Recent advances in research and forecasting of tropical cyclone rainfall

Kevin Cheung*, Zifeng Yu, Russell L. Elsberry, Michael Bell, Haiyan Jiang, Tsz Cheung Lee, Kuo-Chen Lu, Yoshinori Oikawa, Liangbo Qi, Robert F. Rogers, Kazuhisa Tsuboki

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In preparation for the Fourth International Workshop on Tropical Cyclone Landfall Processes (IWTCLP-IV), a summary of recent research studies and the forecasting challenges of tropical cyclone (TC) rainfall has been prepared. The extreme rainfall accumulations in Hurricane Harvey (2017) near Houston, Texas and Typhoon Damrey (2017) in southern Vietnam are examples of the TC rainfall forecasting challenges. Some progress is being made in understanding the internal rainfall dynamics via case studies. Environmental effects such as vertical wind shear and terrain-induced rainfall have been studied, as well as the rainfall relationships with TC intensity and structure. Numerical model predictions of TC-related rainfall have been improved via data assimilation, microphysics representation, improved resolution, and ensemble quantitative precipitation forecast techniques. Some attempts have been made to improve the verification techniques as well. A basic forecast challenge for TC-related rainfall is monitoring the existing rainfall distribution via satellite or coastal radars, or from over-land rain gauges. Forecasters also need assistance in understanding how seemingly similar landfall locations relative to the TC experience different rainfall distributions. In addition, forecasters must cope with anomalous TC activity and landfall distributions in response to various environmental effects.

    Original languageEnglish
    Pages (from-to)106-127
    Number of pages22
    JournalTropical cyclone research and review
    Volume7
    Issue number2
    DOIs
    Publication statusPublished - 15 May 2018

    Keywords

    • tropical cyclone
    • landfall
    • rainfall
    • nowcast
    • forecast verification

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