Modeling Climate Change Uncertainty and Its Impact on the Nemunas River Watershed and Curonian Lagoon Ecosystem
This study advances the understanding of climate projection uncertainties in the Nemunas River, Curonian Lagoon, and southeastern Baltic Sea continuum by analyzing a subset of climate models, focusing on a coupled ocean and drainage basin model. Four downscaled and bias-corrected high-resolution reg...
| Main Authors: | , , , , , |
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| Format: | Text |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/egusphere-2024-890 https://egusphere.copernicus.org/preprints/2024/egusphere-2024-890/ |
| Summary: | This study advances the understanding of climate projection uncertainties in the Nemunas River, Curonian Lagoon, and southeastern Baltic Sea continuum by analyzing a subset of climate models, focusing on a coupled ocean and drainage basin model. Four downscaled and bias-corrected high-resolution regional atmospheric climate models were used to set up the hydrological (SWAT) and hydrodynamic (SHYFEM) modeling system. This study investigates the variability and trends in environmental parameters such as water fluxes, timing, nutrient load, water temperature, ice cover, and saltwater intrusions under Representative Concentration Pathway 4.5 and 8.5 scenarios. The analysis highlights the variability among model results underscoring the inherent uncertainties in forecasting climatic impacts, hence highlighting the necessity of using multi-model ensembles to improve the accuracy of climate change impact assessments. Additionally, modeling results were used to evaluate the possible environmental impact due to climate change through the analysis of the cold water fish species reproduction season. We analyze the duration of cold periods (<1.5 °C) as a thermal window for burbot spawning, calculated assuming different climate forcing scenarios and models. The analysis indicated coherent shrinking of the cold period and presence of the changepoints during historical and different periods in the future, however, not all trends reach statistical significance, and due to high variability within the projections, they are less reliable. This means there is a considerable amount of uncertainty in these projections, highlighting the difficulty in making reliable climate change impact assessments. |
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