Barents Sea

Satellite data


fig1
The boundary of the Barents Sea was taken according to Fairbridge (1996). Based on the natural conditions determining formation of bio-optical characteristics, the whole basin was divided into three sub-regions: the Northern (1), Middle (2) and Southern (3) Fig.1.

The Northern region is predominantly occupied by the flow of cold Arctic Basin water whereas the Middle is under influence of the warm Norwegian Current. The boundary between them was taken along 75° N, in the vicinity of the Polar Front. Of course, a real position of the Polar Front is very changeable and not a straight line (
Rodionov et al. 1998). The Southern region is a shallow basin comprising the Cheshskaya Bay and Fig.2 shows the monthly coverage of the sub-regions by satellite data in different months from 1998 to 2012. The coverage was calculated for the chlorophyll data product (Chl). It should be noted that the presented diagrams do not take into account the number of used images (a bin is considered to be covered even if only one image per month).


The coverages from SeaWiFS and MODIS-Aqua are shown on Fig.2 by different hatching. One can see that the coverage by data from MODIS-Aqua, especially since 2006, is much better than by SeaWiFS data. As mentioned in Introduction, since July 2002 MODIS-Aqua data were used for the computations.

Before 2006 the coverage for all months (from May to September) can be considered as satisfactory only for the Middle Barents. For the North Barents the coverage in May was evidently insufficient, and this also relates to the South Barents in 1998-99 and 2002. It should be kept in mind when analyzing the results in Section Results and discussion.


Algorithms


The algorithms for calculation of the chlorophyll concentration, particle backscattering coefficient and the total suspended matter (TSM) concentration remained as before. The yellow substance absorption coefficient was not derived because the semi-analytic algorithm cannot work in the Barents Sea due to great errors in the atmospheric correction (Burenkov et al. 2001b).

Data of spectral bands 510 and 555 nm are used in the SeaWiFS case and of spectral bands 531 and 547 nm for MODIS-Aqua. At these spectral bands, the satellite and 
in situ measured data on the radiance reflectance are agreed with reasonable accuracy (Burenkov et al. 2001b). We used the water-leaving radiance LNWi) or the above-surface remote-sensing reflectance RRS(λi); the choice between them is of no importance, because these quantities are related to each other by a simple formula: LNW(λi) =RRS(λi) ·F0(λi), where F0(λi) is the extraterrestrial solar irradiance (http://oceancolor.gsfc.nasa.gov).

Algorithm for chlorophyll "a" concentration

The regional algorithm for assessment of chlorophyll "a" concentration was developed on the basis of the field data measured in August-September 1998 (the 13-th and 14-th cruises of R/V Academik Sergey Vavilov). Chlorophyll concentration and the subsurface radiance reflectance ρ(λ) were measured concurrently; the latter was measured by a floating spectroradiometer (Artemiev et al. 2000). The normalized water-leaving radiance LNW(λ) is derived from ρ(λ) with a formula given in Lee et al. (1998).

For SeaWiFS spectral bands 510 and 555 nm, the following regression equation between chlorophyll concentration and the ratio 
LNW(510)/LNW(555) was derived and used:

Chl= 0.34 [LNW(510)/LNW(555)]-1.395.                                (1)


Equation (1) was calculated from the field data covering both the open regions and the Pechora Sea (n=21); a standard error of the regression equation is 0.135 mg/m In the MODIS case, the ration RRS(531)/RRS(547) was used and the regression equation took the form:

Chl= 0.375 [RRS(531)/RRS(547)]-3.25.                                (2)


Algorithm for the particle backscattering coefficient

The algorithm was developed for the cases where the semi-analytic algorithm cannot work properly due to high errors in the atmospheric correction; such situation is just typical in the Barents and White Seas. The simplified algorithm uses only two SeaWiFS spectral bands 510 and 555 nm where errors in atmospheric correction are much less than at 412, 443, and 490 nm (Burenkov et al. 2001a).

To derive the particle backscattering coefficient
bbp(555), the diffuse attenuation coefficient Kd(555) and the parameter of X(555) are calculated:

X(555) =bb(555)/[a(555)+bb(555)],                                (3)


where
a(555) and bb(555) are the seawater absorption and backscattering coefficients. The X(555) value is derived through the value of normalized water-leaving radiance LNW(555) at 555 nm, Kd(555) through the ratio LNW(510)/LNW(555) of values of the normalized water-leaving radiance at 510 and 555 nm.
Then the value of [a(555)+bb(555)] is found from Kd(555) by using the Gordon's formula (Gordon 1989).

The particle backscattering coefficient 
bbp(555) is calculated as a difference between the seawater backscattering coefficient bb(555) and the known value of pure seawater backscattering coefficient bbw(555). The description of the algorithm in more detail is given in Gordon (1989).
In the MODIS case the particle backscattering coefficient 
bbp(555) was derived by similar way with RRS(531) and RRS (547) as the input parameters.

Total suspended matter (TSM)

Concentration of total suspended matter (TSM) was derived for the Barents Sea from SeaWiFS data by the regional algorithm based on the field data measured in 13 and 14 cruises of RV “Akademik Sergey Vavilov” (August-September 1998). Data of concurrent measurements of water-leaving radiances 
LNW (by the floating spectroradiometer) and TSM were used; first values of the particle backscattering coefficient bbp were determined and then the regression relationship TSM vs. bbpwas derived (Burenkov et al. 2001a):

TSM = 73.5bbp + 0.016,                                     (4)


where
bbp is measured in m-1 and TSM is given in mg/l. The mean error in determination of suspended matter concentration is about 30%.

Coccolithophore concentration (Ncoc)

Coccolithophore is a single-celled algae with a spherical cell covered by disk-shaped coccoliths, composed of calcium carbonate, CaCO2. Coccolithophore blooms can spread to vast areas in the various oceans and seas, and have a significant impact on important physical and biogeochemical processes, in particular the exchange of CO2 between the ocean and the atmosphere, and global climate change. Plated cells and detached coccoliths have a strong nonselective light scattering, which makes it possible to detect coccolithophore blooms from satellite color scanner. The water-leaving radiance, recorded by satellite color scanner, is increasing dramatically in the Barents Sea in July-September. A regional algorithm for estimation of the coccolithophore concentration Ncoc in the Barents Sea was derived by using the satellite ocean color data and concurrently measured data on coccolithophore and coccolith concentrations from the ship cruses of 2004 and 2009, as well as and the published data on the optical characteristics of coccolithophore from Voss et al. (1998) (Kopelevich et al. 2012).
A formula for calculation of Ncoc has the form:

Ncoc = 66 bbp,                                              (5)

where Ncoc is in 10 6 cell/l.


The maximum error for the concentration of
Ncoc is about 50%.

Data rejection

There is an evident requirement that LNW(510and LNW(555) in the case of SeaWiFS and LNW(531)/LNW(547) in the MODIS case must be positive. But our analysis showed that in some cases these quantities were strongly underestimated due to errors in the atmospheric correction. According to the obtained results, it occurred when the values of LNW(490) or LNW(670) (or LNW(488) and LNW(667) in the MODIS case) were negative. To avoid the significantly erroneous values of Chl or bbp derived through the ratio LNW(510)/LNW(555) or LNW(531)/LNW(547), the data with negative values of LNW(490) or LNW(670) (LNW(488) and LNW(667) in the MODIS case) were also rejected out.

Results and discussion


The mean monthly distributions of chlorophyll concentrations, the particle backscattering coefficient, TSM and coccolithophore concentration in the Barents Sea in May-September 1998-2012 are presented on the color maps.

Chlorophyll concentration

In the Northern and Middle regions, the relatively high values of chlorophyll concentration (mostly 0.3-0.5 mg/m3, in places more than 0.5 mg/m3) are observed in May caused by spring phytoplankton bloom. The spring bloom can be observed in places in June. In other months chlorophyll concentration in these regions is within 0.15-0.3 mg/m3and even less.

Particle backscattering and TSM

The enhanced values of
bbp in the Northern and Middle regions are also seen in May, but their highest values (>0.02 m-1) are observed in July-September. The latter is attributable to the coccolithophore bloom (see below).

In the Southern region the White Sea chlorophyll concentration is usually higher than 0.3 mg/m3, and enhanced values of the particle backscattering are also observed there.

The mean monthly distributions of
TSM are similar to the bbp distributions. One of the main features of the TSM spatial distribution in the Barents Sea is their high variability (mostly pronounced in July-September). Values of TSM are varied from more 1 mg/l near the Pechora River runoff and Cheshkaya Bay and in the central parts in August-September (during coccolithophore bloom) to less than 0.15-0.1 mg/l for the northern and eastern Barents which are typical for open ocean waters.

Coccolithophore blooms

The direct evidence of the coccolithophore blooms in the Barents Sea was obtained from the Professor Schtokman cruise in August 2004 (Kopelevich et al. 2005) and from the Akademik Mstislav Keldysh in August 2009 (Kopelevich et al. 2011b). In accordance with the satellite data, the water samples were taken, and an intense coccolithophore bloom was found (the coccolithophoride concentration exceeded 10 6 cell/l and even 107cell/l) (Kopelevich et al. 2005). The areas of increased values of bbp are partly controlled by surface seawater temperature (Burenkov et al. 2009).

As seen from the maps, the coccolithophore blooms have been observed in the Barents Sea since 1998, just from the beginning of SeaWiFS observations. (
Smyth et al. 2004), analyzing data from AVHRR visible channel, concluded that coccolithophore blooms unambiguously presented in the Barents Sea between 1989–1992 but probably absent in other pre-SeaWiFS years.

The blooms are observed, as a rule, in the western and central part of the Middle Barents, they start in July and end in September: the most intensive blooms are recorded in August (see
the maps).

Seasonal variability in different regions

Variability of the monthly mean values of chlorophyll concentration, the particle backscattering coefficient, and
TSM in different regions of the Barents Sea throughout 1998-2012 is shown in Fig.345. It is seen that the variations of chlorophyll concentration in the Northern and Middle regions are in phase with each other, whereas they are out of phase with the ones in the Southern Barents. There is significant correlation between the variations of Chl and bbp values observed both in the Northern and Southern regions. This correlation can be explained by the fact that changes of both of the characteristics (Chl and bbp) are connected with the same basic factors: the spring phytoplankton bloom in the Northern Barents and the river run-off in the Southern region. In the Southern Barents both chlorophyll concentration and particle backscattering rise sharply in May-June that corresponds to the Pechora flood-time. The enhanced values of Chl and bbp are held up to September because of the Pechora discharge is high throughout summer and autumn due to frequent rain freshets (River estuaries in the Barents Sea 2001).



No significant correlation is found between the variations of 
Chl and bbp in the Middle and Southern regions suggesting that the processes in coastal zone affect weakly the bio-optical characteristics in the open Barents Sea.

Variability of the monthly mean values of
TSM in different regions of the Barents Sea and in the White Sea throughout 1998-2012 is well pronounced; its mechanism is same as for the bbp.

The mean monthly distributions of sea surface temperature (
SST) are also given on the color maps. They were derived from MODIS-Aqua data available only from July 2002; the variability of their monthly means in different regions of the Barents Sea throughout July 2002 to September 2012 is shown in Fig.6. It is seen that the warmest water is observed in July-August in all regions; the highest mean values can exceed 30C in the Northern Barents, 80C in the Middle Barents, and 90C in the Southern Barents (Fig.6). The maximum values of SST can exceed in places in the Northern Barents, 100C in open part of the Middle Barents, and 120C in coastal zone of the Middle and the Southern Barents (see color maps).



Inter-annual variability

The seasonal (May-September) mean values with their standard deviations for chlorophyll concentration, the particle backscattering coefficient,
TSM and SST in different regions of the Barents Sea in 1998-2012 are given in Table 1.


It is seen that the highest Chl values are observed in the Southern Barents (the average over 1998-2012 is equal to 0.36 mg/m3 ), in the Northern and the Middle regions the seasonal averages are close to each other (the average 0.24-0.25 mg/m3). The inter-annual variability of chlorophyll concentration in the studied regions in 1998-2012 is not pronounced: changes in the mean seasonal values are within 0.21-0.27 mg/m3 in the Northern Barents, 0.24-0.27 in the Middle, 0.35-0.37 mg/m3 in the Southern Barents.

Inter-annual variability of the particle backscattering coefficient and
TSM is more pronounced: the TSM averages are changed within 0.27-0.33 mg/l in the Northern Barents, 0.36-0.57 mg/l (the latter in 2012) in the Middle, 0.75-0.95 mg/l in the Southern Barents.

The mean values of 
bbp in the Northern and Middle regions (3.8 and 5.5·10-3 m-1) are about twice the typical values of bbp in open ocean (Kopelevich 1983). In the Southern region the mean values of bbp increase more than twice.

The mean values of
SST (May-September) varied in 2003-2012 within 1.0-1.70C in the Northern Barents, 4.6-5.80C in the Middle Barents, 4.1-6.30C in the South. Relatively high temperatures in the Middle Barents are explained by influence of the warm Norwegian Curerent.

Fig.7 shows the inter-annual changes in the total content of coccolithophore cells in 1-m layer of the Barents Sea in August 1998-2012. This quantity was derived as the the integral of the mean August distribution coccolithophore concentration, calculated over the area of the coccolithophore bloom; the boundary of coccolithophore bloom was taken as 0.5 10 6 cells/l:

2.3_formula.

Two features of the observed variability should be noted. The first is a sharp increase of the total coccolithophore content in 2001 as compared with 1998-2000; the second is a similar change in 2011-2012 after 2009-2010. Probably, both changes are connected with climatic factors: according to Byshev et al.(2011), in the first decade of the current century, a transition to a new climate scenario began; 2011-2012 were notable as warm ones.