This paper proposes a method for predicting the development of tropical disturbance over the South China Sea(SCS)based on the total latent heat release(TLHR)derived from the Special Sensor Microwave/Imager(SSM/I)satel...This paper proposes a method for predicting the development of tropical disturbance over the South China Sea(SCS)based on the total latent heat release(TLHR)derived from the Special Sensor Microwave/Imager(SSM/I)satellite observations.A threshold value of daily mean TLHR(3×1014 W)for distinguishing the non-developing and developing tropical disturbances is obtained based on the analysis for 25 developing and 43 non-developing tropical disturbances over the SCS during 2000 to 2005.If the mean TLHR within 500 km of a disturbance on the latest day and its daily mean TLHR during previous life are both greater than 3×1014 W,the disturbance will be a developing one in the future.Otherwise,it is a non-developing one.A real-time testing prediction of tropical cyclogenesis over the SCS was conducted for the years 2007 and 2008 using this threshold value of TLHR.We find that the method is successful in detecting the development of 80%of all tropical disturbances over the SCS in 2007 and 2008.展开更多
Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve th...Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve the Antarctic ice-sheet near-surface snowmelt detection accuracy, a new Antarctic icesheet near-surface snowmelt synergistic detection method was proposed based on the principle of complementary advantages of SSM/I data(high reliability) and QuikSCAT data(high sensitivity) by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic snowmelt onset date, snowmelt duration and snowmelt end date. The verification result shows that the proposed snowmelt synergistic detection method improves the detection accuracy from about 75% to 86% based on AWS(Automatic Weather Stations) Butler Island and Larsen Ice Shelf. The algorithm can also be applied to other regions, which provides methodological support and supplement for the global snowmelt detection.展开更多
基金Chinese Key 973 project(2009CB421504)National Science Foundation of China(40730948+1 种基金 4092116038040975059)
文摘This paper proposes a method for predicting the development of tropical disturbance over the South China Sea(SCS)based on the total latent heat release(TLHR)derived from the Special Sensor Microwave/Imager(SSM/I)satellite observations.A threshold value of daily mean TLHR(3×1014 W)for distinguishing the non-developing and developing tropical disturbances is obtained based on the analysis for 25 developing and 43 non-developing tropical disturbances over the SCS during 2000 to 2005.If the mean TLHR within 500 km of a disturbance on the latest day and its daily mean TLHR during previous life are both greater than 3×1014 W,the disturbance will be a developing one in the future.Otherwise,it is a non-developing one.A real-time testing prediction of tropical cyclogenesis over the SCS was conducted for the years 2007 and 2008 using this threshold value of TLHR.We find that the method is successful in detecting the development of 80%of all tropical disturbances over the SCS in 2007 and 2008.
基金supported by National Natural Science Foundation of China(Grant No. 41606209)supported by National Key Research and Development Program of China (Grant No. 2016YFB0501501)+3 种基金supported by Fujian Provincial Key Laboratory of Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China(Grant No. JYG1707)supported by Polar Science Strategic Research Foundation of China (Grant No. 20150312)supported by the Fundamental Research Funds for the Henan Provincial Colleges and Universities (Grant No. 2015QNJH16)supported by Science and technology project of Zhengzhou Science and Technology Bureau(Grant No. 20150251)
文摘Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve the Antarctic ice-sheet near-surface snowmelt detection accuracy, a new Antarctic icesheet near-surface snowmelt synergistic detection method was proposed based on the principle of complementary advantages of SSM/I data(high reliability) and QuikSCAT data(high sensitivity) by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic snowmelt onset date, snowmelt duration and snowmelt end date. The verification result shows that the proposed snowmelt synergistic detection method improves the detection accuracy from about 75% to 86% based on AWS(Automatic Weather Stations) Butler Island and Larsen Ice Shelf. The algorithm can also be applied to other regions, which provides methodological support and supplement for the global snowmelt detection.
