Modeling and prediction of environmental data in space and time using Kalman filtering

DOI10.1007/S00477-002-0097-1zbMath1016.62129OpenAlexW2130896823MaRDI QIDQ1395389

A. J. Segers, Arnold W. Heemink

Publication date: 21 August 2003

Published in: Stochastic Environmental Research and Risk Assessment (Search for Journal in Brave)

Full work available at URL: http://resolver.tudelft.nl/uuid:7da98223-0705-4deb-8e50-822fc20d52a7

zbMATH Keywords

Kalman filteringstate space modeldistributed modelingenvironmental modelingforecast of ozone concentrations

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics to environmental and related topics (62P12)

Related Items (4)

Data assimilation in transport models ⋮ Sequential Data Assimilation Techniques in Oceanography ⋮ Robust state estimation and its application to spacecraft control ⋮ A numerical comparative study on data assimilation using Kalman filters

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