In:
Earth System Science Data, Copernicus GmbH, Vol. 12, No. 2 ( 2020-06-12), p. 1295-1320
Abstract:
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, CO2, 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). 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.2020.006/; Reyer et al., 2020). 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://CRAN.R-project.org/package=ProfoundData; Silveyra
Gonzalez et al., 2020), which provides basic functions to explore, plot and
extract the data for model set-up, calibration and evaluation.
Type of Medium:
Online Resource
ISSN:
1866-3516
DOI:
10.5194/essd-12-1295-2020
DOI:
10.5194/essd-12-1295-2020-supplement
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2020
detail.hit.zdb_id:
2475469-9
