Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the Southeast Atlantic

Abstract

Abstract. Biomass burning smoke is advected over the southeast Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly, in both magnitude and sign. The NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project deployed for field campaigns off the west coast of Africa in three consecutive years (Sept., 2016; Aug., 2017; and Oct., 2018) with the goal of better characterizing this plume as a function of the monthly evolution, by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect, and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models the simulated plume is too vertically diffuse, has smaller vertical gradients, and, in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate under-estimates in modeled plume concentrations, leading in general to under-estimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2018) and September (2017). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and therefore in the aerosol direct radiative effect. Model biases in cloud fraction, and therefore the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is under-estimated in the GEOS model; UM-UKCA simulates significantly too-high cloud optical thickness. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a sub-set of five comparison gridboxes. A significant finding is that the observed gridbox-average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five gridboxes, whereas DARE using the gridbox-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo, but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

Vertical structure of biomass burning aerosol transported over the southeast Atlantic Ocean

“…However, there are segments of the track that can provide information similar to those obtained in the 2016 campaign but for a different time period. Moreover, some flight tracks extended much further from land (Doherty et al, 2021). Analysis of the later campaigns will provide information on the physical evolution of aerosol that has aged for a longer period than is covered in this study.…”

“…The concerns mentioned above were the driving force behind plans for several international multi-year field campaigns; ORACLES (Observations of Aerosols above Clouds and their intEractionS, Redemann et al, 2021), CLARIFY-2017(CLoud-Aerosol-Radiation Interactions and Forcing for Year 2017, Wu et al, 2020, and LASIC (Layered Atlantic Smoke Interactions with Clouds, Zuidema et al, 2016Zuidema et al, , 2018. A key component of the September 2016 NASA ORACLES Intensive Observation Period (IOP) was the vertical profiling of aerosol properties measured by an airborne lidar, the NASA Langley High Spectral Resolution Lidar-2, HSRL-2 (Burton et al, 2018), on-board the NASA ER-2, which was based in Walvis Bay, Namibia, for operations during 2016.…”

“…It must be stressed that the duration is not calculated from the source region on land, which is distributed over a large area of central Africa (e.g., Fig. 9 of Redemann et al, 2021) and cannot be uniquely identified with specific observations made over the ocean. The plume has already been airborne over land for several hours (see Fig.…”

“…If we use the low cut-off of an extinction coefficient of 15 Mm -1 to indicate an aerosol-free layer (Shinozuka et al, 2020), then Fig. 6 indicates that the bulk of the smoke layers encountered at these distances from land were separated from the cloud top, a feature more prevalent during the 2016 IOP (Redemann et al, 2021).…”

Precipitation Susceptibility of Marine Stratocumulus with Variable Above and Below-Cloud Aerosol Concentrations over the Southeast Atlantic

“…The 2017 and 2018 IOPs had 10 PRFs with overlapping flight tracks when the aircraft flew south from 145 0˚ N, 5˚ E toward 15˚ S, 5˚ E, and returned along the same track. PRFs with overlapping tracks acquired statistics for model evaluation (Doherty et al, 2021) while the other PRFs targeted specific locations based on meteorological conditions .…”