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Zachary Espinosa

Headshot of Zachary Espinosa
Program Year:
3
University:
University of Washington
Field of Study:
Atmospheric and Climate Science
Advisor:
Cecilia Bitz
Degree(s):
M.S. Applied and Engineering Physics, Stanford University, 2021; B.S. Computer Science, Stanford University, 2020
Personal URL:
https://zacespinosa.github.io/

Practicum Experience(s)

Lawrence Livermore National Laboratory (2023)

Practicum Supervisor(s):
Mark
Zelinka
Practicum Title:
Could recent cooling in the East Pacific be due to natural variability?

Summary of Research

Trends in surface air temperature are larger in the Arctic than any other region on Earth - a phenomenon known as Arctic amplification. Unprecedented Arctic warming has coincided with a dramatic decrease in perennial sea ice extent. In my current research, I aim to understand trends in interannual variability of sea ice extent in a warming climate. Characterizing trends in Arctic variability is vital to evaluating forecasting systems, interpreting observations, and attributing future weather events to anthropogenic drivers. My research is conducted using a combination of global climate models, observations, and theory.

Annual Program Review Abstracts

The Shortwave Cloud-SST Feedback Amplifies Multi-Decadal Variability in the Southeast Pacific: Implications for Observed Cooling (2024)
The Physics of Summertime Antarctic Extreme Heat Events (2023)

Publications

Espinosa, Zachary I., Edward Blanchard-Wrigglesworth, and Cecilia M. Bitz. "Understanding the drivers and predictability of record low Antarctic sea ice in austral winter 2023." Communications Earth & Environment 5.1 (2024): 723.

Espinosa, Zachary I., and Mark D. Zelinka. "The shortwave cloud‐SST feedback amplifies multi‐decadal Pacific sea surface temperature trends: Implications for observed cooling." Geophysical Research Letters 51.18 (2024): e2024GL111039.

BlanchardWrigglesworth, Edward, et al. "The largest ever recorded heatwave ”Characteristics and attribution of the Antarctic heatwave of March 2022." Geophysical Research Letters 50.17 (2023): e2023GL104910.

Espinosa, Z. I., Sheshadri, A., Cain, G. R., Gerber, E. P., & DallaSanta, K. J. (2022). Machine learning gravity wave parameterization generalizes to capture the QBO and response to increased CO2. Geophysical Research Letters, 49, e2022GL098174. https://doi.org/10.1029/2022GL098174

Awards

1) Achievement Rewards for College Scientists (ARCS) Foundation Scholar (09/2021 - Present)

2) Graduate Opportunities and Minority Achievement Program (GO-MAP) Fellow (09/2021 - Present)

3) The GEM National Consortium Graduate Fellow (06/2021 - Present)