The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability
Open accessAbstract
This review surveys the basic theories, observational methods, satellite algorithms, and land surface models for terrestrial evapotranspiration, E (or λE, i.e., latent heat flux), including a long‐term variability and trends perspective. The basic theories used to estimate E are the Monin‐Obukhov similarity theory (MOST), the Bowen ratio method, and the Penman‐Monteith equation. The latter two theoretical expressions combine MOST with surface energy balance. Estimates of E can differ substantially between these three approaches because of their use of different input data. Surface and satellite‐based measurement systems can provide accurate estimates of diurnal, daily, and annual variability of E. But their estimation of longer time variability is largely not established. A reasonable estimate of E as a global mean can be obtained from a surface water budget method, but its regional distribution is still rather uncertain. Current land surface models provide widely different ratios of the transpiration by vegetation to total E. This source of uncertainty therefore limits the capability of models to provide the sensitivities of E to precipitation deficits and land cover change.
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
Global hydrological cycles and world water resources
Oki, T., & Kanae, S. (2006) · Science · doi:10.1126/science.1128845 · Cited by 4,392
Climate–Carbon Cycle Feedback Analysis: Results from the C4MIP Model Intercomparison
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V., Cadule, P., Doney, S., Eby, M., Fung, I., et al. (2006) · Journal of Climate · doi:10.1175/jcli3800.1 · Cited by 2,902
Cited by
Global warming and changes in drought
Trenberth, K. E., Dai, A., van der Schrier, G., Jones, P. D., Barichivich, J., Briffa, K. R., & Sheffield, J. (2014) · Nature Climate Change · doi:10.1038/nclimate2067 · Cited by 3,382
Improved allometric models to estimate the aboveground biomass of tropical trees
Chave, J., Réjou‐Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B. C., Duque, A., Eid, T., Fearnside, P. M., Goodman, R. C., et al. (2014) · Global Change Biology · doi:10.1111/gcb.12629 · Cited by 3,131
Miralles, D. G., Gentine, P., Seneviratne, S. I., & Teuling, A. J. (2019) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13912 · Cited by 1,080
Remote sensing of drought: Progress, challenges and opportunities
AghaKouchak, A., Farahmand, A., Melton, F. S., Teixeira, J., Anderson, M. C., Wardlow, B. D., & Hain, C. R. (2015) · Reviews of Geophysics · doi:10.1002/2014rg000456 · Cited by 989
Modeling Soil Processes: Review, Key Challenges, and New Perspectives
Vereecken, H., Schnepf, A., Hopmans, J. W., Javaux, M., Or, D., Roose, T., Vanderborght, J., Young, M. H., Amelung, W., Aitkenhead, M., et al. (2016) · Vadose Zone Journal · doi:10.2136/vzj2015.09.0131 · Cited by 833
Metadata
- Authors
- Wang, K., & Dickinson, R. E.
- Venue
- Reviews of Geophysics
- Publisher
- American Geophysical Union (AGU)
- Published
- 2012-05-24
- Volume
- 50
- Issue
- 2
- ISSN
- 0096-1043 (ISSN-L)
- 8755-1209
- 1944-9208
- OpenAlex
- W2167453193
- Cited by
- 1,504
- References
- 2
- FWCI
- 43.54
- 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: A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. https://app.cochat.ai/papers/10.1029/2011rg000373
- The paper
- Wang, K., & Dickinson, R. E. (2012). A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. Reviews of Geophysics. https://doi.org/10.1029/2011rg000373
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.