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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 4 | Copyright
Atmos. Chem. Phys., 17, 2525-2541, 2017
https://doi.org/10.5194/acp-17-2525-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Technical note 17 Feb 2017

Technical note | 17 Feb 2017

Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

Ben Kravitz1, Douglas G. MacMartin2,3, Philip J. Rasch1, and Hailong Wang1 Ben Kravitz et al.
  • 1Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
  • 2Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA
  • 3Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA

Abstract. We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to those of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Furthermore, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.

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We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state.
We introduce system identification techniques to climate science wherein multiple dynamic...
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