Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm
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DOI：
10.3390/rs10111770
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发表时间：
2018-11
期刊：
影响因子：
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通讯作者：
Ruanyu Zhang;Zhenzhan Wang;K. Hilburn
中科院分区：
文献类型：
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作者：
Ruanyu Zhang;Zhenzhan Wang;K. Hilburn
提出了一种利用18.7 GHz和36.5 GHz微波辐射成像仪（MWRI）垂直和水平极化亮度温度（Tbs）反演热带气旋降水的算法。根据18.7 GHz和36.5 GHz处实测液水吸收系数和理论米氏吸收系数的比值对波束填充效应进行了修正。为了评估该算法的性能，MWRI测量值与六个tc的国家冰雪数据中心（NSIDC）降水进行了匹配。MWRI和NSIDC降雨率的比较结果相对令人鼓舞，平均偏差为- 0.14 mm/h，总体均方根误差（RMSE）为1.99 mm/h。对像元间反演结果的比较表明，MWRI反演结果在大多数降雨类别中被限制在合理水平，在10-15 mm/h类别中误差最小为- 1.1%；然而，在最低（0-0.5 mm/h）和最高降雨率（25-30 mm/h）下，最大误差约为- 22%。此外，利用先进微波扫描辐射计对地观测系统（AMSR-E） Tbs反演雨率，评估了算法的灵敏度，平均偏差和RMSE分别为0.90 mm/h和3.11 mm/h。以TC Maon（2011）为例，与降水雷达（PR）在风暴尺度上的观测结果相比，MWRI检索结果低估了6 mm/h以上的降雨率，高估了6 mm/h以下的降雨率。利用遥感系统（RSS）提供的热带降雨测量任务（TRMM）微波成像仪（TMI）降雨资料，对强tc中尺度结构的表征进行了评价，结果表明，这些资料与MWRI检索结果具有较好的一致性。
A rainfall retrieval algorithm for tropical cyclones (TCs) using 18.7 and 36.5 GHz of vertically and horizontally polarized brightness temperatures (Tbs) from the Microwave Radiation Imager (MWRI) is presented. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorption and theoretical Mie absorption coefficients at 18.7 and 36.5 GHz. To assess the performance of this algorithm, MWRI measurements are matched with the National Snow and Ice Data Center (NSIDC) precipitation for six TCs. The comparison between MWRI and NSIDC rain rates is relatively encouraging, with a mean bias of −0.14 mm/h and an overall root-mean-square error (RMSE) of 1.99 mm/h. A comparison of pixel-to-pixel retrievals shows that MWRI retrievals are constrained to reasonable levels for most rain categories, with a minimum error of −1.1% in the 10–15 mm/h category; however, with maximum errors around −22% at the lowest (0–0.5 mm/h) and highest rain rates (25–30 mm/h). Additionally, Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) Tbs are applied to retrieve rain rates to assess the sensitivity of this algorithm, with a mean bias and RMSE of 0.90 mm/h and 3.11 mm/h, respectively. For the case study of TC Maon (2011), MWRI retrievals underestimate rain rates over 6 mm/h and overestimate rain rates below 6 mm/h compared with Precipitation Radar (PR) observations on storm scales. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rainfall data provided by the Remote Sensing Systems (RSS) are applied to assess the representation of mesoscale structures in intense TCs, and they show good consistency with MWRI retrievals.