Simulation Testbed for Trend Detection and Attribution Methods

The field of detection and attribution has been growing for a couple of decades and has recently seen a increase in the quantity and sophistication of methods. The difficulty of comparing these methods has motivated the design of a simulation testbed. Such a testbed is difficult to develop as it involves generating spatiotemporal fields with complex and flexible covariance structures that do not inherently favor any of the methods to be tested. The following testbed has the ability to generate a wide class of isotropic and non-isotropic correlation matrices to simulate the climate variability. The forcing response fields are tunable, spatially correlated fields with adjustable signal-to-noise ratios. The flexibility of the simulation method allows us to replicate a variety of climate model-like output in a controlled setting. In addition to the methods used in the testbed, we present synthetic data for simulated climate scenarios and a user manual for the Matlab software package.

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Author Lenssen, Nathan J.L.
Hannart, Alexis
Hammerling, Dorit
Publisher UCAR/NCAR - Library
Publication Date 2018-12-17T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:06:54.345368
Metadata Record Identifier edu.ucar.opensky::technotes:573
Metadata Language eng; USA
Suggested Citation Lenssen, Nathan J.L., Hannart, Alexis, Hammerling, Dorit. (2018). Simulation Testbed for Trend Detection and Attribution Methods. UCAR/NCAR - Library. Accessed 30 September 2023.

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