Articles | Volume 3, issue 3
https://doi.org/10.5194/wcd-3-977-2022
https://doi.org/10.5194/wcd-3-977-2022
Research article
 | 
19 Aug 2022
Research article |  | 19 Aug 2022

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

Zachary D. Lawrence, Marta Abalos, Blanca Ayarzagüena, David Barriopedro, Amy H. Butler, Natalia Calvo, Alvaro de la Cámara, Andrew Charlton-Perez, Daniela I. V. Domeisen, Etienne Dunn-Sigouin, Javier García-Serrano, Chaim I. Garfinkel, Neil P. Hindley, Liwei Jia, Martin Jucker, Alexey Y. Karpechko, Hera Kim, Andrea L. Lang, Simon H. Lee, Pu Lin, Marisol Osman, Froila M. Palmeiro, Judith Perlwitz, Inna Polichtchouk, Jadwiga H. Richter, Chen Schwartz, Seok-Woo Son, Irina Statnaia, Masakazu Taguchi, Nicholas L. Tyrrell, Corwin J. Wright, and Rachel W.-Y. Wu

Viewed

Total article views: 3,171 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,311 816 44 3,171 155 51 34
  • HTML: 2,311
  • PDF: 816
  • XML: 44
  • Total: 3,171
  • Supplement: 155
  • BibTeX: 51
  • EndNote: 34
Views and downloads (calculated since 03 Mar 2022)
Cumulative views and downloads (calculated since 03 Mar 2022)

Viewed (geographical distribution)

Total article views: 3,171 (including HTML, PDF, and XML) Thereof 2,940 with geography defined and 231 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Discussed (final revised paper)

Latest update: 01 Mar 2024
Download
Short summary
Forecast models that are used to predict weather often struggle to represent the Earth’s stratosphere. This may impact their ability to predict surface weather weeks in advance, on subseasonal-to-seasonal (S2S) timescales. We use data from many S2S forecast systems to characterize and compare the stratospheric biases present in such forecast models. These models have many similar stratospheric biases, but they tend to be worse in systems with low model tops located within the stratosphere.