5.1 Impact of a Proposed Constellation of Radio Occultation Data on Tropical Cyclone Forecasts

Tuesday, 9 January 2018: 10:30 AM
Room 14 (ACC) (Austin, Texas)
Michael Mueller, Univ. of Colorado, Boulder, CO; and A. C. Kren, L. Cucurull, R. Atlas, R. N. Hoffman, G. Ge, and T. R. Peevey

In this study, we conduct an observation system simulation experiment (OSSE) to investigate the impact of a constellation of RO satellites, where RO observations are simulated with the same orbit configuration expected from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) mission. We evaluate the impact of RO on tropical cyclone forecasts in a global numerical weather prediction model. Specifically, the NCEP’s Global Data Assimilation System and Global Forecast System (GDAS/GFS) assimilates simulated observations over a 61-day period (1 August – 30 September) based on the NASA GMAO GEOS-5 Nature Run (G5NR).

We evaluate experiments from 15 August – 30 September and the first two weeks are used for the spin-up period. For each experiment, 168-hr GFS forecasts are generated once per day at 00Z, with a total of 47 forecasts. To test the impact of RO, we conduct two experiments: 1. A control experiment assimilating simulated surface pressure, temperature, specific humidity, u- and v-wind, and satellite radiance; and 2. An RO experiment adding simulated RO observations to the control configuration.

We use tropical cyclone best tracks derived from G5NR to evaluate how the proposed RO constellation impacted the forecasts. Both basin-scale and case study approaches are used. Track and intensity errors are calculated for each forecast and tropical cyclone in the Atlantic, East Pacific, and West Pacific basins. Basin-averaged statistics are presented. Forecasts for two landfalling hurricanes in the Gulf of Mexico are investigated further with an emphasis on the associated convective environment conducive for tornadoes. Preliminary results suggest improvements in track forecasts and mixed results for intensity forecasts during one of the landfalling tropical cyclones.

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