Dataset

Supporting data for "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021)

The University of Adelaide
David McInerney (Aggregated by) Dmitri Kavetski (Aggregated by) Mark Thyer (Aggregated 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:doi10.25909/14604180.v1&rft.title=Supporting data for Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model by McInerney et al. (2021)&rft.identifier=http://doi.org/10.25909/14604180.v1&rft.publisher=The University of Adelaide&rft.description=This dataset contains post-processed rainfall forecast (hincast) data used in the study Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model by McInerney et al. (2021).This dataset was produced by the Australian Bureau of Meteorology. Rainfall forecasts are produced using the Australian Community Climate Earth-System Simulator - Seasonal (ACCESS-S Version 1) (Hudson et al., 2017).The ACCESS-S forecasts are then post-processed to reduce biases and improve reliability (Schepen et al., 2018).ReferencesHudson, D., Alves, O., Hendon, H. H., Lim, E., Liu, G., Luo, J. J., MacLachlan, C., Marshall, A. G., Shi, L., Wang, G., Wedd, R., Young, G., Zhao, M. & Zhou, X. 2017. ACCESS-S1 The new Bureau of Meteorology multi-week to seasonal prediction system. Journal of Southern Hemisphere Earth System Sciences, 67, 132-159.McInerney, D., Thyer, M., Kavetski, D., Laugesen, R.,Woldemeskel, F., Tuteja, N. & Kuczera, G. Improving the reliability of short-term forecasts of high and low flows by using a flow-dependent non-parametric model (under review).Schepen, A., Zhao, T., Wang, Q. J. & Robertson, D. E. 2018. A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments. Hydrol. Earth Syst. Sci., 22, 1615-1628.&rft.creator=David McInerney&rft.creator=Dmitri Kavetski&rft.creator=Mark Thyer&rft.date=2021&rft_rights=CC-BY-4.0&rft_subject=ACCESS-S&rft_subject=sub-seasonal forecasting&rft_subject=rainfall post-processing&rft_subject=forecast rainfall&rft_subject=Hydrology&rft_subject=Climate Science&rft_subject=Water Resources Engineering&rft.type=dataset&rft.language=English Access the data
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Full description

This dataset contains post-processed rainfall forecast (hincast) data used in the study "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021).

This dataset was produced by the Australian Bureau of Meteorology.

Rainfall forecasts are produced using the Australian Community Climate Earth-System Simulator - Seasonal (ACCESS-S Version 1) (Hudson et al., 2017).

The ACCESS-S forecasts are then post-processed to reduce biases and improve reliability (Schepen et al., 2018).

References

Hudson, D., Alves, O., Hendon, H. H., Lim, E., Liu, G., Luo, J. J., MacLachlan, C., Marshall, A. G., Shi, L., Wang, G., Wedd, R., Young, G., Zhao, M. & Zhou, X. 2017. ACCESS-S1 The new Bureau of Meteorology multi-week to seasonal prediction system. Journal of Southern Hemisphere Earth System Sciences, 67, 132-159.

McInerney, D., Thyer, M., Kavetski, D., Laugesen, R.,Woldemeskel, F., Tuteja, N. & Kuczera, G. Improving the reliability of short-term forecasts of high and low flows by using a flow-dependent non-parametric model (under review).

Schepen, A., Zhao, T., Wang, Q. J. & Robertson, D. E. 2018. A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments. Hydrol. Earth Syst. Sci., 22, 1615-1628.

Issued: 2021-06-09

Created: 2021-06-09

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Subjects
ACCESS-S | Climate Science | Hydrology | Water Resources Engineering | forecast rainfall | rainfall post-processing | sub-seasonal forecasting |

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Other Information
Mark Thyer

orcid : http://orcid.org/0000-0002-2830-516x

David McInerney

url : https://figshare.com/authors/David_McInerney/4188115

Dmitri Kavetski

url : https://figshare.com/authors/Dmitri_Kavetski/4197955

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