Skip to main content
Have a personal or library account? Click to login
On the diurnal cycle and variability of winds in the lower planetary boundary layer: evaluation of regional reanalyses and hindcasts Cover

On the diurnal cycle and variability of winds in the lower planetary boundary layer: evaluation of regional reanalyses and hindcasts

Open Access
|Jan 2021

References

  1. Baldauf, M. , Seifert, A. , Förstner, J. , Majewski, D. , Raschendorfer, M. and co-authors. 2011. Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities. Mon. Weather Rev. 139 , 38873905. doi:10.1175/MWR-D-10-05013.1
  2. Barthlott, C. , Kalthoff, N. and Fiedler, F. 2003. Influence of high-frequency radiation on turbulence measurements on a 200 m tower. Meteorol. Z. 12 , 6771. doi:10.1127/0941-2948/2003/0012-0067
  3. Bengtsson, L. , Andrae, U. , Aspelien, T. , Batrak, Y. , Calvo, J. and co-authors. 2017. The HARMONIE–AROME model configuration in the ALADIN–HIRLAM NWP system. Mon. Weather Rev. 145 , 19191935. doi:10.1175/MWR-D-16-0417.1
  4. Best, M. J. , Pryor, M. , Clark, D. B. , Rooney, G. G. , Essery, R. L. H. and co-authors. 2011. The joint UK land environment simulator (JULES), model description – Part 1: energy and water fluxes. Geosci. Model Dev. 4 , 677699. doi:10.5194/gmd-4-677-2011
  5. Beyrich, F. , Herzog, H.-J. and Neisser, J. 2002. The LITFASS project of DWD and the LITFASS-98 experiment: the project strategy and the experimental setup. Theor. Appl. Climatol. 73 , 318. doi:10.1007/s00704-002-0690-8
  6. Bianco, L. , Djalalova, I. V. , Wilczak, J. M. , Cline, J. , Calvert, S. and co-authors. 2016. A wind energy ramp tool and metric for measuring the skill of numerical weather prediction models. Weather Forecast. 31 , 11371156. doi:10.1175/WAF-D-15-0144.1
  7. Bollmeyer, C. , Keller, J. D. , Ohlwein, C. , Wahl, S. , Crewell, S. and co-authors. 2015. Towards a high-resolution regional reanalysis for the European CORDEX domain. Q. J. R. Meteorol. Soc. 141 , 115. 2486. doi:10.1002/qj.2486
  8. Borsche, M. , Kaiser-Weiss, A. K. and Kaspar, F. 2016. Wind speed variability between 10 and 116m height from the regional reanalysis COSMO-REA6 compared to wind mast measurements over Northern Germany and the Netherlands. Adv. Sci. Res. 13 , 151161. doi:10.5194/asr-13-151-2016
  9. Brümmer, B. , Lange, I. and Konow, H. 2012. Atmospheric boundary layer measurements at the 280 m high Hamburg weather mast 1995-2011: mean annual and diurnal cycles. Meteorol. Z. 21 , 319335. doi:10.1127/0941-2948/2012/0338
  10. Brümmer, B. and Schultze, M. 2015. Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast. Meteorol. Z. 24 , 481494. doi:10.1127/metz/2015/0669
  11. Bubnov, R. , Hello, G. , Bénard, P. and Geleyn, J.-F. 1995. Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following coordinate in the framework of the ARPEGE/ALADIN NWP system. Mon. Weather Rev. 123 , 515535. doi:10.1175/1520-0493(1995)123<;0515:IOTFEE>2.0.CO;2
  12. Cannon, D. , Brayshaw, D. , Methven, J. , Coker, P. and Lenaghan, D. 2015. Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain. Renew. Energy 75 , 767778. doi:10.1016/j.renene.2014.10.024
  13. Clark, D. B. , Mercado, L. M. , Sitch, S. , Jones, C. D. , Gedney, N. and co-authors. 2011. The joint UK land environment simulator (JULES), model description – Part 2: carbon fluxes and vegetation dynamics. Geosci. Model Dev. 4 , 701722. doi:10.5194/gmd-4-701-2011
  14. Cuxart, J. , Bougeault, P. and Redelsperger, J.-L. 2000. A turbulence scheme allowing for mesoscale and large-eddy simulations. Q. J. R. Meteorol. Soc. 126 , 130. doi:10.1002/qj.49712656202
  15. Cuxart, J. , Holtslag, A. A. M. , Beare, R. J. , Bazile, E. , Beljaars, A. and co-authors. 2006. Single-column model intercomparison for a stably stratified atmospheric boundary layer. Boundary-Layer Meteorol. 118 , 273303. doi:10.1007/s10546-005-3780-1
  16. Dahlgren, P. , Landelius, T. , Kållberg, P. and Gollvik, S. 2016. A high-resolution regional reanalysis for Europe. Part 1: three-dimensional reanalysis with the regional HIgh-Resolution Limited-Area Model (HIRLAM). Q. J. R. Meteorol. Soc. 142 , 21192131. doi:10.1002/qj.2807
  17. de Rooy, W. and de Vries, H. 2017. Harmonie Verification and Evaluation . Technical Report. Availabe from HIRLAM-A Programme c/o Onvlee, KNMI, P.P. Box. 201, 3730 AE. 79 pp.
  18. Dee, D. P. , Uppala, S. M. , Simmons, A. J. , Berrisford, P. , Poli, P. and co-authors. 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137 , 553597. doi:10.1002/qj.828
  19. Dickinson, R. E. 1984. Modeling evapotranspiration for three-dimensional global climate models. Climate Processes and Climate Sensitivity 58–72. doi:10.1029/gm029p0058
  20. Drechsel, S. , Mayr, G. J. , Messner, J. W. , Stauffer, R. , Drechsel, S. and co-authors. 2012. Wind speeds at heights crucial for wind energy: measurements and verification of forecasts. J. Appl. Meteorol. Climatol. 51 , 16021617. doi:10.1175/JAMC-D-11-0247.1
  21. Dürr, B. 2004. The greenhouse effect in the Alps - by models and observations. Ph.D. thesis.
  22. Emeis, S. , Münkel, C. , Vogt, S. , Müller, W. J. and Schäfer, K. 2004. Atmospheric boundary-layer structure from simultaneous SODAR, RASS, and ceilometer measurements. Atmos. Environ. 38 , 273286. 054. doi:10.1016/j.atmosenv.2003.09.054
  23. Frank, C. , Pospichal, B. , Wahl, S. , Keller, J. D. , Hense, A. and co-authors. 2020. The added value of high resolution regional reanalyses for wind power applications. Renew. Energy 148 , 10941109. doi:10.1016/j.renene.2019.09.138
  24. Frank, C. W. , Wahl, S. , Keller, J. D. , Pospichal, B. , Hense, A. and co-authors. 2018. Bias correction of a novel European reanalysis data set for solar energy applications. Sol. Energy 164 , 1224. doi:10.1016/j.solener.2018.02.012
  25. Gelaro, R. , McCarty, W. , Suárez, M. J. , Todling, R. , Molod, A. and co-authors. 2017. The modern-era retrospective analysis for research and applications, Version 2 (MERRA-2). J. Clim. 30 , 54195454. doi:10.1175/JCLI-D-16-0758.1
  26. Geyer, B. 2014. High-resolution atmospheric reconstruction for Europe 1948–2012: coastDat2. Earth Syst. Sci. Data 6 , 147164. doi:10.5194/essd-6-147-2014
  27. Geyer, B. 2017. coastDat-3_COSMO-CLM_ERAi. World Data Center for Climate (WDCC) at DKRZ, last access at Aug 2018. Online at: http://cera-www.dkrz.de/WDCC/ui/Compact. jsp?acronym=coastDat-3{\_}COSMO-CLM{\_}ERAi.
  28. González-Aparicio, I. , Monforti, F. , Volker, P. , Zucker, A. , Careri, F. and co-authors. 2017. Simulating European wind power generation applying statistical downscaling to reanalysis data. Appl. Energy 199 , 155168. doi:10.1016/j.apenergy.2017.04.066
  29. Gupta, H. V. , Kling, H. , Yilmaz, K. K. and Martinez, G. F. 2009. Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modelling. J. Hydrol. 377 , 8091. doi:10.1016/j.jhydrol.2009.08.003
  30. Heide, D. , Greiner, M. , von Bremen, L. and Hoffmann, C. 2011. Reduced storage and balancing needs in a fully renewable European power system with excess wind and solar power generation. Renew. Energy 36 , 25152523. doi:10.1016/j.renene.2011.02.009
  31. Helbig, N. , Löwe, H. , Lehning, M. , Helbig, N. , Löwe, H. and co-authors. 2009. Radiosity approach for the shortwave surface radiation balance in complex terrain. J. Atmos. Sci. 66 , 29002912. doi:10.1175/2009JAS2940.1
  32. Hong, S.-Y. and Chang, E.-C. 2012. Spectral nudging sensitivity experiments in a regional climate model. Asia-Pacific J. Atmos. Sci. 48 , 345355. doi:10.1007/s13143-012-0033-3
  33. Hoyer, S. and Hamman, J. J. 2017. xarray: N-D labeled arrays and datasets in Python. J. Open Res. Softw. 5 . doi:10.5334/jors.148
  34. Jacob, M. 2013. Beeinflussung Von Windmessungen an Einem Rohrmast Durch Die Maststruktur (Bachelor Thesis). Technical Report, Department MIN, University of Hamburg, 35 pp.
  35. James, P. M. 2007. An objective classification method for Hess and Brezowsky Grosswetterlagen over. Theor. Appl. Climatol. 88 , 1742. doi:10.1007/s00704-006-0239-3
  36. Kaiser-Weiss, A. K. , Kaspar, F. , Heene, V. , Borsche, M. , Tan, D. G. H. and co-authors. 2015. Comparison of regional and global reanalysis near-surface winds with station observations over Germany. Adv. Sci. Res. 12 , 187198. doi:10.5194/asr-12-187-2015
  37. Kaldemeyer, C. , Boysen, C. and Tuschy, I. 2016. Compressed air energy storage in the German energy system – status quo & perspectives. Energy Procedia 99 , 298313. doi:10.1016/j.egypro.2016.10.120
  38. Kalthoff, N. and Vogel, B. 1992. Counter-current and channelling effect under stable stratification in the area of Karlsruhe. Theor. Appl. Climatol. 45 , 113126. doi:10.1007/BF00866400
  39. Konow, H. M. 2015. Tall wind profiles in heterogeneous terrain. Ph.D. thesis.
  40. Landelius, T. , Dahlgren, P. , Gollvik, S. , Jansson, A. and Olsson, E. 2016. A high-resolution regional reanalysis for Europe. Part 2: 2D analysis of surface temperature, precipitation and wind. Q. J. R. Meteorol. Soc. 142 , 21322142. doi:10.1002/qj.2813
  41. Li, D. , von Storch, H. and Geyer, B. 2016. Testing reanalyses in constraining dynamical downscaling. J. Meteorol. Soc. Jpn. 94A , 4768. doi:10.2151/jmsj.2015-044
  42. Lorenc, A. C. and Rawlins, F. 2005. Why does 4D-Var beat 3D-Var? Q. J. R. Meteorol. Soc. 131 , 32473257. doi:10.1256/qj.05.85
  43. Mohan, M. and Siddiqui, T. 1998. Analysis of various schemes for the estimation of atmospheric stability classification. Atmos. Environ. 32 , 37753781. doi:10.1016/S1352-2310(98)00109-5
  44. Monin, A. and Obukhov, 1954. Basic laws of turbulent mixing in the surface layer of the atmosphere. Contrib. Geophys. Inst. Acad. Sci. USSR 151, 163–187.
  45. Neisser, J. , Adam, W. , Beyrich, F. , Leiterer, U. and Steinhagen, H. 2002. Atmospheric boundary layer monitoring at the Meteorological Observatory Lindenberg as a part of the “Lindenberg Column”: facilities and selected results. Meteorol. Z. 11 , 241253. doi:10.1127/0941-2948/2002/0011-0241
  46. Niermann, D. , Borsche, M. , Kaiser-Weiss, A. and Kaspar, F. 2019. Evaluating renewable energy relevant parameters of COSMO-REA6 by comparing against station observations, satellites and other reanalyses. Meteorol. Z. 28 , 347360. doi:10.1127/metz/2019/0945
  47. Noilhan, J. , Planton, S. , Noilhan, J. and Planton, S. 1989. A simple parameterization of land surface processes for meteorological models. Mon. Weather Rev. 117 , 536549. doi:10.1175/1520-0493(1989)117<;0536:ASPOLS>2.0.CO;2
  48. Pfenninger, S. and Staffell, I. 2016. Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy 114 , 12511265. 2016.08.060. doi:10.1016/j.energy.2016.08.060
  49. Rabin, J. , Delon, J. and Gousseau, Y. 2008. Circular earth mover’s distance for the comparison of local features, In: 2008 19th International Conference on Pattern Recognition , IEEE, Tampa, Florida, 1–4,
  50. Randles, C. A. , Da Silva, A. M. , Buchard, V. , Colarco, P. R. , Darmenov, A. and co-authors. 2017. The MERRA-2 aerosol reanalysis, 1980 - onward, Part I: system description and data assimilation evaluation. J. Clim. 30 , 68236850. 1175/JCLI-D-16-0609.1. doi:10.1175/JCLI-D-16-0609.1
  51. Rawlins, F. , Ballard, S. P. , Bovis, K. J. , Clayton, A. M. , Li, D. and co-authors. 2007. The Met Office global four-dimensional variational data assimilation scheme. Q. J. R. Meteorol. Soc. 133 , 347362. doi:10.1002/qj.32
  52. Rienecker, M. M. , Suarez, M. J. , Gelaro, R. , Todling, R. , Bacmeister, J. and co-authors. 2011. MERRA: NASA’s modern-era retrospective analysis for research and applications. J. Clim. 24 , 36243648. doi:10.1175/JCLI-D-11-00015.1
  53. Schraff, C. and Hess, R. 2003. A Description of the Non-Hydrostatic Regional Model LM - Part III: Data Assimilation. Technical Report, Deutscher Wetterdienst, Offenbach, Germany.
  54. Schubert-Frisius, M. , Feser, F. , von Storch, H. and Rast, S. 2017. Optimal spectral nudging for global dynamic downscaling. Mon. Weather Rev. 145 , 909927. doi:10.1175/MWR-D-16-0036.1
  55. Sevlian, R. and Rajagopal, R. 2013. Detection and statistics of wind power ramps. IEEE Trans. Power Syst. 28 , 36103620. doi:10.1109/TPWRS.2013.2266378
  56. Sharp, E. , Dodds, P. , Barrett, M. and Spataru, C. 2015. Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information. Renew. Energy 77 , 527538. doi:10.1016/j.renene.2014.12.025
  57. Staffell, I. and Pfenninger, S. 2016. Using bias-corrected reanalysis to simulate current and future wind power output. Energy 114 , 12241239. doi:10.1016/j.energy.2016.08.068
  58. Stull, R. B. 1988. An Introduction to Boundary Layer Meteorology . Springer, Dordrecht, 670 pp.
  59. Tammelin, B. , Vihma, T. , Atlaskin, E. , Badger, J. , Fortelius, C. and co-authors. 2011. Production of the Finnish Wind Atlas. Wind Energ. 16 , 1935. doi:10.1002/we.517
  60. Unden, P. 2018. Uncertainties in Ensembles of Regional Reanalyses (UERRA) - Final Report. Technical Report, SVERIGES METEOROLOGISKA OCH HYDROLOGISKA INSTITUT.
  61. Urraca, R. , Huld, T. , Gracia-Amillo, A. , Martinez-de Pison, F. J. , Kaspar, F. and co-authors. 2018. Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data. Sol. Energy 164 , 339354. doi:10.1016/j.solener.2018.02.059
  62. Van de Wiel, B. J. H. , Moene, A. F. , Steeneveld, G. J. , Baas, P. , Bosveld, F. C. and co-authors. 2010. A conceptual view on inertial oscillations and nocturnal low-level jets. J. Atmos. Sci. 67 , 26792689. doi:10.1175/2010JAS3289.1
  63. Van Ulden, A. P. and Wieringa, J. 1996. Atmospheric boundary layer research at Cabauw. Boundary-Layer Meteorol. 78 , 3969. doi:10.1007/BF00122486
  64. Verkaik, J. W. and Holtslag, A. A. M. 2007. Wind profiles, momentum fluxes and roughness lengths at Cabauw revisited. Boundary-Layer Meteorol. 122 , 701719. doi:10.1007/s10546-006-9121-1
  65. von Storch, H. , Langenberg, H. , Feser, F. , von Storch, H. , Langenberg, H. and co-authors. 2000. A spectral nudging technique for dynamical downscaling purposes. Mon. Weather Rev. 128 , 36643673. doi:10.1175/1520-0493(2000)128<;3664:ASNTFD>2.0.CO;2
  66. Walters, D. , Boutle, I. , Brooks, M. , Melvin, T. , Stratton, R. and co-authors. 2017. The met office unified model global atmosphere 6.0/6.1 and jules global land 6.0/6.1 configurations. Geosci. Model Dev. 10 , 14871520. doi:10.5194/gmd-10-1487-2017
  67. Wenzel, A. , Kalthoff, N. and Horlacher, V. 1997. On the profiles of wind velocity in the roughness sublayer above a coniferous forest. Boundary Layer Meteorol. 84 , 219230. 1000444911103. doi:10.1023/A:1000444911103
  68. Wohland, J. , Reyers, M. , Märker, C. and Witthaut, D. 2018. Natural wind variability triggered drop in German redispatch volume and costs from 2015 to 2016. PLoS One. 13 , e0190707. doi:10.1371/journal.pone.0190707
  69. Wood, N. , Staniforth, A. , White, A. , Allen, T. , Diamantakis, M. and co-authors. 2014. An inherently mass-conserving semi-implicit semi-Lagrangian discretization of the deep-atmosphere global non-hydrostatic equations. Q. J. R. Meteorol. Soc. 140 , 15051520. doi:10.1002/qj.2235
  70. Yang, Q. , Berg, L. K. , Pekour, M. , Fast, J. D. , Newsom, R. K. and co-authors. 2013. Evaluation of WRF-predicted near-hub-height winds and ramp events over a Pacific Northwest site with complex terrain. J. Appl. Meteorol. Climatol. 52 , 17531763. doi:10.1175/JAMC-D-12-0267.1
  71. Yang, Y. , Uddstrom, M. and Duncan, M. 2011. Effects of short spin-up periods on soil moisture simulation and the causes over New Zealand. J. Geophys. Res. 116 .
  72. Žagar, M. and Rakovec, J. 1999. Small-scale surface wind prediction using dynamic adaptation. Tellus A 51 , 489504. doi:10.3402/tellusa.v51i4.14051
  73. Žagar, N. , Žagar, M. , Cedilnik, J. , Gregorič, G. and Rakovec, J. 2006. Validation of mesoscale low-level winds obtained by dynamical downscaling of ERA40 over complex terrain. Tellus A Dyn. Meteorol. Oceanogr. 58 , 445455. doi:10.1111/j.1600-0870.2006.00186.x
  74. Zerrahn, A. and Schill, W.-P. 2017. Long-run power storage requirements for high shares of renewables: review and a new model. Renew. Sustain. Energy Rev. 79 , 15181534. doi:10.1016/j.rser.2016.11.098
  75. Zhang, Q. , Pan, Y. , Wang, S. , Xu, J. and Tang, J. 2017. High-resolution regional reanalysis in China: evaluation of 1 year period experiments. J. Geophys. Res. Atmos. 122 , 1080110819. doi:10.1002/2017JD027476
Language: English
Page range: 1804294 - 1804294
Published on: Jan 1, 2021
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2021 Ronny Petrik, Beate Geyer, Burkhardt Rockel, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.