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Global warming is the average temperature of the earth's surface which has increased over the past century by about 0.6 °C. This rising temperature may vary precipitation patterns, more frequent droughts, rise in sea level and intense storms and can be termed as climate change. To understand uneven precipitation pattern for monsoon dominated region like India, there is a need to study cloud processes at high resolution with the help of cloud microphysical properties. Ocean is the major and primary source of cloud whereas local water bodies and re-evaporated water over land could be secondary source. Paper focuses over ocean (Arabian Sea) as well as over land (central India) to know the effect of global warming on cloud microphysical properties such as cloud effective radius and cloud liquid water content. Warming signal in terms of rise in sea surface temperature (0.1 °C/decade) as well as rise in surface air temperature (0.05 °C/decade) are observed over Arabian Sea and central India respectively. Satellite data show an increasing (0.5 µm/decade) trend in cloud effective radius over Arabian Sea, whereas it decreases (− 0.1 µm/decade) over central India. Increasing trend in temperature and cloud properties is may be due to warming signal. Aerosol concentration over ocean and land further helped to understand cloud processes with cloud microphysical properties. Paper will focus on the effect of warming signal in cloud properties over Arabian Sea and central India. This type of high resolution study may help to understand cloud processes which in turn may help to understand precipitation patterns. [ABSTRACT FROM AUTHOR]

Joseph, D.; Liya, V.B.; Rojith, G.; Zacharia, P.U., and Grinson, G., 2019. Time series analysis of CMIP5 model and observed sea surface temperature anomaly along Indian coastal zones. In: Jithendran, K.P.; Saraswathy, R.; Balasubramanian, C.P.; Kumaraguru Vasagam, K.P.; Jayasankar, V.; Raghavan, R.; Alavandi, S.V., and Vijayan, K.K. (eds.), BRAQCON 2019: World Brackishwater Aquaculture Conference. Journal of Coastal Research, Special Issue No. 86, pp. 239–247. Coconut Creek (Florida), ISSN 0749-0208. Analysis of the time series Sea Surface Temperature (SST) variations is a key element in understanding the climate change impacts on the phenology, trophodynamics, distribution, and catch of commercial marine fish species. As SST projections are mostly model dependent, the discrepancy in the model and observed values needs to be elucidated so as to derive accurate interpretations and conclusions. In this paper, the decadal and seasonal variations of SST anomaly over the four coastal zones of India were analysed. The selected period of the study is from 1968 to 2017 and the data obtained from the International Comprehensive Ocean Atmosphere Data Sets (ICOADS) and Max Planck Institute Earth System Model (MPI-ESM) was used. The Coupled Model Intercomparison Project 5 (CMIP5) model data were used for comparison with the observed value. The linear trend of observed and modelled values was inferred using the least square method for four seasons. The seasonal variation of SST anomaly of observed data in four coastal zones of India reveals that Northeast zone exhibits the least trend of warming in all seasons, whereas Northwest zone shows the highest trend of warming. SST anomaly of the first decade in all zones exhibited negative values in all seasons, while last decade shows positive value, indicating warming trend. In other decades, no uniform SST trend for all seasons was observed. However, the Northeast zone is exceptional with negative anomaly during all decades. The warming trend was observed in all coasts for both model and observed values. The model and observed SST anomaly follows an almost similar trend, but with noticeable differences in values among both. Owing to the differences in the model and observed values, it could be emphasised that error corrections needs to be applied in futuristic SST projections and related studies of Indian fisheries. [ABSTRACT FROM AUTHOR]

The Indian Ocean Dipole (IOD) can affect the El Niño-Southern Oscillation (ENSO) state of the following year, in addition to the well-known preconditioning by equatorial Pacific Warm Water Volume (WWV), as suggested by a study based on observations over the recent satellite era (1981-2009). The present paper explores the interdecadal robustness of this result over the 1872-2008 period. To this end, we develop a robust IOD index, which well exploits sparse historical observations in the tropical Indian Ocean, and an efficient proxy of WWV interannual variations based on the temporal integral of Pacific zonal wind stress (of a historical atmospheric reanalysis). A linear regression hindcast model based on these two indices in boreal fall explains 50 % of ENSO peak variance 14 months later, with significant contributions from both the IOD and WWV over most of the historical period and a similar skill for El Niño and La Niña events. Our results further reveal that, when combined with WWV, the IOD index provides a larger ENSO hindcast skill improvement than the Indian Ocean basin-wide mode, the Indian Monsoon or ENSO itself. Based on these results, we propose a revised scheme of Indo-Pacific interactions. In this scheme, the IOD-ENSO interactions favour a biennial timescale and interact with the slower recharge-discharge cycle intrinsic to the Pacific Ocean. [ABSTRACT FROM AUTHOR]

The summer monsoon rainfall affects most of the population of the Indian subcontinent. A slight variation of strength and spatial distribution in monsoon rains has huge societal impacts. So understanding the significance of its variability and the factors that control this variability is an imperative task. The Indian monsoon (also regarded as a global phenomenon) varies with the global climatic components like geopotential height, sea surface temperature, outgoing long-wave radiation and mean sea level pressure. The paper presents a statistical analysis of rainfall (over India) and climatic components (over the Arabian Peninsula) and the relationship between them. The period (1979–2013) shows a decrease in monsoon rainfall over the country. During this period, there was an increase in the tropospheric temperature over the Arabian Peninsula. Rainfall showed a direct relationship with the tropospheric temperature and thickness that gets stronger during the period (1979–2013). Except for the northeastern region of India, the rest showed a strong positive correlation with the middle and upper tropospheric temperature over the Arabian Peninsula while the lower tropospheric temperature showed a weak relationship. However, this correlation gets weakened during the El Nino and La Nina years. The findings will be helpful to enhance the Indian rainfall variation and the climatic factors responsible for this variation. [ABSTRACT FROM AUTHOR]