Literature DB >> 11027322

Data assimilation and its applications.

B Wang1, X Zou, J Zhu.   

Abstract

In data assimilation, one prepares the grid data as the best possible estimate of the true initial state of a considered system by merging various measurements irregularly distributed in space and time, with a prior knowledge of the state given by a numerical model. Because it may improve forecasting or modeling and increase physical understanding of considered systems, data assimilation now plays a very important role in studies of atmospheric and oceanic problems. Here, three examples are presented to illustrate the use of new types of observations and the ability of improving forecasting or modeling.

Year:  2000        PMID: 11027322      PMCID: PMC34050          DOI: 10.1073/pnas.97.21.11143

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  4 in total

1.  Incremental parameter evaluation from incomplete data with application to the population pharmacology of anticoagulants.

Authors:  Marcel O Vlad; Alexandru Dan Corlan; Federico Morán; Peter Oefner; John Ross
Journal:  Proc Natl Acad Sci U S A       Date:  2008-03-19       Impact factor: 11.205

2.  Using clinicians' search query data to monitor influenza epidemics.

Authors:  Mauricio Santillana; Elaine O Nsoesie; Sumiko R Mekaru; David Scales; John S Brownstein
Journal:  Clin Infect Dis       Date:  2014-08-12       Impact factor: 9.079

3.  Data-driven prediction in dynamical systems: recent developments.

Authors:  Amin Ghadami; Bogdan I Epureanu
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2022-06-20       Impact factor: 4.019

4.  Dealing with uncertainty in agent-based models for short-term predictions.

Authors:  Le-Minh Kieu; Nicolas Malleson; Alison Heppenstall
Journal:  R Soc Open Sci       Date:  2020-01-15       Impact factor: 2.963

  4 in total

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