HR: 1400h
AN: H53B-06    [Abstracts]
TI: A Satellite-Gauge Merged Analysis of Hourly Precipitation over Southern China
AU: * Liang, J
EM: liang_jy@grmc.gov.cn
AF: CMA Guang-Dong Meteorology Administration, China, CMA Guang-Dong Meteorology Adiministration, China, GuangZhou, China
AU: Xie, P
EM: Pingping.Xie@noaa.gov
AF: CPC/NCEP/NOAA, 5200 Auth Rd. Rm#605, Camp Springs, MD 20746, United States
AU: Janowiak, J E
EM: John.Janowiak@noaa.gov
AF: CPC/NCEP/NOAA, 5200 Auth Rd. Rm#605, Camp Springs, MD 20746, United States
AU: Joyce, R
EM: Robert.Joyce@noaa.gov
AF: CPC/NCEP/NOAA, 5200 Auth Rd. Rm#605, Camp Springs, MD 20746, United States
AU: Chen, M
EM: Mingyue.Chen@noaa.gov
AF: CPC/NCEP/NOAA, 5200 Auth Rd. Rm#605, Camp Springs, MD 20746, United States
AB: A new technique has been developed to construct analyses of hourly precipitation on a 0.125olat/lon over Guang- Dong province in southern China by merging gauge observations and satellite estimates. Hourly precipitation reports from ~400 stations are available on a real-time basis and used in this study to create the merged precipitation analysis over this province of ~150,000 km2. The high-resolution satellite precipitation estimates used here are those of CPC Morphing Technique (CMORPH, Joyce et al. 2004) which generates 30-min precipitation rates on an 8kmx8km grid over the globe by combining information from satellite-based microwave and infrared observations. The original CMORPH precipitation estimates are regridded into hourly and 0.125olat/lon resolution for use as inputs to our merging procedures. A two-step approach is designed to merge the hourly gauge observations and CMORPH satellite precipitation estimates. In the first step, the CMORPH precipitation estimates are calibrated against the gauge data to remove the inherent biases. To this end, ratio between the mean precipitation for the most recent 30 days from the gauge observations and that from the CMORPH estimates is computed for each gauge location and for each target date. An analyzed field of the gauge-vs-CMORPH ratio is then defined by interpolating the station values through the optimal interpolation (OI) technique of Gandin (1965). Biases in the CMORPH are finally removed by multiplying the ratio to the original satellite estimates. The second step is intended to improve the quantitative accuracy of the precipitation analysis. The bias-corrected CMORPH is combined with the gauge data, again, through an OI-based objective analysis technique, in which the bias-corrected CMORPH is utilized as the first guess while the station gauge data are employed as observations to calculate the increments. The weighting coefficients are calculated through the error structures of the CMORPH and gauge observations, so that over areas with dense gauge network, the final merged analysis is determined primarily by the gauge data while over gauge sparse regions the satellite observations plays more important roles. Cross-validation tests revealed that the merged analysis presents complete spatial coverage with stable and improved performance statistics compared with the individual inputs. A test product of the hourly precipitation analysis has been created for a three-month period from April 1 - June 30, 2005, and applied to examine the diurnal cycle of precipitation over this sub-tropical area during a pre-monsoon season. Detailed results will be reported at the meeting.
DE: 1840 Hydrometeorology
DE: 1855 Remote sensing (1640)
DE: 3354 Precipitation (1854)
SC: Hydrology [H]
MN: 2007 Joint Assembly