1. Comparison of depositing and non-depositing processes for atmospheric transport modeling of radionuclides Methods Background & Aims Numerous atmospheric transport models (ATM) have been deployed for operational and research activities, each with unique strengths and weaknesses. Several intermodel comparisons have been performed but, to the best of our knowledge, there is still a requirement for a standardised framework in which to compare the performance of the ATM’s. Our group is pursuing a methodology to evaluate the relative performance of ATM’s in a number of application areas. ATM intercomparisons require the definition of a standard output format to drive numerical and graphical procedures for assessing results in a common framework. In our work, we define a common format and develop a set of Open Source graphical and numerical tools to evaluate the models, allowing for side-by- side comparisons. A case-study is presented in which HYSPLIT and FLEXPART are configured as identically as possible to produce output for 14-day backwards simulations based on hypothetical radionuclide measurements in the Azores. Passive tracers and depositing species are used in the simulations to produce outputs for initial testing of the feasibility to use our postprocessing tools for meaningful model intercomparisons. Models, sites and set-ups Results Summary The primary emphasis at this early stage has been to test and refine the processes for model intercomparison. The graphics presented above clearly demonstrate the utility of comparing models in this way. Continuing work includes incorporation of more models, and more output products including vertical cross-sections and quantitative metrics. Disclaimer: The views expressed on this poster are those of the authors and do not necessarily reflect the views of the CTBTO Preparatory Commission Models FLEXPART and HYSPLIT were used to demonstrate the application of our postprocessing tools to a 14-day backwards simulation based on a hypothetical receptor measurement at the PTP53 radionuclide site in Ponta Delgada, Azores. The two models were configured as similarly as possible for runs with passive and depositing species. The images presented in the Results section demonstrate the utility of the postprocessing system for assessing differences not only between models, but between various model configurations. The images shown below represent a snapshot of nine days into the backwards simulation. Results are grouped in various ways to highlight differences between models, and between model configurations. Additionally, each model run was timed and recorded to illustrate the comparative cost of running the simulation with different models under different configurations. The models were run on two different computing systems in order to gain greater insight on computational performance. D. Morton 1,2, M. Krista 3, J. Kusmierczyk-Michulec 3, D. Arnold 4 1 Boreal Scientific Computing LLC, Fairbanks, Alaska 2 Arctic Region Supercomputing Center, University of Alaska 3 CTBTO, International Data Centre, Vienna, Austria 4 Central Institute of Meteorology and Geodynamics of Austria Contact: Don.Morton@BorealSciComp.com Results of this initial test show FLEXPART runs approximately twenty times faster than HYSPLIT, and maintaining concentrations two to four orders of magnitude less than HYSPLIT. However, an error in model setup is believed to be the more likely cause of concentration differences. We suggest that comparing models in this way allows us to more closely examine differences in models and model setups. Overall requirements:  Display/evaluate results in a common framework  Comparison tools based on single data format  Suitable for research and operational environments Common data format requirements:  Simple format  Easy to understand and manipulate  Suitable for wide range of outputs – forward, backward, regional, global  Efficient storage Common data format implementation:  Based on the Source Receptor Sensitivity (SRS) format, used up to now primarily for storing source-receptor sensitivities from backwards simulations of FLEXPART.  A single SRS file stores a time series of a single entity from a 2D horizontal slice; for example, a single species plume at a specified model output level.  SRS format consists of a header line, followed by a sparse-data listing of time, position and values for each non-zero output point on the horizontal slice  Output with ten species on ten levels results in 100 basic SRS files, and more for depositions Overall vision:  Visualisation and evaluation tools that use SRS format as input. All tools assume this format and no modifications are necessary to incorporate new model output or data  Conversion routines from native model or data output to SRS format. Decouples the native data formats from the postprocessing tools, allowing for consistent visualisation and evaluation.  Once data is in SRS format, various SRS-specific tools can process sets of SRS files to sum levels, species, create cumulative time series, visualise, and more. -152.20 61.30 19920819 01 19920819 04 1.51E+09 28 1 1 0.05 0.05 "ERU_000001" - 172.00 51.00 801 401 61.30 -152.20 -1 1.2515556E-03 61.30 -152.15 -1 2.9597816E-05 61.25 -152.10 -1 1.5828934E-06 61.30 -152.10 -1 4.0168912E-04 61.35 -152.10 -1 5.2936131E-07 61.25 -152.05 -1 6.3315735E-06 61.30 -152.05 -1 3.7156198E-04 61.35 -152.05 -1 3.1761677E-06 61.25 -152.00 -1 5.2763112E-07 61.30 -152.00 -1 1.3160457E-04 61.35 -152.00 -1 2.6468064E-05 61.30 -151.95 -1 2.1352709E-04 61.35 -151.95 -1 4.3407628E-05 61.25 -151.90 -1 4.2210490E-06 61.30 -151.90 -1 1.8710048E-04 61.35 -151.90 -1 1.0798970E-04 61.25 -151.85 -1 6.8592045E-06 61.30 -151.85 -1 1.1363447E-04 61.30 -152.20 -2 1.6310129E-03 61.30 -152.15 -2 5.6552968E-05 61.25 -152.10 -2 1.5828934E-06 61.30 -152.10 -2 8.5042458E-04 61.35 -152.10 -2 5.2936131E-07 61.25 -152.05 -2 1.6356565E-05 61.30 -152.05 -2 7.2357357E-04 61.35 -152.05 -2 7.9404195E-06 61.25 -152.00 -2 5.2763112E-07 61.30 -152.00 -2 2.7748083E-04 61.35 -152.00 -2 4.6054432E-05 61.25 -151.95 -2 1.5828934E-06 61.30 -151.95 -2 4.3128768E-04 61.35 -151.95 -2 1.0269609E-04 61.25 -151.90 -2 8.9697290E-06 61.30 -151.90 -2 3.6416237E-04. 58.45 -140.25 -20 2.3205586E-08 58.00 -140.20 -20 4.1932391E-08 58.05 -140.20 -20 1.4141680E-08 58.25 -140.20 -20 1.0378249E-07 58.30 -140.20 -20 2.0035761E-07 58.35 -140.20 -20 8.4692336E-08 58.40 -140.20 -20 3.0320337E-09 58.35 -140.05 -20 3.4031187E-07 58.40 -140.05 -20 6.4408187E-08 58.35 -140.00 -20 6.6404133E-08 58.40 -140.00 -20 1.2567795E-08 … Acknowledgements: John Burkhart, Norwegian Institute for Air Research (NILU), Jerome Brioude, NOAA ESRL Chemical Sciences Division, and others FLEXPART No DepoDry Depo Wet Depo Wet+Dry Depo HYSPLIT No Depo Dry Depo Wet Depo Wet+Dry Depo No Deposition Dry Deposition Wet Deposition Wet+Dry Deposition FLEXPART HYSPLIT FLEXPART No Convection Convection HYSPLIT FLEXPART Compute time (hours)pacmanalaskawxpacmanalaskawx No depo 2.12.444.637.7 No depo, w/ conv 2.22.5NA Dry depo 2.02.256.749.7 Wet depo 1.92.156.248.4 Wet+dry depo 1.51.756.549.2 Setup The two models were set up with a 1.3E+17/day FLEXPART mass emission and 5.42E+15/hour with HYSPLIT at a 37.74N / 25.70W line source from the surface to 150m AGL. Models were driven by 0.5 degree GFS forecast data (a poor-person’s analysis using Forecast Hour 06 from a series of forecasts) and were output on a 0.5 degree global domain at heights of 150 and 3500m. Significant effort is necessary to set up models as identically as possible. Particularly in backwards simulations, it is important to understand the assumptions made with regards to input/output units of measure. Wet+dry FLEXPART and HYSPLIT deposition parameters GFS 10m Winds GFS Precipitable Water HYSPLITFLEXPART * Recent correspondence with HYSPLIT developers suggests that a new release of HYSPLIT is a factor of two faster than the one we used. Additionally, HYSPLIT has been coded for parallel processing, while FLEXPART hasn’t. Time series No Depo No Convection