Spatio-temporal estimation of rainfall patterns in north and northwestern states of India between 1901 and 2015: change point detections and trend assessments

Kalpana, P.; Parthiban, S.; Gopinathan, P.; Subramani, T.; Roy, Priyadarsi D.; Gautam, Sneha; Brema, J.

doi:10.1007/s12517-020-06098-9

Cited by 11 publications

(2 citation statements)

References 33 publications

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Section: Introductionmentioning

confidence: 99%

“…The amount of water from rainfall is one of the most crucial water cycle and global water components with a significant impact on climate conditions (Copernicus Climate Change Service (C3S) 2017 ; Kalpana et al 2020 ; Gautam et al 2021a , b , c ). Many studies highlighted the possible impact of aerosol on cloud formation and related cycles (Ramanathan et al 2005 ; Ramanathan et al 2001a , b ; Kalpana et al 2020 ; Gautam et al 2021a ). Many researchers showed fluctuations in optical properties due to the impact of aerosol generated by anthropogenic activities (Chelani and Gautam 2021 ; Ackerman et al 2000 ; Ramanathan et al 2001a , b ; Kaufman et al 2005 ).…”

Section: Introductionmentioning

confidence: 99%

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Impact Assessment of Aerosol Optical Depth on Rainfall in Indian Rural Areas

et al. 2022

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Aerosol significantly influences the life cycle of clouds and their formation. Many studies reported worldwide on anthropogenic aerosols and their impact on clouds and their optical properties. Atmospheric remote sensing provides the best way to estimate indirectly air quality surveillance and management in megacities of developing countries like India where many cities have elevated concentration profiles of air pollutants with inadequate coverage of spatial and temporal monitoring. The results of the study highlighted the impact on rainfall patterns due to aerosol optical depth (AOD) and fine particulate matter (PM2.5) for a total of 7 years (2015–2021) over five different Indian rural sites by using MODerate Resolution Imaging Spectroradiometer (MODIS). The AOD (550 nm) and PM2.5 were retrieved from the MODIS sensor Terra satellites and the MEERA 2 model, respectively. Also, we have analyzed in this study the relationship of AOD (550 nm) with PM2.5 and meteorological variables (temperature relative humidity and precipitation) over Indian rural sites during 2015–2021. The maximum concentration of AOD (550 nm) has been measured for Gandhi college (2.94 ± 0.44) and minimum for ARM college (0.01 ± 0.28), while the maximum concentration of PM2.5 has been measured for ARM College 296.37 (µg m −3 ) and minimum for Karunya University 0.02 (µg m −3 ). Also, the relation between AOD (550 nm) with total precipitation is measured positively for all locations except Gandhi college whereby PM2.5 associated with total precipitation is measured negatively for all locations except ARM college. Finally, the relationship between PM2.5 and AOD (550 nm) is measured positively in all selected locations except Singhad Institute. The maximum rainfall has been observed for monsoon months (June–August) and post-monsoon months (October) for all locations during the study period. The maximum total precipitation has been measured for Singhad 11,674.7 (mm) and the minimum for Karunya University 4563.41 (mm). However, the results of the study indicated that there was no direct trend observed in AOD in five different selected rural Indian sites.

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