CYGNSS Ocean Surface Wind Validation in the Tropics

Author:

Asharaf Shakeel12,Waliser Duane E.2,Posselt Derek J.2,Ruf Christopher S.3,Zhang Chidong4,Putra Agie W.5

Affiliation:

1. a Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, California

2. b Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

3. c University of Michigan, Ann Arbor, Michigan

4. d NOAA/Pacific Marine Environmental Laboratory, Seattle, Washington

5. e Agency of Meteorology, Climatology, and Geophysics, Jakarta, Indonesia

Abstract

AbstractSurface wind plays a crucial role in many local/regional weather and climate processes, especially through the exchanges of energy, mass, and momentum across Earth’s surface. However, there is a lack of consistent observations with continuous coverage over the global tropical ocean. To fill this gap, the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission was launched in December 2016, consisting of a constellation of eight small spacecrafts that remotely sense near-surface wind speed over the tropical and subtropical oceans with relatively high sampling rates both temporally and spatially. This current study uses data obtained from the Tropical Moored Buoy Arrays to quantitatively characterize and validate the CYGNSS derived winds over the tropical Indian, Pacific, and Atlantic Oceans. The validation results show that the uncertainty in CYGNSS wind speed, as compared with these tropical buoy data, is less than 2 m s−1 root-mean-square 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, and in convective cold-pool events, identified using buoy rain and temperature data. Results show that CYGNSS winds compare fairly well with buoy observations in the presence of rain, though at low wind speeds the presence of rain appears to cause a slight positive wind speed bias in the CYGNSS data. The comparison indicates the potential utility of the CYGNSS surface wind product, which in turn may help to unravel the complexities of air–sea interaction in regions that are relatively undersampled by other observing platforms.

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

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