Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

Tropical Cyclones in High-Resolution Community Atmosphere Model version 5: Evaluation for Western North Pacific

Tuesday, December 11, 2018 - 13:40
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Climate models at high resolution (~25 km horizontal grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus promising the investigation of these high-impact extreme events under present and future climates. On the global scale, simulations with the Community Atmosphere Model version 5 (CAM5) present a reasonable TC climatology under prescribed present-day (1980-2005) sea surface temperature (SST) and greenhouse gas (GHG) forcing. However, for the disaster-prone western North Pacific (WNP) region, biases in TC genesis frequency and location persist across various configurations. The biases under-represent the basin’s share in global TC climatology, complicating the fidelity of future projections. This study addresses these model biases in WNP by evaluating the large-scale environmental controls of TC genesis in CAM5 with two aerosol configurations. Across the two configurations, the lack of mid-level moisture is consistently identified as the leading cause of the deficit in simulated WNP TC genesis. This lack of mid-level moisture in WNP TC main develop region is potentially linked to previously identified deficits in Pacific warm pool precipitation at high horizontal resolution in CAM5, as well as biases in the East Asian Summer Monsoon circulation and moisture transport. Additional CAM5 simulation experiments will explore the effect of moisture nudging on the large-scale environment and subsequent TC genesis, tracks, and intensity development. For a chosen year, simulations covering WNP peak TC season (July - October) under otherwise identical forcing (SST, GHG etc.) will be run with and without nudging the specific humidity field towards MERRA-2 reanalysis. The insight into the biases of basin-scale TC simulation under the present climate and potential improvements will help reduce the uncertainty in future-climate projections, in the interest of disaster risk management.

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