Intercomparison of Tropospheric and Stratospheric Mesoscale Kinetic Energy Resolved by the High-Resolution Global Reanalysis Datasets
- 1School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
- 2Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, China
- 3Key Laboratory of Tropical Atmosphere-Ocean System, Sun Yat-sen University, Ministry of Education, Zhuhai, China
- 4State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
- 5Department of Mechanical Engineering, Rice University, Houston, Texas, USA
This talk will present our recent published study of Li et al. (2023, QJ). 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 aforementioned 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: European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), China Meteorological Administration Reanalysis (CRA), Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2), National Centers for Environmental Prediction's Climate Forecast System version 2 (CFSv2), Japanese 55-year Reanalysis (JRA-55), and ECMWF Reanalysis-Interim (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, parametrization schemes, moist condition, assimilation methods, and observation inputs. Moreover, all datasets illustrate conclusive behaviors for the prevalence of the rotational component in the troposphere, whereas 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 (approximately −3) at lower wave numbers to a shallower slope (approximately −5/3) at higher wave numbers. 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.
Reference:
How to cite: Li, Z., Wei, J., Bao, X., and Sun, Y. Q.: Intercomparison of Tropospheric and Stratospheric Mesoscale Kinetic Energy Resolved by the High-Resolution Global Reanalysis Datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1826, https://doi.org/10.5194/egusphere-egu24-1826, 2024.