Using the Data Assimilation Research Testbed to Assess Predictability in the Great Lakes

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Sunday, 4 January 2015
James Kessler, University of Michigan, Ann Arbor, MI

The Great Lakes Region is a unique place to assess weather predictability. The lakes act as thermal regulators and sources for atmospheric moisture. Although we are able to characterize some of the weather phenomena of this region, there is still much to be learned regarding which initial states in the atmosphere lead to a more or less predictable future state. The Data Assimilation Research Testbed (DART) can give insight into this matter. The Ensemble Kalman Filter used by DART provides a spread of future states by perturbing initial conditions and running independent ensemble members in a numerical model. By comparing the spread of this ensemble to the initial conditions, we can elucidate which factors contribute to the predictability of the future state of the atmosphere in the Great Lakes.