Kartik Koundal

The Eastern Mediterranean, notably Cyprus, is a climate change hotspot facing severe heatwaves. Accurate numerical weather prediction of these extremes requires precise land–atmosphere modeling and initial and boundary conditions. This study assesses replacing the default USGS Land-Use and Land-Cover (LULC) dataset with the 10 m ESA WorldCover 2021 dataset in the Weather Research and Forecasting (WRF) model to simulate the 15–29 July 2023 Cyprus heatwave. The updated LULC increased urban representation six-fold. Statistical validations showed significant improvements in 2 m temperature, relative humidity, and 10 m wind speed predictions across 85% of observational sites. Dynamically, it restored urban thermal memory, effectively capturing the daytime Urban Cool Island effect and nocturnal heat release. Furthermore, radiosonde validations showed that the update corrected nocturnal Planetary Boundary Layer Height (PBLH) underestimations and dampened exaggerated daytime convective mixing. However, crucial limitations remain. High-frequency diagnostics indicated the model still suffers from damped thermal inertia, missing the abrupt temperature spikes and rapid nocturnal cooling typical of semi-arid microclimates. Additionally, the updated configuration failed to capture severe atmospheric stagnation during peak heatwave conditions, highlighting that deep-rooted kinetic errors persist within default boundary layer parameterizations despite static surface improvements.

Aerosols modulate the radiation budget of the Earth by absorbing and scattering the incoming as well as outgoing radiative fluxes, which result in perturbation of the atmospheric state variables like temperature, pressure, and humidity levels. Inaccurate prescription of the aerosol’s refractive indices in numerical models can lead to unrealistic aerosol-radiation interactions and thus biases in the computed radiative fluxes and consequent meteorological parameters in the model simulations. In this study, the prescribed refractive indices of different aerosol species like black carbon, organic carbon, and mineral dust, in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model have been revised to the latest and more accurate observationally constrained estimates over the Indian region. The resultant simulated clear-sky downwelling shortwave radiation (SWDOWN) shows the largest improvement in mean bias error over the Indo-Gangetic Plain and Eastern regions (~60%), particularly at Bhubaneswar (~94%), followed by Southern India (~47%), and Central and Desert regions (~26%) on an annual scale. Seasonally, SWDOWN mean bias in clear-sky is reduced by ~10–20% across most of the stations. The improved radiative fluxes produce systematic meteorological adjustments, including surface cooling (~−0.2 to −1.5 °C) and increased relative humidity (~3–15%), with the strongest response during the monsoon over Central India. These changes suppress boundary layer development, leading to reduced ventilation and enhanced near-surface PM2.5 in polluted regions, especially during post-monsoon and winter. The revised refractive indices of aerosols also increase the aerosol optical depth by 0.05–0.1 across the domain. The study highlights the significance of realistic aerosol optical properties in chemistry transport models over the Indian region to improve aerosol–radiation–meteorology coupling for more accurate prediction of extreme events.

Severe wintertime PM₂.₅ episodes over the Delhi National Capital Region arise from interactions among emissions, regional transport, and urban-modified boundary-layer dynamics. Chemistry transport models frequently underestimate peak concentrations, partly due to simplified surface representation. This study quantifies how updated land-use/land-cover (LULC) and explicit urban morphology alter urban meteorology and regulate pollution buildup during the 13 November 2024 peak event over the northwestern Indo-Gangetic Plain. WRF-Chem simulations were conducted in three configurations: (i) default USGS LULC, (ii) updated LULC based on ESA WorldCover 2021, and (iii) updated LULC coupled with UT-GLOBUS urban morphology with identical emissions and chemistry across experiments.Updating LULC alone produced minimal changes in near-surface wind speed and PM₂.₅. Whereas, explicit urban morphology introduced building-resolved aerodynamic drag, reducing 10 m wind speeds from 1.21-1.51 m s⁻¹ to ~0.10 m s⁻¹ and decreasing the nocturnal ventilation coefficient by ~62%. Weakened dispersion increased simulated hourly PM₂.₅ peaks from ~100 µg m⁻³ to ~300 µg m⁻³, improved temporal correlation with observations (R = 0.77), and confined enhanced accumulation to the lowest 400-500 m. Elevated aerosol loading further suppressed early daytime boundary-layer growth through aerosol-radiation feedback, reinforcing pollutant persistence. These findings demonstrate that realistic urban morphology corrects wind biases, reduces excessive ventilation, and substantially improves simulation of pollution extremes, underscoring the need to integrate high-resolution urban structure into regional air-quality models globally.