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Validation of PBL Schemes over Southern New England Coastal Waters Using the IMPOWR Field Campaign. Matthew J. Sienkiewicz and Brian A. Colle NROW 2013 11-December-2013. Outline. Motivation (Offshore Wind Energy) PBL Schemes How do schemes perform in coastal waters? - PowerPoint PPT Presentation
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Validation of PBL Schemes over Southern New England Coastal Waters Using the IMPOWR Field
CampaignMatthew J. Sienkiewicz and Brian A. Colle
NROW 201311-December-2013
Outline Motivation (Offshore Wind Energy) PBL Schemes How do schemes perform in coastal
waters? Historical Study Period
Buoy/Tower verification IMPOWR Field Campaign
Long-EZ Aircraft Flights Summary
United States Offshore Wind Resource
Bathymetry Wind Speed at 90 m
Shallow coastal waters and high wind resource at hub height make Southern New England a prime location for offshore wind farms.
National Renewable Energy Laboratory, U.S. Department of Energy
Forecasting for Offshore Wind Farms Day-ahead / Hour-
ahead power output forecasts
NWP mesoscale models
Uncertainty forecasts (ensembles)
Neural Network corrections to obtain power output
CFD models 𝑷𝒐𝒘𝒆𝒓 (𝒗𝒆𝒍𝒐𝒄𝒊𝒕𝒚 )𝟑
http://www.wind-power-program.com/turbine_characteristics.htm
Turbulence Closure Schemes
𝜕𝑢/𝜕𝑡=−𝜌−1𝜕𝑝 /𝜕 𝑥+ 𝑓 𝑣−𝜕 (𝑢′𝑤 ′ )/𝜕 𝑧
𝜕𝑣 /𝜕𝑡=−𝜌− 1𝜕𝑝 /𝜕 𝑦− 𝑓 𝑢−𝜕 (𝑣 ′𝑤 ′ )/𝜕 𝑧
𝜕 𝜃𝑣 /𝜕𝑡=(𝜌𝑐𝑝)−1𝜕 𝑅𝑁 /𝜕 𝑧−𝜕 (𝑤′ 𝜃𝑣 ′ )/𝜕 𝑧
𝜕𝑞 /𝜕𝑡=−𝜕 (𝑤′𝑞 ′ ) /𝜕𝑧
Simplified Mean Equations
𝑢 𝑗′ 𝑠 ′=−𝐾 𝑠𝜕 𝑠/𝜕 𝑥 𝑗
First-order Closure
where is the eddy diffusivity of .
TKE-order Closure
𝐾=Λ 𝑒1 /2
where is an empirical length scale, and is the TKE.
Need to solve for unknown covariance terms
Second-order ClosureCovariance terms are
solved for using their respective rate equations and approximations for the third moments(Garratt 1992)
Most schemes developed and tested over land WRF PBL comparison studies mostly done over land
Kansas – schemes overestimated heights of LLJs and underestimated wind speeds (Storm 2008)
Kansas – large nocturnal wind speed biases, inaccurately simulated stable boundary layer (Shin and Hong 2011)
Few WRF PBL comparison studies done over ocean Japan – positive wind speed bias in lower PBL (Shimada
et al. 2011) North Sea – updating master length scale in MYJ scheme
better represented wind shear in lower PBL (Suselj and Sood 2010)
Planetary Boundary Layer Schemes
How do the WRF PBL schemes perform in the Southern New England coastal marine environment?
Study divided into two distinct periods
Historical Period2003-2011
IMPOWR Field Campaign
2013Set of 4km WRF runs verified using data from the Cape Wind Meteorological Mast, as well as available NDBC platforms.
Joint campaign with University of Delaware to observe MBL with high-frequency tower and aircraft measurements during Spring/Summer 2013.
Historical Study Period WRF-ARW (v3.4.1) CW tower data (2003-2011)
Multi-level winds and temperatures 90 randomly and uniformly
selected dates Cool season/warm season 00z/12z initialization times
Six PBL schemes First-Order
YSU, ACM2 TKE-Order
MYJ, MYNN2, BouLac, QNSE 30-hour simulations
Focus is on operational hour-ahead wind forecasts
NARR as boundary/initial conditions
Cape Wind Meteorological Mast
http://www.capewind.org
41 m
60 m
20 m
WRF DOMAINS
Available Marine Observing Platforms
http://www.ndbc.noaa.gov/maps/northeast_hist.shtml
2003-2011
WRF results were bi-linearly interpolated to each station for verification. Observed winds were corrected from the buoy anemometer height of 5
meters to a standard height of 10 meters using where .
Only focusing on near-shore stations with solid data records
WSP BIASES – Northern Buoys (44013 and 44018)
Stronger Positive Warm Season Biases
Strongest at Night
Weakly Positive Biases during Night
Weaker to Negative during Day
WSP BIASES – Southern Buoys (44017 and 44025)
Weaker Warm season biases than Northern Buoys
Biases now stronger during Day
Smaller to more negative biases for both day and night compared to Northern Buoys
WSP BIASES – CMAN Stations (ALSN6 and BUZM3)
Negative Bias during Night
BouLac scheme shows consistent negative bias
TEMP BIASES – Northern Buoys (44013 and 44018)
Stronger warm biases
Weak warm biases
TEMP BIASES – Southern Buoys (44017 and 44025)
Stronger warm biases than Northern Buoys
Weaker warm biases than Northern Buoys during night
Weak cool biases during day
TEMP BIASES – CMAN Stations (ALSN6 and BUZM3)
Biases similar to Southern Buoys
Mostly negative biases during day
Nighttime biases are variable between schemes
Cases with Model Spread?24-January-2011
BouLac scheme (negative bias)
Buoy/Tower Verification Conclusions Mostly positive wind speed biases at surface
during Warm Season Weaker in South than North
BouLac scheme shows consistent negative wind speed bias during Cool Season
Stronger negative daytime biases in wind speed during Cool Season at Southern Buoys compared to Northern Buoys
Negative daytime bias in wind speed just above surface during Warm Season
More marine boundary layer observations are needed
IMPOWR Field CampaignImproving the Mapping and Prediction of Offshore Wind
Resources
http://dendrite.somas.stonybrook.edu/IMPOWR/impowr.html
Began Spring 2013 Long-EZ Aircraft Flights Instrumented towers
Sonic Anemometers Temperatures Humidities
Long-EZ AIRCRAFT
AIMMS-20
40 Hz Observations 3D Winds Temperature Pressure Humidity
GPS and Inertial Systems Air-flow Probe
NANTUCKET SOUND
CAPE WIND TOWER
Flight Day Weather Conditions
12 November 2012 Cyclone warm sector with south winds
4 April 2013 Southwest flow around anticyclone
7 April 2013 Stable strong south flow ahead of warm front
9 April 2013 Southwest flow ahead of cold front
4 May 2013 Moderate northeast flow with a subsidence inversion at top of PBL
10 May 2013 Southwest flow with coastal sea breezes
16 May 2013 Southwest flow with coastal jet
20 June 2013 Coastal sea breeze with westerly flow aloft
21 June 2013 Coastal sea breeze with westerly flow aloft
23 June 2013 Southwesterly flow with coastal enhancement
24 June 2013 NY Bight jet event
28 September 2013 Northeasterly flow around anticyclone
2 October 2013 Weak westerly flow
12-November-2012Warm Sector of Cyclone
Flight 12-Nov-2012
BUZM3 Obs vs. WRF
16-May-2013Coastal Jet
Flight 16-May-2013
Porpoise Maneuvers1000-980 hPa
WRF vs. Aircraft1000-980 hPa
Rapid Refresh Winds (kts)
1000 hPa 925 hPa
Summary PBL errors over the coastal ocean vary by season, location,
and time of day IMPOWR Field Campaign for MBL
Aircraft Observations Tower Observations
NEXT STEPS Run WRF for each flight case/PBL scheme
Winds, temperatures, moisture Momentum Fluxes Sensible and Latent heat fluxes Turbulent Kinetic Energy
IMPOWR Field Campaign will continue Spring/Summer 2014
ReferencesBougeault, P., and P. Lacarrere, 1989: PARAMETERIZATION OF OROGRAPHY-INDUCED TURBULENCE IN A MESOBETA-SCALE MODEL. Monthly Weather Review, 117, 1872-1890.Dvorak, M. J., E. D. Stoutenburg, C. L. Archer, W. Kempton, and M. Z. Jacobson, 2012: Where is the ideal location for a US East Coast offshore grid? Geophys. Res. Lett., 39.Garratt, J. R., 1992: The Atmospheric Boundary Layer, Cambridge University Press, 316 pp.Hong, S. Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly Weather Review, 134, 2318-2341.Janjic, Z. I., 2001: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso model. Technical report, National Centers for Environmental Prediction: Camp Springs, MD, USA.Nakanishi, M., and H. Niino, 2006: An improved mellor-yamada level-3 model: Its numerical stability and application to a regional prediction of advection fog. Boundary-Layer Meteorology, 119, 397-407.Pleim, J. E., 2007: A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: Model description and testing. J. Appl. Meteorol. Climatol., 46, 1383-1395.Shimada, S., T. Ohsawa, S. Chikaoka, and K. Kozai, 2011: Accuracy of the Wind Speed Profile in the Lower PBL as Simulated by the WRF Model. Sola, 7, 109-112.Shin, H. H., and S. Y. Hong, 2011: Intercomparison of Planetary Boundary-Layer Parametrizations in the WRF Model for a Single Day from CASES-99. Boundary-Layer Meteorology, 139, 261-281.Sukoriansky, S., B. Galperin, and V. Perov, 2006: A quasi-normal scale elimination model of turbulence and its application to stably stratified flows. Nonlinear Process Geophys., 13, 9-22.Suselj, K., and A. Sood, 2010: Improving the Mellor-Yamada-Janjic Parameterization for wind conditions in the marine planetary boundary layer. Boundary-Layer Meteorology, 136, 301-324.
Calculation of Turbulent Quantities
𝑒= (𝑢 ′2+𝑣 ′ 2+𝑤 ′2 ) /2Turbulent Kinetic Energy
𝜏𝑥=−𝜌𝑢 ′𝑤 ′𝜏 𝑦=−𝜌𝑣 ′𝑤 ′
Vertical Momentum Fluxes
𝐻𝑣=𝜌𝑐𝑝𝑤 ′𝜃𝑣 ′𝐸=𝜌 𝐿𝑣𝑤 ′𝑞 ′ .
Sensible and Latent Heat Fluxes
𝑑𝑒𝑑𝑡 =
𝑔𝜃𝑣
(𝑤′ 𝜃𝑣 ′ )−(𝑢′𝑤 ′ 𝜕𝑢𝜕𝑧 +𝑣 ′𝑤′ 𝜕 𝑣
𝜕 𝑧 )−𝜕 (𝑤′ 𝑒′ )𝜕 𝑧 − 1𝜌
𝜕 (𝑤′𝑝 ′ )𝜕𝑧 −𝜀 .
Full TKE Budget Equation
(Garratt 1992)