The DOI matches its Crossref record.
Coordinated Global and Regional Climate Modeling*
Abstract
A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.
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
Cited by
Attribution of the Influence of Human‐Induced Climate Change on an Extreme Fire Season
Kirchmeier‐Young, M. C., Gillett, N. P., Zwiers, F. W., Cannon, A. J., & Anslow, F. S. (2019) · Earth's Future · doi:10.1029/2018ef001050 · Cited by 323
Human influence has intensified extreme precipitation in North America
Kirchmeier-Young, M. C., & Zhang, X. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1921628117 · Cited by 288
Estimating concurrent climate extremes: A conditional approach
Huang, W. K., Monahan, A. H., & Zwiers, F. W. (2021) · Weather and Climate Extremes · doi:10.1016/j.wace.2021.100332 · Cited by 23
Metadata
- Authors
- Scinocca, J. F., Kharin, V. V., Jiao, Y., Qian, M. W., Lazare, M., Solheim, L., Flato, G. M., Biner, S., Desgagne, M., & Dugas, B.
- Venue
- Journal of Climate
- Publisher
- American Meteorological Society
- Published
- 2015-12-22
- Volume
- 29
- Issue
- 1
- Pages
- 17-35
- ISSN
- 0894-8755 (ISSN-L)
- 1520-0442
- OpenAlex
- W1923217618
- Cited by
- 231
- References
- 0
- FWCI
- 13.97
- 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: Coordinated Global and Regional Climate Modeling*. https://app.cochat.ai/papers/10.1175/jcli-d-15-0161.1
- The paper
- Scinocca, J. F., Kharin, V. V., Jiao, Y., Qian, M. W., Lazare, M., Solheim, L., Flato, G. M., Biner, S., Desgagne, M., & Dugas, B. (2016). Coordinated Global and Regional Climate Modeling*. Journal of Climate. https://doi.org/10.1175/jcli-d-15-0161.1
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.