Data

ANUClimate collection

Terrestrial Ecosystem Research Network
Jennifer Kesteven ; Tingbao Xu
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/f30e39a4-15dc-4038-a37f-7fd29744e46a&rft.title=ANUClimate collection&rft.identifier=http://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/f30e39a4-15dc-4038-a37f-7fd29744e46a&rft.publisher=NCI Australia&rft.description=The daily and monthly climate variables contained herein have been generated using ANUClimate 1.0 (though ANUClimate 1.1 data is available for most daily products). This is a spatial model, developed by Michael Hutchinson, that integrates a new approach to the interpolation of Australia’s national point climate data to produce climate variables on a 0.01° longitude/latitude grid. Most climate values have been modelled by expressing each value as a normalised anomaly with respect to the gridded 1976-2005 mean. These means and anomalies were all interpolated by trivariate thin plate smoothing spline functions of longitude, latitude and vertically exaggerated elevation using ANUSPLIN Version 4.5, with additional dependences on proximity to the coast for the temperature and vapour pressure variables. Station elevations for the gridded temperature and vapour pressure variables were obtained from 0.01° local averages of grid values from the GEODATA 9 second DEM version 3. Station elevations for the gridded rainfall and pan evaporation variables were obtained from 0.05° local averages of grid values from the GEODATA 9 second DEM version 3.Progress Code: completed&rft.creator=Jennifer Kesteven &rft.creator=Tingbao Xu &rft.edition=2&rft.coverage=northlimit=-9; southlimit=-44; westlimit=112; eastLimit=154; projection=&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&rft_subject=climatologyMeteorologyAtmosphere&rft_subject=0401 - Atmospheric Sciences&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Open Licence view details
CC-BY

Creative Commons Attribution 4.0 International Licence
http://creativecommons.org/licenses/by/4.0

Access:

Open view details

unclassified

Brief description

The daily and monthly climate variables contained herein have been generated using ANUClimate 1.0 (though ANUClimate 1.1 data is available for most daily products). This is a spatial model, developed by Michael Hutchinson, that integrates a new approach to the interpolation of Australia’s national point climate data to produce climate variables on a 0.01° longitude/latitude grid. Most climate values have been modelled by expressing each value as a normalised anomaly with respect to the gridded 1976-2005 mean. These means and anomalies were all interpolated by trivariate thin plate smoothing spline functions of longitude, latitude and vertically exaggerated elevation using ANUSPLIN Version 4.5, with additional dependences on proximity to the coast for the temperature and vapour pressure variables. Station elevations for the gridded temperature and vapour pressure variables were obtained from 0.01° local averages of grid values from the GEODATA 9 second DEM version 3. Station elevations for the gridded rainfall and pan evaporation variables were obtained from 0.05° local averages of grid values from the GEODATA 9 second DEM version 3.

Notes

Data Usage
04:Earth Sciences

Lineage

Progress Code: completed

Notes

Purpose
The main aim of this project is to support the modelling of the spatial distributions of plants and animals, to make long-term estimates of land surface processes for assessment of agriculture and biodiversity, and to provide a baseline for the assessment of the impacts of projected climate change.

This dataset is part of a larger collection

154,-9 154,-44 112,-44 112,-9 154,-9

133,-26.5

Subjects

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover