This study aims to evaluate the performance of the individual Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) and the ensemble average of the four RCMs to feign the ...This study aims to evaluate the performance of the individual Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) and the ensemble average of the four RCMs to feign the characteristics of the rainfall pattern for the Mbarali River catchment in Rufiji Basin for the period of 1979 to 2005. Statistical analysis for model performance such as Root mean square error, Mean error, Pearson correlation coefficient, Mean, Median, standard deviation and trend analysis are used. In addition to the statistical measure of model performance, the models are tested on their ability to capture the observed annual cycles and interannual variability of rainfall. Results indicated that the RCMs from the CORDEX indicated a better performance to reproduce the rainfall characteristics over Mbarali River catchment in Rufiji Basin. They reproduced fairly the Era Interim annual cycle and inter-annual variability of rainfall. The ensemble average performed better than individual models in representing rainfall over Mbarali River catchment in Rufiji Basin. These suggest that rainfall simulation from the ensemble average will be used for the assessment of the hydrological impact studies over Mbarali River catchment in Rufiji Basin.展开更多
In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation...In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation dynamics across China for the baseline climate of 1981–2010 and two future climates of 2031–2060 and 2061–2090. The global climate model(GCM)—Hadley Centre Global Environment Model version 2-Earth Systems(HadGEM2-ES) is used to drive the two RCMs. The results of baseline simulations show that the two RCMs can correct the obvious underestimation of light rain below 5 mm day^-1 and the overestimation of precipitation above 5 mm day^-1 in Northwest China and the Qinghai–Tibetan Plateau, as being produced by the driving GCM. While PRECIS outperforms RegCM4 in simulating annual precipitation and wet days in several sub-regions of Northwest China, its underperformance shows up in eastern China. For extreme precipitation, the two RCMs provide a more accurate simulation of continuous wet days(CWD) with reduced biases and more realistic spatial patterns compared to their driving GCM. For other extreme precipitation indices, the RCM simulations show limited benefit except for an improved performance in some localized regions. The future projections of the two RCMs show an increase in the annual precipitation amount and the intensity of extreme precipitation events in most regions. Most areas of Southeast China will experience fewer number of wet days, especially in summer, but more precipitation per wet day(≥ 30 mm day^-1). By contrast, number of wet days will increase in the Qinghai–Tibetan Plateau and some areas of northern China. The increase in both the maximum precipitation for five consecutive days and the regional extreme precipitation will lead to a higher risk of increased flooding. The findings of this study can facilitate the efforts of climate service institutions and government agencies to improve climate services and to make climate-smart decisions.展开更多
文摘This study aims to evaluate the performance of the individual Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) and the ensemble average of the four RCMs to feign the characteristics of the rainfall pattern for the Mbarali River catchment in Rufiji Basin for the period of 1979 to 2005. Statistical analysis for model performance such as Root mean square error, Mean error, Pearson correlation coefficient, Mean, Median, standard deviation and trend analysis are used. In addition to the statistical measure of model performance, the models are tested on their ability to capture the observed annual cycles and interannual variability of rainfall. Results indicated that the RCMs from the CORDEX indicated a better performance to reproduce the rainfall characteristics over Mbarali River catchment in Rufiji Basin. They reproduced fairly the Era Interim annual cycle and inter-annual variability of rainfall. The ensemble average performed better than individual models in representing rainfall over Mbarali River catchment in Rufiji Basin. These suggest that rainfall simulation from the ensemble average will be used for the assessment of the hydrological impact studies over Mbarali River catchment in Rufiji Basin.
基金Supported by the National Key Research and Development Program of China(2018YFA0606204)National Natural Science Foundation of China(51761135024 and 41671113)+1 种基金UK–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund(P106409)Social Development Project of Science and Technology Commission of Shanghai Municipality(19DZ1201500)。
文摘In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation dynamics across China for the baseline climate of 1981–2010 and two future climates of 2031–2060 and 2061–2090. The global climate model(GCM)—Hadley Centre Global Environment Model version 2-Earth Systems(HadGEM2-ES) is used to drive the two RCMs. The results of baseline simulations show that the two RCMs can correct the obvious underestimation of light rain below 5 mm day^-1 and the overestimation of precipitation above 5 mm day^-1 in Northwest China and the Qinghai–Tibetan Plateau, as being produced by the driving GCM. While PRECIS outperforms RegCM4 in simulating annual precipitation and wet days in several sub-regions of Northwest China, its underperformance shows up in eastern China. For extreme precipitation, the two RCMs provide a more accurate simulation of continuous wet days(CWD) with reduced biases and more realistic spatial patterns compared to their driving GCM. For other extreme precipitation indices, the RCM simulations show limited benefit except for an improved performance in some localized regions. The future projections of the two RCMs show an increase in the annual precipitation amount and the intensity of extreme precipitation events in most regions. Most areas of Southeast China will experience fewer number of wet days, especially in summer, but more precipitation per wet day(≥ 30 mm day^-1). By contrast, number of wet days will increase in the Qinghai–Tibetan Plateau and some areas of northern China. The increase in both the maximum precipitation for five consecutive days and the regional extreme precipitation will lead to a higher risk of increased flooding. The findings of this study can facilitate the efforts of climate service institutions and government agencies to improve climate services and to make climate-smart decisions.
