Draxl, Caroline

Hahmann, Andrea N.

Nielsen, Joakim Refslund

Pena Diaz, Alfredo

Online Research Database In Technology

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Downloaded from orbit.dtu.dk on: Dec 18, 2017Simulating the vertical structure of the wind with the weather research and forecasting(WRF) modelHahmann, Andrea  N.; Draxl, Caroline; Pena Diaz, Alfredo; Nielsen, Joakim RefslundPublication date:2011Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Hahmann, A. N., Draxl, C., Pena Diaz, A., & Nielsen, J. R. (2011). Simulating the vertical structure of the windwith the weather research and forecasting (WRF) model. Poster session presented at EWEA Annual Event2011, Brussels, Belgium.Simulating the Vertical Structure of the Wind with the Weather Research and Forecasting (WRF) ModelAndrea N. Hahmann, Caroline Draxl, Alfredo Peña, and Joakim R. Nielsen Risø DTU, National Laboratory for Sustainable Energy, DenmarkPO.153Mesoscale numerical weather prediction models are now widely used to forecast wind conditions and to assess regional wind energy resources. As most of these models have been developed to serve the wide meteorological community, they need to be cautiously implemented/adjusted for use in wind energy applications. To obtain an optimal model configuration, careful verification of the boundary-layer winds simulated by these models at several levels is therefore a must. At EWEC 2010 [1] we presented results from the verification of a real-time weather forecasting system for Denmark based on the Advanced Research WRF (ARW-WRF; Weather, Research and Forecasting) mesoscale model against cup anemometer measurements from a tall mast at the Risø National Test Station for Large Wind Turbines at Høvsøre, Denmark. The results showed that the most widely used planetary boundary layer (PBL) parameterisation in WRF, the Yonsei University (YSU) PBL scheme, fails to properly represent the observed vertical wind shear at this location. Consequently, wind speeds are usually over-estimated at 10 meters, the level of most conventional wind measurements. In contrast, winds at a height of 100 meters are fairly well simulated. Here we expand our previous analysis to diagnose the model errors, in particular with their relationship to atmospheric stability. We also study the sensitivity of the simulated vertical wind profile from seven PBL parameterisations available in WRF. This study is unique because: (1) it uses the high quality meteorological observations at Høvsøre, and (2) accurate forecasts at this site are often difficult because stability changes dominate over topographic and mesoscale thermal forcing in determining the wind profile.AbstractResultsExperimental DesignConclusions ReferencesEWEA 2011, Brussels, Belgium: Europe’s Premier Wind Energy EventRisø maintains a real-time weather forecasting system for Denmark based on the WRF model. The model domain and the basic model configuration is presented in Figure 1 and Table1. To explore the sensitivity of the WRF-simulated wind profiles to the PBL scheme used in the model simulations, a set of forecasts were run using the basic model configuration but changing the PBL and corresponding surface layer and land surface schemes.  The seven schemes used are quickly described in Table 2.The simulated wind profiles are validated against measurements at Høvsøre National test center for large wind turbines (Western Denmark).  The terrain around the site is relatively flat and homogeneous and situated at a distance of 1.7 km from the coast.Figure 2.  Shear parameter (α) as a function of time of the day (x-axis) and day of the month (y-axis) for October 2009 for each PBL scheme in Table 1. The bottom center plot represents αcomputed from the wind observations at Høvsøre at 10 and 60 m.  The model equivalent is computed at the closest model grid point over land from two levels at ~14 and 56 m. The black boxes in the bottom right plot display the hours when the observations are in the wake zone of the wind turbines (330º−30º).  PBL SchemePBL Scheme type Land Surface ModelSurface Layer SchemeACM2 First order closure Pleim-Xu Pleim-XuMRF Non-local-K mixing NOAH LSM Monin-ObukhovMYJ TKE closure (1.5-order) NOAH LSM Eta similarityMYNN2 TKE closure (1.5-order) NOAH LSM MYNNMYNN3 TKE closure (2nd-order) NOAH LSM MYNNYSU Non-local-K mixing NOAH LSM Monin-ObukhovQNSE TKE closure (1.5 order) NOAH LSM QNSEFigure 4.  Probability density functions (%) of various parameters as a function of  observed (x-axis) and WRF-simulated values (y-axis).  Each panel contains 4 graphs: heat flux (upper left), friction velocity (upper right), 1/L (lower left) and α parameter (lower right).  The panels are repeated for 4 PBL schemes: MYJ, QNSE, ACM2, and YSU. Hours when the observations are in the wake zone of the wind turbines (330º−30º) are not used in the calculations.Figure 3. Comparison of observed (black solid line)  and simulated (7 PBL schemes in Table 2) wind profiles at Høvsøre during October 2009. Profiles are grouped into 5 stability classes based on the observed Monin-Obukhov length. Unstable: -500<L<-50, neutral: L<-500, L>500, near stable: 200<L<500, stable: 50<L<200, very stable: 10<L<50. Hours when the observations are in the wake zone of the wind turbines (330º−30º) are not used in the calculations.Table 1. WRF configurationDaily runs at 12 GMT driven by GFS(1º×1) initial and boundary conditions for the period 1-30 October 2009; SST from NCEP at 0.5º×0.5º horizontal resolution Each simulation lasts 30 hours; hours 0-5 are not used in the analysisModel domain: 18 km parent domain and two nests at 6 and 2 km  37 vertical levels; lowest 4 at 14, 52, 104, and 162 meters.No data assimilation or nudgingBesides various PBL and surface layer schemes (see Table 1), the model uses: Thompson graupelscheme, Kain-Fritsch cumulus parameterizationThe parameter α is often used to diagnose the shape of the wind profile. It comes from the expressionwhere u(z1) and u(z2) are the wind speeds at heights z1 and z2, respectively. α varies with height, surface roughness length, and atmospheric stability. Using similarity theory, for neutral conditions, surface roughness length of 5 cm, and z1=10 m and z2=60 m, α=0.162. Smaller (larger) values represent unstable (stable) atmospheric BL conditions.Table 2. Description of the PBL schemes used in the WRF experimentsFigure 1.The average wind profile forecasted by WRF using the QNSE scheme generally compares best with the observed profiles for a range of stability classes (Figures 2 and 3).  However, the RMSE errors (Table 3) suggest that different schemes fit better particular stability conditions (for example, YSU for unstable conditions, MYJ for very stable conditions). Although the surface parameters (i.e. sensible heat  and momentum flux) simulated by WRF with different PBL schemes do not exhibit significant variations compared to the observations, the wind profile, and thus the α parameter, does.The results clearly indicate that 10-meter winds cannot be used for verification of mesoscale model simulations, at least when applied to wind energy.  In such applications verification against high-quality wind profiles is a must.Table 3. RMSE between model simulations and observations at Høvsøre.  The verification is grouped into 5 stability classes based on the observed Monin-Obukhov length. Hours when the observations are in the wake zone of the wind turbines (330º−30º) are not used in the calculations.Høvsøre[1] Hahmann, A.N. and A. Peña, 2010: Validation of boundary layer winds from WRF forecasts over Denmark. EWEC 2010, Warsaw, Poland.

Simulating the vertical structure of the wind with the weather research and forecasting (WRF) model

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Simulating the vertical structure of the wind with the weather research and forecasting (WRF) model

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