Abstract <p>The study focuses on the influence of the spectral composition of downwelling irradiance in Arctic seas on the effective light absorption by phytoplankton in the sea surface layer. The diurnal and seasonal variations of the spectral characteristics of light in the Kara and Barents seas were analyzed, in addition to their influence on potential errors in primary production models that use integrated values of photosynthetically active radiation (PAR). It is shown that at PAR values &lt;400 μmol m<sup>−2</sup> s<sup>−1</sup>, the spectral composition of solar irradiance incident on the sea surface frequently shifts towards the red part of the spectrum, leading to errors in estimates of effective light absorption by phytoplankton (up to 20–40%). For higher PAR values (&gt;400 μmol m<sup>−2</sup> s<sup>−1</sup>), spectral variations and associated errors decrease (&lt;10%). Neglecting to account for these spectral variations will impact estimates of primary production magnitudes in modeling efforts across all temporal scales, from instantaneous to seasonal.</p>

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Assessment of the Influence of the Spectral Composition of Downwelling Irradiance on Effective Light Absorption by Phytoplankton in the Sea Surface Layer

  • D. N. Deryagin,
  • D. I. Glukhovets

摘要

Abstract

The study focuses on the influence of the spectral composition of downwelling irradiance in Arctic seas on the effective light absorption by phytoplankton in the sea surface layer. The diurnal and seasonal variations of the spectral characteristics of light in the Kara and Barents seas were analyzed, in addition to their influence on potential errors in primary production models that use integrated values of photosynthetically active radiation (PAR). It is shown that at PAR values <400 μmol m−2 s−1, the spectral composition of solar irradiance incident on the sea surface frequently shifts towards the red part of the spectrum, leading to errors in estimates of effective light absorption by phytoplankton (up to 20–40%). For higher PAR values (>400 μmol m−2 s−1), spectral variations and associated errors decrease (<10%). Neglecting to account for these spectral variations will impact estimates of primary production magnitudes in modeling efforts across all temporal scales, from instantaneous to seasonal.