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A Methodological Framework to Retrospectively Obtain Downscaled Precipitation Estimates over the Tibetan Plateau.

Authors :
He, Kang
Ma, Ziqiang
Zhao, Ruiying
Biswas, Asim
Teng, Hongfen
Xu, Junfeng
Yu, Wu
Shi, Zhou
Source :
Remote Sensing; Dec2018, Vol. 10 Issue 12, p1974, 1p
Publication Year :
2018

Abstract

Long-term precipitation estimates with both finer spatial resolution and better quality are vital and highly needed in various related fields. Numerous downscaling algorithms have been investigated based on the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), to obtain precipitation data with finer resolution (~1 km). However, this research was restricted by the time span of the TMPA dataset, as the starting time of TMPA was 1998. In this study, a new methodological framework incorporating wavelet coherence and Cubist was proposed to retrospectively obtain downscaled precipitation estimates (DS) over the Tibetan Plateau (TP), based on TMPA and ground observations, in 1990s. The correlations and similarities of precipitation patterns between the target years, from 1990 to 1999, and reference years, from 2000 to 2013, were firstly determined using wavelet coherence based on ground observations. Following this, the TMPA data in the reference years were regarded as the reference in the corresponding target years, which were adopted to be downscaled using Cubist models and land surface variables, to obtain the DS in the target years. We found that the DS showed continuous trends, which corresponded well with the ground observations. Additionally, the performances of the DS were better than those of the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over the TP. Therefore, this methodological framework has great potential for obtaining precipitation estimates for the period of the 1990s for which TMPA data is inaccessible. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
10
Issue :
12
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
133722369
Full Text :
https://doi.org/10.3390/rs10121974