Mentor in the CICOES undergraduate intern program at University of Washington
Project: Using Data-Driven Methods to Estimate Cloud Radiative Effects., CICOES, University of Washington, 2024
Student: Liam Schafer, University of Wisconsin - Madison.
Previous studies have shown that clouds play an important role in the Earth’s climate system. The goal of this internship is to apply data-driven methods (e.g., multilinear regression, neural network) to explore relationships between cloud macro- and micro-parameters (e.g., cloud fraction, cloud droplet number concentration) and cloud radiative effects (i.e., how much solar radiation can be reflected by clouds). Data generated by the numerical model over the northeastern Pacific Ocean will be available. The candidate is encouraged to explore different data-driven methods (according to their interests) to see how much cloud radiative effects can be explained by cloud macro- and micro-parameters. Knowledge of cloud or atmospheric science is not necessary, but a basic understanding of programming (e.g., Python) is required.