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MACA

GC11B-1004 . A Comprehensive Framework for Quantitative Evaluation of Downscaled Climate Predictions and Projections Joseph J. Barsugli 1 , Galina Guentchev 2 , NCPP Core and Climate Science Advisory Teams

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MACA

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  1. GC11B-1004. A Comprehensive Framework for Quantitative Evaluation of Downscaled Climate Predictions and Projections Joseph J. Barsugli1, Galina Guentchev2, NCPP Core and Climate Science Advisory Teams 1 - NOAA/CIRES University of Colorado, Boulder, CO; 2 – NCAR RAL CSAP, Boulder, CO Quantitative Evaluation Framework Protocols and Metrics Quantitative Evaluation is only one part of a larger set of comprehensive information to provide guidance on better informed use of climate data What’s best for my application? AQR Delta BCSD BCCA MACA SDSM NARCCAP WorldClim USGS RegClim SNAP Custom The Practitioner’s Dilemma* • Comprehensive Quantitative Evaluation of Local and Regional Climate Projections is Needed • The climate adaptation practitioner in North America is increasingly faced with a bewildering choice of downscaling methods and datasets available from many data portals • Systematic comparisons of downscaling methods are rare • Existing studies do not allow for easy comparison of advantages and disadvantages of downscaling methods • Information is not easily accessible to practitioners • GOAL: Evaluate data in many dimensions, including historical validation, process evaluation, and non-stationarity. Concludingremarks This framework is built around existing practice of downscaling, synthesizing current best practices. The framework is intended to become an "open standard" developed and used by the community, and to inform the development of an international standard. NCPP will be developing softwarebased on the evaluation framework and will facilitate its use through provision of datasets NCPP intends to provide a common database to archive and serve the quantitative results of these evaluations. • Development of the Framework is Guided by these Principles • Systematic evaluation approach • Standardization of the evaluation procedures • Transparency of evaluation methods • Reproducibility of procedures • Flexibility and extensibility to new methods, scales and applications of interest • Relevance to applications For more information on NCPP, please scan this code or visitwww.earthsystemcog.org/projects/ncpp *BCSD – Bias Corrected and Spatially Downscaled CMIP3 dataset, BCCA – Bias Corrected Constructed Analogs dataset, MACA – Multivariate Adaptive Constructed Analogs dataset, SDSM – Statistical Downscaling Model tool, USGS RegClim dynamically downscaled dataset, NARCCAP – North American Regional Climate Change Assessment Program data, SNAP – Scenarios networks for Alaska and Arctic Planning data, AQR – Asynchronous Quantile Regression dataset, WorldClim – global climate data for ecological modeling; These are only some of the options.

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