I am a climate scientist and a lecturer (equivalent to Assistant Professor) in the School of Ocean and Earth Science at the University of Southampton. Before relocating to the UK, I served as a Postdoctoral Scholar at WHOI, subsequent to earning my Ph.D. from Harvard University.
My research focuses on developing statistical and physical tools to
quantify and elucidate the mechanisms underlying climate change.
My interests are wide-ranging and include, but are not limited to:
(1) Climate data and statistical climatology,
(2) Machine learning applications in climate and environmental studies,
(3) Climate variability and projections,
(4) The physics and dynamics of climate change,
(5) Strategies for climate adaptation and policy formulation.
I led the development of the Dynamically Consistent Ensemble of Temperature (DCENT), an ensemble of historical earth surface temperature estimates with sophisticated bias adjustments and comprehensive uncertainty quantification. I have published papers in Nature, Science Advances, Journal of Climate, and other top-tier journals in Earth and Climate Sciences. My work has been featured by NPR, Science, and other international media.
Email: Duo.Chan@soton.ac.uk
I am currently seeking PhD candidates to join us through the INSPIRE PhD training project. Successful candidates will be awarded a full fellowship for at least three years to conduct research on the long-term changes in the equatorial Pacific climate. For more details about the project, please search for Duo Chan on the INSPIRE project page.
Application Requirements:
(1) A strong interest in climate change.
(2) A solid background in mathematics and sciences. Applicants
should have obtained or be close to obtaining a Master’s/Bachelor’s
degree in mathematics, physics, computer science, atmospheric or
oceanic sciences.
(3) Proficiency in English communication and academic skills.
If you are interested in exploring other topics related to climate science, especially in developing and applying mathematical tools to address climate challenges, please do not hesitate to contact me directly.
Chan D., Gebbie G., & Huybers P. (2023). Global and Regional Discrepancies between Early 20th Century Coastal Air and Sea-Surface Temperature Detected by a Coupled Energy-Balance Analysis. Journal of Climate, 34(9), 2205-20. link, pdf, code & data
Chan D., Vecchi G., Yang W., & Huybers P. (2021). Improved simulation of 19th- and 20th-century North Atlantic hurricane frequency after correcting historical sea surface temperatures. Science Advances, 7(26), eabg6931. link, pdf, code, data
Chan D.. (2021). Combining statistical, physical, and historical evidence to improve historical sea surface temperature records. Harvard Data Science Review, 3(1). link, pdf
Chan D., Kent E., Berry D. & Huybers P. (2019). Correcting datasets leads to more homogeneous early 20th century sea surface warming. Nature , 571, 393-397. link, code, data, Harvard Gazette, NPR news