About Me
Hi I am Arman Pouyaei 
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A results-driven atmospheric scientist with extensive experience and expertise in developing and utilizing new and existing methodologies in multi-scale atmospheric models to study the influence of atmospheric pollutants on the environment.
Programming Skills
Fortran
90%
Python
80%
R / Matlab
70%
Other Skills
Climate modeling
95%
Air quality modeling
90%
Weather modeling
90%
Data Engineer, First Street, New York, New York, United States
May 2025 — Aug 2026
(1) Designing and implementing data pipelines for climate risk analysis.
Postdoctoral Research Associate, Princeton University / NOAA GFDL, Princeton
March 2023 — May 2025
(1) Designed and developed a plume injection scheme for biomass burning emissions in GFDL’s AM4 and implemented the scheme into the aerosol module to study the decadal impact of plume injection height from wildfires on coupled climate modeling systems. (2) Implemented the plume injection scheme to AM4.1 full chemistry and analyzed the ENSO-driven variability of ozone sources (biomass burning, lightning NOx, stratospheric exchange, etc.) on tropospheric ozone radiative forcing (3) Developed and implemented interactive fire emissions and injection in GFDL's ESM4.5 coupling emissions from dynamic fire in LM4.2 to atmospheric chemistry and aerosols in AM4.5
Postdoctoral Researcher, University of Houston, Houston
August 2022 — February 2023
(1) Introduced a novel approach for investigating aerosol-cloud interaction using data assimilation and spectral bin method for microphysics. Designed the forward operator for NEXRAD radar assimilation. Designed a 3DVAR framework for the application of radar data assimilation.
Graduate Research Assistant, University of Houston, Houston
June 2018 — August 2022
(1) Introduced a novel Lagrangian model, C-TRAIL v1.0, providing an alternative method for simulating atmospheric diffusion through incorporation in an Eulerian air quality model. (2) Developed a physically accurate sub-grid cloud convection module based on a meteorological approach for accurate quantification of vertical and long-range transport in CMAQ air quality modeling. (3) Developed Forward Operator for OMI HCHO/NO2 and implemented them in the WRF-Chem/DART framework, to study wildfire-related ozone formation during the 2019 FIREX-AQ campaign.