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Evaluating Observational Constraints on Intermodel Spread in Cloud, Temperature, and Humidity Feedbacks
Author(s) -
He Haozhe,
Kramer Ryan J.,
Soden Brian J.
Publication year - 2021
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2020gl092309
Subject(s) - environmental science , forcing (mathematics) , climatology , cloud feedback , sky , atmospheric sciences , term (time) , water vapor , humidity , climate sensitivity , consistency (knowledge bases) , climate model , cirrus , relative humidity , meteorology , climate change , computer science , geology , physics , oceanography , quantum mechanics , artificial intelligence
Uncertainty in climate feedbacks is the primary source of the spread in projected surface temperature responses to anthropogenic forcing. Cloud feedback persistently appears as the main source of disagreement in future projections while the combined lapse‐rate plus water vapor (LR + WV) feedback is a smaller (30%), but non‐trivial source of uncertainty in climate sensitivity. Here we attempt to observationally constrain the feedbacks in an effort to reduce their intermodel uncertainties. The observed interannual variation provides a useful constraint on the long‐term cloud feedback, as evidenced by the consistency of global‐mean values and regional contributions to the intermodel spread on both interannual and long‐term timescales. However, interannual variability does not serve to constrain the long‐term LR + WV feedback spread, which we find is dominated by the varying tropical relative humidity (RH) response to interhemispheric warming differences under clear‐sky conditions and the RH‐fixed LR feedback under all‐sky conditions.

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