Standard NASA ocean color algorithm OC4 was developed on the basis of ocean optical data and while appropriate for Case 1 oceanic waters could not be adequately applied for the Black Sea waters due to its different bio-optical properties. OC4 algorithm is shown to overestimate chlorophyll concentration (Chl-a) in summer and underestimate Chl-a during early spring phytoplankton blooms in the Black Sea. For correct conversion of satellite data to Chl-a, primary production and other indicators regional algorithms should be developed taking into account bio-optical properties of the Black Sea waters. Light absorption by phytoplankton pigments-a ph (λ) have been measured in open sea and shelf Black Sea waters in different seasons since 1998. It was shown that the first optical depth was located within the upper mixed layer (UML) for most of the year with the exception of the spring when seasonal stratification was developing. As a result spectral features of water leaving radiance were determined by optical properties of the UML. Significant seasonal differences in Chl-a specific light absorption coefficients of phytoplankton within UML have been revealed. These differences were caused by adaptive changes of composition and intracellular pigment concentration due to variable environment conditions-mainly light intensity. Empirical relationships between a ph (λ) and Chl-a were derived by least squares fitting to power functions for different seasons. Incorporation of these results will refine the regional ocean color models and provide improved and seasonally adjusted estimates of chlorophyll a concentration, downwelling radiance and primary production in the Black Sea based on satellite data.

No abstract

No abstract

The work presents the underpinning for using of the spectral approach for assessment of primary productivity indicators based on remote sensing data. Existing information has been analysed. Problems, which should be solved for practical implementation of the spectral model of primary production in the Black Sea based on satellite data, have been identified. It has been shown that application of the regional algorithms for the assessment of the Black Sea primary productivity indicators on the basis of satellite data has improved the accuracy of model assessment of phytoplankton pigment concentration in the sea. Obtained for the last decade data of bio-optical water properties and photo-physiological characteristics of phytoplankton in the Black Sea allow to switch to the new level of regional models, which take into account not only amount, but also the spectral composition of radiation available for photosynthesis. The spectral model takes into account differences in phytoplankton light absorption efficiency between seasons as well as between euphotic zone layers separated by thermocline. Conceptually, this model is more realistic, and could be used not only for operational monitoring of the Black Sea waters, but also for development of predictive models for the sea ecosystem changes.

No abstract