Boundary Layer Height and Entrainment Zone Thickness Measured by Lidars and Wind-Profiling Radars

Cohn, Stephen A.; Angevine, W. M.

doi:10.1175/1520-0450(2000)039<1233:blhaez>2.0.co;2

Cited by 265 publications

(221 citation statements)

References 23 publications

Supporting

Mentioning

193

Contrasting

Unclassified

Order By: Relevance

“…We did not make an attempt to determine the resulting bias, as this becomes only important if detailed comparisons with profiles of similarity relationships or LES are performed, which was not the subject of this work. Nevertheless, in order to measure z i (t), we applied the Haar wavelet analysis introduced in Davis et al (2000), which was also used in Cohn and Angevine (2000) and in Wulfmeyer and Janjić (2005). Details of Figure 5 depicts the 12-h observation of mixing ratio, with temporal and spatial resolutions of δt = 10 s and δz = 75 m, respectively.…”

Section: Determination Of Boundary-layer Structure and Depthmentioning

confidence: 99%

“…This difference was mainly driven by the slightly different locations of the maximum values in the gradients of A and m and not by the sampling errors, since the sampling errors only occurred in the relatively few cloudy profiles (resulting in an underestimation when using ASR). As the determination of CBL depth with the ASR gradient is a well-established technique and has demonstrated good accuracy when compared to other methods (Cohn and Angevine 2000;Pal et al 2010), we appliedz i,AS R for CBL scaling.…”

Section: Evolution Of the Mixing-ratio Field During The Observation Pmentioning

confidence: 99%

See 1 more Smart Citation

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Wulfmeyer

Pal

Turner

et al. 2010

Boundary-Layer Meteorol

111

View full text Add to dashboard Cite

High-resolution water vapour measurements made by the Atmospheric Radiation Measurement (ARM) Raman lidar operated at the Southern Great Plains Climate Research Facility site near Lamont, Oklahoma, U.S.A. are presented. Using a 2-h measurement period for the convective boundary layer (CBL) on 13 September 2005, with temporal and spatial resolutions of 10 s and 75 m, respectively, spectral and autocovariance analyses of water vapour mixing ratio time series are performed. It is demonstrated that the major part of the inertial subrange was detected and that the integral scale was significantly larger than the time resolution. Consequently, the major part of the turbulent fluctuations was resolved. Different methods to retrieve noise error profiles yield consistent results and compare well with noise profiles estimated using Poisson statistics of the Raman lidar signals. Integral scale, mixing-ratio variance, skewness, and kurtosis profiles were determined including error bars with respect to statistical and sampling errors. The integral scale ranges between 70 and 130 s at the top of the CBL. Within the CBL, up to the third order, noise errors are significantly smaller than sampling errors and the absolute values of turbulent variables, respectively. The mixing-ratio variance profile rises monotonically from ≈0.07 to ≈3.7 g 2 kg −2 in the entrainment zone. The skewness is nearly zero up to 0.6 z/z i , becomes −1 around 0.7-0.8 z/z i , crosses zero at about 0.95 z/z i , and reaches about 1.7 at 1.1 z/z i (here, z is the height and z i is the CBL depth). The noise errors are too large to derive fourth-order moments with sufficient accuracy. Consequently, to the best of our knowledge, the ARM Raman lidar is the first water vapour Raman lidar with demonstrated capability to retrieve profiles of turbulent variables up to the third order during daytime throughout the atmospheric CBL.

show abstract

Section: Determination Of Boundary-layer Structure and Depthmentioning

confidence: 99%

Section: Evolution Of the Mixing-ratio Field During The Observation Pmentioning

confidence: 99%

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Wulfmeyer

Pal

Turner

et al. 2010

Boundary-Layer Meteorol

111

View full text Add to dashboard Cite

show abstract

“…Many field experiments have demonstrated the feasibility of remote sensing instruments such as radar wind profilers, lidars, and ground-based microwave radiometers to directly and continuously detect the PBL height (Flamant et al 1997;Westwater et al 1999;Cohn and Angevine 2000). These experiments occurred mainly over forests, canyons, suburban areas, and over the ocean.…”

Section: Introductionmentioning

confidence: 99%

Estimate of Boundary-Layer Depth Over Beijing, China, Using Doppler Lidar Data During SURF-2015

Huang

Gao

Miao

et al. 2016

Boundary-Layer Meteorol

View full text Add to dashboard Cite

Planetary boundary-layer (PBL) structure was investigated using observations from a Doppler lidar and the 325-m Institute of Atmospheric Physics (IAP) meteorological tower in the centre of Beijing during the summer 2015 Study of Urban-impacts on Rainfall and Fog/haze (SURF-2015) field campaign. Using six fair-weather days of lidar and tower data under clear to cloudy skies, we evaluate the ability of the Doppler lidar to probe the urban boundary-layer structure, and then propose a composite method for estimating the diurnal cycle of the PBL depth using the Doppler lidar. For the convective boundary layer (CBL), a threshold method using vertical velocity variance (σ 2 w > 0.1 m 2 s −2 ) is used, since it provides more reliable CBL depths than a conventional maximum wind-shear method. The nocturnal boundary-layer (NBL) depth is defined as the height at which σ 2 w decreases to 10 % of its near-surface maximum minus a background variance. The PBL depths determined by combining these methods have average values ranging from ≈270 to ≈1500 m for the six days, with the greatest maximum depths associated with clear skies. Release of stored and anthropogenic heat contributes to the maintenance of turbulence until late evening, keeping the NBL near-neutral and deeper at night than would be expected over a natural surface. The NBL typically becomes more shallow with time, but grows in the presence of low-level nocturnal jets. While current results are promising, data over a broader range of conditions are needed to fully develop our PBL-depth algorithms.

show abstract

“…It is recognized that these approaches are sensitive to noise and smallscale structure in the lidar profiles. A robust algorithm based on CWT (Covariance Wavelet Transform) is proposed by [6,7]. The method can recognize the ABL height in profiles with lower signal to noise ratio than other algorithms.…”

Section: Introductionmentioning

confidence: 99%

Atmospheric Boundary Layer Height Evolution with Lidar in Buenos Aires from 2008 to 2011

Pawelko

Salvador

Ristori

et al. 2016

EPJ Web of Conferences

View full text Add to dashboard Cite

The analysis of the atmospheric boundary layer top height evolution is obtained from 2008 to 2011 in Buenos Aires using the multiwavelength lidar located at CEILAP (CITEDEF-CONICET) (34°33' S; 58°30' W; 17 m asl). Algorithms recognition based on covariance wavelet transform are applied to obtain seasonal statistics. This method is being evaluated for use in the Lidar Network in Argentina and it is being deployed in Patagonia region currently. The technique operates in real time in both low and high aerosol loads and with almost no human supervision.

show abstract

Boundary Layer Height and Entrainment Zone Thickness Measured by Lidars and Wind-Profiling Radars

Cited by 265 publications

References 23 publications

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Estimate of Boundary-Layer Depth Over Beijing, China, Using Doppler Lidar Data During SURF-2015

Atmospheric Boundary Layer Height Evolution with Lidar in Buenos Aires from 2008 to 2011

Contact Info

Product

Resources

About