Abstract
In climate research, an important task is to characterise the relationships between Essential Climate Variables (ECVs). Here, satellite-derived data sets have been used to examine the seasonal cycle of phytoplankton (chlorophyll concentration) in the waters off Somalia, and its relationship to aerosols, winds and Sea Surface Temperature (SST). Chlorophyll-a (Chl-a) concentration, Aerosol Optical Thickness (AOT), A° ngstro¨m Exponent (AE), Dust Optical Thickness (DOT), Sea Surface Temperature (SST) and sea-surface wind data for a 16-year period were assembled from various sources. The data were used to explore whether there is evidence in the data to show that dust aerosols enhance Chl-a concentration in the study area. The Cross 11 Correlation Function (CCF) showed highest positive correlation (r2=0.3) in the western Arabian Sea when AOT led Chl-a by 1 to 2 time steps (here, 1 time step is 8 days). A 2o□ 2obox off Somalia was selected for further investigations. The correlations of alongshore wind speed, Ekman Mass Transport (EMT) and SST with Chl-a were higher than that of AOT, for a lag of 8 days. When all four variables were considered together in a multiple linear regression, the increase in r2 associated with the AOT is only about 0.02, a consequence of covariance among AOT, SST, EMT and alongshore wind speed. The AOT data show presence of dust aerosols most frequently during the summer monsoon season (June- September). When the analyses were repeated for the dust aerosol events, the correlations were generally lower, but still significant. Again, the inclusion of DOT in the multiple linear regression increased the correlation coefficient by only 2%, indicating minor enhancement in Chl-a concentration. Interestingly, during summer monsoon season, there is a higher probability of finding more instances of positive changes in Chl-a after one time step, regardless of whether there is dust aerosol or not. On the other hand, during the winter monsoon season (November-December) and rest of the year, the probability of Chl-a enhancement is higher when dust aerosol is present than when dust aerosol is present than when it is absent. The phase relationship in the annual climatologies of Chl-a and AOT
Highlights
Phytoplankton, Sea-Surface Temperature (SST), sea-surface winds and aerosols are all Essential Climate Variables (ECVs) identified by the Global Climate Observation System (GCOS, 2011) as being worthy of sustained global observations at high spatial resolution and over long time scales, to aid studies of Earth’s climate and climate change
We examine the relationships of Chl-a with winds, Sea Surface Temperature (SST), Aerosol Optical Thickness (AOT) and dust aerosols in the western Arabian Sea, at a selected site off Somalia
The region off Somalia shows high positive correlation between Chl-a and NASA-AOT and it is located along the path of winds carrying dust aerosols emanating from South Asia, South-West Asia, North Africa (Sahara) and the eastern Horn of Africa (Pease et al, 1998; Ginoux et al, 2001; Goudie and Middleton, 2001; Prospero et al, 2002; Léon and Legrand, 2003)
Summary
Phytoplankton, Sea-Surface Temperature (SST), sea-surface winds and aerosols are all Essential Climate Variables (ECVs) identified by the Global Climate Observation System (GCOS, 2011) as being worthy of sustained global observations at high spatial resolution and over long time scales, to aid studies of Earth’s climate and climate change. Dust aerosols, transported by winds over the ocean, can be an important source of micronutrients such as iron, essential for phytoplankton growth (Duce and Tindale, 1991; Martin et al, 1991, 1994; Prospero et al, 2002; Cropp et al, 2005; Jickells et al, 2005; Mahowald et al, 2005; Meskhidze et al, 2005; Gallisai et al, 2014), with the proviso that not all the iron contained in dust particles is usable by phytoplankton. Feedback mechanisms (both positive and negative) have been proposed between dimethyl sulphide in the atmosphere of phytoplanktonic origin and the Earth’s radiation budget, via aerosols (Charlson et al, 1987; Lovelock, 2006)
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