A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia
Satellites offer a way of estimating rainfall away from rain gauges which can be utilised to overcome the limitations imposed by gauge density on traditional rain gauge analyses. In this study, Australian station data along with the Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mappin...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/2/261 |
| _version_ | 1797490769147199488 |
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| author | Zhi-Weng Chua Yuriy Kuleshov Andrew B. Watkins Suelynn Choy Chayn Sun |
| author_facet | Zhi-Weng Chua Yuriy Kuleshov Andrew B. Watkins Suelynn Choy Chayn Sun |
| author_sort | Zhi-Weng Chua |
| collection | DOAJ |
| description | Satellites offer a way of estimating rainfall away from rain gauges which can be utilised to overcome the limitations imposed by gauge density on traditional rain gauge analyses. In this study, Australian station data along with the Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) and the Bureau of Meteorology’s (BOM) Australian Gridded Climate Dataset (AGCD) rainfall analysis are combined to develop an improved satellite-gauge rainfall analysis over Australia that uses the strengths of the respective data sources. We investigated a variety of correction and blending methods with the aim of identifying the optimal blended dataset. The correction methods investigated were linear corrections to totals and anomalies, in addition to quantile-to-quantile matching. The blending methods tested used weights based on the error variance to MSWEP (Multi-Source Weighted Ensemble Product), distance to the closest gauge, and the error from a triple collocation analysis to ERA5 and Soil Moisture to Rain. A trade-off between away-from- and at-station performances was found, meaning there was a complementary nature between specific correction and blending methods. The most high-performance dataset was one corrected linearly to totals and subsequently blended to AGCD using an inverse error variance technique. This dataset demonstrated improved accuracy over its previous version, largely rectifying erroneous patches of excessive rainfall. Its modular use of individual datasets leads to potential applicability in other regions of the world. |
| first_indexed | 2024-03-10T00:37:40Z |
| format | Article |
| id | doaj.art-de9557dcef3a4c6aab3e2bb8f2ce59b4 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T00:37:40Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-de9557dcef3a4c6aab3e2bb8f2ce59b42023-11-23T15:14:41ZengMDPI AGRemote Sensing2072-42922022-01-0114226110.3390/rs14020261A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over AustraliaZhi-Weng Chua0Yuriy Kuleshov1Andrew B. Watkins2Suelynn Choy3Chayn Sun4Bureau of Meteorology, Melbourne, VIC 3008, AustraliaBureau of Meteorology, Melbourne, VIC 3008, AustraliaBureau of Meteorology, Melbourne, VIC 3008, AustraliaSchool of Mathematical and Geospatial Sciences, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3000, AustraliaSchool of Mathematical and Geospatial Sciences, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3000, AustraliaSatellites offer a way of estimating rainfall away from rain gauges which can be utilised to overcome the limitations imposed by gauge density on traditional rain gauge analyses. In this study, Australian station data along with the Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) and the Bureau of Meteorology’s (BOM) Australian Gridded Climate Dataset (AGCD) rainfall analysis are combined to develop an improved satellite-gauge rainfall analysis over Australia that uses the strengths of the respective data sources. We investigated a variety of correction and blending methods with the aim of identifying the optimal blended dataset. The correction methods investigated were linear corrections to totals and anomalies, in addition to quantile-to-quantile matching. The blending methods tested used weights based on the error variance to MSWEP (Multi-Source Weighted Ensemble Product), distance to the closest gauge, and the error from a triple collocation analysis to ERA5 and Soil Moisture to Rain. A trade-off between away-from- and at-station performances was found, meaning there was a complementary nature between specific correction and blending methods. The most high-performance dataset was one corrected linearly to totals and subsequently blended to AGCD using an inverse error variance technique. This dataset demonstrated improved accuracy over its previous version, largely rectifying erroneous patches of excessive rainfall. Its modular use of individual datasets leads to potential applicability in other regions of the world.https://www.mdpi.com/2072-4292/14/2/261satellite precipitation estimatesrainfall blendingsatellite rainfallgauge analysis |
| spellingShingle | Zhi-Weng Chua Yuriy Kuleshov Andrew B. Watkins Suelynn Choy Chayn Sun A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia Remote Sensing satellite precipitation estimates rainfall blending satellite rainfall gauge analysis |
| title | A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia |
| title_full | A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia |
| title_fullStr | A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia |
| title_full_unstemmed | A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia |
| title_short | A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia |
| title_sort | comparison of various correction and blending techniques for creating an improved satellite gauge rainfall dataset over australia |
| topic | satellite precipitation estimates rainfall blending satellite rainfall gauge analysis |
| url | https://www.mdpi.com/2072-4292/14/2/261 |
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