forecasting local weather by means of model output statistics

Experience over the past decade has shown that objective forecasts of local weather elements can best be obtained by using statistical methods to complement the raw output of numerical prediction models. One of the most successful techniques for accomplishing this is called Model Output Statistics (MOS). The MOS method involves matching observations of local weather with output from numerical models. Forecast equations are then derived by statistical techniques such as screening regression, regression estimation of event probabilities, and the logit model. In this way the bias and inaccuracy of the numerical model, as well as the local climatology, can be built into the forecast system. MOS has been applied by the Techniques Development Laboratory to produce automated forecasts of numerous weather elements including precipitation, temperature, wind, clouds, ceiling, visibility, and thunderstorms. In this paper, the derivation and operational application of MOS forecasts for each of these elements are discussed. Many of the products are transmitted nationwide over facsimile and/or teletypewriter; others are provided for internal use within the National Weather Service. Ultimately, a completely automated, computer-worded, local weather forecast will be produced routinely as part of a program for Automation of Field Operations and Services (AFOS).