On the differences in the vertical distribution of modeled aerosol optical depth over the southeast Atlantic

Abstract

Abstract. The southeast Atlantic is home to an expansive smoke aerosol plume overlying a large cloud deck for approximately a third of the year. The aerosol plume is mainly attributed to the extensive biomass burning activity that occurs in southern Africa. Current Earth system models (ESMs) reveal significant differences in their estimates of regional aerosol radiative effects over this region. Such large differences partially stem from uncertainties in the vertical distribution of aerosols in the troposphere. These uncertainties translate into different aerosol optical depths (AOD) in the planetary boundary layer (PBL) and the free troposphere (FT). This study examines differences of AOD fraction in the FT and AOD differences among ESMs (WRF-CAM5, WRF-FINN, GEOS-Chem, EAM-E3SM, ALADIN, GEOS-FP, and MERRA-2) and aircraft-based measurements from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign. Models frequently define the PBL as the well-mixed surface-based layer, but this definition misses the upper parts of decoupled PBLs, in which most low-level clouds occur. To account for the presence of decoupled boundary layers in the models, the height of maximum vertical gradient of specific humidity profiles from each model is used to define PBL heights. Results indicate that the monthly mean contribution of AOD in the FT to the total-column AOD ranges from 44 % to 74 % in September 2016 and from 54 % to 71 % in August 2017 within the region bounded by 25°S–0° and 15°W–15°E (excluding land) among the ESMs. Using the second-generation High Spectral Resolution Lidar (HSRL-2) to derive an aircraft-based constraint on the AOD and the fractional AOD, we found that WRF-CAM5 produces 40 % less AOD than those from the HSRL-2 measurements, but it performs well at separating AOD fraction between the FT and the PBL. AOD fractions in the FT for GEOS-Chem and EAM-E3SM are, respectively, 10 % and 15 % lower than the AOD fractions from the HSRL-2 and their similarities in the mean AODs are the result of cancellation of high and low AOD biases. GEOS-FP, MERRA-2, and ALADIN produce 24 %–36 % less AOD and tend to misplace more aerosols in the PBL compared to aircraft-based observations. The models generally underestimate AODs for measured AODs that are above 0.8, indicating their limitations at reproducing high AODs. The differences in the absolute AOD, FT AOD, and the vertical apportioning of AOD in different models highlight the need to continue improving the accuracy of modeled AOD distributions. These differences affect the sign and magnitude of the net aerosol radiative forcing, especially when aerosols are in contact with clouds.

Low cloud diurnal cycle drives regional aerosol radiative warming

“…The principal component analysis (PCA) is applied to reduce the large data volume and to determine the most representative aerosol properties from a wide range of assimilated aerosol properties that are used as inputs into the radiative transfer model. An evaluation of the MERRA-2 AOD against those from ORACLES measurements 26 indicates that the AOD errors lead to about 38% uncertainty in DARE, which is substantially smaller than the uncertainty due to neglecting the cloud diurnal cycle.…”

“…During austral spring, biomass burning smoke aerosols originating from southern Africa are abundantly present above semi-permanent stratocumulus clouds in the southeast Atlantic Ocean 25,26 . This coexistence of aerosols and clouds establishes a natural laboratory for assessing aerosol-cloud-radiation interactions, and has been the subject of various synergistic field campaigns organized by numerous international research groups during 2016 -2018 16,[27][28][29] .…”

“…Aerosol properties such as AOD, SSA, and asymmetry parameter (ASY) are obtained from the three-hourly Modern-Era Retrospective-analysis for Research and Applications-Version 2 (MERRA-2). In contrast to conventional Earth system models, MERRA-2 AODs are derived by assimilating bias-corrected 550 nm AOD derived from MODIS radiances, and the product has been widely evaluated against Aerosol Robotic Network (AERONET) observations 53 and airborne measurements over the southeast Atlantic 26 . Although above-cloud AOD from passive satellite remote sensing provides larger geographic coverages, they contain larger errors than those derived from MERRA-2 33,26 .…”

“…In contrast to conventional Earth system models, MERRA-2 AODs are derived by assimilating bias-corrected 550 nm AOD derived from MODIS radiances, and the product has been widely evaluated against Aerosol Robotic Network (AERONET) observations 53 and airborne measurements over the southeast Atlantic 26 . Although above-cloud AOD from passive satellite remote sensing provides larger geographic coverages, they contain larger errors than those derived from MERRA-2 33,26 . Moreover, MERRA-2 provides AOD underneath clouds, which are nonnegligible for computing DARESurface.…”