Despite increasing skill, state-of-the-art climate forecasts are not being used to inform decision making. This study will develop case studies that concretely quantify the benefits of using forecasts, specifically seasonal climate forecasts produced by the Climate Forecast System Version 2 (CFSv2). Until recently, practitioners had to rely on reanalysis data or, when available, archived operational forecasts to assess the skill of climate models replicating observed conditions. This has made evaluation of model skill and biases difficult as these data are often archived in hard to use formats, generally unavailable to the end-user, and extend back for short periods less than 5-10 years. With the advent of the CFSv2 and its unique reforecast dataset, a stage has been set to analyze our ability to predict seasonal climate phenomena in the context of decision making in water management. This is powerful, as it allows end-users to evaluate forecast skill and condition system operations accordingly.
This work will build a set of final linkages in the end-to-end chain from global-scale climate research and forecast production, to operational watershed-scale climate and streamflow prediction, to water management and decision making. We will accomplish this through three primary tasks: 1) generating ensemble streamflow forecasts for project settings (hindcasts from CFSv2 reforecast data and real-time); 2) using reforecast data to evaluate prediction skill of GFS and CFSv2, and the related streamflow forecasts, in the context of decision making and reservoir operations; and 3) disseminating data and recommendations to the broader water sector through outreach in the form of workshops and forums and production of hindcast data readily available to managers in the pilot regions.
Through collaboration with our team members and outreach activities, this research will take up the call of creating “an informed society that anticipates and responds to climate and its impacts.” This study broadens our understanding of how climate systems impact water resources management by viewing seasonal forecast data (CFSv2 reforecast data) through the lens of water management decision support tools. Analyzing reforecast data in the context of decision making and consequent changes to system performance provides a quantitative assessment of the utility of seasonal forecasting that is meaningful to water resources managers. Putting the benefits of using seasonal forecasts in terms that are easily understandable facilitates the diffusion of climate products into the broader water management community, creating more informed users of more informed science, ultimately aiding in stewardship decisions. This contributes to creating a more climate literate public, as water managers are using the best available climate science to inform operational and policy decisions. The framework producing climate informed streamflow products and hindcasts is being developed to be easily implemented in other RFCs around the nation, setting a pathway to produce reliable and timely climate informed streamflow forecasts nationally. The framework for determining the benefits of seasonal forecasts and conditioning operations on forecast skill is flexible and readily transferable to water managers across the nation, creating a more weather ready nation.
The objectives of this project aligns with NWS Hydrology Program strategic goals, and in particular the connection of ensemble predictions to risk-based decision support (DSS), and to those of the international Hydrologic Ensemble Prediction Experiment (HEPEX)