overview of the role of ground-based remote sensing during ... · • 11 wind profiling radars •...
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1 ISTP, May 20-24, 2019
Overview of the Role of Ground-Based Remote Sensing during the Second Wind Forecast Improvement Project (WFIP2)
Jim Wilczak
NOAA/Earth Systems Research Laboratory
Boulder, Co
Collaborators: L. Bianco, I. Djalalova, J. Olson, J. Kenyon, K. McCaffrey,
A. Choukulkar, Y. Pichugina, R. Banta, C. Draxl, M. Stoelinga, L. Berg,
T. Bonin, H. Fernando, J. Lundquist, P. Muradyan, G. Scott , J. Sharp,
D. Turner, S. Wharton, R. Worsnop
(Using observations to improve NWP model forecast skill)
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2 ISTP, May 20-24, 2019
Mt Rainier (4392 m)
Mt Hood (3429 m)
Mt Adams (3743 m)
Columbia River Gorge
WFIP2 Study Area
WA
OR
Cold pools Gap flows Mountain waves
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3 ISTP, May 20-24, 2019
• 11 wind profiling radars
• 17 sodars
• 5 wind profiling lidars
• 5 scanning lidars
• 4 microwave radiometers
• 10 microbarographs
• 1 Ceilometer
• 28 sonic anemometers
• 5 radiative flux systems
• 4 soil moisture sites
• ~200 radiosonde
launches
• Wind plant data from 14
wind plants (1,569
turbines)
180m Tower
Multi-Scale Observations
Field Campaign: All 4 seasons Oct 2015 - March 2017 (18 months )
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4 ISTP, May 20-24, 2019
Microwave
Radiometer S-Band 915-MHz Wind Profiling Radar
Met Station Doppler lidar
RASS
WFIP 2 Instrumentation
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5 ISTP, May 20-24, 2019
Model Development within RAP and HRRR (WRF-ARW based)
RAP domain (13 km)
Terrain, HRRR 750m nest
RAP & HRRR 24x/day
HRRR Nest 2x/day
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6 ISTP, May 20-24, 2019
Model improvement process
Obs +
Real time forecasts
Forecast busts (large errors) Extreme events Model Biases
Trial parameterizations
Reforecasts: Four 6-week
blocks cntl & exp
00&12Z, to 24h
Obs verification
Obs: Process-based case studies
Model case studies:
LES
1D single column
3D WFIP2 region
3D other regions
Obs evaluation
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7 ISTP, May 20-24, 2019
Model improvement process
Obs +
Real time forecasts
Forecast busts (large errors) Extreme events Model Biases
Trial parameterizations
Reforecasts: Four 6-week
blocks cntl & exp
00&12Z, to 24h
Obs verification
Obs: Process-based case studies
Model case studies:
LES
1D single column
3D WFIP2 region
3D other regions
Obs evaluation
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8 ISTP, May 20-24, 2019
• Eddy diffusivity: implemented a z-less formulation of mixing length (maintains cold pools better)
• Mass-Flux scheme added to the MYNN PBL scheme (allowing for a direct coupling of the subcloud convective cores and the cloud layer above)
• Subgrid-scale (SGS) clouds and coupling to radiation (improves the downward shortwave forcing in shallow-cumulus and stratocumulus conditions)
• Surface drag due to gravity waves and form drag from SGS topography (reduces wind speed bias)
• Surface layer scalar flux algorithm (improvements to near-surface temperatures over snow)
• Horizontal finite differencing in Cartesian space instead of sigma coordinates (reduces artificial diffusion in steep terrain)
Model Parameterization Development
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9 ISTP, May 20-24, 2019
Cold Pools
Aggregated equivalent wind power
over 22 sodar/lidar sites
Models have a large wintertime
positive speed bias
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10 ISTP, May 20-24, 2019
Cold Pool Mix-Out of 13 January 2016 – Sodar
750m Nest
Sodar (barbs+speed)
Wasco, Oregon
New
MYNN
+Hor Diff
+GWD
3-km HRRR
Control
200m
0m
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11 ISTP, May 20-24, 2019
Recurrent diurnal gap flows due to sea-breeze forcing
Averaged equivalent wind power
over 22 sodar/lidar sites
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12 ISTP, May 20-24, 2019
Mountain Waves
15 min GOES satellite estimates of periodicity
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13 ISTP, May 20-24, 2019 Images: Joe Olson
Mountain Waves: Model view
• Waves can be seen propagating upstream to the west
• ΔU ~ 3m/s peak-trough matches sodar data
• WFIP2 provides first proof that mountain waves do in fact affect wind energy production
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14 ISTP, May 20-24, 2019
Forecast Improvement Skill (80m winds)
10 year average
improvement RMSE
12h 850 mb vector
winds:
NAM: 0.7% per year
GFS: 0.4% per year
≈7%
averages forecast hours 3-24
control
experimental
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15 ISTP, May 20-24, 2019
Forecast Improvement Skill (Radar wind profiler wind speed)
MAE improvement
+0.5 m/s
0 m/s
-0.5 m/s
+0.5 m/s
0 m/s
-0.5 m/s
1100 m
0 m
1100 m
0 m
sunset sunrise
sunset sunset
sunset
sunrise
sunrise
sunrise
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16 ISTP, May 20-24, 2019
• WFIP2 has demonstrated the importance of lower tropospheric profiling observations for improving model forecast skill
• Identify model problems
• Understand physical processes/suggest parameterization improvements
• Evaluate candidate model parameterization additions and revisions in an iterative process
• Verify final set of new parameterizations
• Having instruments measuring different atmospheric parameters was essential to understand the physical processes causing model forecast errors.
WFIP2 CONCLUSIONS
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17 ISTP, May 20-24, 2019
Forecast Improvement Skill (PBL temperatures)
MAE improvement
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18 ISTP, May 20-24, 2019
Normal VAD technique
vr
[m s
-1]
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19 ISTP, May 20-24, 2019
New technique – maximum of the function of accumulated spectra (MFAS)
• Work in Doppler spectrum domain
• Shift spectra with respect to azimuth direction Ɵ, multiplying spectra by sin(δƟ)
Banakh et al. (2001)
Smalikho, 2003
• Spectra accumulate and the peak is more pronounced compared to noise
• Increase in sensitivity is ∝ 𝑁
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20 ISTP, May 20-24, 2019
Wind profile comparison
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21 ISTP, May 20-24, 2019
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22 ISTP, May 20-24, 2019
• Comparison eliminates days when either instrument had missing data, or MLH could not be estimated due to rain/virga, low clouds, low SNR • Mean values and standard deviation of the binned data are plotted.
1. Mixed-Layer Height (MLH) comparison: Statistics of QC’ed data
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23 ISTP, May 20-24, 2019
Model – Obs Evaluation Webpage:
http://wfip.esrl.noaa.gov/
psd/programs/wfip2/
• Compares observations with models
• Used to:
check if instruments running correctly
classify weather events when
models fail
understand physical processes
• Real-time and final QC’d data is being
stored on DAP at PNNL
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24 ISTP, May 20-24, 2019
Time-series of normalized
aggregate wind power
generation on the Bonneville
Power Administration system
(red curves) and the
aggregate equivalent power
derived from a network of 22
WFIP2 remote sensing sites
that measured 80 m winds.
Aggregate Power on BPA System and WFIP2 Network of 22 Remote Sensors
Cold
pool
Cold
pool
Cold
pool
Diurnal gap flow
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25 ISTP, May 20-24, 2019
Outline
Sites measuring hub-height (80m) winds
22 remote sensor sites (19 sodars, 3 lidars)
• IEC Class 2 power curve
• Aggregate power
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26 ISTP, May 20-24, 2019
Conus-wide improvements
Western CONUS Eastern CONUS
Western CONUS Eastern CONUS