{"help": "https://data.gov.au/data/api/3/action/help_show?name=package_show", "success": true, "result": {"author_email": null, "contact_point": "bioregionalassessments@environment.gov.au", "creator_user_id": "2846d45e-3969-4419-a085-84f5716ede91", "duplicate_score": 1, "geospatial_topic": [], "id": "a0e86e32-b09d-443c-9545-503617b8d532", "isopen": false, "language": "eng", "license_id": "Copyright holder gives no warranty and accepts no liability in relation to data.\r\n\r\nData must not be used for direct marketing or be used in breach of the privacy laws.", "license_title": "Copyright holder gives no warranty and accepts no liability in relation to data.\r\n\r\nData must not be used for direct marketing or be used in breach of the privacy laws.", "maintainer": null, "maintainer_email": null, "metadata_created": "2016-04-08T08:02:15.663555", "metadata_modified": "2023-08-11T01:06:46.842899", "name": "0a018b43-58d3-4b9e-b339-4dae8fd54ce8", "notes": "## **Abstract** \n\nThis dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.\n\n\n\nSILO is a Queensland Government database containing continuous daily climate data for Australia from 1889 to present. Gridded datasets are constructed by spatially interpolating the observed point data. Continuous point datasets are constructed by supplementing the available point data with interpolated estimates when observed data are missing.\n\n## **Purpose** \n\nSILO provides climate datasets that are ready to use. Raw observational data typically contain missing data and are only available at the location of meteorological recording stations. SILO provides point datasets with no missing data and gridded datasets which cover mainland Australia and some islands.\n\n## **Dataset History** \n\nLineage statement:\n\n(A)\tProcessing System Version History\n\n\\*\tPrior to 2001\n\nThe interpolation system used the algorithm detailed in Jeffrey et al.1\n\n\\*\t2001-2009\n\nThe normalisation procedure was modified. Observational rainfall, when accumulated over a sufficient period and raised to an appropriate fractional power, is (to a reasonable approximation) normally distributed. In the original procedure the fractional power was fixed at 0.5 and a normal distribution was fitted to the transformed data using a maximum likelihood technique. A Kolmogorov-Smirnov test was used to test the goodness of fit, with a threshold value of 0.8. In 2001 the procedure was modified to allow the fractional power to vary between 0.4 and 0.6. The normalisation parameters (fractional power, mean and standard deviation) at each station were spatially interpolated using a thin plate smoothing spline.\n\n\\*\t2009-2011\n\nThe normalisation procedure was modified. The Kolmogorov-Smirnov test was removed, enabling normalisation parameters to be computed for all stations having sufficient data. Previously parameters were only computed for those stations having data that were adequately modelled by a normal distribution, as determined by the Kolmogorov-Smirnov test.\n\n\\*\tJanuary 2012 - November 2012\n\nThe normalisation procedure was modified:\n\no\tThe Kolmogorov-Smirnoff test was reintroduced, with a threshold value of 0.1.\n\no\tData from Bellenden Ker Top station were included in the computation of normalisation parameters. The station was previously omitted on the basis of having insufficient data. It was forcibly included to ensure the steep rainfall gradient in the region was reflected in the normalisation parameters.\n\no\tThe elevation data used when interpolating normalisation parameters were modified. Previously a mean elevation was assigned to each station, taken from the nearest grid cell in a 0.05°   0.05° digital elevation model. The procedure was modified to use the actual station elevation instead of the mean. In mountainous regions the discrepancy was substantial and cross validation tests showed a significant improvement in error statistics.\n\no\tThe station data are normalised using: (i) a power parameter extracted from the nearest pixel in the gridded power surface. The surface was obtained by interpolating the power parameters fitted at station locations using a maximum likelihood algorithm; and (ii) mean and standard deviation parameters which had been fitted at station locations using a smoothing spline. Mean and standard deviation parameters were fitted at the subset of stations having at least 40 years of data, using a maximum likelihood algorithm. The fitted data were then spatially interpolated to construct: (a) gridded mean and standard deviation surfaces (for use in a subsequent de-normalisation procedure); and (b) interpolated estimates of the parameters at all station locations (not just the subset having long data records). The parameters fitted using maximum likelihood (at the subset of stations having long data records) may differ from those fitted by the interpolation algorithm, owing to the smoothing nature of the spline algorithm which was used. Previously, station data were normalised using mean and standard deviation parameters which were taken from the nearest pixel in the respective mean and standard deviation surfaces.\n\n\\*\tNovember 2012 - May 2013\n\nThe algorithm used for selecting monthly rainfall data for interpolation was modified. Prior to November 2012, the system was as follows:\n\no\tAccumulated monthly rainfall was computed by the Bureau of Meteorology;\n\no\tRainfall accumulations spanning the end of a month were assigned to the last month included in the accumulation period;\n\no\tA monthly rainfall value was provided for all stations which submitted at least one daily report. Zero rainfall was assumed for all missing values; and\n\no\tSILO imposed a complex set of ad-hoc rules which aimed to identify stations which had ceased reporting in real time. In such cases it would not be appropriate to assume zero rainfall for days when a report was not available. The rules were only applied when processing data for January 2001 and onwards.\n\nIn November 2012 a modified algorithm was implemented:\n\no\tSILO computed the accumulated monthly rainfall by summing the daily reports;\n\no\tRainfall accumulations spanning the end of a month were discarded;\n\no\tA monthly rainfall value was not computed for a given station if any day throughout the month was not accounted for - either through a daily report or an accumulation; and\n\no\tThe SILO ad-hoc rules were not applied.\n\n\\*\tMay 2013 - current\n\nThe algorithm used for selecting monthly rainfall data for interpolation was modified. The modified algorithm is only applied to datasets for the period October 2001 - current and is as follows:\n\no\tSILO computes the accumulated monthly rainfall by summing the daily reports;\n\no\tRainfall accumulations spanning the end of a month are pro-rata distributed onto the two months included in the accumulation period;\n\no\tA monthly rainfall value is computed for all stations which have at least 21 days accounted for throughout the month. Zero rainfall is assumed for all missing values; and\n\no\tThe SILO ad-hoc rules are applied when processing data for January 2001 and onwards.\n\nDatasets for the period January 1889-September 2001 are prepared using the system that was in effect prior to November 2012.\n\n\n\nLineage statement:\n\n(A)\tProcessing System Version History\n\nNo changes have been made to the processing system since SILO's inception.\n\n(B)\tMajor Historical Data Updates\n\n\\*\tAll observational data and station coordinates were updated in 2009. \n\n\\*\tStation coordinates were updated on 26 January 2012.\n\n \n\nProcess step:\n\nThe observed data are interpolated using a tri-variate thin plate smoothing spline, with latitude, longitude and elevation as independent variables.4 A two-pass interpolation system is used. All available observational data are interpolated in the first pass and residuals computed for all data points. The residual is the difference between the observed and interpolated values. Data points with high residuals may be indicative of erroneous data and are excluded from a subsequent interpolation which generates the final gridded surface. The surface covers the region 112˚E - 154˚E, 10˚S - 44˚S on a regular 0.05˚ × 0.05˚grid and is restricted to land areas on mainland Australia and some islands.\n\n\n\n\n\nGridded datasets for the period 1957-current are obtained by interpolation of the raw data. \n\nGridded datasets for the period 1957-current are obtained by interpolation of the raw data. Gridded datasets for the period 1889-1956 were constructed using an anomaly interpolation technique. The daily departure from the long term mean is interpolated, and the gridded dataset is constructed by adding the gridded anomaly to the gridded long term mean. The long term means were constructed using data from the period 1957-2001. The anomaly interpolation technique is described in Rayner et al.6  \n\n\n\nThe observed and interpolated datasets evolve as new data becomes available and the existing data are improved through quality control procedures. Modifications gradually decrease over time, with most datasets undergoing little change 12 months after the date of observation.\n\n## **Dataset Citation** \n\n\"Queensland Department of Science, Information Technology, Innovation and the Arts\" (2013) SILO Patched Point data for Narrabri (54120) and Gunnedah (55023) stations in the Namoi subregion. Bioregional Assessment Source Dataset. Viewed 29 September 2017, http://data.bioregionalassessments.gov.au/dataset/0a018b43-58d3-4b9e-b339-4dae8fd54ce8.", "num_resources": 1, "num_tags": 3, "organization": {"id": "69f37b4c-bdf0-4c85-bd56-82fa6d6b087a", "name": "bioregional-assessment-program", "title": "Bioregional Assessment Program", "type": "organization", "description": "The Australian Government's bioregional assessments programs are a collaboration between the Department of Agriculture, Water and the Environment, the Bureau of Meteorology, CSIRO and Geoscience Australia. There are two separate programs of bioregional assessments.\r\n\r\nThe Bioregional Assessment Program (2012 - 2017) seeks to better understand the potential impacts of coal seam gas and large coal mining developments on water resources and water-related assets. It is one of a number of actions undertaken by the Australian Government to strengthen the science underpinning decision making on coal seam gas and large coal mining developments.\r\n\r\nThe Geological and Bioregional Assessment Program (2017 - 2021) assessed the potential impacts of shale and tight gas development on water and the environment. The Program assessed three priority geological basins: the Cooper Basin in Queensland and South Australia, the Isa Superbasin in Queensland and the Beetaloo Sub-basin in the Northern Territory (referred to as GBA regions", "image_url": "2015-10-30-051742.096388Bioregional-assessments-logo-800.jpg", "created": "2015-10-30T05:17:42.164347", "is_organization": true, "approval_status": "approved", "state": "active"}, "original_harvest_source": {"site_url": "https://data.gov.au/data/dataset/", "href": "https://data.gov.au/data/dataset/0a018b43-58d3-4b9e-b339-4dae8fd54ce8", "title": "data.gov.au"}, "owner_org": "69f37b4c-bdf0-4c85-bd56-82fa6d6b087a", "private": false, "spatial_coverage": "NONE", "state": "active", "temporal_coverage_from": "2016-04-08 08:02:15", "title": "SILO Patched Point data for Narrabri (54120) and Gunnedah (55023) stations in the Namoi subregion", "type": "dataset", "unpublished": false, "url": null, "version": null, "extras": [{"key": "contact_info", "value": "false"}, {"key": "data_state", "value": "active"}, {"key": "field_of_research", "value": "[]"}, {"key": "jurisdiction", "value": "New South Wales"}, {"key": "update_freq", "value": "daily"}], "resources": [{"Description": "CSIRO Download Page", "cache_last_updated": null, "cache_url": null, "created": "2017-09-29T14:35:02.084131", "datastore_active": false, "datastore_contains_all_records_of_source_file": false, "description": "Data File", "format": "ZIP", "hash": "", "id": "92f7b2ce-7a07-424e-8628-c017a57a2b92", "last_modified": "2017-09-29T00:00:00", "metadata_modified": "2023-08-11T01:06:46.852419", "mimetype": null, "mimetype_inner": null, "name": "SILO Patched Point data for Narrabri (54120) and Gunnedah (55023) stations in the Namoi subregion", "package_id": "a0e86e32-b09d-443c-9545-503617b8d532", "position": 0, "resource_type": null, "size": 15069668, "state": "active", "url": "https://datagovau.s3.amazonaws.com/bioregionalassessments/NIC/NAM/DATA/Climate/RainfallNamoi_SILO_PPD_Rainfall/0a018b43-58d3-4b9e-b339-4dae8fd54ce8.zip", "url_type": null, "zip_extract": false}], "tags": [{"display_name": "Namoi subregion", "id": "11cbf605-34cc-4c80-8d3e-78645cf10e2f", "name": "Namoi subregion", "state": "active", "vocabulary_id": null}, {"display_name": "New South Wales", "id": "e767d4c4-dcfe-4939-81a4-20cafa72d96e", "name": "New South Wales", "state": "active", "vocabulary_id": null}, {"display_name": "climatologyMeteorologyAtmosphere", "id": "11def81f-1309-4baf-9740-1e8e9fe40045", "name": "climatologyMeteorologyAtmosphere", "state": "active", "vocabulary_id": null}], "groups": [], "relationships_as_subject": [], "relationships_as_object": []}}