Statistical properties of precipitation as observed by the TRMM precipitation radar

被引:29
作者
Yang, Song [1 ]
Nesbitt, Stephen W. [2 ]
机构
[1] Naval Res Lab, Monterey, CA 93943 USA
[2] Univ Illinois, Dept Atmospher Sci, Urbana, IL 61801 USA
关键词
TRMM; precipitation; radar; RAIN-PROFILING ALGORITHM; STRATIFORM PRECIPITATION; DIURNAL VARIABILITY; SATELLITE; CLIMATOLOGY; DATASETS; CLOUDS; MODES; CYCLE;
D O I
10.1002/2014GL060683
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The statistical properties of tropic-subtropic precipitation are revealed with 13years of Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) measurements. About 3% of PR observations are raining pixels. The average daily rainfall over 37.5 degrees N-37.5 degrees S is 1.28, 1.18, and 2.46mmd(-1) for convective, stratiform, and total rain, respectively, indicating 51.85% from convective rain and 48.09% from stratiform rain. The related values are 1.300, 1.272, and 2.573mmd(-1) over ocean and 1.22, 0.97, and 2.19mmd(-1) over land, indicating a convective rain fraction of 50.51% over ocean and 55.77% over land. The 92% (93%) and 73% (55%) of rain events over ocean (land) are from stratiform and convective rain <5mmh(-1), respectively, while the associated rainfall contributions in stratiform and convective rain are 62% (68%) and 27% (15%) over ocean (land). Results demonstrate that contributions from large rain intensity events are very importation in total precipitation, especially over land. The rainfall missed by TRMM PR is mostly light rain and does not significantly impact large-scale statistics of convective and stratiform rain amount. Light rain will increase the total precipitation by about 10% and, if considered a separate category, decrease the observed convective and stratiform rain contributions about 10% over the PR domain. These statistical properties of precipitation could be utilized as a baseline in the assessment of precipitation from operational numerical weather prediction and climate models.
引用
收藏
页码:5636 / 5643
页数:8
相关论文
共 50 条
[41]   Radar observations of the kinematic, microphysical, and precipitation characteristics of two MCSs in TRMM LBA [J].
Cifelli, R ;
Petersen, WA ;
Carey, LD ;
Rutledge, SA ;
Dias, MAFD .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2002, 107 (D20) :LBA44-1
[42]   Comparisons of Reflectivities from the TRMM Precipitation Radar and Ground-Based Radars [J].
Wang, Jianxin ;
Wolff, David B. .
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2009, 26 (05) :857-875
[43]   Drop Size Distribution Observed by Dual-frequency Precipitation Radar onboard Global Precipitation Measurement Core Satellite [J].
Yamaji, Moeka ;
Kubota, Takuji ;
Takahashi, Hiroshi G. ;
Hamada, Atsushi ;
Takayabu, Yukari N. ;
Oki, Riko .
REMOTE SENSING AND MODELING OF THE ATMOSPHERE, OCEANS, AND INTERACTIONS VII, 2018, 10782
[44]   A statistical spatial downscaling algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of China [J].
Jia, Shaofeng ;
Zhu, Wenbin ;
Lu, Aifeng ;
Yan, Tingting .
REMOTE SENSING OF ENVIRONMENT, 2011, 115 (12) :3069-3079
[45]   Evaluation of Spatial Errors of Precipitation Rates and Types from TRMM Spaceborne Radar over the Southern CONUS [J].
Chen, S. ;
Kirstetter, P. E. ;
Hong, Y. ;
Gourley, J. J. ;
Tian, Y. D. ;
Qi, Y. C. ;
Cao, Q. ;
Zhang, J. ;
Howard, K. ;
Hu, J. J. ;
Xue, X. W. .
JOURNAL OF HYDROMETEOROLOGY, 2013, 14 (06) :1884-1896
[46]   Evaluation of TRMM Satellite Precipitation Product in Hydrologic Simulations of Hai Basin [J].
Xiong Jun ;
Mao Defa ;
Yan Nana .
RIVER BASIN RESEARCH AND PLANNING APPROACH, 2009, :180-+
[47]   Differences in the Diurnal Variation of Precipitation Estimated by Spaceborne Radar, Passive Microwave Radiometer, and IMERG [J].
Hayden, Lindsey ;
Liu, Chuntao .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2021, 126 (09)
[48]   Validation of Satellite-Based Precipitation Products from TRMM to GPM [J].
Wang, Jianxin ;
Petersen, Walter A. ;
Wolff, David B. .
REMOTE SENSING, 2021, 13 (09)
[49]   Diurnal Variations of Precipitation over the Steep Slopes of the Himalayas Observed by TRMM PR and VIRS [J].
Xiao Pan ;
Yunfei Fu ;
Sen Yang ;
Ying Gong ;
Deqin Li .
Advances in Atmospheric Sciences, 2021, 38 :641-660
[50]   Evaluating the TRMM Multisatellite Precipitation Analysis for Extreme Precipitation and Streamflow in Ganjiang River Basin, China [J].
Jiang, Shanshan ;
Zhang, Zengxin ;
Huang, Yuhan ;
Chen, Xi ;
Chen, Sheng .
ADVANCES IN METEOROLOGY, 2017, 2017