English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

How clouds will respond to Earth's warming climate is the greatest contributor to intermodel spread of Equilibrium Climate Sensitivity (ECS). Although global climate models (GCMs) generally agree that the total cloud feedback is positive, GCMs disagree on the magnitude of cloud feedback. Satellite instruments with sufficient accuracy to detect climate change-scale trends in cloud properties will provide improved confidence in our understanding of the relationship between observed climate change and cloud property trends, thus providing essential information to the effort to better constrain ECS. However, a robust framework is needed to determine what constitutes sufficient or necessary accuracy for such an achievement. Our study presents and applies such an accuracy framework to quantify the impact of absolute calibration accuracy requirements on climate change-scale trend detection times for cloud amount, height, optical thickness, and effective radius. The accuracy framework used here was previously applied to SW cloud radiative effect and global mean surface temperature in a study that demonstrated the importance of high instrument accuracy to constrain trend detection times for essential climate variables (ECVs). This paper expands upon these previous studies by investigating cloud properties, demonstrating the versatility of applying this framework to other ECVs and the implications of the results within climate science studies.

Quantifying the Dependence of Satellite Cloud Retrievals on Instrument Uncertainty