Chua, Zhi-Weng (2021): Monthly blended rainfall data created using GSMaP satellite and AGCD rainfall analysis from 2001 to 2021 over Australia, version 1 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.936719
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Published: 2021-10-05 • DOI registered: 2022-04-19
Abstract:
This NetCDF4 dataset contains gridded rainfall estimates created from a blend of Global Satellite Mapping of Precipitation (GSMaP) satellite rainfall and Australian Gridded Climate Dataset (AGCD) rain gauge analysis data. The blending process consisted of a two-step method.
The first step involved correcting the data through the use of multiplicative ratio grids. For each month, the ratio of the satellite data to the rain gauge data was found at each station. These ratios were then converted into a grid using Ordinary Kriging. The ratio grid was then applied onto the original GSMaP data to form the corrected GSMaP data.
The second step involved blending the corrected GSMaP data and AGCD data. The blend is formed from the weighted average of the two datasets using weights derived from their error variances. The weights were inversely proportional to the error variances of the respective datasets. The error variances were calculated on a seasonal basis using the Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset as truth. The weighted average is the final blended product.
The temporal coverage of the data spans a total of 20 years from January 2001 to December 2020, on a monthly basis.
The spatial domain of the data is a rectangular domain centred over Australia. The latitude ranges from 108 to 156 degrees east while the longitude ranges from -45 to -9 degrees north. The resolution is 0.1 degrees.
The data was created in an attempt to provide better representation of rainfall away from rain gauges whilst retaining strong correlations to rain gauges where they exist. The algorithm described earlier was performed using Python 3.
This is version 1 of the data. Refinements are planned in the future.
Supplement to:
Chua, Zhi-Weng; Kuleshov, Yuriy; Watkins, Andrew; Choy, Suelynn; Sun, Chayn (2022): A Two-Step Approach to Blending GSMaP Satellite Rainfall Estimates with Gauge Observations over Australia. Remote Sensing, 14(8), https://doi.org/10.3390/rs14081903
Further details:
bld maker Version 1 (Jupyter Notebook) (A Python notebook containing scripts that can be used to replicate the generation of the data. The environment will have to be set.)
Coverage:
Latitude: -26.216000 * Longitude: 134.904000
Date/Time Start: 2001-01-01T00:00:00 * Date/Time End: 2020-12-01T00:00:00
Comment:
MSWEP data, AGCD data and GSMaP data will have to be sourced for the generation process.
GSMaP can be sourced at ftp://swcem@hokusai.eorc.jaxa.jp/EAWP/GSMaP_GNRT/DATA/
AGCD can be sourced at http://www.bom.gov.au/metadata/catalogue/19115/ANZCW0503900567
Permission to access MSWEP can be found at http://www.gloh2o.org/mswep/
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | DATE/TIME | Date/Time | Chua, Zhi-Weng | Geocode | ||
| 2 | Binary Object | Binary | Chua, Zhi-Weng | GsMaP data | ||
| 3 | Binary Object (File Size) | Binary (Size) | Bytes | Chua, Zhi-Weng | GsMaP data | |
| 4 | Binary Object | Binary | Chua, Zhi-Weng | Gauge data | ||
| 5 | Binary Object (File Size) | Binary (Size) | Bytes | Chua, Zhi-Weng | Gauge data |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
480 data points
Data
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