Stable boundary layer height on a gentle slope

2020 ◽  
Author(s):  
Ivana Stiperski ◽  
Albert A.M. Holtslag ◽  
Manuela Lehner ◽  
C. David Whiteman
Keyword(s):  
Boundary Layer ◽  
Stable Boundary Layer ◽  
Maximum Height ◽  
Free Atmosphere ◽  
Near Surface ◽  
Stable Boundary ◽  
Boundary Layer Height ◽  
Flat Terrain ◽  
Katabatic Flows ◽  
The Difference

<p>Height of the stable boundary layer (SBL) presents an important diagnostic used to describe the relevant processes governing the evolution and characteristics of SBL, and the extent to which the surface is communicating with the free atmosphere.  Here we investigate the SBL height over a gentle (1°) mesoscale slope on which relatively deep mid-latitude katabatic flows (with jet maxima between 20 and 50 m) develop during clear nights. We show that detecting the SBL top depends on the method used (Richardson number, flux- and anisotropy-profiles). The detected SBL depth, mostly deviates from the jet maximum height or the top of the near-surface inversion. The flat terrain formulations for the SBL height correlate well with the detected top of the SBL if instead of background stratification, near-surface stratification is used in their formulations, however, they mostly largely overestimate the SBL height. The difference to flat-terrain SBL is also shown through the dependence of size of the dominant eddy with height. In katabatic flows the eddy size is semi-constant with height throughout the SBL, whereas in flat terrain eddy size varies significantly with height.</p>

scholarly journals Thermal Submeso Motions in the Nocturnal Stable Boundary Layer. Part 2: Generating Mechanisms and Implications

2021 ◽  
Author(s):  
Lena Pfister ◽  
Karl Lapo ◽  
Larry Mahrt ◽  
Christoph K. Thomas
Keyword(s):  
Boundary Layer ◽  
Stable Boundary Layer ◽  
Side Wall ◽  
Cold Pool ◽  
Continuous Data ◽  
Valley Bottom ◽  
Near Surface ◽  
Cold Air ◽  
Stable Boundary ◽  
Surface Temperatures

AbstractIn the stable boundary layer, thermal submesofronts (TSFs) are detected during the Shallow Cold Pool experiment in the Colorado plains, Colorado, USA in 2012. The topography induces TSFs by forming two different air layers converging on the valley-side wall while being stacked vertically above the valley bottom. The warm-air layer is mechanically generated by lee turbulence that consistently elevates near-surface temperatures, while the cold-air layer is thermodynamically driven by radiative cooling and the corresponding cold-air drainage decreases near-surface temperatures. The semi-stationary TSFs can only be detected, tracked, and investigated in detail when using fibre-optic distributed sensing (FODS), as point observations miss TSFs most of the time. Neither the occurrence of TSFs nor the characteristics of each air layer are connected to a specific wind or thermal regime. However, each air layer is characterized by a specific relationship between the wind speed and the friction velocity. Accordingly, a single threshold separating different flow regimes within the boundary layer is an oversimplification, especially during the occurrence of TSFs. No local forcings or their combination could predict the occurrence of TSFs except that they are less likely to occur during stronger near-surface or synoptic-scale flow. While classical conceptualizations and techniques of the boundary layer fail in describing the formation of TSFs, the use of spatially continuous data obtained from FODS provide new insights. Future studies need to incorporate spatially continuous data in the horizontal and vertical planes, in addition to classic sensor networks of sonic anemometry and thermohygrometers to fully characterize and describe boundary-layer phenomena.

On stable boundary-layer height estimation using backscatter lidar data and variance processing

2021 ◽  
Author(s):  
Marcos Paulo Araujo da Silva ◽  
Constantino Muñoz-Porcar ◽  
Umar Saeed ◽  
Francesc Rey ◽  
Maria Teresa Pay ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Stable Boundary Layer ◽  
Adaptive Estimation ◽  
Microwave Radiometer ◽  
Minimum Variance ◽  
Initial Guess ◽  
Layer Height ◽  
Stable Boundary ◽  
Boundary Layer Height ◽  
Temporal Variance

<p>This study describes a method to estimate the nocturnal stable boundary layer height (SBLH) by means of lidar observations. The method permits two approaches which yield independent retrievals through either spatial or temporal variance vertical profiles of the attenuated backscatter. Then, the minimum variance region (MVR) on this profile is identified. Eventually, when multiple MVRs are detected, a temperature-based SBLH estimation derived from radiosonde, launched within the searching time, is used to disambiguate the initial guess. In order to test the method, two study cases employing lidar-ceilometer (Jenoptik CHM 15k Nimbus) measurements are investigated. Temperature-based estimates from a collocated microwave radiometer permitted validation, using either temporal or spatial backscatter variances. The dataset was collected during the HD(CP)2 Observational Prototype Experiment (HOPE) [1].   </p><p>[1] U. Saeed, F. Rocadenbosch, and S. Crewell, “Adaptive Estimation of the Stable Boundary Layer Height Using Combined Lidar and Microwave Radiometer Observations,” IEEE Trans. Geosci. Remote Sens., 54(12), 6895–6906 (2016), DOI: 10.1109/TGRS.2016.2586298.</p><p>[2] U. Löhnert, J. H. Schween, C. Acquistapace, K. Ebell, M. Maahn, M. Barrera-Verdejo, A. Hirsikko, B. Bohn, A. Knaps, E. O’Connor, C. Simmer, A. Wahner, and S. Crewell, “JOYCE: Jülich Observatory for Cloud Evolution,” Bulletin of the American Meteorological Society, 96(7), 1157-1174 (2015). DOI: 10.1175/BAMS-D-14-00105.1</p>

scholarly journals Local Characteristics of the Nocturnal Boundary Layer in Response to External Pressure Forcing

2017 ◽  
Vol 56 (11) ◽  
pp. 3035-3047 ◽  
Author(s):  
Steven J. A. van der Linden ◽  
Peter Baas ◽  
J. Antoon van Hooft ◽  
Ivo G. S. van Hooijdonk ◽  
Fred C. Bosveld ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Stable Boundary Layer ◽  
Dynamical Behavior ◽  
Geostrophic Wind ◽  
External Pressure ◽  
Near Surface ◽  
Stable Boundary ◽  
Wind Speeds ◽  
Turbulent Characteristics

AbstractGeostrophic wind speed data, derived from pressure observations, are used in combination with tower measurements to investigate the nocturnal stable boundary layer at Cabauw, the Netherlands. Since the geostrophic wind speed is not directly influenced by local nocturnal stability, it may be regarded as an external forcing parameter of the nocturnal stable boundary layer. This is in contrast to local parameters such as in situ wind speed, the Monin–Obukhov stability parameter (z/L), or the local Richardson number. To characterize the stable boundary layer, ensemble averages of clear-sky nights with similar geostrophic wind speeds are formed. In this manner, the mean dynamical behavior of near-surface turbulent characteristics and composite profiles of wind and temperature are systematically investigated. The classification is found to result in a gradual ordering of the diagnosed variables in terms of the geostrophic wind speed. In an ensemble sense the transition from the weakly stable to very stable boundary layer is more gradual than expected. Interestingly, for very weak geostrophic winds, turbulent activity is found to be negligibly small while the resulting boundary cooling stays finite. Realistic numerical simulations for those cases should therefore have a comprehensive description of other thermodynamic processes such as soil heat conduction and radiative transfer.

scholarly journals Submeso Motions within the Stable Boundary Layer and Their Relationships to Local Indicators and Synoptic Regime in Moderately Complex Terrain

2015 ◽  
Vol 54 (2) ◽  
pp. 352-369 ◽  
Author(s):  
Joshua D. Hoover ◽  
David R. Stauffer ◽  
Scott J. Richardson ◽  
Larry Mahrt ◽  
Brian J. Gaudet ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Complex Terrain ◽  
Stable Boundary Layer ◽  
Flow Direction ◽  
Reanalysis Data ◽  
Near Surface ◽  
Stable Boundary ◽  
Synoptic Conditions ◽  
Allegheny Mountains ◽  
Submeso Motions

AbstractTo better understand the physical processes of the stable boundary layer and to quantify “submeso motions” in moderately complex terrain, exploratory case-study analyses were performed using observational field data supplemented by gridded North American Regional Reanalysis data and Pennsylvania State University real-time Weather Research and Forecasting Model output. Submeso motions are nominally defined as all motions between the largest turbulent scales and the smallest mesoscales. Seven nighttime cases from August and September of 2011 are chosen from a central Pennsylvania [“Rock Springs” (RS)] network of eight ground-based towers and two sound detection and ranging (sodar) systems . The observation network is located near Tussey Ridge, ~15 km southeast of the Allegheny Mountains. The seven cases are classified by the dominant synoptic-flow direction and proximity to terrain to assess the influence of synoptic conditions on the local submeso and mesogamma motions. It is found that synoptic winds with a large crossing angle over nearby Tussey Ridge can generate mesogamma wave motions and larger-magnitude submeso temperature and wind fluctuations in the RS network than do winds from the direction of the more distant Allegheny Mountains. Cases with synoptic winds that are nearly parallel to the topographic contours or are generally weak exhibit the smallest fluctuations. Changes in the magnitude of near-surface submeso temperature and wind fluctuations in response to local indicator variables are also analyzed. The observed submeso wind and temperature fluctuations are generally larger when the low-level wind speed and thermal stratification, respectively, are greater, but the synoptic flow and its relation to the terrain also play an important role.

Near-Surface Vertical Flux Divergence in the Stable Boundary Layer

2018 ◽  
Vol 169 (3) ◽  
pp. 373-393 ◽  
Author(s):  
L. Mahrt ◽  
Christoph K. Thomas ◽  
Andrey A. Grachev ◽  
P. Ola G. Persson
Keyword(s):  
Boundary Layer ◽  
Stable Boundary Layer ◽  
Vertical Flux ◽  
Flux Divergence ◽  
Near Surface ◽  
Stable Boundary
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