Global Lake Evaporation Estimates by Integrating Penman Method with Equilibrium Temperature Approach
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Le résumé fourni par la source
Abstract Modeling evaporation E from inland water bodies is challenging largely due to the uncertainties of input data, particularly surface water temperature that plays a key role in the available energy, i.e., net radiation R n minus rate of water heat storage change G . The equilibrium temperature approach (ETA) for estimating water surface temperature offers an alternative method to calculate R n and G using standard meteorological data. This study evaluates the global lake E estimates from the widely used Penman model (PM) coupled with the ETA (PM-ETA) against field observations and model simulations from the Lake, Ice, Snow, and Sediment Simulator (LISSS). Our analysis reveals that the PM-ETA tends to overestimate E by approximately 36% and 24% compared to observations and the LISSS simulations, respectively, despite being driven by the same input data. The biases of the PM-ETA E are more pronounced in the cold and polar regions with distinct seasonality of R n and G . Furthermore, the E trends from the PM-ETA deviate from the LISSS simulations over the period of 2001–16 due to the bias trends in the available energy. By incorporating the LISSS-simulated R n and G into the PM, the bias in E is reduced to less than ±5% compared to the LISSS results. This study highlights the need to improve the available energy input of the PM to improve the estimates of global lake E for better water resource management and planning. Significance Statement This study addresses a crucial challenge in modeling evaporation E from inland water bodies—uncertainties in surface water temperature and available energy inputs, particularly net radiation R n and rate of heat storage change G . By evaluating the widely used Penman model (PM) coupled with the equilibrium temperature approach (ETA), we reveal a tendency for the PM-ETA to overestimate E globally, with the largest biases observed in cold and polar regions. Incorporating higher-quality R n and G estimates from the Lake, Ice, Snow, and Sediment Simulator (LISSS) significantly reduces these biases. These findings highlight the importance of alternative higher-quality data products for available energy inputs for improving E estimates by the PM.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Global Lake Evaporation Estimates by Integrating Penman Method with Equilibrium Temperature Approach
- Date Crossref
- 01/09/2025
- Éditeur
- American Meteorological Society
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Commonwealth Scientific and Industrial Research Organisation pays non établi dans la noticeOrganisme public
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Agriculture and Food pays non établi dans la noticeStructure de recherche
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ACT Government pays non établi dans la noticeOrganisme public
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Washington State University Department of Civil and Environmental Engineering pays non établi dans la noticeUniversité ou école supérieure
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Georgia Institute of Technology pays non établi dans la noticeUniversité ou école supérieure
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Saint Anthony College of Nursing pays non établi dans la noticeUniversité ou école supérieure
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Clunies Ross Street pays non établi dans la noticeInstitution
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School of Civil and Environmental Engineering pays non établi dans la noticeUniversité ou école supérieure
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University of Minnesota Department of Mechanical Engineering and St. Anthony Falls Laboratory pays non établi dans la noticeUniversité ou école supérieure
Commonwealth Scientific and Industrial Research Organisation, Agriculture and Food et ACT Government, avec 6 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.