Hello, A new project on the LCRC cluster has been requested. Please forward the information on to the LCRC Allocation sub-committee. Applicant's name: Robert Jacob Applicant's institution: ANL Applicant's division: MCS Project Name: Climate_Emulator Project title: Building a climate emulator for use in energy policy analysis Associated funding: NSF Other Systems: pending application with NCAR Science: State-of-the-art general circulation models (GCMs) provide the best estimates of future climate change. While they are valuable tools for assessing impacts of climate change for a given scenario of future greenhouse gas emissions, they cannot be used in iterative economic models since a single multi-century simulation can take weeks to months to run and the iterative models require hundreds of thousands of iterations. For this reason, we aim to develop a statistical emulator that will accurately and efficiently reproduce GCM forecasts of regional climate change for an arbitrary trajectory of CO2 concentrations by using a library of pre-computed GCM output. Library based statistical emulation has not been possible to this date because there is no consistent and comprehensive library of climate model runs corresponding to a range of scenarios of future CO2 concentrations. Computing time on Fusion will enable us to build this unique resource by perform ing a series of simulations using the Community Climate System Model (CCSM3). Since library-based statistical emulation is currently not possible, the most common approach to emulating regional climate uses linear pattern scaling, in which changes in regional temperature and precipitation are assumed to be linearly proportional to the change in global mean temperature (GMT). That is, regional climate is effectively assumed to depend solely on GMT, and not on the rate or duration of warming. Our preliminary analysis of CCSM3 output from the Climate Model Intercomparison Project (CMIP3) archive shows that this assumption is not valid for temperature projections over time scales of multiple centuries and breaks down for projections of precipitation even over decadal time scales. The CMIP3 archive, however, is not sufficient for full statistical emulation, since it is both restricted in number of runs and inconsistent in its treatment of regional climate forcing. The carefully designed library we propose here will be used to develop and test a number of alternative approaches for emulating climate model responses, including (i) nearest neighbor interpolation, (ii) a variant of pattern scaling that accounts for the rate of warming, and (iii) principal component analysis (PCA). The intended outcome of this research is a new climate emulator that will aid in the evaluation of energy policies for greenhouse gas mitigation. We anticipate that there will be a wide interest in a user-friendly, computationally tractable emulation tool from the policy, economics, and climate communities. The library itself will also be made public for further use by the community Project description: Building a new climate library is a prerequisite for developing and testing climate emulation techniques due to the limitations of existing climate libraries. We are applying here for computing time to build a library of CCSM3 runs with a large number of scenarios, multiple realizations of each scenario, and multi-century simulations. This would represent a substantial advance over the library of CCSM3 runs in the CMIP3 archive, which contains only three scenarios for future CO2 concentration growth, does not study CO2 growth beyond 2100, and considers different regional sulphate aerosol emissions for each scenario, complicating any understanding of regional climate patterns expected in a warming world. By addressing these limitations, the consistent and comprehensive climate library we propose here will make possible new emulation methods. CCSM's atmosphere component is the Community Atmosphere Model. CAM currently supports three different numerical cores for solving the basic equations: a spectral transform method, a Semi-Lagrangian scheme, and a finite-volume scheme. The ocean component is a finite-difference model called the Parallel Ocean Program and was developed at Los Alamos. CCSM's sea ice and land surface models are each among the most complex and complete models in existence. CCSM requires Fortran90 and C compilers and the MPI and NetCDF libraries to run. In order to make the project computationally tractable we will use the low-resolution (T31) version of CCSM3. Scenarios of future CO2 concentration will follow a tree design. We will consider two scenarios between 2010 and 2050, branch to six scenarios between 2050 and 2100, and branch again to 12 scenarios between 2100 and 2200. Finally, we will consider six scenarios between 2200 and 2400, for the study of very long-term effects. The tree design allows significant savings to be made in computing resources as multiple scenarios can use the same restart files, and allows examination of hysteresis (i.e., the importance of CO2 history) for scenarios with overlapping branches. Multiple realizations of each scenario (obtained by running the model with different initial conditions) are required to allow robust separation of true signals from internal variability in the climate system. We will take 10 realizations of each scenario between 2010 and 2200 and five realizations for scenarios between 2200 and 2400, when we expect long-term trends to be more pronounced. Finally, we will conduct a detailed exploration on the importance of natural variability by considering a much larger number of realizations (30) for a single 200 year scenario. This yields a total of (40*3*10) + (50*6*10) + (100*12*10) + (200*6*5) + (200*1*30) = 28,200 model years. We have sufficient disk space to store the output offsite. Project URL: Requested allocation: 830000 Justification: Preliminary testing of CCSM3 at T31 on Fusion using 4 nodes (32 processors) required 55 minutes for a simulation of one model year. Therefore, we are requesting 28,200*32*(55/60) ~= 830,000 CPU hours for the full suite of simulations. Several simulations can be run at the same time to scale the project out to the full machine if available. CCSM3 was the recipient of a great deal of tuning and evaluation by combined DOE and NCAR computational scientists so we do not expect further improvements in the per node performance. The requester has used 0 hours of their initial startup project. In addition to approving an initial amount, please specify a Category and Subcategory for this project. For a list of the current selection of approved categories, please see: https://wiki.lcrc.anl.gov/wiki/Processes/Categories Once the Allocation committee has approved the project, please go to the Project Management page to create it: https://accounts.lcrc.anl.gov/projects.php Thank You, The LCRC Accounts System