Coordinated Regional Climate Downscaling Experiment Research Articles

Concurrent daytime and nighttime heatwaves in the late 21st century over the CORDEX‐East Asia phase 2 domain using multi‐GCM and multi‐RCM chains

AbstractThe adverse impacts of extreme heat on human health when a concurrent daytime and nighttime heatwave (CDNHW) occurs are greater than when daytime or nighttime heatwaves occur individually, because of the reduced recovery time from heat exposure. This study projects increases in CDNHW over the whole of East Asia under two Representative Concentration Pathway scenarios (RCP2.6 and RCP8.5) and two Shared Socioeconomic Pathway scenarios (SSP1‐2.6 and SSP5‐8.5). The daily maximum and minimum temperatures, which are used to define a CDNHW, are calculated of 3‐hourly temperatures of 25 km horizontal resolution produced by 12 general circulation model and regional climate model chains participating in the Coordinated Regional Climate Downscaling Experiment East Asia phase 2 project. In Historical simulation (1981–2005), occurrence period and occurrence rate of CDNHW from April to September area‐averaged in East Asia are 10.9 days and 0.9%, respectively. In projections for the future (2071–2100), occurrence period and occurrence rate of CDNHW will be 3 weeks and 3.7% (RCP2.6), 2 months and 20.5% (RCP8.5), 2 months and 15.6% (SSP1‐2.6), and 3 months and 45.7% (SSP5‐8.5). In addition, it is expected that the CDNHW intensity will increase, and the spatial extent of CDNHW will be extended. Although a CDNHW lasting less than 3 days is the most common, the proportion of CDNHWs lasting more than 10 days, compared to the total CDNHW frequency, will increase to 1.2% (RCP2.6), 7.2% (RCP8.5), 6.1% (SSP1‐2.6), and 17.3% (SSP5‐8.5) from 0.2% (Historical). Both occurrence rate and intensity of CDNHW will increase to a relatively large extent in Indochina, East and West China, and India. If the current greenhouse gas emissions continue, East Asia will experience unprecedented heat stress because the frequency and intensity of CDNHWs, which rarely occur during present‐day, will increase significantly over all regions by the end of the 21st century.

Evaluation of bias correction methods for a multivariate drought index: case study of the Upper Jhelum Basin

Abstract. Bias correction (BC) is often a necessity to improve the applicability of global and regional climate model (GCM and RCM, respectively) outputs to impact assessment studies, which usually depend on multiple potentially dependent variables. To date, various BC methods have been developed which adjust climate variables separately (univariate BC) or jointly (multivariate BC) prior to their application in impact studies (i.e., the component-wise approach). Another possible approach is to first calculate the multivariate hazard index from the original, biased simulations and bias-correct the impact model output or index itself using univariate methods (direct approach). This has the advantage of circumventing the difficulties associated with correcting the inter-variable dependence of climate variables which is not considered by univariate BC methods. Using a multivariate drought index (i.e., standardized precipitation evapotranspiration index – SPEI) as an example, the present study compares different state-of-the-art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) applied to climate model simulations stemming from different experiments at different spatial resolutions (namely Coordinated Regional Climate Downscaling Experiment (CORDEX), CORDEX Coordinated Output for Regional Evaluations (CORDEX-CORE), and 6th Coupled Intercomparison Project (CMIP6)). The BC methods are calibrated and evaluated over the same historical period (1986–2005). The proposed framework is demonstrated as a case study over a transboundary watershed, i.e., the Upper Jhelum Basin (UJB) in the Western Himalayas. Results show that (1) there is some added value of multivariate BC methods over the univariate methods in adjusting the inter-variable relationship; however, comparable performance is found for SPEI indices. (2) The best-performing BC methods exhibit a comparable performance under both approaches with a slightly better performance for the direct approach. (3) The added value of the high-resolution experiments (CORDEX-CORE) compared to their coarser-resolution counterparts (CORDEX) is not apparent in this study.

The impact of lateral boundary forcing in the CORDEX-Africa ensemble over southern Africa

Abstract. The region of southern Africa (SAF) is among the most exposed climate change hotspots and is projected to experience severe impacts across multiple economical and societal sectors. For this reason, producing reliable projections of the expected impacts of climate change is key for local communities. In this work we use an ensemble of 19 regional climate model (RCM) simulations performed in the context of the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa and a set of 10 global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) that were used as the driving GCMs in the RCM simulations. We are concerned about the degree to which RCM simulations are influenced by their driving GCMs, with regards to monthly precipitation climatologies, precipitation biases and precipitation change signal, according to the Representative Concentration Pathway (RCP) 8.5 for the end of the 21st century. We investigate the degree to which RCMs and GCMs are able to reproduce specific climatic features over SAF and over three sub-regions, namely the greater Angola region, the greater Mozambique region, and the greater South Africa region. We identify that during the beginning of the rainy season, when regional processes are largely dependent on the coupling between the surface and the atmosphere, the impact of the driving GCMs on the RCMs is smaller compared to the core of the rainy season, when precipitation is mainly controlled by the large-scale circulation. In addition, we show that RCMs are able to counteract the bias received by their driving GCMs; hence, we claim that the cascade of uncertainty over SAF is not additive, but indeed the RCMs do provide improved precipitation climatologies. The fact that certain bias patterns during the historical period (1985–2005) identified in GCMs are resolved in RCMs provides evidence that RCMs are reliable tools for climate change impact studies over SAF.

Future Projections of EURO‐CORDEX Raw and Bias‐Corrected Daily Maximum Wind Speeds Over Scandinavia

AbstractTwenty historical and future Coordinated Regional Climate Downscaling Experiment ensemble for Europe simulations are bias corrected to investigate the future changes in the daily maximum wind speed over Scandinavia. We use quantile mapping to adjust the wind for the historical period (1985–2014) and quantile delta mapping for two future periods (2041–2070, 2071–2100, RCP8.5) with the 3‐km spatial resolution NORA3 hindcast as the reference data set. Decomposing the variance, we find that most of the inter‐model spread in the bias and the response to climate change is due to the regional climate model over land and mainly to the general climate model over sea. On average, the mean daily maximum wind speed is projected to increase everywhere except along the western coast of Norway and Denmark. In summer, we see an opposite sign over Sweden and Finland. The Norwegian Sea experiences weaker mean and high wind whereas the Baltic Sea experiences a strengthening. Bias correction influences the amplitude of the response, not the response pattern. Wind speed distributions can have different shapes in the future, with, for example, a flattening of the distribution off the coast of Norway with more frequent weak and very strong winds. Apart from a few locations in Norway, we find an increase in the number of days in the local highest historical wind category. Overall, summer exhibits opposite signals compared to the three other seasons. At country scale, the sign of the change in the mean and 98th percentile varies greatly depending on the region and among the simulations, especially for Norway.

Promoting involvement of early-career scientists from the Asia-Pacific region in regional integrated and sustainable development through active participation and networking

Climate change is affecting global ecosystems, natural resources, and human well-being. The near- and long-term future sustainable development of society requires robust climate change information at regional scales. To contribute to the purpose mentioned above, WCRP CORDEX (the World Climate Research Programme’s Coordinated Regional Climate Downscaling Experiment) initialised a collaboration with the APN (Asia-Pacific Network for Global Change Research), as the two programmes share common goals in advocating climate science as well as transferring climate knowledge for effective management. This APN project, entitled “Promoting Involvement of Early Career Scientists from the Asia-Pacific Region in Regional Integrated and Sustainable Development through Active Participation and Networking”, was a result of this collaboration. Specifically, the project was aimed at supporting early-career scientists from the Asia-Pacific region to attend an international science conference on regional climate science (ICRC-CORDEX 2019) and facilitate them in international partnership-building. It also contributed to enhancing communication and cooperation amongst regional climate research teams within and beyond the Asia-Pacific region. As one of the most important activities of the conference, the project supported an event for early-career scientists. The completion of the project consolidated global collaboration between the climate research community and that of adaptation-impact studies, as well as facilitated interaction with end-users. It was also a successful showcase of the scientific strategies of APN and CORDEX.

Extreme Dry and Wet Events in the Pacific Region of Colombia estimated in the 21st Century Based on the Standardized Precipitation Index and CORDEX Climate Projections

The Pacific region of Colombia is known to be one of the most vulnerable to changes in precipitation patterns. A study was conducted using standardized precipitation index (SPI) analyses to understand the potential changes in precipitation in this region during the 21st century. The analyses were conducted using historical precipitation data from 1950 to 2005 and projected precipitation data from 2022 to 2100 under the Coordinated Regional Climate Downscaling Experiment (CORDEX) climate scenarios (RCP 4.5 and RCP 8.5). The results of the study showed that compared to historical data, SPI3 precipitation in this region is predicted to increase by 2040 under both climatic scenarios. However, in the 2041–2070 period, the region is expected to be wetter under RCP 8.5, although the difference between the two scenarios was not statistically significant. Similarly, SPI 6 precipitation is predicted to increase in the 2022–2040 and 2071–2100 periods under both scenarios. SPI 12 precipitation is also predicted to increase in the 2022–2040 period under RCP 4.5. In the 2041–2070 period, dryness is predicted to be more frequent under RCP 4.5, and wetness is predicted under RCP 8.5. The findings of this study can help in determining the most pertinent reference periods and computation time increments for evaluating the effects of future climate change on agricultural production and food security in the Pacific region of Colombia. It suggests that changes in precipitation patterns are likely to occur in the coming decades, which may significantly impact crop growth, water availability, and other aspects of agricultural production.

Projected changes in precipitation characteristics over the Drakensberg Mountain Range

AbstractThis study examines the potential impacts of climate change on the characteristics of precipitation over the Drakensberg Mountain Range (DMR) at different global warming levels (GWLs: 1.5, 2.0, 2.5 and 3.0°C) under the Representative Concentration Pathway 8.5 (RCP8.5) scenario, using dynamical and statistical downscaled datasets. The dynamical datasets consist of 19 multi‐model simulations datasets from the Coordinated Regional Climate Downscaling Experiment (CORDEX), whereas the statistical downscaled datasets comprise 19 multi‐model simulations from the National Aeronautics and Space Administration (NASA) Earth Exchange (NEX) Global Daily Downscaled Projections (NEX‐GDDP, hereafter NEX). The capacity of the CORDEX and NEX datasets to represent past characteristics of extreme precipitation over the DMR was evaluated against eight observation datasets. The precipitation characteristics were represented by eight precipitation indices. Both CORDEX and NEX realistically capture the characteristics of extreme precipitation over the Drakensberg and, in most cases, their biases lie within the observation uncertainty. However, NEX performs better than CORDEX in reproducing most of the precipitation characteristics, except in simulating the threshold of extreme rainfall. The ensemble means of CORDEX and NEX agree on a future increase in the intensity of normal precipitation, in the frequency and intensity of extreme precipitation, as well as an increase in widespread extreme events, with a decrease in the number of precipitation days and continuous wet days. However, they disagree on the projected changes of annual precipitation, for which CORDEX projects an increase over most parts of the DMR, whereas NEX indicates a decrease. The self‐organizing‐map analysis, which reveals diversity in the projection patterns hidden in the ensemble means, shows the most probable combinations of projected changes in the annual precipitation and extreme precipitation events (in terms of intensity and frequency): (a) increase in both annual precipitation and extreme precipitation events; (b) decrease in both annual precipitation and extreme precipitation events; (c) decrease in annual precipitation but increase in extreme precipitation events. The results of this study can thus provide a basis for developing climate change adaptation and mitigating strategies over the DMR.

Spatio-temporal variation of precipitation projection based on bias-adjusted CORDEX-SA regional climate model simulations for arid and semi-arid region

Global warming significantly affects the hydrological cycle that influences hydrological systems worldwide. Knowledge of precipitation variation under a changing climate can provide effective ways to deal with its impacts on water resource management. Hence, in this study, spatiotemporal variability of precipitation under future climatic scenarios was studied using suitable regional climate models (RCMs) extracted from the South Asia Coordinated Regional Climate Downscaling Experiments (CORDEX-SA) based on the control period (1976-2005). Additionally, this research attempted to evaluate the changes in precipitation patterns in Iran by integrating output from a set of RCMs extracted from CORDEX-SA with selected bias-correction (BC) methods, namely quantile ranking-based bias correction (QRBC), linear scaling (LS), empirical quantile mapping (EQM), Gamma quantile mapping (GQM), and Gamma-Pareto quantile mapping (GPQM). Regarding the findings, the performance of RCMs varied based on the climates of regions. Moreover, QRBC played an essential role in improving the output of RCMs to simulate precipitation values. Under RCP4.5 and RCP8.5, the projection of seasonal precipitation indicated that a slight wetting pattern might occur across the northern area in all seasons, especially in the southern regions. Whereas the southern area exhibited a strong wetting tendency in autumn, and the maximum percentage changes (PC) of precipitation were projected to increase by 35% for the mid (2040-2070) and far future (2070-2100) periods, based on RCP4.5 and RCP8.5, respectively. This study will be helpful in understanding the uncertainties in CORDEX-SA RCM projections of climate changes in Iran. Using the outcomes of this study, strategies can be adopted to better manage water resources for various regions of Iran.

Projected Impact of Increased Global Warming on Heat Stress and Exposed Population Over Africa

AbstractThis study investigates the impact of increased global warming on heat stress changes and the potential number of people exposed to heat risks over Africa. For this purpose a heat index has been computed based on an ensemble‐mean of high‐resolution regional climate model simulations from the Coordinated Output for Regional Evaluations embedded in the COordinated Regional Climate Downscaling EXperiment, under two Representative Concentration Pathways (RCPs) scenarios (RCP2.6 and RCP8.5), combined with projections of population growth developed based on the Shared Socioeconomic Pathways (SSPs) scenarios (SSP1 and SSP5). Results show that by the late 21st century, the increased global warming is expected to induce a 12‐fold increase in the area extent affected by heat stress of high‐risk level. This would result in an increase of about 10%–30% in the number of days with high‐risk heat conditions, as well as about 6%–20% in their magnitude throughout the seasonal cycle over West, Central, and North‐East Africa. Therefore, and because of the lack of adaptation and mitigation policies, the exacerbation of ambient heat conditions could contribute to the exposure of about 2–8.5 million person‐events to heat stress of high‐risk level over Burkina Faso, Ghana, Niger, and Nigeria. Furthermore, it was found that the interaction effect between the climate change and population growth seems to be the most dominant in explaining the total changes in exposure due to moderate and high heat‐related risks over all subregions of the African continent.

Climate Change Impacts on Extreme Rainfall in Eastern Africa in a Convection-Permitting Climate Model

Abstract Climate change is expected to increase the frequency and intensity of rainfall extremes. Understanding future changes in rainfall is necessary for adaptation planning. Eastern Africa is vulnerable to rainfall extremes because of low adaptive capacity and high future population growth. Convection-permitting climate models have been found to better represent moderate (yearly) rainfall extremes than parameterized convection models, but there is limited analysis of rare extremes that occur less frequently than once per year. These events often have the largest socioeconomic impacts. We use extreme value theory and regional frequency analysis to quantify rare rainfall extremes over East Africa in a convection-permitting climate model (CP4A). We compare the results with its parameterized counterpart (P25), the Coordinated Regional Climate Downscaling Experiment for the African region (CORDEX-Africa) ensemble, and observations to understand how the convection parameterization impacts the results. We find that CP4A better matches observations than the parameterized models. With climate change, we find the parameterized convection models have unrealistically high changes in the shape parameter of the extreme value distribution, which controls the tail behavior (i.e., the most extreme events), leading to large increases in return levels of events with a return period of >20 years. This suggests that parameterized convection models may not be suitable for looking at relative changes in rare rainfall events with climate change and that convection-permitting models should be preferred for this type of work. With the more realistic CP4A, RCP8.5 end-of-century climate change leads to 1-in-100-yr events becoming 1-in-23-yr events, which will necessitate serious adaptation efforts to avoid devastating socioeconomic impacts. Significance Statement We use a new, high-resolution climate model to examine how rare extreme rainfall events in East Africa might change in the future with climate change and compare the results with those from standard-resolution climate models. We find that the standard-resolution models have unrealistically large increases in rainfall for events that occur less frequently than every 20 years. The high-resolution model is more realistic and is required to illustrate possible future changes in rare rainfall extremes. Extreme events will become more common with climate change, and in the more realistic model we show that a 1-in-100-yr event may become a 1-in-23-yr event by the end of the century if greenhouse gas emissions are not significantly reduced.

Climate change impact on hydro-climatic variables of Ribb watershed, Tana sub-basin, Ethiopia

In Ethiopia, the Ribb River is one of the tributaries of the Lake Tana sub-basin. Temperature, precipitation, and streamflow would all be affected by climate change in the Ribb watershed. As a result of the disruption of regular hydrological processes, these climate changes have an impact on water resources. The goal of this study was to look into the effects of climate change on the Ribb watershed’s hydro-climatic characteristics. The forecasted climatic data for rainfall and temperature (minimum and maximum) came from the CORDEX (Coordinated Regional Climate Downscaling Experiments) Africa database. Climate change consequences were investigated using RCP 4.5 emission scenarios for the 2021–2060 time range, compared to the 1985–2005 baselines. The observed precipitation and temperature data were used to adjust for bias. The simulation of stream flow was carried out using the semi-distributed and physically based soil and water assessment tool (SWAT). From 1997 to 2003, the model was calibrated, and from 2004 to 2007, it was validated. To determine the trend of the climate variables, trend test analyses were performed on the various time series data. In all of the experiments conducted, the trend test revealed that historical and forecast precipitation recording stations showed statistically negligible trends for all critical values. At a level of 0.05, the historical and prospective maximum and minimum temperature data revealed increasing patterns. In general, the results demonstrated that meteorological conditions cause the flow to decrease over the season. As a result, climate change will have an impact on the Ribb watersheds water resources.

Historical and projected spatial and temporal rainfall status of Dar es Salaam, Tanzania, from 1982 to 2050

Dar es Salaam, like other cities in Africa, experiences flash floods during the rainfall season that destroy infrastructure due to the overflow of rivers and blocked sewage. This study investigates the historical and future variability and changes in spatial and temporal rainfall over Dar es Salaam. Station data and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) gridded data crossing 38 years (1982–2019) were used as a baseline and the Coordinated Regional Climate Downscaling Experiment (CORDEX) dataset from 2021 to 2050 was used for projection under Representative Concentration Pathway (RCP 4.5) forcing scenarios. A trend analysis of historical data was conducted at monthly, seasonal, and annual timescales. Mann–Kendall statistical tests and Sen’s slope estimator were applied to identify the current trend direction and magnitude of changes in rainfall patterns over time. A standardized anomaly index (SAI) was also employed to detect the region’s trends in wetness and dryness. The spatial distribution of rainfall in the city was investigated using an inverse distance weighted (IDW) interpolation technique. The statistical results reveal that a non-significant trend in rainfall was observed on monthly, seasonal, and annual timescales. Generally, in the future (2021–2050), the annual cycle of rainfall shows a slight decrease in monthly rainfall, especially from January to August, and an increase from September to December compared to historical (1982–2019) rainfall, for most of studied locations. Spatially, the distribution of projected rainfall shows that the southern part of the city will experience higher rainfall than other parts. The most significant findings were a decrease in annual projected rainfall by 20%, the MAM projected rainfall season increased by 42%, and an increase of 38% of the OND-projected rainfall season. The findings of this study will be useful for the improved management and planning of the city.

The Worldwide C3S CORDEX Grand Ensemble: A Major Contribution to Assess Regional Climate Change in the IPCC AR6 Atlas

Abstract The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of regional climate model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to ­assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and ­activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS).

Future changes in monsoon extreme climate indices over the Sikkim Himalayas and West Bengal

Utilizing an ensemble of regional climate models (RCMs) from Coordinated Regional Climate Downscaling Experiment (CORDEX) South Asia, projected changes in mean and extreme climate indices are analysed for future period (SCEN; 2021–2060). The parametric transformation bias correction technique is applied to enhance the model agreement in calibration period (1961–2005) and to produce reliable results for evaluation period. The observed pattern of temperature and precipitation indices is illustrated for control period (CTRL; 1961–2005), which exhibits high spatial variability with the altitudinal differences, especially over the Himalayas. Strong meridional moisture flow from the Bay of Bengal contributes higher, heavier and more intense precipitation events over the Sikkim Himalayas and northern Sub-Himalayan West Bengal (SWB). Despite spatial difference in the occurrences of return value for 5-, 10- and 50-year levels, some indices show close similarity between the Sikkim Himalayas and Gangetic West Bengal (GWB). The projected uncertainties under the RCPs remain very high for extreme temperatures over the Himalayas. Change in minimum temperature is largely significant. Conversely, maximum temperature shows insignificant change. Diurnal temperature range shows an expected decline for projected scenarios. Lower atmospheric easterlies towards east-central India enhance future moisture transport, which don’t eventually bring positive change for precipitation amount. Instead, the Sikkim Himalayas and the Eastern Ghats exhibit expected rise in higher, heavier and intense precipitation events. Consecutive dry days exhibit significant future rise over the plain and lower plateaus, which show significant decline over the mountains. The topographic forcings to the convective mechanism as well as model sensitivity evidently control the spatial pattern and occurrences of extreme events. Future rise in moisture level is more conspicuous under RCP8.5 along with the significant changes in extreme climate indices.

Performance Evaluation of Bias Correction Methods and Projection of Future Precipitation Changes Using Regional Climate Model over Thanjavur, Tamil Nadu, India

The use of regional climate models in climate change risk assessments is uncertain because of the threat of biases. Prior to using simulations, some corrections must be made. The aim of this study is to evaluate the effectiveness of simple and complex correction approaches on CORDEX (Coordinated Regional Climate Downscaling Experiment) precipitation datasets over Thanjavur in Tamil Nadu, India. The various bias correction approaches were assessed using the two-sample cross-validation technique, and the best method was chosen using statistical metrics such as the correlation coefficient, root mean square error, and percent bias for correcting the future scenario datasets. According to the findings, all methods significantly improved raw simulated estimations after correction. The Delta Change method was used to adjust the RCP2.6 and RCP8.5 scenarios datasets for this study region because it produced good agreement (0.98) and low wet bias (1%) against observed precipitation. In addition, this study found that the annual mean precipitation projections showed an increase in precipitation intensity of between 4.2 and 6.8% under the RCP2.6 scenario and between 14 and 20.1% under the RCP8.5 scenario, compared to observed data (1976–2005). Furthermore, the analysis showed that most years in the twenty-first century will experience heavy precipitation, resulting in floods. This research has offered reliable knowledge about future precipitation to environmentalists, urban administrators, and policy-makers, enable them to make plausible strategies to mitigate the detrimental effects of climate change.

Changes in photovoltaic potential over China in a warmer future

Solar photovoltaic (PV) technology offers a promising path for addressing energy demand and mitigating climate change. However, climatic conditions relevant to the productivity of solar power may be changed in a warmer future. Here, we quantify the impact of climate change on PV potential over China based on high-resolution climate projections within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). Our results indicate that the annual mean PV power potential (PV POT) over China would decrease by several percent relative to the reference period (1986–2005) under a warmer climate, with the most pronounced decrease over the Tibetan Plateau, which is currently the most solar-rich region in China. However, beyond changes in the mean climate state, we demonstrate a substantial increase in events of extreme low PV power outputs (i.e. those falling below the 10th percentile of the probability distribution of the daily PV POT anomalies). For instance, the frequency of extreme low PV events is projected to reach nearly three times the reference period level over the Tibetan Plateau under the scenario of 3 °C global warming (similar to late-century warming projected based on current mitigation policies). Future changes in PV POT are dominated by changes in surface solar irradiance, while the warming condition further exacerbates the decrease in PV POT. Our results highlight that both the mean and extreme conditions of solar inputs should be considered simultaneously when assessing the impacts of climate change on PV power outputs.

Projected Changes in Future Extreme Precipitation over the Northeast United States in the NA-CORDEX Ensemble

Abstract The northeastern United States (NEUS) is a densely populated region with a number of major cities along the climatological storm track. Despite its economic and social importance, as well as the area’s vulnerability to flooding, there is significant uncertainty around future trends in extreme precipitation over the region. Here, we undertake a regional study of the projected changes in extreme precipitation over the NEUS through the end of the twenty-first century using an ensemble of high-resolution, dynamically downscaled simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) project. We find that extreme precipitation increases throughout the region, with the largest changes in coastal regions and smaller changes inland. These increases are seen throughout the year, although the smallest changes in extreme precipitation are seen in the summer, in contrast to earlier studies. The frequency of heavy precipitation also increases such that there are relatively fewer days with moderate precipitation and relatively more days with either no or strong precipitation. Averaged over the region, extreme precipitation increases by +3%–5% °C−1 of local warming, with the largest fractional increases in southern and inland regions and occurring during the winter and spring seasons. This is lower than the +7% °C−1 rate expected from thermodynamic considerations alone and suggests that dynamical changes damp the increases in extreme precipitation. These changes are qualitatively robust across ensemble members, although there is notable intermodel spread associated with models’ climate sensitivity and with changes in mean precipitation. Together, the NA-CORDEX simulations suggest that this densely populated region may require significant adaptation strategies to cope with the increase in extreme precipitation expected at the end of the next century. Significance Statement Observations show that the northeastern United States has already experienced increases in extreme precipitation, and prior modeling studies suggest that this trend is expected to continue through the end of the century. Using high-resolution climate model simulations, we find that coastal regions will experience large increases in extreme precipitation (+6.0–7.5 mm day−1), although there is significant intermodel spread in the trends’ spatial distribution and in their seasonality. Regionally averaged, extreme precipitation will increase at a rate of ∼2% decade−1. Our results also suggest that the frequency of extreme precipitation will increase, with the strongest storms doubling in frequency per degree of warming. These results, taken with earlier studies, provide guidance to aid in resiliency preparation and planning by regional stakeholders.

Climate change impacts the future offshore wind energy resources in India: Evidence drawn from CORDEX-SA Regional Climate Models

Harnessing offshore wind energy is a potential solution to meet rising energy demand. Concurrently, exploitable wind energy is susceptible to climate change. In this study, an ensemble of six RCMs derived from Coordinated Regional Climate Downscaling Experiment — South Asia (CORDEX-SA) regional climate models is created to study future variation of wind speed and wind power density. The variation with respective to the historic time periods is examined for near-future (2020–2046), mid-future (2047–73), and far-future time periods (2074–2099). Two Representative Concentration Pathways (RCP) scenarios, such as RCP4.5 and RCP8.5, are considered for the analysis. The credibility of RCM data is assessed by comparing it with European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) reanalysis dataset which is validated against buoy datasets. Findings reveal that annual mean wind speed in the considered period ranges between 2% and −8% in the case of RCP4.5 while it is 7% and −16% in the RCP8.5 scenario. Seasonal percentage variation in WPD is between 80% and −56% in the RCP4.5 scenario, and it is relatively higher (105% and −75%) in the RCP8.5 scenario. By 2099, it is expected that WPD may increase by 10% and 30% in the southern coast, whereas 20% and 40% decrement is expected near the coast of Gujarat for RCP4.5 and RCP8.5 scenarios, respectively. The findings of this study enable stakeholders to harness wind energy in the Indian offshore region.

Projected changes in mild weather frequency over China under a warmer climate

Previous studies have largely focussed on changes in mean climate state and climate extremes under a warmer climate, and little is known about changes in mild weather, which is a positive and pleasant condition and is highly related to human outdoor activities. Although changes in observed mild weather frequency over China, and their drivers, have been revealed, the understanding of how mild weather evolves with projected warming is still limited. Here, we examine future changes in mild weather frequency over China based on comprehensive thermal comfort indices, and dynamically downscaled climate projections produced by the Regional Climate Model version 4 within the framework of the Coordinated Regional Climate Downscaling Experiment—Coordinated Output for Regional Evaluations. We demonstrate that changes in mild weather frequency in a warmer future exhibit remarkable regional discrepancy. In particular, densely populated southeastern China will experience a robust decrease in mild weather relative to the current level, although a general increasing trend is observed in this area over recent decades. On a seasonal scale, the decrease in mild weather in summer overwhelms the increase in spring and autumn, and this is more prominent in warmer regions. Regarding the drivers, it is suggested that changes in mild weather frequency are dominated by elevated temperatures, with little contribution from relative humidity, wind speed, and sunshine duration.

CORDEX-EA Phase 2 다중 지역기후모델 앙상블을 이용한 전지구 온난화 제한 목표(1.5, 2.0℃)하에서의 한반도 미래 기온 전망

This study presents a future projection of temperature over the Korean Peninsula (KP) under the global warming targets of 1.5℃ and 2.0℃ set in the 2015 Paris Agreement. For projection, simulation data from the multi-Regional Climate Model (RCM) ensemble in Coordinated Regional Climate Downscaling Experiment (CORDEX)-East Asia (EA) Phase 2 are used. Under the 2.0℃ (1.5℃) global warming condition, mean temperature over KP would increase 2.13℃ (1.51℃) compared to the present period (1985 ~ 2005 years). Extreme minimum and maximum temperature intensity indices (TNn and TXx) would also increase 2.61℃ (1.91℃) and 2.38℃ (1.58℃). In addition, changes in probabilities of extreme temperature events that occurs once in 20 years during the present period are investigated. Extreme cold events would occur once in 28.9 years (22.6 years) and warm events once in 5.9 years (7.2 years). Meanwhile, there are several noteworthy points about the future projection. The temperature over KP would increase more over the northern KP than the southern KP and this feature is more distinct in TNn. The uncertainties of the projection are higher for the 1.5℃ warming condition than the 2.0℃ warming condition and for extreme temperature versus mean temperature. The spatial pattern of change in extreme temperature frequency is different from that of intensity. In other words, a smaller increase in the frequency of extreme cold events is expected over the inland KP.