Evaluation for Characteristics of Tropical Cyclone Induced Heavy Rainfall over the Sub-basins in The Central Hokkaido, Northern Japan by 5-km Large Ensemble Experiments

Tsuyoshi Hoshino,Tomohito J Yamada,Hiroaki Kawase

doi:10.3390/atmos11050435

Tsuyoshi Hoshino, Tomohito J Yamada + Show 1 more

Open Access

https://doi.org/10.3390/atmos11050435

Copy DOI

Journal: Atmosphere	Publication Date: Apr 25, 2020
Citations: 22	License type: CC BY 4.0

Affiliation: Hokkaido University, Japan Meteorological Agency

Abstract

Previous studies have shown that the acceleration of global warming will increase the intensity of rainfall induced by tropical cyclones (TCs) (hereinafter referred to as “TC-induced rainfall”). TC-induced rainfall is affected by TC position and topography (slope shape and direction). Thus, TC-induced rainfall is expected to vary by sub-basin due to varying topographies. However, these relationships have not been explained, as historical TCs, which occurred several decades earlier, do not exhaustively encompass all TC positions that could potentially affect each basin. We used large ensemble regional climate model experiments with 5 km grid spacing, which enabled us to prepare a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins. We quantified the characteristics of TC-induced rainfall (rainfall volume, relationship between TC position and rainfall intensity, and contribution of TC intensity on rainfall) over four sub-basins in the Tokachi River basin, central Hokkaido, northern Japan. The results reveal differences in TC-induced rainfall characteristics between the sub-basins. In addition, the large ensemble data under a future climate scenario were used to evaluate future changes in the characteristics of TC-induced rainfall for each sub-basin.

Highlights

The acceleration of global warming will affect the frequency and intensity of extreme weather events such as tropical cyclones (TCs)
We prepared large ensemble regional climate model experiments with higher grid spacing than RCM experiment in d4PDF using the Non hydrostatic Regional Climate Model (NHRCM) [15] which enabled us to arrive at a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins
72 h 72 rainfall volume shows shows that the d4PDF-5km from the past experiment has enough reproducibility to be able to predict that the d4PDF-5km from the past experiment has enough reproducibility to be able to predict rainfall rainfall volume

Summary

Introduction

The acceleration of global warming will affect the frequency and intensity of extreme weather events such as tropical cyclones (TCs). Endo et al [13] examined changes in the annual maximum daily rainfall (Rx1d) based on d4PDF and showed that Rx1d will increase in entire East Asia, under future climatic conditions with notable increases in rainfall across northern Japan. We prepared large ensemble regional climate model experiments with higher grid spacing than RCM experiment in d4PDF using the Non hydrostatic Regional Climate Model (NHRCM) [15] which enabled us to arrive at a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins.

Target River Basins

Simulated and Observed Rainfall Data

Tropical Cyclone Tracking Data

Results

Future Change of TC-induced Rainfall

Discussion