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- Title
Impact of Assimilating Himawari‐8‐Derived Layered Precipitable Water With Varying Cumulus and Microphysics Parameterization Schemes on the Simulation of Typhoon Hato.
- Authors
Lu, Jiazheng; Feng, Tao; Li, Jun; Cai, Zelin; Xu, Xunjian; Li, Li; Li, Jinlong
- Abstract
Understanding moisture information ahead of tropical cyclone (TC) convection is very important for predicting TC track, intensity, and precipitation. The advanced Himawari imager onboard the Japanese Himawari‐8/‐9 satellite can provide high spatial and temporal resolution moisture information. Three‐layered precipitable water (LPW) with its three water vapor absorption infrared bands can be assimilated to generate better understanding and prediction of TC evolution. The impacts of LPW assimilation in the Weather Research and Forecasting model with nine combinations of physical parameterization schemes, including three cumulus parameterization (CP) and three microphysics parameterization (MP) schemes on TC prediction, have been comprehensively analyzed using Typhoon Hato as a case study. The results indicate that LPW assimilation reduces the average track error and speed up TC movement by better adjustment of the atmospheric circulation fields via changing the vertical structure of moisture and thermal profile. The track forecasts retain sensitivity to CP schemes after LPW assimilation. Also, LPW assimilation improves TC intensity prediction because the latent heat release process is accurately adjusted. It has been revealed that LPW assimilation can weaken the intensity sensitivity to MP schemes more than to CP schemes. Skill scores were used to evaluate precipitation forecasts after Hato's landfall. The results indicate that heavy precipitation forecasts are more sensitive to the choice of MP schemes. After LPW assimilation, the equitable threat scores among different results become similar and all forecast skills are increased. In addition, group statistic results with different initial time show the same conclusions. Key Points: Assimilation of LPW products shows improvement on tropical cyclone (TC) prediction regardless of which parameterization scheme is appliedTC prediction incorporating the Kain‐Frish (KF) scheme shows the most improvement when LPWs are assimilated in this caseCombining LPW assimilation with an appropriate physical parameterization scheme has a positive impact on TC prediction
- Subjects
METEOROLOGICAL precipitation; PRECIPITABLE water; ATMOSPHERIC physics; HYDROLOGIC cycle; ATMOSPHERIC water vapor
- Publication
Journal of Geophysical Research. Atmospheres, 2019, Vol 124, Issue 6, p3050
- ISSN
2169-897X
- Publication type
Article
- DOI
10.1029/2018JD029364