Abstract
This paper evaluates the predictability and skill of the models from the North American Multi-Model Ensemble project (NMME) in South America on seasonal timescales using analysis of variance (ANOVA). The results show that the temperature variance is dominated by the multi-model ensemble signal in the austral autumn and summer and by the inter-model biases in the austral spring and winter. The temperature predictability is higher at low latitudes, although moderate values are found in extratropical latitudes in the austral spring and summer. The predictability of precipitation is lower than that of temperature because noise dominates the variance. The highest levels of precipitation predictability are reached in tropical latitudes with large inter-seasonal variations. Southeastern South America and Patagonia present the highest predictability at midlatitudes. The NMME skill of temperature is better than that of precipitation, and it is better at low latitudes for both variables. At extratropical latitudes, the skill is moderate for temperature and low for precipitation, although precipitation reaches a local maximum in southeastern South America.
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Data availability
Raw data can be found at http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/. Data supporting the findings of this article is available upon request.
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Acknowledgements
We thank the two anonymous reviewers for their comments. We acknowledge the agencies that support the NMME-Phase II system, and we thank the climate modeling groups (Environment Canada, NASA, NCAR, NOAA/GFDL, NOAA/NCEP, and University of Miami) for producing and making available their model output. NOAA/NCEP, NOAA/CTB, and NOAA/CPO jointly provided coordinating support and led development of the NMME-Phase II system.
Funding
The research was supported by UBACyT20020170100428BA, PDE 46 2019, PICT-2018-03046, CLIMAT-AMSUD 21-CLIMAT-05 and the CLIMAX Project funded by Belmont Forum/ANR-15-JCL/-0002-01. LGA is supported by a fellowship grant from CONICET.
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LGA: data curation; formal analysis; investigation; methodology; visualization; writing—original draft; writing—review and editing. MO: conceptualization; data curation; supervision; methodology; writing—review and editing. CSV: conceptualization; funding acquisition; methodology; project administration; resources; supervision; writing—review and editing.
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All codes used in this work can be found at https://github.com/LucianoAndrian/tesis
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Andrian, L.G., Osman, M. & Vera, C.S. Climate predictability on seasonal timescales over South America from the NMME models. Clim Dyn 60, 3261–3276 (2023). https://doi.org/10.1007/s00382-022-06506-8
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DOI: https://doi.org/10.1007/s00382-022-06506-8