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Lucas Harris

Physical Scientist

Deputy Division Leader, Weather and Climate Dynamics Division

Lead, NOAA Research Global-Nest Initiative


Contact Information


Focus Areas:

  • Global and global-nested kilometer-scale modeling
  • Weather and climate extremes
  • Numerical algorithms and dynamical cores
  • Atmosphere digital twins

Lucas Harris

My research is focused on the development of the algorithms and software within the GFDL Finite-Volume Cubed-Sphere Dynamical Core, FV3, and its applications in the GFDL Modeling Suite and specifically the System for High-resolution prediction on Earth-to-Local Domains (SHiELD). Global and variable-resolution forecasts from SHiELD are available in real-time. I also contribute to applications in other FV3-based modeling systems including the Unified Forecast System. A recent article on the GFDL website describes our experimental model development work.

My personal expertise is on grid refinement techniques. The two methods for doing this in FV3 are grid nesting and grid stretching. These techniques allow FV3-powered models to be run at a very high resolution over a limited area convection-resolving forecasting, seasonal prediction, and regional climate modeling. Here is an introduction to variable-resolution techniques. Currently the FV3 Team is using grid nesting and grid stretching to develop global models suitable for storm-scale severe thunderstorm and hurricane forecasting, and for subseasonal prediction of severe weather, intense hurricanes, and the Madden-Julian Oscillation. An article and video about this work have been featured on the GFDL website.

I have also become more involved in the development of global storm resolving models (GSRMs). I led the development of the X-SHiELD GSRM contributed to DYAMOND. This development also supports our collaboration with Allen Institute for Artificial Intelligence (AI2) Climate Modeling, which is creating a ML-corrected FV3-based climate model.

GFDL and NASA Goddard are leading the community effort behind Pace. This is a new performance-portable model incorporating FV3 numerics and ports of physical parameterizations written in the Python-based GT4py domain-specific language. The goal is performance-portability onto new computing architectures, especially GPUs. This is wholly open-developed and open to new contributors.

Recent presentations:

Other projects and documents

I have written a simple but efficient and highly flexible feature tracker, called GFDL QuickTracks, primarily for tropical and extratropical cyclones. An unmaintained version of the code and scripts is available on GitHub.

I have a few nice GrADS scripts, along with examples, that I use for some of my work that others may find helpful.

Ray Pierrehumbert’s classic essay on mountain gravity-wave drag parameterization is difficult to find online. A copy is available at ECMWF. (Many other excellent ECMWF conference proceedings, including many classic contributions by GFDL scientists, are available as well.) A conference proceeding describing the use of the Pierrehumbert and Wyman scheme in the Miyakoda GFDL model, also hard to find, is available here.

My colleague Xi Chen and I have submitted a comment on an article about grid staggering.