Supporting data for "Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts" by Laugesen et.al. (2023)

Includes input forecasts (CSV), forecast value datasets (HDF5), and generated figures (PNG, PDF). Organised into subdirectories for each figure.<br>The code used for this work has been released as a software library, along with an associated publication. This is available at https://github.com/richardlaugesen/ruvpy and can now be used by researchers and industry to quantify the value of forecast for decision making using RUV (pip install ruvpy).<b>References</b><i>Laugesen, Richard and Thyer, Mark and McInerney, David and Kavetski, Dmitri, Software Library to Quantify the Value of Forecasts for Decision-Making: Case Study on Sensitivity to Damages. </i><i>http://dx.doi.org/10.2139/ssrn.5001881</i><i> (under review)</i><i>Laugesen, R., Thyer, M., McInerney, D., &amp; Kavetski, D. (2023). Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts. Hydrology and Earth System Sciences, 27(4), 873-893. </i><i>https://doi.org/10.5194/hess-27-873-2023</i>Laugesen, R., Thyer, M., McInerney, D., &amp; Kavetski, D. (2024). RUVPY software library to quantify the value of forecasts for decision-making using RUV (v0.9.0). Zenodo. https://doi.org/10.5281/zenodo.13939199