Ocean Colour Monitor Research Articles

Absolute vicarious calibration of OCM2 and AWiFS sensors using a reflectance-based method over land sites in the Rann of Kutch, Gujarat

A study was carried out to estimate vicarious calibration coefficients for the OCM2 (Ocean Color Monitor) sensor onboard Oceansat-2 and also the AWiFS (Advanced Wide Field Sensor) sensor onboard Resourcesat-1 using reflectance measurements over three land sites – Dhrangadhra, Desalpar, and Bhachau – in the Rann of Kutch, Gujarat, India, on four dates (17 October 2010, 25 and 29 April 2011, and 1 May 2011). Hyperspectral field reflectance measurements of the study sites (of extent ˜2 km × 2 km) in the wavelength range 325–2500 nm, along with measurements of atmospheric parameters (aerosol optical depth (AOD), water vapour, ozone) and sensor spectral response functions, were input to the 6S atmosphere correction code to compute top-of-atmosphere (TOA) at-satellite radiance in the eight visible and near infrared (NIR) bands of OCM2 and the four visible, NIR, and shortwave infrared (SWIR) bands of the AWiFS sensor. The uncertainty in vicarious calibration coefficients due to measured spatial variability of field reflectance, aerosol optical thickness (AOT), water vapour, and ozone, was also computed for the OCM2 sensor for three dates (25 and 29 April 2011, 1 May 2011). The effect of surface anisotropy on TOA radiance was studied using a 15 day Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) product covering the study sites. The results show that there is an indication of change in calibration coefficients in OCM2, for band 2 (25 April Desalpar data), bands 2 and 5 (29 April Desalpar data), and bands 2–5 and 7 in Bhachau (1 May data), all at the 1σ level. For these bands, in the inverse mode, the 6S corrected surface reflectance was closer to field surface reflectance when estimated at-sensor radiances were used as input to the code. For AWiFS, there was no evidence of change in calibration coefficients of all four bands at the 1σ level. It was found that site spatial variability was a critical factor in estimating change in sensor calibration coefficients and influencing uncertainty in TOA radiance for all three sites.

Validation of OCM-2 sensor performance in retrieving chlorophyll and TSM along the southwest Bay of Bengal coast

The Chlorophyll and Total Suspended Matter (TSM) data retrieved from Ocean Colour Monitor (OCM-2) onboard Oceansat-2 were tested for the accuracy using in-situ measurements made along the southwest Bay of Bengal coast during cruises and monthly samplings synchronized with satellite overpass from January 2010 to May 2011. The observed range of in-situ chlorophyll a and TSM concentrations were 0.10–4.60 μgl − 1 and 12.70–34.56 mgl − 1 respectively, while OCM-2 derived chlorophyll a and TSM concentration ranged from 0.324 to 1.552 μgl − 1 and 3.537 to 32.11 mgl − 1, respectively. The in-situ dataset was grouped into low (0.1–0.5 μgl − 1), moderate (0.51–1.0 μgl − 1) and high (>1 μgl − 1) chlorophyll concentration and low (12.7–17.81 mgl − 1), moderate (18.1–29.0 mgl − 1) and high (>30 mgl − 1) TSM concentration for evaluating the performance of algorithms against different ranges of field measurements. The OCM-2 chlorophyll retrieval algorithm (OC4V4) showed a systematic and large overestimation of low chlorophyll values with r 2 = 0.607, root mean square error (RMSE) = 0.33 μgl − 1 and mean normalized bias (MNB) = 1.57 and consistent underestimation of high chlorophyll values with r 2 = 0.497, RMSE = 1.486 μgl − 1 and MNB = 0.52 especially at nearshore waters due to the interference of suspended matter and coloured dissolved organic matter. However, moderate range of chlorophyll values showed better performance of OC4V4 algorithm in chlorophyll retrieval with r 2 = 0.676, RMSE = 0.254 μgl − 1 and MNB = 0.09 when compared to low and high chlorophyll values. The TSM algorithm (modified algorithm of Tassan 1994) showed large underestimation in TSM retrievals and this was proved by the statistical results which shown maximum r 2 = 0.551 for low TSM values with less RMSE = 0.909 mgl − 1 and MNB = 0.616 error compared to moderate and high TSM values. OCM-2 retrieved TSM values were not well correlated with in-situ TSM concentration and constantly underestimates four times lesser than the in-situ measurements especially near the coast when TSM concentration was measured high. Though there was significant correlation exists between OCM-2 retrieved chlorophyll and TSM with in-situ measurements, the empirical algorithms employed did not give logical retrieval of both chlorophyll and TSM for the southwest Bay of Bengal (BoB). Thus, the present study revealed that the OCM-2 chlorophyll and TSM retrieval algorithms need to be tested further with extensive in-situ dataset around BoB to improve the regional algorithms for accurate measurements of chlorophyll and TSM in this region.

Study of Chlorophyll-a Enhancement Over the Northern Arabian Sea

Northern Arabian Sea is one of the most biologically rich region in the North Indian ocean during winter season. In the present study I wish to investigate the the dynamics behind the enrichment of Chlorophyll-a at the above region using multi satellite observations. Ocean Color Monitor (OCM) imageries are used to identify these areas along the west coast of India during February 2000 & 2001 and the mechanisms that can upwell nutrients to sustain the bloom are investigated using sea surface temperature and winds. The variability of Ekman pumping velocity along the northeast Arabian sea is 0.5 - 3.0x10 -6 m/s and the Ekman depth is 25 - 55m. Sea surface temperature was 1 0 C cooler in 2001 winter. This increased cooling resulted in more intense convection and vertical mixing.

Detection of Fronts from Ocean Colour Monitor Images Using Entropic Technique: A Case Study of Meso- and Micro-Scale Chlorophyll Mapping in Bay of Bengal, India

This paper discusses a robust technique using entropy-based detection for delineating edges in ocean colour images. The detection process relies on Jhensen-Shannon divergence based image segmentation, which has been found to be the most suitable for noisy ocean colour images. In the attempted technique, partial removal of the noise in the images is performed and the edges are detected using entropic method. In our approach, Jhensen-Shannon divergence for the images is calculated, and the divergence image is arrived at after applying an appropriate threshold and filter to estimate the gradients. An attempted case study on retrieving chlorophyll front edges using this technique indicates that entropic method is far superior to conventional edge-enhancement tools, in terms of its insensitivity to impulsive noises and, capability in detecting meso- and micro-scale changes. This procedure would largely decrease the ambiguities associated with the ocean colour edges and hence has promising application potential in targeting fishing zones, sediment dispersion modeling and climate related studies.

Review on Study of Lake Water Using Multi Sensor Remote Sensing Data

In this paper multi sensor satellite data i.e. IRS LISS III or Landsat TM/ETM+ or OCEANSAT1(IRS-P4) consisting of an Ocean Color Monitoring operating in eight spectral band data are used for extracting information useful to hydrological projects such as monitoring the water quality of lakes. Changes of the area extent of the lakes are estimated from the multitemporal satellite images. Surface water temperature patterns of the lakes are mapped and anomalies are identified. Emphasis is given on the investigation of capabilities of IRS LISS III or Landsat TM/ETM+ or OCEANSAT-1(IRS-P4) data in monitoring water quality of lakes. A classification scheme regarding various water quality parameters (Secchi depth, Turbitidity, Chlorophylle –α and Total Total phosphorus) is created based on combinations of different bands.

Spectral Models for Improving Atmospheric Correction Results in Complex Oceanic Waters around India

Atmospheric correction over turbid and productive waters continues to be problematic and often results in excessive errors in retrieved water-leaving radiance and bio-geo-physical products. This may be likely due to overestimation of La + Lra (atmospheric signal due to aerosol and Rayleigh scattering) in the visible and thus reduction in Lw which appears as an elevated pigment concentration. Spectral models for reconstructing the atmospherically distorted data are developed and their results are thoroughly validated with in-situ data from a wide range of waters. Good agreement was found between the retrieved products and in-situ data. Our results indicate that the new spectral models have the potential to improve the accuracy of ocean colour retrievals in optically complex waters, and can become an important part of the processing of data from ocean colour sensors (e.g., Ocean colour monitor OCM2) with only two near-infrared bands (i.e., 765 and 865 nm).

Spatiotemporal Spectral Variations of AOT in India’s EEZ over Arabian Sea: Validation of OCM-II

We report the results of sun-photometric measurements of Aerosol Optical Thickness (AOT) in India’s Exclusive Economic Zone (EEZ) over the Arabian Sea along with synchronous Ocean Color Monitor (OCM-II) derived AOT estimates during December 12, 2009–January 10, 2010. Relatively higher values of Angstrom exponent (α) around 1.2 near coast and 0.2–0.8 in the India’s EEZ, observed during the cruise period, indicate the presence of smaller particles near the coast due to anthropogenic activities; and larger particles in the India’s EEZ due to advection of pollutants from Indian subcontinent via long-range transport. Results related to α and its derivative reveal four different aerosol types (urban-industrial, desert-dust, clean-marine, and mixed-type) with varying fraction during the study period. Surface radiative forcing due to aerosols is found to be 20 W/m2 over India’s EEZ. OCM-derived AOTs showed good corroboration with in situ measurements with a correlation coefficient of about 0.95. A reasonably good correlation was also observed between AOT and wind speed (R = 0.6); AOT and relative humidity (R = 0.58). The concurrent MODIS AOT data also agree well with those observed by the OCEANSAT (OCM-II) satellite during the campaign period.

Observation of Oceanic Eddy in the Northeastern Arabian Sea Using Multisensor Remote Sensing Data

An oceanic eddy of size about 150 kilometer diameter observed in the northeastern Arabian Sea using remote sensing satellite sensors; IRS-P4 OCM, NOAA-AVHRR and NASA Quickscat Scatterometer data. The eddy was detected in the 2nd week of February in Indian Remote Sensing satellite (IRS-P4) Ocean Color Monitor (OCM) sensor retrieved chlorophyll image on 10th February 2002, between latitude 16°90′–18°50′N and longitude 66°05′–67°60′E. The chlorophyll concentration was higher in the central part of eddy (~1.5 mg/m3) than the peripheral water (~0.8 mg/m3). The eddy lasted till 10th March 2002. NOAA-AVHRR sea surface temperature (SST) images generated during 15th February-15th March 2002. The SST in the eddy’s center (~23°C) was lesser than the surrounding water (~24.5°C). The eddy was of cold core type with the warmer water in periphery. Quickscat Scatterometer retrieved wind speed was 8–10 m/sec. The eddy movement observed southeast to southwest direction and might helped in churning. The eddy seemed evident due to convective processes in water column. The processes like detrainment and entrainment play role in bringing up the cooler water and the bottom nutrient to surface and hence the algal blooming. This type of cold core/anti-cyclonic eddy is likely to occur during late winter/spring as a result of the prevailing climatic conditions.

Primary productivity and nitrogen fixation by Trichodesmium spp. in the Arabian Sea

Trichodesmium was studied with the purpose of understanding its distribution, organic production and nitrogen fixation in the Arabian Sea. Out of the 143 stations sampled, a total of 93 stations showed the presence of Trichodesmium filaments. Two species of Trichodesmium namely, T. thiebautii and T. erythraeum were found. These were distributed on the basis of the physico-chemical conditions of the Arabian Sea. This was the first time that we managed to detect and record the presence of Trichodesmium thiebautii bloom in the Arabian Sea at depths as deep as 60–70m. Total counts of Trichodesmium varied between 0 and 400737 filamentsL−1. T. thiebautii developed in offshore waters during the fall intermonsoon, when the water temperature was around 28°C and nitrate content was as low as 0.34μM. After the northeast monsoon, Trichodesmium erythraeum developed in the offshore area and then spread to coastal waters. Both species of Trichodesmium together produced a total of 0.263TgCyear−1 and fixed a total of 0.2976TgNyear−1 in the Arabian Sea. The study revealed that Trichodesmium was a major contributor to the organic matter productivity of the Arabian Sea during the period from November to April. The seasonality of the blooms of Trichodesmium is discussed with the help of Ocean Color Monitoring (OCM) data and biogeochemical implication of these findings in the Arabian Sea.

Atmospheric Correction and Vicarious Calibration of Oceansat-1 Ocean Color Monitor (OCM) Data in Coastal Case 2 Waters

The Ocean Color Monitor (OCM) provides radiance measurements in eight visible and near-infrared bands, similar to the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) but with higher spatial resolution. For small- to moderate-sized coastal lakes and estuaries, where the 1 × 1 km spatial resolution of SeaWiFS is inadequate, the OCM provides a good alternative because of its higher spatial resolution (240 × 360 m) and an exact repeat coverage of every two days. This paper describes a detailed step-by-step atmospheric correction procedure for OCM data applicable to coastal Case 2 waters. This development was necessary as accurate results could not be obtained for our Case 2 water study area in coastal Louisiana with OCM data by using existing atmospheric correction software packages. In addition, since OCM-retrieved radiances were abnormally low in the blue wavelength region, a vicarious calibration procedure was developed. The results of our combined vicarious calibration and atmospheric correction procedure for OCM data were compared with the results from the SeaWiFS Data Analysis System (SeaDAS) software package outputs for SeaWiFS and OCM data. For Case 1 waters, our results matched closely with SeaDAS results. For Case 2 waters, our results demonstrated closure with in situ radiometric measurements, while SeaDAS produced negative normalized water leaving radiance (nLw) and remote sensing reflectance (Rrs). In summary, our procedure resulted in valid nLw and Rrs values for Case 2 waters using OCM data, providing a reliable method for retrieving useful nLw and Rrs values which can be used to develop ocean color algorithms for in-water substances (e.g., pigments, suspended sediments, chromophoric dissolved organic matter, etc.) at relatively high spatial resolution in regions where other software packages and sensors such as SeaWiFS and Moderate Resolution Imaging Spectrometer (MODIS) have proven unsuccessful. The method described here can be applied to other sensors such as OCM-2 or other Case 2 water areas.

Regionally tuned algorithm to study the seasonal variation of suspended sediment concentration using IRS-P4 Ocean Colour Monitor data

Satellite data product validation and algorithm development activities both require the substantial accumulation of high-quality in situ observations. Data were acquired from Ocean Colour Monitor (OCM) and in situ observations for tuning of Tassan’s algorithm (Tassan, 1994) to retrieve the suspended sediment concentration (SSC) in the coastal waters off southern Karnataka, India. Tassan’s algorithm has been modified regionally by adopting statistical/graphical criteria to characterize the spatial and seasonal distribution of SSC. A concurrent and collocated datasets (n=120) of in situ SSC and OCM based remote sensing reflectance [Rrs(λ) in bands 490, 555 and 670nm] were regressed. The linear fit yielded regionally tuned new coefficients which were replaced in place of Tassan’s global coefficients. The tuned algorithm was shown to retrieve SSC with range of 1.1–37.12mg/l, which means it can be used for coastal waters. Since in situ samples were collected within the continental margin (average depth of ∼20m), we retain the global SSC algorithm (Tassan, 1994) approach for deeper bathymetric values (>50m depth) where we have no in situ measurements. Comparative analysis indicated statistically significant relationship (R2=0.99; n=45; p<0.05 at 95% confidence level) between in situ SSC and regionally tuned algorithm based SSC, with bias of 0.36mg/l and root mean square (RMS) difference of 0.73mg/l. This result clearly demonstrated the improvement of SSC measurement from OCM using regionally tuned Tassan’s algorithm (RMS=0.73mg/l) over the globally coefficient based Tassan’s algorithm (RMS=16.1mg/l).The tuned regional algorithm was used to estimate SSC in 2004, 2005 and 2007 which shows the concentration varied from 1.13 to 28.1mg/l in 2004, 1.84 to 23.12mg/l in 2005 and 2 to 27.85mg/l in 2007. Graphical and statistical methods using analysis of variance (ANOVA) have shown significant seasonal variability and inter-station spatial variability in SSC. Peak concentrations were recorded in the post-monsoon followed by the pre-monsoon period. The wind, wave and current pattern associated with southwest monsoon possibly controls the seasonal distribution, while nearshore turbulence and littoral transport influence the spatial distribution. This paper clearly demonstrated the potential application of regionally tuned algorithm for SSC mapping to study the spatial and seasonal pattern in shallow water off southern Karnataka.

Observation of Algal Bloom in the Northwest Arabian Sea Using Multisensor Remote Sensing Satellite Data

Algal bloom observed using Indian Remote Sensing Satellite IRS-P4 Ocean Color Monitor (OCM) derived chlorophyll images during December 23, 2003–January 8, 2004, off the Oman coast. High chlorophyll concentration (∼20 mg m−3) patches were observed. MODIS-Aqua data of January 1, 2004, were analyzed to generate normalized water leaving radiance (nLw) images for seven visible channels: 412, 443, 488, 531, 551, 667 and 678 nm. The channels 667 and 678 nm showed interesting algal bloom features. The bloom features were detected in OCM image of January 2, 2004, using Subramanian's Trichodesmium detection Protocol. MODIS-Aqua retrieved Sea Surface Temperature (SST) around the bloom patches was observed to be >240°C. The OCM chlorophyll mean observed to be very high (>10.0 mg m−3) in two bloom pockets. Quickscat scatterometer derived wind speed was found to be optimum in the range of 3–5 m/sec.

Binning algorithm for high-resolution IRS-P4 OCM chlorophyll image

Daily chlorophyll-a concentration from the Ocean Colour Monitor (OCM) sensor onboard the Indian Remote Sensing satellite (IRS-P4) is used to make weekly and monthly chlorophyll-a concentration maps. The pathwise swath data at 12 noon for every alternate day over the north Indian Ocean (NIO) during February 2004 and February 2005 were used to compare the existing algorithms for binning the data. Atmospherically corrected and geocorrected OCM data were used in the comparative study of three averaging algorithms – arithmetic mean (AVG), geometric mean (GEO) and maximum likelihood estimator (MLE). The analysis shows that the AVG algorithm is best suited when compared with the two other algorithms. However, for case 1 water, MLE gives nearly the same value as AVG. Based on this result, AVG was selected for operational weekly and monthly averaging of OCM data over the NIO. These high-resolution-derived chlorophyll-a weekly and monthly products will be useful to resolve inter-annual-to-decadal changes in chlorophyll-a concentration over the NIO.

Application of Satellite Remote Sensing for Investigation of Suspended Sediment Dispersion Pattern in the Near Shore Region: A Case Study from the Central West Coast of India

NAYAK, S.R.; HEGDE, V.S.; SHALINI, R.; RAJAWAT, A.S.; ALI, M.; VENKATESHWARLU, B., and RAMANA, I.V., 2012. Application of satellite remote sensing for investigation of suspended sediment dispersion pattern in the near shore region: A case study from the Central West Coast of India.Indian Remote Sensing -P4 (IRS P4) Ocean Color Monitor (OCM) data is used to understand seasonal variations in suspended sediment (SS) dispersal pattern in the near-shore waters of the Central West Coast of India. Four distinct patterns of sediment dispersion are observed. (1) During monsoon, plume-like sediment dispersion seaward is observed especially in the mouths of rivers. (2) As the monsoon progresses, there is northerly transport of sediments with anticlockwise pattern within the plumes. (3) During NE monsoon, sediment concentration is less and its transport is southward. (4) During premonsoon, SS concentration is high in the near-shore water and transport is landward. Sequential OCM data analyses indicated the influence of tidal currents, especially during premonsoon in the vicinity of the river mouths on sediments dispersion. During rising tide, sediments move into the estuary, and during falling tide they flow seaward resulting in erosion and formation of shoals. Sediment-dispersal patterns largely follow wind and wave patterns, a characteristic feature of the mesotidal coast. Presence of a number of mudflats within the estuary along with the siltation in the channels suggests that a net landward transport of sediments occur in the region.

Derivation of Calibration Coefficients for OCM-2 Sensor for Coastal Waters

The radiometric calibration coefficients that are required to enhance the preflight calibration coefficients to improve the performance of the Ocean Colour Monitor (OCM-2) onboard the Indian Remote Sensing Satellite (IRS) are determined using in-situ measurements in coastal waters around southern India. These coefficients were applied to OCM-2 data acquired over coastal waters off Point Calimere (Palk Strait) and Gulf of Mannar of the Bay of Bengal, and are compared with similar coefficients included in the SeaDAS software and those provided by the Space Application Centre (SAC). Two atmospheric correction algorithms were used in conjunction with these coefficients to obtain the water-leaving radiances (Lw) from OCM-2 data, namely the CAAS algorithm and SeaDAS algorithm. An evaluation of the results of these coefficients and atmospheric correction algorithms showed large deviations in Lw values derived with the SAC (positive deviation) coefficients and SeaDAS (negative deviation) coefficients when applied to OCM-2 data along with the SeaDAS atmospheric correction algorithm. The deviations were less remarkable with new coefficients when the same (SeaDAS) atmospheric correction algorithm was used. However, application all three coefficients to OCM-2 using the CAAS algorithm showed a similar trend but with less deviations with respect to in-situ Lw data. The results obtained with the new coefficients showed good agreement with the in-situ water-leaving radiances (except channels 412-443nm). These results suggest that the new calibration coefficients can be used along with the CAAS atmospheric correction algorithm to improve the performance of OCM-2 sensor for quantitative assessments of the various water constituents in coastal waters (including bloom) around India.

Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data

Cyanobacteria represent a major harmful algal group in fresh to brackish water environments. Lac des Allemands, a freshwater lake of 49 km 2 southwest of New Orleans, Louisiana on the upper end of the Barataria Estuary, provides a natural laboratory for remote characterization of cyanobacterial blooms because of their seasonal occurrence. The Oceansat-1 satellite Ocean Colour Monitor (OCM) provides measurements similar to SeaWiFS but with higher spatial resolution, and this work is the first attempt to use OCM measurements to quantify cyanobacterial pigments. The satellite signal was first vicariously calibrated using SeaWiFS as a reference, and then corrected to remove the atmospheric effects using a customized atmospheric correction procedure. Then, empirical inversion algorithms were developed to convert the OCM remote sensing reflectance ( R rs ) at bands 4 and 5 (centered at 510.6 and 556.4 nm, respectively) to concentrations of phycocyanin (PC), the primary cyanobacterial pigment. A holistic approach was used to minimize the influence of other optically active constituents on the PC algorithm. Similarly, empirical algorithms to estimate chlorophyll a (Chl a) concentrations were developed using OCM bands 5 and 6 (centered at 556.4 and 669 nm, respectively). The best PC algorithm (R 2 = 0.7450, p < 0.0001, n = 72) yielded a root mean square error (RMSE) of 36.92 μg/L with a relative RMSE of 10.27% (PC from 2.75 to 363.50 μg/L, n = 48). The best algorithm for Chl a (R 2 = 0.7510, p < 0.0001, n = 72) produced an RMSE of 31.19 μg/L with a relative RMSE of 16.56% (Chl a from 9.46 to 212.76 μg/L, n = 48). While more field data are required to further validate the long-term performance of these algorithms, currently they represent the best protocol for establishing a long time-series of cyanobacterial blooms in the Lac des Allemands using OCM data.

Dynamics of chromophoric dissolved organic matter in Mandovi and Zuari estuaries — A study through in situ and satellite data

The spatial and temporal distribution of absorption of chromophoric dissolved organic matter at 440 nm ( a CDOM (440)) in the Mandovi and Zuari estuaries situated along the west coast of India, has been analysed. The study was carried out using remotely sensed data, obtained from the Ocean Colour Monitor (OCM) on board the Indian Remote Sensing satellite — P4, together with in situ data during the period January to December 2005. Satellite retrieval of CDOM absorption was carried out by applying an algorithm developed for the site. A good correlation ( R = 0.98 ) was obtained between satellite derived CDOM and in situ data. Time series analysis revealed that spatial distribution of CDOM has a direct link with the seasonal hydrodynamics of the estuaries. The effect of remnant fresh water on CDOM distribution could be analysed by delineating a plume in the offshore region of the Zuari estuary. Though fresh water flux from terrestrial input plays a major role in the distribution of CDOM throughout the Mandovi estuary, its role in the Zuari estuary is significant up to the middle zone. Other processes responsible for feeding CDOM in both the estuaries are coastal advection, in situ production and resuspension of bottom settled sediments. The highest value of a CDOM(440) was observed in the middle zone of the Mandovi estuary during the post-monsoon season. The relation between a CDOM(440) and S (spectral slope coefficient of CDOM) could differentiate CDOM introduced in to estuaries through multiple sources. The algorithm developed for the Mandovi estuary is S = 0.003 [ a CDOM(440) −0.7091] while for the Zuari estuary, S = 0.0031 [ a CDOM(440) −0.777], respectively.

Remote Sensing of Chlorophyll and Sea Surface Temperature in Indian Water with Impact of 2004 Sumatra Tsunami

The daily and weekly averaged Indian Remote Sensing satellite IRS-P4 Ocean Color Monitor (OCM) derived chlorophyll images were generated and interpreted in terms of pretsunami, tsunami, and posttsunami periods in the Bay of Bengal and Andaman Sea. There has been observation of increase in chlorophyll concentration up to 5.0 mg/m3 in the tsunami-affected coastal waters. The high chlorophyll concentration lasted for about one week after the tsunami catastrophe. The standard deviation for different transects in the tsunami-affected water were plotted. The high chlorophyll has been observed for selected transects in the aftermath of the tsunami event in coastal regions, and offshore water has also shown increase in chlorophyll concentration (∼1.0 mg/m3) in the Bay of Bengal. The analysis indicated that the tsunami waves might have displaced and spread the high chlorophyll coastal water towards offshore. NASA Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua daytime sea surface temperature (SST) daily images were retrieved and displayed during December 21, 2004, to January 6, 2005, and indicated the cooling (0.5–1°C) in the Bay of Bengal around Tamil Nadu and Andhra coast. The National Oceanographic and Atmospheric Prediction-National Center for Environment Prediction (NOAA-NCEP) data for five weeks (December 9, 2004–January 12, 2005) were retrieved to study the SST variability trend in prior to MODIS data and indicated 0.5–1°C cooling of the Bay of Bengal water off Kakinada, Chennai, Cuddalore, and Nagapattinam region on December 26 and 28, 2004.

Phytoplankton Variability in the Bay of Bengal During Winter Monsoon Using Oceansat-1 Ocean Colour Monitor Data

Quantitative assessment of chlorophyll-a concentration and its variability is an important input for the oceanic primary productivity modeling and also a key parameter in the global carbon cycle studies. This present work is focused to understand the spatial and temporal variability of phytoplankton in the Bay of Bengal (BOB) during winter monsoon season of October 1999 to March 2000 using Ocean Colour Monitor (OCM) sensor onboard OCEANSAT-1 satellite. Daily chlorophyll-a images from OCM sensor were used in the study. Efforts were also put to study the correlation between chlorophyll-a concentrations; NOAA-AVHRR derived Sea Surface Temperature (SST) and QuickSCAT scatterometer derived wind stress data. Analysis of the chlorophyll-a images shows the presence of extensive phytoplankton blooms during mid December 1999 to early January 2000 in the western part of BOB. The bloom dominated regions also exhibit reduced SST (∼24–27°C) and enhanced wind stress indicating upwelling processes leading nutrient entrainment in the upper column of the sea surface. Apart from this, higher phytoplankton biomass associated with the fresh water reverine plumes has also been observed. During October 1999 a super cyclone was active in the BOB, as increase in the productivity was observed in the early November 1999 images of OCM data due to the cyclone induced churning of the water column.

Aerosol optical thickness and spatial variability along coastal and offshore waters of the eastern Arabian Sea

AbstractMenon, H. B., Sangekar, N., Lotliker, A., Krishna Moorthy, K., and Vethamony, P. 2011. Aerosol optical thickness and spatial variability along coastal and offshore waters of the eastern Arabian Sea. – ICES Journal of Marine Science, 68: 745–750. Data from the ocean-colour monitor (OCM) on board the Indian Remote Sensing Satellite P4 were used to analyse the spatial and temporal distribution of aerosol optical thickness (AOT) over the coastal and offshore waters of the eastern Arabian Sea. Zero water-leaving radiance from the near infrared (NIR) region was assumed for oceanic (open ocean) waters, because of the absorption of long-wave radiation by water molecules. As this assumption fails in coastal waters, it was necessary to correct for water-leaving radiance and sun glint to the NIR bands. The aerosol size-distribution parameter (α) was derived from a relationship between two NIR bands. The Ångström turbidity parameter (β) was obtained using an algorithm relating in situ hand-held, sun-photometer measurements and aerosol radiance (La) at 490 nm. The relationship between β and La (490) was derived with a sensitivity analysis, using a calibrated radiative transfer model. AOTs were retrieved for each pixel of 500 nm. The algorithm's performance was tested by comparing OCM-derived AOT values with in situ AOT and MODIS-derived values. Aerosol maps thus generated from January to December 2005 demonstrate the potential of this new retrieval method for producing AOT climatology from OCM data over coastal waters.