Updates on CYGNSS Ocean Surface Wind Validation in the Tropics
Updates on CYGNSS Ocean Surface Wind Validation in the Tropics
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CYGNSS 热带地区海洋表面风验证的更新
DOI：
10.1175/jtech-d-21-0168.1
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发表时间：
2022
影响因子：
2.2
通讯作者：
C. Ruf
中科院分区：
文献类型：
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作者：
S. Asharaf;D. Posselt;Faozi Said;C. Ruf
基于全球导航卫星系统反射计（GNSS-R）的风场反演技术利用从海洋表面向前散射的全球定位系统（GPS）信号，并且可以潜在地在所有天气条件下工作。概述了气旋全球导航卫星系统（CYGNSS）2级地面风产品的最新进展。为此，四个公开发布的CYGNSS表面风产品-科学数据记录（SDR）v2.1，SDR v3.0，气候数据记录（CDR）v1.1，和科学风速产品NOAA v1.1，对热带浮标阵列的高质量数据进行了定量验证。最新发布的CYGNSS风力产品（例如，CDR v1.1，SDR v3.0，NOAA v1.1），与这些热带浮标数据相比，显着优于SDR v2.1。此外，这些产品之间的不确定性被发现小于2 m s−1均方根差，满足美国宇航局科学使命1级不确定性要求风速低于20 m s−1。在不同的降水条件下，在低风速，并在大尺度对流区的CYGNSS风的质量进一步评估。结果表明，降雨的存在似乎会导致轻微的正风速偏差在所有CYGNSS数据。尽管如此，对于最近发布的CYGNSS风力产品以及具有降水深对流的区域的CYGNSS数据，结果是令人鼓舞的。总体比较表明，从旧版本到任何新数据集时，风速质量和样本量都有显着改善。
Global Navigation Satellite System Reflectometry (GNSS-R) based wind retrieval techniques use the global positioning system (GPS) signals scattered from the ocean surface in the forward direction, and can potentially work in all weather conditions. An overview of recent progress made in the Cyclone Global Navigation Satellite System (CYGNSS) Level-2 surface wind products is given. To this end, four publicly released CYGNSS surface wind products- Science Data Record (SDR) v2.1, SDR v3.0, Climate Data Record (CDR) v1.1, and science wind speed product NOAA v1.1, are validated quantitatively against high quality data from tropical buoy arrays. The latest released CYGNSS wind products (e.g., CDR v1.1, SDR v3.0, NOAA v1.1), as compared with these tropical buoy data, significantly outperform the SDR v2.1. Moreover, the uncertainty among these products is found to be less than 2 m s−1 root mean squared difference, meeting the NASA science mission Level-1 uncertainty requirement for wind speeds below 20 m s−1. The quality of the CYGNSS wind is further assessed under different precipitation conditions in low winds, and in large-scale convective regions. Results show that the presence of rain appears to cause a slight positive wind speed bias in all CYGNSS data. Nonetheless, the outcomes are encouraging for the recently released CYGNSS wind products in general, and for CYGNSS data in regions with precipitating deep convection. The overall comparison indicates a significant improvement in wind speed quality and sample size when going from the older version to any of the newer datasets.