The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
State‐of‐the‐art with regional climate models
Abstract
Regional climate models are used by a large number of groups, for more or less all regions of the world. Regional climate models are complementary to global climate models. A typical use of regional climate models is to add further detail to global climate analyses or simulations, or to study climate processes in more detail than global models allow. The relationship between global and regional climate models is much akin to that of global and regional weather forecasting models. Over the past 20 years, the development of regional climate models has led to increased resolution, longer model runs, and steps towards regional climate system models. During recent years, community efforts have started to emerge in earnest, which can be expected to further advance the state‐of‐the‐art in regional climate modeling. Applications of regional climate models span both the past and possible future climates, facilitating climate impact studies, information and support to climate policy, and adaptation. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Climate Models and Modeling > Earth System Models
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
Christensen, J. H., Boberg, F., Christensen, O. B., & Lucas‐Picher, P. (2008) · Geophysical Research Letters · doi:10.1029/2008gl035694 · Cited by 729
Fine-scale processes regulate the response of extreme events to global climate change
Diffenbaugh, N. S., Pal, J. S., Trapp, R. J., & Giorgi, F. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506042102 · Cited by 498
Bayesian multi-model projection of climate: bias assumptions and interannual variability
Buser, C. M., Künsch, H. R., Lüthi, D., Wild, M., & Schär, C. (2009) · Climate Dynamics · doi:10.1007/s00382-009-0588-6 · Cited by 181
Cited by
Regional Climate Models Add Value to Global Model Data: A Review and Selected Examples
Feser, F., Rockel, B., von Storch, H., Winterfeldt, J., & Zahn, M. (2011) · Bulletin of the American Meteorological Society · doi:10.1175/2011bams3061.1 · Cited by 508
Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling
Sillero, N., Arenas-Castro, S., Enriquez‐Urzelai, U., Vale, C. G., Sousa-Guedes, D., Martínez-Freiría, F., Real, R., & Barbosa, A. M. (2021) · Ecological Modelling · doi:10.1016/j.ecolmodel.2021.109671 · Cited by 456
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
Sha, Y., Gagne II, D. J., West, G., & Stull, R. (2020) · Journal of Applied Meteorology and Climatology · doi:10.1175/jamc-d-20-0057.1 · Cited by 141
Stochastic models support rapid peopling of Late Pleistocene Sahul
Bradshaw, C. J. A., Norman, K., Ulm, S., Williams, A. N., Clarkson, C., Chadœuf, J., Lin, S. C., Jacobs, Z., Roberts, R. G., Bird, M. I., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21551-3 · Cited by 58
Metadata
- Authors
- Rummukainen, M.
- Venue
- WIREs Climate Change
- Publisher
- Wiley
- Published
- 2009-12-22
- Volume
- 1
- Issue
- 1
- Pages
- 82-96
- ISSN
- 1757-7780 (ISSN-L)
- 1757-7799
- OpenAlex
- W2142463025
- Cited by
- 698
- References
- 3
- FWCI
- 22.52
- 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
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.
