National Centre for Medium Range Weather Forecasting

Abstract. We present a novel methodology, AEROCHEMPro/GRASP (AEROsol CHEMical PROfiling), for retrieving vertical concentration profiles of aerosol chemical species by synergistically combining co-located measurements from a multiwavelength lidar and a multi-angular polarimeter. AEROCHEMPro represents the first retrieval framework for remote sensing of the vertically-resolved aerosol chemical composition, and it is based on an improved, vertical profiling version of the GRASP (Generalized Retrieval of Aerosol and Surface Properties) chemical component framework. The methodology is developed within the context of the Atmosphere Observing System (AOS) international initiative, which proposes a spaceborne observing system to advance our knowledge of aerosols, clouds, convection, and precipitation. Moreover, the retrieval strategy remains broadly applicable to future satellite missions and observing systems involving combined lidar and multi-angular polarimeter aerosol remote sensing. Based on a statistically optimized and physically-constrained inversion, AEROCHEMPro/GRASP delivers three distinct aerosol vertical profiles: (i) a fine mode composed of black carbon, brown carbon, inorganic salts, and associated water uptake; (ii) a coarse mode representing mineral dust, decomposed into iron oxide and quartz species; and (iii) a hydrophilic coarse mode consisting of sea salt particles and their associated water content. The approach explicitly retrieves these three aerosol profiles, along with the fractional abundance of each of the six mentioned aerosol chemical species and their water content. This retrieval of aerosol chemical composition vertical profiles offers, for the first time, a direct observational link between aerosol optical measurements and their speciation resolved in altitude. We demonstrate the feasibility and performance of this technique through an innovative retrieval experiment, where synthetic lidar and polarimeter observations are generated using the MOCAGE chemical transport model and a comprehensive radiative transfer simulator. These pseudo-observations include multi-wavelength attenuated backscatter and depolarization ratios, along with polarized radiances across multiple viewing angles and spectral bands. Results from global-scale transects spanning marine, urban, dust, and complex mixture-dominated regions show that the retrieval captures with good fidelity the main features of vertical aerosol composition and their bulk optical properties. Fine-mode species are well retrieved, particularly in the boundary layer, even for atmospheres with complex mixtures of multiple aerosol species. Dust is accurately retrieved and well defined in terms of vertical extent, load, and composition, and sea salt concentrations are very well reproduced. Some limitations for deriving water content in the upper atmospheric layers are remarked. AEROCHEMPro/GRASP reliably derives optical properties such as aerosol optical depth (AOD), single scattering albedo (SSA), and lidar ratio (LR), demonstrating the approach's robustness. This new retrieval approach represents a significant advancement in spaceborne aerosol remote sensing, as it provides vertically resolved chemical speciation that is directly related to chemical transport model results. It offers new opportunities to improve our understanding of aerosol processes and their effects on climate and air quality.

Abstract. The Indo-Gangetic Plains (IGP) of India frequently experience widespread and dense winter fog with substantial health and economic consequences. This season also coincides with elevated aerosol loading. This study investigates the influence of aerosols, particularly aerosol-radiation interactions (ARI), on the development and evolution of dense fog over the IGP, using high-resolution numerical experiments. While aerosol-cloud interactions related to fog have been extensively studied, the role of ARI has received relatively less attention, due to the limited prevalence of absorbing aerosols in many other parts of the world. However, the increasing number of absorbing aerosols over IGP prompted this study to isolate and examine the contributions of both scattering and absorbing components of ARI. The results of numerical experiments reveal that disabling aerosol absorption led to nearly doubling the area affected by dense fog, increasing fog height by ~20 %, and delaying fog dissipation by about two hours. In contrast, turning off the scattering reduced fog coverage by 18 %. Satellite-derived absorbing aerosol indices corroborated the model’s representation of strong absorption over the region. Another key insight is the contrasting influence of absorbing versus scattering aerosols on the vertical development of fog. Scattering effects were spatially uniform, promoting the vertical growth of fog. Conversely, absorption had a spatially variable impact, enhancing or suppressing fog height depending on whether the absorbing aerosols resided within or above the boundary layer. These findings emphasize the need to accurately represent ARI in numerical weather prediction models for improved fog forecasting over aerosol-rich regions like the IGP.

Accurate forecasting of PM₂.₅ (particulate matter ≤ 2.5 μm) is essential for effective air quality management, particularly in urban areas like Delhi, which frequently experience severe pollution episodes. This study evaluates the predictive capabilit