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<div style="background-color: #D4E2FC; border-top: 1px solid #5F92F2; font-size: bigger; padding-left: 15px; margin: 12px -5px -5px -5px;">'''BOINC project page template'''</div>
[[File:{{#setmainimage:Clim.jpg}}|alt=climateprediction.net logo|center|frameless]]
 
 
{{Infobox software
| name = climateprediction.net
| logo = Clim.jpg
| screenshot = Climateprediction.gif
| caption = climateprediction.net BOINC climate simulation screensaver
| developer = University of Oxford, UK Met Office, Open University, University of Reading
| released = 2003
| latest release version = Continuously updated BOINC-based climate models
| operating system = Cross-platform (Windows, Linux, macOS)
| platform = [[BOINC]]
| genre = Volunteer distributed computing, climate modelling
| license = Research software (climate model dependent)
| website = https://www.cpdn.org
| status = Active
}}
[[File:Boinc client rosetta climateprediction net.jpg|thumb|BOINC manager, running Rosetta@home and ClimatePrediction.net]]
'''climateprediction.net''' ('''CPDN''') is a volunteer distributed computing project operating on the [[BOINC]] infrastructure, designed to improve understanding of climate change by running large ensembles of global climate model simulations. It is jointly coordinated by the University of Oxford and partner institutions including the UK Met Office and multiple UK research centres <ref name=cpdn_about>https://www.cpdn.org/about.php</ref>.
 
The project is one of the largest climate modelling experiments ever conducted in terms of computational scale and ensemble size, producing statistically significant distributions of future climate states rather than single deterministic projections <ref name=wiki>https://en.wikipedia.org/wiki/Climateprediction.net</ref>.
[[File:Global Warming Predictions.png|thumb|Global Warming Predictions]]
 
== Overview ==
climateprediction.net applies distributed computing to climate science by running thousands of perturbed climate simulations on volunteer computers worldwide. Each simulation varies uncertain physical parameters within plausible ranges, enabling probabilistic climate prediction through ensemble statistics <ref name=oxford_news>https://www.ox.ac.uk/news/2004-09-16-climatepredictionnet-boinc</ref>.
 
This approach addresses a fundamental limitation in traditional climate modelling: uncertainty quantification in long-term climate projections.


[[File:{{#setmainimage:Clim.jpg}}|alt=climateprediction.net logo|center|frameless]]
== Scientific Rationale ==
The project is based on the recognition that climate models contain structural and parametric uncertainty. Instead of producing a single forecast, CPDN explores a probability distribution of outcomes by varying:


[https://www.cpdn.org/cpdnboinc/ '''climate''prediction''.net'''] is a '''''[[wikipedia:Volunteer computing|volunteer distributed computing]]''''' project that needs your help to do research in climate science.[[File:Climateprediction.gif|alt=screensaver image|thumb|Climate''prediction''.net HadSM3 Screensaver]]
* Cloud parameterizations 
* Ocean heat uptake 
* Aerosol forcing 
* Radiative transfer parameters 


== Wikipedia page ==
This ensemble-based method allows estimation of climate sensitivity ranges consistent with observed climate data <ref name=stainforth2005>Stainforth et al., Nature (2005)</ref>.
[[wikipedia:Climateprediction.net|'''''climateprediction.net''''']]


== Why climate''prediction''.net? ==
== History ==
[[wikipedia:Myles_Allen|'''''Myles Allen''''']] first thought about the need for large [[wikipedia:Climate_ensemble|'''''climate ensembles''''']] in 1997, and was introduced to the success of SETI@home in 1999. A 2003 launch only offered a Windows "classic" client. On 26 August 2004 a BOINC client was launched which supported Windows, Linux and Mac OS X.  
The concept for CPDN was introduced by Myles Allen in 1999 in the Nature commentary “Do-it-yourself climate prediction” <ref name=allen1999>Allen, M. (1999), Nature</ref>.


== Goal ==
Key milestones include:
Investigate the approximations that have to be made in state-of-the-art climate models.


== Methods ==
* '''1999''' – Concept proposal for distributed climate modelling
By running the model thousands of times we hope to find out how the model responds to slight tweaks to these approximations - slight enough to not make the approximations any less realistic. This will allow us to improve our understanding of how sensitive our models are to small changes and also to things like changes in carbon dioxide and the sulphur cycle. This will allow us to explore how climate may change in the next century under a wide range of different scenarios.
* '''2002''' – UK research council funding secured
* '''2003''' – Project launch
* '''2004''' – Migration to BOINC platform
* '''2006''' – BBC Climate Change Experiment
* '''2009''' – BBC experiment concluded and data archived


== Scientific Projects ==
== Scientific Projects ==


==== Current: ====
CPDN runs multiple research streams grouped into active and completed experiments.
 
=== Current Projects ===
* DOCILE (Drives Of Change In mid-Latitude weather Events)
* DOCILE (Drives Of Change In mid-Latitude weather Events)
* TNC (The Nature Conservancy)
* TNC (The Nature Conservancy partnership studies)
* GOTHAM (Globally Observed Teleconnections and their role and representation in Hierarchies of Atmospheric Models)
* GOTHAM (Globally Observed Teleconnections and their role and representation in Hierarchies of Atmospheric Models)
* AFLAME (attributing Amazon Forest fires from Land-use Alteration and Meteorological Extremes)
* AFLAME (Attributing Amazon Forest fires from Land-use Alteration and Meteorological Extremes)
* HIASA
* HIASA (High Impact Atmospheric Simulation Analysis)
* EMBARK
* EMBARK (ensemble-based climate risk modelling initiative)
* National Trust
* National Trust climate resilience modelling
 
These projects focus on attribution science, extreme event analysis, and climate risk quantification in regional systems <ref name=cpdn_projects>https://climateprediction.net/projects/</ref>.
 
=== Completed Projects ===
* weather@home <ref name=weatherhome>https://climateprediction.net/projects/completed-project/completed-weatherhome-projects/</ref>
* HadCM3 and other models ensemble experiments <ref name=hadcm3>https://climateprediction.net/projects/completed-project/hadcm3-and-other-models/</ref>
 
These completed studies provided foundational datasets for understanding climate variability, extreme weather attribution, and ensemble climate uncertainty.
 
== Model Systems ==
CPDN has used multiple generations of climate models:
 
=== HadCM3-based Models ===
The HadCM3 coupled atmosphere-ocean general circulation model formed the basis of early CPDN experiments. It allowed long-duration simulations at relatively low computational cost.
 
=== Weather@Home System ===
An extension enabling regional downscaling of global climate projections, widely used in extreme weather attribution studies.
 
=== OpenIFS Models ===
Recent CPDN simulations use ECMWF OpenIFS configurations, enabling higher-resolution global modeling. Some configurations require multicore execution and up to tens of gigabytes of RAM per job <ref name=reddit_openifs>https://www.reddit.com/r/BOINC/comments/1mhrgkw</ref>.
 
== BBC Climate Change Experiment ==
The BBC Climate Change Experiment (2006–2009) was a major public engagement initiative involving over 120,000 volunteers.
 
Participants ran simulations covering:
 
* 20th century climate (1920–2000)
* Future scenarios (2000–2080)
 
The experiment demonstrated the feasibility of large-scale public participation in climate modelling and contributed to early climate risk communication efforts <ref name=bbc>https://www.bbc.co.uk/sn/climateexperiment</ref>.
 
== Computational Methodology ==
Each CPDN work unit typically includes:
 
# Model initialization and spin-up
# Control simulation under baseline parameters
# Perturbed simulation with modified physical constants
 
Outputs are aggregated across thousands of independent runs to derive probabilistic climate response functions <ref name=stainforth2005/>.
[[File:Climateprediction.gif|center|thumb|BOINC client running CPDN work units]]
[[File:Climate Zones, Scenario B1 2001 - 2025, Global (7242981050).jpg|thumb|Climate Zones, Scenario B1 2001 - 2025]]
 
== Scientific Output ==
CPDN data has contributed to numerous peer-reviewed studies in climate science, including:
 
* Stainforth et al. (2005) — climate sensitivity uncertainty distributions
* Murphy et al. (2004) — probabilistic climate modelling framework
* Sexton et al. (2012) — regional climate uncertainty analysis
* Philip et al. (2019) — extreme weather attribution studies
 
The BOINC scientific publication archive also lists CPDN-derived contributions across multiple climate research domains <ref name=boinc_pubs>https://boinc.berkeley.edu/pubs.php</ref>.
 
== Project Team and Sponsors ==
The project is led by:
 
* Prof Myles R. Allen 
* Andy Bowery 
* Dr Neven S. Fuckar 
* Dr Sihan Li 
* Dr Friederike E. L. Otto 
* Prof David Wallom 
 
CPDN is based at the University of Oxford, primarily within:
 
* Environmental Change Institute 
* Oxford e-Research Centre 
* Atmospheric, Oceanic and Planetary Physics group 
 
<ref name=cpdn_people>https://climateprediction.net/about/people/</ref>
 
== Impact ==
climateprediction.net has had significant scientific and societal impact:
 
* One of the largest ensemble climate datasets ever produced
* Early demonstration of probabilistic climate prediction
* Major contribution to extreme weather attribution science
* Public engagement through BBC collaboration
* Influence on IPCC uncertainty framing methodologies


==== Completed: ====
== Scientific Publications ==
A full list of CPDN-related publications is maintained at:
https://climateprediction.net/publications/ <ref name=cpdn_pubs>https://climateprediction.net/publications/</ref>


* [https://climateprediction.net/projects/completed-project/completed-weatherhome-projects/ weather@home]
Key peer-reviewed works include publications in Nature, Journal of Climate, and Environmental Research Letters.
* [https://climateprediction.net/projects/completed-project/hadcm3-and-other-models/ HadCM3 and other models]


== [https://climateprediction.net/about/people/ Project team] / Sponsors ==
== See also ==
Prof Myles R. Allen, Andy Bowery, Dr Neven S. Fuckar, Dr Sihan Li, Dr Friederike E. L. Otto, Professor David Wallom.
* [[BOINC]]
* [[Climate model]]
* [[Climate sensitivity]]
* [[Global circulation model]]
* [[Extreme weather attribution]]


Based at the [https://www.ox.ac.uk/ '''''University of Oxford'''''] in the [https://www.eci.ox.ac.uk/ '''''Environmental Change Institute'''''], the '''''[https://www.oerc.ox.ac.uk/ Oxford e-Research Centre]''''' and '''''A[https://www2.physics.ox.ac.uk/research/atmospheric-oceanic-and-planetary-physics tmospheric, Oceanic and Planetary Physics]'''''
== External links ==
* https://www.cpdn.org
* https://climateprediction.net
* https://www.ox.ac.uk
* https://www.metoffice.gov.uk
* https://boinc.berkeley.edu


== Scientific publications ==
== References ==
[https://climateprediction.net/publications/ '''''climateprediction.net/publications/''''']
<references/>

Revision as of 21:46, 18 May 2026

[[File:{{#setmainimage:Clim.jpg}}|alt=climateprediction.net logo|center|frameless]]











climateprediction.net
climateprediction.net BOINC climate simulation screensaver
Project
StatusActive
Development
DeveloperUniversity of Oxford, UK Met Office, Open University, University of Reading
Initial release2003
Software
Operating systemCross-platform (Windows, Linux, macOS)
Metadata
Websitehttps://www.cpdn.org
LicenseResearch software (climate model dependent)
BOINC manager, running Rosetta@home and ClimatePrediction.net

climateprediction.net (CPDN) is a volunteer distributed computing project operating on the BOINC infrastructure, designed to improve understanding of climate change by running large ensembles of global climate model simulations. It is jointly coordinated by the University of Oxford and partner institutions including the UK Met Office and multiple UK research centres [1].

The project is one of the largest climate modelling experiments ever conducted in terms of computational scale and ensemble size, producing statistically significant distributions of future climate states rather than single deterministic projections [2].

Global Warming Predictions

Overview

climateprediction.net applies distributed computing to climate science by running thousands of perturbed climate simulations on volunteer computers worldwide. Each simulation varies uncertain physical parameters within plausible ranges, enabling probabilistic climate prediction through ensemble statistics [3].

This approach addresses a fundamental limitation in traditional climate modelling: uncertainty quantification in long-term climate projections.

Scientific Rationale

The project is based on the recognition that climate models contain structural and parametric uncertainty. Instead of producing a single forecast, CPDN explores a probability distribution of outcomes by varying:

  • Cloud parameterizations
  • Ocean heat uptake
  • Aerosol forcing
  • Radiative transfer parameters

This ensemble-based method allows estimation of climate sensitivity ranges consistent with observed climate data [4].

History

The concept for CPDN was introduced by Myles Allen in 1999 in the Nature commentary “Do-it-yourself climate prediction” [5].

Key milestones include:

  • 1999 – Concept proposal for distributed climate modelling
  • 2002 – UK research council funding secured
  • 2003 – Project launch
  • 2004 – Migration to BOINC platform
  • 2006 – BBC Climate Change Experiment
  • 2009 – BBC experiment concluded and data archived

Scientific Projects

CPDN runs multiple research streams grouped into active and completed experiments.

Current Projects

  • DOCILE (Drives Of Change In mid-Latitude weather Events)
  • TNC (The Nature Conservancy partnership studies)
  • GOTHAM (Globally Observed Teleconnections and their role and representation in Hierarchies of Atmospheric Models)
  • AFLAME (Attributing Amazon Forest fires from Land-use Alteration and Meteorological Extremes)
  • HIASA (High Impact Atmospheric Simulation Analysis)
  • EMBARK (ensemble-based climate risk modelling initiative)
  • National Trust climate resilience modelling

These projects focus on attribution science, extreme event analysis, and climate risk quantification in regional systems [6].

Completed Projects

  • weather@home [7]
  • HadCM3 and other models ensemble experiments [8]

These completed studies provided foundational datasets for understanding climate variability, extreme weather attribution, and ensemble climate uncertainty.

Model Systems

CPDN has used multiple generations of climate models:

HadCM3-based Models

The HadCM3 coupled atmosphere-ocean general circulation model formed the basis of early CPDN experiments. It allowed long-duration simulations at relatively low computational cost.

Weather@Home System

An extension enabling regional downscaling of global climate projections, widely used in extreme weather attribution studies.

OpenIFS Models

Recent CPDN simulations use ECMWF OpenIFS configurations, enabling higher-resolution global modeling. Some configurations require multicore execution and up to tens of gigabytes of RAM per job [9].

BBC Climate Change Experiment

The BBC Climate Change Experiment (2006–2009) was a major public engagement initiative involving over 120,000 volunteers.

Participants ran simulations covering:

  • 20th century climate (1920–2000)
  • Future scenarios (2000–2080)

The experiment demonstrated the feasibility of large-scale public participation in climate modelling and contributed to early climate risk communication efforts [10].

Computational Methodology

Each CPDN work unit typically includes:

  1. Model initialization and spin-up
  2. Control simulation under baseline parameters
  3. Perturbed simulation with modified physical constants

Outputs are aggregated across thousands of independent runs to derive probabilistic climate response functions [4].

BOINC client running CPDN work units
Climate Zones, Scenario B1 2001 - 2025

Scientific Output

CPDN data has contributed to numerous peer-reviewed studies in climate science, including:

  • Stainforth et al. (2005) — climate sensitivity uncertainty distributions
  • Murphy et al. (2004) — probabilistic climate modelling framework
  • Sexton et al. (2012) — regional climate uncertainty analysis
  • Philip et al. (2019) — extreme weather attribution studies

The BOINC scientific publication archive also lists CPDN-derived contributions across multiple climate research domains [11].

Project Team and Sponsors

The project is led by:

  • Prof Myles R. Allen
  • Andy Bowery
  • Dr Neven S. Fuckar
  • Dr Sihan Li
  • Dr Friederike E. L. Otto
  • Prof David Wallom

CPDN is based at the University of Oxford, primarily within:

  • Environmental Change Institute
  • Oxford e-Research Centre
  • Atmospheric, Oceanic and Planetary Physics group

[12]

Impact

climateprediction.net has had significant scientific and societal impact:

  • One of the largest ensemble climate datasets ever produced
  • Early demonstration of probabilistic climate prediction
  • Major contribution to extreme weather attribution science
  • Public engagement through BBC collaboration
  • Influence on IPCC uncertainty framing methodologies

Scientific Publications

A full list of CPDN-related publications is maintained at: https://climateprediction.net/publications/ [13]

Key peer-reviewed works include publications in Nature, Journal of Climate, and Environmental Research Letters.

See also

External links

References

  1. ↑ https://www.cpdn.org/about.php
  2. ↑ https://en.wikipedia.org/wiki/Climateprediction.net
  3. ↑ https://www.ox.ac.uk/news/2004-09-16-climatepredictionnet-boinc
  4. ↑ 4.0 4.1 Stainforth et al., Nature (2005)
  5. ↑ Allen, M. (1999), Nature
  6. ↑ https://climateprediction.net/projects/
  7. ↑ https://climateprediction.net/projects/completed-project/completed-weatherhome-projects/
  8. ↑ https://climateprediction.net/projects/completed-project/hadcm3-and-other-models/
  9. ↑ https://www.reddit.com/r/BOINC/comments/1mhrgkw
  10. ↑ https://www.bbc.co.uk/sn/climateexperiment
  11. ↑ https://boinc.berkeley.edu/pubs.php
  12. ↑ https://climateprediction.net/about/people/
  13. ↑ https://climateprediction.net/publications/
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