Intercomparison of Tropospheric and Stratospheric Mesoscale Kinetic Energy Resolved by the High‐Resolution Global Reanalysis Datasets

Abstract With the development of advanced data assimilation and computing techniques, many modern global reanalysis datasets aim to resolve the atmospheric mesoscale spectrum. However, large uncertainties remain with respect to the representation of mesoscale motions in these reanalysis datasets, for which a clear understanding is lacking. The above challenges have served as a strong motivation to reveal and quantify their mesoscale differences. This study presents the first comprehensive global intercomparison of the tropospheric and stratospheric mesoscale kinetic energy and its spectra over two selected periods of summer and winter events among six leading high‐resolution atmospheric reanalysis products, including ERA5, CRA, MERRA2, CFSv2, JRA‐55, and ERA‐I. A state‐of‐the‐art global operational model is adopted as a supplementary reference. Although all reanalysis datasets can reproduce broad distribution characteristics that are grossly consistent with the 9‐km model, there are substantial discrepancies among them in magnitudes. The ability to capture mesoscale signals is closely linked to their resolutions, but it is also impacted by other factors, including but not limited to the selected types of energy, seasons, altitudes, latitudes, model diffusions, parameterization schemes, moist condition, assimilation methods, and observation inputs. Moreover, all datasets illustrate conclusive behaviors for the prevalence of the rotational component in the troposphere, while only very few products fail to exhibit the dominance of the divergent component in the stratosphere. Overall, stratospheric ERA5 and CFSv2 outperform the other reanalysis datasets, and only these two can reproduce the feature of the canonical kinetic energy spectrum with a distinct shift from a steeper slope (~‐3) at lower wavenumbers to a shallower slope (~‐5/3) at higher wavenumbers. In addition, the relative disparities among datasets increase dramatically with height and they are more pronounced in the divergent component. It is also found that the correlations among these datasets are much weaker in the tropics. This article is protected by copyright. All rights reserved.