Climate Downscaling Research Articles

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.

Future wind speed trends in the Indian offshore region

Climate models help assess the future availability of wind speeds to extract wind power; however, these climate models are mathematical models that include uncertainty in wind forecasts. Finding an appropriate climate model for analyzing future wind power generation is critical. Therefore, in the present work, six Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) climate models and their ensembles were statistically examined in the Indian offshore region using in-situ buoy readings and ERA5 reanalysis data. Statistical parameters like correlation coefficient, bias, RMSD, and standard deviation are computed to examine the applicable model at buoy locations. With ERA5 wind speeds, the overlapping percentage of climate models is later analyzed for the Indian offshore regions. The ensemble model statistically outperforms individual climate models at buoy sites, with 77% overlap with ERA5 wind speeds in the offshore region. Further, the trends and cumulative variations in wind speeds are calculated for ensemble models under two emission scenarios RCP (Representative Concentration Pathway) 4.5 and RCP 8.5. In the future, the North-East (NE) zone will have the most advantageous change in wind speeds (0.21 to 8.68%), whereas the North-West (NW) area will have a negative cumulative change in wind speeds.

Climate variability impacts on runoff projection under quantile mapping bias correction in the support CMIP6: An investigation in Lushi basin of China

In this study, we modelled the XAJ (Xin’anjiang) hydrologic model parameters for the Lushi basin of China, an important tributary of the Yellow River. Time series of daily precipitation, evaporation, and runoff data from 1976 to 1995 were used to calibrate the model, while the data from 1996 to 2000 were used for validation. Thereafter, the future climate variability was projected from 2021 to 2100 for 0.22° grids under CMIP6 CORDEX-East-Asia (Coordinated Regional Climate Downscaling Experiment-East-Asia) RCP2.6 and RCP8.5 climate scenarios. The non-parametric quantile mapping (QM) bias correction method was used to minimize the large differences between climate variability directly derived from the regional circulation model (RCM) and the historical observations, and the results were also compared with the baseline period (1976–2000). Overall, when compared to the baseline case, results showed a decline in the annual precipitation by 7.22 % and 5.01 %, while an increase was observed for the annual evaporation by 2.03 % and 3.58 % under RCP2.6 and RCP8.5 climate scenarios in the 21st century. Annual runoff projection by XAJ model indicate reduction, with 9.3 % and 31.2 % fall for short-term (2021–2040), 31.5 % and 41.2 % fall for mid-term (2051–2070) and 32.3 % and 77.4 % fall for long-term (2081–2100), respectively. The extreme streamflow projects increase during the dry period (November to June) with 76.5 m3/s and 84.6 m3/s under RCP2.6 and RCP8.5 compared to 45.6 m3/s from the baseline period. In contrast, there is a decrease during the wet period (July to October) by 390 m3/s and 237 m3/s compared to 405 m3/s in the baseline data of the same period. Such projections become more pronounced toward the end of the 21st century, and the reduction is likely to continue if future climate projections occur. The hydrological parameters can be applied to adjacent and similar landscape basins for disaster forecasting and early warning. The QM method is effective in bias correction. The findings can also be used for flood and drought mitigation planning and water resources management in the Yellow River Basin.

Downscaled Climate Change Projections in Urban Centers of Southwest Ethiopia Using CORDEX Africa Simulations

Projections of future climate change trends in four urban centers of southwest Ethiopia were examined under a high Representative Concentration Pathways (RCP8.5) scenario for near- (2030), mid- (2050), and long-term (2080) periods based on high-resolution (0.220) Coordinated Regional Climate Downscaling Experiment (CORDEX) for Africa data. The multi-model ensemble projects annual maximum and minimum temperatures increasing by 0.047 °C per year (R2 > 0.3) and 0.038 °C per year (R2 > 0.7), respectively, with the rates increased by a factor of 10 for decadal projections between the 2030s and 2080s. The monthly maximum temperature increase is projected to be 1.41 °C and 2.82 °C by 2050 and 2080, respectively. In contrast, the monthly minimum temperature increase is projected to reach +3.2 °C in 2080. The overall seasonal multi-model ensemble average shows an increment in maximum temperature by +1.1 °C and +1.9 °C in 2050 and 2080, with the highest change in the winter, followed by spring, summer, and autumn. Similarly, the future minimum temperature is projected to increase across all seasons by 2080, with increases ranging from 0.4 °C (2030s) to 3.2 °C (2080s). All models consistently project increasing trends in maximum and minimum temperatures, while the majority of the models projected declining future precipitation compared to the base period of 1971–2005. A two-tailed T-test (alpha = 0.05) shows a significant change in future temperature patterns, but no significant changes in precipitation were identified. Changes in daily temperature extremes were found in spring, summer, and autumn, with the largest increases in extreme heat in winter. Therefore, our results support proactive urban planning that considers suitable adaptation and mitigation strategies against increasing air temperatures in urban centers in southwest Ethiopia. Future work will examine the likely changes in temperature and precipitation extremes.

Groundwater recharge evaluation due to climate change using WetSpass-M distributed hydrological model in Bilate river basin of Ethiopia

Sporadic change in climate is altering the hydrologic processes affecting the groundwater recharge (GWR) systems across the planet. Distributed groundwater recharge (DGWR) is studied in the Bilate river basin of Ethiopia to predict the current and future for long-term groundwater utilization, planning and management. Precipitation and temperature were acquired from the Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa platform using RCP4.5 and RCP8.5 scenarios for the periods 1986–2015, 2041–2070, and 2071–2100. WetSpass-M distributed hydrological model was used to analyze the seasonal and annual GWR under varying amplitude and dispersion. Particularly in the spring and summer, due to increase in temperature and scanty rainfall GWR is severely affected. Average minimum and maximum temperatures are anticipated to rise by 0.11 °C–0.61 °C and 0.75°C–2.15 °C respectively during mid-RCP4.5 and long-term RCP8.5 scenarios. For the baseline period, RCP4.5, and RCP8.5 for both mid-term and long-term periods, the maximum annual GWR was predicted to be 442.5 mm/yr, 371.6 mm/yr, 347.6 mm/yr, 319.6 mm/yr, and 327.41 mm/yr, respectively. The maximum annual GWR is decreased by 83.3 mm–138.7 mm in the RCP4.5 scenario during the years 2041–2071, but in the RCP8.5 scenario during the years 207–2100, the maximum annual GWR is decreased by 26.1 mm–72.3 mm, while the mean annual GWR is decreased by 26.1 mm–72.3 mm. There have been numerous studies about how climate change (CC) may affect GWR, but this study focuses specifically on forecasting precipitation and temperature to determine GWR in the basin. The results could be crucial for suitable water management use by interpreting the direct and indirect effects of climate change on recharge systems.

Once and future changes in climate and phenology within the Adirondack uplands (New York, USA)

Long-term monitoring of the spring and autumn phenology of five animal species, four plant species, phytoplankton communities, lake temperatures and ice cover on the Paul Smith’s College Phenology Trail in the uplands of the Adirondack State Park (NY, USA) has produced time series spanning 1990–2020 for the biological and water temperature records and 1909–2020 for lake ice. In conjunction with climate records from three nearby weather stations these observations demonstrate that the ice on Lower Saint Regis Lake now thaws one week earlier, on average, than it did in 1909 while the region as a whole warmed by 1.7°C and received 19 cm more precipitation annually. Statistically significant warming trends between 1990 and 2020 were restricted to July and September and therefore contributed to a scarcity of temporal shifts in the spring phenologies of species and lake ice during that shorter time frame, but the lake surface warmed by 1.9°C on average in October. Although most of the phenological records displayed no statistically significant directional change within the 1990–2020 time interval they revealed strong correlations between phenology and monthly air temperatures that are of predictive value. Together with projections from regionally down-scaled climate models these relationships suggest that the phenologies of the species and ice dynamics in question could shift by ca. 1–3 weeks by 2100 depending on the analytical approach used and the magnitude of fossil fuel emissions during this century. As Adirondack winters become shorter and milder before potentially losing snow and ice altogether over the longer term, the unique cultural ecology of the region’s human residents will face profound existential challenges along with the ecosystems and species around them.

Future Projections of Extreme Precipitation Climate Indices over South America Based on CORDEX-CORE Multimodel Ensemble

Climate change is undeniable, and its effects, like droughts and intense precipitation, evidence this reality. However, many questions remain unanswered, such as climate extremes’ future frequency and intensity. International collaboration projects such as the Coordinated Regional Climate Downscaling Experiment (CORDEX)-Coordinated Output for Regional Evaluations (CORE) have emerged to address these questions, creating protocols to facilitate the intercomparison among simulations obtained by different regional climate models (RCMs). Given this context, this study aims to describe the projected changes in the extreme precipitation events over the South America domain by using a set of projections of three RCMs (Eta, RegCM, and REMO) under the CORDEX-CORE framework (except Eta). These models were nested in different global climate models (GCMs) from Coupled Model Intercomparison Project phase 5 (CMIP5) under the RCP8.5 scenario and integrated with a grid space of 25 km. In addition, six climate indices (PRCPTOT, SDII, R95p, P95, CDD, and CWD) were computed by season for the historical period (1995–2014) and four future time-slices (2020–2039, 2040–2059, 2060–2079, and 2080–2099). For brevity, this study focuses on the austral summer. RCMs are generally capable of representing the spatial pattern of climate indices but with differences in intensity. The ensemble with all RCMs shows a slightly better spatial correlation with the reference data than the ensemble of each RCM. The signal of the projections is similar between RegCM and REMO and, in general, opposite to Eta (mainly in the South Atlantic Convergence Zone region). Of the six climate indices analyzed, the ensemble performed with the three RCMs projects statistically significant negative (positive) trends for four indices in the Amazon (La Plata Basin), indicating a signal of dry (wet) conditions increasing towards the end of the century. Furthermore, both regions have significant positive (negative) trends of consecutive dry (wet) days. The region with higher uncertainties lies over southeastern Brazil, where Eta projects a dry climate and RegCM and REMO, a wet one.

Modelling wind speed across Zambia: Implications for wind energy

AbstractWind energy is a key option in global dialogues about climate change mitigation. Here, we combined observations from surface wind stations, reanalysis datasets, and state‐of‐the‐art regional climate models from the Coordinated Regional Climate Downscaling Experiment (CORDEX Africa) to study the current and future wind energy potential in Zambia. We found that winds are dominated by southeasterlies and are rarely strong with an average speed of 2.8 m·s−1. When we converted the observed surface wind speed to a turbine hub height of 100 m, we found a ~38% increase in mean wind speed for the period 1981–2000. Further, both simulated and observed wind speed data show statistically significant increments across much of the country. The only areas that divert from this upward trend of wind speeds are the low land terrains of the Eastern Province bordering Malawi. Examining projections of wind power density (WPD), we found that although wind speed is increasing, it is still generally too weak to support large‐scale wind power generation. We found a meagre projected annual average WPD of 46.6 W·m−2. The highest WPDs of ~80 W·m−2 are projected in the northern and central parts of the country while the lowest are to be expected along the Luangwa valley in agreement with wind speed simulations. On average, Zambia is expected to experience minor WPD increments of 0.004 W·m−2 per year from 2031 to 2050. We conclude that small‐scale wind turbines that accommodate cut‐in wind speeds of 3.8 m·s−1 are the most suitable for power generation in Zambia. Further, given the limitations of small wind turbines, they are best suited for rural and suburban areas of the country where obstructions are few, thus making them ideal for complementing the government of the Republic of Zambia's rural electrification efforts.

Performance evaluation of CORDEX-Africa regional climate models in simulating climate variables over Ethiopian main rift valley: Evidence from Gidabo river basin for impact modeling studies

Measuring the simulation skill of regional climate models (RCMs) is vital in selecting the best performing model that can be used for climate change studies. To that end, the performance of eleven Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa RCMs were evaluated against observed datasets from 1991 to 2005 over Gidabo river basin (GRB), main Ethiopian rift valley. RCMs’ outputs were evaluated using coefficient of variation (CV), percent of bias (PBIAS), Root Means Square Error (RMSE), Pearson's correlation coefficient (r), revised R-squared (RR2), Taylor Skill Score (TSS), Mann-Kendall (MK) trend test and Sen’s slope estimator. The results confirm the difference of RCMs in capturing the annual and seasonal climate variables. In relation to the spatial pattern of the rainfall, RACMO22T (EC-EARTH) strongly reproduced the mean annual rainfall. CCLM4–8 (MPI) and mean ensemble reproduced the annual patterns of the observed rainfall despite the fact with varying rainfall amounts reproduced. The seasonal rainfall pattern was satisfactorily captured by RACMO22T (EC-EARTH), CCLM4–8 (MPI) and REMO2009 (MPI). The agreement between the observed and modeled rainfall is superior in CCLM4–8 (MPI) and RACMO22T (EC-EARTH) at station level. CRCM5 (MPI) satisfactory replicated the patterns of both minimum and maximum temperature. RACMO22T (EC-EARTH) showed best performance in simulating annual and seasonal rainfall trends in GRB. In overall, models that performs better in replicating the observed climatology include RACMO22T (EC-EARTH), CCLM4–8 (MPI), CRCM5 (MPI), CCLM4–8 (CNRM), and REMO2009 (EC-EARTH). The study underscored the use of the mean ensemble of model simulation did not always guarantee better agreement with observation than individual models. Therefore prior to climate impact study, it is advisable to correct the systematic bias and employ the multi-model ensemble of best performing models for climate change impact and adaptation studies in the GRB.

Envisaging the actual evapotranspiration and elucidating its effects under climate change scenarios on agrarian lands of bilate river basin in Ethiopia

The earth's natural water and energy systems rely on actual evapotranspiration (AET). Climate change plays a crucial role in affecting the hydrologic processes of Abayya-Chamo lake basin in Ethiopia's Rift Valley, resulting into a distributed actual evapotranspiration (DAET) system. Various studies have already been undertaken on the effects of climate change (CC) on AET but forecasted precipitation and temperature to determine space-time distribution of AET across the basin have not been studied yet. Estimates for precipitation and temperature were acquired from the Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa platform, using RCP4.5 and RCP8.5 scenarios, during 1986–2015, 2041–2070, and 2071–2100 periods. WetSpass-M model was employed to investigate seasonal and annual DAET under varied climate amplitude and distribution. For the baseline period (1986–2015), the maximum annual AET was predicted to be 2815.8 mm/yr. For 2041–2070, and 2071–2100 periods, the estimated maximum annual AET for RCP4.5 scenarios was 3019.2 and 3212.1 mm/yr, respectively, while for RCP8.5 scenarios, it was 3116 and 3352.2 mm/yr, respectively. The baseline annual AET was 516.6 mm/yr, while the mid-term (RCP4.5 and RCP8.5) and long-term (RCP4.5 and RCP8.5) models predicted mean annual AETs of 423.8 and 432 mm/yr and 429.6, and 438.5 mm/yr, respectively. Between 2041 and 2070, the RCP4.5 and RCP8.5 scenarios predicted a 92.8 and 84.6 mm/yr decrease in mean annual AET, respectively. The model predicted a decline in mean annual AET of 87 and 78.2 mm/yr for both scenarios in 2071 and 2100, respectively. With the exception of the basin's maximum AET, the mean annual AET for both RCP4.5 and RCP8.5 emission scenarios may decline during 2041–2070 and 2071–2100. As rainfall declines and temperature rises and the projected AET in the basin gets disrupted in the future decades. This research may add information to the water management and utilization, and a better knowledge of how climate change directly affects AET systems.

Potential changes in temperature extreme events under global warming at 1.5 °C and 2 °C over Côte d’Ivoire *

This work investigated the impact of 1.5 °C and 2 °C of global warming levels (GWLs) above pre-industrial levels on annual and seasonal mean changes in temperature extremes over Côte d’Ivoire and its different climatic zones. We used the multi-model Coordinated Regional Climate Downscaling Experiment for Africa of 25 regional climate models under the RCP8.5 scenario. The changes in temperature are quantified relative to the period 1971–2000 based on five Expert Team on Climate Change Detection and Indices indexes namely for warm spells, hot nights, hot days, cold nights and cold days. We show that a global warming of 1.5 °C and 2 °C will lead to an increase in the frequency of warm days and warm nights and a decrease in the occurrence of cold days and cold nights across Côte d’Ivoire in all climatic zones and seasons. More than 80% of the model ensemble members project this change at both GWLs. Moreover, the assessment of differences in GWLs highlights that the difference between the 1.5 °C and 2 °C thresholds may intensify the changes over all the country, climatic zones and seasons. Therefore this 0.5 °C difference in global warming is likely to impact upon energy demand and the agricultural system throughout the country and over all of the seasons. This study provides climate information for decision makers related to sectors such as agriculture, energy in their adaptation strategies.

Assessment of Climate Models Performance and Associated Uncertainties in Rainfall Projection from CORDEX over the Eastern Nile Basin, Ethiopia

The adverse impact of climate change on different regionally important sectors such as agriculture and hydropower is a serious concern and is currently at the epicentre of global interest. Despite the extensive efforts to project the future climate and assess its potential impact, it is surrounded by uncertainties. This study aimed to assess climate models’ performance and associated uncertainties in rainfall projection over the eastern Nile basin, Ethiopia. Seventeen climate models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and their four ensemble models were evaluated in terms of their historical prediction performance (1986–2005) and future simulation skill (2006–2016) at rainfall station (point location), grid-scale (0.44° × 0.44°) and basin scale. Station-based and spatially interpolated observed rainfall data were used as a reference during climate model performance evaluation. In addition, CRU data was used as an alternative reference data to check the effect of the reference data source on the climate models evaluation process. As the results showed, climate models have a large discrepancy in their projected rainfall and hence prior evaluation of their performance is necessary. For instance, the bias in historical mean annual rainfall averaged over the basin ranges from +760 mm (wet bias) to −582 mm (dry bias). The spatial pattern correlation (r) of climate models output and observed rainfall ranges from −0.1 to 0.7. The ensemble formed with selected (performance-based) member models outperforms the widely used multi-model ensemble in most of the evaluation metrics. This showed the need for reconsidering the widely used multi-model approach in most climate model-based studies. The use of CRU data as a reference resulted in a change in the magnitude of climate model bias. To conclude, each climate model has a certain degree of uncertainty in the rainfall projection, which potentially affects the studies on climate change and its impact (e.g., on water resources). Therefore, climate-related studies have to consider uncertainties in climate projections, which will help end-users (decision-makers) at least to be aware of the potential range of deviation in the future projected outcomes of interest.

Climate variability in agroecosystems: A quantitative assessment of stakeholder-defined policies for enhanced socio-ecological resilience

CONTEXTThe development of methods for improving the assessment of resilience of socio-ecological systems has become increasingly important as the severity and variability of global climate patterns continue to compound and intensify. OBJECTIVEThe present study was conducted with the aim of using a dynamically-coupled bio-physical and socioeconomic model to test the efficacy of stakeholder-defined policy measures in conferring resilience to two agroecological variables, farm income and water-table depth, experiencing both socio-ecological shocks and climatic stress in the Rechna Doab basin of northeastern Pakistan. METHODSThe objective was accomplished by using a dynamically-coupled physical and group-built system dynamics modelling framework for scenario testing and output generation, including three NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-DGGP), two relevant socio-ecological shock scenarios (market inflation and canal water supply variability), and three stakeholder-defined policy measures. Resilience was assessed using the following system functionality metrics: 1) The degree of return for each variable after a perturbation, i.e., the extent to which the observed variable returns to baseline functioning; 2) The return time of the variable to baseline functioning; 3) The rate of variable return to baseline; 4) Overall perturbation of the system post-disturbance; and 5) The corrective impact of the shock on system functionality. Differences in the resilience metrics were subsequently compared based on the behavioral change(s) of the study variables in response to the application of the three selected policy scenarios. RESULTS AND CONCLUSIONSThe results presented here indicate that rainwater harvesting is the most effective stakeholder-defined policy measure for improving or maintaining resilience of the tested study variables in the Rechna Doab agricultural basin; this holds true for every climate and shock scenario with the exception of water-table depth in the upper and mid-watershed regions under canal supply shock conditions, for which canal lining is the most effective policy measure. The irrigation improvement and canal lining policies were more effective in improving the resilience metrics of water-table depth than those of the farm income variable, as the water-table depth variable is not bound so tightly by economic constraints; although there were regional differences in policy efficacy, these trends hold true, on average, for the entire watershed. The results presented herein align well with previous studies conducted in the region which note similar patterns in spatial resilience of agroecosystem variables (i.e., upper to lower watershed) in the Recha Doab basin as well as regional differences in the efficacy of the stakeholder-defined policy measures. SIGNIFICANCEThis unique approach for assessing socio-environmental policies can help improve decision-making processes with respect to agro-infrastructure and climate change mitigation strategies in vulnerable agroecosystems.

Evaluation of Observed and Future Climate Change Projection for Uttarakhand, India, Using CORDEX-SA

The climate change scenarios, especially global warming, have raised significant concerns, and the Himalayan regions such as Uttarakhand are highly vulnerable to such climatic shifts. Considering 10 Coordinated Regional Climate Downscaling Experiments in South Asia (CORDEX-SA), experiments with 3 regional climate models (RCMs), driven by 13 global climate models, historical estimates and future projections are analyzed from the mid-century (MC) i.e., from 2021–2050 to the end of the century (EC) i.e., from 2070–2099 to characterize annual and seasonal variations in precipitation and temperature. The analysis shows a decrease in the annual average precipitation by 5.92% at MC and an increase of 5.97% at EC for the Representative Climate Pathway (RCP) 4.5, while precipitation may likely increase from 2.83% to 15.89% towards MC and EC in the RCP 8.5. The maximum temperature may likely increase from 0.42 °C to 3.07 °C from MC to EC in the RCP 4.5 and from 0.83 °C to 5.49 °C in the RCP 8.5. In addition, the minimum temperature may increase from 0.80 °C to 3.25 °C from MC to EC in the RCP 4.5 and from 0.30 °C to 5.86 °C from MC to EC in the RCP 8.5. Notably, a decrease in the pre-monsoon precipitation at EC and a higher increase in the maximum temperature during the monsoon season are observed. An increase in the maximum temperature along with precipitation may lead to an increase in the frequency of the monsoon season’s extreme rainfall events.

Uncovering the strengths and weaknesses of an ensemble of quantile mapping methods for downscaling precipitation change in Southern Africa

Study regionSouthern Africa. Study focusWe assessed quantile mapping strengths and weaknesses in climate downscaling based on global climate models projections. An ensemble of methods is used: six methods using parametric transformations, three methods with non-parametric transformations and one method with theoretical distributions transformations. Seventeen climate indices related to precipitation are applied to the locations of 15 UNESCO biosphere reserves. The methods are validated using a cross-validation procedure. The results of the projections for two different future scenarios from the Coupled Model Intercomparison Project Phase 6 are analysed and their contribution to the overall uncertainty in the climate indices is quantified. Quantile mapping stationary assumptions are also investigated. New hydrological insights on the regionThe relative error from the cross-validation shows that both the non-parametric methods and the parametric methods using an exponential-type transformation have in general a good skill in correcting the biases. The method using theoretical distributions shows a good skill for low extremes. The analysis of the methods’ uncertainty contribution reveals that the largest contributors to the overall uncertainty are the climate models whereas in some cases, the methods have the highest uncertainty share. The uncertainty contribution from the methods is higher for the high extremes compared to the low extremes. The stationary assumptions seem robust. The projections indicate a tendency of the region towards dryer conditions and intensified precipitation events. However, this trend contains strong intra-regional variations.

Climate Change Impact Assessment for Future Wind and Solar Energy Installations in India

Solar and wind assets are climate-dependent and changes in climate will result in variations in their generation and intermittency. Developers of solar and wind parks in India have observed changes in climate conditions and variability in solar irradiation and wind profiles at the seasonal and year-to-year timescales. Future climate change perturbations, including monsoon shifts, could lead to lower-than-predicted wind and solar energy production and affect the economics of solar and wind assets. Regional climate models (RCMs) are the basis of climate impact assessments and the most trusted source of information to extract knowledge about future trends in climate variables. However, RCM projections are tainted with variability and uncertainty about the future trends. For India as a case study, we use the RCMs generated by the Coordinated Regional Climate Downscaling Experiment West Asia project (CORDEX WAS) to calculate individual wind, radiation, and temperature trends at selected sites; estimate wind and solar PV energy time series; and embed them in portfolio methods to test the impact of combining wind and solar assets on the variability of the total production and the uncertainty about the predicted production. We include a comparison of CORDEX RCMs with the ERA5 reanalysis dataset and conclude that all available RCMs reasonably simulate the main annual and seasonality features of wind speed, surface solar radiation, and temperature in India. The analysis demonstrates that the uncertainty about the portfolio return can be reduced by optimizing the combination of wind and solar assets in a producer portfolio, thus mitigating the economic impact of climate change. We find that the reduction obtained with a mixed portfolio ranges from 33 to 50% compared to a wind only portfolio, and from 30 to 96% compared to a solar only portfolio.