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This article examines the role of the meteorological variable in the spread of the ongoing pandemic coronavirus disease 2019 (COVID-19) across India. COVID-19 has created an unprecedented situation for public health and brought the world to a standstill. COVID-19 had caused more than 1,523,242 deaths out of 66,183,029 confirmed cases worldwide till the first week of December 2020. We have examined the surface temperature, relative humidity, and rainfall over five cities: Delhi, Mumbai, Kolkata, Bengaluru, and Chennai, which were severely affected by COVID-19. It is found that the prevailing southwest (SW) monsoon during the pandemic has acted as a natural sanitizer in limiting the spread of the virus. The mean rainfall is  ~ 20–40 mm over the selected cities, resulting in an average decrease in COVID cases by ~ 18–26% for the next 3 days after the rainfall. The day-to-day variations of the meteorological parameters and COVID-19 cases clearly demonstrate that both surface temperature and relative humidity play a vital role in the indirect transport of the virus. Our analysis reveals that most COVID-19 cases fall within the surface temperature range from 24 to 30 °C and relative humidity range from 50% to 80%. At a given temperature, COVID-19 cases show a large dependency on the relative humidity; therefore, the coastal environments were more prone to infections. Wavelet transforms coherence analysis of the daily COVID-19 cases with temperature and relative humidity reveals a significant coherence within 8 days.

Abstract. Spatial and temporal variability in the convective boundary layer (CBL) height for the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) study period are examined using the data collected from high-resolution radiosondes during May-September 2009 over the Indian monsoon region. In total, 57 radiosonde launchings were carried out at ∼ 11:00-17:00 IST over six different stations covering a large geographical region, ranging from latitude ∼ 13 to 32 • N and longitude 73 to 92 • E. Of the total 57 launchings, 17 were made during cloudy conditions during which relative humidity (RH) was found to be greater than 83 % for an ∼ 1.0 km layer at various altitudes below 6 km. Within the layer the difference between saturated equivalent potential temperature and equivalent potential temperature is small, and it satisfies the condition that RH > 83 % for about 1 km is considered as the cloudy layer. There are eight cases when the cloud-topped boundary layer (CTBL) and 19 cases when fair-weather boundary layer (FWBL) is observed. The CBL heights are obtained using thermodynamic profiles, which vary from ∼ 0.4 to 2.5 km a.g.l. The formation of the cloud layers above the boundary layer generally lowers the CBL height and is responsible for its day-to-day variability. The development of the cloud beneath the boundary layer generally elevates the CBL, which is also responsible for the large day-to-day variability in the CBL. The FWBL identified using relative invariance of the thermodynamic profiles varies from ∼ 2.0 to 5.5 km, which is clearly marked by a local minimum in the refractivity gradient. During cloudy days, the CBL is found to be shallow and the surface temperature lower when compared to clear-sky days. The CBL and the lifting condensation level (LCL) heights are randomly related and are found to be at a lower height during cloudy days when compared to clear-sky days. Finally, the typical comparison between the CBL height obtained using thermodynamic profiles and backscattering profiles using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is examined.

This paper examines the role of the meteorological variable on the spread of the ongoing pandemic coronavirus disease 2019 (COVID-19) across India. COVID-19 has created an unprecedented situation for public health and brought the world to a standstill. The COVID-19 has caused more than 1,523,242 deaths out of 66,183,029 confirmed cases and around the world till the first week of December 2020. We have examined the surface temperature, relative humidity, and rainfall over five cities namely Delhi, Mumbai, Kolkata, Bengaluru, and Chennai severely affected by COVID-19. It is found that the prevailing southwest (SW) monsoon during the pandemic has acted as a natural sanitizer in limiting the spread of the virus. The day-to-day variation of the meteorological parameters and COVID-19 cases clearly demonstrate both surface temperature and relative humidity play a vital role in the indirect transport of the virus. Our analysis reveals that the majority of the COVID-19 cases fall within the surface temperature ranging from 24oC to 30oC and relative humidity ranging from 50–80%. At a given temperature, COVID-19 cases show a large dependency on the relative humidity which attributes those coastal environments were more prone to infections. Wavelet transforms coherence analysis of the daily COVID-19 cases with temperature and relative humidity reveal a significant coherence within 8 days.