Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations

We document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 (GC3.1) and UKESM1, which are contributing to the 6th 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 leads 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 the 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 characterization of the aerosol climatology in both models facilitating the understanding of the numerous aerosol-climate interaction studies that will be conducted as part of CMIP6 and beyond

Site representativity of AERONET and GAW remotely sensed aerosol optical thickness and absorbing aerosol optical thickness observations

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

Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system

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

Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs)

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 550gnm (AOD550), Ångström exponent from 550 to 865gnm (AE550-865), and single-scattering albedo at 550gnm (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 33g% to 117g%. 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 5g%. Despite its limited coverage, the SPEXone sampling shows similar results, with somewhat larger errors for DU and SS (both having a MAE equal to 11g%). Further, experiments show that doubling the measurement error increases the global relative MAE up to 22g% 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

Inverting the east Asian dust emission fluxes using the ensemble Kalman smoother and Himawari-8 AODs: A case study with WRF-Chem v3.5.1

We present the inversions (back-calculations or optimizations) of dust emissions for a severe winter dust event over East Asia in November 2016. The inversion system based on a fixedlag ensemble Kalman smoother is newly implemented in the Weather Research and Forecasting model and is coupled with Chemistry (WRF-Chem). The assimilated observations are the hourly aerosol optical depths (AODs) from the next-generation geostationary satellite Himawari-8. The posterior total dust emissions (2.59 Tg) for this event are 3.8 times higher than the priori total dust emissions (0.68 Tg) during 25-27 November 2016. The net result is that the simulated aerosol horizontal and vertical distributions are both in better agreement with the assimilated Himawari-8 observations and independent observations from the ground-based AErosol RObotic NETwork (AERONET), the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The developed emission inversion approach, combined with the geostationary satellite observations, can be very helpful for properly estimating the Asian dust emissions