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PCA analysis of wind direction climate in the baltic states Cover

PCA analysis of wind direction climate in the baltic states

Open Access
|Jan 2021

References

  1. Bethere, L. , Sennikovs, J. and Bethers, U. 2017. Climate indices for the Baltic states from principal component analysis. Earth Syst. Dynam. 8, 951962. https://esd.copernicus.org/articles/8/951/2017/. doi:10.5194/esd-8-951-2017
  2. Briede, A. 2016. Klimats un ilgtspejga attistiba . Latvijas Universitate, Chap. 4., 78–81 isbn 978-9934.18-136-8.
  3. ECMWF . 2019. UERRA regional reanalysis for Europe on single levels from 1961 to 2019. Online at: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-uerra-europe-single-levels?tab=overview.
  4. Gupta, A. and Dhir, A. 2013. Estimation of horizontal pollution potential by calculating impact area for Patiala, Punjab using wind data. Int. J. Innov. Res. Sci. Eng. Technol. 2, 22712279.
  5. Hahmann, A. N. , Sīle, T. , Witha, B. , Davis, N. N. , Dörenkämper, M. and co-authors. 2020. The making of the New European Wind Atlas - Part 1: Model sensitivity. Geosci. Model Dev. 13 , 50535078. In: url: https://gmd.copernicus.org/articles/13/5053/2020/. doi:10.5194/gmd-13-5053-2020
  6. Jaagus, J. and Kull, A. 2011. Changes in surface wind directions in Estonia during 1966-2008 and their relationships with large-scale atmospheric circulation. Estonian J. Earth Sci. 60, 220. In: doi:10.3176/earth.2011.4.03
  7. Jaagus, J. , Briede, A. , Rimkus, E. and Remm, K. 2009. Precipitation pattern in the Baltic countries under the influence of large-scale atmospheric circulation and local landscape factors. Int. J. Climatol. 30, n/a720. In: doi:.
  8. Jolliffe, I. T. 2002. Principal Component Analysis. Springer Series in Statistics . New York: Springer-Verlag. ISBN: 0-387-95442-2. http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-95442-4.
  9. Jungo, P. , Goyette, S. and Beniston, M. 2002. Daily wind gust speed probabilities over Switzerland according to three types of synoptic circulation. Int. J. Climatol. 22, 485499. In: doi:. doi:10.1002/joc.741
  10. Klink, K. and Willmott, C. 1989. Principal components of the surface wind field in the United States: A comparison of analyses based upon wind velocity, direction, and speed. Int. J. Climatol. 9, 293308. doi:10.1002/joc.3370090306
  11. Koch, W. 2004. Directional analysis of SAR images aiming at wind direction. IEEE Trans. Geosci. Remote Sens. 42, 702710. doi:10.1109/TGRS.2003.818811
  12. Kouts, T. 1998. Forcing Factors for Hydrography and Currents – Meteorological and Hydrological Variables . In: The Gulf of Riga Project (funded by The Nordic Council of Ministers). SMHI, Norrkoping, Sweden.
  13. Lea, D. A. and Helvey, R. A. 1971. A directional bias in wind roses due to mixed compass formats. J. Appl. Meteor. 10, 10371039. In: Oct. > 2.0.CO;2. url: https://journals.ametsoc.org/view/journals/apme/10/5/1520-0450_1971_010_1037_adbiwr_2_0_co_2.xml. doi:10.1175/1520-0450(1971)010<;1037:ADBIWR>2.0.CO;2
  14. Met Office . 2010. Cartopy: A Cartographic Python Library with a Matplotlib Interface . Exeter, Devon, 2010–2015. https://scitools.org.uk/cartopy.
  15. Mezaache, H. , Bouzgou, H. and Raymond, C. 2016. Kernel principal components analysis with extreme learning machines for wind speed prediction. In Seventh International Renewable Energy Congress, IREC 2016. Hammamet, Tunisia, March. https://hal.inria.fr/hal-01394000.
  16. Pedro, A. J. , González‐Rouco, J. F. , Montávez, J. P. , García‐Bustamante, E. , & Navarro, J. 2009. Climatology of wind patterns in the northeast of the Iberian Peninsula. Int. J. Climatol. 29.4, 501525. doi:.
  17. Pele, O. and Werman, M. 2008. A linear time histogram metric for improved sift matching. In: Computer Vision – ECCV . Springer, Berlin, Heidelberg, Oct., pp. 495508.
  18. Pele, O. and Werman, M. 2009. Fast and robust earth mover's distances. In: 2009 IEEE 12th Inter-national Conference on Computer Vision . IEEE. Sept., pp. 460467.
  19. Ratner, B. 1950. A method for eliminating directional bias in wind roses. Mon. Wea. Rev. 78, 185188. 0493(1950)078 < 0185:AMFEDB > 2.0.CO;2. url: https://journals.ametsoc.org/view/journals/mwre/78/10/1520-0493_1950_078_0185_amfedb_2_0_co_2.xml. doi:10.1175/1520-0493(1950)078<;0185:AMFEDB>2.0.CO;2
  20. Rubner, Y. , Tomasi, C. and Guibas, L. J. 2000. The earth mover's distance as a metric for image retrieval. Int. J. Computer Vision . 40, 99121. url: https://doi.org/10.1023/A:1026543900054. doi:10.1023/A:1026543900054
  21. Rutgersson, A. 2015. Recent change | atmosphere. In: Second Assessment of Climate Change for the Baltic Sea Basin (ed. The BACC II Author Team). Springer International Publishing, Cham, pp. 6997. ISBN: 978-3-319-16006-1. 1007/978 - 3 - 319 - 16006 - 1 _ 4. url: https://doi.org/10.1007/978-3-319-16006-1_4.
  22. Sepp, M. , Post, P. , Mändla, K. , & Aunap, R. et al. 2018. On cyclones entering the Baltic Sea region. Boreal Environ. Res. 23, 1–14.
  23. Sīle, T. , Seņņikovs, J. and Bethers, U. June 2018. Evidence for low-level jets caused by coastal baroclinity at the Kurzeme shore of the Baltic Sea. Estonian J. Earth Sci. 67, 149. In: doi:10.3176/earth.2018.11
  24. Soomere, T. and Keevallik, S. 2001. Anisotropy of moderate and strong winds in the Baltic Proper. Proc. Estonian Acad. Sci. Eng. 7, 3549.
  25. Team, B. A. 2008. Assessment of Climate Change for the Baltic Sea Basin . Springer, Berlin Heidelberg. isbn: 978-3-540-72786-6. url: https://doi.org/10.1007/978-3-540-72786-6.
  26. WMO. 2017. WMO Guidelines on the Calculation of Climate Normal. 2017th ed. World Meteorological Organization (WMO). isbn: 978-92-63-11203-3.
Language: English
Page range: 1962490 - 1962490
Published on: Jan 1, 2021
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2021 Maksims Pogumirskis, Tija Sīle, Juris Seņņikovs, Uldis Bethers, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.