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Call with D. Maraun Statistical Downscaling Controlled Vocabulary

Call with D. Maraun Statistical Downscaling Controlled Vocabulary. 5 DEC 2013. Update on the Downscaling metadata project. NCPP extended the CIM schema to allow for the description of downscaling methods Added StatisticalModelComponent Added DownscalingSimulation Dynamical downscaling CV

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Call with D. Maraun Statistical Downscaling Controlled Vocabulary

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  1. Call with D. MaraunStatistical Downscaling Controlled Vocabulary 5 DEC 2013

  2. Update on the Downscaling metadata project • NCPP extended the CIM schema to allow for the description of downscaling methods • Added StatisticalModelComponent • Added DownscalingSimulation • Dynamical downscaling CV • The existing CMIP5 CVs for atmosphere and land are being re-used and added to • Work under way with the help of Seth McGinnis from NARCCAP and Shuyan Liu from University of Maryland to develop instances of dynamical downscaling • Statistical downscaling CV • Current version is ready for comments and collaborative work with the community – will be presented today

  3. CIM Concepts • StatisticalModelComponent • Describe “method as implemented” (in software!) • Training • Validation (how much should be described along with the method?) • Application – describe how it is applied (if different than during training period) • DownscalingSimulation -- for another call! • Application Specifics for a given use • downscaled from…. which GCMsor RCMs • Ensembles of DownscalingSimulations can be grouped.

  4. Elements of the statistical CV Pre-processing Input variables Post-processing Output variables Variables Key properties Statistical Model Component details

  5. Elements of the statistical CV Abstraction Input variables Pre-processing Pre-processing Input variables Post-processing Output variables Statistical Model Variables Key properties; Variables Post-processing Statistical Model Component Child components Output variables

  6. Challenges • Level of specificity when describing downscaling method (e.g. “weather typing” vs. “hierarchical clustering”) • Variable-specific attributes hard to describe in the CV (e.g. sqrt-precipitation pre-processing) • Variable-centric vs. method-centric description • “Key attribute” vs. method detail • Compound methods, e.g. Weather Typing + Regression + Analogs. (we use child components as “building blocks”) • Where to describe validation? As part of StatisticalModelComponent or as a downscalingSimulation • When is a new CIM document needed as methods evolve? • Many more……

  7. Guidelines • Favor description over classification. • Describe method as implemented. Build from examples of methods. Focus (first) on method that have been used to generate available datasets. • WWCD: What Would the Comparator Do? • Implication is to keep as much as possible at the same level in the CV Mind Map, and properties we want to compare across methods as “leaves on the same twig”. • How will this appear in the Questionnaire? Is this too much detail to ask for? Are the property names intuitive? • Be flexible. A lot of the “boundaries” between concepts are not absolute. Allow multiple choices. • When mired in complexity, use a free text box.

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