The paper discusses the use of Model Output Statistics (MOS) in objective weather forecasting, which involves determining statistical relationships between predictands and variables forecast by numerical models. MOS is applied to predict surface wind, probability of precipitation, maximum temperature, cloud amount, and conditional probability of frozen precipitation. The technique uses surface observations and model outputs from the Subsynoptic Advection Model (SAM) and the Primitive Equation model. Verification scores are computed and compared with other objective techniques and official forecasts. MOS forecasts are disseminated by the National Weather Service over teletype and facsimile. The paper highlights the usefulness of MOS in objective weather forecasting, particularly for probability forecasts, and discusses the operational implementation and verification of MOS products.The paper discusses the use of Model Output Statistics (MOS) in objective weather forecasting, which involves determining statistical relationships between predictands and variables forecast by numerical models. MOS is applied to predict surface wind, probability of precipitation, maximum temperature, cloud amount, and conditional probability of frozen precipitation. The technique uses surface observations and model outputs from the Subsynoptic Advection Model (SAM) and the Primitive Equation model. Verification scores are computed and compared with other objective techniques and official forecasts. MOS forecasts are disseminated by the National Weather Service over teletype and facsimile. The paper highlights the usefulness of MOS in objective weather forecasting, particularly for probability forecasts, and discusses the operational implementation and verification of MOS products.