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search.filters.applied.f.access: openAccess × Author: Lange, Stefan × DDC: 550 × Has files: Yes × Publisher: Katlenburg-Lindau : Copernics Publications ×

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    WFDE5: Bias-adjusted ERA5 reanalysis data for impact studies
    (Katlenburg-Lindau : Copernics Publications, 2020) Cucchi, Marco; Weedon, Graham P.; Amici, Alessandro; Bellouin, Nicolas; Lange, Stefan; Müller Schmied, Hannes; Hersbach, Hans; Buontempo, Carlo
    The WFDE5 dataset has been generated using the WATCH Forcing Data (WFD) methodology applied to surface meteorological variables from the ERA5 reanalysis. The WFDEI dataset had previously been generated by applying the WFD methodology to ERA-Interim. The WFDE5 is provided at 0.5 spatial resolution but has higher temporal resolution (hourly) compared to WFDEI (3-hourly). It also has higher spatial variability since it was generated by aggregation of the higher-resolution ERA5 rather than by interpolation of the lower-resolution ERA-Interim data. Evaluation against meteorological observations at 13 globally distributed FLUXNET2015 sites shows that, on average, WFDE5 has lower mean absolute error and higher correlation than WFDEI for all variables. Bias-adjusted monthly precipitation totals of WFDE5 result in more plausible global hydrological water balance components when analysed in an uncalibrated hydrological model (WaterGAP) than with the use of raw ERA5 data for model forcing. The dataset, which can be downloaded from https://doi.org/10.24381/cds.20d54e34 (C3S, 2020b), is distributed by the Copernicus Climate Change Service (C3S) through its Climate Data Store (CDS, C3S, 2020a) and currently spans from the start of January 1979 to the end of 2018. The dataset has been produced using a number of CDS Toolbox applications, whose source code is available with the data - allowing users to regenerate part of the dataset or apply the same approach to other data. Future updates are expected spanning from 1950 to the most recent year. A sample of the complete dataset, which covers the whole of the year 2016, is accessible without registration to the CDS at https://doi.org/10.21957/935p-cj60 (Cucchi et al., 2020). © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
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    The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
    (Katlenburg-Lindau : Copernics Publications, 2020) 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; Trotta, Carlo; Matteucci, Giorgio; D'Andrea, Ettore; Foltýnová, Lenka; Krejza, Jan; Ibrom, Andreas; Pilegaard, Kim; Loustau, Denis; Bonnefond, Jean-Marc; Berbigier, Paul; Picart, Delphine; Lafont, Sébastien; Dietze, Michael; Cameron, David; Vieno, Massimo; Tian, Hanqin; Palacios-Orueta, Alicia; Cicuendez, Victor; Recuero, Laura; Wiese, Klaus; Büchner, Matthias; Lange, Stefan; Volkholz, Jan; Kim, Hyungjun; Horemans, Joanna A.; Bohn, Friedrich; Steinkamp, Jörg; Chikalanov, Alexander; Weedon, Graham P.; Sheffield, Justin; Babst, Flurin; Vega del Valle, Iliusi; Suckow, Felicitas; Martel, Simon; Mahnken, Mats; Gutsch, Martin; Frieler, Katja
    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.