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

Abstract

Dynamical 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.

Contribution of Historical Global Warming to Local‐Scale Heavy Precipitation in Western Japan Estimated by Large Ensemble High‐Resolution Simulations

“…The correlation in W‐Kyushu (Figure c) is negative in the south of Kyushu, and the magnitude is lower than that in Figure d. These results are consistent with previous studies using the station data and the Radar/Raingauge‐Analyzed Precipitation product (Oki et al, ; Tamaki et al, ; Tsuguti & Kato, ). Figures and indicate that the impact of global warming on heavy precipitation depends on the synoptic patterns causing heavy precipitation most frequently in each region.…”

Possible hydrological effect of rainfall duration bias in dynamical downscaling

“…To clarify the effect of rainfall duration bias to runoff, we developed a new method to artificially extend rainfall duration while maintaining total rainfall. According to Tamaki et al (2018), the ratio of average rainfall duration between dynamical downscaling data and observed data was 1.41 at the Shimouke dam site (site a in Fig. 1) under strong monsoon patterns, and 1.28 at Iwase dam site (site f in Fig.…”

“…However, it cannot correct a duration bias. Recently, Tamaki et al (2018) suggested that the DDS tended to prolong heavy rainfall events in Kyushu, and the extent of this duration bias was closely related to synoptic weather patterns such as a persistent Baiu rainband across the island and the passage of a typhoon along the island.…”

“…The purpose of this study is to evaluate a possible hydrological effect of rainfall duration bias as shown in Tamaki et al (2018). Since the bias extent depends on synoptic weather patterns, we selected two typical heavy rainfall periods over Kyushu, Japan, in the summertime.…”

“…These two periods are quite typical of heavy rainfall events in Kyushu that are closely related to synoptic weather patterns (See Fig. 5 of Tamaki et al 2018). To clarify the effect of rainfall duration bias to runoff, we developed a new method to artificially extend rainfall duration while maintaining total rainfall.…”