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Uncertainty in Atmospheric Dispersion Modeling. Nuclear Utility Meteorological Data Users Group (NUMUG) Walter D. Bach, Jr., Ph.D. Science and Technology Corporation Samuel P. Williamson Federal Coordinator for Meteorological Services and Supporting Research Margaret R. McCalla
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Uncertainty in Atmospheric Dispersion Modeling Nuclear Utility Meteorological Data Users Group (NUMUG) Walter D. Bach, Jr., Ph.D. Science and Technology Corporation Samuel P. Williamson Federal Coordinator for Meteorological Services and Supporting Research Margaret R. McCalla Office of the Federal Coordinator for Meteorological Services and Supporting Research 28 June 2011 Oak Brook, IL
The Report • Purpose • User’s Needs from User’s Perspective • Model Capabilities to Meet User’s Needs • Modeling and Measurement Research Needs • R&D Strategy to Meet User’s Needs • Recommendations www.ofcm.gov/r23/r23-2004/fcm-r23.htm
A R&D Strategy to Meet User Needs Interpret Uncertainty GOALS Routinely Quantify Uncertainty CAPTURE AND USE EXISTING DATA SETS MODEL EVAL STANDARDS OBJECTIVES MEASUREMENT CAPABILITIES BRIDGE THE SCALE GAP LOCAL/ REGIONAL MEASUREMENT SITING ATD TEST BEDS COORDINATED AGENCY SUPPORT & FUNDING
Why Emphasize Uncertainty? • Critical to making intelligent life/death decisions • Ubiquitous (permeates all aspects of life) • Poorly characterized in modeling efforts • Measure of the robustness of the modeling/observing system. • Reducing uncertainty requires knowledge of current uncertainty • Believability of our products
ATD Modeling Uncertainty The total model uncertainty is measured by the variance in the predictedand the observedquantity over a large number of events that have similar properties (an ensemble).
Total Model Variance Error variance of input data Let Co = Coa +dCo and Cp = Cpa +dCp Square of model bias Total model variance Stochastic uncertainty Error variance of observations
Contributions to Model Uncertainty Internal: Numerical approximations, modeling errors, and treatment of dynamical processes External: Data errors in execution and evaluation, model parameterizations, and initial & boundary conditions Stochastic: Natural variability of the atmosphere (turbulence)
What to Do? • Capture and Use Existing Data Sets • Basis of present ATD knowledge • Accessible • Establish Test Beds • All-weather conditions (24/7 operation) • Daily test and evaluations • Feedback among operational modeling and users • Develop Measurement Technologies • Meteorological variables – T, RH, winds, turbulence • Tracer materials – cheap, harmless, remote, in situ • Conduct controlled experiments • Physical modeling – flow channels, wind tunnels, convection tanks • Computational modeling – DNS, CFD, LES
Recommendations Use existing facilities to begin routinely quantifying model uncertainty at NUMUG sites. Establish a local benchmark for model uncertainty Expand observational network and capabilities Initiate and nurture interaction between modelers and model product users to incorporate and understand uncertainty Evaluate improvements to model and observation networks using uncertainty benchmarks.