This paper demonstrates regional characteristics, a long-term decreasing trend, and decadal variations in the frequency of cold surge events based on daily mean temperature and daily minimum temperature data in China&...This paper demonstrates regional characteristics, a long-term decreasing trend, and decadal variations in the frequency of cold surge events based on daily mean temperature and daily minimum temperature data in China's Mainland from 1960 to 2008. During these 48 years four high frequency centers of cold surge events were located in Xinjiang, central North China, northeast China, and southeast China. A main frequency peak of cold surge events occurs in autumn for the four regions and another peak is detected in spring over northeast China and southeast China. The regional pattern of cold surge frequencies is in accordance with the perturbation kinetic energy distribution in October December, January, and February April. The long-term decreasing trend ( 0.2 times/decade) of cold surge frequencies in northeast China and decadal variations in China are related to the variations of the temperature difference between southern and northern China in the winter monsoon season; these variations are due to the significant rising of winter temperatures in high latitudes.展开更多
Soil Moisture and Ocean Salinity （SMOS） Level 3 （L3） sea surface salinity （SSS） products are provided by the Barcelona Expert Centre （BEC）. Strong biases were observed on the SMOS SSS products, thus the data f...Soil Moisture and Ocean Salinity （SMOS） Level 3 （L3） sea surface salinity （SSS） products are provided by the Barcelona Expert Centre （BEC）. Strong biases were observed on the SMOS SSS products, thus the data from the Centre Aval de Traitement des Donnees SMOS （CATDS） were adjusted for biases using a large-scale correction derived from observed differences between the SMOS SSS and World Ocean Atlas （WOA） climatology data. However, this large-scale correction method is not suitable for correcting the large gradient of salinity biases. Here, we present a method for the correction of SSS regional bias of the monthly L3 products. Based on the stable characteristics of the large SSS biases from month to month in some regions, corrected SMOS SSS maps can be obtained from the monthly mean values after removing the regional biases. The accuracy of the SMOS SSS measurements is greatly improved, especially near the coastline, at high latitudes, and in some open ocean regions. The SMOS and ISAS SSS data are also compared with Aquarius SSS to verify the corrected SMOS SSS data. The correction method presented here only corrects annual mean biases. The measurement accuracy of the SSS may be improved by considering the influence of atmospheric and ocean circulation in different seasons and years.展开更多
基金supported jointly by the National Natural Science Foundation of China (40975039)the National Basic Research Program of China (2006CB400504/ 2009CB421401 and GYHY20070605)
文摘This paper demonstrates regional characteristics, a long-term decreasing trend, and decadal variations in the frequency of cold surge events based on daily mean temperature and daily minimum temperature data in China's Mainland from 1960 to 2008. During these 48 years four high frequency centers of cold surge events were located in Xinjiang, central North China, northeast China, and southeast China. A main frequency peak of cold surge events occurs in autumn for the four regions and another peak is detected in spring over northeast China and southeast China. The regional pattern of cold surge frequencies is in accordance with the perturbation kinetic energy distribution in October December, January, and February April. The long-term decreasing trend ( 0.2 times/decade) of cold surge frequencies in northeast China and decadal variations in China are related to the variations of the temperature difference between southern and northern China in the winter monsoon season; these variations are due to the significant rising of winter temperatures in high latitudes.
基金Supported by the National Natural Science Foundation of China(No.41076117)
文摘Soil Moisture and Ocean Salinity （SMOS） Level 3 （L3） sea surface salinity （SSS） products are provided by the Barcelona Expert Centre （BEC）. Strong biases were observed on the SMOS SSS products, thus the data from the Centre Aval de Traitement des Donnees SMOS （CATDS） were adjusted for biases using a large-scale correction derived from observed differences between the SMOS SSS and World Ocean Atlas （WOA） climatology data. However, this large-scale correction method is not suitable for correcting the large gradient of salinity biases. Here, we present a method for the correction of SSS regional bias of the monthly L3 products. Based on the stable characteristics of the large SSS biases from month to month in some regions, corrected SMOS SSS maps can be obtained from the monthly mean values after removing the regional biases. The accuracy of the SMOS SSS measurements is greatly improved, especially near the coastline, at high latitudes, and in some open ocean regions. The SMOS and ISAS SSS data are also compared with Aquarius SSS to verify the corrected SMOS SSS data. The correction method presented here only corrects annual mean biases. The measurement accuracy of the SSS may be improved by considering the influence of atmospheric and ocean circulation in different seasons and years.
