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. Two feature-based verification methods, thus far only used for thediagnostic evaluation of atmospheric models, have been applied to compare∼7 km resolution pre-operational analyses of chlorophyll-a(Chl-a) concentrations to a 1 km gridded satellite-derived Chl-aconcentration product. The aim of this study was to assess the value ofapplying such methods to ocean models. Chl-a bloom objects were identified inboth data sets for the 2019 bloom season (1 March to 31 July). These bloomobjects were analysed as discrete (2-D) spatial features, but also asspace–time (3-D) features, providing the means of defining the onset,duration and demise of distinct bloom episodes and the season as a whole. The new feature-based verification methods help reveal that the modelanalyses are not able to represent small coastal bloom objects, given thecoarser definition of the coastline, also wrongly producing more bloomobjects in deeper Atlantic waters. Model analyses' concentrations aresomewhat higher overall. The bias manifests itself in the size of the modelanalysis bloom objects, which tend to be larger than the satellite-derivedbloom objects. The onset of the bloom season is delayed by 26 d in themodel analyses, but the season also persists for another month beyond thediagnosed end. The season was diagnosed to be 119 d long in the modelanalyses, compared to 117 d from the satellite product. Geographically,the model analyses and satellite-derived bloom objects do not necessarilyexist in a specific location at the same time and only overlapoccasionally.

ocean science

Using feature-based verification methods to explore the spatial and temporal characteristics of the 2019 chlorophyll-&amp;lt;i&amp;gt;a&amp;lt;/i&amp;gt; bloom season in a model of the European Northwest Shelf