The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Statistical and dynamical downscaling of the Seine basin climate for hydro‐meteorological studies
Abstract
Two downscaling methods designed for the study of the hydrological impact of climate change on the Seine basin in France are tested for present climate. First, a multivariate statistical downscaling (SD) methodology based on weather typing and conditional resampling is described. Then, a bias correction technique for dynamical downscaling based on quantile–quantile mapping is introduced. To evaluate the end‐to‐end SD methodology, the atmospheric forcing derived from the large‐scale circulation (LSC) of the ERA40 reanalysis by SD is used to force a hydrological model. Simulated discharges reproduce historical values reasonably well. Next, the dynamical and statistical approaches are compared using the Météo–France ARPEGE general circulation model in a variable resolution configuration (resolution around 60 km over France). The ARPEGE simulation is downscaled using the two methodologies, and hydrological simulations are performed. Regarding downscaled temperature and precipitation, the statistical approach is more efficient in reproducing the temporal and spatial autocorrelation properties. The simulated river discharges from the two approaches are nevertheless very similar: the two methods reproduce well the seasonal cycle and the daily distribution of streamflows. Finally, the results of the study are discussed from a practical impact study perspective. Copyright © 2007 Royal Meteorological Society
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
A Simple Parameterization of Land Surface Processes for Meteorological Models
Noilhan, J., & Planton, S. (1989) · Monthly Weather Review · doi:10.1175/1520-0493(1989)117<0536:aspols>2.0.co;2 · Cited by 2,166
Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs
Wood, A. W., Leung, L. R., Sridhar, V., & Lettenmaier, D. P. (2004) · Climatic Change · doi:10.1023/b:clim.0000013685.99609.9e · Cited by 1,886
Quantification of modelling uncertainties in a large ensemble of climate change simulations.
Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., & Stainforth, D. A. (2004) · Nature · doi:10.1038/nature02771 · Cited by 1,655
Some applications of statistics to meteorology
Panofsky, H. A., Brier, G. W., & Best, W. H. (1958) · University of Michigan Library Repository · Cited by 1,083
Improved Extended Reconstruction of SST (1854–1997)
Smith, T. M., & Reynolds, R. W. (2004) · Journal of Climate · doi:10.1175/1520-0442(2004)017<2466:ieros>2.0.co;2 · Cited by 1,031
Zorita, E., & von Storch, H. (1999) · Journal of Climate · doi:10.1175/1520-0442(1999)012<2474:tamaas>2.0.co;2 · Cited by 758
DEQUE, M. (2007) · Global and Planetary Change · doi:10.1016/j.gloplacha.2006.11.030 · Cited by 709
Bias reduction in short records of satellite soil moisture
Reichle, R. H., & Koster, R. D. (2004) · Geophysical Research Letters · doi:10.1029/2004gl020938 · Cited by 626
The ARPEGE/IFS atmosphere model: a contribution to the French community climate modelling
Déqué, M., Dreveton, C., Braun, A., & Cariolle, D. (1994) · Climate Dynamics · doi:10.1007/bf00208992 · Cited by 590
Diaz-Nieto, J., & Wilby, R. L. (2005) · Climatic Change · doi:10.1007/s10584-005-1157-6 · Cited by 494
Cited by
Cannon, A. J., Sobie, S. R., & Murdock, T. Q. (2015) · Journal of Climate · doi:10.1175/jcli-d-14-00754.1 · Cited by 1,700
Gudmundsson, L., Bremnes, J. B., Haugen, J. E., & Engen-Skaugen, T. (2012) · Hydrology and Earth System Sciences · doi:10.5194/hess-16-3383-2012 · Cited by 1,318
A trend-preserving bias correction – the ISI-MIP approach
Hempel, S., Frieler, K., Warszawski, L., Schewe, J., & Piontek, F. (2013) · Earth System Dynamics · doi:10.5194/esd-4-219-2013 · Cited by 1,238
“…in the variance or even higher moments of the simulated data are adjusted to the observations Published by Copernicus Publications on behalf of the European Geosciences Union. by parametric or non-parametric (empirical) quantile mapping (Boe et al., 2007; Piani et al., 2010; Themeßl et al., 2011).”
MethodJakob Themeßl, M., Gobiet, A., & Leuprecht, A. (2011) · International Journal of Climatology · doi:10.1002/joc.2168 · Cited by 770
Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6
Mishra, V., Bhatia, U., & Tiwari, A. D. (2020) · Scientific Data · doi:10.1038/s41597-020-00681-1 · Cited by 472
Metadata
- Authors
- Boé, J., Terray, L., Habets, F., & Martin, E.
- Venue
- International Journal of Climatology
- Publisher
- Wiley
- Published
- 2007-08-22
- Volume
- 27
- Issue
- 12
- Pages
- 1643-1655
- ISSN
- 0899-8418 (ISSN-L)
- 1097-0088
- OpenAlex
- W2053974573
- Cited by
- 572
- References
- 21
- FWCI
- 4.13
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Statistical and dynamical downscaling of the Seine basin climate for hydro‐meteorological studies. https://app.cochat.ai/papers/10.1002/joc.1602
- The paper
- Boé, J., Terray, L., Habets, F., & Martin, E. (2007). Statistical and dynamical downscaling of the Seine basin climate for hydro‐meteorological studies. International Journal of Climatology. https://doi.org/10.1002/joc.1602
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.
