Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region
This paper presents spatial interpolation techniques to produce finer-scale daily rainfall data from regional climate modeling. Four common interpolation techniques (ANUDEM, Spline, IDW, and Kriging) were compared and assessed against station rainfall data and modeled rainfall. The performance was a...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2015/563629 |
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| _version_ | 1832559859389693952 |
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| author | Xihua Yang Xiaojin Xie De Li Liu Fei Ji Lin Wang |
| author_facet | Xihua Yang Xiaojin Xie De Li Liu Fei Ji Lin Wang |
| author_sort | Xihua Yang |
| collection | DOAJ |
| description | This paper presents spatial interpolation techniques to produce finer-scale daily rainfall data from regional climate modeling. Four common interpolation techniques (ANUDEM, Spline, IDW, and Kriging) were compared and assessed against station rainfall data and modeled rainfall. The performance was assessed by the mean absolute error (MAE), mean relative error (MRE), root mean squared error (RMSE), and the spatial and temporal distributions. The results indicate that Inverse Distance Weighting (IDW) method is slightly better than the other three methods and it is also easy to implement in a geographic information system (GIS). The IDW method was then used to produce forty-year (1990–2009 and 2040–2059) time series rainfall data at daily, monthly, and annual time scales at a ground resolution of 100 m for the Greater Sydney Region (GSR). The downscaled daily rainfall data have been further utilized to predict rainfall erosivity and soil erosion risk and their future changes in GSR to support assessments and planning of climate change impact and adaptation in local scale. |
| format | Article |
| id | doaj-art-c145bd7f1d7b4ce49245c552dcb8c363 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-c145bd7f1d7b4ce49245c552dcb8c3632025-02-03T01:29:10ZengWileyAdvances in Meteorology1687-93091687-93172015-01-01201510.1155/2015/563629563629Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney RegionXihua Yang0Xiaojin Xie1De Li Liu2Fei Ji3Lin Wang4New South Wales Office of Environment and Heritage, P.O. Box 3720, Parramatta, NSW 2150, AustraliaJiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaNSW Department of Industry, Skills & Regional Development, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, AustraliaNew South Wales Office of Environment and Heritage, P.O. Box 733, Queanbeyan, NSW 2620, AustraliaJiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaThis paper presents spatial interpolation techniques to produce finer-scale daily rainfall data from regional climate modeling. Four common interpolation techniques (ANUDEM, Spline, IDW, and Kriging) were compared and assessed against station rainfall data and modeled rainfall. The performance was assessed by the mean absolute error (MAE), mean relative error (MRE), root mean squared error (RMSE), and the spatial and temporal distributions. The results indicate that Inverse Distance Weighting (IDW) method is slightly better than the other three methods and it is also easy to implement in a geographic information system (GIS). The IDW method was then used to produce forty-year (1990–2009 and 2040–2059) time series rainfall data at daily, monthly, and annual time scales at a ground resolution of 100 m for the Greater Sydney Region (GSR). The downscaled daily rainfall data have been further utilized to predict rainfall erosivity and soil erosion risk and their future changes in GSR to support assessments and planning of climate change impact and adaptation in local scale.http://dx.doi.org/10.1155/2015/563629 |
| spellingShingle | Xihua Yang Xiaojin Xie De Li Liu Fei Ji Lin Wang Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region Advances in Meteorology |
| title | Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region |
| title_full | Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region |
| title_fullStr | Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region |
| title_full_unstemmed | Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region |
| title_short | Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region |
| title_sort | spatial interpolation of daily rainfall data for local climate impact assessment over greater sydney region |
| url | http://dx.doi.org/10.1155/2015/563629 |
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