A Reconstruction of May–June Mean Temperature since 1775 for Conchos River Basin, Chihuahua, Mexico, Using Tree-Ring Width

Author:

Martínez-Sifuentes Aldo Rafael1,Villanueva-Díaz José1,Trucíos-Caciano Ramón1ORCID,López-Hernández Nuria Aide1ORCID,Estrada-Ávalos Juan1,Rodríguez-Moreno Víctor Manuel2ORCID

Affiliation:

1. National Institute of Forestry, Agricultural and Livestock Research, National Center for Disciplinary Research on Water, Soil, Plant and Atmosphere Relationships, Gómez Palacio 35150, Mexico

2. National Institute of Forestry, Agricultural and Livestock Research, National, Experimental Field Pabellón, Pabellón de Arteaga 20678, Mexico

Abstract

Currently there are several precipitation reconstructions for northern Mexico; however, there is a lack of temperature reconstructions to understand past climate change, the impact on ecosystems and societies, etc. The central region of Chihuahua is located in a transition zone between the Sierra Madre Occidental and the Great Northern Plain, characterized by extreme temperatures and marked seasonal variability. The objectives of this study were (1) to generate a climatic association between variables from reanalysis models and the earlywood series for the center of Chihuahua, (2) to generate a reconstruction of mean temperature, (3) to determine extreme events, and (4) to identify the influence of ocean–atmosphere phenomena. Chronologies were downloaded from the International Tree-Ring Data Bank and climate information from the NLDAS-2 and ClimateNA reanalysis models. The response function was performed using climate models and regional dendrochronological series. A reconstruction of mean temperature was generated, and extreme periods were identified. The representativeness of the reconstruction was evaluated through spatial correlation, and low-frequency events were determined through multitaper spectral analysis and wavelet analysis. The influence of ocean–atmosphere phenomena on temperature reconstruction was analyzed using Pearson correlation, and the influence of ENSO was examined through wavelet coherence analysis. Highly significant correlations were found for maximum, minimum, and mean temperature, as well as for precipitation and relative humidity, before and after the growth year. However, the seasonal period with the highest correlation was found from May to June for mean temperature, which was used to generate the reconstruction from 1775 to 2022. The most extreme periods were 1775, 1801, 1805, 1860, 1892–1894, 1951, 1953–1954, and 2011–2012. Spectral analysis showed significant frequencies of 56.53 and 2.09 years, and wavelet analysis from 0 to 2 years from 1970 to 1980, from 8 to 11 years from 1890 to 1910, and from 30 to 70 years from 1860 to 2022. A significant association was found with the Multivariate ENSO Index phenomenon (r = 0.40; p = 0.009) and Pacific Decadal Oscillation (r = −0.38; p = 0.000). Regarding the ENSO phenomenon, an antiphase association of r = −0.34; p = 0.000 was found, with significant periods of 1 to 4 years from 1770 to 1800, 1845 to 1850, and 1860 to 1900, with periods of 6 to 10 years from 1875 to 1920, and from 6 to 8 years from 1990 to 2000. This study allowed a reconstruction of mean temperature through reanalysis data, as well as a historical characterization of temperature for central Chihuahua beyond the observed records.

Funder

Sectoral Research Fund for Education

Publisher

MDPI AG

Reference66 articles.

1. National Meteorological Service of Mexico (NMSM) (2024, January 20). National Meteorological Service of Mexico. Climatology. Available online: https://smn.conagua.gob.mx/es/.

2. Análisis de la variabilidad climática en Chihuahua, México;Rev. Mex. Cienc. Agrícolas,2018

3. National Institute of Statistics and Geography (2024, January 15). Weather Statistics: Chihuahua. Available online: https://www.inegi.org.mx/.

4. Climate Computing Project (2024, April 10). Climate Computing Project Database. Available online: http://clicom-mex.cicese.mx.

5. Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products;Xia;J. Geoph. Res.,2012

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