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- Blanke, Jan HendrikLund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science (author)
Effect of climate data on simulated carbon and nitrogen balances for Europe
- Article/chapterEnglish2016
Publisher, publication year, extent ...
- 2016
- 20 s.
Numbers
- LIBRIS-ID:oai:lup.lub.lu.se:58bccab0-7ce4-47cb-b2e1-d0db4bcc2d79
- https://lup.lub.lu.se/record/58bccab0-7ce4-47cb-b2e1-d0db4bcc2d79URI
- https://doi.org/10.1002/2015JG003216DOI
Supplementary language notes
- Language:English
- Summary in:English
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Notes
- In this study, we systematically assess the spatial variability in carbon and nitrogen balance simulations related to the choice of global circulation models (GCMs), representative concentration pathways (RCPs), spatial resolutions, and the downscaling methods used as calculated with LPJ-GUESS. We employed a complete factorial design and performed 24 simulations for Europe with different climate input data sets and different combinations of these four factors. Our results reveal that the variability in simulated output in Europe is moderate with 35.6%–93.5% of the total variability being common among all combinations of factors. The spatial resolution is the most important factor among the examined factors, explaining 1.5%–10.7% of the total variability followed by GCMs (0.3%–7.6%), RCPs (0%–6.3%), and downscaling methods (0.1%–4.6%). The higher-order interactions effect that captures nonlinear relations between the factors and random effects is pronounced and accounts for 1.6%–45.8% to the total variability. The most distinct hot spots of variability include the mountain ranges in North Scandinavia and the Alps, and the Iberian Peninsula. Based on our findings, we advise to conduct the application of models such as LPJ-GUESS at a reasonably high spatial resolution which is supported by the model structure. There is no notable gain in simulations of ecosystem carbon and nitrogen stocks and fluxes from using regionally downscaled climate in preference to bias-corrected, bilinearly interpolated CMIP5 projections.
Subject headings and genre
- NATURVETENSKAP Geovetenskap och miljövetenskap Klimatforskning hsv//swe
- NATURAL SCIENCES Earth and Related Environmental Sciences Climate Research hsv//eng
- climate data
- DGVM
- downscaling
- LPJ-GUESS
- sensitivity
- spatial resolution
Added entries (persons, corporate bodies, meetings, titles ...)
- Lindeskog, MatsLund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science(Swepub:lu)mmb-mli (author)
- Lindström, JohanLund University,Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH(Swepub:lu)mats-jli (author)
- Lehsten, VeikoLund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science(Swepub:lu)nate-vel (author)
- Institutionen för naturgeografi och ekosystemvetenskapNaturvetenskapliga fakulteten (creator_code:org_t)
Related titles
- In:Journal of Geophysical Research - Biogeosciences121:5, s. 1352-13712169-8953
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