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The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests

Reyer, Christopher P. O.; Silveyra Gonzalez, Ramiro; Dolos, Klara; Hartig, Florian; Hauf, Ylva; Noack, Matthias; Lasch-Born, Petra; Rötzer, Thomas; Pretzsch, Hans; Meesenburg, Henning; Fleck, Stefan; Wagner, Markus; Bolte, Andreas; Sanders, Tanja G. M.; Kolari, Pasi; Mäkelä, Annikki; Vesala, Timo; Mammarella, Ivan; Pumpanen, Jukka; Collalti, Alessio; ... mehr

Abstract:
Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO$_{2}$, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000121174
Veröffentlicht am 10.07.2020
Originalveröffentlichung
DOI: 10.5194/essd-12-1295-2020
Web of Science
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Geographie und Geoökologie (IFGG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1866-3516
KITopen-ID: 1000121174
Erschienen in Earth system science data
Band 12
Heft 2
Seiten 1295–1320
Vorab online veröffentlicht am 12.06.2020
Nachgewiesen in Web of Science
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