Zhiquan Liu
Project Scientist at National Center for Atmospheric Research
Boulder, Colorado, United States
Summary
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Rockstar🎓
Top SchoolZhiquan Liu is a Project Scientist based in Boulder, Colorado with over 20 years of experience applying satellite remote sensing, radiative transfer modeling, and advanced data assimilation to mesoscale and aerosol forecasting. At NCAR he develops and integrates algorithmic capabilities—most notably contributions to the widely used WRF model that added Himawari-8 AHI radiance assimilation and adjoint/tangent-linear code—bridging research-grade theory with production modeling. His background includes long-term work at China’s National Satellite Meteorological Center on satellite retrievals and data assimilation, and he holds graduate training in meteorology from French institutions and a BSc in Atmospheric Physics. Known for fixing subtle model errors (e.g., radar reflectivity and moist theta) and synchronizing complex codebases, he combines deep domain expertise with practical software engineering to improve forecast fidelity.
20 years of coding experience
13 years of employment as a software developer
Bachelor of Science, Atmospheric Physics, Bachelor of Science, Atmospheric Physics at The Nanjing UniversityMaster of Science, Meteorology, Master of Science, Meteorology at L’Ecole Nationale de la MétéorologiePh. D, Meteorology, Ph. D, Meteorology at The University of Paul Sabatier (Toulouse III)
Github Skills (16)
algorithm10
model-building10
fortran10
algorithms10
prediction10
numerical10
weather10
numeric10
modeling10
model-driven10
model-driven-development10
meteorology9
climate-model9
cluster-computing8
scientific-computing8
Programming languages (6)
Github contributions (5)
wrf-model/WRF
Dec 2017 - Apr 2022
The official repository for the Weather Research and Forecasting (WRF) model
Role in this project:
Back-end Developer / Algorithm Engineer
Back-end Developer / Algorithm EngineerContributions:64 reviews, 30 commits, 68 PRs in 4 years 4 months
Contributions summary:Zhiquan contributed significantly to the Weather Research and Forecasting (WRF) model, focusing on integrating new capabilities for data assimilation, specifically for Himawari-8 AHI radiance data. They also worked on incorporating and synchronizing WRFPlus code, which included modifications to various modules and the addition of new features, primarily related to the development of adjoint and tangent-linear code. Furthermore, the user addressed bug fixes related to radar reflectivity and moist theta, ensuring the model's accuracy.
forecastingmeteorologyclimateatmospheric-modellingmodel
wrf-model/GENBE_2.0
Oct 2017 - Aug 2021
Repository for the new stand-alone GEN_BE capability for WRFDA.
Contributions:1 review, 6 commits, 4 PRs in 3 years 11 months
standstand-alonegencapability
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