Comparison of Five Eulerian Air Pollution Forecasting Systems for the Summer of 1999 Using the German Ozone Monitoring Data View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2002-05

AUTHORS

Stefan Tilmes, JØrgen Brandt, Frode FlatØy, Robert Bergström, Johannes Flemming, Joakim Langner, Jesper H. Christensen, Lise M. Frohn, Øystein Hov, Ingo Jacobsen, Eberthard Reimer, Rainer Stern, Jörg Zimmermann

ABSTRACT

Eulerian state-of-the-art air pollution forecasting systems on the European scale are operated routinely by several countries in Europe. DWD and FUB, both Germany, NERI, Denmark, NILU, Norway, and SMHI, Sweden, operate some of these systems. To apply such modeling systems, e.g. for regulatory purposes according to new EU directives, an evaluation and comparison of the model systems is fundamental in order to assess their reliability. One step in this direction is presented in this study: The model forecasts from all five systems have been compared to measurements of ground level ozone in Germany. The outstanding point in this investigation is the availability of a huge amount of data – from forecasts by the different model systems and from observations. This allows for a thorough interpretation of the findings and assures the significance of the observed features. Data from more than 300 measurement stations for a 5-month period (May–September 1999) of the German monitoring networks have been used in this comparison. Different spatial and temporal statistical parameters were applied in the evaluation. Generally, it was found that the most comprehensive models gave the best results. However, the less comprehensive and computational cheaper models also produced good results. The extensive comparison made it possible to point out weak points in the different models and to describe the individual model behavior for a full summer period in a climatological sense. The comparison also gave valuable information for an assessment of individual measurement stations and complete monitoring networks in terms of the representativeness of the observation data. More... »

PAGES

91-121

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1015753302760

DOI

http://dx.doi.org/10.1023/a:1015753302760

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010370078


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1023/a:1015753302760'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1023/a:1015753302760'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1015753302760'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1015753302760'


 

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