Two new PhD positions available!#

I’m happy to announce that I will be recruiting two new graduate students for fully funded PhD positions in my group starting Fall 2021. Both projects are funded on new grants from the National Science Foundation, involve exciting opportunities for cutting edge science and interdisciplinary training, and will result in significant contributions back to the open-source scientific software community.

Details about both opportunities follow.

Land-atmosphere interactions and amplified desert warming#

I’m seeking one PhD student to work on the theory of land-atmosphere interaction, primarily understanding the amplified warming of arid desert regions under climate change. Funded by a new NSF grant, this work will apply hierarchies of climate models ranging from single-column representations of the land-atmosphere system to full-complexity global models to study the interactions between local arid-surface processes and large-scale climate dynamics.

This will be an interdisciplinary team effort in collaboration with Prof. Liming Zhou. The student will receive advanced training at the intersection of theoretical climate dynamics, numerical modeling, remote sensing, and data analysis.

This project will make extensive use of the climlab modeling toolkit, and will spur development of significant new capabilities within climlab.

Climate sensitivity and natural variability: a Big Data approach with Project Pythia#

Project Pythia is an exciting newly funded partnership between NCAR, Unidata and UAlbany bringing together climate scientists and software engineers to deliver a public, web-accessible, community-owned learning resource for geoscientists, the focus of which will be:

  • Using the Pangeo stack of Python tools for analysis and discovery of geoscience data

  • Deploying scalable and reproducible scientific workflows in the Cloud

We have funding under this project for a data-intensive basic research project that will catalyze development of the Pythia compute platform and content. Using large ensembles of very high resolution climate model simulations generated by our partners at iHESP, we will investigate how the intrinsic variability of the coupled atmosphere-ocean system affects the planetary energy balance on scales of years to centuries. We want to understand how ultra-high-resolution simulations that resolve the ocean “weather” reduce biases in key atmospheric feedback processes such as subtropical cloud cover. The ultimate goal is to better inform the use of observational constraints in narrowing uncertainties in future climate sensitivity – a problem of enormous societal importance.

The shear volume of simulation data will present an unprecedented analysis challenge. The funded student will work with me and the whole Pythia team to develop clear, expressive, parallelized workflows that scale up to very large datasets to generate new scientific knowledge while also serving as examplars for the research community.

Who am I looking for?#

Here’s a short list of things I would consider assets for a prospective student on either project:

  • a background in atmospheric science, oceanography, physics, or related STEM field

  • deep scientific curiosity and enthusiasm for the complexity of nature

  • excellent quantitative skills

  • a working knowledge of programming in Python and/or other exposure to scientific computing.

  • a passion for open-source scientific software and a willingness to contribute back to the community

This is not a “hard list” of requirements. I will be glad to talk more about these opportunities with any prospective student whose passions align with the above project goals.

Interested in applying?#

I encourage you to do the following:

New website!   New paper on vertical structure of poleward energy flux
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