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<p>The Arabian Gulf functions as an important regional carbon sink, yet limited knowledge exists regarding the dynamics of particulate organic carbon (POC) and its environmental drivers. This study investigates the spatial and temporal variability of POC and its relationships with sea surface temperature (SST) and chlorophyll-a (Chl-a) using MODIS/Aqua satellite data from 2003 to 2023. Results reveal distinct seasonality, with higher POC concentrations in winter and lower levels in summer. The average maximum trends derived from the two methods indicated decreases of approximately − 13.5&#xa0;mg m⁻³ yr⁻¹ for POC and − 0.14&#xa0;mg m⁻³ yr⁻¹ for Chl-a, while SST exhibited an increasing trend of approximately + 0.43&#xa0;°C yr⁻¹, particularly across the northern and western regions. Correlation analysis shows a positive association between POC and Chl-a and a negative one with SST. Machine learning models identify Chl-a and SST as key predictors of POC, achieving high accuracy (R² = 0.93, RMSE = 2.24&#xa0;mg/m³). The Geographically Weighted Regression (GWR) model was employed to analyse and map the spatial distribution of these relationships, revealing that POC increases by approximately 107.39&#xa0;mg/m³ per 1&#xa0;mg/m³ rise in Chl-a, while a 1&#xa0;°C rise in SST decreases POC by about 11.75&#xa0;mg/m³. These results improve understanding of carbon processes in Gulf waters and provide insights for effective regional carbon management.</p>

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Spatiotemporal variability of particulate organic carbon in relation to chlorophyll-a and sea surface temperature in the Arabian Gulf

  • 期刊论文

  • 发表日期：

    2026年7月16日

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  • Md Masudur Rahman,
  • Roman Shults,
  • Rajendran Sankaran,
  • Wanchang Zhang,
  • Mahfuzur Rahman,
  • Muhammad Usman

摘要

The Arabian Gulf functions as an important regional carbon sink, yet limited knowledge exists regarding the dynamics of particulate organic carbon (POC) and its environmental drivers. This study investigates the spatial and temporal variability of POC and its relationships with sea surface temperature (SST) and chlorophyll-a (Chl-a) using MODIS/Aqua satellite data from 2003 to 2023. Results reveal distinct seasonality, with higher POC concentrations in winter and lower levels in summer. The average maximum trends derived from the two methods indicated decreases of approximately − 13.5 mg m⁻³ yr⁻¹ for POC and − 0.14 mg m⁻³ yr⁻¹ for Chl-a, while SST exhibited an increasing trend of approximately + 0.43 °C yr⁻¹, particularly across the northern and western regions. Correlation analysis shows a positive association between POC and Chl-a and a negative one with SST. Machine learning models identify Chl-a and SST as key predictors of POC, achieving high accuracy (R² = 0.93, RMSE = 2.24 mg/m³). The Geographically Weighted Regression (GWR) model was employed to analyse and map the spatial distribution of these relationships, revealing that POC increases by approximately 107.39 mg/m³ per 1 mg/m³ rise in Chl-a, while a 1 °C rise in SST decreases POC by about 11.75 mg/m³. These results improve understanding of carbon processes in Gulf waters and provide insights for effective regional carbon management.