The DOI matches its Crossref record.
Advancing dynamical prediction of Indian monsoon rainfall
Abstract
Despite advances in seasonal climate forecasting using dynamical models, skill in predicting the Indian monsoon by such methods has proven poor. Our analysis identifies a flaw in the hitherto popular design of prediction systems in which atmospheric models are driven with a projected ocean surface temperature. Such a configuration presupposes Indian monsoon variability to be a consequence solely of the atmosphere reacting to the ocean. It is becoming increasingly evident that the Indian monsoon is suitably described as a fully coupled ocean‐land‐atmospheric system, though implications for skill have not been demonstrated. We discover significant improvements in the skill of Indian monsoon predictions when atmospheric models are not constrained by specified observed SSTs in the Indian Ocean warm pool region. Evidence comes from intercomparing 50‐years of monsoon skill in atmospheric models using specified SSTs with skill in coupled ocean atmosphere 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
Cited by
Unraveling the Mystery of Indian Monsoon Failure During El Niño
Kumar, K. K., Rajagopalan, B., Hoerling, M., Bates, G., & Cane, M. (2006) · Science · doi:10.1126/science.1131152 · Cited by 784
Self-citationFundamental challenge in simulation and prediction of summer monsoon rainfall
Wang, B., Ding, Q., Fu, X., Kang, I., Jin, K., Shukla, J., & Doblas‐Reyes, F. (2005) · Geophysical Research Letters · doi:10.1029/2005gl022734 · Cited by 655
Wang, B., Lee, J.-Y., Kang, I.-S., Shukla, J., Park, C.-K., Kumar, A., Schemm, J., Cocke, S., Kug, J.-S., Luo, J.-J., et al. (2009) · Climate Dynamics · doi:10.1007/s00382-008-0460-0 · Cited by 409
Kucharski, F., Bracco, A., Yoo, J. H., & Molteni, F. (2007) · Journal of Climate · doi:10.1175/jcli4254.1 · Cited by 241
Dynamics of the boreal summer African monsoon in the NSIPP1 atmospheric model.
Giannini, A., Saravanan, R., & Chang, P. (2005) · Climate Dynamics · doi:10.1007/s00382-005-0056-x · Cited by 71
Metadata
- Authors
- Krishna Kumar, K., Hoerling, M., & Rajagopalan, B.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2005-04
- Volume
- 32
- Issue
- 8
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2107473870
- Cited by
- 235
- References
- 0
- FWCI
- 10.66
- 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: Advancing dynamical prediction of Indian monsoon rainfall. https://app.cochat.ai/papers/10.1029/2004gl021979
- The paper
- Krishna Kumar, K., Hoerling, M., & Rajagopalan, B. (2005). Advancing dynamical prediction of Indian monsoon rainfall. Geophysical Research Letters. https://doi.org/10.1029/2004gl021979
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.