A New Spatial Distance Metric for Verification of Precipitation

Abstract

Precipitation is an essential meteorological variable affecting the biosphere and human societies. At the same time, precipitation is notoriously difficult to predict and verify. A new spatial distance metric for verification of precipitation is presented. It is called the Precipitation Smoothing Distance (PSD). The aim was to develop a measure that would provide a good and meaningful approximation of the displacement of precipitation events in the two fields. An estimate of spatial displacement is very appealing for forecast interpretation because it is easy to understand and mimics how humans tend to judge fields by eye. Contrary to most other distance metrics, the new metric does not require thresholding and can thus be used to analyze binary and non-binary fields (e.g., continuous or multi-level). The analysis of idealized situations showed that the new metric provides a meaningful approximation of the displacement. Typically the estimate of displacement provided by PSD was better than the results provided by most other metrics. The measure is also not overly sensitive to noise, its results are directly related to the actual displacements of precipitation events, and the events with a larger magnitude have a bigger influence on the resulting value. The analysis of ECMWF precipitation forecasts over Europe and North Africa confirmed that the new metric provides a meaningful approximation of the displacement even in more complex real-world situations.