Understanding the impact of assimilating FORMOSAT-7/COSMIC-2 radio occultation refractivity on tropical cyclone genesis: Observing system simulation experiments using Hurricane Gordon (2006) as a case study

Shu Chih Yang, Shu Hua Chen, Chih Chien Chang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Studies have shown that assimilating the radio occultation (RO) observations, including those from the FORMOSAT-3/COSMIC (constellation observing systems for meteorology, ionosphere, and climate) (FS3-C), provides positive impacts on tropical cyclone (TC) forecasts. The FS3-C's successor, the FORMOSAT-7/COSMIC-2 (FS7-C2), provides denser spatial data coverage over the Tropics and Subtropics, where severe weather systems often occur. This study investigates the impact of FS7-C2 refractivity profiles on the prediction of TC genesis. A quick observing system simulation experiment is conducted for the period when Hurricanes Helene and Gordon (2006) occurred over the North Atlantic Ocean using a regional ensemble data assimilation system. Though assimilating FS3-C or FS7-C2 ROs successfully reproduces Helene's development, assimilating FS7-C2 ROs better captures the genesis and development of Gordon with abundant moisture and vorticity in Gordon's core region, providing conditions favorable for the development of deep convection. A minimum area-mean total precipitable water vapor of 54 mm, as well as the existence of mid-level cyclonic vorticity (e.g., 500 hPa), at the storm core region in the initial condition is required for forecasting Gordon's genesis. Also, the assimilation of FS7-C2 ROs in our experiments reduces the 500 hPa geopotential error by 22% and improves probabilistic quantitative precipitation forecast compared with assimilating FS3-C ROs. Two sensitivity tests are conducted to evaluate the impact of low-level negatively biased FS7-C2 RO profiles and the removal of FS7-C2 data below 3 km on Gordon's genesis. The former test does not degrade Gordon's genesis forecast skills due to a dipole error correlation between the background ROs and the moisture field over an observed RO profile near Gordon. The latter test does degrade Gordon's forecast skills but is still better than the assimilation of FS3-C ROs since the features of low-level moisture and mid-level vorticity are preserved to some extent.

Original languageEnglish
Pages (from-to)1293-1318
Number of pages26
JournalQuarterly Journal of the Royal Meteorological Society
Volume149
Issue number753
DOIs
StatePublished - 1 Apr 2023

Keywords

  • GNSS-RO
  • data assimilation
  • ensemble forecast
  • predictability
  • probabilistic quantitative precipitation forecast (PQPF)
  • quick OSSE
  • tropical cyclone genesis

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