An ensemble of trend preserving statistically downscaled projections for key marine variables under three different future scenarios for the Baltic Sea
Creators
- 1. Norwegian Institute for Water Research (NIVA)
- 2. Ocean Modeling and Data Assimilation Division, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC)
Description
The ensemble provides future projections of key marine variables under climate change for the Baltci Sea region. The datasets were produced for three different future scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) and five different variables (potential temperature, salinity, dissolved oxygen, pH and chlorophyll) at three different depth levels (5m, 25m and seafloor with the exception of chlorophyll) at monthly frequency for the years 1993 - 2099. The statistical metrics provided are the mean, standard deviation, minimum, maximum median, 2.5 and 97.5 percentile. The ensemble is computed over 4-7 different CMIP6 model realisations (depending on variable), the bias corrections and statistical downscaling applied is based on the methodology by Lange, 2019 and was trained on the GLORYS12V1 reanalysis provided by the Copernicus Marine Environment Monitoring Service (CMEMS).
Analogue datasets are provided in separate zenodo entries for the regions of the Mediterranean Sea, the North Sea, the Bay of Biscay, the Chilean coast and the area around the Yucatán Peninsula, see “Related identifiers”.
The following Earth System Models were used in building the ensemble:
- CMCC-ESM2 (Lovato et al. 2022)
- CMCC-CM2-SR5 (Cherchi et al. 2019)
- CanESM-CanOE (Swart et al., 2019)
- GFDL-ESM4 (Dunne et al., 2020)
- MIROC-ES2L (Hajima et al., 2020)
- MPI-ESM1-2-LR (Mauritsen et al., 2020)
- UKESM1-0-LL (Sellar et al., 2019)
We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP. Generated using E.U. Copernicus Marine Service Information; https://doi.org/10.48670/moi-00021, https://doi.org/10.48670/moi-00019.
This data is distributed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Files
Baltic_Sea_doc.pdf
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Additional details
Funding
References
- Boucher, Olivier, Jérôme Servonnat, Anna Lea Albright, Olivier Aumont, Yves Balkanski, Vladislav Bastrikov, Slimane Bekki, et al. 2020. "Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model." Journal of Advances in Modeling Earth Systems 12 (7). https://doi.org/10.1029/2019ms002010.
- Cherchi, A., Fogli, P.G., Lovato, T., Peano, D., Iovino, D., Gualdi, S., Masina, S., Scoccimarro, E., Materia, S., Bellucci, A., Navarra, A., 2019. "Global Mean Climate and Main Patterns of Variability in the CMCC-CM2 Coupled Model". Journal of Advances in Modeling Earth Systems 11: 185–209. https://doi.org/10.1029/2018MS001369
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- Lange, S., 2019. Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0). Geoscientific Model Development 12, 3055–3070. https://doi.org/10.5194/gmd-12-3055-2019
- Lovato, T., D. Peano, M. Butenschön, S. Materia, D. Iovino, E. Scoccimarro, P. G. Fogli, et al. 2022. "CMIP6 Simulations with the CMCC Earth System Model (CMCC‐ESM2)." Journal of Advances in Modeling Earth Systems 14 (3). https://doi.org/10.1029/2021ms002814.
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