Paper Info
Title
Evaluation of FY-4A Temperature Profile Products and Application to Winter Precipitation Type Diagnosis in Southern China
Abstract
FY-4A GIIRS temperature profile products have provided unprecedented information for studying the atmospheric characteristics of thermal structures since 2020. The main objective of this paper is to evaluate GIIRS temperature profile products by using radiosonde observations and then apply them to the diagnosis of winter precipitation types in southern China. GIIRS temperature profile products for four types (clear sky perfect quality, cloudy sky perfect quality, cloudy sky good quality and cloudy sky bad quality) show different performances. Relatively, the cloud can affect the quality and quantity of GIIRS products. At different pressure levels, the perfect flagged data under the clear or cloudy sky show the best agreement with radiosonde observations, yielding the highest Pearson correlation coefficient and lowest mean bias as well as root mean square error. The good flagged data have a slight deviation from the perfect data. The impact on the quantity of the GIIRS temperature data is greater than that on the quality with an increase in cloud top height. A case investigation was carried out to analyze the performance of GIIRS temperature profiles for the diagnosis of precipitation types in a winter storm of 2022. The GIIRS temperature profiles represent the reasonable atmospheric thermal structures in the rain and snow in Hubei and Hunan provinces. The GIIRS temperature below 700 hPa is an important indictor to precipitation type diagnosis. Furthermore, two critical thresholds for GIIRS temperatures, which are below -2 degrees C at 850 hPa and below 0 degrees C at 925 hPa, respectively, are proposed for the occurrence of snowfall in this winter storm. In addition, the distribution of GIIRS temperature at different pressure levels is consistent with radiosonde observations in a freezing rain event in Guiyang, all of which show the warm rain mechanism by combining the cloud top information.
Year
DOI
Venue
2022
10.3390/rs14102363
REMOTE SENSING
Keywords
DocType
Volume
GIIRS temperature profile, winter precipitation types, evaluation, application
Journal
14
Issue
ISSN
Citations 
10
2072-4292
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yang Gao142.07
Dongyan Mao200.34
Xin Wang3018.25
Danyu Qin402.03