The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Global warming increases the frequency of river floods in Europe
Open accessAbstract
Abstract. EURO-CORDEX (Coordinated Downscaling Experiment over Europe), a new generation of downscaled climate projections, has become available for climate change impact studies in Europe. New opportunities arise in the investigation of potential effects of a warmer world on meteorological and hydrological extremes at regional scales. In this work, an ensemble of EURO-CORDEX RCP8.5 scenarios is used to drive a distributed hydrological model and assess the projected changes in flood hazard in Europe through the current century. Changes in magnitude and frequency of extreme streamflow events are investigated by statistical distribution fitting and peak over threshold analysis. A consistent method is proposed to evaluate the agreement of ensemble projections. Results indicate that the change in frequency of discharge extremes is likely to have a larger impact on the overall flood hazard as compared to the change in their magnitude. On average, in Europe, flood peaks with return periods above 100 years are projected to double in frequency within 3 decades.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An Overview of CMIP5 and the Experiment Design
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00094.1 · Cited by 14,052
Robustness and uncertainties in the new CMIP5 climate model projections
Knutti, R., & Sedláček, J. (2013) · Nature Climate Change · doi:10.1038/nclimate1716 · Cited by 1,569
Cited by
Ensemble flood risk assessment in Europe under high end climate scenarios
Alfieri, L., Feyen, L., Dottori, F., & Bianchi, A. (2015) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.09.004 · Cited by 346
Self-citationTapia, C., Abajo, B., Feliu, E., Mendizabal, M., Martinez, J. A., Fernández, J. G., Laburu, T., & Lejarazu, A. (2017) · Ecological Indicators · doi:10.1016/j.ecolind.2017.02.040 · Cited by 238
Kjellström, E., Nikulin, G., Strandberg, G., Christensen, O. B., Jacob, D., Keuler, K., Lenderink, G., van Meijgaard, E., Schär, C., Somot, S., et al. (2018) · Earth System Dynamics · doi:10.5194/esd-9-459-2018 · Cited by 202
Multi-Model Projections of River Flood Risk in Europe under Global Warming
Alfieri, L., Dottori, F., Betts, R., Salamon, P., & Feyen, L. (2018) · Climate · doi:10.3390/cli6010006 · Cited by 149
“were chosen among those with the best performance in reproducing the past climate patterns and variability [48].”
BackgroundSelf-citationIncrease in Population Exposure Due to Dry and Wet Extremes in India Under a Warming Climate
Kumar, R., & Mishra, V. (2020) · Earth's Future · doi:10.1029/2020ef001731 · Cited by 43
Metadata
- Authors
- Alfieri, L., Burek, P., Feyen, L., & Forzieri, G.
- Venue
- Hydrology and Earth System Sciences
- Publisher
- Copernicus GmbH
- Published
- 2015-05-11
- Volume
- 19
- Issue
- 5
- Pages
- 2247-2260
- ISSN
- 1027-5606 (ISSN-L)
- 1607-7938
- OpenAlex
- W1979388868
- Cited by
- 581
- References
- 2
- FWCI
- 32.24
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
