by Naomi Wharton

The ocean can store approximately 1000 times more heat than the atmosphere. As a result, where and when energy is released from the ocean to the atmosphere can have significant consequences for weather and climate patterns. Sea surface temperature (SST) is a key indicator of air-sea processes that transfer energy between the ocean and atmosphere across many spatial and temporal scales. Mesoscale (horizontal scales of ~20-200 km) SST fronts are coupled to the atmosphere, influencing wind speeds, storm tracks, and both oceanic and atmospheric circulation.

Ocean dynamics are less constrained by Earth’s rotation at smaller scales, so submesoscale (horizontal scales of ~1-20 km) processes have the potential to amplify vertical heat fluxes into the upper ocean and atmosphere, with implications for biological productivity and ocean carbon uptake. However, much less is known about the role of submesoscale SST fronts in weather and climate compared to mesoscale SST fronts because most gridded observations and models lack the resolution needed to capture processes at these smaller scales.

With support from the Graubard Fellowship in the Program on Climate Change, I have been working to blend satellite observations into high resolution maps of SST anomalies at multiple spatiotemporal scales. With these maps, I aim to provide insight on the relationship between submesoscale SST fronts and large-scale climate variability.

Although the satellite SST record spans over four decades, SST observations vary vastly in spatiotemporal resolution and coverage. Infrared (IR) radiometers can measure SST at resolutions up to 1 km, but are commonly blocked by clouds. Microwave radiometers are able to see through water vapor in the atmosphere, but are limited to a coarser resolution of around 25 km. To leverage the strengths of both types of instruments, I am blending IR and microwave observations together from multiple satellites. However, in order for the final high-resolution SST product to be meaningful for investigating climate science questions, it is essential to also include estimates of uncertainty for each point in space and time.

The flexibility provided by the Graubard Fellowship funding has allowed me to delve deeply into the critical process of quantifying uncertainty in gridded SST products. This summer, I attended the US CLIVAR Ocean Uncertainty Quantification Summer School at the University of Miami. There, I shared my research progress and engaged in valuable discussions with oceanographers, statisticians, and mathematicians about the specifics of my project. These conversations have continued beyond the Summer School as I work to integrate cutting-edge machine learning methods into my research.

I am grateful to the Graubard Fellowship for enabling me to broaden the scope of my graduate research to include direct ties to climate. I look forward to continuing to apply the skills and connections I have gained throughout the Graubard Fellowship in my research going forward.

Naomi is a 3rd year Ph.D. student in the School of Oceanography at the University of Washington and is a former member of the PCC Graduate Steering Committee and leader of ACORN. She is also pursuing the Graduate Certificate in Climate Science.