scholarly journals VALIDAÇÃO DO MODELO LES PALM POR MEIO DE DADOS DE RADIOSONDAGENS E DE AERONAVE COLETADOS DURANTE O EXPERIMENTO GOAMAZON

2016 ◽  
Vol 38 ◽  
pp. 34
Author(s):  
Thomas Kaufmann ◽  
Gilberto Fisch
Keyword(s):  
Boundary Layer ◽  
Observational Data ◽  
Convective Boundary Layer ◽  
Amazon Rainforest ◽  
Layer Depth ◽  
Convective Boundary ◽  
Late Afternoon ◽  
Dry Seasons ◽  
Field Campaigns ◽  
Wet And Dry Seasons

In the present study, the evolution of the convective boundary layer over heterogeneous surface simulated by PALM LES is validated with radiosounding and airborne data from GoAmazon field campaigns, held in Amazon Rainforest during the 2014 wet and dry seasons. It is shown that, in general case, the growth of the convective boundary layer simulated by PALM compares well with observational data. However, during the morning time, the convective boundary layer depth is underestimated, whereas it showed acceptable response to the decreasing of the surface forcings along the late afternoon.

Marginal Stability of the Convective Boundary Layer

2020 ◽  
Vol 77 (2) ◽  
pp. 435-442
Author(s):  
John Thuburn ◽  
Georgios A. Efstathiou
Keyword(s):  
Boundary Layer ◽  
Stability Analysis ◽  
Linear Stability Analysis ◽  
Convective Boundary Layer ◽  
Eddy Viscosity ◽  
Potential Temperature ◽  
Marginal Stability ◽  
Layer Depth ◽  
Convective Boundary ◽  
Layer Potential

Abstract We hypothesize that the convective atmospheric boundary layer is marginally stable when the damping effects of turbulence are taken into account. If the effects of turbulence are modeled as an eddy viscosity and diffusivity, then an idealized analysis based on the hypothesis predicts a well-known scaling for the magnitude of the eddy viscosity and diffusivity. It also predicts that the marginally stable modes should have vertical and horizontal scales comparable to the boundary layer depth. A more quantitative numerical linear stability analysis is presented for a realistic convective boundary layer potential temperature profile and is found to support the hypothesis.

scholarly journals Convective Boundary Layer Depth Estimation from S-Band Dual-Polarization Radar

2018 ◽  
Vol 35 (8) ◽  
pp. 1723-1733 ◽  
Author(s):  
John R. Banghoff ◽  
David J. Stensrud ◽  
Matthew R. Kumjian
Keyword(s):  
Boundary Layer ◽  
New York ◽  
Convective Boundary Layer ◽  
Depth Estimation ◽  
Dual Polarization ◽  
Layer Depth ◽  
Reasonable Estimate ◽  
Convective Boundary ◽  
Using Data ◽  
Differential Reflectivity

AbstractThis study investigates Bragg scatter signatures in dual-polarization radar observations, which are defined by low differential reflectivity values, as a proxy for convective boundary layer (CBL) depth. Using data from the WSR-88D in Twin Lakes, Oklahoma (KTLX), local minima in quasi-vertical profiles of are found to provide a reasonable estimate of CBL depth when compared with depth estimates from upper-air soundings from Norman, Oklahoma (KOUN), during 2014. The 243 Bragg scatter and upper-air sounding CBL depth estimates have a correlation of 0.90 and an RMSE of 254 m. Using Bragg scatter as a proxy for CBL depth was expanded to other seasons and locations—performing well in Wilmington, Ohio; Fairbanks, Alaska; Tucson, Arizona; Minneapolis, Minnesota; Albany, New York; Portland, Oregon; and Tampa, Florida—showing its potential usefulness in monitoring CBL depth throughout the year in a variety of geographic locations and meteorological conditions.

scholarly journals Convective boundary layer characterization in the Amazon rainforest before and after the passage of Mesoscale convective systems

2020 ◽  
Vol 42 ◽  
pp. e2
Author(s):  
Vanessa Monteiro
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Growth Rates ◽  
Mesoscale Convective Systems ◽  
Amazon Rainforest ◽  
Specific Humidity ◽  
Convective Boundary ◽  
Data Set ◽  
Convective Systems ◽  
Mesoscale Convective

This study describes thermodynamic variables (e.g., temperature and humidity) of the atmospheric convective boundary layer (CBL) and its growth rates preceding and following the passage of mesoscale convective systems (MCSs) in the Amazon rainforest. Using the data set provided by GoAmazon 2014/15, this study will address its objectives through the evaluation of case studies and an ensemble of days when there was the passage of MCSs. The results show that the convective boundary layer experiences reductions in the equivalent potential temperature within 2 to 8K and in the specific humidity up to 2 g kg-1 after the passage of a MCS, due to the cold and dry air brought to the surface by storms downdrafts. These two variables in addition to others (e.g., energy fluxes) are responsible for the low growth rates of the convective boundary layer, that were reduced by 100 m h-1 in the following two hours after the rainfall ceases, when compared to undisturbed conditions. Nonetheless, this work provides a quantitative evaluation of the thermodynamic features of the convective boundary layer under the passage of mesoscale convective systems in the Amazon rainforest.

scholarly journals Using WSR-88D Data and Insolation Estimates to Determine Convective Boundary Layer Depth

2012 ◽  
Vol 29 (4) ◽  
pp. 581-588 ◽  
Author(s):  
Kimberly L. Elmore ◽  
Pamela L. Heinselman ◽  
David J. Stensrud
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Radar Reflectivity ◽  
Layer Depth ◽  
Convective Boundary ◽  
Clear Sky ◽  
Testing Dataset ◽  
Human Interpretation ◽  
The One ◽  
Linear Regressions

Abstract Prior work shows that Weather Surveillance Radar-1988 Doppler (WSR-88D) clear-air reflectivity can be used to determine convective boundary layer (CBL) depth. Based on that work, two simple linear regressions are developed that provide CBL depth. One requires only clear-air radar reflectivity from a single 4.5° elevation scan, whereas the other additionally requires the total, clear-sky insolation at the radar site, derived from the radar location and local time. Because only the most recent radar scan is used, the CBL depth can, in principle, be computed for every scan. The “true” CBL depth used to develop the models is based on human interpretation of the 915-MHz profiler data. The regressions presented in this work are developed using 17 summer days near Norman, Oklahoma, that have been previously investigated. The resulting equations and algorithms are applied to a testing dataset consisting of 7 days not previously analyzed. Though the regression using insolation estimates performs best, errors from both models are on the order of the expected error of the profiler-estimated CBL depth values. Of the two regressions, the one that uses insolation yields CBL depth estimates with an RMSE of 208 m, while the regression with only clear-air radar reflectivity yields CBL depth estimates with an RMSE of 330 m.

scholarly journals Convective Boundary Layer Depth Estimation from Wind Profilers: Statistical Comparison between an Automated Algorithm and Expert Estimations

2008 ◽  
Vol 25 (8) ◽  
pp. 1397-1413 ◽  
Author(s):  
Laura Bianco ◽  
James M. Wilczak ◽  
Allen B. White
Keyword(s):  
Boundary Layer ◽  
Fuzzy Logic ◽  
Vertical Velocity ◽  
Convective Boundary Layer ◽  
Index Structure ◽  
Small Scale ◽  
Vertical Profiles ◽  
Improved Method ◽  
Layer Depth ◽  
Convective Boundary

Abstract A previous study showed success in determining the convective boundary layer depth with radar wind-profiling radars using fuzzy logic methods, and improvements to the earlier work are discussed. The improved method uses the Vaisala multipeak picking (MPP) procedure to identify the atmospheric signal in radar spectra in place of a fuzzy logic peak picking procedure that was previously used. The method then applies fuzzy logic techniques to calculate the depth of the convective boundary layer. The planetary boundary layer depth algorithm is improved with respect to the one used in the previous study in that it adds information obtained from the small-scale turbulence (vertical profiles of the spectral width of the vertical velocity), while also still using vertical profiles of the radar-derived refractive index structure parameter C2n and the variance of vertical velocity. Modifications to the fuzzy logic rules (especially to those using vertical velocity data) that improve the algorithm’s accuracy in cloudy boundary layers are incorporated. In addition, a reliability threshold value to the fuzzy logic–derived score is applied to eliminate PBL depth data values with low score values. These low score values correspond to periods when the PBL structure does not match the conceptual model of the convective PBL built into the algorithm. Also, as a final step, an optional temporal continuity test on boundary layer depth has been developed that helps improve the algorithm’s skill. A comparison with independent boundary layer depth estimations made “by eye” by meteorologists at two radar wind-profiler sites, significantly different in their characteristics, shows that the new improved method gives significantly more accurate estimates of the boundary layer depth than does the previous method, and also much better estimates than the simpler “standard” method of selecting the peak of C2n. The new method produces an absolute error of the mixing-depth estimates comparable to the vertical range resolution of the profilers.

scholarly journals Turbulence measurements with a tethered balloon

2016 ◽  
Author(s):  
G. Canut ◽  
F. Couvreux ◽  
M. Lothon ◽  
D. Legain ◽  
B. Piguet ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Convective Boundary Layer ◽  
Motion Sensor ◽  
Tethered Balloon ◽  
Inertial Motion ◽  
Convective Boundary ◽  
Momentum Fluxes ◽  
Field Campaigns

Abstract. This study presents the first deployment of a turbulence probe below a tethered balloon in field campaigns. This system allows to measure turbulent temperature fluxes, momentum fluxes as well as turbulent kinetic energy in the lower part of the boundary layer. It is composed of a sonic thermoanemometer and inertial motion sensor. It has been validated during three campaigns with different convective boundary layer conditions using turbulent measurements from atmospheric towers and aircraft.

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