Statistics of Heavy Rainfall Occurrences in Taiwan

2007 ◽  
Vol 22 (5) ◽  
pp. 981-1002 ◽  
Author(s):  
Ching-Sen Chen ◽  
Yi-Leng Chen ◽  
Che-Ling Liu ◽  
Pay-Liam Lin ◽  
Wan-Chin Chen

Abstract The seasonal variations of heavy rainfall days over Taiwan are analyzed using 6-yr (1997–2002) hourly rainfall data from about 360 rainfall stations, including high-spatial-resolution Automatic Rainfall and Meteorological Telemetry System stations and 25 conventional stations. The seasonal variations and spatial variations of nontyphoon and typhoon heavy rainfall occurrences (i.e., the number of rainfall stations with rainfall rate >15 mm h−1 and daily accumulation >50 mm) are also analyzed. From mid-May to early October, with abundant moisture, potential instability, and the presence of mountainous terrain, nontyphoon heavy rainfall days are frequent (>60%), but only a few stations recorded extremely heavy rainfall (>130 mm day−1) during the passage of synoptic disturbances or the drifting of mesoscale convective systems inland. During the mei-yu season, especially in early June, these events are more widespread than in other seasons. The orographic effects are important in determining the spatial distribution of heavy rainfall occurrences with a pronounced afternoon maximum, especially during the summer months under the southwesterly monsoon flow. After the summer–autumn transition, heavy rainfall days are most frequent over northeastern Taiwan under the northeasterly monsoon flow. Extremely heavy rainfall events (>130 mm day−1) are infrequent during the winter months because of stable atmospheric stratification with a low moisture content. Typhoon heavy rainfall events start in early May and become more frequent in late summer and early autumn. During the analysis period, heavy rainfall occurrences are widespread and dominated by extremely heavy rainfall events (>130 mm day−1) on the windward slopes of the storm circulations. The spatial distribution of typhoon heavy rainfall occurrences depends on the typhoon track with very little diurnal variation.

2011 ◽  
Vol 101 (3) ◽  
pp. 595-610 ◽  
Author(s):  
Ching-Sen Chen ◽  
Yuh-Lang Lin ◽  
Nai-Ning Hsu ◽  
Che-Ling Liu ◽  
Chih-Ying Chen

2013 ◽  
Vol 122 ◽  
pp. 310-335 ◽  
Author(s):  
Ching-Sen Chen ◽  
Yuh-Lang Lin ◽  
Hui-Ting Zeng ◽  
Chih-Ying Chen ◽  
Che-Ling Liu

2005 ◽  
Vol 73 (1-2) ◽  
pp. 101-130 ◽  
Author(s):  
Ching-Sen Chen ◽  
Wan-Chin Chen ◽  
Yi-Leng Chen ◽  
Pay-Liam Lin ◽  
Hsin-Chih Lai

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.


2012 ◽  
Vol 69 (2) ◽  
pp. 521-537 ◽  
Author(s):  
Christopher A. Davis ◽  
Wen-Chau Lee

Abstract The authors analyze the mesoscale structure accompanying two multiday periods of heavy rainfall during the Southwest Monsoon Experiment and the Terrain-Induced Mesoscale Rainfall Experiment conducted over and near Taiwan during May and June 2008. Each period is about 5–6 days long with episodic heavy rainfall events within. These events are shown to correspond primarily to periods when well-defined frontal boundaries are established near the coast. The boundaries are typically 1 km deep or less and feature contrasts of virtual temperature of only 2°–3°C. Yet, owing to the extremely moist condition of the upstream conditionally unstable air, these boundaries appear to exert a profound influence on convection initiation or intensification near the coast. Furthermore, the boundaries, once established, are long lived, possibly reinforced through cool downdrafts and prolonged by the absence of diurnal heating over land in generally cloudy conditions. These boundaries are linked phenomenologically with coastal fronts that occur at higher latitudes.


Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 875
Author(s):  
Li Zhou ◽  
Lin Xu ◽  
Mingcai Lan ◽  
Jingjing Chen

Heavy rainfall events often cause great societal and economic impacts. The prediction ability of traditional extrapolation techniques decreases rapidly with the increase in the lead time. Moreover, deficiencies of high-resolution numerical models and high-frequency data assimilation will increase the prediction uncertainty. To address these shortcomings, based on the hourly precipitation prediction of Global/Regional Assimilation and Prediction System-Cycle of Hourly Assimilation and Forecast (GRAPES-CHAF) and Shanghai Meteorological Service-WRF ADAS Rapid Refresh System (SMS-WARR), we present an improved weighting method of time-lag-ensemble averaging for hourly precipitation forecast which gives more weight to heavy rainfall and can quickly select the optimal ensemble members for forecasting. In addition, by using the cross-magnitude weight (CMW) method, mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (CC), the verification results of hourly precipitation forecast for next six hours in Hunan Province during the 2019 typhoon Bailu case and heavy rainfall events from April to September in 2020 show that the revised forecast method can more accurately capture the characteristics of the hourly short-range precipitation forecast and improve the forecast accuracy and the probability of detection of heavy rainfall.


Author(s):  
Chanil Park ◽  
Seok-Woo Son ◽  
Joowan Kim ◽  
Eun-Chul Chang ◽  
Jung-Hoon Kim ◽  
...  

AbstractThis study identifies diverse synoptic weather patterns of warm-season heavy rainfall events (HREs) in South Korea. The HREs not directly connected to tropical cyclones (TCs) (81.1%) are typically associated with a midlatitude cyclone from eastern China, the expanded North Pacific high and strong southwesterly moisture transport in between. They are frequent both in the first (early summer) and second rainy periods (late summer) with impacts on the south coast and west of the mountainous region. In contrast, the HREs resulting from TCs (18.9%) are caused by the synergetic interaction between the TC and meandering midlatitude flow, especially in the second rainy period. The strong south-southeasterly moisture transport makes the southern and eastern coastal regions prone to the TC-driven HREs. By applying a self-organizing map algorithm to the non-TC HREs, their surface weather patterns are further classified into six clusters. Clusters 1 and 3 exhibit frontal boundary between the low and high with differing relative strengths. Clusters 2 and 5 feature an extratropical cyclone migrating from eastern China under different background sea-level pressure patterns. Cluster 4 is characterized by the expanded North Pacific high with no organized negative sea-level pressure anomaly, and cluster 6 displays a development of a moisture pathway between the continental and oceanic highs. Each cluster exhibits a distinct spatio-temporal occurrence distribution. The result provides useful guidance for predicting the HREs by depicting important factors to be differently considered depending on their synoptic categorization.


Sign in / Sign up

Export Citation Format

Share Document