The DOI matches its Crossref record.
A microphysically based precipitation scheme for the UK meteorological office unified model
Abstract
Many numerical weather prediction models are moving towards more prognostic schemes for the prediction of ice and liquid water contents within clouds. This paper describes a large‐scale cloud and precipitation scheme developed for the UK Meteorological Office's Unified Model. It uses physically based transfer equations to predict ice as a prognostic variable. We review similar schemes and then describe our new scheme, giving examples of its performance in mesoscale forecasts compared with the current operational scheme and with observations. the microphysical processes occurring in a frontal cloud are well modelled. the prediction of supercooled stratocumulus cloud is much improved.
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
Precipitation Characteristics in Eighteen Coupled Climate Models
Dai, A. (2006) · Journal of Climate · doi:10.1175/jcli3884.1 · Cited by 1,098
Realism of Rainfall in a Very High-Resolution Regional Climate Model
Kendon, E. J., Roberts, N. M., Senior, C. A., & Roberts, M. J. (2012) · Journal of Climate · doi:10.1175/jcli-d-11-00562.1 · Cited by 503
The New Hadley Centre Climate Model (HadGEM1): Evaluation of Coupled Simulations
Johns, T. C., Durman, C. F., Banks, H. T., Roberts, M. J., McLaren, A. J., Ridley, J. K., Senior, C. A., Williams, K. D., Jones, A., Rickard, G. J., et al. (2006) · Journal of Climate · doi:10.1175/jcli3712.1 · Cited by 428
A Stochastic Parameterization for Deep Convection Based on Equilibrium Statistics
Plant, R. S., & Craig, G. C. (2008) · Journal of the Atmospheric Sciences · doi:10.1175/2007jas2263.1 · Cited by 285
Metadata
- Authors
- Wilson, D. R., & Ballard, S. P.
- Venue
- Quarterly Journal of the Royal Meteorological Society
- Publisher
- Wiley
- Published
- 1999-07
- Volume
- 125
- Issue
- 557
- Pages
- 1607-1636
- ISSN
- 0035-9009 (ISSN-L)
- 1477-870X
- OpenAlex
- W2161315815
- Cited by
- 672
- References
- 0
- FWCI
- 5.50
- 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: A microphysically based precipitation scheme for the UK meteorological office unified model. https://app.cochat.ai/papers/10.1002/qj.49712555707
- The paper
- Wilson, D. R., & Ballard, S. P. (1999). A microphysically based precipitation scheme for the UK meteorological office unified model. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.49712555707
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.