India experienced two extreme summer monsoons, 2007 (active monsoon) and 2009 (weak monsoon) in the recent past decade. The characteristic features of these two contrasting Indian summer monsoons have been presented. The country received 11.8% excess and 17.1% deficit rainfall during 2007 and 2009 monsoon seasons, respectively. These large deviations in rainfall encourage us to study the influence of meteorological factors on rainfall activity. The distributions of rainfall over India, latent heat flux, wind, Vertically Integrated Moisture Transport (VIMT), and Vertically Integrated Moisture Divergence (VIMD) values in the layer 1000–300 hPa for the domain, 0$^{\circ}$–40$^{\circ}$N, 40$^{\circ}$–120$^{\circ}$E in the two contrasting monsoon seasons are evaluated. In active monsoon, (i) predominant low level southwesterly flow over the Arabian sea and deflection of winds over the Bay of Bengal, strengthening of the tropical easterly jet stream, wide area extent of easterlies in the upper troposphere, the maximum strength of easterlies in the upper troposphere (150 hPa) is observed over the area around 10$^{\circ}$–15$^{\circ}$N and 70$^{\circ}$–75$^{\circ}$E; (ii) position of subtropical ridge is more northward, i.e., 32$^{\circ}$N; (iii) a predominant moisture transport in the layer 1000–300 hPa from Southern Hemisphere, Arabian Sea and the Bay of Bengal to the Indian mainland, westward/northward transport of moisture and area coverage of larger quantum of moisture flux is seen; and (iv) India experienced more number of mesoscale systems. The reverse is true for weak monsoon. Positive (neutral) Indian Ocean Dipole (IOD) and La-Nina (El-Nino) conditions lead to active (poor) summer monsoon conditions over India in 2007 (2009) year.

$\bf{Highlights}$

$\bullet$ The inter-annual variations in summer monsoon rainfall over India exhibited two extreme summer monsoons 2007 (active) and 2009 (weak) during recent past decade, 2001–2010.

$\bullet$ Dominant lower and upper tropospheric circulations over monsoon region are evident in the active monsoon.

$\bullet$ The incursion of subtropical westerlies in the mid as well as upper troposphere inhibits the rainfall activity over India in the weak monsoon season.

$\bullet$ A predominant moisture transport from the surrounding oceanic area as well as Southern Hemisphere to Indian mainland is seen in the active monsoon.

$\bullet$ The moisture divergence over the surrounding oceanic area is high in active monsoon.

A numerical hydrodynamic modelling study has been implemented based on the seasonal salinity variations in a networked system (comprising creek and an estuary), which is the first of its kind attempted for the Indian subcontinent. Salinity variations in the estuaries and creeks exhibited unique characteristics caused by the combined effects of various external forces such as tidal flow, freshwater runoff, wind and geometric effects. Precise understanding of dynamical conditions in estuaries and creeks is necessary to address pertinent issues related to oceanography, water quality and ecosystem dynamics. In a broader perspective, it is noted that due to the influence of winds during monsoon, the salinity fields in the estuarine environment are not in a steady state. However, in creeks, tidal Cow plays a major role in altering the salinity structure apart from runoff. The results from this study decipher the fact that the networked system was vertically homogenous during all seasons. However, a horizontal salinity gradient was observed in the system depending on the river runoff. The flushing time for the Ulhas estuary was about 1.5 and 2.57 days during the monsoon and non-monsoon seasons, respectively. Similarly, for the Thane creek, tide-driven flushing time was about 3.68 days. The low flushing time during the wet season provides a suitable dynamic environment for effluent discharge in the mid and upstream reaches of the estuary, wherein the freshwater influx is higher. On the contrary, during the dry season over this region, the low runoff and the highest flushing times can increase the pollution or can support the growth of phytoplankton biomass accumulation.

Assessment of consistency in seasonal variability of CO$_2$ Cuxes between GOSAT-IM, NASA-GEOS, and NOAA-CT databases was carried out over major biogeographic regions across the globe. A blended data product was composited through a linear least square error optimization procedure from the weighted mean of the three datasets. The blended-product is in closer agreement with GOSAT-IM followed by NOAA-CT and NASA-GEOS for most parts of the globe; however, the blended-product was found to be closer to NASA-GEOS for the Arabian Sea and India. Comparison with limited in-situ FLUXNET observations shows NASA-GEOS has a better agreement for India, and NOAA-CT is better for Europe, Africa, and the US. The mean climatology of these datasets exhibits spatially distinct and coherent patterns of positive and negative Cuxes that characterize the source and sink of atmospheric CO$_2$ across the globe. The tropical oceanic and terrestrial regions and the southern circumpolar oceans have been playing as the sources, whereas the temperate oceanic and terrestrial ecosystems and the Eurasian Boreal are the sinks. The seasonal cycles of the Cuxes are intense over the northern temperate and boreal terrestrial and oceanic regions; wherein annual amplitudes dominate over the semi-annual amplitudes. The mean climatology varies in the range of -6 to 6 gC m$^{-2}$ month$^{-1}$ for oceans as well as continents; however, amplitudes of the seasonal cycle are one order higher for the continents (${\ge}$20 gC m$^{-2}$ month$^{-1}$) than that of the oceans (${\le}$1 gC m$^{-2}$ month$^{-1}$). The tropical desert tracts, especially Sahara and Thar, and the equatorial oceans show minima in their climatological mean with the reduced seasonal cycle. All these data, however, depict a broad agreement in their seasonal cycle and mean climatology; they exhibit significant differences in their annual budgets, amplitude, and phases of annual and semi-annual harmonics.

Extraction of shorelines using satellite imagery is an effective method because customary digitization is a longand hectic process. This study focuses on extracting and detecting shoreline changes from Landsat-8 imageries ofthe Visakhapatnam–Kakinada coast along the east coast of India using an object-based approach. An object-based approach for the automatic detection of coastline from Landsat imagery using the Feature Extraction Workflow by Maximum Likelihood is implemented by the maximum classification method (MLC). The resulting vector polyline is smoothened for every 100 m using ArcGIS software. Delineation of multi-temporal satellite images was performed by visual interpretation from 2014 to 2019 to detect the shoreline changes. Different available techniques and methods are employed to observe shoreline changes. In addition to this, the shoreline information simulated by satellite remote sensing is in fair agreement with RTK GPS observations. The observed and remote sensing shoreline changes help to identify the areas of accretion and eroding zones overthe long term. During this study, erosion and deposition changes were observed along RK beach, Rushikonda beach, Uppada beach, and Kakinada beach. The spatial variation rates were calculated using the statistical methods of the Digital Shoreline Analysis System (DSAS) during specific periods. The maximum observed shoreline accretion and erosion rates at Kakinada are 5.3 and –4.35 m/year indicates slight accretion. The maximum observed accretion and erosion rates at Uppada beach are 3.8 and –6.78 m/year, respectively indicatingerosion. Similarly, at RK Beach the maximum observed shoreline accretion and erosion rates are 3.68 and –3.68 m/year, respectively indicating the beach is in a stable state. At Rushikonda beach, the maximum observed shoreline accretion and erosion rates are 2.24 and –3.04 m/year, respectively indicating erosion.