We present a statistical procedure that generates reliable short-term streamflow ensemble forecasts from operational single-value forecasts. Referred to as the Hydrologic Model Output Statistics (HMOS) streamflow ensemble processor, the procedure uses linear regression between observed and forecast streamflows in the normal space that minimizes a weighted sum of the root mean square error and the error in the probability distribution
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