Tropical Precipitation Estimated by GPCP and TRMM PR Observations

LI Rui; FU Yunfei

doi:10.1007/BF02918685

Impact Factor: 5.8

Volume 22 Issue 6

Nov. 2005

Article Contents

Article > ADVANCES IN ATMOSPHERIC SCIENCES > 2005 > 22(6): 852-864

Tropical Precipitation Estimated by GPCP and TRMM PR Observations

LI Rui,
FU Yunfei

1.
School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026,School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026

LI Rui,
FU Yunfei

doi: 10.1007/BF02918685

Abstract
References
Related papers
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Abstract:
In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project (GPCP) version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are compared in temporal and spatial scales in order to comprehend tropical rainfall climatologically. Reasons for the rainfall differences derived from both datasets are discussed. Results show that GPCP and TRMM PR datasets present similar distribution patterns over the Tropics but with some differences in amplitude and location. Generally, the average difference over the ocean of about 0.5 mm d-1 is larger than that of about 0.1 mm d-1 over land. Results also show that GPCP tends to underestimate the monthly precipitation over the land region with sparse rain gauges in contrast to regions with a higher density of rain gauge stations. A Probability Distribution Function (PDF) analysis indicates that the GPCP rain rate at its maximum PDF is generally consistent with the TRMM PR rain rate as the latter is less than 8 mm d-1. When the TRMM PR rain rate is greater than 8 mm d-1, the GPCP rain rate at its maximum PDF is less by at least 1 mm d-1compared to TRMM PR estimates. Results also show an absolute bias of less than 1 mm d-1 between the two datasets when the rain rate is less than 10 mm d-1. A large relative bias of the two datasets occurs at weak and heavy rain rates.
- GPCP,
- TRMM PR,
- precipitation
References

[1]	Yilun CHEN, Aoqi ZHANG, Yunfei FU, Shumin CHEN, Weibiao LI, 2021: Morphological Characteristics of Precipitation Areas over the Tibetan Plateau Measured by TRMM PR, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 677-689. doi: 10.1007/s00376-020-0233-1
[2]	FU Yunfei, LIN Yihua, Guosheng LIU, WANG Qiang, 2003: Seasonal Characteristics of Precipitation in 1998 over East Asia as Derived from TRMM PR, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 511-529. doi: 10.1007/BF02915495
[3]	JIE Weihua, WU Tongwen, WANG Jun, LI Weijing, LIU Xiangwen, 2014: Improvement of 6-15 Day Precipitation Forecasts Using a Time-Lagged Ensemble Method, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 293-304. doi: 10.1007/s00376-013-3037-8
[4]	LIU Ge, WU Renguang, ZHANG Yuanzhi, and NAN Sulan, 2014: The Summer Snow Cover Anomaly over the Tibetan Plateau and Its Association with Simultaneous Precipitation over the Mei-yu-Baiu region, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 755-764. doi: 10.1007/s00376-013-3183-z
[5]	Yali LUO, Weimiao QIAN, Yu GONG, Hongyan WANG, Da-Lin ZHANG, 2016: Ground-Based Radar Reflectivity Mosaic of Mei-yu Precipitation Systems over the Yangtze River-Huaihe River Basins, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1285-1296. doi: 10.1007/s00376-016-6022-1
[6]	Xiao PAN, Yunfei FU, Sen YANG, Ying GONG, Deqin LI, 2021: Diurnal Variations of Precipitation over the Steep Slopes of the Himalayas Observed by TRMM PR and VIRS, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 641-660. doi: 10.1007/s00376-020-0246-9
[7]	REN Guoyu, DING Yihui, ZHAO Zongci, ZHENG Jingyun, WU Tongwen, TANG Guoli, XU Ying, 2012: Recent Progress in Studies of Climate Change in China, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 958-977. doi: 10.1007/s00376-012-1200-2
[8]	Leilei KOU, Zhuihui WANG, Fen XU, 2018: Three-dimensional Fusion of Spaceborne and Ground Radar Reflectivity Data Using a Neural Network-Based Approach, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 346-359. doi: 10.1007/s00376-017-6334-9
[9]	Aoqi ZHANG, Weibiao LI, Shumin CHEN, Yilun CHEN, Yunfei FU, 2021: Satellite Observations of Reflectivity Maxima above the Freezing Level Induced by Terrain, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 627-640. doi: 10.1007/s00376-020-0221-5
[10]	Athanassios A. ARGIRIOU, Zhen LI, Vasileios ARMAOS, Anna MAMARA, Yingling SHI, Zhongwei YAN, 2023: Homogenised Monthly and Daily Temperature and Precipitation Time Series in China and Greece since 1960, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1326-1336. doi: 10.1007/s00376-022-2246-4
[11]	Tian FENG, Fumin REN, Da-Lin ZHANG, Guoping LI, Wenyu QIU, Hui YANG, 2020: Sideswiping Tropical Cyclones and Their Associated Precipitation over China, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 707-717. doi: 10.1007/s00376-020-9224-5
[12]	Meng YAN, Johnny C. L. CHAN, Kun ZHAO, 2020: Impacts of Urbanization on the Precipitation Characteristics in Guangdong Province, China, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 696-706. doi: 10.1007/s00376-020-9218-3
[13]	WANG Shaowu, ZHU Jinhong, CAI Jingning, 2004: Interdecadal Variability of Temperature and Precipitation in China since 1880, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 307-313. doi: 10.1007/BF02915560
[14]	ZHANG Xinping, JIN Huijun, SUN Weizhen, 2006: Stable Isotopic Variations in Precipitation in Southwest China, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 649-658. doi: 10.1007/s00376-006-0649-2
[15]	GE Quansheng, WANG Shaowu, WEN Xinyu, Caiming SHEN, HAO Zhixin, 2007: Temperature and Precipitation Changes in China During the HoloceneTemperature and Precipitation Changes in China During the Holocene, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 1024-1036. doi: 10.1007/s00376-007-1024-7
[16]	Xingmin LI, Yan DONG, Zipeng DONG, Chuanli DU, Chuang CHEN, 2016: Observed Changes in Aerosol Physical and Optical Properties before and after Precipitation Events, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 931-944. doi: 10.1007/s00376-016-5178-z
[17]	Xiaoling YANG, Botao ZHOU, Ying XU, Zhenyu HAN, 2021: CMIP6 Evaluation and Projection of Temperature and Precipitation over China, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 817-830. doi: 10.1007/s00376-021-0351-4
[18]	ZHANG Xinping, LIU Jingmiao, TIAN Lide, HE Yuanqing, YAO Tandong, 2004: Variations of 18O in Precipitation along Vapor Transport Paths, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 562-572. doi: 10.1007/BF02915724
[19]	SONG Lianchun, A. J. CANNON, P. H. WHITFIELD, 2007: Changes in Seasonal Patterns of Temperature and Precipitation in China During 1971--2000, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 459-473. doi: 10.1007/s00376-007-0459-1
[20]	Geng Quanzhen, Ding Yihui, Huang Chaoying, 1997: Influences of the Extratropical Pacific SST on the Precipitation of the North China Region, ADVANCES IN ATMOSPHERIC SCIENCES, 14, 339-349. doi: 10.1007/s00376-997-0054-5

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Manuscript History

Manuscript received: 10 November 2005

Manuscript revised: 10 November 2005

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Tropical Precipitation Estimated by GPCP and TRMM PR Observations

LI Rui,
FU Yunfei

1. School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026,School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026

Manuscript received: 2005-11-10
Manuscript revised: 2005-11-10

Abstract: In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project (GPCP) version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are compared in temporal and spatial scales in order to comprehend tropical rainfall climatologically. Reasons for the rainfall differences derived from both datasets are discussed. Results show that GPCP and TRMM PR datasets present similar distribution patterns over the Tropics but with some differences in amplitude and location. Generally, the average difference over the ocean of about 0.5 mm d-1 is larger than that of about 0.1 mm d-1 over land. Results also show that GPCP tends to underestimate the monthly precipitation over the land region with sparse rain gauges in contrast to regions with a higher density of rain gauge stations. A Probability Distribution Function (PDF) analysis indicates that the GPCP rain rate at its maximum PDF is generally consistent with the TRMM PR rain rate as the latter is less than 8 mm d-1. When the TRMM PR rain rate is greater than 8 mm d-1, the GPCP rain rate at its maximum PDF is less by at least 1 mm d-1compared to TRMM PR estimates. Results also show an absolute bias of less than 1 mm d-1 between the two datasets when the rain rate is less than 10 mm d-1. A large relative bias of the two datasets occurs at weak and heavy rain rates.

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