EGU22-12148, updated on 08 Apr 2024
https://doi.org/10.5194/egusphere-egu22-12148
EGU General Assembly 2022
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Stratospheric prognostic ozone for seamless Earth System Models

Beatriz Monge-Sanz1,2, Alessio Bozzo3, Nicholas Byrne4, Martyn Chipperfield5,6, Michail Diamantakis7, Johannes Flemming7, Lesley Gray1,2, Robin Hogan7,4, Luke Jones7, Linus Magnusson7, Inna Polichtchouk7, Theodore Shepherd4, Nils Wedi7, and Antje Weisheimer1,2,7
Beatriz Monge-Sanz et al.
  • 1Physics Department, University of Oxford, Oxford, United Kingdom – (beatriz.monge-sanz@physics.ox.ac.uk)
  • 2National Centre for Atmospheric Science, University of Oxford, Oxford, United Kingdom
  • 3European Organisation for the Exploitation of Meteorological Satellites, Darmstadt, Germany
  • 4Department of Meteorology, University of Reading, Reading, United Kingdom
  • 5School of Earth and Environment, University of Leeds, United Kingdom
  • 6National Centre for Earth Observation, University of Leeds, United Kingdom
  • 7European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

Our study shows the relevance of the interactions between atmospheric chemistry and physics to achieve better weather predictions. We provide evidence of the role that stratospheric ozone plays to improve weather forecasts on several timescales, and highlight the need for seamless models to include realistic prognostic ozone interactive with radiation.

Representing realistic feedbacks between ozone, radiation, temperature and dynamics is essential to correctly simulate the behaviour of the stratosphere and its links with tropospheric weather and climate. We have implemented an alternative stratospheric ozone model (Monge-Sanz et al., 2011) in the ECMWF system interactively with radiation, and we have assessed its performance and feedbacks with meteorological fields for different timescales, from medium-range to seasonal.  Here we will discuss results from the experiments and analyses conducted in our study (Monge-Sanz et al., 2021), showing the feasibility of this ozone model for a seamless numerical weather prediction approach.

We will show that the stratospheric ozone distribution provided by this new prognostic ozone model compares very well with observations even for unusual meteorological conditions. On assessing impacts on meteorological variables, the new ozone model improves the representation of the stratosphere, clearly reducing temperature biases in this region. We will also show the benefits it brings to tropospheric meteorological fields, highlighting the potential of this new ozone description to exploit stratospheric sources of predictability and improve weather predictions over Europe on a range of time scales.

Therefore, our results show the value of this prognostic stratospheric ozone model for seamless Earth System Models, as well as for global systems where atmospheric composition is coupled to weather forecasts, like the systems being run within the Copernicus Atmosphere Monitoring Service (CAMS). We will also discuss challenges and possible strategies for the inclusion of chemistry-dynamics feedbacks in seamless Earth System Models.

 

References:

Monge-Sanz BM, Chipperfield MP, Cariolle D, Feng W. Results from a new linear O3 scheme with embedded heterogeneous chemistry compared with the parent full-chemistry 3-D CTM. Atmos. Chem. Phys. 11, 1227-1242, 2011.

Monge-Sanz, B. M., Bozzo, A., Byrne, N., Chipperfield, M. P., Diamantakis, M., Flemming, J., Gray, L. J., Hogan, R. J., Jones, L., Magnusson, L., Polichtchouk, I., Shepherd, T. G., Wedi, N., and Weisheimer, A.: A stratospheric prognostic ozone for seamless Earth System Models: performance, impacts and future, Atmos. Chem. Phys., accepted, https://doi.org/10.5194/acp-2020-1261, 2021.

How to cite: Monge-Sanz, B., Bozzo, A., Byrne, N., Chipperfield, M., Diamantakis, M., Flemming, J., Gray, L., Hogan, R., Jones, L., Magnusson, L., Polichtchouk, I., Shepherd, T., Wedi, N., and Weisheimer, A.: Stratospheric prognostic ozone for seamless Earth System Models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12148, https://doi.org/10.5194/egusphere-egu22-12148, 2022.