Particle Size Analysis of African Dust Haze over the Last 20 Years: A Focus on the Extreme Event of June 2020

Over the last decades, the impact of mineral dust from African deserts on human health and climate has been of great interest to the scientific community. In this paper, the climatological analysis of dusty events of the past 20 years in the Caribbean area has been performed using a particulate approach. The focus is made on June 2020 extreme event dubbed “Godzilla”. To carry out this study, different types of data were used (ground-based, satellites, model, and soundings) on several sites in the Caribbean islands. First, the magnitude of June 2020 event was clearly highlighted using satellite imagery. During the peak of this event, the value of particulate matter with an aerodynamic diameter of less than 10 μμm (PM10) reached a value 9 times greater than the threshold recommended by the World Health Organization in one day. Thereafter, the PM10, the aerosol optical depth, and the volume particle size distribution analyses exhibited their maximum values for June 2020. We also highlighted the exceptional characteristics of the Saharan air layer in terms of thickness and wind speed for this period. Finally, our results showed that the more the proportion of particulate matter with an aerodynamic diameter of less than 2.5 μμm (PM2.5) in PM10 increases, the more the influence of sea salt aerosols is significant.

Developing Land Surface Directional Reflectance and Albedo Products from Geostationary GOES-R and Himawari Data: Theoretical Basis, Operational Implementation, and Validation

The new generation of geostationary satellite sensors is producing an unprecedented amount of Earth observations with high temporal, spatial and spectral resolutions, which enable us to detect and assess abrupt surface changes. In this study, we developed the land surface directional reflectance and albedo products from Geostationary Operational Environment Satellite-R (GOES-R) Advanced Baseline Imager (ABI) data using a method that was prototyped with the Moderate Resolution Imaging Spectroradiometer (MODIS) data in a previous study, and was also tested with data from the Advanced Himawari Imager (AHI) onboard Himawari-8. Surface reflectance is usually retrieved through atmospheric correction that requires the input of aerosol optical depth (AOD). We first estimated AOD and the surface bidirectional reflectance factor (BRF) model parameters simultaneously based on an atmospheric radiative transfer formulation with surface anisotropy, and then calculated the “blue-sky” surface broadband albedo and directional reflectance. This algorithm was implemented operationally by the National Oceanic and Atmospheric Administration (NOAA) to generate the GOES-R land surface albedo product suite with a daily updated clear-sky satellite observation database. The “operational” land surface albedo estimation from ABI and AHI data was validated against ground measurements at the SURFRAD sites and OzFlux sites and compared with the existing satellite products, including MODIS, Visible infrared Imaging Radiometer (VIIRS), and Global Land Surface Satellites (GLASS) albedo products, where good agreement was found with bias values of −0.001 (ABI) and 0.020 (AHI) and root-mean-square-errors (RMSEs) less than 0.065 for the hourly albedo estimation. Directional surface reflectance estimation, evaluated at more than 74 sites from the Aerosol Robotic Network (AERONET), was proven to be reliable as well, with an overall bias very close to zero and RMSEs within 0.042 (ABI) and 0.039 (AHI). Results show that the albedo and reflectance estimation can satisfy the NOAA accuracy requirements for operational climate and meteorological applications.

Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: first results from EPIC/DSCOVR at Lagrange-1 point

We presented an algorithm for inferring aerosol layer height (ALH) and optical depth (AOD) over ocean surface from radiances in oxygen A and B bands measured by the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory orbiting at Lagrangian-1 point. The algorithm was applied to EPIC imagery of a two-day dust outbreak over the North Atlantic Ocean. Retrieved ALHs and AODs were evaluated against counterparts observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network. The comparisons showed 71.5% of EPIC-retrieved ALHs were within ±0.5 km of those determined from CALIOP and 74.4% of EPIC AOD retrievals fell within a ±(0.1+10%) envelope of MODIS retrievals. This study demonstrates the potential of EPIC measurements for retrieving global aerosol height multiple times daily, which are essential for evaluating aerosol profile simulated in climate models and for better estimating aerosol radiative effects.