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--- cloudscheme [2017/11/07 14:13] – griewank
+++ cloudscheme [2022/09/14 16:24] (current) – ibartolo
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 Our research into cloud schemes focuses on how to represent clouds and cloud processes in numerical models which do not have sufficient resolution to resolve clouds. As both weather forecast or climate models fall into this category this research has high societal and academic relevance.
-There are many possible way to parametrize clouds, but the approach we focus on is called a PDF scheme. PDF stands for probability density function, and the scheme receives it's name from the analytical PDF it uses to describe the distribution of total water in each model cell. The scheme we use is derived from the scheme Adrian Tompkins presented in his 2002 paper "A Prognostic Parameterization for the Subgrid-Scale Variability of Water Vapor and
+There are many possible way to parametrize clouds, but the approach we focus on is called a PDF scheme. PDF stands for probability density function, and the scheme receives its name from the analytical PDF it uses to describe the distribution of total water in each model cell. The scheme we use is derived from the scheme Adrian Tompkins presented in his 2002 paper "A Prognostic Parameterization for the Subgrid-Scale Variability of Water Vapor and
 Clouds in Large-Scale Models and Its Use to Diagnose Cloud Cover" which Vera Schemann revised and extended in her 2014 PhD Thesis "Towards a scale aware cloud process parametrization for global climate models".
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 Here is an example of the total water histogram of a 55x55 km subdomain of the LES Simulation containing over 125000 grid cells. Overlaid are two PDFs from our scheme with slightly differing assumptions, as well as the resulting cloud fractions and how much they overlap with the histogram.
-With these tools we can now quantify many aspects of cloud parametrizations which were previously not measurable. Such aspects include how parametrization performance changes with model resolution, and breaking down the various error sources. For more information get in contact with [[http://www.geomet.uni-koeln.de/das-institut/mitarbeiter/griewank/|Philipp Griewank]] or [[http://www.geomet.uni-koeln.de/das-institut/mitarbeiter/schemann/|Vera Schemann]].
+With these tools we can now quantify many aspects of cloud parametrizations which were previously not measurable. Such aspects include how parametrization performance changes with model resolution, and breaking down the various error sources.
+Related publication: Griewank et al, 2018: https://doi.org/10.1029/2018MS001421