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Space–time structure of mesoscale motions in the stable boundary layer
Author(s) -
Mahrt L.,
Thomas C. K.,
Prueger J. H.
Publication year - 2008
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.348
Subject(s) - mesoscale meteorology , boundary layer , coherence (philosophical gambling strategy) , planetary boundary layer , scale (ratio) , wind speed , turbulence , flow (mathematics) , meteorology , geology , grid , temporal scales , mechanics , physics , geodesy , mathematics , statistics , ecology , quantum mechanics , biology
In this article, we examine the stochastic characteristics of non‐turbulent motions in the stable boundary layer. The behaviour of mesoscale motions in the atmospheric stable boundary layer is poorly understood beyond case studies of unusually well‐defined events or monotonic waves. Eight networks of wind observations are analysed in order to examine stochastically the space–time characteristics of such motions in the stable boundary layer. The networks include a variety of surface conditions and network configurations, although none of the networks is optimal for our studies. Collectively, the networks allow examination of scales from tens of metres to tens of kilometres. A variety of analysis tools reveal the complexity of mesoscale motions near the surface in stratified flow. For the data as a whole, the horizontal scale of coherence increases systematically with time‐scale, albeit with large scatter between records. The relationship between spatial coherence and time‐scale is posed in terms of a velocity scale, which is found to be unrelated to the wind speed. The time variability of the flow decreases systematically with increasing spatial averaging, suggesting that comparison of model winds (with implied spatial averaging over the grid area) with observations requires suitable spatial averaging of the observations. Additional characteristics are discussed in terms of non‐dimensional ratios of velocity scales. Necessary improvements of network measurements are also noted. Copyright © 2008 Royal Meteorological Society