Abstract
Abstract. The global aerosol–climate model ECHAM6.3–HAM2.3 (E63H23) as well as the previous model versions ECHAM5.5–HAM2.0 (E55H20) and ECHAM6.1–HAM2.2 (E61H22) are evaluated using global observational datasets for clouds and precipitation. In E63H23, the amount of low clouds, the liquid and ice water path, and cloud radiative effects are more realistic than in previous model versions. E63H23 has a more physically based aerosol activation scheme, improvements in the cloud cover scheme, changes in the detrainment of convective clouds, changes in the sticking efficiency for the accretion of ice crystals by snow, consistent ice crystal shapes throughout the model, and changes in mixed-phase freezing; an inconsistency in ice crystal number concentration (ICNC) in cirrus clouds was also removed. Common biases in ECHAM and in E63H23 (and in previous ECHAM–HAM versions) are a cloud amount in stratocumulus regions that is too low and deep convective clouds over the Atlantic and Pacific oceans that form too close to the continents (while tropical land precipitation is underestimated). There are indications that ICNCs are overestimated in E63H23. Since clouds are important for effective radiative forcing due to aerosol–radiation and aerosol–cloud interactions (ERFari+aci) and equilibrium climate sensitivity (ECS), differences in ERFari+aci and ECS between the model versions were also analyzed. ERFari+aci is weaker in E63H23 (−1.0 W m−2) than in E61H22 (−1.2 W m−2) (or E55H20; −1.1 W m−2). This is caused by the weaker shortwave ERFari+aci (a new aerosol activation scheme and sea salt emission parameterization in E63H23, more realistic simulation of cloud water) overcompensating for the weaker longwave ERFari+aci (removal of an inconsistency in ICNC in cirrus clouds in E61H22). The decrease in ECS in E63H23 (2.5 K) compared to E61H22 (2.8 K) is due to changes in the entrainment rate for shallow convection (affecting the cloud amount feedback) and a stronger cloud phase feedback. Experiments with minimum cloud droplet number concentrations (CDNCmin) of 40 cm−3 or 10 cm−3 show that a higher value of CDNCmin reduces ERFari+aci as well as ECS in E63H23.
Highlights
Clouds are the largest modulators of radiation in Earth’s atmosphere
For all variables the root mean square error (RMSE) is smaller than or equal to the RMSE in ECHAM6.3– HAM2.3 (E63H23) compared to E61H22 and E55H20
E55H20 has higher correlations of LW cloud radiative effect (CRE), ice water path (IWP), and precipitation because the ratio of the peaks in these variables in the tropics compared to midlatitudes is better represented in E55H20
Summary
Clouds are the largest modulators of radiation in Earth’s atmosphere. Cloud hydrometeors are generally shorter lived than other modulators of radiation in the atmosphere like aerosol particles, greenhouse gases, or changes in surface albedo through changes in land use. Neubauer et al.: The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 2 air and on convective and turbulent motions at different scales These convective and turbulent motions in turn are driven in large part by diabatic heating (and cooling) and radiative cooling (and heating) involving cloud and precipitation hydrometeors, leading to a tight coupling between clouds and circulation (e.g., Wood, 2012; Voigt et al, 2014; Vial et al, 2016). The range of microphysical properties of cloud droplets and ice crystals adds to the complexity of clouds in Earth’s atmosphere This complexity makes clouds difficult to observe and to simulate using models, substantially contributing to the current large uncertainties in future climate projections. It is crucial to evaluate clouds in these models with reliable observations and account for the complexity in clouds in the process
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