Observed trends in daily temperature extreme indices in Aguascalientes, Mexico
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ORIGINAL PAPER
Observed trends in daily temperature extreme indices in Aguascalientes, Mexico Osias Ruiz-Alvarez 1,2 & Vijay P. Singh 3 & Juan Enciso-Medina 4 & Ronald Ernesto Ontiveros-Capurata 5 & Carlos Antonio Costa dos Santos 6,7 Received: 8 March 2019 / Accepted: 15 September 2020 # Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract Climate change is a pernicious and irrefutable reality. The objective of this work was to analyze trends in extreme temperature indices in Aguascalientes. With RClimdex 1.0 and data on daily maximum (Tmax) and minimum temperature (Tmin), 16 temperature indices were calculated. The trend in indices was determined with the non-parametric Mann-Kendall test (p ≤ 0.05), while the rate of change was obtained with Theil-Sen’s trend estimator. Significant positive trends were observed in 72 time series of indices associated with Tmax and in 39 time series of indices associated with Tmin. Significant negative trends were observed in 22 time series of indices associated with Tmax, and in 45 time series of indices associated with Tmin. In some regions of Aguascalientes, diurnal warming is occurring; in others, warmer or less cold nights prevail. The changes in extreme temperature indices might have severe implications in the use of irrigation water, cause physiological stress in crops, promote respiratory and cardiac diseases, and improve the reproduction cycles and populations of insects. Also, the fruit production, such as guava, could be affected under the reduction of minimum temperature, and the increase in warm days where other fruit trees are cultivated can intensify the use of chemical compensators of cold. These results are of significance for long-term economic planning and design of strategies of adaptation/mitigation to climate change. In Aguascalientes, the changes observed in extreme temperature indices could be due to climate change of a bigger scale, either regional or at the watershed level.
1 Introduction * Osias Ruiz-Alvarez [email protected]; [email protected] 1
Water Management and Hydrological Science, Texas A&M University, College Station, TX 77843, USA
2
National Laboratory of Modeling and Remote Sensing (LNMySR) of Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias (INIFAP), 20660, Pabellon de Arteaga, Aguascalientes, Mexico
3
Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX 77843, USA
4
Department of Biological and Agricultural Engineering, Texas A&M AgriLife Research, Weslaco, TX 78596, USA
5
Catedra CONACYT, Instituto Mexicano de Tecnologia del Agua, 62550 Jiutepec, Morelos, Mexico
6
Department of Atmospheric Science, Federal University of Campina Grande, Avenida Aprígio Veloso, 882, Bodocongó, Campina Grande, PB CEP 58109-970, Brazil
7
Daugherty Water for Food Global Institute, University of Nebraska-Lincoln, Lincoln, NE, USA
Currently, climate change is an inescapable reality. According to Intergovernmental Panel on Climate Change (2007), during
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