The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Added value of regional climate modeling over areas characterized by complex terrain—Precipitation over the Alps
Open accessAbstract
We present an analysis of the added value (AV) of downscaling via regional climate model (RCM) nesting with respect to the driving global climate models (GCMs). We analyze ensembles of driving GCM and nested RCM (two resolutions, 0.44° and 0.11°) simulations for the late 20th and late 21st centuries from the CMIP5, EURO‐CORDEX, and MED‐CORDEX experiments, with a focus on the Alpine region. Different metrics of AV are investigated, measuring aspects of precipitation where substantial AV can be expected in mountainous terrains: spatial pattern of mean precipitation, daily precipitation intensity distribution, and daily precipitation extremes tails. Comparison with a high‐quality, fine‐scale (5 km) gridded observational data set shows substantial AV of RCM downscaling for all metrics selected, and results are mostly improved compared to the driving GCMs also when the RCM fields are upscaled at the scale of the GCM resolution. We also find consistent improvements in the high‐resolution (0.11°) versus medium‐resolution (0.44°) RCM simulations. Finally, we find that the RCM downscaling substantially modulates the GCM‐produced precipitation change signal in future climate projections, particularly in terms of fine‐scale spatial pattern associated with the complex topography of the region. Our results thus point to the important role that high‐resolution nested RCMs can play in the study of climate change over areas characterized by complex topographical features.
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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
The next generation of scenarios for climate change research and assessment
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., et al. (2010) · Nature · doi:10.1038/nature08823 · Cited by 6,467
Griggs, D. J., & Noguer, M. (2002) · Weather · doi:10.1256/004316502320517344 · Cited by 5,754
EURO-CORDEX: new high-resolution climate change projections for European impact research
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., et al. (2014) · Regional Environmental Change · doi:10.1007/s10113-013-0499-2 · Cited by 2,730
Addressing climate information needs at the regional level: the CORDEX framework
Giorgi, F., Jones, C., & Asrar, G. (2009) · Cited by 1,706
Self-citationDevelopment and evaluation of an Earth-System model – HadGEM2
Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P., Hinton, T., Hughes, J., Jones, C. D., Joshi, M., Liddicoat, S., et al. (2011) · Geoscientific Model Development · doi:10.5194/gmd-4-1051-2011 · Cited by 1,516
Mean seasonal and spatial variability in gauge‐corrected, global precipitation
Legates, D. R., & Willmott, C. J. (1990) · International Journal of Climatology · doi:10.1002/joc.3370100202 · Cited by 1,468
Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections
Sillmann, J., Kharin, V. V., Zwiers, F. W., Zhang, X., & Bronaugh, D. (2013) · Journal of Geophysical Research: Atmospheres · doi:10.1002/jgrd.50188 · Cited by 1,466
RegCM4: model description and preliminary tests over multiple CORDEX domains
Giorgi, F., Coppola, E., Solmon, F., Mariotti, L., Sylla, M., Bi, X., Elguindi, N., Diro, G., Nair, V, Giuliani, G., et al. (2012) · Climate Research · doi:10.3354/cr01018 · Cited by 1,456
Self-citationThe CNRM-CM5.1 global climate model: description and basic evaluation
Voldoire, A., Sanchez-Gomez, E., Salas y Mélia, D., Decharme, B., Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A., Chevallier, M., et al. (2013) · Climate Dynamics · doi:10.1007/s00382-011-1259-y · Cited by 1,366
Cited by
WCRP COordinated Regional Downscaling EXperiment (CORDEX): a diagnostic MIP for CMIP6
Gutowski Jr., W. J., Giorgi, F., Timbal, B., Frigon, A., Jacob, D., Kang, H.-S., Raghavan, K., Lee, B., Lennard, C., Nikulin, G., et al. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-4087-2016 · Cited by 462
Self-citationEnhanced summer convective rainfall at Alpine high elevations in response to climate warming
Giorgi, F., Torma, C., Coppola, E., Ban, N., Schär, C., & Somot, S. (2016) · Nature Geoscience · doi:10.1038/ngeo2761 · Cited by 284
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Metadata
- Authors
- Torma, C., Giorgi, F., & Coppola, E.
- Venue
- Journal of Geophysical Research: Atmospheres
- Publisher
- American Geophysical Union (AGU)
- Published
- 2015-05-12
- Volume
- 120
- Issue
- 9
- Pages
- 3957-3972
- ISSN
- 0148-0227 (ISSN-L)
- 2169-897X
- 2169-8996
- OpenAlex
- W1751190512
- Cited by
- 364
- References
- 36
- FWCI
- 14.78
- Type
- journal article
- Language
- en
- Open access
- bronze
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