scholarly journals Analysis of the Influence of the Length Scales in a Boundary-Layer Model

2021 ◽  
Author(s):  
Enrico Ferrero ◽  
Massimo Canonico
Keyword(s):  
Boundary Layer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Layer Model ◽  
Length Scales ◽  
Boundary Layer Model ◽  
Low Wind Speed ◽  
Stable Conditions ◽  
Sonic Anemometers ◽  
Numerical Weather Prediction Models

AbstractWe consider the Janjic (NCEP Office Note 437:61, 2001) boundary-layer model, which is one of the most widely used in numerical weather prediction models. This boundary-layer model is based on a number of length scales that are, in turn, obtained from a master length multiplied by constants. We analyze the simulation results obtained using different sets of constants with respect to measurements using sonic anemometers, and interpret these results in terms of the turbulence processes in the atmosphere and of the role played by the different length scales. The simulations are run on a virtual machine on the Chameleon cloud for low-wind-speed, unstable, and stable conditions.

scholarly journals Improved observations of turbulence dissipation rates from wind profiling radars

2017 ◽  
Vol 10 (7) ◽  
pp. 2595-2611 ◽  
Author(s):  
Katherine McCaffrey ◽  
Laura Bianco ◽  
James M. Wilczak
Keyword(s):  
Boundary Layer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Spectral Width ◽  
High Spectral Resolution ◽  
Dissipation Rates ◽  
Sonic Anemometers ◽  
Processing Algorithms ◽  
Processing Techniques ◽  
Numerical Weather Prediction Models

Abstract. Observations of turbulence dissipation rates in the planetary boundary layer are crucial for validation of parameterizations in numerical weather prediction models. However, because dissipation rates are difficult to obtain, they are infrequently measured through the depth of the boundary layer. For this reason, demonstrating the ability of commonly used wind profiling radars (WPRs) to estimate this quantity would be greatly beneficial. During the XPIA field campaign at the Boulder Atmospheric Observatory, two WPRs operated in an optimized configuration, using high spectral resolution for increased accuracy of Doppler spectral width, specifically chosen to estimate turbulence from a vertically pointing beam. Multiple post-processing techniques, including different numbers of spectral averages and peak processing algorithms for calculating spectral moments, were evaluated to determine the most accurate procedures for estimating turbulence dissipation rates using the information contained in the Doppler spectral width, using sonic anemometers mounted on a 300 m tower for validation. The optimal settings were determined, producing a low bias, which was later corrected. Resulting estimations of turbulence dissipation rates correlated well (R2 = 0. 54 and 0. 41) with the sonic anemometers, and profiles up to 2 km from the 449 MHz WPR and 1 km from the 915 MHz WPR were observed.

scholarly journals Vertical Velocity Variance Measurements from Wind Profiling Radars

2016 ◽  
Author(s):  
Katherine McCaffrey ◽  
Laura Bianco ◽  
Paul Johnston ◽  
James M. Wilczak
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Planetary Boundary Layer ◽  
Vertical Velocity ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Stable Conditions ◽  
Sonic Anemometers ◽  
Velocity Variance

Abstract. Observations of turbulence in the planetary boundary layer are critical for developing and evaluating boundary layer parameterizations in mesoscale numerical weather prediction models. These observations, however, are expensive, and rarely profile the entire boundary layer. Using optimized configurations for 449 MHz and 915 MHz wind profiling radars during the eXperimental Planetary boundary layer Instrumentation Assessment, improvements have been made to the historical methods of measuring vertical velocity variance through the time series of vertical velocity, as well as the Doppler spectral width. Using six heights of sonic anemometers mounted on a 300-m tower, correlations of up to R2 = 0.74 are seen in measurements of the large-scale variances from the radar time series, and R2 = 0.79 in measurements of small-scale variance from radar spectral widths. The total variance, measured as the sum of the small- and large-scales agrees well with sonic anemometers, with R2 = 0.79. Correlation is higher in daytime, convective boundary layers than nighttime, stable conditions when turbulence levels are smaller. With the good agreement with the in situ measurements, highly-resolved profiles up to 2 km can be accurately observed from the 449 MHz radar, and 1 km from the 915 MHz radar. This optimized configuration will provide unique observations for the verification and improvement to boundary layer parameterizations in mesoscale models.

scholarly journals A comparison of vertical velocity variance measurements from wind profiling radars and sonic anemometers

2017 ◽  
Vol 10 (3) ◽  
pp. 999-1015 ◽  
Author(s):  
Katherine McCaffrey ◽  
Laura Bianco ◽  
Paul Johnston ◽  
James M. Wilczak
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Planetary Boundary Layer ◽  
Vertical Velocity ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Stable Conditions ◽  
Sonic Anemometers ◽  
Velocity Variance

Abstract. Observations of turbulence in the planetary boundary layer are critical for developing and evaluating boundary layer parameterizations in mesoscale numerical weather prediction models. These observations, however, are expensive and rarely profile the entire boundary layer. Using optimized configurations for 449 and 915 MHz wind profiling radars during the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA), improvements have been made to the historical methods of measuring vertical velocity variance through the time series of vertical velocity, as well as the Doppler spectral width. Using six heights of sonic anemometers mounted on a 300 m tower, correlations of up to R2 = 0. 74 are seen in measurements of the large-scale variances from the radar time series and R2 = 0. 79 in measurements of small-scale variance from radar spectral widths. The total variance, measured as the sum of the small and large scales, agrees well with sonic anemometers, with R2 = 0. 79. Correlation is higher in daytime convective boundary layers than nighttime stable conditions when turbulence levels are smaller. With the good agreement with the in situ measurements, highly resolved profiles up to 2 km can be accurately observed from the 449 MHz radar and 1 km from the 915 MHz radar. This optimized configuration will provide unique observations for the verification and improvement to boundary layer parameterizations in mesoscale models.

Numerical Prediction of Submesoscale Flow in the Nocturnal Stable Boundary Layer over Complex Terrain

2012 ◽  
Vol 140 (3) ◽  
pp. 956-977 ◽  
Author(s):  
Nelson L. Seaman ◽  
Brian J. Gaudet ◽  
David R. Stauffer ◽  
Larry Mahrt ◽  
Scott J. Richardson ◽  
...  
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Stable Boundary Layers ◽  
Stable Boundary ◽  
Central Pennsylvania ◽  
Stable Conditions ◽  
Improved Model ◽  
Mean Square Errors ◽  
Numerical Weather Prediction Models

Abstract Numerical weather prediction models often perform poorly for weakly forced, highly variable winds in nocturnal stable boundary layers (SBLs). When used as input to air-quality and dispersion models, these wind errors can lead to large errors in subsequent plume forecasts. Finer grid resolution and improved model numerics and physics can help reduce these errors. The Advanced Research Weather Research and Forecasting model (ARW-WRF) has higher-order numerics that may improve predictions of finescale winds (scales <~20 km) in nocturnal SBLs. However, better understanding of the physics controlling SBL flow is needed to take optimal advantage of advanced modeling capabilities. To facilitate ARW-WRF evaluations, a small network of instrumented towers was deployed in the ridge-and-valley topography of central Pennsylvania (PA). Time series of local observations and model forecasts on 1.333- and 0.444-km grids were filtered to isolate deterministic lower-frequency wind components. The time-filtered SBL winds have substantially reduced root-mean-square errors and biases, compared to raw data. Subkilometer horizontal and very fine vertical resolutions are found to be important for reducing model speed and direction errors. Nonturbulent fluctuations in unfiltered, very finescale winds, parts of which may be resolvable by ARW-WRF, are shown to generate horizontal meandering in stable weakly forced conditions. These submesoscale motions include gravity waves, primarily horizontal 2D motions, and other complex signatures. Vertical structure and low-level biases of SBL variables are shown to be sensitive to parameter settings defining minimum “background” mixing in very stable conditions in two representative turbulence schemes.

scholarly journals Seamless Stratocumulus Simulation across the Turbulent Gray Zone

2014 ◽  
Vol 142 (4) ◽  
pp. 1655-1668 ◽  
Author(s):  
I. A. Boutle ◽  
J. E. J. Eyre ◽  
A. P. Lock
Keyword(s):  
Boundary Layer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Aircraft Observations ◽  
Microphysical Parameterization ◽  
Grid Length ◽  
Numerical Weather Prediction Models

Abstract A pragmatic approach for representing partially resolved turbulence in numerical weather prediction models is introduced and tested. The method blends a conventional boundary layer parameterization, suitable for large grid lengths, with a subgrid turbulence scheme suitable for large-eddy simulation. The key parameter for blending the schemes is the ratio of grid length to boundary layer depth. The new parameterization is combined with a scale-aware microphysical parameterization and tested on a case study forecast of stratocumulus evolution. Simulations at a range of model grid lengths between 1 km and 100 m are compared to aircraft observations. The improved microphysical representation removes the correlation between precipitation rate and model grid length, while the new turbulence parameterization improves the transition from unresolved to resolved turbulence as grid length is reduced.

An Evaluation of Scatterometer-Derived Oceanic Surface Pressure Fields

2008 ◽  
Vol 47 (3) ◽  
pp. 835-852 ◽  
Author(s):  
Jérôme Patoux ◽  
Ralph C. Foster ◽  
Robert A. Brown
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Surface Pressure ◽  
Weather Prediction ◽  
Layer Model ◽  
Boundary Layer Model ◽  
Pressure Fields ◽  
Oceanic Surface ◽  
The Tropics ◽  
Planetary Boundary Layer Model

Abstract Oceanic surface pressure fields are derived from the NASA Quick Scatterometer (QuikSCAT) surface wind vector measurements using a two-layer similarity planetary boundary layer model in the midlatitudes and a mixed layer planetary boundary layer model in the tropics. These swath-based surface pressure fields are evaluated using the following three methods: 1) a comparison of bulk pressure gradients with buoy pressure measurements in the North Pacific and North Atlantic Oceans, 2) a least squares difference comparison with the European Centre for Medium-Range Weather Forecasts (ECMWF) surface pressure analyses, and 3) a parallel spectral analysis of the QuikSCAT and ECMWF surface pressure fields. The correlation coefficient squared between scatterometer-derived pressure fields and buoys is found to be R2 = 0.936. The average root-mean-square difference between the scatterometer-derived and the ECMWF pressure fields ranges from 1 to 3 hPa, depending on the latitude and season, and decreases after the assimilation of QuikSCAT winds in the ECMWF numerical weather prediction model. The spectral components of the scatterometer-derived pressure fields are larger than those of ECMWF surface analyses at all scales in the midlatitudes and only at shorter wavelengths in the tropics.

scholarly journals Improved Observations of Turbulence Dissipation Rates from Wind Profiling Radars

2016 ◽  
Author(s):  
Katherine McCaffrey ◽  
Laura Bianco ◽  
James M. Wilczak
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Spectral Width ◽  
High Spectral Resolution ◽  
Spectral Moments ◽  
Dissipation Rates ◽  
Sonic Anemometers ◽  
Processing Algorithms ◽  
Processing Techniques ◽  
Numerical Weather Prediction Models

Abstract. Observations of turbulence in the planetary boundary layer are crucial for validation of parameterizations in numerical weather prediction models. However, these observations are sparse. For this reason, demonstrating the ability of commonly-used wind profiling radars (WPRs) to measure turbulence dissipation rates would be greatly beneficial. During the XPIA field campaign at the Boulder Atmospheric Observatory, two WPRs operated in an optimized configuration, using high spectral resolution for increased accuracy of Doppler spectral width, specifically chosen to measure turbulence from a vertically-pointing beam only. Multiple post-processing techniques, including different numbers of spectral averages and peak-processing algorithms for calculating spectral moments, were analyzed to determine the most accurate procedures for measuring turbulence dissipation rates using the information contained in the Doppler spectral width, and compared to sonic anemometers mounted on a 300-meter tower. The optimal settings were determined, producing a constant low bias, which was later corrected. Resulting measurements of turbulence dissipation rates correlated well (R2 = 0.57) with sonic anemometers, and profiles up to 2 km from the 449-MHz WPR and 1 km from the 915-MHz WPR were observed.

scholarly journals Spatial and temporal variability of turbulence dissipation rate in complex terrain

2018 ◽  
Author(s):  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Raghavendra Krishnamurthy ◽  
Mikhail Pekour ◽  
Larry K. Berg
Keyword(s):  
Spatial Variability ◽  
Structure Function ◽  
Dissipation Rate ◽  
Prediction Models ◽  
Weather Prediction ◽  
Spatial And Temporal Variability ◽  
Strong Impact ◽  
Stable Conditions ◽  
Sonic Anemometers ◽  
Order Of Magnitude

Abstract. To improve the parametrizations of turbulence dissipation rate (ε) in numerical weather prediction models, the temporal and spatial variability of ε must be assessed. In this study, we explore influences on the variability of ε at various scales in the Columbia River Gorge during the WFIP2 field experiment between 2015 and 2017. We calculate ε from five sonic anemometers all deployed in a ~ 4 km2 area; and from two scanning Doppler lidars and four profiling Doppler lidars, whose locations span a ~ 300 km wide region. We retrieve ε from the sonic anemometers using the second-order structure function method, from the scanning lidars with the azimuth structure function approach, and from the profiling lidars with a novel technique using the variance of the line-of-sight velocity. Turbulence dissipation rate shows large spatial variability, even at the microscale, especially during nighttime stable conditions. Orographic features have a strong impact on the variability of ε, with the correlation between ε at different stations being highly influenced by terrain. ε shows larger values in sites located downwind of complex orographic structures or in wind farm wakes. A clear diurnal cycle in ε is found, with daytime convective conditions determining values over an order of magnitude higher than nighttime stable conditions. ε also shows a distinct seasonal cycle, with differences greater than an order of magnitude between average ε values in summer and winter.

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