Wang et al. (2026) Modeling Climate Change Impacts on Large and Small Lakes of the Tibetan Plateau: Responses and Drivers

Identification

• Journal: Water
• Year: 2026
• Date: 2026-03-10
• Authors: Liping Wang, Xuan Li, Yaoming Ma, Weiqiang Ma, Mao Chen
• DOI: 10.3390/w18060653

Research Groups

• Land-Atmosphere Interaction and its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
• College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
• College of Atmospheric Science, Lanzhou University, Lanzhou, China
• National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri, China
• Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing, China
• China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, Islamabad, Pakistan

Short Summary

This study evaluates the FLake model's performance in simulating thermal structure and heat fluxes in large and small lakes on the Tibetan Plateau using in situ observations. It finds that the model generally reproduces seasonal variations but underestimates diurnal amplitudes, and that long-term warming trends are primarily driven by downward longwave and shortwave radiation and air temperature.

Objective

• To assess FLake model performance in simulating thermal structure, surface water temperature (T_s), and turbulent heat fluxes at both diurnal and longer timescales for lakes on the Tibetan Plateau.
• To quantify differences in FLake simulations when forced by "land-environment" versus "lake-environment" meteorological data for both large and small lakes.
• To identify the dominant climatic drivers of long-term trends in simulated T_s and turbulent heat fluxes after establishing model fidelity.

Study Configuration

• Spatial Scale: Tibetan Plateau (TP), focusing on Nam Co ("large lake" with ~2000 km² surface area, ~90 m maximum depth, ~40 m mean depth) and an adjacent "small lake" (~1.4 km² surface area, ~14 m maximum depth, ~7 m mean depth).
• Temporal Scale:
  • In situ observations: "small lake" (2012–2013), "large lake" (2015–2016).
  • Long-term simulations: 1981–2024.
  • China Meteorological Forcing Dataset (CMFD): 1979–2016.
  • PBL tower observations: since 2005.
  • Automatic Weather Station (AWS) observations: since August 2015.

Methodology and Data

• Models used: FLake (Fresh water Lake model), a one-dimensional bulk model.
• Data sources:
  • In situ eddy covariance (EC) measurements (3-D wind components, air temperature, humidity, CO2 concentration, turbulent heat fluxes).
  • In situ radiation measurements (downward/upward shortwave and longwave radiation).
  • In situ water temperature profiles (at multiple depths).
  • In situ water level measurements.
  • Secchi depth observations.
  • China Meteorological Forcing Dataset (CMFD) (air temperature, air pressure, specific humidity, wind speed, downward longwave radiation, downward shortwave radiation).
  • Planetary Boundary Layer (PBL) tower observations (air temperature, air humidity, wind speed, wind direction, global solar radiation at 5 heights).
  • Automatic Weather Station (AWS) data (air temperature, humidity, wind speed, direction, rain gauge).

Main Results

• The FLake model generally reproduces the seasonal variations in mixed-layer depth (Dml) and surface water temperature (Ts) but underestimates diurnal amplitudes.
• Simulated sensible (H) and latent (LE) heat fluxes show good agreement with observations when appropriate lake depth and light extinction coefficients (Kd) are applied, with RMSEs of approximately 1 °C for Ts, 8 W m⁻² for H, and 22 W m⁻² for LE.
• For the "large lake", LE simulations differ markedly between land-based and lake-based forcing, primarily due to differences in wind speed and air temperature.
• Long-term simulations (1981–2024) indicate a progressive warming of lake surface waters (0.15 °C decade⁻¹), strengthened thermal stratification (D_ml decline of -0.27 m decade⁻¹), and increasing surface heat fluxes (LE: 12.2 W m⁻² decade⁻¹, H: 4.18 W m⁻² decade⁻¹).
• Downward longwave radiation (Rl↓) is identified as the dominant driver of lake surface warming, with downward shortwave radiation (Rs↓) and near-surface air temperature (T_a) playing secondary roles.
• The increase in Rl↓ is the primary contributor to enhanced evaporation (LE), with Ta and R_s↓ exerting weaker influences.
• Changes in H are governed by the combined effects of Rl↓, Rs↓, and T_a through their modulation of lake–atmosphere temperature gradients.
• Model deficiencies include a lag in simulated ice-melt dates and an underestimation of diurnal Ts variability, primarily attributed to limitations in the Dml parameterization.

Contributions

• Provides a rigorous evaluation of the FLake model's performance for high-elevation large and small lakes on the Tibetan Plateau using comprehensive in situ observations at both diurnal and seasonal timescales.
• Quantifies the significant differences in model performance when forced by land-environment versus lake-environment meteorological data, emphasizing the importance of over-lake measurements for accurate simulations in large lakes.
• Identifies and quantifies the dominant climatic drivers (downward longwave radiation, air temperature, and downward shortwave radiation) responsible for long-term trends in lake surface temperature and turbulent heat fluxes on the Tibetan Plateau.
• Highlights the critical need for improved parameterization of mixed-layer dynamics within the FLake model to better represent diurnal variations in Dml and Ts across different lake sizes and thermal regimes.

Funding

• National Natural Science Foundation of China (Grant No. U2442213)
• Youth Innovation Promotion Association of the Chinese Academy of Sciences (2022069)

Citation

@article{Wang2026Modeling,
  author = {Wang, Liping and Li, Xuan and Ma, Yaoming and Ma, Weiqiang and Chen, Mao},
  title = {Modeling Climate Change Impacts on Large and Small Lakes of the Tibetan Plateau: Responses and Drivers},
  journal = {Water},
  year = {2026},
  doi = {10.3390/w18060653},
  url = {https://doi.org/10.3390/w18060653}
}