“Loading the dice: climate change and extreme weather in Ireland, Europe and the World” Professor Myles Allen, University of Oxford
Source:  Climateprediction.net
lundi 27 février 2017 12:17

Monday 27th February, 18.30-20.00  |  Room 1.07  |  Western Gateway Building  |  Western Road, UCC, Cork   |  Tickets free | Eventbrite


Professor Allen will explore the role of human influence on climate in recent extreme weather events. The talk will present findings from recent analysis of storms in Ireland and UK to show that we can now answer this question with some degree of certainty.

Myles Allen is Professor of Geosystem Science in the Environmental Change Institute, School of Geography and the Environment and Department of Physics, University of Oxford, and co-Director of the Oxford Martin Programme on Resource Stewardship. His research focuses on how human and natural influences on climate contribute to observed climate change and risks of extreme weather and in quantifying their implications for long-range climate forecasts. He has served on the Intergovernmental Panel on Climate Change 3rd, 4th and 5th Assessments, most recently on the IPCC Synthesis Report Core Writing Team in 2014.

This is a free event open to the public organized by UCC Climate CoLab at the Environmental Research Institute, University College Cork, Ireland.


New translate feature added to the website
Source:  Climateprediction.net
lundi 20 février 2017 12:35

In keeping with the international outlook of the climateprediction.net project we have now added a new translation feature to the website. This translation feature is powered by Google Translate which provides automatic, machine-based translation.

First Scientific Results of DENIS in the Biophysical Society 61st Annual Meeting
Source:  DENIS@Home
mardi 7 février 2017 13:40

Dear volunteers,
Next week, I will attend the 61st Annual Meeting of the Biophysical Society in New Orleans. During the conference I will present a modification of one of the currents of our model (the calcium current). This current was modified to solve some problems of the model. We decided to modify this current thanks to the results obtained in DENIS, so we can say that this is the first scientific result in cardiac electrophysiology obtained thanks to your collaboration. Thank you very much!

You computed the exploratory study to locate the part of the model that was causing the problem. Thanks to your collaboration we were able to find it and propose a solution.

We continue to work to make our heart cell model as realistic as possible, we hope we can continue to give you great news like this in which your effort is rewarded enriching science.

Thank you very much for being by our side and helping us in this and in future works.

Source: DENIS News
Link: First Scientific Results of DENIS in the Biophysical Society 61st Annual Meeting

CPDN in 2016 – a look back over the last year
Source:  Climateprediction.net
vendredi 3 février 2017 15:52

With the Paris agreement freshly on everyone’s mind and in the media 2016 started of as a very exciting year for climate science. On a global scale it took slightly unexpected turns but from a scientific point of view 2016 was a year to celebrate in particular for CPDN.

With respect to our knowledge and understanding of the climate system and the interaction between weather and climate we, the climate science community,  made huge progress to no small degree thanks to CPDN, the teams of academic researchers from partner groups around the world but most importantly the volunteers. Without you, the volunteers, there would be no very large ensemble simulations of possible weather and without that our ability to undertake research about rare and extreme weather events would be greatly limited.

Moving into 2017 we, the climateprediction.net and weather@home teams would like to take this oppurtunity to provide a very brief summary of activities and successes over the past 12 months to show what your continued engagement with us has led to AND of course say a big fat thank you to all of the volunteer community, without whom none of this would be possible.


CPDN is unique in providing large ensembles that enable us to simulate statistics of extremely rare events hence the main focus of our work has been on extreme weather and in particular its attribution to external climate drivers.
Whenever an extreme event happens in the world “was it climate change?” is one of the first questions being asked. With our World Weather Attribution (WWA) project we provided a scientific answer to that question, in real time, for example for the floods in Paris and Southern Germany in May  and the Arctic Heatwave just before Christmas.

And the media did register our efforts and reported on it broadly with, by and large, great scientific accuracy.

Apart from providing attribution information when it is needed most the team did a lot of work on the methodological development of extreme event attribution methods using CPDN data and published this in the peer reviewed literature (1-9).

A particular highlight of all these publications is the proof of concept paper on real-time attribution by Karsten Haustein et al.

and the first end-to-end attribution study, from the atmospheric circulation to inundated properties ever in Schaller et al.

The team did not only look at specific events however but also published a number of conceptual papers on attribution as a science, CPDN as a unique capability and climate modelling in general (10-15).
All these publications answered some important scientific questions but also highlighted other questions, that still need to be addressed and provide new challenges towards scientific evidence of the impacts of external climate drivers. The National Academy of Science in the United States commissioned an assessment of the state of the science which was published in March. For CPDN this publication was fantastic news as it concluded that the way WWA approaches the attribution of extreme events is the best way possible to make use of all available science.

Many of these scientific publications are the result of collaborations with scientists around the world in the international teams of our research projects that make up the science teams of CPDN.


EUCLEIA, a european project that ended this year, did not only explore many of the challenges and limitations of extreme event attribution but in particular fostered and strengthened a scientific community that will live on in other projects for the coming years.

With WWA, CPDN has been part of the first science team ever to provide real-time event attribution but with it’s new 2016 spin-off RRA, WWA and the EUCLEIA legacy will generate a global community and enable in particular scientists from developing countries to become active members of this community. The ground work to make this possible not only came from WWA but also from the NERC funded CPDN project ACE-Africa which ended in 2016. A main achievement of this project beyond the scientific findings is to provide the necessary climate model simulations to explore the impacts of climate change under 1.5 and 2 degrees.

New and unique model simulations have also been made available through the MaRIUS project under which CPDN created a very large ensemble of possible weather and extreme weather in Europe from the beginning of the 20th century up to the end of the 21st.

A different focus of the world has another new project largely relying on CPDN’s modelling infrastructure, LOTUS. A collaboration with the University of Edinburgh, the UK Met Office and various Chinese universities.
Under the new project GOTHAM, CPDN is not only a key partner in an international consortium to explore the drivers of global teleconnection but offer another 2016 CPDN development, a training course on how to use the CPDN infrastructure to desgin climate model experiments, to all members of the consortium but also any scientist who applies to the first CPDN summer school.

Modelling and infrastructure

How have we actually produced all this science in the past year? Through the efforts of you our volunteers and the moderating team for which we particularly thankful, projects within the program have submitted 582k workunits providing a total of 7557 CPU years of computational resource. We have had returned ~384k workunits during the year which is 20Million model years simulated! We have also been considering how we maximise the value of data that is generated during the project. To facilitate these we will be focusing on data curations, publishing and reuse ensuring that the data you, the volunteers have generated is available to all.
Alongside the scientific advances that have been enabled by CPDN we have also made a significant number of advances within the underpinning technological system upon which CPDN and W@H depend. This has included transitions in the configurations of models that we run, in particular away from the individual regional Weather@Home1 applications. These were a significant maintenance load as we developed more and more regions we wanted to work with simultaneously. This has led to the development of the single region-independent Weather@Home2 application, within which we could dynamically pick the region of interest, resolution (25 or 50km) and even the time length of individual work units depending on scientific requirements. This allows us to simplify the number of individual applications that we are running as well as engage with more and more different research questions and hence collaborations. As you can see below we have dramatically expanded the regions on which we are able to study. We understand that there are still some issues and are thereby making the full roll out onto all platforms of all models a priority.

At the beginning of the project we only deposited data within Oxford or Rutherford laboratory, expanding to both Oregon and Tasmania as further projects were funded. Within 2016 this has increased with the commissioning of further upload servers around the globe including Mexico, South Korea and India. We have strived to rationalise the upload servers moving towards a common deployment mechanism for them all. This will allow us to more rapidly deal with problems by redeploying servers on timescales relevant to allow continued uninterrupted operations in the case of infrastructure problems.


We have also been investigating how we may support different types of project who require results with a more accurate definition of when they may be able to return results or with urgent computing requirements. This has included investigations  of the use of the cloud, with significant grants from AWS to allow us to do proof of concept development on tiering resources attached to BOINC projects (16-17).


The two snapshots representing our longstanding partnerships give an idea the possibilities arising from new partnerships in Mexico, South Korea, India, Kenya and Ethiopia in 2017 and beyond.

2016 partner snapshot



During 2016, the Oregon State University team made progress on three experiments. The first attempts to improve regional climate model simulations of both the climate and vegetation of the western US.  A central part of this experiment is exploring the sensitivity of energy fluxes, water transport, and vegetation distribution to model parameters.  The second experiment investigates future forest health by looking at projections of climatic forest stressors into the mid-21st century.

Lastly, the third experiment asks this specific question:  Did anthropogenic greenhouse gases increase the probability of major bark beetle outbreaks in western North America during the first decade of the 21st century? A warmer and drier growing season can reduce the vigor of trees increasing their susceptibility to insects and in recent years bark beetles killed many white bark pine trees throughout the western US and British Columbia.

Results from prior experiments were also published this year.  These include studies that explored the role of anthropogenic greenhouse gases in the Central US drought of 2012 (8) and the 2015 “snow drought” of the US west coast states (2), as well as our first looks at the future climate of the western US as simulated by weather@home (9,18).

Weather@Home ANZ

The weather@home regional climate modelling system for Australia and New Zealand has been used for a number of different experiments in 2016. These include:

  •     Climatological simulations for the 29-year period 1985-2014 under ALL (present day greenhouse gas, aerosol and SST) forcings and NAT (natural-only) forcings to evaluate the performance of the regional model across Australia and New Zealand
  •     Simulations for composite two-year El Niño, La Niña and neutral sea surface temperatures under ALL and NAT forcings
  •     2008-09 simulations under ALL and NAT forcings to examine the conditions for the Black Saturday bushfires in south-east Australia
  •     2015 simulations under ALL and NAT forcings to examine extreme events in 2015
  •     perturbed physics simulations, to assess the role of variations in some of the model’s physical parameters on the distributions of daily rainfall and temperature extremes.

In total, more than 100,000 years of simulations have been completed and most have been analyzed.

Significant outputs during the year include publication of the paper describing the weather@home ANZ modelling system and the evaluation of its performance (10). Two papers analyzing extreme events in 2015 in Australia using the 2015 simulations were published in the 2016 Bulletin of the American Meteorological Society supplement on Explaining Extreme Events. These examined the record high temperatures in October 2015 in southeast Australia and the record low rainfall in Tasmania in October 2015 (20,21).

Mitchell Black also completed and submitted his PhD thesis in October 2016, which used all these simulations. Examiners’ reports have been received and recommend minor revisions only. Mitch was the key person involved in setting up and running the w@h ANZ experiments for the last three years and he has now moved to a postdoctoral research position in CSIRO. Andrew King at Melbourne University and Sue Rosier at NIWA in New Zealand will take greater roles in setting up and running w@h ANZ experiments in 2017.


  1. Haustein, K., Otto, F.E.L., Uhe, P., Schaller, N., Allen, M.R., Hermanson, L., Christidis, N., McLean, P. and Cullen, H. (2016) Real-time extreme weather event attribution with forecast seasonal SSTs. Environmental Research Letters, 11(6). 064006.
  2. Mote, P., Rupp, D., Li, S. Sharp, D. Otto, F., Uhe, P., Xiao, M., Lettermaier, D., Cullen, H. and Allen, M. (2016) Perspectives on the causes of exceptionally low 2015 snowpack in the western United States. Geophysical Research Letters: 10980-10988.
  3. Parker, H., Lott, F., Cornforth, R., Mitchell, D., Sparrow, S., and Wallom, D., A comparison of model ensembles for attributing 2012 West African rainfall, Environmental Research Letters, In press. 2016
  4. Schaller, N., Kay, A.L., Lamb, R., Massey, N.R., van Oldenborgh, G.J., Otto, F.E.L., Sparrow, S.N., Vautard, R., Yiou, P., Ashpole, I., Bowery, A., Crooks, S.M., Haustein, K., Huntingford, C., Ingram, W.J., Jones, R.G., Legg, T., Miller, J., Skeggs, J., Wallom, D., Weisheimer, A., Wilson, S., Stott, P.A. and Allen, M.R. (2016) Human influence on climate in the 2014 southern England winter floods and their impacts. Nature Climate Change.
  5. Sippel, S., Otto, F., Forkel, M., Allen, M., Guillod, B., Heimann, M., Reichstein, M., Seneviratne, S., Thonicke, K. and Mahecha, M. (2016) A novel bias correction methodology for climate impact simulations. Earth System Dynamics, 7(1): 71-88.
  6. Uhe, P., Otto, F.E.L., Haustein, K., van Oldenborgh, G.J., King, A.D., Wallom, D.C.H., Allen, M.R. and Cullen, H. (2016) Comparison of methods: Attributing the 2014 record European temperatures to human influences. Geophysical Research Letters.
  7. Vautard, R., Yiou, P., Otto, F., Stott, P., Christidis, N., van Oldenborgh, G.J. and Schaller, N. (2016) Attribution of human-induced dynamical and thermodynamical contributions in extreme weather events. Environmental Research Letters, 11(11). 114009.
  8. Rupp, Sihan Li, Philip W Mote, Neil Massey, Sarah N Sparrow, David CH Wallom, Influence of the ocean and greenhouse gases on severe drought likelihood in the central US in 2012, Journal of Climate, 2016
  9. Rupp, D.E., Li, S., Mote, P.W., Shell, K.M., Massey, N., Sparrow, S.N., Wallom, D.C. and Allen, M.R., 2016. Seasonal spatial patterns of projected anthropogenic warming in complex terrain: a modeling study of the western US. Climate Dynamics, pp.1-23
  10. Black, M. T., Karoly, D. J., Rosier, S. M., Dean, S. M., King, A. D., Massey, N. R., Sparrow, S. N., Bowery, A., Wallom, D., Jones, R. G., Otto, F. E. L., and Allen, M. R.: The weather@home regional climate modelling project for Australia and New Zealand, Geosci. Model Dev., 9, 3161-3176, doi:10.5194/gmd-9-3161-2016, 2016.
  11.  Guillod, B.P., Bowery, A., Haustein, K., Jones, R.G., Massey, N.R., Mitchell, D.M., Otto, F.E.L., Sparrow, S., Uhe, P., Wallom, D.C.H., Wilson, S., Allen, M.R. (2016) weather@home 2: validation of an improved global-regional climate modelling system. Geoscientific Model Development Discussions
  12. Mitchell, D., Davini, P., Harvey, B., Massey, N., Haustein, K., Woolings, T., Jones, R., Otto, F., Guillod, B., Sparrow, S., Wallom, D. and Allen, M. (2016) Assessing mid-latitude dynamics in extreme event attribution systems. Climate Dynamics.
  13. Mulholland D, Haines K, Sparrow S. N., Wallom D.C.H, Climate Model Forecast Biases assessed with a perturbed physics ensemble, 2016, “Climate Dynamics”
  14. Otto, F.E.L. (2016) Extreme events: The art of attribution. Nature Climate Change, 6: 342-343.
  15. Otto, F.E.L., van Oldenborgh, G.J., Eden, J., Stott, P.A., Karoly, D.J. and Allen, M.R. (2016) The attribution question. Nature Climate Change, 6: 813-816.
  16. Montes, D., Añel, J. A., Pena, T. F., Uhe, P., and Wallom, D. C. H.: Enabling BOINC in Infrastructure as a Service Cloud Systems, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-193, accepted, 2016.
  17. Uhe P, Otto F.E.L, Rashid, M.M. and Wallom, D C.H. Utilising Amazon Web Services to provide an on demand urgent computing facility for Climateprediction.net. IEEE eScience 2016.
  18. Rupp, D. E., S. Li. 2016. Less warming projected during heavy winter precipitation in the Cascades and Sierra Nevada. International Journal of Climatology, doi:10.1002/joc.4963.
  19. Mote, P. W., M. R. Allen, R. G. Jones, S. Li, R. Mera, D. E. Rupp, A. Salahuddin, D. Vickers. 2016a. Superensemble regional climate modeling for the western US.  Bulletin of the American Meteorological Society (97), 203-215, doi:10.1175/BAMS-D-14-00090.1.
  20. Black, M.T., and D. J. Karoly (2016) Climate change was an important driver of southern Australia’s warmest October on record [in “Explaining Extremes of 2015 from a Climate Perspective”]. Bull. Am. Met. Soc., 97, S118-S121. DOI: http://dx.doi.org/10.1175/BAMS-D-16-0124.1
  21. Karoly, D. J., M.T. Black, M.R. Grose and A. D. King (2016) The roles of climate change and El Niño in the record low rainfall in October 2015 in Tasmania, Australia [in “Explaining Extremes of 2015 from a Climate Perspective”]. Bull. Am. Met. Soc., 97, S127-S130. DOI: http://dx.doi.org/10.1175/BAMS-D-16-0139.1

Summer school – How do Global Teleconnections Impact on Climate?
Source:  Climateprediction.net
jeudi 2 février 2017 22:25

 Organized by the Potsdam Institute for Climate Impact Research (PIK), the GOTHAM Summer School (18th-22nd September 2017) will train young scientists on a unique combination of interdisciplinary scientific topics and tools relevant for understanding teleconnections and their role in causing extreme weather events. Professor Wallom and Dr Sparrow will be training attendees on data management skills along with how to use CPDN within their scientific experiments.
Teleconnections are defined by the American Meteorological Society as “a linkage between weather changes occurring in widely separated regions of the globe”. GOTHAM is a new project involving CPDN, that aims to identify the relative impact of different teleconnections (remote drivers) on regional climate and extreme weather events.
The school, this year themed on Global Teleconnections in the Earth’s Climate System – Processes, Modelling and Advanced Analysis Methods, comprises lectures as well as tutorial sessions by some of the world’s leading experts in this field.
Specific topics include:
•             Global consequences of extreme El Niños
•             Mid-latitude weather extremes and their drivers
•             Stratosphere dynamics
•             South and East Asian monsoon systems.
•             Interactions between global teleconnection patterns
•             Data management skills
•             New methods of teleconnections identification.


The Summer School is intended to host 25 young researchers working in relevant topical areas, both from GOTHAM partners and external institutes.
Application processes to be announced soon at the official website of the Summer School.

Source:  Gerasim@home
jeudi 2 février 2017 08:16

Another our article was published:

Vatutin E.I., Zaikin O.S., Zhuravlev A.D., Manzyuk M.O., Kochemazov S.E., Titov V.S. Using grid systems for enumerating combinatorial objects on example of diagonal Latin squares // CEUR Workshop proceedings. Selected Papers of the 7th International Conference Distributed Computing and Grid-technologies in Science and Education. 2017. Vol. 1787.pp. 486–490. urn:nbn:de:0074-1787-5.

Source:  Gerasim@home
dimanche 22 janvier 2017 15:18

 Запущен новый короткий эксперимент, целью которого является анализ комбинаторных характеристик диагональных латинских квадратов порядка 8.

The new short experiment was started. It is aimed to investigate some values of combinatorial characteristics for diagonal Latin squares of order 8.

ECM@ARM error, you need more swap
Source:  yoyo@home
mercredi 11 janvier 2017 00:00

Since ECM runs also on ARM I see many error on such systems. Thosesystems are mostly small single board systems as Raspberry Pi or Odroids. They have many cores but less RAM and mostly no swap. The ECM wokunits consume less RAM at the beginning but after some time require adhoc 1 or 2 GB of RAM. Boinc can handle it but not so fast as the RAM is allocated and running multiple ECM workunits in parallel makes it worse. They often allocate much RAM at the same time. tl;dr Configure more swap in your system. Consider the old rule swap size = 2 times RAM for systems up to 2 GB. Here a tutorial how to create more swap space: https://www.digitalocean.com/community/tutorials/how-to-add-swap-on-ubuntu-14-04#check-available-space-on-the-hard-drive-partition

Launch of new Application
Source:  DENIS@Home
mercredi 4 janvier 2017 19:03

Hi everyone,

As some of you have noticed, there are new WUs in the system. We are starting with a small peak of work, but the idea is to maintain a continuous flow of new WUs.

This new part of the project is related to a Database of markers of the simulations. We are populating a database with relevant values of the simulations to make to scientist easy the way to make a exploratory study of the model or avoid making all the time the same simulations.

We are working on the interface of this database and how to integrate in our website, also, we are developing a post to explain more this idea of the Database of markers.

Happy New Year!! And Happy Crunching!
Source: DENIS News
Link: Launch of new Application

ECM: native apps for ARM
Source:  yoyo@home
mercredi 4 janvier 2017 00:00

Since some days native ECM apps are available for ARM 64 and 32 bit Linux systems. No need anymore to install gmp-ecm package.