Role of the residual layer and large-scale subsidence on the development and evolution of the convective boundary layer

Blay-Carreras, E.; Pino, David; Arellano, Jordi Vilà‐Guerau de; Boer, A. van de; Coster, O. de; Darbieu, Clara; Hartogensis, Oscar; Lohou, Fabienne; Pietersen, H.

doi:10.5194/acp-14-4515-2014

Cited by 54 publications

(45 citation statements)

References 67 publications

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“…However, as mentioned in Table 1, transitioning between two methods for LiDAR-radon combination remains a challenge for both morning and evening transition periods. Notwithstanding, the detection of boundary layer transitions, and in particular the evening transition period, is indeed a challenging topic for the atmospheric science community, as has been recently elucidated in the Boundary-Layer Late Afternoon and Sunset Turbulence (BLLAST) project (e.g., [101][102][103]). For the LiDAR and encroachment model combination, the transitioning between two methods depends on time of the heat flux crossover in the morning transition period.…”

Section: Discussionmentioning

confidence: 99%

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

Pal

2014

Remote Sensing

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Abstract:There is compelling evidence that the incomplete laser beam receiver field-of-view overlap (i.e., partial overlap) of ground-based vertically-pointing aerosol LiDAR restricts the observational range for detecting aerosol layer boundaries to a certain height above the LiDAR. This height varies from one to few hundreds of meters, depending on the transceiver geometry. The range, or height of full overlap, is defined as the minimum distance at which the laser beam is completely imaged onto the detector through the field stop in the receiver optics. Thus, the LiDAR signal below the height of full overlap remains erroneous. In effect, it is not possible to derive the atmospheric boundary layer (ABL) top (z i ) below the height of full overlap using lidar measurements alone. This problem makes determination of the nocturnal z i almost impossible, as the nocturnal z i is often lower than the minimum possible retrieved height due to incomplete overlap of lidar. Detailed studies of the nocturnal boundary layer or of variability of low z i would require changes in the LiDAR configuration such that a complete transceiver overlap could be achieved at a much lower height. Otherwise, improvements in the system configuration or deployment (e.g., scanning LiDAR) are needed. However, these improvements are challenging due to the instrument configuration and the need for Raman channel signal, eye-safe laser transmitter for scanning deployment, etc. This paper presents a brief review of some of the challenges and opportunities in overcoming the partial overlap of the LiDAR transceiver to determine z i below the height of full-overlap using complementary approaches to derive low z i . A comprehensive discussion focusing on four different techniques is presented. These are based on the combined (1) ceilometer and LiDAR; (2) tower-based trace gas (e.g., CO 2 ) concentration profiles and LiDAR measurements; (3) 222 Rn budget approach and LiDAR-derived results; and (4) encroachment model and LiDAR observations.

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Section: Discussionmentioning

confidence: 99%

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

Pal

2014

Remote Sensing

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“…Moeng and Sullivan (1994). A comparison to Blay-Carreras et al (2014) is also conform regarding the vertical dependence and the order of magnitude of the individual TKE 500 budget terms. Further, the contributions from the individual TKE budget terms are in agreement with 18 Atmos.…”

Section: Discussionmentioning

confidence: 99%

“…The main surface characteristics are listed in Table 2. In simulation B, cubic obstacles with a size of 100 m × 100 m × 5 m, separated by 100 m from each other in zonal and meridional direction, are implemented via the immersed boundary method in Equations (1) A detailed description can be found in Lothon et al (2014).…”

Section: Surface Heterogeneitymentioning

confidence: 99%

“…We use the IOP of the BLLAST campaign from the 1st of July 2011 (Lothon et al (2014)) for the validation of our method of the simulation of a diurnal cycle with the LES model EULAG. We chose 250 the 1st of July because it is characterised by anticyclonic conditions minimising large-scale forcings except subsidence and radiative cooling.…”

Section: Surface Heterogeneitymentioning

confidence: 99%

“…Therefore, the BLLAST dataset is used to validate our results and to compare them with the accompanying numerical simulations published in ACP (e.g. Blay-Carreras et al (2014), Nilsson et al (2015)). …”

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confidence: 99%

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The impact of the diurnal cycle of the atmospheric boundary layer on physical variables relevant for wind energy applications

Englberger¹,

Dörnbrack²

2016

Preprint

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Abstract. This paper provides a quantification of the temporal evolution of physical variables in the atmospheric boundary layer (ABL) relevant for wind energy applications. For this purpose, we use the unique dataset gathered during the BLLAST (Boundary Layer Late Afternoon and Sun- This results in a quantification of the diurnal cycle influence on the vertical wind shear, the stratifi-10 cation and the turbulence intensity in the atmosphere. Further, the impact of different heterogeneous surface conditions on shear near the surface layer of the ABL is investigated.

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Forcing mechanisms governing diurnal, seasonal, and interannual variability in the boundary layer depths: Five years of continuous lidar observations over a suburban site near Paris

Pal

Haeffelin

2015

JGR Atmospheres

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The atmospheric boundary layer (ABL) depth, zi, is a fundamental variable of ABL and a climatologically important quantity. The exchange of energy between the Earth's surface and the atmosphere is governed by turbulent mixing processes in the daytime ABL, and thus, zi is important for scaling turbulence and diffusion in both meteorological and air quality models. A long‐term data set of zi was derived at the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) observatory near Paris, using measurements obtained from a ground‐based vertically pointing aerosol lidar and an autonomous algorithm STRAT+. Using multiparameter observational data sets covering a 5 year period (October 2008 to September 2013), this study aims to explore two interconnected ABL research topics: brief climatology involving multiscale temporal zi variability (diurnal, seasonal, annual, and interannual) and the relationship between zi and near‐surface thermodynamic parameters to determine meteorological processes governing zi variability. Both the zi and the growth rate over SIRTA showed large seasonal variability with higher mean values in spring (1633 m and 225 m h−1) and summer (1947 m and 247 m h−1) than in autumn (1439 m and 196 m h−1) and winter (1033 m and 149 m h−1). Seasonal variability of daytime maximum zi is found to be strongly and linearly correlated with downwelling solar radiation at the surface (r = 0.92), while the dependence between daytime maximum zi and sensible heat flux (SHF) at seasonal scales is not fully linear, in particular, for summer months. Interannual variability is studied using deseasonalized monthly‐mean anomalies of each variable. Conditional sampling and linear regression analyses between the anomalies of deseasonalized SHF and daytime maximum zi, show (1) stronger correlation between the two parameters for the soil conditions compared to the wet soil conditions, (2) that zi anomalies were more dependent on SHF anomalies for negative than for positive boundary layer wind speed anomalies, and (3) in the summer season, zi anomalies varied more consistently with SHF anomalies for conditions with negative cloud cover anomalies than in conditions with positive cloud cover anomalies.

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Role of the residual layer and large-scale subsidence on the development and evolution of the convective boundary layer

Cited by 54 publications

References 67 publications

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

The impact of the diurnal cycle of the atmospheric boundary layer on physical variables relevant for wind energy applications

Forcing mechanisms governing diurnal, seasonal, and interannual variability in the boundary layer depths: Five years of continuous lidar observations over a suburban site near Paris

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