R. M. Dwivedi

Nitrogen Uptake Rates during Spring in the NE Arabian Sea

We present new data on N uptake rates and f-ratios in the north-eastern (NE) Arabian Sea, where significant amounts of Trichodesmium were present in spring, 2006. The measured total nitrogen uptake rates ranged from 0.34 to 1.58 mmol N m−2d−1. N2 fixation associated with Trichodesmium varied from 0.002 to 0.54 mmol N m−2d−1 estimated from the abundance of Trichodesmium and specific N2 fixation rates of 1.5 pmol N trichome−1h−1. Inclusion of N2 fixation rates significantly changes f-ratios particularly in the coastal stations. Nitrogen isotopic data of surface suspended particles suggest that recently fixed nitrogen contributes as high as ~79% of the nitrogen in surface suspended particles. In addition, water column gained ~30 mmol N m−2 in the form of nitrate, likely due to nitrification of ammonium released by Trichodesmium. For better estimations, direct measurement of N2 fixation is recommended.

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.

a

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.

Algorithm for Ocean Colour Monitor Onboard OCEANSAT-2 Satellite

Sequence of the images from IRS P4 / OCM satellite and extensive shipboard sampling programme are used to understand the seasonal variation of phytoplankton abundance and types in the Northeastern (NE) Arabian Sea and Lakshadweep Sea. An appreciable degree of spatial and temporal variability is observed in chlorophyll a distribution from November to April months, as well as coastal and offshore stations, indicating marked seasonality in phytoplankton distribution in NE Arabian Sea. During November month (fall intermonsoon) average chlorophyll a (Chl a) by fluorometer was (0.799 mgm^-3) and by OCM it was 0.584 mgm^-3. The higher chlorophyll a observed was due to Trichodesmium (cyanobacteria) blooms. During December the average chlorophyll a was 0.34 mgm^-3 also due to Trichodesmium filaments in water column. During January onwards winter cooling led to increase in nutrients which enhanced chlorophyll a value to 0.64 mgm^-3 due to growth of flagellates (as seen by high chlorophyll b besides chlorophyll a) in water column. February, March and April supported moderately high chlorophyll value (0. 3 to 0.5 mgm^-3) due to growth of prasinophytes (as seen by pigment prasinoxanthin) and blooms of the Noctiluca miliaris. Time series monitoring of Noctiluca bloom was also conducted using OCM based chlorophyll images in NE Arabian Sea. During February chlorophyll a retrieved by OCM was 0.3 to 0.9 mgm^-3. Pigment analysis of water samples indicated the equal important of accessory pigment like zeaxanthin, prasinoxanthin, beta-carotene. The relevance of these pigments estimated by HPLC like zeaxanthin (cyanobacteria), fucoxanthin (diatoms), peridinin (dinoflagellates) is presented and discussed. Similarly, exercise is conducted in Lakshadweep waters where Trichodesmium related peak in chlorophyll a was observed during March onwards in OCM data. The average chlorophyll a in NE Arabian Sea at surface during November was (0.726 mgm^-3), December (0.34 mgm^-3), January (0.723 mgm^-3), February (0.344 mgm^-3), March (0.963 mgm^-3) and April 0.665 mgm^-3. Similar trend was observed in primary productivity estimates. The attempt is made to work out seasonality in the productivity of the Arabian Sea using OCM derived chlorophyll and relation of enhancement in productivity due to development of winter blooms in the Arabian Sea. The environmental conditions (temperature, wind, nutrients and mixed layer depth) affecting these blooms responsible for year to year variation in bloom biomass and productivity is also presented in detail.

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

Trichodesmium spp. is widely spread in the Arabian Sea. It form dense patches. During 2000-2005 (5 years period) extensive sampling was done in the Arabian Sea covering large area and different months starting from November to May. Three prominent sites are identified as Trichodesmium bloom sites in the Arabian Sea: 1) Lakshadweep waters 2) Off Goa and 3) Off Gujarat area. Bloom of around 100 km2 area with 4 to 400737 filamentsL-1 concentrations are recorded. Two species of Trichodesmium are encountered based upon seasonality and environmental conditions. OCM derived chlorophyll a during bloom was as high as 0.5 to 1 mgm-3, at time increased upto 5 mgm-3 and depends upon number of filaments in water. The Trichodesmium features were identified at 869, 670, 555nm in OCM data. Trichodesmium was detected as stripes and eddies in OCM images. The bloom patches appear darker which is taken as measurement of spread of the bloom in water. Total 133 stations are covered during 5 years period out of which 63 stations showed presence of Trichodesmium with discolouration of water. In offshore water Trichodesmium was detected as early as November and continued upto April month whereas in the coastal water Trichodesmium prevailed from February to May. The seasonality of these blooms was observed with respect to inshore/offshore and two species of Trichodesmium is discussed with the help of OCM data processed for chlorophyll a during Trichodesmium growth period, at 3 identified sites in the Arabian Sea.

Satellite and ship studies of phytoplankton in the northeastern Arabian during 2000-2006 period

Arabian Sea is highly influenced by monsoon systems like SW monsoon (June-September) and NE monsoon (December-February). This affects distribution pattern of phytoplankton, availability of nutrients and changing temperature specially during winter cooling period (February-March). These and other conditions like quality and quantity of light influence phytoplankton (type and concentration) in the Arabian Sea. In our study we have observed monsoon related peaks in phytoplankton and chlorophyll a in the Arabian Sea. These chlorophyll a (Chl a) concentrations detected by OCM sensor onboard IRS-P4 satellite is helping us to work out seasonality of phytoplankton in the Arabian Sea, which is of the great importance in the field of biology and biogeochemistry of this region. However, during these study subsurface chlorophyll a maxima (SCM) was observed as characteristics feature of chlorophyll a distribution in the Arabian Sea. The subsurface chlorophyll a maxima varies from 30m to 55m in the Arabian Sea during various seasons. During November at St. 1 surface chlorophyll a was 1.503 mgm^-3 and subsurface chlorophyll maxima was 12.692 mgm^-3. Similarly, at St. 13 surface chlorophyll a was 0.584 mgm^-3 and surface chlorophyll maxima was 8.517 mgm^-3. During upwelling, nutrients remained unused at sub surface due to shortage of light which may lead to subsurface blooms, detection of which is critical for precise estimation of chlorophyll a from ocean colour sensor. During our 5 year study (covering all the seasons) in northeastern (NE) Arabian Sea, we have observed more than 50 % stations were with subsurface chlorophyll a maxima where chlorophyll a was approximately 10 times higher compared to surface value. The high chlorophyll some time detected by OCM is mainly because of detection of subsurface chlorophyll maxima by the satellite but may not actually sampled during ship studies. The satellite penetration depth (ze), subsurface chlorophyll maxima depth, OCM derived chlorophyll a for different seasons in NE Arabian Sea is presented and discussed in this paper.

Basin scale distribution of Trichodesmium spp. in the Arabian Sea using Oceansat I/OCM

An artificial neural network (ANN) based procedure is developed to estimate concentrations of Chlorophyll-a, Suspended Particulate Matter (SPM) and absorption due to chromophoric dissolved organic matter (CDOM) in the seawater from satellite detected normalized water-leaving radiance (nLw) of the IRS-P4 Ocean Colour Monitor (OCM) satellite data. An ocean colour reflectance model was used to generate surface spectral reflectance corresponding to first five bands of IRS-P4 OCM sensor, using three optically active oceanic water constituents as inputs. ANN model making use of reflectance in five visible bands was trained, tested and validated to invert the spectral reflectance for the simultaneous estimation of three optically active constituents. The retrieved chlorophyll-a concentrations from ANN based algorithm were compared with the corresponding chlorophyll-a distribution obtained by global empirical algorithms e.g. Ocean Chlorophyll-4 (OC4) algorithm. ANN derived chlorophyll-a estimates were found to have reduced the over estimation in coastal waters often observed with the use of band ratio algorithms.

Seasonality in subsurface chlorophyll maxima in the Arabian Sea: detection by IRS-P4/OCM and implication of it to primary productivity

In-situ measurements of the bio-optical properties of the seawater are important to develop algorithms for seawater constituent estimation using satellite remote sensing. A data collection campaign was conducted for bio-optical characterization of the open and coastal waters of the Arabian Sea during April 15-29, 2006. Bio-optical measurements were made using the Satlantic hyper-spectral underwater radiometer (Hyperpro-II) for 13 sampling stations include oligotrophic, Trichodesmium bloom dominated and coastal waters in 400-800 nm spectral range. For open oceans stations 1% light was available at 50 to 70 meter depth, whereas, for coastal waters it varied from 18 to 35 meter. The deep chlorophyll maxima (DCM) was observed at 30 to 42 meter depth during the bloom conditions with surface chlorophyll-a concentration ranging between 0.1 to 0.85 mg m-3 whereas, for open ocean and non-bloom conditions the DCM depth varied from 35 to 60 m with surface chlorophyll ranging between 0.05 to 0.12 mgm-3. Particulate back scattering coefficient at 700-nm vary from 0.0011 to 0.0031 for bloom waters and 0.00046 to 0.0012 for open ocean waters. The normalized water leaving radiance computed from these spectra in the spectral bands of IRS-P4, OCM bands were examined. The global ocean chlorophyll-2 (OC2), and 4 (OC4) algorithms performed reasonably well for open ocean waters, however both the algorithms overestimated chlorophyll concentration for bloom dominated waters.