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

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. Moreover, 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.
Authors:
ORCiD logo [1] ; ORCiD logo [2] ;  [1] ;  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. California Inst. of Technology (CalTech), Pasadena, CA (United States); Cornell Univ., Ithaca, NY (United States)
Publication Date:
Report Number(s):
PNNL-SA-119611
Journal ID: ISSN 1680-7324; 400403809
Grant/Contract Number:
AC05-76RL01830
Type:
Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 17; Journal Issue: 4; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1346283

Kravitz, Ben, MacMartin, Douglas G., Rasch, Philip J., and Wang, Hailong. Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models. United States: N. p., Web. doi:10.5194/acp-17-2525-2017.
Kravitz, Ben, MacMartin, Douglas G., Rasch, Philip J., & Wang, Hailong. Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models. United States. doi:10.5194/acp-17-2525-2017.
Kravitz, Ben, MacMartin, Douglas G., Rasch, Philip J., and Wang, Hailong. 2017. "Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models". United States. doi:10.5194/acp-17-2525-2017. https://www.osti.gov/servlets/purl/1346283.
@article{osti_1346283,
title = {Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models},
author = {Kravitz, Ben and MacMartin, Douglas G. and Rasch, Philip J. and Wang, Hailong},
abstractNote = {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. Moreover, 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.},
doi = {10.5194/acp-17-2525-2017},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 4,
volume = 17,
place = {United States},
year = {2017},
month = {2}
}