Extreme weather events (EWEs) related to variations in the energy and water cycles have important economic and societal consequences. EWEs include extreme temperature events such as cold air outbreaks and heat waves as well as extreme precipitation events such as floods and droughts. The frequency of EWEs is strongly impacted by planetary-scale climate modes (PCMs) such as El-Nino Southern Oscillation or the Pacific Decadal Oscillation. PCMs alone are insufficient, however, in producing EWEs and intermediary large-scale meteorological patterns (LMPs) such as atmospheric blocking events, cyclones, and polar anticyclones are required for EWE occurrence.  There are several existing scientific needs related to EWEs and their associated LMPs: (1) establishing uniformity and simplicity in determining the LMPs linked to EWEs, (2) pursuing coordinated research on the physical mechanisms causing LMPs, (3) identifying key atmospheric features and physical processes that can be used to define metrics for climate model diagnosis and (4) pursuing coordinated research on validating EWEs and LMPs structure and physics in coupled climate models.

The research is a collaborative effort between Georgia Tech and DOE’s ORNL that addresses the existing knowledge shortcomings in relation to DOE RGCM research priorities. The research examines the following energy and water cycle extremes: winter cold air outbreaks and warm waves, summer heat waves, and droughts and floods. The research concentrates on revealing a dynamical pathway for the large-scale organization and scale interaction bridging PCMs, LMPs, and EWEs. The initial part of our research employs atmospheric observational data and focuses on (a) objectively characterizing LMPs associated with different classes of EWEs and (b) developing simple and concise atmospheric circulation metrics for identifying such LMPs in gridded datasets.

The second part of our project is a diagnosis of the physical mechanisms by which (a) the implicated LMPs arise, (b) LMPs enact EWEs and (c) natural modes of climate variability (i.e., PCMs) serve to modulate LMPs/EWEs. Inferences are based upon the collective consideration of various dynamical diagnostic tools geared to assess sources for large-scale extratropical atmospheric circulation patterns. Processes assessed include anomalous boundary forcing (local and remote), large-scale flow instability and multi-scale interactions. The diagnostic analyses are supplemented with sensitivity experiments (using DOE models at ORNL) to discriminate among the respective roles of anomalous forcing related to sea surface temperature, Arctic sea ice and Eurasian snow cover. The diagnostic results are then used to construct a set of dynamical metrics representing key circulation features and physical processes essential to forcing EWEs. Both circulation and dynamical metrics will be incorporated into a formal evaluation process to be used in DOE model development efforts.

The third part of our project is the parallel study of EWEs, LMPs and PCMs in CGCM simulations of historical and future climate, emphasizing CMIP5 model output and DOE model development efforts related to the CESM. There is particular interest in assessing the benefits gained via the enhanced spatial resolution of emerging coupled model simulations at ORNL.  The model validation studies are (a) informed by our observational analyses and (b) facilitated by our circulation and dynamical metrics. Existing model shortcomings are then studied mechanistically to determine the physical and dynamical processes that are missing or misrepresented in the models, providing valuable information for model improvement. Lastly, future changes in EWE behavior, and the evolving role(s) of LMPs and PCMs in enacting these changes, are isolated.