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dc.contributor.authorKumar,Harshbardhan
dc.contributor.authorTiwari, S.
dc.date.accessioned2025-09-30
dc.date.accessioned2025-09-30T04:44:05Z
dc.date.available2025-08-05
dc.date.available2025-09-30T04:44:05Z
dc.date.issued2025
dc.identifier.citationAdvances in Space Research,vol.76(5);2025; pp: 2608-2625
dc.identifier.issn1879-1948
dc.identifier.otherhttps://www.sciencedirect.com/science/article/pii/S0273117725006362
dc.identifier.urihttps://doi.org/10.1016/j.asr.2025.06.024.
dc.identifier.urihttp://drs.nio.res.in/drs/handle/2264/9506
dc.descriptionIF2024= 2.8
dc.description.abstractIn this study, we analysed nearly two decades (2001�2021) of satellite borne multi-sensor low-level cloud fraction (LCF) datasets and reanalysis meteorological parameters over the Indian Ocean, to examine spatial�temporal variations, trends and susceptibility to influencing factors. Results show higher LCF over the Arabian Sea (AS) and Southern Indian Ocean (SIO), while lower levels are observed over the Bay of Bengal (BoB). Zonal variations in low-level cloud reveal a deeper extension (up to 3 km) over southern region compared to a shallower depth (below 2 km) over northern portion. Seasonal pattern exhibits maxima in LCF during the monsoon season (JJAS), while minima during the pre-monsoon (MAM) and post-monsoon (DJF) seasons across the domain. Trend analysis indicates a significant enhancement in LCF over the Northern Indian Ocean (NIO) (up to 0.003/year), except for a decreasing trend for International Satellite Cloud Climatology Project (ISCCP) dataset. Furthermore, cloud-controlling factor analysis reveals a negative response of sea surface temperature (SST) and latent heat flux (LHF) to the regressed LCF records, while the other selected predictors show a positive response. However, the magnitude and statistical significance of the estimated susceptibility coefficients vary depending on the regressed LCF datasets. Overall, our results underscores substantial variability in LCF responses to meteorological drivers, particularly over the BoB. It cautions against broad generalizations due to methodological differences across LCF datasets and emphasizes the need for future research to focus on key influencing factors to improve predictions of basin-scale low-cloud feedbacks.
dc.languageen
dc.publisherElsevier
dc.relation.isreferencedbySCI
dc.rightsOnly the author version of the copright reserved papers uploaded. Contact drs@nio.org for any complaints regarding copyright violations
dc.titleMulti-sensor analysis of low-level cloudiness and its controlling factors over the Indian Ocean
dc.typeJournal Article
dc.affiliation.authorCSIR-National Institute of Oceanography, Dona Paula, Goa, India


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