Effects of local and non-local closure PBL schemes on the simulation of Super Typhoon Mangkhut (2018)

Abstract

With the convection-permitting simulation of Super Typhoon Mangkhut (2018) with a 3 km resolution for 10.5 days using mesoscale numerical model, Weather Research and Forecasting Model Version 4.1 (WRFV4.1), the influences of local closure QNSE planetary boundary layer (PBL) scheme and non-local closure GFS planetary boundary layer scheme on super typhoon Mangkhut are mainly discussed. It is found that in terms of either track or intensity of typhoon, the local closure QNSE scheme is better than the non-local closure GFS scheme. Local and non-local closure PBL schemes have a large influence on both the intensity and the structure of typhoon. The maximum intensity difference of the simulated typhoon is 50 hPa. The intensity of typhoon is closely related to its variations in structure. In the rapid intensification stage, the typhoon simulated by the QNSE scheme has a larger friction velocity, stronger surface latent heat flux, sensible heat flux and vapor flux, related to a higher boundary height and stronger vertical mixing. The latent heat flux and sensible heat flux on the surface conveyed energy upward for the typhoon while the water vapor was transported upward through vertical mixing. While the water vapor condensed, the latent heat was released, which further warmed the typhoon eyewall, strengthening the convection. The stronger winds also intensified the vertical mixing and the warm-core structure, further strengthened the typhoon. The differences in surface layer schemes dominated the differences between the two simulations.

Keywords

typhoon / planetary boundary layer scheme / WRF model

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Acknowledgments

This study was funded by the National Key Research and Development Program of China (No. 2016YFA0602701), the National Natural Science Foundation of China (Grant Nos. 42075064 and 41875168), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies (No. 2020B1212060025), and this work was supported by the Jiangsu Collaborative Innovation Center for Climate Change.

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