Global climate scenarios and model development

The climate is a global system; its understanding and possible projections into the future need to build on a range of spatial scales including the global dimension.

Background

Global climate models are developed under the rationale that coupled representations of climate-relevant processes can describe the combined effects that constitute the overall climate system. When development is focusing on individual processes and their interactions within the climate system, the resulting overall performance will improve. SMHI is leading the development of the global climate model and Earth System Model EC-Earth, based on the world-leading weather forecast model of the ECMWF (European Centre of Medium Range Weather Forecast) in its seasonal prediction configuration.

Focus

The major tasks in this research area are:

  • to develop an Earth system model in several configurations for usage in climate change projections, predictions and process studies
  • to generate climate change scenario simulations in the context of several Model Intercomparison projects (MIPs) as part of the 6th phase of the Climate Model Intercomparison Project (CMIP6)
  • to provide global scale climate change information for regional downscaling and impact research.

Climate change projections are the base for assessment of possible future climate change and for climate services supporting climate change adaptation and estimating the consequences of climate change mitigation.

Research questions

SMHI prioritizes the following research questions:

  • How does the Earth system respond to forcing by a range of possible emission scenarios and land use?
  • How can we best assess future climate changes given various sources of uncertainty?
  • How can we best evaluate and improve Earth System Models from a climate science and IT perspective?
  • What are the impacts of projected climate change?

To best address these tasks and questions, SMHI sees strongest benefits from engaging in new climate scenarios following the CMIP6 emission scenario framework of Shared Socio-economic Pathways (SSP), representing 5 alternative global society and energy-use models in combination with mitigation ambitions. Results are expected to illustrate consequences of alternative global choices including the politically envisioned Paris agreement pathway and additional overshoot scenarios.

Tools

The major tool for global climate modelling is the EC-Earth model in different configurations. For improved model evaluation, SMHI participates in the development of standard analysis metrics and analysis software that covers a range of climate-related processes. For improved technical sustainability of the model, SMHI participates in climate model infrastructure efforts.

SMHI collaborates with Swedish and European partners to develop the EC-Earth Earth System Model, and with the CMIP6-ScenarioMIP (and related MIPs) to carry out simulations.

Fig 1 - sea ice extent
Figure 1. March (dashed) and September (solid) sea ice extent in m2 in the northern hemisphere in the twentieth century simulations (black), RCP4.5 (blue), RCP8.5 (red), RCP2.6 (green) with EC-Earth and in satellite observations (stars). (Koenigk et al. 2013.)

Recent Publications

Berg, P., R. Döscher, T. Koenigk, 2016. On the effects of constraining atmospheric circulation in a coupled atmosphere-ocean Arctic regional climate model. Clim Dyn 46: 3499, doi:10.1007/s00382-015-2783-y.

Brodeau, L., & Koenigk, T. (2016). Extinction of the northern oceanic deep convection in an ensemble of climate model simulations of the 20th and 21st centuries. Climate Dynamics, 46(9-10), 2863-2882. Clim Dyn (2016) 46: 2863. doi:10.1007/s00382-015-2736-5.

Caian, M., Koenigk, T., Döscher, R., Devasthale, A., accepted: An inter-annual link between Arctic sea-ice cover and North Atlantic Oscillation. Climate Dynamics.

Döscher, R., Vihma, T., & Maksimovich, E. (2014). Recent advances in understanding the Arctic climate system state and change from a sea ice perspective: a review. Atmospheric Chemistry and Physics, 14(24), 13571-13600. doi:10.5194/acp-14-13571-2014.

Döscher, R. and Koenigk, T. (2013): Arctic rapid sea ice loss events in regional coupled climate scenario experiments, Ocean Sci., 9, 217-248, doi:10.5194/os-9-217-2013.

van den Hurk, B. J., Bouwer, L. M., Buontempo, C., Döscher, R., Ercin, E., Hananel, C., ... & Pappenberger, F. (2016). Improving predictions and management of hydrological extremes through climate services: www. imprex. eu. Climate Services, 1, 6-11. doi:10.1016/j.cliser.2016.01.001.

Koenigk, T., Brodeau, L., Graversen, R. G., Karlsson, J., Svensson, G., Tjernström, M., ... & Wyser, K. (2013). Arctic climate change in 21st century CMIP5 simulations with EC-Earth. Climate Dynamics, 40(11-12), 2719-2743. doi:10.1007/s00382-012-1505-y