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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 10
Geosci. Model Dev., 10, 3793–3803, 2017
https://doi.org/10.5194/gmd-10-3793-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 3793–3803, 2017
https://doi.org/10.5194/gmd-10-3793-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model evaluation paper 17 Oct 2017

Model evaluation paper | 17 Oct 2017

Sensitivity analysis of the meteorological preprocessor MPP-FMI 3.0 using algorithmic differentiation

John Backman et al.
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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by John Backman on behalf of the Authors (30 Aug 2017)  Author's response    Manuscript
ED: Publish as is (03 Sep 2017) by David Ham
Publications Copernicus
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Short summary
Meteorological input parameters for urban- and local-scale dispersion models can be derived from meteorological observations. This study presents a sensitivity analysis of a meteorological model that utilises readily available meteorological data to derive specific parameters required to model the atmospheric dispersion of pollutants. The study shows that wind speed is the most fundamental meteorological input parameter followed by solar radiation.
Meteorological input parameters for urban- and local-scale dispersion models can be derived from...
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