Evaluation of CMPA precipitation estimate in the evolution of typhoon-related storm rainfall in Guangdong, China

The merged precipitation data of Climate Prediction Center Morphing Technique and gauge observations (CMPA) generated for continental China has relatively high spatial and temporal resolution (hourly and 0.1°), while few studies have applied it to investigate the typhoon-related extreme rainfall. Th...

Full description

Saved in:
Bibliographic Details
Published in:Journal of hydroinformatics 2016-11, Vol.18 (6), p.1055-1068
Main Authors: Wang, Dashan, Wang, Xianwei, Liu, Lin, Wang, Dagang, Huang, Huabing, Pan, Cuilin
Format: Article
Language:English
Subjects:
Alarm systems
Atmospheric precipitations
Basins
Casualties
Climate prediction
Coasts
Coefficients
Correlation coefficient
Correlation coefficients
Detection
Estimates
Evolution
Extreme weather
Flooding
Floods
Gauges
Hurricanes
Hydrologic data
Hydrology
Measuring instruments
Modelling
Morphing
Performance evaluation
Precipitation
Probability theory
Rain
Rain gauges
Rainfall
Real time
Storms
Temporal resolution
Typhoons
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The merged precipitation data of Climate Prediction Center Morphing Technique and gauge observations (CMPA) generated for continental China has relatively high spatial and temporal resolution (hourly and 0.1°), while few studies have applied it to investigate the typhoon-related extreme rainfall. This study evaluates the CMPA estimate in quantifying the typhoon-related extreme rainfall using a dense rain gauge network in Guangdong Province, China. The results show that the event-total precipitation from CMPA is generally in agreement with gauges by relative bias (RB) of 2.62, 10.74 and 0.63% and correlation coefficients (CCs) of 0.76, 0.86 and 0.91 for typhoon Utor, Usagi and Linfa events, respectively. At the hourly scale, CMPA underestimates the occurrence of light rain (16 mm/h), while overestimates the occurrence of moderate rain. CMPA shows high probability of detection (POD = 0.93), relatively large false alarm ratio (FAR = 0.22) and small missing ratio (0.07). CMPA captures the spatial patterns of typhoon-related rain depth, and is in agreement with the spatiotemporal evolution of hourly gauge observations by CC from 0.93 to 0.99. In addition, cautiousness should be taken when applying it in hydrologic modeling for flooding forecasting since CMPA underestimates heavy rain (>16 mm/h).
ISSN:1464-7141
1465-1734
DOI:10.2166/hydro.2016.241