In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and ...In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North American Multi-model Ensemble (NMME) over Ethiopia during the June to September (JJAS) season. The NMME, one of the multi-model seasonal forecasting systems, regularly generates monthly seasonal rainfall forecasts over the globe with 0.5 <span style="font-family:Verdana;">-</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> 11.5 months lead time. The skill and predictability of seasonal rainfall are assessed using 28 years of hindcast data from the NMME models. The forecast skill is quantified using canonical correlation analysis (CCA) and root mean square error. The results show that the NMME models capture the JJAS seasonal rainfall over central, northern, and northeastern parts of Ethiopia while exhibiting weak or limited skill across western and southwestern Ethiopia. The performance of each model in predicting the JJAS seasonal rainfall is variable, showing greater skill in predicting dry conditions. Overall, the performance of the multi-model ensemble was not consistently better than any single ensemble member. The correlation of observed and predicted </span><span style="font-family:Verdana;">seasonal rainfall for the better performing models</span></span><span style="font-family:Verdana;">—GFDL-CM2p5-FLOR-A06,</span><span style="font-family:Verdana;"> CMC2-CanCM4, GFDL-CM2p5-FLOR-B01 and NASA-GMAO-062012</span><span style="font-family:Verdana;">—</span><span style="font-family:Verdana;">is 0.68, 0.58, 0.52, and 0.5, respectively. The COLA-RSMAS-CCSM4, CMC1-</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">CanCM3 and NCEP-CFSv2 models exhibit less skill, with correlations less than 0.4. In general, the NMME offers promising skill to predict seasonal rainfall展开更多
Climate change has increased extreme events over globe and the most robust occurrences of concurrent drought and floods have become more common in Africa. This study focuses on the observed and projected analysis of r...Climate change has increased extreme events over globe and the most robust occurrences of concurrent drought and floods have become more common in Africa. This study focuses on the observed and projected analysis of rainfall extremes of consecutive dry day (CDD) and maximum monthly five day precipitation (RX5day) from Expert Team on Climate Change Detection and Indices (ETCCDI) in June-August season over Africa. The daily CORDEX Africa, reanalysis and CRU datasets were analyzed for extreme trends under RCP4.5 and RCP8.5 scenarios for the periods of 1980 to 2100. The spatiotemporal variability, trend, and magnitude of JJA seasonal rainfall performance exhibits a significant decreasing tendency over Eastern Africa compared to West Africa. The observed results of consecutive dry day (CDD) reveal that increasing trend and moreover RX5day shows that promising positive trend. Both rainfall extremes are influenced by the combined effect of large scale indexes and appear to be correlated negatively and positively with ENSO, NAO and AO. The CORDEX ensemble mean projections of JJA seasonal rainfall performance show a widespread significant change and the first mode of EOF depicts that 13.8% and 24.9% under the RCP4.5 and the highest variability is under RCP8.5 scenario. The projected CDD extreme exhibit an increasing trend in the coming periods and the percentage change revealed that increasing from 25.11%, 28.02% over West and 26.49%, 31.66% East Africa under RCP4.5 and RCP8.5 scenarios respectively. This situation will exacerbate increasing of frequent and intensified drought extremes over Africa. Additionally, the future RX5day indicated that mixed trend and revealed that increasing 3.72%, 2.54% over West and decreases -16.12%, -22.47% over East Africa under RCP4.5 and RCP8.5 respectively. Generally, rainfall extremes of CDD are projected to increase and RX5day shows a mixed trend in the coming periods over Africa and calls for further verification by using high resolution datasets.展开更多
文摘In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North American Multi-model Ensemble (NMME) over Ethiopia during the June to September (JJAS) season. The NMME, one of the multi-model seasonal forecasting systems, regularly generates monthly seasonal rainfall forecasts over the globe with 0.5 <span style="font-family:Verdana;">-</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> 11.5 months lead time. The skill and predictability of seasonal rainfall are assessed using 28 years of hindcast data from the NMME models. The forecast skill is quantified using canonical correlation analysis (CCA) and root mean square error. The results show that the NMME models capture the JJAS seasonal rainfall over central, northern, and northeastern parts of Ethiopia while exhibiting weak or limited skill across western and southwestern Ethiopia. The performance of each model in predicting the JJAS seasonal rainfall is variable, showing greater skill in predicting dry conditions. Overall, the performance of the multi-model ensemble was not consistently better than any single ensemble member. The correlation of observed and predicted </span><span style="font-family:Verdana;">seasonal rainfall for the better performing models</span></span><span style="font-family:Verdana;">—GFDL-CM2p5-FLOR-A06,</span><span style="font-family:Verdana;"> CMC2-CanCM4, GFDL-CM2p5-FLOR-B01 and NASA-GMAO-062012</span><span style="font-family:Verdana;">—</span><span style="font-family:Verdana;">is 0.68, 0.58, 0.52, and 0.5, respectively. The COLA-RSMAS-CCSM4, CMC1-</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">CanCM3 and NCEP-CFSv2 models exhibit less skill, with correlations less than 0.4. In general, the NMME offers promising skill to predict seasonal rainfall
文摘Climate change has increased extreme events over globe and the most robust occurrences of concurrent drought and floods have become more common in Africa. This study focuses on the observed and projected analysis of rainfall extremes of consecutive dry day (CDD) and maximum monthly five day precipitation (RX5day) from Expert Team on Climate Change Detection and Indices (ETCCDI) in June-August season over Africa. The daily CORDEX Africa, reanalysis and CRU datasets were analyzed for extreme trends under RCP4.5 and RCP8.5 scenarios for the periods of 1980 to 2100. The spatiotemporal variability, trend, and magnitude of JJA seasonal rainfall performance exhibits a significant decreasing tendency over Eastern Africa compared to West Africa. The observed results of consecutive dry day (CDD) reveal that increasing trend and moreover RX5day shows that promising positive trend. Both rainfall extremes are influenced by the combined effect of large scale indexes and appear to be correlated negatively and positively with ENSO, NAO and AO. The CORDEX ensemble mean projections of JJA seasonal rainfall performance show a widespread significant change and the first mode of EOF depicts that 13.8% and 24.9% under the RCP4.5 and the highest variability is under RCP8.5 scenario. The projected CDD extreme exhibit an increasing trend in the coming periods and the percentage change revealed that increasing from 25.11%, 28.02% over West and 26.49%, 31.66% East Africa under RCP4.5 and RCP8.5 scenarios respectively. This situation will exacerbate increasing of frequent and intensified drought extremes over Africa. Additionally, the future RX5day indicated that mixed trend and revealed that increasing 3.72%, 2.54% over West and decreases -16.12%, -22.47% over East Africa under RCP4.5 and RCP8.5 respectively. Generally, rainfall extremes of CDD are projected to increase and RX5day shows a mixed trend in the coming periods over Africa and calls for further verification by using high resolution datasets.
