Differences

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--- students [2023/07/14 11:44] – [A year in LES (AYIL): Large eddy simulation of the complete MOSAiC drift] neggers
+++ students [2024/03/16 16:06] (current) – [Other possible projects] removing no longer active projects chylik
@@ Line 4: / Line 4: @@
 ==== A year in LES (AYIL): Large eddy simulation of the complete MOSAiC drift  ====
-From September 2019 to September 2020 the Polarstern Research Vessel drifted with the sea ice through the central Arctic, as part of the [[https://mosaic-expedition.org/|MOSAiC]] field campaign. Based on the observational data collected on the ship and by the instrumentation on the sea ice (MetCity), we performed daily Large-Eddy Simulations (LES) of the atmospheric domain surrounding the ship. The spatial and temporal resolutions were high enough to resolve small scale turbulence and clouds. The computational burden of this effort has been considerable, and performing these kind of simulations for a full year in the central Arctic has never been achieved before. With the production runs now completed, the model output can be evaluated against independent measurements. In addition, the simulated turbulence and clouds can be used to gain deeper insight into the ongoing rapid warming of the Arctic. This process is often referred to as Arctic Amplification, which is the central focus of the ongoing [[https://www.ac3-tr.de/|AC3]] project. If you are interested in working with these data, please contact [[https://geomet.uni-koeln.de/institut/beschaeftigte/neggers|Roel Neggers]]
+From September 2019 to October 2020 the Polarstern Research Vessel drifted with the sea ice through the central Arctic, as part of the [[https://mosaic-expedition.org/|MOSAiC]] field campaign. Based on the observational data collected on the ship and by the instrumentation on the sea ice (MetCity), we performed daily Large-Eddy Simulations (LES) of the atmospheric domain surrounding the ship. The spatial and temporal resolutions were high enough to resolve small scale turbulence and clouds. The computational burden of this effort has been considerable, and performing these kind of simulations for a full year in the central Arctic has never been achieved before. With the production runs now completed, the model output can be evaluated against independent measurements. In addition, the simulated turbulence and clouds can be used to gain deeper insight into the ongoing rapid warming of the Arctic. This process is often referred to as Arctic Amplification, which is the central focus of the ongoing [[https://www.ac3-tr.de/|AC3]] project. If you are interested in working with these data, for example to evaluate the LES against measurements or to use the high resolution model output as a virtual laboratory, please contact [[https://geomet.uni-koeln.de/institut/beschaeftigte/neggers|Roel Neggers]] or [[https://geomet.uni-koeln.de/institut/beschaeftigte/chylik|Jan Chylík]]
 {{::mosaic_1.png?nolink&200|MOSAiC logo}}
-{{:20170525_ps106017_sschoen-720px-4132655360.jpeg?direct&200|The Polarstern RV during MOSAiC, surrounded by instrumentation in MetCity on the sea ice}}
+{{:20170525_ps106017_sschoen-720px-4132655360.jpeg?direct&200|The Polarstern RV during MOSAiC, surrounded by instrumentation on the sea ice (MetCity)}}
-{{::mosaic_routine_20200419_crop_small.png?direct&200|Ray tracing rendering of simulatged mixed phase clouds during MOSAiC}}
+{{::mosaic_routine_20200419_crop_small.png?direct&240|Ray tracing rendering of simulated low level mixed-phase clouds during MOSAiC}}
-==== The role of humidity inversions in the Arctic climate system  ====
-Humidity inversion describes the situation where the specific humidity in some layer of air is increasing with altitude instead of decreasing. Humidity inversion atop a cloudy boundary layer are relatively common [[arcticclouds|in the Arctic]]. The entrainment at the top of the top of the cloud layer then often leads to transport of humidity from the free atmosphere into the boundary layer. This can then effect both the precipitation from the clouds and the thermodynamic properties of the clouds.
-Does the presence of humidity inversion lead to warming of cooling of the cloud layer? And does it lead to increase the turbulence in the boundary layer? These questions will be investigated with both conceptual mixed-layer model and large eddy simulation. If you are interested in this topic please contact [[https://geomet.uni-koeln.de/institut/beschaeftigte/chylik|Jan Chylík]]
-==== How does changing ice microphysics affect cloud formation? ====
-Clouds at freezing temperatures can contain various ice particles. There are a few different type of ice crystals that can grow in supersaturated conditions. The differences in shape between  different ice crystals lead to differences in fall velocities, optical properties, but also in their ability to rime liquid droplets or aggregate with other ice crystals.
-That said, an important question is whether the changes in optical properties and precipitation also lead to differences in the vertical structure of a cloud. Based on the observational data from recent campaigns in the Arctic, the problem will be investigated on large-eddy simulations in [[http://atmos.meteo.uni-koeln.de/inscape/doku.php?id=models|DALES]].
-If you are interested in this topic please contact [[https://geomet.uni-koeln.de/institut/beschaeftigte/chylik|Jan Chylík]]
-{{ :difprofiles_tke_b.png?500 | The differences in TKE in model runs with different concentration of ice particles. }}
@@ Line 57: / Line 39: @@
 (A full description will follow shortly)
-  * Confronting fine-scale models with ACLOUD field campaign data on Arctic clouds (Vera Schemann, Jan Chylík, Roel Neggers)
+  * Confronting fine-scale models with ACLOUD and AFLUX field campaign data on Arctic clouds (Vera Schemann, Jan Chylík, Roel Neggers)
-  * Comparing various cloud sampling approaches (Jan Chylík)
-  * Analyze resolution dependency of eddy representation (Jan Chylík)
@@ Line 83: / Line 63: @@
 === Classic cloud fraction parametrizations vs machine learning ===
  We have millions of samples from high-resolution simulations over Germany comparing cloud fraction to other meteorological variables. These samples are a side product of the paper Evaluating and improving a PDF cloud scheme using high-resolution super-large-domain simulations (https://doi.org/10.1029/2018MS001421), and allow a student to very easily and quickly apply various machine learning techniques to derive empirical cloud fraction parameterizations. The first technical steps are already laid, the scope and complexity of the project can be easily adjusted to suit either a Bachelor or Masters thesis. Requirement: Basic Python. To discuss this topic feel free to contact [[https://geomet.uni-koeln.de/institut/beschaeftigte/griewank|Philipp Griewank]].
+==== How does changing ice microphysics affect cloud formation? ====
+Clouds at freezing temperatures can contain various ice particles. There are a few different type of ice crystals that can grow in supersaturated conditions. The differences in shape between  different ice crystals lead to differences in fall velocities, optical properties, but also in their ability to rime liquid droplets or aggregate with other ice crystals.
+That said, an important question is whether the changes in optical properties and precipitation also lead to differences in the vertical structure of a cloud. Based on the observational data from recent campaigns in the Arctic, the problem will be investigated on large-eddy simulations in [[http://atmos.meteo.uni-koeln.de/inscape/doku.php?id=models|DALES]].
+If you are interested in this topic please contact [[https://geomet.uni-koeln.de/institut/beschaeftigte/chylik|Jan Chylík]]
+{{ :difprofiles_tke_b.png?500 | The differences in TKE in model runs with different concentration of ice particles. }}
+==== The role of humidity inversions in the Arctic climate system  ====
+Humidity inversion describes the situation where the specific humidity in some layer of air is increasing with altitude instead of decreasing. Humidity inversion atop a cloudy boundary layer are relatively common [[arcticclouds|in the Arctic]]. The entrainment at the top of the top of the cloud layer then often leads to transport of humidity from the free atmosphere into the boundary layer. This can then effect both the precipitation from the clouds and the thermodynamic properties of the clouds.
+Does the presence of humidity inversion lead to warming of cooling of the cloud layer? And does it lead to increase the turbulence in the boundary layer? These questions will be investigated with both conceptual mixed-layer model and large eddy simulation. If you are interested in this topic please contact [[https://geomet.uni-koeln.de/institut/beschaeftigte/chylik|Jan Chylík]]