Evaluation of New Methods for Verification of Cloud Predictions

Verification of gridded cloud predictions continues to be a challenge, particularly with regard to obtaining information about how well forecasts replicate spatial features.  Recently, a variety of spatial verification methods (e.g., object-based, neighborhood, scale separation, image warping) have been developed, primarily focused on application to numerical weather prediction (NWP) model forecasts of precipitation. Although these approaches are suitable for application to any variable characterized by coherent spatial features, they have not been widely applied to other fields.  In a project collaboration between NCAR and the Air Force 557th Weather Wing, a number of new approaches for evaluation of gridded cloud predictions have been examined.  The forecasts included advection products as well as predictions from NWP models. The verification approaches examined include the Method for Object-based Diagnostic Evaluation (MODE); several distance measures; the Structure, Amplitude, and Location (SAL) approach; and image warping.  Results of application of these different approaches to a set of advection and NWP-based cloud amount predictions will be presented; positive and negative aspects associated with application of each method will be discussed.