Abstract
A statistical downscaling approach is applied to the output of five different global climate model simulations driven by twenty-first century future scenarios of greenhouse gas concentrations. The contribution of sea-level pressure (SLP) and precipitation changes to regional future winter sea-level changes is estimated for four Baltic sea-level stations by establishing statistical relationships between sea level as predictand and large-scale climate fields as predictors. Using SLP as predictor for the central and eastern Baltic Sea level stations, three climate models lead to statistically significant twenty-first century future trends in the range of the order of 1–2 mm/year. Using precipitation as predictor for the stations in the southern Baltic coast all five models lead to statistically significant trends with a range of the order of 0.4 mm/year. These numbers are smaller, but of the order of magnitude as the predicted global sea-level rise.
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Acknowledgments
This study is part of the German Science Foundation project SINCOS and of the BALTEX program. I acknowledge the international modelling groups for providing their data for analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the model data. I am grateful to E. Zorita for his help with this manuscript. I thank D. Bray for proof-reading.
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Hünicke, B. Contribution of regional climate drivers to future winter sea-level changes in the Baltic Sea estimated by statistical methods and simulations of climate models. Int J Earth Sci (Geol Rundsch) 99, 1721–1730 (2010). https://doi.org/10.1007/s00531-009-0470-0
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DOI: https://doi.org/10.1007/s00531-009-0470-0