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Climatic Change

, Volume 59, Issue 1–2, pp 75–99 | Cite as

20th Century Climate Change in the Tropical Andes: Observations and Model Results

  • Mathias Vuille
  • Raymond S. Bradley
  • Martin Werner
  • Frank Keimig
Article

Abstract

Linear trend analysis of observational data combined with model diagnostics from an atmospheric general circulation model are employed to search for potential mechanisms related to the observed glacier retreat in the tropical Andes between 1950 and 1998. Observational evidence indicates that changes in precipitation amount or cloud cover over the last decades are minor in most regions and are therefore rather unlikely to have caused the observed retreat. The only exception is in southern Peru and western Bolivia where there is a general tendency toward slightly drier conditions. Near-surface temperature on the other hand has increased significantly throughout most of the tropical Andes. The temperature increase varies markedly between the eastern and western Andean slopes with a much larger temperature increase to the west. Simulations with the ECHAM-4 model, forced with observed global sea surface temperatures (SST) realistically reproduce the observed warming trend as well as the spatial trend pattern. Model results further suggest that a significant fraction of the observed warming can be traced to a concurrent rise in SST in the equatorial Pacific and that the markedly different trends in cloud cover to the east and west of the Andes contributed to the weaker warming east of the Andes in the model. The observed increase in relative humidity, derived from CRU 05 data, is also apparent in the model simulations, but on a regional scale the results between model and observations vary significantly. It is argued that changes in temperature and humidity are the primary cause for the observed glacier retreat during the 2nd half of the 20th century in the tropical Andes.

Keywords

Peru Cloud Cover Atmospheric General Circulation Model Trend Pattern Linear Trend Analysis 
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.

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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Mathias Vuille
    • 1
  • Raymond S. Bradley
    • 2
  • Martin Werner
    • 3
  • Frank Keimig
    • 2
  1. 1.U.S.A.
  2. 2.U.S.A
  3. 3.Germany

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