An appraisal of the Great Lakes advanced hydrologic prediction system

Great Lakes water level forecasts are used to inform decisions ranging from personal choices of recreational activities to corporate evaluations of alternative cargo transport options. For effective decision-making it is important that these model-based forecasts include an accurate expression of the forecast uncertainty, as well as information regarding the model forecasting skill. We provide an assessment of water level forecasts from 1997 through 2009 that were made using the National Oceanic and Atmospheric Administration (NOAA) Great lakes Environmental Research Laboratory (GLERL) Advanced Hydrologic Prediction System (AHPS). A visual comparison between observed and forecast water levels suggests that AHPS generally captures seasonal and inter-annual patterns. A more quantitative assessment based on the percentage of observations within 90% prediction intervals, however, indicates that AHPS generally underestimates the observed variability of Great Lakes water levels. This assessment provides a benchmark for forecast performance against which alternative model structures (including future evolutions of AHPS) can be tested, and a basis to identify and prioritize the implementation of those alternatives. Including a calibrated model error term into the AHPS framework, to accommodate the underestimated variability, is a priority for short-term development and research, and represents one step toward more accurately quantifying forecast uncertainty. Our results also underscore the importance of storing historical forecasts and the data from which they were derived to serve as a basis for assessing model performance and prioritizing future model improvements. Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.