Technical note: Introduction to MIMICA, a large‐eddy simulation solver for cloudy planetary boundary layers

Savre, Julien; Ekman, Annica M. L.; Svensson, Gunilla

doi:10.1002/2013ms000292

Cited by 42 publications

(60 citation statements)

References 104 publications

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“…In LEV3, the CCN (i.e. cloud droplet) concentration is set to 55 cm −3 , which roughly corresponds to the number of cloud droplets initially produced by LEV4 and is also the number used in other LES simulations based on this particular case (Ackerman et al, 2009;Savre et al, 2014).…”

Section: Reference Case Experimentsmentioning

confidence: 99%

“…However, the treatment of cloud microphysics is subject to high variability in terms of the level of detail and computational cost (Khain et al,moment bulk schemes, where droplet mass is predicted typically through saturation adjustment, with either prescribed or varying droplet number concentrations (Khairoutdinov and Kogan, 2000;Golaz et al, 2005;Beheng, 2001, 2006;Stevens et al, 2005;Savre et al, 2014), to more elaborate ones with modal or sectional representations for the droplet size distributions (Feingold et al, 1996;Feingold and Kreidenweis, 2002;Saleeby et al, 2015) and Lagrangian particle-based methods (Shima et al, 2009). In addition, there has been an increasing trend towards including representations for aerosol particles in these models as well (Feingold and Kreidenweis, 2002;Kazil et al, 2011;Maalick et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation

et al. 2017

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Abstract. Challenges in understanding the aerosol-cloud interactions and their impacts on global climate highlight the need for improved knowledge of the underlying physical processes and feedbacks as well as their interactions with cloud and boundary layer dynamics. To pursue this goal, increasingly sophisticated cloud-scale models are needed to complement the limited supply of observations of the interactions between aerosols and clouds. For this purpose, a new large-eddy simulation (LES) model, coupled with an interactive sectional description for aerosols and clouds, is introduced. The new model builds and extends upon the well-characterized UCLA Large-Eddy Simulation Code (UCLALES) and the Sectional Aerosol module for Large-Scale Applications (SALSA), hereafter denoted as UCLALES-SALSA. Novel strategies for the aerosol, cloud and precipitation bin discretisation are presented. These enable tracking the effects of cloud processing and wet scavenging on the aerosol size distribution as accurately as possible, while keeping the computational cost of the model as low as possible. The model is tested with two different simulation set-ups: a marine stratocumulus case in the DYCOMS-II campaign and another case focusing on the formation and evolution of a nocturnal radiation fog. It is shown that, in both cases, the size-resolved interactions between aerosols and clouds have a critical influence on the dynamics of the boundary layer. The results demonstrate the importance of accurately representing the wet scavenging of aerosol in the model. Specifically, in a case with marine stratocumulus, precipitation and the subsequent removal of cloud activating particles lead to thinning of the cloud deck and the formation of a decoupled boundary layer structure. In radiation fog, the growth and sedimentation of droplets strongly affect their radiative properties, which in turn drive new droplet formation. The size-resolved diagnostics provided by the model enable investigations of these issues with high detail. It is also shown that the results remain consistent with UCLALES (without SALSA) in cases where the dominating physical processes remain well represented by both models.

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Section: Reference Case Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation

et al. 2017

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“…Cloud droplets are activated from aerosol particles following Khvorostyanov and Curry [2006], but adapted to use the kappa-Kohler theory of Petters and Kreidenweis [2007]. Ice crystal number concentrations are kept quasi-constant [Savre et al, 2014] following the method of Morrison et al [2011]. Wet deposition occurs if cloud droplets fall out as rain.…”

Section: Model Descriptionmentioning

confidence: 99%

The free troposphere as a potential source of arctic boundary layer aerosol particles

Igel

Ekman

Leck

et al. 2017

Geophysical Research Letters

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This study investigates aerosol particle transport from the free troposphere to the boundary layer in the summertime high Arctic. Observations from the Arctic Summer Cloud Ocean Study field campaign show several occurrences of high aerosol particle concentrations above the boundary layer top. Large‐eddy simulations suggest that when these enhanced aerosol concentrations are present, they can be an important source of aerosol particles for the boundary layer. Most particles are transported to the boundary layer by entrainment. However, it is found that mixed‐phase stratocumulus clouds, which often extend into the inversion layer, also can mediate the transport of particles into the boundary layer by activation at cloud top and evaporation below cloud base. Finally, the simulations also suggest that aerosol properties at the surface sometimes may not be good indicators of aerosol properties in the cloud layer.

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“…ICA; Savre et al, 2014) and the Consortium for Small-scale Modeling (COSMO) model configured as an LES model (Loewe et al, 2017) (hereafter referred to as COSMO-LES). The NWP models are v3.6.1 of the Polar Weather Research and Forecasting model (Polar WRF; Hines et al, 2015), the Met Office Unified Model with Cloud AeroSol Interacting Microphysics (UM-CASIM; Grosvenor et al, 2017), and COSMO configured as an NWP model (Steppeler et al, 2003) (hereafter referred to as COSMO-NWP).…”

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confidence: 99%

“…The CCN activation is described by the 'kappa-Köhler' theory (Petters and Kreidenweis, 2007). A four-stream radiative transfer solver (Fu and Liou, 1993) is used Savre et al (2014).…”

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confidence: 99%

A Model Intercomparison of CCN-Limited Tenuous Clouds in the High Arctic

Stevens¹,

Loewe²,

Dearden³

et al. 2017

Preprint

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. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, 5 COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNC) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing.There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concen-10 trations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts on autoconversion rates. Our results therefore suggest that properly estimating aerosol-cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in-situ observations of hydrometeor size distributions to constrain them.The results strongly support the hypothesis that the liquid water content of these clouds is CCN-limited. For the observed 15 meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between 5 clouds, surface temperatures and atmospheric stability need to be considered for weather and climate predictions in this region.

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Technical note: Introduction to MIMICA, a large‐eddy simulation solver for cloudy planetary boundary layers

Cited by 42 publications

References 104 publications

UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation

UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation

The free troposphere as a potential source of arctic boundary layer aerosol particles

A Model Intercomparison of CCN-Limited Tenuous Clouds in the High Arctic

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