Articles | Volume 13, issue 12
Geosci. Model Dev., 13, 6131–6148, 2020
https://doi.org/10.5194/gmd-13-6131-2020
Geosci. Model Dev., 13, 6131–6148, 2020
https://doi.org/10.5194/gmd-13-6131-2020
Model description paper
03 Dec 2020
Model description paper | 03 Dec 2020

Detection of atmospheric rivers with inline uncertainty quantification: TECA-BARD v1.0.1

Travis A. O'Brien et al.

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Latest update: 28 Sep 2022
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Short summary
Researchers utilize various algorithms to identify extreme weather features in climate data, and we seek to answer this question: given a plausible weather event detector, how does uncertainty in the detector impact scientific results? We generate a suite of statistical models that emulate expert identification of weather features. We find that the connection between El Niño and atmospheric rivers – a specific extreme weather type – depends systematically on the design of the detector.