This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Low-frequency atmospheric variability, with time scales from one week to a few months, will be studied by identifying a small number of flow states that persist longer than most other states. Such states are widely referred to as flow regimes. The regimes are important for medium-range forecasting since their elevated persistence may translate into enhanced predictability. They are thought to arise due to planetary wave/zonal mean flow interaction in the presence of topography (Pacific and Atlantic zonal/blocked flow regimes), or low-frequency organization of the fast synoptic eddies and their subsequent feedback onto the large-scale flow (regimes associated with annular modes). Theoretical evidence suggests that the above two regime types have different spatial patterns and persistence characteristics; it is hypothesized that the regimes of the first type tend to be more geographically confined, and less persistent than the regimes of the second type. It is further conjectured that dynamical processes that drive the two types of regimes are likely to coincide, resulting in mixed regime types such as the North Atlantic Oscillation.
These hypotheses will be explored using a combination of observational analyses, theoretical modeling, and General Circulation Model (GCM) experiments. A new technique, which emerged from the investigators' previous work, will be used to isolate regimes in the observations of the Northern Hemisphere's atmospheric flow by, defining them as the episodes of flow sequences for which linear statistical forecasts have an abnormally low skill; these calculations will be performed for two-dimensional, as well as for the zonally averaged fields. A set of long simulations of idealized, quasi-geostrophic, baroclinic models, and simplified-physics general circulation models will be performed and analyzed for a wide range of parameters. Additional experiments will include case studies of regime episodes and simulations subjected to surgical removal of potentially important interactions; these analyses will elucidate processes responsible for regime behavior.
The broader impacts of this study relate to the societal significance of the problem of medium- and long-range weather forecasting. The project will strengthen scientific partnerships between the two institutions and further the development of graduate curricula and training in atmospheric dynamics and statistical methods.
