Vertical Profile Analysis of Cloud Feedbacks

Abstract Cloud feedback is the largest source of uncertainty in climate sensitivity. This feedback is generally discussed in terms of radiative flux at the top of the atmosphere, but the vertical distribution of the contribution of cloud changes to the top‐of‐atmosphere cloud feedback should be discussed to understand the feedback in greater detail. We have developed a simple analysis method called “vertical profile analysis of cloud feedback,” which simply uses radiative flux data from each level of the model. The analysis is applied for typical cloud regimes and the results are discussed together with cloud fraction change profiles. The advantages and disadvantages of the vertical profile analysis, compared with the commonly used International Satellite Cloud Climatology Project (ISCCP) histogram kernel method, are discussed. Our analysis has the advantage of resolving the detailed vertical profiles of the contribution to the top‐of‐atmosphere cloud feedback from the changes in cloud regimes associated with warming, such as reduced cloud cover and upward shifts of the cloud layer in subtropical low‐cloud regions as well as the increased height of the melting layer in tropical deep convection. The main disadvantage is that the vertical profile analysis cannot represent the feedback components sorted by cloud optical thickness as in the ISCCP histogram kernel method.

Authors

Institutions

Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2024-10-16
DOI
https://doi.org/10.1029/2023jd040530
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Vertical Profile Analysis of Cloud Feedbacks

Hideaki Kawai, Tsuyoshi Koshiro, Seiji Yukimoto
Journal of Geophysical Research Atmospheres
Atmospheric aerosols and clouds
article

Vertical Profile Analysis of Cloud Feedbacks

Hideaki Kawai, Tsuyoshi Koshiro, Seiji Yukimoto
article en

Abstract

Abstract Cloud feedback is the largest source of uncertainty in climate sensitivity. This feedback is generally discussed in terms of radiative flux at the top of the atmosphere, but the vertical distribution of the contribution of cloud changes to the top‐of‐atmosphere cloud feedback should be discussed to understand the feedback in greater detail. We have developed a simple analysis method called “vertical profile analysis of cloud feedback,” which simply uses radiative flux data from each level of the model. The analysis is applied for typical cloud regimes and the results are discussed together with cloud fraction change profiles. The advantages and disadvantages of the vertical profile analysis, compared with the commonly used International Satellite Cloud Climatology Project (ISCCP) histogram kernel method, are discussed. Our analysis has the advantage of resolving the detailed vertical profiles of the contribution to the top‐of‐atmosphere cloud feedback from the changes in cloud regimes associated with warming, such as reduced cloud cover and upward shifts of the cloud layer in subtropical low‐cloud regions as well as the increased height of the melting layer in tropical deep convection. The main disadvantage is that the vertical profile analysis cannot represent the feedback components sorted by cloud optical thickness as in the ISCCP histogram kernel method.

Journal of Geophysical Research AtmospheresVol. 129(20)
Japan Meteorological Agency (JP), Meteorological Research Institute (JP)
Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science
Climate action
Openalex Percentile: Top 84%
Atmospheric aerosols and clouds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.