Multi-column modelling of lake Geneva for climate applications

The interaction between large inland water bodies and the atmosphere impacts the evolution of regional weather and climate, which in turn affects the lake dynamics, thermodynamics, ice-formation, and, therefore, ecosystems. Over the last decades, various approaches have been used to model lake thermodynamics and dynamics in standalone mode or coupled to numerical atmospheric models. We assess a turbulence-closure $$k-\epsilon$$ k - ϵ multi-column lake model in standalone mode as a computationally-efficient alternative to a full three-dimensional hydrodynamic model in the case of Lake Geneva. While it struggles to reproduce some short-term features, the multi-column model reasonably reproduces the seasonal mean of the thermal horizontal and vertical structures governing heat and mass exchanges between the lake surface and the lower atmosphere (stratified period, thermocline depth, stability of the water column). As it requires typically two orders of magnitude less computational ressources, it may allow a two-way coupling with a RCM on timescales or spatial resolutions where full 3D lake models are too demanding.

Climate Projections over the Great Lakes Region: Using Two-way Coupling of a Regional Climate Model with a 3-D Lake Model

Warming trends of the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world’s largest freshwater system. To date, many regional climate models used for the Great Lakes projection either neglected the lake-atmosphere interactions or only coupled with 1-D column lake models to represent the lake hydrodynamics. The study presents the Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics important for large lakes. Using the three carefully selected CMIP5 AOGCMS, we show that the GLARM ensemble average substantially reduces the surface air temperature and precipitation biases of the driving AOGCM ensemble average in present-day climate simulations. The improvements are not only displayed from the atmospheric perspective but also evidenced in accurate simulations of lake surface temperature, and ice coverage and duration. After that, we present the GLARM projected climate change for the mid-21st century (2030–2049) and the late century (2080–2099) for the RCP4.5 and RCP8.5. Under RCP 8.5, the Great Lakes basin is projected to warm by 1.3–2.2 °C by the mid-21st century and 4.0–4.9 °C by the end of the century relative to the early-century (2000–2019). Moderate mitigation (RCP 4.5) reduces the mid-century warming to 0.8–1.9 °C and late-century warming to 1.8–2.7 °C. Annual precipitation in GLARM is projected to increase for the entire basin, varying from −0.4 % to 10.5 % during the mid-century and 1.2 % to 28.5 % during the late-century under different scenarios and simulations. The most significant increases are projected in spring and early summer when current precipitation is highest and little increase in winter when it is lowest. Lake surface temperatures (LSTs) are also projected to increase across the five lakes in all of the simulations, but with strong seasonal and spatial heterogeneities. The most significant LST increase will occur in Lake Superior. The strongest warming was projected in spring, followed by strong summer warming, suggesting earlier and more intense stratification in the future. In contrast, a relatively smaller increase in LSTs during fall and winter are projected with heat transfer to the deepwater due to strong mixing and energy required for ice melting. Correspondingly, the highest monthly mean ice cover is projected to be 3–6 % and 8–20 % across the lakes by the end of the century in RCP 8.5 and RCP 4.5, respectively. In the coastal regions, ice duration will decrease by up to 30–50 days.

Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model

The freshwater 1-D FLake lake model was coupled to the ORCHIDEE land surface model to simulate lake energy balance at the global scale. A multi-tile approach has been chosen to allow the modelling of various types of lakes within the ORCHIDEE grid cell. The different categories have been defined according to lake depth which is the most influential parameter of FLake, but other properties could be considered in the future. Several depth parameterization strategies have been compared, differing by the way to aggregate the depth of the subgrid lakes, i.e., arithmetical, geometrical, harmonical mean and median. Five atmospheric reanalysis datasets available at 0.5° or 0.25° resolution, have been used to force the model and assess model systematic errors. Simulations have been performed, evaluated and intercompared against observations of lake water temperatures provided by the GloboLakes database over about 1000 lakes and ice phenology derived from the Global Lake and River Ice Phenology database. The results highlighted the large impact of the atmospheric forcing on the lake energy budget simulations and the improvements brought by the highest resolution products (ERA5 and E2OFD). The median of the Root Square Mean Errors (RMSE) calculated at global scale range between 3.2 K and 2.7 K among the forcings, CRUJRA and ERA5 leading respectively to the best and worst results. Depth parameterization strategy appeared to be less influent, with RMSE differences less than 0.1 K for the four aggregation scenarios tested. The simulation of ice phenology presented systematic errors whatever the forcing used and the depth parameterization. Freezing onset was shown to be the less sensitive to forcing and depth parameterization with median of the errors ranging between 10 and 14 days. Larger errors were observed on the simulation of the end of the freezing period significantly influenced by the atmospheric forcing used. Such errors already highlighted in previous works, could be the result of deficiencies in the modeling of snow/ice parameterization processes. Various pathways are drawn to improve the model results, including the use of remote sensing data to better constrain the lake radiative parameters (albedo and extinction coefficient) as well as the lake depth thanks to the recent and forthcoming high resolution satellite missions.

Dynamics and Economics of Shallow Lakes: A Survey

We provide an overview of the results devoted to the analysis of the dynamics and economics of shallow lakes, spanning the period from 1999 until now. A shallow lake serves as a typical representative of an ecological system subject to (possibly irreversible) regime shifts. The dynamics of a shallow lake are described by a non-linear model with multiple steady states and multiple domains of attraction and is thus suitable to model the evolution of an ecosystem featuring both resilience within a domain of stability and an abrupt regime shift outside of it. Beyond this, the shallow lake model can also be viewed as a metaphor for many other ecological problems. Due to the broad applicability of this model, there is substantial interest in the management of shallow lakes and both their optimal regulation and competitive usage.

Dianchi Shallow Lake Management

Lake Dianchi in the Chinese province Yunnan is a shallow lake suffering from algae blooms for years due to high pollution. We conducted a thorough survey of the water quality of the northern part of the lake called Caohai. This study was intended as the basis for the system understanding of the shallow lake of Caohai. The study consisted of two steps. First we collected available environmental, hydrological and pollution data from Kunming authorities and other sources. It was possible to parameterise a lake model model based on the preliminary data set. It supported first estimations of management scenarios. But the first and quick answers came with a relevant vagueness. Relevant monitoring data was still missing like P release from lake-internal sediment.Because data uncertainty causes model uncertainty and model uncertainty causes planning and management uncertainties, we recommended and conducted a thorough sediment and river pollution monitoring campaign in 2017. Examination of the sediment phosphorus release and additional measurements of N and P was crucial for the improvement of the shallow lake model of Caohai. In May 2018 we presented and discussed the results of StoLaM shallow lake model of Caohai and the outcomes of a set of management scenarios.The StoLaM shallow lake model for Caohai used in SINOWATER indicates that sediment dredging could contribute to the control of algae by limitation of phosphorus, but sediment management can only produce sustainable effects when the overall nutrient input and especially the phosphorus input from the inflows will be reduced significantly.

Assessment of a Multi-column Deep Lake Model for Climate Applications: The Case of Lake Geneva

The interaction between large inland water bodies and the atmosphere impacts the evolution of regional weather and climate, which in turn affects the lake dynamics, thermodynamics, ice-formation, and, therefore, ecosystems. Over the last decades, various approaches have been used to model lake thermodynamics and dynamics in standalone mode or coupled to numerical atmospheric models. We assess a turbulence-closure k − ε multi-column lake model in standalone mode as a computationally-efficient alternative to a full three-dimensional hydrodynamic model in the case of Lake Geneva. While it struggles to reproduce some short-term features, the multi-column model reasonably reproduces the seasonal mean of the thermal horizontal and vertical structures governing heat and mass exchanges between the lake surface and the lower atmosphere (stratified period, thermocline depth, stability of the water column). It may therefore allow a two-way coupling with a RCM on timescales or spatial resolutions where full 3D lake models are too demanding in terms of computational resources.

Cold Season Performance of the NU-WRF Regional Climate Model in the Great Lakes Region

As Earth’s largest collection of fresh water, the Laurentian Great Lakes have enormous ecological and socio-economic value. Their basin has become a regional hotspot of climatic and limnological change, potentially threatening its vital natural resources. Consequentially, there is a need to assess the current state of climate models regarding their performance across the Great Lakes region and develop the next generation of high-resolution regional climate models to address complex limnological processes and lake-atmosphere interactions. In response to this need, the current paper focuses on the generation and analysis of a 20-member ensemble of 3-km National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) simulations for the 2014-2015 cold season. The study aims to identify the model’s strengths and weaknesses; optimal configuration for the region; and the impacts of different physics parameterizations, coupling to a 1D lake model, time-variant lake-surface temperatures, and spectral nudging. Several key biases are identified in the cold-season simulations for the Great Lakes region, including an atmospheric cold bias that is amplified by coupling to a 1D lake model but diminished by applying the Community Atmosphere Model radiation scheme and Morrison microphysics scheme; an excess precipitation bias; anomalously early initiation of fall lake turnover and subsequent cold lake bias; excessive and overly persistent lake ice cover; and insufficient evaporation over Lakes Superior and Huron. The research team is currently addressing these key limitations by coupling NU-WRF to a 3D lake model in support of the next generation of regional climate models for the critical Great Lakes Basin.

A Hydrodynamic Lake Model Coupled with a Three-Dimensional Dynamic Visualization Method

The hydrodynamic lake model is an important tool for lake management and decision-making. When model results are analyzed by the traditional analysis methods, the multi-source heterogeneous data are not expressed systematically and intuitively, which leads to the inability to extract useful information efficiently. In order to solve the above problems, a three-dimensional dynamic visualization analysis method of the hydrodynamic lake model (3DV-HLM) is proposed by coupling the hydrodynamic lake model and the three-dimensional dynamic visualization technology. Chaohu Lake is taken as an example to verify the feasibility of the method. 13 working conditions are set up and the simulated water flows changing with space and time are analyzed and compared by the 3DV-HLM method. Results show that the 3DV-HLM method proposed in this study is more systematic and effective in the expression of multi-source heterogeneous information than the traditional analysis methods. It is easier to discover rules and obtain useful information from huge data set by the 3DV-HLM method. Besides, the intuitive display of the model results by the 3DV-HLM method is close to the real environment, which can enhance the understanding of the hydrodynamic characteristics of the lake by the water environment managers.

Invasive Dreissenid Mussel Effects on Phosphorus Dynamics in Lake Ontario: Insights from Integrated Hydrodynamic-Ecological Modeling

Invasive dreissenid mussels have a profound effect on the total phosphorus (TP) budget in Lake Ontario, which in turn influences ecological processes such as the resurgence of the benthic alga Cladophora. A validated three-dimensional integrated hydrodynamic and ecological modeling framework is applied to quantify the impact that dreissenids have on the spatial and species distribution of TP in the lake. Model results for April to September 2013 show that dreissenids decrease TP in the water column by about 1812 metric tons (MT), which is about 60% of the tributary TP loading to the lake. This reduction in TP affects other processes controlling its distribution. Physical transport of TP from nearshore to offshore waters is reduced, and the amount of TP involved in chemical reactions is reduced, while TP processed by biological transformations is increased. This study provides the first attempt to quantify the TP budget changes in Lake Ontario by dreissenids using numerical modeling, and findings of this study can be generalized to other lakes with similar conditions.