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Title: Constraining the low-cloud optical depth feedback at middle and high latitudes using satellite observations

Journal Article · · Journal of Geophysical Research: Atmospheres
DOI:https://doi.org/10.1002/2016JD025233· OSTI ID:1329360

The increase in cloud optical depth with warming at middle and high latitudes is a robust cloud feedback response found across all climate models. This study builds on results that suggest the optical depth response to temperature is timescale invariant for low-level clouds. The timescale invariance allows one to use satellite observations to constrain the models' optical depth feedbacks. Three passive-sensor satellite retrievals are compared against simulations from eight models from the Atmosphere Model Intercomparison Project (AMIP) of the 5th Coupled Model Intercomparison Project (CMIP5). This study confirms that the low-cloud optical depth response is timescale invariant in the AMIP simulations, generally at latitudes higher than 40°. Compared to satellite estimates, most models overestimate the increase in optical depth with warming at the monthly and interannual timescales. Many models also do not capture the increase in optical depth with estimated inversion strength that is found in all three satellite observations and in previous studies. The discrepancy between models and satellites exists in both hemispheres and in most months of the year. A simple replacement of the models' optical depth sensitivities with the satellites' sensitivities reduces the negative shortwave cloud feedback by at least 50% in the 40°–70°S latitude band and by at least 65% in the 40°–70°N latitude band. Furthermore, based on this analysis of satellite observations, we conclude that the low-cloud optical depth feedback at middle and high latitudes is likely too negative in climate models.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1329360
Report Number(s):
LLNL-JRNL-688437
Journal Information:
Journal of Geophysical Research: Atmospheres, Vol. 121, Issue 16; ISSN 2169-897X
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 47 works
Citation information provided by
Web of Science

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Cited By (18)

Cloud feedback mechanisms and their representation in global climate models: Cloud feedback mechanisms and their representation in GCMs journal May 2017
Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors book January 2017
Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review book May 2016
Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors journal November 2017
Processes Responsible for Cloud Feedback journal October 2016
Mechanisms Behind the Extratropical Stratiform Low‐Cloud Optical Depth Response to Temperature in ARM Site Observations journal February 2019
Quantifying climate feedbacks in polar regions journal May 2018
Progressing emergent constraints on future climate change journal March 2019
The importance of mixed-phase and ice clouds for climate sensitivity in the global aerosol–climate model ECHAM6-HAM2 journal January 2018
Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations journal January 2019
Elucidating ice formation pathways in the aerosol–climate model ECHAM6-HAM2 journal January 2019
Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project journal January 2017
The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model journal January 2019
A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness journal January 2020
Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review journal October 2017
A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness posted_content May 2020
Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project posted_content June 2017
A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness posted_content August 2019

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