Impact of Refractivity Profiles from a Proposed GNSS-RO Constellation on Tropical Cyclone Forecasts in a Global Modeling System

Author:

Mueller Michael J.1ORCID,Kren Andrew C.2,Cucurull Lidia3,Casey Sean P. F.2,Hoffman Ross N.2,Atlas Robert3,Peevey Tanya R.4

Affiliation:

1. a University of Colorado Boulder, Cooperative Institute for Research in the Environmental Sciences, and NOAA/OAR/ESRL/Global Systems Laboratory, Boulder, Colorado

2. b Cooperative Institute for Marine and Atmospheric Studies, and NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

3. c NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

4. d Colorado State University, Cooperative Institute for Research in the Atmosphere, and NOAA/OAR/ESRL/Global Systems Laboratory, Boulder, Colorado

Abstract

Abstract A global observing system simulation experiment (OSSE) was used to assess the potential impact of a proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellation on tropical cyclone (TC) track, maximum 10-m wind speed (Vmax), and integrated kinetic energy (IKE) forecasts. The OSSE system was based on the 7-km NASA nature run and simulated RO refractivity determined by the spatial distribution of observations from the original planned (i.e., including both equatorial and polar orbits) Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2). Data were assimilated using the NOAA operational weather analysis and forecasting system. Three experiments generated global TC track, Vmax, and IKE forecasts over 6 weeks of the North Atlantic hurricane season in the North Atlantic, east Pacific, and west Pacific basins. Confidence in our results was bolstered because track forecast errors were similar to those of official National Hurricane Center forecasts, and Vmax errors and IKE errors showed similar results. GNSS-RO assimilation did not significantly impact global track forecasts, but did slightly degrade Vmax and IKE forecasts in the first 30–60 h of lead time. Global forecast error statistics show adding or excluding explicit random errors to RO profiles made little difference to forecasts. There was large forecast-to-forecast variability in RO impact. For two cases studied in depth, track and Vmax improvements and degradations were traced backward through the previous 24 h of assimilation cycles. The largest Vmax degradation was traced to particularly good control analyses rather than poor analyses caused by GNSS-RO.

Funder

University of Colorado Boulder, Cooperative Institute for Research in the Environmental Sciences, and NOAA/OAR/ESRL/Global Systems Division, Boulder, Colorado

Publisher

American Meteorological Society

Subject

Atmospheric Science

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