Explore the vast range of titles available.

Lake temperature forecasting is crucial for understanding and mitigating climate change impacts on aquatic ecosystems. The meteorological time series data and their relationship have a high degree of complexity and uncertainty, making it difficult to predict lake temperatures. In this study, we propose a novel approach, Probabilistic Quantile Multiple Fourier Feature Network (QMFFNet), for accurate lake temperature prediction in Qinghai Lake. Utilizing only time series data, our model offers practical and efficient forecasting without the need for additional variables. Our approach integrates quantile loss instead of L2-Norm, enabling probabilistic temperature forecasts as probability distributions. This unique feature quantifies uncertainty, aiding decision-making and risk assessment. Extensive experiments demonstrate the method’s superiority over conventional models, enhancing predictive accuracy and providing reliable uncertainty estimates. This makes our approach a powerful tool for climate research and ecological management in lake temperature forecasting. Innovations in probabilistic forecasting and uncertainty estimation contribute to better climate impact understanding and adaptation in Qinghai Lake and global aquatic systems.

The significance of the diurnal variability of Lake Surface Temperature (LST) has been recognized; yet, its magnitude in terms of spatial and temporal variability is not well known. Attempts have been made to derive such information from satellites at a high spatial resolution; however, most have been made from polar orbiting satellites that sample only twice per day. We have developed an approach to derive such information from geostationary satellites at an hourly time scale and at a spatial resolution of about 5 km. The approach to derive LST uses the Radiative Transfer for TIROS Operational Vertical Sounder (TOVS) (RTTOV) model driven by the Modern-Era Retrospective analysis for Research and Applications (MERRA)-2 information. The methodology has been implemented over Lake Huron for about six years. We present the results of the evaluation against various independent satellite products and demonstrate that there is a strong diurnal variability in the skin temperature over the lake and that the lowest and highest values, as derived twice per day from polar orbiting satellites, may not represent the magnitude of the Diurnal Temperature Range (DTR).

Thousands of glacial lakes exist across the Himalaya. However, the physical characteristics of these lakes that drive changes in glacier mass balance and meltwater delivery downstream are poorly understood. We measured water temperature with depth in Thulagi Lake, Nepal, between May and October 2023 to give the first observations of the thermal dynamics of a Himalayan ice‐contact glacial lake spanning the entirety of the glacier melt season. During the pre‐monsoon and early monsoon periods, we observed lake temperatures greater than 9°C as high incoming shortwave radiation and wind‐driven vertical mixing drove warming at the lake surface. Lake temperature consistently cooled with depth, indicating that the lake was stratified (74% of days within this period). However, these conditions were short lived, with a curtailed summer stratification period after which the lake cooled and vertical mixing was more common. During the pre‐monsoon and early monsoon periods (May–July), consistently higher temperatures were measured near the glacier front than at distal locations (mean differences of 0.30°C–0.96°C at the lake surface) indicating intense convection and the delivery of heat to the ice front resulting in subaqueous melt. Our results show that monsoon conditions (increased precipitation, reduced incoming solar shortwave radiation and lower wind speed) and the input of glacial meltwater inhibit prolonged lake warming, suggesting that subaqueous melt‐driven frontal ablation may play a less important role in driving glacier mass loss here than it does in other glacierised regions.

Although the African Great Lakes are important regulators for the East African climate, their influence on atmospheric dynamics and the regional hydrological cycle remains poorly understood. This study aims to assess this impact by comparing a regional climate model simulation that resolves individual lakes and explicitly computes lake temperatures to a simulation without lakes. The Consortium for Small-Scale Modelling model in climate mode (COSMO-CLM) coupled to the Freshwater Lake model (FLake) and Community Land Model (CLM) is used to dynamically downscale a simulation from the African Coordinated Regional Downscaling Experiment (CORDEX-Africa) to 7-km grid spacing for the period of 1999–2008. Evaluation of the model reveals good performance compared to both in situ and satellite observations, especially for spatiotemporal variability of lake surface temperatures (0.68-K bias), and precipitation (−116 mm yr−1or 8% bias). Model integrations indicate that the four major African Great Lakes almost double the annual precipitation amounts over their surface but hardly exert any influence on precipitation beyond their shores. Except for Lake Kivu, the largest lakes also cool the annual near-surface air by −0.6 to −0.9 K on average, this time with pronounced downwind influence. The lake-induced cooling happens during daytime, when the lakes absorb incoming solar radiation and inhibit upward turbulent heat transport. At night, when this heat is released, the lakes warm the near-surface air. Furthermore, Lake Victoria has a profound influence on atmospheric dynamics and stability, as it induces circular airflow with over-lake convective inhibition during daytime and the reversed pattern at night. Overall, this study shows the added value of resolving individual lakes and realistically representing lake surface temperatures for climate studies in this region.

Credible modeling, tools, and guidance, regarding the changing Laurentian Great Lakes and the climatic impacts, are needed by local decision-makers to inform their management and planning. The present study addresses this need through a model evaluation study of the representation of lake–atmosphere interactions and resulting lake-effect snowfall in the Great Lakes region. Analysis focuses on an extensive ensemble of 74 historical simulations generated by 23 high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP). The model assessment addresses the modeling treatment of the Great Lakes, the spatial distribution and seasonality of climatological snowfall, the seasonal cycle of lake-surface temperatures and overlake turbulent fluxes, and the lake-effect ratio between upwind and downwind precipitation. A deeper understanding of model performance and biases is achieved by partitioning results between HighResMIP GCMs that are 1) coupled to 1D lake models versus GCMs that exclude lake models, 2) between prescribed-ocean model configurations versus fully coupled configurations, and 3) between deep Lake Superior versus relatively shallow Lake Erie. While the HighResMIP GCMs represent the Great Lakes by a spectrum of approaches that include land grid cells, ocean grid cells (with lake surface temperature and ice cover boundary conditions provided by the Met Office Hadley Center Sea Ice and Sea Surface Temperature Dataset), and 1D lake models, the current investigation demonstrates that none of these rudimentary approaches adequately represent the complex nature of seasonal lake temperature and ice cover evolution and its impact on lake–atmosphere interactions and lake-effect precipitation in the Great Lakes region.

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 6–8 m 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.

Lake surface temperatures are projected to increase under climate change, which could trigger shifts in the future distribution of thermally sensitive aquatic species. Of particular concern for lake ecosystems are when temperatures increase outside the range of natural variability, without analogue either today or in the past. However, our knowledge of when such no-analogue conditions will appear remains uncertain. Here, using daily outputs from a large ensemble of SSP3-7.0 Earth system model projections, we show that these conditions will emerge at the surface of many northern lakes under a global warming of 4.0 °C above pre-industrial conditions. No-analogue conditions will occur sooner, under 2.4 °C of warming, at lower latitudes, primarily due to a weaker range of natural variability, which increases the likelihood of the upper natural limit of lake temperature being exceeded. Similar patterns are also projected in subsurface water, with no-analogue conditions occurring first at low latitudes and occurring last, if at all, at higher latitudes. Our study suggests that global warming will induce changes across the water column, particularly at low latitudes, leading to the emergence of unparalleled climates with no modern counterparts, probably affecting their habitability and leading to rearrangements of freshwater habitats this century. Earth system models project that lake temperatures will warm beyond the range of natural variability to which aquatic ecosystems are adapted in the coming decades, with conditions exceeding natural analogues sooner at lower latitudes.

Lake surface water temperatures (LSWTs) are sensitive to atmospheric warming and have previously been shown to respond to regional changes in the climate. Using a combination of in situ and simulated surface temperatures from 20 Central European lakes, with data spanning between 50 and ∼100 years, we investigate the long-term increase in annually averaged LSWT. We demonstrate that Central European lakes are warming most in spring and experience a seasonal variation in LSWT trends. We calculate significant LSWT warming during the past few decades and illustrate, using a sequential t test analysis of regime shifts, a substantial increase in annually averaged LSWT during the late 1980s, in response to an abrupt shift in the climate. Surface air temperature measurements from 122 meteorological stations situated throughout Central Europe demonstrate similar increases at this time. Climatic modification of LSWT has numerous consequences for water quality and lake ecosystems. Quantifying the response of LSWT increase to large-scale and abrupt climatic shifts is essential to understand how lakes will respond in the future.

Projections of regional climate, net basin supply (NBS), and water levels are developed for the mid- and late twenty-first century across the Laurentian Great Lakes basin. Two state-of-the-art global climate models (GCMs) are dynamically downscaled using a regional climate model (RCM) interactively coupled to a one-dimensional lake model, and then a hydrologic routing model is forced with time series of perturbed NBS. The dynamical downscaling and coupling with a lake model to represent the Great Lakes create added value beyond the parent GCM in terms of simulated seasonal cycles of temperature, precipitation, and surface fluxes. However, limitations related to this rudimentary treatment of the Great Lakes result in warm summer biases in lake temperatures, excessive ice cover, and an abnormally early peak in lake evaporation. While the downscaling of both GCMs led to consistent projections of increases in annual air temperature, precipitation, and all NBS components (overlake precipitation, basinwide runoff, and lake evaporation), the resulting projected water level trends are opposite in sign. Clearly, it is not sufficient to correctly simulate the signs of the projected change in each NBS component; one must also account for their relative magnitudes. The potential risk of more frequent episodes of lake levels below the low water datum, a critical shipping threshold, is explored.

As the global climate warms, the fate of lacustrine fish is of huge concern, especially given their sensitivity as ectotherms to changes in water temperature. The Arctic charr (Salvelinus alpinus L.) is a salmonid with a Holarctic distribution, with peripheral populations persisting at temperate latitudes, where it is found only in sufficiently cold, deep lakes. Thus, warmer temperatures in these habitats particularly during early life stages could have catastrophic consequences on population dynamics. Here, we combined lake temperature observations, a 1-D hydrodynamic model, and a multi-decadal climate reanalysis to show coherence in warming winter water temperatures in four European charr lakes near the southernmost limit of the species’ distribution. Current maximum and mean winter temperatures are on average ~ 1 °C warmer compared to early the 1980s, and temperatures of 8.5 °C, adverse for high charr egg survival, have frequently been exceeded in recent winters. Simulations of winter lake temperatures toward century-end showed that these warming trends will continue, with further increases of 3–4 °C projected. An additional 324 total accumulated degree-days during winter is projected on average across lakes, which could impair egg quality and viability. We suggest that the perpetuating winter warming trends shown here will imperil the future status of these lakes as charr refugia and generally do not augur well for the fate of coldwater-adapted lake fish in a warming climate.