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Radiometry Calibration With High-Resolution Profiles of GPM: Application to ATMS 183-GHz Water Vapor Channels and Comparison Against Reanalysis Profiles

机译:具有GPM高分辨率轮廓的辐射定标:应用于ATMS 183-GHz水蒸气通道并与再分析轮廓进行比较

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The reanalysis data produced by numerical weather prediction (NWP) models and data assimilation have been widely used for radiometer calibration. They provide atmospheric profiles that are necessary for radiative transfer simulation against observation. However, there are biases and uncertainties in the reanalysis due to NWP model mechanism, parameterization, boundary conditions, and assimilation skills. As spaceborne radiometer data have been used in deriving reanalyses, reanalyses are not independent of these radiometers and should be used with caution when used as reference for radiometer calibration. In addition, these data often have coarse spatial (similar to 100 km horizontally) and temporal resolution (similar to 6 h). An independent data set with high resolution can be very useful to diagnose reanalyses and might improve calibration. The Global Precipitation Measurement (GPM) core observatory measures atmospheric water signatures with an onboard radar and radiometer. A GPM data set including atmospheric water vapor, cloud liquid water, and precipitation has been produced based on observational retrieval with high spatiotemporal resolution (similar to 5 km horizontally and 250 m vertically). We have developed a scheme to ingest the high-resolution GPM profiles and perform rigorous simulation and calibration taking into account the radiometer spectral response function, footprint size variation, and antenna pattern. GPM data exhibit different water vapor profiles and weighting functions from reanalyses. It produces overall consistent results of calibration as reanalyses and outperforms them in some aspects. The GPM profiles and our scheme are very useful and will be routinely applied to monitor Advanced Technology Microwave Sounder inflight status.
机译:由数值天气预报(NWP)模型产生的再分析数据和数据同化已广泛用于辐射计校准。它们提供了辐射分布模拟和观测所必需的大气廓线。但是,由于NWP模型机制,参数化,边界条件和同化技巧,在重新分析中存在偏差和不确定性。由于星载辐射计数据已用于进行重新分析,因此重新分析并不独立于这些辐射计,在用作辐射计校准参考时应谨慎使用。此外,这些数据通常具有粗糙的空间(水平方向类似于100 km)和时间分辨率(类似于6 h)。具有高分辨率的独立数据集对于诊断重新分析非常有用,并且可以改善校准。全球降水量测量(GPM)核心天文台使用机载雷达和辐射计测量大气水特征。基于高时空分辨率(类似于水平5 km,垂直250 m)的观测资料,已经产生了包含大气水蒸气,云状液态水和降水的GPM数据集。我们已经开发出一种方案,以吸收高分辨率GPM轮廓并考虑辐射计光谱响应功能,覆盖区尺寸变化和天线方向图进行严格的仿真和校准。 GPM数据通过重新分析显示出不同的水蒸气曲线和加权函数。通过重新分析,它在某些方面能使校准产生总体上一致的结果,并且性能优于它们。 GPM配置文件和我们的方案非常有用,将被常规用于监视Advanced Technology Microwave Sounder的飞行状态。

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