Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

Details

This publication is an old version. This notice is replaced by serval:BIB_D22C7CF509AB
Ressource 1 Under indefinite embargo.
UNIL restricted access
State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_30002312DC98
Type
Article: article from journal or magazin.
Collection
Publications
Institution
UNIL/CHUV
Title
Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems
Journal
Weather and Climate Dynamics
Author(s)
Lawrence Zachary D., Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Butler Amy H., Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Domeisen Daniela I. V., Etienne Dunn-Sigouin, Javier García-Serrano, Chaim I. Garfinkel Chaim I., Neil P. Hindley Neil P., Liwei Jia, Martin Jucker, Karpechko Alexey Y., Hera Kim, Lang Andrea L., Lee Simon H., Pu Lin, Marisol Osman, Palmeiro Froila M., Judith Perlwitz, Inna Polichtchouk, Richter Jadwiga H., Chen Schwartz, Seok-Woo Son, Irina Statnaia, Masakazu Taguchi, Nicholas L. Tyrrell, Wright Corwin J., Wu Rachel W.-Y.
ISSN
2698-4016 (electronic)
Publication state
Submitted to the publisher
Peer-reviewed
Oui
Language
english
URN
urn:nbn:ch:serval-BIB_30002312DC983
DOI
10.5194/wcd-2022-12
Publisher's website
https://doi.org/10.5194/wcd-2022-12
Create date
08/03/2022 15:13
Last modification date
30/10/2023 9:45
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