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A new procedure for estimating observation errors in AMSU data and its application to retrieval

机译:一种估计AMSU数据中观测误差的新程序及其在检索中的应用

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An accurate estimate of observation errors is crucial to the retrieval of atmospheric profiles from satellite data using a variational method. In practice, observation errors, both systematic and random, are often estimated from the difference betweensatellite observations and simulated satellite observations obtained from a radiative-transfer operator with a 12 h forecast as its input. Observation errors estimated by this approach may be contaminated by errors in the 12 h forecast. This work describes a practical way to eliminate the 12 h forecast error and improve the estimate of the observation error in the Advanced Microwave Sounding Unit (AMSU) data. Following the philosophy of the National Meteorological Center (NMC) method (that derives thestatistics of forecast error from the differences between pairs of forecasts at disparate ranges valid at the same time), in this study the pairs of forecasts at different ranges in the NMC method are first converted to brightness temperatures in the AMSU channels by a radiative-transfer operator. The 12 h forecast errors are then determined from the representations of these forecasts in radiance space spanned by the AMSU channels. Since most AMSU channels have beam position-dependent systematic observation errors, the procedure further takes into account this dependence by performing the statistics separately for sub-groups of data in each AMSU channel with different beam positions. In a case-study, after eliminating the 12 h forecast error obtained by this procedure from the total estimated observation error, the remaining random error of the satellite observation is shown to be smaller than the background error (provided by 12 h forecasts of a numerical weather-prediction model) in most of the AMSUtemperature sounding channels. Using the error-corrected AMSU data in these channels, a retrieval experiment using a one-dimensional variational scheme shows an improvement of 0.2-0.4 K over the background error in the retrieved temperature profiles above 780 hPa.
机译:观测误差的准确估计对于使用变分方法从卫星数据中获取大气廓线至关重要。在实践中,经常根据卫星观测值与模拟辐射观测值之间的差异来估算系统误差和随机观测误差,这些辐射值是从以12 h预报作为输入的辐射传输算子获得的。用这种方法估算的观测误差可能被12小时预报中的误差所污染。这项工作描述了一种实用的方法,可以消除12小时预报误差并改善高级微波探测单元(AMSU)数据中观测误差的估计。遵循国家气象中心(NMC)方法的原理(该方法从同时有效的不同范围的预测对之间的差异得出预测误差的统计量),本研究采用NMC方法的不同范围的预测对首先由辐射传递算子将其转换为AMSU通道中的亮度温度。然后根据这些预测在AMSU通道跨越的辐射空间中的表示来确定12 h预测误差。由于大多数AMSU通道具有与波束位置有关的系统观测误差,因此该过程通​​过对每个AMSU通道中具有不同波束位置的数据子组分别执行统计,进一步考虑了这种依赖性。在案例研究中,从总估计观测误差中消除了通过此程序获得的12小时预测误差后,卫星观测的剩余随机误差显示为小于背景误差(由数值的12小时预测提供)气象预报模型)在大多数AMSU温度探测通道中。在这些通道中使用经过误差校正的AMSU数据,使用一维变分方案进行的检索实验显示,在780 hPa以上的检索温度曲线中,背景误差比背景误差提高了0.2-0.4K。

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