Opendata, web and dolomites


Emergent Constraints on Climate-Land feedbacks in the Earth System

Total Cost €


EC-Contrib. €






Project "ECCLES" data sheet

The following table provides information about the project.


Organization address
city: EXETER
postcode: EX4 4QJ

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 2˙249˙834 €
 EC max contribution 2˙249˙834 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-ADG
 Funding Scheme ERC-ADG
 Starting year 2017
 Duration (year-month-day) from 2017-10-01   to  2022-09-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE UNIVERSITY OF EXETER UK (EXETER) coordinator 2˙249˙834.00


 Project objective

The Land Biosphere is a critical component of the Earth System, linking to climate through multiple feedback processes. Understanding these feedback processes is a huge intellectual challenge. In part because of the pioneering work of the PI (Cox et al., 2000), many of the climate projections reported in the IPCC 5th Assessment Report (AR5) now include climate-carbon cycle feedbacks. However the latest Earth System Models (ESMs) continue to show a huge range in the projected responses of the land carbon cycle over the 21st century. This uncertainty threatens to undermine the value of these projections to inform climate policy. This project (ECCLES) is designed to produce significant reductions in the uncertainties associated with land-climate interactions, using the novel concept of Emergent Constraints - relationships between future projections and observable variations in the current Earth System that are common across the ensemble of ESMs. Emergent Constraints have many attractive features but chief amongst these is that they can make ensembles of ESMs more than the sum of the parts - allowing the full range of ESM projections to be used collectively, alongside key observations, to reduce uncertainties in the future climate. The project will deliver: (i) a theoretical foundation for Emergent Constraints; (ii) new datasets on the changing function of the land biosphere; (iii) Emergent Constraints on land-climate interactions based on observed temporal and spatial variations; (iv) a new generation of scientists expert in land-climate interactions and Emergent Constraints. ECCLES will benefit from the expertise and experience of the PI, which includes training as a theoretical physicist, an early career developing models of the land biosphere for ESMs, and a current career in a department of mathematics where he is at the forefront of efforts to develop and apply the concept of Emergent Constraints (Cox et al., 2013, Wenzel et al., 2016).


year authors and title journal last update
List of publications.
2018 Mark S Williamson, Peter M Cox, Femke J M M Nijsse
Theoretical foundations of emergent constraints: relationships between climate sensitivity and global temperature variability in conceptual models
published pages: , ISSN: 2059-6987, DOI: 10.1093/climsys/dzy006
Dynamics and Statistics of the Climate System 3/1 2019-06-07
2018 Jonathan R Moore, Kai Zhu, Chris Huntingford, Peter M Cox
Equilibrium forest demography explains the distribution of tree sizes across North America
published pages: 84019, ISSN: 1748-9326, DOI: 10.1088/1748-9326/aad6d1
Environmental Research Letters 13/8 2019-06-03
2018 Cleiton B. Eller, Lucy Rowland, Rafael S. Oliveira, Paulo R. L. Bittencourt, Fernanda V. Barros, Antonio C. L. da Costa, Patrick Meir, Andrew D. Friend, Maurizio Mencuccini, Stephen Sitch, Peter Cox
Modelling tropical forest responses to drought and El Niño with a stomatal optimization model based on xylem hydraulics
published pages: 20170315, ISSN: 0962-8436, DOI: 10.1098/rstb.2017.0315
Philosophical Transactions of the Royal Society B: Biological Sciences 373/1760 2019-06-03
2018 Peter M. Cox, Mark S. Williamson, Femke J. M. M. Nijsse, Chris Huntingford
Cox et al. reply
published pages: E10-E15, ISSN: 0028-0836, DOI: 10.1038/s41586-018-0641-x
Nature 563/7729 2019-06-03
2018 William J Collins, Christopher P Webber, Peter M Cox, Chris Huntingford, Jason Lowe, Stephen Sitch, Sarah E Chadburn, Edward Comyn-Platt, Anna B Harper, Garry Hayman, Tom Powell
Increased importance of methane reduction for a 1.5 degree target
published pages: 54003, ISSN: 1748-9326, DOI: 10.1088/1748-9326/aab89c
Environmental Research Letters 13/5 2019-06-03
2018 Peter M. Cox, Chris Huntingford, Mark S. Williamson
Emergent constraint on equilibrium climate sensitivity from global temperature variability
published pages: 319-322, ISSN: 0028-0836, DOI: 10.1038/nature25450
Nature 553/7688 2019-06-03
2019 Veronika Eyring, Peter M. Cox, Gregory M. Flato, Peter J. Gleckler, Gab Abramowitz, Peter Caldwell, William D. Collins, Bettina K. Gier, Alex D. Hall, Forrest M. Hoffman, George C. Hurtt, Alexandra Jahn, Chris D. Jones, Stephen A. Klein, John P. Krasting, Lester Kwiatkowski, Ruth Lorenz, Eric Maloney, Gerald A. Meehl, Angeline G. Pendergrass, Robert Pincus, Alex C. Ruane, Joellen L. Russell, Benjamin M. Sanderson, Benjamin D. Santer, Steven C. Sherwood, Isla R. Simpson, Ronald J. Stouffer, Mark S. Williamson
Taking climate model evaluation to the next level
published pages: 102-110, ISSN: 1758-678X, DOI: 10.1038/s41558-018-0355-y
Nature Climate Change 9/2 2019-06-03
2018 Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, Carolina Duran-Rojas
Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types
published pages: 2857-2873, ISSN: 1991-9603, DOI: 10.5194/gmd-11-2857-2018
Geoscientific Model Development 11/7 2019-06-03
2018 Anna B. Harper, Tom Powell, Peter M. Cox, Joanna House, Chris Huntingford, Timothy M. Lenton, Stephen Sitch, Eleanor Burke, Sarah E. Chadburn, William J. Collins, Edward Comyn-Platt, Vassilis Daioglou, Jonathan C. Doelman, Garry Hayman, Eddy Robertson, Detlef van Vuuren, Andy Wiltshire, Christopher P. Webber, Ana Bastos, Lena Boysen, Philippe Ciais, Narayanappa Devaraju, Atul K. Jain, Andreas Krause, Ben Poulter, Shijie Shu
Land-use emissions play a critical role in land-based mitigation for Paris climate targets
published pages: , ISSN: 2041-1723, DOI: 10.1038/s41467-018-05340-z
Nature Communications 9/1 2019-06-03
2019 Ye Liu, Yongkang Xue, Glen MacDonald, Peter Cox, Zhengqiu Zhang
Global vegetation variability and its response to elevated CO<sub>2</sub>, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data
published pages: 9-29, ISSN: 2190-4987, DOI: 10.5194/esd-10-9-2019
Earth System Dynamics 10/1 2019-06-03
2018 Edward Comyn-Platt, Garry Hayman, Chris Huntingford, Sarah E. Chadburn, Eleanor J. Burke, Anna B. Harper, William J. Collins, Christopher P. Webber, Tom Powell, Peter M. Cox, Nicola Gedney, Stephen Sitch
Carbon budgets for 1.5 and 2 °C targets lowered by natural wetland and permafrost feedbacks
published pages: 568-573, ISSN: 1752-0894, DOI: 10.1038/s41561-018-0174-9
Nature Geoscience 11/8 2019-06-03

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "ECCLES" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email ( and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "ECCLES" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)


The Enemy of the Good: Towards a Theory of Moral Progress

Read More  

NanoPD_P (2020)

High throughput multiplexed trace-analyte screening for diagnostics applications

Read More  

HOLI (2019)

Deep Learning for Holistic Inference

Read More