IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0268097.html
   My bibliography  Save this article

Incorporating the effect of heterogeneous surface heating into a semi-empirical model of the surface energy balance closure

Author

Listed:
  • Luise Wanner
  • Marc Calaf
  • Matthias Mauder

Abstract

It was discovered several decades ago that eddy covariance measurements systematically underestimate sensible and latent heat fluxes, creating an imbalance in the surface energy budget. Since then, many studies have addressed this problem and proposed a variety of solutions to the problem, including improvements to instruments and correction methods applied during data postprocessing. However, none of these measures have led to the complete closure of the energy balance gap. The leading hypothesis is that not only surface-attached turbulent eddies but also sub-mesoscale atmospheric circulations contribute to the transport of energy in the atmospheric boundary layer, and the contribution from organized motions has been grossly neglected. The problem arises because the transport of energy through these secondary circulations cannot be captured by the standard eddy covariance method given the relatively short averaging periods of time (~30 minutes) used to compute statistics. There are various approaches to adjust the measured heat fluxes by attributing the missing energy to the sensible and latent heat flux in different proportions. However, few correction methods are based on the processes causing the energy balance gap. Several studies have shown that the magnitude of the energy balance gap depends on the atmospheric stability and the heterogeneity scale of the landscape around the measurement site. Based on this, the energy balance gap within the surface layer has already been modelled as a function of a nonlocal atmospheric stability parameter by performing a large-eddy simulation study with idealized homogeneous surfaces. We have further developed this approach by including thermal surface heterogeneity in addition to atmospheric stability in the parameterization. Specifically, we incorporated a thermal heterogeneity parameter that was shown to relate to the magnitude of the energy balance gap. For this purpose, we use a Large-Eddy Simulation dataset of 28 simulations with seven different atmospheric conditions and three heterogeneous surfaces with different heterogeneity scales as well as one homogeneous surface. The newly developed model captures very well the variability in the magnitude of the energy balance gap under different conditions. The model covers a wide range of both atmospheric stabilities and landscape heterogeneity scales and is well suited for application to eddy covariance measurements since all necessary information can be modelled or obtained from a few additional measurements.

Suggested Citation

  • Luise Wanner & Marc Calaf & Matthias Mauder, 2022. "Incorporating the effect of heterogeneous surface heating into a semi-empirical model of the surface energy balance closure," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-21, June.
  • Handle: RePEc:plo:pone00:0268097
    DOI: 10.1371/journal.pone.0268097
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0268097
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0268097&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0268097?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Frederik De Roo & Sha Zhang & Sadiq Huq & Matthias Mauder, 2018. "A semi-empirical model of the energy balance closure in the surface layer," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-23, December.
    2. Graham, Scott L. & Kochendorfer, John & McMillan, Andrew M.S. & Duncan, Maurice J. & Srinivasan, M.S. & Hertzog, Gladys, 2016. "Effects of agricultural management on measurements, prediction, and partitioning of evapotranspiration in irrigated grasslands," Agricultural Water Management, Elsevier, vol. 177(C), pages 340-347.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Feng, Genxiang & Zhu, Chengli & Wu, Qingfeng & Wang, Ce & Zhang, Zhanyu & Mwiya, Richwell Mubita & Zhang, Li, 2021. "Evaluating the impacts of saline water irrigation on soil water-salt and summer maize yield in subsurface drainage condition using coupled HYDRUS and EPIC model," Agricultural Water Management, Elsevier, vol. 258(C).
    2. Anapalli, Saseendran S. & Pinnamaneni, Srinivasa R. & Reddy, Krishna N. & Sui, Ruixiu & Singh, Gurbir, 2022. "Investigating soybean (Glycine max L.) responses to irrigation on a large-scale farm in the humid climate of the Mississippi Delta region," Agricultural Water Management, Elsevier, vol. 262(C).
    3. Anapalli, Saseendran S. & Pinnamaneni, Srinivasa R. & Chastain, Daryl R. & Reddy, Krishna N. & Simmons, Clyde Douglas, 2023. "Eddy covariance quantification of carbon and water dynamics in twin-row vs. single-row planted corn," Agricultural Water Management, Elsevier, vol. 281(C).
    4. Graham, Scott L. & Laubach, Johannes & Hunt, John E. & Eger, Andre & Carrick, Sam & Whitehead, David, 2019. "Predicting soil water balance for irrigated and non-irrigated lucerne on stony, alluvial soils," Agricultural Water Management, Elsevier, vol. 226(C).
    5. Dong, Juan & Xing, Liwen & Cui, Ningbo & Guo, Li & Liang, Chuan & Zhao, Lu & Wang, Zhihui & Gong, Daozhi, 2024. "Estimating reference crop evapotranspiration using optimized empirical methods with a novel improved Grey Wolf Algorithm in four climatic regions of China," Agricultural Water Management, Elsevier, vol. 291(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0268097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.