Objective identification of tropical cyclone‐induced remote moisture transport using digraphs

Abstract

Tropical cyclone (TC)–induced remote moisture transport is the fundamental cause of TC‐induced remote precipitation. However, despite increasing attention having been paid to TC‐induced remote moisture transport over the past few decades, a method for the objective identification of TC remote moisture transport remains lacking, which is crucial to understanding the complex rainfall mechanisms associated with TC‐induced remote moisture transport over recent decades. We set out to solve this issue in the present study by using a series of newly developed processing algorithms. Firstly, we identified vertically integrated water vapor transport (IVT) pathways using spatially smoothed moving window quantiles, and then used the maximum gradient method to segment IVT clusters from pathways. Relationship digraphs were constructed for IVT clusters to flexibly interpret the spatiotemporal merging and splitting processes among them. Finally, TC clusters (TCCs) and TC remote Clusters (TRCs) were identified in succession based on the TC tracks and diagraphs of IVT clusters. Applications of these processing algorithms showed that the TCCs and TRCs at the same timestep can be identified successfully by applying our method. The generality of the objective identification method was validated using data covering four decades. Our algorithms revealed discontinuous and uneven moisture transport, especially those associated with TCs, which benefits studies of remote rainfall associated with TCs. Furthermore, it facilitates the construction of IVT pathway and cluster datasets covering the past several decades, which can be used for analyzing related characteristics and thereby revealing possible physical mechanisms underlying the nature of TRCs.This article is protected by copyright. All rights reserved.