Abstract
Lake ecosystems are impacted by changes in climatic conditions. Climate changes forecasted to occur are reflected in models by slow gradual changes over extended periods of time. Output from weather generators, on the other hand, can simulate short-term extreme conditions and weather patterns. In order to evaluate the likely impact of climate changes on a large sub-tropical lake, specifically the thermal regime of the lake, we constructed climate scenarios using a weather generator. The 30-year scenarios included no change in climate conditions, a gradual change, increased frequency of heat waves and a merging of the latter two. The projected impact on the lake’s physical properties was evaluated using an ensemble of 1-D hydrodynamic lake models. The gradual increase scenario had the largest impact on annual temperatures and stratification period; however, increased heat waves had a large effect on the summer lake conditions and introduced a larger degree of variability in water temperature. The use of the ensemble of models resulted in variability in the projected impacts; yet, the large degree of similarity between projected trends and patterns increased confidence in the results. The projected effect the heat waves will have on the lake conditions highlights the need to include heat waves in climate studies and the need for impact studies in order to better understand possible consequences for lake ecosystems.
Highlights
Climate models are widely used by scientists to explore the present, as well as climate change scenarios, and serve as a basis for policy debates and decisions [1]
Details about the model can be found in Burchard et al [42]. As this is the first application of general oceanographic turbulence model (GOTM) and a calibrated version of general lake model (GLM) to Lake Kinneret, we provide a description of the calibration and validation of both models
Though the probability of these extreme temperatures is low, the pattern is consistent over all three models and similar to the pattern observed during August 2010
Summary
Climate models are widely used by scientists to explore the present, as well as climate change scenarios, and serve as a basis for policy debates and decisions [1]. In an attempt to apply global climate change models (GCMs) to spatially limited areas and use higher resolution models, a number of approaches have developed, which include regional climate models (RCMs), statistical downscaling and weather generators [2,3]. Each of these approaches provides different benefits, but they suffer from various limitations, and their efficiency depends on the objectives of the study at hand. One of the shortcomings of climate models, regardless of the spatial and temporal extent and resolution, is the monotonous change over time in the model variables.
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