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climateprediction.net (CPDN) is a research project that uses Internet-connected computers to do research in climate science. You can participate by downloading and running a free program on your computer.
CPDN is based at the University of Oxford.
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Release of a new multicore configuration of the OpenIFS application
A new multicore configuration of the OpenIFS application, known as Tl319, is being released by CPDN. This is the first time CPDN has deployed a multicore app and we believe the first time BOINC has been used for large memory applications.
As this configuration has a peak total memory requirement of 26Gb, we have introduced a new option under the 'CPDN Project Preferences' found in 'Your account' which must be selected in order to receive workunits using this configuration. Please ensure your machine has enough resources assigned to the boinc client even if this option is selected. CPDN will soon release batches for several projects using this configuration. For further information and discussion on this new app and batches, please use the forums.
22 Jul 2025, 10:29:24 UTC
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Statement on the recent disruption to the climateprediction.net project
We profoundly apologise for the disruption of the last few days to the project. We apologise for any lost workunits you have had during this period. Any workunits that were aborted during this period you will receive full credit for. This period represents an attempted rebranding of the project. Any future change on this scale including to the name of the project to be more representative of the research supported will be completed following significant testing to reduce impact. For the foreseeable future we will continue to use the name 'climateprediction.net'. Please use the project forum if you have any questions.
18 Sep 2024, 15:51:08 UTC
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New batch going out to volunteer's machines: STORMS, investigating how low-pressure systems may change in the future
Project: Quantifying controls on the intensity, variability and impacts of extreme European STORMS
by Clément Bouvier and Victoria Sinclair (University of Helsinki)
Throughout the year, low-pressure systems regularly move across Europe, usually from west to east, bringing cloud, rain and windy weather. Sometimes these weather systems can become very intense, and the winds and rain associated with them can cause damage to buildings and infrastructure, flooding, and can disrupt electricity supply and travel. Although the short-term weather forecasts of these storms are now quite accurate, it still remains uncertain how these storms, and their impacts, are likely to change in the future as our climate changes. Some of this uncertainty is because our understanding of what controls the strength and impacts of these storms is incomplete.
The aim of this project is to understand what controls the strength and structure of these low-pressure systems. We will quantify how the atmospheric state that the low-pressure systems develop in affects the strength and structure of these low-pressure systems. This atmospheric state can be described by various parameters, for example, the mean temperature, moisture content, and upper-level wind speeds (i.e. the strength and width of the jet stream). Since there are lots of different parameters we want to study (not just the ones described above), we want to do lots of experiments in a high controlled manner. Therefore, we will run a large ensemble of simulations of idealised low-pressure systems using the numerical weather prediction model OpenIFS. Although the simulations are idealised, the weather systems that develop look very like real weather systems that we observed in reality. Each ensemble member differs in its initial atmospheric state, and we choose these initial states to cover everything from the current climate to past pre-industrial climates to the most extreme future climate projections. This is exciting because although idealised simulations of low-pressure systems have been performed before, this is the first time that such an extensive exploration of the parameter space will be conducted.
Once we have the results from the large ensemble, we will calculate different measures of the strength of the storms and then use machine learning techniques to see how these relate to the initial states. Our results will hopefully increase in confidence in how these storms and their impacts will change in the future.
Technical information:
Run time: between 8 and 9 hours for 1 workunit (1 core, Xeon Gold 6230)
Number of files: 480 files
Maximum size of individual files: 1.3MB for 2D fields output files, 13.3MB for spectral output files, 7.1MB for 3D fields output files
Total disk load: 2.0GB
12 Jun 2024, 19:58:43 UTC
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BOINC Needs Votes at a UN Upcoming Forum
BOINC is a finalist for an notable award, and needs your vote (*by Sunday)
The World Summit on the Information Society (WSIS) (https://www.itu.int/net4/wsis/forum/2024) is a United Nations-sponsored initiative aimed at harnessing the potential of information and communication technologies to build inclusive and equitable information societies worldwide. BOINC has been nominated for a prize at the 2024 forum (https://www.itu.int/net4/wsis/stocktaking/Prizes/2024), and has passed initial hurdles; the next and last step ("Phase 3") requires public votes. The award would be a very nice boost and validation for BOINC and all our projects; if we can get our communities to vote, we should have a decent shot at this point...
Voting is pretty simple, takes just a few minutes; instructions are here: https://docs.google.com/document/d/1x9Xi3tq7Y9dlDD0Xb0Ul0yYCXct5pDqIqssqARxvrXg/edit.
(*The deadline for votes is Thursday April 04 (23:00 UTC+02:00))
26 Mar 2024, 20:30:23 UTC
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New study going out to volunteer's machines
Indian Ocean experiment
This experiment aims to evaluate the importance of the Indian Ocean Dipole (IOD) event of the winter 2019/2020 on the strong and well predicted North Atlantic Oscillation (NAO) of the same winter. The NAO is of large importance to European winter weather as it governs the winds over the North Atlantic which are related to the mild and wet winters of northern Europe. It has been shown that the NAO is in some years influenced by anomalous tropical ocean conditions (like El Nino). We aim to show that the strong positive IOD of 2019/2020 had an influence on the NAO and resulting warm conditions of this winter. We use the large ensemble of the OpenIFS@Home to identify the connections between the tropical Indian Ocean and the North Atlantic region.
Technical information
CPDN app-name: oifs_43r3
Run time: ~8 hrs/task on a modern CPU
Max memory: ~7Gb
Total number of files: 783 files
Model output: 8.5Mb per output step (uncompressed)
Total size of uploaded files: 2.6GB
Checkpoint filesize: ~800Mb (these are periodically created & deleted in the slot dir and not uploaded)
(The total size of the upload is one member zipped.)
20 Feb 2023, 16:14:10 UTC
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