5/18/2015Air Resources Laboratory Boundary –Layer Dispersion NOAA/ATDD - Duke Energy Cooperative Research and Development Agreement Joint Wind Energy Program:

Slides:

Advertisements

Similar presentations

Parametrization of surface fluxes: Outline

Advertisements

Training course: boundary layer; surface layer Parametrization of surface fluxes: Outline Surface layer (Monin Obukhov) similarity Surface fluxes: Alternative.

Urban Test Beds: Productivity, Problems, and Progress Measurement Networks, Logistics, and Models William J. Shaw 12 th GMU Conference on Transport and.

Operational Wind Observations and Forecasts Andrew Stern, NOAA/NWS Local Forecast and Warnings Program Manager Silver Spring, MD

Joint GABLS-GLASS/LoCo workshop, September 2004, De Bilt, Netherlands Interactions of the land-surface with the atmospheric boundary layer: Single.

A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.

How do model errors and localization approaches affects model parameter estimation Juan Ruiz, Takemasa Miyoshi and Masaru Kunii

Some Measurement Issues for Urban Test Beds R. P. Hosker, Jr. NOAA / OAR / ARL Atmospheric Turbulence & Diffusion Division Oak Ridge, TN USA.

A drag parameterization for extreme wind speeds that leads to improved hurricane simulations Gerrit Burgers Niels Zweers Vladimir Makin Hans de Vries EMS.

The Atmospheric Boundary Layer (ABL) over Mesoscale Surface Heterogeneity 25 June 2009 Song-Lak Kang Research Review.

Meteorological Data Issues for Class II Increment Analysis.

Sensitivity of High-Resolution Simulations of Hurricane Bob (1991) to Planetary Boundary Layer Parameterizations SCOTT A. BRAUN AND WEI-KUO TAO PRESENTATION.

Current and future work: the ACTUAL and ClearfLo projects.

THE PARAMETERIZATION OF STABLE BOUNDARY LAYERS BASED ON CASES-99 Zbigniew Sorbjan Marquette University, Milwaukee Zbigniew Sorbjan Marquette University,

Reading: Text, (p40-42, p49-60) Foken 2006 Key questions:

Will Pendergrass NOAA/ARL/ATDD OAR Senior Research Council Meeting Oak Ridge, TN August 18-19, 2010 Boundary–Layer Dispersion Urban Meteorology 5/20/2015Air.

0 Future NWS Activities in Support of Renewable Energy* Dr. David Green NOAA, NWS Office of Climate, Water & Weather Services AMS Summer Community Meeting.

Fog Forecasting at Roissy Airport (Paris) with 1D model Thierry Bergot and Joël Noilhan Météo-France 1) Methodology Cobel : 1D model of boundary layer.

CEREA – Group « Meteorological Measurements » 15 September METEOROLOGICAL MEASUREMENTS IN THE ATMOSPHERIC BOUNDARY LAYER E. Dupont – D. Demengel.

The 8 th GAME International Science Panel Meeting (Thailand, November, 2003) Dr. C. H. Cho Meteorological Research Institute, KMA

0.1m 10 m 1 km Roughness Layer Surface Layer Planetary Boundary Layer Troposphere Stratosphere height The Atmospheric (or Planetary) Boundary Layer is.

Atmospheric structure from lidar and radar Jens Bösenberg 1.Motivation 2.Layer structure 3.Water vapour profiling 4.Turbulence structure 5.Cloud profiling.

Brian Ancell, Cliff Mass, Gregory J. Hakim University of Washington

Weather Research & Forecasting Model (WRF) Stacey Pensgen ESC 452 – Spring ’06.

Unstable Science Question 2 John Hanesiak CEOS, U. Manitoba Unstable Workshop, Edmonton, AB April 18-19, 2007.

Potential measurement strategy with lidar and sonics: Opportunity and issues R.J. Barthelmie 1 and S.C. Pryor 2 1 Sibley School of Mechanical and Aerospace.

COST 715 Meteorology Applied to Urban Air Pollution Problems September 98-September 2003 Problem Issues covered Successes Conclusions.

Observed Structure of the Atmospheric Boundary Layer Many thanks to: Nolan Atkins, Chris Bretherton, Robin Hogan.

Wind Driven Circulation I: Planetary boundary Layer near the sea surface.

SODAR: Uses and Acceptance Laura Tabor Wind Engineering Intern EAPC Wind Energy Services August 7, 2009.

Evaporation Slides prepared by Daene C. McKinney and Venkatesh Merwade

ATD Research Needs and Priorities Panelists Dr. Jay Boris – Navy/NRL Mr. Walter Schalk – NOAA/ARL Mr. John Pace – DoD/DTRA Ms. Jocelyn Mitchell - NuRC.

Oceanic and Atmospheric Modeling of the Big Bend Region Steven L. Morey, Dmitry S. Dukhovksoy, Donald Van Dyke, and Eric P. Chassignet Center for Ocean.

Xin Xi. 1946: Obukhov Length, as a universal length scale for exchange processes in surface layer. 1954: Monin-Obukhov Similarity Theory, as a starting.

Effects of Upwind Roughness Changes and Impacts on Hub-Height Winds Peter A. Taylor 1,2, Wensong Weng 1 and James R. Salmon 2 1 Centre for Research in.

Understanding the USEPA’s AERMOD Modeling System for Environmental Managers Ashok Kumar Abhilash Vijayan Kanwar Siddharth Bhardwaj University of Toledo.

Météo-France / CNRM – T. Bergot 1) Introduction 2) The methodology of the inter-comparison 3) Phase 1 : cases study Inter-comparison of numerical models.

Observational and theoretical investigations of turbulent structures generated by low-Intensity prescribed fires in forested environments X. Bian, W. Heilman,

1/26 APPLICATION OF THE URBAN VERSION OF MM5 FOR HOUSTON University Corporation for Atmospheric Research Sylvain Dupont Collaborators: Steve Burian, Jason.

A canopy model of mean winds through urban areas O. COCEAL and S. E. BELCHER University of Reading, UK.

Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:

Ekaterina Batchvarova, NIMH, Sofia – NATO-ATC-MTTP 1-10 August 2007 Surface exchange and boundary-layer parametrisations in MM5 and WRF and the European.

Estimating the Optimal Location of a New Wind Farm based on Geospatial Information System Data Dec Chungwook Sim.

Simulation of Summertime Wind Speed at Turbine Hub Height: Model Sensitivities to Speed and Shear Characteristics Shannon L. Rabideau, Daniel A. Rajewski,

How well can we model air pollution meteorology in the Houston area? Wayne Angevine CIRES / NOAA ESRL Mark Zagar Met. Office of Slovenia Jerome Brioude,

Meteorology meets Astronomy : open discussion 1.Usefullness of atmospheric mesoscale modelling for astrophysical applications - to forecast astrophysical.

Photo image area measures 2” H x 6.93” W and can be masked by a collage strip of one, two or three images. The photo image area is located 3.19” from left.

Analysis of PBL Turbulent and Non-turbulent Fluxes M. Hicks 1, S. Kang 2, B. Demoz 1, E. Joseph 1, 1 Howard University, Washington, DC, USA 2 UCAR, Boulder,

Results Time Study Site Measured data Alfalfa Numerical Analysis of Water and Heat Transport in Vegetated Soils Using HYDRUS-1D Masaru Sakai 1), Jirka.

Boundary layer depth verification system at NCEP M. Tsidulko, C. M. Tassone, J. McQueen, G. DiMego, and M. Ek 15th International Symposium for the Advancement.

Modeling and Evaluation of Antarctic Boundary Layer

Observed Structure of the Atmospheric Boundary Layer

Katja Friedrich Associate Professor Dept. of Atmospheric and Oceanic Sciences, U. of Colorado Science Plan & Experimental Design.

Challenges in PBL and Innovative Sensing Techniques Walter Bach Army Research Office

ISTP 2003 September15-19, Airborne Measurement of Horizontal Wind and Moisture Transport Using Co-deployed Doppler and DIAL lidars Mike Hardesty,

Météo-France / CNRM – T. Bergot 1) Methodology 2) The assimilation procedures at local scale 3) Results for the winter season Improved Site-Specific.

CWEX-10/11: Overview of Results from the First Two Crop/Wind Energy eXperiments E. S. Takle 1 D. A. Rajewski 1, J. Prueger 2, Steven Oncley 3, J. K. Lundquist.

A revised formulation of the COSMO surface-to-atmosphere transfer scheme Matthias Raschendorfer COSMO Offenbach 2009 Matthias Raschendorfer.

Talents of tomorrow: Wind meteorology

LA-UR The Effect of Boundary-Layer Scheme on WRF model simulations of the Joint Urban 2003 Field Campaign Matthew A. Nelson1, M. J. Brown1, S.

Cost effective power performance testing with nacelle mounted Lidars

Characterizing urban boundary layer dynamics using

Similarity theory 1. Buckingham Pi Theorem and examples

Mark A. Bourassa and Qi Shi

Winter storm forecast at 1-12 h range

Cliff Mass University of Washington

Radiation Fog Forecasting Using a 1-D Model

NRL POST Stratocumulus Cloud Modeling Efforts

Generation of Simulated GIFTS Datasets

Meteorological Measurements for Improved Air Quality Modeling

Presentation transcript:

5/18/2015Air Resources Laboratory Boundary –Layer Dispersion NOAA/ATDD - Duke Energy Cooperative Research and Development Agreement Joint Wind Energy Program: Atmospheric Velocity Gradients Will Pendergrass NOAA/ARL/ATDD OAR Senior Research Council Meeting Oak Ridge, TN August 18-19, 2010

5/18/2015Air Resources Laboratory (1) Can the forecast of wind turbine hub-height wind speeds be improved through inclusion of near- neutral and unstable flux-gradient wind modeling techniques? (2) What is the uncertainty associated with high resolution WRF mesoscale in both now-cast and forecast of winds at 10 m and hub-height? (3) Does assimilation of surface energy flux measurements (heat flux, shear stress, surface roughness, displacement height, and mixed layer height) improve mesoscale forecasts through mesoscale model land surface exchange methodologies? (4) What is the impact of spatial variability in surface energy-balance on forecasted gradient winds at 10 m and hub-height? Science Questions NOAA/DUKE CRADA Goal: Improved Forecasts of Hub Height Winds

5/18/2015Air Resources Laboratory NOAA/DUKE CRADA Forecast Confidence Level

5/18/2015Air Resources Laboratory field measurements mesoscale modeling Phase one (1) is an evaluation of the flux gradient velocity profile technique based on directly measured surface energy balances. Phase two (2) is an evaluation of results from Phase one as implemented in the WRF model through alternative land use model parameterizations. Boundary-Layer Velocity Gradient Program NOAA/DUKE CRADA Velocity Gradient Profile Monin-Obukov Stability

5/18/2015Air Resources Laboratory Based on conversations between NOAA/ATDD and Duke Energy, the Ocottilo wind farm was selected as the initial focused study area. During a joint site survey, NOAA/ATDD and Duke Energy engineers evaluated the Ocotillo area for installation of a NOAA 10-meter energy balance system and 30- meter wind/temperature profiling system. Additional siting was evaluated for Doppler SODAR operation, additional surface based energy-balance system, and possible radiosonde operations. Site Selection Big Spring, Texas Duke Energy Ocotillo Wind Farm NOAA/DUKE CRADA Prevailing winds

5/18/2015Air Resources Laboratory In cooperation with Duke Energy field engineers, NOAA/ATDD install a 30- meter tower monitoring winds and temperature within the surface roughness layer. Wind Flux Profiling Tower Acquired Observations 15, 30, 60 minute output u, v, w, ws, wd σ u, σ v,σ w, u’v’, u’w’, v’w’, T, T’ 2, w’T’, u’ 2, v’ 2, w’ 2, u run, v run, w run NOAA/DUKE CRADA

5/18/2015Air Resources Laboratory In cooperation with Duke Energy field engineers, NOAA/ARL installed a 10-meter energy balance monitoring system NOAA/DUKE CRADA 15, 30, 60 minute output u, v, w, ws, wd σ u, σ v,σ w, u’v’, u’w’, v’w’, T, T’ 2, w’T’, u’ 2, v’ 2, w’ 2, u run, v run, w run, soil temperature (5 levels), soil moisture, solar energy components, surface temperature, CO 2 /H 2 O Surface Energy Balance system

5/18/2015Air Resources Laboratory NOAA/ATDD established a web-based data management site to provide both NOAA/ATDD and Duke Energy with access to acquired measurements from both the Energy balance system 8 NOAA/DUKE CRADA

5/18/2015Air Resources Laboratory9 WRF Model Output NOAA/DUKE CRADA

5/18/2015Air Resources Laboratory NOAA/DUKE CRADA Gradient profile Requirements: U *, z 0, h, z/L Observed Duke Energy Ocotillo 80 m winds Evaluated Ocotillo gradient profile parameters

5/18/2015Air Resources Laboratory NOAA/DUKE CRADA Intercomparison of forecast/measured winds and temperature RTMA – red ATDD - black Wind Speed Wind Direction Temperature

5/18/2015Air Resources Laboratory Technical Interchange Meetings (TIMs) : Researchers from NOAA/ARL and Duke Energy have planned routine (TIMs) to review collaborative efforts (next meeting late September, 2010). Evaluation/comparison of measured Duke Ocotillo 80-meter winds using measured e-balance surface winds and boundary layer variables using basic velocity gradient profile methodologies. Evaluation/comparison of measured Duke Ocotillo 80-meter winds using RTMA and WRF forecast surface winds and boundary layer variables using evaluated basic velocity gradient profile methodologies. Late Summer-2010 study intensive – measurement of vertical profiles using Doppler Sodar, evaluation of CTW lidar, and high frequency spectral wind measurements. 12 Next Steps NOAA/DUKE CRADA