Experimental LAMP 1-h Probabilistic QPF Guidance for the CONUS in Support of the National Weather Service’s National Blend of Models

The National Weather Service (NWS) is developing the National Blend of Models (NBM) to provide a nationally-consistent and skillful starting point for making National Digital Forecast Database (NDFD) forecasts. In 2017, the NBM began producing Precipitation Potential Index (PPI) and Quantitative Precipitation Forecast (QPF) guidance over the CONUS for 1-h periods through 36 hours, derived with an ad hoc expert-weighting scheme applied to each NBM grid point. While the provision of hourly PPI and QPF was designed to assist forecasters with the timing of weather events in the day 1-2 period, these products are uncalibrated and may exhibit biases inherent in the underlying model QPFs used as input.

The Localized Aviation MOS Program (LAMP) is a critical component of the NBM in the short-range period through 24 hours. An upgrade is planned for late 2018 to expand the LAMP suite of guidance in response to growing NBM requirements. This upgrade will include 1) expansion of the Gridded LAMP (GLMP) spatial extent over the CONUS to cover the full NBM domain, 2) expansion of forecast projections out to 36 hours, and 3) addition of 1-h Probabilistic QPF (hereafter “PQPF01”) guidance over the CONUS. LAMP PQPF01 will provide probabilities of exceedance for several precipitation thresholds and a corresponding derived QPF amount, which will serve as calibrated precipitation inputs to the NBM.

The LAMP PQPF01 predictand is derived from Multi-Radar Multi-Sensor (MRMS) 1-h gauge-corrected quantitative precipitation estimates (QPE) interpolated to the 2.5 km NBM grid. Candidate predictors for the “Base LAMP” PQPF01 regression equations include initial and advected observations of 1-h QPE and composite reflectivity from MRMS, total lightning flashes, GFS-based and NAM-based MOS, and a high-resolution precipitation climatology. The GLMP “Meld” approach is employed for the development, which statistically combines model output from the High Resolution Rapid Refresh (HRRR) with Base LAMP PQPF01 to yield calibrated and skillful forecasts. Further details on the development procedure, verification results, a few case studies, and plans for operational implementation will be presented at the conference.