首页> 外文会议>International Society for Photogrammetry and Remote Sensing Commission Technical Commission Symposium >SENSOR SYNERGY OF ACTIVE AND PASSIVE MICROWAVE INSTRUMENTS FOR OBSERVATIONS OF MARINE SURFACE WINDS
【24h】

SENSOR SYNERGY OF ACTIVE AND PASSIVE MICROWAVE INSTRUMENTS FOR OBSERVATIONS OF MARINE SURFACE WINDS

机译:用于观察海洋表面风的主动和被动微波仪器的传感器协同

获取原文
获取外文期刊封面目录资料

摘要

An example of sensor synergy of active and passive microwave instruments for observations of marine surface winds is demonstrated using data from the Advanced Earth Observing Satellite-II (ADEOS-II), which carried a Ku-band microwave scatterometer, SeaWinds, and the Advanced Microwave Scanning Radiometer (AMSR). Scalar wind speed observed by AMSR was evaluated by using wind speed observed by SeaWinds. The intercomparison between the AMSR and SeaWinds wind speeds was largely contributed to improvements of the wind retrieval algorithm for AMSR. The latest version of AMSR wind speed agrees well with buoy and SeaWinds data with negligibly small bias and root-mean-squared difference of approximately 1.5 ms~(-1). A discontinuous trend in the wind speed, which was discernible in the earlier versions, was much reduced in the latest version. Wind speed bias which depends on the relative wind direction was significantly reduced compared to the previous versions. Rain flag algorithm developed for the SeaWinds wind products was also assessed using rain data derived from AMSR. Global statistical analyses indicated significant improvements of the rain flag algorithm compared to the previous version. Evaluation of wind speed algorithm of ASMR and rain flag algorithm for SeaWinds will contribute not only to improvements of the wind products of AMSR and SeaWinds on ADEOS-II but also to those of AMSR-E on Aqua and SeaWinds on QuikSCAT, which are not accompanied by active and passive microwave sensor, respectively.
机译:使用来自先进地球观察卫星-II(ADEOS-II)的数据进行了用于观察海洋表面风的主动和被动微波仪器的传感器协同仪器的示例,该数据携带Ku带微波散射仪,海风和先进的微波炉扫描辐射计(AMSR)。通过使用Seawinds观察到的风速来评估AMSR的标量风速。 AMSR和Seawinds Wind Speed之间的相互熟悉基本上有助于改善AMSR的风检测算法。最新版本的AMSR风速与浮标和海卷数据吻合较小的偏差小,均匀平均差异约为1.5ms〜(-1)。在早期版本中可辨别的风速的不连续趋势在最新版本中得多。与先前版本相比,取决于相对风向的风速偏差显着减少。利用来自AMSR的雨量数据,还评估了为Seawinds Wind产品开发的雨旗算法。与以前的版本相比,全局统计分析表明雨标志算法的显着改进。海风的ASMR和雨旗算法的风速算法评估将不仅有助于改进ADEOS-II上的AMSR和Seawinds的风产品,而且还贡献了AMSR-E在Quikscat上的AMSR-E的那些,这不是伴随的通过主动和无源微波传感器。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号