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Title: Insensitivity of the Cloud Response to Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud Microphysics: Results From the Ultraparameterized CAM

Abstract

We study the cloud response to a +4K surface warming in a new multiscale climate model that uses enough interior resolution to begin explicitly resolving boundary layer turbulence (i.e., ultraparameterization or UP). UP's predictions are compared against those from standard superparameterization (SP). The mean cloud radiative effect feedback turns out to be remarkably neutral across all of our simulations, despite some radical changes in both cloud microphysical parameter settings and cloud-resolving model grid resolution. The overall low cloud response to warming is a positive low cloud feedback over land, a negative feedback (driven by cloud optical depth increase) at high latitudes, and weak feedback over the low-latitude oceans. The most distinct effects of UP result from tuning decisions impacting high-latitude cloud feedback. UP's microphysics is tuned to optimize the model present-day, top-of-atmosphere radiation fluxes against CERES observations, by lowering the cloud ice-liquid phase shift temperature ramp, adjusting the ice/liquid autoconversion rate, and increasing the ice fall speed. This reduces high-latitude low cloud amounts and damps the optical depth feedback at high latitudes, leading to a slightly more positive global cloud feedback compared to SP. Lastly, a sensitivity test that isolates these microphysical impacts from UP's grid resolution confirms that themore » microphysical settings are mostly responsible for the differences between SP and UP cloud feedback.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [4]
  1. Univ. of California, Irvine, CA (United States). Dept. of Earth System Science
  2. Univ. of Washington, Seattle, WA (United States). Dept. of Atmospheric Sciences
  3. Stony Brook Univ., NY (United States). School of Marine and Atmospheric Sciences
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Atmospheric Sciences and Global Change Division
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1490381
Report Number(s):
PNNL-SA-140100
Journal ID: ISSN 1942-2466
Grant/Contract Number:  
SC0012548; AC05-76RL01830
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 10; Journal Issue: 12; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; ultraparameterization; cloud feedback; boundary layer; surface warming; model tuning; low clouds

Citation Formats

Parishani, Hossein, Pritchard, Michael S., Bretherton, Christopher S., Terai, Christopher R., Wyant, Matthew C., Khairoutdinov, Marat, and Singh, Balwinder. Insensitivity of the Cloud Response to Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud Microphysics: Results From the Ultraparameterized CAM. United States: N. p., 2018. Web. doi:10.1029/2018MS001409.
Parishani, Hossein, Pritchard, Michael S., Bretherton, Christopher S., Terai, Christopher R., Wyant, Matthew C., Khairoutdinov, Marat, & Singh, Balwinder. Insensitivity of the Cloud Response to Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud Microphysics: Results From the Ultraparameterized CAM. United States. doi:10.1029/2018MS001409.
Parishani, Hossein, Pritchard, Michael S., Bretherton, Christopher S., Terai, Christopher R., Wyant, Matthew C., Khairoutdinov, Marat, and Singh, Balwinder. Tue . "Insensitivity of the Cloud Response to Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud Microphysics: Results From the Ultraparameterized CAM". United States. doi:10.1029/2018MS001409. https://www.osti.gov/servlets/purl/1490381.
@article{osti_1490381,
title = {Insensitivity of the Cloud Response to Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud Microphysics: Results From the Ultraparameterized CAM},
author = {Parishani, Hossein and Pritchard, Michael S. and Bretherton, Christopher S. and Terai, Christopher R. and Wyant, Matthew C. and Khairoutdinov, Marat and Singh, Balwinder},
abstractNote = {We study the cloud response to a +4K surface warming in a new multiscale climate model that uses enough interior resolution to begin explicitly resolving boundary layer turbulence (i.e., ultraparameterization or UP). UP's predictions are compared against those from standard superparameterization (SP). The mean cloud radiative effect feedback turns out to be remarkably neutral across all of our simulations, despite some radical changes in both cloud microphysical parameter settings and cloud-resolving model grid resolution. The overall low cloud response to warming is a positive low cloud feedback over land, a negative feedback (driven by cloud optical depth increase) at high latitudes, and weak feedback over the low-latitude oceans. The most distinct effects of UP result from tuning decisions impacting high-latitude cloud feedback. UP's microphysics is tuned to optimize the model present-day, top-of-atmosphere radiation fluxes against CERES observations, by lowering the cloud ice-liquid phase shift temperature ramp, adjusting the ice/liquid autoconversion rate, and increasing the ice fall speed. This reduces high-latitude low cloud amounts and damps the optical depth feedback at high latitudes, leading to a slightly more positive global cloud feedback compared to SP. Lastly, a sensitivity test that isolates these microphysical impacts from UP's grid resolution confirms that the microphysical settings are mostly responsible for the differences between SP and UP cloud feedback.},
doi = {10.1029/2018MS001409},
journal = {Journal of Advances in Modeling Earth Systems},
issn = {1942-2466},
number = 12,
volume = 10,
place = {United States},
year = {2018},
month = {12}
}

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