Application of geostatistical models for aridity scenarios in northern Mexico
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Abstract
An annual mean temperature map was calculated using the Kriging interpolation method for the north-central zone of Mexico to obtain the current aridity, as well as possible scenarios for the near and distant future. The altitudinal gradient was estimated by linear regression, and it was used to estimate the mean temperature. Climate Influence Areas (CIA) were obtained by superimposing the official precipitation layer and the annual mean temperature layer using Geographic Information Systems tools. Monthly databases of climatic variables were generated for each CIA and potential evapotranspiration was estimated using the Thorthwaite methodology. The Aridity Index (AI) was calculated and mapped for a base scenario (1970-2000). Subsequently, the aridity behavior of some scenarios was projected and mapped using the global climate models HADGEM 2.0, GFDLCM 3.0, MIP_ESM, and CRNMCM5. Under the best scenario projected, aridity will weaken the humid ecosystems and in the worst scenario, hyper-arid climates will appear in the study region.
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