Downscaled Climate Data Research Articles

Limitations to recovery following wildfire in dry forests of southern Colorado and northern New Mexico, USA.

Climate warming is contributing to increases in wildfire activity throughout the western United States, leading to potentially long-lasting shifts in vegetation. The response of forest ecosystems to wildfire is thus a crucial indicator of future vegetation trajectories, and these responses are contingent upon factors such as seed availability, interannual climate variability, average climate, and other components of the physical environment. To better understand variation in resilience to wildfire across vulnerable dry forests, we surveyed conifer seedling densities in 15 recent (1988-2010) wildfires and characterized temporal variation in seed cone production and seedling establishment. We then predicted postfire seedling densities at a 30-m resolution within each fire perimeter using downscaled climate data, monthly water balance models, and maps of surviving forest cover. Widespread ponderosa pine (Pinus ponderosa) seed cone production occurred at least twice following each fire surveyed, and pulses of conifer seedling establishment coincided with years of above-average moisture availability. Ponderosa pine and Douglas-fir (Pseudotsuga menziesii) seedling densities were higher on more mesic sites and adjacent to surviving trees, though there were also important interspecific differences, likely attributable to drought and shade tolerance. We estimated that postfire seedling densities in 42% (for ponderosa pine) and 69% (for Douglas-fir) of the total burned area were below the lowest reported historical tree densities in these forests. Spatial models demonstrated that an absence of mature conifers (particularly in the interior of large, high-severity patches) limited seedling densities in many areas, but 30-yr average actual evapotranspiration and climatic water deficit limited densities on marginal sites. A better understanding of the limitations to postfire forest recovery will refine models of vegetation dynamics and will help to improve strategies of adaptation to a warming climate and shifting fire activity.

Stream Flow Response to Climate Change on Tikur Wuha Catchment, Rift Valley of Ethiopia

Climate changes alter regional hydrologic conditions and results in a variety of impacts on water resource systems. This study aims to assess the streamflow response to Climate Change: the case of Tikur Wuha Sub-watershed, Rift Valley Basin of Ethiopia. In the study, the daily hydro-meteorological data values for the baseline period of 1981-2005 were used. Historical Representative Concentration Pathway (RCPs) data along with observed data of precipitation and temperature were used for extraction and bias correction using CMhyd tool. After evaluation of bias correction methods using RMSE, MAE and RE, the downscaled climate data such as, RCP4.5 and RCP8.5 scenarios was used for the future period assessment. Soil water assessment tool (SWAT) model were used to assess the streamflow response to Climate Change. The model calibration and validation results, using SWAT-CUP(SUFI-2), shows a good agreement with the observed flow with the coefficient of determination 0.79 and 8.6, and a Nash Sutcliffe efficiency was 0.56 and 0.64, respectively. The dynamically downscaled daily climate variables (precipitation and temperature) were used to simulate future projections of streamflow. Streamflow projections for future time periods showed that mean annual streamflow may increase by 15.43, 23.48, and 25.42% in 2020s, 2050s, and 2080s, respectively, from the baseline period for RCP 4.5 scenario, whereas for RCP 8.5 scenario, it will be expect to increase by 29.58, 34.20, and 38.72% in 2020s, 2050s, and 2080s, respectively. The model simulations considered only future climate change scenarios assuming all spatial data constant. Therefore, future study need to consider impact of land use/cover change on the sub-watershed for future sustainable development plan. Keywords : Climate Change, Streamflow, RCPs, Bias Correction, CMhyd, SWAT, SWAT-CUP DOI : 10.7176/JEES/9-8-01 Publication date : August 31 st 2019

Past, Present, and Future of Marcescent Mediterranean Forests

Mediterranean forests are unique and one of the most threatened biomes worldwide (Klausmeyer and Shaw 2009). They are distributed through marked ecological gradients that are supported by a wide variety of diverse geology and contrasting bioclimatic conditions. Marcescence (i.e., the abscence of leaf fall abscission; Addicott 1982), is a life-history trait related to contrasting or transitional climatic areas such as those across Eurosiberian and Mediterranean Regions (García-Mijangos et al. 2014). Thus, marcescent forests are ecotones located in the transition between temperate areas with cold winters and mild rainy summers and mediterranean regions with dry and hot summers (Rivas-Martínez et al. 2017). We aim to provide a global overview of marcescent forests in the Mediterranean basin, a significant ecotone in terms of biogeography and conservation, by exploring the main ecological drivers that have promoted past, current and future changes in the distribution ranges of several oak species. We used a subset of oak species from the subsection Galliferae (Quercus L.), to unveil biogeographic relationships and recent or past contact between taxa, thus bringing insights to its evolutionary history and speciation. A database was built with records obtained from extensive fieldwork, herbaria review and online resources (e.g., Global Biodiversity Information Facility (GBIF), scrutinized by taxonomic experts. We used downscaled climate data to obtain potential distribution of each species through an ensemble-modelling framework (biomod2 - R package, Araújo and New 2007, Thuiller et al. 2009), across different past (Last Glacial Maximum and Middle Holocene), present and future scenarios (2050 and 2080 Hijmans et al. 2005; Representative Concentration Pathway (RCP) 4.5 IPCC 2013). Results provide new insights to advance our current understanding of the biogeographic trajectories of transiently co-occurring oak species, at the boundary of two major biomes and biogeographic regions in Southern Europe and North Africa. Furthermore, we highlight the importance of these forests for biodiversity conservation, not only as refuge of relict and narrow endemic species, but particularly for understanding white oak biogeography and evolution in Europe, anticipating future shifts driven by anthropogenic climate change.

Subsampling Impact on the Climate Change Signal over Poland Based on Simulations from Statistical and Dynamical Downscaling

ABSTRACTMost impact studies using downscaled climate data as input assume that the selection of few global climate models (GCMs) representing the largest spread covers the likely range of future changes. This study shows that including more GCMs can result in a very different behavior. We tested the influence of selecting various subsets of GCMs on the climate change signal over Poland from simulations based on dynamical and empirical–statistical downscaling methods. When the climate variable is well simulated by the GCM, such as temperature, results showed that both downscaling methods agree on a warming over Poland by up to 2° or 5°C assuming intermediate or high emission scenarios, respectively, by 2071–2100. As a less robust simulated signal through GCMs, precipitation is expected to increase by up to 10% by 2071–2100 assuming the intermediate emission scenario. However, these changes are uncertain when the high emission scenario and the end of the twenty-first century are of interest. Further, an additional bootstrap test revealed an underestimation in the warming rate varying from 0.5° to more than 4°C over Poland that was found to be largely influenced by the selection of few driving GCMs instead of considering the full range of possible climate model outlooks. Furthermore, we found that differences between various combinations of small subsets from the GCM ensemble of opportunities can be as large as the climate change signal.

Simulating the effects of climate variability on waterbodies and wetland‐dependent birds in the Prairie Pothole Region

AbstractUnderstanding how bird populations respond to changes in waterbody availability in the climatically variable Prairie Pothole Region (PPR) of North America hinges on being able to couple hydrological and climate modeling to represent potential future landscapes. Model experiments run with the Pothole Complex Hydrologic Model using downscaled climate data (variables relating to precipitation, temperature, and potential evapotranspiration at 1/8° spatial resolution under four general circulation climate models and two gas emissions scenarios) were used to forecast the abundances of six focal wetland‐dependent bird species in the Missouri Coteau portion of the PPR, providing ensemble scenarios at a spatial scale relevant to resource management. Although the projected number of May ponds (waterbodies present during bird breeding season) fluctuated through time with some decadal periodicity (and with the number present in a given year reflecting abundance over the previous three years), the ensemble model average indicated an increase in the average number of waterbodies present by the turn of the next century. Overall, the model experiments conservatively projected an 11.75% increase in the number of waterbodies present by 2090–2099 compared to a baseline period from 1967 to 2005 in the PPR. Wetland‐dependent bird occurrence and abundance were significantly associated with temporal patterns and decadal periodicity in waterbody dynamics. Because of the strong associations between wetland‐dependent bird occurrence and abundance and the number of prairie potholes, projected waterbody increases are forecasted to result in an 11.97% overall increase in occurrence and 8.63% increase in abundance of the six focal species by the end of the 21st century; these results contrast with forecasted drought‐associated declines in waterbodies and birds in the PPR. This integrated hydrological–climatological approach offers a means of assessing how wetland‐dependent bird populations may respond to changes in wetland habitat availability due to a changing climate. Our results provide information that can help managers decide how to mitigate the effects of climate shifts on the distribution of wetland habitat and biota.

Impacts of future climate change on water resource availability of eastern Australia: A case study of the Manning River basin

Hydrological responses of catchments to climate change require detailed examination to ensure sustainable management of both water resources and natural ecosystems. This study evaluated the impacts of climate change on water resource availability of a catchment in eastern Australia (i.e. the Manning River catchment) and analyzed climate-hydrology relationships. For this evaluation, the Xinanjiang (XAJ) model was used and validated to simulate monthly rainfall-runoff relationships of the catchment. Statistically downscaled climate data based on 28 global climate models (GCMs) under RCP8.5 scenarios were used to assess the impacts of climate changes on the Manning River catchment. Our results showed that the XAJ model was able to reproduce observed monthly rainfall-runoff relationships with an R2 ≥ 0.94 and a Nash-Sutcliffe Efficiency ≥0.92. The median estimates from the ensemble of downscaled GCM projections showed a slight decrease in annual rainfall and runoff for the period 2021–2060 and an increase for the period 2061–2100. Annual actual evapotranspiration was projected to increase slightly, while annual soil moisture content was predicted to decrease in the future. Our results also demonstrated that future changes in seasonal and annual runoff, actual evapotranspiration and soil moisture are largely dominated by changes in rainfall, with a smaller influence arising from changes in temperature. An increase in the values of high runoffs and a decrease in the values of low runoffs predicted from the ensemble of the 28 GCMs suggest increased variability of water resources at monthly and seasonal time-scales in the future. A trend of decreasing values in winter runoff and soil moisture content in the future is likely to aggravate possible future reductions in water availability in eastern Australia. These results contribute to the development of adaptive strategies and future policy options for the sustainable management of water resources in eastern Australia.

The Dependence of Hydroclimate Projections in Snow‐Dominated Regions of the Western United States on the Choice of Statistically Downscaled Climate Data

AbstractWe assess monthly temperature and precipitation data derived by six statistically downscaled data sets for 14 general circulation models (GCMs) from the Climate Model Intercomparison Program Phase 5. We use a simple monthly water balance model to quantify and decompose uncertainties associated with the GCMs and statistical techniques in projections for four snow‐dominated regions in the western United States. The end‐of‐century projections from GCMs exhibit substantial variation in change over the regions (temperature range of 2.8–8.0 °C and precipitation range of −22–31%). The six downscaled data sets exhibit disparate high‐resolution representations of the magnitude and spatial patterns of future temperature (up to 2.2 °C) and precipitation (up to 30%) for a common GCM. Two data sets derived by the same downscaling method (Multivariate Adaptive Constructed Analogs) produce median losses of snow water equivalent over the Upper Colorado of 51% and 81%. The principal causes of the differences among the downscaled projections are related to the gridded observations used to bias correct the historical GCM output. Specifically, (1) whether a fixed atmospheric lapse rate (−6.5 °C/km) or a spatially and temporally varying lapse rate is used to extrapolate lower elevation observations to high‐elevations and (2) whether high‐elevation station data (e.g., SNOTEL) are included in the observations. The GCM projections are the largest source of uncertainty in the monthly water balance model simulations; however, the differences among seasonal projections produced by downscaled data sets in some regions highlight the need for careful evaluation of the statistically downscaled data in climate impact studies.

Assessment of present and future climate change over Kashmir Himalayas, India

Climate change over mountainous basins necessitates thorough understanding of present and future temperature and precipitation regimes for better water resource management, cryospheric resources, hydropower generation, natural hazard risk assessment, and ecosystem response. Global and regional climate models (GCMs/RCMs) do not represent valley/ridge scale interactions well. There are inherent model biases due to coarser reorientation of model forcings. The present study is an attempt to use the statistical downscaling model (SDSM) to calibrate and validate Canadian Earth System Model (CanESM2) outputs. The outputs have been compared with corresponding in situ observations available at six meteorological stations within the Kashmir basin in western Himalayas. Daily temperatures and precipitation records during present and future time slices have been considered. The three Representative Concentration Pathways (RCPs) were divided into three future time slices of 2030s, 2060s, and 2090s. Downscaled climate data reveals increase of the mean maximum temperature in the range of 0.3–2.3 °C and the mean minimum temperature increase from 0.3–1.9 °C under different RCPs when compared with the baseline period of 1980–2010. An increasing trend from 2 to 17% at different meteorological stations under different RCPs has been observed in precipitation. Seasonally, autumn shows the highest variability both in temperature and precipitation followed by spring.

Assessments of downscaled climate data with a high‐resolution weather station network reveal consistent but predictable bias

Ecological analyses often incorporate high‐resolution environmental data to capture species‐environment relationships in modelling applications, and downscaled climate data are increasingly being used for such analyses. While such data products provide high precision, the accuracy of these data is seldom directly tested. Consequently, introduced bias from downscaling algorithms may propagate through analyses that incorporate these data products. Here, we utilize data from the Foothills Climate Array (FCA), a mesoscale grid of 232 weather stations in the prairies and eastern slopes of the Rocky Mountains in southern Alberta, Canada, to evaluate several publicly available downscaled climate products. We consider daily, monthly, and annual records for a suite of temperature and humidity variables. The FCA data are ideal to evaluate climate downscaling because they contain multi‐year observations and cover a range of topographic conditions, from flat prairie grass‐ and croplands to mountainous terrain. We find that the downscaling algorithms improve the accuracy of climate variables over simple interpolations of low‐resolution data, but errors are often large at validation locations (e.g., several °C for temperature variables), and downscaled datasets show notable elevational and seasonal bias for all variables. A bias adjustment analysis demonstrates that such bias can be greatly reduced with relatively simple regression‐based models, even when only a small subset of observational data are used, provided they cover a relatively large spread of elevations. We discuss our findings in the context of climate change and ecological modelling and make general recommendations for consumers of downscaled climate data products.

A Multi-Hazard Probabilistic Framework for Quantifying Bridge Failure Risk Considering Climate Change

Climate change has recently been recognized as a significant factor that can drive changes to current design and life-cycle assessment practices of infrastructure systems. The instability in temperature profiles and precipitation patterns in recent decades indicate that the future flood hazard occurrence rate may not necessarily follow historical trends. In addition to the impact of climate change on flood hazard occurrence rate and the associated scour progression, it could also affect the corrosion propagation in structural components. This paper presents a probabilistic framework for quantifying the multi-hazard failure risk of bridges under gradual and sudden deterioration considering climate change. Downscaled climate data adopted from the global climate models are employed to predict the future streamflow and temperature profiles at a given location. These profiles are subsequently used to quantify future failure probability and risk under corrosion and flood hazard. The proposed framework is illustrated on an existing bridge located in Oklahoma.

Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska.

Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska and forecast to 2020, 2050, and 2080. We assess 6 model outputs representing downscaled climate data from 3 global climate model outputs and 2 representative concentration pathways. We use two lines of evidence, model convergence and empirically measured rates of change, to identify the following plausible ecological trajectories for the peninsula: (1.) alpine tundra and sub-alpine shrub decrease, (2.) perennial snow and ice decrease, (3.) forests remain on the Kenai Lowlands, (4.) the contiguous white-Lutz-Sitka spruce complex declines, and (5.) mixed conifer afforestation occurs along the Gulf of Alaska coast. We suggest that converging models in the context of other lines of evidence is a viable approach to increase certainty for adaptation planning. Extremely dynamic areas with multiple outcomes (i.e., disagreement) among models represent ecological risk, but may also represent opportunities for facilitated adaptation and other managerial approaches to help tip the balance one way or another. By reducing uncertainty, this eclectic approach can be used to inform expectations about the future.

Reconstruction and Future Prediction of the Distribution of Wetlands in China

AbstractDue to lack of historical and accurate data, less well known is how the wetlands of China were changed and affected by human disturbance and climate change during past millennia and also, whether climate warming could impact the surviving wetlands in China. Using niche‐based distribution models and downscaled climate data of the past and future, we projected the potential distribution of wetlands in China. Our results show that more than half of the wetlands in China have been destroyed over the past few millennia. Also, future warming will have a negative effect on remaining wetlands. Freshwater swamp and seasonal salt marsh are predicted to dramatically reduce under future scenarios. Wetlands in high mountain regions and inland arid regions are under threat of degeneration and water salinization. This research could provide valuable information for the future conservation and management of wetlands in China.

Modelling seasonal flows alteration in the Vietnamese Mekong Delta under upstream discharge changes, rainfall changes and sea level rise

ABSTRACTThe Vietnamese Mekong Delta (VMD) is one of the world’s most vulnerable deltas to climate change and sea level rise. Adequate understandings of future hydrological changes are crucial for effective water management and risk-proofing, however, this knowledge body is currently very limited. This study quantifies the responses of the VMD’s river flow regime to multiple stimuli, namely future upstream inflow variation, local climate change, and sea level rise. The one-dimensional hydrodynamic model MIKE 11 was used to simulate discharges and water levels across the delta. We developed four scenarios to represent changes in the upstream discharges, precipitation changes and sea level rise, covering the 2036–2065 period. We downscaled climate data and applied three bias-correction methods for five General Circulation Models (GCM), and two Representative Concentration Pathways (RCPs). The climate change projections show similar trends of increasing wet season precipitation and decreasing dry season precipitation. However, cross-scenario variations are sometimes large, depending on the individual GCMs, the RCPs and specific locations. The hydraulic simulation results indicate that, under discharge changes between −20% and +10%, combined with in-delta precipitation variations during the dry season, river discharges at the four representative stations could reduce substantially from −2.5% to −100.2%. During the wet season, the calculated river discharges show increase between 7.3% and 46.7% under four considered scenarios. Substantial changes in the VMD’s river flow regime could have potentially serious implications for water management, especially saltwater intrusion, and therefore calling for timely adaptation measures.

Modelling blue and green water availability under climate change in the Beninese Basin of the Niger River Basin, West Africa

AbstractThe aim of this study was to quantify climate change impact on future blue water (BW) and green water (GW) resources as well as the associated uncertainties for 4 subbasins of the Beninese part of the Niger River Basin. The outputs of 3 regional climate models (HIRHAM5, RCSM, and RCA4) under 2 emission scenarios (RCP4.5 and RCP8.5) were downscaled for the historical period (1976–2005) and for the future (2021–2050) using the Statistical DownScaling Model (SDSM). Comparison of climate variables between these 2 periods suggests that rainfall will increase (1.7% to 23.4%) for HIRHAM5 and RCSM under both RCPs but shows mixed trends (−8.5% to 17.3%) for RCA4. Mean temperature will also increase up to 0.48 °C for HIRHAM5 and RCSM but decrease for RCA4 up to −0.37 °C. Driven by the downscaled climate data, future BW and GW were evaluated with hydrological models validated with streamflow and soil moisture, respectively. The results indicate that GW will increase in all the 4 investigated subbasins, whereas BW will only increase in one subbasin. The overall uncertainty associated with the evaluation of the future BW and GW was quantified through the computation of the interquartile range of the total number of model realizations (combinations of regional climate models and selected hydrological models) for each subbasin. The results show larger uncertainty for the quantification of BW than GW. To cope with the projected decrease in BW that could adversely impact the livelihoods and food security of the local population, recommendations for the development of adequate adaptation strategies are briefly discussed.

Future vulnerability mapping based on response to extreme climate events: Dieback thresholds in an endemic California oak

AbstractAimThis study presents a bioclimate modelling approach, using responses to extreme climate events, rather than historical distributional associations, to project future species vulnerability and refugia. We aim to illustrate the compounding effects of groundwater loss and climate on species vulnerability.LocationCalifornia, USA.MethodsAs a case study, we used the 2012–2015 California drought and resulting extensive dieback of blue oak (Quercus douglasii). We used aerial dieback surveys, downscaled climate data and subsurface water change data to develop boosted regression tree models identifying key thresholds associated with dieback throughout the blue oak distribution. We (1) combined observed dieback–climatic threshold relationships with climate futures to anticipate future areas of vulnerability and (2) used satellite‐derived measurements of subsurface water loss in drought/dieback modelling to capture the mediating effect of groundwater on species response to climatic drought.ResultsA model including climate, climate anomalies and subsurface water change explained 46% of the variability in dieback. Precipitation in 2015 and subsurface water change accounted for 62.6% of the modelled probability of dieback. We found an interaction between precipitation and subsurface water in which dieback probability increased with low precipitation and subsurface water loss. The relationship between precipitation and dieback was nonlinear, with 99% of dieback occurring in areas that received <363 mm precipitation. Based on a MIROC_rcp85 future climate scenario, relative to historical conditions, 13% of the blue oak distribution is predicted to experience more frequent years below this precipitation threshold by mid‐century and 81% by end of century.Main conclusionsAs ongoing climate change and extreme events impact ecological processes, the identification of thresholds associated with observed dieback may be combined with climate futures to help identify vulnerable populations and refugia and prioritize climate change‐related conservation efforts.

Future climate change projects positive impacts on sugarcane productivity in southern China

Abstract Climate change is recognised to alter the distribution of rainfall and increase temperature and atmospheric CO2 concentration [CO2] and pose a formidable challenge to the sustainability of various cropping industries around the world. Additionally, in specific regions, like China, and for particular crops, like sugarcane, the likely effects of climate change are not straightforward. This is because of non-linearity of the interacting climatic factors on crop growth and yield. In our study, the APSIM-Sugarcane model was used to examine the likely response of sugarcane in future climate scenarios. Statistically downscaled climate data based on 28 global climate models (GCMs) under RCP4.5 and RCP8.5 scenarios were used to generate the change in climate in southern China. The results show that the model well reproduced observations for biomass dry matter (DM), biomass fresh matter (FM), sugar yields (S) and leaf area index (LAI), with values for the index of agreement of 0.65, 0.71, 0.84 and 0.70, respectively. The values of RMSE were relatively low with 7.10 t ha−1 for DM, 18.87 t ha−1 for FM, 0.84 t ha−1 for S and 1.03 m2 m−2 for LAI. On average, the ensemble of downscaled GCM projections showed a small increase in radiation and rainfall in the future at the four locations considered, with significantly increased temperature. Sugarcane yields in southern China appeared to be positively affected under future climate and [CO2] changes. Overall, DM was projected to increase by 5.6 and 6.4 and 6.6 t ha−1 for RCP4.5 in 2030s, 2060s and 2090s relative to 1961–2010, respectively. However, RCP8.5 had less promotion compared to RCP4.5 on DM. Similar increased trends for three future time periods could be found in FM and S. Our results showed that the largest percentage change in S occurred at high latitude locations (e.g., Hezhou), with mean values 28.1% and 39.4% for RCP4.5 and RCP8.5 in 2030s, 44.2% and 23.5% in 2060s, and 41.1% and 45.5% for in 2090s, respectively. In addition, our multiple linear regression analyses showed that the changes in radiation, rainfall and temperature together with elevated [CO2] could explain more than 70% of sugarcane yields change across four locations. Across all locations, increases in sugarcane yields were strongly correlated (P = .001) with each degree (Celsius) increase in future temperature and per mm increase in future rainfall. For example, the DM, FM and S increased 7.8–14.2, 16.6–36.1 and 2.7–6.1 kg ha−1 mm−1 responding to rainfall, respectively. Although uncertainties in our study on the impact of climate change on sugarcane might arise from the choice of crop model and GCMs, the results would be pivotal for developing high-yield adaptive strategies as well as informing policy makers to improve sugarcane productivity in China.

Australian climate extremes in the 21st century according to a regional climate model ensemble: Implications for health and agriculture

The negative impacts of climate extremes on socioeconomic sectors in Australia makes understanding their behaviour under future climate change necessary for regional planning. Providing robust and actionable climate information at regional scales relies on the downscaling of global climate model data and its translation into impact-relevant information. The New South Wales/Australian Capital Territory Regional Climate Modelling (NARCliM) project contains downscaled climate data over all of Australia at a 50 km resolution, with ensembles of simulations for the recent past (1990–2009), near future (2020–2039) and far future (2060–2079). Here we calculate and examine sector-relevant indices of climate extremes recommended by the Expert Team on Sector-specific Climate Indices (ET-SCI). We demonstrate the utility of NARCliM and the ET-SCI indices in understanding how future changes in climate extremes could impact aspects of the health and agricultural sectors in Australia. Consistent with previous climate projections, our results indicate that increases in heat and drought related extremes throughout the 21st century will occur. In the far future, maximum day time temperatures are projected to increase by up to 3.5 °C depending on season and location. The number of heatwaves and the duration of the most intense heatwaves will increase significantly in the near and far future, with greater increases in the north than south. All capital cities are projected to experience at least a tripling of heatwave days each year by the far future, compared to the recent past. Applying published heat-health relationships to projected changes in temperature shows that increases in mortality due to high temperatures for all cities examined would occur if projected future climates occurred today. Drought and the number of days above 30 °C are also projected to increase over the major wheat-growing regions of the country, particularly during spring when sensitivity of wheat to heat stress is greatest. Assuming no adaptation or acclimatisation, published statistical relationships between drought and national wheat yield suggest that national yields will have a less than one quarter chance of exceeding the annual historical average under far future precipitation change (excluding impacts of future temperature change and CO2 fertilization). The NARCliM data examined here, along with the ET-SCI indices calculated, provide a powerful and publicly available dataset for regional planning against future changes in climate extremes.

Optimal Operation of Hydropower Reservoirs under Climate Change: The Case of Tekeze Reservoir, Eastern Nile

Optimal operation of reservoirs is very essential for water resource planning and management, but it is very challenging and complicated when dealing with climate change impacts. The objective of this paper was to assess existing and future hydropower operation at the Tekeze reservoir in the face of climate change. In this study, a calibrated and validated Soil and Water Assessment Tool (SWAT) was used to model runoff inflow into the Tekeze hydropower reservoir under present and future climate scenarios. Inflow to the reservoir was simulated using hydro-climatic data from an ensemble of downscaled climate data based on the Coordinated Regional climate Downscaling Experiment over African domain (CORDEX-Africa) with Coupled Intercomparison Project Phase 5 (CMIP5) simulations under Representative Concentration Pathway (RCP)4.5 and RCP8.5 climate scenarios. Observed and projected inflows to Tekeze hydropower reservoir were used as input to the US Army Corps of Engineer’s Reservoir Evaluation System Perspective Reservoir Model (HEC-ResPRM), a reservoir operation model, to optimize hydropower reservoir release, storage and pool level. Results indicated that climate change has a clear impact on reservoir inflow and showed increase in annual and monthly inflow into the reservoir except in dry months from May to June under RCP4.5 and RCP8.5 climate scenarios. HEC-ResPRM optimal operation results showed an increase in Tekeze reservoir power storage potential up to 25% and 30% under RCP4.5 and RCP8.5 climate scenarios, respectively. This implies that Tekeze hydropower production will be affected by climate change. This analysis can be used by water resources planners and mangers to develop reservoir operation techniques considering climate change impact to increase power production.

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies.

Multiple Climate Change Scenarios and Runoff Response in Biliu River

The impacts of temperature and precipitation changes on regional evaporation and runoff characteristics have been investigated for the Biliu River basin, which is located in Liaoning Province, northeast China. Multiple climate change scenarios from phase 3 and phase 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) (21 scenarios in total) were utilized. A calibrated hydrologic model—SWAT model—was used to simulate future discharges based on downscaled climate data through a validated morphing method. Results show that both annual temperature and precipitation increase under most of the CMIP3 and CMIP5 scenarios, and increase more in the far future (2041–2065) than in the near future (2016–2040). These changes in precipitation and temperature lead to an increase in evaporation under 19 scenarios and a decrease in runoff under two-thirds of the selected scenarios. Compared to CMIP3, CMIP5 scenarios show higher temperature and wider ranges of changes in precipitation and runoff. The results provide important information on the impacts of global climate change on water resources availability in the Biliu River basin, which is beneficial for the planning and management of water resources in this region.