Coefficient bbpis computed by using the MODIS

Selleck Ganetespib standard products of Rrs(531), Rrs(547) and Kd(490) (http://oceancolor.gsfc.nasa.gov); a brief description of the algorithm is given at (http://optics.ocean.ru) and in more detail by Burenkov et al. (2001). The regression equation TSM vs. bbp was derived from our field data of 2012 and 2013; the combined data set included 39 stations (15 in 2012, 24 in 2013). The TSM concentration varied from 1.0 mg 1−1 (St. 19F) to 5.5 mg 1−1 (St. 3L) in 2012 and from 1.7 mg 1−1 (St. 10F and 33F) to 4.4 mg 1−1 (St. 3FG) in 2013. The regression equation was derived in logarithmic form: equation(3) logTSM=0.79logbbp+1.95,where TSM is expressed in mg 1−1, bbp in m−1.

Figure 8 shows the regression line TSM vs. bbp on a logarithmic scale; Figure 9 is a scatterplot showing TSMcalc vs. TSMmeas. As seen from the figure, the agreement is rather good: the coefficient of determination r2 = 0.61, the standard error of the regression is equal to 0.62 mg 1−1; the averages of TSMcalc and TSMmeas are close to each other at 2.56 and 2.62 mg 1−1 respectively; the averaged ratio of TSMcalc/TSMmeas is equal to 1.03, and the ratio range is 0.72-1.5. Figure 10 shows the spatial distributions of TSM concentration calculated from MODIS-Aqua data check details on 22 July 2012 and 27 July 2013 using (3). One can see a general similarity of these distributions with the distributions of chlorophyll concentration in Figure 7. Such a similarity is to be expected, because NADPH-cytochrome-c2 reductase there is a common factor determining the distribution of both TSM and chlorophyll: the River

Neva carries suspended particles and phytoplankton with chlorophyll and nutrients for primary bioproduction. We evaluated the applicability of the regional Baltic algorithms by Darecki & Stramski (2004) and Woźniak et al. (2008) for determining chlorophyll concentrations in the Gulf of Finland by using our data set of 2012–2013. The input parameter of the second of them (the DESAMBEM algorithm – Development of a Satellite Method for Baltic Ecosystem Monitoring) is the ratio XR = [Rrs(490) —Rrs(665)]/[Rrs(550) —Rrs(665)], which is completely unsuitable for the Gulf of Finland because of the abnormally high values of Rrs(665). The regional parameterisation of MODIS algorithms for chlorophyll retrieval in the Baltic was presented by Darecki & Stramski (2004) in two versions: #9 Baltic_chlor_MODIS: Chl = 100.4692–20.6802X, where X = log[Lwn(443) + Lwn(488)/Lwn(551)], The values of Lwn are related to Rrs by a simple formula: Lwn(λ) = F0(λ) Rrs(λ), where F0(λ) is the mean extra-terrestrial solar irradiance (http://oceancolor.gsfc.nasa.gov). The results of the evaluation of these algorithms are presented in Table 2 and can be compared with the results for algorithms #4 and #8 from Table 1.