Preliminary Studies on Merged Techniques Based on Precipitation Information from Multiplatform(Radar,Satellite and Rain Gauge)
Xiaorong Gao
Abstract
Xiaorong Gao
Abstract
To improve satellite Quantitative Precipitation Estimation(QPE) techniques,combining CMORPH precipitation data and rain gauge observations based on OI(Optimal Interpolation),the QPE with 0.125°×0.125° resolutions was obtained.In order to enlarge the scale of precipitation,the CMORPH QPE with 0.125°×0.125° resolution and multi-radar QPE with of 0.01°×0.01° resolutions were merged by weight coefficient of square multiplicative inverse of its root mean square error.Error statistical analysis indicated that using rain gauge data to correct CMORPH data can reduce bias;cross-validation,some conclusions were obtained that the satellite QPE merging with rain gauge data is better than gauge's OI.QPE output with different resolutions has obvious regional difference.Merging is an effective way to improve the precision and enlarge the scale of QPE from multiple sources of precipitation information and applied to take advantage of precipitation information from multiple platform.
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To improve satellite Quantitative Precipitation Estimation(QPE) techniques,combining CMORPH precipitation data and rain gauge observations based on OI(Optimal Interpolation),the QPE with 0.125°×0.125° resolutions was obtained.In order to enlarge the scale of precipitation,the CMORPH QPE with 0.125°×0.125° resolution and multi-radar QPE with of 0.01°×0.01° resolutions were merged by weight coefficient of square multiplicative inverse of its root mean square error.Error statistical analysis indicated that using rain gauge data to correct CMORPH data can reduce bias;cross-validation,some conclusions were obtained that the satellite QPE merging with rain gauge data is better than gauge's OI.QPE output with different resolutions has obvious regional difference.Merging is an effective way to improve the precision and enlarge the scale of QPE from multiple sources of precipitation information and applied to take advantage of precipitation information from multiple platform.
Key concepts: Quantitative precipitation estimation, Rain gauge, Precipitation, Satellite, Radar, Environmental science, Scale (ratio), Interpolation (computer graphics)