Data

Climate Victoria: Precipitation (9 second, approx. 250 m)

Commonwealth Scientific and Industrial Research Organisation
Stewart, Stephen ; Fedrigo, Melissa ; Roxburgh, Stephen ; Kasel, Sabine ; Nitschke, Craig
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/5e3be5193e301&rft.title=Climate Victoria: Precipitation (9 second, approx. 250 m)&rft.identifier=https://doi.org/10.25919/5e3be5193e301&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=Daily (1981-2019), monthly (1981-2019) and monthly mean (1981-2010) surfaces of precipitation across Victoria at a spatial resolution of 9 seconds (approx. 250 m). \nLineage: A) Data modelling:\n1. Weather station observations collected by the Australian Bureau of Meteorology were obtained via the SILO patched point dataset (https://data.qld.gov.au/dataset/silo-patched-point-datasets-for-queensland), followed by the removal of all interpolated records.\n2. Climate normals representing the 1981-2010 reference period were calculated for each weather station. A regression patching procedure (Hopkinson et al. 2012) was used to correct for biases arising due to differences in record length where possible.\n3. Climate normals for each month were interpolated using trivariate splines (latitude, longitude and elevation as spline variables) using a DEM smoothed (Gaussian filter with a standard deviation of 10 and a search radius of 0.0825°, optimised using cross validation) to account for the lack of strong correlation between elevation and precipitation at short distances (Hutchinson 1998; Sharples et al. 2005). All data was interpolated using ANUSPLIN 4.4 (Hutchinson & Xu 2013).\n4. Monthly surfaces were interpolated directly from monthly station records using the methods described in step 3. \n5. Daily anomalies were calculated as a proportion of monthly precipitation, and interpolated with full spline dependence on latitude and longitude.\n6. Interpolated anomalies (constrained to values between 0 and 1) were multiplied by monthly precipitation to obtain the final daily surfaces. \nB) Spatial data inputs:\n1. Fenner School of Environment and Society and Geoscience Australia. 2008. GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3.\nC) Model performance:\nAccuracy assessment was conducted with leave-one-out cross validation. \nMean monthly precipitation: RMSE = 7.65 mm (14.0% relative to mean)\nMonthly precipitation: RMSE = 13.12 mm (24.7% relative to mean)\nDaily precipitation: RMSE = 2.21 mm (26.3% relative to mean)&rft.creator=Stewart, Stephen &rft.creator=Fedrigo, Melissa &rft.creator=Roxburgh, Stephen &rft.creator=Kasel, Sabine &rft.creator=Nitschke, Craig &rft.date=2020&rft.edition=v3&rft.relation=https://www.mdpi.com/2072-4292/11/1/93&rft.coverage=westlimit=140.95999999999998; southlimit=-39.16; eastlimit=149.9775; northlimit=-33.980000000000004; projection=WGS84&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO, The University of Melbourne 2020.&rft_subject=climate&rft_subject=weather&rft_subject=daily&rft_subject=monthly&rft_subject=climate normals&rft_subject=precipitation&rft_subject=interpolation&rft_subject=victoria&rft_subject=Climatology&rft_subject=Climate change science&rft_subject=EARTH SCIENCES&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 4.0 International Licence
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Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO, The University of Melbourne 2020.

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Brief description

Daily (1981-2019), monthly (1981-2019) and monthly mean (1981-2010) surfaces of precipitation across Victoria at a spatial resolution of 9 seconds (approx. 250 m).
Lineage: A) Data modelling:
1. Weather station observations collected by the Australian Bureau of Meteorology were obtained via the SILO patched point dataset (https://data.qld.gov.au/dataset/silo-patched-point-datasets-for-queensland), followed by the removal of all interpolated records.
2. Climate normals representing the 1981-2010 reference period were calculated for each weather station. A regression patching procedure (Hopkinson et al. 2012) was used to correct for biases arising due to differences in record length where possible.
3. Climate normals for each month were interpolated using trivariate splines (latitude, longitude and elevation as spline variables) using a DEM smoothed (Gaussian filter with a standard deviation of 10 and a search radius of 0.0825°, optimised using cross validation) to account for the lack of strong correlation between elevation and precipitation at short distances (Hutchinson 1998; Sharples et al. 2005). All data was interpolated using ANUSPLIN 4.4 (Hutchinson & Xu 2013).
4. Monthly surfaces were interpolated directly from monthly station records using the methods described in step 3.
5. Daily anomalies were calculated as a proportion of monthly precipitation, and interpolated with full spline dependence on latitude and longitude.
6. Interpolated anomalies (constrained to values between 0 and 1) were multiplied by monthly precipitation to obtain the final daily surfaces.
B) Spatial data inputs:
1. Fenner School of Environment and Society and Geoscience Australia. 2008. GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3.
C) Model performance:
Accuracy assessment was conducted with leave-one-out cross validation.
Mean monthly precipitation: RMSE = 7.65 mm (14.0% relative to mean)
Monthly precipitation: RMSE = 13.12 mm (24.7% relative to mean)
Daily precipitation: RMSE = 2.21 mm (26.3% relative to mean)

Available: 2020-06-14

Data time period: 1981-01-01 to 2019-12-31

This dataset is part of a larger collection

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149.9775,-33.98 149.9775,-39.16 140.96,-39.16 140.96,-33.98 149.9775,-33.98

145.46875,-36.57

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