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Dynamic spatio-temporal generation of large-scale synthetic gridded precipitation: with improved spatial coherence of extremes
2019
Stochastic environmental research and risk assessment (Print)
With the ongoing development of distributed hydrological models, flood risk analysis calls for synthetic, gridded precipitation data sets. The availability of large, coherent, gridded re-analysis data sets in combination with the increase in computational power, accommodates the development of new methodology to generate such synthetic data. We tracked moving precipitation fields and classified them using self-organising maps. For each class, we fitted a multivariate mixture model and generated
doi:10.1007/s00477-019-01724-9
fatcat:jk5rq3hcjrfzjgpk2xjkb3s67a