Constraining uncertainty of multi-decadal climate projections (CONSTRAIN)
The EU-funded project “Constraining uncertainty of multi-decadal climate projections” (CONSTRAIN) will address crucial knowledge gaps in climate science to significantly improve our understanding of how natural and human factors affect multi-decadal regional climate change. The project will deliver improved climate projections of policy relevance for the next 20 to 50 years, contributing to European research on fundamental climate system processes and climate variability.
The ZERO IN report series, to be published annually, will provide information on crucial scientific concepts relevant to the Paris Agreement, as well as background and context on new developments that relate to the science-policy interface.
ZERO IN on a new generation of climate models, COVID-19 and the Paris Agreement
The second ZERO IN report focuses on the new CMIP6 climate models and the science behind the Paris Agreement Long-Term Temperature Goal, highlighting how improved understanding in both areas can help us to better plan for what lies ahead. In particular, it finds that while the effect of COVID-19 on climate has so far been negligible, a green recovery could profoundly alter the trajectory of climate change over the next two decades. The project’s findings also reaffirm the importance of stringent near-term emission reductions and reaching net-zero CO2 emissions by 2050 to get the world on a 1.5°C pathway. The report also provides an update on the remaining global carbon budget.
ZERO IN on the remaining carbon budget and decadal warming rates
This first CONSTRAIN report zeroes in on the remaining carbon budget as well as projected surface warming rates over the next 20 years. Both topics are crucially important to the implementation of the Paris Agreement.
CONSTRAIN on Twitter
1 July 2019 – 30 June 2023
EU Horizon 2020 Programme
1. Coordinator: University of Leeds
2. ETH Zürich
3. Max-Planck-Gesellschaft Zur Förderung Der Wissenschaften eV (MPG)
5. Cicero Senter Klimaforskning Stiftelse (CICERO)
6. Technische Universiteit Delft (TU Delft)
7. Met Office (Met Office)
8. Universitaet Leipzig (ULEI)
9. Centre National De La Recherche Scientifique (CNRS)
10. Stockholms Universitet (SU)
11. Weizmann Institute Of Science (Weizmann)
12. Imperial College Of Science Technology And Medicine (Imperial)
13. Internationales Institut Fuer Angewandte Systemanalyse (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:
- 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
- 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
- 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.