Chlorophyll-Specific Absorption Coefficient of Phytoplankton in World Oceans: Seasonal and Regional Variability

This study investigates the seasonal and regional variability in the chlorophyll-specific absorption coefficient of phytoplankton at 443 nm (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>a</mi></mrow><mrow><mi mathvariant="italic">ph</mi></mrow><mrow><mo>*</mo></mrow></msubsup><mrow><mo stretchy="false">(</mo><mn>443</mn><mo stretchy="false">)</mo></mrow></mrow></semantics></math></inline-formula>; unit: m² mg⁻¹) in surface oceans. It is focused on the time series data derived from the satellite products of chlorophyll-a (Chl-a) concentration and the phytoplankton absorption coefficient. Global estimates of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>a</mi></mrow><mrow><mi mathvariant="italic">ph</mi></mrow><mrow><mo>*</mo></mrow></msubsup><mrow><mo stretchy="false">(</mo><mn>443</mn><mo stretchy="false">)</mo></mrow></mrow></semantics></math></inline-formula> reveal a decreasing gradient from the open ocean toward the coastal environment, with considerable spatial variance. Seasonal variations are prominent over most oceans, resulting in substantial deviations from the climatological means. A sinusoidal model was fitted to the monthly time series data to characterize the annual and semiannual features. The amplitudes and the phases of the monthly data were latitudinally dependent. The occurrence times of the maximum <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>a</mi></mrow><mrow><mi mathvariant="italic">ph</mi></mrow><mrow><mo>*</mo></mrow></msubsup><mrow><mo stretchy="false">(</mo><mn>443</mn><mo stretchy="false">)</mo></mrow></mrow></semantics></math></inline-formula> values were six months out of phase between the northern and southern hemispheres. Satellite observations present a global mean relationship between <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>a</mi></mrow><mrow><mi mathvariant="italic">ph</mi></mrow><mrow><mo>*</mo></mrow></msubsup><mrow><mo stretchy="false">(</mo><mn>443</mn><mo stretchy="false">)</mo></mrow></mrow></semantics></math></inline-formula> and Chl-a comparable with those obtained via in situ measurements. However, the seasonal/regional <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>a</mi></mrow><mrow><mi mathvariant="italic">ph</mi></mrow><mrow><mo>*</mo></mrow></msubsup><mrow><mo stretchy="false">(</mo><mn>443</mn><mo stretchy="false">)</mo></mrow></mrow></semantics></math></inline-formula> and Chl-a relationships can significantly depart from the global mean relationship. We propose a hypothesis that <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>a</mi></mrow><mrow><mi mathvariant="italic">ph</mi></mrow><mrow><mo>*</mo></mrow></msubsup><mrow><mo stretchy="false">(</mo><mn>443</mn><mo stretchy="false">)</mo></mrow></mrow></semantics></math></inline-formula> can be predicted as a function of geolocation and time. Preliminary validations with in situ matchup data confirm that the proposed model is a promising alternative to the traditional approaches requiring Chl-a as the input. The present exploration helps understand the phytoplankton biogeography and facilitates future efforts to improve bio-optical modeling, including estimating the primary production.