WCD-14. Cloud Analysis Studies in the Rapid Refresh Forecast System (RRFS) and the Real-Time Mesoscale Analysis (RTMA)

Numerical models require successful data assimilation to provide accurate analyses and forecasts. Among the most challenging aspects is the assimilation of cloud observations. NOAA’s Global Systems Laboratory (GSL) has worked to develop state-of-the-art cloud assimilation techniques for the High-Resolution Rapid Refresh (HRRR) model currently in operation. NOAA’s regional cloud assimilation R&D efforts are now focused on the Rapid Refresh Forecast System (RRFS). Current work includes improving the stratiform cloud hydrometeor analysis to leverage interaction with the model subgrid cloud fraction. The existing cloud assimilation techniques focus on explicit clouds, which restricts the use of partial cloud observations (e.g. scattered clouds). Given the physical parameterization development to account for cloudiness within a grid cell, new analysis experiments are underway to incorporate background model cloud fraction data and use partial cloud observations from surface ceilometers. Detailed results for several case studies will be presented. GSL is also working with the NOAA Environmental Modeling Center (EMC) to create a three-dimensional real-time mesoscale analysis, 3DRTMA. This analysis requires special considerations relative to the RRFS model. Since it provides no forecast, it is desirable to represent observations as closely as possible, particularly near the surface, and it is not necessary for fields to be tightly balanced. Studies are underway to determine the optimal cloud assimilation for 3DRTMA and determine differences relative to the RRFS results. Case analysis examples will be presented to highlight the development in this area.