Post-Processing of the National Blend of Models Daily Maximum and Minimum Temperature Percentiles to Obtain a Single Value Solution

The National Blend of Models (NBM) is a nationally consistent and skillful suite of calibrated forecast guidance based on numerical weather prediction model data. The NBM is instrumental in the National Weather Service’s (NWS) efforts to provide decision support services to protect life and property by minimizing time spent on forecast-generation and maximizing time spent on communicating potential weather hazards and their associated uncertainties with customers and core partners. NBM v4.2 is scheduled for operational implementation at the National Centers for Environmental Prediction in December of 2023.

The NBM has more recently been leveraging individual member solutions rather than an ensemble-mean to arrive at both probabilistic and deterministic guidance. A variety of ensemble models are used as input including the Global Ensemble Forecasting System (30 members), ECMWF Ensemble Prediction System (50 members), Canadian Meteorological Center Ensemble (20 members), Navy Global Environment Ensemble (20 members), and the Short-Range Ensemble Forecasting System (20 members). Two of the weather elements where NBM quantile mapping (QM) is applied are the maximum and minimum daily temperatures. While a full spectrum (1-99) of percentiles is generated for each cycle/projection/grid point and is useful in determining the uncertainty of the forecasts, some users still require a single value forecast. For any given day the 50th percentile may not be the best choice. The question then becomes what value inside the percentile distribution is the best estimate for the daily maximum or minimum deterministic forecast. This presentation explores the use of Model Output Statistics (MOS) as a possible method to arrive at such a solution which performs more skillfully than the median QM forecast values.