The effects of bias, drift, and trends in calculating anomalies for evaluating skill of seasonal-to-decadal initialized climate predictions-Reference-Cited by-同舟云学术

The effects of bias, drift, and trends in calculating anomalies for evaluating skill of seasonal-to-decadal initialized climate predictions

Published:2022-04-30 Issue:11-12 Volume:59 Page:3373-3389
ISSN:0930-7575
Container-title:Climate Dynamics
language:en
Short-container-title:Clim Dyn

Author:

Meehl Gerald A.^ORCID,Teng Haiyan,Smith Doug,Yeager Stephen,Merryfield William,Doblas-Reyes Francisco,Glanville Anne A.

Funder

U.S. Department of Energy

National Center for Atmospheric Research

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

https://link.springer.com/content/pdf/10.1007/s00382-022-06272-7.pdf

Reference29 articles.

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2. Cassou C et al (2018) Decadal climate variability and predictability: challenges and opportunities. Bull Am Meteorol Soc 99:479–490

3. CLIVAR (2011) Data and bias correction for decadal climate predictions. World Climate Research Programme (WCRP) Report, International CLIVAR Project Office, CLIVAR Publication Series no. 150

4. Doblas-Reyes FJ et al (2013) Initialized near-term regional climate change prediction. Nat Commun. https://doi.org/10.1038/ncomms2704

5. Fučkar NS, Volpi D, Guemas V, Doblas-Reyes FJ (2014) A ˇ posteriori adjustment of near-term climate predictions: accounting for the drift dependence on the initial conditions. Geophys Res Lett 41:5200–5207. https://doi.org/10.1002/2014GL060815

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