Regional Climate Model Version Research Articles

Object-oriented analysis as a foundation for building climate storylines of compounding short-term drought and crop heat stress

IntroductionCrops are vulnerable to precipitation and heat extremes during late spring through summer.MethodsWe analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041-2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap.ResultsIdentified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type.DiscussionThe information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels.

Characterization of temperature and humidity effects on extreme heat stress under global warming and urban growth in the Pearl and Yangtze River deltas of China

With global warming accelerating, the heavily populated and rapidly urbanized coastal regions of the Pearl River Delta (PRD) and the Yangtze River Delta (YRD) stand as representative areas with mounting concerns about extreme heat stress. This study analyzes differentiated effects of temperature (TAS) and relative humidity (RH) on human heat stress measured by wet-bulb globe temperature (WBGT) in those urban regions based on machine learning and mathematical derivation, while also examining the impacts of global warming and urbanization on prospective heat risks. To generate fine-scale climate projections targeted at the PRD and YRD, two global projections forced by Representative Concentration Pathway (RCP) 8.5 scenario are dynamically downscaled using non-hydrostatic Regional Climate Model version 4.7 (RegCM4), with the urban density and extent updated every year based on SSP5 scenario, thereby incorporating the transient urban growth into future projections. The bias-corrected downscaled simulations effectively capture the distinct interdependencies between TAS and RH on WBGT across different regions, similar to the observed patterns during the historical period. While the absolute contribution of TAS to WBGT is larger than RH regardless of warming levels and regions, the relative increase in RH becomes more pronounced with warming. Under RCP8.5 scenario, the unprecedentedly extreme WBGT is projected to emerge in far future (2080–2099). In contrast, the effect of urbanization appears to be more dominant in near future (2030–2049) as urban density under Shared Socioeconomic Pathways 5 (SSP5) scenario is projected to peak around the 2040s and then gradually decrease. The reduction of RH is found in the intensely urbanized areas locally, but it does not significantly lower WBGT because the positive contribution of increased TAS is more dominant. As a result, highly urbanized regions still exhibit higher WBGT compared to other areas. In addition, urban heat island effect is more pronounced for compact areas with high urban density (i.e., PRD) and at night. Despite the smaller temperature increase from urban heat island effect compared to global warming, it can play a critical role in exacerbating heat stress, adding to the already dangerous humid and hot conditions.

Comparison of RegCM4.7.1 Simulation with the Station Observation Data of Georgia, 1985–2008

The global climate change, driven by natural processes and increasing human activities, is especially significant for Georgia. The region is experiencing increases in temperature, desertification, redistribution of precipitation, and a rise in the frequency and severity of extreme weather events. Georgia’s complex topography and its proximity to the Black and Caspian seas make it essential to employ high-resolution regional climate models to evaluate future climate change risks. In this study, we examine the results of a high-resolution simulation of mean and extreme precipitation and temperature using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 4.7.1 for the period 1985–2008, providing an initial evaluation of the model’s performance for the territory of Georgia. The model domain (1524 km; 2388 km) encompasses the entirety of Georgia’s territory and surrounding regions. The simulation, conducted at a 12 km horizontal grid spacing using ERA5 data as boundary conditions, indicates that the least discrepancy between observed and modeled average annual temperatures and precipitation, falling within a −1 to 1 °C and −200 to 200 mm range, respectively, was observed at most stations of eastern Georgia. The largest disparities between the model and observed average annual precipitation totals were noted along the Black Sea coast, in the Kolkheti Lowland, and in some high mountain stations in western Georgia. The most significant differences in average annual temperatures between the model and observations were observed in Ambrolauri, Mt. Sabueti, and Dedoplistskaro. For Georgia territory, such a long run with such a high resolution using ERA5 as boundary conditions was conducted for the first time. Overall, the modeling results are quite satisfactory, providing a solid basis for the successful utilization of the regional climate model RegCM4.7.1 with the selected parameterization for modeling monthly mean and extreme temperatures and precipitation in Georgia.

Assessment of the Sensitivity of the Mean Climate Simulation over West Africa to Planetary Boundary Layer Parameterization Using RegCM5 Regional Climate Model

This study evaluates the performance of two planetary boundary parameterizations in simulating the mean climate of West Africa using the Regional Climate Model version 5 (RegCM5). These planetary boundary parameterizations are the Holtslag scheme and the University of Washington scheme. Two sets of three one-year simulations were carried out at 25 km horizontal resolution with three different initial conditions. The first set of simulations used the Holtslag scheme (hereafter referred to as Hol), while the second used the University of Washington (UW) scheme (hereafter referred to as UW). The results displayed in this study are an average of the three simulations. During the JJAS rainy season, with respect to GPCP, both models overestimated total rainfall in the orographic regions. The UW experiment represented total rainfall fairly well compared to its counterpart, Hol. Both models reproduced convective rainfall well, with a relatively weak dry bias over the Guinean coast subregion. Globally, UW performed better than Hol in simulating precipitation. The pattern of near-surface temperature in both models was well reproduced with a higher bias with Hol than with UW. Indeed, the UW scheme led to a cooling effect owing to the reduction in eddy heat diffusivity in the lower troposphere contributing to reduce the bias. As a consequence, the height of the planetary boundary layer (PBL) was best simulated using the UW scheme but was underestimated compared to ERA5, while using the Hol scheme failed to capture the height of the PBL. This is coherent with the distribution of total cloud cover, which was better simulated with the UW scheme compared to the Hol scheme. This study shows that use of both planetary boundary parameterizations leads to a good simulation of most of the climatological characteristics of the West African region. Nevertheless, use of the UW scheme contributes to a better performance than use of the Hol scheme, and the differentiation between the two schemes is significant along the Guinea Coast and in orographic regions. In these topographically complex regions, UW appears to be more appropriate than Hol. This study emphasizes the importance of planetary boundary parameterizations for accurately simulating climate variables and for improving climate forecasts and projections in West Africa.

Climate change impacts on regional fire weather in heterogeneous landscapes of central Europe

Abstract. Wildfires have reached an unprecedented scale in the Northern Hemisphere. The summers of 2022 and 2023 demonstrated the destructive power of wildfires, especially in North America and southern Europe. Global warming leads to changes in fire danger. Specifically, fire seasons are assumed to become more extreme and will extend to more temperate regions in northern latitudes in the future. However, the extent to which the seasonality and severity of fire danger in regions of central Europe will change in the future remains to be investigated. Multiple studies claim that natural variability and model uncertainty hide the trend of increasing fire danger in multi-model climate simulations for future potentially fire-prone areas. Such a trend might be isolated with single-model initial-condition large ensembles (SMILEs), which help scientists to distinguish the forced response from natural variability. So far, the SMILE framework has only been applied for fire danger estimation on a global scale. To date, only a few dynamically downscaled regional SMILEs exist, although they enhance the spatial representation of climatic patterns on a regional or local scale. In this study, we use a regional SMILE of the Canadian Regional Climate Model version 5 Large Ensemble (CRCM5-LE) over a region in central Europe under the RCP8.5 (Representative Concentration Pathway) scenario from 1980 to 2099 to analyze changes in fire danger in an area that is currently not fire prone. We use the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. The study area covers four heterogeneous landscapes, namely the Alps, the Alpine Foreland, the lowlands of the South German Escarpment, and the Eastern Mountain Ranges of the Bavarian Forest. We demonstrate that the CRCM5-LE is a dataset suitable for disentangling climate trends from natural variability in a multi-variate fire danger metric. Our results show the strongest increases in the median (50th) and extreme (90th) quantiles of the FWI in the northern parts (South German Escarpment and Eastern Mountain Ranges) of the study area in the summer months of July and August. There, high fire danger becomes the median condition by the end of the century, and levels of high fire danger occur earlier in the fire season. The southern parts (Alps and Alpine Foreland) are less strongly affected by changes in fire danger than the northern parts. However, these regions reach their time of emergence (TOE) in the early 2040s because of very low current fire danger. In the northern parts, the climate change trend exceeds natural variability only in the late 2040s. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by the end of the century. Our results highlight the potential for severe future fire events in central Europe, which is currently not very fire prone, and demonstrate the need for fire management even in regions with a temperate climate.

Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1

Abstract. Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs).

Precipitation Extremes over India in a Coupled Land–Atmosphere Regional Climate Model: Influence of the Land Surface Model and Domain Extent

The frequency and intensity of extreme precipitation events are on the rise worldwide. Despite extensive efforts, regional climate models still show significant biases for extreme precipitation events, often due to factors like improper physics, the choice of land surface model, and spatial domain. Thus, this study uses a Coupled Land–Atmosphere Regional Climate Model version 4.7 (RegCM4.7) to explore how the choice of land surface models (LSMs) and domain extent affects the simulation of extreme precipitation over India. In this regard, a total of four sensitivity experiments have been carried out using two LSMs (CLM4.5 and BATS) over each of the two domains (one over the bigger South Asia CORDEX domain and another for the smaller domain over the Indian region). The main objective is to provide a holistic idea for obtaining an optimum model domain and LSMs for precipitation extremes over India. The model performance is demonstrated for extreme precipitation and associated processes. The result shows the systematic discrepancy in simulating extreme precipitation with a strong inter-simulation spread, indicating the strong sensitivity of extreme precipitation on the LSMs as well as the model domain. The BATS configuration shows a significant overestimation of consecutive wet days and very low precipitation, partially associated with a deficiency in convection. By contrast, the considerable underestimation of intense precipitation can be attributed to the presence of frequent, light drizzle, which hinders the accumulation of moisture in the atmosphere to a sufficient degree to prevent extreme rainfall. Despite significant improvement, the best-configured model (CLM with Indian domain) still indicates substantial bias for extreme precipitation. This deficiency in the model could potentially be mitigated by enhancing both horizontal and vertical resolutions. Nevertheless, further research is needed to explore other physics parameterizations and dynamic mechanisms to address this issue.

Impact of Sub‐Grid Turbulent Orographic Form Drag on the Summer Monsoon Precipitation Simulation Over China

AbstractTerrain has multi‐scale dynamic impacts on the climate. The Regional Climate Model version 4 (RegCM4) has simulation uncertainty partly due to insufficient description of sub‐grid orographic drag (SOD). In this study, the sub‐grid turbulent orographic form drag (TOFD) scheme has been adopted into the RegCM4 to better describe SOD. Results show that the overestimated near surface wind over rugged areas leads to non‐negligible biases of the summer monsoon precipitation simulation over China in the original RegCM4, whose skill in simulating the summer precipitation over the monsoonal regions of China can be remarkably improved by adopting the sub‐grid TOFD scheme. Compared to the original RegCM4, the Taylor scores (root mean square error) of the precipitation simulated by the RegCM4 with the sub‐grid TOFD scheme are increased (decreased) by 4%, 13%, 11%, and 7% (8%, 5%, 30%, and 16%) over the southeastern China, the mid‐lower Yangtze River Basin, the Huang‐Huai Basin, and the northeastern China, respectively. The improved precipitation simulation mainly comes from the atmospheric circulation simulation improved by adopting the sub‐grid TOFD scheme, which leads to cyclonic (anti‐cyclonic) wind differences over the southeastern (northeastern) China from the boundary layer to the mid‐troposphere and thereafter vertical motion differences in the middle troposphere, further resulting in the variation of the simulated precipitation intensity (heavy to torrential) and the convective precipitation and consequential improvement of summer monsoon precipitation simulation. This study indicates that the dynamic impact of micro‐scale terrain plays an important role in the summer monsoon precipitation simulation.

Assessment of simulations of a polar low with the Canadian Regional Climate Model.

Polar lows (PLs), which are intense maritime polar mesoscale cyclones, are associated with severe weather conditions. Due to their small size and rapid development, PL forecasting remains a challenge. Convection-permitting models are adequate to forecast PLs since, compared to coarser models, they provide a better representation of convection as well as surface and near-surface processes. A PL that formed over the Norwegian Sea on 25 March 2019 was simulated using the convection-permitting Canadian Regional Climate Model version 6 (CRCM6/GEM4, using a grid mesh of 2.5 km) driven by the reanalysis ERA5. The objectives of this study were to quantify the impact of the initial conditions on the simulation of the PL, and to assess the skill of the CRCM6/GEM4 at reproducing the PL. The results show that the skill of the CRCM6/GEM4 at reproducing the PL strongly depends on the initial conditions. Although in all simulations the synoptic environment is favourable for PL development, with a strong low-level temperature gradient and an upper-level through, only the low-level atmospheric fields of three of the simulations lead to PL development through baroclinic instability. The two simulations that best captured the PL represent a PL deeper than the observed one, and they show higher temperature mean bias compared to the other simulations, indicating that the ocean surface fluxes may be too strong. In general, ERA5 has more skill than the simulations at reproducing the observed PL, but the CRCM6/GEM4 simulation with initialisation time closer to the genesis time of the PL reproduces quite well small scale features as low-level baroclinic instability during the PL development phase.

Influences of Lateral Boundary Forcings on the 2020 Extreme Meiyu in the Yangtze‐Huaihe River Valley

AbstractMeiyu occurs in Yangtze‐Huaihe River valley (YHRV) every summer. Its intensity, distribution, and intraseasonal variation are greatly influenced by atmospheric forcings from different directions, such as the monsoon southwesterlies from the south, the western Pacific subtropical high (WPSH) in the east, the atmospheric longwave activities in the north, the southwest vortex from the west, and so on. In this study, to explore the contributions of the atmospheric forcings from different directions to 2020 extreme Meiyu, Regional Climate Model version 4.6 (RegCM4.6) is employed. A series of sensitivity experiments are conducted with realistic or climatological averaged lateral boundary conditions. The results show that the monsoon westerlies from the south transport moisture and heat to YHRV, converge with the cold air brought by the frequent atmospheric longwave activities in the north, and result in this extreme Meiyu. The frequent cold air from the north can lift warm air, provide unstable conditions, and make the distribution of precipitation similar to the teleconnection pattern in East Asia. The stable WPSH in the east anchors the 2020 Meiyu rainband to the YHTV for a long time. In addition, the contributions of the atmospheric forcings from different directions to evolution of 2020 Meiyu change with time. Before 10 June, the WPSH in the east mainly contributes to the Meiyu evolution. From 11 June to 3 July, the combined effects of atmospheric forcings from the south and north are dominant. From 3 July to 10 July, the cold air from the north plays a major role.

Hydrological models weighting for hydrological projections: The impacts on future peak flows

Reliable hydrological projections are of great importance for climate change impact studies, especially knowing that these analyses can allow identifying regional adaptation and mitigation strategies for the future. However, the literature has highlighted that hydrological models used under climate conditions that are contrasting to those used during their calibrations can lower their performance and reliability, an issue that lowers the confidence in hydrological projections and adds uncertainty to their analyses. More studies are needed to explore this issue and evaluate potential strategies that might improve hydrological models’ reliability in climate change impact studies. Thus, the present study evaluates the robustness of hydrological models under contrasting climatic conditions and investigates the use of weighting techniques to improve their combined performance and reliability. The robustness of five lumped hydrological models is analysed using a Differential Split-Sample Testing (DSST) that evaluates their performance under cold, warm, humid and dry historical contrasting conditions over 77 basins covering different hydroclimatic conditions (two domains, one located in Quebec, Canada, and one in Mexico). Additionally, four basins were selected from the study area to evaluate the robustness of a more complex semi-distributed and more physically-based hydrological model and compare its simulations against the simpler lumped hydrological models. Based on the resulting performance of each hydrological model, five different weighting methods were applied to evaluate the potential improvements in the multi-model ensemble performance and quantify their effects on hydrological projections, particularly on future peak flows. For each basin, these streamflow projections were produced using two regional climate simulations (one per studied domain) issued from the Canadian Regional Climate Model version 5 (CRCM5) under the Representative Concentration Pathway (RCP) 8.5 for the 1976–2005, 2041–2070 and 2070–2099 periods. The results showed that weighting hydrological models, even with the most simplistic methods, showed better performances over historical contrasting conditions than the best-performing lumped hydrological model. Between the different weighting methods, the Granger-Ramanathan type A showed the overall best performance among the different basins and climate conditions, particularly in peak streamflows. Over the CRCM5-driven peak flow projections, the weighting methods Granger-Ramanathan types A and B produced the largest impacts on the projected floods magnitudes and climate change signals. On the other hand, the additional tests using the semi-distributed and more physically-based hydrological model revealed that this model showed more robust simulations than the weighted lumped hydrological models on low flows over the four selected basins. Additionally, more robust high-flow simulations were observed over a small snow-dominated basin, suggesting a potential added value in adding more complex hydrological models to simulate conditions under a changed climate.

Precipitation Extremes and Their Links with Regional and Local Temperatures: A Case Study over the Ottawa River Basin, Canada

In the context of global warming, the Clausius–Clapeyron (CC) relationship has been widely used as an indicator of the evolution of the precipitation regime, including daily and sub-daily extremes. This study aims to verify the existence of links between precipitation extremes and 2 m air temperature for the Ottawa River Basin (ORB, Canada) over the period 1981–2010, applying an exponential relationship between the 99th percentile of precipitation and temperature characteristics. Three simulations of the Canadian Regional Climate Model version 5 (CRCM5), at three different resolutions (0.44°, 0.22°, and 0.11°), one simulation using the recent CRCM version 6 (CRCM6) at “convection-permitting” resolution (2.5 km), and two reanalysis products (ERA5 and ERA5-Land) were used to investigate the CC scaling hypothesis that precipitation increases at the same rate as the atmospheric moisture-holding capacity (i.e., 6.8%/°C). In general, daily precipitation follows a lower rate of change than the CC scaling with median values between 2 and 4%/°C for the ORB and with a level of statistical significance of 5%, while hourly precipitation increases faster with temperature, between 4 and 7%/°C. In the latter case, rates of change greater than the CC scaling were even up to 10.2%/°C for the simulation at 0.11°. A hook shape is observed in summer for CRCM5 simulations, near the 20–25 °C temperature threshold, where the 99th percentile of precipitation decreases with temperature, especially at higher resolution with the CRCM6 data. Beyond the threshold of 20 °C, it appears that the atmospheric moisture-holding capacity is not the only determining factor for generating precipitation extremes. Other factors need to be considered, such as the moisture availability at the time of the precipitation event, and the presence of dynamical mechanisms that increase, for example, upward vertical motion. As mentioned in previous studies, the applicability of the CC scaling should not be generalised in the study of precipitation extremes. The time and spatial scales and season are also dependent factors that must be taken into account. In fact, the evolution of precipitation extremes and temperature relationships should be identified and evaluated with very high spatial resolution simulations, knowing that local temperature and regional physiographic features play a major role in the occurrence and intensity of precipitation extremes. As precipitation extremes have important effects on the occurrence of floods with potential deleterious damages, further research needs to explore the sensitivity of projections to resolution with various air temperature and humidity thresholds, especially at the sub-daily scale, as these precipitation types seem to increase faster with temperature than with daily-scale values. This will help to develop decision-making and adaptation strategies based on improved physical knowledge or approaches and not on a single assumption based on CC scaling.

Historical simulation of photovoltaic potential over China within the CORDEX-EA-II framework

This study evaluates historical simulation of solar photovoltaic potential (PVpot) during 1989–2008 over China against the ERA5 reanalysis, using the Weather Research and Forecasting (WRF) model and Regional Climate Model version 4 (RegCM4) within the framework of the Coordinated Regional Downscaling Experiment-East Asia second phase (CORDEX-EA-II). The impacts of spectral nudging technique and land surface model on the simulated PVpot are investigated as well. Results indicate that the observed PVpot is abundant over western China, which can reach up to 26% in summer particularly. The WRF simulations significantly overestimate the PVpot over most areas of China, with the bias about 9% over southeastern China, while the utilization of spectral nudging method and CLM4 land surface model can greatly reduce the deviation. The RegCM4 simulations generate underestimation of PVpot over Northwest China and overestimation over Southeast China. As for the interannual variation, the observed PVpot features an increase of 0.9%/decade over southeastern China. The WRF and RegCM4 simulations can reproduce the rising trend of PVpot, while the magnitude is much lower than ERA5. The WRF simulations can properly portray the characteristics of seasonal cycle of PVpot, with the peaks in May over entire China and most subregions, while RegCM4 exhibits poor skill in reproducing the intra-annual variation. Moreover, the simulated bias in the clear-sky solar radiation (RSDSCS), low-level cloud fraction, and light rain during the daylight may contribute to the deficiency of PVpot.

Future projections of wind and solar energy resources over China from regional climate models based on bias correction

In this study, the wind and solar energy resources over China are projected during 2031–2060 under the Representative Concentration Pathway (RCP) 8.5 scenario with the Weather Research and Forecasting (WRF) model and Regional Climate Model version 4 (RegCM4). The bias correction method based on probability distribution is applied to correct the simulated 100-m wind speed and surface down-welling shortwave radiation. The results show that the bias correction method can remarkably improve the skill of the individual simulations and the ensemble mean in capturing the features of wind speed and shortwave radiation from the aspects of spatial distribution, annual cycle, quantile distribution, probability distribution and cumulative probability distribution. The future projections from the bias-corrected ensemble show that both the wind and solar energy resources are abundant over northwestern China, with higher wind power density reaching up to 130 W m−2 in winter and richer surface down-welling shortwave radiation above 240 W m−2 in summer. Generally, the wind and solar energy resources will decrease in the future, by around 6% over the western regions and 4% over southeastern China in winter, respectively. The interannual variability of the two resources is projected to increase over most areas of northern China, indicating a decrease in the stability of resources, while tends to decrease over Southeastern China.

Future change in amplitude and timing of high-flow events in a Canadian subarctic watershed

The Hudson Bay basin is a large contributor of freshwater input in the Arctic Ocean and is also an area affected by destructive spring floods. In this study, the hydrological model MESH (Modelisation Environmentale Communautaire - Surface and hydrology) was set up for the Groundhog River watershed situated in the Hudson Bay basin, to simulate the future evolution of streamflow and annual maximum streamflow. MESH was forced by meteorological data from ERA5 reanalyses in the historical period (1979–2018) and 12 models of the Coupled model intercomparison Project Phase 5 (CMIP5) downscaled with the Canadian Regional Climate model version 5 (CRCM5) in historical (1979–2005) and scenario period (2006–2098). The projections consistently indicate an earlier spring flow and a reduction in the amount of annual maximum streamflow by the end of the 21st century. Under the RCP8.5 scenario, the annual maximum streamflow occurring in the spring is expected to be advanced by 2 weeks and reduced on average from 852 m3/s (±265) in the historical period (1979–2018) to 717m3/s (±250) by the end of the 21st century (2059–2098). Because the seasonal projection of streamflow was not investigated in previous studies, this work is an important first step to assess the seasonal change of streamflow in the Hudson Bay region under climate change.

Inter-seasonal connection of typical European heatwave patterns to soil moisture

Although prolonged heat periods have become a recurring feature of European climate, little knowledge is available on dominant spatial patterns of heatwaves and their influence on moisture-related processes. Increased knowledge will help to improve heatwave and drought prediction and mitigation. This study uses hierarchical agglomerative clustering to derive nine dominating spatial heatwave patterns from a 50-member regional climate model (Canadian Regional Climate Model version 5, CRCM5-LE). The heatwave patterns correspond well with clusters derived from an observational data set (E-OBS) and with extreme historical heatwave events. Moreover, we analyse the occurrence of heatwaves in the identified spatial patterns regarding a soil moisture deficit present before and after the event. We show that negative soil moisture anomalies in the preceding winter/spring (JFMA) can serve as a predictor for heatwaves in South Europe. For North Europe, we find a negative correlation between the number of heatwave days in summer and autumn (OND) soil moisture content.

Evaluation of climate change, urbanization, and low-impact development practices on urban flooding

The Personal Computer Storm Water Management Model was used in this study to evaluate the potential impacts of climate change, urbanization, and low-impact developments (LIDs) on urban flooding in Robe town, Ethiopia. To achieve the objective, four scenarios were developed in order to simulate changes in peak runoff, inundated volume, and the performance of existing drainage systems. The findings revealed that as urbanization increased from 10% to 70%, the inundated volume of nodes and peak runoff increased from 35,418 to 52,118 × 103 m3 and 89.4–111.96 m3/s, respectively. Furthermore, the peak runoff in response to climate change is increased by 46.9%, 34.8%, and 37.5%, respectively, as a result of the Rossby Centre Regional Climate Model version 4 (RCA4), Regional Atmospheric Climate Model (RACMO22T), and the hydrostatic version of the regional model (REMO2009). Overall, the findings showed that existing drainage systems were unable to collect and convey the amplified inundation from different simulated scenarios, and the Welmel sub-city to roundabout was threatened by increased flooding, causing significant damage to properties and infrastructure. The implemented LIDs are capable of reducing the expected peak runoff, flooding magnitude, and flooded junctions in climate change and urbanization scenarios; however, combining both mitigation measures can further reduce the study area. The implementation of a mitigation strategy with adequate drainage systems will be required to mitigate the flooding risks in Robe town.

Solar Energy Powered Decentralized Smart-Grid for Sustainable Energy Supply in Low-Income Countries: Analysis Considering Climate Change Influences in Togo

A smart and decentralized electrical system, powered by grid-connected renewable energy (RE) with a reliable storage system, has the potential to change the future socio-economic dynamics. Climate change may, however, affect the potential of RE and its related technologies. This study investigated the impact of climate change on photovoltaic cells’ temperature response and energy potential under two CO2 emission scenarios, RCP2.6 and 8.5, for the near future (2024–2040) and mid-century (2041–2065) in Togo. An integrated Regional Climate Model version 4 (RegCM4) from the CORDEX-CORE initiative datasets has been used as input. The latter platform recorded various weather variables, such as solar irradiance, air temperature, wind speed and direction, and relative humidity. Results showed that PV cells’ temperature would likely rise over all five regions in the country and may trigger a decline in the PV potential under RCP2.6 and 8.5. However, the magnitude of the induced change, caused by the changing climate, depended on two major factors: (1) the PV technology and (2) geographical position. Results also revealed that these dissimilarities were more pronounced under RCP8.5 with the amorphous technology. It was further found that, nationally, the average cell temperature would have risen by 1 °C and 1.82 °C under RCP2.6 and 8.5, in that order, during the 2024–2065 period for a-Si technology. Finally, the PV potential would likely decrease, on average, by 0.23% for RCP2.6 and 0.4% for RCP8.5 for a-Si technology.

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.

The Wet Bias of RegCM4 Over Tibet Plateau in Summer Reduced by Adopting the 3D Sub‐Grid Terrain Solar Radiative Effect Parameterization Scheme

AbstractThe Regional Climate Model Version 4 (RegCM4) with the conventional plane‐parallel radiative transfer scheme severely overestimates the summer precipitation over the Tibetan Plateau (TP) due to the excessive surface heat source, which results from the poor representation of the sub‐grid terrain‐related radiation processes. To realistically describe the surface sub‐grid radiation process in the RegCM4, a 3‐dimensional sub‐grid terrain solar radiative effect (3DSTSRE) parameterization scheme is implemented into the RegCM4 to improve the original plane‐parallel radiative transfer scheme. Results show that adopting the 3DSTSRE scheme in RegCM4 can significantly reduce the summer (June–August) wet bias over the TP produced by the model with the plane‐parallel radiative transfer scheme. Mechanism analysis indicates that the 3DSTSRE scheme largely improves the description of the TP surface energy balance in the RegCM4 by reducing the positive bias of downward surface solar radiation (DSSR). The reduced DSSR leads to the weakened surface heat source and cooler near‐surface air over the TP. Consequently, the local atmospheric circulation adapts to the temperature field as the low‐level anti‐cyclonic (high‐level cyclonic) anomaly over the TP. The adjustment of the temperature and wind field attenuates the water vapor transport, enhances the low‐level atmospheric stability, inhibits the updraft motion, and eventually reduces the rainfall over TP. Although the 3DSTSRE improves the DSSR simulation only during daytime, the precipitation simulation is also improved at nighttime, which is fundamentally attributed to the maintenance of the cooled atmosphere throughout the daytime and nighttime.