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Abstract
One element of a complete verification system is the ability to determine why forecasts behave as they do. This paper describes and demonstrates an operationally feasible method for conducting this type of diagnostic verification analysis. Hindcasts are generated using different configurations of the forecast system and then the skill of the generated hindcasts is compared. The hindcasts and comparisons are constructed to isolate individual elements of the forecast process. The approach is used to evaluate the role of model calibration, model initial conditions, and precipitation forecasts in generating skill for deterministic river forecasts. The authors find that calibration and initial conditions provide skill for the short lead-time forecasts, with precipitation forecasts providing the majority of the skill in forecasts of high stages at longer lead times. At all lead times, this study shows model calibration is essential, as the calibration makes forecasts reliable.
Abstract
One element of a complete verification system is the ability to determine why forecasts behave as they do. This paper describes and demonstrates an operationally feasible method for conducting this type of diagnostic verification analysis. Hindcasts are generated using different configurations of the forecast system and then the skill of the generated hindcasts is compared. The hindcasts and comparisons are constructed to isolate individual elements of the forecast process. The approach is used to evaluate the role of model calibration, model initial conditions, and precipitation forecasts in generating skill for deterministic river forecasts. The authors find that calibration and initial conditions provide skill for the short lead-time forecasts, with precipitation forecasts providing the majority of the skill in forecasts of high stages at longer lead times. At all lead times, this study shows model calibration is essential, as the calibration makes forecasts reliable.
Traditionally, little attention has been focused on the systematic verification of operational hydrologic forecasts. This paper summarizes the results of forecast verification from 15 river basins in the United States. The verification scores for these forecast locations do not show improvement over the periods of record despite a number of forecast process improvements. In considering a root cause for these results, the authors note that the current paradigm for designing hydrologic forecast process improvements is driven by expert opinion and not by objective verification measures. The authors suggest that this paradigm should be modified and objective verification metrics should become the primary driver for hydrologic forecast process improvements.
Traditionally, little attention has been focused on the systematic verification of operational hydrologic forecasts. This paper summarizes the results of forecast verification from 15 river basins in the United States. The verification scores for these forecast locations do not show improvement over the periods of record despite a number of forecast process improvements. In considering a root cause for these results, the authors note that the current paradigm for designing hydrologic forecast process improvements is driven by expert opinion and not by objective verification measures. The authors suggest that this paradigm should be modified and objective verification metrics should become the primary driver for hydrologic forecast process improvements.
