The DOI matches its Crossref record.
Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models
Open accessAbstract
We evaluated daily and monthly statistics of maximum and minimum temperatures and precipitation in an ensemble of 16 regional climate models (RCMs) forced by boundary conditions from reanalysis data for 1961-1990.A high-resolution gridded observational data set for land areas in Europe was used.Skill scores were calculated based on the match of simulated and observed empirical probability density functions.The evaluation for different variables, seasons and regions showed that some models were better/worse than others in an overall sense.It also showed that no model that was best/worst in all variables, seasons or regions.Biases in daily precipitation were most pronounced in the wettest part of the probability distribution where the RCMs tended to overestimate precipitation compared to observations.We also applied the skill scores as weights used to calculate weighted ensemble means of the variables.We found that weighted ensemble means were slightly better in comparison to observations than corresponding unweighted ensemble means for most seasons, regions and variables.A number of sensitivity tests showed that the weights were highly sensitive to the choice of skill score metric and data sets involved in the comparison.
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
Schreier, S. F., Suomi, I., Bröde, P., Formayer, H., Rieder, H. E., Nadeem, I., Jendritzky, G., Batchvarova, E., & Weihs, P. (2013) · International Journal of Biometeorology · doi:10.1007/s00484-012-0525-y · Cited by 27
Metadata
- Authors
- Kjellström, E., Boberg, F., Castro, M., Christensen, J., Nikulin, G., & Sánchez, E.
- Venue
- Climate Research
- Publisher
- Inter-Research Science Center
- Published
- 2010-12-09
- Volume
- 44
- Issue
- 2-3
- Pages
- 135-150
- ISSN
- 0936-577X (ISSN-L)
- 1616-1572
- OpenAlex
- W1975139612
- Cited by
- 181
- References
- 0
- FWCI
- 16.29
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models. https://app.cochat.ai/papers/10.3354/cr00932
- The paper
- Kjellström, E., Boberg, F., Castro, M., Christensen, J., Nikulin, G., & Sánchez, E. (2010). Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models. Climate Research. https://doi.org/10.3354/cr00932
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.