Gutenberg Open Science: Implementation of a Lagrangian Stochastic Particle Trajectory Model (LaStTraM) to simulate concentration and flux footprints using the microclimate model ENVI-Met

Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-6512

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DC Field	Value	Language
dc.contributor.author	Simon, Helge	-
dc.contributor.author	Heusinger, Jannik	-
dc.contributor.author	Sinsel, Tim	-
dc.contributor.author	Weber, Stephan	-
dc.contributor.author	Bruse, Michael	-
dc.date.accessioned	2021-11-15T11:06:59Z	-
dc.date.available	2021-11-15T11:06:59Z	-
dc.date.issued	2021	-
dc.identifier.uri	https://openscience.ub.uni-mainz.de/handle/20.500.12030/6522	-
dc.description.abstract	The number of studies evaluating flux or concentration footprints has grown considerably in recent years. These footprints are vital to understand surface–atmosphere flux measurements, for example by eddy covariance. The newly developed backwards trajectory model LaStTraM (Lagrangian Stochastic Trajectory Model) is a post-processing tool, which uses simulation results of the holistic 3D microclimate model ENVI-met as input. The probability distribution of the particles is calculated using the Lagrangian Stochastic method. Combining LaStTraM with ENVI-met should allow us to simulate flux and concentration footprints in complex urban environments. Applications and evaluations were conducted through a comparison with the commonly used 2D models Kormann Meixner and Flux Footprint Predictions in two different meteorological cases (stable, unstable) and in three different detector heights. LaStTraM is capable of reproducing the results of the commonly used 2D models with high accuracy. In addition to the comparison with common footprint models, studies with a simple heterogeneous and a realistic, more complex model domain are presented. All examples show plausible results, thus demonstrating LaStTraM’s potential for the reliable calculation of footprints in homogeneous and heterogenous areas.	en_GB
dc.description.sponsorship	Open Access-Publizieren Universität Mainz / Universitätsmedizin Mainz	de
dc.language.iso	eng	de
dc.rights	CC BY	*
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	550 Geowissenschaften	de_DE
dc.subject.ddc	550 Earth sciences	en_GB
dc.title	Implementation of a Lagrangian Stochastic Particle Trajectory Model (LaStTraM) to simulate concentration and flux footprints using the microclimate model ENVI-Met	en_GB
dc.type	Zeitschriftenaufsatz	de
dc.identifier.doi	http://doi.org/10.25358/openscience-6512	-
jgu.type.dinitype	article	en_GB
jgu.type.version	Published version	de
jgu.type.resource	Text	de
jgu.organisation.department	FB 09 Chemie, Pharmazie u. Geowissensch.	de
jgu.organisation.number	7950	-
jgu.organisation.name	Johannes Gutenberg-Universität Mainz	-
jgu.rights.accessrights	openAccess	-
jgu.journal.title	Atmosphere	de
jgu.journal.volume	12	de
jgu.journal.issue	8	de
jgu.pages.alternative	977	de
jgu.publisher.year	2021	-
jgu.publisher.name	MDPI AG	de
jgu.publisher.place	Basel, Switzerland	de
jgu.publisher.uri	https://doi.org/10.3390/atmos12080977	de
jgu.publisher.issn	2073-4433	de
jgu.organisation.place	Mainz	-
jgu.subject.ddccode	550	de
jgu.publisher.doi	10.3390/atmos12080977
jgu.organisation.ror	https://ror.org/023b0x485
Appears in collections:	JGU-Publikationen

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