Study On Key Technologies Of Quantitative Precipitation Estimation With Dual Polarimetric Weather Radar

Spatio-temporal distribution of precipitation is an important topic in geography researches.Precipitation information extracted from remote sensing platform observations has become an increasing important information source of Geographic information system.As development of remote sensing technologies especially the dual polarimetric radar technologies,more and more attentions have been paid to the technologies of quantitative precipitation estimation?QPE?with dual polarimetric weather radar to obtain more accurate QPE products.Dual polarimetric radar has seen more and more applications in China.However,there is a lot of challenges of QPE with dual polarimetric weather radar,for example,the quality control?QC?of dual polarimetric radar observations.To address these challenges,this study focusses on the algorithms on the QC and QPE based on observations from S-band dual polarimetric radar over southern China.The observations of Guangzhou S-band dual polarimetric radar on 7 May 2017 were used to test and validate the QC and QPE algorithm.Firstly,a QC algorithm named MetEcho is developed and used to remove non-meteorological echoes from radar data.The MetEcho algorithm is a fuzzy logic technique with a few postprocessing rule.Secondly,discrimination between different precipitation particle phases is necessary for a number of radar applications.In the hydrometeor classification algorithm,five radar variables are directly utilized for discrimination.The hydrometeor categories include:1)large drops?LD?,2)drizzle?DR?,3)rain?RA?,4)heavy rain?HR?,5)rain-hail mixture?RH?,6)hail?HA?,7)graupel?GR?,8)wet ice?WI?,9)dry ice?DI?,10)crystals?CR?,11)dendrites?DN?.Ground clutter?CL?is identified as the 12^th category in the MetEcho algorithm.Secondly,in order to improving QPE accuracy,the Z-R relationship was calculated using rain DSD data that collected with a particle Size and Velocity?PARSIVEL?disdrometer during April to June of 2014 and 2015 in southwestern Guangdong Province.Finally,the dual polarimetric radar QPE?RQPE?during an extreme precipitation storm over Guangzhou on 7 May 7 2017 is evaluated with gauge observations with statistics indexes.These indexes include correlative coefficient?CC?,relative bias?RB?,root mean square error?RMSE?,and contingency scores?probability of detection?POD?,critical success index?CSI?and false alarm ratio?FAR??.The results show that:1)the RQPE generally capture the spatio-temporal patterns of storm-accumulated rainfall with high CC about 0.93;2)RQPE capture well the temporal variation of the total precipitation over Guangdong province;3)RQPE can accurately estimates the extreme precipitation in complex terrain and warm rain.The main conclusions include:1)The quality of radar data has a great impact on the subsequent operational use of radar,including hydrometeorological applications such as flood forecast,early warning,and QPE and precipitation forecast.The MetEcho algorithm has been developed to remove most of the non-meteorological echoes.2)Dual polarization parameters have different characteristics and sensitivity to the phase of precipitation particles.Through fuzzy logic operation,0? height identification and comparison with the threshold,a hydrometeor classification algorithm?HCA?was developed to classify the hydrometeors into 11 categories with 4 kinds of input radar variables.The HCA reliability is assessed with visual examination and gauge observations.3)After assessment the performance of RQPE calculated with the new Z-R relationship,it is found that RQPE has a high CC,small RMSE,and performs well in monitor extreme storms.