Quantitative evaluations of the seasonal forecasts demonstrate that simple approaches, using “hit or miss” criteria (e.g., probability of detection, false alarm rate) or traditional summary statistics (e.g., root mean squared error, correlation) neglect important aspects of forecast performance and can even be misleading, potentially affecting resource management decisions. On the other hand, distributions-oriented evaluation criteria are more informative and allow decision makers to target those aspects of forecast performance that are important for their situation. For example, using the criteria of “discrimination”, predictions of seasonal streamflow volumes for Colorado River tributaries are shown to convey useable information not revealed by other criteria, even with lead-times of several months. From a decision maker’s perspective, it is important that forecast evaluations be frequently updated and target the regions, seasons, lead times, and criteria important to specific decision making situations. From an operational perspective, more information needs to be archived than has been the traditional practice, especially for probabilistic predictions.
From the perspective of resource managers, risks of using new forecast products can be reduced as individuals accurately interpret the products and properly gauge prediction uncertainty. Effective communication of prediction uncertainty, in ways understandable by diverse audiences, requires further attention to product formats. Several alternative formats for deterministic and probabilistic forecasts are presented, as are formats for expressing historical regional variability and potential variability unrelated to specific forecast methodologies. Feedback from resource managers has been solicited through workshops, interviews, and online surveys. Tutorial materials intended to improve forecast interpretation have been well received.