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  • 1
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    Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing
    Copernicus GmbH ; 2020
    In:  Atmospheric Chemistry and Physics Vol. 20, No. 15 ( 2020-08-13), p. 9491-9524
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 20, No. 15 ( 2020-08-13), p. 9491-9524
    Abstract: Abstract. The effect of observational constraint on the ranges of uncertain physical and chemical process parameters was explored in a global aerosol–climate model. The study uses 1 million variants of the Hadley Centre General Environment Model version 3 (HadGEM3) that sample 26 sources of uncertainty, together with over 9000 monthly aggregated grid-box measurements of aerosol optical depth, PM2.5, particle number concentrations, sulfate and organic mass concentrations. Despite many compensating effects in the model, the procedure constrains the probability distributions of parameters related to secondary organic aerosol, anthropogenic SO2 emissions, residential emissions, sea spray emissions, dry deposition rates of SO2 and aerosols, new particle formation, cloud droplet pH and the diameter of primary combustion particles. Observational constraint rules out nearly 98 % of the model variants. On constraint, the ±1σ (standard deviation) range of global annual mean direct radiative forcing (RFari) is reduced by 33 % to −0.14 to −0.26 W m−2, and the 95 % credible interval (CI) is reduced by 34 % to −0.1 to −0.32 W m−2. For the global annual mean aerosol–cloud radiative forcing, RFaci, the ±1σ range is reduced by 7 % to −1.66 to −2.48 W m−2, and the 95 % CI by 6 % to −1.28 to −2.88 W m−2. The tightness of the constraint is limited by parameter cancellation effects (model equifinality) as well as the large and poorly defined “representativeness error” associated with comparing point measurements with a global model. The constraint could also be narrowed if model structural errors that prevent simultaneous agreement with different measurement types in multiple locations and seasons could be improved. For example, constraints using either sulfate or PM2.5 measurements individually result in RFari±1σ ranges that only just overlap, which shows that emergent constraints based on one measurement type may be overconfident.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-20-9491-2020
    DOI: 10.5194/acp-20-9491-2020-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
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  • 2
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    Investigating the assimilation of CALIPSO global aerosol vertical observations using a four-dimensional ensemble Kalman filter
    Copernicus GmbH ; 2019
    In:  Atmospheric Chemistry and Physics Vol. 19, No. 21 ( 2019-11-05), p. 13445-13467
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 19, No. 21 ( 2019-11-05), p. 13445-13467
    Abstract: Abstract. Aerosol vertical information is critical to quantify the influences of aerosol on the climate and environment; however, large uncertainties still persist in model simulations. In this study, the vertical aerosol extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are assimilated to optimize the hourly aerosol fields of the Non-hydrostatic ICosahedral Atmospheric Model (NICAM) online coupled with the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) using a four-dimensional local ensemble transform Kalman filter (4-D LETKF). A parallel assimilation experiment using bias-corrected aerosol optical thicknesses (AOTs) from the Moderate Resolution Imaging Spectroradiometer (MODIS) is conducted to investigate the effects of assimilating the observations (and whether to include vertical information) on the model performances. Additionally, an experiment simultaneously assimilating both CALIOP and MODIS observations is conducted. The assimilation experiments are successfully performed for 1 month, making it possible to evaluate the results in a statistical sense. The hourly analyses are validated via both the CALIOP-observed aerosol vertical extinction coefficients and the AOT observations from MODIS and the AErosol RObotic NETwork (AERONET). Our results reveal that both the CALIOP and MODIS assimilations can improve the model simulations. The CALIOP assimilation is superior to the MODIS assimilation in modifying the incorrect aerosol vertical distributions and reproducing the real magnitudes and variations, and the joint CALIOP and MODIS assimilation can further improve the simulated aerosol vertical distribution. However, the MODIS assimilation can better reproduce the AOT distributions than the CALIOP assimilation, and the inclusion of the CALIOP observations has an insignificant impact on the AOT analysis. This is probably due to the nadir-viewing CALIOP having much sparser coverage than MODIS. The assimilation efficiencies of CALIOP decrease with increasing distances of the overpass time, indicating that more aerosol vertical observation platforms are required to fill the sensor-specific observation gaps and hence improve the aerosol vertical data assimilation.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-19-13445-2019
    DOI: 10.5194/acp-19-13445-2019-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
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  • 3
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    Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations
    Copernicus GmbH ; 2020
    In:  Geoscientific Model Development Vol. 13, No. 12 ( 2020-12-21), p. 6383-6423
    Details
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 13, No. 12 ( 2020-12-21), p. 6383-6423
    Abstract: Abstract. We document and evaluate the aerosol schemes as implemented in the physical and Earth system models, the Global Coupled 3.1 configuration of the Hadley Centre Global Environment Model version 3 (HadGEM3-GC3.1) and the United Kingdom Earth System Model (UKESM1), which are contributing to the sixth Coupled Model Intercomparison Project (CMIP6). The simulation of aerosols in the present-day period of the historical ensemble of these models is evaluated against a range of observations. Updates to the aerosol microphysics scheme are documented as well as differences in the aerosol representation between the physical and Earth system configurations. The additional Earth system interactions included in UKESM1 lead to differences in the emissions of natural aerosol sources such as dimethyl sulfide, mineral dust and organic aerosol and subsequent evolution of these species in the model. UKESM1 also includes a stratospheric–tropospheric chemistry scheme which is fully coupled to the aerosol scheme, while GC3.1 employs a simplified aerosol chemistry mechanism driven by prescribed monthly climatologies of the relevant oxidants. Overall, the simulated speciated aerosol mass concentrations compare reasonably well with observations. Both models capture the negative trend in sulfate aerosol concentrations over Europe and the eastern United States of America (US) although the models tend to underestimate sulfate concentrations in both regions. Interactive emissions of biogenic volatile organic compounds in UKESM1 lead to an improved agreement of organic aerosol over the US. Simulated dust burdens are similar in both models despite a 2-fold difference in dust emissions. Aerosol optical depth is biased low in dust source and outflow regions but performs well in other regions compared to a number of satellite and ground-based retrievals of aerosol optical depth. Simulated aerosol number concentrations are generally within a factor of 2 of the observations, with both models tending to overestimate number concentrations over remote ocean regions, apart from at high latitudes, and underestimate over Northern Hemisphere continents. Finally, a new primary marine organic aerosol source is implemented in UKESM1 for the first time. The impact of this new aerosol source is evaluated. Over the pristine Southern Ocean, it is found to improve the seasonal cycle of organic aerosol mass and cloud droplet number concentrations relative to GC3.1 although underestimations in cloud droplet number concentrations remain. This paper provides a useful characterisation of the aerosol climatology in both models and will facilitate understanding in the numerous aerosol–climate interaction studies that will be conducted as part of CMIP6 and beyond.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    URL: Article
    URL: Article
    DOI: 10.5194/gmd-13-6383-2020
    DOI: 10.5194/gmd-13-6383-2020-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
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  • 4
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    Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system
    Copernicus GmbH ; 2021
    In:  Atmospheric Chemistry and Physics Vol. 21, No. 4 ( 2021-02-23), p. 2637-2674
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 21, No. 4 ( 2021-02-23), p. 2637-2674
    Abstract: Abstract. A data assimilation system for aerosol, based on an ensemble Kalman filter, has been developed for the ECHAM – Hamburg Aerosol Model (ECHAM-HAM) global aerosol model and applied to POLarization and Directionality of the Earth's Reflectances (POLDER)-derived observations of optical properties. The advantages of this assimilation system is that the ECHAM-HAM aerosol modal scheme carries both aerosol particle numbers and mass which are both used in the data assimilation system as state vectors, while POLDER retrievals in addition to aerosol optical depth (AOD) and the Ångström exponent (AE) also provide information related to aerosol absorption like aerosol absorption optical depth (AAOD) and single scattering albedo (SSA). The developed scheme can simultaneously assimilate combinations of multiple variables (e.g., AOD, AE, SSA) to optimally estimate mass mixing ratio and number mixing ratio of different aerosol species. We investigate the added value of assimilating AE, AAOD and SSA, in addition to the commonly used AOD, by conducting multiple experiments where different combinations of retrieved properties are assimilated. Results are evaluated with (independent) POLDER, Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target, MODIS Deep Blue and Aerosol Robotic Network (AERONET) observations. The experiment where POLDER AOD, AE and SSA are assimilated shows systematic improvement in mean error, mean absolute error and correlation for AOD, AE, AAOD and SSA compared to the experiment where only AOD is assimilated. The same experiment reduces the global ME against AERONET from 0.072 to 0.001 for AOD, from 0.273 to 0.009 for AE and from −0.012 to 0.002 for AAOD. Additionally, sensitivity experiments reveal the benefits of assimilating AE over AOD at a second wavelength or SSA over AAOD, possibly due to a simpler observation covariance matrix in the present data assimilation framework. We conclude that the currently available AE and SSA do positively impact data assimilation.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-21-2637-2021
    DOI: 10.5194/acp-21-2637-2021-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
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  • 5
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    Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs)
    Copernicus GmbH ; 2022
    In:  Geoscientific Model Development Vol. 15, No. 8 ( 2022-04-21), p. 3253-3279
    Details
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 8 ( 2022-04-21), p. 3253-3279
    Abstract: Abstract. We present a top-down approach for aerosol emission estimation from Spectropolarimeter for Planetary Exploration (SPEXone) polarimetric retrievals related to the aerosol amount, size, and absorption using a fixed-lag ensemble Kalman smoother (LETKS) in combination with the ECHAM-HAM model. We assess the system by performing observing system simulation experiments (OSSEs) in order to evaluate the ability of the future multi-angle polarimeter instrument, SPEXone, as well as a satellite with near-perfect global coverage. In our OSSEs, the nature run (NAT) is a simulation by the global climate aerosol model ECHAM-HAM with altered aerosol emissions. The control (CTL) and the data assimilation (DAS) experiments are composed of an ensemble of ECHAM-HAM simulations, where the default aerosol emissions are perturbed with factors taken from a Gaussian distribution. Synthetic observations, specifically aerosol optical depth at 550 nm (AOD550), Ångström exponent from 550 to 865 nm (AE550–865), and single-scattering albedo at 550 nm (SSA550) are assimilated in order to estimate the aerosol emission fluxes of desert dust (DU), sea salt (SS), organic carbon (OC), black carbon (BC), and sulfate (SO4), along with the emission fluxes of two SO4 precursor gases (SO2, DMS). The prior emission global relative mean absolute error (MAE) before the assimilation ranges from 33 % to 117 %. Depending on the species, the assimilated observations sampled using the satellite with near-perfect global coverage reduce this error to equal to or lower than 5 %. Despite its limited coverage, the SPEXone sampling shows similar results, with somewhat larger errors for DU and SS (both having a MAE equal to 11 %). Further, experiments show that doubling the measurement error increases the global relative MAE up to 22 % for DU and SS. In addition, our results reveal that when the wind of DAS uses a different reanalysis dataset (ERA5 instead of ERA-Interim) to the NAT, the estimated SS emissions are negatively affected the most, while other aerosol species are negatively affected to a smaller extent. If the DAS uses dust or sea salt emission parametrizations that are very different from the NAT, posterior emissions can still be successfully estimated, but this experiment revealed that the source location is important for the estimation of dust emissions. This work suggests that the upcoming SPEXone sensor will provide observations related to aerosol amount, size, and absorption with sufficient coverage and accuracy in order to estimate aerosol emissions.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    URL: Article
    URL: Article
    DOI: 10.5194/gmd-15-3253-2022
    DOI: 10.5194/gmd-15-3253-2022-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
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  • 6
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    Site representativity of AERONET and GAW remotely sensed aerosol optical thickness and absorbing aerosol optical thickness observations
    Copernicus GmbH ; 2020
    In:  Atmospheric Chemistry and Physics Vol. 20, No. 12 ( 2020-06-26), p. 7473-7488
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 20, No. 12 ( 2020-06-26), p. 7473-7488
    Abstract: Abstract. Remote sensing observations from the AERONET (AErosol RObotic NETwork) and GAW (Global Atmosphere Watch) networks are intermittent in time and have a limited field of view. A global high-resolution simulation (Goddard Earth Observing System Model (GEOS-5) Nature Run) is used to conduct an OSSE (observing system simulation experiment) for AERONET and GAW observations of AOT (aerosol optical thickness) and AAOT (absorbing aerosol optical thickness) and estimate the spatiotemporal representativity of individual sites for larger areas (from 0.5 to 4∘ in size). GEOS-5 NR and the OSSE are evaluated and have shown to have sufficient skill, although daily AAOT variability is significantly underestimated, while the frequency of AAOT observations is overestimated (both resulting in an underestimation of temporal representativity errors in AAOT). Yearly representation errors are provided for a host of scenarios: varying grid-box size, temporal collocation protocols and site altitudes are explored. Monthly representation errors show correlations from month to month, with a pronounced annual cycle that suggests temporal averaging may not be very successful in reducing multi-year representation errors. The collocation protocol for AEROCOM (AEROsol Comparisons between Observations and Models) model evaluation (using daily data) is shown to be suboptimal and the use of hourly data is advocated instead. A previous subjective ranking of site spatial representativity (Kinne et al., 2013) is analysed and a new objective ranking proposed. Several sites are shown to have yearly representation errors in excess of 40 %. Lastly, a recent suggestion (Wang et al., 2018) that AERONET observations of AAOT suffer a positive representation bias of 30 % globally is analysed and evidence is provided that this bias is likely an overestimate (the current paper finds 4 %) due to methodological choices.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-20-7473-2020
    DOI: 10.5194/acp-20-7473-2020-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
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  • 7
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    Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0
    Copernicus GmbH ; 2017
    In:  Geoscientific Model Development Vol. 10, No. 3 ( 2017-03-10), p. 1107-1129
    Details
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 10, No. 3 ( 2017-03-10), p. 1107-1129
    Abstract: Abstract. A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter – LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets. The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    URL: Article
    DOI: 10.5194/gmd-10-1107-2017
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
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  • 8
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    Will a perfect model agree with perfect observations? The impact of spatial sampling
    Copernicus GmbH ; 2016
    In:  Atmospheric Chemistry and Physics Vol. 16, No. 10 ( 2016-05-24), p. 6335-6353
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 16, No. 10 ( 2016-05-24), p. 6335-6353
    Abstract: Abstract. The spatial resolution of global climate models with interactive aerosol and the observations used to evaluate them is very different. Current models use grid spacings of  ∼ 200 km, while satellite observations of aerosol use so-called pixels of  ∼ 10 km. Ground site or airborne observations relate to even smaller spatial scales. We study the errors incurred due to different resolutions by aggregating high-resolution simulations (10 km grid spacing) over either the large areas of global model grid boxes ("perfect" model data) or small areas corresponding to the pixels of satellite measurements or the field of view of ground sites ("perfect" observations). Our analysis suggests that instantaneous root-mean-square (RMS) differences of perfect observations from perfect global models can easily amount to 30–160 %, for a range of observables like AOT (aerosol optical thickness), extinction, black carbon mass concentrations, PM2.5, number densities and CCN (cloud condensation nuclei). These differences, due entirely to different spatial sampling of models and observations, are often larger than measurement errors in real observations. Temporal averaging over a month of data reduces these differences more strongly for some observables (e.g. a threefold reduction for AOT), than for others (e.g. a twofold reduction for surface black carbon concentrations), but significant RMS differences remain (10–75 %). Note that this study ignores the issue of temporal sampling of real observations, which is likely to affect our present monthly error estimates. We examine several other strategies (e.g. spatial aggregation of observations, interpolation of model data) for reducing these differences and show their effectiveness. Finally, we examine consequences for the use of flight campaign data in global model evaluation and show that significant biases may be introduced depending on the flight strategy used.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    DOI: 10.5194/acp-16-6335-2016
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2016
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  • 9
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    Hourly Aerosol Assimilation of Himawari‐8 AOT Using the Four‐Dimensional Local Ensemble Transform Kalman Filter
    American Geophysical Union (AGU) ; 2019
    In:  Journal of Advances in Modeling Earth Systems Vol. 11, No. 3 ( 2019-03), p. 680-711
    Details
    In: Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), Vol. 11, No. 3 ( 2019-03), p. 680-711
    Abstract: Four‐dimensional LETKF is applied to assimilate hourly aerosol observations from the next geostationary satellite Himawari‐8 4D‐LETKF can significantly enhance the computational efficiency and assimilate more asynchronous observations The analyses correctly reduce the significantly positive biases and root‐mean‐square errors of the control experiment
    Type of Medium: Online Resource
    ISSN: 1942-2466 , 1942-2466
    URL: Article
    DOI: 10.1029/2018MS001475
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2019
    detail.hit.zdb_id: 2462132-8
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  • 10
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    Assimilation of POLDER observations to estimate aerosol emissions
    Copernicus GmbH ; 2023
    In:  Atmospheric Chemistry and Physics Vol. 23, No. 16 ( 2023-08-29), p. 9495-9524
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 23, No. 16 ( 2023-08-29), p. 9495-9524
    Abstract: Abstract. We apply a local ensemble transform Kalman smoother (LETKS) in combination with the global aerosol–climate model ECHAM–HAM to estimate aerosol emissions from POLDER-3/PARASOL (POLarization and Directionality of the Earth's Reflectances) observations for the year 2006. We assimilate aerosol optical depth at 550 mnm (AOD550), the Ångström exponent at 550 and 865 nm (AE550–865), and single-scattering albedo at 550 nm (SSA550) in order to improve modeled aerosol mass, size and absorption simultaneously. The new global aerosol emissions increase to 1419 Tg yr−1 (+28 %) for dust, 1850 Tg yr−1 (+75 %) for sea salt, 215 Tg yr−1 (+143 %) for organic aerosol and 13.3 Tg yr−1 (+75 %) for black carbon, while the sulfur dioxide emissions increase to 198 Tg yr−1 (+42 %) and the total deposition of sulfates to 293 Tg yr−1 (+39 %). Organic and black carbon emissions are much higher than their prior values from bottom-up inventories, with a stronger increase in biomass burning sources (+193 % and +90 %) than in anthropogenic sources (115 % and 70 %). The evaluation of the experiments with POLDER (assimilated) and AERONET as well as MODIS Dark Target (independent) observations shows a clear improvement compared with the ECHAM–HAM control run. Specifically based on AERONET, the global mean error in AOD550 improves from −0.094 to −0.006, while absorption aerosol optical depth at 550 nm (AAOD550) improves from −0.009 to −0.004 after the assimilation. A smaller improvement is also observed in the AE550–865 mean absolute error (from 0.428 to 0.393), with a considerably higher improvement over isolated island sites at the ocean. The new dust emissions are closer to the ensemble median of AEROCOM I, AEROCOM III and CMIP5 as well as some of the previous assimilation studies. The new sea salt emissions have become closer to the reported emissions from previous studies. Indications of a missing fraction of coarse dust and sea salt particles are discussed. The biomass burning changes (based on POLDER) can be used as alternative biomass burning scaling factors for the Global Fire Assimilation System (GFAS) inventory distinctively estimated for organic carbon (2.93) and black carbon (1.90) instead of the recommended scaling of 3.4 (Kaiser et al., 2012). The estimated emissions are highly sensitive to the relative humidity due to aerosol water uptake, especially in the case of sulfates. We found that ECHAM–HAM, like most of the global climate models (GCMs) that participated in AEROCOM and CMIP6, overestimated the relative humidity compared with ERA5 and as a result the water uptake by aerosols, assuming the kappa values are not underestimated. If we use the ERA5 relative humidity, sulfate emissions must be further increased, as modeled sulfate AOD is lowered. Specifically, over East Asia, the lower AOD can be attributed to the underestimated precipitation and the lack of simulated nitrates in the model.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-23-9495-2023
    DOI: 10.5194/acp-23-9495-2023-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
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