The Global Atmosphere-aerosol Model ICON-A-HAM2.3– Initial Model Evaluation...

Salzmann, M., S. Ferrachat, C. Tully, S. Münch, D. Watson-Parris, D. Neubauer, C. S. Drian, S. Rast, B. Heinold, T. Crueger, R. Brokopf, J. Mülmenstädt, J. Quaas, H. Wan, K. Zhang, U. Lohmann, P. Stier, and I. Tegen (2022), The Global Atmosphere-aerosol Model ICON-A-HAM2.3– Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness, J. Adv. Modeling Earth Syst., 22(9), 6347-6364, doi:10.1029/2021MS002699.

The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3-HAM2.3 global atmosphere-aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON-A (iconaes-1.3.00) global atmosphere model to yield the new ICON-A-HAM2.3 atmosphere-aerosol model. The ICON-A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub-grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6-HAM2.3 two-moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICONA-HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON-A-HAM2.3 and ECHAM6.3-HAM2.3, but the bias is larger in ICON-A-HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub-tropical oceans. ICON-A-HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON-A-HAM2.3 compared to standard ICON-A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON-A-HAM2.3 and in ECHAM6.3-HAM2.3. In the extra-tropics, a smaller multivariable bias is found for ICON-A-HAM2.3 than for ECHAM6.3-HAM2.3. Plain Language Summary Aerosols are tiny particles in the air which are either emitted into the atmosphere directly or formed from precursor gases such as sulfur dioxide. Aerosols reflect and absorb solar radiation and affect the radiative properties of clouds. In order to estimate how changing emissions of aerosol precursor gases and aerosols affect the radiation budget of the atmosphere, aerosol models are coupled to global atmosphere models. Here, an aerosol model that has already been part of a well-established coupled model is coupled to a recently developed atmosphere model. The reasons for differences between the original and the new model are investigated and simulated aerosol optical thickness is evaluated against observations. The aerosol optical thickness over subtropical oceans is lower in the new model, which is in better agreement with estimates from satellite observations. This better agreement is traced back to a parameter setting in the cloud description part in the new model. However, because cancellation of positive and negative biases is reduced in the new model, the global mean aerosol optical thickness is biased lower the new model. A bias score based on several meteorological variables is lower in the new model because of lower biases in the extra-tropics.

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Atmospheric Composition
Tropospheric Composition Program (TCP)