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Research

Scientific goals

Our research focus is on understanding climate variability and the sources of predictability and improving the forecast quality of our prediction system, in particular through the addition of new model components, increase in model resolution or the development of new initialization strategies. We are involved in a number of research activities, at the national, European and international level.

Projects

EUCP

The H2020 European Climate Prediction system (EUCP) project develops an innovative European ensemble climate prediction system based on a new generation of improved, typically higher-resolution climate models, covering timescales from seasons to decades initialized with observations. The climate information provided by the system will be co-designed with users to support practical and strategic climate adaptation and mitigation decision-taking on local, national and global scales.

EUCP

DCPP

The coordination of the scientific and practical aspects of decadal climate prediction research within WCRP is undertaken by the DCPP Panel under the guidance of the Working Group on Subseasonal to Interdecadal Prediction (WGSIP). The DCPP is organized into 3 components:

  • Component A, Hindcasts
  • Component B, Forecasts
  • Component C, Predictability, mechanisms, and case studies.

It also contributes to the WCRP Grand Challenge on Near-Term Climate Prediction:

DCPP

Real-time decadal forecast exchange

The Lead Centre for Annual-to-Decadal Climate Prediction collects and provides hindcasts, forecasts and verification data from a number of contributing centres worldwide.It also produces the WMO Global Annual to Decadal Climate Update.

Real-time decadal forecast exchange

CLINSA

The CLINSA project, funded by the Spanish Ministry for Economy, Industry and Competitivity (MINECO) addresses the challenge of developing a decadal climate forecast system through two main activities. First, it proposes the development of a capability for the formulation of decadal predictions, including both a full hindcast contribution to the Decadal Climate Prediction Project of CMIP6 and the regular formulation of real-time forecasts. As a second main activity, the knowledge and climate data obtained will be used to illustrate the potential benefits of decadal prediction in several sectors (in particular renewable energy and crop yield estimation).

4C

The H2020 Climate-Carbon Interactions in the Coming Century (4C) project addresses the crucial knowledge gap in the climate sensitivity to carbon dioxide emissions, by reducing uncertainty in our quantitative understanding of carbon-climate interactions and feedbacks. This will be achieved through innovative integration of models and observations, providing new constraints on modelled carbon-climate interactions and climate projections, and supporting IPCC assessments and policy objectives.

H2020 Climate-Carbon Interactions in the Coming Century

C3S_34c

The Copernicus Climate Change Service project will provide a robust, credible and reliable encoding standard for decadal forecasts and products. It also aims to provide a robust definition of methods for post-processing of forecast data including the generation of multi-model products comparing different formulations and best practises for forecast quality assessment. Finally, this project will deliver case studies involving stakeholders from the various sectors as real users of decadal prediction.

Copernicus Climate Change Service Copernicus Climate Change Service

Other relevant initiatives in decadal predictions community:

 

The MiKlip project

https://www.fona-miklip.de/

 

Decadal Prediction at Met-Office

https://www.metoffice.gov.uk/research/climate/seasonal-to-decadal/long-range/decadal-fc/index

 

Decadal Prediction at NCAR

http://www.cesm.ucar.edu/working_groups/CVC/simulations/decadal-prediction.html

Related links

 

The s2dverification package

https://cran.r-project.org/web/packages/s2dverification/index.html

 

The CSTools package

https://cran.r-project.org/web/packages/CSTools/index.html

 

The startR R package

https://cran.r-project.org/web/packages/startR/startR.pdf

 

The ClimProjDiags R package

https://cran.r-project.org/web/packages/ClimProjDiags/ClimProjDiags.pdf

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