The Canadian Updateable Model Output Statistics (UMOS) System: Design and Development Tests

Abstract

The use of model output statistics (MOS) in operational weather element prediction has been hindered since the mid-1980s by frequent changes in the operational numerical weather prediction models that supply the predictors for the weather element forecasts. Once the model changes, a new archive of model output must be collected for a long enough period that statistically stable equations can be developed. This paper describes a new statistical interpretation system that addresses this problem and permits the rapid adaptation of the statistical forecast to changes in the formulation of the driving model. In comparison with traditional MOS development, the new system incorporates two main features. First, the data are stored in the form of the cross-products matrices used in multivariate statistical techniques rather than as raw observations and forecasts. It is these matrices that are updated regularly with new output from the model. Second, equations are developed by a weighted blending of the new and old model data, with weights chosen to emphasize the new model data while including enough old model data in the development to ensure stable equations and a smooth transition to dependency on the new model. This paper describes the design of the new system and shows tests of the equation development method following a major change of the Canadian operational model. Tests were carried out for surface temperature, probability of precipitation, and wind direction and speed for about 200 Canadian stations that have a reliable observation record. For all three elements, the coefficients and predictors selected remained remarkably stable through the transition from dependence on old model data to new model data. Although some degradation of the goodness of fit was noticed during the period when new and old model forecasts were blended, especially for wind, these effects were minor, which means that useful MOS equations could be obtained relatively soon after a change of model. Results from a comparison of forecasts from the new system with operational perfect prog forecasts and direct model output forecasts are the subject of a second paper.