Journal cover Journal topic
Earth System Science Data The data publishing journal
Journal topic

Journal metrics

Journal metrics

  • IF value: 10.951 IF 10.951
  • IF 5-year value: 9.899 IF 5-year
    9.899
  • CiteScore value: 9.74 CiteScore
    9.74
  • SNIP value: 3.111 SNIP 3.111
  • IPP value: 8.99 IPP 8.99
  • SJR value: 5.229 SJR 5.229
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 38 Scimago H
    index 38
  • h5-index value: 33 h5-index 33
Discussion papers
https://doi.org/10.5194/essd-2019-220
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-220
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 29 Nov 2019

Submitted as: data description paper | 29 Nov 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).

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

Christopher P. O. Reyer1, Ramiro Silveyra Gonzalez1, Klara Dolos2, Florian Hartig3, Ylva Hauf1, Matthias Noack4, Petra Lasch-Born1, Thomas Rötzer5, Hans Pretzsch5, Henning Mesenburg6, Stefan Fleck6, Markus Wagner6, Andreas Bolte7, Tanja G. M. Sanders7, Pasi Kolari8, Annikki Mäkelä8, Timo Vesala8, Ivan Mammarella8, Jukka Pumpanen9, Alessio Collalti10,11, Carlo Trotta11, Giorgio Matteucci12, Ettore D'Andrea12, Lenka Foltýnová13, Jan Krejza13, Andreas Ibrom14, Kim Pilegaard14, Denis Loustau15, Jean-Marc Bonnefond15, Paul Berbigier15, Delphine Picart15, Sébastien Lafont15, Michael Dietze16, David Cameron17, Massimo Vieno18, Hanqin Tian19, Alicia Palacios-Orueta20, Victor Cicuendez20, Laura Recuero20, Klaus Wiese20, Matthias Büchner1, Stefan Lange1, Jan Volkholz1, Hyungjun Kim21, Graham P. Weedon26, Justin Sheffield27, Iliusi Vega del Valle1, Felicitas Suckow1, Joanna A. Horemans22, Simon Martel16, Friedrich Bohn23, Jörg Steinkamp24, Alexander Chikalanov25, Mats Mahnken1, Martin Gutsch1, and Katja Frieler1 Christopher P. O. Reyer et al.
  • 1Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, P.O. Box 601203, 14412 Potsdam, Germany
  • 2Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
  • 3University of Regensburg, Regensburg, Germany
  • 4Fachagentur Nachwachsende Rohstoffe e.V. (FNR), Gülzow-Prüzen, Germany
  • 5Technical University of Munich, Munich, Germany
  • 6Northwest German Forest Research Institute, Göttingen, Germany
  • 7Thünen Institute of Forest Ecosystems, 16225 Eberswalde, Germany
  • 8University of Helsinki, Helsinki, Finland
  • 9University of Eastern Finland, Kuopio, Finland
  • 10National Research Council of Italy, Institute for Agriculture and Forestry Systems in the Mediterranean, Rende (CS), Italy
  • 11Department of Innovation in Biological, Agro-food and Forest System, University of Tuscia, 01100 Viterbo, Italy
  • 12National Research Council of Italy, Institute for Agriculture and Forestry System in the Mediterranean, Ercolano (NA), Italy
  • 13Global Change Research Institute, Brno, Czech Republic
  • 14Technical University of Denmark, Lyngby, Denmark
  • 15French National Institute for Agricultural Research, Bordeaux, France
  • 16Boston University, Boston, USA
  • 17Centre for Ecology and Hydrology, Edinburgh, UK
  • 18Centre for Ecology and Hydrology, Lancaster, UK
  • 19Auburn University, Auburn, USA
  • 20Technical University of Madrid, Madrid, Spain
  • 21University of Tokyo, Tokyo, Japan
  • 22Centre of Excellence PLECO, University of Antwerpen, Antwerpen, Belgium
  • 23Helmholz Center for Environmental Research, Leipzig, Germany
  • 24Senckenberg Biodiversity and Climate Research Centre, Senckenberg, Germany
  • 25University of Library Study and Information Technology, Sofia, Bulgaria
  • 26Met Office, Wallingford, UK
  • 27Princeton University, Dept. Civil & Environ. Eng., Princeton, NJ 08544, USA

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 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, CO2, nitrogen deposition, tree and forest stand-level, as well as 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). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a SQLite relational database or ASCII flat file version (at https://doi.org/10.5880/PIK.2019.008). The data policies of the individual, contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R-package (https://github.com/COST-FP1304-PROFOUND/ProfoundData), which provides basic functions to explore, plot, and extract the data for model set-up, calibration and evaluation.

Christopher P. O. Reyer et al.
Interactive discussion
Status: open (until 24 Jan 2020)
Status: open (until 24 Jan 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
  • RC1: 'Review', Anonymous Referee #1, 12 Dec 2019 Printer-friendly Version
Christopher P. O. Reyer et al.
Data sets

The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests C. P. O. Reyer, R. Silveyra Gonzalez, K. Dolos, F. Hartig, Y. Hauf, M. Noack, P. Lasch-Born, T. Rötzer, H. Pretzsch, H. Meesenburg, S. Fleck, M. Wagner, A. Bolte, T. Sanders, P. Kolari, A. Mäkelä, T. Vesala, I. Mammarella, J. Pumpanen, G. Matteucci, A. Collalti, E. D’Andrea, L. Foltýnová, J. Krejza, A. Ibrom, K. Pilegaard, D. Loustau, J.-M. Bonnefond, P. Berbigier, D. Picart, S. Lafont, M. Dietze, D. Cameron, M. Vieno, H. Tian, A. Palacios-Orueta, V. Cicuendez, L. Recuero, K. Wiese, M. Büchner, S. Lange, J. Volkholz, H. Kim, G. P. Weedon, J. Sheffield, I. Vega del Valle, F. Suckow, J. Horemans, S. Martel, F. Bohn, J. Steinkamp, A. Chikalanov, and K. Frieler https://doi.org/10.5880/PIK.2019.008

Christopher P. O. Reyer et al.
Viewed  
Total article views: 336 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
254 79 3 336 18 6 5
  • HTML: 254
  • PDF: 79
  • XML: 3
  • Total: 336
  • Supplement: 18
  • BibTeX: 6
  • EndNote: 5
Views and downloads (calculated since 29 Nov 2019)
Cumulative views and downloads (calculated since 29 Nov 2019)
Viewed (geographical distribution)  
Total article views: 195 (including HTML, PDF, and XML) Thereof 191 with geography defined and 4 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 13 Dec 2019
Download
Short summary
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 provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development.
Process-based vegetation models are widely used to predict local and global ecosystem dynamics...
Citation