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Assimilation of Typhoon Wind Field Retrieved from Scatterometer and SAR Based on the Huber Norm Quality Control

机译:基于Huber范数质量控制的散射仪和SAR反演台风风场同化

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Observations of sea surface wind field are critical for typhoon prediction. The scatterometer observation is one of the most important sources of sea surface winds, which provides both wind speed and wind direction information. However, the spatial resolution of scatterometer wind is low. Synthetic Aperture Radar (SAR) can provide a more detailed wind structure of the tropical cyclone. In addition, the cross-polarization observation of SAR can provide more detailed information of high speed wind (>25 m·s ? 1 ) than the scatterometer. Nevertheless, due to the narrow swath of SAR, the number of retrieved sea surface wind data used in the data assimilation is limited, and another limitation of SAR wind observation is that it does not provide true wind direction information. In this paper, the joint assimilation of the Advanced Scatterometer (ASCAT) wind and Sentinel-1 SAR wind was investigated. Another limitation in the current operational typhoon prediction is the inefficient quality control (QC) method used in the data assimilation since a large number of high speed wind observations was rejected by the traditional Gaussian distribution QC. We introduce the Huber norm distribution quality control (QC) into the data assimilation successfully. A numerical simulation experiment of typhoon by Lionrock (2016) is conducted to test the proposed method. The experimental results showed that the new quality control scheme not only greatly increases the availability of wind data in the area of the typhoon center, but also improves the typhoon track prediction, as well as the intensity prediction. The joint assimilation of scatterometer and SAR winds does have a positive impact on the typhoon prediction.
机译:海面风场的观测对于台风预报至关重要。散射仪观测是海面风的最重要来源之一,它提供了风速和风向信息。但是,散射仪风的空间分辨率很低。合成孔径雷达(SAR)可以提供热带气旋的更详细的风结构。另外,与散射仪相比,SAR的交叉极化观测可以提供更详细的高速风信息(> 25 m·s?1)。然而,由于SAR的范围狭窄,在数据同化中使用的检索到的海面风数据的数量是有限的,并且SAR风观测的另一个限制是它不能提供真实的风向信息。本文研究了高级散射仪风和Sentinel-1 SAR风的联合同化。当前运行中的台风预测的另一个限制是数据同化中使用的效率低下的质量控制(QC)方法,因为大量的高速风观测被传统的高斯分布QC拒绝了。我们成功地将Huber范式分布质量控制(QC)引入到数据同化中。 Lionrock(2016)进行了台风数值模拟实验以验证该方法。实验结果表明,新的质量控制方案不仅大大提高了台风中心区域风数据的利用率,而且改善了台风径迹预报和强度预报。散射仪和SAR风的联合吸收确实对台风预报有积极影响。

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