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Article

A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO

1
University of Alabama in Huntsville, Huntsville, AL 35805, USA
2
NASA Marshall Space Flight Center, Huntsville, AL 35812, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(8), 1243; https://doi.org/10.3390/rs12081243
Received: 27 February 2020 / Revised: 28 March 2020 / Accepted: 10 April 2020 / Published: 14 April 2020
(This article belongs to the Special Issue GPS/GNSS for Earth Science and Applications)
The National Aeronautics and Space Administration (NASA) Cyclone Global Navigation Satellite System (CYGNSS) mission was launched in December 2016. CYGNSS provides ocean surface wind speed retrieval along specular reflection tracks at an interval resolution of approximately 25 km. With a median revisit time of 2.8 h covering a ±35° latitude, CYGNSS can provide more frequent and accurate measurements of surface wind over the tropical oceans under heavy precipitation, especially within tropical cyclone cores and deep convection regions, than traditional scatterometers. In this study, CYGNSS v2.1 Level 2 wind speed data were assimilated into the Weather Research and Forecasting (WRF) model using the WRF Data Assimilation (WRFDA) system with hybrid 3- and 4-dimensional variational ensemble technology. Case studies were conducted to examine the impact of the CYGNSS data on forecasts of tropical cyclone (TC) Irving and a westerly wind burst (WWB) during the Madden–Julian oscillation (MJO) event over the Indian Ocean in early January 2018. The results indicate a positive impact of the CYGNSS data on the wind field. However, the impact from the CYGNSS data decreases rapidly within 4 h after data assimilation. Also, the influence of CYGNSS data only on precipitation forecast is found to be limited. The assimilation of CYGNSS data was further explored with an additional experiment in which CYGNSS data was combined with Global Precipitation Mission (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) hourly precipitation and Advanced Scatterometer (ASCAT) wind vector and were assimilated into the WRF model. A significant positive impact was found on the tropical cyclone intensity and track forecasts. The short-term forecast of wind and precipitation fields were also improved for both TC Irving and the WWB event when the combined satellite data was assimilated. View Full-Text
Keywords: CYGNSS; data assimilation; tropical cyclone; tropical convection; MJO CYGNSS; data assimilation; tropical cyclone; tropical convection; MJO
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MDPI and ACS Style

Li, X.; Mecikalski, J.R.; Lang, T.J. A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO. Remote Sens. 2020, 12, 1243. https://doi.org/10.3390/rs12081243

AMA Style

Li X, Mecikalski JR, Lang TJ. A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO. Remote Sensing. 2020; 12(8):1243. https://doi.org/10.3390/rs12081243

Chicago/Turabian Style

Li, Xuanli, John R. Mecikalski, and Timothy J. Lang 2020. "A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO" Remote Sensing 12, no. 8: 1243. https://doi.org/10.3390/rs12081243

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