Random Fields Simplified: Spatiotemporal simulation preserving extremes using the CoSMoS R package

Abstract:

Nature manifests itself in space and time. The spatiotemporal complexity of processes such as precipitation, temperature, wind, etc., does not allow purely deterministic modelling. Spatiotemporal random fields have a long history in modelling 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, as well 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. This framework is implemented in the CoSMoS R package which is freely available on CRAN.