An evaluation of tropical cyclone forecast in the Southwest Indian Ocean basin with AROME‐Indian Ocean convection‐permitting numerical weather predicting system

Olivier Bousquet,Sylvie Malardel,Soline Bielli,Laure Raynaud,Ghislain Faure,David Barbary,Selim Kebir

doi:10.1002/asl.950

Abstract

AbstractIn order to contribute to ongoing efforts on tropical cyclone (TC) forecasting, a new, convection‐permitting, limited‐area coupled model called AROME‐Indian Ocean (AROME‐IO) was deployed in the Southwest Indian Ocean basin (SWIO) in April 2016. The skill of this numerical weather predicting system for TC prediction is evaluated against its coupling model (European Center for Medium Range Weather Forecasting‐Integrated Forecasting System [ECMWF‐IFS]) using 120‐hr reforecasts of 11 major storms that developed in this area over TC seasons 2017–2018 and 2018–2019. Results show that AROME‐IO generally provides significantly better performance than IFS for intensity (maximum wind) and structure (wind extensions, radius of maximum wind) forecasts at all lead times, with similar performance in terms of trajectories. The performance of a prototype, 12‐member ensemble prediction system (EPS), of AROME‐IO is also evaluated on the case of TC Fakir (April 2018), a storm characterized by an extremely low predictability in global deterministic and ensemble models. AROME‐IO EPS is shown to significantly improve the predictability of the system with two scenarios being produced: a most probable one (~66%), which follows the prediction of AROME‐IO, and a second one (~33%) that closely matches reality.

Highlights

Socioeconomic losses resulting from landfalling tropical cyclones (TC) have increased sharply worldwide over the last decades (Pielke Jr. et al, 2008; Zhang et al, 2009) due to the ever-increasing population and expending social development (Pielke Jr. and Landsea, 1998)
The performance of AROME-IO for TC forecasting was evaluated from 120-hr reforecasts of 11 storms that developed in this basin during TC seasons 2017–2018 and 2018–2019
The skill of the model for track, intensity, and structure forecasts was compared against the performance of its coupling model IFS (~9-km resolution) using Regional Specialized Meteorological Center (RSMC) La Reunion BT data as ground-truth

Summary

Introduction

Socioeconomic losses resulting from landfalling tropical cyclones (TC) have increased sharply worldwide over the last decades (Pielke Jr. et al, 2008; Zhang et al, 2009) due to the ever-increasing population and expending social development (Pielke Jr. and Landsea, 1998). Among these five NWP systems, the Southwest Indian Ocean (SWIO) configuration, called AROME Indian Ocean (AROME-IO), is considered as the flagship of all AROME overseas models and has been used since 2012 to test, and evaluate, new developments aiming at improving TC prediction (Bousquet et al, 2014), in close collaboration with the Tropical Cyclone Regional Specialized Meteorological Center (RSMC) La Reunion.

Results

Conclusion