Chlorophyll distribution by oceanic model and satellite data in the Bay of Bengal and Andaman Sea

2013 ◽  
Vol 42 (2) ◽  
Author(s):  
Sakharin Suwannathatsa ◽  
Prungchan Wongwises
Keyword(s):  
Satellite Data ◽  
Bay Of Bengal ◽  
Seasonal Distribution ◽  
Sea Surface ◽  
Andaman Sea ◽  
Wide Field ◽  
Sample Collection ◽  
Chl A ◽  
Phytoplankton Absorption ◽  
Oceanic Model

AbstractAn oceanic model and satellite data are used to evaluate the seasonal distribution of chlorophyll-a (Chl-a) in the Bay of Bengal (BoB) and Andaman Sea.Satellite data show high Chl-a concentrations because high Chl-a concentrations reduce CO2 and increase O2 at the sea surface, indicating fish abundance in the ocean. Sample collection alone cannot provide an accurate overview of Chl-a concentration over an entire region.The satellite data concerning Chl-a concentration, phytoplankton absorption coefficient, and Sea Surface Temperature (SST) are from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) project and from the Moderate Resolution Imaging Spectroradiometer (MODIS). The oceanic model is created to give the surface circulation as a result. The research finds that the simulation is in agreement with SST, Chl-a concentration, and phytoplankton absorption coefficients obtained from satellites. The conclusion is that the oceanic model can be used to implicitly explain the seasonal distribution of Chl-a in the Bay of Bengal and Andaman sea.

scholarly journals Phytoplankton Tracking by Oceanic Model and Satellite Data in the Bay of Bengal and Andaman Sea

2012 ◽  
Vol 2 ◽  
pp. 183-189 ◽  
Author(s):  
Sakharin Suwannathatsa ◽  
Prungchan Wongwises ◽  
Suphat Vongvisessomjai ◽  
Worachat Wannawong ◽  
Donlaporn Saetae
Keyword(s):  
Satellite Data ◽  
Bay Of Bengal ◽  
Andaman Sea ◽  
Oceanic Model

scholarly journals Adjusting Neural Network to a Particular Problem: Neural Network-Based Empirical Biological Model for Chlorophyll Concentration in the Upper Ocean

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Vladimir Krasnopolsky ◽  
Sudhir Nadiga ◽  
Avichal Mehra ◽  
Eric Bayler
Keyword(s):  
Neural Network ◽  
Chlorophyll A ◽  
Ocean Dynamics ◽  
Sea Surface ◽  
Biological Model ◽  
Upper Ocean ◽  
Wide Field ◽  
Biological Processes ◽  
Chl A ◽  
The Impact

The versatility of the neural network (NN) technique allows it to be successfully applied in many fields of science and to a great variety of problems. For each problem or class of problems, a generic NN technique (e.g., multilayer perceptron (MLP)) usually requires some adjustments, which often are crucial for the development of a successful application. In this paper, we introduce a NN application that demonstrates the importance of such adjustments; moreover, in this case, the adjustments applied to a generic NN technique may be successfully used in many other NN applications. We introduce a NN technique, linking chlorophyll “a” (chl-a) variability—primarily driven by biological processes—with the physical processes of the upper ocean using a NN-based empirical biological model for chl-a. In this study, satellite-derived surface parameter fields, sea-surface temperature (SST) and sea-surface height (SSH), as well as gridded salinity and temperature profiles from 0 to 75m depth are employed as signatures of upper-ocean dynamics. Chlorophyll-a fields from NOAA’s operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a concentrations. Different methods of optimizing the NN technique are investigated. Results are assessed using the root-mean-square error (RMSE) metric and cross-correlations between observed ocean color (OC) fields and NN output. To reduce the impact of noise in the data and to obtain a stable computation of the NN Jacobian, an ensemble of NN with different weights is constructed. This study demonstrates that the NN technique provides an accurate, computationally cheap method to generate long (up to 10 years) time series of consistent chl-a concentration that are in good agreement with chl-a data observed by different satellite sensors during the relevant period. The presented NN demonstrates a very good ability to generalize in terms of both space and time. Consequently, the NN-based empirical biological model for chl-a can be used in oceanic models, coupled climate prediction systems, and data assimilation systems to dynamically consider biological processes in the upper ocean.

scholarly journals Assessment of a global climatology of oceanic dimethylsulfide (DMS) concentrations based on SeaWiFS imagery (1998-2001)

2004 ◽  
Vol 61 (5) ◽  
pp. 804-816 ◽  
Author(s):  
S Belviso ◽  
C Moulin ◽  
L Bopp ◽  
J Stefels
Keyword(s):  
North Atlantic ◽  
Surface Waters ◽  
Sea Surface ◽  
Wide Field ◽  
Chl A ◽  
The North ◽  
Wide Field Of View ◽  
Lyase Activity ◽  
Mixed Populations

A method is developed to estimate sea-surface particulate dimethylsulfoniopropionate (DMSPp) and dimethylsulfide (DMS) concentrations from sea-surface concentrations of chlorophyll a (Chl a). When compared with previous studies, the 1° × 1° global climatology of oceanic DMS concentrations computed from 4 years (1998–2001) of Chl a measurements derived from SeaWiFS (satellite-based, sea-viewing wide field of view sensor) exhibits lower seasonal variability in the southern hemisphere than in the northern hemisphere. A first evaluation of the method shows that it reasonably well represents DMSPp and DMS in the North Atlantic subtropical gyre, in large blooms of mixed populations of diatoms and Phaeocystis spp., and in massive blooms of Phaeocystis spp. but fails for large, almost pure blooms of diatoms. DMSPp and DMS concentrations derived from SeaWiFS were also compared with spatially and temporally coincident in situ measurements acquired independently in the Atlantic between 39°N and 45°N and in subtropical and subantarctic Indian Ocean surface waters. Moderate spring and summer phytoplankton blooms there exhibited similar trends in DMSPp and DMS levels vs. moderate blooms of mixed populations of prymnesiophytes and dinoflagellates investigated by others. Measured DMS largely exceeded simulated DMS concentrations, whereas measured and simulated DMSPp levels were in close agreement. DMS accumulation is tentatively attributed to dinoflagellate DMSP lyase activity.

scholarly journals SATELLITE-MEASURED SPATIAL AND TEMPORAL CHLOROPHYLL-A VARIABILITY IN THE GULF OF TOMINI, SULAWESI

2009 ◽  
Vol 4 (2) ◽  
pp. 147
Author(s):  
I Nyoman Radiarta
Keyword(s):  
Chlorophyll A ◽  
Temporal Variations ◽  
Sea Surface ◽  
Spatial And Temporal Variability ◽  
Wide Field ◽  
Wind Condition ◽  
Marine Aquaculture ◽  
Chl A ◽  
Fisheries Resources ◽  
Aquaculture Development

Chlorophyll-a concentration, an index of phytoplankton biomass, is an important parameter for fisheries resources and marine aquaculture development. Spatial and temporal variability of surface cholophyll-a (chl-a) concentration and water condition in the Gulf of Tomini were investigated using monthly climatologies the Sea-viewing Wide Field-of-view sensor (SeaWiFS), sea surface temperature (SST), and wind data from January 2000 to December 2007. The results showed seasonal variation of chla and SST in the Gulf of Tomini. High chl-a concentrations located in the eastern part of the gulf were observed during the southeast monsoon in August. During the northwest monsoon, chl-a concentrations were relatively low (<0.2 mg m-3) and distributed uniformly throughout most of the region. Chl-a concentrations peaked in August at every year, and chl-a concentrations were observed low in November at every year from 2000 to 2007. SSTs were relatively high (> 28oC) during the northwest monsoon, but low during the southeast monsoon. High wind speed was coincided with high chl-a concentrations. Local forcing such as sea surface heating and wind condition are the mechanisms that controlled the spatial and temporal variations of chlorophyll concentrations.

scholarly journals Spatio-Temporal Variability of Chlorophyll-A and Environmental Variables in the Panama Bight

2020 ◽  
Vol 12 (13) ◽  
pp. 2150
Author(s):  
Andrea Corredor-Acosta ◽  
Náyade Cortés-Chong ◽  
Alberto Acosta ◽  
Matias Pizarro-Koch ◽  
Andrés Vargas ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Temporal Variability ◽  
Phytoplankton Growth ◽  
Sea Surface ◽  
Chl A ◽  
Physical Variables ◽  
Spatio Temporal

The analysis of synoptic satellite data of total chlorophyll-a (Chl-a) and the environmental drivers that influence nutrient and light availability for phytoplankton growth allows us to understand the spatio-temporal variability of phytoplankton biomass. In the Panama Bight Tropical region (PB; 1–9°N, 79–84°W), the spatial distribution of Chl-a is mostly related to the seasonal wind patterns and the intensity of localized upwelling centers. However, the association between the Chl-a and different physical variables and nutrient availability is still not fully assessed. In this study, we evaluate the relationship between the Chl-a and multiple physical (wind, Ekman pumping, geostrophic circulation, mixed layer depth, sea level anomalies, river discharges, sea surface temperature, and photosynthetically available radiation) and chemical (nutrients) drivers in order to explain the spatio-temporal Chl-a variability in the PB. We used satellite data of Chl-a and physical variables, and a re-analysis of a biogeochemical product for nutrients (2002–2016). Our results show that at the regional scale, the Chl-a varies seasonally in response to the wind forcing and sea surface temperature. However, in the coastal areas (mainly Gulf of Panama and off central-southern Colombia), the maximum non-seasonal Chl-a values are found in association with the availability of nutrients by river discharges, localized upwelling centers and the geostrophic circulation field. From this study, we infer that the interplay among these physical-chemical drivers is crucial for supporting the phytoplankton growth and the high biodiversity of the PB region.

scholarly journals Assessment of chlorophyll-a and sea surface temperature variability around the Mascarene Plateau, Nazareth Bank (Mauritius) using satellite data

2017 ◽  
Vol 64 (4) ◽  
Author(s):  
V. Ramchandur ◽  
Soonil D. D. V. Rughooputh ◽  
R. Boojawon ◽  
B. A. Motah
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Phytoplankton Biomass ◽  
Winter Season ◽  
Sea Surface ◽  
Chl A ◽  
The Past ◽  
Western Side

The Mascarene Plateau is characterised by shallow banks namely Saya de Malha and Nazareth which are known to harbour high phytoplankton biomass along the slope down to the ridge. Correlation between sea surface temperature (SST) and Chlorophyll-a (Chl-a) distribution surrounding the plateau was investigated. Higher Chl-a concentration was observed during the period July to September, indicating higher productivity due to upwelling. The regions east (61-630E) and west (57-590E) of the Mascarene Plateau were also studied along latitudes 130S up to 180S in the exclusive economic zone of Mauritius, where most of the fishing activities are concentrated. In general, 2008 was observed to be less warm during the past 14 years registering a drop with respect to the maximum monthly mean records, whilst 2006 was the most productive during winter season in the region of study. Chl-a bloom was observed after cyclone Imelda in April 2013 showing Chl-a concentration above 0.3 mg m-3 along latitude 130S and longitude 570E. The study reveals that the western side of the plateau is more productive with relatively warmer surface temperature compared to the eastern side of the plateau.

scholarly journals Impact of Climate Change on Past Indian Monsoon and Circulation: A Perspective Based on Radiogenic and Trace Metal Geochemistry

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 330
Author(s):  
Harunur Rashid ◽  
Yang Wang ◽  
Alexandra T. Gourlan
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Indian Subcontinent ◽  
North Indian Ocean ◽  
Sea Surface ◽  
Andaman Sea ◽  
Northern Indian Ocean ◽  
Hafnium Isotopes ◽  
Neodymium Isotopes ◽  
The Last Glacial

The Indian summer monsoon (ISM), one of the dramatic illustrations of seasonal hydrological variability in the climate system, affects billions of lives. The ISM dominantly controls the northern Indian Ocean sea-surface salinity, mostly in the Bay of Bengal and the Andaman Sea, by the Ganga-Brahmaputra-Meghna and Irrawaddy-Salween rivers outflow and direct rainfall. In the past decade, numerous studies have used radiogenic neodymium (εNd) isotopes of seawater to link Indian subcontinent erosion and the ensuing increase in discharge that results in changes in the north Indian Ocean sea surface. Here we synthesized the state of the ISM and ocean circulation using the neodymium and hafnium isotopes from north Indian Ocean deep-sea sediments. Our data suggest that the Bay of Bengal and north Indian Ocean sea-surface conditions were most likely modulated by changes in the ISM strength during the last glacial-interglacial cycle. These findings contrast to the hypothesis that suggests that the bottom water neodymium isotopes of the northern Indian Ocean were modulated by switching between two distant sources, namely North Atlantic Deep Water and Antarctic bottom water. Furthermore, the consistency between the neodymium and hafnium isotopes during the last glacial maximum and Holocene suggests a weak and dry ISM and strong and wet conditions, respectively. These data also indicate that the primary source of these isotopes was the Himalayas. Our results support the previously published paleo-proxy records, indicating weak and strong monsoons for the same periods. Moreover, our data further support the hypothesis that the northern Indian Ocean neodymium isotopes were decoupled from the global ocean neodymium budget due to the greater regional influence by the great Ganga-Brahmaputra-Meghna and Irrawaddy-Salween discharge draining the Indian subcontinent to the Bay of Bengal and the Andaman Sea.

SATELLITE DATA FOR INVESTIGATION OF RECENT STATE AND PROCESSES IN THE SIVASH BAY

2017 ◽  
Author(s):  
Ekaterina Shchurova ◽  
Ekaterina Shchurova ◽  
Rimma Stanichnaya ◽  
Rimma Stanichnaya ◽  
Sergey Stanichny ◽  
...  
Keyword(s):  
Satellite Data ◽  
Water Exchange ◽  
High Salinity ◽  
Meteorological Data ◽  
Sea Surface ◽  
Azov Sea ◽  
Seasonal Wind ◽  
Ice Regime ◽  
Very High

Sivash bay is the shallow-water lagoon of the Azov Sea. Restricted water exchange and high evaporation form Sivash as the basin with very high salinity. This factor leads to different from the Azov Sea thermal and ice regimes of Sivash. Maine aim of the study presented to investigate recent state and changes of the characteristics and processes in the basin using satellite data. Landsat scanners TM, ETM+, OLI, TIRS together with MODIS and AVHRR were used. Additionally NOMADS NOAA and MERRA meteorological data were analyzed. The next topics are discussed in the work: 1. Changes of the sea surface temperature, ice regime and relation with salinity. 2. Coastal line transformation – long term and seasonal, wind impact. 3. Manifestation of the Azov waters intrusions through the Arabat spit, preferable wind conditions.

scholarly journals The Role of Environmental Factors on the Fishery Catch of the Squid Uroteuthis chinensis in the Pearl River Estuary, China

2021 ◽  
Vol 9 (2) ◽  
pp. 131
Author(s):  
Dongliang Wang ◽  
Lijun Yao ◽  
Jing Yu ◽  
Pimao Chen
Keyword(s):  
River Estuary ◽  
Pearl River Estuary ◽  
Sea Surface ◽  
Spatiotemporal Variability ◽  
Pearl River ◽  
Coastal Current ◽  
Catch Per Unit Effort ◽  
Chl A ◽  
The Pearl River Estuary ◽  
The Pearl River

The Pearl River Estuary (PRE) is one of the major fishing grounds for the squid Uroteuthis chinensis. Taking that into consideration, this study analyzes the environmental effects on the spatiotemporal variability of U. chinensis in the PRE, on the basis of the Generalized Additive Model (GAM) and Clustering Fishing Tactics (CFT), using satellite and in situ observations. Results show that 63.1% of the total variation in U. chinensis Catch Per Unit Effort (CPUE) in the PRE could be explained by looking into outside factors. The most important one was the interaction of sea surface temperature (SST) and month, with a contribution of 26.7%, followed by the interaction effect of depth and month, fishermen’s fishing tactics, sea surface salinity (SSS), chlorophyll a concentration (Chl a), and year, with contributions of 12.8%, 8.5%, 7.7%, 4.0%, and 3.1%, respectively. In summary, U. chinensis in the PRE was mainly distributed over areas with an SST of 22–29 °C, SSS of 32.5–34‰, Chl a of 0–0.3 mg × m−3, and water depth of 40–140 m. The distribution of U. chinensis in the PRE was affected by the western Guangdong coastal current, distribution of marine primary productivity, and variation of habitat conditions. Lower stock of U. chinensis in the PRE was connected with La Niña in 2008.

scholarly journals Spatiotemporal Variability of Surface Phytoplankton Carbon and Carbon-to-Chlorophyll a Ratio in the South China Sea Based on Satellite Data

2020 ◽  
Vol 13 (1) ◽  
pp. 30
Author(s):  
Wenlong Xu ◽  
Guifen Wang ◽  
Long Jiang ◽  
Xuhua Cheng ◽  
Wen Zhou ◽  
...  
Keyword(s):  
South China Sea ◽  
Chlorophyll A ◽  
South China ◽  
Satellite Data ◽  
Phytoplankton Biomass ◽  
The South China Sea ◽  
Spatiotemporal Variability ◽  
The South ◽  
Chl A ◽  
China Sea

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

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