Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling

From Descriptive to Explanatory: Using Metrics to Identify Candidate Phenomena for Process Evaluation in NA-CORDEX and NARCCAP

Tuesday, December 12, 2017 - 11:05
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The Framework for Assesing Climate's Energy-Water-Land nexus by Targeted Simulations (FACETS) is a new program funded by the U.S. Department of Energy that aims to develop a hierarchical framework for the evaluation of different climate models and downscaling methodologies and their added value for decision-making related to climate impacts, adaptation, and mitigation. Simulations from the North American branch of CORDEX and from NARCCAP feature prominently in FACETS.

Central to the FACETS program is the concept of a hierarchical cascade of quantitative metrics of increasing complexity. Simple, standard descriptive metrics are used to identify regions of interest for the application of more complex explanatory metrics that indicate where and how the model may be simulating the weather incorrectly. Process analysis of these errors then leads to the development of phenomena-based metrics that combine the descriptive and explanatory metrics with phenomena-specific diagnostics. Finally, integrated regional metrics combine all of these metrics in a targeted manner for specific regions.

We demonstrate the evaluation process for the first part of this hierarchy of metrics. We use standard descriptive metrics to evaluate the quality of NARCCAP and NA-CORDEX simulations in 10 study locations of interest across North America. We evaluate the distributions of daily precipitation and daily minimum, maximum, and average surface air temperature and their seasonality for both raw model output and output bias-corrected using quantile mapping via Kernel Density Distribution Mapping (KDDM). We then use these evaluations to identify locations where explanatory metrics can be applied to characterize model errors and guide the choice of process analysis and development of phenomena-based metrics.

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