A one-dimensional (1-D) model for an enclosed basin (lake) is presented, which reproduces temperature, horizontal velocities, oxygen, carbon dioxide and methane in the basin. All prognostic variables are treated in a unified manner via a generic 1-D transport equation for horizontally averaged property. A water body interacts with underlying sediments. These sediments are represented by a set of vertical columns with heat, moisture and CH₄ transport inside. The model is validated vs. a comprehensive observational data set gathered at Kuivajärvi Lake (southern Finland), demonstrating a fair agreement. The value of a key calibration constant, regulating the magnitude of methane production in sediments, corresponded well to that obtained from another two lakes. We demonstrated via surface seiche parameterization that the near-bottom turbulence induced by surface seiches is likely to significantly affect CH₄ accumulation there. Furthermore, our results suggest that a gas transfer through thermocline under intense internal seiche motions is a bottleneck in quantifying greenhouse gas dynamics in dimictic lakes, which calls for further research.

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5^∘ × 0.5^∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

Recent progress of including lake subroutines in numerical weather prediction (NWP) models has led to more accurate forecasts. In lake models, one essential parameter is water clarity, parameterized via the light extinction coefficient, K_d, for which a global constant value is usually used. We used direct eddy covariance fluxes and basic meteorological measurements coupled with lake water temperature and clarity measurements from a boreal lake to estimate the performance of two lake models, LAKE and FLake. These models represent two 1‐D modeling frameworks broadly used in NWP. The results show that the lake models are very sensitive to changes in K_d when it is lower than 0.5 m⁻¹. The progress of thermal stratification depended strongly on K_d. In dark‐water simulations the mixed layer was shallower, longwave and turbulent heat losses higher, and therefore the average water column temperatures lower than in clear‐water simulations. Thus, changes in water clarity can also affect the onset of ice cover. The more complex LAKE modeled the seasonal thermocline deepening, whereas it remained virtually constant during summer in the FLake model. Both models overestimated the surface water temperatures by about 1°C and latent heat flux by >30%, but the variations in heat storage and sensible heat flux were adequately simulated. Our results suggest that, at least for humic lakes, a lake‐specific, but not time‐depending, constant value for K_d can be used and that a global mapping of K_d would be most beneficial in regions with relatively clear lakes, e.g., in lakes at high altitudes.

Heat uptake is a key variable for understanding the Earth system response to greenhouse gas forcing. Despite the importance of this heat budget, heat uptake by inland waters has so far not been quantified. Here we use a unique combination of global‐scale lake models, global hydrological models and Earth system models to quantify global heat uptake by natural lakes, reservoirs, and rivers. The total net heat uptake by inland waters amounts to 2.6 ± 3.2 ×10²⁰ J over the period 1900–2020, corresponding to 3.6% of the energy stored on land. The overall uptake is dominated by natural lakes (111.7%), followed by reservoir warming (2.3%). Rivers contribute negatively (‐14%) due to a decreasing water volume. The thermal energy of water stored in artificial reservoirs exceeds inland water heat uptake by a factor ∼10.4. This first quantification underlines that the heat uptake by inland waters is relatively small, but non‐negligible.