Paper Info
Title
A Two-Step Approach to Blending GSMaP Satellite Rainfall Estimates with Gauge Observations over Australia
Abstract
An approach to developing a blended satellite-rainfall dataset over Australia that could be suitable for operational use is presented. In this study, Global Satellite Mapping of Precipitation (GSMaP) satellite precipitation estimates were blended with station-based rain gauge data over Australia, using operational station data that has not been harnessed by other blended products. A two-step method was utilized. First, GSMaP satellite precipitation estimates were adjusted using rain gauge data through multiplicative ratios that were gridded using ordinary kriging. This step resulted in reducing dry biases, especially over topography. The adjusted GSMaP data was then blended with the Australian Gridded Climate Dataset (AGCD) rainfall analysis, an operational station-based gridded rain gauge dataset, using an inverse error variance weighting method to further remove biases. A validation that was performed using a 20-year range (2001 to 2020) showed the proposed approach was successful; the resulting blended dataset displayed superior performance compared to other non-gauge-based datasets with respect to stations as well as displaying more realistic patterns of rainfall than the AGCD in areas with no rain gauges. The average mean absolute error (MAE) against station data was reduced from 0.89 to 0.31. The greatest bias reductions were obtained for extreme precipitation totals and over mountainous regions, provided sufficient rain gauge availability. The newly produced dataset supported the identification of a general positive bias in the AGCD over the north-west interior of Australia.
Year
DOI
Venue
2022
10.3390/rs14081903
REMOTE SENSING
Keywords
DocType
Volume
Australian rainfall, satellite rainfall, satellite rainfall blending, rainfall estimation
Journal
14
Issue
ISSN
Citations 
8
2072-4292
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Zhi-Weng Chua100.68
Yuriy Kuleshov200.68
Andrew B. Watkins300.68
suelynn choy453.80
Chayn Sun500.34