Search

There are thousands of lakes in the Tibetan Plateau (TP), and most are saline. However, little is known about the responses of TP lakes to climate change, especially saline ones. We investigated the thermal responses of the largest freshwater lake (Ngoring Lake) in the TP and its nearby small saline lake (Hajiang Salt Pond) to climate change using the improved lake scheme in the Community Land model (CLM4-LISSS), in which we primarily developed the salinity parameterizations previously evaluated in the Great Salt Lake in USA and further considered the effect of salinity on the temperature of the maximum density of saline water in the present study. The improved lake model with salinity parameterizations was first applied to a saline lake in the TP, where saline lakes make up the majority of water bodies. The CLM4-LISSS model could effectively simulate lake surface water temperature (LSWT), lake water temperature (LT) and ice thickness in Ngoring Lake. Additionally, the model including our salinity parameterizations significantly improved simulations of LSWT and LT in Hajiang Salt Pond, especially in winter. The LSWT of the two completely opposite lakes were warming in the simulations at a rate above 0.6 °C/decade. Meteorological forces were the main driving factor, with increasing downward longwave radiation, air temperature and air humidity, as well as weakening winds contributing to LSWT increase. Compared to a hypothetical shallow freshwater lake, the greater depth of Ngoring Lake made its surface warm faster, and salinity slightly accelerated the warming of Hajiang Salt Pond. Monthly mean LSWT differences between the two lakes were induced by salinity effects in cold periods and lake depth in the unfrozen period. In response to a warming climate, the LSWT in the ice-free Hajiang Salt Pond rapidly increased from January to April due to the warming climate, whereas the LSWT of Ngoring Lake increased faster in the first and last month of the ice-cover period due to later ice-on and earlier ice-off. This study will provide a useful tool for saline lakes in the TP and help deepen our knowledge about the responses of TP lakes, especially the saline lakes, to climate change, as well as response differences between freshwater and saline lakes and the reasons for these differences. [ABSTRACT FROM AUTHOR]

The complexity of the state-of-the-art climate models requires high computational resources and imposes rather simplified parameterization of inland waters. The effect of lakes and reservoirs on the local and regional climate is commonly parameterized in regional or global climate modeling as a function of surface water temperature estimated by atmosphere-coupled one-dimensional lake models. The latter typically neglect one of the major transport mechanisms specific to artificial reservoirs: heat and mass advection due to inflows and outflows. Incorporation of these essentially two-dimensional processes into lake parameterizations requires a trade-off between computational efficiency and physical soundness, which is addressed in this study. We evaluated the performance of the two most used lake parameterization schemes and a machine-learning approach on high-resolution historical water temperature records from 24 reservoirs. Simulations were also performed at both variable and constant water level to explore the thermal structure differences between lakes and reservoirs. Our results highlight the need to include anthropogenic inflow and outflow controls in regional and global climate models. Our findings also highlight the efficiency of the machine-learning approach, which may overperform process-based physical models in both accuracy and computational requirements if applied to reservoirs with long-term observations available. Overall, results suggest that the combined use of process-based physical models and machine-learning models will considerably improve the modeling of air–lake heat and moisture fluxes. A relationship between mean water retention times and the importance of inflows and outflows is established: reservoirs with a retention time shorter than ∼ 100 d, if simulated without inflow and outflow effects, tend to exhibit a statistically significant deviation in the computed surface temperatures regardless of their morphological characteristics. [ABSTRACT FROM AUTHOR]

The complexity of the state-of-the-art climate models requires high computational resources and imposes rather simplified parameterization of inland waters. The effect of lakes and reservoirs on the local and regional climate is commonly parameterized in regional or global climate modeling as a function of surface water temperature estimated by atmosphere-coupled one-dimensional lake models. The latter typically neglect one of the major transport mechanisms specific to artificial reservoirs: heat and mass advection due to in- and outflows. Incorporation of these essentially two-dimensional processes into lake parameterizations requires a trade-off between computational efficiency and physical soundness, which is addressed in this study. We evaluated the performance of the two most used lake parameterization schemes and a machine learning approach on high-resolution historical water temperature records from 24 reservoirs. Simulations were also performed at both variable and constant water level to explore the thermal structure differences between lakes and reservoirs. Our results highlight that surface water temperatures in reservoirs differ significantly from those found in lakes, reinforcing the need to include anthropogenic inflow and outflow controls in regional and global climate models. Our findings also highlight the efficiency of the machine learning approach, which may overperform process-based physical models both in accuracy and in computational requirements, if applied to reservoirs with long-term observations available. A relationship between mean water retention times and the importance of inflows and outflows is established: reservoirs with the retention time shorter than ~100 days, if simulated without in- and outflow effects, tend to exhibit a statistically significant deviation in the computed surface temperatures regardless of their morphological characteristics. [ABSTRACT FROM AUTHOR]

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 km 2 ; 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. [ABSTRACT FROM AUTHOR]

The physical response of lakes to climate warming is regionally variable and highly dependent on individual lake characteristics, making generalizations about their development difficult. To qualify the role of individual lake characteristics in their response to regionally homogeneous warming, we simulated temperature, ice cover, and mixing in four intensively studied German lakes of varying morphology and mixing regime with a one-dimensional lake model. We forced the model with an ensemble of 12 climate projections (RCP4.5) up to 2100. The lakes were projected to warm at 0.10–0.11 ∘ C decade -1 , which is 75 %–90 % of the projected air temperature trend. In simulations, surface temperatures increased strongly in winter and spring, but little or not at all in summer and autumn. Mean bottom temperatures were projected to increase in all lakes, with steeper trends in winter and in shallower lakes. Modelled ice thaw and summer stratification advanced by 1.5–2.2 and 1.4–1.8 days decade -1 respectively, whereas autumn turnover and winter freeze timing was less sensitive. The projected summer mixed-layer depth was unaffected by warming but sensitive to changes in water transparency. By mid-century, the frequency of ice and stratification-free winters was projected to increase by about 20 %, making ice cover rare and shifting the two deeper dimictic lakes to a predominantly monomictic regime. The polymictic lake was unlikely to become dimictic by the end of the century. A sensitivity analysis predicted that decreasing transparency would dampen the effect of warming on mean temperature but amplify its effect on stratification. However, this interaction was only predicted to occur in clear lakes, and not in the study lakes at their historical transparency. Not only lake morphology, but also mixing regime determines how heat is stored and ultimately how lakes respond to climate warming. Seasonal differences in climate warming rates are thus important and require more attention. [ABSTRACT FROM AUTHOR]

Highlights: [•] We studied effects of nuclear plant thermal pollution and climate warming on a lake. [•] Temperature model FLake and 50-years data from Lake Stechlin, Germany were used. [•] Thermal pollution counteracts the stability increase due to climate warming. [•] Thermal pollution in winter increases the summer hypolimnion temperatures. [•] Both thermal pollution and climate warming prolong the summer stagnation period. [ABSTRACT FROM AUTHOR]

Abstract: The phenomenon of “temperature dichotomy”, or anomalous heating of surface water under the ice up to temperatures exceeding 4°C is known to take place occasionally in solar-heated ice-covered freshwater lakes and has usually been explained by the stabilizing effect of the weak vertical salinity gradient created by the melt water flux from the ice and supporting the unstable temperature distribution. Here, we report an observation of the local temperature maximum in the upper part of the water column of ice-covered Lake Vendyurskoe (northwestern Russia). The observation was accompanied by vertically resolved measurements of the conductivity allowing estimation of the dissolved salts effect on the vertical density distribution. The results demonstrate insufficiency of the salt gradient to support the vertical stability of water column. Therefore, we suggest the vertically inhomogeneous radiation absorption to be the probable stabilizing mechanism here, similarly to radiatively heated boundary layers in the ocean, the atmosphere and star interiors. An analytical solution of the heat transfer equation is derived describing the temperature profile evolution in ice-covered lakes subject to solar radiation heating above the maximum density temperature. Observed daytime temperature profiles agree well with the analytical model that suggests the absence of convective mixing. According to the model, the temperature maximum is formed within a day that supports the hypothesis about the stabilizing effect of the solar radiation absorption. We conclude that in temperate lakes the warm layer should have diurnal character and should be destroyed during the nighttime by convection. In polar lakes, in turn, the warm layer can exist during essentially longer periods that is supported by application of the model to the previously published data from Lake Peters, Alaska. In this case, the ice melting rate can be significantly affected by the increased temperature gradient beneath the ice. Apart from potential effects on the ice melting rate and the spring plankton development in lakes, the regime represents a rare geophysical example of instability driven solely by radiative heating with many useful analogies in planetary and stellar physics. [Copyright &y& Elsevier]

Abstract: A model of seasonal heat storage by lake sediments is proposed oriented at applications in climate modeling and at lake parameterization in numerical weather prediction. The computational efficiency is achieved by reformulating of the heat transfer problem as a set of ordinary differential equations for evolution of the temperature wave inside the upper sediment layer. Arising temperature and depth scales completely replace the conductivity of the sediment in the heat transfer equation and can be easily achieved from the lake water temperature observations without any data on the sediment thermal properties. The method is proposed for the scales estimation from the inverse solution of the model equations in special case of the constant water-sediment heat flux in ice-covered lakes. The method is tested on data from sediments of Lake Krasnoye, North-Western Russia. The long-term (1961–2002) modeling of temperature in German lakes Müggelsee and Heiligensee with a coupled one-dimensional model of lake water column and sediments has demonstrated an appreciable effect of the sediment heat storage on near-bottom temperatures in both lakes. Thus, incorporation of the sediment layer into lake temperature models can essentially improve, at low computational costs, the model performance, especially for shallow lakes. In addition, a better forecast of near-bottom temperature evolution on climatic scales can provide a better understanding of the response of lake benthic communities to global warming. [Copyright &y& Elsevier]