Development of climate models and methods

In 2024, the global average temperature has exceeded 1.5 degrees of warming compared to the pre-industrial temperature for the first time and CO2 emissions continue to increase. It is increasingly likely that even higher temperature levels will be reached in the future, and that extremes become more intense and frequent. It is therefore important to continue working towards more complete climate models able to better understand climate processes and deliver improved climate projections, both globally and for Sweden.

This research area focuses on advancing the models, tools and methods for the simulation, analysis and understanding of the climate system. It encompasses the development and improvement of SMHI’s global Earth system model EC-Earth as well as the convective permitting, regional climate model HCLIM. The EC-Earth model is currently undergoing a major update before delivering Swedens’s contribution to CMIP7 (Coupled Model Intercomparison Project-Phase 7) which will provide input for the next IPCC report (AR7) and boundary conditions for regional climate models.

Compared to the previous model version, the new EC-Earth4 will feature more Earth system components and allow for simulating an interactive carbon cycle. Many of the model’s components - e.g. aerosols, hydrological cycle, sea ice - have been upgraded to match the developments in the different fields of research. The regional model HCLIM will be updated to produce new regional climate simulations. The main developments will focus on questions related to higher resolution and improving realism by adding new components such as aerosols, dynamic vegetation or coupling an ocean model. Many of these developments will be coordinated with the international HCLIM community and research areas at Rossby Centre and the rest of SMHI.

In support of a more resource-efficient production of climate data and as a complement to the dynamical modelling, as well as supporting future model development, the research area will also explore new opportunities in machine learning to i) generate ensembles, ii) efficiently downscale models to higher resolutions, iii) predict extremes and iv) investigate possibilities for replacing complex parameterisations in climate models.

Objectives

The main objective is to coordinate the development of SMHI’s climate models and associated tools and methods that are used within Rossby Centre to improve our understanding of the climate and produce future climate scenarios, by:

• Improving the scientific performance of the EC-Earth and HCLIM models
• Following the discourse in the international climate community, identifying gaps in and opportunities for climate model development
• Exploiting synergies in the model and tool development at various spatial scales
• Advancing the implementation of Earth System Model (ESM) components to EC-Earth and HCLIM
• Establishing strategies and priorities for future updates of climate models for improved scientific and technical performance
• Driving the development of Machine Learning (ML) based emulators for regional climate, climate extremes, and improved efficiency