Information AboutClimateprediction.net |
| CATEGORIES ABOUT CLIMATEPREDICTION.NET | |
| berkeley open infrastructure for network computing | |
| numerical climate and weather models | |
| meteorology and climate education | |
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Climateprediction.net, or CPDN, is a Distributed Computing project to investigate and reduce uncertainties in Climate Modelling . It aims to do this by running hundreds of thousands of different models (a large Ensemble ) using the donated idle time of ordinary Personal Computers , thereby leading to a better understanding of how models are affected by small changes in the many Parameters known to influence the global climate. Anyone with a reasonable computer can join and help this project by running their own model and the project encourages as many people as possible to do so. It is run primarily by Oxford University in England and has harnessed the most computing power and generated more data than any other climate modelling project. AIMS The aim of the Climate''prediction''.net project is to investigate the uncertainties in various parametrizations that have to be made in state-of-the-art climate models (see " Modelling The Climate "). The model is run thousands of times with slight perturbations to various physics parameters (a 'large Ensemble ') and the project examines how the model output changes. These parameters are not known exactly, and the variations are within what is subjectively considered to be a plausible range. This will allow the project to improve understanding of how sensitive the models are to small changes and also to things like changes in Carbon Dioxide and Sulphur Cycle . In the past, estimates of climate change have had to be made using one or, at best, a very small ensemble (tens rather than thousands!) of model runs. By using participants' computers, the project will be able to improve understanding of, and confidence in, climate change predictions more than would ever be possible using the supercomputers currently available to scientists. The Climate''prediction''.net experiment should help to "improve methods to quantify uncertainties of climate projections and scenarios, including long-term ensemble simulations using complex models", identified by the Intergovernmental Panel On Climate Change (IPCC) in 2001 as a high priority. Hopefully, the experiment will give decision makers a better scientific basis for addressing one of the biggest potential global problems of the 21st century. As shown in the graph above, the various models have a fairly wide distribution of results over time. For each curve, on the far right, there is a bar showing the final temperature range for the corresponding model version. As you can see and would expect, the further into the future the model is extended, the wider the variances between them. Roughly half of the variation depends on the future Climate Forcing scenario rather than uncertainties in the model. Any reduction in those variations whether from better scenarios or improvements in the models are wanted. Climate''prediction''.net is working on model uncertainties not the scenarios. The crux of the problem is that scientists can run models and see that x% of the models warm y degrees in response to z climate forcings, but how do we know x% is a good representation of the probability of that happening in the real world? The answer is that scientists are uncertain about this and want to improve the level of confidence that can be achieved. Some models will be good and some poor at producing past climate when given past climate forcings and initial conditions (a Hindcast ). It does make sense to trust the models that do well at recreating the past more than those that do poorly. Therefore models that do poorly will be downweighted. THE EXPERIMENTS The different models that Climate''prediction''.net has and will distribute are detailed below in time order. Therefore anyone that has joined recently is likely to be running the Sulphur Cycle Model, or, if you started after February 2006, the Transient Coupled Model .
HISTORY distributed computing project]] Myles Allen first thought about the need for large Ensembles in 1997 but was only introduced to the success of SETI@home in 1999 . The first funding proposal in April 1999 was rejected as utterly unrealistic. Following a presentation at the , thousands signed up to this supposedly imminently available program. The Dot Com bust did not help and the project realised they would have to do most of the programming themselves rather than outsourcing. It was launched September 12 , 2003 and on September 13 , 2003 the project exceeded the capacity of the Earth Simulator to become the world's largest climate modelling facility. The 2003 launch only offered a Windows "classic" client. On 26th August 2004 a BOINC client was launched which supported Windows, Linux and Mac OS X clients. "Classic" will continue to be available for a number of years in support of the Open University course. BOINC has stopped distributing these model in favour of Sulfur cycle models. A Thermohaline Circulation Slowdown Experiment was launched in May 2004 under the classic framework to co-incide with the film The Day After Tomorrow . This program can still be run but is no longer downloadable. The scientific analysis has been written up in Nick Faull 's thesis. A paper about the thesis is still to be completed. There is no further planned research with this model. A Sulfur cycle model was launched in August 2005 . These take longer to run than the original having five phases instead of three and each timestep is also more complicated and takes longer. By November 2005 completed results returned totals were 45914 classic models, 3455 thermohaline models, 85685 BOINC models and 352 sulfur cycle models. This represents over 6 million model years processed. In meaning that there is a realistic ocean for the first time. This allows the experiment to investigate changes in the climate response as the Climate Forcing s are changed rather than just an equilibrium response to a significant change like doubling the Carbon Dioxide level. Therefore the experiment has now moved on to doing a hindcast of 1920 to 2000 as well as a forecast of 2000 to 2080. This model therefore takes much longer. The BBC gave this much publicity and over 120,000 computers at least tried to run it in the first three weeks. In March 2006 , a high resolution model was released as another project the Seasonal Attribution Project In April 2006 the coupled models were found to have a data input problem. The work was useful for a different purpose than advertised. New models had to be handed out. Further information on this here . RESULTS TO DATE The first results of the experiment were published in Nature in January 2005 and show that with only slight changes to the parameters within plausible ranges, the models can show climate sensitivities ranging from less than 2 °C to more than 11 °C (see abstract or full version or Explanation ). The higher climate sensitivities have been challenged as implausible [http://news.nationalgeographic.com/news/2006/04/0419_060419_global_warming_2.html]. Explanation Climate Sensitivity is defined as the equilibrium response of global mean temperature to doubling levels of carbon dioxide. Current levels of carbon dioxide are around 380 ppm and growing at a rate of 1.8 ppm per year compared with preindustrial levels of 280 ppm. Therefore doubling is an extreme change that does not happen rapidly. The experiment is carrying out this forcing more as a way of finding out about what the model does than about saying the outcomes are realistic. Climate sensitivities of greater than 5 have produced such behaviour". Even the models with very high climate sensitivity were found to be "as realistic as other state-of-the-art climate models". The test of realism was done with a root mean square error test. This does not check on realism of seasonal changes and it is possible that more diagnostic measures may place stronger constraints on what is realistic. Better tests of realism are being worked on. It is important to the experiment and the goal of obtaining a Probability Distribution Function (pdf) of climate outcomes to get a very wide range of behavours even if only to rule out such behaviour as not realistic. Unless you start with the whole range of behaviours, you would not be able to have confidence that a pdf was reliable. Therefore it is good to see that models with climate sensitivity as high as 11 °C are included. More worrying is the lack of models with climate sensitivity of less than 2 °C. The sulfur cycle experiment is likely to extend the range downwards. Piani et al 2005 published in Geophysical Review Letters, December 2005 concludes: When an internally consistent representation of the origins of model-data discrepancy is used to calculate the probability density function of climate sensitivity, the 5th and 95th percentiles are 2.2 K and 6.8 K respectively. These results are sensitive, particularly the upper bound, to the representation of the origins of model data discrepancy. Explanation The really high sensitivities are being found to be unlikely. USE IN EDUCATION There is an Open University short course and teaching material available for schools to teach subjects relating to climate and climate modelling. There is also teaching material available for use in Key Stage 3/4 Science, A level Physics (Advanced Physics), Key Stage 3/4 Mathematics, Key Stage 3/4 Geography, 21st Century Science, Science for Public Understanding, Use of Mathematics, Primary. THE ORIGINAL MODEL The original experiment is run with HadSM3 , which is the atmosphere from the HadCM3 model but with only a "slab" ocean rather than a full dynamic ocean. This is faster (and requires less memory) than the full model, but lacks dynamical feedbacks from the ocean, which are incorporated into the full coupled-ocean-atmosphere models used to make projections of climate change out to 2100. Each downloaded model comes with a slight variation in the various model Parameters . There is an initial "calibration phase" of 15 model years in which the model calculates the "flux correction"; extra ocean-atmosphere fluxes that are needed to keep the model ocean in balance (the model ocean does not include currents; these fluxes to some extent replace the heat that would be transported by the missing currents). Then there is a "control phase" of 15 years in which the ocean temperatures are allowed to vary. The flux correction ought to keep the model stable, but Feedback s developed in some of the runs. There is a quality control check, based on the annual mean temperatures, and models which fail this check are discarded. Then there is a "double CO2 phase" in which the CO2 content is instantaneously doubled and the model run for a further 15 years, which in some cases is not quite sufficient model time to settle down to a new (warmer) equilibrium. In this phase some models which produced physically unrealistic results were again discarded.
The temperature in the doubled CO2 phase is exponentially extrapolated to work out the equilibrium temperature. Difference in temperature between this and the control phase then gives a measure of the Climate Sensitivity of that particular version of the model. VISUALISATIONS Most distributed computing projects have Screensaver s to visually indicate what they are doing but this falls short of giving the impression that the participant is shown the result. In contrast, Climateprediction.net not only uses a built-in visualisation to show the climate of the world being modelled but it is interactive to show different aspects of climate and result graphs are available on the website. In addition, there are other advanced visualisation programs that allow the user to see more of what the model is doing, as well as compare it to what it did previously and other models. Many more graphs and maps can be created. The Climateprediction.net "Advanced Visualisation" progams in use are ''CPView'' and the ''IDL Advanced Visualisation''. They will both do quite a lot of the same things. CPView was written by a participant, Martin Sykes. The Advanced Visualisation was written by Andy Heaps of the University Of Reading ( UK ), and modified to work with the BOINC version by Tesella Support Services plc. Only CPView allows you to look at unusual diagnostics (rather than the usual Temperature, Pressure, Rainfall, Snow, and Clouds). See Data Index . Up to 5 sets of data can be displayed on a map. It also has a wider range of functions like Max, Min, further memory functions, and other features. The Advanced Visualisation has functions for graphs of local areas and over 1 day 2 days and 7 days (as well as the more usual graphs of season and annual averages which both packages do). There are also Latitude - Height plots and Time - Height plots. The download size is much smaller for CPView and CPView works with Windows 98 . Running the visulaization/screensaver may slow down the processing and is not recommended to be used. SEE ALSO
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