The Met Office climate model Had SM 3

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The Hadley Centre for Climate Change § Branch of the Met Office - UK national meteorological service § Opened by Prime Minister Mrs Thatcher in 1990 § Funded by DEFRA and MOD to research climate change § Moved from Bracknell to Exeter in 2004 § 120 staff © Crown copyright 2007 Page 2

climateprediction. net § University of Oxford, Rutherford Appleton Laboratory, The Open University § Funded by NERC, DTI, EU and BBC § Goals § Improve public understanding of the nature of uncertainty in climate prediction. § Harness the power of idle home and business PCs to help forecast the climate of the 21 st century. © Crown copyright 2007 Page 3

The Unified Model - origins § By the end of the 1980 s the Met Office had developed separate numerical prediction models to sustain climate research and operational forecast capabilities. § Each model had its own control, file and output structure, as well as separate scientific formulations, with separate teams responsible for development. § UM reduces the effort required to implement models on new hardware. § CDC Cyber 205, Cray YMP-8, C 90, T 3 E, NEC SX 6, SX 8 © Crown copyright 2007 Page 4

Unified Model - today § Met Office using NEC SX 6 and SX 8 § MPI introduced at 4. 1 (T 3 E) § Ported Unified Model (PUM). Cray, IBM, Clusters, even single CPU § Current release UM 6. 3. Had. GEM 1 § UM 4. 7 Had. CM 3 etc. widely used, esp. ensembles § C for I/O. Tcl/Tk for UI © Crown copyright 2007 Page 5

Development environment § Linux workstations (32 bit) § Linux front-end and fileservers. (64 bit Intel) § NEC SX 6/SX 8. Super UX. Vector processors § Code management with FCM (Open Source) – uses Subversion and lots of Perl § Automated change from fixed to free format § Last release ~750 k lines Fortran § ~250 k lines changed! © Crown copyright 2007 Page 7

Climate model development Had. GEM 2 N 144 HI-GEM Reading CGAM Had. GEM 1 N 96 L 50 atmosphere, ocean, sulphur Running on NEC Had. CEM atmosphere, ocean Had. CM 3 atmosphere, ocean, sulphur © Crown copyright 2007 Page 9

CPDN volunteer computing challenges. . . § Model is about 1 million lines of Fortran (40 MB src) § Proprietary, licenced by UK Met. Office § distribute executable/binary form only § Resolution used: 2. 75 x 3. 75 degrees (73 lat x 96 long) § Typically run on a supercomputer (i. e. Cray T 3 E) or 8 node Linux cluster (minimum) § Ported to a single-processor, 32 -bit Linux box § Original: Windows only, now also Mac OS X, Linux § Intel Fortran Win & Linux, IBM XLF for Mac, soon Intel Mac § Many validation runs made on single-proc/32 -bit to compare to supercomputer 64 -bit § Current coupled model takes ~6 months to run on a P 4/2 GHz PC 24/7! Page 10

Volunteer Computing § A specialized form of “distributed computing” § Uses BOINC - Berkeley Open Infrastructure for Network Computing § Was around before '99 but took off with SETI@home § SETI@home peak cap with 500 K users about 1 PF = 1000 TF § for comparison Earth Sim in Kyoto = 35 TF max § climateprediction. net (CPDN) running at about 60 TF (60 K concurrent users each 1 GF machine average, i. e. PIV 2 GHz conservatively rated) § Offers high CPU power at low cost Page 11

The experiments n Expt 1: Unified Model with simple, thermodynamic ocean. (Had. SM 3) n Aim: To identify parameter combinations which have little effect on the mean climate but a large effect on climate sensitivity. Double CO 2 15 yr, 2 x CO 2 Calibration 15 yr spin-up n Derived fluxes 15 yr, base case CO 2 Diagnostics from final 8 yrs. Control Expt 2: Fully coupled model. (Had. CM 3) n n Distribute pre-packaged simulations of 1950 -2050. Downweight or eliminate runs which compare badly with observations. Re-distribute the surviving versions to simulate 2000 -2050. Estimate uncertainty from collated results and map the response manifold. © Crown copyright 2007 Page 12

climateprediction. net users worldwide >300, 000 users total : ~60, 000 active (currently running) >19 million model-years simulated (as of January 2007) ~200, 000 completed simulations The world's largest climate modelling supercomputer! (NB: a black dot is one or more computers running climateprediction. net) Page 13

climateprediction. net Screensavers Page 14

Example BBC experiment run Page 15

Climate sensitivities from climateprediction. net The frequency distribution of simulated climate sensitivity using all (2, 578) model versions (black), all model versions except those with perturbations to the cloud-to -rain conversion threshold (red), and all model versions except those with perturbations to the entrainment coefficient (blue). Sensitivity is the equilibrium response of the global mean temperature of doubling atmospheric levels of carbon dioxide. Stainforth et al, Nature, 27 Jan ‘ 05

Frequency Distribution of Simulations From Stainforth et al, Nature, 27 Jan ‘ 05 Page 17

climateprediction. net recent publications § § § § § D. A. Stainforth, T. Aina, C. Christensen, M. Collins, N. Faull, D. J. Frame, J. A. Kettleborough, S. Knight, A. Martin, J. M. Murphy, C. Piani, D. Sexton, L. A. Smith, R. A. Spicer, A. J. Thorpe & M. R. Allen, Uncertainty in predictions of the climate response to rising levels of greenhouse gases, Nature, 433, pp. 403 -406, 27/01/2005 D. J. Frame, B. Booth, J. A. Kettleborough, D. A. Stainforth, J. M. Gregory, M. Collins, and M. R. Allen, Constraining climate forecasts: The role of prior assumptions, Geophysical Review Letters, 32, L 09702, May 2005. C. Piani, D. J. Frame, D. A. Stainforth, and M. R. Allen, Constraints on climate change from a multi-thousand member ensemble of simulations, Geophysical Review Letters, 32, L 23825, December 2005. G. C. Hegerl, T. J. Crowley, W. T. Hyde and D. J. Frame, Climate sensitivity constrained by temperature reconstructions over the past seven centuries, Nature, 440, p 1029 -1032, April 2006. Allen, M. , N. Andronova, B. Booth, S. Dessai, D. Frame, C. Forest, J. Gregory, G. Hegerl, R. Knutti, C. Piani, D. Sexton, D. Stainforth, 2006, Observational constraints on climate sensitivity, in Avoiding Dangerous Climate Change, (Eds. ) J. S. Schellnhuber, W. Cramer, N. Nakicenovic, T. M. L. Wigley, G. Yohe. , Cambridge Univ. Press. PDF of complete book (17 MB), see chapter 29 Knutti, R. , G. A. Meehl, M. R. Allen and D. A. Stainforth, Constraining climate sensitivity from the seasonal cycle in surface temperature, Journal of Climate, in press Designing a Runtime System for Volunteer Computing, David P. Anderson, Carl Christensen and Bruce Allen, To appear in Supercomputing ’ 06 (the International Conference for High Performance Computing, Networking, Storage and Analysis), Tampa, Florida, USA, November 2006. N. Massey, T. Aina, M. Allen, C. Christensen, D. Frame, D. Goodman, J. Kettleborough, A. Martin, S. Pascoe and D. Stainforth, Data access and analysis with distributed federated data servers in climateprediction. net , Advances in Geosciences, 8, p 49 -56, 2006. Carl Christensen, Tolu Aina, David Stainforth, The Challenge of Volunteer Computing With Lengthy Climate Modelling Simulations, Proceedings of the 1 st IEEE Conference on e-Science and Grid Computing, Melbourne, Australia, 5 -8 Dec 2005 David Stainforth, Andrew Martin, Andrew Simpson, Carl Christensen, Jamie Kettleborough, Tolu Aina, and Myles Allen, Security Principles for Public-Resource Modeling Research, Proceedings of the 13 th IEEE Conference on Enabling Grid Technologies (ENTGRID), Modena, Italy, June 2004 Page 18