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Abstract Ground heat flux (G0) is a key component of the land‐surface energy balance of high‐latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming,G0is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstructG0across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using availableG0data (measured or modeled) for snow‐free period as a reference. When observedG0is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state‐of‐the‐art uncertainty quantification methods, the developedG0reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.
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This content will become publicly available on September 15, 2026
Global Lake Evaporation Estimates by Integrating Penman Method with Equilibrium Temperature Approach
Abstract Modeling evaporationEfrom 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 radiationRnminus rate of water heat storage changeG. The equilibrium temperature approach (ETA) for estimating water surface temperature offers an alternative method to calculateRnandGusing standard meteorological data. This study evaluates the global lakeEestimates 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 overestimateEby 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-ETAEare more pronounced in the cold and polar regions with distinct seasonality ofRnandG. Furthermore, theEtrends 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-simulatedRnandGinto the PM, the bias inEis 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 lakeEfor better water resource management and planning. Significance StatementThis study addresses a crucial challenge in modeling evaporationEfrom inland water bodies—uncertainties in surface water temperature and available energy inputs, particularly net radiationRnand rate of heat storage changeG. By evaluating the widely used Penman model (PM) coupled with the equilibrium temperature approach (ETA), we reveal a tendency for the PM-ETA to overestimateEglobally, with the largest biases observed in cold and polar regions. Incorporating higher-qualityRnandGestimates 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 improvingEestimates by the PM.
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- PAR ID:
- 10636037
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Hydrometeorology
- Volume:
- 26
- Issue:
- 9
- ISSN:
- 1525-755X
- Page Range / eLocation ID:
- 1301 to 1313
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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