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)

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.

本数据集包含用于研究《通过使用基于流量依赖的非参数模型提高高流量和低流量短期预报的可靠性》的经过后处理的降雨预报（hincast）数据，该研究由McInerney等人于2021年发表。此数据集由澳大利亚气象局制作。降雨预报采用澳大利亚社区气候地球系统模拟器季节性版本1（ACCESS-S Version 1）（Hudson等人，2017年）。随后，对ACCESS-S预报进行后处理，以降低偏差并提升预报的可靠性（Schepen等人，2018年）。参考文献：Hudson, D. 等人（2017年）。ACCESS-S1：澳大利亚气象局新的多周至季节性预测系统。南方半球地球系统科学杂志，67，132-159。McInerney, D. 等人（2021年）。通过使用基于流量依赖的非参数模型提高高流量和低流量短期预报的可靠性（待审）。Schepen, A. 等人（2018年）。一种用于后处理全球气候模型每日次季节至季节性降雨预报的贝叶斯建模方法及其在12个澳大利亚流域的评估。水文地球系统科学，22，1615-1628。