Page 94 - 《高原气象》2026年第1期

高 原 气 象 45 卷
90

Exploration on the Changes and Causes of Lake Surface Temperature

and Lake Heatwave in Qinghai Lake from 1980 to 2022

1， 2
3
WANG Tiantian 1， 2， 3 ， WEN Lijuan ， XIE Gang ， WANG Mengxiao ， HAN Tianxiang 1， 2， 3 ， CHEN
1， 2
Shiqiang ， YU Tao 3
1， 2
（1. State Key Laboratory of Cryospheric Science and Frozen Soil Engineering， Northwest Institute of Eco-Environment and Resources，
Chinese Academy of Sciences， Lanzhou 730000， Gansu， China；
2. Qinghai Lake Comprehensive Observation and Research Station， Chinese Academy of Sciences， Gangcha 812300， Qinghai，
China；
3. College of Petrochemical Engineering， Lanzhou University of Technology， Lanzhou 730050， Gansu， China）

Abstract： Under the influence of global warming， the surface temperature of lakes on the Qinghai-Xizang Pla‐
teau， along with the total duration and mean intensity of lake heatwaves， has exhibited significant increases.
These trends amplify the susceptibility of lake surface temperatures to heating during thermal stratification peri‐
ods， accelerating summer warming rates and potentially inducing surface hypoxia. Previous studies analyzing
lake heatwave characteristics have predominantly focused on spatially averaged metrics across broad regions，
leaving the specific heatwave dynamics of Qinghai Lake poorly characterized. To address this knowledge gap，
this study integrates in-situ observations of Qinghai Lake's water temperature and surface temperature， meteoro‐
logical data from Gangcha Station， MODIS land surface temperature products， the Third Pole high-resolution
near-surface meteorological forcing dataset （TPMFD）， and simulations from the one-dimensional Freshwater
Lake Model （FLake） to investigate long-term changes in surface temperature and heatwave characteristics of
Qinghai Lake from 1980 to 2022. Through correlation analysis and detrended decomposition methods， the driv‐
ing mechanisms underlying these changes were systematically elucidated. The research shows that： （1） The air
temperature， specific humidity and wind speed of TPMFD reanalysis data are highly correlated with those ob‐
served by Gangcha meteorological station， and the biases （BIAS） and root mean square errors （RMSE） are
small. The correlation coefficients of the two data are 0. 96， 0. 84 and 0. 74， respectively， and the BIAS is

0. 55 ℃， 0. 00068 g·g and -0. 31 m·s ， respectively. The RMSE is 0. 59 ℃， 0. 00069 g·g and 0. 38 m·s ， re‐
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spectively. The change rate of the air temperature in TPMFD ［0. 48 ℃·（10a）］ is close to that of the observed air
temperature ［0. 44 ℃·（10a）］. The variation rate of the specific humidity in TPMFD ［0. 0001 g·g ·（10a）］ is
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consistent with the observed variation rate. The variation rate of the wind speed in TPMFD ［ -0. 1 m·s ·（10a）］
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is slightly smaller than that of the observation ［ -0. 25 m·s ·（10a）］. Moreover， the change rates of the air tem‐
perature， specific humidity， and wind speed in both TPMFD and the Gangcha Meteorological Station have
passed the significance test at the 95% confidence level. The simulated water temperature and lake surface tem‐
perature of Qinghai Lake have a very good correlation with the in-situ observed water temperature and lake sur‐
face temperature of Qinghai Lake， and the biases and root mean square errors are relatively small. The long-term
sequential simulated lake surface temperature also has a good correlation with the MODIS surface temperature，
and both the BIAS and RMSE are within a reasonable range. The correlation coefficients between the simulation
results and the three kinds of observations are 0. 99， 0. 96， and 0. 98 respectively， the BIAS are 0. 25 ℃ ，
-0. 1 ℃， and 0. 87 ℃ respectively， and the RMSE are 0. 58 ℃， 2. 65 ℃， and 2. 20 ℃ respectively.（2） From
1980 to 2022， both the characteristics of the lake surface temperature and lake heatwaves in Qinghai Lake
showed a significant increasing trend （p<0. 05）. The frequency of lake heatwaves fluctuated between 0 and 6