Two ensemble experiments were conducted using a general atmospheric circulation model. These experiments were used to investigate the impacts of initial snow anomalies over the Tibetan Plateau(TP) on China precipitati...Two ensemble experiments were conducted using a general atmospheric circulation model. These experiments were used to investigate the impacts of initial snow anomalies over the Tibetan Plateau(TP) on China precipitation prediction. In one of the experiments, the initial snow conditions over the TP were climatological values; while in the other experiment, the initial snow anomalies were snow depth estimates derived from the passive microwave remote-sensing data. In the current study, the difference between these two experiments was assessed to evaluate the impact of initial snow anomalies over the TP on simulated precipitation. The results indicated that the model simulation for precipitation over eastern China had certain improvements while applying a more realistic initial snow anomaly, especially for spring precipitation over Northeast China and North China and for summer precipitation over North China and Southeast China. The results suggest that seasonal prediction could be enhanced by using more realistic initial snow conditions over TP, and microwave remote-sensing snow data could be used to initialize climate models and improve the simulation of eastern China precipitation during spring and summer. Further analyses showed that higher snow anomalies over TP cooled the surface, resulting in lower near- surface air temperature over the TP in spring and summer. The surface cooling over TP weakened the Asian summer monsoon and brought more precipitation in South China in spring and more precipitation to Southeast China during summer.展开更多
Rwanda is a landlocked country in central-eastern Africa.As a country highly dependent on rain-fed agriculture,Rwanda is vulnerable to rainfall variability.Observational data show that there are two rainy seasons in R...Rwanda is a landlocked country in central-eastern Africa.As a country highly dependent on rain-fed agriculture,Rwanda is vulnerable to rainfall variability.Observational data show that there are two rainy seasons in Rwanda,i.e.,the long rainy season and the short rainy season.This study mainly focuses on the dominant intraseasonal rainfall mode during the long rainy season(February-May),and evaluates the forecast skill for the intraseasonal variability(ISV)over Rwanda and its surrounding regions in a state-of-the-art dynamic model.During the long rainy season,observational results reveal that the dominant intraseasonal rainfall mode in Rwanda exhibits a significant variability on the 10-25-day time scale.One-point-correlation analysis further unveils that the 10-25-day intraseasonal rainfall variability in Rwanda co-varies with that in its adjacent areas,indicating that the overall 10-25-day rainfall variability in Rwanda and its adjacent regions(8°S-3°N,29°-37°E)should be considered collectively when studying the dominant intraseasonal rainfall variability in Rwanda.Composite results show that the development of the 10-25-day rainfall variability is associated with the anomalous westerly wind in Rwanda and its surrounding regions,which may trace back to a pair of westward-propagating equatorial Rossby waves.Based on the observational findings,an ISO_rainfall_index and an ISO_wind_index are proposed for quantitatively evaluating the forecast skill.The ECMWF model has a comparable skill in predicting the wind index and the rainfall index,with both indices showing a skill of 18 days.展开更多
基金supported by the National Basic Research Program of China (Grant No. 2009CB421407)the Special Fund for Public Welfare (Meteorology) (Grant No. GYHY200906018)+1 种基金"Strategic Priority Research Program-Climate Change: Carbon Budget and Related Issues" of the Chinese Academy of Sciences (Grant No. XDA05110201)the National Key Technologies R&D Program of China (Grant No. 2007BAC29B03)
文摘Two ensemble experiments were conducted using a general atmospheric circulation model. These experiments were used to investigate the impacts of initial snow anomalies over the Tibetan Plateau(TP) on China precipitation prediction. In one of the experiments, the initial snow conditions over the TP were climatological values; while in the other experiment, the initial snow anomalies were snow depth estimates derived from the passive microwave remote-sensing data. In the current study, the difference between these two experiments was assessed to evaluate the impact of initial snow anomalies over the TP on simulated precipitation. The results indicated that the model simulation for precipitation over eastern China had certain improvements while applying a more realistic initial snow anomaly, especially for spring precipitation over Northeast China and North China and for summer precipitation over North China and Southeast China. The results suggest that seasonal prediction could be enhanced by using more realistic initial snow conditions over TP, and microwave remote-sensing snow data could be used to initialize climate models and improve the simulation of eastern China precipitation during spring and summer. Further analyses showed that higher snow anomalies over TP cooled the surface, resulting in lower near- surface air temperature over the TP in spring and summer. The surface cooling over TP weakened the Asian summer monsoon and brought more precipitation in South China in spring and more precipitation to Southeast China during summer.
基金jointly supported by the National Key Research and Development Program of China[grant number 2019YFC1510004]and the LASG Open Project.
文摘Rwanda is a landlocked country in central-eastern Africa.As a country highly dependent on rain-fed agriculture,Rwanda is vulnerable to rainfall variability.Observational data show that there are two rainy seasons in Rwanda,i.e.,the long rainy season and the short rainy season.This study mainly focuses on the dominant intraseasonal rainfall mode during the long rainy season(February-May),and evaluates the forecast skill for the intraseasonal variability(ISV)over Rwanda and its surrounding regions in a state-of-the-art dynamic model.During the long rainy season,observational results reveal that the dominant intraseasonal rainfall mode in Rwanda exhibits a significant variability on the 10-25-day time scale.One-point-correlation analysis further unveils that the 10-25-day intraseasonal rainfall variability in Rwanda co-varies with that in its adjacent areas,indicating that the overall 10-25-day rainfall variability in Rwanda and its adjacent regions(8°S-3°N,29°-37°E)should be considered collectively when studying the dominant intraseasonal rainfall variability in Rwanda.Composite results show that the development of the 10-25-day rainfall variability is associated with the anomalous westerly wind in Rwanda and its surrounding regions,which may trace back to a pair of westward-propagating equatorial Rossby waves.Based on the observational findings,an ISO_rainfall_index and an ISO_wind_index are proposed for quantitatively evaluating the forecast skill.The ECMWF model has a comparable skill in predicting the wind index and the rainfall index,with both indices showing a skill of 18 days.
