Shortwave (SW) cloud feedback ($$SW_{FB}$$) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report ‘likely’ maximum (4.5K) due to extratropical $$SW_{FB}$$’s that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean $$SW_{FB}$$ can be predicted from the sensitivity of column-integrated liquid water mass (LWP) to moisture convergence and to surface temperature. In this work, the response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean $$SW_{FB}$$— inconsistent with extreme ECS.
McCoy, Daniel T., et al. "Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle." Geophysical Research Letters, vol. 49, no. 8, Mar. 2022. https://doi.org/10.1029/2021gl097154
McCoy, Daniel T., Field, Paul, Frazer, Michelle E., Zelinka, Mark D., Elsaesser, Gregory S., Mülmenstädt, Johannes, Tan, Ivy, Myers, Timothy A., & Lebo, Zachary J. (2022). Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle. Geophysical Research Letters, 49(8). https://doi.org/10.1029/2021gl097154
McCoy, Daniel T., Field, Paul, Frazer, Michelle E., et al., "Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle," Geophysical Research Letters 49, no. 8 (2022), https://doi.org/10.1029/2021gl097154
@article{osti_1847915,
author = {McCoy, Daniel T. and Field, Paul and Frazer, Michelle E. and Zelinka, Mark D. and Elsaesser, Gregory S. and Mülmenstädt, Johannes and Tan, Ivy and Myers, Timothy A. and Lebo, Zachary J.},
title = {Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle},
annote = {Shortwave (SW) cloud feedback ($SW_{FB}$) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report ‘likely’ maximum (4.5K) due to extratropical $SW_{FB}$’s that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean $SW_{FB}$ can be predicted from the sensitivity of column-integrated liquid water mass (LWP) to moisture convergence and to surface temperature. In this work, the response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean $SW_{FB}$— inconsistent with extreme ECS.},
doi = {10.1029/2021gl097154},
url = {https://www.osti.gov/biblio/1847915},
journal = {Geophysical Research Letters},
issn = {ISSN 0094-8276},
number = {8},
volume = {49},
place = {United States},
publisher = {American Geophysical Union (AGU)},
year = {2022},
month = {03}}
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center; Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
European Unions Horizon 2020; National Aeronautics and Space Administration (NASA); National Science Foundation (NSF); Natural Sciences and Engineering Research Council of Canada (NSERC); USDOE; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Biological and Environmental Research (BER)
Contributing Organization:
Argonne National Laboratory (ANL); Brookhaven National Laboratory (BNL); Oak Ridge National Laboratory (ORNL); Pacific Northwest National Laboratory (PNNL)
Grant/Contract Number:
AC05-76RL01830; AC52-07NA27344; SC0020192
OSTI ID:
1847915
Alternate ID(s):
OSTI ID: 2350675 OSTI ID: 1864916 OSTI ID: 1871407
Report Number(s):
LLNL-JRNL-829480; PNNL-SA--171829
Journal Information:
Geophysical Research Letters, Journal Name: Geophysical Research Letters Journal Issue: 8 Vol. 49; ISSN 0094-8276