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.
为了提高风速模拟预报的准确性,利用中尺度区域模式（weather and research forecasting model,WRF）,同化QuickSCAT风场资料,模拟浙江省近海风场。与实测值对比后发现同化后模拟效果得到提升,特别是在四、七月份得到了显著的提升。在300~2 000 m不同高度同化模拟与未同化模拟结果对比中发现,1、4、7月份大部分区域同化模拟风速小于未同化风速,有利于提高模拟效果;同化后对初始场的优化会被模式约束向上传递,优化更高高度的模拟结果,但这种传递有其极限,效果随高度增加逐渐稳定甚至减小。而10月份由于台风和南退副高的影响,同化模拟风速大于未同化模拟,大部区域两者间的差异会随高度增加而增加。
