Wang et al. (2026) Energy-conservation datasets of global land surface radiation and heat fluxes from 2000–2020 generated by CoSEB

Identification

• Journal: Earth system science data
• Year: 2026
• Date: 2026-01-16
• Authors: Junrui Wang, Ronglin Tang, Meng Liu, Zhao-Liang Li
• DOI: 10.5194/essd-18-443-2026

Research Groups

• State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
• University of Chinese Academy of Sciences, Beijing 100049, China
• State Key Laboratory of Efficient Utilization of Arable Land in China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Short Summary

This study introduces the first data-driven, energy-conservation datasets of global land surface radiation and heat fluxes (2000-2020) generated by the CoSEB model, which uniquely satisfies both surface radiation and heat balance while maintaining high accuracy. This advancement provides a comprehensive and physically consistent dataset crucial for understanding Earth's surface energy dynamics.

Objective

• To develop high-accuracy datasets of global land surface radiation and heat fluxes (SWIN, SWOUT, LWIN, LWOUT, Rn, L_E, H, G) that comply with the principles of radiation balance and heat balance, using the CoSEB model renewed based on in situ observations, remote sensing data, and reanalysis datasets.
• To validate the developed datasets and model estimates against in situ observations, mainstream products, and estimates from uncoordinated random forest techniques.

Study Configuration

• Spatial Scale: Global, 0.05° spatial resolution (final dataset product), with the model constructed at 500 meters.
• Temporal Scale: 2000–2020, with daily and 8-day estimates.

Methodology and Data

• Models used: Coordinated estimates of land Surface Energy Balance components (CoSEB) model, employing a multivariate random forest technique. For comparison, RF-based uncoordinated models were also constructed.
• Data sources:
  • In situ observations: 302 eddy covariance (EC) sites (from AmeriFlux, EuroFlux, OzFlux, FLUXNET, JapanFlux, ChinaFLUX, TPDC networks) and 9 SURFRAD radiation sites, used for training and independent validation.
  • Remote sensing data: GLASS (Leaf Area Index, Fractional Vegetation Cover), MOD44B (Percent Tree Cover).
  • Reanalysis datasets: ERA5-Land (2 m air temperature, soil temperature in layer 1, soil volumetric moisture content in layer 1, solar radiation reaching the surface, net thermal radiation at the surface, atmospheric pressure, 10 m wind speed, precipitation, 2 m dewpoint temperature, daily minimum and maximum air temperature).
  • Other: NOAA/GML atmospheric CO2 concentration data, GMTED2010 topographic data (Digital Elevation Model, slope, aspect), longitude, latitude, and inverse relative distance from Earth to the Sun.

Main Results

• The CoSEB model achieved perfect surface radiation balance (Radiation Imbalance Ratio = 0%) and heat balance (Energy Imbalance Ratio = 0%), a significant improvement over uncoordinated models which showed substantial imbalances (absolute mean RIR 38.84%, EIR 31.22%).
• The CoSEB-based datasets demonstrated high accuracy when validated against 44 independent test sites:
  • Daily estimates: RMSEs (R²) for SWIN, SWOUT, LWIN, LWOUT, Rn, LE, H, and G were 37.52 W m⁻² (0.81), 14.20 W m⁻² (0.42), 22.47 W m⁻² (0.90), 13.78 W m⁻² (0.95), 29.66 W m⁻² (0.77), 30.87 W m⁻² (0.60), 29.75 W m⁻² (0.44), and 5.69 W m⁻² (0.44), respectively.
  • 8-day estimates: RMSEs (R²) for SWIN, SWOUT, LWIN, LWOUT, Rn, LE, H, and G were 18.54 W m⁻² (0.87), 12.19 W m⁻² (0.39), 18.50 W m⁻² (0.92), 9.41 W m⁻² (0.97), 19.12 W m⁻² (0.82), 22.31 W m⁻² (0.67), 21.63 W m⁻² (0.39), and 4.60 W m⁻² (0.47), respectively.
• Compared to mainstream products, CoSEB-based datasets showed better agreement with in situ observations, reducing RMSE by 0.01 to 4.58 W m⁻² at daily scale and 0.24 to 10.48 W m⁻² at 8-day scale for various fluxes.
• The datasets effectively captured global spatial and temporal patterns of land surface radiation and heat fluxes, aligning well with mainstream products.

Contributions

• Development of the first data-driven global datasets of land surface radiation and heat fluxes (2000–2020) that simultaneously satisfy both surface radiation balance (SWIN - SWOUT + LWIN - LWOUT = Rn) and heat balance (L_E + H + G = Rn) among eight key fluxes.
• Achieved higher accuracy in estimating these fluxes compared to existing mainstream remote sensing products and reanalysis datasets.
• Provides a comprehensive, physically consistent, and open-access dataset with significant potential for applications in agriculture, forestry, hydrology, meteorology, ecology, and environmental science, facilitating studies on climate change impacts and mitigation.

Funding

• Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDB0740202)
• National Natural Science Foundation of China (grant no. 42271378)

Citation

@article{Wang2026Energyconservation,
  author = {Wang, Junrui and Tang, Ronglin and Liu, Meng and Li, Zhao-Liang},
  title = {Energy-conservation datasets of global land surface radiation and heat fluxes from 2000–2020 generated by CoSEB},
  journal = {Earth system science data},
  year = {2026},
  doi = {10.5194/essd-18-443-2026},
  url = {https://doi.org/10.5194/essd-18-443-2026}
}