Completed

July 2019– June 2023

Constraining uncertainty of multi-decadal climate projections

Partners

University of Leeds, ETH Zürich, Max-Planck-Gesellschaft Zur Förderung Der Wissenschaften, Météo-France, CICERO, TU Delft, Met Office, Universitaet Leipzig, Centre National De La Recherche Scientifique, Stockholms Universitet, Weizmann Institute Of Science, Imperial College London, IIASA

The 2015 Paris Agreement sets out a global action plan to avoid dangerous climate change by limiting global warming to well below 2°C, whilst pursuing efforts to limit warming to 1.5°C. However, predicting how the climate will change over the next 20-50 years, as well as defining the emissions pathways that will set and keep the world on track, requires a better understanding of how several human and natural factors will affect the climate in coming decades. These include how atmospheric aerosols affect the Earth’s radiation budget, and the roles of clouds and oceans in driving climate change.

The EU-funded CONSTRAIN project, a consortium of 14 European partners, is developing a better understanding of these variables, feeding them into climate models to reduce uncertainties, and creating improved climate projections for the next 20-50 years in regional as well as global scales. In doing so, CONSTRAIN will take full advantage of existing knowledge from the Sixth Climate Model Intercomparison Project (CMIP6) as well as other Horizon 2020 and European Research Council projects.

CONSTRAIN will focus research on three climate science knowledge gaps:
  1. The magnitude and pattern of how much solar radiation is captured in the Earth’s atmosphere when accounting for the full range of agents (particles or elements capturing solar radiation) including aerosols
  2. The role of clouds and their interactions with other atmospheric drivers that influence how sensitively the climate system responds to an increase in atmospheric GHG concentrations
  3. The manner in which ocean variability influences the response of the climate system to changes in the atmospheric radiative balance across different timescales.

The project will deliver updated climate model projections for the 2023 UNFCCC Global Stocktake. CONSTRAIN will take full advantage of the climate model integration provided by the sixth Climate Model Intercomparison Project (CMIP6) and will leverage existing European research projects funded under the Horizon 2020 programme and European Research Council (ERC) flagship research projects. The project will combine novel analysis of CMIP6 data with dedicated high-resolution simulations and new observations to address the three identified knowledge gaps.

A fourth knowledge gap identified is the effective translation of new physical science understanding into an improved evidence base for policy decisions. CONSTRAIN will address this by developing simplified calibrated models that integrate and operationalise learnings from across the project consortium to provide new capability to assess impacts of climate change under a broad range of possible emission futures. The project will focus on the expected spatially resolved decadal changes until mid-century providing robust evidence on key climate system response indicators, surface temperature, precipitation and circulation changes, thereby enabling evidence-based policy decisions that will directly benefit the EU’s adaptation and mitigation strategy.

Climate Analytics has a leading role in translating the project results to policy and dissemination of findings. Based on the results of the research, we will publish a yearly “CONSTRAIN report” summarising and synthesising the findings for policy-makers at the EU and international level. The results will feed into the IPCC process and a Stakeholder Committee comprised of journalists, IPCC focal points, activists and researchers will provide regular input on stakeholder and communication needs related to the research topics. The feedback will be integrated into the research to ensure the findings can be used to improve policy decisions on mitigation and adaptation.