Arctic Climate Predictions: Pathways to Resilient, Sustainable Societies ARCPATH

How can Arctic climate projections be improved on a regional and local scale? That is one of the main topics that the Nordic Centre of Excellence funded project ARCPATH seeks to answer.

In the high latitude regions climate change is amplified via a number of different feedback mechanisms. This leads to a faster warming compared to the projected global mean trend leading to less sea ice, warmer oceanic and atmospheric temperatures and a moister atmosphere.

As a consequence, the living conditions not only for the wild life, but also for the millions of people living in the region, are affected. Global climate predictions give robust and realistic results on a large scale but on a local scale the results suffer from the relatively coarse resolution.

To better meet the demands for adaptation and responsible governance more detailed information and research is needed.

Project goals

The overarching goals of the ARCHPATH project are three-fold:

  • To improve Arctic climate prediction by using innovative methods to capture both anthropogenic and natural factors in global and high-resolution regional models;
  • To increase understanding and reduce uncertainties regarding how changes in climate interact with multiple societal factors including the development of local and regional adaptation measures; and
  • To supply this knowledge as potential “pathways to action” to the specific Arctic regions singled out for special focus in the project.

Role of SMHI

SMHIs role in the project is to contribute with expertise on, and perform, climate simulations on both a global scale (with the earth system model EC-EARTH) and a regional scale (with models HARMONIE and MITgcm). The work will focus on developing techniques to improve near-term (seasonal to decadal) climate predictions.

Previous studies by SMHI have already shown that there is a relatively high potential for predictability in the northern North Atlantic and Arctic regions, see red areas in Figure 1.

Estimate of EC-EARTH’s predictability of 2 meter air temperature.
Figure 1: An estimate of EC-EARTH’s predictability of 2 meter air temperature. Red areas show regions with the potential for high predictability.
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In addition, a recent SMHI study with the regional atmospheric model RCA have shown that there is more added value in using a regional model, which gives more detailed local information in e.g. Arctic precipitation (see Figure 2), compared to using a global climate model.

The change in seasonal precipitation for an ensemble of regionally downscaled projections.
Figure 2: The change in seasonal precipitation for an ensemble of regionally downscaled projections using RCA (top row) and global climate projections (bottom row).
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Collaboration

The project will run over five years (2016–2020) and is funded by NordForsk.

SMHI will collaborate with scientist from: Nansen Environmental and Remote Sensing Center, Bergen University, Norwegian Institute for Air Research, Arctic University in Tromsö, Danish Meteorological Institute and Iceland University.