The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The 2010/2011 snow season in California's Sierra Nevada: Role of atmospheric rivers and modes of large-scale variability
Abstract
[1] The anomalously snowy winter season of 2010/2011 in the Sierra Nevada is analyzed in terms of snow water equivalent (SWE) anomalies and the role of atmospheric rivers (ARs)—narrow channels of enhanced meridional water vapor transport between the tropics and extratropics. Mean April 1 SWE was 0.44 m (56%) above normal averaged over 100 snow sensors. AR occurrence was anomalously high during the period, with 20 AR dates during the season and 14 in the month of December 2010, compared to the mean occurrence of nine dates per season. Fifteen out of the 20 AR dates were associated with the negative phases of the Arctic Oscillation (AO) and the Pacific-North American (PNA) teleconnection pattern. Analysis of all winter ARs in California during water years 1998–2011 indicates more ARs occur during the negative phase of AO and PNA, with the increase between positive and negative phases being ∼90% for AO, and ∼50% for PNA. The circulation pattern associated with concurrent negative phases of AO and PNA, characterized by cyclonic anomalies centered northwest of California, provides a favorable dynamical condition for ARs. The analysis suggests that the massive Sierra Nevada snowpack during the 2010/2011 winter season is primarily related to anomalously high frequency of ARs favored by the joint phasing of −AO and −PNA, and that a secondary contribution is from increased snow accumulation during these ARs favored by colder air temperatures associated with −AO, −PNA, and La Niña.
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
Moore, B. J., Neiman, P. J., Ralph, F. M., & Barthold, F. E. (2012) · Monthly Weather Review · doi:10.1175/mwr-d-11-00126.1 · Cited by 219
Self-citation
Cited by
Detection of atmospheric rivers: Evaluation and application of an algorithm for global studies
Guan, B., & Waliser, D. E. (2015) · Journal of Geophysical Research: Atmospheres · doi:10.1002/2015jd024257 · Cited by 717
Self-citationExtreme winds and precipitation during landfall of atmospheric rivers
Waliser, D., & Guan, B. (2017) · Nature Geoscience · doi:10.1038/ngeo2894 · Cited by 432
Self-citationHow Do Atmospheric Rivers Form?
Dacre, H. F., Clark, P. A., Martinez-Alvarado, O., Stringer, M. A., & Lavers, D. A. (2015) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-14-00031.1 · Cited by 310
All-Season Climatology and Variability of Atmospheric River Frequencies over the North Pacific
Mundhenk, B. D., Barnes, E. A., & Maloney, E. D. (2016) · Journal of Climate · doi:10.1175/jcli-d-15-0655.1 · Cited by 264
Lute, A. C., Abatzoglou, J. T., & Hegewisch, K. C. (2015) · Water Resources Research · doi:10.1002/2014wr016267 · Cited by 121
Metadata
- Authors
- Guan, B., Molotch, N. P., Waliser, D. E., Fetzer, E. J., & Neiman, P. J.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 2013-10
- Volume
- 49
- Issue
- 10
- Pages
- 6731-6743
- ISSN
- 0043-1397 (ISSN-L)
- OpenAlex
- W1911058877
- Cited by
- 166
- References
- 1
- FWCI
- 7.81
- 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: The 2010/2011 snow season in California's Sierra Nevada: Role of atmospheric rivers and modes of large-scale variability. https://app.cochat.ai/papers/10.1002/wrcr.20537
- The paper
- Guan, B., Molotch, N. P., Waliser, D. E., Fetzer, E. J., & Neiman, P. J. (2013). The 2010/2011 snow season in California's Sierra Nevada: Role of atmospheric rivers and modes of large-scale variability. Water Resources Research. https://doi.org/10.1002/wrcr.20537
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.