New method for estimating the impact of heterogeneous forcing on atmospheric circulations

Authors

  • Tomislava Vukicevic,

    1. Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado, USA
    2. Also at Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, Colorado, USA.
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  • Roger A. Pielke Sr.,

    1. Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado, USA
    2. Also at Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, Colorado, USA.
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  • Adriana Beltrán-Przekurat

    1. Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado, USA
    2. Also at Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, Colorado, USA.
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Abstract

[1] In this study, a new method for estimating the impact of heterogeneous forcing on atmospheric circulations is discussed. This new method is similar to the commonly used model-based sensitivity studies in that the impact of forcing is diagnosed by a suitable measure of differences between atmospheric states with and without forcing, but it differs in the way the atmospheric states are evaluated: by combining standard atmospheric data analysis, observationally based estimates of the forcing, atmospheric observations, and general circulation model (GCM) ensemble simulations. A new numerical technique, derived from the ensemble Kalman filter data assimilation approach, is used for objective estimation of the atmospheric state not affected by the forcing. Using a tutorial example, numerical experiments were conducted varying an asymmetric thermal forcing as a proxy for the heterogeneous forcing. Results show that the method is capable of producing skilled estimates of the impact of the forcing. Strategies for application of the method with real-world data and GCMs are discussed. This new method is expected to produce more realistic estimates of the forcing impact than the standard model sensitivity approach because of the explicit use of the observationally based estimates of atmospheric states and forcing.