Correction of TRMM 3B42V7 Based on Linear Regression Models over China
Joint Authors
Yan, Denghua
Liu, Shaohua
Qin, Tianling
Weng, Baisha
Li, Meng
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-08
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
High temporal-spatial precipitation is necessary for hydrological simulation and water resource management, and remotely sensed precipitation products (RSPPs) play a key role in supporting high temporal-spatial precipitation, especially in sparse gauge regions.
TRMM 3B42V7 data (TRMM precipitation) is an essential RSPP outperforming other RSPPs.
Yet the utilization of TRMM precipitation is still limited by the inaccuracy and low spatial resolution at regional scale.
In this paper, linear regression models (LRMs) have been constructed to correct and downscale the TRMM precipitation based on the gauge precipitation at 2257 stations over China from 1998 to 2013.
Then, the corrected TRMM precipitation was validated by gauge precipitation at 839 out of 2257 stations in 2014 at station and grid scales.
The results show that both monthly and annual LRMs have obviously improved the accuracy of corrected TRMM precipitation with acceptable error, and monthly LRM performs slightly better than annual LRM in Mideastern China.
Although the performance of corrected TRMM precipitation from the LRMs has been increased in Northwest China and Tibetan plateau, the error of corrected TRMM precipitation is still significant due to the large deviation between TRMM precipitation and low-density gauge precipitation.
American Psychological Association (APA)
Liu, Shaohua& Yan, Denghua& Qin, Tianling& Weng, Baisha& Li, Meng. 2016. Correction of TRMM 3B42V7 Based on Linear Regression Models over China. Advances in Meteorology،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1095418
Modern Language Association (MLA)
Liu, Shaohua…[et al.]. Correction of TRMM 3B42V7 Based on Linear Regression Models over China. Advances in Meteorology No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1095418
American Medical Association (AMA)
Liu, Shaohua& Yan, Denghua& Qin, Tianling& Weng, Baisha& Li, Meng. Correction of TRMM 3B42V7 Based on Linear Regression Models over China. Advances in Meteorology. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1095418
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1095418