A Global, Rapidly Updating Cloud Analysis and Forecast System

The Multi-sensor Advection Diffusion nowCast system (MADCast; Descombes et al 2014)  provides regional cloud analyses and forecasts (CAF).  It employs the Weather Research and Forecasting model to advect a three-dimensional field of cloud fraction as a tracer and the Gridpoint Statistical Interpolation system as a front end to compute forward operators.  The estimated cloud fraction is updated using the multivariate minimum residual technique of Auligné (2014) and simplified cloudy radiative transfer via inexpensively computed “overcast” radiances (i.e. the radiance that would be obtained for a specified temperature and moisture profiles and a single layer of opaque cloud at each model level).  We have extended MADCast to a global CAF system by replacing WRF with the Model for Prediction Across Scales.  The assimilation step has also been enhanced, including replacing the former variational minimization with a particle-filter algorithm.  The resulting system produces hourly global CAF with only moderate computational requirements and improves on the regional system in its estimates of cloud-top and cloud-bottom pressures.