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sizedistribution [2021/04/27 21:05] – neggerssizedistribution [2022/09/14 16:42] (current) – [3D cloud reconstructions using stereo cameras] burchart
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 ==== 3D cloud reconstructions using stereo cameras ==== ==== 3D cloud reconstructions using stereo cameras ====
  
-<stereo camera description here>+{{:movie_joyce_tsi_dales_20140724-hr014_rs256_20s.mp4?&300|Time lapse movie of simulated cumulus clouds on 24 July 2014 at the JOYCE site. The ray tracing renderings are generated using the open-source Blender tool. A hemispheric projection is used, allowing comparison to Total Sky Imager (TSI) data.}} 
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 +The SOCLES project (Stereo Observations of Clouds for LES Validation and Sub-scale Cloud Parameterizations) combines high-frequency cloud observations by multiple hemispheric cameras with high-resolution Large-Eddy Simulations (LES) at the [[https://atmos.meteo.uni-koeln.de/ag_crewell/doku.php?id=sites:joyce|JOYCE]] meteorological site. The main science objective is to better understand and quantify the fine-scale spatial and temporal structures of shallow cumulus cloud populations. These transient cloud fields are highly heterogeneous, a behavior that has complicated their representation in numerical weather prediction and climate models for decades.  
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 +SOCLES aims to fill a critical data gap concerning cumulus cloud geometry with new tools and methods, thus creating new opportunities for making progress. The high-resolution sampling capability of stereo reconstruction in four dimensions, combined with its considerable spatial coverage, allows capturing cumulus cloud populations in unprecedented detail. The LES realizations supplement this observational data, used as a virtual laboratory for gaining insight and for testing measurement strategies. Assessing the realism of the LES is of key importance, involving the determination of the resolution at which simulated cloud irregularity starts to match the stereo camera observations. For this purpose, the open source [[http://blender.org|Blender]] tool and its path-tracing engine are used to generate realistic renderings of three-dimensional cloud fields from LES, including optical effects such as absorption, scattering, sun glare, and haze effects. Among others, hemispheric projections are used as a camera instrument simulator for LES, exactly mimicking the way visual instruments like Total Sky Imagers (TSI) view the world. This allows a fair comparison between models and measurements. An example hemispheric Blender movie of simulated clouds over JOYCE is shown on the right. 
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 +SOCLES is an ongoing joint effort by scientists at the University of Bonn and the University of Cologne, supported by DFG: https://gepris.dfg.de/gepris/projekt/430226822 
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 ==== Size statistics of shallow cumulus ==== ==== Size statistics of shallow cumulus ====
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 In a recent study by [[https://doi.org/10.1175/JAS-D-18-0084.1|Van Laar et al (2019)]], a total of 146 Scu days are simulated using [[models#dales|DALES]], which provides a broad parameter space and the possibility to compute cloud size statistics. Some first results show that the shape of the cloud size distribution greatly depends on the cloud fraction and the same is the case for the maximum cloud size in the domain (Fig. 1). Previous research points to a correlation between cloud size and spacing, this is the next thing that will be investigated.  In a recent study by [[https://doi.org/10.1175/JAS-D-18-0084.1|Van Laar et al (2019)]], a total of 146 Scu days are simulated using [[models#dales|DALES]], which provides a broad parameter space and the possibility to compute cloud size statistics. Some first results show that the shape of the cloud size distribution greatly depends on the cloud fraction and the same is the case for the maximum cloud size in the domain (Fig. 1). Previous research points to a correlation between cloud size and spacing, this is the next thing that will be investigated. 
  
-{{:csd-2.png?200|}}+{{:csd-2.png?300|}}
  
 //Figure 1 – Cloud size distributions for five different days with all a different cloud fraction. The distribution is described by a power law–exponential function.//  //Figure 1 – Cloud size distributions for five different days with all a different cloud fraction. The distribution is described by a power law–exponential function.// 
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 //Figure 3 – Cloud size distributions derived from MODIS (left) and ICON-LEM (right)//  //Figure 3 – Cloud size distributions derived from MODIS (left) and ICON-LEM (right)// 
  
-{{ ::nns_fit_short-crop.png?direct&600 |}}+{{ ::nns_fit_short-crop.png?direct&300 |}}
  
-//Figure 4 – Logarithmic and exponential dependence on cloud size in spacing between clouds of any size (top) and clouds of equal size (bottom)// +//Figure 4 – Logarithmic and exponential dependence on cloud size in the Nearest Neighbor Spacing (NNS) between clouds of any size (top) and clouds of equal size (bottom)// 
  
  
sizedistribution.1619550347.txt.gz · Last modified: 2021/04/27 21:05 by neggers