Attribution of Observed Recent Decrease in Low Clouds Over the Northeastern Pacific to Cloud‐Controlling Factors. Issue 3 (28th January 2022) - Andersen, Hendrik; Cermak, Jan; Zipfel, Lukas; Myers, Timothy A.
Abstract: Marine low clouds cool the Earth's climate, with their coverage (LCC) being controlled by their environment. Here, an observed significant decrease of LCC in the northeastern Pacific over the past two decades is linked quantitatively to changes in cloud‐controlling factors. In a comparison of different statistical and machine learning methods, a decrease in the inversion strength and near‐surface winds, and an increase in sea surface temperatures (SSTs) are unanimously shown to be the main causes of the LCC decrease. While the decreased inversion strength leads to more entrainment of dry free‐tropospheric air, the increasing SSTs are shown to lead to an increased vertical moisture gradient that enhances evaporation when entrainment takes place. While the LCC trend is likely driven by natural variability, the trend‐attribution framework developed here can be used with any method in future analyses. We find the choice of predictors is more important than the method. Plain Language Summary: Marine low clouds efficiently cool the Earth's climate, and their prevalence is controlled by environmental factors. Here, a decrease of the cover of marine low clouds in the northeastern Pacific over the past 20 years is analyzed to attribute the trend to changes in environmental factors known to be important for low clouds. A decrease in the strength of the temperature inversion and an increase in sea surface temperatures (SSTs) are shown to be the main causes of the low‐cloud trend. The decreased inversion strength leads to more mixing in of dry air from above the clouds, leading to cloud evaporation. The increasing SSTs increase the atmospheric moisture levels near the surface more than above the cloud, enhancing evaporation when the mixing takes place. While the trend in low clouds is likely driven by natural variability rather than climate change, the analytical framework developed here can be deployed to attribute causes for trends with any statistical or machine learning method in the future. The analysis shows that the choice of environmental factors used for the analysis has a larger impact on the results than the method. Key Points: Significant decrease of low cloud cover in northeastern Pacific in last two decades Increased vertical moisture gradient, decreased inversion strength, and winds drive low cloud trend Good agreement between statistical and machine‐learning methods, predictor choice more important