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ORIGINAL RESEARCH article

Front. Earth Sci.
Sec. Atmospheric Science
Volume 12 - 2024 | doi: 10.3389/feart.2024.1418158
This article is part of the Research Topic Tropical Cyclone Modeling and Prediction: Advances in Model Development and Its Applications View all 11 articles

Influence of CyGNSS L2 Wind Data on Tropical Cyclone Analysis and Forecasts in the Coupled HAFS/HYCOM System

Provisionally accepted
Bachir Annane Bachir Annane *Lewis J. Gramer Lewis J. Gramer
  • The Cooperative Institute For Marine And Atmospheric Studies,University of Miami, Miami, United States

The final, formatted version of the article will be published soon.

    This study examines the influence of NASA Cyclone Global Navigation Satellite System (CyGNSS) Level 2-derived 10 m (near-surface) wind speed over the ocean on numerical weather prediction (NWP) analyses and forecasts within the NOAA operational Hurricane Analysis and Forecast System (HAFS). HAFS is coupled with a regional configuration of the HYCOM ocean model. The primary advantages of data from the CyGNSS constellation of satellites in the analysis and prediction of tropical cyclones (TCs) include higher revisit frequency compared to polar-orbiting satellites, and the availability of reliable wind observations over the ocean surface during convective precipitation. In addition, CyGNSS data are available early in the life cycle of TCs when aerial reconnaissance observations are not available. We focus on TCs whose forecasts were initialized when the TC was a tropical storm or depression. In the present study, we find first, that assimilation of CyGNSS near-surface winds improves storm track, intensity, and structure statistics in the analysis and early in the forecast, for many cases. Second, we find that assimilation of CyGNSS observations provides additional insights into the evolution of air-sea interaction in intensifying TCs: In effect, the ocean responds in the coupled model to modifications in the initial 10 m wind field, thereby impacting forecasts of intensity, storm structure, and sea surface height, as demonstrated by two case studies. We also discuss some forecasts where assimilating CYGNSS appears to degrade performance for either intensity or structure.

    Keywords: tropical cyclones, Numerical Weather Prediction, Surface winds, Data impact, data assimilation, Ocean models, heat fluxes, verification

    Received: 16 Apr 2024; Accepted: 02 Sep 2024.

    Copyright: © 2024 Annane and Gramer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Bachir Annane, The Cooperative Institute For Marine And Atmospheric Studies,University of Miami, Miami, United States

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