2.4 Evaluating the Impact of Grell-Freitas Convective Parameterization into 2017 Atlantic Hurricane Season Simulations Using FV3GFS

Monday, 7 January 2019: 11:15 AM
North 232C (Phoenix Convention Center - West and North Buildings)
Keren Rosado, NCAS/ESRL/GSD, Boulder, CO; and G. Grell, L. Bernardet, and E. A. Kalina

After The National Oceanic and Atmospheric Administration (NOAA) selected the Finite-Volume on a Cubed-Sphere (FV3) atmosphere dynamical core for The Next Generation Global Prediction System, is now engaged in defining the physics suites to be used in upcoming operational implementations of the FV3-based Global Forecast System (FV3GFS). In this investigation, we tested and evaluated the Grell-Freitas (GF) convective parameterization for the 2017 Atlantic Hurricane Season. Simulations for each tropical cyclone were initiated two times a day, lasting for 120 hours for their entire life cycle. The impact of the GF physics and its interaction with other members of the FV3GFS physics suites will be addressed relative to observations. Preliminary results show that when a tropical cyclone is simulated using FV3GFS with GF convective parameterization, convective precipitation, as well as the total precipitation values are reasonable alongside observed total precipitation satellite derived from NOAA Climate Prediction Center Morphing Technic (CMORPH) and the Climatology-Calibrated Precipitation Analysis (CCPA). These results were also compared alongside with simulations using FV3GFS with the Simplified Arakawa-Schubert (SAS) convective parameterization. Results of the comparison of these two convective parameterizations show that the tropical cyclone simulated using GF convective parameterization has more convective and total precipitation than the simulation using SAS convective parameterization. The analysis of tropical cyclone forecasts in FV3GFS will provide insight and understanding of the mesoscale and synoptic systems that directly impact track and intensity forecasts, therefore advancing the knowledge of mechanisms associated with forecast model errors.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner