Data

Evaluating 3-6 month seasonal climate forecasts for decision-making in farm case studies using APSIM

Commonwealth Scientific and Industrial Research Organisation
Meier, Elizabeth ; Gaydon, Donald
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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/erjq-4g56&rft.title=Evaluating 3-6 month seasonal climate forecasts for decision-making in farm case studies using APSIM&rft.identifier=https://doi.org/10.25919/erjq-4g56&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=This data consists of APSIM v7.10 model set ups and weather files used to simulate crop production under usual practice and in response to the 3 and/or 6 month seasonal climate forecasts at 8 different case study farms. Case studies were from individual farms in the grains (including cotton), sugarcane, and rice industries in Australia (farm managers deidentified). The model setups include any modified xml files to better represent crops and other modules). The weather files include historical records obtained from the SILO data base for the nearest weather station to the farms (modified by radiation sourced from Senaps data source), 'perfect' forecasts calculated from the historical record, and seasonal climate forecasts generated from the Access-S2 and ECMWF general circulation models.\nLineage: The data collection represents one package of work from the larger project AgScore: An agricultural approach to assessing the skill of seasonal climate forecasting systems and their value for aiding on-farm decision making. In work packages 1 and 2, the methodology for downscaling a number of general circulation models (GCMs) of climate over Australia was developed and implemented. In work package 3, the methodology was used to downscale the Access-S2 and ECMWF GCM models to the location of the weather stations used to simulate the case study farms. These forecasts were used to simulate change in farm outcomes (production and gross margins) when decision-making could be informed by using a seasonal climate forecast.&rft.creator=Meier, Elizabeth &rft.creator=Gaydon, Donald &rft.date=2024&rft.edition=v4&rft_rights=Creative Commons Attribution-Noncommercial 4.0 Licence https://creativecommons.org/licenses/by-nc/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2022.&rft_subject=seasonal climate forecast&rft_subject=APSIM&rft_subject=Access-S2&rft_subject=ECMWF&rft_subject=Agricultural production systems simulation&rft_subject=Agriculture, land and farm management&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Agricultural systems analysis and modelling&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-Noncommercial 4.0 Licence
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Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2022.

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Brief description

This data consists of APSIM v7.10 model set ups and weather files used to simulate crop production under usual practice and in response to the 3 and/or 6 month seasonal climate forecasts at 8 different case study farms. Case studies were from individual farms in the grains (including cotton), sugarcane, and rice industries in Australia (farm managers deidentified). The model setups include any modified xml files to better represent crops and other modules). The weather files include historical records obtained from the SILO data base for the nearest weather station to the farms (modified by radiation sourced from Senaps data source), 'perfect' forecasts calculated from the historical record, and seasonal climate forecasts generated from the Access-S2 and ECMWF general circulation models.
Lineage: The data collection represents one package of work from the larger project "AgScore: An agricultural approach to assessing the skill of seasonal climate forecasting systems and their value for aiding on-farm decision making". In work packages 1 and 2, the methodology for downscaling a number of general circulation models (GCMs) of climate over Australia was developed and implemented. In work package 3, the methodology was used to downscale the Access-S2 and ECMWF GCM models to the location of the weather stations used to simulate the case study farms. These forecasts were used to simulate change in farm outcomes (production and gross margins) when decision-making could be informed by using a seasonal climate forecast.

Available: 2024-07-08

Data time period: 1888-12-31 to 2021-06-30

This dataset is part of a larger collection

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Other Information

Grains Research & Development Corporation (GRDC) : CSP2004-007RTX