Cristin-resultat-ID: 1479873
Sist endret: 20. mai 2019 11:38
NVI-rapporteringsår: 2017
Resultat
Vitenskapelig artikkel
2017

Calibration of imperfect models to biased observations

Bidragsytere:
  • Dean Oliver og
  • Miguel Angel Alfonzo

Tidsskrift

Computational Geosciences
ISSN 1420-0597
e-ISSN 1573-1499
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2017
Publisert online: 2017
Trykket: 2018
Volum: 22
Hefte: 1
Sider: 145 - 161

Importkilder

Scopus-ID: 2-s2.0-85021273725

Finansiering

  • Norges forskningsråd

    • Prosjektkode: 243680

Beskrivelse Beskrivelse

Tittel

Calibration of imperfect models to biased observations

Sammendrag

In this paper, we propose a workflow for calibration of imperfect models to biased observations that involves model construction, model calibration, model criticism and model improvement. Model criticism is based on computation of model diagnostics which provide an indication of the validity of assumptions. During the model improvement step, we advocate identification of additional physically-motivated parameters based on examination of data mismatch after calibration and addition of bias correction terms. If model diagnostics indicates the presence of residual model error after parameters have been added, then we estimate a `total' observation error covariance matrix based on model discrepancy. We illustrate the approach with two examples involving prediction of the future velocity of fall of a sphere from a short time series of biased measurements with independent additive random noise. The models into which the data are assimilated contain model errors due to neglect of physical processes and neglect of uncertainty in parameters. In every case, the estimated total error covariance is larger than the true observation covariance implying that we need not attempt to match data to the accuracy of the measuring instrument. Predictions are much improved when all model improvement steps were taken.

Bidragsytere

Dean Oliver

  • Tilknyttet:
    Forfatter
    ved Uni Research CIPR ved NORCE Norwegian Research Centre AS

Miguel Angel Alfonzo

  • Tilknyttet:
    Forfatter
    ved Institutt for geovitenskap ved Universitetet i Bergen
  • Tilknyttet:
    Forfatter
    ved Uni Research CIPR ved NORCE Norwegian Research Centre AS
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