ALLOCATION DIFFERENCE ANALYSES OF WATER SUBSTANCES DURING TYPHOON LANDING PROCESSES
doi: 10.16555/j.1006-8775.2018.03.004
- Rev Recd Date: 2018-06-15
Abstract: Based on a successful simulation of Typhoon Haikui (2012) using WRF (Weather Research & Forecasting) model with the WSM6 microphysics scheme, a high-resolution model output is presented and analyzed in this study. To understand the cause of the average gridded rainfall stability and increases after Haikui’s landfall, this research examines the fields of the physical terms as well as the vapor and condensate distributions and budgets, including their respective changes during the landing process. The environmental vapor supply following the typhoon landfall has no significant difference from that before the landfall. Although Haikui’s secondary circulation weakens, this circulation is not conducive to typhoon rainfall stability or increases, although the amounts of the six kinds of water substances (vapor, cloud water, cloud ice, snow, rain, and graupel) increase in the outer region of the typhoon. This reallocation of water substances is essential to the maintenance of rainfall. The six kinds of water substances are classified as vapor, clouds (cloud water and ice) and precipitation (snow, rain, and graupel) to diagnose their budgets. This sorting reveals that the changes in the budgets of different kinds of water substances, caused by the reduced mixing ratios of snow and ice, the water consumption of clouds, and the transformation of graupel, induce increased concentrations of precipitation fallout, which occur closer to the ground after typhoon landfall. In addition, this pattern is an efficient way for Haikui’s rainfall to remain stable after its landfall. Thus, the allocation and budget analyses of water substances are meaningful when forecasting the typhoon rainfall stability and increases after landfall.
Citation: | LIU Ji-chen, ZHONG Wei, LIU Shuang, et al. ALLOCATION DIFFERENCE ANALYSES OF WATER SUBSTANCES DURING TYPHOON LANDING PROCESSES [J]. Journal of Tropical Meteorology, 2018, 24(3): 300-313, https://doi.org/10.16555/j.1006-8775.2018.03.004 |