Model and Observational Datasets, Source Code Description, and Analysis Scripts for Radiation Fog (3–4 January 2025) and Cloud-Base-Lowering Fog (6–7 January 2025) Events over Delhi, India

This repository contains observational datasets, processed WRF model outputs in excel sheets, source code documentation, and analysis scripts used for the study title: "Urban Fog Prediction Based on Aerosol Microphysics and Visibility Parameterization in a High-Resolution Model".The study investigate two winter fog events over Delhi, India: (i) a Radiation Fog event during 3–4 January 2025 and (ii) a Cloud Base Lowering (CBL) Fog event during 6–7 January 2025. The observational datasets were utilized from the Winter Fog EXperiment (WiFEX) campaign 2024-25 at Indira Gandhi International (IGI) Airport, Delhi, India. The model simulations were performed using WRF version 4.5.1 with the Thompson–Eidhammer (TE) aerosol-aware microphysics scheme. Two model configurations are included: CTRL: Default Thompson–Eidhammer aerosol-aware microphysics scheme. EXP: Modified Thompson–Eidhammer aerosol-aware microphysics scheme incorporating aerosol activation, fog droplet formation, and visibility parameterizations. The repository includes: Observational and Model Datasets Surface meteorological variables (temperature, relative humidity, radiation fluxes, and soil variables). Visibility observations and simulations at 2 m and 110 m above ground level. Model simulated fog droplet number concentration (Nd) and water-soluble aerosol number concentration (QNWFA). Radiosonde profiles of temperature, humidity, wind speed, wind direction, potential temperature, equivalent potential temperature, model simulated water vapor mixing ratio, and cloud water mixing ratio. Source Code Description Documentation describing modifications implemented in the WRF Thompson–Eidhammer aerosol-aware microphysics scheme and associated WRF framework files. Analysis Scripts CORA_CWVM.ipynb: Python notebook used to plot cooling rate (CORA) and water-vapor tendency (CWVM) diagnostics associated with aerosol activation and fog formation. LWC_Plot.ipynb: Python notebook used for processing and visualization of liquid water content (LWC). All timestamps are provided in Indian Standard Time (IST, UTC +5:30). The datasets are intended to support reproducibility of the analysis, model evaluation, and interpretation of aerosol–fog interactions during winter fog events over the Indo-Gangetic Plain.