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arcticclouds [2021/09/24 14:29] – [Mixed-phase clouds in transforming Arctic air masses] neggersarcticclouds [2024/01/26 19:20] (current) – [Cold air outbreaks] adding link to COMBLE chylik
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 ====== Arctic clouds ====== ====== Arctic clouds ======
  
-{{ :wiki:svalbard_pic.jpg?nolink&200|Low-level clouds observed on Svalbard}}+{{ :wiki:svalbard_pic.jpg?nolink&300|Low-level clouds observed on Svalbard}}
  
 Arctic climate features an abundance of low-level clouds. It is well known from scientific studies in the past that these clouds can significantly affect the radiative energy budget of the atmosphere and at the surface(( Tsay, S. C., Stamnes, K. and K. Jayaweera (1989). //Radiative energy budget in the cloudy and hazy Arctic//. Journal of the atmospheric sciences, **46** (7), pp. 1002-1018. )). For these reasons it can be expected that low-level clouds could play an important role in the currently ongoing warming of the Arctic climate, a process also known as Arctic Amplification.(( Wendisch M., Yang, P., and Ehrlich, A. (2013). //Amplified climate changes in the Arctic: Role of clouds and Arctic climate features an abundance of low-level clouds. It is well known from scientific studies in the past that these clouds can significantly affect the radiative energy budget of the atmosphere and at the surface(( Tsay, S. C., Stamnes, K. and K. Jayaweera (1989). //Radiative energy budget in the cloudy and hazy Arctic//. Journal of the atmospheric sciences, **46** (7), pp. 1002-1018. )). For these reasons it can be expected that low-level clouds could play an important role in the currently ongoing warming of the Arctic climate, a process also known as Arctic Amplification.(( Wendisch M., Yang, P., and Ehrlich, A. (2013). //Amplified climate changes in the Arctic: Role of clouds and
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-===== Mixed-phase clouds in transforming Arctic air masses =====+===== Mixed-phase clouds in transforming air masses =====
  
 Particles of liquid and frozen water in Earth's atmosphere are known as //hydrometeors//. Both phases can co-exist, a situation referred to as //mixed phase// clouds. Such clouds are persistently observed in the Arctic. The liquid phase can occur at temperatures that are far below freezing. Such supercooled cloud droplets are often found when few ice condensation nucleii are present in the volume of air. After the formation of supercooled droplets, it takes some time for them to freeze over and become ice crystals. These delicacies make mixed phase clouds difficult to model. This applies not only to large-scale weather and climate models, but also high resolution models such as LES. Hydrometeor sizes often do not exceed the micrometer scale, and are always much smaller than the typical gridspacing in models. As a result, hydrometeors have to be parameterized through a //microphysics scheme//. Such schemes are not perfect and introduce sensitivity to parametric choices, in both LES experiments and weather and climate model simulations. This motivates further research into this topic. Particles of liquid and frozen water in Earth's atmosphere are known as //hydrometeors//. Both phases can co-exist, a situation referred to as //mixed phase// clouds. Such clouds are persistently observed in the Arctic. The liquid phase can occur at temperatures that are far below freezing. Such supercooled cloud droplets are often found when few ice condensation nucleii are present in the volume of air. After the formation of supercooled droplets, it takes some time for them to freeze over and become ice crystals. These delicacies make mixed phase clouds difficult to model. This applies not only to large-scale weather and climate models, but also high resolution models such as LES. Hydrometeor sizes often do not exceed the micrometer scale, and are always much smaller than the typical gridspacing in models. As a result, hydrometeors have to be parameterized through a //microphysics scheme//. Such schemes are not perfect and introduce sensitivity to parametric choices, in both LES experiments and weather and climate model simulations. This motivates further research into this topic.
  
-{{ ::schematic.png?direct&450|}}+{{ ::schematic.png?direct&450|Schematic illustration of the control of subsidence on Arctic mixed-layer evolution. Figure copied from Neggers et al (2019)}}
 Mixed phase clouds in the Arctic are typically embedded in a much larger air mass, the origin of which can be far remote, even outside the Arctic. Mixed phase clouds play a key role in how such air masses transform as they move in and out of the Arctic. The presence of liquid hydrometeors in such air masses has been reported to greatly affect the speed at which the sea ice melts in the warming Arctic climate. Accelerated melt has been observed to coincide with liquid cloud presence as part of intrusions of warm and moist air into the Artic. This is linked to the strong impact of liquid clouds on the downwelling long wave radiation at the surface. Another way in which mixed phase clouds interact with the Arctic climate system is through subsidence, which can act as a control on the persistence of mixed-phase cloud systems (see illustration). Mixed phase clouds in the Arctic are typically embedded in a much larger air mass, the origin of which can be far remote, even outside the Arctic. Mixed phase clouds play a key role in how such air masses transform as they move in and out of the Arctic. The presence of liquid hydrometeors in such air masses has been reported to greatly affect the speed at which the sea ice melts in the warming Arctic climate. Accelerated melt has been observed to coincide with liquid cloud presence as part of intrusions of warm and moist air into the Artic. This is linked to the strong impact of liquid clouds on the downwelling long wave radiation at the surface. Another way in which mixed phase clouds interact with the Arctic climate system is through subsidence, which can act as a control on the persistence of mixed-phase cloud systems (see illustration).
  
-High-resolution simulations of mixed-phase clouds can provide insights, acting as a virtual laboratory for studies at process level. To gain confidence in the model, it is of key importance to thoroughly evaluate its realizations of mixed-phase clouds against local measurements is of key importance. Achieving this is a key science objective of the InScAPE group.+High-resolution simulations of mixed-phase clouds can provide insights, acting as a virtual laboratory for studies at process level. To gain confidence in the model, it is of key importance to thoroughly evaluate simulations of mixed-phase clouds against relevant measurements. Achieving this is a key science objective of the InScAPE group.
  
 Related papers: Related papers:
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   * Local and remote controls on Arctic mixed layer evolution [[https://doi.org/10.1029/2019MS001671|Neggers et al, (2019)]]   * Local and remote controls on Arctic mixed layer evolution [[https://doi.org/10.1029/2019MS001671|Neggers et al, (2019)]]
   * Investigating Arctic humidity inversions using balloon-borne measurements and large-eddy simulations [[https://doi.org/10.5194/acp-2020-584|Egerer et al. (2021)]]   * Investigating Arctic humidity inversions using balloon-borne measurements and large-eddy simulations [[https://doi.org/10.5194/acp-2020-584|Egerer et al. (2021)]]
-  * Aerosol-cloud-turbulence interactions in well-coupled Arctic boundary layers over open water. Chylik et al., in preparation for ACPD, September 2021+  * Aerosol-cloud-turbulence interactions in well-coupled Arctic boundary layers over open water. [[https://doi.org/10.5194/acp-23-4903-2023|Chylik et al. (2023)]]
  
  
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 Cold air outbreaks (CAOs) in the Arctic are situations in which a low level mass of cold air initially situated over the sea ice is advected across the ice edge and continues over open water. This process is accompanied by the formation of a convective boundary layer that deepens rapidly, featuring strong surface heat fluxes as well as the formation of low-level mixed-phase clouds. The dynamics in the CAO boundary layer are often complex, as illustrated in Fig. 2. Often these clouds are organized into streets, which at some point downstream of the ice edge tend to break up into bigger individual cells. These cells, often arranged into a spoke-pattern, can appear as either open cells (with a cloud free center) or as closed cells. Recent research has suggested that microphysical processes play an important role in determining the eventual cloudiness in the cell centers. Cold air outbreaks (CAOs) in the Arctic are situations in which a low level mass of cold air initially situated over the sea ice is advected across the ice edge and continues over open water. This process is accompanied by the formation of a convective boundary layer that deepens rapidly, featuring strong surface heat fluxes as well as the formation of low-level mixed-phase clouds. The dynamics in the CAO boundary layer are often complex, as illustrated in Fig. 2. Often these clouds are organized into streets, which at some point downstream of the ice edge tend to break up into bigger individual cells. These cells, often arranged into a spoke-pattern, can appear as either open cells (with a cloud free center) or as closed cells. Recent research has suggested that microphysical processes play an important role in determining the eventual cloudiness in the cell centers.
  
-In the recent ACLOUD field campaign in May 2017, which is part of the ongoing (AC)<sup>3</sup> project, some cold air outbreaks where sampled in the Fram Strait west of the Svalbard group of islands. At InScAPE we are currently performing fine-scale model simulations of these CAO cases, making use of ACLOUD measurements to assess their realism.+In the recent ACLOUD field campaign in May 2017, which is part of the ongoing (AC)<sup>3</sup> project, some cold air outbreaks where sampled in the Fram Strait west of the Svalbard group of islands. At InScAPE we are currently performing [[models#dales|fine-scale model]] simulations of these CAO cases, making use of measurements from field campaigns such as [[narvalsimulations#mosaic|ACLOUD and MOSAiC]] to assess their realism.
  
 Related papers: Related papers:
   * Turbulent transport in the Grey Zone: A large-eddy simulation model intercomparison study of the CONSTRAIN cold air outbreak case [[https://doi.org/10.1029/2018MS001443|De Roode et al. (2019)]]   * Turbulent transport in the Grey Zone: A large-eddy simulation model intercomparison study of the CONSTRAIN cold air outbreak case [[https://doi.org/10.1029/2018MS001443|De Roode et al. (2019)]]
 +
 +Ongoing projects:
 +  * COMBLE Model-Observation Intercomparison Project: 13 March 2020 cold-air outbreak over Fram Strait [[https://arm-development.github.io/comble-mip/README.html|arm-development.github.io/comble-mip]] 
  
 ===== Arctic clouds in complex terrain ===== ===== Arctic clouds in complex terrain =====
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 Various field campaigns have taken place near the Svalbard archipelago in the context of the ongoing (AC)<sup>3</sup> research project. Various instrument platforms were involved, including fixed sites (AWIPEV site at Ny Aalesund), ship cruises with the PolarStern research vessel, and flights with the Polar 5 and 6 research aircraft. A key part of the overall research strategy was to combine the benefits of all three platforms. For example, on many research flights the aircraft met with the PolarStern on its journey North towards the ice edge, and during the period in which it was frozen into the solid pack-ice. During some periods all three platforms were situated at the same location at Ny Aalesund, combining all instrumentation. In the modeling of Arctic clouds at InScAPE we focus on these IOP periods, to optimize the availability of relevant data to support the simulations. Various field campaigns have taken place near the Svalbard archipelago in the context of the ongoing (AC)<sup>3</sup> research project. Various instrument platforms were involved, including fixed sites (AWIPEV site at Ny Aalesund), ship cruises with the PolarStern research vessel, and flights with the Polar 5 and 6 research aircraft. A key part of the overall research strategy was to combine the benefits of all three platforms. For example, on many research flights the aircraft met with the PolarStern on its journey North towards the ice edge, and during the period in which it was frozen into the solid pack-ice. During some periods all three platforms were situated at the same location at Ny Aalesund, combining all instrumentation. In the modeling of Arctic clouds at InScAPE we focus on these IOP periods, to optimize the availability of relevant data to support the simulations.
  
-More information about the (AC)<sup>3</sup> project and its field campaigns in the Arctic can be found [[http://www.ac3-tr.de/overview/observations/|here]]+More information about the (AC)<sup>3</sup> project and its field campaigns in the Arctic can be found on the [[http://www.ac3-tr.de/overview/observations/|project website]]
  
 Related datasets and papers: Related datasets and papers:
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   * LES results to accompany measurements at the POLARSTERN Research Vessel during the PASCAL field campaign on 7 June 2017 [[https://doi.pangaea.de/10.1594/PANGAEA.919946|Neggers (2020b)]]   * LES results to accompany measurements at the POLARSTERN Research Vessel during the PASCAL field campaign on 7 June 2017 [[https://doi.pangaea.de/10.1594/PANGAEA.919946|Neggers (2020b)]]
   * Glimpsing the ins and outs of the Arctic atmospheric cauldron [[https://doi.org/10.1029/2021EO155959|Wendisch et al. (2020)]]   * Glimpsing the ins and outs of the Arctic atmospheric cauldron [[https://doi.org/10.1029/2021EO155959|Wendisch et al. (2020)]]
 +  *  Case study of a humidity layer above Arctic stratocumulus using balloon-borne turbulence and radiation measurements and large eddy simulations [[https://doi.org/10.5194/acp-2020-584| Egerer et al. (2021)]]
 +  * The COMBLE campaign: a study of marine boundary-layer clouds in Arctic cold-air outbreaks [[https://doi.org/10.1175/BAMS-D-21-0044.1|Geerts et al. (2022)]]
 ===== Large Eddy Simulations ===== ===== Large Eddy Simulations =====
  
 ==== Model codes ==== ==== Model codes ====
  
-At InScAPE the fine-scale simulations of Arctic clouds are performed with two models. The Dutch Atmospheric Large Eddy Simulation model (DALES)+At InScAPE the fine-scale simulations of Arctic clouds are performed with two models. The Dutch Atmospheric Large Eddy Simulation model ([[https://github.com/dalesteam/dales|DALES]])
 (( Heus, T., Heerwaarden, C. C. v.,  and coauthors (2010). //Formulation of the Dutch Atmospheric Large-Eddy (( Heus, T., Heerwaarden, C. C. v.,  and coauthors (2010). //Formulation of the Dutch Atmospheric Large-Eddy
-Simulation (DALES) and overview of its applications.// Geoscientific model development, **3** (2), pp. 415-444. )) is an LES code that has been developed decades ago, and has participated in many scientific model intercomparison and evaluation studies. The Icosahedral Non-hydrostatic (ICON) model was recently developed at both MPI Hamburg and the German Weather Service (DWD), and can be applied at multiple resolutions. While both codes share many features, in particular their capability to perform realistic high-resolution simulations of boundary layer clouds, there are also a few key differences. Apart from numerical differences these mainly concern the spatial homogeneity of surface properties such as orography, and the capability to perform simulations in a nested setting. At InScAPE we aim to use both codes in conjunction, profiting from the benefits of both approaches.+Simulation (DALES) and overview of its applications.// Geoscientific model development, **3** (2), pp. 415-444. )) is an LES code that has been developed decades ago, and has participated in many scientific model intercomparison and evaluation studies. The Icosahedral Non-hydrostatic ([[https://code.mpimet.mpg.de/projects/iconpublic|ICON]]) model was recently developed at both MPI Hamburg and the German Weather Service (DWD), and can be applied at multiple resolutions. While both codes share many features, in particular their capability to perform realistic high-resolution simulations of boundary layer clouds, there are also a few key differences. Apart from numerical differences these mainly concern the spatial homogeneity of surface properties such as orography, and the capability to perform simulations in a nested setting. At InScAPE we aim to use both codes in conjunction, profiting from the benefits of both approaches.
  
-The DALES and ICON models are described in more detail [[models|here]].+The DALES and ICON models are described in more detail in the [[models|overview of models]].
  
 ==== Mixed-Phase Microphysics in LES ==== ==== Mixed-Phase Microphysics in LES ====
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   * CCN and INP concentration can differ with altitude, not just a constant   * CCN and INP concentration can differ with altitude, not just a constant
   * latent heat of freezing included in the heat budget   * latent heat of freezing included in the heat budget
-  * initial conditions and large-scale forcings derived from large-scale models following the method used in parameterization testbeds (( Neggers, R. A. J., A. P. Siebesma and T. Heus, 2012: Continuous single-column model evaluation at a permanent meteorological supersite. Bull. Amer. Meteor. Soc., 93, p1389-1400, DOI:10.1175/BAMS-D-11-00162.1  ))+  * initial conditions and large-scale forcings derived from large-scale models following the method used in [[testbed|parameterization testbeds]] (( Neggers, R. A. J., A. P. Siebesma and T. Heus, 2012: Continuous single-column model evaluation at a permanent meteorological supersite. Bull. Amer. Meteor. Soc., 93, p1389-1400, DOI:10.1175/BAMS-D-11-00162.1  ))
  
 The performance of this implementation has been tested on chosen semi-idealised cold-air outbreak cases. This includes the  including M-PACE (( Solomon, A., Morrison, H., Persson, O., Shupe, M. D., and J. W. Bao (2009). //Investigation of microphysical parameterizations of snow and ice in Arctic clouds during M-PACE through model-observation comparisons.// Monthly Weather Review, **137** (9), pp. 3110-3128. )), which was an observed cold-air outbreak case of the coast of Alaska, and ARM (( Klein, S. A., Neggers, R. A. J., and coauthors (2009). //Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud.// Quart. J. Roy. Meteor. Soc., **135**, pp. 979–1002. )). However, it is intended to be employed also for the fine simulation of Arctic spring stratocumulus. With the aim to properly represent a varying concentration of aerosols in Arctic, this implementation also allows to define vertical profiles of CCN. The performance of this implementation has been tested on chosen semi-idealised cold-air outbreak cases. This includes the  including M-PACE (( Solomon, A., Morrison, H., Persson, O., Shupe, M. D., and J. W. Bao (2009). //Investigation of microphysical parameterizations of snow and ice in Arctic clouds during M-PACE through model-observation comparisons.// Monthly Weather Review, **137** (9), pp. 3110-3128. )), which was an observed cold-air outbreak case of the coast of Alaska, and ARM (( Klein, S. A., Neggers, R. A. J., and coauthors (2009). //Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud.// Quart. J. Roy. Meteor. Soc., **135**, pp. 979–1002. )). However, it is intended to be employed also for the fine simulation of Arctic spring stratocumulus. With the aim to properly represent a varying concentration of aerosols in Arctic, this implementation also allows to define vertical profiles of CCN.
arcticclouds.1632486563.txt.gz · Last modified: 2021/09/24 14:29 by neggers