scholarly journals Seasonal coastal upwelling in the Bali Strait: a model study

2021 ◽  
Vol 944 (1) ◽  
pp. 012055
Author(s):  
A Suprianto ◽  
A S Atmadipoera ◽  
J Lumban-Gaol
Keyword(s):  
Chlorophyll A ◽  
Coastal Upwelling ◽  
Fish Distribution ◽  
Sea Surface ◽  
Monsoon Period ◽  
Easterly Wind ◽  
Chl A ◽  
Model Study ◽  
Velocity Surface ◽  
Upwelling Event

Abstract Bali Strait is part of fisheries management zone (WPP 573), where abundant fishery potential, of lemuru fish commodity. Here, physical oceanographic setting such as upwelling event plays an important role on maintaining high primary productivity and lemuru fish distribution. This study aims to describe physical process and dynamics of seasonal coastal upwelling using time-series datasets (2008 and 2014) of temperature, salinity, current velocity, surface chlorophyll-a (chl-a) from INDESO model and satellite imagery. The results showed that upwelling in the Bali Strait only during the southeast monsoon period when the south-easterly wind force surface Ekman drift of about 5.5 × 10−3 Sv flowing south-eastward (toward offshore). Upwelling event is characterized by minimum parameter of sea surface temperature (24.93 °C), and sea level anomaly (0.75 m), but maximum of surface chlorophyll-a (1.33 mg/m3). Furthermore, isotherm of 26 °C and Isohaline 33.7 psu are outcropped at sea surface in the center of upwelling zone. In contrast, during the nortwest monsoon period these isolines remain at deeper layer of about 80-90 m depth. Mean temperature-based upwelling index during peak of upwelling in August (1.19±0.19 °C). Upwelling impact on high abundance of lemuru fish (Sardinella sp.) production two month later after peak of chl-a.

scholarly journals STUDY ON CYCLONE INDUCED PHYTOPLANKTON BLOOM IN THE ARABIAN SEA THROUGH GAP-FREE RECONSTRUCTED CHLOROPHYLL-A DATA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1391-1396
Author(s):  
R. Shunmugapandi ◽  
S. Gedam ◽  
A. B. Inamdar
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Arabian Sea ◽  
Phytoplankton Bloom ◽  
Suitable Condition ◽  
Sea Surface ◽  
Cyclone Track ◽  
Chl A ◽  
The Impact

Abstract. Ocean surface phytoplankton responses to the tropical cyclone (TC)/storms have been extensively studied using satellite observations by aggregating the data into a weekly or bi-weekly composite. The reason behind is the significant limitations found in the satellite-based observation is the missing of valid data due to cloud cover, especially at the time of cyclone track passage. The data loss during the cyclone is found to be a significant barrier to efficiently investigate the response of chl-a and SST during cyclone track passage. Therefore it is necessary to rectify the above limitation to effectively study the impact of TC on the chlorophyll-a concentration (chl-a) and the sea surface temperature (SST) to achieve a complete understanding of their response to the TC prevailed in the Arabian Sea. Intending to resolve the limitation mentioned above, this study aims to reconstruct the MODIS-Aqua chl-a, and SST data using Data Interpolating Empirical Orthogonal Function (DINEOF) for all the 31 cyclonic events occurred in the Arabian Sea during 2003-2018 (16 years). Reconstructed satellite retrieved data covering all the cyclonic events were further used to investigate the chl-a and SST dynamics during TC. From the results, the exciting fact has been identified that only two TC over the eastern-AS were able to induce phytoplankton bloom. On investigating this scenario using sea surface temperature, it was disclosed that the availability of nutrients decides the suitable condition for the phytoplankton to proliferate in the surface ocean. Relevant to the precedent criterion, the results witnessed that the 2 TC (Phyan and Ockhi cyclone) prevailed in the eastern AS invoked a suitable condition for phytoplankton bloom. Other TC found to be less provocative either due to less intensity, origination region or the unsuitable condition. Thereby, gap-free reconstructed daily satellite-derived data efficiently investigates the response of bio-geophysical parameters during cyclonic events. Moreover, this study sensitised that though several TC strikes the AS, only two could impact phytoplankton productivity and SST found to highly consistent with the chl-a variability during the cyclone passage.

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 Chlorophyll-a Variability during Upwelling Events in the South-Eastern Baltic Sea and in the Curonian Lagoon from Satellite Observations

2020 ◽  
Vol 12 (21) ◽  
pp. 3661
Author(s):  
Toma Dabuleviciene ◽  
Diana Vaiciute ◽  
Igor E. Kozlov
Keyword(s):  
Baltic Sea ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Coastal Upwelling ◽  
Curonian Lagoon ◽  
The Baltic Sea ◽  
Chl A ◽  
Resolution Imaging ◽  
The Baltic ◽  
Eastern Baltic

Based on the analysis of multispectral satellite data, this work demonstrates the influence of coastal upwelling on the variability of chlorophyll-a (Chl-a) concentration in the south-eastern Baltic (SEB) Sea and in the Curonian Lagoon. The analysis of sea surface temperature (SST) data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua/Terra satellites, together with Chl-a maps from Medium Resolution Imaging Spectrometer (MERIS) onboard Envisat, shows a significant decrease of up to 40–50% in Chl-a concentration in the upwelling zone. This results from the offshore Ekman transport of more productive surface waters, which are replaced by cold and less-productive waters from deeper layers. Due to an active interaction between the Baltic Sea and the Curonian Lagoon which are connected through the Klaipeda Strait, coastal upwelling in the SEB also influences the hydrobiological conditions of the adjacent lagoon. During upwelling inflows, SST drops by approximately 2–8 °C, while Chl-a concentration becomes 2–4 times lower than in pre-upwelling conditions. The joint analysis of remotely sensed Chl-a and SST data reveals that the upwelling-driven reduction in Chl-a concentration leads to the temporary improvement of water quality in terms of Chl-a in the coastal zone and in the hyper-eutrophic Curonian Lagoon. This study demonstrates the benefits of multi-spectral satellite data for upscaling coastal processes and monitoring the environmental status of the Baltic Sea and its largest estuarine lagoon.

scholarly journals RELATIONSHIP BETWEEN CHLOROPHYLL-A AND SEA SURFACE TEMPERATUR WITH Sardinella lemuru CATCHING IN BALI STRAIT

2021 ◽  
Vol 15 (1) ◽  
pp. 12
Author(s):  
Niken Gustantia ◽  
Takahiro Osawa ◽  
I Gusti Bagus Sila Dharma ◽  
Wayan Sandi Adnyana
Keyword(s):  
Chlorophyll A ◽  
Sea Surface ◽  
Fishing Ground ◽  
Fish Production ◽  
Resource Potential ◽  
Chl A ◽  
Remote Sensing Technique ◽  
Fish Resources ◽  
Fish Catch ◽  
Total Fish

The Bali Strait is one of Indonesia's territorial waters that have high natural resource potential. The area is only about 2,500 km2 but has a high potential fishing ground. The Bali Strait has unique and dynamic waters that can cause fluctuations in fish production amount each year. The largest type of fish caught in the Bali Strait is lemuru (Sardinella lemuru), a fish found only in the Bali Strait. This fish plays a significant role in the economy of fishers in the Bali Strait. Each year the catch of lemuru has fluctuated, making fishing locations challenging to predict. Sea Surface Temperature (SST) and Chlorophyll-a (Chl-a) are oceanographic parameters that can affect the resources of the ocean. Oceanographic phenomena, such as upwelling, can also influence the condition of fish resources. Therefore, understanding the relationships between these factors is essential in practical fisheries management. Observation of oceanographic factors is very hard with the field observation due to time and cost limitations. The remote sensing technique is an efficient method to determine SST distributions and Chl-a concentrations using satellite imagery. This study analyzes SST and Chl-a concentration in the Bali Strait using the Global Change Observation Mission(GCOM-C) satellite and determines the correlation between Chl-a and SST with a total fish catch(lemuru) during 2019. The results showed the maximum average Chl-a concentration observed on August 1.62 mg/m3 and the lowest concentration observed on January 0.45 mg/m3, the maximum SST on March was 28.12° C, and on August (Dry season) with 22.40° C. The SST variable's influence provides a negative correlation (R = -0.209) with changes in lemuru catch, while the Chl-a parameter has a positive correlation (R = 0.375) with changes in the catch. The pattern of relationship between Chl-a with fish catching had a good relationship than the SST in 2019.Keywords: Bali Strait; Sardinella lemuru; SST; Chl-a.

scholarly journals High Chlorophyll-a Areas along the Western Coast of South Sulawesi-Indonesia during the Rainy Season Revealed by Satellite Data

2021 ◽  
Vol 13 (23) ◽  
pp. 4833
Author(s):  
Anindya Wirasatriya ◽  
Raden Dwi Susanto ◽  
Joga Dharma Setiawan ◽  
Fatwa Ramdani ◽  
Iskhaq Iskandar ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Primary Productivity ◽  
Rainy Season ◽  
Surface Wind ◽  
Western Coast ◽  
Southern Coast ◽  
Easterly Wind ◽  
Chl A ◽  
South Sulawesi ◽  
Upwelling Area

The southern coast of South Sulawesi-Indonesia is known as an upwelling area occurring during dry season, which peaks in August. This upwelling area is indicated by high chlorophyll-a (Chl-a) concentrations due to a strong easterly wind-induced upwelling. However, the investigation of Chl-a variability is less studied along the western coast of South Sulawesi. By taking advantages of remote sensing data of Chl-a, sea surface temperature, surface wind, and precipitation, the present study firstly shows that along the western coast of South Sulawesi, there are two areas, which have high primary productivity occurring during the rainy season. The first area is at 119.0° E–119.5° E; 3.5° S–4.0° S, while the second area is at 119.0° E–119.5° E; 3.5° S–4.0° S. The maximum primary productivity in the first (second) area occurs in April (January). The generating mechanism of the high primary productivity along the western coast of South Sulawesi is different from its southern coast. The presence of river runoff in these two areas may bring anthropogenic organic compounds during the peak of rainy season, resulting in increased Chl-a concentration.

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 VARIABILITY OF SEA SURFACE TEMPERATURE (SST) AND CHLOROPHYLL-A (CHL-A) CONCENTRATIONS IN THE EASTERN INDIAN OCEAN DURING THE PERIOD 2002–2017

2019 ◽  
Vol 16 (1) ◽  
pp. 55
Author(s):  
Michelia Mashita ◽  
Jonson Lumban-Gaol
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Sea Surface ◽  
Asia Pacific ◽  
Eastern Indian Ocean ◽  
Positive Anomaly ◽  
Chl A ◽  
Annual Variability

We analysed the variability of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) in the eastern Indian Ocean (EIO). We used monthly mean Chl-a and SST data with a 4-km spatial resolution derived from Level-3 Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) distributed by the Asia-Pacific Data-Research Center (APDRC) for the period 2002–2017. Wavelet analysis shows the annual and interannual variability of SST and Chl-a concentration in the EIO. The annual variability of SST and Chl-a is influenced by monsoon systems. During a southeast monsoon, SST falls while Chl-a increases due to upwelling. The annual variability of SST and Chl-a is also influenced by the Indian Ocean Dipole (IOD). During positive phases of the IOD (2006, 2012 and 2015), there was more intense upwelling in the EIO caused by the negative anomaly of SST and the positive anomaly of Chl-a concentration.

scholarly journals An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2769
Author(s):  
Yingying Gai ◽  
Dingfeng Yu ◽  
Yan Zhou ◽  
Lei Yang ◽  
Chao Chen ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Wind Waves ◽  
Biological Indicator ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
New Model ◽  
Chl A ◽  
Improved Model

Chlorophyll-a (Chl-a) is an objective biological indicator, which reflects the nutritional status of coastal waters. However, the turbid coastal waters pose challenges to the application of existing Chl-a remote sensing models of case II waters. Based on the bio-optical models, we analyzed the suppression of coastal total suspended matter (TSM) on the Chl-a optical characteristics and developed an improved model using the imagery from a hyper-spectrometer mounted on an unmanned aerial vehicle (UAV). The new model was applied to estimate the spatiotemporal distribution of Chl-a concentration in coastal waters of Qingdao on 17 December 2018, 22 March 2019, and 20 July 2019. Compared with the previous models, the correlation coefficients (R2) of Chl-a concentrations retrieved by the new model and in situ measurements were greatly improved, proving that the new model shows a better performance in retrieving coastal Chl-a concentration. On this basis, the spatiotemporal variations of Chl-a in Qingdao coastal waters were analyzed, showing that the spatial variation is mainly related to the TSM concentration, wind waves, and aquaculture, and the temporal variation is mainly influenced by the sea surface temperature (SST), sea surface salinity (SSS), and human activities.

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 MODIS Derived Sea Surface Salinity, Temperature, and Chlorophyll-a Data for Potential Fish Zone Mapping: West Red Sea Coastal Areas, Saudi Arabia

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2069 ◽  
Author(s):  
Saleh Daqamseh ◽  
A’kif Al-Fugara ◽  
Biswajeet Pradhan ◽  
Anas Al-Oraiqat ◽  
Maan Habib
Keyword(s):  
Linear Regression ◽  
Chlorophyll A ◽  
Red Sea ◽  
High Potential ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Chl A ◽  
Modis Data ◽  
The Impact

In this study, a multi-linear regression model for potential fishing zone (PFZ) mapping along the Saudi Arabian Red Sea coasts of Yanbu’ al Bahr and Jeddah was developed, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived parameters, such as sea surface salinity (SSS), sea surface temperature (SST), and chlorophyll-a (Chl-a). MODIS data was also used to validate the model. The model expanded on previous models by taking seasonal variances in PFZs into account, examining the impact of the summer, winter, monsoon, and inter-monsoon season on the selected oceanographic parameters in order to gain a deeper understanding of fish aggregation patterns. MODIS images were used to effectively extract SSS, SST, and Chl-a data for PFZ mapping. MODIS data were then used to perform multiple linear regression analysis in order to generate SSS, SST, and Chl-a estimates, with the estimates validated against in-situ data obtained from field visits completed at the time of the satellite passes. The proposed model demonstrates high potential for use in the Red Sea region, with a high level of congruence found between mapped PFZ areas and fish catch data (R2 = 0.91). Based on the results of this research, it is suggested that the proposed PFZ model is used to support fisheries in determining high potential fishing zones, allowing large areas of the Red Sea to be utilized over a short period. The proposed PFZ model can contribute significantly to the understanding of seasonal fishing activity and support the efficient, effective, and responsible use of resources within the fishing industry.

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