Dataset

Meteorological Data for Australian Postal Areas

The Australian National University
Dr Keith Dear (Owned by) Gillian Hall (Associated with) Mr Ivan Charles Hanigan (Owned by)
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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:doi10.4225/13/50BBFCFE08A12&rft.title=Meteorological Data for Australian Postal Areas&rft.identifier=10.4225/13/50BBFCFE08A12&rft.publisher=Australian Data Archive&rft.description=Background: To explain the possible effects of exposure to weather conditions on population health outcomes, weather data need to be calculated at a level in space and time that is appropriate for the health data. There are various ways of estimating exposure values from raw data collected at weather stations but the rationale for using one technique rather than another; the significance of the difference in the values obtained; and the effect these have on a research question are factors often not explicitly considered. In this study we compare different techniques for allocating weather data observations to small geographical areas and different options for weighting averages of these observations when calculating estimates of daily precipitation and temperature for Australian Postal Areas. Options that weight observations based on distance from population centroids and population size are more computationally intensive but give estimates that conceptually are more closely related to the experience of the population. Results: Options based on values derived from sites internal to postal areas, or from nearest neighbour sites; that is, using proximity polygons around weather stations intersected with postal areas; tended to include fewer stations observations in their estimates, and missing values were common. Options based on observations from stations within 50 kilometres radius of centroids and weighting of data by distance from centroids gave more complete estimates. Using the geographic centroid of the postal area gave estimates that differed slightly from the population weighted centroids and the population weighted average of sub-unit estimates. Conclusion: To calculate daily weather exposure values for analysis of health outcome data for small areas, the use of data from weather stations internal to the area only, or from neighbouring weather stations (allocated by the use of proximity polygons), is too limited. The most appropriate method conceptually is the use of weather data from sites within 50 kilometres radius of the area weighted to population centres, but a simpler acceptable option is to weight to the geographic centroid. &rft.creator=Hanigan, Ivan &rft.date=2010&rft.relation=10.1017/S0950268810001901&rft.relation=10.1186/1476-072X-5-38&rft.relation=https://github.com/ivanhanigan/POAweather&rft.relation=http://www.garnautreview.org.au/ca25734e0016a131/WebObj/03-AThreehealthoutcomes/%24File/03-A%20Three%20health%20outcomes.pdf&rft.coverage=AU&rft_rights=Copyright (c) 2011, The Australian National University. All rights reserved.| (c) Copyright Commonwealth of Australia 2005, Bureau of Meteorology. All rights reserved.| ABS Copyright (c) Commonwealth of Australia 2001, Australian Bureau of Statistics Census data is licensed under a Creative Commons Attribution 2.5 Australia licence. All rights reserved.&rft_subject=Epidemiology&rft_subject=Medical and Health Sciences&rft_subject=Public Health and Health Services&rft_subject=Geographical Areas&rft_subject=Health&rft_subject=Humidity&rft_subject=Population&rft_subject=Postal Area&rft_subject=Postcode&rft_subject=Precipitation&rft_subject=Temperature&rft_subject=Weather&rft_subject=Environment, Conservation, Land Use&rft_subject=Postcodes&rft_subject=Rainfall&rft_subject=Zones&rft.type=dataset&rft.language=English Go to Data Providers

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Copyright (c) 2011, The Australian National University. All rights reserved.| (c) Copyright Commonwealth of Australia 2005, Bureau of Meteorology. All rights reserved.| ABS Copyright (c) Commonwealth of Australia 2001, Australian Bureau of Statistics Census data is licensed under a Creative Commons Attribution 2.5 Australia licence. All rights reserved.

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Available to staff and students at The Australian National University. Contact Ivan Hanigan for further information. The copyright for the material this collection is based upon is not held by The Australian National University. To utilise the items in this collection permission must be sought from the original copyright holders. Please email the contact person to gain further information about obtaining permission to utilise parts of this collection.

Contact Information

ivan.hanigan@anu.edu.au

Full description

Background: To explain the possible effects of exposure to weather conditions on population health outcomes, weather data need to be calculated at a level in space and time that is appropriate for the health data. There are various ways of estimating exposure values from raw data collected at weather stations but the rationale for using one technique rather than another; the significance of the difference in the values obtained; and the effect these have on a research question are factors often not explicitly considered. In this study we compare different techniques for allocating weather data observations to small geographical areas and different options for weighting averages of these observations when calculating estimates of daily precipitation and temperature for Australian Postal Areas. Options that weight observations based on distance from population centroids and population size are more computationally intensive but give estimates that conceptually are more closely related to the experience of the population.

Results: Options based on values derived from sites internal to postal areas, or from nearest neighbour sites; that is, using proximity polygons around weather stations intersected with postal areas; tended to include fewer stations observations in their estimates, and missing values were common. Options based on observations from stations within 50 kilometres radius of centroids and weighting of data by distance from centroids gave more complete estimates. Using the geographic centroid of the postal area gave estimates that differed slightly from the population weighted centroids and the population weighted average of sub-unit estimates.

Conclusion: To calculate daily weather exposure values for analysis of health outcome data for small areas, the use of data from weather stations internal to the area only, or from neighbouring weather stations (allocated by the use of proximity polygons), is too limited. The most appropriate method conceptually is the use of weather data from sites within 50 kilometres radius of the area weighted to population centres, but a simpler acceptable option is to weight to the geographic centroid.

Created: 2010

Data time period: 1990 to 2005

166.7429167,-0.6911344 166.7429167,-51.6633232 100.0911072,-51.6633232 100.0911072,-0.6911344 166.7429167,-0.6911344

133.41701195,-26.1772288

iso31661: AU

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