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Phytoplankton community response to extreme climate variability has an important effect on the regional marine ecosystem. The 2015–2016 El Niño event has been the strongest El Niño event on record of the century, which has a high chance of impacting the most productive ecological zone like the Arabian Sea. In this study, we investigated the influence of the 2015–2016 El Niño on the seasonal pattern and its impact on the phytoplankton size class (PSC) distribution in the Arabian Sea based on monthly satellite PSC observations and physical observations from various sources from 2003 to 2019. Results showed that the 2015–2016 El Niño event influenced the physical drivers and consequently weakened the monsoonal pattern that led to the enhancement or inhibition of specific PSC in the Arabian Sea. During the 2015 summer monsoon, the intensity of summer upwelling was weaker than normal, which caused a reduction in the abundance of microplankton to ~8% and an increase in the abundance of picoplankton to ~12%. Similarly, during the 2016 winter monsoon, the weakening of convective mixing and the formation of warm core eddy led to a reduction in the abundance of microplankton to ~6% and an increase in the abundance of picoplankton to ~9%. However, the nanoplankton distribution was observed stable with no significant response to the extreme physical condition due to its ubiquitous nature. The effect of the 2015–2016 El Niño event altered the physical conditions and associated specific PSC distribution in the Arabian Sea. Notably, the distinct response of each PSC to the changing climate and their environmental adaptation was identified in this study. Our results indicated that the phytoplankton community structure and associated marine ecosystem are sensitive to the effects of climate change. [ABSTRACT FROM AUTHOR]

Short-term events like tropical cyclones often have a strong impact on the upper ocean, causing transient changes in the physical and chemical properties of the sea. These changes could potentially affect the distribution pattern of the phytoplankton community. The present study aims to investigate the impact of the distribution of phytoplankton size classes (PSCs) caused by the tropical cyclonic event Ockhi in the Arabian Sea (AS) in 2017. Multiple datasets, including satellite remote sensing and reanalysis data, were utilized to observe the biogeochemical variability and the corresponding changes in PSCs distribution caused by the Ockhi cyclone event. One of the predominant issues in using satellite remote sensing data is the loss of data due to overcast conditions, which was resolved by reconstructing the chl-a and SST using an empirical orthogonal function. The results show a short-term shift in the PSCs pattern from the pico and nano-rich region to the micro-dominated environment in the cyclone passage region during the post-cyclone period. When comparing the results with the physical and biochemical parameters, it was found that the cyclonic event triggered the deep-seated nutrients to the surface, which promoted favourable conditions for microorganisms to proliferate for a short span in the cyclone passage region. The overall study highlights the impact of the Ockhi cyclone on biogeochemical changes and corresponding shifts in the phytoplankton size distribution along the cyclone path. [ABSTRACT FROM AUTHOR]

The present study has been carried out to analyze the seasonal variation of the Urban Heat and Cool Island over the nine developing cities of India. The magnitude of urban heat/cool island and vegetation gradient (∆NDVI) were measured from the daytime satellite datasets. Results of this study show that during the pre-monsoon (March to May) season, the maximum magnitude of the Surface Urban Heat Island (SUHI) was experienced over Kolhapur city, whereas, in the winter, the highest intensity of SUHI was noticed over Pune city. Subsequently, outcomes also depict that the changes in ∆NDVI restrain the pre-monsoon means and the seasonal alterations in SUHI magnitude. However, during the winter (November to February) season, it is controlled by the temperature–vegetation conditions of the rural areas. For pre-monsoon and seasonal changes in SUHI, with the aid of ∆NDVI and the surface temperature of the urban area, regression equations were fitted for pre-monsoon and seasonal changes in SUHI, which explains nearly 90% of SUHI variation. Similarly, the variation of SUHI has been modeled for winter, which elucidates up to 84% of SUHI discrepancy. The study reveals that, on a seasonal scale, a decrement of 0.1 in seasonal ∆NDVI leads to an increase in the seasonal intensity of SUHI by 1.74 °C, which is quite a significant augmentation. [ABSTRACT FROM AUTHOR]

Haze, an atmospheric condition that degrades many remote sensing images, is part of the atmospheric correction. In this study, a new method is proposed to reduce the effect of haze on hyperspectral imagery over inland water bodies using the spectral unmixing approach. If haze is present in the image, spectral unmixing can result an end member corresponding to haze, and a corresponding haze abundance map (HAM) can be generated. The spectrally and spatially varying haze contribution to reflectance spectra, referred to as hyperspectral haze reflectance cube, is estimated using the HAM and the reflectance spectra extracted from haze affected areas of the hyperspectral image. Actual reflectance from water bodies can thus be obtained by subtracting this cube from the observed hyperspectral reflectance cube. Two hyperspectral images acquired with Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor over the Ujani reservoir of Maharashtra, India, are used to develop and validate the proposed hyperspectral haze correction method. We demonstrate the successful removal of haze effects by validating with field measured reflectance spectra, visual, spectral and statistical interpretation of the haze corrected AVIRIS-NG imagery. The proposed methodology can be readily implemented for existing and future hyperspectral imagery from NASA's Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission. [ABSTRACT FROM AUTHOR]