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Climate Dynamics

, Volume 42, Issue 7–8, pp 1857–1872 | Cite as

High-resolution sea wind hindcasts over the Mediterranean area

  • M. Menendez
  • M. García-Díez
  • L. Fita
  • J. Fernández
  • F. J. Méndez
  • J. M. Gutiérrez
Article

Abstract

The goal of this study is to develop a high-resolution atmospheric hindcast over the Mediterranean area using the WRF-ARW model, focusing on offshore surface wind fields. In order to choose the most adequate model configuration, the study provides details on the calibration of the experimental saet-up through a sensitivity test considering the October–December 2001 period (the 2001 super-storm event in the West Mediterranean). A daily forecast outperforms the spectral technique of previous products and the boundary data from ERA-Interim reanalysis produces the most accurate estimates in terms of wind variability and hour-to-hour correspondence. According to the sensitivity test, two data sets of wind hindcast are produced: the SeaWind I (30-km horizontal resolution for a period of 60 years) and the SeaWind II (15-km horizontal resolution for 20 years). The validation of the resulting surface winds is undertaken considering two offshore observational datasets. On the one hand, hourly surface buoy stations are used to validate wind time series at specific locations; on the other hand, wind altimeter satellite observations are considered for spatial validation in the whole Mediterranean Sea. The results obtained from this validation process show a very good agreement with observations for the southern Europe region. Finally, SeaWind I and II are used to characterize offshore wind fields in the Mediterranean Sea. The statistical structure of sea surface wind is analyzed and the agreement with Weibull probability distribution is discussed. In addition, wind persistence and extreme wind speed (50 year return period) are characterized and relevant areas of wind power generation are described by estimating wind energy quantities.

Keywords

Dynamical downscaling Multiphysics Hindcast Offshore surface wind WRF 

Notes

Acknowledgments

The authors would like to thank Puertos del Estado (Spanish National Ports and Harbour Authority) for providing the information from the buoy records and model outputs from the HIPOCAS project. The work was partly funded by the projects iMar21 (CTM2010-15009) and CORWES (GL2010-22158-C02-01) from the Spanish government, and the FP7 European project CoCoNet (287844). The large amount of WRF simulations performed in this study were managed by WRF4G, which is an open-source tool funded by the Spanish government and co-funded by the European Regional Development Fund under grant CGL2011-28864.

References

  1. Ardhuin F, Bertotti L, Bidlot J-R, Cavaleri L, Filipetto V, Lefevre J-M, Wittmann P (2007) Comparison of wind and wave measurements and models in the Western Mediterranean Sea. Ocean Eng 34:526–541CrossRefGoogle Scholar
  2. Arreola J, Homar V, Romero R, Ramis C, Alonso S (2003) Multiscale numerical study of the 10–12 November 2001 strong cyclogenesis event in the western mediterranean. In: MEDITERRANEAN STORMS-Proceedings of the 4th EGS Plinius conference, Mallorca, Spain, 2–4 October 2002, pp 1–4Google Scholar
  3. Bauer E (1996) Characteristic frequency distributions of remotely sensed in situ and modelled wind speeds. Int J Climatol 16:1087–1102CrossRefGoogle Scholar
  4. Bengtsson L, Hagemann S, Hodges KI (2004) Can climate trends be calculated from reanalysis data? J Geophys Res 109:D11111CrossRefGoogle Scholar
  5. Brands S, Gutiérrez JM, Herrera S, Cofiño AS (2012) On the use of reanalysis data for downscaling. J Clim 25:2517–2526CrossRefGoogle Scholar
  6. Castro CL, Pielke SRA, Leoncini G (2005) Dynamical downscaling: assessment of value retained and added using the regional atmospheric modeling system (rams). J Geophys Res 110(D05):108Google Scholar
  7. Cavaleri L, Bertotti L, Tescaro N (1996) Long term wind hindcast in the Adriatic Sea. Il Nuovo Cimento 19:67–89CrossRefGoogle Scholar
  8. Charney J, Halem M, Jastrow R (1969) Use of incomplete historical data to infer the present state of the atmosphere. J Atmos Sci 26:1160–1163CrossRefGoogle Scholar
  9. Chen F, Dudhia J (2001) Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I. Model implementation and sensitivity. Mon Weather Rev 129:569–585CrossRefGoogle Scholar
  10. Chronis T, Papadopoulos V, Nikolopoulos EI (2011) QuickSCAT observations of extreme wind events over the Mediterranean and Black Seas during 2000–2008. Int J Climatol 31:2068–2077. doi: 10.1002/joc.2213 CrossRefGoogle Scholar
  11. Dee DP et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597CrossRefGoogle Scholar
  12. Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107CrossRefGoogle Scholar
  13. Erickson DJ, Taylor JA (1989) Non-Weibull behavior observed in a model-generated global surface wind field frequency distribution. J Geophys Res 94(12):693–698Google Scholar
  14. Fernández J, Montávez JP, Sáenz J, González-Rouco JF, Zorita E (2007) Sensitivity of MM5 mesoscale model to physical parameterizations for regional climate studies: annual cycle. J Geophys Res 112(D04):101Google Scholar
  15. Feser F, Rockel B, von Storch H, Winterfeldt J, Zahn M (2011) Regional climate models add value. Bull Amer Meteor Soc 92:1181–1192CrossRefGoogle Scholar
  16. Fita L, Romero R, Ramis C (2007) Objective quantification of perturbations produced with a piecewise pv inversion technique. Ann Geophys 25:2335–2349CrossRefGoogle Scholar
  17. Fita L, Fernández J, García-Díez M (2010) Clwrf: Wrf modifications for regional climate simulation under future scenarios. In: Extended abstracts of the 11th WRF Users’ Workshop, Boulder. 21–25 June 2010, pp 1–4Google Scholar
  18. García-Díez M, Fernández J, Fita L, Yagüe C (2013) Seasonal dependence of WRF model biases and sensitivity to PBL schemes over Europe. Q J R Meteorol Soc 139:501–514CrossRefGoogle Scholar
  19. Genovés A, Jansà A (2003) Diabatic processes contribution to the november 2001 storm. In: MEDITERRANEAN STORMS-Proceedings of the 4th EGS Plinius conference, Mallorca. 2–4 October 2002, pp 1–4Google Scholar
  20. Giorgi F (1990) Simulation of regional climate using limited area model nested in a general circulation model. J Clim 3:941–963CrossRefGoogle Scholar
  21. Grell G, Devenyi D (2002) A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys Res Lett 29:1693. doi: 10.1029/2002GL015311 CrossRefGoogle Scholar
  22. Günter H, Rosenthal W, Stawarz M, Carretero JC, Gomez M, Lozano I, Serrano O, Reistad M (1997) The wave climate of the northeast Atlantic over the period 1955–1994: the was a wave hindcast. GKSS Forschungszentrum Geesthacht GmbH 73:1–34Google Scholar
  23. Hong S, Lim J (2006) The WRF single-moment 6-class microphysics scheme (WSM6). J Korean Meteorol Soc 42:129–151Google Scholar
  24. Hong S, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341CrossRefGoogle Scholar
  25. Hsu SA, Meindl EA, Gilhousen DB (1994) Determining the power-law wind profile exponent under near-neutral stability conditions at sea. J Appl Meteorol 33(6):757–765CrossRefGoogle Scholar
  26. Hu X-M, Nielsen-Gammon JW, Zhang F (2010) Evaluation of three planetary boundary layer schemes in the WRF model. J Appl Meteor Climatol 49:1831–1844CrossRefGoogle Scholar
  27. Jacob D, Podzun R (1997) Sensitivity studies with the regional climate model REMO. Meteorol Atmos Phys 63:119–129CrossRefGoogle Scholar
  28. Janjić ZI (1990) The step-mountain coordinate: physical package. Mon Weather Rev 118:1429–1443CrossRefGoogle Scholar
  29. Janjić ZI (1994) The step-mountain eta coordinate model: further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon Weather Rev 122:927–945CrossRefGoogle Scholar
  30. Janjić ZI (2002) Nonsingular implementation of the Mellor–Yamada level 2.5 scheme in the NCEP Meso model. NCEP Office Note No. 437Google Scholar
  31. Jiménez PA, Dudhia J (2012) Improving the Representation of Resolved and Unresolved Topographic Effects on Surface Wind in the WRF Model. J Appl Meteorol Climatol 51(2):300–316CrossRefGoogle Scholar
  32. Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds R, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Jenne R, Joseph D (1996) The ncep/ncar 40-year reanalysis project. B Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  33. Lenderink G, van Meijgaard E, Selten F (2009) Intense coastal rainfall in the netherlands in response to high sea surface temperatures: analysis of the event of August 2006 from the perspective of a changing climate. Clim Dyn 32(1):19–33CrossRefGoogle Scholar
  34. Lionello P, Malanotte-Rizzoli P, Boscolo R (eds) (2006a) Mediterranean climate variability. Elsevier, AmsterdamGoogle Scholar
  35. Lionello P, Bhend J, Buzzi A, Della-Marta PM, Krichak SO et al (2006b) Cyclones in the Mediterranean region: climatology and effects on the environment. Dev Earth Environ Sci 4:5463–5467Google Scholar
  36. Liu WT, Tang W, Xie X (2008) Wind power distribution over the ocean. Geophys Res Lett 35(L13808):6Google Scholar
  37. Lo J, Yang Z, Pielke R Sr (2008) Assessment of three dynamical climate downscaling methods using the weather research and forecasting (wrf) model. J Geophys Res 113(D09):112Google Scholar
  38. Marcos M, Tsimplis MN, Shaw AGP (2009) Sea level extremes in southern Europe. J Geophys Res 114:C01007. doi: 10.1029/2008JC004912 Google Scholar
  39. Mlawer E, Taubman S, Brown P, Iacono M, Clough S (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the long wave. J Geophys Res 102(D14):16663–16682CrossRefGoogle Scholar
  40. Monahan AH (2006) The probability distribution of sea surface wind speeds. Part I: theory and SeaWinds observations. J Clim 19(4):497–520CrossRefGoogle Scholar
  41. Pavia EG, O’Brien JJ (1986) Weibull statistics of wind speed over the ocean. J Clim Appl Meteorol 25:1324–1332CrossRefGoogle Scholar
  42. Pleim JE (2006) A simple, efficient solution of flux–profile relationships in the atmospheric surface layer. J Appl Meteorol Climatol 45:341–347CrossRefGoogle Scholar
  43. Pleim JE (2007a) A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: Model description and testing. J Appl Meteorol Climatol 46:1383–1395CrossRefGoogle Scholar
  44. Pleim JE (2007b) A combined local and nonlocal closure model for the atmospheric boundary layer. Part II: Application and evaluation in a mesoscale meteorological model. J Appl Meteorol Climatol 46:1396–1409CrossRefGoogle Scholar
  45. Pryor SC, Nielsen M, Barthelmie RJ, Mann J (2004) Can satellite sampling of offshore wind speeds realistically represent wind speed distributions? Part II: quantifying uncertainties associated with distribution fitting methods. J Appl Meteorol 43:739–750CrossRefGoogle Scholar
  46. Qian J, Seth A, Zebiak S (2003) Reinitialized versus continuous simulations for regional climate downscaling. Mon Weather Rev 131(11):2857–2874CrossRefGoogle Scholar
  47. Rockel B, Castro CL, Pielke RSA, von Storch H, Leoncini G (2008) Dynamical downscaling: assessment of model system dependent retained and added variability for two different regional climate models. J Geophys Res 113(D21):107Google Scholar
  48. Sanchez-Vidal A, Canals M, Calafat AM, Lastras G, Pedrosa-Pa`mies R et al (2012) Impacts on the deep-sea ecosystem by a severe coastal storm. PLoSONE 7(1):e30395. doi: 10.1371/journal.pone.0030395 CrossRefGoogle Scholar
  49. Skamarock WC, Klemp JB, Dudhia J, Gill DO, Baker DM, Duda MG, Huang XY, Wang W, Powers JG (2008). A description of the advanced research WRF version 3. NCAR Tech Note NCAR/TN-475 + STR, p 125Google Scholar
  50. Sotillo MG, Ratsimandresy AW, Carretero JC, Bentamy A, Valero F, González-Rouco F (2005) A high-resolution 44-year atmospheric hindcast for the mediterranean basin: contribution to the regional improvement of global reanalysis. Clim Dyn 25:219–236CrossRefGoogle Scholar
  51. Stauffer DR, Seaman NL (1990) Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I: experiments with synoptic-scale data. Mon Weather Rev 118:1250–1277CrossRefGoogle Scholar
  52. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106:7183–7192CrossRefGoogle Scholar
  53. Uppala S, Kallberg P, Simmons A, Andrae U, da Costa Bechtold V, Fiorino M, Gibson J, Haseler J, Hernandez A, Kelly G, Li X, Onogi K, Saarinen S (2005) The era-40 re-analysis. Q J R Meteorol Soc 131:2961–3012CrossRefGoogle Scholar
  54. Von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. MWR 128:3664–3673CrossRefGoogle Scholar
  55. WASA group (1998) Changing waves and storms in the northeast atlantic? BAMS 79(5):741–760CrossRefGoogle Scholar
  56. Weisse R, Feser F (2003) Evaluation of a method to reduce uncertainty in wind hindcasts performed with regional atmosphere models. Coast Eng 48:211–225CrossRefGoogle Scholar
  57. Weisse R, von Storch H, Callies U, Chrastansky A, Feser F, Grabemann I, Günther H, Pluess A, Stoye T, Tellkamp J, Winterfeldt J, Woth K (2009) Regional meteorological-marine reanalyses and climate change projections: results for Northern Europe and potential for coastal and offshore applications Bull. Am Meteorol Soc 90(6):849–860CrossRefGoogle Scholar
  58. Weisse R, von Storch H, Niemeyer HD, Knaack H (2012) Changing North Sea storm surge climate: An increasing hazard? Ocean Coast Manag 68:58–68CrossRefGoogle Scholar
  59. Winterfeldt J, Weisse R (2009) Assessment of value added for surface marine wind speed obtained from two regional climate models. Mon Weather Rev 137(9):2955–2965CrossRefGoogle Scholar
  60. Winterfeldt J, Geyer B, Weisse R (2011) Using QuikSCAT in the added value assessment of dynamically downscaled wind speed. Int J Climatol 31:1028–1039CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • M. Menendez
    • 1
  • M. García-Díez
    • 2
  • L. Fita
    • 2
  • J. Fernández
    • 2
  • F. J. Méndez
    • 1
  • J. M. Gutiérrez
    • 3
  1. 1.Environmental Hydraulics InstituteUniversidad de CantabriaSantanderSpain
  2. 2.Department of Applied Mathematics and Computer ScienceUniversidad de CantabriaSantanderSpain
  3. 3.Instituto de Física de Cantabria CSIC-UCSantanderSpain

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