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Here we present for the first time a proof of concept for an emulation-based method that uses a large-eddy simulations (LESs) to present sub-grid cloud processes in a general circulation model (GCM). We focus on two key variables affecting the properties of shallow marine clouds: updraft velocity and precipitation formation. The LES is able to describe these processes with high resolution accounting for the realistic variability in cloud properties. We show that the selected emulation method is able to represent the LES outcome with relatively good accuracy and that the updraft velocity and precipitation emulators can be coupled with the GCM practically without increasing the computational costs. We also show that the emulators influence the climate simulated by the GCM but do not consistently improve or worsen the agreement with observations on cloud-related properties, although especially the updraft velocity at cloud base is better captured. A more quantitative evaluation of the emulator impacts against observations would, however, have required model re-tuning, which is a significant task and thus could not be included in this proof-of-concept study. All in all, the approach introduced here is a promising candidate for representing detailed cloud- and aerosol-related sub-grid processes in GCMs. Further development work together with increasing computing capacity can be expected to improve the accuracy and the applicability of the approach in climate simulations. [ABSTRACT FROM AUTHOR]

Here we present for the first time a proof of concept for an emulation-based method that uses a large-eddy simulations (LES) to present sub-grid cloud processes in a general circulation model (GCM). We focus on two key variables affecting the properties of shallow marine clouds: updraft velocity and precipitation formation. The LES is able to describe these processes with high resolution accounting for the realistic variability in cloud properties. We show that the selected emulation method is 5 able to represent the LES outcome with relatively good accuracy and that the updraft velocity and precipitation emulators can be coupled with the GCM practically without increasing the computational costs. We also show that the emulators influence the climate simulated by the GCM, but do not consistently improve or worsen the agreement with observations on cloud related properties. Although especially the updraft velocity at cloud base is better captured. A more quantitative evaluation of the emulator impacts against observations would, however, have required model re-tuning, which is a significant task and thus could 10 not be included in this proof-of-concept study. All in all, the approach introduced here is a promising candidate for representing detailed cloud and aerosol related sub-grid processes in GCMs. Further development work together with increasing computing capacity can be expected to improve the accuracy and the applicability of the approach in climate simulations. [ABSTRACT FROM AUTHOR]

Shallow marine mixed-phase clouds are important for the Earth's radiative balance, but modelling their formation and dynamics is challenging. These clouds depend on boundary layer turbulence and cloud top radiative cooling, which is related to the cloud phase. The fraction of frozen droplets depends on the availability of suitable ice-nucleating particles (INPs), which initiate droplet freezing. While mineral dust is the dominating INP type in most regions, high-latitude boundary layer clouds can be dependent on local marine INP emissions, which are often related to biogenic sources including phytoplankton. Here we use high resolution large eddy simulations to examine the potential effects of marine emissions on boundary layer INP concentrations and their effects on clouds. Surface emissions have a direct effect on INP concentration in a typical well-mixed boundary layer whereas a steep inversion can block the import of background INPs from the free troposphere. The importance of the marine source depends on the background INP concentration, so that marine INP emissions become more important with lower background INP concentrations. For the INP budget it is also important to account for INP recycling. Finally, with the high-resolution model we show how ice nucleation hotspots and high INP concentrations are focused on updraught regions. Our results show that marine INP emissions contribute directly to the boundary layer INP budget and therefore have an influence on mixed-phase clouds. [ABSTRACT FROM AUTHOR]

The number of cloud droplets formed at the cloud base depends both on the properties of aerosol particles and the updraft velocity of an air parcel at the cloud base. As the spatial scale of updrafts is too small to be resolved in global atmospheric models, the updraft velocity is commonly parameterised based on the available turbulent kinetic energy. Here we present alternative methods through parameterising updraft velocity based on high-resolution large eddy simulation (LES) runs in the 5 case of marine stratocumulus clouds. First we use our simulations to assess the accuracy of a simple linear parametrisation where the updraft velocity depends only on cloud top radiative cooling. In addition, we present two different machine learning methods (Gaussian process emulation and random forest) that account for different boundary layer conditions and cloud properties. We conclude that both machine learning parameterisations reproduce the LES-based updraft velocities at about the same accuracy, while the simple approach employing radiative cooling only produce on average lower coefficient 10 of determination and higher root mean square error values. Finally, we apply these machine learning methods to find the key parameters affecting cloud base updraft velocities. [ABSTRACT FROM AUTHOR]

Shallow marine mixed-phase clouds are important for the radiative balance, but modelling their formation and dynamics is challenging. These clouds depend on boundary layer turbulence and cloud top radiative cooling, which is related to the cloud phase. The fraction of frozen droplets depends on the availability of suitable ice nucleating particles (INPs), which initiate droplet freezing. While desert dust is the dominating INP type in most regions, remote boundary layer clouds are dependent on local marine INP emissions, which are often related to biogenic sources including phytoplankton. Here we use high resolution large eddy simulations to examine the potential effects of marine emissions on boundary layer INP concentrations and their effects on clouds. Surface emissions have a direct effect on INP concentration in a typical well-mixed boundary layer whereas a steep inversion can block the import of background INPs from the free troposphere. The importance of the marine source depends on the background INP concentration, so that marine emissions become dominant with low background concentrations. For the INP budget it is also important to account for INP recycling. Finally, with the high-resolution model we show how ice nucleation hotspots and high INPs concentrations are focused on updraught regions. Our results show that marine INP emissions contribute directly to the boundary layer INP budget and therefore have an influence on mixed-phase clouds. [ABSTRACT FROM AUTHOR]

The large-eddy model UCLALES-SALSA, with exceptionally detailed aerosol description for both aerosol number and chemical composition, has been extended for ice and mixed-phase clouds. Comparison to a previous mixed-phase cloud model intercomparison study confirmed the accuracy of newly implemented ice microphysics. Further simulation with a heterogeneous ice nucleation scheme, where also ice nucleating particles (INP) are a prognostic variable, captured the typical layered structure of Arctic mid-altitude mixed-phase cloud: a liquid layer near cloud top and ice within and below the liquid layer. In addition, the simulation showed realistic freezing rate of droplets within the vertical cloud structure. The represented detailed sectional ice microphysics with prognostic aerosols is crucially important in reproducing mixed-phase clouds. [ABSTRACT FROM AUTHOR]

The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2-m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for ten Finnish, four Swedish, two Russian and one Estonian lakes. The results show that the model can reproduce these characteristic with reasonably high accuracy. The cold bias during winter causes e.g. overestimation of ice layer thickness at several of the studied lakes, but overall the values from the model are realistic and represent well the lake physics in a long-term simulation. We also analyzed the snow depth on ice from ten Finnish lakes and vertical temperature profiles from five Finnish lakes and the model results are in realistic. [ABSTRACT FROM AUTHOR]

Clouds are an integral part of the climate system. Due to the importance of small-scale phenomena such as turbulence, cloud processes cannot be resolved in global climate models and need to be parametrised. In their current form, cloud parametrisations are unable to accurately reproduce the effects of clouds, which introduces uncertainties to climate models. A much more accurate description of clouds can be obtained through large eddy simulation (LES) but it comes with a very high computational cost.To improve the parametrisation of marine stratocumulus clouds in global climate models, we have developed an approach using a statistical emulator. The emulator is based on the binary space partitioning method and was trained using an ensemble of LESs performed using the UCLALES-SALSA model. All of our training simulations concerned marine stratocumulus clouds due to their relative simplicity and their high importance on the global radiative budget. We coupled the emulator with the ECHAM6 global climate model using several different variables such as inversion strength and aerosol concentrations. The emulator was applied in grid boxes where marine stratocumulus clouds were present. [ABSTRACT FROM AUTHOR]

Typical marine boundary layer clouds are dependent on sensible and latent heat fluxes, turbulent updrafts and radiative cooling from the cloud top. In addition, clouds are dependent on aerosol that can act as a cloud condensation nuclei (CCN). Large eddy simulation (LES) models that are coupled with a radiative transfer solver and a cloud microphysics package are excellent tools for examining such clouds. Here we compare predictions from a LES model that is coupled with two very different cloud microphysics packages. The LES model is UCLALES (e.g., Stevens et al., Mon. Wea. Rev., 133, 1443-1462, 2005), which has a built-in bulk microphysics package where cloud droplet number concentration is constant and cloud water is diagnosed from total water. The same LES core was coupled with a highly detailed bin microphysics package and this setup is called UCLALES-SALSA (Tonttila et al., Geosci. Model Dev., 10, 169-188, 2017). In this setup water vapor condensation and cloud activation are modelled using several aerosol and cloud droplet size bins. Both bulk and bin schemes also include precipitation and ice microphysics, but here the focus is on non-precipitating liquid clouds.The model intercomparison is based on 130 cases with different initial atmospheric temperature and humidity profiles and CCN concentrations, which were sampled from ECHAM6 simulations. Both bulk and bin microphysics LES models were run for 3.5 hours and statistics were sampled from the last simulation hour. These simulations show that the final cloud state depends mostly on meteorological conditions. However, there is a range of meteorological conditions, which represent the intermediate region between steady and unsteady cloud conditions, where CCN concentration and microphysics scheme become important for the cloud development. Examination of different cloud stability parameters showed that these regions and the final cloud state can be predicted based on the initial inversion strength (e.g., Lock, Q. J. R. Meteorol. Soc., 135, 941-952, 2009). Even if the effects of CCN concentration and microphysics are relatively small in these simulations, their effects become larger with longer simulation time and with increasing complexity such as when accounting for precipitation and ice microphysics. [ABSTRACT FROM AUTHOR]