Understanding the relationship between rainfall anomalies and large-scale systems is critical for driving adaptation and mitigation strategies in socioeconomic sectors. This study therefore aims primarily to investiga...Understanding the relationship between rainfall anomalies and large-scale systems is critical for driving adaptation and mitigation strategies in socioeconomic sectors. This study therefore aims primarily to investigate the correlation between rainfall anomalies in Rwanda during the months of September to December (SOND) with the occurrences of Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) events. The study is useful for early warning and forecasting of negative effects associated with extreme rainfall anomalies across the country, using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), the National Centers for Environmental Prediction (NCEP) National Center for Atmospheric Research (NCAR) reanalysis sea surface temperature and ERA5 reanalysis datasets, during the period of 1983-2021. Both empirical orthogonal function (EOF), correlation analysis and composite analysis were used to delineate variability, relationship and the related atmospheric circulation between Rwanda seasonal rainfall September to December (SOND) with Indian Ocean Dipole (IOD) and El-Nino Southern Oscillation (ENSO). The results for Empirical Orthogonal Function (EOF) for the reconstructed rainfall data set showed three modes. EOF-1, EOF-2 and EOF-3 with their total variance of 63.6%, 16.5% and 4.8%, Indian ocean dipole (IOD) events resulted to a strong positive correlation of rainfall anomalies and Dipole model index (DMI) (r = 0.42, p value = 0.001, DF = 37) significant at 95% confidence level. The composite analysis for the reanalysis dataset was carried out to show the circulation patterns during four different events correlated with September to December seasonal rainfall in Rwanda using T-test at 95% confidence level. Wind anomaly revealed that there was a convergence of south westerly winds and easterly wind over the study area during positive Indian Ocean Diploe (PIOD) and PIOD with El Nino concurrence event years. The finding of this study will contribute to the enhancement of SOND seasonal rainfall forecasting and the reduction of vulnerability during IOD (ENSO) event years.展开更多
通过对近百年 El Nino/ L a Nina事件与北京气候相关性研究发现 ,El Nino/ L aNina事件与北京夏季 ( 6～ 8月 )降水、平均最高气温 ( 7月 )和冬季 ( 1月 )平均最低气温之间相互关系显著。 El Nino事件与夏季降水、冬季平均最低气温呈负...通过对近百年 El Nino/ L a Nina事件与北京气候相关性研究发现 ,El Nino/ L aNina事件与北京夏季 ( 6～ 8月 )降水、平均最高气温 ( 7月 )和冬季 ( 1月 )平均最低气温之间相互关系显著。 El Nino事件与夏季降水、冬季平均最低气温呈负相关 ,与夏季平均最高气温呈正相关 ,造成降水减少 ,气温年较差增大 ,大陆性增强的气候特点。L a Nina事件与夏季降水、冬季平均最低气温呈正相关 ,与夏季平均最高气温呈负相关 ,使降水增加 ,气温年较差减小 。展开更多
文摘Understanding the relationship between rainfall anomalies and large-scale systems is critical for driving adaptation and mitigation strategies in socioeconomic sectors. This study therefore aims primarily to investigate the correlation between rainfall anomalies in Rwanda during the months of September to December (SOND) with the occurrences of Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) events. The study is useful for early warning and forecasting of negative effects associated with extreme rainfall anomalies across the country, using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), the National Centers for Environmental Prediction (NCEP) National Center for Atmospheric Research (NCAR) reanalysis sea surface temperature and ERA5 reanalysis datasets, during the period of 1983-2021. Both empirical orthogonal function (EOF), correlation analysis and composite analysis were used to delineate variability, relationship and the related atmospheric circulation between Rwanda seasonal rainfall September to December (SOND) with Indian Ocean Dipole (IOD) and El-Nino Southern Oscillation (ENSO). The results for Empirical Orthogonal Function (EOF) for the reconstructed rainfall data set showed three modes. EOF-1, EOF-2 and EOF-3 with their total variance of 63.6%, 16.5% and 4.8%, Indian ocean dipole (IOD) events resulted to a strong positive correlation of rainfall anomalies and Dipole model index (DMI) (r = 0.42, p value = 0.001, DF = 37) significant at 95% confidence level. The composite analysis for the reanalysis dataset was carried out to show the circulation patterns during four different events correlated with September to December seasonal rainfall in Rwanda using T-test at 95% confidence level. Wind anomaly revealed that there was a convergence of south westerly winds and easterly wind over the study area during positive Indian Ocean Diploe (PIOD) and PIOD with El Nino concurrence event years. The finding of this study will contribute to the enhancement of SOND seasonal rainfall forecasting and the reduction of vulnerability during IOD (ENSO) event years.
