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

Details

Ressource 1Download: wcd-3-977-2022-2.pdf (7256.59 [Ko])
State: Public
Version: author
License: CC BY 4.0
Serval ID
serval:BIB_D22C7CF509AB
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., Abalos Marta, Ayarzagüena Blanca, Barriopedro David, Butler Amy H., Calvo Natalia, de la Cámara Alvaro, Charlton-Perez Andrew, Domeisen Daniela I. V., Dunn-Sigouin Etienne, García-Serrano Javier, Garfinkel Chaim I., Hindley Neil P., Jia Liwei, Jucker Martin, Karpechko Alexey Y., Kim Hera, Lang Andrea L., Lee Simon H., Lin Pu, Osman Marisol, Palmeiro Froila M., Perlwitz Judith, Polichtchouk Inna, Richter Jadwiga H., Schwartz Chen, Son Seok-Woo, Statnaia Irina, Taguchi Masakazu, Tyrrell Nicholas L., Wright Corwin J., Wu Rachel W.-Y.
ISSN
2698-4016
Publication state
Published
Issued date
19/08/2022
Peer-reviewed
Oui
Volume
3
Number
3
Pages
977-1001
Language
english
Keywords
General Earth and Planetary Sciences, General Environmental Science
URN
urn:nbn:ch:serval-BIB_D22C7CF509AB2
OAI-PMH
oai:serval.unil.ch:BIB_D22C7CF509AB
DOI
10.5194/wcd-3-977-2022
Open Access
Yes
Funding(s)
Swiss National Science Foundation / PP00P2_170523
Swiss National Science Foundation / PP00P2_198896
Create date
19/01/2023 18:38
Last modification date
20/01/2023 8:14
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