Heavy Rainfall Duration Bias in Dynamical Downscaling and Its Related Synoptic Patterns in Summertime Asian Monsoon

Author:

Tamaki Yuta1,Inatsu Masaru2,Nguyen-Le Dzung3,Yamada Tomohito J.3

Affiliation:

1. Graduate School of Science, Hokkaido University, Sapporo, Japan

2. Faculty of Science, Hokkaido University, Sapporo, Japan

3. Faculty of Engineering, Hokkaido University, Sapporo, Japan

Abstract

AbstractDynamical downscaling (DDS) was conducted over Japan by using a regional atmospheric model with reanalysis data to investigate the rainfall duration bias over Kyushu, Japan, in July and August from 2006 to 2015. The model results showed that DDS had a positive rainfall duration bias over Kyushu and a dry bias over almost all of Kyushu, which were emphasized for extreme rainfall events. Investigated was the rainfall duration bias for heavy rainfall days, accompanied by synoptic-scale forcing, in which daily precipitation exceeded 30 mm day−1 and covered over 20% of the Kyushu area. Heavy rainfall days were sampled from observed rainfall data that were based on rain gauge and radar observations. A set of daily climatic variables of horizontal wind and equivalent potential temperature at 850 hPa and sea level pressure, around southwestern Japan, corresponding to the sampled dates, was selected to conduct a self-organizing map (SOM) and K-means method. The SOM and K-means method objectively classified three synoptic patterns related to heavy rainfall over Kyushu: strong monsoon, weak monsoon, and typhoon patterns. Rainfall duration had a positive bias in western Kyushu for the strong monsoon pattern and a positive bias in southern and east-coast Kyushu for the typhoon pattern, whereas there was little rainfall duration bias in the weak monsoon pattern. The bias for the typhoon pattern was related to rainfall events with a strong rainfall peak. The results suggest that bias correction for rainfall duration would be required for accurately estimating direct runoff in a catchment area in addition to the precipitation amount.

Funder

Social Implementation Program on Climate Change Adaptation Technology

Publisher

American Meteorological Society

Subject

Atmospheric Science

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