Monthly mean satellite derived Chl-a, aerosols, wind, SST, PAR, and turbidity datasets were used to investigate the possible factors regulating phytoplankton variability in the Persian Gulf. The spatial correlation analysis revealed two distinct regions of SST and PAR, and a relatively uniform spatial correlation pattern of the other parameters. The cross correlation between aeolian dusts and Chl-a was significantly positive with 1–3 months offset. The pattern of spatial correlation between Chl-a and SST was positive in the shallow regions without time lag, and was negative with time offset of 3–5 months in deeper regions. The cross correlation between Chl-a and north-ward winds were positive with time lags of 1–3 months. Vertical mixing under the influence of north-ward winds in the deeper region, availability of light and nutrients in the shallow regions, and dust fertilizations over the whole area were suggested to be the major controlling factors regulating phytoplankton growth.

Spatial and temporal variations and trends of SST and Chl-a in the Persian Gulf were evaluated using MODIS data from 2002 to 2018. Trend indicator and key features were built up based on Mann-Kendall test, Hurst exponents and Wavelet Transform (WT) techniques to investigated the volatilities, trend estimation and persistence of original and WT signals. The key features revealed that the Chl-a pattern is heterogeneous in both time and spatial scale, whereas SST pattern is more homogenous. Trend analysis of the study area showed identifiable and sustainable trend with maximum tendency to decrease of Chl-a, and increase of SST. More than 48% of the study area is under slight decrease, and about 20% area mostly located at the northern parts show slight increase of Chl-a values. The presented methodology is applicable to the data signals that keep the range of inter-annual approximation components of DWT not less than scale level-4.

Since 2011, huge amounts of Sargassum algae are detected in the equatorial Atlantic, causing large strandings events on the coasts of the West Indies, Brazil and West Africa. The distribution of this stock shows strong annual and interannual variability, whose drivers are not settled yet. Here we use satellite Sargassum observations from MODIS and currents from an ocean reanalysis to simulate the passive transport of algae in 2017. Wind effect was necessary to fit the observed distribution. Simulations reasonably reproduce the satellite monthly distribution for up to seven months, confirming the prominent role of transport in the distribution cycle. Annual cycle appears as a zonal exchange between eastern (EAR) and western accumulation regions (WAR). EAR is well explained by advection alone, with sharp meridional distribution controlled by converging currents below the inter-tropical Convergence Zone. Instead, WAR is not explained by advection alone, suggesting local growth.