Clouds play a crucial role in Earth's climate by reflecting sunlight and trapping heat. Understanding how clouds respond to global warming (cloud feedback) is essential for climate change. However, the natural climate variability, like ENSO, can distort these estimates. Relying on long-term reanalysis data and simulations, this study finds that ENSO with a typical periodicity of 2–7 years can introduce a significant bias on cloud feedback estimates on even decadal to century time scales.

This letter explores a novel approach for the formation of cloud droplets in rising adiabatic air parcels. Our approach combines microphysical equations accounting for moisture, updrafts and concentration of aerosols. Our analysis reveals three regimes: A) Low moisture and high concentration can hinder activation; B) Droplets can activate and stabilize above critical sizes, and C) sparse clouds can have droplets exhibiting activation and deactivation cycles.

Clouds' responses to global warming contribute the largest uncertainty in climate prediction. Here, we analyze 42 years of global cloud cover in reanalysis data and show a decreasing trend over most continents and an increasing trend over the tropical and subtropical oceans. A reduction in near-surface relative humidity can explain the decreasing trend in cloud cover over land. Our results suggest potential stress on the terrestrial water cycle, associated with global warming.

We used record-breaking statistics together with spatial information to create record-breaking SST maps. The maps reveal warming patterns in the overwhelming majority of the ocean and coherent islands of cooling, where low records occur more frequently than high ones. Some of these cooling spots are well known; however, a surprising elliptical area in the Southern Ocean is observed as well. Similar analyses can be performed on other key climatological variables to explore their trend patterns.

Wind observations of an advanced doppler lidar are successfully compared to a meteorological mast, a tethered balloon, and free radiosondes. Analysis of boundary layer structure using Lidar observation show Good agreement with WRF model simulations. A specific potential for synergic use of WRF model with the Lidar observations is demonstrated. WRF simulations can be used to indicate atmospheric layers in which Lidar observations are challenged.