Spatio-Temporal Cross-Covariance Functions under the Lagrangian Framework with Multiple Advections

Mary Lai O. Salvaña*, Amanda Lenzi, Marc G. Genton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

When analyzing the spatio-temporal dependence in most environmental and earth sciences variables such as pollutant concentrations at different levels of the atmosphere, a special property is observed: the covariances and cross-covariances are stronger in certain directions. This property is attributed to the presence of natural forces, such as wind, which cause the transport and dispersion of these variables. This spatio-temporal dynamics prompted the use of the Lagrangian reference frame alongside any Gaussian spatio-temporal geostatistical model. Under this modeling framework, a whole new class was birthed and was known as the class of spatio-temporal covariance functions under the Lagrangian framework, with several developments already established in the univariate setting, in both stationary and nonstationary formulations, but less so in the multivariate case. Despite the many advances in this modeling approach, efforts have yet to be directed to probing the case for the use of multiple advections, especially when several variables are involved. Accounting for multiple advections would make the Lagrangian framework a more viable approach in modeling realistic multivariate transport scenarios. In this work, we establish a class of Lagrangian spatio-temporal cross-covariance functions with multiple advections, study its properties, and demonstrate its use on a bivariate pollutant dataset of particulate matter in Saudi Arabia. Supplementary materials for this article are available online.

Original languageEnglish (US)
Pages (from-to)2746-2761
Number of pages16
JournalJOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume118
Issue number544
DOIs
StateAccepted/In press - 2022

Bibliographical note

Publisher Copyright:
© 2022 American Statistical Association.

Keywords

  • Cross-covariance function
  • Lagrangian framework
  • Multiple advections
  • Multivariate random field
  • Spatio-temporal
  • Transport effect

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint

Dive into the research topics of 'Spatio-Temporal Cross-Covariance Functions under the Lagrangian Framework with Multiple Advections'. Together they form a unique fingerprint.

Cite this