Validation of PBL Schemes over Southern New England Coastal Waters Using the IMPOWR Field

CampaignMatthew 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? 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 models𝑷𝒐𝒘𝒆𝒓 (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 Closure

Covariance 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)