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An example of principal component analysis application on climate change assessment

  • Lidija TadićEmail author
  • Ognjen Bonacci
  • Tamara Brleković
Original Paper

Abstract

Climate change assessment is usually based upon air temperature and precipitation changes on an annual and seasonal basis, but there are more levels to their significance as presented by parameters derived from these two basic parameters. In order to define their relevance for climate changes, the principal component analysis (PCA) was performed. In this case, ten meteorological parameters and climate change indicators were defined for two meteorological stations located in geographically completely opposite parts of the country; station Osijek is in continental region of Croatia, and Dubrovnik station is located in the Mediterranean region. Analyses were done for the period 1985–2016 on an annual and seasonal basis. All defined indicators present basic climate change characteristics on annual and seasonal basis as follows: precipitation sum, mean air temperature, air temperature sum, standard deviation of daily air temperature, maximum daily air temperature, maximum daily precipitation, number of days with precipitation > 30 mm, number of days with no precipitation, 1-month standardized precipitation index, and aridity index. In the first step, it was applied on the set of linear regression coefficients defined for 10 climate change indicators. During the second step, PCA was applied on the computed Mann–Kendall test statistic, ZMK.in order to determine the existence of significant temporal tendencies in the indicator values. The provided research proves PCA is a very useful tool for implementing this approach, particularly in the Mediterranean region which shows high sensitivity to many variables important for climate characterization.

Keywords

Climate change indicators Principal component analysis 

Notes

References

  1. Ács F, Takács D, Breuer H, Skarbit N (2018) Climate and climate change in the Austrian–Swiss region of the European Alps during the twentieth century according to Feddema. Theor Appl Climatol 133:899–910.  https://doi.org/10.1007/s00704-017-2230-6 CrossRefGoogle Scholar
  2. Alpert P, Ben-Gai T, Baharad A, Benjamini Y, Yekutieli D, Colacino M, Diodato L, Ramis C, Homar V, Romero R, Michaelides S, Manes A (2002) The paradoxical increase of Mediterranean extreme daily rainfall in spite of decrease in total values. Geophys Res Lett 29:311–314.  https://doi.org/10.1029/2001GL013554 CrossRefGoogle Scholar
  3. Asfaw A, Simane B, Hassen A, Bantider A (2018) Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: a case study in Woleka sub-basin. Weather Clim Extremes 19:29–41.  https://doi.org/10.1016/j.wace.2017.12.002 CrossRefGoogle Scholar
  4. Bonacci O (2010) Analiza nizova srednjih godišnjih temperatura zraka u Hrvatskoj. Građevinar 62:781–791Google Scholar
  5. Bonacci O (2012) Increase of mean annual surface air temperature in the Western Balkans during last 30 years. Vodoprivreda 44:75–89Google Scholar
  6. Breuer H, Ács F, Skarbit N (2017) Climate change in Hungary during the twentieth century according to Feddema. Theor Appl Climatol 127:853–863.  https://doi.org/10.1007/s00704-015-1670-0 CrossRefGoogle Scholar
  7. Costa AC, Soares A (2009) Trends in extreme precipitation indices derived from a daily rainfall database for the south of Portugal. Int J Climatol 29:1956–1975.  https://doi.org/10.1002/joc.1834 CrossRefGoogle Scholar
  8. Daigle A, St-Hilaire A, Beveridge D, Caissie D, Benyahya L (2011) Multivariate analysis of the low-flow regimes in eastern Canadian rivers. Hydrol Sci J 56:51–67.  https://doi.org/10.1080/02626667.2010.535002 CrossRefGoogle Scholar
  9. Fulgosi A (1984) Factor analysis (in Croatian). Školska knjiga, ZagrebGoogle Scholar
  10. Gajić-Čapka M, Cindrić K, Pasarić Z (2015) Trends in precipitation indices in Croatia, 1961–2010. Theor Appl Climatol 121:167–177.  https://doi.org/10.1007/s00704-014-1217-9 CrossRefGoogle Scholar
  11. Gilbert RO (1987) Statistical methods for environmental pollution monitoring. Wiley, New YorkGoogle Scholar
  12. Gocić M, Trajković S (2013) Analysis of changes in meteorological variables using Mann-Kendall. Glob Planet Chang 100:172–182.  https://doi.org/10.1016/j.gloplacha.2012.10.014 CrossRefGoogle Scholar
  13. Guo H, Wang T, Louie PKK (2004) Source apportionment of ambient non-methane hydrocarbons in Hong Kong: application of a principal component analysis/absolute principal component scores (PCA/APCS) receptor model. Environ Pollut 129:489–498.  https://doi.org/10.1016/j.envpol.2003.11.006 CrossRefGoogle Scholar
  14. Hargreaves GH, Samani ZA (1982) Estimation of potential evapotranspiration. Journal of Irrigation and Drainage Division. Proc Am Soc Civ Eng 108:225–230Google Scholar
  15. Irannezhad M, Marttila H, Chen D, Kløve B (2016) Century-long variability and trends in daily precipitation characteristics at three Finnish stations. Adv Clim Chang Res 7:54–69.  https://doi.org/10.1016/j.accre.2016.04.004 CrossRefGoogle Scholar
  16. Kendall MG (1962) Rank correlation methods. Charles Griffin & Company Limited, LondonGoogle Scholar
  17. Kumar PV, Bindi M, Crisci A, Maracchi G (2005) Detection of variations in air temperature at different time scales during the period 1889–1998 at Firenze, Italy. Clim Chang 72:123–150.  https://doi.org/10.1007/s10584-005-5970-8 CrossRefGoogle Scholar
  18. Kyselý J (2009) Trends in heavy precipitation in the Czech Republic over 1961–2005. Int J Climatol 29:1745–1758.  https://doi.org/10.1002/joc.1784 CrossRefGoogle Scholar
  19. Loska K, Wiechuła D (2003) Application of principal component analysis for the estimation of source of heavy metal contamination in surface sediments from the Rybnik reservoir. Chemosphere 51:723–733.  https://doi.org/10.1016/S0045-6535(03)00187-5 CrossRefGoogle Scholar
  20. Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259CrossRefGoogle Scholar
  21. Ministry of Environmental and Nature Protection, Republic of Croatia (2013) Sixth National Communication of the Republic of Croatia under the United Nation Framework Convention on Climate Change (UNFCCC)Google Scholar
  22. Moberg A, Jones PD, Lister D, Walther A, Brunet M, Jacobeit J, Alexander LV, Della-Marta PM, Luterbacher J, Yiou P, Chen D, Klein Tank AMG, Saladie O, Sigro J, Aguilar E, Alexandersson H, Almarza C, Auer I, Barriendos M, Begert M, Bergström H, Böhm R, Butler CJ, Caesar J, Drebs A, Founda D, Gerstengarbe FW, Micela G, Maugeri M, Österle H, Pandzic K, Petrakis M, Srnec L, Tolasz R, Tuomenvirta H, Werner PC, Linderholm H, Philipp A, Wanner H, Xoplaki E (2006) Indices for daily temperature and precipitation extremes in Europe analyzed for the period 1901–2000. J Geophys Res 111:D22106.  https://doi.org/10.1029/2006JD007103 CrossRefGoogle Scholar
  23. Othman M, Ash’aari ZH, Mohamad ND (2015) Long-term daily rainfall pattern recognition: application of principal component analysis. Procedia Environ Sci 30:127–132.  https://doi.org/10.1016/j.proenv.2015.10.022 CrossRefGoogle Scholar
  24. Pandžić K (1986) Factor analysis of temperature field on a relatively small area. Idojaras 90:321–331Google Scholar
  25. Pandžić K (1988) Principal component analysis of precipitation in the Adriatic-Pannonian area of Yugoslavia. Int J Climatol 8:357–370.  https://doi.org/10.1002/joc.3370080404 CrossRefGoogle Scholar
  26. Pandžić K, Trninić D, Likso T, Bošnjak T (2009) Long-term variations in water balance components for Croatia. Theor Appl Climatol 95:39–51.  https://doi.org/10.1007/s00704-007-0366-5 CrossRefGoogle Scholar
  27. Parinet B, Lhote A, Legube B (2004) Principal component analysis: an appropriate tool for water quality evaluation and management—application to a tropical lake system. Ecol Model 178:295–311.  https://doi.org/10.1016/j.ecolmodel.2004.03.007 CrossRefGoogle Scholar
  28. Perčec Tadić M, Gajić-Čapka M, Zaninović K, Cindrić K (2014) Drought vulnerability in Croatia. Agric Conspec Sci 79:31–38Google Scholar
  29. Philandras CM, Nastos PT, Kapsomenakis J, Douvis KC, Tselioudis G, Zerefos CS (2011) Long term precipitation trends and variability within the Mediterranean region. Nat Hazards Earth Syst Sci 11:3235–3250.  https://doi.org/10.5194/nhess-11-3235-2011 CrossRefGoogle Scholar
  30. Preisendorfer RW (1988) Principal component analysis in meteorology and oceanography. Elsevier, AmsterdamGoogle Scholar
  31. Rao AR, Burke TT (1997) Principal component analysis of hydrologic data. In: Harmancioglu NB, Alpaslan MN, Ozkul SD, Singh VP (eds) Integrated approach to environmental data management systems. NATO ASI series, series 2: Environment, vol 31Google Scholar
  32. Richman MB (1986) Rotation of principal components. Int J Climatol 6:293–335.  https://doi.org/10.1002/joc.3370060305 CrossRefGoogle Scholar
  33. Richman MB, Lamb PJ (1985) Climatic pattern analysis 0f 3-and 7-day summer rainfall in the Central United States: some methodological considerations and a regionalizations. J Clim Appl Meteorol 24:1325–1343CrossRefGoogle Scholar
  34. Sahu P, Kisku GC, Singh PK, Kumar V, Kumar P, Shukla N (2018) Multivariate statistical interpretation on seasonal variations of fluoride-contaminated groundwater quality of Lalganj Tehsil, Raebareli District (UP), India. Environ Earth Sci 77:484.  https://doi.org/10.1007/s12665-018-7658-1 CrossRefGoogle Scholar
  35. Salmi T, Määttä A, Anttila P, Ruoho-Airola T, Amnell T (2002) Detecting trends of annual values of atmospheric pollutants by the Mann-Kendall test and Sen’s slope estimates –the Excel template application MAKESENS. Publications on Air Quality No. 31. Finnish Meteorological Institute. HelsinkiGoogle Scholar
  36. Sharma SK, Gajbhiye S, Tignath S (2015) Application of principal component analysis in grouping geomorphic parameters of a watershed for hydrological modeling. Appl Water Sci 5:89–96.  https://doi.org/10.1007/s13201-014-0170-1 CrossRefGoogle Scholar
  37. Singh PK, Kumar V, Purohit RC, Kothari Dashora PK (2009) Application of principal component analysis in grouping geomorphic parameters for hydrologic modeling. Water Resour Manag 23:325–339.  https://doi.org/10.1007/s11269-008-9277-1 CrossRefGoogle Scholar
  38. Trajković S (2007) Hargreaves versus Penman-Monteith under humid conditions. J Irrig Drain Eng 133:38–42.  https://doi.org/10.1061/(ASCE)0733-9437(2007)133:1(38) CrossRefGoogle Scholar
  39. Westra S, Fowler HJ, Evans JP, Alexander LV, Berg P, Johnson F, Kendon EJ, Lenderink G, Roberts NM (2014) Future changes to the intensity and frequency of short duration extreme rainfall. Rev Geophys 52:522–555.  https://doi.org/10.1002/2014RG000464 CrossRefGoogle Scholar
  40. Zaninovic K (2010) Temporal changes in temperature extremes since the beginning of 20th century over Croatia. In: 11th International Meeting on Statistical Climatology. EdinburghGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Civil Engineering and ArchitectureUniversity of OsijekOsijekCroatia
  2. 2.Faculty of Civil Engineering, Architecture and GeodesyUniversity of SplitSplitCroatia

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