Cheng-Hsuan Lu
University at Albany, NY·Earth & Environmental Science
Predicting how chemicals and particles move and change in the atmosphere matters for public health, agriculture, energy, weather forecasts and environmental policy. Doing this well requires computer models that link processes from neighborhood to planetary scales.
- Fields
Earth & Environmental Science
Computer Science
- Topics
atmospheric chemistry
air quality
aerosols
- Grants
- 1 known grant, through Jul 2030
What they work on
- Integrate the MUSICA chemistry and aerosol library into the MPAS-A global weather model to create CheMPAS-A, which simulates atmospheric chemistry seamlessly from global to local scales.
- Develop QUACS, a scripting capability that lets domain specialists and students add custom chemistry and aerosol parameterizations through an open-source scripting language without changing the model's stable core.
- Build configuration options and pre- and post-processing tools that make CheMPAS-A portable, high-performance and accessible to new users.
More about the research
Those models also need to make it easy for scientists to test new ideas and share results. This collaborative project builds such a system.
Why it matters
Better atmospheric chemistry models could improve air quality and weather forecasts and inform environmental policies that protect public health, agriculture and energy systems. Open, easy-to-modify modeling software could let more scientists and students test and share new representations of atmospheric chemistry faster.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Amato Evan
University of California-San Diego, CA·Earth & Environmental Science
Estimate how much dust downslope windstorms and haboobs emit globally, by feeding surface winds from high-resolution 3.75 km MPAS simulations into an offline dust emission model.
Rong Fu
University of California-Los Angeles, CA·Earth & Environmental Science
Simulate mesoscale convective systems over the Congo Basin with the Model for Prediction Across Scales (MPAS), a global cloud-resolving model, to explain how these storm clusters start, develop and travel.
Jeffrey Potoff
Wayne State University, MI·Chemistry
Speed up py-MCMD, the tool that links the molecular dynamics program NAMD with the Monte Carlo program GOMC, by cutting the delay in each MC/MD cycle through improved memory and disk usage.
The school
University at Albany: 15 labs on PI Pages, $472M a year on research, 144 research doctorates a year.
Reach out
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