Climate Dynamics

, Volume 50, Issue 11–12, pp 4455–4480 | Cite as

Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models

  • Andreina BelušićEmail author
  • Maja Telišman Prtenjak
  • Ivan Güttler
  • Nikolina Ban
  • David Leutwyler
  • Christoph Schär


Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the-art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection-parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA-Interim reanalysis, while the performance of the high-resolution simulations surpasses that of ERA-Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.


Adriatic region CORDEX Regional climate models Convection-resolving models 



This work has been supported by the ongoing Croatian Science Foundation (HrZZ) projects CARE (no. 2831) and VITCLIC (PKP-2016-06-2975).The authors would like to thank the reviewers for their suggestions, which have helped improve this paper. A primary idea for this research was established on behalf of the past HrZZ project CATURBO (no. 09/151). The work of the ETH group was supported by the Swiss National Science Foundation through the Sinergia grant CRSII2_154486 ‘crCLIM’. We want to thank Lidija Srnec and Mirta Patarčić for their contribution in performing parts of the DHMZ-RegCM42 simulations. We also thank Anika Obermann and Bodo Ahrens for providing the QuikSCAT data and to all CORDEX group members for providing useful information. We acknowledge the World Climate Research Programme’s Working Group on Regional Climate and, Working Group on Coupled Modelling, the former coordinating body of CORDEX and the responsible panel for CMIP5. We also thank the climate modelling groups (listed in Table 1 of this paper) for producing and making available their model output. We acknowledge the Earth System Grid Federation infrastructure, an international effort led by the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling and other partners in the Global Organisation for Earth System Science Portals (GOESSP). Additionally, the simulations used in this work were downloaded from the Med-CORDEX database ( ERA-Interim data for wind components were obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) MARS database. The authors acknowledge ECMWF for providing the MARS database account. The observed data used in this study were acquired from NOAA’s National Climatic Data Center (, DHMZ database and Crocontrol database.


  1. Accadia C, Zecchetto S, Lavagnini A, Speranza A (2007) Comparison of 10-m wind forecasts from a regional area model and QuikSCAT scatterometer wind observations over the Mediterranean Sea. Mon Wea Rev 135:1945–1960. doi: 10.1175/MWR3370.1 CrossRefGoogle Scholar
  2. Baklanov A, Grisogono B (2007) Atmospheric boundary layers: nature, theory and applications to environmental modelling and security. Springer, New YorkCrossRefGoogle Scholar
  3. Ban N, Schmidli J, Schär C (2014) Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J Geophys Res Atmos 119:7889–7907. doi: 10.1002/2014JD021478 CrossRefGoogle Scholar
  4. Ban N, Schmidli J, Schär C (2015) Heavy precipitation in a changing climate: does short-term summer precipitation increase faster? Geophys Res Lett 42:1165–1172. doi: 10.1002/2014GL062588 CrossRefGoogle Scholar
  5. Belušić D, Güttler I (2010) Can mesoscale models reproduce meandering motions? QJR Meteorol Soc 136:553–565. doi: 10.1002/qj.606 Google Scholar
  6. Brands S, Herrera S, Fernández J, Gutiérrez JM (2013) How well do CMIP5 earth system models simulate present climate conditions in Europe and Africa? Clim Dyn 41:803–817. doi: 10.1007/s00382-013-1742-8 CrossRefGoogle Scholar
  7. Branković Č, Güttler I, Gajić-Čapka M (2013) Evaluating climate change at the Croatian Adriatic from observations and regional climate models’ simulations. Clim Dyn 41:2353–2373. doi: 10.1007/s00382-012-1646-z CrossRefGoogle Scholar
  8. Cavaleri L, Bertotti L, Tescaro N (1996) Long term wind hindcast in the Adriatic Sea. Il nuovo cimento C 19:67–89. doi: 10.1007/BF02511834 CrossRefGoogle Scholar
  9. Christensen OB, Drews M, Christensen JH, Dethloff K, Ketelsen K, Hebestadt I, Rinke A (2006) The HIRHAM regional climate model, version 5, Tech. Rep. 06–17, Dan Meteorol Inst, Copenhagen. Accessed 21 Sep 2016
  10. Colin J, Déqué M, Radu R, Somot S (2010) Sensitivity study of heavy precipitations in Limited Area Model climate simulation: influence of the size of the domain and the use of the spectral nudging technique. Tellus A 62:591–604. doi: 10.1111/j.1600-0870.2010.00467.x CrossRefGoogle Scholar
  11. Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM., Van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, De Rosnay P, Tavolato C, Thépaut JN, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. QJR Meteorol Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  12. Di Luca A, De Elía R, Laprise R (2015) Challenges in the Queste for added value of regional climate dynamical downscaling. Curr Clim Change Rep 1:10–21. doi: 10.1007/s40641-015-0003-9 CrossRefGoogle Scholar
  13. Domínguez M, Gaertner MA, De Rosnay P, Losada T (2010) A regional climate model simulation over West Africa: parameterization tests and analysis of land surface fields. Clim Dyn 35:249–265. doi: 10.1007/s00382-010-0769-3 CrossRefGoogle Scholar
  14. Dunion JP, Landsea CW, Houston SH, Powell MD (2003) A reanalysis of the surface winds for Hurricane Donna of 1960. Mon Wea Rev 131:1992–2011. doi: 10.1175/1520-0493(2003)131<1992:AROTSW>2.0.CO;2 CrossRefGoogle Scholar
  15. Feser F, Rockel B, Von Storch H, Winterfeldt J, Zahn M (2011) Regional climate models add value to global model data: a review and selected examples. B Am Meteorol Soc 92:1181–1192. doi: 10.1175/2011BAMS3061.1 CrossRefGoogle Scholar
  16. Gibbons JD, Chakraborti S (2011) Nonparametric statistical inference, 5th edn. Chapman & Hall/CRC Press, Taylor & Francis Group, Boca Raton, FLGoogle Scholar
  17. Giorgi F, Gutowski W Jr (2015) Regional dynamical downscaling and the CORDEX initiative. Annu Rev Env Resour 40:467–490. doi: 10.1146/annurev-environ-102014-021217 CrossRefGoogle Scholar
  18. Giorgi F, Coppola E, Solmon F, Mariotti L, Sylla MB, Bi X, Elguindi N, Diro GT, Nair V, Giuliani G, Cozzini S, Güttler I, O’Brien TA, Tawfik AB, Shalaby A, Zakey AS, Steiner AL, Stordal F, Sloan LC, Branković Č (2012) RegCM4: model description and preliminary tests over multiple CORDEX domains. Clim Res 52:7–29. doi: 10.3354/cr01018 CrossRefGoogle Scholar
  19. Giorgi F, Csaba T, Coppola E, Ban N, Schär C, Somot S (2016) Enhanced summer convective rainfall at Alpine high elevations in response to climate warming. Nat Geosci. doi: 10.1038/ngeo2761 Google Scholar
  20. Gómez-Navarro JJ, Raible CC, Dierer S (2015) Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain. Geosci Model Dev 8:3349–3363. doi: 10.5194/gmd-8-3349-2015 CrossRefGoogle Scholar
  21. Grisogono B, Belušić D (2009) A review of recent advances in understanding the meso- and microscale properties of the severe Bora wind. Tellus A 61:1–16. doi: 10.1111/j.1600-0870.2008.00369.x CrossRefGoogle Scholar
  22. Güttler I, Stepanov I, Branković Č, Nikulin G, Colin J (2015) Impact of Horizontal resolution on precipitation in complex orography simulated by the regional climate model RCA3. Mon Wea Rev 143:3610–3627. doi: 10.1175/MWR-D-14-00302.1 CrossRefGoogle Scholar
  23. Halpern D (1979) Surface wind measurements and low-level cloud motion vectors near the Inter-tropical Convergence Zone in the central Pacific Ocean from November 1977 to March 1978. Mon Wea Rev 107:1525–1534CrossRefGoogle Scholar
  24. Heimann D (2001) A model-based wind climatology of the eastern Adriatic coast. Meteorol Z 10:5–16. doi: 10.1127/0941-2948/2001/0010-0005 CrossRefGoogle Scholar
  25. Herrmann M, Somot S, Calmanti S, Dubois C, Sevault F (2011) Representation of spatial and temporal variability of daily wind speed and of intense wind events over the Mediterranean Sea using dynamical downscaling: impact of the regional climate model configuration. Nat Hazards Earth Sys Sci 11:1983–2001. doi: 10.5194/nhess-11-1983-2011 CrossRefGoogle Scholar
  26. Horvath K, Lin Y-L, Ivančan-Picek B (2008) Classification of cyclone tracks over Apennines and the Adriatic Sea. Mon Wea Rev 136:2210–2227. doi: 10.1175/2007MWR2231.1 CrossRefGoogle Scholar
  27. Horvath K, Bajić A, Ivatek-Šahdan S (2011) Dynamical Downscaling of wind speed in complex terrain prone to bora-type flows. J Appl Meteorol Clim 50:1676–1691. doi: 10.1175/2011JAMC2638.1 CrossRefGoogle Scholar
  28. Jacob D, Petersen J, Eggert B, Alias A, Christensen OB, Bouwer L, Braun A, Colette A, Déqué M, Georgievski G, Georgopoulou E, Gobiet A, Menut L, Nikulin G, Haensler A, Hempelmann N, Jones C, Keuler K, Kovats S, Kröner N, Kotlarski S, Kriegsmann A, Martin E, Van Meijgaard E, Moseley C, Pfeifer S, Preuschmann S, Radermacher C, Radtke K, Rechid D, Rounseve llM, Samuelsson P, Somot S, Soussana JF, Teichmann C, Valentini R, Vautard R, Weber B, Yiou P (2013) EURO-CORDEX: new high-resolution climate change projections for European impact research. Regl Environ Change 14:563–578. doi: 10.1007/s10113-013-0499-2 CrossRefGoogle Scholar
  29. Kotlarski S, Keuler K, Christensen OB, Colette A, Déqué M, Gobiet A, Goergen K, Jacob D, Lüthi D, Van Meijgaard E, Nikulin G, Schär C, Teichmann C, Vautard R, Warrach-Sagi K, Wulfmeyer V (2014) Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble. Geosci Model Dev 7:1297–1333. doi: 10.5194/gmd-7-1297-2014 CrossRefGoogle Scholar
  30. Leutwyler D, Fuhrer O, Lapillonne X, Lüthi D, Schär C (2016) Towards European-scale convection-resolving climate simulations. Geosci Model Dev 9:3393–3412. doi: 10.5194/gmd-2016-119 Google Scholar
  31. Leutwyler D, Lüthi D, Ban N, Fuhrer O, Schär C (2017) Evaluation of the convection-resolving climate modeling approach on continental scales. J Geophys Res Atmos 122:5237–5258. doi: 10.1002/2016JD026013
  32. Ludwig FL, Horel J, Whiteman CD (2004) Using EOF analysis to identify important surface wind patterns in mountain valleys. J Appl Meteorol 43:969–983. doi: 10.1175/1520-0450 CrossRefGoogle Scholar
  33. Mayer S, Fox Maule C, Sobolowski S, Christensen OB, Sorup HJD, Sunyer MA, Arnbjerg-Nielsen K, Barstad I (2015) Identifying added value in high-resolution climate simulations over Scandinavia. Tellus A 67:1–18. doi: 10.3402/tellusa.v67.24941 CrossRefGoogle Scholar
  34. Menendez M, García-Díez M, Fita L, Fernández J, Méndez FJ, Gutiérrez JM (2014) High-resolution sea wind hindcasts over the Mediterranean area. Clim Dyn 42:1857–1872. doi: 10.1007/s00382-013-1912-8 CrossRefGoogle Scholar
  35. Obermann A, Bastin S, Belamari S, Conte D, Gaertner MA, Li L, Ahrens B (2016) Mistral and Tramontane wind speed and wind direction patterns in regional climate simulation. Clim Dyn 47:1–18. doi: 10.1007/s00382-016-3053-3 CrossRefGoogle Scholar
  36. Pasarić M, Orlić M (2004) Meteorological forcing of the Adriatic: present vs. projected climate conditions. Geofizika 21:69–87Google Scholar
  37. Pašičko R, Branković Č, Šimić Z (2012) Assessment of climate change impacts on energy generation from renewable sources in Croatia. Renew Energy 46:224–231. doi: 10.1016/j.renene.2012.03.029 CrossRefGoogle Scholar
  38. Peacock JA (1983) Two-dimensional goodness-of-fit testing in astronomy. Mon Not R Astron Soc 202:615–627. doi: 10.1093/mnras/202.3.615 CrossRefGoogle Scholar
  39. Perkins SE, Pitman AJ, Holbrook NJ, McAneney J (2007) Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. J Clim 20:4356–4376. doi: 10.1175/JCLI4253.1 CrossRefGoogle Scholar
  40. Perry KL (2001) Sea winds on QuikSCAT level 3 daily, gridded Ocean wind vectors (JPL Sea Winds Project) version 1.1. (JPL Document D-20335). Jet Propulsion, Pasadena, CAGoogle Scholar
  41. Pielke RA (2002) Mesoscale meteorological modeling. Academic, USAGoogle Scholar
  42. Poje D (1992) Wind persistence in Croatia. Int J Climatol 12:569–586. doi: 10.1002/joc.3370120604 CrossRefGoogle Scholar
  43. Powell MD, Houston SH, Ares I (1995) Real-time damage assessment in hurricanes. Preprints, 21st Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., pp 500–502Google Scholar
  44. Prein AF, Langhans W, Fosser G, Ferrone A, Ban N, Goergen K, Keller M, Tlle M, Gutjahr O, Feser F, Brisson E, Kollet S, Schmidli J, van Lipzig NPM, Leung R (2015) A review on regional convection-permitting climate modeling: demonstrations, prospects, and challenges. Rev Geophys 53:323–361. doi: 10.1002/2014RG000475 CrossRefGoogle Scholar
  45. Prein AF, Gobiet A, Truhetz H, Keuler K, Goergen K, Teichmann C, Fox Maule C, Van Meijgaard E, Déqué M, Nikulin G, Vautard R, Colette A, Kjellström E, Jacob D (2016) Precipitation in the EURO-CORDEX 0.11° and 0.44° simulations: high resolution, high benefits? Clim Dyn 46:383–412. doi: 10.1007/s00382-015-2589-y CrossRefGoogle Scholar
  46. Prtenjak MT, Tomažić I, Kavčič I, Đivanović S (2010a) Characteristics of shallow thermally driven flow in the complex topography of the south-eastern Adriatic. Ann Geophys 28:1905–1922. doi: 10.5194/angeo-28-1905-2010 CrossRefGoogle Scholar
  47. Prtenjak MT, Viher M, Jurković J (2010b) Sea-land breeze development during a summer Bora event along the north-eastern Adriatic coast. QJR Meteorol Soc 136:1554–1571. doi: 10.1002/qj.649 CrossRefGoogle Scholar
  48. Prtenjak MT, Horvat I, Tomažić I, Kvakić M, Viher M, Grisogono B (2015) Impact of mesoscale meteorological processes on anomalous radar propagation conditions over the northern Adriatic area. J Geophys Res 120:8759–8782. doi: 10.1002/2014JD022626 Google Scholar
  49. Pryor SC, Nikulin G, Jones C (2012) Influence of spatial resolution on regional climate model derived wind climates. J Geophys Res 117:D03117. doi: 10.1029/2011JD016822 Google Scholar
  50. Ranjha R, Tjernström M, Svensson G, Semedo A (2016) Modelling coastal low-level wind-jets: does horizontal resolution matter? Meteorol Atmos Phys 128:263–278. doi: 10.1007/s00703-015-0413-1 CrossRefGoogle Scholar
  51. Ray RD, Poulose S (2005) Terdiurnal surface–pressure oscillations over the Continental United States. Mon Wea Rev 133:2526–2534. doi: 10.1175/MWR2988.1 CrossRefGoogle Scholar
  52. Rockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM (CCLM). Meteorol Z 17:347–348. doi: 10.1127/0941-2948/2008/0309 CrossRefGoogle Scholar
  53. Rummukainen M (2010) State-of-the-art with regional climate models. WIREs Clim Change 1:82–96. doi: 10.1002/wcc.8 CrossRefGoogle Scholar
  54. Rummukainen M (2016) Added value in regional climate modeling. WIREs Clim Change 7:145–459. doi: 10.1002/wcc.378 CrossRefGoogle Scholar
  55. Ruti PM, Marullo S, D’ Ortenzio F, Tremant M (2008) Comparison of analysed and measured wind speeds in the perspective of oceanic simulations over the Mediterranean basin: analyses, QuikSCAT and buoy data. J Mar Syst 70:33–48. doi: 10.1016/j.jmarsys.2007.02.02640 CrossRefGoogle Scholar
  56. Ruti PM, Somot S, Giorgi F, Dubois C, Flaounas E, Obermann A, Dell’Aquila A, Pisacane G, Harzallah A, Lombardi E, Ahrens B, Akhtar N, Alias A, Arsouze T, Aznar R, Bastin S, Bartholy J, Béranger K, Beuvier J, Bouffies-Cloché S, Brauch J, Cabos W, Calmanti S, Calvet J, Carillo A, Conte D, Coppola E, Djurdjevic V, Drobinski P, Elizalde-Arellano A, Gaertner M, Galàn P, Gallardo C, Gualdi S, Goncalves M, Jorba O, Jordà G, L’Heveder B, Lebeaupin-Brossier C, Li L, Liguori G, Lionello P, Maciàs D, Nabat P, Önol B, Raikovic B, Ramage K, Sevault F, Sannino G, Struglia MV, Sanna A, Torma C, Vervatis V (2016) Med-CORDEX initiative for Mediterranean climate studies. B Am Meteorol Soc 97:1187–1208.  10.1175/BAMS-D-14-00176.1 CrossRefGoogle Scholar
  57. Samuelsson P, Jones CG, Willén U, Ullerstig A, Gollvik S, Hansson U, Jansson C, Kjellström E, Nikulin G, Wyser K (2011) The Rossby Centre regional climate model RCA3: model description and performance. Tellus A 63:4–23. doi: 10.1111/j.1600-0870.2010.00478.x CrossRefGoogle Scholar
  58. Skamarock W, Klemp J, Dudhia J, Gill D, Barker D, Duda M, Huang X, Wang W, Powers J (2008) A description of the advanced research WRF version 3. Technical Report, NCAR. Accessed 21 Sep 2016
  59. Smith A, Lott N, Vose R (2011) The integrated surface database: recent developments and partnerships. B Am Meteorol Soc 92:704–708. doi: 10.1175/2011BAMS3015.1 CrossRefGoogle Scholar
  60. Somot S, Ruti PM; The MedCORDEX team (2011) The Med-CORDEX initiative: towards fully coupled Regional Climate System Models to study the Mediterranean climate variability, change and impact. Accessed 9 Nov 2016
  61. 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 25:219–236. doi: 10.1007/s00382-005-0030-7 CrossRefGoogle Scholar
  62. Stiperski I, Ivančan-Picek B, Grubišić V, Bajić A (2012) Complex Bora flow in the lee of Southern Velebit. QJR Meteorol Soc 138:1490–1506. doi: 10.1002/qj.1901 CrossRefGoogle Scholar
  63. Tang W, Liu WT, Stiles BW (2004) Evaluation of high-resolution ocean surface vector winds measured by QuikSCAT scatterometer in coastal regions. IEEE Trans Geosci Remote Sens 42:1762–1769. doi: 10.1109/TGRS.2004.831685 CrossRefGoogle Scholar
  64. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos 106:7183–7192. doi: 10.1029/2000JD900719 CrossRefGoogle Scholar
  65. Torma C, Giorgi F, Coppola E (2015) Added value of regional climate modeling over areas characterized by complex terrain- Precipitation over the Alps. J Geophys Res Atmos 120:3957–3972. doi: 10.1002/2014JD022781 CrossRefGoogle Scholar
  66. Turuncoglu UU, Sannino G (2016) Validation of newly designed regional earth system model (RegESM) for Mediterranean Basin. Clim Dyn 47:1–29. doi: 10.1007/s00382-016-3241-1 CrossRefGoogle Scholar
  67. Van Meijgaard E, Van Ulft LH, Van De Berg WJ, Bosvelt FC, Van Den Hurk BJJM, Lenderink G, Siebesma AP (2008) The KNMI regional atmospheric model RACMO version 2.1, technical report 302. Technical report, De Bilt KNMI, The Netherlands. Accessed 21 Sep 2016
  68. Vautard R, Gobiet A, Jacob D, Belda M, Colette A, Déqué M, Fernández J, García-Díez M, Goergen K, Güttler I, Halenka T, Karacostas T, Katragkou E, Keuler K, Kotlarski S, Mayer S, Van Meijgaard E, Nikulin G, Patarčić M, Scinocca J, Sobolowski S, Suklitsch M, Teichmann C, Warrach-Sagi K, Wulfmeyer V, Yiou P (2013) The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project. Clim Dyn 41:2555–2575. doi: 10.1007/s00382-013-1714-z CrossRefGoogle Scholar
  69. Večenaj Ž, Belušić D, Grisogono B (2010) Characteristics of the near-surface turbulence during a Bora event. Ann Geophys 28:155–163CrossRefGoogle Scholar
  70. von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Wea Rev 128:3664–3673. doi: 10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2 Google Scholar
  71. Weisman M, Skamarock W, Klemp J (1997) The resolution dependence of explicitly modeled convective systems. Mon Wea Rev 125:527–548CrossRefGoogle Scholar
  72. Winterfeldt J, Weisse R (2009) Assessment of value added for surface marine wind speed obtained from two regional climate models. Mon Wea Rev 137:2955–2965. doi: 10.1175/2009MWR2704.1 CrossRefGoogle Scholar
  73. Winterfeldt J, Geyer B, Weisse R (2011) Using QuikSCAT in the added value assessment of dynamically downscaled wind speed. Int J Climatol 31:1028–1039. doi: 10.1002/joc.2105 CrossRefGoogle Scholar
  74. Žagar N, Žagar M, Cedilnik J, Gregorič G, Rakovec J (2006) Validation of mesoscale low-level winds obtained by dynamical downscaling of ERA40 over complex terrain. Tellus A 58:445–455. doi: 10.1111/j.1600-0870.2006.00186.x CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Andrija Mohorovičić Geophysical Institute, Department of Geophysics, Faculty of ScienceUniversity of ZagrebZagrebCroatia
  2. 2.Meteorological and Hydrological Service of Croatia (DHMZ)ZagrebCroatia
  3. 3.Institute for Atmospheric and Climate ScienceETH ZürichZürichSwitzerland

Personalised recommendations