Multi-model evaluation of aerosol optical properties in the AeroCom phase III Control experiment, using ground and space based columnar observations from AERONET, MODIS, AATSR and a merged satellite product as well as surface in-situ observations from GAW sites

Abstract

<p><strong>Abstract.</strong> Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the present day modelling of aerosol optical properties has been assessed using simulated data representative for the year 2010, from 14 global aerosol models participating in the Phase III Control experiment. The model versions are close or equal to those used for CMIP6 and AerChemMIP and inform also on bias in state of the art ESMs. Modelled column optical depths (total, fine and coarse mode AOD) and Angstrom Exponents (AE) were compared both with ground based observations from the Aerosol Robotic Network (AERONET, version 3) as well as space based observations from AATSR-SU instruments. In addition, the modelled AODs were compared with MODIS (Aqua and Terra) data and a satellite AOD data-set (MERGED-FMI) merged from 12 different individual AOD products. Furthermore, for the first time, the modelled near surface scattering (under dry conditions) and absorption coefficients were evaluated against measurements made at low relative humidity at surface in-situ GAW sites.</p> <p>Statistics are based mainly on normalised mean biases and Pearson correlation coefficients from colocated model and observation data in monthly resolution. Hence, the results are mostly representative for the regions covered by each of the observation networks. Model biases established against satellite data yield insights into remote continental areas and oceans, where ground-based networks lack site coverage. The satellite data themselves are evaluated against AERONET observations, to test our aggregation and re-gridding routines, suggesting relative AOD biases of −5 %, −6 %, +9 % and +18 % for AATSR-SU, MERGED-FMI, MODIS-aqua and MODIS-terra, respectively, with high correlations exceeding 0.8. Biases of fine and coarse AOD and AE in AATSR are found to be +2 %, −16 % and +14.7 % respectively, at AERONET sites, with correlations of the order of 0.8.</p> <p>The AeroCom MEDIAN and most of the participating models underestimate the optical properties investigated, relative to remote sensing observations. AERONET AOD is underestimated by 21 % ± 17 %. Against satellite data, the model AOD biases range from −38 % (MODIS-terra) to −17 % (MERGED-FMI). Correlation coefficients of model AODs with AERONET, MERGED-FMI and AATSR-SU are high (0.8–0.9) and slightly lower against the two MODIS data-sets (0.6–0.8). Investigation of fine and coarse AODs from the MEDIAN model reveals biases of −10% ± 20 % and −41 % ± 29 % against AERONET and −13 % and −24 % against AATSR-SU, respectively. The differences in bias against AERONET and AATSR-SU are in agreement with the established satellite bias against AERONET. These results indicate that most of the AOD bias is due to missing coarse AOD in the regions covered by these observations.</p> <p>Underestimates are also found when comparing the models against the surface GAW observations, showing AeroCom MEDIAN mean bias and inter-model variation of −44 % ± 22 % and −32 % ± 34 % for scattering and absorption coefficients, respectively. Dry scattering shows higher underestimation than AOD at ambient relative humidity and is in agreement with recent findings that suggest that models tend to overestimate scattering enhancement due to hygroscopic growth. Broadly consistent negative bias in AOD and scattering suggest a general underestimate in aerosol effects in current global aerosol models.</p> <p>The large diversity in the surface absorption results suggests differences in the model treatment of light absorption by black carbon (BC), dust (DU) and to a minor degree, organic aerosol (OA). Considerable diversity is found among the models in the simulated near surface absorption coefficients, particularly in regions associated with dust (e.g. Sahara, Tibet), biomass burning (e.g. Amazonia, Central Australia) and biogenic emissions (e.g. Amazonia). Regions associated with high anthropogenic BC emissions such as China and India exhibit comparatively good agreement for all models.</p> <p>Evaluation of modelled column AEs shows an underestimation of 9 % ± 24 % against AERONET and −21 % against AATSR-SU. This suggests that overall, models tend to overestimate particle size, with implications for lifetime and radiative transfer calculations.</p> <p>An investigation of modelled emissions, burdens and lifetimes, mass-specific-extinction coefficients (MECs) and optical depths (ODs) for each species and model reveals considerable diversity in most of these parameters. These are discussed in detail for each model individually. Inter-model spread of aerosol species lifetime appears to be similar to that of mass extinction coefficients, suggesting that AOD uncertainties are still associated to a broad spectrum of parameterised aerosol processes.</p>

A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories

“…Some preliminary information on trends and comparisons with models that are further developed in Collaud Coen et al (2020a), Gliß et al (2020) and Mortier et al (2020) are presented in this paper. Additional manuscripts are in preparation to further investigate variability of the optical and physical properties.…”

“…It also provides an overview of the variability of the variables, and of some additional derived variables from the collection of data for the reference year 2017. The present paper is jointly written with companion papers, three of which (Collaud Coen et al, 2020a;Gliß et al, 2020 andMortier et al, 2020) are in review in 2020 in parallel with this paper. Gliß et al (2020) and Mortier et al (2020) also belong to the Ae-roCom initiative for IPCC.…”

“…- Gliß et al (2020) use the AeroCom (Aerosol Comparisons between Observations and Models, https:// aerocom.met.no/, last access: 11 August 2020) models to assess performances of global-scale model performance for global and regional variables distributions, and variability.…”

“…The recent generation of AeroCom models has been asked to provide additional diagnostics on dry scattering and absorption coefficients at ground level. These are currently being analysed by the two companion papers of Gliß et al (2020) and Mortier et al (2020) using 14 model simulations of present-day (2010 emissions and meteorology) to construct an ensemble mean AeroCom model and aerosol information extracted from SARGAN surface Figure 9. Seasonal medians of the total particle number concentration (N tot ).…”

“…Natural and anthropogenic emissions of primary aerosol and their gaseous precursors have been estimated at different scales in many studies and inventories are now providing fairly accurate information on historical emission trends. Historical emission estimates for anthropogenic aerosol and precursor compounds are key data needed for assessing aerosol impact on climate but are difficult to obtain with precision, and there are discrepancies amongst different estimates even for key aerosol climate forcers like black carbon (Granier et al, 2011;Klimont et al, 2017;Lamarque et al, 2010;Wang et al, 2014). For example, in a recent study using ice-core records from Alpine regions, Lim et al (2017) showed that BC emission inventories for the period 1960s-1970s may be strongly underestimating European anthropogenic emissions.…”