首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic
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An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic

机译:一种先进的算法,可以从北极海冰和海水表面的高级微波扫描辐射计数据中检索总大气水蒸气含量

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An advanced algorithm for atmospheric water vapor column (WVC) retrieval from the Advanced Microwave Scanning Radiometer (AMSR) measurements over the Arctic sea ice (SI) and open ocean waters is presented. The algorithm is built on the physical modeling of the brightness temperature (BT) of the microwave radiation of the SI-open ocean-atmosphere system at the AMSR frequencies and polarizations. The BTs are calculated using a data set of the SI, atmospheric, and oceanic parameters changing in the range of their natural variability in the Arctic, and using the SI microwave emission coefficients varied according to the published experimental data. The inverse operator explores neural networks (NNs), trained on an ensemble of modeled BTs. The algorithm is applied both to the AMSR-E and to the AMSR2 measurement data. Validation of the algorithm is performed with radiosonde (r/s) WVC measurements from the four Arctic coastal stations at different SI conditions during 2014-2017. The results of the application of the new algorithm to satellite radiometer measurements are also compared with the Era-Interim reanalysis WVC, as well as with other satellite WVC products, based on the data of the Moderate Resolution Imaging Spectrometer (MODIS) and on the data of the Advanced Microwave Sounding Unit-B (AMSU-B) for 2008 and 2015. To justify the usage of the Era-Interim WVC as a reference data set for the algorithm accuracy estimation in the Arctic area, Era-Interim WVC is also compared with the r/s WVC measurements.
机译:提出了一种高级微波扫描辐射计(AMSR)测量的大气水蒸气柱(WVC)测量的先进算法,并在北极海冰(SI)和开阔的海水中。该算法基于AMSR频率和偏振的Si-Open海洋气氛系统微波辐射的亮度温度(BT)的物理建模。使用Si,大气和海洋参数的数据集来计算BTS在北极的自然可变性范围内变化,并且使用Si微波发射系数根据已发布的实验数据而变化。逆转录员探讨了神经网络(NNS),在建模BTS的集合上培训。算法应用于AMSR-E和AMSR2测量数据。在2014-2017期间,使用来自不同SI条件的四个北极沿海站的无线电(R / S)WVC测量来执行算法的验证。还将新算法应用于卫星辐射计测量的结果,以及基于中频分辨率成像光谱仪(MODIS)和数据的数据,以及其他卫星WVC产品的卫星辐射计测量结果。在2008年和2015年的高级微波探测单元-B(AMSU-B)。为了证明ERA-Interim WVC的使用作为北极区域的算法精度估计的参考数据集,也比较了ERA-Interim WVC使用R / S WVC测量。

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