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A two‐dimensional Lagrangian stochastic dispersion model for daytime conditions
Author(s) -
Rotach Mathias W.,
Gryning SvenErik,
Tassone Caterina
Publication year - 1996
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.49712253004
Subject(s) - probability density function , stability (learning theory) , plume , convection , dispersion (optics) , lagrangian , function (biology) , gaussian , statistical physics , daytime , constant (computer programming) , physics , mathematics , mechanics , meteorology , mathematical analysis , atmospheric sciences , statistics , optics , quantum mechanics , computer science , machine learning , evolutionary biology , biology , programming language
A two‐dimensional ( x, z ) Lagrangian stochastic dispersion model is presented that is correct (i.e. fulfils the well‐mixed condition) for neutral to convective conditions. The probability density function (pdf) of the particle velocities is constructed as a weighted sum of a neutral pdf ( u and w jointly Gaussian) and a convective pdf ( w skewed, u and w uncorrelated). The transition function ℱ varies continuously with stability and therefore ensures that the model results are not confined to a finite number of stability classes. The model is described in full detail and some sensitivity tests are presented. In particular, the role of C o , the universal constant in the Lagrangian structure function for the inertial subrange, in determining average plume characteristics is discussed. Furthermore, the evolution of average plume‐height and ‐width is investigated for different boundary‐layer stabilities ranging from ideally neutral to fully convective. Finally, the model is applied to the situation of a tracer experiment in Copenhagen, and it is shown that the measured surface‐concentrations can be well simulated.