Quantifying the Impact of Model Resolution on the Representation of Marine Heat Waves

Hosts: Marion Alberty and John Krasting

Marine heat waves (MHW) are prolonged periods of elevated ocean temperatures which can strongly impact ocean ecosystems and regional weather. MHWs are formed by the interplay of heat transport by the ocean into a region and exchanges of heat between the ocean and atmosphere. Coupled climate models projections indicate the MHWs will increase in frequency and intensity under anthropogenic induced global warming. Coupled climate models are also being run at higher resolution to better resolve important ocean processes and air-sea interactions, leading to improved representation of MHWs with statistics that are approaching the observed MHW strength and frequency.

The goal of this project is to characterize the frequency, intensity, and duration of MHWs in a hierarchy of GFDL models. Particular attention will be paid to MHWs which may impact the physical and ecological state of the Arctic through either direct or indirect connections. Over the duration of the project the potential candidate will work with the project mentors to (a) gain knowledge about the earth system, MHWs and their impact on the earth system, (b) use existing python modules to analyze GFDL ocean model data, and (c) produce figures and statistics that convey the representation of MHWs in these models. This project is highly adaptable depending on the potential candidate’s specific skills and interests.

Potential candidates should have an interest in oceanography, physics, and/or math. Experience in computer programming (for example using Python or MATLAB) is helpful.