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--- greyzone [2021/09/24 09:28] – neggers
+++ greyzone [2021/09/24 12:23] (current) – neggers
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-====== Greyzone ======
+====== Convective Grey Zone ======
-==== Scale-aware and scale-adaptive parameterization ====
 {{:greyzone.png?300|}}
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 One of the main goals of the InScAPE research group is to develop scale-adaptive schemes for moist convective transport and clouds in the boundary layer for use in next-generation circulation models. Topics of interest include the size statistics of cumulus cloud populations, cloud macrophysics and microphysics, and convective and diffusive transport in the boundary layer. Various ways of parameterizing these phenomena are explored, including PDF modeling and multi-plume modeling. We strive to integrate and unite the representation of many subgrid-scale processes into one internally consistent framework, that is generally applicable at a broad range of resolutions and that is well-constrained by relevant measurements.
-More information in these papers:
+Related papers:
+  * Exploring a size-filtered mass flux scheme [[https://doi.org/10.1175/JAS-D-17-0231.1|Brast et al (2018)]]
-[[https://doi.org/10.1175/JAS-D-17-0231.1|Brast et al (2018)]]
+  * Powerlaw scaling in subsampled cumulus cloud populations [[https://doi.org/10.1175/JAS-D-18-0194.1|Neggers 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)]]
-[[https://doi.org/10.1175/JAS-D-18-0194.1|Neggers et al (2019)]]
+  *  A binomial stochastic framework for efficiently modeling discrete statistics of convective populations [[https://doi.org/10.1029/2020MS002229|Neggers and Griewank (2021)]]