My research focuses on investigating air pollution climatology and the factors that influence it, using available observational data, satellite retrieval data, and model simulation results.

Technical Skills

Atmospheric Modelling Skills

Running global atmospheric chemistry models (UKCA v11.0)
Running Met Office NERC Cloud model (MONC) coupled with CASIM (Cloud-Aerosol Interacting Microphysics) and SOCRATES (Suite of Community Radiative Transfer codes)
Modifying model subroutines and altering the setup of the model
Processing/analysing large model, satellite and observational datasets in various file formats (.nc, .hdf etc.)

Computational Skills

Proficiency in using Unix/Linux and Windows operating systems
Experience in using the super computational facility – JASMIN, ARCHER2, MONSOON3
Experience with version control / Git

Data Analysis Skills

Python, Matlab for data analysis and visualization
CDO, NCL, NCO
Remote Sensing and GIS Software – ArcGIS, ENVI, ERDAS

Research Highlights

Evaluating tropospheric nitrogen dioxide in UKCA using OMI satellite retrievals over South and East Asia

Comparison of monthly mean tropospheric column NO2, averaged over 2005–2015 for the whole S and E Asia region from OMI (green, with uncertainty indicated by shading), and from UKCA sampled in three different ways: (i) simple monthly mean (blue); (ii) sampled at the OMI overpass time (cyan); and (iii) sampled at the overpass time and with satellite averaging kernels applied (magenta).

Seasonal tropospheric column NO2 (1015 molec. cm2) distributions from OMI (left), simulated by UKCA (middle), and the percentage difference (100% x (UKCA-OMI)/UKCA) between UKCA and OMI (right).

CO variability and its association with household cooking fuels consumption over the Indo-Gangetic Plains

Urban Heat Island (UHI) variations with Aerosol Optical Depth over Delhi

Temporal and spatial trends of the surface urban heat island (UHI) formation over Delhi are examined with respect to aerosol load and land-cover variations. The study reveals that temperatures over Delhi are higher than those over the surrounding regions almost through-out the year during the night time. The nocturnal heat island intensity is minimum (0–2 K) during the monsoon months and maximum during the month of March (4–6 K). The UHI trends during the day-time are however, significantly different. It is observed that a day-time cool island forms over Delhi twice during the year in the months of May–June and October–December. Analysis of temporal variations in urban heat island intensity (UHII) and aerosol load over Delhi reveals a significant negative correlation between UHII and aerosol optical depth (AOD). Spatial analysis of LST, land-cover and AOD for the months of March, May and November confirms the significant role of AOD along with land-cover variables such as percentage area under the classes built-up, rock, vegetation and bare soil. Comparative analysis of LST in the regions lying north, south, east and west of Delhi in relation to the prevailing land-cover suggests that thermal inertia is also a very important factor determining the urban-rural thermal structure.

UK Ammonia Emissions Estimated With Satellite

Observations and GEOS-Chem

Infrared Atmospheric Sounding Interferometer (IASI)-derived NH3 emissions for March-September. Maps are 24-h total emissions at 0.1° × 0.1°. Inset values are monthly emissions that sum to 271.5 Gg.

Cross-track Infrared Sounder (CrIS)-derived NH3 emissions for March-September. Maps are 24-h total emissions at 0.1° × 0.1°. Inset values are monthly emissions that sum to 389.4 Gg.

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