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Observational constraints from global ice-phase fraction indicate moderate climate sensitivity.
Rui Zhou1,2, Tingfeng Dou1,2, Chen Zhou3,4
1College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China.
Science Advances
|June 5, 2026
Summary
Cloud feedback uncertainty impacts climate sensitivity estimates. This study uses satellite data to constrain cloud optical depth feedback, reducing the uncertainty and suggesting moderate climate sensitivity.
Area of Science:
- Climate Science
- Atmospheric Physics
- Remote Sensing
Background:
- Cloud feedback is the primary source of uncertainty in climate sensitivity.
- The cloud optical depth (τ) feedback, a negative feedback mechanism, is poorly constrained by current observations.
- Accurate estimation of τ feedback is crucial for refining climate models.
Purpose of the Study:
- To constrain the τ feedback in Climate Model Intercomparison Project Phase 6 (CMIP6) models using satellite observations.
- To update estimates of climate sensitivity based on improved τ feedback constraints.
- To assess the consistency of τ feedback constraints derived from different satellite datasets.
Main Methods:
- Utilized global satellite observations of ice-phase fraction from CloudSat (active sensor), MODIS (passive sensor), and DARDAR-MODIS (combined active-passive dataset).
- Applied Bayesian estimation to update the τ feedback and equilibrium climate sensitivity (ECS).
- Compared τ feedback estimates derived from different satellite data sources.
Main Results:
- The shortwave (SW) τ feedback was updated from -0.18 ± 0.14 to -0.43 ± 0.12 W/m²/K using the DARDAR-MODIS constraint.
- τ feedback estimates from MODIS (-0.58 ± 0.17 W/m²/K) and CloudSat (-0.46 ± 0.16 W/m²/K) were comparable.
- The likely range of ECS was updated from [2.6 to 4.0] K to [2.5 to 3.7] K, with the median decreasing from 3.2 K to 3.0 K.
Conclusions:
- Satellite-derived constraints on τ feedback suggest a moderate climate sensitivity.
- Consistency across multiple satellite datasets enhances confidence in the updated ECS range.
- Reducing uncertainty in cloud feedback is vital for improving climate projections.
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