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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Sensitivity of Ocean Surface Salinity Measurements From Spaceborne L-Band Radiometers to Ancillary Sea Surface Temperature
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Sensitivity of Ocean Surface Salinity Measurements From Spaceborne L-Band Radiometers to Ancillary Sea Surface Temperature

机译:星载L波段辐射计测量海洋表面盐度对辅助海面温度的敏感性

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Sea surface temperature (SST) serves as a crucial ancillary input field to the retrieval algorithm for sea surface salinity (SSS) from L-band satellite radiometers, such as Soil Moisture and Ocean Salinity mission, Aquarius, and Soil Moisture Active Passive mission. It is needed for inverting the radiative transfer model equation of the ocean surface emissivity, which depends both on ocean surface salinity and ocean surface temperature. Our analysis studies the sensitivity of the performance of the Aquarius salinity retrieval algorithm to the ancillary SST that is used in the algorithm. We have retrieved Aquarius salinities using four different SST fields as ancillary input, namely, the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR)-only Optimum Interpolation SST (OISST), the SST from WindSat, the SST from the Canadian Meteorological Center (CMC), and the Multi-scale Ultra-high Resolution (MUR) SST from the National Aeronautics and Space Administration's Jet Propulsion Laboratory. The retrieved Aquarius SSS is compared with ground truth data; thus, the performance of the salinity retrieval algorithm in all four cases can be evaluated. The WindSat, CMC, and MUR SST products, which are all based on or are assimilating SST measurements from the passive microwave (MW) sensors, give better performance than the NOAA AVHRR-only OISST, which does not use any MW SST data, but which is solely based on the in situ data and observations from the infrared AVHRR sensor. The CMC SST gives the best overall performance for the retrieved SSS. The sensitivity of the SSS retrievals and therefore the performance differences between the various ancillary input fields increases in cold water.
机译:海表温度(SST)是从L波段卫星辐射计(例如土壤湿度和海洋盐度任务,水瓶座和土壤水分主动被动任务)检索海表盐度(SSS)的算法的关键辅助输入字段。需要反演海洋表面辐射率的辐射传递模型方程,该方程取决于海洋表面盐度和海洋表面温度。我们的分析研究了Aquarius盐度检索算法的性能对算法中使用的辅助SST的敏感性。我们已经使用四个不同的SST场作为辅助输入检索了水瓶座盐度,即仅美国国家海洋和大气管理局(NOAA)先进超高分辨率辐射计(AVHRR)最佳插值SST(OISST),WindSat的SST,加拿大气象中心(CMC),以及国家航空航天局喷气推进实验室的多尺度超高分辨率(MUR)SST。将检索到的水瓶座SSS与地面真实数据进行比较;因此,可以评估盐度检索算法在所有四种情况下的性能。与基于NOAA AVHRR的OISST(不使用任何MW SST数据)相比,WindSat,CMC和MUR SST产品均基于无源微波(MW)传感器或从无源微波(MW)传感器获取的SST测量,其性能更高。它完全基于红外AVHRR传感器的现场数据和观测结果。 CMC SST为检索的SSS提供最佳的整体性能。在冷水中,SSS取回的敏感性以及因此各种辅助输入场之间的性能差异会增加。

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