This research area gives SMHI the tools to produce detailed information on what climate change and its effects may look like, depending on the amount of climate-affecting emissions and land use. The information forms the basis for authorities, companies and researchers on which they produce even more specific and detailed information. All knowledge needs to be updated regularly to reflect the evolving state of science.
Although we know that climate is changing and that the society has to adapt to that, there is still information missing. Both in terms of how climate actually will change, and in terms of how this information should be presented. My research area is about developing methods to construct and use climate information. An important part of that work is to make the information relevant and useful for the end user. Models and scenarios should be selected in a careful way. Uncertainties, variability and extremes should be able to quantify and describe. It’s important that climate information is scientifically based, consequent, understandable and relevant.
- How should concepts of ensemble selection, bias adjustment and user-focused indices be developed and applied?
- How can we quantify and express uncertainty, natural variability and extremes?
- What are the roles of scenarios, warming levels and model resolution in the climate scenario?
- How should knowledge about climate change be distributed to stakeholders?
- Large model ensembles of both global and regional climate models
- Methods for ensemble selection
- Statistical methods for calculation of trends and variability
- SMHI web pages
Strandberg, G. and Lind, P.: The importance of model resolution on simulated precipitation in Europe – from global to regional model, Weather Clim. Dynam., https://doi.org/10.5194/wcd-2020-31, 2020.
T. Koenigk, L. Bärring, D. Matei, G. Nikulin, G. Strandberg, E. Tyrlis, S. Wang & R. Wilcke (2020) On the contribution of internal climate variability to European future climate trends, Tellus A: Dynamic Meteorology and Oceanography, 72:1, 1-17, DOI: 10.1080/16000870.2020.1788901
Wilcke, R. A. I., Kjellström, E., Lin, C., Matei, D., Moberg, A., and Tyrlis, E.: The extremely warm summer of 2018 in Sweden – set in a historical context, Earth Syst. Dynam., 11, 1107–1121, https://doi.org/10.5194/esd-11-1107-2020, 2020.
Christensen, O. B., Kjellström, E., 2020: Partitioning uncertainty components of mean climate and climate change in a large ensemble of European regional climate model projections, Clim. Dyn., 54, 4293–4308, https://doi.org/10.1007/s00382-020-05229-y
Bärring, L., and Strandberg, G., 2018: Does the projected pathway to global warming targets matter? Environ Res Lett 13, https://doi.org/10.1088/1748-9326/aa9f7
Kjellström, E., Nikulin, G., Strandberg, G., Bøssing Christensen, O., Jacob, D., Keuler, K., Lenderink, G., van Meijgaard, E., Schär, C., Somot, S., Lund Sørland, S., Teichmann, C. and Vautard, R., 2018: European climate change at global mean temperature increases of 1.5 and 2 °C above pre-industrial conditions as simulated by the EURO-CORDEX regional climate models. Earth Syst. Dynam., 9, 459-478.