The interannual variability of autumn precipitation over South China and its relationship with atmospheric circulation and SST anomalies are examined using the autumn precipitation data of 160 stations in China and th...The interannual variability of autumn precipitation over South China and its relationship with atmospheric circulation and SST anomalies are examined using the autumn precipitation data of 160 stations in China and the NCEP-NCAR reanalysis dataset from 1951 to 2004. Results indicate a strong interannual variability of autumn precipitation over South China and its positive correlation with the autumn western Pacific subtropical high (WPSH). In the flood years, the WPSH ridge line lies over the south of South China and the strengthened ridge over North Asia triggers cold air to move southward. Furthermore, there exists a significantly anomalous updraft and cyclone with the northward stream strengthened at 850 hPa and a positive anomaly center of meridional moisture transport strengthening the northward warm and humid water transport over South China. These display the reverse feature in drought years. The autumn precipitation interannual variability over South China correlates positively with SST in the western Pacific and North Pacific, whereas a negative correlation occurs in the South Indian Ocean in July. The time of the strongest lag-correlation coefficients between SST and autumn precipitation over South China is about two months, implying that the SST of the three ocean areas in July might be one of the predictors for autumn precipitation interannual variability over South China. Discussion about the linkage among July SSTs in the western Pacific, the autumn WPSH and autumn precipitation over South China suggests that SST anomalies might contribute to autumn precipitation through its close relation to the autumn WPSH.展开更多
Long-term observational data indicated a decreasing trend for the amount of autumn precipitation(i.e. 54.3 mm per decade) over Mid-Eastern China, especially after the 1980s(~ 5.6% per decade). To examine the cause of ...Long-term observational data indicated a decreasing trend for the amount of autumn precipitation(i.e. 54.3 mm per decade) over Mid-Eastern China, especially after the 1980s(~ 5.6% per decade). To examine the cause of the decreasing trend, the mechanisms associated with the change of autumn precipitation were investigated from the perspective of water vapor transportation, atmospheric stability and cloud microphysics. Results show that the decrease of convective available potential energy(i.e. 12.81 J kg-1/ decade) and change of cloud microphysics, which were closely related to the increase of aerosol loading during the past twenty years, were the two primary factors responsible for the decrease of autumn precipitation. Our results showed that increased aerosol could enhance the atmospheric stability thus weaken the convection. Meanwhile, more aerosols also led to a significant decline of raindrop concentration and to a delay of raindrop formation because of smaller size of cloud droplets. Thus, increased aerosols produced by air pollution could be one of the major reasons for the decrease of autumn precipitation. Furthermore, we found that the aerosol effects on precipitation in autumn was more significant than in other seasons, partly due to relatively more stable synoptic systems in autumn. The impact of large-scale circulation dominant in autumn and the dynamic influence on precipitation was more important than the thermodynamic activity.展开更多
Based on daily precipitation data from 109 stations in the Yangtze River Basin(YRB)over the past 36 years(1980-2015),the Empirical Orthogonal Function(EOF)is employed to analyze changes in autumn precipitation.We used...Based on daily precipitation data from 109 stations in the Yangtze River Basin(YRB)over the past 36 years(1980-2015),the Empirical Orthogonal Function(EOF)is employed to analyze changes in autumn precipitation.We used the monthly mean re-analysis datasets of atmospheric circulation and sea surface temperature(SST)to investigate the possible causes of the two leading modes,based on which the predictive equations were constructed and tested.The results of the EOF analysis show that the variance contribution of the first mode is 31.07%,and the spatial distribution shows a uniform variation over the whole region.The variance contribution of the second mode is 15.02%,and the spatial distribution displays a north-south dipole pattern in the YRB.The leading mode shows a dominant interannual variation,which is mainly due to the West Pacific subtropical high and anticyclones over the Philippine islands.The SST field corresponds to the positive phase of the eastern Pacific El Niño and the tropical Indian Ocean dipole.The second mode may be related to the Indian Ocean-East Asian teleconnection and early withdrawal of the summer monsoon.The SST field corresponds to a weaker central Pacific El Niño.Through a stepwise regression analysis,SST anomalies in some areas during summer show a good predictive effect on the autumn precipitation mode in the YRB region.展开更多
Associations between autumn Arctic sea ice concentration(SIC) and early winter precipitation in China are studied using singular value decomposition analysis. The results show that a reduced SIC almost everywhere in...Associations between autumn Arctic sea ice concentration(SIC) and early winter precipitation in China are studied using singular value decomposition analysis. The results show that a reduced SIC almost everywhere in the Arctic Ocean, except the northern Greenland Sea and Canadian Basin, are accompanied by dry conditions over central China, extending northeast from the Tibetan Plateau toward the Japan Sea, the Bohai Sea and the Yellow Sea, and wet conditions over South China and North China. Atmospheric circulation anomalies associated with SIC variability show two wave-train structures, which are persistent from autumn to winter, leading to the identified relationship between autumn Arctic SIC and early winter precipitation in China. Given that the decline in autumn SIC in the Arctic Ocean is expected to continue as the climate warms, this relationship provides a possible long-term outlook for early winter precipitation in China.展开更多
文摘The interannual variability of autumn precipitation over South China and its relationship with atmospheric circulation and SST anomalies are examined using the autumn precipitation data of 160 stations in China and the NCEP-NCAR reanalysis dataset from 1951 to 2004. Results indicate a strong interannual variability of autumn precipitation over South China and its positive correlation with the autumn western Pacific subtropical high (WPSH). In the flood years, the WPSH ridge line lies over the south of South China and the strengthened ridge over North Asia triggers cold air to move southward. Furthermore, there exists a significantly anomalous updraft and cyclone with the northward stream strengthened at 850 hPa and a positive anomaly center of meridional moisture transport strengthening the northward warm and humid water transport over South China. These display the reverse feature in drought years. The autumn precipitation interannual variability over South China correlates positively with SST in the western Pacific and North Pacific, whereas a negative correlation occurs in the South Indian Ocean in July. The time of the strongest lag-correlation coefficients between SST and autumn precipitation over South China is about two months, implying that the SST of the three ocean areas in July might be one of the predictors for autumn precipitation interannual variability over South China. Discussion about the linkage among July SSTs in the western Pacific, the autumn WPSH and autumn precipitation over South China suggests that SST anomalies might contribute to autumn precipitation through its close relation to the autumn WPSH.
基金National Basic Research Program of China(2012CB955301)
文摘Long-term observational data indicated a decreasing trend for the amount of autumn precipitation(i.e. 54.3 mm per decade) over Mid-Eastern China, especially after the 1980s(~ 5.6% per decade). To examine the cause of the decreasing trend, the mechanisms associated with the change of autumn precipitation were investigated from the perspective of water vapor transportation, atmospheric stability and cloud microphysics. Results show that the decrease of convective available potential energy(i.e. 12.81 J kg-1/ decade) and change of cloud microphysics, which were closely related to the increase of aerosol loading during the past twenty years, were the two primary factors responsible for the decrease of autumn precipitation. Our results showed that increased aerosol could enhance the atmospheric stability thus weaken the convection. Meanwhile, more aerosols also led to a significant decline of raindrop concentration and to a delay of raindrop formation because of smaller size of cloud droplets. Thus, increased aerosols produced by air pollution could be one of the major reasons for the decrease of autumn precipitation. Furthermore, we found that the aerosol effects on precipitation in autumn was more significant than in other seasons, partly due to relatively more stable synoptic systems in autumn. The impact of large-scale circulation dominant in autumn and the dynamic influence on precipitation was more important than the thermodynamic activity.
基金This work is supported by the National Natural Science Foundation of China(NSFC)(Nos.41975061 and 41605037).
文摘Based on daily precipitation data from 109 stations in the Yangtze River Basin(YRB)over the past 36 years(1980-2015),the Empirical Orthogonal Function(EOF)is employed to analyze changes in autumn precipitation.We used the monthly mean re-analysis datasets of atmospheric circulation and sea surface temperature(SST)to investigate the possible causes of the two leading modes,based on which the predictive equations were constructed and tested.The results of the EOF analysis show that the variance contribution of the first mode is 31.07%,and the spatial distribution shows a uniform variation over the whole region.The variance contribution of the second mode is 15.02%,and the spatial distribution displays a north-south dipole pattern in the YRB.The leading mode shows a dominant interannual variation,which is mainly due to the West Pacific subtropical high and anticyclones over the Philippine islands.The SST field corresponds to the positive phase of the eastern Pacific El Niño and the tropical Indian Ocean dipole.The second mode may be related to the Indian Ocean-East Asian teleconnection and early withdrawal of the summer monsoon.The SST field corresponds to a weaker central Pacific El Niño.Through a stepwise regression analysis,SST anomalies in some areas during summer show a good predictive effect on the autumn precipitation mode in the YRB region.
基金The Chinese Polar Environment Comprehensive Investigation and Assessment Programmes,State Oceanic Administration under contact Nos CHINARE2014-03-01 and CHINARE2014-04-03the Public Science and Technology Research Funds Projects of Ocean under contact No.201205007the Basic Research Operating Funds of the First Institute of Oceanography,State Oceanic Administration under contact Nos 2014T02 and 2014G02
文摘Associations between autumn Arctic sea ice concentration(SIC) and early winter precipitation in China are studied using singular value decomposition analysis. The results show that a reduced SIC almost everywhere in the Arctic Ocean, except the northern Greenland Sea and Canadian Basin, are accompanied by dry conditions over central China, extending northeast from the Tibetan Plateau toward the Japan Sea, the Bohai Sea and the Yellow Sea, and wet conditions over South China and North China. Atmospheric circulation anomalies associated with SIC variability show two wave-train structures, which are persistent from autumn to winter, leading to the identified relationship between autumn Arctic SIC and early winter precipitation in China. Given that the decline in autumn SIC in the Arctic Ocean is expected to continue as the climate warms, this relationship provides a possible long-term outlook for early winter precipitation in China.