Case studies of seasonal rainfall forecasts for Hong Kong and its vicinity using a regional climate model

Seasonal climate forecasts are one of the most promising tools for providing early warnings for natural hazards such as floods and droughts. Using two case studies, this paper documents the skill of a regional climate model in the seasonal forecasting of below normal rainfall in southern China durin...

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Bibliographic Details
Published in:	Natural hazards (Dordrecht) 2007-07, Vol.42 (1), p.193-207
Main Authors:	TAI-WAI HUI, David, KIT-YING SHUM, Karen, JI CHEN, CHEN, Shyh-Chin, RITCHIE, Jack, ROADS, John O
Format:	Article
Language:	eng
Subjects:	Case studies Climate Climate models Documents Drought Earth sciences Earth, ocean, space East Asian monsoon Engineering and environment geology. Geothermics Exact sciences and technology Hydrology Hydrology. Hydrogeology Meteorology Modelling Monsoons Natural hazards: prediction, damages, etc Rain Rainfall Rainfall forecasting Rainy season Regional climate models Regional climates Seasonal forecasting Seasonal rainfall Wet season
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Summary:	Seasonal climate forecasts are one of the most promising tools for providing early warnings for natural hazards such as floods and droughts. Using two case studies, this paper documents the skill of a regional climate model in the seasonal forecasting of below normal rainfall in southern China during the rainy seasons of July–August–September 2003 and April–May–June 2004. The regional model is based on the Regional Spectral Model of the National Centers for Environmental Prediction of the United States. It is the first time that the model has been applied to a region dominated by the East Asian Monsoon.The article shows that the regional climate model, when being forced by reasonably good forecasts from a global model, can generate useful seasonal rainfall forecasts for the region, where it is dominated by the East Asia monsoon. The spatial details of the dry conditions obtained from the regional climate model forecast are also found to be comparable with the observed distribution.
ISSN:	0921-030X 1573-0840