The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
REPRESENTING MODEL UNCERTAINTY IN WEATHER AND CLIMATE PREDICTION
Abstract
▪ Abstract Weather and climate predictions are uncertain, because both forecast initial conditions and the computational representation of the known equations of motion are uncertain. Ensemble prediction systems provide the means to estimate the flow-dependent growth of uncertainty during a forecast. Sources of uncertainty must therefore be represented in such systems. In this paper, methods used to represent model uncertainty are discussed. It is argued that multimodel and related ensembles are vastly superior to corresponding single-model ensembles, but do not provide a comprehensive representation of model uncertainty. A relatively new paradigm is discussed, whereby unresolved processes are represented by computationally efficient stochastic-dynamic schemes.
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
Climate Change 2001: The Scientific Basis
Cooper, R. N., Houghton, J. T., McCarthy, J. J., & Metz, B. (2002) · Foreign Affairs · doi:10.2307/20033020 · Cited by 12,889
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
Forecast Verification: A Practitioner's Guide in Atmospheric Science
(2011) · Wiley eBooks · doi:10.1002/9781119960003 · Cited by 1,267
Ensemble Forecasting at NMC: The Generation of Perturbations
Toth, Z., & Kalnay, E. (1993) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1993)074<2317:efantg>2.0.co;2 · Cited by 1,222
Weather Prediction by Numerical Process
Phillips, N. A., & Richardson, L. F. (1966) · Mathematics of Computation · doi:10.2307/2003575 · Cited by 1,177
Uncertainty in predictions of the climate response to rising levels of greenhouse gases
Stainforth, D. A., Aina, T., Christensen, C., Collins, M., Faull, N., Frame, D. J., Kettleborough, J. A., Knight, S., Martin, A., Murphy, J. M., et al. (2005) · Nature · doi:10.1038/nature03301 · Cited by 1,166
Stochastic representation of model uncertainties in the ECMWF ensemble prediction system
Buizza, R., Milleer, M., & Palmer, T. N. (1999) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.49712556006 · Cited by 1,103
Self-citationWeather Prediction by Numerical Process.
Bennett, A. A., & Richardson, L. F. (1923) · The American Mathematical Monthly · doi:10.2307/2298921 · Cited by 1,083
Predictability – a problem partly solved
Lorenz, E. N. (2006) · Predictability of Weather and Climate · doi:10.1017/cbo9780511617652.004 · Cited by 1,046
Palmer, T. N., Alessandri, A., Andersen, U., Cantelaube, P., Davey, M., Délécluse, P., Déqué, M., Díez, E., Doblas-Reyes, F. J., Feddersen, H., et al. (2004) · Bulletin of the American Meteorological Society · doi:10.1175/bams-85-6-853 · Cited by 959
Self-citation
Cited by
The use of the multi-model ensemble in probabilistic climate projections
Tebaldi, C., & Knutti, R. (2007) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2007.2076 · Cited by 1,862
Accurate medium-range global weather forecasting with 3D neural networks
Bi, K., Xie, L., Zhang, H., Chen, X., Gu, X., & Tian, Q. (2023) · Nature · doi:10.1038/s41586-023-06185-3 · Cited by 1,670
Seasonal climate predictability and forecasting: status and prospects
Doblas‐Reyes, F. J., García‐Serrano, J., Lienert, F., Biescas, A. P., & Rodrigues, L. R. L. (2013) · WIREs Climate Change · doi:10.1002/wcc.217 · Cited by 478
Self-citationMalaria early warnings based on seasonal climate forecasts from multi-model ensembles
Thomson, M. C., Doblas-Reyes, F. J., Mason, S. J., Hagedorn, R., Connor, S. J., Phindela, T., Morse, A. P., & Palmer, T. N. (2006) · Nature · doi:10.1038/nature04503 · Cited by 470
Self-citationEnforcing Analytic Constraints in Neural Networks Emulating Physical Systems
Beucler, T., Pritchard, M., Rasp, S., Ott, J., Baldi, P., & Gentine, P. (2021) · Physical Review Letters · doi:10.1103/physrevlett.126.098302 · Cited by 451
Metadata
- Authors
- Palmer, T. N., Shutts, G. J., Hagedorn, R., Doblas-Reyes, F. J., Jung, T., & Leutbecher, M.
- Venue
- Annual Review of Earth and Planetary Sciences
- Publisher
- Annual Reviews
- Published
- 2005-05-31
- Volume
- 33
- Issue
- 1
- Pages
- 163-193
- ISSN
- 0084-6597 (ISSN-L)
- 1545-4495
- OpenAlex
- W2105062738
- Cited by
- 320
- References
- 38
- FWCI
- 4.15
- 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: REPRESENTING MODEL UNCERTAINTY IN WEATHER AND CLIMATE PREDICTION. https://app.cochat.ai/papers/10.1146/annurev.earth.33.092203.122552
- The paper
- Palmer, T. N., Shutts, G. J., Hagedorn, R., Doblas-Reyes, F. J., Jung, T., & Leutbecher, M. (2005). REPRESENTING MODEL UNCERTAINTY IN WEATHER AND CLIMATE PREDICTION. Annual Review of Earth and Planetary Sciences. https://doi.org/10.1146/annurev.earth.33.092203.122552
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.
