelphia, Pennsylvania is expected to experience the greatest increase of precipitation due to an increase in annual extreme events in the US. New York City, New York and Chicago, Illinois are anticipated to have similarly large increases in annual extreme precipitation events. In order to produce more accurate results, we downscale Philadelphia, Chicago, and New York City using the Weather Research and Forecasting model (WRF). We analyze historical precipitation data and WRF output utilizing a Log Pearson Type III (LP3) distribution for frequency of extreme precipitation events. This study aims to determine the likelihood of extreme precipitation in future years and its effect on the of cost of stormwater management for these three cities.

Explorations Around "Graceful Failure" in Transportation Infrastructure: Lessons Learned By the Infrastructure and Climate Network (ICNet)

NASA Astrophysics Data System (ADS)

Jacobs, J. M.; Thomas, N.; Mo, W.; Kirshen, P. H.; Douglas, E. M.; Daniel, J.; Bell, E.; Friess, L.; Mallick, R.; Kartez, J.; Hayhoe, K.; Croope, S.

2014-12-01

Recent events have demonstrated that the United States' transportation infrastructure is highly vulnerable to extreme weather events which will likely increase in the future. In light of the 60% shortfall of the $900 billion investment needed over the next five years to maintain this aging infrastructure, hardening of all infrastructures is unlikely. Alternative strategies are needed to ensure that critical aspects of the transportation network are maintained during climate extremes. Preliminary concepts around multi-tier service expectations of bridges and roads with reference to network capacity will be presented. Drawing from recent flooding events across the U.S., specific examples for roads/pavement will be used to illustrate impacts, disruptions, and trade-offs between performance during events and subsequent damage. This talk will also address policy and cultural norms within the civil engineering practice that will likely challenge the application of graceful failure pathways during extreme events.

Service Center for Climate Change Adaptation in Agriculture - an initiative of the University of West Hungary

NASA Astrophysics Data System (ADS)

Matyas, Cs.; Berki, I.; Drüszler, A.; Eredics, A.; Galos, B.; Moricz, N.; Rasztovits, E.

2012-04-01

In whole Central Europe agricultural production is highly vulnerable and sensitive to impacts of projected climatic changes. The low-elevation regions of the Carpathian Basin (most of the territory of Hungary), where precipitation is the minimum factor of production, are especially exposed to climatic extremes, especially to droughts. Rainfed agriculture, animal husbandry on nature-close pastures and nature-close forestry are the most sensitive sectors due to limited possibilities to counterbalance moisture supply constraints. These sectors have to be best prepared to frequency increase of extreme events, disasters and economic losses. So far, there is a lack of information about the middle and long term consequences on regional and local level. Therefore the importance of complex, long term management planning and of land use optimation is increasing. The aim of the initiative is to set up a fine-scale, GIS-based, complex, integrated system for the definition of the most important regional and local challenges and tasks of climate change adaptation and mitigation in agriculture, forestry, animal husbandry and also nature protection. The Service Center for Climate Change Adaptation in Agriculture is planned to provide the following services: § Complex, GIS-supported database, which integrates the basic information about present and projected climates, extremes, hydrology and soil conditions; § Evaluation of existing satellite-based and earth-based monitoring systems; § GIS-supported information about the future trends of climate change impacts on the agroecological potential and sensitivity status on regional and local level (e.g. land cover/use and expectable changes, production, water and carbon cycle, biodiversity and other ecosystem services, potential pests and diseases, tolerance limits etc.) in fine-scale horizontal resolution, based first of all on natural produce, including also social and economic consequences; § Complex decision supporting system on regional and local scale for middle- and long term adaptation and mitigation strategies, providing information on optimum technologies and energy balances. Cooperation with already existing Climate Service Centres and national and international collaboration in monitoring and research are important elements of the activity of the Centre. In the future, the Centre is planned to form part of a national information system on climate change adaptation and mitigation, supported by the Ministry of Development. Keywords: climate change impacts, forestry, rainfed agriculture, animal husbandry

Climate change impact on North Sea wave conditions: a consistent analysis of ten projections

NASA Astrophysics Data System (ADS)

Grabemann, Iris; Groll, Nikolaus; Möller, Jens; Weisse, Ralf

2015-02-01

Long-term changes in the mean and extreme wind wave conditions as they may occur in the course of anthropogenic climate change can influence and endanger human coastal and offshore activities. A set of ten wave climate projections derived from time slice and transient simulations of future conditions is analyzed to estimate the possible impact of anthropogenic climate change on mean and extreme wave conditions in the North Sea. This set includes different combinations of IPCC SRES emission scenarios (A2, B2, A1B, and B1), global and regional models, and initial states. A consistent approach is used to provide a more robust assessment of expected changes and uncertainties. While the spatial patterns and the magnitude of the climate change signals vary, some robust features among the ten projections emerge: mean and severe wave heights tend to increase in the eastern parts of the North Sea towards the end of the twenty-first century in nine to ten projections, but the magnitude of the increase in extreme waves varies in the order of decimeters between these projections. For the western parts of the North Sea more than half of the projections suggest a decrease in mean and extreme wave heights. Comparing the different sources of uncertainties due to models, scenarios, and initial conditions, it can be inferred that the influence of the emission scenario on the climate change signal seems to be less important. Furthermore, the transient projections show strong multi-decadal fluctuations, and changes towards the end of the twenty-first century might partly be associated with internal variability rather than with systematic changes.

Mangrove expansion and contraction at a poleward range limit: climate extremes and land-ocean temperature gradients.

PubMed

Osland, Michael J; Day, Richard H; Hall, Courtney T; Brumfield, Marisa D; Dugas, Jason L; Jones, William R

2017-01-01

Within the context of climate change, there is a pressing need to better understand the ecological implications of changes in the frequency and intensity of climate extremes. Along subtropical coasts, less frequent and warmer freeze events are expected to permit freeze-sensitive mangrove forests to expand poleward and displace freeze-tolerant salt marshes. Here, our aim was to better understand the drivers of poleward mangrove migration by quantifying spatiotemporal patterns in mangrove range expansion and contraction across land-ocean temperature gradients. Our work was conducted in a freeze-sensitive mangrove-marsh transition zone that spans a land-ocean temperature gradient in one of the world's most wetland-rich regions (Mississippi River Deltaic Plain; Louisiana, USA). We used historical air temperature data (1893-2014), alternative future climate scenarios, and coastal wetland coverage data (1978-2011) to investigate spatiotemporal fluctuations and climate-wetland linkages. Our analyses indicate that changes in mangrove coverage have been controlled primarily by extreme freeze events (i.e., air temperatures below a threshold zone of -6.3 to -7.6°C). We expect that in the past 121 yr, mangrove range expansion and contraction has occurred across land-ocean temperature gradients. Mangrove resistance, resilience, and dominance were all highest in areas closer to the ocean where temperature extremes were buffered by large expanses of water and saturated soil. Under climate change, these areas will likely serve as local hotspots for mangrove dispersal, growth, range expansion, and displacement of salt marsh. Collectively, our results show that the frequency and intensity of freeze events across land-ocean temperature gradients greatly influences spatiotemporal patterns of range expansion and contraction of freeze-sensitive mangroves. We expect that, along subtropical coasts, similar processes govern the distribution and abundance of other freeze-sensitive organisms. In broad terms, our findings can be used to better understand and anticipate the ecological effects of changing winter climate extremes, especially within the transition zone between tropical and temperate climates. © 2016 by the Ecological Society of America.

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.

Relative impacts of land use and climate change on summer precipitation in the Netherlands

NASA Astrophysics Data System (ADS)

Daniels, Emma; Lenderink, Geert; Hutjes, Ronald; Holtslag, Albert

2016-10-01

The effects of historic and future land use on precipitation in the Netherlands are investigated on 18 summer days with similar meteorological conditions. The days are selected with a circulation type classification and a clustering procedure to obtain a homogenous set of days that is expected to favor land impacts. Changes in precipitation are investigated in relation to the present-day climate and land use, and from the perspective of future climate and land use. To that end, the weather research and forecasting (WRF) model is used with land use maps for 1900, 2000, and 2040. In addition, a temperature perturbation of +1 °C assuming constant relative humidity is imposed as a surrogate climate change scenario. Decreases in precipitation of, respectively, 3-5 and 2-5 % are simulated following conversion of historic to present, and present to future, land use. The temperature perturbation under present land use conditions increases precipitation amounts by on average 7-8 % and amplifies precipitation intensity. However, when also considering future land use, the increase is reduced to 2-6 % on average, and no intensification of extreme precipitation is simulated. In all, the simulated effects of land use changes on precipitation in summer are smaller than the effects of climate change, but are not negligible.

Projected changes of extreme precipitation over Contiguous United States with Nested regional climate model (NRCM)

NASA Astrophysics Data System (ADS)

Wang, J.

2013-12-01

Extreme weather events have already significantly influenced North America. During 2005-2011, the extreme events have increased by 250 %, from four or fewer events occurring in 2005, while 14 events occurring in 2011 (www.ncdc.noaa.gov/billions/). In addition, extreme rainfall amounts, frequency, and intensity were all expected to increase under greenhouse warming scenarios (Wehner 2005; Kharin et al. 2007; Tebaldi et al. 2006). Global models are powerful tools to investigate the climate and climate change on large scales. However, such models do not represent local terrain and mesoscale weather systems well owing to their coarse horizontal resolution (150-300 km). To capture the fine-scale features of extreme weather events, regional climate models (RCMs) with a more realistic representation of the complex terrain and heterogeneous land surfaces are needed (Mass et al. 2002). This study uses the Nested Regional Climate model (NRCM) to perform regional scale climate simulations on a 12-km × 12-km high resolution scale over North America (including Alaska; with 600 × 515 grid cells at longitude and latitude), known as CORDEX_North America, instead of small regions as studied previously (eg., Dominguez et al. 2012; Gao et al. 2012). The performance and the biases of the NRCM extreme precipitation calculations (2000-2010) have been evaluated with PRISM precipitation (Daly et al. 1997) by Wang and Kotamarthi (2013): the NRCM replicated very well the monthly amount of extreme precipitation with less than 3% overestimation over East CONUS, and the frequency of extremes over West CONUS and upper Mississippi River Basin. The Representative Concentration Pathway (RCP) 8.5 and RCP 4.5 from the new Community Earth System Model version 1.0 (CESM v1.0) are dynamically downscaled to predict the extreme rainfall events at the end-of-century (2085-2095) and to explore the uncertainties of future extreme precipitation induced by different scenarios over distinct regions. We have corrected the CO2 atmospheric concentration in the longwave/shortwave radiation schemes of the NRCM according to the recommended datasets by CMIP5 (Clarke et al. 2007; Riahi et al. 2007). We have also corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask of CLM 4.0 as mentioned by Gao et al. (2012). Acknowledgements: This work was supported under a military interdepartmental purchase request from the SERDP, RC-2242, through U.S. Department of Energy contract DE-AC02-06CH11357.

Hell and High Water: Practice-Relevant Adaptation Science

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

Moss, Richard H.; Meehl, G.; Lemos, Maria Carmen

2013-11-08

Recent extreme weather such as Hurricane Sandy and the 2012 drought demonstrate the vulnerability of the United States to climate extremes in the present and point to the potential for increased future damages under a changing climate. They also provide lessons for reducing harm and realizing any potential benefits. Preparedness measures – also referred to as adaptation – can cost-effectively increase resilience today and in the future. The upfront costs will be more than offset by reductions in property damage, lives and livelihoods lost, and expensive post-disaster recovery processes. While others have addressed use of science for adaptation in specificmore » sectors including biodiversity (Heller and Zavaleta, 2009) and freshwater ecosystem management (Wilby et al., 2010), or by simply taking a more pragmatic approach to adaptation under uncertainty (Hallegatte, 2009), here the authors make the case that a new, comprehensive approach is needed to create and use science to inform adaptations with applicable and sound knowledge (Kerr et al., 2011).« less

Investigation of Changes in Extreme Temperature and Humidity Over China Through a Dynamical Downscaling Approach

NASA Astrophysics Data System (ADS)

Zhu, Jinxin; Huang, Gordon; Wang, Xiuquan; Cheng, Guanhui

2017-11-01

Impacts of climate change relating to public health are often determined by multiple climate variables. The health-related metrics combining high-temperature and relative humidity are most concerned. Temperatures, relative humidity and relationship among them are investigated here for a comprehensive assessment of climate change impacts over China. A projection of combined temperatures and humidity through the PRECIS model is addressed. The PRECIS model's skill in reproducing the historical climate over China was first gauged through validating its historical simulation with the observation data set in terms of the two contributing variables. With good results of validation, a plausible range of combined temperatures and relative humidity were generated under RCPs. The results suggested that the annual mean temperature of China will increase up to 6°C at the end of 21st century. Opposite to the significantly change in the temperature, the maximum magnitude of changes in relative humidity is only 8% from the value in the baseline period. The dew point temperature is projected to be 14.9°C (within the comfortable interval) over the whole nation under high radiative forcing scenario at the end of this century. Therefore, the combination effects of high temperatures and relative humidity are substantially smaller than generally anticipated for China. Even though the impact-relevant metric like the dew point temperature is not projected as bad as the generally anticipated, we found that the frequency of high-temperature extremes increases up to 40% and the duration increases up to 150% in China. China is still expected to have more number of extremely hot days, more frequent high-temperature extremes, and longer duration of warm spell than before. Regionally, South China has the smallest changes in the mean, maximum and minimum temperatures while the largest increases in all five high-temperature indices. Consequently, the climate over South China for two future periods will be changing more drastically than the baseline period. Extra cautions need to be given to South China in the future.

Under the weather?-The direct effects of climate warming on a threatened desert lizard are mediated by their activity phase and burrow system.

PubMed

Moore, Danae; Stow, Adam; Kearney, Michael Ray

2018-05-01

For ectotherms such as lizards, the importance of behavioural thermoregulation in avoiding thermal extremes is well-established and is increasingly acknowledged in modern studies of climate warming and its impacts. Less appreciated and understood are the buffering roles of retreat sites and activity phase, in part because of logistical challenges of studying below-ground activity. Burrowing and nocturnal activity are key behavioural adaptations that have enabled a diverse range of reptiles to survive extreme environmental temperatures within hot desert regions. Yet, the direct impact of recent global warming on activity potential has been hypothesised to have caused extinctions in desert lizards, including the Australian arid zone skink Liopholis kintorei. We test the relevance of this hypothesis through a detailed characterisation of the above- and below-ground thermal and hydric microclimates available to, and used by, L. kintorei. We integrate operative temperatures with observed body temperatures to construct daily activity budgets, including the inference of subterranean behaviour. We then assess the likelihood that contemporary and future local extinctions in this species, and those of similar burrowing habits, could be explained by the direct effects of warming on its activity budget and exposure to thermal extremes. We found that L. kintorei spent only 4% of its time active on the surface, primarily at dusk, and that overall potential surface activity will be increased, not restricted, with climate warming. The burrow system provides an exceptional buffer to current and future maximum extremes of temperature (≈40°C reduction from potential surface temperatures), and desiccation (burrows near 100% humidity). Therefore, any climate warming impacts on this species are likely to be indirect. Our findings reflect the general buffering capacity of underground microclimates, therefore, our conclusions for L. kintorei are more generally applicable to nocturnal and crepuscular ectotherms, and highlight the need to consider the buffering properties of retreat sites and activity phase when forecasting climate change impacts. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

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.

Projected increases in the annual flood pulse of the western Amazon

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Manz, Bastian; Veliz Rosas, Claudia; Willems, Patrick; Lavado-Casimiro, Waldo; Guyot, Jean-Loup; Santini, William

2016-04-01

The impact of a changing climate on the Amazon basin is a subject of intensive research due to its rich biodiversity and the significant role of rain forest in carbon cycling. Climate change has also direct hydrological impact, and there have been increasing efforts to understand such dynamics at continental and subregional scales such as the scale of the western Amazon. New projections from the Coupled Model Inter- comparison Project Phase 5 (CMIP5) ensemble indicate consistent climatic warming and increasing seasonality of precipitation in the Peruvian Amazon basin. Here we use a distributed land surface model to quantify the potential impact of this change in the climate on the hydrological regime of the river. Using extremes value analysis, historical and future projections of the annual minimum, mean, and maximum river flows are produced for a range of return periods between 1 and 100 years. We show that the RCP 4.5 and 8.5 scenarios of climate change project an increased severity of the wet season flood pulse (7.5% and 12% increases respectively for the 100- year return floods). These findings are in agreement with previously projected increases in high extremes under the Special Report on Emissions Scenarios (SRES) climate projections, and are important to highlight due to the potential consequences on reproductive processes of in-stream species, swamp forest ecology, and socio-economy in the floodplain, amid a growing literature that more strongly emphasises future droughts and their impact on the viability of the rain forest system over the greater Amazonia.

Influence of urban land cover changes and climate change for the exposure of European cities to flooding during high-intensity precipitation

NASA Astrophysics Data System (ADS)

Skougaard Kaspersen, P.; Høegh Ravn, N.; Arnbjerg-Nielsen, K.; Madsen, H.; Drews, M.

2015-06-01

The extent and location of impervious surfaces within urban areas due to past and present city development strongly affects the amount and velocity of run-off during high-intensity rainfall and consequently influences the exposure of cities towards flooding. The frequency and intensity of extreme rainfall are expected to increase in many places due to climate change and thus further exacerbate the risk of pluvial flooding. This paper presents a combined hydrological-hydrodynamic modelling and remote sensing approach suitable for examining the susceptibility of European cities to pluvial flooding owing to recent changes in urban land cover, under present and future climatic conditions. Estimated changes in impervious urban surfaces based on Landsat satellite imagery covering the period 1984-2014 are combined with regionally downscaled estimates of current and expected future rainfall extremes to enable 2-D overland flow simulations and flood hazard assessments. The methodology is evaluated for the Danish city of Odense. Results suggest that the past 30 years of urban development alone has increased the city's exposure to pluvial flooding by 6% for 10-year rainfall up to 26% for 100-year rainfall. Corresponding estimates for RCP4.5 and RCP8.5 climate change scenarios (2071-2100) are in the order of 40 and 100%, indicating that land cover changes within cities can play a central role for the cities' exposure to flooding and conversely also for their adaptation to a changed climate.

A 500 year climate reconstruction of Southwest Germany based on documentary and direct data with a special focus on high resolute reconstructed extreme rain events

NASA Astrophysics Data System (ADS)

Dostal, P.; Seidel, J.; Imbery, F.

2010-09-01

A 500 year climate reconstruction of Southwest Germany based on documentary and direct data with a special focus on high resolute reconstructed extreme rain events Against the background of an increasing world population and the changes that this is causing to the earth, the increasing industrialisation resulting in more emissions of greenhouse gases, it is indispensable to differentiate between natural and anthropogenic climate changes. This applies equally to global as well as regional climates. Due to the fact, that the weather data measurement series in the upper Rhine valley go back a maximum of 150 years, it is not possible to use this data to grasp long term climate fluctuations. For example, the current climate is integrated in long scale climate cycles which last thousands of years. To describe these changes accurately, it is necessary to reconstruct the climate beyond that of instrumental series measurements. With the application of direct and indirect data (proxy data) a climate reconstruction will be attempted for the area of region TriRhena. With the application of documentary data it is possible to reconstruct the climate prior to instrumental measurements. These historical records are made up of, for e.g. weather descriptions, information about the wine harvest and other agricultural products, as well as their price fluctuations. Using this data it is possible to calculate meteorological parameters creating an index of air temperature and precipitation values. Climate is an integration of weather and therefore its worth to set the focus also on single interesting weather events. Especially extreme events can contribute to the thesis "learning from the past for a better future". Aim of the research is to identify and apply extreme flood events of the past 500 years as a basis for further analysis like a contribution to improve current flood hazard maps. The data which will be presented were extracted from historical records such as local annuals and chronologies from 1500-1900 and supplemented by instrumental observations since 1755.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Extreme Landfalling Atmospheric River Events in Arizona: Possible Future Changes

NASA Astrophysics Data System (ADS)

Singh, I.; Dominguez, F.

2016-12-01

Changing climate could impact the frequency and intensity of extreme atmospheric river events. This can have important consequences for regions like the Southwestern United Sates that rely upon AR-related precipitation for meeting their water demand and are prone to AR-related flooding. This study investigates the effects of climate change on extreme AR events in the Salt and Verde river basins in Central Arizona using a pseudo global warming method (PGW). First, the five most extreme events that affected the region were selected. High-resolution control simulations of these events using the Weather Research and Forecasting model realistically captured the magnitude and spatial distribution of precipitation. Subsequently, following the PGW approach, the WRF initial and lateral boundary conditions were perturbed. The perturbation signals were obtained from an ensemble of 9 General Circulation Models for two warming scenarios - Representative Concentration Pathway (RCP) 4.5 and RCP8.5. Several simulations were conducted changing the temperature and relative humidity fields. PGW simulations reveal that while the overall dynamics of the storms did not change significantly, there was marked strengthening of associated Integrated Vertical Transport (IVT) plumes. There was a general increase in the precipitation over the basins due to increased moisture availability, but heterogeneous spatial changes. Additionally, no significant changes in the strength of the pre-cold frontal low-level jet in the future simulations were observed.

The role of humidity in determining scenarios of perceived temperature extremes in Europe

NASA Astrophysics Data System (ADS)

Scoccimarro, Enrico; Fogli, Pier Giuseppe; Gualdi, Silvio

2017-11-01

An increase of the 2 m temperature over Europe is expected within the current century. In order to consider health impacts, it is important to evaluate the combined effect of temperature and humidity on the human body. To achieve this, projections of a basic index—the humidex—representative of the perceived temperature, under different scenarios and periods, have been investigated. The simultaneous occurrence of observed extreme temperature events and perceived extreme temperature events is seldom found within the present climate, reinforcing the importance of investigating the combination of the two fields. A set of 10 km resolution regional climate simulations, provided within the EURO-CORDEX multi-model effort, demonstrates an ability in representing moderate to extreme events of perceived temperature over the present climate, and to be useful as a tool for quantifying future changes in geographical patterns of exposed areas over Europe. Following the RCP8.5 emission scenario, an expansion of the area subject to dangerous conditions is suggested from the middle of the current century, reaching 60 °N. The most significant increase of perceived extreme temperature conditions is found comparing the 2066-2095 projections to the 1976-2005 period; bearing in mind that changes in relative humidity may either amplify or offset the health effects of temperature, a less pronounced projected reduction of relative humidity in the north-eastern part of Europe, associated with extreme humidex events, makes northern Europe the most prone region to an increase of moderate to extreme values of perceived temperature. This is in agreement with a pronounced projected specific humidity increase.

Projecting the Influence of Climate Change on Extreme Ground-level Ozone Events in Selected Ontario Cities =

NASA Astrophysics Data System (ADS)

Leung, Kinson He Yin

Ground-level ozone (O3) is perhaps one of the most familiar pollutants in Ontario, Canada because it is associated with most smog alerts in the province. O3 varies on a number of spatial and temporal scales, primarily due to meteorological variability and the impact of long-range transport of its precursors on the photochemical processes. The goal of this thesis is to project the change in the probability of occurrence of future Extreme Ground-level Ozone Events (EGLOEs) due to changes in atmospheric conditions as a result of climate change for cities located in the southern, eastern and northern parts of Ontario, Canada by using a combination of General Circulation / Global Climate Models (GCMs) and statistical downscaling. These Ontario cities are Toronto, Windsor, London, Kingston, Ottawa, Thunder Bay, Sudbury and North Bay. The successful downscaling method used in this research to generate city-specific climate change scenarios was the Statistical DownScaling Model (SDSM) version 4.2.2, which is a hybrid of regression-based and stochastic weather-generator downscaling methods. The results indicate that the mean values of the daily maximum ground-level ozone concentrations could increase by up to 12-17% in Southern Ontario, 8-16% in Eastern Ontario and 1.5-9% in Northern Ontario by the end of the century due largely to changes in long-range transport. Three important themes emerge from the results: 1) the research successfully model O3 concentration in a region where long-range transport plays a substantial role. 2) The clear confirmation regarding the role of long-range transport in determining O 3 concentration in most areas of Ontario. 3) The projected increase of ozone in Ontario, due largely to an increase of long-range transport, caused by shifting atmospheric dynamics rather than a direct temperature effect on ozone production. Moreover, the results indicate that the future Southern, Eastern and Northern Ontario's EGLOEs with the O3 concentration ≥ 80 ppb (the current Ontario 1-hour Ambient Air Quality criterion for extreme ozone concentration) will have an increase of over 60%, 50% and 62% respectively by the year of 2100 under the different future scenarios in the third version of the Coupled Global Climate Model (CGCM3) and the Hadley Centre's Climate Model (HadCM3).

A palaeo-ecological assessment of the resilience of south-east Asian dry forests to monsoon extremes

NASA Astrophysics Data System (ADS)

Hamilton, R. J.; Penny, D.; Maxwell, A.

2014-12-01

Predictions that the frequency and intensity of monsoon extremes will rise in coming decades are being made with increasing confidence. There is concern that these climatic changes may drive tropical monsoon forests across critical thresholds, triggering ecological regime shifts. The global consequences of such shifts, coupled with knowledge gaps around the nature and intensity of drivers needed to instigate ecosystem reorganization, highlights the need for research that analyses the resilience of these seasonal forest to future climatic change. While work has indicated that these forests may be susceptible to reorganization to savanna under changing precipitation regimes, the interactions between climatic drivers and ecosystem response is still poorly understood, particularly in the seasonal forests outside of the neo- and afro-tropics. This study presents results on the threshold dynamics of the extensive south-east Asian seasonally dry tropical forest ecoregion (SASDTF) through analysis of plant microfossils and charcoal archived in sediment cores extracted from two tropical crater lakes in Cambodia. These data are compared with regional paleoclimatic reconstructions to gauge past forest response to monsoon extremes, and provide insight into the magnitude and duration of climatic events most likely to result in the breaching of critical thresholds. Our results suggest that, at a biome level, the SASDTF appears resilient to low-amplitude climatic variations over millennia, despite instrumental observations of strong precipitation-tree cover coupling in global dry forest resilience models.

Risk analysis for the flood control capacity of dikes under climate change

NASA Astrophysics Data System (ADS)

Wei, Hsiao Ping; Yeh, Keh-Chia; Hsiao, Yi-Hua

2017-04-01

Climate change is the major reason for many extreme disaster events. In recent years, scientists have revealed many findings and most of them agree that the frequency of extreme weather and its corresponding hydrological impact will increase due to climate change. In such situation, the current hydrologic designs based upon historical observation, which could be changed, are necessary to review again under the scenario of climate change. It is for this reason that this study uses Kao-Ping River Basin as an example, using high resolution dynamical downscaling data (base period, near future, and end of the century) to simulate changes in hourly flow rate of typhoon events in each of the three 25-year periods. Results are further compared with the design flow rate announced by the competent authority of water resources, as well as recorded river water levels of the most severe typhoon event in history and risk analysis basic on factors, to evaluate the risk and impact of river flooding under climate change.From the simulation results, the frequency of exceeding design discharge in Kao-ping river catchment will increase in the end of century. The water level at these LI-LIN BRIDGE and SAN-TI-MEN gauges could be obviously influenced due to the extreme rainfall events, so that their flood control capacity should be assessed and improved.