Low CO2 evasion rate from the mangrove-surrounding waters of the Sundarbans

Globally, water bodies adjacent to mangroves are considered significant sources of atmospheric CO2. We directly measured the partial pressure of CO2 in water pCO2(water) and related biogeochemical parameters with high temporal resolution, covering both diel and tidal cycles, in the mangrove-surrounding waters around the northern Bay of Bengal during the post-monsoon season. Mean pCO2(water) was marginally oversaturated in two creeks (470 ± 162 µatm, mean ± SD) and undersaturated in the adjoining estuarine stations (387 ± 58 µatm) compared to atmospheric pCO2, and was considerably lower than the global average. We further estimated the pCO2(water) and buffering capacity of all possible sources of the mangrove-surrounding waters and concluded that their character as a CO2 sink or weak source is due to the predominance of marine water from the Bay of Bengal with low pCO2 and high buffering capacity. Marine water with high buffering capacity suppresses the effect of pCO2 increase within the mangrove system and lowers the CO2 evasion even in creek stations. The δ13C of dissolved inorganic carbon (DIC) in the mangrove-surrounding waters indicated that the DIC sources were a mixture of mangrove plants, pore-water, and groundwater, in addition to marine water. Finally, we showed that the CO2 evasion rate from the estuaries of the Sundarbans is much lower than the recently estimated world average. Our results demonstrate that mangrove areas having such low emissions should be considered when up-scaling the global mangrove carbon budget from regional observations

Development of Satellite Data-Based Multiple Regression Equations for the Estimation of Total Coliform and Petroleum Hydrocarbons Along South West Coast of India

Coastal waters are showing deteriorating trend in its quality. This leads to the damage of marine ecosystems and interferes in its normal use. In order to tackle this issue, it is important to know about the extent of pollution. Conventional method of water quality estimation includes analysis of water samples from various locations. This is a tiresome and costly process limiting its application to small scales and accessible sampling sites. In this paper, an attempt has been made to quickly estimate the concentration of Petroleum Hydrocarbons (PHC) and counts of Total Coliform (TC) which are important water quality parameters, along the south west coast of India. This study formulated satellite data-based multiple regression equations for determining the count of total coliform bacteria and concentration of petroleum hydrocarbons. The sea surface temperature and remote sensing reflectance values of different bands of MODIS sensor along with field values were used in the process. The developed algorithm is validated for future use. Maps are created using these equations, showing the distribution of these parameters along the coast using Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) data. Hence, the feasibility of VIIRS for determination of these parameters with the same algorithm is examined. Thus, based on the results, areas of high PHC and TC could be identified and necessary control measures could be adopted

A Roadmap for Unified Ocean Modeling and Forecasting system for INCOIS

INCOIS, being the nodal organization to provide operational oceanographic services, is actively involved in the numerical modeling of ocean circulation, waves, tsunami and storm-surge as well as regional coupled ocean-atmosphere models for the prediction of track and intensity of tropical cyclones. In order to optimise the models used in INCOIS for these activities and to make a seamless prediction system from global to regional domains, it was decided to have a revisit on the ocean modeling efforts of INCOIS. Outcome of this review as well as a proposal to develop a seamless prediction system is documented in this report. It is envisaged that this document will be used as a guideline for the future ocean modeling efforts in INCOI

Quantifying Tropical Cyclone's Effect on the Biogeochemical Processes Using Profiling Float Observations in the Bay of Bengal

Physical and biogeochemical observations from an autonomous profiling Argo float in the Bay of Bengal show significant changes in upper ocean structure during the passage of tropical cyclone (TC) Hudhud (7–14 October 2014). TC Hudhud mixed water from a depth of about 50 m into the surface layers through a combination of upwelling and turbulent mixing. Mixing was extended into the depth of nutricline, the oxycline, and the subsurface‐chlorophyll‐maximum and thus had a strong impact on the biogeochemistry of the upper ocean. Before the storm, the near‐surface layer was nutrient depleted and was thus oligotrophic with the chlorophyll‐a concentration of less than 0.15 mg/m3. Storm mixing initially increased the chlorophyll by 1.4 mg/m3, increased the surface nitrate concentration to about 6.6 μM/kg, and decreased the subsurface dissolved oxygen (30–35 m) to 31% of saturation (140 μM). These conditions were favorable for phytoplankton growth resulting in an estimated increase in primary productivity averaging 1.5 g C·m−2·day−1 over 15 days. During this bloom, chlorophyll‐a increased by 3.6 mg/m3, and dissolved oxygen increased from 111% to 123% of saturation. Similar observations during TC Vardah (6–12 December 2016) showed much less mixing. Our analysis suggests that relatively small (high) translation speed and the presence of cold (warm) core eddy leads to strong (weak) oceanic response during TC Hudhud (TC Vardah). Thus, although cyclones can cause strong biogeochemical responses in the Bay of Bengal, the strength of response depends on the properties of the storm and the prevailing upper ocean structure such as the presence of mesoscale eddie

Seasonal dynamics of phytoplankton in response to environmental variables in contrasting coastal ecosystems

Seasonal distribution of phytoplankton community and size structure was assessed in three different tropical ecosystems of the western Bay of Bengal viz. estuary (Mahanadi), lagoon (Chilika), and coastal waters (off Gopalpur) in response to ambient hydrobiology. Salinity regimes differentiated the study regions as contrasting ecosystems irrespective of seasons (pre-monsoon, monsoon, post-monsoon). Taxonomic account revealed a total no of 175, 65, and 101 phytoplankton species in the estuary, lagoon, and coastal waters, respectively. Prevalence of marine, brackish, and fresh water types in the coastal waters, lagoon, and estuary, respectively, characterized the contrasting nature of the study regions in hosting the phytoplankton community. In general, phytoplankton abundance was observed in increasing order of coastal waters > estuary > lagoon during post-monsoon and pre-monsoon, while lagoon > coastal waters > estuary during monsoon. Bacillariophyta dominated the phytoplankton community in the estuary and coastal waters during all the seasons. In contrast, the lagoon exhibited a diverse array of phytoplankton group such as cyanophyta, dinophyta, and bacillariophyta during monsoon, post-monsoon, and pre-monsoon, respectively. Over the seasons, microphytoplankton emerged as the dominant phytoplankton size class in the coastal waters. Diversely, nanophytoplankton contributed to major fraction of chlorophyll-a concentration in the estuary and lagoon. Interestingly, pre-monsoon dinophyta bloom (causative species: Noctiluca scintillans with cell density 9 × 104 cells·l−1) and monsoon bacillariophyta bloom (causative species: Asterionellopsis glacialis 5.02 × 104 cells·l−1) resulted decline in species diversity. Multivariate statistical analysis deciphered salinity as a major environmental player in determining the distribution, diversity, and composition of phytoplankton communities in the three contrasting environments. Trophic state indices signified the lagoon and estuary as hypereutrophic during all season. The coastal water was marked as highly eutrophic through trophic state index during monsoon and pre-monsoo

Tidal Circulation in the Hooghly Estuary and Adjacent Coastal Oceans

A terrain-following ocean general circulation model is implemented for simulating tidal and residual circulation patterns in the Hooghly Estuary and its adjacent coastal oceans (HECO) on the east coast of India. The model is forced with time-varying tidal levels and momentum fluxes at the eastern and southern open boundaries, and winds at the air�sea interface. Simulated tidal levels and currents are compared well with the observations. Based on model solutions, spatial patterns of semi-diurnal and diurnal tides and circulation are described. The residual circulation shows prevalence of ocean-ward along channel flow from north to south with distinct differential circulation patterns on its right and left flanks of the outer estuary. A mesoscale eddy associated with residual circulation has been occurring in the southwestern flank of the HECO, adjacent to the Digha coast. This is associated with enriched chlorophylla concentration (Chla), causing the region as the suitable place for the fishing activity. The residual currents in the left of the channel (toward the Sunderban) in the southeastern flank of the HECO are eastward and diverging in nature and are associated with reduced Chla. © 2019, Indian Society of Remote Sensing

Evaluation of the impact of high-resolution winds on the coastal waves

This study discusses the impact of high-resolution winds on the coastal waves and analyses the effectiveness of the high-resolution winds in recreating the fine-scale features along the coastal regions during the pre-monsoon season (March–May). The influence of the diurnal variation of winds on waves is studied for the Tamil Nadu coastal region using wind fields from weather research and forecast (WRF) (3 km) and European Centre for Medium-Range Weather Forecasts (ECMWF) (27.5 km). The improvement in the coastal forecast is then quantified with wave rider buoy observations. The high-resolution wind fields simulated fine-scale features like land–sea breeze events and showed good agreement with observation results. The error in the wave height and period is reduced by 8% and 46%, respectively, with the use of high-resolution forcing winds WRF over ECMWF, although the overestimation of wave energy on high frequencies due to overestimated WRF winds remains as a challenge in forecasting. The analysis also shows the importance of accurate wave forecast during a short-duration sudden wind (~12 m/s) occurrence in southern Tamil Nadu near Rameswaram during the pre-monsoon period. Low pressure forms over Tamil Nadu due to the land surface heating, resulting in a sudden increase of winds. High winds and steep waves which cause damage to the property of the coastal community near Rameswaram also were well simulated in the high-resolution forecast system with WRF winds

INCOIS-Real time Automatic Weather Station(IRAWS) dataset - Quality control and significance of height correction

The INCOIS-Real time Automatic Weather Station(IRAWS) program was started in the year 2009 and was first installed onboard ORV Sagar Nidhi. Currently, there are 36 ships carrying IRAWS setup. Apart from storing one minute observations in the log onboard the ship, hourly averaged observations are reported through INSAT satellite communication. This report briefs about the hourly dataset of IRAWS and its quality control. In this report, QC results of SST and all meteorological parameters except radiation parameters is discussed. Specific quality check was applied to wind speed (WS) and sea surface temperature (SST) observations. The WS observations measured onboard few ships had a dimensional correction and SST was observed only on few ships. As SST observations are required to compute meteorological variables like DBT, RH, WS to standard height of 10 m, level-3 dataset of AVHRR SST was utilized in place of IRAWS SST wherever the data is found to be faulty. On similar terms bias correction could not be applied to IRAWS SST with the help of AVHRR SST as the error in SST observations are due to the failure of sensor. However all those IRAWS SST observations that passed the QC check were observed to be of high quality and have a correlation coefficient of 0.5 with AVHRR SST and is significant at 95% significant level. Apart from SST and radiation observations, all other parameters observations are found out to be of good quality with 70 to 90 QC pass percentage . Apart from the details of QC check, significance of representing climate variable at a homogeneous standard height is also shown in this repor

Role of Andaman and Nicobar Islands in eddy formation along western boundary of the Bay of Bengal

Eddies along western boundary of the Bay of Bengal (WBoB) play an important role in regulating regional climate and marine productivity of the north Indian Ocean. In this paper, role of Andaman and Nicobar islands (ANIs) in the formation of eddies along the WBoB is studied using an ocean general circulation model. Our analysis shows that, in the absence of ANIs, there is a significant reduction in the total number of mesoscale eddies in this region. The impact is particularly evident for the cyclonic eddies as a reduction of ~50% can be noticed in the absence of the islands. In contrast, influence of ANIs on anticyclonic eddies is not homogeneous in the WBoB; while absence of ANIs significantly increases anticyclonic eddies in the central part of the WBoB, a decrease can be noticed in the southern part. We further show that the reduction in number of cyclonic eddies along the WBoB is primarily driven by reduced baroclinic and barotropic instabilities. This process is more conspicuous during winter (October–January) season compared to summer (June–September) and spring (February–May) seasons

Application of Singular Spectrum Analysis for Investigating Chaos in Sea Surface Temperature

The goal of this study is to explore the chaotic behavior of sea surface temperature (SST) in the Indian Ocean and in the equatorial Pacific Ocean. The SST time series is analyzed for Bay of Bengal, Arabian Sea and South Indian Ocean as well as for two extreme phenomena: El Niño and Indian Ocean Dipole (IOD). The analysis is based on Singular spectrum analysis, and singular value decomposition (SVD). Our analysis reveals that the dynamics of SST is chaotic in varying degrees in all the studied cases, since Lyapunov exponent, an indicator of chaoticity, is positive in each case. To study the degree of predictability of these SST series, we search for embedded periodic component(s) using two different approaches: Orthogonal functions extracted from the Singular spectrum analysis and Periodicity spectrum analysis based on SVD. Both the methods reveal presence of a strong periodic component(s) for the SST signals in the Arabian Sea, Bay of Bengal and South Indian Ocean, whereas no periodicity is found for El Niño and IOD. Therefore, it can be concluded that the dynamics of SST is more complex in the El Niño and IOD region compared to Bay of Bengal, Arabian Sea and South Indian Ocean; hence it is much more difficult to predict El Niño and IOD