Spatial Approach of Peaks‐Over‐Thresholds in Trend Detection of Extremes

Béwentaoré Sawadogo; Diakarya Barro

doi:10.1002/env.70086

journal article Mar 24, 2026

Spatial Approach of Peaks‐Over‐Thresholds in Trend Detection of Extremes

Béwentaoré Sawadogo

Diakarya Barro

Environmetrics Vol. 37 No. 3 · Wiley

View at Publisher Save 10.1002/env.70086

Abstract

ABSTRACT
In this study, recent trends in extreme temperatures and rainfall are evaluated using the statistical theory of extreme values, in a non‐stationary context. We extend the non‐stationary pointwise threshold exceedances approach to spatial threshold exceedances. The temporal evolution of the extremes is handled pointwise by the peaks‐over‐threshold approach. First, evolution of the parameters of the distribution of exceedances and the intensity of extreme event occurrences for several meteorological variables are described as functions of time. Then, the spatial dependence structure attached to threshold exceedances is integrated using generalized ‐Pareto processes in a non‐stationary framework. In addition to better taking spatial dependence into account, our method allows us to simulate spatial exceedance processes at different dates and predict non‐stationary return levels at desired times by extrapolating the trends identified in the marginal distributions and the estimated dependence structure. Our approach is applied to temperature and rainfall data in Burkina Faso.

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Details

Published: Mar 24, 2026
Vol/Issue: 37(3)
License: View

Authors

B

Béwentaoré Sawadogo

Département de Mathématiques, Institut des Sciences et de Technologie École Normale Supérieure Ouagadougou Burkina Faso

D

Diakarya Barro

UFR‐SEG Université Thomas SANKARA Ouagadougou Burkina Faso

Funding

Campus France Award: 953705H,915626G,946727L,104697Z

Cite This Article

Béwentaoré Sawadogo, Diakarya Barro (2026). Spatial Approach of Peaks‐Over‐Thresholds in Trend Detection of Extremes. Environmetrics, 37(3). https://doi.org/10.1002/env.70086

Spatial Approach of Peaks‐Over‐Thresholds in Trend Detection of Extremes

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