Project Overview

Understanding the causes and impacts of climate change remains one of the most important scientific challenges of our time, with profound societal and policy implications. Despite major progress in climate modeling, substantial uncertainties persist in projections of **global cloud** and **sea ice cover** — two of the most sensitive components of the climate system. Clouds can either amplify or dampen global warming depending on their type and location, while sea ice loss or gain strongly alters Earth’s radiative balance through powerful feedbacks.

Robustly separating the **human-driven (anthropogenic)** and **naturally occurring** contributions to observed climate variability is therefore essential for improving future projections. Modern global climate models (e.g., CMIP5/CMIP6) show a wide spread in cloud feedbacks and polar sea ice trends, limiting confidence in their simulations. This project addresses these challenges by combining **satellite observations**, **reanalysis datasets**, and **CMIP6 model simulations**, applying advanced statistical tools to disentangle the human influence from natural climate variability — offering a clearer view of the processes driving recent global changes.

Methods Objectives Strategy