Assimilating Retrievals of Sea Surface Temperature from VIIRS and AMSR2
Assimilating Retrievals of Sea Surface Temperature from VIIRS and AMSR2
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从 VIIRS 和 AMSR2 同化反演海面温度
DOI：
10.1175/jtech-d-15-0093.1
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发表时间：
2016
影响因子：
2.2
通讯作者：
Dorina Surcel Colan
中科院分区：
文献类型：
--
作者：
B. Brasnett;Dorina Surcel Colan
为评估两个新的卫星数据集对加拿大气象中心(CMC)全球海洋表面温度(SST)分析的质量的潜在贡献，进行了实验，这两个数据集来自Suomi-National极轨伙伴卫星上的可见光红外成像辐射计套件(VIIRS)和全球变化观测站-水(GCOM-W)卫星上的高级微波扫描辐射计2号(AMSR2)。新的数据集分别和一起被同化。对独立数据的验证表明，VIIRS和AMSR2数据集产生的分析具有类似的全球平均误差，VIIRS分析在某些季节表现更好，AMSR2分析在其他季节表现更好。根据AMSR2的分析，一些地区的季节性多云减少了VIIRS反演的可用性，导致了更好的性能。这两个数据集与来自Advanced Very HIG的数据一起被同化。
AbstractExperiments are carried out to assess the potential contributions of two new satellite datasets, derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi–National Polar-Orbiting Partnership satellite and the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission–Water (GCOM-W) satellite, to the quality of global sea surface temperature (SST) analyses at the Canadian Meteorological Centre (CMC). The new datasets are assimilated both separately and together. Verification of the analyses against independent data shows that the VIIRS and AMSR2 datasets yield analyses with similar global average errors, with the VIIRS analysis performing better during some seasons and the AMSR2 analysis performing better in others. Seasonal cloudiness in some regions diminishes the availability of VIIRS retrievals, resulting in better performance by the AMSR2 analysis. Both datasets were assimilated together along with data from the Advanced Very Hig...
影响因子：
8
作者：
Donlon, C.;Robinson, I.;Rayner, N.
通讯作者：
Rayner, N.