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Optimization of Cloud-Radiation Databases for Passive Microwave Precipitation Retrievals over Oceanfirst spaceborne precipitation radar (PR). In particular, PR provides valuable measurements to validate and improve the rainfall amount estimated from TMI (e.g., Iguchi et al. 2000 ; Olson et al. 1999 ; Kummerow et al. 2001 , 2011 ; Berg et al. 2006 ; Shige et al. 2006 , 2008 ; Seo et al. 2007 , 2015 ; Gopalan et al. 2010 ). The official TMI precipitation algorithm, the Goddard profiling algorithm (GPROF), is based on the derivation and use of an a priori cloud-radiation database. The
first spaceborne precipitation radar (PR). In particular, PR provides valuable measurements to validate and improve the rainfall amount estimated from TMI (e.g., Iguchi et al. 2000 ; Olson et al. 1999 ; Kummerow et al. 2001 , 2011 ; Berg et al. 2006 ; Shige et al. 2006 , 2008 ; Seo et al. 2007 , 2015 ; Gopalan et al. 2010 ). The official TMI precipitation algorithm, the Goddard profiling algorithm (GPROF), is based on the derivation and use of an a priori cloud-radiation database. The
Improvements in Detection of Light Precipitation with the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR)improving rainfall retrieval algorithms based on spaceborne passive infrared/microwave measurements. Following the success of TRMM, the Global Precipitation Measurement (GPM) core observatory was launched successfully at the end of February 2014 and started its observations ( Hou et al. 2014 ). On board the GPM core observatory is a dual-frequency precipitation radar (DPR) that operates in the Ku (13.6 GHz) and Ka (35.5 GHz) bands, making observations between ~65°S and ~65°N from a non
improving rainfall retrieval algorithms based on spaceborne passive infrared/microwave measurements. Following the success of TRMM, the Global Precipitation Measurement (GPM) core observatory was launched successfully at the end of February 2014 and started its observations ( Hou et al. 2014 ). On board the GPM core observatory is a dual-frequency precipitation radar (DPR) that operates in the Ku (13.6 GHz) and Ka (35.5 GHz) bands, making observations between ~65°S and ~65°N from a non
Enhancing PMW Satellite Precipitation Estimation: Detecting Convective Classespecially pronounced in satellite observations. Since the first spaceborne passive microwave instruments were launched in early 1970s, satellite precipitation retrievals have exploited the link between upwelling radiation and state of atmospheric column. Leveraging decades of ever-improving algorithms, coverage, and data latency, the Global Precipitation Measurement (GPM) mission ( Skofronick-Jackson et al. 2018 ; Hou et al. 2014 ) represents the most advance satellite precipitation project to date
especially pronounced in satellite observations. Since the first spaceborne passive microwave instruments were launched in early 1970s, satellite precipitation retrievals have exploited the link between upwelling radiation and state of atmospheric column. Leveraging decades of ever-improving algorithms, coverage, and data latency, the Global Precipitation Measurement (GPM) mission ( Skofronick-Jackson et al. 2018 ; Hou et al. 2014 ) represents the most advance satellite precipitation project to date
Improvements of Rain/No-Rain Classification Methods for Microwave Radiometer over Coasts by Dynamic Surface-Type Classification1. Introduction Global precipitation information is critical for understanding the global energy and water cycle. Since the 1970s, scientists have been developing techniques to estimate precipitation from satellite radiometric observations, which can cover most of the globe. The first techniques used visible or infrared (IR) data to infer precipitation intensity based on cloud reflectivities or cloud-top temperature ( Barrett 1970 ). The IR technique performs poorly in estimation of warm rain
1. Introduction Global precipitation information is critical for understanding the global energy and water cycle. Since the 1970s, scientists have been developing techniques to estimate precipitation from satellite radiometric observations, which can cover most of the globe. The first techniques used visible or infrared (IR) data to infer precipitation intensity based on cloud reflectivities or cloud-top temperature ( Barrett 1970 ). The IR technique performs poorly in estimation of warm rain
