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Verification of objective sensitivity climatologies of Mediterranean intense cyclones: test against human judgement

A variety of sensitivity climatologies of Mediterranean intense cyclones have been recently built owing to the growing international interest in contributing to the basic understanding and the short‐range forecasting of high‐impact weather events. The verification of these climatologies is essential to ensure the reliability of the sensitivity products and ultimately provide robust guidance to policy‐makers on plans to redefine routine observational strategies. This work tackles the arduous task of verifying the available (an adjoint‐based and two different ensemble‐based) sensitivity climatologies of Mediterranean intense cyclones. We perform Observing System Simulation Experiments (OSSE) with the WRF ARW model for 25 of the most intense Mediterranean cyclones detected in the ERA‐40 database to test the ability of each method in identifying areas where perturbations in the initial conditions derived from the sensitivity fields lead to a greater impact on the forecast of intense cyclones. For the sake of a sensible reference, the performance of the available sensitivity climatologies is tested against the judgement of an experienced severe weather meteorologist. In addition, a control measure of the background random response is also carried out. The impact on the prediction of intense Mediterranean cyclones of prescribed perturbations to the initial conditions is evaluated comparing each perturbed experiment with a control simulation. Furthermore, a quantitative study of the linearity of the evolution of the perturbations is performed using twin perturbations. Results confirm a statistically significant superior skill of the human and adjoint sensitivity fields against both ensemble sensitivity climatologies. Climatological ensemble sensitivities only show a noticeable improvement upon non‐sensitivity experiments when an ad hoc classification of cyclones is used. This reveals one fundamental limitation of the ensemble sensitivity technique in climatological mode when it is applied to rare events insufficiently sampled in the available datasets. Copyright © 2011 Royal Meteorological Society