Monitoring multiple satellite aerosol optical depth (AOD) products within the Copernicus Atmosphere Monitoring Service (CAMS) data assimilation system

Abstract

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) provides near-real-time forecast and reanalysis of aerosols using the ECMWF Integrated Forecasting System with atmospheric composition extension, constrained by the assimilation of MODIS and the Polar Multi-Sensor Aerosol Optical Properties (PMAp) aerosol optical depth (AOD). The objective of this work is to evaluate two new near-real-time AOD products to prepare for their assimilation into CAMS, namely the Copernicus AOD (collection 1) from the Sea and Land Surface Temperature Radiometer (SLSTR) on board Sentinel 3-A/B over ocean and the NOAA EPS AOD (v2.r1) from VIIRS on board S-NPP and NOAA20 over both land and ocean. The differences between MODIS (C6.1), PMAp (v2.1), VIIRS (v2.r1), and SLSTR (C1) AOD as well as their departure from the modeled AOD were assessed at the model grid resolution (i.e., level-3) using the 3-month AOD average (December 2019–February 2020 and March–May 2020). VIIRS and MODIS show the best consistency across the products, which is explained by instrument and retrieval algorithm similarities. VIIRS AOD is frequently lower over the ocean background and higher over biomass burning and dust source land regions compared to MODIS. VIIRS shows larger spatial coverage over land and resolves finer spatial structures such as the transport of Australian biomass burning smoke over the Pacific, which can be explained by the use of a heavy aerosol detection test in the retrieval algorithm. Our results confirm the positive offset over ocean (i) between Terra/MODIS and Aqua/MODIS due to the non-corrected radiometric calibration degradation of Terra/MODIS in the Dark Target algorithm and (ii) between SNPP/VIIRS and NOAA20/VIIRS due to the positive bias in the solar reflective bands of SNPP/VIIRS. SLSTR AOD shows much smaller level-3 values than the rest of the products, which is mainly related to differences in spatial representativity at the IFS grid spatial resolution due to the stringent cloud filtering applied to the SLSTR radiances. Finally, the geometry characteristics of the instrument, which drive the range of scattering angles sampled by the instrument, can explain a large part of the differences between retrievals such as the positive offset between PMAp datasets from MetOp-B and MetOp-A.

Impact of assimilating NOAA VIIRS Aerosol Optical Depth (AOD) observations on global AOD analysis from the Copernicus Atmosphere Monitoring Service (CAMS)

“…The similarities and differences between the NOAA VIIRS and NASA MODIS AOD products are summarized here. More detailed information on MODIS and VIIRS algorithms, their relative performances assessed at the IFS spatial resolution as well as the PMAp product which is assimilated over ocean but is not the focus of this paper, can be found in Garrigues et al, 2022. MODIS and VIIRS are two imaging radiometers.…”

“…Trace gas species and chemistry processes are simulated using the modified Carbon Bond 05 (CB05) chemistry scheme (Flemming et al, 2015 andHuijnen et al,2019). A bulk-bin scheme is used for aerosol modelling (Remy et al, 2022). 14 aerosol tracers are simulated which include 7 distinct species (dust, sea salt, organic matter, black carbon, sulfate, nitrate and ammonium), 3 bin sizes for dust and sea salt, fine and coarse mode for nitrate and hydrophilic and hydrophobic for black carbon and organic matter.…”

“…The CAMS-GLOB- ANT 4.2 (Elguindi et al, 2020) and the CAMS-GLOB-BIO v1.1 (Sindelarova et al, 2014) emission inventories provide the rest of the static primary aerosol for anthropogenic sources and biogenic sources, respectively. More detailed on the aerosol model implemented in IFS can be found in Remy et al (2019Remy et al ( , 2022.…”

“…Besides, the satellite altitude is slowly decreasing with time, leading to decrease in pixel size on the ground and increasing gaps between orbits which may negatively impact the aerosol analysis and the performances of the forecast. In this context, VIIRS AOD has been recently compared with MODIS, PMAp and the modelled AOD to prepare for its future assimilation in the IFS and increase the resilience of the DA system against MODIS instrument failure or product disruption (Garrigues et al, 2022). VIIRS AODs have been produced by both NASA (Sayers et al, 2018, Hsu et al, 2019, Sawyer et al, 2020 and NOAA (Laszlo and Liu, 2022).…”

“…At the time of its implementation in CAMS, only the NOAA product was produced in near real time (NRT) and provided retrievals from both S-NPP and NOAA20 platforms. Garrigues et al, 2022 have evaluated the consistency of the NOAA VIIRS (v2.r1) AOD with MODIS (C6.1) AOD at the model spatial resolution over both land and ocean from December 2019 to May 2021. They reported that VIIRS AOD is generally lower than MODIS over ocean and larger over biomass burning and some dust source land regions.…”