The Spatial-Temporal Variability of Chlorophyll-a across the Eastern Indonesian Seas Region Using Sentinel-3 OLCI

doi:10.21203/rs.3.rs-3618539/v1

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The Spatial-Temporal Variability of Chlorophyll-a across the Eastern Indonesian Seas Region Using Sentinel-3 OLCI

https://doi.org/10.21203/rs.3.rs-3618539/v1

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published 23 Sep, 2024

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The Eastern Indonesian Seas are among the most biodiverse maritime habitats. Changing chlorophyll-a concentrations affects primary productivity, and ecological changes. Monitoring chlorophyll levels is crucial for ocean health and nutrient availability. High-resolution ocean color data from the Sentinel-3 Ocean and Land Color Instrument allows for global chlorophyll monitoring. This study analyzes how monsoon activity affects chlorophyll distribution in eastern Indonesian oceans. Monthly Chlorophyll-a Concentration Retrieval with Sentinel-3 Ocean and Land Color Instrument Imageries was utilized to study the Eastern Indonesian Seas region from 2016-2021. The Case-2 Regional Coast Color processor, a neural network-based algorithm, was applied to all images for atmospheric correction processing and for ocean color products’ extraction. The distribution of chlorophyll-a in the eastern region of Indonesia varies significantly, with average concentrations ranging from 0.09 to 0.45 mg/m3 in the Banda Sea, Arafura Sea, Flores Sea, and Timor Sea. The Asian-Australian Monsoon System significantly impacts these patterns, with chlorophyll-a levels increasing during the Southeast Monsoon and decreasing during the Northwest Monsoon, particularly in areas with annual upwelling events.

chlorophyll-a

Sentinel-3

OLCI

C2RCC

Eastern Indonesia seas region

The marine ecosystem is a highly complex and continually shifting organism that plays significant importance in the biogeochemical cycles of the Earth and provides essential support for a wide range of ecological and socioeconomic processes [Refulio-Coronado et al., 2021; Saunders et al., 2017). The chlorophyll-a concentration is a significant parameter among the several indicators used to assess the health of marine environment (Franklin et al., 2020; Park et al., 2015). This resource provides significant insights into primary productivity and phytoplankton biomass. Phytoplankton, being the fundamental constituents of marine food webs, have a significant influence on the trophic organisation and carbon dynamics within oceanic ecosystems. Therefore, it is important to have a comprehensive understanding of the geographical and temporal patterns in the distribution of chlorophyll-a in order to acquire useful insights on the dynamics of the marine environment. (Lu et al., 2021; Bierman, et al., 2011).

The Indonesian seas play an essential role in the climate system and influences interactions between oceans on a global scale. The Indonesian Through Flow (ITF), the flow of water from the Pacific Ocean to the Indian Ocean through Indonesian waters mixed with regional water masses, makes the water conditions in Indonesia unique (Gordon, 2005). Indonesia has marine areas with abundant marine resources. Indonesia's marine biodiversity is supported by the fertile waters of Indonesia, which are certainly rich in phytoplankton. The Indonesian region is subject to the impact of the Asian monsoon, particularly the Northwest Monsoon (NWM) from October to April, and the Australian monsoon, known as the Southeast Monsoon (SEM), from April to October. These monsoons follow an annual cycle (Hermawan, 2015). These monsoon phenomena cause changes in the direction of water masses in some areas of Indonesian waters that affect chlorophyll-a concentrations. The upwelling phenomenon occurs during the SEM, and the downwelling phenomenon occurs during the NWM (Gordon, 2005).

The Indonesian Seas, which includes a wide range of waterways, islands, and straits, is distinguished by its notable marine biodiversity and substantial oceanographic complexity. The geographical area in question plays a crucial role as an essential link between the Pacific and Indian Oceans (Sprintall and Révelard, A, 2014). It is home to a wide array of ecosystems, encompassing various habitats such as coral reefs and deep-sea trenches. The complex interaction between ocean currents, upwelling phenomena, inputs from waterways and local physicochemical circumstances results in a diverse pattern of chlorophyll-a dynamics (Nazeer, et al., 2016).

The Eastern Indonesian seas region, as shown at Fig. 1, are widely acknowledged as being among the most biodiverse marine ecosystems on a worldwide scale (Gonzales, A T et al., 2019; Padilla J E & Hudson A et al., 2019). Changes in chlorophyll-a concentration have a direct effect on primary productivity, which has big effects on how the food web works and how ecosystems change over time (Zhang K. et al., 2023). Understanding the subtleties of the distinctive biodiversity in this area requires a comprehensive knowledge of the variations of chlorophyll-a.

Numerous factors influence the variation of chlorophyll-a throughout the Indonesian Seas Region. Physical forces, such as monsoon winds, ocean currents, and coastal upwelling, can have a substantial effect on nutrient transport and mixing, and thus on phytoplankton growth [Ningsih et al., 2013; Yu et al., 2019, Mandal, et al., 2022]. These activities have a large impact on the distribution of nutrients and plankton, which affects chlorophyll-a levels. Insights into the linked oceanographic mechanisms that control nutrient transport, mixing, and ecosystem dynamics can be gained by studying the spatial-temporal variability of chlorophyll-a in this region. Additionally, anthropogenic inputs, such as nutrient discharges from land-based activities, further confound chlorophyll-a's spatial distribution. Climate change and ocean warming can alter stratification patterns, which in turn influences nutrient availability and phytoplankton blooms (Asch, et al., 2019).

The monitoring of the concentration of chlorophyll contributes significantly to the comprehension of the ocean's health. This study delivers valuable insights into the accessibility of nutrients and the overall condition of the marine ecosystem. The Sentinel-3 Ocean and Land Color Instrument (OLCI) provides frequent and comprehensive worldwide coverage of ocean color data at a high resolution.

High spatial and temporal resolution makes it possible to look at chlorophyll levels in the world's oceans on a regular basis and in large amounts. The primary aim of this study is to examine the influence of monsoon activity on the variation of chlorophyll distribution in the seas of the eastern Indonesian region. This investigation will be conducted utilizing data from the Sentinel-3 Ocean and Land Color Instrument (OLCI).

Study Area

This study emphasizes the spatio-temporal variability of chlorophyll-a around the Eastern Indonesian Seas Region, which range between 11°S and 8°N latitude and 115°E and 145°E longitude. The boundaries of the region encompass a region extending from the western Pacific Ocean to the eastern Indian Ocean. The seas included in the publication "Limit of Oceans and Seas" by the International Hydrographic Organisation (IHO) in 1953 include the Banda Sea, Flores Sea, Sulawesi Sea, Maluku Sea, Seram Sea, Halmahera Sea, Timor Sea, Arafura Sea, and Savu Sea (IHO, 1953). (shown at Fig. 1).

Chlorophyll-a

Chlorophylls are identified as compounds that absorb light and are essential to the process of photosynthesis. The process of photosynthesis converts carbon dioxide (CO₂) into organic matter using the energy in the sun. The quantification of chlorophylls can yield insights into the photosynthetic capacity of the heterotrophic community or the capacity of primary production to be consumed (Zhu et al., 2021). The net primary production of the remaining available carbon takes place in the ocean and is facilitated by phytoplankton, which are microscopic plants. In the process of monitoring phytoplankton populations in space and time, field data sets pertinent to ocean productivity estimates have been compiled. A considerable positive correlation was observed between phytoplankton and chlorophyll-a in marine water. Chlorophyll-a constitutes most phytoplankton pigments (Yun et al., 2019). Most marine productivity models incorporate chlorophyll-a as a crucial component in determining the primary productivity of the ocean (D. Nugroho et al. 2018). Initially, the criterion for ocean productivity data in Indonesian littoral and marine waters was a "chlorophyll-based" model. Chlorophyll-a levels in marine water are variable according to nutrient and radiation availability. The magnitude of chlorophyll-a independence is demonstrated by trends at various locations in Indonesia (Munandar B et al., 2023), whereas nutrient levels reflect the inherent distinctions between low, moderate, and high biological productivity. A temperature-dependent description of chlorophyll-a in transitional is utilized to generalize its net primary production as a function of available light, chlorophyll, and specific photosynthetic efficiency. The advancement towards productivity modeling was additionally acknowledged for the chlorophyll concentration, which is derived from carbon concentration and serves as a metric for phytoplankton biomass. Utilizing particulate scattering coefficients as a spectral matching algorithm for phytoplankton pigment absorption and colored dissolved organic carbon absorption (Behrenfeld et al. 2005; Li X., et al., 2021). There exists a correlation between the light scattering properties of phytoplankton biomass and the total particulate carbon concentration (Campbell, J. D. et al., 2002; I. Iskandar et al. 2009).

Monthly Chlorophyll-a Concentration Retrieval with Sentinel-3 OLCI Imageries

The Sentinel-3 Mission is a joint project between the European Space Agency (ESA) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). Its primary objective is to facilitate comprehensive observations of both oceanic and terrestrial environments. This involves the precise measurement of surface topography, surface temperature, and surface colour. Two satellites, specifically identified as Sentinel-3A and Sentinel-3B, were successfully sent into orbit on the dates of February 16th, 2016, and April 25th, 2018, respectively. Every satellite is equipped with three primary sensors, namely the ocean and land colour instrument (OLCI), the sea and land surface temperature radiometer (SLSTR), and the SAR radar altimeter (SRAL). Among them, the OLCI instrument is designed to extract the radiances or reflectance of the land and water objects which are available in Sentinel-3 OLCI Level-1 (Shimoda et al., 2012).

Several Sentinel-3 OLCI Level-1 imageries in the Eastern Indonesian Seas region during 2016–2021 were utilized. Each Level-1 image contains top of atmosphere (ToA) radiances for the 21 spectral bands in OLCI sensor with spatial resolution of 300 m and revisit time of around 5 days. Temporally, there were at least 5 different images at the same location but acquired at distinct times during a specific month; and an image among them which has the lowest percentage of cloud coverages was used to represent the radiances during that month. While spatially, eight temporally selected images at different locations were required to cover the whole region; in which they were further mosaicked and subsetted.

Furthermore, the Case-2 Regional Coast Color (C2RCC) processor, a neural network (NN)-based algorithm containing of multiple neural networks and was trained with around 5 million labelled data (Doerffer & Schiller., 2007; Fan Yongzhen et al., 2017), were then applied via Sentinel-3 Toolbox in SNAP to all images for atmospheric correction processing and for ocean color products’ extraction. The first NN is to transform the ToA radiances to water leaving reflectance for all the spectral bands. The input to the first NN are Sentinel 3 OLCI ToA Radiance bands O1-O11, O14 (778 nm), O16 (865 nm), O18 (885 nm), and O19 (900 nm), as well as solar zenith angle (degrees), viewing zenith angle (degrees), difference between solar and viewing azimuth angle (degrees), surface pressure (from aux data), ozone (from aux data), water temperature (°C), and salinity (Practical Salinity Unit). Those required input are available in its Level-1 product. Then, the first NN produces water-leaving radiation reflection (RLw) which is further utilized again in the second NN. The data required in the NN are 9 RLw (O1-O8 and O10) and three angles (solar zenith angle, view zenith angle, and viewing azimuth angle). Five IOPs are obtained as the output where one of which is absorption by phytoplankton pigments. The absorption will be converted into absorption by phytoplankton (a_pig) and calculated into chlorophyll-a concentration (chla) using the following formula (Doerffer, 2010).

𝑐ℎ𝑙𝑎 = \({22 \text{a}\_\text{p}\text{i}\text{g}\left(443\right)}^{\text{1,04}}\) …………………………………………………………. (1)

In total, there were 57 chlorophyll-a images over the study area from April 2016 to December 2021. The images were then reprojected to WGS1984 with the output grid of 0.05° and interpolation radius of 0.1° for visualization and analysis along with the movement of ocean current. The current data is Altimetric Geostrophic Current data from Global Total Surface and 15m Current data (https://data.marine.copernicus.eu/product)

This section presents results and discussion. It consists of a spatial and temporal pattern of chlorophyll variation across the seas around the eastern Indonesian region.

According to the data presented in Fig. 2, there is a significant variety in the spatial distribution of chlorophyll-a concentrations within the Arafura Sea. The observed values vary from a minimum of 0.02 mg/m³ to a maximum of 30 mg/m³. In contrast, oceanic regions situated at considerable distances from land show a tendency to lower concentration. This phenomenon could occur because of coastal upwelling, an inflow of nutrients transported by rivers to the coastal region, or the presence of coastal environmental factors leading to elevated concentrations of chlorophyll-a in coastal areas (Susanto et al., 2006).

The white parts in Fig. 2 indicate regions where chlorophyll-a concentration measurements are unknown. The absence of data was caused by clouds covering the Arafura Sea region during the Sentinel-3 satellite’s recording. Indonesia is a country whose 2/3 of its territory is controlled by the ocean, with the remaining half being land. Consequently, Indonesian country is regularly covered by huge clouds (Hermawan, 2015). In the chlorophyll-a distribution map (Fig. 2), it seems that the coastal areas around Merauke (in the Arafura Sea) exhibit very high chlorophyll-a concentrations throughout the year.

Concentrations of chlorophyll-a in the seas of eastern Indonesia region tend to be highest during SEM, which reaches its highest points in June, July, and August, when long-term variations in chlorophyll-a are considered. During the NWM, which reaches its highest points in December, January, and February, chlorophyll-a levels are typically lowest. The subsequent months contain two transitional seasons, namely Season I (March, April, and May) and Season II (September, October, and November), which continue to be affected by the following season. The Indonesian region experiences a significant impact from the Asian-Australian Monsoon System due to its strategically located geographical situation between the Asian and Australian continents. (Susanto et al., 2006).

In addition, the continuous change follows a pattern that is dependent on the seasons. The current tends to migrate from the southeast (the Arafura Sea) to the northwest, in the direction of the Banda, Flores, and Timor Seas. This movement occurs during SEM. The current tends to flow from the northwest (in the direction of the Banda Sea, Flores Sea, and Timor Sea) to the southeast (in the direction of the Arafura Sea) while the NWM is in effect. According to Sprintall et al. (2014) and Sprintall and Révelard (2014), the Asian-Australian monsoon has significant effects on the circulation and transport of water masses in the Indonesian Sea. The Asian-Australian monsoon is responsible for producing upwelling by blowing dry winds from the southeast during the Southeast Monsoon (SEM) and moist winds from the northwest during the Northwest Monsoon (NWM).

Figure 3 illustrates the impact of the Asian-Australian Monsoon System on the marine environments surrounding eastern Indonesia. From 2016 to 2021, the average chlorophyll-a concentration in the Banda Sea, Arafura Sea, Flores Sea, and Timor Sea was recorded monthly. The annual variation in the average chlorophyll-a concentrations of the Banda and Arafura Seas is shown in Figs. 3a and 3b, respectively. The Banda Sea exhibits a chlorophyll-a concentration that varies between 0.09 and 0.45 mg/m^3. In contrast, the Arafura Sea exhibits an average chlorophyll-a concentration that varies between 0.21 and 1.78 mg/m^3. Annual variations in chlorophyll-a concentrations are observed in the Banda Sea and the Arafura Sea. During the SEM season, the chlorophyll-a concentration phase was observed to be high, whereas it was found to be low during the NWM season. The findings of the Capuano et al. (2022) study yielded comparable results, with chlorophyll-a reaching its maximum during the SEM and gradually diminishing during the NWM.

However, this research did not observe seasonal chlorophyll-a patterns in any of the investigated areas. The average chlorophyll-a concentrations in the Flores and Timor Seas show an absence of seasonal pattern and appear to be random from 2016 to 2021, as displayed in Figs. 3c and 3d. The Flores Sea presents a chlorophyll-a concentration that varies between 0.1 mg/m³ and 0.52 mg/m³. In contrast, the Timor Sea exhibits an average chlorophyll-a concentration ranging between 0.09 and 0.63 mg/m³. The fluctuations of chlorophyll-a is associated with the upwelling phenomenon, as the monsoon causes substantial control over the upwelling process in the Indonesian Sea region, according to Purba & Khan (2019). Throughout the year, the Banda and Arafura Seas contain the most permanent upwelling sites in Indonesia. Permanent upwelling areas in the Flores Sea encompass a negligible portion of the coastline. In contrast, permanent upwelling locations do not exist in the Timor. The absence of seasonal flow patterns in chlorophyll-a in the Flores and Timor Seas seems to be due to this reason.

The concentration ranges of chlorophyll-a content vary throughout the four oceans. According to the data presented in Fig. 3, the Arafura Sea samples showed the highest average concentrations of chlorophyll-a, followed by the Timor Sea, Flores Sea, and Banda Sea. The Arafura Sea shows a notably situated average chlorophyll-a concentration, which can be related to several factors. These include the presence of wide and ongoing upwelling areas, the nutrient-rich coastal environment impacted by river supplies, and the shallow sea depth that allows most effective phytoplankton growth due to sufficient light penetration (Capuano et al., 2022; Susanto et al., 2006). The Arafura Sea's fertility is demonstrated by the abundant capture of marine fish and its strong association with chlorophyll-A levels, as indicated by Hadiyanto et al., 2018.

The spatial and temporal distribution of chlorophyll-a in the seas surrounding the eastern region of Indonesia demonstrates variations in the estimated values are performed. The typical chlorophyll-a concentration in the Banda Sea shows a variability of 0.09 mg/m³ to 0.45 mg/m³. Additionally, the Arafura Sea exhibits a range of concentrations between 0.21 mg/m³ and 1.78 mg/m³. The typical chlorophyll-a concentration in the Flores Sea varies between 0.1 mg/m³ and 0.52 mg/m³. Continuing the above, the range in the Timor Sea is between 0.09 and 0.63 mg/m³. Furthermore, the Indo-Australian Monsoon System strongly impacts the environmental patterns observed in the surrounding area of Indonesia. This has a big effect on the changes in chlorophyll-a levels in the Banda Sea and the water nearby. In the Banda Sea and nearby areas, the number of chlorophyll-a increases during the Southeast Monsoon (SEM) and decreases during the Northwest Monsoon (NWM). This is especially true in places where upwelling events happen all year long.

Acknowledgment

This research was funded by Directorate of Research and Community Service Institut Teknologi Sepuluh Nopember, Ministry of Education and Culture, Research, and Technology in accordance with the ITS Fund Partnership Research Implementation Agreement Batch 2: Year 2023 Master Contract Number: 2247/PKS/ITS/2023, dated June 26, 2023, Researcher Contract Number: 2250/PKS/ITS/2023, dated June 26, 2023

Author Contributions: Eko Yuli Handoko and Muhammad Aldila Syariz conceived the experiments. Eko Yuli Handoko, Noorlaila Hayati, and Megivareza designed and performed the experiments; Eko Yuli Handoko, Muhammad Muryono, and Chung-Yen Kuo wrote the manuscript. All authors analysed the data, reviewed the study, and edited the manuscript.

Conflicts of Interest: The authors declare no conflict of interest.

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The Spatial-Temporal Variability of Chlorophyll-a across the Eastern Indonesian Seas Region Using Sentinel-3 OLCI

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Abstract

Figures

Introduction

Study Area

Method

Chlorophyll-a

Monthly Chlorophyll-a Concentration Retrieval with Sentinel-3 OLCI Imageries

𝑐ℎ𝑙𝑎 = \({22 \text{a}\_\text{p}\text{i}\text{g}\left(443\right)}^{\text{1,04}}\) …………………………………………………………. (1)

Results and discussion

Conclusion

Declarations

References

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