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Transactions of the Karelian Research Centre of the Russian Academy of Sciences No. 9. 2019. P. 125-135 DOI: 10.17076/lim1107
Труды Карельского научного центра РАН № 9. 2019. С.125-135
УДК 551.46.06 + 528.8.04
SATELLITE EVIDENCE FOR ENHANCEMENT OF THE COLUMN MIXING RATIO OF ATMOSPHERIC CO2 OVER E. HUXLEYI BLOOMS
D. V. Kondrik1, E. E. Kazakov1, D. V. Pozdnyakov1, O. M. Johannessen2
1 Nansen International Environmental and Remote Sensing Centre, St. Petersburg, Russia
2 Nansen Scientific Society, Bergen, Norway
Emiliania huxleyi algae are known to enhance CO2 partial pressure in their ambient water, (pCO2)w. Thus, over such bloom areas, the atmospheric column-averaged dry air mole fraction of carbon dioxide (XCO2) is likely to increase, which has not yet been quantified on basin scales. Here we report on an Orbiting Carbon Observatory (OCO-2) satellite study of the influence of E. huxleyi blooms on XCO2 over the Black Sea. We established that concurrently with a significant (pCO2)w rise, there was an increase in the overlying XCO2 within the range ~1 to nearly 2 ppmv, which is commensurate with the planetary annual increase of XCO2. As we found, (ApCO2)w in the Black Sea and Subpolar and Polar seas are closely comparable. This strongly indicates that E. huxleyi blooms do weaken carbon sinks in the ocean on a large scale, which can be consequential for global climatology and marine biogeochemistry.
Keywords: Black Sea; blooms of Emiliania huxleyi; CO2 partial pressure in water; satellite remote sensing; OCO-2 data; enhancement of atmospheric columnar CO2 content over E. huxleyi blooms.
Д. В. Кондрик, Э. Э. Казаков, Д. В. Поздняков, О. М. Йоханнессен. СПУТНИКОВОЕ ДОКАЗАТЕЛЬСТВО УВЕЛИЧЕНИЯ КОНЦЕНТРАЦИИ СО2 В АТМОСФЕРНОМ СТОЛБЕ НАД ОБЛАСТЬЮ ЦВЕТЕНИЯ E. HUXLEYI
Известно, что водоросли Emiliania huxleyi повышают парциальное давление CO2 в окружающей их воде, (pCO2)w. Таким образом, над областями цветения может увеличиваться средняя по атмосферному столбу мольная доля диоксида углерода (XCO2) сухого воздуха. Значения (XCO2) количественно еще не определялись в масштабах бассейна. Здесь мы сообщаем о спутниковом исследовании влияния цветений E. huxleyi на значения XCO2 над Черным морем, основанном на данных Orbiting Carbon Observatory (OCO-2). Установлено, что одновременно со значительным увеличением (pCO2)w в атмосферном столбе над цветением наблюдается увеличение XCO2 в диапазоне от ~ 1 до почти 2 ppmv, что по величине сравнимо с планетарным годовым увеличением XCO2. Показано, что значения (pCO2)w в Черном море и в субполярных и полярных морях тесно сопоставимы. Это убедительно свидетельствует о том, что цветения E. huxleyi в значительной степени ослабляют способность океана поглощать углерод на значительных протяженностях, и это может иметь значение для глобальной климатологии и морской биогеохимии.
Ключевые слова: Черное море; цветения Emiliania huxleyi; парциальное давление СО2 в воде; спутниковое дистанционное зондирование; данные ОСО-2; возрастание содержания СО2 в атмосферном столбе над цветениями Emiliania huxleyi.
Introduction
Phytoplankton blooms of Emiliania huxleyi are known to produce CO2, causing less uptake of atmospheric CO2 by the ocean. A recent study based on 18 years (1998-2015) of quantitative satellite observations of CO2 partial pressure in surface waters, (pCO2)w of five seas in the North Atlantic, Arctic and North Pacific, revealed that within the areas of E. huxleyi blooms, the increment in pCO2, (ApCO2)w was significant, constituting tens to hundreds of microatmospheres [Kondrik et al., 2018; the respective database and its description can be found in Kondrik et al., 2019].
When normalized to CO2 partial pressure in the absence of blooms ("background" pCO2 in water - (pCO2)wb), the mean and maximum (ApCO2)w values proved to be in the range 20.4-44.2 and 31.6-62.5 %, respectively. The bloom areas in the target seas varied significantly among the years with maximum values in the range of several tens to several hundreds of square kilometres [Kondrik et al., 2017].
The aforementioned E. huxleyi bloom-driven enhancement of dissolved CO2 partial pressure can reduce, nullify or even reverse the flux of CO2 at the atmosphere-ocean interface. Indeed, Shut-ler et al. [2013] report on an average reduction in the monthly air-sea CO2 flux by about 55 % across the marine tracts encompassing extensive E. huxleyi blooms in the North Atlantic, whereas the maximum reduction over the time period 1998-2007 was registered at 155 %.
In the southern hemisphere E. huxleyi blooms are also vast: e. g., the area of the gigantic Great Calcite Belt extending from ~ 38 to ~ 60 °S is reportedly in excess of 50 million square kilometres [Balch et al., 2016].
Given these estimations, it is reasonable to expect that at least within the areas of E. huxleyi blooms, the CO2 balance between the atmosphere and the ocean can shift, causing a considerable reduction in the CO2 flux from atmosphere to ocean and even its reversal.
Due to the global nature of the phenomenon of E. huxleyi blooms [Brown, Yoder, 1994; Iglesias-Rodrigues et al., 2002; Moore et al., 2012], this can have appreciable ramifications, among which are a reduction in the world's ocean carbon sink and a consequential enhancement of global warming [IPCC, 2014].
However, until recently, numerical assessments of the impact of E. huxleyi blooms on CO2 exchange between atmosphere and ocean were confined to isolated shipborne in situ measurements [e. g. Robertson et al., 1994], and as such could not be considered representative because of data
paucity. With the launch of the Orbiting Carbon Observatory 2 (OCO-2) satellite mission [Crisp, 2015] in 2014 such studies became feasible: the column-averaged dry air mole fraction of carbon dioxide (XCO2) retrieved by OCO-2 can be obtained over the target bloom of E. huxleyi in order to detect the XCO2 enhancement in the atmosphere.
Here we report on the results of our satellite study of the Black Sea, as a test example. The reason for this selection is twofold: firstly, the Black Sea is an area of intense E. huxleyi blooms [Cokacar et al., 2001], and secondly, such intense blooms occur there annually, in contrast to other seas [Smyth et al., 2004; Oguz, Merico, 2006]. At the maximum of their development (e. g. in 2012), the blooms cover areas as large as ~ 354x103 km2, thus accounting for ~ 84 % of the entire surface of the sea.
Materials and Methods
To implement the present study, spatially and temporally collocated data on two remotely-sensed variables are required, viz. on spectral remote sensing reflectance, Rre(sr-1) and XCO2 (ppmv). These data are from, respectively, OC CCI (in six channels centred at 412, 443, 490, 510, 555 and 670 nm, at 4 km spatial and 8 day temporal resolution, http://www.esa-oceancolour-cci.org) and OCO-2 (OCO-2 Level 2 bias-corrected XCO2 product at 3 km2 spatial resolution, NASA Data Archive Page https://disc.gsfc.nasa.gov/data-sets?project=OCO).
The period of satellite observations covers two years (2015-2016), when both Ocean Colour Climate Change Initiative (OC CCI) and OCO-2 data were available. Although also available for 2017 and 2018, OCO-2 data could not be used as they proved to be deficient due to either extensive cloud masking or heavy flagging (the prevailing amount of data points contained low-quality flags) over the areas encompassing OCO-2 footprint trajectories within E. huxleyi blooms in the Black Sea.
The work was performed in the following major sequential steps: (1) identification and precise delineation/quantification of an E. huxleyi bloom area, (2) quantification of the enhancement of CO2 partial pressure in surface water, (ApCO2)w (^atm) within the bloom area, (3) identification of XCO2 (ppmv) data availability on the target marine areas, (4) establishment of XCO2 variations over the target area, and (5) quantification of increments in XCO2, AXCO2 during the bloom period against the respective XCO2 background values.
The methodologies of fulfilling steps 1 and 2 are described in detail in our previous papers [Kondrik et al., 2017, 2018]. Here only their brief descriptions are given.
In step 1, spectra of Rrs from the turquoise areas produced by E. huxleyi algae were automatically analyzed to select those complying with the preselected thresholds and the location of maxima for this variable at the OC CCI wavelengths in the visible. Summation of the pixels thus identified gave the bloom area.
In step 2, values of CO2 partial pressure in surface waters, (ApCO2)w within the bloom area were obtained making use of the algorithm developed in [Kondrik et al., 2018]. The algorithm is based on the regression dependency between the values of Rrs (490 nm) and (ApCO2)w, which has been confidently established with the root mean square error of +/-23.4 ^atm on the basis of more than 2500 data points located throughout the subarctic and arctic seas.
In step 3, XCO2 data from OCO-2 were selected that conformed to a single-sounding random error between 0.5 and 1 ppmv [Crisp, 2015] and respective quality control flags.
Step 4. Some XCO2 values were not available for each 8-day intervals of observations because of either cloud filtering or OCO-2 data flagging/ unreliable quality. To fill such gaps in the sequence of XCO2 values, i. e. the missing segments of the XCO2 intraannual variations, a linear interpolation approach was employed. Further, the sequence of XCO2 values was subjected to a polynomial approximation of order 7.
This approach was applied separately to both (i) all data over the entire two-year term (i. e. 2015-2016), including the periods of E. huxleyi blooming, and (ii) to the data registered each year but excluding the E. huxleyi blooming period per se plus one week before and after the blooming.
The difference AXCO2 between the actually recorded XCO2 values and the respective approximated XCO2 values beyond the E. huxleyi blooming period reflects for the excess of XCO2 over the bloom area.
In step 5, AXCO2 values were quantified and their temporal variability was analyzed.
Results
Our quantitative assessments of the E. hux-leyi bloom extent in the target sea indicate that we are dealing with a huge phenomenon. Indeed, as Figure 1, a illustrates, both in 2015 and 2016 the bloom areas at the stage of maximum development reached 177.0-205.3 thousand square kilometers, which corresponds to 41.9-48.6 %, i. e. almost half of the entire surface of the Black Sea with depths in excess of 200 m (e. g. [Ozsoy, Un-luata, 1997], see also Figure 2, a).
Importantly, for the periods of blooming in 2015 and 2016, the concurrent OCO-2 daily data are in most cases amply available with only rare exceptions (black bars in Figure 1, a).
The obtained data reveal enhanced values of XCO2 over the bloom areas. The magnitude of XCO2 increment for both years proved to be significant: the maximum increments of XCO2 are close to 2 ppmv (Fig. 1, c), which constitutes ~ 0.5 % of the present mean pCO2 in the atmosphere [Dlugokencky, 2016] or is on the same order of magnitude as the annual increase. Given that (i) the single-sounding random errors are between 0.5 and 1 ppmv [Crisp, 2015] and (/'/') the number of OCO-2 observations in our case is up to 400 (Fig. 1, a), the increments established in this study should generally be considered as reliable. An independent confirmation of validity of this statement can be found e. g. in [Wu et al., 2018].
However, there was one case on 24.05.2016 when the XCO2 increment value was highly negative, about ~1.5 ppmv, i. e. beyond the stated error of a single sounding, 0.5-1.0 ppmv. This case corresponds to the situation when the number of return signals was at least ten times less than that registered in other measurements during the period of high bloom intensity (compare Fig. 1, a and c), and hence the respective retrievals were insufficiently reliable. This case is illustrated in Figure 2, a: for 24.05.2016 the number of red points (reflecting the OCO-2 footprints) in the marginal eastern part of the sea is far less than for e. g., 16.05.2016 (Fig. 2, b) - the date of concurrently high values of max (ApCO2)w in surface water and the number of satellite observations and strongly positive XCO2 increment. The same arguments refer to a few cases in 2015 (Fig. 1, c), when the resultant AXCO2 values, although very small, were non-positive.
As the Black Sea is essentially a landlocked waterbody, the influence of watershed-based CO2 sources (both of rural and industrial/urban origin) can affect XCO2 readings through the transport of polluted atmospheric air over the E. hux-leyi blooms. A good clarification of this issue could be the situation when satellite footprints passed through both the bloom and bloom-free areas during one and same overflight. Because of the paucity of high quality OCO-2 data during 2015-2016 on the Black Sea (no clouds, no heavy data flagging) such situations were found solely on two occasions, viz. on 02.06.2015 and 16.05.2016 (Fig. 3 and 2, b, respectively). The mean XCO2 values (in ppmv) over the long footprint passing through the area of E. huxleyi bloom, and two footprint segments intersecting the bloom-free area (both are encircled in Fig. 3)
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Fig. 1. The phenomenon and effects of E. huxleyi blooms in the Black Sea in 2015 and 2016 as observed and characterized from satellite sensors. Panel a: (/') bloom area (green bars), and (/'/') number of XC02 observations (black bars); panel b: (ApC02) w maximal values in water within the bloom area (green bars); panel c: XC02 increments over the bloom areas. The pale green columns in panels a-c reflect the period of blooming
Fig. 2. Spatial distribution of CO2 partial pressure increment, (ApCO2)w, in the Black Sea surface water as retrieved from OC CCI data on a) 24.05.2016 and b) 16.05.2016. Red linesare the locations of the OCO-2 footprints across the E. huxleyi bloom on each of the two dates. The encircled area is explained in the text
Fig. 3. Spatial distribution of CO2 partial pressure increment, (ApCO2)w, in the Black Sea surface water as retrieved from OC CCI data on 02.06.2015.
Red lines designate the OCO-2 footprints across the sea. The encircled areas are explained in the text
were, respectively, 400.07 and 399.2. Thus, these data indicate that there was no significant influence exerted by CO2 atmospheric advection from the watershed. The same conclusion can be drawn from the second example: on 16.05.2065 the mean XCO2 values (in ppmv) along the footprint extending over the south-western region of the Black Sea, and along a short part of it (encircled in Fig. 2, b) in the close vicinity of the coast were, respectively, 403.5 and 401.75. Should there be any CO2 atmospheric advection from the watershed, the proportion between these two numbers would be essentially different. Both results should not be considered as incidental. Indeed, all available XCO2 data registered along the footprints (which passed through different parts of the sea) were used collectively, and on this basis common statistical characteristics were calculated. In other words, there was no specific reference to a concrete point in the footprint, but a general aggregation of spatio-temporal variability in XCO2 was established. Had there been an impact of CO2 advection, it would have been reflected in the entire set of XCO2 determined along the footprint.
Finally, as mentioned above, on some occasions in 2015 and 2016 AXCO2 values are negative (Fig. 1, plate c). Although we assume that the negative AXCO2 values are not reliable because they were retrieved from a small number of OCO-2 return signals, nevertheless, they can arguably be interpreted as an explicit indication of the absence of advected CO2 from the marine watershed in those parts of the sea.
Excluding the unreliable data discussed immediately above leads to a value of the mean XCO2 increment over the blooming period close to 1 ppmv. Given that this assessment is based on a statistically significant number of measurements (Fig. 1, a), it should be assumed as reliable, and hence the trustworthy range of XCO2 increments over the Black Sea extends from 1 ppmv to the maximum observed value close to 2 ppmv (Fig. 1, c).
As our ApCO2 retrieval algorithm was developed and verified for high latitude marine environments, the appropriateness of its application to the conditions of the Black Sea needed confirmation. To the best of our knowledge, there are no
Temporal pattern of CO2 partial pressure excess (in percent) within E. huxleyi blooms in surface waters of the target seas over the period of spaceborne observations (1998-2016)
Year A
North Sea (750)* Norwegian Sea (1383) Greenland Sea (1205) Barents Sea (1400) Bering Sea (2292) Black Sea (436)
1998 31.8(9.6 ; 0.4)** 35.6 (67.0; 12.2) - (2.8; 0.2) 40.6 (118.4; 8.1) 62.3 (220.2; 8.9) 21.7 (74.2; 17.6)
1999 43.1 (28.1; 1.2) 28.8 (65.1; 11.9) 20.0 (17.2; 1.4) 42.5 (186.1; 12.8) 54.3 (201.2; 8.1) 25.8 (13.8; 3.3)
2000 35.4 (58.9; 2.5) 24.6 (59.6; 10.9) - (1.2; 0.1) 34.5 (178.0; 12.2) 53.7 (247.3; 10.0) 35.8 (104.9; 24.8)
2001 27.7 (43.9; 1.9) 26.3 (36.7; 6.7) 21.1 (5.8; 0.5) 62.5 (269.4; 18.5) 19.2 (209.0; 8.4) 12.8 (1.7; 0.4)
2002 23.9 (76.4; 3.2) 15.6 (36.4; 6.7) 31.0 (5.2; 0.4) 39.2 (248.0; 17.0) 17.0 (5.5; 0.2) 36.7 (345.2; 81.8)
2003 38.1 (72.6; 3.1) 39.1 (105.4; 19.3) - (4.8; 0.4) 50.6 (201.9; 13.8) 22.0 (27.0; 1.1) 11.8 (20.1; 4.8)
2004 27.9 (24.8; 1.0) 20.8 (30.7; 5.6) 12.5 (10.0; 0.8) 41.0 (234.0; 16.0) 20.0 (22.3; 0.9) 17.0 (206.4; 48.9)
2005 30.1 (83.2; 3.5) 17.6 (46.3; 8.5) 23.5 (20.9; 1.7) 27.5 (120.4; 8.3) 16.0 (22.3; 0.9) 20.3 (198.3; 47.0)
2006 24.1 (10.8; 0.5) 46.9 (65.6; 12.0) 12.4 (10.4; 0.8) 30.9 (167.9; 11.5) 19.8 (8.9; 0.4) 37.0 (344.9; 81.7)
2007 21.2 (21.8; 0.9) 11.8 (25.5; 4.7) - (7.1; 0.6) 47.3 (218.6; 15.0) 25.5 (63.6; 2.6) 14.1 (277.1; 65.6)
2008 41.1 (54.7; 2.3) 17.5 (19.1; 3.5) 31.6 (48.2; 3.8) 37.4 (156.3; 10.7) 15.4 (12.0; 0.5) 31.4 (320.7; 76.0)
2009 18.4 (74.9; 3.2) 27.8 (26.0; 4.8) - (7.4; 0.6) 27.6 (129.9; 8.9) 28.1 (46.8; 1.9) 11.0 (68.5; 16.2)
2010 45.6 (145.3; 6.1) 29.7 (109.2; 20.0) 23.5 (43.2; 3.4) 21.2 (116.2; 8.0) - (4.2; 0.2) 10.2 (118.1; 28.0)
2011 40.8 (106.3; 4.5) 45.4 (51.8; 9.5) - (4.7; 0.4) 55.1 (267.7; 18.4) 43.8 (47.6; 1.9) 10.2 (292.2; 69.2)
2012 28.0 (55.5; 2.3) 16.2 (11.6; 2.1) 16.1 (18.8; 1.5) 58.7 (371.5; 25.5) 24.6 (1.5; 0.1) 58.6 (353.8; 83.8)
2013 25.5 (31.8; 1.3) 26.3 (27.3; 5.0) 20.2 (16.1; 1.3) 60.5 (246.8; 16.9) 14.1 (5.3; 0.2) 16.8 (121.6; 28.8)
2014 32.6 (55.1; 2.3) 26.4 (29.2; 5.3) 18.8 (53.6; 4.3) 56.5 (169.1; 11.6) 47.2 (102.4; 4.1) 10.9 (170.2; 40.3)
2015 49.0 (54.5; 2.3) 14.6 (69.9; 12.8) - (5.5; 0.4) 46.4 (289.6; 19.9) 40.3 (13.4; 0.5) 13.9 (205.3; 48.6)
2016 41.9 (10.3; 0.4) 34.8 (63.4; 11.6) 14.5 (8.1; 0.6) 59.6 (387.6; 26.6) 37.9 (56.3; 2.3) 23.0 (177.0; 41.9)
B 33.0 (53.6; 2.3) 26.6 (49.8; 9.1) 20.4 (15.3; 1.2) 44.2 (214.6; 14.7) 31.2 (69.3; 2.8) 22.0 (179.7; 42.6)
C 49.0 (145.3; 6.1) 46.9 (109.2; 20.0) 31.6 (53.6; 4.3) 62.5 (387.6; 26.6) 62.3 (247.3; 10.0) 58.6 (353.8; 83.8)
Note. A: [(ApCO2)w / (pCO2)wb] 100 % maximum values as determined within E. huxleyi blooms in the target seas for each year of satellite observations. B and C: mean and maximum values of the above ratio over the period of observations. * The number in parenthesis is the area (in 103 km2) of each sea. ** The first and second numbers in parenthesis in each column are, respectively, the maximum bloom area (103 km2) and its ratio to the sea area (in percent).
published reports on ApCO2 in surface water due to E. huxleyi blooming in the Black Sea. However, we found that our results obtained on the CO2 partial pressure within the bloom in the Black Sea proved to be closely in line with the set of multi-year in situ measurements of this variable within an E. huxleyi bloom persistently appearing at one and the same station in the area of typical but not most intense blooms of E. huxleyi in the Black Sea (south-east off the Crimea) during late May-July in 2009, 2010 and 2013 [Khoruzhiy et al., 2010; Konovalov et al., 2014]. Indeed, the in situ measurements have shown that pCO2 values were well within the ranges reported by us. Thus, in 2013 pCO2 levels in the surface waters varied within 420-530 Matm. Through a comparison of these data with those in our Table and assumption that ApCO2 averaged over both the sea and the period of bloom observations in 2015-2016 is 100120 Matm (Fig. 1, b) it can be drawn that our data on pCO2 are within the range 405-554 Matm. Noting that these numbers refer to the entire bloom area in the Black Sea, the correspondence is close
enough and therefore justifies the application of our ApCO2 retrieval algorithm to the Black Sea case.
Thus, the blooming-driven enhancement of atmospheric CO2 partial pressure over the Black Sea is shown to be caused by the increase in CO2 partial pressure in water, (ApCO2)w, whose maximum was in the range 125-150 ^atm (Fig. 1, b). This corresponds to 44.7-65.8 % of the bloom-driven increase in CO2 partial pressure in water, assessed as (ApCO2)w normalized to CO2 partial pressure in water in the absence of blooming (pCO2)wb.
Discussion
Importantly, these results for both (ApCO2)w and normalized ratio (ApCO2)w / (pCO2)wb are quite comparable with the respective values registered in blooming surface waters of the polar Barents Sea, as well as in some subpolar marine environments, such as the North, Norwegian, Greenland and Bering Seas [Kondrik et al., 2018] - see Table and Figure 4. Hence, a similar blooming-driven
flpco2/(pccyb(%l North Sea
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1998 1999 20») 2«>1 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Norwegian Sea
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1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
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1998 1999 2000 2031 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
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1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2C08 2009 2010 2011 2012 2013 2014 2015
Bering Sea
50.0 40.0 300 10.0
1998 1999 20D0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Year
Fig. 4. Spatial and temporal variations in [(ApCO2)w/ (pCO2)wb] -100 % maximum values within E. huxleyi bloom areas in the North, Norwegian, Greenland, Barents, and Bering Seas during 1998-2015 (Source: [Kondrik et al., 2018]).
The data are absent for some years and target seas as the respective (ApCO2)w values proved to be lower than the assessed retrieval error of 23.4 |atm. Some of the y-axes have different scales
enhancement of atmospheric CO2 partial pressure could be expected over them as well. Unfortunately, OCO-2 data on XCO2 for high latitudes are scarce and generally heavily quality flagged. At least for the two selected years, this precluded a direct determination of AXCO2 over E. huxleyi blooms in the subpolar and polar seas mentioned above.
However, since it is the normalized ratio (ApCO2)w/(pCO2)wb that controls the direction of the CO2 flux in the atmosphere - ocean surface system, the closeness of the normalized ratio values found for such geographically disparate marine environments suggests that the effect of E. huxleyi blooms on CO2 partial pressure increment in marine surface waters is not latitude-longitude specific.
It is also worth of noting that the blooms in the aforementioned seas are not extraordinarily extensive or denser than those in other marine environments in the world's oceans: there are reports on either comparable or even more vast and dense E. huxleyi blooms in both Northern and Southern Hemispheres [Brown, Yoder, 1994; Morozov et al., 2013; Balch et al., 2016].
Despite the obvious oneness of the E. huxleyi blooming phenomenon at subpolar and polar seas on the one hand and in the Black Sea on the other, one specific feature inherent in the Black Sea is worth mentioning, viz. the moment of the bloom onset: in the Black Sea it occurs much earlier. The registered E. huxleyi blooms in the Black Sea in 2015 and 2016 occurred during the time period between late April and late June, with the maximum in mid-May, which is supported by previous observations by e. g. [Oguz & Merico, 2006] see also refs. therein. This specific feature of the E. huxleyi outburst timing is known to be controlled by the timing of the preceding photosynthetic phytoplankton mass development. The latter increases the nitrogen to phosphorus (N : P) ratio and creates conditions favoring a successive development of E. huxleyi [Tyrrell, Merico, 2004]. Thus, this mechanism of water chemical "preparation" largely (but not exclusively) predetermines the timing of E. huxleyi bloom onset. As the outburst and eventual dying off of yearly spring phytoplankton (which are prevalently diatoms) occur in the Black Sea earlier that at high latitudes [Vinogradov et al., 1999; Moncheva et al., 2001], E. huxleyi blooms also start developing earlier.
In conclusion, we believe that the results reported here are of relevance to the phenomenon of E. huxleyi blooms in general and can be considered as a reference point in future large-scale studies, which are needed in order to attain quantitative assessments of the overall role of E. huxleyi blooms in the global carbon cycle.
We express our gratitude for the financial support of this study provided by the Russian Science Foundation (RSF) under the project number 17-17-01117. We also acknowledge the use of the Ocean Colour Climate Change Initiative dataset, Version 3.1, European Space Agency, available online at http://www.esaoceancolour-cci.org/. XCO2 data were produced by the OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center.
References
Balch W. M., Bates N. R., Lam P. J., Twining B. S., Rosengard S. Z., Bowler B. C., and Drapeau D. T. Factors regulating the Great Calcite Belt in the Southern Ocean, and its biogeochemical significance. Global Bio-geochem. Cy. 2016. Vol. 30, no. 8. P. 1124-1144. doi: 10.1002/2016GB005414
Brown C. W., Yoder J. A. Coccolithophorid blooms in the Global Ocean. J. Geophys. Res. 1994. Vol. 99. P. 7467-7482. doi: 10.1029/93JC02156
Cokacar T., Kubilay N., and Oguz T. Structure of Emi-liania huxleyi blooms in the Black Sea surface waters as detected by SeaWiFS imagery. Geophys. Res. Lett. 2001. Vol. 28, no. 24. P. 4607-4610. doi: 10.1029/2001GL013770 Crisp D. Measuring atmospheric carbon dioxide from space with the Orbiting Carbon Observatory-2 (OCO-2). Proceed. SPIE. Earth Observing Systems XX, 960702 (Sept. 8, 2015). 2015. Vol. 9607. doi: 10.1117/12.2187291 Dlugokencky E. Annual mean carbon dioxide data. NOAA ESRL. 2016.
Garcia H. E., Locarnini R. A., Boyer T. P., Anto-nov J. I., Baranova O. K., Zweng M. M., Reagan J. R., and Johnson D. R. World Ocean Atlas 2013. Vol. 4: Dissolved inorganic nutrients (phosphate, nitrate, silicate). Eds. S. Levitus, A. Mishonov, Technical Eds. NOAA Atlas NESDIS 76. 2013.
Iglesias-Rodrigues M. D., Brown C. W., Doney S. C., Kleypas J., Kolber D., KolberZ., Hayes P. K., and Fal-kowskiP. G. Representing key phytoplankton functional groups in ocean carbon cycle models: Coccolitho-phorids. Global Biogeochem. Cy. 2002. Vol. 16, no. 4. P. 47-1-47-20. doi: 10.1029/2001GB001454
IPCC. Climate Change 2014: Synthesis report. Contribution of working groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Eds. Core Writing Team, R. K. Pachauri, L. A. Meyer. IPCC, Geneva, Switzerland, 2014. 151 p.
KeyR. M., Olsen A., van Heuven S., Lauvset S. K., Velo A., LinX., SchirnickC., Kozyr A., Tanhua T., Hop-pema M., Jutterstrom S., Steinfeldt R., Jeansson E., Ishii M., Perez F. F., and Suzuki T. Global Ocean Data Analysis Project, Version 2 (GLODAP v2). 2015. URL: http://cdiac.ornl.gov/oceans/GLODAPv2/ (accessed: 20.06.2019). doi: 10.3334/CDIAC/OTG. NDP093_ GLODAPv2
KhoruzhjyD. S., KondratyevS. I., MedvedevE. V., and ShutovS. A. Dinamika partsial'nogo davleniya
uglekislogo gaza i kontsentratsii rastvorennogo kis-loroda v shel'fovykh vodakh yuzhnogo berega Kry-ma v 2009-2010 gg. [Dynamics of the carbon dioxide partial pressure in the Southern Crimea shelf zone in 2009-2010]. Ekol. bezopasnost' pribrezhnoi i shel'fo-voi zon i kompleksnoe ispol'zovanie resursov shel'fa [J. Ecol. Safety of the Coastal and Shelf Zones and Comprehensive Exploitation of the Shelf Res.]. 2010. Vol. 21. P. 136-145.
KondrikD., KazakovE., and PozdnyakovD. A Synthetic satellite dataset of the spatio-temporal distributions of Emiliania huxleyi blooms and their impact on Arctic and Sub-Arctic marine environments (1998-2016). Earth System Sci. Data. 2019. Vol. 11. P. 119-128. doi: 10.5194/essd-11-119-2019
Kondrik D. V., Pozdnyakov D. V., and Johannessen O. M. Satellite evidence that E. huxleyi phyto-plankton blooms weaken marine carbon sinks. Geo-phys. Res. Lett. 2018. Vol. 45, no. 2. P. 846-854. doi: 10.1002/2017GL076240
Kondrik D. V., PozdnyakovD. V., and Petters-son L. H. Particulate inorganic carbon production within E. huxleyi blooms in subpolar and polar seas: A satellite time series study (1998-2013). Int. J. Rem. Sens. 2017. Vol. 38, no. 22. P. 6179-6205. doi: 10.1080/01431161.2017.1350304
KonovalovS. K., KondratyevS. I., KhoruzhiyD. S., MedvedevE. V., and Moiseenko O. G. Obshchii neor-ganicheskii uglerod, karbonatnaya sistema i potoki uglekislogo gaza v pribrezhnoi zone yuzhnogo berega Kryma: monitoring, kharakteristika, dinamika [Total inorganic carbon, carbonate system and fluxes of carbon dioxide in the Crimean shelf zone: monitoring, characterization, dynamics]. Monitoring pribrezhnoi zony na Chernomorskom eksperimental'nom podsputnikovom poligone [Monitoring of the coastal zone in the Black Sea experimental sub-satellite testing area]. Eds. V. A. Ivanov, V. A. Dulov. Sevastopol: NAS of Ukraine, Marine Hydrophysical Institute, 2014. P. 335-372.
Moncheva S., Gotsis O., Pagou K., and KrastevA. Phytoplankton blooms in the Black Sea and Mediterranean coastal ecosystems subjected to anthropogenic eutrophication: similarities and differences. Estuarine, Coastal and Shelf Sci. 2001. Vol. 53, no. 3. P. 281-295. doi: 10.1006/ecss.2001.0767
Moore T., Dowel M. D., and Franz B. A. Detection of coccolithophore blooms in ocean color imagery: A generalized approach for use with multiple sensors. Rem. Sens. Environ. 2012. Vol. 117. P. 249-263. doi: 10.1016/j.rse.2011.10.001
Morozov E., Pozdnyakov D., Smyth T., Sychev V., and Grassl H. Space-borne study of seasonal, multi-year, and decadal phytoplankton dynamics in the Bay of Biscay. Int. J. Rem. Sens. 2013. Vol. 34, no. 4. P. 1297-1331. doi: 10.1080/01431161.2012.718462
Oguz T., and Merico A. Factors controlling the summer Emiliania huxleyi bloom in the Black Sea: A modeling
study. J. Marine Syst. 2006. Vol. 59, no. 3-4. P. 173-188. doi: 10.1016/j.jmarsys.2005.08.002
Olsen A., KeyR. M., van Heuven S., Lauvset S. K., Velo A., LinX., Schirnick C., Kozyr A., Tanhua T., Hop-pema M., Jutterstrom S., Steinfeldt R., Jeansson E., Ishii M., Pérez F. F., and Suzuki T. The Global Ocean Data Analysis Project Version 2 (GLODAPv2) - an internally consistent data product for the World Ocean. Earth System Sci. Data. 2016. Vol. 8, no. 2. P. 297-323. doi: 10.5194/essd-8-297-2016
Ozsoy E., and Ünlüata Ü. Oceanography of the Black Sea: A review of some recent results. Earth-Sci. Rev. 1997. Vol. 42, no. 4. P. 231-272. doi: 10.1016/ S0012-8252(97)81859-4
Robertson J. E., Robinson C., Turner D. R., Hol-ligan P., Watson A. J., Boyd P., Fernandez E., and Finch M. The impact of a coccolithophore bloom on oceanic carbon uptake in the northeast Atlantic during summer 1991. Deep Sea Res. 1994. Vol. 41, no. 2. P. 297-314. doi: 10.1016/0967
Shutler J. D., Land P. E., Brown C. W., Findlay H. S., Donlon C. J., MedlandM., Snooke R., and Blackford J. C. Coccolithophore surface distributions in the North Atlantic and their modulation of the air-sea flux of CO2 from 10 years of satellite earth observation data. Biogeosciences. 2013. Vol. 10. P. 2699-2709. doi: 10.5194/bg-10-2699-2013
Smyth T. J., Tyrrell T., and Tarrant B. Time series of coccolithophore activity in the Barents Sea from twenty years of satellite imagery. Geophys. Res. Lett. 2004. Vol. 31. doi: 10.1029/2004GL019735
Tyrrell T., and Merico A. Emiliania huxleyi: bloom observations and the conditions that induce them. In Coccolithophores: from molecular processes to global impact. Eds. H. R. Thierstein and J. R. Young. Berlin: Springer, 2004. P. 75-97. doi: 10.1007/978-3-662-06278-4_4
VinogradovM. E., Shushkina E. A., Mikaelyan A. S., and Nezlin N. P. Temporal (seasonal and interannual) changes of ecosystem of the open waters of the Black Sea. In Environmental Degradation of the Black Sea: Challenges and Remedies. Eds. S. T. Besiktepe, Ü. Ünlüa-ta, and A. S. Bologa. NATO Science Partnership Sub-series: 2(56). Dordrecht: Springer Netherlands, 1999. P. 109-129. doi: 10.1007/978-94-011-4568-8_8
Wu L., Hasekamp O., Hu H., Landgraf J., Butz A., aan de Brugh J., Aben I., Pollard D. F., Griffith D. W. T., Feist D. G., Koshelev D., Hase F., Toon G. C., Ohya-ma H., Morino I., Notholt J., ShiomiK., Iraci L., Schneider M., de Maziére M., Sussmann R., Kivi R., Warneke T., Goo T.-Y., and Té Y. Carbon dioxide retrieval from OCO-2 satellite observations using the Re-moTeC algorithm and validation with TCCON measurements. Atmos. Meas. Tech. 2018. Vol. 11. P. 3111-3130. doi: 10.5194/amt-11 -3111 -2018
Received July 08, 2019
СВЕДЕНИЯ ОБ АВТОРАХ:
CONTRIBUTORS:
Кондрик Дмитрий Вячеславович
научный сотрудник
Научный фонд «Международный центр по окружающей среде и дистанционному зондированию имени Нансена» 14-я линия В. О., оф. 49, Санкт-Петербург, Россия, 199034 эл. почта: dmitry.kondrik@niersc.spb.ru
Казаков Эдуард Эдуардович
научный сотрудник
Научный фонд «Международный центр по окружающей среде и дистанционному зондированию имени Нансена» 14-я линия В. О., оф. 49, Санкт-Петербург, Россия, 199034 эл. почта: ekazakov@niersc.spb.ru
Поздняков Дмитрий Викторович
заместитель директора по науке, руководитель группы водных экосистем, д. ф.-м. н., проф. Научный фонд «Международный центр по окружающей среде и дистанционному зондированию имени Нансена» 14-я линия В. О., оф. 49, Санкт-Петербург, Россия, 199034 эл. почта: dmitry.pozdnyakov@niersc.spb.ru
Йоханнессен Ола Матиас
Президент Научного Общества имени Нансена; Президент Уставного Фонда Нансен-Центров в Норвегии и Санкт-Петербурге; Почетный профессор Геофизического Института при университете Бергена, Норвегия Берген, Норвегия, 5006
эл. почта: ola.johannessen@nansenscientificsociety.no
Kondrik, Dmitry
Scientific Foundation "Nansen Environmental
and Remote Sensing Centre"
14th Line, 7, Office 49, Vasilievsky Island, 199034
St. Petersburg, Russia
e-mail: dmitry.kondrik@niersc.spb.ru
Kazakov, Eduard
Scientific Foundation "Nansen Environmental
and Remote Sensing Centre"
14th Line, 7, Office 49, Vasilievsky Island, 199034
St. Petersburg, Russia
e-mail: ekazakov@niersc.spb.ru
Pozdnyakov, Dmitry
Scientific Foundation "Nansen Environmental
and Remote Sensing Centre"
14th Line, 7, Office 49, Vasilievsky Island, 199034
St. Petersburg, Russia
e-mail: dmitry.pozdnyakov@niersc.spb.ru
Johannessen, Ola
Nansen Scientific Society; Nansen Centres in St. Petersburg and Bergen; Geophysical Institute, University of Bergen Kong Christian Frederiks Plass 6, 5006 Bergen, Norway e-mail: ola.johannessen@nansenscientificsociety.no
