Evaluating Tropical Cyclones Simulated by a Global Convection-Permitting Model
Global models traditionally have low resolutions (~15 km) that impede accurate tropical cyclone intensity forecasts. Recent breakthroughs in global convection-permitting numerical weather prediction models have led to cost-efficient, high-resolution forecasts at the global scale. While numerous studies have examined the predictive skill of tropical cyclones in coarse resolution global models, few have investigated their predictive skill at convection-permitting resolutions. For this study, a 20-day long simulation was produced with the Model for Prediction Across Scales (MPAS) using a globally uniform 4-km resolution mesh. The tropical cyclones simulated in eight tropical cyclone basins during this period were compared against observations. Specifically, the GFDL Vortex Tracker was adapted to this high-resolution run to determine MPAS’s forecast skill with regard to tropical cyclone track and intensity. It was found that MPAS tends to spin up more cyclones than observed (4 hits, 2 misses, and 18 false alarms). While reproducing the intensity of Typhoon Son-Tinh (2012), the model tends to overintensify the cyclones it captured in the Indian Ocean. These biases indicate that MPAS needs to be improved to provide accurate tropical cyclone forecasts at convection-permitting resolution.
Fox, K. Ryder, Falko Judt, and David Ahijevych, 2018: Evaluating Tropical Cyclones Simulated by a Global Convection-Permitting Model. Third Symposium on Multi-Scale Predictability: Data-model Integration and Uncertainty Quantification for Climate and Earth System Monitoring and Prediction, 98th AMS Annual Meeting. Austin, TX. Amer. Meteor. Soc.
Fox, K. Ryder, Falko Judt, and David Ahijevych, 2018: Evaluating Tropical Cyclones Simulated by a Global Convection-Permitting Model. 33rd Conference on Hurricanes and Tropical Meteorology, Ponte Vedra, FL. Amer. Meteor. Soc.