Identifying and Comparing Flavors of Tropospheric Rossby Wave Breaking and Their Associated Sensible Weather Features between the ERA5 and LENS2 Datasets.

Rossby wave breaking (RWB) occurs when synoptic-scale Rossby waves become highly amplified and break, leading to tropospheric impacts ranging from changes in jet stream intensity and position to precipitation extremes. Traditionally, the type of breaking is categorized as anticyclonic (AWB) or cyclonic (CWB) and can be identified using the orientation of streamers of high potential temperature (θ) and low θ air on a potential vorticity surface. Self-organizing maps (SOM), a machine learning method, can be used to cluster RWB events into archetypal patterns, or “flavors”, for each type of RWB (i.e., AWB and CWB). We recently completed an examination of differences in RWB flavors, and their associated tropospheric impacts, using the European Centre for Medium Range Weather Forecasting Reanalysis v5 (ERA5) dataset. We found that a subset of flavors within each wave break type can result in robust moisture transport and large synoptic scale precipitation. Given these impacts, it is important to also understand how RWB events, and their associated sensible weather features, are represented in climate models. In this study, AWB and CWB are identified from overturning isentropes on the dynamic tropopause (DT) in the Community Earth System Large Ensemble v2 (CESM-LENS2) climate model output during December, January, and February (DJF) 1980-2014 (i.e., historical period). RWB flavors are identified in the LENS2 for comparison to the ERA5 dataset for the same time period. Composites of tropospheric dynamic and thermodynamic fields are calculated for each RWB flavor to understand the impact of AWB and CWB structure on the overall circulation pattern and sensible weather extremes. Next, we compare the RWB flavors between the LENS2 and the ERA5. First, the frequency of occurrence of each RWB flavor is calculated for each dataset to identify differences in how often these flavors occur. Second, differences in the sensible weather features associated with each flavor are quantified. This process-orientated climate model evaluation of the LENS2 as compared to the ERA5 can provide insight into the source of model errors in the LENS2 climate model.