the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review of the global models used within phase 1 of the Chemistry–Climate Model Initiative (CCMI)
Olaf Morgenstern
Michaela I. Hegglin
Eugene Rozanov
Fiona M. O'Connor
N. Luke Abraham
Hideharu Akiyoshi
Alexander T. Archibald
Slimane Bekki
Neal Butchart
Martyn P. Chipperfield
Makoto Deushi
Sandip S. Dhomse
Rolando R. Garcia
Steven C. Hardiman
Larry W. Horowitz
Patrick Jöckel
Beatrice Josse
Douglas Kinnison
Meiyun Lin
Eva Mancini
Michael E. Manyin
Marion Marchand
Virginie Marécal
Martine Michou
Luke D. Oman
Giovanni Pitari
David A. Plummer
Laura E. Revell
David Saint-Martin
Robyn Schofield
Andrea Stenke
Kane Stone
Kengo Sudo
Taichu Y. Tanaka
Simone Tilmes
Yousuke Yamashita
Kohei Yoshida
Guang Zeng
Related authors
Emphasis is placed on the Antarctic ozone hole, which is very important considering its role modulating Southern Hemisphere surface climate. While the model simulates the global distribution of ozone well, there is a disparity in the vertical location of springtime ozone depletion over Antarctica, highlighting important areas for future development.
Our research explored changes in ozone levels in the northwest Pacific region over 30 years, revealing a significant increase in the middle-to-upper troposphere, especially during spring and summer. This rise is influenced by both stratospheric and tropospheric sources, which affect climate and air quality in East Asia. This work underscores the need for continued study to understand underlying mechanisms.
hiddensource of inter-model variability and may be leading to bias in some climate model results.
detergent, removing air pollutants and greenhouse gases like methane from the atmosphere. Thus, understanding how it is changing and responding to its various drivers is important for air quality and climate. We found that OH has increased by about 5 % globally from 1980 to 2014 in our model, mostly driven by increasing nitrogen oxide (NOx) emissions. This suggests potential climate tradeoffs from air quality policies solely targeting NOx emissions.
model worlddifferent methods for estimating the mean age of air trends based on a combination of stratospheric water vapour and methane data. We also provide simple practical advice of a more reliable estimation of the mean age of air trends.
nudgeto the observed winds. Here we systematically evaluate how well this technique performs across a large suite of chemistry–climate models in terms of its ability to reproduce key aspects of both the tropospheric and stratospheric circulations.
agetracers. The largest variability occurs near the surface close to the tropical convergence zones, but the peak is further south and there is a smaller tropical–extratropical contrast for tracers with more rapid loss. Hence the variability of trace gases in the southern extratropics will vary with their chemical lifetime.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
Emphasis is placed on the Antarctic ozone hole, which is very important considering its role modulating Southern Hemisphere surface climate. While the model simulates the global distribution of ozone well, there is a disparity in the vertical location of springtime ozone depletion over Antarctica, highlighting important areas for future development.
Related subject area
Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
This study introduces a new 3D lake–ice–atmosphere coupled model that significantly improves winter climate simulations for the Great Lakes compared to traditional 1D lake model coupling. The key contribution is the identification of critical hydrodynamic processes – ice transport, heat advection, and shear-driven turbulence production – that influence lake thermal structure and ice cover and explain the superior performance of 3D lake models to their 1D counterparts.
Cited articles
- Article
(4321 KB) - Full-text XML