Urban areas experience significant alterations in their local surface energy balance due to changes in the thermal properties of impervious surfaces, albedo, land use, and land cover. In addition, the embedded influence of urbanization and heat-trapping in the urban canopy cause city temperature warmer compared to its surroundings peri-urban regions. However, the influence of urbanization on winter surface temperatures remains unclear. In this study, the urbanization influence on winter surface temperature in Bhubaneswar, a tropical two-tier city in India, is assessed using a high-resolution (4 km × 4 km) urban canopy model coupled with the Weather Research and Forecasting model. Numerical experiments are conducted with no urban coupling (CTL) and with coupling of a single-layer urban canopy model (UCM) for the winters of 2004 and 2015. The study suggests that both model simulations exhibit a similar warm bias in mean surface temperature (~ 2.2 °C), but UCM’s surface temperature better agrees with the observations compared to CTL. The warm bias in both experiments is primarily contributed by a higher nighttime warm bias (~ 3.2 °C). The study reveals that urbanization contributes to ~ 0.4 °C increase in surface temperature in 2015, especially in the eastern lowland regions of the city, while the impact is minimal in 2004. In the western region, the influence is nullified, possibly due to lower surface specific humidity affecting longwave radiation in a higher terrain setting. This study underscores the significance of terrain and local microclimate conditions in shaping winter urban surface temperatures, shedding light on the complex interplay between urbanization and climate.

The performance of the Weather Research and Forecasting regional model with chemistry (WRF-Chem) in simulating the spatial and temporal variations in aerosol mass, composition, and size over California is quantified using the extensive meteorological, trace gas, and aerosol measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010. The overall objective of the field campaigns was to obtain data needed to better understand processes that affect both climate and air quality, including emission assessments, transport and chemical aging of aerosols, aerosol radiative effects. Simulations were performed that examined the sensitivity of aerosol concentrations to anthropogenic emissions and to long-range transport of aerosols into the domain obtained from a global model. The configuration of WRF-Chem used in this study is shown to reproduce the overall synoptic conditions, thermally driven circulations, and boundary layer structure observed in region that controls the transport and mixing of trace gases and aerosols. Reducing the default emissions inventory by 50% led to an overall improvement in many simulated trace gases and black carbon aerosol at most sites and along most aircraft flight paths; however, simulated organic aerosol was closer to observed when there were no adjustments to the primary organic aerosol emissions. We found that sulfate was better simulated over northern California whereas nitrate was better simulated over southern California. While the overall spatial and temporal variability of aerosols and their precursors were simulated reasonably well, we show cases where the local transport of some aerosol plumes were either too slow or too fast, which adversely affects the statistics quantifying the differences between observed and simulated quantities. Comparisons with lidar and in situ measurements indicate that long-range transport of aerosols from the global model was likely too high in the free troposphere even though their concentrations were relatively low. This bias led to an over-prediction in aerosol optical depth by as much as a factor of 2 that offset the underpredictions of boundary-layer extinction resulting primarily from local emissions. Lowering the boundary conditions of aerosol concentrations by 50% greatly reduced the bias in simulated aerosol optical depth for all regions of California. This study shows that quantifying regional-scale variations in aerosol radiative forcing and determining the relative role of emissions from local and distant sources is challenging during 'clean' conditions and that a wide array of measurements are needed to ensure model predictions are correct for the right reasons. In this regard, the combined CalNex and CARES data sets are an ideal test bed that can be used to evaluate aerosol models in great detail and develop improved treatments for aerosol processes.