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The seasonal ice cover in lakes of the Qinghai–Tibet Plateau is a transient and vulnerable part of the cryosphere, whose characteristics depend on the regional climate: strong solar radiation in the context of the dry and cold environment because of the high altitude and relatively low latitude. We use the first under-ice temperature observations from the largest Tibetan freshwater lake, Ngoring Lake, and a one-dimensional lake model to quantify the mechanism of solar thermal accumulation under ice, which relies on the ice optical properties and weather conditions, as well as the effect of the accumulated heat on the land–atmosphere heat exchange after the ice breakup. The model was able to realistically simulate the feature of the Ngoring Lake thermal regime: the "summer-like" temperature stratification with temperatures exceeding the maximum density point of 3.98 ∘ C across the bulk of the freshwater column. A series of sensitivity experiments revealed solar radiation was the major source of under-ice warming and demonstrated that the warming phenomenon was highly sensitive to the optical properties of ice. The heat accumulated under ice contributed to the heat release from the lake to the atmosphere for 1–2 months after ice-off, increasing the upward sensible and latent surface heat fluxes on average by ∼ 50 and ∼ 80 W m -2 , respectively. Therefore, the delayed effect of heat release on the land–atmosphere interaction requires an adequate representation in regional climate modeling of the Qinghai–Tibet Plateau and other lake-rich alpine areas. [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]

Seasonal ice cover on lakes and polar seas creates seasonally developing boundary layer at the ice base with specific features: fixed temperature at the solid boundary and stable density stratification beneath. Turbulent transport in the boundary layer determines the ice growth and melting conditions at the ice–water interface, especially in large lakes and marginal seas, where large-scale water circulation can produce highly variable mixing conditions. Since the boundary mixing under ice is difficult to measure, existing models of ice cover dynamics usually neglect or parameterize it in a very simplistic form. We present the first detailed observations on mixing under ice of Lake Baikal, obtained with the help of advanced acoustic methods. The dissipation rate of the turbulent kinetic energy (TKE) was derived from correlations (structure functions) of current velocities within the boundary layer. The range of the dissipation rate variability covered 2 orders of magnitude, demonstrating strongly turbulent conditions. Intensity of mixing was closely connected to the mean speeds of the large-scale under-ice currents. Mixing developed on the background of stable density (temperature) stratification, which affected the vertical structure of the boundary layer. To account for stratification effects, we propose a model of the turbulent energy budget based on the length scale incorporating the dissipation rate and the buoyancy frequency (Dougherty–Ozmidov scaling). The model agrees well with the observations and yields a scaling relationship for the ice–water heat flux as a function of the shear velocity squared. The ice–water heat fluxes in the field were the largest among all reported in lakes (up to 40 Wm-2) and scaled well against the proposed relationship. The ultimate finding is that of a strong dependence of the water–ice heat flux on the shear velocity under ice. The result suggests large errors in the heat flux estimations when the traditional "bulk" approach is applied to stratified boundary layers. It also implies that under-ice currents may have much stronger effect on the ice melt than estimated by traditional models. [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]

Lakes are sensitive indicators of climate change. There are thousands of lakes on the Tibetan Plateau (TP), more than 1200 of them having an area larger than 1 km², but few observation data of lakes are available. Therefore, the thermal condition of the plateau lakes under the background of climate warming remain poorly understood. In this study, the China Meteorological Forcing Dataset developed by Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS), MODIS Land Surface Temperature (LST) data and buoy observation data were used to reveal the response of thermal conditions of Qinghai Lake to the recent climate change and to analyze the applicability of Freshwater Lake Model (FLake) to Qinghai Lake. Despite some deviations caused by model simplifications and uncertain forcing data, FLake demonstrated a good ability in capturing the seasonal variations of the lake surface temperature and the internal thermal structure of Qinghai Lake. The simulated lake surface temperature demonstrated a positive trend from 1979 to 2012, positively correlated with the air temperature and the downward longwave radiation, while negatively correlated with the wind speed and with the solar radiation but failing to pass the significance test. The simulated internal thermodynamic structure revealed that, if the impact of salinity is not considered, the Qinghai Lake is a dimictic lake with two overturn periods occurring in late spring and late autumn respectively. The surface and mean water temperatures 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 LST and air temperature. With the warming of the climate, the earlier ice break-up and later ice-on were simulated, having a strong effect on lake-air temperature differences in January and May. [ABSTRACT FROM AUTHOR]

We performed a field study on mixing and vertical heat transport under the ice cover of an Arctic lake. Mixing intensities were estimated from small-scale oscillations of water temperature and turbulent kinetic energy dissipation rates derived from current velocity fluctuations. Well-developed turbulent conditions prevailed in the stably stratified interfacial layer separating the ice base from the warmer deep waters. The source of turbulent mixing was identified as whole-lake (barotropic) oscillations of the water body driven by strong wind events over the ice surface. We derive a scaling of ice–water heat flux based on dissipative Kolmogorov scales and successfully tested against measured dissipation rates and under-ice temperature gradients. The results discard the conventional assumption of nearly conductive heat transport within the stratified under-ice layer and suggest contribution of the basal heat flux into the melt of ice cover is higher than commonly assumed. Decline of the seasonal ice cover in the Arctic is currently gaining recognition as a major indicator of climate change. The heat transfer at the ice–water interface remains the least studied among the mechanisms governing the growth and melting of seasonal ice. The outcomes of the study find application in the heat budget of seasonal ice on inland and coastal waters. [ABSTRACT FROM AUTHOR]

This article reports the results of three field campaigns conducted in Lake Issyk-Kul in 2015, 2016, and 2017. During the campaigns, CTD profiling and water sampling were performed at 34 locations all over the lake. A total of 75 CTD profiles were obtained. Some biogeochemical and thermohaline parameters at the lake surface were also mapped at high horizontal resolution along the ship's track. In addition, thermistor chains were deployed at three mooring stations in the eastern littoral region of the lake, yielding 147-day-long records of temperature data. The measurements revealed that – while the thermal state of the active layer, as well as some biogeochemical characteristics, were subject to significant interannual variability mediated by atmospheric forcing – the haline structure of the entire lake was remarkably stable at the interannual scale. Our data do not confirm the reports of progressive warming of the deep Issyk-Kul waters as suggested in some previous publications. However, they do indicate a positive trend of salinity in the lake's interior over the last 3 decades. A noteworthy newly found feature is a weak but persistent salinity maximum below the thermocline at a depth of 70–120 m, from where salinity slightly decreased downwards. The data from the moored thermistor chains support the previously published hypothesis about the significant role of the submerged ancient riverbeds on the eastern shelf in advecting littoral waters into the deep portion of the lake during differential cooling period. We hypothesize that the less saline littoral water penetrating into the deep layers due to this mechanism is responsible for the abovementioned features of salinity profile, and we substantiate this hypothesis by estimates based on simple model assumptions. [ABSTRACT FROM AUTHOR]

The hydrology of the lake-rich Tibetan Plateau is important for the global climate, yet little is known about the thermal regime of Tibetan lakes due to scant data. We (i) investigated the characteristic seasonal temperature patterns and recent trends in the thermal and stratification regimes of lakes on the Tibetan Plateau and (ii) tested the performance of the one-dimensional lake parameterization scheme FLake for the Tibetan lake system. For this purpose, we combined 3 years of in situ lake temperature measurements, several decades of satellite observations, and the global reanalysis data. We chose the two largest freshwater Tibetan lakes, Ngoring and Gyaring, as study sites. The lake model FLake faithfully reproduced the specific features of the high-altitude lakes and was subsequently applied to reconstruct the vertically resolved heat transport in both lakes during the last 4 decades. The model suggested that Ngoring and Gyaring were ice-covered for about 6 months and stratified in summer for about 4 months per year with a short spring overturn and a longer autumn overturn. In summer the surface mixed boundary layer extended to 6-8m of depth and was about 20% shallower in the more turbid Gyaring. The thermal regime of the transparent Ngoring responded more strongly to atmospheric forcing than Gyaring, where the higher turbidity damped the response. According to the reanalysis data, air temperatures and humidity have increased, whereas solar radiation has decreased, since the 1970s. Surprisingly, the modeled mean lake temperatures did not change, nor did the phenology of the ice cover or stratification. Lake surface temperatures in summer increased only marginally. The reason is that the increase in air temperature was offset by the decrease in radiation, probably due to increasing humidity. This study demonstrates that air temperature trends are not directly coupled to lake temperatures and underscores the importance of shortwave radiation for the thermal regime of high-altitude lakes. [ABSTRACT FROM AUTHOR]

The hydrology of the lake-rich Tibetan Plateau is important for the global climate yet little is known about the thermal regime of Tibetan lakes due to scant data. We (i) investigated the characteristic seasonal temperature patterns and recent trends in thermal and stratification regime of lakes on the Tibetan Plateau and (ii) tested theperformance of the one-dimensional lake parameterization scheme FLake for the Tibetan lake system. For this purpose we combined three years of in situ lake temperature measurements, several decadesof satellite observations and the global reanalysis data. We chose the two largest freshwater Tibetan lakes - Ngoring and Gyaring - as study sites. The lake model FLake faithfully reproduced the specific features of the high-altitude lakes and was subsequently applied to reconstruct the vertically resolved heat transport in both lakes during the last four decades. The modelsuggested Ngoring and Gyaring were ice-covered forabout 6 months and stratified in summer for about 4 months per year with a short spring overturn and longer autumn overturn. In summer the surface mixed boundary layer extended to 6-8 m depth and was about 20% shallower in the more turbid Gyaring. The thermal regime of transparent Ngoring responded more strongly to atmospheric forcing than Gyaring, where the higher turbidity dampened the response. According to reanalysis data, air temperatures and humidity increased, whereas solar radiation decreased since the 1970s. Surprisingly, mean lake temperatures did not change, nor did the phenology of ice cover or stratification. Lake surface temperatures in summerincreased only marginally. The reason is that the increase in air temperature was offset by the decrease in radiation, probably due to increasing humidity. This study demonstrates that air temperature trends are not directly coupled to lake temperatures and underscores the importance of short-wave radiation for the thermal regime of high-altitude lakes. [ABSTRACT FROM AUTHOR]

Hutchinson and Löffler's (1956) classification of lakes based on the seasonal thermal mixing regime has become a cornerstone of any analysis of lakes as elements of the earth surface. Until now however the lake classification has lacked a physically sound quantitative criterion distinguishing between two fundamental lake types: thermally stratified during a large portion of the year (mono- and dimictic) and predominantly mixed to the bottom (polymictic). Using the mechanistic balance between potential and kinetic energy we derived a generalized scaling for seasonal stratification in a closed lake basin. The scaling parameter is the critical mean basin depth, Hcrit, that delineates lakes that mix regularly from those that stratify seasonally based on lake water transparency, lake length, and an annual mean estimate for the Monin-Obukhov length. The scaling criterion consistently describes the mixing regime significantly better than either the conventional unbounded basin scaling or a simple depth threshold. Thus, the generalized scaling is universal for freshwater lakes and allows the seasonal mixing regime to be estimated without numerically solving the heat transport equations. [ABSTRACT FROM AUTHOR]

Understanding the fate of organic carbon (OC) inputs in aquatic ecosystems is of primaryimportance for comprehending their functioning, in particular in relation to their carboncycle. A large part of terrigenous OC, coming from the watershed, enters aquatic ecosystemsin the form of refractory organic matter (ROM), which are difficult to oxidise. Recent studiesin the literature have suggested, however, that ROM mineralisation rates may be enhanced inpresence of labile organic matter (LOM), making ROM compounds easier to degrade, with aconsequent alteration of the carbon budget in those systems. This process refers to as primingeffect. In lakes, zooplankton carcasses represent an abundant and high quality LOM substrate formicroorganisms that has the potential of priming ROM mineralisation in water column andcreating new and overlooked pathways in the lake carbon cycle. To investigate this, it iscrucial to measure the in-situ sedimentation rate and residence time of dead zooplankton, as afunction of hydrodynamic conditions, microbial decomposition and organisms’characteristics (such as size and density). Current velocimetry acoustic methods cannot measure, however, velocities of singlemillimetre-sized carcasses because particles are too small and measurements are not accuratedue to the low correlation of the acoustic pings. To overcome this, we propose an inexpensiveparticle tracking velocimetry (PTV) system to estimate the instantaneous 3D velocity ofparticles in the field. From the data it is possible to measure sinking rates of deadzooplankton and potentially infer carbon fluxes in lakes in relation to the primingeffect. The PTV rig consists of two GoPro cameras arranged in a frontal parallel arrangementand installed in a waterproof case. The case is mounted on a stainless-steel frame with alaminate blank screen placed in front of the cameras to restrict the system sampling volume.A torch was also attached on the frame to enhance lighting underwater conditions. Thecameras are set up to acquire stereoscopic films of sinking particles at 48 frames per secondand calibrated in a calibration tank to estimate their distortion and rectification parameters. Asoftware package was also developed with new stereo algorithms to sync the videos,detect and track carcasses, as they move in the water, and measure their velocity andlength. In this study, we also present early results of sedimentation rates from the PTV system,estimated from 2 deployments in summer 2018 in the mesocosm of Lake Stechlin (Germany)at 7m. Finally, the settling rates are compared with (1) those inferred from the Stokes’ lawand (2) the daily settling rates estimated from sedimentation traps installed in the mesocosmat the same depth. [ABSTRACT FROM AUTHOR]