Keywords
lightning, air temperature, relative humidity, COVID-19, thunderstorm
This article is included in the Research Synergy Foundation gateway.
lightning, air temperature, relative humidity, COVID-19, thunderstorm
Many countries have enforced lockdown since the beginning of the COVID-19 pandemic.1-3 Energy-intensive human activities such as travelling and the hospitality sector were drastically reduced resulting in reduced emissions of greenhouse gases.4 The global emission is estimated to drop by 8.8% (−1551 Mt) in the first half-year of 2020 compared to the same period in 2019. Moreover, almost 18% of emissions in recent years were produced from ground transportation.5
Therefore, the trend of temperature is expected also to be reduced. A significant positive correlation between the atmospheric temperature and emission is reported in.6 Furthermore, COVID-19 lockdown has caused micro-climate changes such as localized variations in air temperature and relative humidity.7 The pandemic is also having an effect on , causing a decline that could possibly lead to short-term cooling.8 Air humidity will also be affected as global warming are dependent on both temperature and humidity.9
Lightning, a natural atmospheric discharge, is affected by various environmental factors. Lightning brings about hazards to human life and appropriate risk assessment has to be conducted for any habitable structure.10,11 Atmospheric variables such as climate change, humidity, aerosol level, and wind motion can affect the cloud charge distribution, electric field and threshold electromagnetic fields that give rise to air breakdown. It is predicted that lightning may strike more frequently as a result of the ongoing climate change.12 The lightning intensity may also increase due to the high greenhouse gases in the atmosphere.
Lightning could also be triggered by aerosols released by industrial processes and transportation activities.13,14 During the lockdown period, many industrial sectors stopped operating. Thus, human activities have considerably reduced during the COVID-19 pandemic which may affect the rate of lightning. Lightning ground flash density tends to increase with drier and warmer surface air.15 The frequency of thunderstorms in Denver and Colorado shows a major peak during summer time.17 Previous studies have also found a strong relationship between relative humidity and lightning occurrence.17,18 Hence, it is of interest to investigate the correlation between the environmental changes that happened during the period of COVID-19 related restriction of human activities and the lightning occurrence density. This study is an attempt to analyse this situation. This study investigates the trend of five months of lightning occurring from March to July in 2020 compared with the same period (March-July) in 2015-2019 in Europe and Oceania. The outcomes of this work could yield interesting insights into the correlation between human activities and lightning frequency.
Lightning stroke counts (LSC) and two atmospheric factors namely air temperature and relative humidity are considered as the variables in this study. The relationship between LSC with respect to air temperature and relative humidity will be statistically analysed via the dependent t-test and Pearson correlational studies.
From March until July in Europe and Oceania, the total LSC from the year 2015 to 2020 were extracted from LightningMaps.org.19 LightningMaps.org provides historical data of LSC and has been widely used in previous studies.20,21 The distribution of LSC data is presented in Tables 1 and 2.
The air temperature and relative humidity data from March until July in Europe and Oceania from year 2020 are extracted from the Physical Sciences Laboratory using Panoply Version 4.12.0.22 Europe is divided into seven sub-regions such as North Europe, West Europe, Central Europe, East Europe, South Europe, Southeast Europe, and the British Isles. After that, eight points (57.5°N, 10.0°E; 42.5°N, 12.5°E; 50.0°N, 25.0°E; 50.0°N, 5.0°E; 50.0°N, 10.0°E; 50.0°N, 20.0°E; 52.5°N, 0.0°; 42.5°N, 22.5°E) of around the sub-regions of Europe were selected in this study. For the Oceania region, five points (−12.5°N, 132.5°E; −37.5°N, 142.5°E; −27.5°N, 152.5°E; −30.0°N, 115.0°E; −27.5°N, 135.0°E) covering the North, South, East and West of Australia; Three points (−37.5°N, 175°E; −45.0°N, 167.5°E; −42.5°N, 170.0°E) covering the North, South and Centre of New Zealand; one point (−10.0°N, 147.5°E) from Papua were considered. Tables 3 and 4 show the average value of air temperature and relative humidity in Europe and Oceania in year 2020.
A dependent t-test is was conducted using Microsoft Excel 2016 (Microsoft Excel, RRID:SCR_016137) to determine whether there is a statistically significant difference between the LSC during the lockdown period in the year 2020 and the LSC in the same period (March-July) in year 2015 until 2019. The LSC is measured from a single population (Europe or Oceania) and two different timelines (before and during). Period A represents the lightning activities before lockdown period i.e. March to July in year 2015 to 2019. Period B represents the lightning activities during the lockdown i.e. March to July in the year 2020.
The t-test is conducted by comparing the data from Period B and Period A. The null hypothesis, and the alternative hypothesis, is defined as below:
H0: There is no significant difference in lightning frequency in between Period A and Period B.
Ha: There is a significant difference in lightning frequency in between Period A and Period B.
The confidence level of 95% at a significant level, is used. This approach tests the hypothesis and calculates the probability of determining whether there is evidence to reject the null hypothesis. When the P value < 0.05, the null hypothesis is rejected, and vice versa.
Next, the Pearson correlation coefficient is used to evaluate the correlation between the frequency of lightning activities with the atmospheric changes. The Pearson’s correlation coefficient, r, is computed to measure the strength of the relationship between total lightning strikes, air temperature, and relative humidity in Period B.
Furthermore, the correlation between the variables was analysed using regression and correlation analyses. The significant level, P value can be obtained from the regression data analysis. The null hypothesis, and the alternative hypothesis, is defined as below:
Null hypothesis, H0: P = 0, There is no significant relationship between lightning strikes with air temperature or relative humidity.
Alternative hypothesis, HA: P ≠ 0, There is a significant relationship between lightning strikes with air temperature or relative humidity
By using the P-value method (), the decision on rejection or acceptance of the null hypothesis can be made. There is sufficient evidence to conclude that there is a significant correlation between lightning strikes and air temperature or relative humidity as the correlation coefficient is significantly different from zero. Exact P values are provided in Table 5.
Figure 1 shows the LSC has dropped significantly in the year 2020 when the lockdown started. The dependent t-test shows a statistically significant (P-value <0.05) difference between 2020 and each previous year as shown in Table 5. Notably, LSC in Europe during the five-month lockdown period were reduced by more than 50% compared to the same period in the year 2019, 2018, and 2017.
Figure 2 illustrates the variation of LSC against air temperature levels in Europe. Figure 3. illustrates the relationship between LSC and relative humidity in Europe. Table 6 shows that the correlation of lightning strikes with air temperature and relative humidity in Europe are statistically significant. The Pearson correlation between lightning strikes and air temperature is 0.92, indicating a strong positive relationship between the variables. Pearson correlation between LSC and relative humidity is 0.52, indicating a moderate positive relationship between the variables. The positive correlation between lightning strikes with air temperature and relative humidity in Europe concurs with the findings of.15,17,18,23,24
There was a 44% drop in LSC from 2019 to 2020 as shown in Figure 4. Table 7 shows there is statistically significant difference between the year 2020 with all previous years except 2017. Figure 5 and Table 8 indicates a moderate positive correlation between LSC and air temperature in Oceania during the lockdown period. Unlike Europe, Figure 6 and Table 8 shows that the relationship between LSC and relative humidity in Oceania is negatively correlated. The positive correlation of LSC and air temperature is consistent with previous studies.23,24 The negative correlation of LSC and relative humidity in Oceania obtained in this study contradicted the study of.18
In conclusion, there was a drastic drop in LSC in Europe and Oceania during the first lockdown period in 2020. A dependent t-test confirmed that a statistically significant difference in LSC between Period A and Period B. There is a positive relationship between LSC and air temperature in Europe (r = 0.92) and Oceania (r = 0.55). Furthermore, there is a positive relationship between LSC and relative humidity in Europe (r = 0.52) but a negative relationship between LSC and relative humidity in Oceania (r = −0.54).
The differences in correlation between lightning, air temperature, and relative humidity in Europe and Oceania may also be due to other possible factors such as aerosol level, wind motions, and particulate matter. Future work should be replicated in other geographical regions such as America and Asia.
Fazandra Y: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing;
Siow C.L.: Conceptualization, Supervision, Writing – Review & Editing
Chandima G.: Conceptualization, Writing – Review & Editing
Aravind C.: Methodology, Validation
Lee C.P.: Validation, Supervision
All data underlying the results are available as part of the article and no additional source data are required.
The authors would like to thank LightningMaps.org and National Centers for Environmental Prediction (NCEP) and National Centers for Atmospheric Research (NCAR) for providing the data for this research, and Faculty of Engineering, MMU for providing the necessary support for this study.
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Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Lightning
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
No
References
1. Jones CD, Hickman JE, Rumbold ST, Walton J, et al.: The Climate Response to Emissions Reductions Due to COVID-19: Initial Results From CovidMIP.Geophys Res Lett. 2021; 48 (8): e2020GL091883 PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Atmospheric electricity, meteorology, plasma physics.
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