For this post, we are seeking candidates with expertise in weather/chemistry transport modelling, and satellite data analysis and visualisation. The applicant must have experience working with the Weather Research and Forecasting model with Chemistry (WRF-Chem) and/or the Comprehensive Air Quality Model with Extensions (CAMx) on High-Performance Computing (HPC) platforms. She/he should also have experience working with satellite datasets (e.g. MODIS and TROPOMI) and should be proficient in high-level programming languages for data processing.
The Senior Associate will work on WRF-CAMx and/or WRF-Chem or equivalent modelling systems to perform model inter-comparison and validation using satellite/ground-based measurements, make adjustments to the model setup to improve model performance, and assist in preparing model inputs for use in reduced-complexity model(s).
Responsibilities
- Develop, configure, and optimise regional-scale chemical transport models (e.g. WRF-Chem and WRF-CAMx) on HPCs.
- Analyse and validate model outputs against ground-based and satellite measurements.
- Create data visualisations and effectively communicate findings to both technical and non-technical audiences.
- Generate new ideas leading to project proposals and contribute to/lead project reports/journal articles/Op-Eds, etc.
- Participate in relevant conferences and workshops, as required.
Qualifications
- PhD in a discipline related to air pollution, atmospheric chemistry, meteorology, or equivalent.
- Should have studied chemistry/atmospheric chemistry and meteorology as part of the Master’s degree/PhD coursework.
- Minimum two years of research experience in WRF-Chem, CAMx and/or any chemical transport model during PhD.
Skills set
- Experience with CTMs: Hands-on experience with WRF-Chem/WRF-CAMx, or similar CTMs.
- Data Analysis Skills: Ability to analyse model outputs and validate them with measurement data using statistical methods
- Programming Skills: Proficiency in Python for data analysis and visualisation, shell scripting for running models, FORTRAN to debug model code.
- High-Performance Computing: Familiarity with Linux/Unix and running CTM simulations on HPC systems.
- Ability to handle large volume of datasets (NetCDF, HDF, GRIB, ASCII, geo-referenced data).
- Should have published peer-reviewed journal articles in international journals.
- Excellent written and verbal communication skills for presenting findings, writing reports/journal articles, and contributing to proposals.
