Turbulence Dissipation Rate in the Atmospheric Boundary Layer: Observations and WRF Mesoscale Modeling during the XPIA Field Campaign

2018 ◽  
Vol 146 (1) ◽  
pp. 351-371 ◽  
Author(s):  
Domingo Muñoz-Esparza ◽  
Robert D. Sharman ◽  
Julie K. Lundquist
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Planetary Boundary Layer ◽  
Dissipation Rate ◽  
Vertical Structure ◽  
Sonic Anemometer ◽  
Wrf Model ◽  
Order Structure ◽  
Field Campaign ◽  
Statistical Behavior

Abstract A better understanding and prediction of turbulence dissipation rate ε in the atmospheric boundary layer (ABL) is important for many applications. Herein, sonic anemometer data from the Experimental Planetary boundary layer Instrumentation Assessment (XPIA) field campaign (March–May 2015) are used to derive energy dissipation rate (EDR; =) within the first 300 m above the ground employing second-order structure functions. Turbulence dissipation rate is found to be strongly driven by the diurnal evolution of the ABL, presenting a distinct statistical behavior between daytime and nighttime conditions that follows log–Weibull and lognormal distributions, respectively. In addition, the vertical structure of EDR is characterized by a decrease with height above the surface, with the largest gradients occurring within the surface layer (z < 50 m). Convection-permitting mesoscale simulations were carried out with all of the 1.5-order turbulent kinetic energy (TKE) closure planetary boundary layer (PBL) schemes available in the Weather Research and Forecasting (WRF) Model. Overall, the three PBL schemes capture the observed diurnal evolution of EDR as well as the statistical behavior and vertical structure. However, the Mellor–Yamada-type schemes underestimate the large EDR levels during the bulk of daytime conditions, with the quasi-normal scale elimination (QNSE) scheme providing the best agreement with observations. During stably stratified nighttime conditions, Mellor–Yamada–Janjić (MYJ) and QNSE tend to exhibit an artificial “clipping” to their background TKE levels. A reduction in the model constant in the dissipation term for the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme did not have a noticeable impact on EDR estimates. In contrast, application of a postprocessing statistical remapping technique reduced the systematic negative bias in the MYNN results by 75%.

scholarly journals Turbulence dissipation rate estimated from lidar observations during the LAPSE-RATE field campaign

2021 ◽  
Vol 13 (7) ◽  
pp. 3539-3549
Author(s):  
Miguel Sanchez Gomez ◽  
Julie K. Lundquist ◽  
Petra M. Klein ◽  
Tyler M. Bell
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Dissipation Rate ◽  
Unmanned Aircraft ◽  
Lapse Rate ◽  
Diurnal Variability ◽  
Field Campaign ◽  
University Of Oklahoma ◽  
Remotely Piloted Aircraft ◽  
The University

Abstract. The International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) hosted a flight week in July 2018 to demonstrate unmanned aircraft systems' (UASs) capabilities in sampling the atmospheric boundary layer. This week-long experiment was called the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. Numerous remotely piloted aircraft and ground-based instruments were deployed with the objective of capturing meso- and microscale phenomena in the atmospheric boundary layer. The University of Oklahoma deployed one Halo Streamline lidar, and the University of Colorado Boulder deployed two WindCube lidars. In this paper, we use data collected from these Doppler lidars to estimate turbulence dissipation rate throughout the campaign. We observe large temporal variability of turbulence dissipation close to the surface with the WindCube lidars that is not detected by the Halo Streamline. However, the Halo lidar enables estimating dissipation rate within the whole boundary layer, where a diurnal variability emerges. We also find a higher correspondence in turbulence dissipation between the WindCube lidars, which are not co-located, compared to the Halo and WindCube lidar that are co-located, suggesting a significant influence of measurement volume on the retrieved values of dissipation rate. This dataset has been submitted to Zenodo (Sanchez Gomez and Lundquist, 2020) for free and is openly accessible (https://doi.org/10.5281/zenodo.4399967).

scholarly journals Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model

2019 ◽  
Author(s):  
Jiali Wang ◽  
Prasanna Balaprakash ◽  
Rao Kotamarthi
Keyword(s):  
Neural Network ◽  
Boundary Layer ◽  
Neural Networks ◽  
Water Vapor ◽  
Atmospheric Boundary Layer ◽  
Planetary Boundary Layer ◽  
Diurnal Cycle ◽  
Deep Neural Networks ◽  
Wrf Model ◽  
Physical Processes

Abstract. Parameterizations for physical processes in weather and climate models are computationally expensive. We use model output from a set of simulations performed using the Weather Research Forecast (WRF) model to train deep neural networks and evaluate whether trained models can provide an accurate alternative to the physics-based parameterizations. Specifically, we develop an emulator using deep neural networks for a planetary boundary layer (PBL) parameterization in the WRF model. PBL parameterizations are commonly used in atmospheric models to represent the diurnal variation of the formation and collapse of the atmospheric boundary layer – the lowest part of the atmosphere. The dynamics of the atmospheric boundary layer, mixing and turbulence within the boundary layer, velocity, temperature, and humidity profiles are all critical for determining many of the physical processes in the atmosphere. PBL parameterizations are used to represent these processes that are usually unresolved in a typical numerical weather model that operates at horizontal spatial scales in the tens of kilometers. We demonstrate that a domain-aware deep neural network, which takes account of underlying domain structure that are locality specific (e.g., terrain, spatial dependence vertically), can successfully simulate the vertical profiles within the boundary layer of velocities, temperature, and water vapor over the entire diurnal cycle. We then assess the spatial transferability of the domain-aware neural networks by using a trained model from one location to nearby locations. Results show that a single trained model from a location over the midwestern United States produces predictions of wind components, temperature, and water vapor profiles over the entire diurnal cycle and all nearby locations with errors less than a few percent when compared with the WRF simulations used as the training dataset.

scholarly journals Turbulence Dissipation Rate Estimated from Lidar Observations During the LAPSE-RATE Field Campaign

2021 ◽  
Author(s):  
Miguel Sanchez Gomez ◽  
Julie K. Lundquist ◽  
Petra M. Klein ◽  
Tyler M. Bell
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Dissipation Rate ◽  
Unmanned Aircraft ◽  
Lapse Rate ◽  
Diurnal Variability ◽  
Field Campaign ◽  
University Of Oklahoma ◽  
Remotely Piloted Aircraft ◽  
The University

Abstract. The International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) hosted a flight week in July 2018 to demonstrate Unmanned Aircraft Systems’ (UAS) capabilities in sampling the atmospheric boundary layer. This week-long experiment was called the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. Numerous remotely piloted aircrafts and ground-based instruments were deployed with the objective of capturing meso- and microscale phenomena in the atmospheric boundary layer. The University of Oklahoma deployed one Halo Streamline lidar and the University of Colorado Boulder deployed two Windcube lidars. In this paper, we use data collected from these Doppler lidars to estimate turbulence dissipation rate throughout the campaign. We observe large temporal variability of turbulence dissipation close to the surface with the Windcube lidars that is not detected by the Halo Streamline. However, the Halo lidar enables estimating dissipation rate within the whole boundary layer, where a diurnal variability emerges. We also find a higher correspondence in turbulence dissipation between the Windcube lidars, which are not co-located, compared to the Halo and Windcube lidar that are co-located, suggesting a significant influence of measurement volume on the retrieved values of dissipation rate. This dataset have been submitted to Zenodo (Sanchez Gomez and Lundquist, 2020) for free and open access (https://doi.org/10.5281/zenodo.4399967).

scholarly journals Meteorological observations of the coastal boundary layer structure at the Bulgarian Black Sea coast

2011 ◽  
Vol 6 (1) ◽  
pp. 251-259 ◽  
Author(s):  
D. Barantiev ◽  
M. Novitsky ◽  
E. Batchvarova
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Black Sea ◽  
Vertical Structure ◽  
Sonic Anemometer ◽  
Sea Breeze ◽  
Turbulence Measurements ◽  
Black Sea Coast ◽  
Meteorological Observatory ◽  
Sea Coast

Abstract. Continuous wind profile and turbulence measurements were initiated in July 2008 at the coastal meteorological observatory of Ahtopol on the Black Sea (south-east Bulgaria) under a Bulgarian-Russian collaborative program. These observations are the start of high resolution atmospheric boundary layer vertical structure climatology at the Bulgarian Black Sea coast using remote sensing technology and turbulence measurements. The potential of the measurement program with respect to this goal is illustrated with examples of sea breeze formation and characteristics during the summer of 2008. The analysis revealed three distinct types of weather conditions: no breeze, breeze with sharp frontal passage and gradually developing breeze. During the sea breeze days, the average wind speed near the ground (from sonic anemometer at 4.5 m and first layer of sodar at 30–40 m) did not exceed 3–4 m s−1. The onset of breeze circulation was detected based on surface layer measurements of air temperature (platinum sensor and acoustic), wind speed and direction, and turbulence parameters. The sodar measurements revealed the vertical structure of the wind field.

scholarly journals Estimating Daytime Planetary Boundary Layer Heights over a Valley from Rawinsonde Observations at a Nearby Airport: An Application to the Page Valley in Virginia, United States

2016 ◽  
Vol 55 (3) ◽  
pp. 791-809 ◽  
Author(s):  
Temple R. Lee ◽  
Stephan F. J. De Wekker
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Weather Forecasting ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Dispersion Modeling ◽  
Blue Ridge Mountains ◽  
Terrain Following ◽  
Regional Reanalysis

AbstractThe planetary boundary layer (PBL) height is an essential parameter required for many applications, including weather forecasting and dispersion modeling for air quality. Estimates of PBL height are not easily available and often come from twice-daily rawinsonde observations at airports, typically at 0000 and 1200 UTC. Questions often arise regarding the applicability of PBL heights retrieved from these twice-daily observations to surrounding locations. Obtaining this information requires knowledge of the spatial variability of PBL heights. This knowledge is particularly limited in regions with mountainous terrain. The goal of this study is to develop a method for estimating daytime PBL heights in the Page Valley, located in the Blue Ridge Mountains of Virginia. The approach includes using 1) rawinsonde observations from the nearest sounding station [Dulles Airport (IAD)], which is located 90 km northeast of the Page Valley, 2) North American Regional Reanalysis (NARR) output, and 3) simulations with the Weather Research and Forecasting (WRF) Model. When selecting days on which PBL heights from NARR compare well to PBL heights determined from the IAD soundings, it is found that PBL heights are higher (on the order of 200–400 m) over the Page Valley than at IAD and that these differences are typically larger in summer than in winter. WRF simulations indicate that larger sensible heat fluxes and terrain-following characteristics of PBL height both contribute to PBL heights being higher over the Page Valley than at IAD.

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