Applying the Diagnostic Cloud Forecast (DCF) Model to the Global Air-Land Weather Exploitation Model (GALWEM) at the U.S. Air Force 557th Weather Wing

Air Force Weather uses cloud forecasts from the Diagnostic Cloud Forecast (DCF) model to support global Department of Defense (DoD) missions and the missions of their external partners. Four times per day, the DCF model generates global, three-dimensional cloud forecasts out to five days using data from the World-Wide Merged Cloud Analysis (WWMCA) and a Numerical Weather Prediction (NWP) model. Predictor variables from the NWP model are statistically related to the observed clouds represented by the WWMCA, and predictive coefficients are generated. These coefficients are then applied to a current NWP model run to predict cloud amount on 21 pressure levels, with cloud layers being derived using the vertical cloud profile and the geopotential heights of the pressure levels. DCF is purely a statistical model that uses no additional physics beyond those inherent in the NWP model. Historically, the DCF process has been applied to several NWP models, including MM5, WRF, GFS, and the Air Force's Mesoscale Ensemble Prediction System.

As part of Air Force Weather's ongoing transition to the Global Air-Land Weather Exploitation Model (GALWEM) as the global model of choice, work has been done to incorporate this model in the DCF process. The Air Force currently runs GALWEM with 17 km horizontal resolution, which is much finer than the operational GFS-based DCF which is on a global, 0.5 degree grid. This presentation will include an overview of the DCF model and how it is used with the GALWEM to generate three-dimensional cloud forecasts. Ideas for future work also will be addressed.