Reconstruction of the Net Land Surface Energy Flux Constrained by the Energy Conservation and Land Surface Model Simulations

The net land surface energy flux (F_LS) is a key variable controlling land–atmosphere coupling, and climate feedback mechanisms yet observational coverage is limited, and the model simulated F_LS values are quite spread. To address this deficiency, a novel energy conservation method is applied to CMIP6 LS3MIP (Land Surface, Snow and Soil Moisture Model Intercomparison Project) simulations to establish the relationship between the net land surface energy flux and surface temperature change at each grid point, and reconstruct gridded monthly F_LS from 1985-2024. Systematic validation against eddy covariance station observations demonstrates that our reconstructed F_LS outperforms existing products. The reconstructed F_LS maintains consistency with reanalyses and model simulations in terms of globally averaged anomaly variability during the common period 1985–2012, with an average correlation coefficient of 0.77. The estimated F_LS data show statistically significant correlations with observations at all stations used, a performance superior to that of reanalysis data. For turbulent fluxes derived from the reconstructed F_LS, approximately 71% of sites exhibit higher anomaly correlation coefficients than those from reanalysis data. The high F_LS uncertainties are mainly distributed in Northern Hemisphere high latitudes and high-altitude zones due to large errors in snowmelt. The difference between LS3MIP and our estimation is mainly over 50-70°N, where the land area mean standard deviation (STD) from multiannual mean F_LS is 0.80 Wm⁻² for LS3MIP and 0.55 Wm⁻² for our estimation. This study provides a rigorously validated F_LS product for diagnosing land-atmosphere interactions and evaluating climate models.