Reduction of uncertainties through Data Model Integration (DMI) - Bewerkingsoverzicht

MaartenDeRijcke op 3 aug 2011 om 13:48

2011-08-03T13:48:08Z

Wouter Kreiken: featured

2009-07-09T13:42:00Z

featured

Jackgeerlings: /* References */

2008-12-02T16:43:39Z

‎References

Margaretha op 11 jan 2008 om 15:14

2008-01-11T15:14:20Z

Joanne: /* Objective */

2007-12-11T08:21:03Z

‎Objective

Joanne op 11 dec 2007 om 08:20

2007-12-11T08:20:30Z

Joanne: /* See also */

2007-12-11T08:20:17Z

‎See also

Joanne: /* References */

2007-12-10T16:03:31Z

‎References

Joanne op 10 dec 2007 om 09:18

2007-12-10T09:18:01Z

Joanne: /* Introduction */

2007-12-10T09:17:01Z

‎Introduction

@@ Regel 94: / Regel 94: @@
-{{authors
+{{2Authors
 |AuthorID1=16024
 |AuthorFullName1= Gerritsen, Herman

← Oudere versie		Versie van 9 jul 2009 om 13:42
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		+	{{featured}}
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	This article describes how [[data]] and models can be combined in a structured way, in order to reduce uncertainties. This process is also called [[Data Model Integration (DMI)]]. This article describes the criteria which can be used to evaluate models, how to reduce uncertainties, and two DMI-approaches: [[model calibration]] and data assimilation.		This article describes how [[data]] and models can be combined in a structured way, in order to reduce uncertainties. This process is also called [[Data Model Integration (DMI)]]. This article describes the criteria which can be used to evaluate models, how to reduce uncertainties, and two DMI-approaches: [[model calibration]] and data assimilation.

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-{{author
+{{authors
-|AuthorID=16024
+|AuthorID1=16024
-|AuthorFullName= Gerritsen, Herman
+|AuthorFullName1= Gerritsen, Herman
-|AuthorName=Gerritsen, Herman}}
+|AuthorName1=Gerritsen, Herman
-{{author
+[[Category: Articles by Boogaard, Henk van den]]
-|AuthorID=16023
-|AuthorFullName= Boogaard, Henk van den
-|AuthorName=Boogaard, Henk van den}}
 [[Category:Theme_9]]

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 [[Category:Theme_9]]
 [[Category:Techniques and methods in coastal management]]
-[[Category:Evaluation and assesment in coastal management]]
+[[Category:Evaluation and assessment in coastal management]]
 [[Category:Coastal and marine information and knowledge management]]

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 ===Objective===
-The main goal of a [[model calibration]] is the identification of uncertain model parameters. The model is assumed to be perfect, except for a number of not well known parameters or “control variables”. These control variables may originate from parameterisations of uncertain coefficients in the model, initial or boundary conditions, and/or the external forcing. Measurements are used to obtain estimates for these parameters. These estimates are the values of these parameters for which, in some sense, the model outcomes agree best with the measurements. Therefore calibration is often also called “model fitting” or “parameter estimation”. Uncertainties in the measurements can be taken into account, and be used in the definition of the calibration criterion (see below) and the assessment of the uncertainties in the identified model parameters. [[Model calibration should not be confused with [[model validation]], for which a set of independent data is used and model forcing and parameters are fixed.
+The main goal of a [[model calibration]] is the identification of uncertain model parameters. The model is assumed to be perfect, except for a number of not well known parameters or “control variables”. These control variables may originate from parameterisations of uncertain coefficients in the model, initial or boundary conditions, and/or the external forcing. Measurements are used to obtain estimates for these parameters. These estimates are the values of these parameters for which, in some sense, the model outcomes agree best with the measurements. Therefore calibration is often also called “model fitting” or “parameter estimation”. Uncertainties in the measurements can be taken into account, and be used in the definition of the calibration criterion (see below) and the assessment of the uncertainties in the identified model parameters. [[Model calibration]] should not be confused with [[model validation]], for which a set of independent data is used and model forcing and parameters are fixed.
 ===Approach===

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	This article describes how [[data]] and models can be combined in a structured way, in order to reduce uncertainties. This process is also called [[Data Model Integration (DMI)]]. This article describes the criteria which can be used to evaluate models, how to reduce uncertainties, and two DMI-approaches: [[model calibration]] and data assimilation.		This article describes how [[data]] and models can be combined in a structured way, in order to reduce uncertainties. This process is also called [[Data Model Integration (DMI)]]. This article describes the criteria which can be used to evaluate models, how to reduce uncertainties, and two DMI-approaches: [[model calibration]] and data assimilation.

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 ==See also==
 Good examples of the application of data assimilation techniques can be found in:
-* [http://www.ecmwf.int/ weather forecasts]
+* [http://www.ecmwf.int/ Weather forecasts]
 * [http://www.rws.nl/themas/water/meetsystemen_watergegevens/index.aspx Water level forecasts (in Dutch)]
 ==References==

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 <references/>
-This article is written by Herman Gerritsen and Henk van den Boogaard from [http://www.wldelft.nl WL|Delft Hydraulics]
 [[Category:Theme_9]]

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 {{revision}}
-This article is currently to long for a WIKI-article and does not contain author-ID's.
+''This article does not contain author-ID's yet.''
 This article describes how [[data]] and models can be combined in a structured way, in order to reduce uncertainties. This process is also called [[Data Model Integration (DMI)]]. This article describes the criteria which can be used to evaluate models, how to reduce uncertainties, and two DMI-approaches: [[model calibration]] and data assimilation.

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 # (Sequential) '''data assimilation''' and data assimilation techniques: This may results in an improved forecast, detection of significant deviation from established patterns (faulty component, credit card use,…).
-[[Image:DMI.jpg|thumb|700px|centre|Figure 1: Data Model Integration approach to support the monitoring and assessment of marine systems]]
+[[Image:DMI.jpg|thumb|750px|centre|Figure 1: Data Model Integration approach to support the monitoring and assessment of marine systems]]
 ==Error criteria and Goodness of Fit==