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Using Active Remote Sensing to Evaluate Cloud-Climate Feedbacks: a Review and a Look to the Future.
Gerald G Mace1, Elizabeth Berry1
1Department of Atmospheric Sciences, University of Utah, 135 South 1460 East Rm 819 (WBB), Salt Lake City, UT 84112-0110 USA.
Active remote sensing from space is crucial for understanding cloud feedback, a key factor in Earth's uncertain climate sensitivity (ECS). This technology can help observe tropical cirrus changes and marine boundary layer cloud processes, improving climate models.
Area of Science:
- Climate science
- Atmospheric physics
- Remote sensing
Background:
- Equilibrium climate sensitivity (ECS) uncertainty remains large, with cloud feedback identified as a fundamental contributor.
- Climate change impacts on cloud forcing involve changes in cloud occurrence and rapid adjustments, enhancing warming through upper tropospheric and marine boundary layer cloud changes.
Purpose of the Study:
- To highlight the critical role of active remote sensing in constraining uncertainties in climate sensitivity.
- To differentiate and understand the contributions of tropical cirrus and marine boundary layer clouds to climate feedback.
Main Methods:
- Decomposition of cloud forcing changes into temperature-dependent and independent components.
- Utilizing active and passive remote sensing synergy for observing cloud processes.
- Analysis of cloud-resolving and global-scale climate models.
Main Results:
- Tropical cirrus feedback is predicted to emerge from statistical noise within 1-2 decades, requiring continued active remote sensing for vertical cloud observation.
- Marine boundary layer cloud changes are linked to microphysics, air motions, and thermodynamics, particularly in remote ocean basins.
- Combined active and passive remote sensing offers a unique approach to validate theoretical understanding and global models.
Conclusions:
- Active remote sensing is essential for observing key cloud feedback mechanisms impacting climate sensitivity.
- Understanding tropical cirrus and marine boundary layer cloud processes is vital for reducing ECS uncertainty.
- Synergistic remote sensing approaches are necessary for advancing climate model accuracy and validation.
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