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

Abstract

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.

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References

  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

    Article  Google Scholar 

  2. Baklanov A, Grisogono B (2007) Atmospheric boundary layers: nature, theory and applications to environmental modelling and security. Springer, New York

    Book  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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. http://www.dmi.dk/dmi/tr06-17.pdf. 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

  16. Gibbons JD, Chakraborti S (2011) Nonparametric statistical inference, 5th edn. Chapman & Hall/CRC Press, Taylor & Francis Group, Boca Raton, FL

    Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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 107:1525–1534

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

  36. Pasarić M, Orlić M (2004) Meteorological forcing of the Adriatic: present vs. projected climate conditions. Geofizika 21:69–87

    Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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, CA

    Google Scholar 

  41. Pielke RA (2002) Mesoscale meteorological modeling. Academic, USA

    Google Scholar 

  42. Poje D (1992) Wind persistence in Croatia. Int J Climatol 12:569–586. doi:10.1002/joc.3370120604

    Article  Google 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 500–502

  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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

  53. Rummukainen M (2010) State-of-the-art with regional climate models. WIREs Clim Change 1:82–96. doi:10.1002/wcc.8

    Article  Google Scholar 

  54. Rummukainen M (2016) Added value in regional climate modeling. WIREs Clim Change 7:145–459. doi:10.1002/wcc.378

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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. http://opensky.ucar.edu/islandora/object/technotes:500. 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

    Article  Google 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. https://www.medcordex.eu/somot_MedCORDEX_WCRP2011_Denver_oct2011.pdf. 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google 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. http://bibliotheek.knmi.nl/knmipubTR/TR302.pdf. 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

    Article  Google Scholar 

  69. Večenaj Ž, Belušić D, Grisogono B (2010) Characteristics of the near-surface turbulence during a Bora event. Ann Geophys 28:155–163

    Article  Google 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 125:527–548

    Article  Google 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

    Article  Google 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

    Article  Google 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

    Article  Google Scholar 

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Acknowledgements

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 (http://www.medcordex.eu). 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 (http://www.ncdc.noaa.gov), DHMZ database and Crocontrol database.

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Belušić, A., Prtenjak, M.T., Güttler, I. et al. Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models. Clim Dyn 50, 4455–4480 (2018). https://doi.org/10.1007/s00382-017-3885-5

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Keywords

  • Adriatic region
  • CORDEX
  • Regional climate models
  • Convection-resolving models