Using UKESM1 to model the climate response to reductions in emissions caused by COVID-19

Jeremy Walton13, Steve Rumbold12, Yongming Tang13 and Chris Jones3

1UKESM Core Group, 2National Centre for Atmospheric Science, 3Met Office Hadley Centre

Many countries responded to the COVID-19 pandemic by restricting travel and other activities in 2020.  This in turn caused a temporary reduction in emissions of CO2 and other greenhouse gases,  as well as ozone and aerosol precursors.  We have used UKESM1 to investigate whether these reductions have any impact on the Earth’s climate in the near future.

The magnitude and distribution of the reduction of greenhouse gas emissions  due to COVID-19 have been determined by several research groups using both bottom-up estimates (based on sector activity data) and top-down analysis (using atmospheric observations) during 2020.  The magnitude of these reductions appears to be small, but the long lifetime of CO2 and CH4 suggests that their impact could be long-lived.

Using this data, Forster et al. [1] have developed an emissions reduction scenario which posits an initial drop in emissions of around 35% for NOx, 27% for CO2 and 5% for CH4 during the first four months of 2020, followed by a period of around two years during which emissions remain constant before rising back to pre-2020 levels.  These emissions have been collated, gridded and made available for use by CMIP Earth system models [2]; in addition, a modelling protocol has been developed [2] to investigate the impact of emissions reductions on climate, using the scenario of Forster et al. [1].

We have used forcings from the so-called Two-Year Blip emissions scenario [1] to run simulations with UKESM1.  Because we are investigating the effect the reductions have on future climate, we need a baseline against which to measure changes.  The SSP2-4.5 scenario has been selected [2] for this – specifically, simulations are run parallel to SSP2-4.5 up until the beginning of 2020, when the new forcings are applied.

Since the effect is likely to be small, we need to run an initial-condition ensemble with a large number of members in order to better enable detection of a climate change signal.  Initially (i.e., prior to this study), our UKESM1 SSP2-4.5 ensemble contained five variants, whilst the UKESM1 historical ensemble consisted of sixteen members, each of which can act as the starting point for a scenario run.  Accordingly, we first ran eleven new SSP2-4.5 experiments, and then sixteen Two-Year Blip runs.

Global annual means for three variables are plotted in Figure 1 for the period 2020-2024.  We show the results for each of the sixteen variants for each ensemble and, for each variant, the difference between the result for Two-Year Blip and that for SSP2-4.5.

Figure 1 shows that, for 2020, there is a reduction in aerosol optical depth (AOD) at 550 nm whose magnitude is greater than the standard deviation of the ensemble.  Beyond this point, the size of the reduction decreases (becoming statistically insignificant after two years) as emissions reductions recover to baseline scenario levels.  This behaviour is reflected in the amount of solar radiation reaching the surface (see Figure 1), which increases somewhat in 2020 (by an amount less than the standard deviation).  As in the case of AOD, the positive anomaly quickly recovers before becoming negligible from 2022 onwards.

Figure 1:  Annual mean, global average variables from UKESM1 simulations for SSP2-4.5 and Two-Year Blip experiments, for Aerosol Optical Depth (top), Downward Shortwave Radiation (middle) and Surface Air Temperature (bottom).  Plots on the left show results from each of the sixteen variants in the ensembles, while those on the right show the ensemble of differences (Two-Year Blip minus SSP2-4.5), the ensemble average (heavy line) and standard deviation (shaded area).

By contrast, globally averaged surface air temperature (see Figure 1) shows no significant change for any year.  This is also the case for globally averaged precipitation (not shown here), implying that the impact of the change in radiation on surface climate at a global scale is very small.  The spatial distribution of the Two-Year Blip anomaly for surface air temperature is shown in Figure 2.  The difference is positive over northern Russia and Antarctica, and negative in the Arctic, but the effect is small (specifically, the absolute magnitude of the anomaly is only about a quarter of a degree Celsius).

Figure 2:  2020-2024 mean of surface air temperature anomaly from UKESM1 for Two-year Blip experiment.

The results we have presented in this article form part of our contribution [3] to CovidMIP, a coordinated Model Intercomparison Project which aims to use several Earth System models to run prescribed simulations [2], one of which is the Two-Year Blip experiment described here.  To date, eleven models (including UKESM1) have performed over 280 runs using multiple initial-condition ensembles.  The reduction in aerosol amounts, the increases in radiation at the surface and the weak climate signal which we have found with UKESM1 are consistent with the consensus found from the other models.  More details about CovidMIP and the results from the multi-model ensemble for the Two-Year Blip experiment for the period 2020-2024 can be found elsewhere [3].

In addition to Two-Year Blip, Forster et al. [1] created a set of scenarios spanning possible future economic recovery strategies: Fossil-Fuelled Recovery, which sees an increase in anthropogenic CO2 emissions relative to SSP2-4.5 after 2020 consistent with investment in more traditional fossil-fuel based energy production, Moderate Green Stimulus, where anthropogenic CO2 emissions are reduced post-2020 consistent with an enhanced investment in environmentally-friendly technologies, and Strong Green Stimulus, in which a greater proportion of gross domestic product is devoted to this enhanced investment.  All of these scenarios (including the Two-Year Blip) are defined over the period 2020-2050, and have become part of the CovidMIP set of experiments [2].

We have used UKESM1 to run the full extent of each scenario (using an initial-condition ensemble set up in the same way as the Two-Year Blip runs described here) and are in the process of transferring the results to the CMIP6 data archive on the Earth System Grid Federation [4].  Note that this repository already contains the data we have used in CovidMIP [3] to date.

This investigation of the impact of COVID-19 on global climate is still in its infancy, and analysis of the results from the other scenarios is currently under way.  In addition, Jones et al. [3] have identified further areas of analysis which would be fruitful; these include fixed-SST simulations to facilitate the quantification of changes to effective radiative forcing due to emission reductions, and more detailed examination of local effects, changes in extremes, and the influence on atmospheric circulation.

The 2020 pandemic has had an impact on many aspects of human life on Earth, including health, economics and society.  However, its scale also gives us an unprecedented opportunity to study how the planet’s climate responds to anthropogenic changes in its atmosphere.  The work described in this note and elsewhere [3] will help advance our understanding in this important field.


  1. Forster, P. M., Forster, H. I., Evans, M. J., Gidden, M. J., Jones, C. D., Keller, C. A., et al. (2020). Current and future global climate impacts resulting from COVID-19.  Nat. Clim. Chang.  doi:
  2. Lamboll, R.D., Jones, C.D., Skeie, R.B., Fiedler, S., Samset, B.H., Gillett, N.P., et al. (2020). Modifying emission scenario projections to account for the effects of COVID-19: protocol for Covid-MIP.  Geosci. Mod. Dev., submitted.  doi:
  3. Jones, C.D., Hickman, J.E., Rumbold, S.T., Walton, J., Lamboll, R.D., Skeie, R.B., et al. (2020). The Climate Response to Emissions Reductions due to COVID-19.  Geo. Res. Letts., submitted.
  4. Rumbold, S., Walton, J., Tang, Y. (2020). MOHC UKESM1.0-LL model output prepared for CMIP6 DAMIP ssp245-covid. Version 20201126.  Earth System Grid Federation.
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