Skill Tests and Parametric Statistics for Model Evaluation

Dingman, J. Steven; Bedford, Keith W.

doi:10.1061/(asce)0733-9429(1986)112:2(124)

Cited by 8 publications

(3 citation statements)

References 13 publications

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“…A time difference of 0 h is given a score of 1.0. Following Dingman and Bedford (1986), early forecasts of the time of occurrence received a higher score than a late prediction.…”

Section: Generation and Evaluation Of Coupled Forecastsmentioning

confidence: 99%

“…It is considered an alternative to the correlation coefficient, which suffers from its inability to discern differences in proportionality and/or constant additive differences between the two variables (Willmott 1982). The two skill tests included the peak amplitude skill and the phase tests (Dingman and Bedford 1986). The amplitude skill test was used to determine the ability of the model to forecast the maximum and minimum water levels at opposite ends of the lake.…”

Section: Generation and Evaluation Of Coupled Forecastsmentioning

confidence: 99%

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Generation of Three-Dimensional Lake Model Forecasts for Lake Erie*

et al. 1998

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A one-way coupled atmospheric-lake modeling system was developed to generate short-term, mesoscale lake circulation, water level, and temperature forecasts for Lake Erie. The coupled system consisted of the semioperational versions of the Pennsylvania State University-National Center for Atmospheric Research threedimensional, mesoscale meteorological model (MM4), and the three-dimensional lake circulation model of the Great Lakes Forecasting System (GLFS). The coupled system was tested using archived MM4 36-h forecasts for three cases during 1992 and 1993. The cases were chosen to demonstrate and evaluate the forecasts produced by the coupled system during severe lake conditions and at different stages in the lake's annual thermal cycle. For each case, the lake model was run for 36 h using surface heat and momentum fluxes derived from MM4's hourly meteorological forecasts and surface water temperatures from the lake model. Evaluations of the lake forecasts were conducted by comparing forecasts to observations and lake model hindcasts. Lake temperatures were generally predicted well by the coupled system. Below the surface, the forecasts depicted the evolution of the lake's thermal structure, although not as rapidly as in the hindcasts. The greatest shortcomings were in the predictions of peak water levels and times of occurrence. The deficiencies in the lake forecasts were related primarily to wind direction errors and underestimation of surface wind speeds by the atmospheric model. The three cases demonstrated both the potential and limitations of daily high-resolution lake forecasts for the Great Lakes. Twice daily or more frequent lake forecasts are now feasible for Lake Erie with the operational implementation of mesoscale atmospheric models such as the U.S. National Weather Service's Eta Model and Rapid Update Cycle.

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“…A time difference of 0 h is given a score of 1.0. Following Dingman and Bedford (1986), early forecasts of the time of occurrence received a higher score than a late prediction.…”

Section: Generation and Evaluation Of Coupled Forecastsmentioning

confidence: 99%

Section: Generation and Evaluation Of Coupled Forecastsmentioning

confidence: 99%

Generation of Three-Dimensional Lake Model Forecasts for Lake Erie*

et al. 1998

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“…IOA is related to the RMSE and is defined as IOA=1-(n×RMSE 2 )/PE, where PE is the potential error and IOA ranges from 0 to 1 with 1 being perfect agreement. Skill score is a non-parametric-based statistic developed by Dingman and Bedford (1986) to assess the model credibility. …”

Section: Statistic Metricsmentioning

confidence: 99%