Climate dynamics

Background
Assessing why the spread of the COVID-19 virus slowed down in many countries in March through to May of 2020 is of great significance. The relative role of restrictions on behaviour (“lockdowns”) and of a natural slowing for other reasons is difficult to assess when mass testing was not widely done. This paper assesses the evolution of the spread of the COVID-19 virus over this period when there was no data on test results for a large, random sample of the population.

Method
We estimate a version of the susceptible-infected-recovered model applied to data on the numbers who were tested positive in several countries over the period when the virus spread very fast and then its spread slowed sharply. Up to the end of April 2020, test data came from non-random samples of populations who were overwhelmingly those who displayed symptoms. Using data from a period when the criteria used for testing (which was that people had clear symptoms) was relatively consistent is important in drawing out the message from test results. We use this data to assess two things: how large might be the group of those infected who were not recorded and how effective were lockdown measures in slowing the spread of the infection.

Results
We find that to match data on daily new cases of the virus, the estimated model favours high values for the number of people infected but not recorded.

Conclusions
Our findings suggest that the infection may have spread far enough in many countries by April 2020 to have been a significant factor behind the fall in measured new cases. Government restrictions on behaviour—lockdowns—were only one factor behind slowing in the spread of the virus.

We consider the utility of the annual inter-polar difference (IPD) as a metric for changes in Arctic emissions of methane (CH4). The IPD has been previously defined as the difference between weighted annual means of CH4 mole fraction data collected at stations from the two polar regions (defined as latitudes poleward of 53∘ N and 53∘ S, respectively). This subtraction approach (IPD) implicitly assumes that extra-polar CH4 emissions arrive within the same calendar year at both poles. We show using a continuous version of the IPD that the metric includes not only changes in Arctic emissions but also terms that represent atmospheric transport of air masses from lower latitudes to the polar regions. We show the importance of these atmospheric transport terms in understanding the IPD using idealized numerical experiments with the TM5 global 3-D atmospheric chemistry transport model that is run from 1980 to 2010. A northern mid-latitude pulse in January 1990, which increases prior emission distributions, arrives at the Arctic with a higher mole fraction and ≃12 months earlier than at the Antarctic. The perturbation at the poles subsequently decays with an e-folding lifetime of ≃4 years. A similarly timed pulse emitted from the tropics arrives with a higher value at the Antarctic ≃11 months earlier than at the Arctic. This perturbation decays with an e-folding lifetime of ≃7 years. These simulations demonstrate that the assumption of symmetric transport of extra-polar emissions to the poles is not realistic, resulting in considerable IPD variations due to variations in emissions and atmospheric transport. We assess how well the annual IPD can detect a constant annual growth rate of Arctic emissions for three scenarios, 0.5 %, 1 %, and 2 %, superimposed on signals from lower latitudes, including random noise. We find that it can take up to 16 years to detect the smallest prescribed trend in Arctic emissions at the 95 % confidence level. Scenarios with higher, but likely unrealistic, growth in Arctic emissions are detected in less than a decade. We argue that a more reliable measurement-driven approach would require data collected from all latitudes, emphasising the importance of maintaining a global monitoring network to observe decadal changes in atmospheric greenhouse gases.