Prakash Chauhan

Bifurcation of the East India Coastal Current east of Sri Lanka

The East India Coastal Current (EICC) flows equatorward during October–December carrying low salinity water from the Bay of Bengal en route. Using results from a high resolution ocean general circulation model, satellite altimeter data, Argo float profiles and ocean color images we show that the EICC bifurcates east of Sri Lanka. One part continues along the coast of Sri Lanka but the major part of the EICC, called here as the East Sri Lanka Jet (ESLJ) flows eastward into the Bay of Bengal. As a result of this bifurcation, there is offshore transport of chlorophyll a rich low salinity water from the coast of Sri Lanka. Altimeter data from 1993–2004 show that the bifurcation occurred every year except during the Indian Ocean Dipole (IOD) years of 1994 and 1997. The bifurcation occurs when an anticyclonic eddy that propagates westward ahead of a downwelling Rossby wave front impinges on the Sri Lanka coast. This new finding suggests that the main route of the low salinity water from the Bay of Bengal into the southeastern Arabian Sea may not be along the coast around Sri Lanka but through the Winter Monsoon Current.

Remote Sensing of suspended sediments along the Tamil Nadu coastal waters

Indian Remote Sensing satellite (IRS) 1A & 1B digital data in combination with field measurement were used to map distribution and concentration of suspended sediments along the Tamil Nadu coastal waters for monsoon and non-monsoon periods. Qualitative suspended sediment mapping was done for entire Tamil Nadu coast while quantitative studies were taken at two selected sites (eg. Tuticorin and Ennore). For qualitative mapping both monsoon (17-12-90) and non-monsoon (18-4-90) season data were analysed by level slicing technique and a qualitative scale was assigned to different sediment classes based on tonal variations. The suspended sediment concentration (SSC) samples were collected on April 15, 1992 and March 10, 1992 around Ennore and Tuticorin coastal waters respectively, synchronous to IRS-1A satellite overpass. This data was used for quantitative estimation of SSC using digital chromaticity technique. The study shows that the plumes of high suspended sediment concentration are contributed from the nearshore wetlands and river mouths and were finally dispersing towards Jaffna coast. Different classes of high to low SSC values ranging from less than 5 mg/L in offshore areas to 21 mg/L in nearshore of Tuticorin were also delineated. The dispersal pattern of the sediments on different is discussed.

Cover: Remote sensing of Trichodesmium blooms in the coastal waters off Gujarat, India using IRS‐P4 OCM

Abundant phytoplankton blooms can usually be recognized from far away due to discoloration of the sea surface. Occasionally the algae grows very fast or ‘blooms’ and accumulates into dense, visible...

Development of Chlorophyll-

An empirical chlorophyll algorithm has been developed using the coincident in situ chlorophyll-a and remote sensing reflectance Rrs measurements from global ocean waters. The basic data set used for developing the algorithm was obtained by merging the bio-optical data from the global NASA bio-Optical Marine Algorithm Data (NOMAD) (~2438 spectra from ~3000 stations) and from the waters of the northern Arabian Sea (~159 spectra) collected by the Space Applications Centre, Ahmedabad, India. The chlorophyll-a concentration ranged from 0.01 to 50.0 mg ldr m-3 for the data set used. Regression analysis between chlorophyll-a concentration and remote sensing reflectance in different bands and a combination of band ratios was performed. Algorithms using modified cubic polynomial (MCP) regression of Rrs ratios with chlorophyll-a concentration showed good estimates of chlorophyll-a in full range of 0.01 to 50.0 mg ldr m-3 of the merged data set. However, the best results were obtained by using MCP regression between maximum band ratio (MBR) of Rrs (443, 490, 510 nm)/Rrs 555 nm with chlorophyll-a concentration having an r2 of 0.96 and rms error of 0.12 for log-transformed data. The developed MBR-based algorithm named Ocean Colour Monitor (OCM)-2 chlorophyll algorithm was compared with the OC4v4 algorithm routinely used the for Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data processing. For the used data set, OC4v4 algorithm overestimated chlorophyll-a concentration for > 5.0 mg ldr m-3 and yielded an r2 of 0.90 with rms error of 0.23, when compared to the newly developed OCM-2 chlorophyll algorithm. It is proposed to use this OCM-2 chlorophyll algorithm with OCEANSAT-2 OCM data to be launched in the third quarter of the year 2008 by the Indian Space Research Organisation.

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Remote sensing-based analysis has been carried out to study the impact of “Phailin” cyclone on ocean phytoplankton distribution off Odisha coast and on the northern Bay of Bengal water. Oceansat-2 Ocean Colour Monitor (OCM) and MODISTerra sensors-derived chlorophyll images have been generated over the study area during October 2013. There has been observation of drastic change in the chlorophyll concentration of the north-western Bay of Bengal water with effect of the cyclone “Phailin,” which hit Gopalpur, Odisha coast on 12 October night at around 21:00 h IST. The postcyclone images of Oceansat-2 OCM data and retrieved chlorophyll concentration were observed to be very high, 3.0-4.0 mg/m3 in coastal water, which was around 0.5-1.0 mg/m3 during precyclone. Similarly, the postcyclone chlorophyll was around 0.80-1.50 mg/m3 in the offshore water, unusually high compared to precyclone concentration (<;0.60 mg/m3). The cyclone track of India Meteorological Department (IMD) has been superimposed on chlorophyll images and observed as proxy along the chlorophyll front with algal bloom features. There has been observation of cooling in the northern Bay of Bengal and off Odisha coast with impact of the induced upwelling, entrainment and mixing of the water column, as evident from the sea surface temperature (SST) data analysis. Interesting features such as cold core eddies and fronts have been visualized. This study is important to assess the impact of Phailin cyclone on ocean productivity on the local and basin scale and its deviation from seasonal trend as well.

Algorithm for Ocean Colour Monitor Onboard OCEANSAT-2 Satellite

In-situ chlorophyll concentration data and remote sensing reflectance (Rrs) measurements collected in six different ship campaigns in the Arabian Sea were used to evaluate the accuracy, precision, and suitability of different ocean color chlorophyll algorithms for the Arabian Sea. The bio-optical data sets represent the typical range of biooptical conditions expected in this region and are composed of 47 stations encompassing chlorophyll concentration, between 0.072 and 5.90 mg m-3, with 43 observations in case I water and 4 observations in case II water. Six empirical chlorophyll algorithms [i.e. Aiken-C, POLDER-C, OCTS-C, Morel-3, Ocean Chlorophyll-2 (OC2) and Ocean Chlorophyll-4 (OC4)] were selected for analysis on the Arabian Sea data set. Numerous statistical and graphical criterions were used to evaluate the performance of these algorithms. Among these six chlorophyll algorithms two chlorophyll algorithms (i.e. OC2 and OC4) performed well in the case I waters of the Arabian Sea. The OC2 algorithm, a modified cubic polynomial function which uses ratio of Rrs490 nm and Rrs555 nm (where, Rrs is remote sensing reflectance), performed well with r2=0.85; rms =0.15. The OC4 algorithm, a four-band (443, 490, 510, 555 nm), maximum band ratio formulation was found best on the basis of statistical analysis results with r2=0.85 and rms=0.14. Both OC2 and OC4 algorithms failed to estimate chlorophyll inTrichodesmium dominated waters. The OC2 algorithm was preferred over OC4 algorithm for routine processing of the OCM data to generate chlorophyll-a images, as it uses a band ratio of 490/555 nm and atmospheric correction is more accurate in 490 nm compared to 443 nm band, which is used by OC4 algorithm.

Remote Sensing Observations on Impact of Phailin Cyclone on Phytoplankton Distribution in Northern Bay of Bengal

The study of swell wave refraction phenomena using synthetic aperture radar (SAR) data has been found to be very useful in estimating the underwater topography (seabed structure). Near-shore water regions generate a wide range of surface signatures due to rapidly changing underwater depths, which cause waves to refract and finally align parallel to the shoreline. Another significant change, which is observed as gravity waves approach the shoreline, is that their wavelength decreases and, as the energy of the wave is constant in the absence of dissipating forces, amplitude increases. The strong correlation between the change in wavelength and the underlying topography makes it possible to estimate the bathymetry from the measured wavelength. Normally available global bathymetric maps (e.g., ETOPO-1 bathymetry toposheets) are out of date and provide bathymetry at a very coarse resolution. In this letter, swell wave refraction phenomena using Radar Imaging Satellite C-band SAR data over coastal regions of Mumbai have been studied. The wave-tracing technique has been used to derive the wavelength of swell waves in near-shore regions and analyze the wavelength change in order to retrieve underwater topography using dispersion relation with swell wave properties. This SAR-based technique can be used to derive high-resolution bathymetric maps for near-coastal regions. Also, with this technique, temporal variations in the seabed can be measured to infer geological processes.

Comparison of ocean color chlorophyll algorithms for IRS-P4 OCM sensor usingin-situ data

An artificial neural network (ANN) based chlorophyll-a algorithm was developed to estimate chlorophyll-a concentration using OCEANSAT-I Ocean Colour Monitor (OCM) satellite-data. A multi-layer perceptron (MLP) type neural network was trained using simulated reflectances (~60,000 spectra) with known chlorophyll-a concentration, corresponding to the first five spectral bands of OCM. The correlation coefficient(r2) andRMSE for the log transformed training data was found to be 0.99 and 0.07, respectively. The performance of the developed ANN-based algorithm was tested with the global SeaWiFS Bio-optical Algorithm Mini Workshop (SeaBAM) data (~919 spectra), 0.86 and 0.13 were observed asr2 andRMSE for the test data set. The algorithm was further validated with thein-situ bio-optical data collected in the northeastern Arabian Sea (~215 spectra), ther2 andRMSE were observed as 0.87 and 0.12 for this regional data set. Chlorophyll-a images were generated by applying the weight and bias matrices obtained during the training, on the normalized water leaving radiances (nLW) obtained from the OCM data after atmospheric correction. The chlorophyll-a image generated using ANN based algorithm and global Ocean Chlorophyll-4 (OC4) algorithm was compared. Chlorophyll-a estimated using both the algorithms showed a good correlation for the open ocean regions. However, in the coastal waters the ANN algorithm estimated relatively smaller concentrations, when compared to OC4 estimated chlorophyll-a.

Estimation of Coastal Bathymetry Using RISAT-1 C-Band Microwave SAR Data

Ocean Colour Monitor (OCM) payload, onboard Indian Remote Sensing Satellite (IRS)-P4, detects the water constituents from the spectrum of solar radiation backscattered from the ocean waters. The radiation received by the sensor is contaminated by the specularly reflected solar radiation from the water surface. This specularly reflected radiation, called sunglint, contains no information on the water constituents, as it has not entered into the seawater and interacted with it. The intensity and spread of sunglint is determined by the solar illumination and sensor viewing directions and the sea surface roughness caused by the wind. For the accurate estimation of oceanic constituents, it is essential to minimize the sunglint in the detected radiances (preferably below ∼2-3%). In this work, sunglint simulations were computed for the instrument specifications of OCM and the optimal sensor viewing tilt angle identified for each month for the oceans around India.

Estimation of chlorophyll-A concentration using an artificial neural network (ANN)-based algorithm with oceansat-I OCM data

In the absence of many gauging stations in the major and mighty river systems, there is a need for satellite-based observations to estimate temporal variations in the river water storage and associated water management. In this study, SARAL/AltiKa application for setting up hydraulic model (HEC-RAS) and river flow simulations over Tapi River India has been discussed. Waveform data of 40 Hz from Ka band altimeter has been used for water levels retrieval in the Tapi river. SARAL/AltiKa retrieved water levels were converted to discharge in the upstream location (track-926) using the rating curve available for the nearby gauging site and using linear spatial interpolation technique. Steady state simulations were done for various flow conditions in the upstream. Validation of river flow model was done in the downstream location (track-367) by comparing simulated and altimeter retrieved water levels (RMSE 0.67 m). Validated model was used to develop rating curve between water levels and simulated discharge for the downstream location which enables to monitor discharge variations from satellite platform in the absence of in situ observations. It has been demonstrated that SARAL/AltiKa data has potential for river flow monitoring and modeling which will feed for flood disaster forecasting, management and planning.