scholarly journals Boundary-layer turbulent processes and mesoscale variability represented by numerical weather prediction models during the BLLAST campaign

2016 ◽  
Vol 16 (14) ◽  
pp. 8983-9002 ◽  
Author(s):  
Fleur Couvreux ◽  
Eric Bazile ◽  
Guylaine Canut ◽  
Yann Seity ◽  
Marie Lothon ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Heat Flux ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Weather Prediction ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Mesoscale Variability ◽  
Near Surface ◽  
Order Of Magnitude

Abstract. This study evaluates the ability of three operational models, with resolution varying from 2.5 to 16 km, to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence (BLLAST) field campaign. We analyse the representation of the vertical profiles of temperature and humidity and the time evolution of near-surface atmospheric variables and the radiative and turbulent fluxes over a total of 12 intensive observing periods (IOPs), each lasting 24 h. Special attention is paid to the evolution of the turbulent kinetic energy (TKE), which was sampled by a combination of independent instruments. For the first time, this variable, a central one in the turbulence scheme used in AROME and ARPEGE, is evaluated with observations.In general, the 24 h forecasts succeed in reproducing the variability from one day to another in terms of cloud cover, temperature and boundary-layer depth. However, they exhibit some systematic biases, in particular a cold bias within the daytime boundary layer for all models. An overestimation of the sensible heat flux is noted for two points in ARPEGE and is found to be partly related to an inaccurate simplification of surface characteristics. AROME shows a moist bias within the daytime boundary layer, which is consistent with overestimated latent heat fluxes. ECMWF presents a dry bias at 2 m above the surface and also overestimates the sensible heat flux. The high-resolution model AROME resolves the vertical structures better, in particular the strong daytime inversion and the thin evening stable boundary layer. This model is also able to capture some specific observed features, such as the orographically driven subsidence and a well-defined maximum that arises during the evening of the water vapour mixing ratio in the upper part of the residual layer due to fine-scale advection. The model reproduces the order of magnitude of spatial variability observed at mesoscale (a few tens of kilometres). AROME provides a good simulation of the diurnal variability of the turbulent kinetic energy, while ARPEGE shows the right order of magnitude.

scholarly journals Boundary-layer turbulent processes and mesoscale variability represented by Numerical Weather Prediction models during the BLLAST campaign

2016 ◽  
Author(s):  
Fleur Couvreux ◽  
Eric Bazile ◽  
Guylaine Canut ◽  
Yann Seity ◽  
Marie Lothon ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Heat Flux ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Sensible Heat Flux ◽  
Grid Size ◽  
Global Model ◽  
Sensible Heat ◽  
Mesoscale Variability ◽  
Order Of Magnitude

Abstract. This study evaluates the ability of three operational models, AROME, ARPEGE and ECMWF, to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence (BLLAST) field campaign. AROME is a 2.5 km limited area non-hydrostatic model operated over France, ARPEGE a global model with a 10 km grid-size over France and ECMWF a global model with a 16 km grid-size. We analyze the representation of the vertical profiles of temperature and humidity and the time evolution of near surface atmospheric variables as well as the radiative and turbulent fluxes for a total of 12 24h-long Intensive Observing Periods. Special attention is paid to the evolution of the turbulent kinetic energy that was sampled by a combination of independent instruments. For the first time, this variable, which is a central variable in the turbulence scheme used in AROME and ARPEGE, is evaluated with observations. In general, the 24h-forecasts succeed in reproducing the variability from one day to the other in term of cloud cover, temperature, boundary-layer depth. However, they exhibit some systematic biases, in particular a cold bias within the daytime boundary layer for all models. An overestimation of the sensible heat flux is noted for two points in ARPEGE, partly related to an inaccurate simplification of surface characteristics and over-predominance of forests. AROME shows a moist bias within the daytime boundary layer, consistently with overestimated latent heat fluxes. ECMWF presents a dry bias at 2 m above surface and also overestimates the sensible heat flux. The high-resolution model AROME better resolves the vertical structures, in particular the strong daytime inversion and the evening thin stable boundary layer. This model is also capable to capture the peculiar observed features, such as the orographically-driven subsidence and a well-defined maximum in water vapor mixing ratio in the upper part of the residual layer that arises during the evening due to mesoscale advection. The mesoscale variability is analyzed and the order of magnitude is also well reproduced in AROME. AROME provides a good simulation of the diurnal variability of the turbulent kinetic energy while ARPEGE shows a right order of magnitude.

scholarly journals Turbulent and boundary layer characteristics during VOCALS-REx

2021 ◽  
Vol 21 (3) ◽  
pp. 1937-1961
Author(s):  
Dillon S. Dodson ◽  
Jennifer D. Small Griswold
Keyword(s):  
Boundary Layer ◽  
Heat Flux ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Sensible Heat Flux ◽  
Cloud Layer ◽  
Cloud Base ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Turbulent Characteristics

Abstract. Boundary layer and turbulent characteristics (surface fluxes, turbulent kinetic energy – TKE, turbulent kinetic energy dissipation rate – ϵ), along with synoptic-scale changes in these properties over time, are examined using data collected from 18 research flights made with the CIRPAS Twin Otter Aircraft. Data were collected during the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) at Point Alpha (20∘ S, 72∘ W) in October and November 2008 off the coast of South America. The average boundary layer depth is found to be 1148 m, with 28 % of the boundary layer profiles analyzed displaying decoupling. Analysis of correlation coefficients indicates that as atmospheric pressure decreases, the boundary layer height (zi) increases. As has been shown previously, the increase in zi is accompanied by a decrease in turbulence within the boundary layer. As zi increases, cooling near cloud top cannot sustain mixing over the entire depth of the boundary layer, resulting in less turbulence and boundary layer decoupling. As the latent heat flux (LHF) and sensible heat flux (SHF) increase, zi increases, along with the cloud thickness decreasing with increasing LHF. This suggests that an enhanced LHF results in enhanced entrainment, which acts to thin the cloud layer while deepening the boundary layer. A maximum in TKE on 1 November (both overall average and largest single value measured) is due to sub-cloud precipitation acting to destabilize the sub-cloud layer while acting to stabilize the cloud layer (through evaporation occurring away from the surface, primarily confined between a normalized boundary layer height, z/zi, of 0.40 to 0.60). Enhanced moisture above cloud top from a passing synoptic system also acts to reduce cloud-top cooling, reducing the potential for mixing of the cloud layer. This is observed in both the vertical profiles of the TKE and ϵ, in which it is found that the distributions of turbulence for the sub-cloud and in-cloud layer are completely offset from one another (i.e., the range of turbulent values measured have slight or no overlap for the in-cloud and sub-cloud regions), with the TKE in the sub-cloud layer maximizing for the analysis period, while the TKE in the in-cloud layer is below the average in-cloud value for the analysis period. Measures of vertical velocity variance, TKE, and the buoyancy flux averaged over all 18 flights display a maximum near cloud middle (between normalized in-cloud height, Z*, values of 0.25 and 0.75). A total of 10 of the 18 flights display two peaks in TKE within the cloud layer, one near cloud base and another near cloud top, signifying evaporative and radiational cooling near cloud top and latent heating near cloud base. Decoupled boundary layers tend to have a maximum in turbulence in the sub-cloud layer, with only a single peak in turbulence within the cloud layer.

scholarly journals Observation of sensible and latent heat flux profiles with lidar

2020 ◽  
Vol 13 (6) ◽  
pp. 3221-3233 ◽  
Author(s):  
Andreas Behrendt ◽  
Volker Wulfmeyer ◽  
Christoph Senff ◽  
Shravan Kumar Muppa ◽  
Florian Späth ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Sensible Heat Flux ◽  
Ground Level ◽  
Sensible Heat ◽  
Flux Divergence ◽  
Convective Boundary ◽  
The Mean

Abstract. We present the first measurement of the sensible heat flux (H) profile in the convective boundary layer (CBL) derived from the covariance of collocated vertical-pointing temperature rotational Raman lidar and Doppler wind lidar measurements. The uncertainties of the H measurements due to instrumental noise and limited sampling are also derived and discussed. Simultaneous measurements of the latent heat flux profile (L) and other turbulent variables were obtained with the combination of water-vapor differential absorption lidar (WVDIAL) and Doppler lidar. The case study uses a measurement example from the HOPE (HD(CP)2 Observational Prototype Experiment) campaign, which took place in western Germany in 2013 and presents a cloud-free well-developed quasi-stationary CBL. The mean boundary layer height zi was at 1230 m above ground level. The results show – as expected – positive values of H in the middle of the CBL. A maximum of (182±32) W m−2, with the second number for the noise uncertainty, is found at 0.5 zi. At about 0.7 zi, H changes sign to negative values above. The entrainment flux was (-62±27) W m−2. The mean sensible heat flux divergence in the observed part of the CBL above 0.3 zi was −0.28 W m−3, which corresponds to a warming of 0.83 K h−1. The L profile shows a slight positive mean flux divergence of 0.12 W m−3 and an entrainment flux of (214±36) W m−2. The combination of H and L profiles in combination with variance and other turbulent parameters is very valuable for the evaluation of large-eddy simulation (LES) results and the further improvement and validation of turbulence parameterization schemes.

scholarly journals Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model

2012 ◽  
Vol 140 (9) ◽  
pp. 3017-3038 ◽  
Author(s):  
Anna C. Fitch ◽  
Joseph B. Olson ◽  
Julie K. Lundquist ◽  
Jimy Dudhia ◽  
Alok K. Gupta ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Kinetic Energy ◽  
Wind Farm ◽  
Weather Prediction ◽  
Wind Farms ◽  
Mean Flow ◽  
Thrust Coefficient ◽  
Near Surface ◽  
Neutral Boundary Layer

Abstract A new wind farm parameterization has been developed for the mesoscale numerical weather prediction model, the Weather Research and Forecasting model (WRF). The effects of wind turbines are represented by imposing a momentum sink on the mean flow; transferring kinetic energy into electricity and turbulent kinetic energy (TKE). The parameterization improves upon previous models, basing the atmospheric drag of turbines on the thrust coefficient of a modern commercial turbine. In addition, the source of TKE varies with wind speed, reflecting the amount of energy extracted from the atmosphere by the turbines that does not produce electrical energy. Analyses of idealized simulations of a large offshore wind farm are presented to highlight the perturbation induced by the wind farm and its interaction with the atmospheric boundary layer (BL). A wind speed deficit extended throughout the depth of the neutral boundary layer, above and downstream from the farm, with a long wake of 60-km e-folding distance. Within the farm the wind speed deficit reached a maximum reduction of 16%. A maximum increase of TKE, by nearly a factor of 7, was located within the farm. The increase in TKE extended to the top of the BL above the farm due to vertical transport and wind shear, significantly enhancing turbulent momentum fluxes. The TKE increased by a factor of 2 near the surface within the farm. Near-surface winds accelerated by up to 11%. These results are consistent with the few results available from observations and large-eddy simulations, indicating this parameterization provides a reasonable means of exploring potential downwind impacts of large wind farms.

scholarly journals Dissipation of Turbulent Kinetic Energy in the Oscillating Bottom Boundary Layer of a Large Shallow Lake

2020 ◽  
Vol 37 (3) ◽  
pp. 517-531 ◽  
Author(s):  
Aidin Jabbari ◽  
Leon Boegman ◽  
Reza Valipour ◽  
Danielle Wain ◽  
Damien Bouffard
Keyword(s):  
Boundary Layer ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Bottom Boundary Layer ◽  
Inertial Subrange ◽  
Order Structure ◽  
Inertial Method ◽  
Bottom Boundary ◽  
Law Of The Wall ◽  
Order Of Magnitude

AbstractMixing rates and biogeochemical fluxes are commonly estimated from the rate of dissipation of turbulent kinetic energy ε as measured with a single instrument and processing method. However, differences in measurements of ε between instruments/methods often vary by one order of magnitude. In an effort to identify error in computing ε, we have applied four common methods to data from the bottom boundary layer of Lake Erie. We applied the second-order structure function method (SFM) to velocity measurements from an acoustic Doppler current profiler, using both canonical and anisotropy-adjusted Kolmogorov constants, and compared the results with those computed from the law of the wall, Batchelor fitting to temperature gradient microstructure, and inertial subrange fitting to acoustic Doppler velocimeter data. The ε from anisotropy-adjusted constants in SFM increased by a factor of 6 or more at 0.2 m above the bed and showed a better agreement with microstructure and inertial method estimations. The maximum difference between SFM ε, computed using adjusted and canonical constants, and microstructure values was 25% and 50%, respectively. This difference was 30% and 55%, respectively, for those from inertial subrange fitting at times of high-intensity turbulence (Reynolds number at 1 m above the bed of more than 2 × 104). Comparison of the SFM ε to those from law of the wall was often poor, with errors as large as one order of magnitude. From the considerable improvement in ε estimates near the bed, anisotropy-adjusted Kolmogorov constants should be applied to compute dissipation in geophysical boundary layers.

scholarly journals Potential and Limitations in Estimating Sensible-Heat-Flux Profiles from Consecutive Temperature Profiles Using Remotely-Piloted Aircraft Systems

2019 ◽  
Vol 174 (1) ◽  
pp. 145-177 ◽  
Author(s):  
Line Båserud ◽  
Joachim Reuder ◽  
Marius O. Jonassen ◽  
Timothy A. Bonin ◽  
Phillip B. Chilson ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Heat Flux ◽  
Mesoscale Model ◽  
Potential Temperature ◽  
Sensible Heat Flux ◽  
Time Of Day ◽  
Sensible Heat ◽  
Tethered Balloon ◽  
Flux Divergence ◽  
Remotely Piloted Aircraft

Abstract Profiles of the sensible heat flux are key to understanding atmospheric-boundary-layer (ABL) structure and development. Based on temperature profiling by a remotely-piloted aircraft system (RPAS), the Small Unmanned Meteorological Observer (SUMO) platform, during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign, 108 heat-flux profiles are estimated using a simplified version of the prognostic equation for potential temperature $$\theta $$θ that relates the tendency in $$\theta $$θ to the flux divergence over the time span between two consecutive flights. We validate for the first time RPAS-based heat-flux profiles against a network of 12 ground-based eddy-covariance stations (2–60 m above ground), in addition to a comparison with fluxes from a manned aircraft and a tethered balloon, enabling the detailed investigation of the potential and limitations related to this technique for obtaining fluxes from RPAS platforms. We find that appropriate treatment of horizontal advection is crucial for obtaining realistic flux values, and present correction methods specific to the state of the ABL. Advection from a mesoscale model is also tested as another correction method. The SUMO heat-flux estimates with appropriate corrections compare well with the reference measurements, with differences in the performance depending on the time of day, since the evening period shows the best results (94$$\%$$% within the spread of ground stations), and the afternoon period shows the poorest results (63$$\%$$% within the spread). The diurnal cycle of the heat flux is captured by the SUMO platform for several days, with the flux values from the manned aircraft and tethered balloon coinciding well with those from the SUMO platform.

scholarly journals How Does Soil Moisture Influence the Early Stages of the South American Monsoon?

2008 ◽  
Vol 21 (2) ◽  
pp. 195-213 ◽  
Author(s):  
Estela A. Collini ◽  
Ernesto H. Berbery ◽  
Vicente R. Barros ◽  
Matthew E. Pyle
Keyword(s):  
Boundary Layer ◽  
Heat Flux ◽  
Soil Moisture ◽  
Latent Heat ◽  
Sensible Heat Flux ◽  
South American ◽  
Sensible Heat ◽  
The South ◽  
Early Stages ◽  
Initial Soil

Abstract This article discusses the feedbacks between soil moisture and precipitation during the early stages of the South American monsoon. The system achieves maximum precipitation over the southern Amazon basin and the Brazilian highlands during the austral summer. Monsoon changes are associated with the large-scale dynamics, but during its early stages, when the surface is not sufficiently wet, soil moisture anomalies may also modulate the development of precipitation. To investigate this, sensitivity experiments to initial soil moisture conditions were performed using month-long simulations with the regional mesoscale Eta model. Examination of the control simulations shows that they reproduce all major features and magnitudes of the South American circulation and precipitation patterns, particularly those of the monsoon. The surface sensible and latent heat fluxes, as well as precipitation, have a diurnal cycle whose phase is consistent with previous observational studies. The convective inhibition is smallest at the time of the precipitation maximum, but the convective available potential energy exhibits an unrealistic morning maximum that may result from an early boundary layer mixing. The sensitivity experiments show that precipitation is more responsive to reductions of soil moisture than to increases, suggesting that although the soil is not too wet, it is sufficiently humid to easily reach levels where soil moisture anomalies stop being effective in altering the evapotranspiration and other surface and boundary layer variables. Two mechanisms by which soil moisture has a positive feedback with precipitation are discussed. First, the reduction of initial soil moisture leads to a smaller latent heat flux and a larger sensible heat flux, and both contribute to a larger Bowen ratio. The smaller evapotranspiration and increased sensible heat flux lead to a drier and warmer boundary layer, which in turn reduces the atmospheric instability. Second, the deeper (and drier) boundary layer is related to a stronger and higher South American low-level jet (SALLJ). However, because of the lesser moisture content, the SALLJ carries less moisture to the monsoon region, as evidenced by the reduced moisture fluxes and their convergence. The two mechanisms—reduced convective instability and reduced moisture flux convergence—act concurrently to diminish the core monsoon precipitation.

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