Global‐Krigger: A Global Kriging Interpolation Toolbox With Paleoclimatology Examples

Bibliographic Details
Title: Global‐Krigger: A Global Kriging Interpolation Toolbox With Paleoclimatology Examples
Authors: N. J. Cosentino, N. E. Opazo, F. Lambert, A. Osses, E. van 'tWout
Source: Geochemistry, Geophysics, Geosystems, Vol 24, Iss 6, Pp n/a-n/a (2023)
Publisher Information: Wiley, 2023.
Publication Year: 2023
Collection: LCC:Geophysics. Cosmic physics
LCC:Geology
Subject Terms: dust, paleoclimate, MATLAB, model‐data comparison, gridded data, Geophysics. Cosmic physics, QC801-809, Geology, QE1-996.5
More Details: Abstract Many applications in Earth sciences require spatial prediction, that is, obtaining a continuous scalar field from a set of discrete scalar data points on the Earth's surface. Such applications include model‐data comparisons and derivation of continuous scalar fields as input for Earth system models. The advantage of kriging as an interpolation method is that it provides predictions with confidence intervals for data sets of irregularly distributed points in space. However, the theory of kriging for non‐Euclidean domains such as oblate spheroids (e.g., the Earth's surface) is poorly developed, and existing kriging algorithms for global interpolation oftentimes cannot guarantee the validity of their predictions. Here, we present Global‐Krigger, a new kriging interpolation algorithm adapted for local to global applications that (a) incorporates a numerical check to guarantee that the necessary conditions for the kriging system of linear equations are met, and (b) derives a combined uncertainty field due both to spatial variations in data density and measurement error. The robustness of the method is demonstrated by cross‐validating predictions against reanalysis fields of traditional climatological scalar variables. We also show an example application in paleoclimatology for Holocene mineral dust deposition fluxes. The toolbox includes a user‐friendly graphical user interface that guides users through a range of choices during data pre‐interpolation analysis, kriging, and post‐processing.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1525-2027
Relation: https://doaj.org/toc/1525-2027
DOI: 10.1029/2022GC010821
Access URL: https://doaj.org/article/f4a5cdebeb38448e8a81916c18b594e4
Accession Number: edsdoj.f4a5cdebeb38448e8a81916c18b594e4
Database: Directory of Open Access Journals
More Details
ISSN:15252027
DOI:10.1029/2022GC010821
Published in:Geochemistry, Geophysics, Geosystems
Language:English