Changes between Version 6 and Version 7 of doc/tec/microphysics


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Timestamp:
May 31, 2016 7:48:27 PM (8 years ago)
Author:
Giersch
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  • doc/tec/microphysics

    v6 v7  
    7070== Diffusional growth of cloud water ==
    7171
     72The diagnostic estimation of ''q'',,c,, is based on the assumption that water supersaturations are immediately removed by the diffusional growth of cloud droplets only. This can be justified since the bulk surface area of cloud droplets exceeds that of rain drops considerably ([#stevens2008 Stevens and Seifert, 2008]). Following this saturation adjustment approach, ''q'',,c,, is obtained by
     73{{{
     74#!Latex
     75\begin{align*}
     76  & q_\mathrm{c}=\max{\left(0, q - q_\mathrm{r} - q_\mathrm{s}
     77    \right)},
     78\end{align*}
     79}}}
     80where ''q'',,s,, is the saturation specific humidity. Because ''q'',,s,, is a function of ''T'' (not predicted), ''q'',,s,, is computed from the liquid water temperature ''T'',,l,, = ''Π θ,,l,, in a first step:
     81{{{
     82#!Latex
     83\begin{align*}
     84 q_\mathrm{s}(T_\mathrm{l}) = \frac{R_\mathrm{d}}{R_\mathrm{v}}
     85 \frac{p_\text{v, s}(T_\mathrm{l})}{p-\left(1-R_\mathrm{d}/R_\mathrm{v}\right)\,p_\text{v, s}(T_\mathrm{l})},
     86\end{align*}
     87}}}
     88using an empirical relationship for the saturation water vapor pressure ''p'',,v,s,, ([#bougeault1981 Bougeault, 1981]):
     89{{{
     90#!Latex
     91\begin{align*}
     92  & p_\text{v, s}(T_\mathrm{l}) = 610.78 \text{Pa} \cdot
     93  \exp{\left(17.269\,\frac{T_\mathrm{l}-273.16\,\text{K}}{T_\mathrm{l}-35.86\,\text{K}}
     94    \right)}.
     95\end{align*}
     96}}}
     97''q'',,s,,(''T'') is subsequently calculated from a 1st-order Taylor series expansion of ''q'',,s,, at ''T'',,l,, ([#sommeria1977 Sommeria and Deardorff, 1977]):
     98{{{
     99#!Latex
     100\begin{align*}
     101  & q_\mathrm{s}(T)=q_\mathrm{s}(T_\mathrm{l})\frac{1+\beta\,q}{1+
     102    \beta\,q_\mathrm{s}(T_\mathrm{l})},
     103\end{align*}
     104}}}
     105with
     106{{{
     107#!Latex
     108\begin{align*}
     109  & \beta = \frac{L_\mathrm{v}^2}{R_\mathrm{v} c_p
     110    T_\mathrm{l}^2}.
     111\end{align*}
     112}}}
     113
    72114== Autoconversion ==
    73115
     
    96138* [=#heus2010]'''Heus T, van Heerwaarden CC, Jonker HJJ, Pier Siebesma A, Axelsen S, van den Dries K, Geoffroy O, Moene AF, Pino D, de Roode SR, Vilà-Guerau de Arellano J.''' 2010. Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and overview of its applications. Geosci. Model Dev. 3: 415–444. [http://dx.doi.org/10.5194/gmd-3-415-2010 doi]
    97139
     140* [=#stevens2008]'''Stevens B, Seifert A.''' 2008. Understanding macrophysical outcomes of microphysical choices in simulations of shallow cumulus convection. J. Meteor. Soc. Jpn. 86: 143–162.
     141
     142* [=#bougeault1981]'''Bougeault, P.''' 1981. Modeling the trade-wind cumulus boundary layer. Part I: Testing the ensemble cloud relations against numerical data. J. Atmos. Sci. 38: 2414–2428.
     143
     144* [=#sommeria1977]'''Sommeria G, Deardorff JW.''' 1977. Subgrid-scale condensation in models of nonprecipitating clouds. J. Atmos. Sci. 34: 344–355.