The selective dynamical downscaling method for extreme wind atlases. Xiaoli Guo Larsén Jake Badger Andrea N. Hahmann Søren Ott

Transcription

1 The selective dynamical downscaling method for extreme wind atlases Xiaoli Guo Larsén Jake Badger Andrea N. Hahmann Søren Ott 1 EWEC 2011

2 Why is such a method needed? Lack of long term measurements Global model data: not sufficient in resolution Regional climate modeled data: not optimal in storm events 2 Risø DTU, Technical University of Denmark EWEC 2011

3 The method 3 steps of the selective dynamical downscaling method : 1.Identification of storm events for a selected area 2.Mesoscale modeling using WRF 3.Post-processing 3 Risø DTU, Technical University of Denmark EWEC 2011

4 The method Step 1: Identify storm events for a selected area based on -- annual wind maximum method for U annual max G and u 10

5 The method Step 2: Mesoscale modeling using WRF (Denmark case) 1. Run WRF for the 58 cases 2. WRF setup: WRF V3.1 FNL 1 data, 6 hrly SST km 37 vertical layers YSU PBL scheme Liu et al microphysics Time step: 4 min (D1) Run time <=48 hrs, no nudging 10 min output 3. The 50-year wind using the Annual Maxima Method. 5

6 The method Step 3: Post-processing To generalize the winds to standard conditions (at a certain height over a homogeneous surface of certain roughness, here 10 m or hub height, roughness length=5 cm) To prepare for data validation To prepare platform to pass the mesoscale winds to microscale modeling 6

7 The method Step 3: Post-processing For measurements (WAsP cleaning procedure): u 0,z : measured wind at height z s o, s r : sectorwise speed-up coefficients for orography and roughness change z 0= 5 cm u*,r z 0= 5 cm ust 7

8 The method Step 3: Post-processing For WRF output, approach-1: WRF winds Roughness length used in WRF z 0= 5 cm u*,r z 0= 5 cm ust 8 Risø DTU, Technical University of Denmark EWEC 2011

9 The method Step 3: Post-processing For WRF output, approach-2: Using LINCOM (from Risø) to the orography and roughness maps as used in WRF, we get Coefficients of directional orographical change at different heights Coefficients of directional upstream roughness change at different heights Details in Badger et al. 2010: A universal mesoscale to microscale modeling interface tool. EWEC Warsaw, Poland, 2010) Coefficients of directional upstream roughness effective z 0= 5 cm roughness u*,r z 0= 5 cm ust 9 Risø DTU, Technical University of Denmark EWEC 2011

10 The method Step 3: Post-processing For WRF output, approach-2: e.g. West Sector Upstream orography m Upstream roughness 50 m Effective roughness length 10

11 Results (no post-processing) The 50-year winds at different model levels, including 10 m, 15 m, 50 m, 105 m U 10 m 32 m/s Latitude 24 m/s 16 m/s Longitude 11 Risø DTU, Technical University of Denmark EWEC 2011

12 Results (no post-processing) 12

13 Results (no post-processing) * * : due to Gumbel fitting 13

14 Results (with post-processing) The 50-year wind at standard condition with post-processing approach-1 (PP 1) z 0 u ch ch 2 * / g 14

15 Results (with post-processing) The 50-year wind at standard condition with post-processing approach-1 (PP 1) z 0 u ch ch 2 * 0.03 / g 15

16 Results (with post-processing) The 50-year wind at standard condition with post-processing approach-2 (PP 2) z 0 u ch ch 2 * / g 16

17 Results (with post-processing) The 50-year wind at standard condition with post-processing approach-2 (PP 2) z 0 u ch ch 2 * 0.03 / g 17

18 Results (with post-processing) Stations wrf PP1 wrf PP2 OBS ± The 50-year wind of standard conditions (at 10 m, over z0=0.05 m). Charnock parameter = *: values from Larsén and Mann (2009): Extreme winds from NCEP/NCAR reanalysis data, Wind Energy 18

19 Conclusions The selective dynamical downscaling method is robust and efficient The 50-year winds from this method using WRF simulatiuons without post-processing are reasonable offshore extreme winds seem underestimated The 50-year winds corrected to standard conditions are in better agreement with measurements that are also corrected to the same conditions 19

20 Conclusions The selective dynamical downscaling method is robust and efficient The 50-year winds from this method using WRF simulatiuons without post-processing are reasonable offshore extreme winds seem underestimated The 50-year winds corrected to standard conditions are in better agreement with measurements that are also corrected to the same conditions In places of simple orography and roughness fields, post-processing approaches I and II do not bring significant differences Otherwise, post-processing approach II takes into account the upstream orographical change, roughness change and effective roughness length, and it gives better spatial distribution than the simpler approach I. Improvement of WRF simulation is needed over ocean 20

21 Conclusions The selective dynamical downscaling method is robust and efficient The 50-year winds from this method using WRF simulatiuons without post-processing are reasonable offshore extreme winds seem underestimated The 50-year winds corrected to standard conditions are in better agreement with measurements that are also corrected to the same conditions In places of simple orography and roughness fields, post-processing approaches I and II do not bring significant differences Otherwise, post-processing approach II takes into account the upstream orographical change, roughness change and effective roughness length, and it gives better spatial distribution than the simpler approach I. Improvement of WRF simulation is needed over ocean 21

22 Thanks for your attention Acknowledgement: This work is supported by Danish PSO grant and EU SafeWind project (213740) Data from FINO 1 are provided by Deutsches Windenergie Institut, German Wind Energy Institute, through EU-Norsewind project. 22 Risø DTU, Technical University of Denmark EWEC 2011