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Random fields simplified: preserving marginal distributions, correlations, and intermittency, with applications from rainfall to humidity
Publikationstyp
Journal Article
Date Issued
2020-01-10
Sprache
English
Journal
Volume
56
Issue
2
Article Number
e2019WR026331
Citation
Water Resources Research 56 (2): e2019WR026331 (2020)
Publisher DOI
Scopus ID
Publisher
Wiley
Nature manifests itself in space and time. The spatiotemporal complexity of processes such as precipitation, temperature, and wind, does not allow purely deterministic modeling. Spatiotemporal random fields have a long history in modeling such processes, and yet a single unified framework offering the flexibility to simulate processes that may differ profoundly does not exist. Here we introduce a blueprint to efficiently simulate spatiotemporal random fields that preserve any marginal distribution, any valid spatiotemporal correlation structure, and intermittency. We suggest a set of parsimonious yet flexible marginal distributions and provide a rule of thumb for their selection. We propose a new and unified approach to construct flexible spatiotemporal correlation structures by combining copulas and survival functions. The versatility of our framework is demonstrated by simulating conceptual cases of intermittent precipitation, double-bounded relative humidity, and temperature maxima fields. As a real-word case we simulate daily precipitation fields. In all cases, we reproduce the desired properties. In an era characterized by advances in remote sensing and increasing availability of spatiotemporal data, we deem that this unified approach offers a valuable and easy-to-apply tool for modeling complex spatiotemporal processes.
Subjects
Hydroclimatic processes simulation
Precipitation simulation
Random field simulation
Spatiotemporal correlation structures
Spatiotemporal risk analysis
Stochastic modelling
DDC Class
600: Technology