Rebecca Beadling

Rebecca (Becki) Beadling is an Assistant Professor at Temple University in the department of Earth and Environmental Science where she leads the Ocean Climate Connections (OCC) research group (https://sites.temple.edu/oceanclimateconnections/). She is a climate scientist / oceanographer who uses observations and climate model simulations to understand the ocean's role in the climate system. Given their role in the carbon and heat budget of our planet, understanding our oceans and how they will evolve will help reduce uncertainty in climate change projections. Her research particularly focuses on ocean circulation and processes within the Southern Ocean, their projected changes under continued warming, and the role these remote processes play in the global climate. Dr. Beadling also works to develop diagnostics to identify and understand causes of biases in coupled climate model simulations and to understand how processes may be represented differently across models. Dr. Beadling collaborates closely with NOAA's Geophysical Fluid Dynamics Laboratory where she is a member of the High Resolution Model Development Team, contributing to the development of high resolution coupled climate models. She is also actively involved in international climate model intercomparison projects and serves as a member of the World Climate Research Programme’s (WCRP) Working Group on Coupled Modeling's (WGCM) Coupled Model Intercomparison Project Model (CMIP) Benchmarking Task Team. This CMIP task team aims to develop methods for systematic and rapid assessment of models participating in the next phase of CMIP and will play a key role in shaping future climate model development globally and model analysis for the next Intergovernmental Panel on Climate Change (IPCC) report.

Becki designs and teaches courses on climate dynamics and climate change at Temple University. Her courses aim to provide students with the foundational knowledge of the processes that govern the climate system and climate change, while also providing students with the technical and data science skills required for meaningful analysis of global observational datasets and climate model simulations.