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Multiscale spatial variographic analysis of hydroclimatic data

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Abstract

The spatial structure of the variance related to hydroclimatic datasets over multi-decadal timescales was studied for Mexico. The changes of variance at different spatial scales were investigated for precipitation and temperature normals by variographic analysis. The objective of the study was to determine the proper spatial scales for studying key climatic elements. Isotropy, anisotropy, 12 different models, and 50 distances from 0.1 to 100% of the study area diameter were tested for raw temperature and precipitation normals, as well as for the residuals resulting from polynomial detrending. Each variogram was tested, and the suitable ones were used to describe and understand the spatial variation of the phenomena. The variance structure in the data of each climatological element varies as a function of the scale, relief, and the application of detrending because the spatial evolution of the phenomena is complex. The active lag distances related to structures that best fit the data belong to meso-β scale and are shorter than the study area radius. Moreover, various mesoscale distances highlight different structures that have physical meanings.

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Data availability

All the data used in this work are available at Servicio Meteorológico Nacional and are free of charge.

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Acknowledgments

The authors thank Servicio Meteorologico Nacional for providing data. DR thanks the “Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica (PAPIIT)” of the UNAM, grant number IA302220. The authors also acknowledge Dr. Alfonso Condal from Université Laval and Pedro-Luis Ardisson from Cinvestav-Mérida for providing writing assistance, and Erik Granados for language editing.

Funding

This work was supported by the “Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica (PAPIIT)” of the Universidad Nacional Autónoma de México (grant number IA302220).

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Conceptualization: David Romero; methodology: David Romero, Roger Orellana; formal analysis and investigation: David Romero; writing—original draft preparation: David Romero; writing—review and editing: Roger Orellana, María-Engracia Hernández Cerda; funding acquisition: David Romero; Resources: David Romero, Roger Orellana; supervision: María-Engracia Hernández Cerda

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Correspondence to David Romero.

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The authors declare that they have no conflict of interest.

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Software used for the work is opensource R: A Language and Environment for Statistical Computing.

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Romero, D., Orellana, R. & Hernández-Cerda, M.E. Multiscale spatial variographic analysis of hydroclimatic data. Theor Appl Climatol 144, 55–66 (2021). https://doi.org/10.1007/s00704-020-03513-9

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  • DOI: https://doi.org/10.1007/s00704-020-03513-9

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