Process-oriented diagnosis of tropical cyclones based on the moist static energy variance budget in reanalyses and high-resolution climate models

<p>Process-oriented diagnostics of tropical cyclones (TCs) facilitate a comparison of models to observations with respect to the&#160;physical processes relevant to TCs,&#160;informing which processes to target for model improvement. Here we use diagnostics&#160;based on the column-integrated moist&#160;static energy (MSE) variance budget, which focuses on how convection, moisture,&#160;clouds, and related processes are coupled.&#160;We use five different reanalysis datasets to provide an 'observation'-based&#160;reference against which high-resolution global&#160;climate models can be evaluated: ERA-Interim, MERRA-2, CFSR, ERA-5, and&#160;JRA-55. We calculate the budget in 10 x 10&#160;degree boxes following tracked TCs composites over storm snapshots of the same intensity. The composites are&#160;qualitatively similar to prior work, with radiative feedbacks contributing&#160;most to MSE variance growth in the early stages of TC&#160;development and in weaker storms, and with surface flux feedbacks&#160;increasing strongly with intensity. Reanalyses that have&#160;a stronger radiative feedback, normalized by the box-mean MSE&#160;variance, in a given intensity bin exhibit a higher percentage&#160;of storms that intensify to the next bin, which emphasizes the&#160;value of the MSE variance budget as a process-oriented&#160;diagnostic for understanding model simulation of TCs. However, there is a large spread in MSE variance and the radiative&#160;and surface flux feedback contributions to MSE variance growth across reanalyses,&#160;even when considering composites over&#160;storms of the same intensity. The spread across reanalyses is comparable to the spread across the high-resolution climate&#160;models considered by Wing et al. (2019). This suggests that the data assimilation present in reanalyses does little to&#160;constrain the TC-MSE variance budget and indicates that caution must be taken when evaluating climate models against&#160;reanalysis.&#160;Ongoing work continues to evaluate climate model simulations, including those from the HighResMIP ensemble,&#160;against the reanalysis-based reference, and examine the large-scale environments associated with TC formation in&#160;reanalyses.</p>