Barbara Casati

Intercomparison of Spatial Forecast Verification Methods

Abstract Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because of the increased small-scale variability so that the true quality of the forecasts is not always characterized well. As a result, numerous new methods for verifying these forecasts have been proposed. These new methods can mostly be classified into two overall categories: filtering methods and displacement methods. The filtering methods can be further delineated into neighborhood and scale separation, and the displacement methods can be divided into features based and field deformation. Each method gives considerably more information than the traditional scores, but it is not clear which method(s) should be used for which purpose. A verification methods intercomparison project has been established in order to glean a better understanding of the proposed me...

New Developments of the Intensity-Scale Technique within the Spatial Verification Methods Intercomparison Project

Abstract The intensity-scale verification technique introduced in 2004 by Casati, Ross, and Stephenson is revisited and improved. Recalibration is no longer performed, and the intensity-scale skill score for biased forecasts is evaluated. Energy and its percentages are introduced in order to assess the bias on different scales and to characterize the overall scale structure of the precipitation fields. Aggregation of the intensity-scale statistics for multiple cases is performed, and confidence intervals are provided by bootstrapping. Four different approaches for addressing the dyadic domain constraints are illustrated and critically compared. The intensity-scale verification is applied to the case studies of the Intercomparison of Spatial Forecast Verification Methods Project. The geometric and synthetically perturbed cases show that the intensity-scale verification statistics are sensitive to displacement and bias errors. The intensity-scale skill score assesses the skill for different precipitation in...

The set-up of the Mesoscale Verification Inter-Comparison over Complex Terrain (MesoVICT) Project

CapsuleThe project focuses on spatial verification methods as applied to high resolution forecasts of deterministic and ensemble precipitation, wind and temperature forecasts over complex terrain, and includes observation uncertainty assessment.