2020
DOI: 10.1029/2020wr027173
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Wind as a Main Driver of Spatial Variability of Surface Energy Balance Over a Shallow 102‐km2 Scale Lake: Lake Kasumigaura, Japan

Abstract: Lakes have often been treated as one‐dimensional entities for energy balance (EB) studies mostly based on point measurements. Therefore, our knowledge of the spatial variability of lake EB is quite limited. We created EB maps of Lake Kasumigaura, a 172‐km2 shallow lake in Japan, with a 90‐m horizontal resolution at a 3‐hr interval over 5 years based on spatially interpolated meteorological variables and water surface temperature, with turbulent fluxes estimated by the bulk equations. The results indicate that … Show more

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Cited by 13 publications
(15 citation statements)
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References 29 publications
(68 reference statements)
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“…Firstly, solar radiation and atmospheric longwave radiation at Qomolangma station were used to represent those at Paiku Co. To evaluate the spatial difference, we made a comparison of solar radiation at Paiku Co and Qomolangma station using Himawari-8 satellite data (Tang et al, 2019;Fig. S4 in the Supplement).…”
Section: Uncertainty Of Lake Evaporationmentioning
confidence: 99%
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“…Firstly, solar radiation and atmospheric longwave radiation at Qomolangma station were used to represent those at Paiku Co. To evaluate the spatial difference, we made a comparison of solar radiation at Paiku Co and Qomolangma station using Himawari-8 satellite data (Tang et al, 2019;Fig. S4 in the Supplement).…”
Section: Uncertainty Of Lake Evaporationmentioning
confidence: 99%
“…Here, the Aqua MODIS 8 d lake surface temperature product is used to determine the difference between lake bulk temperature and skin temperature. The product is produced with a spatial resolution of about 1 km, and the accuracy is estimated to be 1 K under clear-sky conditions (Wan, 2013). During the pre-monsoon and monsoon seasons when the lake water got warm, the skin temperature derived from MODIS data was about 1.2 • C higher than lake body temperature.…”
Section: Uncertainty Of Lake Evaporationmentioning
confidence: 99%
“…where 1 is emissivity [¼1.0; dimensionless; Sugita et al (2020)], and T w is the surface water temperature (K). Sensible and latent heat fluxes were calculated with the following bulk formulae:…”
Section: Heat Flux Model At the Lake Surfacementioning
confidence: 99%
“…There are heat fluxes other than those through the water surface, such as heat fluxes associated with river/groundwater inflow and the heat flux through the bottom (Chikita et al 2019;Masunaga & Komuro 2019;Sugita et al 2020). The values of these heat fluxes were unknown at the time of this study.…”
Section: Heat Fluxes Other Than Fluxes Through the Lake Surface: Uncertainties And Limitationsmentioning
confidence: 99%
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