Description:

The largest uncertainty in estimating anthropogenic climate radiative forcing is caused by inaccurate assessment of radiative forcing due to aerosol-radiation and aerosol-cloud interactions. Additionally, our level of scientific understanding (LOSU) for these interactions remained low or very low in all previous Intergovernmental Panel on Climate Change (IPCC) reports. Multiple factors, including observational limitations and equifinality in climate models, have led to these persistent uncertainties in assessing the aerosol radiative forcing from pre-industrial to present times. In this session, we invite novel research work on the application of ground-based, airborne and satellite remote sensing of atmospheric aerosols, in particular, addressing and reducing instrumental uncertainties in observing aerosol characteristics such as aerosol optical depth (AOD), Angstrom exponent, surface albedo, and relevant aerosol products. Key research work dealing with high resolution measurements using ground-based networks such as Aerosol Robotic Network (AERONET) and satellite instruments such as MODerate resolution Imaging Spectrometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), Geostationary Operational Environmental Satellite (GOES) Imager, and Multiangle Imaging Spectro Radiometer (MISR) are solicited for this session. Satellite observations are particularly important, as they offer truly global constraints for climate models and air quality applications. Aerosol-cloud (indirect) and aerosol-radiation (direct) interactions generate intricate feedback processes that affect both meteorological phenomena and aerosol features. Oftentimes, it remains challenging to distinguish between natural aerosol variability (“signal”) and errors in remote sensing (“noise”) arising due to multi-scale (both temporal and spatial) atmospheric dynamics. Innovative approaches to accurately capture the heterogeneities in aerosol regimes across varying surface types, weather, and climate conditions are considered valuable. We welcome research contributions from multiple fields working at the intersection of weather, climate, and remote sensing that propose novel strategies to enhance the quality of aerosol observations and improve aerosol retrieval algorithms and measurements. Contributions that offer new approaches for managing and refining aerosol records for weather forecasting and climate models are also encouraged.