Spatial Modeling of Precipitation Based on Data-Driven Warping of Gaussian Processes

Spatial Modeling of Precipitation Based on Data-Driven Warping of Gaussian Processes

Modeling and forecasting spatiotemporal patterns of precipitation is crucial for managing water resources and mitigating water-related hazards. Globally valid spatiotemporal models of precipitation are not available. This is due to the intermittent nature, non-Gaussian distribution, and complex geog...

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Bibliographic Details
Main Authors: Vasiliki D. Agou, Andrew Pavlides, Dionissios T. Hristopulos
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Entropy
Subjects:
non-Gaussian data
skewed distributions
Gaussian anamorphosis
reanalysis data
kriging
warped Gaussian processes
Online Access:https://www.mdpi.com/1099-4300/24/3/321

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