Geoscientific Model Development (Mar 2018)
Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)
- N. Butchart,
- J. A. Anstey,
- K. Hamilton,
- S. Osprey,
- C. McLandress,
- C. McLandress,
- A. C. Bushell,
- Y. Kawatani,
- Y.-H. Kim,
- F. Lott,
- J. Scinocca,
- T. N. Stockdale,
- M. Andrews,
- O. Bellprat,
- P. Braesicke,
- C. Cagnazzo,
- C.-C. Chen,
- H.-Y. Chun,
- M. Dobrynin,
- R. R. Garcia,
- J. Garcia-Serrano,
- L. J. Gray,
- L. Holt,
- T. Kerzenmacher,
- H. Naoe,
- H. Pohlmann,
- J. H. Richter,
- A. A. Scaife,
- A. A. Scaife,
- V. Schenzinger,
- F. Serva,
- F. Serva,
- S. Versick,
- S. Watanabe,
- K. Yoshida,
- S. Yukimoto
Affiliations
- N. Butchart
- Met Office Hadley Centre (MOHC), Exeter, UK
- J. A. Anstey
- Canadian Centre for Climate Modelling and Analysis (CCCma), Victoria, Canada
- K. Hamilton
- International Pacific Research Center (IPRC), Honolulu, USA
- S. Osprey
- National Centre for Atmospheric Science (NCAS), University of Oxford, Oxford, UK
- C. McLandress
- Canadian Centre for Climate Modelling and Analysis (CCCma), Victoria, Canada
- C. McLandress
- University of Toronto, Toronto, Canada
- A. C. Bushell
- Met Office, Exeter, UK
- Y. Kawatani
- Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
- Y.-H. Kim
- Ewha Womans University, Seoul, South Korea
- F. Lott
- Laboratoire de Météorologie Dynamique (LMD), Paris, France
- J. Scinocca
- Canadian Centre for Climate Modelling and Analysis (CCCma), Victoria, Canada
- T. N. Stockdale
- European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
- M. Andrews
- Met Office Hadley Centre (MOHC), Exeter, UK
- O. Bellprat
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- P. Braesicke
- Karlsruher Institut für Technologie (KIT), Karlsruhe, Germany
- C. Cagnazzo
- Istituto di Scienze Dell'Atmosfera e del Clima (ISAC-CNR), Rome, Italy
- C.-C. Chen
- National Center for Atmospheric Research (NCAR), Boulder, USA
- H.-Y. Chun
- Yonsei University, Seoul, South Korea
- M. Dobrynin
- Universität Hamburg, Hamburg, Germany
- R. R. Garcia
- National Center for Atmospheric Research (NCAR), Boulder, USA
- J. Garcia-Serrano
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- L. J. Gray
- National Centre for Atmospheric Science (NCAS), University of Oxford, Oxford, UK
- L. Holt
- NorthWest Research Associates (NWRA), Boulder, USA
- T. Kerzenmacher
- Karlsruher Institut für Technologie (KIT), Karlsruhe, Germany
- H. Naoe
- Meteorological Research Institute (MRI), Tsukuba, Japan
- H. Pohlmann
- Max-Planck-Institut für Meteorologie (MPI), Hamburg, Germany
- J. H. Richter
- National Center for Atmospheric Research (NCAR), Boulder, USA
- A. A. Scaife
- Met Office Hadley Centre (MOHC), Exeter, UK
- A. A. Scaife
- University of Exeter, Exeter, UK
- V. Schenzinger
- Universität Wien, Vienna, Austria
- F. Serva
- Istituto di Scienze Dell'Atmosfera e del Clima (ISAC-CNR), Rome, Italy
- F. Serva
- Università degli Studi di Napoli “Parthenope”, Naples, Italy
- S. Versick
- Karlsruher Institut für Technologie (KIT), Karlsruhe, Germany
- S. Watanabe
- Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
- K. Yoshida
- Meteorological Research Institute (MRI), Tsukuba, Japan
- S. Yukimoto
- Meteorological Research Institute (MRI), Tsukuba, Japan
- DOI
- https://doi.org/10.5194/gmd-11-1009-2018
- Journal volume & issue
-
Vol. 11
pp. 1009 – 1032
Abstract
The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) aims to improve the fidelity of tropical stratospheric variability in general circulation and Earth system models by conducting coordinated numerical experiments and analysis. In the equatorial stratosphere, the QBO is the most conspicuous mode of variability. Five coordinated experiments have therefore been designed to (i) evaluate and compare the verisimilitude of modelled QBOs under present-day conditions, (ii) identify robustness (or alternatively the spread and uncertainty) in the simulated QBO response to commonly imposed changes in model climate forcings (e.g. a doubling of CO2 amounts), and (iii) examine model dependence of QBO predictability. This paper documents these experiments and the recommended output diagnostics. The rationale behind the experimental design and choice of diagnostics is presented. To facilitate scientific interpretation of the results in other planned QBOi studies, consistent descriptions of the models performing each experiment set are given, with those aspects particularly relevant for simulating the QBO tabulated for easy comparison.