scholarly journals Estimation of Partial Pressure of CO2 (pCO2) Around Mount Krakatau waters, Sunda Straits, Indonesia

2021 ◽  
Vol 5 (1) ◽  
pp. 25-31
Author(s):  
Susanna Nurdjaman

The study aimed to develop the formula and validation the value of oceanic carbon dioxide partial pressure (pCO2sea) around Krakatau Waters in the Sunda Strait using parameters such as sea surface temperature (SST), sea surface salinity (SSS), and chlorophyll-a (Chl). Using observation data from different seasons (September 2017 and April 2018) The formulation of the empirical equation by using a multivariate polynomial regression method. The results of the study show that the empirical equation for estimating the pCO2 sea is as follows: : pCO2= -472.069+1044.043x log(SST) -435.897xlog(SSS) -5.03xlog (Chl).This formula can be applied for both seasons.  The results of the analysis of the T-student test and p-value showed a strong relationship between the SST parameters and pCO2 with a correlation of 0.91 then followed by salinity with a correlation of -0.82. Whereas chlorophyll-a holds a weak proportion with a correlation of 0.32. The increase in SST accelerates the solubility of CO2 from atmosphere to the sea thereby increasing CO2 sea concentration and increasing pCO2 sea. While the increase in salinity and chlorophyll-a only gives a weak effect

2019 ◽  
Vol 11 (8) ◽  
pp. 919 ◽  
Author(s):  
Ziyao Mu ◽  
Weimin Zhang ◽  
Pinqiang Wang ◽  
Huizan Wang ◽  
Xiaofeng Yang

Ocean salinity has an important impact on marine environment simulations. The Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite in the world to provide large-scale global salinity observations of the oceans. Salinity remote sensing observations in the open ocean have been successfully applied in data assimilations, while SMOS salinity observations contain large errors in the coastal ocean (including the South China Sea (SCS)) and high latitudes and cannot be effectively applied in ocean data assimilations. In this paper, the SMOS salinity observation data are corrected with the Generalized Regression Neural Network (GRNN) in data assimilation preprocessing, which shows that after correction, the bias and root mean square error (RMSE) of the SMOS sea surface salinity (SSS) compared with the Argo observations can be reduced from 0.155 PSU and 0.415 PSU to −0.003 PSU and 0.112 PSU, respectively, in the South China Sea. The effect is equally significant in the northwestern Pacific region. The preprocessed salinity data were applied to an assimilation in a coastal region for the first time. The six groups of assimilation experiments set in the South China Sea showed that the assimilation of corrected SMOS SSS can effectively improve the upper ocean salinity simulation.


Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2769
Author(s):  
Yingying Gai ◽  
Dingfeng Yu ◽  
Yan Zhou ◽  
Lei Yang ◽  
Chao Chen ◽  
...  

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.


Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2069 ◽  
Author(s):  
Saleh Daqamseh ◽  
A’kif Al-Fugara ◽  
Biswajeet Pradhan ◽  
Anas Al-Oraiqat ◽  
Maan Habib

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.


2018 ◽  
Author(s):  
Young-Tae Son ◽  
Jae-Hyoung Park ◽  
SungHyun Nam

Abstract. We present intensive observational data of surface chlorophyll-a bloom episodes occurring over several days in the summers of 2011, 2012, and 2013, accompanying the equatorward advection of low sea-surface salinity (SSS) water near the east coast of Korea. Time-series analysis of meteorological and oceanographic (physical and biochemical) parameter data, such as chlorophyll fluorescence (CF) from surface mooring, ocean color (chlorophyll a and total suspended sediment), sea surface height (satellite-derived), and serial hydrographic data (from in-situ measurements) were used to investigate the relationship between surface bloom events and changes in seawater characteristics and currents. In the summers of the three years, a total of 10 bloom events (E01–E10) were identified where the surface CF was significantly (> 2 μg/l) enhanced over a relatively long (> 1 day) period. The bloom events in the summers of 2011 and 2012 accompanied low or decreasing SSS for several days to a week after heavy rainfalls at upstream stations and equatorward currents. Unlike the typical 8 of the 10 events (80 %), E07 was potentially derived from the onshore advection of high CF offshore water of southern origin into the coastal zone near the mooring, whereas E10 is likely prevailed by offshore advection of high CF plume water trapped by the coastal area. Contrasting with many coastal systems, these findings indicate that event-scale productivity near the east coast of Korea in summer is not controlled by local blooms triggered by either nutrients or light availability, but by the equatorward and cross-shore advections of high CF plume water.


2018 ◽  
Vol 15 (16) ◽  
pp. 5237-5247
Author(s):  
Young-Tae Son ◽  
Jae-Hyoung Park ◽  
SungHyun Nam

Abstract. We present intensive observational data of surface chlorophyll a bloom episodes occurring over several days in the summers of 2011, 2012 and 2013, accompanying the equatorward advection of low sea surface salinity (SSS) water near the east coast of the Korean Peninsula. Time-series analysis of meteorological and oceanographic (physical and biochemical) parameter data, such as chlorophyll fluorescence (CF) from surface mooring, ocean color (chlorophyll a and total suspended sediment), sea surface height (satellite-derived) and serial hydrographic data (from in situ measurements), was used to investigate the relationship between surface bloom events and changes in seawater characteristics and currents. In the summers of the 3 years, a total of 10 bloom events (E01–E10) were identified during which the surface CF was significantly (> 2 µg L−1) enhanced over a relatively long (> 1 day) period. The bloom events in the summers of 2011 and 2012 were accompanied by low or decreasing SSS for several days to a week after heavy rainfall at upstream stations and equatorward currents. Unlike the typical 8 of the 10 events (80 %), E07 was potentially derived from the onshore advection of high CF offshore water of southern origin into the coastal zone near the mooring, whereas E10 possibly prevailed by offshore advection of high CF plume water trapped by the coastal area. Contrasting with many coastal systems, these findings indicate that event-scale productivity near the east coast of the Korean Peninsula in summer is not controlled by local blooms triggered by either nutrients or light availability, but by the equatorward and cross-shore advection of high CF plume water.


2017 ◽  
Author(s):  
Sayaka Yasunaka ◽  
Eko Siswanto ◽  
Are Olsen ◽  
Mario Hoppema ◽  
Eiji Watanabe ◽  
...  

Abstract. We estimated monthly air–sea CO2 fluxes in the Arctic Ocean and its adjacent seas north of 60° N from 1997 to 2014, after mapping partial pressure of CO2 in the surface water (pCO2w) using a self-organizing map (SOM) technique incorporating chlorophyll-a concentration (Chl-a), sea surface temperature, sea surface salinity, sea ice concentration, atmospheric CO2 mixing ratio, and geographical position. The overall relationship between pCO2w and Chl-a is negative in most regions when Chl-a ≤ 1 mg m−3, whereas there is no significant relationship when Chl-a > 1 mg m−3. In the Kara Sea and the East Siberian Sea and the Bering Strait, however, the relationship is typically positive in summer. The addition of Chl-a as a parameter in the SOM process enabled us to improve the estimate of pCO2w via better representation of its decline in spring, which resulted from biologically mediated pCO2w reduction. Mainly as a result of the inclusion of Chl-a, the uncertainty in the CO2 flux estimate was reduced, and a net annual Arctic Ocean CO2 uptake of 180 ± 130 TgC y−1 was determined to be significant.


2015 ◽  
Vol 36 (2) ◽  
pp. 51-70 ◽  
Author(s):  
Sam Wouthuyzen

Observations on oceanographic parameters using remote sensing techniques intensively have been done for more than 3 decades for estimating and mapping the sea surface temperature (SST) and the abundance of phytoplankton expressed as the concentration of chlorophyll-a and applied them in studying the ocean phenomenon. As a result, the product of these 2 parameters for all over the oceans in the world has been established and available in daily basis. However, on the contrary, there is still limited application for sea surface salinity (SSS) which is also one of the most important oceanographic features. This paper describes a novel method of deriving SSS from remotely sensed ocean color. The method is based on two important observations of optical properties in regions of freshwater influences. The first is the strong effect of Colored Dissolved Organic Matter (CDOM or yellow substance) on ocean color when present in relatively high concentrations. The second is the close relationship between salinity and CDOM originating from fresh water runoff. In this paper, these relationships are demonstrated for the Jakarta Bay, Indonesia. The MODIS sensor in Terra and Aqua satellites imageries and 10 in situ measurements conducted near-simultaneously with the satellites over flight over the bay in 2004 and 2006 were implemented for deriving CDOM and SSS. The empirical relationships demonstrated in this study allow the satisfactory prediction of CDOM and SSS in the Jakarta Bay from remotely sensed ocean color. The root mean square (r.m.s) error difference between the observed and predicted parameters are 0.14 m-1 and 0.93 psu for CDOM g440 g and SSS, respectively, over a range of salinity from 24 to 33 psu. This range is in good agreement with field surveys. Parameters that may influence CDOM, such as Chlorophyll-a (CHL-a) and total suspended material (TSM) concentrations were also analyzed. Results showed that there were no relationship at all between CDOM and CHL-a, and between CDOM and TSM. These indicate that phytoplankton plays a minor role in regulating CDOM abundance, and also suggest that CDOM contribution from sediment and/or from sediment resuspension is negligible. Thus, CDOM sources in the Jakarta Bay are mainly from riverine inputs. SSS maps created from the satellite-retrieved ocean color identify features in the surface salinity distribution such as salinity front of > 32 psu that migrated in and out of the bay according to seasons. Therefore, the ability to obtain synoptic views of SSS such as presented in this paper provides great potential in furthering the understanding of coastal environments.


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