Numerical study on the response of the largest lake in China to climate change

Abstract

Abstract. Lakes are sensitive indicators of climate change. There are thousands of lakes on the Tibetan Plateau (TP), and more than 1200 of them have an area larger than 1 km2; they respond quickly to climate change, but few observation data of lakes are available. Therefore, the thermal condition of the plateau lakes under the background of climate warming remains poorly understood. In this study, the China regional surface meteorological feature dataset developed by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS), MODIS lake surface temperature (LST) data and buoy observation data were used to evaluate the performance of lake model FLake, extended by simple parameterizations of the salinity effect, for brackish lake and to reveal the response of thermal conditions, radiation and heat balance of Qinghai Lake to the recent climate change. The results demonstrated that the FLake has good ability in capturing the seasonal variations in the lake surface temperature and the internal thermal structure of Qinghai Lake. The simulated lake surface temperature showed an increasing trend from 1979 to 2012, positively correlated with the air temperature and the downward longwave radiation while negatively correlated with the wind speed and downward shortwave radiation. The simulated internal thermodynamic structure revealed that Qinghai Lake is a dimictic lake with two overturn periods occurring in late spring and late autumn. The surface and mean water temperatures of the lake significantly increased from 1979 to 2012, while the bottom temperatures showed no significant trend, even decreasing slightly from 1989 to 2012. The warming was the strongest in winter for both the lake surface and air temperature. With the warming of the climate, the later ice-on and earlier ice-off trend was simulated in the lake, significantly influencing the interannual and seasonal variability in radiation and heat flux. The annual average net shortwave radiation and latent heat flux (LH) both increase obviously while the net longwave radiation and sensible heat flux (SH) decrease slightly. Earlier ice-off leads to more energy absorption mainly in the form of shortwave radiation during the thawing period, and later ice-on leads to more energy release in the form of longwave radiation, SH and LH during the ice formation period. Meanwhile, the lake–air temperature difference increased in both periods due to shortening ice duration.

Last Decade Progress in Understanding and Modeling the Land Surface Processes on the Tibetan Plateau

“…Considering that there are a number of salt lakes in the TP, Su et al (2019) incorporated the salinity effects on the temperatures of maximum water density and freezing point into the Flake model and validated its performance in the brackish endorheic Qinghai Lake. The results showed that consideration of salinity effects reduces the simulated maximum ice thickness and advances the break-up date that are closer to the in situ buoy measurements.…”

Numerical study of the seasonal thermal and gas regimes of the large artificial reservoir in Western Europe using LAKE2.0 model

“…the mean water temperature during the simulation run and apart of it provides mixed layer and bottom temperature, thermocline shape factor, and mixed layer depth in the output. FLake model is widely used in climate and numerical weather prediction studies (Salgado and Le Moigne, 2010;Samuelsson et al, 2006;Le Moigne et al, 2016;Su et al, 2019) to simulate the feedback of freshwater lakes on the atmospheric boundary layer, and in the intercomparison experiments with other parameterizations. In particular, FLake has been applied in studies of the Alqueva reservoir by Iakunin et al (2018), Potes et al (2012), and Salgado and Le Moigne (2010).…”

Attention: Incorrect implementation/interpretation of one of the models

“…The latter is not resolved in FLake numerically, but parameterized via few "shape factor"-constants related to the spatial integrals over the stratified layer. Several recent publications, including co-authorship of one of the authors of the present study, (Shatwell et al, 2016;Kirillin et al, 2017;Shatwell et al, 2019;Su et al, 2019) discussed the appropriate choice of the shape factor constants in FLake and have demonstrated that the set of constants used in the NWP-version of the model should be amended if the vertical thermal structure is in question apart from the lake surface temperatures. In particular, the unrealistically weak deep stratification and the corresponding high depth of the surface mixed layer, as reported in the present study, are the results of applying the NWP-constants together with the maximum lake depth as the model lake depth.…”