Identifying Climate Change Driven Critical Weather Conditions that Result in Dramatic Shifts in Lakes

Lakes provide essential ecosystem services to society and are showing alarming responses to ongoing climate change worldwide. Apart from long-term changes, events on a shorter time scale can also have medium- to long-term impacts on lakes. Therefore, we aim to investigate the extent to which short- to medium-term weather conditions, together with long-term climatic changes, have critical implications for lakes. To accomplish this, we are jointly advancing our methods for stochastic weather generation and lake modeling to combine them into a model chain. This model chain will allow us to model iteratively, in an inverse manner, which weather events can cause predefined, dangerous changes in lake states, i.e., identify critical weather conditions. As a specific example of a lake, we use Lake Kinneret in Israel, which is already under pressure from changing climatic conditions and is located in a region where significant changes are projected to continue. Our approach will allow us to combine identified critical weather conditions with long-term changes to assess the relative importance of the two influences. This will further enable us to evaluate whether weather events that have a crucial impact on the lake under current climatic conditions become even more dangerous due to climate change, and whether weather conditions that would have been irrelevant in the past become hazardous only when combined with long-term climatic changes.

In the second phase of the project, to expand the assessment of the impact of climate change and critical weather conditions, we plan to extend the model chain to include catchment-scale processes and to resolve three-dimensional flow patterns in the lake. This extension will allow us to include river discharges and nutrient loadings consistent with the generated weather and to model flow patterns such as breaking internal waves, which may become a crucial contributor to mixing under future conditions. Since these models will be driven by the same stochastically generated weather, it is necessary to further develop the corresponding weather generator to produce spatially resolved values. In the second phase of the project, we will not only be able to refine the results of the first half but also determine to what extent targeted water management actions can counteract the identified critical weather conditions.