Theoretical and Applied Climatology

, Volume 116, Issue 1–2, pp 211–225 | Cite as

Analysis and modeling of extreme temperatures in several cities in northwestern Mexico under climate change conditions

  • O. Rafael García-CuetoEmail author
  • M. Tereza Cavazos
  • Pamela de Grau
  • Néstor Santillán-Soto
Original Paper


The generalized extreme value distribution is applied in this article to model the statistical behavior of the maximum and minimum temperature distribution tails in four cities of Baja California in northwestern Mexico, using data from 1950–2010. The approach used of the maximum of annual time blocks. Temporal trends were included as covariates in the location parameter (μ), which resulted in significant improvements to the proposed models, particularly for the extreme maximum temperature values in the cities of Mexicali, Tijuana, and Tecate, and the extreme minimum temperature values in Mexicali and Ensenada. These models were used to estimate future probabilities over the next 100 years (2015–2110) for different time periods, and they were compared with changes in the extreme (P90th and P10th) percentiles of maximum and minimum temperature scenarios for a set of six general circulation models under low (RCP4.5) and high (RCP8.5) radiative forcings. By the end of the twenty-first century, the scenarios of the changes in extreme maximum summer temperature are of the same order in both the statistical model and the high radiative scenario (increases of 4–5 °C). The low radiative scenario is more conservative (increases of 2–3 °C). The winter scenario shows that minimum temperatures could be less severe; the temperature increases suggested by the probabilistic model are greater than those projected for the end of the century by the set of global models under RCP4.5 and RCP8.5 scenarios. The likely impacts on the region are discussed.


Heat Wave Couple Model Intercomparison Project Phase Generalize Extreme Value Return Level Generalize Extreme Value Distribution 
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.



We are grateful to the Department of Physical Oceanography at the Center of Scientific Research and Higher Education of Ensenada because this work was carried out while the first author was on sabbatical at that institution. We thank Manuel Colima, engineer from the National Water Commission, for providing the temperature data. This project was partially funded by projects supported by the National Council on Science and Technology/Environmental and Natural Resources Department (Consejo Nacional de Ciencia y Tecnología/Secretaría de Medio Ambiente y Recursos Naturales—CONACyT/SEMARNAT), the National Institute of Ecology (INE), and the Network of Disasters Associated with Hydrometeorological and Climate Phenomena (Red de Desastres Asociados a Fenómenos Hidrometeorológicos y Climáticos—REDESClim).


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Copyright information

© Springer-Verlag Wien 2013

Authors and Affiliations

  • O. Rafael García-Cueto
    • 1
    Email author
  • M. Tereza Cavazos
    • 2
  • Pamela de Grau
    • 2
  • Néstor Santillán-Soto
    • 1
  1. 1.Instituto de Ingeniería, UABCBlvd. Benito Juárez y Calle de la Normal S/NMexicaliMexico
  2. 2.Centro de Investigación Científica y de Educación Superior de EnsenadaCarretera Ensenada-Tijuana #3918EnsenadaMexico

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