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Stable Boundary Layer Depth from High-Resolution Measurements of the Mean Wind Profile

Stable Boundary Layer Depth from High-Resolution Measurements of the Mean Wind Profile The depth h of the stable boundary layer (SBL) has long been an elusive measurement. In this diagnostic study the use of high-quality, high-resolution (Δ z = 10 m) vertical profile data of the mean wind U ( z ) and streamwise variance σ u 2 ( z ) is investigated to see whether mean-profile features alone can be equated with h . Three mean-profile diagnostics are identified: h J , the height of maximum low-level-jet (LLJ) wind speed U in the SBL; h 1 , the height of the first zero crossing or minimum absolute value of the magnitude of the shear ∂ U /∂ z profile above the surface; and h 2 , the minimum in the curvature ∂ 2 U /∂ z 2 profile. Boundary layer BL here is defined as the surface-based layer of significant turbulence, so the top of the BL was determined as the first significant minimum in the σ u 2 ( z ) profile, designated as h σ . The height h σ was taken as a reference against which the three mean-profile diagnostics were tested. Mean-wind profiles smooth enough to calculate second derivatives were obtained by averaging high-resolution Doppler lidar profile data, taken during two nighttime field programs in the Great Plains, over 10-min intervals. Nights are chosen for study when the maximum wind speed in the lowest 200 m exceeded 5 m s −1 (i.e., weak-wind, very stable BLs were excluded). To evaluate the three diagnostics, data from the 14-night sample were divided into three profile shapes: Type I, a traditional LLJ structure with a distinct maximum or “nose,” Type II, a “flat” structure with constant wind speed over a significant depth, and Type III, having a layered structure to the shear and turbulence in the lower levels. For Type I profiles, the height of the jet nose h J , which coincided with h 1 and h 2 in this case, agreed with the reference SBL depth to within 5%. The study had two major results: 1) among the mean-profile diagnostics for h , the curvature depth h 2 gave the best results; for the entire sample, h 2 agreed with h σ to within 12%; 2) considering the profile shapes, the layered Type III profiles gave the most problems. When these profiles could be identified and eliminated from the sample, regression and error statistics improved significantly: mean relative errors of 8% for h J and h 1 , and errors of <5% for h 2 , were found for the sample of only Type I and II profiles. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Meteorology and Climatology American Meteorological Society

Stable Boundary Layer Depth from High-Resolution Measurements of the Mean Wind Profile

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References (33)

Publisher
American Meteorological Society
Copyright
Copyright © 2008 American Meteorological Society
ISSN
1558-8432
DOI
10.1175/2009JAMC2168.1
Publisher site
See Article on Publisher Site

Abstract

The depth h of the stable boundary layer (SBL) has long been an elusive measurement. In this diagnostic study the use of high-quality, high-resolution (Δ z = 10 m) vertical profile data of the mean wind U ( z ) and streamwise variance σ u 2 ( z ) is investigated to see whether mean-profile features alone can be equated with h . Three mean-profile diagnostics are identified: h J , the height of maximum low-level-jet (LLJ) wind speed U in the SBL; h 1 , the height of the first zero crossing or minimum absolute value of the magnitude of the shear ∂ U /∂ z profile above the surface; and h 2 , the minimum in the curvature ∂ 2 U /∂ z 2 profile. Boundary layer BL here is defined as the surface-based layer of significant turbulence, so the top of the BL was determined as the first significant minimum in the σ u 2 ( z ) profile, designated as h σ . The height h σ was taken as a reference against which the three mean-profile diagnostics were tested. Mean-wind profiles smooth enough to calculate second derivatives were obtained by averaging high-resolution Doppler lidar profile data, taken during two nighttime field programs in the Great Plains, over 10-min intervals. Nights are chosen for study when the maximum wind speed in the lowest 200 m exceeded 5 m s −1 (i.e., weak-wind, very stable BLs were excluded). To evaluate the three diagnostics, data from the 14-night sample were divided into three profile shapes: Type I, a traditional LLJ structure with a distinct maximum or “nose,” Type II, a “flat” structure with constant wind speed over a significant depth, and Type III, having a layered structure to the shear and turbulence in the lower levels. For Type I profiles, the height of the jet nose h J , which coincided with h 1 and h 2 in this case, agreed with the reference SBL depth to within 5%. The study had two major results: 1) among the mean-profile diagnostics for h , the curvature depth h 2 gave the best results; for the entire sample, h 2 agreed with h σ to within 12%; 2) considering the profile shapes, the layered Type III profiles gave the most problems. When these profiles could be identified and eliminated from the sample, regression and error statistics improved significantly: mean relative errors of 8% for h J and h 1 , and errors of <5% for h 2 , were found for the sample of only Type I and II profiles.

Journal

Journal of Applied Meteorology and Climatology – American Meteorological Society

Published: Dec 9, 2008

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