2024
DOI: 10.1029/2023ms003700
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The Green's Function Model Intercomparison Project (GFMIP) Protocol

Jonah Bloch‐Johnson,
Maria A. A. Rugenstein,
Marc J. Alessi
et al.

Abstract: The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.” To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the b… Show more

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Cited by 7 publications
(2 citation statements)
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References 112 publications
(115 reference statements)
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“…The response of climate to localized tropical SST perturbations demonstrates considerable non-linearity, highlighting the importance of both the spatial pattern and magnitude of SST changes 43 . This pattern effect, therefore, should be carefully understood addressing the drivers of the amplitude and sign of SST perturbations 44 , 45 . Indeed, for the analysis on the relationship between TOA radiative fluxes and SST, there was disparities by the selection of domain 14 .…”
Section: Discussionmentioning
confidence: 99%
“…The response of climate to localized tropical SST perturbations demonstrates considerable non-linearity, highlighting the importance of both the spatial pattern and magnitude of SST changes 43 . This pattern effect, therefore, should be carefully understood addressing the drivers of the amplitude and sign of SST perturbations 44 , 45 . Indeed, for the analysis on the relationship between TOA radiative fluxes and SST, there was disparities by the selection of domain 14 .…”
Section: Discussionmentioning
confidence: 99%
“…We developed a precipitation Green's function (GF P ) to identify which SST regions influence SWUS (32°-40°N, 124°-105°W) precipitation (e.g., Alessi & Rugenstein, 2023b;Bloch-Johnson et al, 2024;Y. Dong et al, 2019;Zhang et al, 2023;Zhou et al, 2017).…”
Section: Methodsmentioning
confidence: 99%