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Detecting Climate Change in Using Extreme Data from Two Surface Weather Stations: Case Study Valle of Comitan and La Esperanza, Chiapas, Mexico
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作者 Martín Mundo-Molina Eber A. Godinez-Gutiérrez +1 位作者 José Luis Pérez-Díaz Daniel Hernández-Cruz 《Journal of Water Resource and Protection》 2021年第12期1061-1075,共15页
The study area is located between the cities of Comitan (16&deg;10'43"N and 92&deg;04'20''W) a city with 150,000 inhabitants and La Esperanza (16&deg;9'15''N and 91&deg... The study area is located between the cities of Comitan (16&deg;10'43"N and 92&deg;04'20''W) a city with 150,000 inhabitants and La Esperanza (16&deg;9'15''N and 91&deg;52'5''W) a town with 3000 inhabitants. Both weather stations are 30 km from each other in the Chiapas State, México. 54 years of daily records of the series of maximum (<em>t</em><sub>max</sub>) and minimum temperatures (<em>t</em><sub>min</sub>) of the weather station 07205 Comitan that is on top of a house and 30 years of daily records of the weather station 07374 La Esperanza were analyzed. The objective is to analyze the evidence of climate change in the Comitan valley. 2.07% and 19.04% of missing data were filled, respectively, with the WS method. In order to verify homogeneity three methods were used: Standard Normal Homogeneity Test (SNHT), the Von Neumann method and the Buishand method. The heterogeneous series were homogenized using climatol. The trends of <em>t</em><sub>max</sub> and <em>t</em><sub>min</sub> for both weather stations were analyzed by simple linear regression, Sperman’s rho and Mann-Kendall tests. The Mann-Kendal test method confirmed the warming trend at the Comitan station for both variables with <em>Z<sub>MK</sub></em> statistic values equal to 1.57 (statistically not significant) and 4.64 (statistically significant). However, for the Esperanza station, it determined a cooling trend for tmin and a slight non-significant warming for <em>t</em><sub>max</sub> with a <em>Z</em><sub><em>MK</em></sub> statistic of -2.27 (statistically significant) and 1.16 (statistically not significant), for a significance level <em>α</em> = 0.05. 展开更多
关键词 Detecting Climate Change in Using Extreme Data from Two surface Weather Stations: Case Study Valle of Comitan and La Esperanza CHIAPAS Mexico
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