Nov.  2019

Article Contents

# Influences of the NAO on the North Atlantic CO2 Fluxes in Winter and Summer on the Interannual Scale

Fund Project:

National Key Research and Development Program of China (GrantNo. 2016YFB0200800) and the National Natural Science Founda-tion of China (Grant No. 41530426)

• The differences in the influences of the North Atlantic Oscillation (NAO) on the air–sea CO2 fluxes (fCO2) in the North Atlantic (NA) between different seasons and between different regions are rarely fully investigated. We used observation-based data of fCO2, surface-ocean CO2 partial pressure (pCO2sea), wind speed and sea surface temperature (SST) to analyze the relationship between the NAO and fCO2 of the subtropical and subpolar NA in winter and summer on the interannual time scale. Based on power spectrum estimation, there are significant interannual signs with a 2–6 year cycle in the NAO indexes and area-averaged fCO2 anomalies in winter and summer from 1980 to 2015. Regression analysis with the 2–6 year filtered data shows that on the interannual scale the response of the fCO2 anomalies to the NAO has an obvious meridional wave-train-like pattern in winter, but a zonal distribution in summer. This seasonal difference is because in winter the fCO2 anomalies are mainly controlled by the NAO-driven wind speed anomalies, which have a meridional distribution pattern, while in summer they are dominated by the NAO-driven SST anomalies, which show distinct zonal difference in the subtropical NA. In addition, in the same season, there are different factors controlling the variation of pCO2sea in different regions. In summer, SST is important to the interannual variation of pCO2sea in the subtropical NA, while some biogeochemical variables probably control the pCO2sea variation in the subpolar NA.
摘要: 北大西洋海气CO2通量（fCO2）在不同季节和不同海域对北大西洋涛动（NAO）的响应差异很少被研究。我们用基于观测的fCO2、海表CO2分压（pCO2sea）、风速和海表温度（SST）资料来分析北大西洋副热带和副极地海域冬季和夏季fCO2的年际变化及其与NAO的关系。基于功率谱的分析显示，无论夏季还是冬季，从1980年到2015年，NAO和区域平均的fCO2异常都有显著的2-6年周期的年际变化信号。对提取的年际信号数据进行回归分析，结果表明：在年际尺度上，fCO2异常对NAO的响应在冬季具有明显的经向波列传播模式，但在夏季具有明显的纬向分布特征。这种季节性差异是因为在冬季，fCO2异常主要由NAO驱动的风速异常所控制，且风速异常具有沿经向传播特征；在夏季，fCO2异常是由NAO驱动的SST异常所控制，而SST异常在副热带海域表现出了明显的纬向差异。此外，在同一季节里，主导北大西洋不同海域pCO2sea变化的因子也有所不同。比如，在夏季，SST对副热带海域pCO2sea年际变化的影响很重要，而一些生物地球化学变量可能是控制副极地海域pCO2sea年际变化的主要因子。
• Figure A1.  Power spectrum of NAOGong (a, b) and NAONCAR (c, d) in winter (December–January–February) (a, c) and summer (June–July–August) (b, d). Red and green lines indicate 5% and 90% “red noise” confidence bounds. The time period for NAOGong and NAONCAR is 1980–2015.

Figure A2.  Power spectrum of the area-averaged air–sea CO2 flux in winter (December–January–February) (a, b) and summer (June–July–August) (c, d) in the subtropical (a, c) and subpolar (b, d) regions. Red and green lines indicate 5% and 90% “red noise” confidence bounds. All data are from 1980 to 2015.

Figure 1.  Regression coefficients (RCs) of the air–sea CO2 flux anomalies against NAOGong and NAONCAR in winter (December–January–February) on the interannual scale. Shaded areas indicate that RCs are statistically significant at the 95% confidence level of the Student’s t-test. The time period for the data ranges from 1980 to 2015.

Figure 2.  Multi-year mean CO2 fluxes in winter (a), and RCs of the fCO2 anomalies against the 10-m wind speed anomalies (b) and against the partial pressures of CO2 in the sea surface anomalies (c) in winter, respectively. Shaded areas indicate that RCs are significant at the 95% confidence level of the Student’s t-test. The time period for (a) and (b) ranges from 1980 to 2015, and for (c) ranges from 1983 to 2011.

Figure 3.  Regression coefficients (RCs) of the vm10 anomalies against NAOGong and NAONCAR in winter on the interannual scale. Shaded areas indicate that RCs are statistically significant at the 95% confidence level. The time period for the data ranges from 1980 to 2015.

Figure 4.  Regression coefficients (RCs) of the pCO2sea anomalies against NAOGong and NAONCAR in winter on the interannual scale. Shaded areas indicate that RCs are statistically significant at the 95% confidence level. The time period for the data ranges from 1983 to 2011.

Figure 5.  Regression coefficients (RCs) of the pCO2sea anomalies against the SST anomalies in winter (a), and RCs of the SST anomalies against NAOGong (b) and NAONCAR (c) in winter. Shaded areas indicate that RCs are significant at the 95% confidence level of the Student’s t-test. The time period for the data ranges from 1983 to 2011.

Figure 6.  Regression coefficients (RCs) of the fCO2 anomalies against NAOGong and NAONCAR in summer (June–July–August) on the interannual scale. Shaded areas indicate that RCs are statistically significant at the 95% confidence level of the Student’s t-test. The time period for the data ranges from 1980 to 2015.

Figure 7.  Multi-year mean CO2 fluxes in summer (a), and regression coefficients (RCs) of the fCO2 anomalies against the vm10 anomalies (b) and the pCO2sea anomalies (c) in summer. Shaded areas indicate that RCs are significant at the 95% confidence level of the Student’s t-test. The time period for (a) and (b) ranges from 1980 to 2015, and for (c) ranges from 1983 to 2011.

Figure 8.  Regression coefficients (RCs) of the pCO2sea anomalies against NAOGong and NAONCAR in summer on the interannual scale. Shaded areas indicate that RCs are statistically significant at the 95% confidence level of the Student’s t-test. The time period for the data ranges from 1983 to 2011.

Figure 9.  Regression coefficients (RCs) of the pCO2sea anomalies against the SST anomalies in summer (a), and RCs of the SST anomalies against NAOGong (b) and NAONCAR (c) in summer. Shaded areas indicate that RCs are significant at the 95% confidence level of the Student’s t-test. The time period for the data ranges from 1983 to 2011.

•  Bates, N. R., 2007: Interannual variability of the oceanic CO2 sink in the subtropical gyre of the North Atlantic Ocean over the last 2 decades. J. Geophys. Res., 112, C09013, https://doi.org/10.1029/2006JC003759. Bennington, V., G. A. McKinley, S. Dutkiewicz, and D. Ullman, 2009: What does chlorophyll variability tell us about export and air-sea CO2 flux variability in the North Atlantic? Global Biogeochemical Cycles, 23, GB3002, https://doi.org/10.1029/2008GB003241. Bretherton, C. S., M. Widmann, V. P. Dymnikov, J. M. Wallace, and I. Bladé, 1999: The effective number of spatial degrees of freedom of a time-varying field. J. Climate, 12, 1990−2009, https://doi.org/10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2. Cayan, D. R., 1992: Latent and sensible heat flux anomalies over the northern oceans: Driving the sea surface temperature. J. Phys. Oceanogr., 22, 859−881, https://doi.org/10.1175/1520-0485(1992)022<0859:LASHFA>2.0.CO;2. Corbière, A., N. Metzl, G. Reverdin, C. Brunet, and T. Takahashi, 2007: Interannual and decadal variability of the oceanic carbon sink in the North Atlantic subpolar gyre. Tellus B: Chemical and Physical Meteorology, 59, 168−178, https://doi.org/10.1111/j.1600-0889.2006.00232.x. Couldrey, M. P., K. I. C. Oliver, A. Yool, P. R. Halloran, and E. P. Achterberg, 2016: On which timescales do gas transfer velocities control North Atlantic CO2 flux variability? Global Biogeochemical Cycles, 30, 787−802, https://doi.org/10.1002/2015GB005267. Delworth, T. L., and F. R. Zeng, 2016: The impact of the North Atlantic Oscillation on climate through its influence on the Atlantic meridional overturning circulation. J. Climate, 29, 941−962, https://doi.org/10.1175/JCLI-D-15-0396.1. Delworth, T. L., F. R. Zeng, G. A. Vecchi, X. S. Yang, L. P. Zhang, and R. Zhang, 2016: The North Atlantic Oscillation as a driver of rapid climate change in the Northern Hemisphere. Nature Geoscience, 9, 509−512, https://doi.org/10.1038/ngeo2738. Dong, F., Y. C. Li, and B. Wang, 2017: Assessment of responses of tropical Pacific air-sea CO2 flux to ENSO in 14 CMIP5 models. J. Climate, 30, 8595−8613, https://doi.org/10.1175/JCLI-D-16-0543.1. Friedrich, T., A. Oschlies, and C. Eden, 2006: Role of wind stress and heat fluxes in interannual-to-decadal variability of air-sea CO2 and O2 fluxes in the North Atlantic. Geophys. Res. Lett., 33, L21S04, https://doi.org/10.1029/2006GL026538. Gong, D. Y., and S. W. Wang, 2000: The North Atlantic Oscillation index and its interdecadal variability. Chinese Journal of Atmospheric Sciences, 2002, 24, 187−192, https://doi.org/10.3878/j.issn.1006-9895.2000.02.07. (in Chinese with English abstract) Gruber, N., and Coauthors, 2009: Oceanic sources, sinks, and transport of atmospheric CO2. Global Biogeochemical Cycles, 23, GB1005, https://doi.org/10.1029/2008GB003349. Halloran, P. R., B. B. B. Booth, C. D. Jones, F. H. Lambert, D. J. McNeall, I. J. Totterdell, and C. Völker, 2015: The mechanisms of North Atlantic CO2 uptake in a large earth system model ensemble. Biogeosciences, 12, 4497−4508, https://doi.org/10.5194/bg-12-4497-2015. Jing, Y., Y. Li, Y. Xu, and G. Zhou, 2019: Influences of different definitions of the winter NAO index on NAO action centers and its relationship with SST. Atmospheric and Oceanic Science Letters, https://doi.org/10.1080/16742834.2019.1628607. Johnston, D. W., M. T. Bowers, A. S. Friedlaender, and D. M. Lavigne, 2012: The effects of climate change on harp seals (pagophilus groenlandicus). Plos One, 7, e29158, https://doi.org/10.1371/journal.pone.0029158. Keller, K. M., and Coauthors, 2012: Variability of the ocean carbon cycle in response to the North Atlantic Oscillation. Tellus B: Chemical and Physical Meteorology, 64, 18738, https://doi.org/10.3402/tellusb.v64i0.18738. Landschützer, P., N. Gruber, D. C. E. Bakker, U. Schuster, S. Nakaoka, M. R. Payne, T. P. Sasse, and J. Zeng, 2013: A neural network-based estimate of the seasonal to inter-annual variability of the Atlantic Ocean carbon sink. Biogeosciences, 10, 7793−7815, https://doi.org/10.5194/bg-10-7793-2013. Landschützer, P., N. Gruber, D., and D. C. E. Bakker, 2015: A 30 years observation-based global monthly gridded sea surface pCO2 product from 1982 through 2011. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory. [Available from http://cdiac.ornl.gov/ftp/oceans/SPCO2_1982_2011_ETH_SOM_FFN/.] Li, Y. C., and Y. F. Xu, 2012: Uptake and storage of anthropogenic CO2 in the pacific ocean estimated using two modeling approaches. Adv. Atmos. Sci., 29(4), 795−809, https://doi.org/10.1007/s00376-012-1170-4. Metzl, N., and Coauthors, 2010: Recent acceleration of the sea surface fCO2 growth rate in the North Atlantic subpolar gyre (1993−2008) revealed by winter observations. Global Biogeochemical Cycles, 24, GB4004, https://doi.org/10.1029/2009GB003658. Patra, P. K., S. Maksyutov, M. Ishizawa, T. Nakazawa, T. Takahashi, and J. Ukita, 2005: Interannual and decadal changes in the sea-air CO2 flux from atmospheric CO2 inverse modeling. Global Biogeochemical Cycles, 19, GB4013, https://doi.org/10.1029/2004GB002257. Pérez, F. F., H. Mercier, M. Vázquez-Rodríguez, P. Lherminier, A. Velo, P. C. Pardo, G. Rosón, and A. F. Ríos, 2013: Atlantic Ocean CO2 uptake reduced by weakening of the meridional overturning circulation. Nature Geoscience, 6, 146−152, https://doi.org/10.1038/ngeo1680. Pokorná, L., and R. Huth, 2015: Climate impacts of the NAO are sensitive to how the NAO is defined. Theor. Appl. Climatol., 119, 639−652, https://doi.org/10.1007/s00704-014-1116-0. Rödenbeck, C., R. F. Keeling, D. C. E. Bakker, N. Metzl, A. Olsen, C. Sabine, and M. Heimann, 2013: Global surface-ocean $p^{\rm {CO}_2}$ and sea-air CO2 flux variability from an observation-driven ocean mixed-layer scheme. Ocean Science, 9, 193−216, https://doi.org/10.5194/os-9-193-2013. Scaife, A. A., J. R. Knight, G. K. Vallis, and C. K. Folland, 2005: A stratospheric influence on the winter NAO and North Atlantic surface climate. Geophys. Res. Lett., 32, L18715, https://doi.org/10.1029/2005GL023226. Schuster, U., and Coauthors, 2013: An assessment of the Atlantic and Arctic sea-air CO2 fluxes, 1990−2009. Biogeosciences, 10, 607−627, https://doi.org/10.5194/bg-10-607-2013. Schuster, U., A. J. Watson, N. R. Bates, A. Corbiere, M. Gonzalez-Davila, N. Metzl, D. Pierrot, and M. Santana-Casiano, 2009: Trends in North Atlantic sea-surface fCO2 from 1990 to 2006. Deep Sea Research Part II: Topical Studies in Oceanography, 56(8−10), 620−629, https://doi.org/10.1016/j.dsr2.2008.12.011. Takahashi, T., and Coauthors, 2009: Climatological mean and decadal change in surface ocean pCO2, and net sea-air CO2 flux over the global oceans. Deep Sea Research Part II: Topical Studies in Oceanography, 56, 554−577, https://doi.org/10.1016/j.dsr2.2008.12.009. Thomas, H., A. E. Friederike Prowe, I. D. Lima, S. C. Doney, R. Wanninkhof, R. J. Greatbatch, U. Schuster, and A. Corbière, 2008: Changes in the North Atlantic Oscillation influence CO2 uptake in the North Atlantic over the past 2 decades. Global Biogeochemical Cycles, 22, GB4027, https://doi.org/10.1029/2007GB003167. Ullman, D. J., G. A. McKinley, V. Bennington, and S. Dutkiewicz, 2009: Trends in the North Atlantic carbon sink: 1992−2006. Global Biogeochemical Cycles, 23, GB4011, https://doi.org/10.1029/2008GB003383. Viles, H. A., and A. S. Goudie, 2003: Interannual, decadal and multidecadal scale climatic variability and geomorphology. Earth-Science Reviews, 61, 105−131, https://doi.org/10.1016/S0012-8252(02)00113-7. Walker, G. T, 1925: Correlation in seasonal variations of weather — A further study of world weather. Mon. Wea. Rev., 53, 252−254, https://doi.org/10.1175/1520-0493(1925)53<252:CISVOW>2.0.CO;2. Walter, K., and H. F. Graf, 2002: On the changing nature of the regional connection between the North Atlantic Oscillation and sea surface temperature. J. Geophys. Res, 107, ACL-1−ACL 7-13, https://doi.org/10.1029/2001jd000850. Wanninkhof, R., 1992: Relationship between wind speed and gas exchange over the ocean. J. Geophys. Res., 97, 7373−7382, https://doi.org/10.1029/92JC00188. Watson, A. J., and Coauthors, 2009: Tracking the variable North Atlantic sink for atmospheric CO2. Science, 326, 1391−1393, https://doi.org/10.1126/science.1177394. Woollings, T., C. Franzke, D. L. R. Hodson, B. Dong, E. A. Barnes, C. C. Raible, and J. G. Pinto, 2015: Contrasting interannual and multidecadal NAO variability. Climate Dyn., 45, 539−556, https://doi.org/10.1007/s00382-014-2237-y.

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## Manuscript History

Manuscript revised: 07 June 2019
Manuscript accepted: 25 June 2019
###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

## Influences of the NAO on the North Atlantic CO2 Fluxes in Winter and Summer on the Interannual Scale

###### Corresponding author: Yangchun LI, lyc@mail.iap.ac.cn;
• 1. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
• 2. School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China
• 3. Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
• 4. Department of Atmospheric Chemistry and Environmental Sciences, College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China

Abstract: The differences in the influences of the North Atlantic Oscillation (NAO) on the air–sea CO2 fluxes (fCO2) in the North Atlantic (NA) between different seasons and between different regions are rarely fully investigated. We used observation-based data of fCO2, surface-ocean CO2 partial pressure (pCO2sea), wind speed and sea surface temperature (SST) to analyze the relationship between the NAO and fCO2 of the subtropical and subpolar NA in winter and summer on the interannual time scale. Based on power spectrum estimation, there are significant interannual signs with a 2–6 year cycle in the NAO indexes and area-averaged fCO2 anomalies in winter and summer from 1980 to 2015. Regression analysis with the 2–6 year filtered data shows that on the interannual scale the response of the fCO2 anomalies to the NAO has an obvious meridional wave-train-like pattern in winter, but a zonal distribution in summer. This seasonal difference is because in winter the fCO2 anomalies are mainly controlled by the NAO-driven wind speed anomalies, which have a meridional distribution pattern, while in summer they are dominated by the NAO-driven SST anomalies, which show distinct zonal difference in the subtropical NA. In addition, in the same season, there are different factors controlling the variation of pCO2sea in different regions. In summer, SST is important to the interannual variation of pCO2sea in the subtropical NA, while some biogeochemical variables probably control the pCO2sea variation in the subpolar NA.

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