Convective Boundary-Layer Entrainment: Short Review and Progress using Doppler Lidar

Träumner, K.; Kottmeier, C.; Corsmeier, U.; Wieser, Andreas

doi:10.1007/s10546-011-9657-6

Cited by 64 publications

(56 citation statements)

References 73 publications

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“…Technically, a higher data rate of 10 Hz would be possible, but a temporal resolution of 1 Hz is considered the optimal setting for the vertical stare mode, as it ensures higher signal-to-noise ratios by longer averaging. The effective range-gate resolution is about 60 m (Träumner et al, 2011). The measurements are mainly restricted to the cloud-free atmosphere, because the radiation emitted by the lidar is attenuated within clouds.…”

Section: Doppler Lidars At Three Sitesmentioning

confidence: 99%

“…As in Träumner et al (2011), the variances were corrected for uncorrelated random noise using a technique proposed by Lenschow et al (2000). Additionally, the statistical error was considered as described by Lenschow et al (1994).…”

Section: Errors Considered For Variance Calculationsmentioning

confidence: 99%

“…Tucker et al (2009) systematically investigated the determination of the z i using variance profiles and found that a threshold value to which the variance decreases was the best objective criterion. Träumner et al (2011) determined this threshold value for the HYB for several field campaigns and found that a value of 0.16 m 2 s −2 gave the best results.…”

Section: Scales and Scaling Parametersmentioning

confidence: 99%

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Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain

et al. 2016

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Abstract. In the spring of 2013, extensive measurements with multiple Doppler lidar systems were performed. The instruments were arranged in a triangle with edge lengths of about 3 km in a moderately flat, agriculturally used terrain in northwestern Germany. For 6 mostly cloud-free convective days, vertical velocity variance profiles were calculated. Weighted-averaged surface fluxes proved to be more appropriate than data from individual sites for scaling the variance profiles; but even then, the scatter of profiles was mostly larger than the statistical error. The scatter could not be explained by mean wind speed or stability, whereas time periods with significantly increased variance contained broader thermals. Periods with an elevated maximum of the variance profiles could also be related to broad thermals. Moreover, statistically significant spatial differences of variance were found. They were not influenced by the existing surface heterogeneity. Instead, thermals were preserved between two sites when the travel time was shorter than the large-eddy turnover time. At the same time, no thermals passed for more than 2 h at a third site that was located perpendicular to the mean wind direction in relation to the first two sites. Organized structures of turbulence with subsidence prevailing in the surroundings of thermals can thus partly explain significant spatial variance differences existing for several hours. Therefore, the representativeness of individual variance profiles derived from measurements at a single site cannot be assumed.

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Section: Doppler Lidars At Three Sitesmentioning

confidence: 99%

Section: Errors Considered For Variance Calculationsmentioning

confidence: 99%

Section: Scales and Scaling Parametersmentioning

confidence: 99%

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Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain

et al. 2016

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“…Pearson et al, 2010). MLH can be estimated by using a threshold value for the vertical velocity standard deviation σ w (e.g Tucker et al, 2009;Pearson et al, 2010;Barlow et al, 2011;Träumner et al, 2011). Another method is to use turbulent energy dissipation rate as proposed by O'Connor et al (2010).…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

“…In their multi-sensor approach for a boundary layer classification Harvey et al (2013) use the second derivative of the vertical velocity variance with respect to height: if the profile is convex in the lower half of the ABL it is a ML with mixing originating from the surface. Träumner et al (2011) discuss several methods based on the semi-theoretical σ w profile as proposed by Lenschow et al (1980). They find that the use of a threshold for σ w is the most robust method.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Mixing-layer height retrieval with ceilometer and Doppler lidar: from case studies to long-term assessment

Hirsikko²,

et al. 2014

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Abstract. Aerosol signatures observed by ceilometers are frequently used to derive mixing-layer height (MLH) which is an essential variable for air quality modelling. However, Doppler wind lidar measurements of vertical velocity can provide a more direct estimation of MLH via simple thresholding. A case study reveals difficulties in the aerosol-based MLH retrieval during transition times when the mixing layer builds up in the morning and when turbulence decays in the afternoon. The difficulties can be explained by the fact that the aerosol distribution is related to the history of the mixing process and aerosol characteristics are modified by humidification. The results of the case study are generalized by evaluating one year of joint measurements by a Vaisala CT25K and a HALO Photonics Streamline wind lidar. On average the aerosol-based retrieval gives higher MLH than the wind lidar with an overestimation of MLH by about 300 m (600 m) in the morning (late afternoon). Also, the daily aerosol-based maximum MLH is larger and occurs later during the day and the average morning growth rates are smaller than those derived from the vertical wind. In fair weather conditions classified by less than 4 octa cloud cover the mean diurnal cycle of cloud base height corresponds well to the mixing-layer height showing potential for a simplified MLH estimation.

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Improved boundary layer depth retrievals from MPLNET

et al. 2013

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[1] Continuous lidar observations of the planetary boundary layer (PBL) depth have been made at the Micropulse Lidar Network (MPLNET) site in Greenbelt, Maryland, since April 2001. However, because of issues with the operational PBL depth algorithm, the data are not reliable for determining seasonal and diurnal trends. Therefore, an improved PBL depth algorithm has been developed which uses a combination of the wavelet technique and image processing. The new algorithm is less susceptible to contamination by clouds and residual layers and, in general, produces lower PBL depths. A 2010 comparison shows the operational algorithm overestimates the daily mean PBL depth when compared to the improved algorithm (1.85 and 1.07 km, respectively). The improved MPLNET PBL depths are validated using radiosonde comparisons, which suggests the algorithm performs well to determine the depth of a fully developed PBL. A comparison with the Goddard Earth Observing System version 5 (GEOS-5) model suggests that the model may underestimate the maximum daytime PBL depth by 410 m during the spring and summer. The best agreement between MPLNET and GEOS-5 occurred during the fall and they differed the most in the winter.

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Convective Boundary-Layer Entrainment: Short Review and Progress using Doppler Lidar

Cited by 64 publications

References 73 publications

Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain

Observed spatiotemporal variability of boundary-layer turbulence over flat, heterogeneous terrain

Mixing-layer height retrieval with ceilometer and Doppler lidar: from case studies to long-term assessment

Improved boundary layer depth retrievals from MPLNET

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