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Theoretical and Applied Climatology

, Volume 130, Issue 1–2, pp 419–434 | Cite as

Wet-bulb, dew point, and air temperature trends in Spain

  • R. Moratiel
  • B. Soriano
  • A. Centeno
  • D. Spano
  • R.L. Snyder
Original Paper

Abstract

This study analyses trends of mean (T m), maximum (T x), minimum (T n), dew point (T d), and wet-bulb temperatures (T w) on an annual, seasonal, and monthly time scale over Spain during the period 1981–2010. The main purpose was to determine how temperature and humidity changes are impacting on T w, which is probably a better measure of climate change than temperature alone. In this study, 43 weather stations were used to detect data trends using the nonparametric Mann-Kendall test and the Sen method to estimate the slope of trends. Significant linear trends observed for T m, T x, and T n versus year were 56, 58, and 47 % of the weather stations, respectively, with temperature ranges between 0.2 and 0.4 °C per decade. The months with bigger trends were April, May, June, and July with the highest trend for T x. The spatial behaviour of T d and T w was variable, with various locations showing trends from −0.6 to +0.3 °C per decade for T d and from −0.4 to +0.5 °C per decade for T w. Both T d and T w showed negative trends for July, August, September, November, and December. Comparing the trends versus time of each variable versus each of the other variables exhibited poor relationships, which means you cannot predict the trend of one variable from the trend of another variable. The trend of T x was not related to the trend of T n. The trends of T x, T m, and T n versus time were unrelated to the trends versus time of either T d or T w. The trend of T w showed a high coefficient of determination with the trend of T d with an annual value of R 2 = 0.86. Therefore, the T w trend is more related to changes in humidity than temperature.

Keywords

Heat Stress Negative Trend North Atlantic Oscillation Ordinary Kriging Annual Trend 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

Thanks are due to the Agencia Estatal de Meteorología (AEMET) for facilitating the data and especially to Ms. Juana Arolo.

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Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  • R. Moratiel
    • 1
    • 2
  • B. Soriano
    • 2
  • A. Centeno
    • 1
    • 2
  • D. Spano
    • 3
    • 4
  • R.L. Snyder
    • 5
  1. 1.Departamento de Producción AgrariaTechnical University of MadridMadridSpain
  2. 2.CEIGRAM, Research Centre for the Management of Agricultural and Environmental RisksMadridSpain
  3. 3.Department of Science for Nature and Environmental Resources (DipNet)University of SassariSassariItaly
  4. 4.IAFENTs DivisionEuroMediterranean Center for Climate Change (CMCC)SassariItaly
  5. 5.Department of Land, Air and Water ResoursesUniversity of CaliforniaDavisUSA

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