POLE

Finished ProjectsPOLE

POLE: Past and Future of the Ozone Layer Evolution

Overview

Overview

The POLE project (Past and future of the Ozone Layer Evolution) aims to analyse the benefits of the Montreal Protocol and its Amendments (MPA) to increase public acceptance of its necessity, to project and estimate the time when ozone layer recovery will occur, and to analyse observational and model data to detect changes in the ozone layer evolution.

The project will provide understanding and direction about how to protect the ozone layer and to make more accurate climate predictions. An impact on society and policymakers is foreseen, because we will suggest a way to guarantee ozone recovery even if extremely unfavorable future scenarios play out. The project will allow Switzerland to expand its participation in international assessments and activities aimed at conservation of the ozone layer as well as to underpin policy positions on sustainable development.

Introduction

The evolution of the ozone layer remains a central problem to contemporary science because of its importance for the sustainable development of human civilization. It is now recognized and confirmed that the ozone layer is not only shielding the biosphere from dangerous solar UV radiation, but it is also important for the global atmosphere and climate. Explanations for the massive Southern polar ozone loss, later termed “ozone hole”, confirmed the previously suggested anthropogenic halogen-induced global ozone depletion and led to limitations on the production of halogen containing ozone depleting substances (hODS) by the Montreal Protocol and its Amendments (MPA). Further research aimed to analyze the benefits of the MPA in order to increase public acceptance of its necessity, to project and estimate the time at which ozone layer recovery will occur, and to analyse observational and model data to detect changes in the ozone layer evolution.

The Project Team

PI Dr. Eugene Rozanov

Scientist Dr. William Ball

Scientist Dr. Timofey Sukhodolov

Scientist Dr. Tatiana Egorova

PhD student Arseni Doyennel

Specific Aims

  1. Explain past ozone layer trends in the lower stratosphere.
  2. Revisit the role of the Montreal Protocol in sustaining recovery of the ozone layer and protecting climate.
  3. Project future behavior of the ozone layer considering very-short lived species, newly discovered hODS, solar and volcanic activity, as well as possible climate intervention.
  4. Investigate and suggest additional measures to guarantee ozone layer recovery.
  5. Evaluate uncertainties in the stratospheric aerosol loading, by participating in international the ISA-MIP project, and estimate its potential impact on the ozone in the lower stratosphere.
  6. Validate the aerosol microphysics module and prepare for future explosive volcanic eruptions participating in the international VolRES project.

Methods

We intend to use our new Atmosphere-Ocean-Aerosol-Chemistry-Climate Model (AOACCM) SOCOLv4 which consists of the MPI-MET Earth System model (ESM) coupled to chemical and sulphate aerosol modules. The model output will be compared to observations and other models using comprehensive statistical tools.

Expected Results

  • Establish the processes responsible for the persistent ozone depletion in the lower stratosphere.
  • Newly assessing and judging the benefits of the MPA, which is an issue of utmost importance for sustainable development of the environment.
  • Assess the potential danger for the ozone layer recovery from very-short lived substances, newly discovered hODS, solar and volcanic activity, as well as possible climate intervention.
  • Suggest possible additional measures to guarantee ozone layer recovery.
  • Characterise the uncertainties in stratospheric aerosol loading.

SOCOL Model

SOCOLv4 Model Description

The Atmosphere-Ocean-Aerosol-Chemistry-Climate Model (AOACCM) SOCOLv4.0 consists of the Earth System Model MPI-ESM1.2 (Mauritsen et al., 2019), the chemistry model MEZON (Egorova et al., 2003), and the sulfate aerosol microphysical model AER (Weisenstein et al., 1997), with all these parts being interactively coupled to each other, as schematically presented in Figure 1. In simple terms, chemistry and aerosol microphysics rely on atmospheric temperature, winds, and relative humidity and in turn influence the atmosphere and ocean through the short- and long-wave radiation schemes, while aerosol microphysics depend on sulfur chemistry and provide the aerosol surface area density and number density necessary for heterogeneous chemistry calculations. Transport of individual gases and aerosols is performed by the flux-form semi-Lagrangian scheme of Lin and Rood (1996) in the dynamical core of ECHAM6 that has remained unchanged from its predecessor ECHAM5. Transport is calculated every dynamical time step (15 min). The dry and wet deposition of gases and aerosols is also based on the ECHAM6 parameters such as near-surface turbulence and precipitation.

Figure 1

SOCOLv4 is based on the low resolution (LR) configuration of the MPI-ESM model. This configuration corresponds to a spectral truncation at T63 providing an approximate horizontal grid spacing of 1.9° x 1.9°. The vertical resolution of the atmosphere is set to 47 levels from the surface to 0.01 hPa, using a hybrid sigma-pressure coordinate system. Although other higher horizontal and vertical resolutions of MPI-ESM are also tuned and available for use, we chose the LR configuration since it is the most used and better tuned one (Mauritsen et al., 2019), and better suited for long-term climate simulations in terms of required computational resources and storage. The earth system model MPI-ESM1.2 (Mauritsen et al., 2019) is a further development of its predecessor MPI-ESM (Giorgetta et al., 2013). The main components of MPI-ESM are highlighted by the dark blue boxes in Figure 1. The ocean dynamical model, MPIOM 1.6.3, transports tracers of the ocean biogeochemistry model, HAMOCC6. The atmosphere model, ECHAM6.3, is directly coupled to the land model, JSBACH3.2, through a surface exchange of mass, momentum, and heat. These two major model blocks are then coupled via the OASIS3-MCT coupler (Craig et al., 2017). The coupler aggregates, interpolates, and exchanges fluxes and state variables once a day between ECHAM6-JSBACH and MPIOM-HAMOCC. The SOCOLv4 treats the majority of the processes responsible for the behavior of the ozone layer from the ground up to the mesopause. In addition to the interactive gas-phase / heterogeneous chemistry and bin-resolved stratospheric sulfate aerosol, the model can simulate the dynamical vegetation, carbon cycle, emission of sulfur-containing species from the ocean, and other necessary quantities to simulate direct forcing and feedbacks responsible for the ozone layer behavior.

Figure 2 shows the global mean total ozone evolution for the period 1980-2018 simulated with SOCOLv4 (red: ensemble-mean and single ensemble members) and compared to the mean total ozone derived from MSRv2 reanalysis data.

The four decades shown are characterized by anthropogenic and natural forcing contributions with varying importance during different periods. Overall, the presented general behavior of the total ozone column evolution is very well captured by the model.

Figure 2

The geographical distribution of the total ozone column (TOC) over the Northern (right column) and Southern (left column) hemispheres for the period 1980-2018 simulated with SOCOLv4 and derived from MSRv2 reanalysis data is shown in Figure 3. The percentage difference between SOCOLv4 and MSRv2 ozone (that is demonstrated at the lower panel of Figure 3) shows that SOCOLv4 ozone agrees very well with MSRv2 at the tropical and middle latitudes, however, underestimates the MSRv2 over the southern ozone hole area by about 10% and shows a bit higher ozone over the high latitudes of both hemispheres. These issues might be caused by the imperfection of the model dynamic core impacting the transport and the strength of the polar vortex. Despite this, we can say that the geographical distribution of TOC is well captured by the model.

Figure 3

Figure 4 illustrates the seasonal ozone cycle at 70 hPa for the period 1984-2012 simulated with SOCOLv4 (upper panel) and derived from GOZCARDS ozone composite (lower panel).

SOCOLv4 shows a generally good agreement of the seasonal ozone cycle with GOZCARDS albeit showing some deviations in timing and magnitude of extremes that can also be partly attributed to the deficiencies in transport.

Figure 4

Figure 5 shows the geographical distribution of the 2-meter air temperature climatology for 1980-2018 as simulated with SOCOLv4 (upper panel) and derived from the ERA5.1 reanalysis (lower panel). ERA5.1 data have been interpolated to the model grid.

SOCOLv4 properly reproduces the observed geographical pattern of the surface air temperature with cold high-latitude areas in both hemispheres and warm tropics and subtropics. However, there are some regional discrepancies between the model and the reanalysis data. Most of these biases in high-altitude regions are a common feature of all coupled models, which is usually attributed to the simplified model’s topography and uncertainties in the observational data.

Figure 5

Figure 6 illustrates the global mean 2-meter temperature (upper panel) and Arctic sea ice extent (lower panel) annual anomalies simulated with SOCOLv4 and different reanalysis data. Upper panel: global and annual mean 2-meter temperature anomaly relative to 1980 (K): bold black line: simulated mean of 3-member SOCOLv4 ensemble; faded black lines: SOCOLv4 individual ensemble members; red line: ERA5.1 reanalysis; blue line: BEST reanalysis. Lower panel: Arctic sea ice extent anomaly (million km2). Bold black line: simulated mean of 3-member SOCOLv4 ensemble; faded black lines: SOCOLv4 individual ensemble members; red line: ERA5.1 reanalysis. Anomalies were calculated as a deviation from the mean over the 1980-2018 period. The model shows a warming trend similar to observations, whereas the ensemble mean curve shows less inter-annual variability, as expected. In the case of Arctic sea ice extent annual anomalies, in SOCOLv4 they are in line with observations, showing a similar decline with time because of global warming.

Figure 6

Evaluation of SOCOLv4.0 against available observations and reanalysis data showed that SOCOLv4 is suitable for studies of the past and future climate changes. More analysis can be found in Sukhodolov et al. (2021).

References

Craig, A., Valcke, S., and Coquart, L .: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297-3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017.
Egorova, T., Rozanov, E., Gröbner, J., Hauser, M., and Schmutz, W .: Montreal Protocol Benefits simulated with CCM SOCOL, Atmos. Chem. Phys., 13, 3811-3823, https://doi.org/10.5194/acp-13-3811-2013, 2013.
Giorgetta, MA, et al.: Climate and carbon cycle changes demo 1850 to 2100 in MPI – ESM simulations for the Coupled Model Intercomparison Project phase 5, J.Adv. Mod. Earth Sys., 5, 572–597, https://doi.org/10.1002/jame.20038, 2013.
Lin, SJ, and Rood, RB: Multidimensional flux-form semi-Lagrangian transport schemes, Month. Weather Rev., 124, 2046-2070, https://doi.org/10.1175/1520-0493(1996)124<2046:MFFSLT>2.0.CO;2, 1996.
Mauritsen, T. et al.: Developments in the MPI – M Earth System Model version 1.2 (MPI – ESM1.2) and its response to increasing CO2, J. Adv. Model. Earth Syst., 11, 998-1038, https://doi.org/10.1029/2018MS001400, 2019.
Sukhodolov, T., Egorova, T., Stenke, A., Ball, WT, Brodowsky, C., Chiodo, G., Feinberg, A., Friedel, M., Karagodin-Doyennel, A., Peter, T., Vattioni, S., and Rozanov, E .: Atmosphere-Ocean-Aerosol-Chemistry-Climate Model SOCOLv4.0: description and evaluation, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2021-35, in review, 2021
Weisenstein, DK, Yue, GK, Ko, MKW, Sze, N.-D., Rodriguez, JM, and Scott, CJ: A two-dimensional model of sulfur species and aerosols, J. Geophys. Res., 102, 13019-13035, https://doi.org/10.1029/97JD00901, 1997.

Numerical experiments

Numerical Experiments

For the planned experiments, we will mostly use the standard model version (T63 / L47) with all model components switched on. We plan to run the model in ensemble mode for most transient experiments. All deviations from the standard model version will be mentioned.
The standard boundary condition set includes external drivers (eg, greenhouse gas (GHG) and the concentration or emissions of ozone depleting substances (ODS), solar irradiance, energetic particles) of the climate and ozone recommended for the participants of IGAC / SPARC CCMI or , if ready, IPCC CMIP6. Sulphate emissions from volcanos applied in the ongoing SNSF project VEC will be used as standard. Sulfur and VSLSs emissions from the ocean will be interactively calculated in the model. All deviations from the standard version will be mentioned. The reference run with the standard model configuration and boundary condition will cover the 1960-2018 period. The necessary initial conditions for 1960 will be acquired from the available results from the spin-up SOCOLv4 run performed in the framework of the ongoing SNSF project VEC. The intended experiments enlisted below is preliminary, because the exact way how to proceed depends on the results already obtained and availability of upgraded modules. Therefore, while the general line will be maintained, some deviations from the detailed planning are possible. The intended experiments enlisted below is preliminary, because the exact way how to proceed depends on the results already obtained and availability of upgraded modules. Therefore, while the general line will be maintained, some deviations from the detailed planning are possible. The intended experiments enlisted below is preliminary, because the exact way how to proceed depends on the results already obtained and availability of upgraded modules. Therefore, while the general line will be maintained, some deviations from the detailed planning are possible.

A list of the intended numerical experiments is given below in Sections 1 – 4.

1. Study of Past Ozone Trends

We will perform the following SOCOLv4 runs covering 1985-2018:

  • Excluding time-evolving halogen containing VSLSs.
  • Excluding stratospheric aerosol variability.
  • Prescribing time-evolving aerosol from the GloSSAC (CMIP6) data set.
  • Using climatological sea surface temperature and sea ice distributions.
  • Applying fixed hODS at 1985 level.
  • Applying fixed GHG at 1985 level.
  • Enhancing mixing efficiency.
  • Exploiting the model version with higher vertical (L95) and horizontal (T126) resolutions.
  • Installing an updated version of the aerosol module.

The analysis of these model results will allow us to determine which process is likely to be responsible for the persistent negative ozone trend in the lower stratosphere. In the case that no instructive conclusions can be made, this will provide a direction to investigate other mechanisms or reasons.

2. Study of the MPA Benefits

We will start with the following SOCOLv4 runs covering 1985-2100:

  • Set with standard configuration and boundary conditions.
  • Applying an hODS increase according to the case with no MPA limitations.

The necessary initial conditions will be acquired from the reference run. The analysis will demonstrate the response of the ozone layer, surface UV and climate to unconstrained hODS production considering multiple feedbacks in the climate system. Surface UV will be calculated using off-line libRadtran code as done by Egorova et al. (2013).

3. Projections of the Ozone Layer

We plan to perform the following SOCOLv4 runs covering 2018-2100:

  • Continue reference run to 2100 (same as in 2).
  • Applying emissions of newly discovered hODS or or hODS unaccounted for by the MPA.
  • Applying a decline in solar activity.
  • Introducing geo-engineering scenarios of sulphur injection.
  • Combining all factors from three previous experiments.
  • Fixing sulphur and VSLS emissions from the ocean at 2018 levels.
  • Applying a stronger limitation on N2O emissions.
  • Applying stronger alternative scenarios for CH4.

The results of reference run will be used for the initialisation. For the case of solar activity decline, we will apply a scenario with a strong decline (Arsenovic et al., 2018). Sulphur and VSLS emissions from the ocean will be interactively calculated in the model. Several ‘most-probable’ geo-engineering scenarios of sulphur injection (variable height, latitudinal belt and injected species) will be defined from the analysis of recent publications. The results will allow us to characterise any danger to ozone layer recovery. If this danger is real, we will estimate whether it is possible to compensate for it through regulation of N2O or CH4 emissions. If even this turns out to be impossible, we will analyse what other measures might be applied.

4. Evaluate Aerosol Microphysics Module

The central aim of ISA-MIP is to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardised model experiments with a range of observations. In this activity, we will exploit the latest version of SOCOL-AER and a new SOCOLv4. Exploitation of both models will allow us to learn more about their behaviour. The list of runs for ISA-MIP activity was defined by Timmreck et al. (2018), but we will only perform a limited subset of runs:

  • The “Background” (BG) is a time-slice 20-year long experiment that focuses on microphysics and transport processes under volcanically quiescent conditions, when the stratospheric aerosol is controlled by the transport of aerosols and their precursors from the troposphere to the stratosphere.
  • The “Transient Aerosol Record” (TAR) experiment that explores the role of small- to moderate-magnitude volcanic eruptions, anthropogenic sulphur emissions and transport processes over the period 1998-2012 and their role in the warming hiatus.
  • The “Historical Eruptions SO2 Emission Assessment” (HErSEA) experiment that focuses on the uncertainty in the initial emission of recent large-magnitude volcanic eruptions.
  • “Pinatubo Emulation in Multiple models” (PoEMS) experiment to provide a comprehensive uncertainty analysis of the radiative forcing from the 1991 Mt. Pinatubo eruption.

 

ISA-MIP provides the necessary sulphur emissions for the satellite era. We will also use these emissions for experiments 1. Participation in this project will require a detailed output of aerosol-related information also including installation of new passive tracers and additional diagnostical fields. We will try to address most of the requested details in SOCOLv4, while in SOCOL-AER we will only focus on the main fields to save manpower.

For the VolRES project, we will exploit SOCOL-AER (Sukhodolov et al., 2018) or SOCOLv4 in specified dynamics mode and higher vertical resolution L95, which can be important for aerosol sedimentation. For the pre-eruption period we will train the model using continuously updated observational sulphur emission databases (provided by ISA-MIP and VolRES teams) and observed circulation from reanalysis datasets (ERA-Interim, ERA-5 or MERRA-2). If the major eruption happens during the duration of this project, observational groups will report the emission strength and profile. Together with the forecasted circulation fields this information will be used to initiate our model runs and thus forecast the volcanic plume evolution.

Existing Datasets

For the implementation of the project, we will use the following data sets:

  • CCMI boundary conditions and model output.
  • CMIP6 boundary conditions and model output.
  • ISA-MIP boundary conditions and model output.
  • Ozone composites (Ball et al., 2018; Frith et al., 2014).
  • ERA-Interim.
  • ERA-5.
  • MERRA-2.
  • Future volcanic sulphur emissions from project VEC.
  • VolRES observations.
  • VSLS concentration in the ocean (Ziska et al., 2017).
  • Solar modulation potential (Arsenovic et al., 2018; Egorova et al., 2018).
  • GloSSAC (Stratospheric aerosol properties, Thomasson et al., 2018).

Time schedule

POLE Time Schedule

Time Activity Staff involved
Month 1-6 Model preparation for all experiments, compiling boundary conditions until 2018, optimization of the output, experimental design, post-processing. Execution of the reference run. T. Sukhodolov, T. Egorova, W. Ball, E. Rozanov
Month 1-6 Acquaintance with the model, work on the project web-page. Application for the CSCS (Switzerland national computer center) access. A. Doyennel, E. Rozanov
Month 7-12 Execute runs for 1985-2018 period, preparation of the boundary conditions until 2100. Analysis of the results. All project staff
Milestone A, Month 12
 Reference run is completed. Web-page is active. Runs planned for the experiments 1, 2 and 4 have started. The results of first runs have been analyzed.
Month 13-18 Complete the main runs from 1. Continue runs from 4. Execute runs for 2018-2100 period. Analysis of the results. All project staff
Month 19-24 Complete analysis of the main 1 and 2 run results, prepare publications. Continue runs from 4. All project staff
Milestone B, Month 24
 All main runs from the experiments 1 and 2 are finalized and the results prepared for publication. Model is trained for the VolRES project. Future runs from 3 have been started.
Month 25-30 Complete runs from 4. Continue runs from 3. Analysis of the results. All project staff
Month 30-36 Complete analysis of 4 run results, prepare publications. Complete most of runs from 3. Analysis of the results. All project staff
Milestone C, Month 36
 Papers based on the experiment 4 are prepared. Updated aerosol module is ready.
Month 37-42 Repeat the experiments from 1 with updated aerosol module. Complete all runs from 3. All project staff
Month 43-48 Complete analysis of all results, prepare publications. All project staff
Month 37-48 Preparation of PhD thesis. A. Doyennel
End of the project

Numbers of the numerical experiments here correspond to those in the “Numerical experiments” inset.

Useful links

Useful Links

IGAC/SPARC CCMI:
The goal is to coordinate the evaluation of the chemistry-climate model and associated modelling activities (http://www.sparc-climate.org/activities/ccm-initiative/).

VolMIP:
Aims to assess climate model performance under strong volcanic forcing.(http://www.volmip.org/).

SPARC SSiRC:
The purpose of SPARC SSiRC is to coordinate individual activities, support new measurement of sulphur containing species and initiate new model/data comparisons. (http://www.sparc-climate.org/activities/stratospheric-sulfur/).

VolRES:
Aims to prepare for the next volcanic eruption (http://www.sparc-climate.org/2016/11/14/call-for-participation-in-shaping-a-new-volcano-response-plan/).

ISA-MIP:
Aims to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardised model experiments with a range of observations.(http://isamip.eu/index.php?id=4213).

SOLARIS/HEPPA:
The project coordinates studies related to the influence of solar irradiance and energetic particles on the ozone layer and climate (http://www.sparc-climate.org/activities/solar-influence/).

LOTUS:
LOTUS will update and extend ozone time-series providing a data set for the comparison with models (http://www.sparc-climate.org/activities/ozone-trends/).

News

News List

October, 2023 – POLE final scientific report

May 2023 – Key project manuscript: “Montreal Protocol’s impact on the ozone layer and climate” published: https://doi.org/10.5194/acp-23-5135-2023

April 2023 – Key project’s manuscript:” The future ozone trends in changing climate simulated with SOCOLv4″ published: https://doi.org/10.5194/acp-23-4801-2023 

January 2023 – The POLE project has been prolonged till August 2023

December 2022 –  Key project manuscript: “The historical ozone trends simulated with the SOCOLv4 and their comparison with observations and reanalyses” published: https://doi.org/10.5194/acp-22-15333-2022

November 18, 2022 – The project’s PhD student Arseni Doyennel successfully defended his PhD thesis at ETH, Zurich. Congratulation! Well done!

September 2021 – Key project manuscript about SOCOLv4 validation  published in GMD: https://doi.org/10.5194/gmd-14-5525-2021

May 2021 – Dr. Jan Sedlacek started to work on the POLE project

March 2021 – Sukhodolov, T., Egorova, T., Stenke, A., Ball, WT, Brodowsky, C., Chiodo, G., Feinberg, A., Friedel, M., Karagodin-Doyennel, A., Peter, T., Vattioni, S., and Rozanov, E .: Atmosphere-Ocean-Aerosol-Chemistry-Climate Model SOCOLv4.0: description and evaluation, Geosci. Model Dev. Discuss . [preprint], https://doi.org/10.5194/gmd-2021-35 in review, 2021.

January 28th – February 4th, 2021 – Participation at the 43rd COSPAR Scientific Assembly with an oral talk: “The mesospheric H2O and CO response to solar irradiance changes in models and observations”

January 11th, 2021 – Karagodin-Doyennel, A., Rozanov, E., Kuchar, A., Ball, W., Arsenovic, P., Remsberg, E., Jöckel, P., Kunze, M., Plummer, DA , Stenke, A., Marsh, D., Kinnison, D., and Peter, T .: The response of mesospheric H2O and CO to solar irradiance variability in models and observations, Atmos. Chem. Phys ., 21, 201-216, https://doi.org/10.5194/acp-21-201-2021 , 2021.

July 2020 – All SOCOLv4 reference experiments have been completed.

March 2020 – Development of SOCOLv4 has been finished; three reference experiments have begun.

April 2019 – A. Doyennel started to work on the POLE project as a PhD student

For further information please contact: Dr. E. Rozanov, Dr. T. Egorova, Dr. T. Sukhodolov, Dr. J. Sedlacek, Dr. A. Doyennel (POLE editor)