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?
 Historical Study Period
 Buoy/Tower verification
 IMPOWR Field Campaign
 Long-EZ Aircraft Flights
 Summary
United States Offshore
Wind Resource
National Renewable Energy Laboratory, U.S. Department of Energy
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.
Forecasting for Offshore
Wind Farms
 Day-ahead / Hourahead power output
forecasts
 NWP mesoscale
models
 Uncertainty forecasts
(ensembles)
 Neural Network
corrections to obtain
power output
 CFD models
http://www.wind-power-program.com/turbine_characteristics.htm
𝑷𝒐𝒘𝒆𝒓~(𝒗𝒆𝒍𝒐𝒄𝒊𝒕𝒚)𝟑
Turbulence Closure Schemes
Simplified Mean Equations
𝜕𝑢 𝜕𝑡 = −𝜌−1 𝜕𝑝 𝜕𝑥 + 𝑓𝑣 − 𝜕 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
Need to solve for unknown covariance terms
First-order Closure
𝑢𝑗′ 𝑠 ′ = −𝐾𝑠 𝜕𝑠 𝜕𝑥𝑗
where 𝐾𝑠 is the eddy diffusivity of 𝑠.
(Garratt 1992)
TKE-order Closure
𝐾 = Λ𝑒 1
2
where 𝛬 is an empirical length
scale, and 𝑒 is the TKE.
Second-order Closure
Covariance terms are
solved for using their
respective rate
equations and
approximations for the
third moments
Planetary Boundary Layer
Schemes
 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)
How do the WRF PBL schemes
perform in the Southern New England
coastal marine environment?
Study divided into two distinct periods
Historical Period
2003-2011
Set of 4km WRF runs
verified using data from
the Cape Wind
Meteorological Mast, as
well as available NDBC
platforms.
IMPOWR Field Campaign
2013
Joint campaign with
University of Delaware to
observe MBL with highfrequency 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
WRF DOMAINS
Cape Wind Meteorological Mast
60 m
 Six PBL schemes
 First-Order
 YSU, ACM2
 TKE-Order
 MYJ, MYNN2, BouLac, QNSE
 30-hour simulations
 Focus is on operational hour-ahead
wind forecasts
41 m
20 m
 NARR as boundary/initial
conditions
http://www.capewind.org
Available Marine Observing Platforms
2003-2011
Only focusing on nearshore stations with solid
data records
http://www.ndbc.noaa.gov/maps/northeast_hist.shtml
 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
𝑢2
𝑢1
=
𝑧2 𝑃
where
𝑧1
𝑃 = 0.11.
WSP BIASES – Northern Buoys
(44013 and 44018)
 Weakly Positive Biases
during Night
 Weaker to Negative during
Day
 Stronger Positive Warm
Season Biases
 Strongest at Night
WSP BIASES – Southern Buoys
(44017 and 44025)
 Smaller to more negative
biases for both day and
night compared to Northern
Buoys
 Weaker Warm season biases
than Northern Buoys
 Biases now stronger during
Day
WSP BIASES – CMAN Stations
(ALSN6 and BUZM3)
 BouLac scheme shows
consistent negative bias
 Negative Bias during
Night
TEMP BIASES – Northern Buoys
(44013 and 44018)
 Weak warm biases
 Stronger 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)
 Mostly negative
biases during day
 Nighttime biases are
variable between
schemes
 Biases similar to
Southern Buoys
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 Campaign
Improving the Mapping and Prediction of Offshore Wind Resources
 Began Spring 2013
 Long-EZ Aircraft Flights
 Instrumented towers
 Sonic Anemometers
 Temperatures
 Humidities
http://dendrite.somas.stonybrook.edu/IMPOWR/impowr.html
Long-EZ AIRCRAFT
 40 Hz Observations
 3D Winds
 Temperature
 Pressure
 Humidity
 GPS and Inertial Systems
 Air-flow Probe
AIMMS-20
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-2012
Warm Sector of Cyclone
Flight 12-Nov-2012
BUZM3 Obs vs. WRF
16-May-2013
Coastal Jet
Flight 16-May-2013
Porpoise Maneuvers
1000-980 hPa
WRF vs. Aircraft
1000-980 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
References
Bougeault, 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
Turbulent Kinetic Energy
𝑒 = 𝑢′2 + 𝑣′2 + 𝑤′2
Vertical Momentum Fluxes
2
Sensible and Latent Heat
Fluxes
𝐻𝑣 = 𝜌𝑐𝑝 𝑤′𝜃𝑣 ′
𝐸 = 𝜌𝐿𝑣 𝑤′𝑞′.
𝜏𝑥 = −𝜌𝑢′𝑤′
𝜏𝑦 = −𝜌𝑣′𝑤′
Full TKE Budget Equation
′𝑒′
′ 𝑝′
𝑑𝑒 𝑔
𝜕𝑢
𝜕𝑣
𝜕
𝑤
1
𝜕
𝑤
=
𝑤 ′ 𝜃𝑣 ′ − 𝑢′ 𝑤 ′
+ 𝑣 ′𝑤 ′
−
−
− 𝜀.
𝑑𝑡 𝜃𝑣
𝜕𝑧
𝜕𝑧
𝜕𝑧
𝜌 𝜕𝑧
(Garratt 1992)