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
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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
Observed and model‐simulated diurnal cycles of precipitation over the contiguous United States
Dai, A., Giorgi, F., & Trenberth, K. E. (1999) · Journal of Geophysical Research: Atmospheres · doi:10.1029/98jd02720 · Cited by 483
Palmer, T. N. (2001) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.49712757202 · Cited by 466
Gibelin, A.-L., & Déqué, M. (2003) · Climate Dynamics · doi:10.1007/s00382-002-0277-1 · Cited by 429
Hydrological responses to dynamically and statistically downscaled climate model output
Wilby, R. L., Hay, L. E., Gutowski, W. J., et al. (2000) · Geophysical Research Letters · doi:10.1029/1999gl006078 · Cited by 337
Wilby, R. L., Whitehead, P. G., Wade, A. J., Butterfield, D., Davis, R. J., & Watts, G. (2006) · Journal of Hydrology · doi:10.1016/j.jhydrol.2006.04.033 · Cited by 261
Philipp, A., Della-Marta, P. M., Jacobeit, J., Fereday, D. R., Jones, P. D., Moberg, A., & Wanner, H. (2007) · Journal of Climate · doi:10.1175/jcli4175.1 · Cited by 239
On the Use of “Inflation” in Statistical Downscaling
von STORCH, H. (1999) · Journal of Climate · doi:10.1175/1520-0442(1999)012<3505:otuoii>2.0.co;2 · Cited by 223
Arnell, N. W. (2003) · Journal of Hydrology · doi:10.1016/s0022-1694(02)00288-3 · Cited by 205
Salathé, E. P. (2003) · International Journal of Climatology · doi:10.1002/joc.922 · Cited by 160
A simple statistical‐dynamical downscaling scheme based on weather types and conditional resampling
Boé, J., Terray, L., Florence Habets, L., & Martin, É. (2006) · Journal of Geophysical Research Atmospheres · doi:10.1029/2005jd006889 · Cited by 137
Self-citationRowell, D. P. (2006) · Climatic Change · doi:10.1007/s10584-006-9100-z · Cited by 91
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
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