Nicola Bodini et al. Correspondence to: Nicola Bodini

Similar documents
Boundary Layer Science Challenges in the Context of Wind Energy

Supplement of Upside-down fluxes Down Under: CO 2 net sink in winter and net source in summer in a temperate evergreen broadleaf forest

Supplement of A dual-inlet, single detector relaxed eddy accumulation system for long-term measurement of mercury flux

Meteorological Measurements made during RxCADRE

ACTION: STSM: TOPIC: VENUE: PERIOD:

Observed Reduction of Sensitivities of Windcube Measurements by Vector Averaging

SCIENTIFIC REPORT. Host: Sven-Erik Gryning (DTU Wind Energy, Denmark) Applicant: Lucie Rottner (Météo-France, CNRM, France)

Windcube TM Pulsed lidar wind profiler Overview of more than 2 years of field experience J.P.Cariou, R. Parmentier, M. Boquet, L.

Supplement of Vegetation greenness and land carbon-flux anomalies associated with climate variations: a focus on the year 2015

UFO Database. UFO Dissemination Workshop 23/04/2015. NLR, Amsterdam. Oleg A. Krasnov and the UFO team

Deutscher Wetterdienst

Jasna Bogunović Jakobsen a a

Air-Sea Interface and Marine Boundary-Layer Anemometers

18B.2 USING THE TLS TO IMPROVE THE UNDERSTANDING OF ATMOSPHERIC TURBULENT PROCESSES

Comparison of 3D turbulence measurements using three staring wind lidars and a sonic anemometer

7.6 SMALL SCALE TURBULENCE MODULATION BY DUCTED GRAVITY WAVES ABOVE THE NOCTURNAL BOUNDARY LAYER

Identification of Tower Wake Distortions. in Sonic Anemometer Measurements during XPIA

Remote Wind Measurements Offshore Using Scanning LiDAR Systems

Statistics of wind direction and its increments

UPPLEMENT. INVESTIGATING EXCHANGE PROCESSES OVER COMPLEX TOPOGRAPHY The Innsbruck Box (i-box)

Supplement of Vertical profiles of aerosol mass concentration derived by unmanned airborne in situ and remote sensing instruments during dust events

SCIENTIFIC REPORT. Universität zu Köln, Germany. Institut für Geophysik und Meteorologie, Universität zu Köln, Germany

Variations in the power-law index with stability and height for wind profiles in the urban boundary layer

6.4 EXPERIMENTAL DETERMINATION OF THE TURBULENT KINETIC ENERGY BUDGET WITHIN AND ABOVE AN URBAN CANOPY

WYANDOTTE MUNICIPAL SERVICES COMMUNITY WIND ENERGY PROJECT WIND RESOUCE SUMMARY

Carbon Trust Offshore Wind Accelerator (OWA) Designing an Offshore Wind Measurement Campaign to Promote the Development of Wake Effects Models

Alignment of stress, mean wind, and vertical gradient of the velocity vector

MPAS Atmospheric Boundary Layer Simulation under Selected Stability Conditions: Evaluation using the SWIFT dataset

arxiv: v1 [physics.data-an] 5 Nov 2015

Turbulence Measurements. Turbulence Measurements In Low Signal-to-Noise. Larry Cornman National Center For Atmospheric Research

4.4 COMPARISON OF WIND MEASUREMENTS AT THE HOWARD UNIVERSITY BELTSVILLE RESEARCH CAMPUS. Science Systems and Applications, Inc.

Section 7.8 from Basic Mathematics Review by Oka Kurniawan was developed by OpenStax College, licensed by Rice University, and is available on the

Stability and turbulence in the atmospheric boundary layer: A comparison of remote sensing and tower observations

J3.7 MEASURING METEOROLOGY IN HIGHLY NON-HOMOGENEOUS AREAS. Ekaterina Batchvarova* 1 and Sven-Erik Gryning 2. Denmark ABSTRACT

October 1991 J. Wang and Y. Mitsuta 587 NOTES AND CORRESPONDENCE. Turbulence Structure and Transfer Characteristics

Supplement of Studying the vertical aerosol extinction coefficient by comparing in situ airborne data and elastic backscatter lidar

Measurements and Simulations of Wakes in Onshore Wind Farms Julie K. Lundquist 1,2

Environmental Atmospheric Turbulence at Florence Airport

EAS rd Scored Assignment (20%) Due: 7 Apr. 2016

Study of wind variability over Moscow city by sodar

MODELING AND MEASUREMENTS OF THE ABL IN SOFIA, BULGARIA

National Center for Atmospheric Research Research Applications Laboratory Renewable Energy

The effect of turbulence and gust on sand erosion and dust entrainment during sand storm Xue-Ling Cheng, Fei Hu and Qing-Cun Zeng

Eliezer Kit School of Mechanical Engineering, Tel-Aviv University. In collaboration with: Joe Fernando Chris Hocut Dan Liberzon

BIAS ON THE WIND-SPEED GUST CAUSED BY QUANTIZATION AND DISJUNCT SAMPLING OF THE CUP-ANEMOMETER SIGNAL

A Note on the Estimation of Eddy Diffusivity and Dissipation Length in Low Winds over a Tropical Urban Terrain

1. Introduction/Goals and expected outcomes

7.5 THERMALLY-DRIVEN WIND SYSTEMS AND HIGH-ALTITUDE OZONE CONCENTRATIONS IN YOSEMITE NATIONAL PARK

Supplement of Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

WLS70: A NEW COMPACT DOPPLER WIND LIDAR FOR BOUNDARY LAYER DYNAMIC STUDIES.

8.6 METEOROLOGICAL SENSOR ARRAY (MSA) OBSERVATIONS AND HIGH RESOLUTION MODEL VALIDATION

Logarithmic velocity profile in the atmospheric (rough wall) boundary layer

2d-Laser Cantilever Anemometer

Triple Doppler wind lidar observations during the mountain terrain atmospheric modeling and observations field campaign

Wake meandering under non-neutral atmospheric stability conditions theory and facts. G.C. Larsen, E. Machefaux and A. Chougule

Lecture 2 Atmospheric Boundary Layer

Jonathan M. Liebmann et al. Correspondence to: John N. Crowley

Steven Greco* and George D. Emmitt Simpson Weather Associates, Charlottesville, VA. 2. Experiments

Investigating low-level jet wind profiles using two different lidars

Obukhov Length Computation using simple measurements from weather stations and AXYS Wind Sentinel Buoys

A Tall Tower Study of the Impact of the Low-Level Jet on Wind Speed and Shear at Turbine Heights

Detecting wind turbine wakes with nacelle lidars

Supplement of Constraining uncertainties in particle-wall deposition correction during SOA formation in chamber experiments

Wind velocity profile observations for roughness parameterization of real urban surfaces

LIDAR OBSERVATIONS OF FINE-SCALE ATMOSPHERIC GRAVITY WAVES IN THE NOCTURNAL BOUNDARY LAYER ABOVE AN ORCHARD CANOPY

Observational Needs for Polar Atmospheric Science

Research within the Coastal Highway Route E39 project. University of Stavanger

R. Fröhlich et al. Correspondence to: A. Prévôt

Anemometry Anemometer Calibration Exercise

Upsidence wave during VOCALS. David A. Rahn and René Garreaud Department of Geophysics Universidad de Chile

Eddy viscosity. AdOc 4060/5060 Spring 2013 Chris Jenkins. Turbulence (video 1hr):

SOLVING INEQUALITIES and 9.1.2

Wave-current-turbulence interaction near the sea surface

1 INTRODUCTION. showed that, for this particular LES model, the main features of the SBL are well reproduced when compared to observational data.

Development of micro-scale CFD model to predict wind environment on complex terrain In-bok Lee

Nowcasting and Urban Interactive Modeling Using Robotic and Remotely Sensed Data James Cogan, Robert Dumais, and Yansen Wang

Magnetic structuring at spatially unresolved scales. Jan Stenflo ETH Zurich and IRSOL, Locarno

Radar/Lidar Sensors for Wind & Wake-Vortex Monitoring on Airport: First results of SESAR P XP0 trials campaign at Paris CDG Airport

Effects of different terrain on velocity standard deviations

P1.17 Super-high-resolution Numerical Simulation of Atmospheric Turbulence in an Area of Complex Terrain

Observational analysis of storms and flooding events in the Pacific Northwest. Introduction

SPECIAL PROJECT PROGRESS REPORT

4.5 Comparison of weather data from the Remote Automated Weather Station network and the North American Regional Reanalysis

The role of coherent structures in subfilter-scale dissipation of turbulence measured in the atmospheric surface layer

4.7 GENERATION OF TURBULENCE AND WIND SHEAR ALERTS: ANATOMY OF A WARNING SYSTEM

DOPPLER LIDAR IN THE WIND FORECAST IMPROVEMENT PROJECTS

* Corresponding author address: Yelena L. Pichugina, CSD / NOAA, 325 Broadway, Boulder, CO 80305;

Influence of atmospheric stratification on the integral scale and fractal dimension of turbulent flows

Edinburgh Research Explorer

The Impacts of Atmospheric Stability on the Accuracy of Wind Speed Extrapolation Methods

Understanding and monitoring Arctic weather using Iqaluit Supersite meteorological observations

Wind velocity measurements using a pulsed LIDAR system: first results

1.0 Implications of using daily climatological wind speed prior to 1948

INVESTIGATION OF THREE PHASE SYSTEM

Application of a Three-Dimensional Prognostic Model During the ETEX Real-Time Modeling Exercise: Evaluatin of Results (u)

Exercises in Combustion Technology

Field Experiment on the Effects of a Nearby Asphalt Road on Temperature Measurement

Analysis of Flow inside Soundproofing Ventilation Unit using CFD

7.1 DEVELOPMENT OF A FINE SCALE SMOKE DISPERSION MODELING SYSTEM. PART II - CASE STUDY OF A PRESCRIBED BURN IN THE NEW JERSEY PINE BARRENS

19 th INTERNATIONAL CONGRESS ON ACOUSTICS MADRID, 2-7 SEPTEMBER 2007

Transcription:

Supplement of Atmos. Meas. Tech., 11, 4291 4308, 2018 https://doi.org/10.5194/amt-11-4291-2018-supplement Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Supplement of Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign Nicola Bodini et al. Correspondence to: Nicola Bodini (nicola.bodini@colorado.edu) The copyright of individual parts of the supplement might differ from the CC BY 4.0 License.

1. Second-order structure function from sonic anemometer measurements 1 0.500 Du(τ) [m 2 s -2 ] 0.100 0.050 0.010 0.005 0.001 0.01 0.10 1 10 100 τ [s] Figure S1: Second-order structure function from sonic anemometer measurements at 100m AGL, for March 2015, 19:58 UTC. The dashed line represents the theoretical Kolmogorov s inertial range slope τ "/$.

2. Comparison of turbulence dissipation rate from sonic anemometers in opposite tower booms (a) - - - (b) - Figure S2: (a) histogram of the fractional median error between turbulence dissipation rate calculated from the sonic anemometers on the northwest booms and the average dissipation from both the boom directions. Results for the sonic anemometers on the southeast booms are similar. (b) as in (a), but median absolute error. Raw values of ε are used.

3. Variation of the sample size with height for the Halo Streamline lidar Figure S3: variability of the appropriate sample size with height for the Halo Streamline lidar, during stable conditions. The best-fit is performed by using the orange dots only, as these correspond to heights with a match with the levels of the sonic anemometers on the BAO tower.

Figure S4: variability of the appropriate sample size with height for the Halo Streamline lidar, during unstable conditions. The best-fit is performed by using the orange dots only, as these correspond to heights with a match with the levels of the sonic anemometers on the BAO tower. 4. Climatology of turbulence dissipation rate from the WINDCUBE v1s ϵ [m " s +$ ] Figure S5: Daily climatology of turbulence dissipation rate derived from the WINDCUBE v1-61 lidar. Data at 120m and 140m AGL are not shown due to hard strikes with the guy wire of the BAO tower.

Figure S6: Daily climatology of turbulence dissipation rate derived from the WINDCUBE v1-68 lidar. Data at 40m, 60m and 80m AGL are not shown due to hard strikes with the guy wire of the BAO tower. ϵ [m " s +$ ]

5. Turbulence dissipation rate as a function of the absolute value of the Obukhov Length from the WINDCUBE v1s 0.010 Unstable conditions 0.001 ϵ [m 2 s -3 ] 10-4 Stable conditions 10-5 WINDCUBE v1-61 WINDCUBE v1-68 10-6 0.5 1 5 10 50 100 500 Absolute value of Obukhov length [m] Figure S7: Turbulence dissipation rate (measurements at 100 m AGL) as a function of the absolute value of the Obukhov Length, for the WINDCUBE v1s. The continuous lines in the plot represent the median value for the different instruments, while the shaded area creates a band corresponding to the 1st and 3rd quartiles of the distributions.

6. Turbulence dissipation rate as a function of wind speed from the WINDCUBE v1s 0.010 Unstable conditions 0.001 ϵ [m 2 s -3 ] 10-4 Stable conditions 10-5 10-6 WINDCUBE v1-61 WINDCUBE v1-68 2 4 6 8 10 12 14 Horizontal wind speed [m s -1 ] Figure S8: Turbulence dissipation rate as a function of the 2-min average wind speed, as measured at 100 m AGL, for the WINDCUBE v1s. The continuous lines in the plot represent the median value for the different instruments, while the shaded area creates a band corresponding to the 1st and 3rd quartiles of the distributions.