Abstract Water temperature, ice cover, and lake stratification are important physical properties of lakes and reservoirs that control mixing as well as bio-geo-chemical processes and thus influence the water quality. We used an ensemble of vertical one-dimensional hydrodynamic lake models driven with regional climate projections to calculate water temperature, stratification, and ice cover under the A1B emission scenario for the German drinking water reservoir Lichtenberg. We used an analysis of variance method to estimate the contributions of the considered sources of uncertainty on the ensemble output. For all simulated variables, epistemic uncertainty, which is related to the model structure, is the dominant source throughout the simulation period. Nonetheless, the calculated trends are coherent among the five models and in line with historical observations. The ensemble predicts an increase in surface water temperature of 0.34 K per decade, a lengthening of the summer stratification of 3.2 days per decade, as well as decreased probabilities of the occurrence of ice cover and winter inverse stratification by 2100. These expected changes are likely to influence the water quality of the reservoir. Similar trends are to be expected in other reservoirs and lakes in comparable regions. 

/pdf/ensemble-of-models-shows-coherent-response-of-a-reservoirs-u64tl5jh.pdf

Ensemble of models shows coherent response of a reservoir’s stratification and ice cover to climate warming

Abstract. Heat storage within the Earth system is a fundamental metric for understanding climate change. The current energy imbalance at the top of the atmosphere causes changes in energy storage within the ocean, the atmosphere, the cryosphere, and the continental landmasses. After the ocean, heat storage in land is the second largest term of the Earth heat inventory, affecting physical processes relevant to society and ecosystems, such as the stability of the soil carbon pool. Here, we present an update of the continental heat storage, combining for the first time the heat in the land subsurface, inland water bodies, and permafrost thawing. The continental landmasses stored 23.8 ± 2.0 × 1021 J during the period 1960–2020, but the distribution of heat among the three components is not homogeneous. The sensible diffusion of heat through the ground accounts for ∼90 % of the continental heat storage, with inland water bodies and permafrost degradation (i.e. latent heat) accounting for ∼0.7 % and ∼9 % of the continental heat, respectively. Although the inland water bodies and permafrost soils store less heat than the solid ground, we argue that their associated climate phenomena justify their monitoring and inclusion in the Earth heat inventory.


Continental heat storage: contributions from the ground, inland waters, and permafrost thawing

Phosphorus (P) precipitation is among the most effective treatments to mitigate lake eutrophication. However, after a period of high effectiveness, studies have shown possible re-eutrophication and the return of harmful algal blooms. While such abrupt ecological changes were attributed to the internal P loading, the role of lake warming and its potential synergistic effects with internal loading, thus far, has been understudied. Here, in a eutrophic lake in central Germany, we quantified the driving mechanisms of the abrupt re-eutrophication and cyanobacterial blooms in 2016 (30 years after the first P precipitation). A process-based lake ecosystem model (GOTM-WET) was established using a high-frequency monitoring data set covering contrasting trophic states. Model analyses suggested that the internal P release accounted for 68% of the cyanobacterial biomass proliferation, while lake warming contributed to 32%, including direct effects via promoting growth (18%) and synergistic effects via intensifying internal P loading (14%). The model further showed that the synergy was attributed to prolonged lake hypolimnion warming and oxygen depletion. Our study unravels the substantial role of lake warming in promoting cyanobacterial blooms in re-eutrophicated lakes. The warming effects on cyanobacteria via promoting internal loading need more attention in lake management, particularly for urban lakes.

Synergistic Effects of Warming and Internal Nutrient Loading Interfere with the Long-Term Stability of Lake Restoration and Induce Sudden Re-eutrophication.

Lake Ice Will Be Less Safe for Recreation and Transportation Under Future Warming

How fast does lake surface water temperature (LSWT) react to climate warming or cooling? The thermal response of lakes varies with the season and, typically, day-to-day fluctuations are larger in summer. The reason is that lakes are stratified systems where the thermally reactive volume is smaller in summer and, hence, its heat capacity (thermal inertia) is reduced. We define the dimensionless parameter δ as the ratio between the surface volume reacting to the net heat flux through the air-water interface and the volume of the whole lake. By referring to a fully controlled case study obtained by means of a one-dimensional physically based model (Simstrat), we investigate the variability of δ throughout the year and its dependence on LSWT. Then, we compare the results with the parameterization adopted in the hybrid data-driven model air2water. Our analysis confirms that δ follows an exponential decay with increasing LSWT (i.e., a thinner surface layer in summer), and shows that this functional dependence varies between the warming and the cooling periods. These findings contribute to the understanding of the effect of a warming climate on water bodies and ecosystems by providing a simple tool to estimate the rate of change in lakes' water temperature. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2021WR031755

Estimation of the Thermally Reactive Layer in Lakes Based on Surface Water Temperature

Abstract. 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. 

/pdf/a-framework-for-ensemble-modelling-of-climate-change-impacts-1brp0wi8.pdf

A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

South Asian monsoon rainfall varies rapidly in the paleoclimate record, and this has been interpreted using simple models as arising from tipping points. This study explores a class of simple monsoon models, based on convective quasi-equilibrium, and the bifurcations permitted by their mathematical forms. Specifically, low-order models are derived starting from the Quasi-equilibrium tropical circulation model (QTCM) to examine the bifurcations present. Previous studies that have pointed to an abrupt transition in low-order monsoon models typically identify a saddle node bifurcation occurring as a result of changes in the radiation budget. The present study shows how such saddle node structures arise across a wide range of modeling assumptions and parameter values, and yet permit a continuous transition into and out of precipitating regimes without any bifurcation being physically manifest. This is because the bifurcation points lie in a regime that is not physically relevant when the dry thermal stratification is sufficiently large. As a result, these low-order models can be interpreted as possessing abrupt transitions that are latent in the equations but do not express themselves physically. However, when the dry thermal stratification is reduced, bifurcations can occur. This paper also shows that these latent saddle-node structures are themselves part of the unfolding of a pitchfork bifurcation. These findings help understand the role of stabilizing phenomena on the general absence of abrupt monsoon transitions despite the presence of nonlinear terms in these models. 

Comment on esd-2022-30

Abstract. Extreme weather events often trigger massive population displacement. A compounding factor is that the frequency and intensity of such events is affected by anthropogenic climate change. However, the effect of historical climate change on displacement risk has so far not been quantified. Here, we show how displacement can be partially attributed to climate change, using the example of the 2019 tropical cyclone Idai in Mozambique. We estimate the population exposed to flooding following Idai’s landfall, using a combination of storm surge modeling and flood depth estimation from remote sensing images, for factual (climate change) and counterfactual (no climate change) mean sea level and maximum wind speed conditions. We find that climate change has increased displacement risk from this event by approximately 3.1 to 3.5 %, corresponding to 16,000–17,000 additional displaced persons. Besides highlighting the significant effects on humanitarian conditions already imparted by climate change, our study provides a blueprint for event-based displacement attribution. 

Abdullayeva Madina Madaminovna

Papers

A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Comment on esd-2022-30

Human displacements from tropical cyclone Idai attributable to climate change