Importance of Human-Induced Nitrogen Flux Increases for Simulated Arctic Warming

Hyung-Gyu Lim Princeton University/Atmospheric and Oceanic Sciences Program, Princeton, New Jersey
Division of Environmental Science and Engineering, POSTECH, Pohang, South Korea

Search for other papers by Hyung-Gyu Lim in
Current site
Google Scholar
PubMed
Close
,
Jong-Yeon Park Department of Earth and Environmental Sciences, Jeonbuk National University, Jeollabuk-do, South Korea

Search for other papers by Jong-Yeon Park in
Current site
Google Scholar
PubMed
Close
,
John P. Dunne National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

Search for other papers by John P. Dunne in
Current site
Google Scholar
PubMed
Close
,
Charles A. Stock National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

Search for other papers by Charles A. Stock in
Current site
Google Scholar
PubMed
Close
,
Sung-Ho Kang Korea Polar Research Institute, Incheon, South Korea

Search for other papers by Sung-Ho Kang in
Current site
Google Scholar
PubMed
Close
, and
Jong-Seong Kug Division of Environmental Science and Engineering, POSTECH, Pohang, South Korea

Search for other papers by Jong-Seong Kug in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Human activities such as fossil fuel combustion, land-use change, nitrogen (N) fertilizer use, emission of livestock, and waste excretion accelerate the transformation of reactive N and its impact on the marine environment. This study elucidates that anthropogenic N fluxes (ANFs) from atmospheric and river deposition exacerbate Arctic warming and sea ice loss via physical–biological feedback. The impact of physical–biological feedback is quantified through a suite of experiments using a coupled climate–ocean–biogeochemical model (GFDL-CM2.1-TOPAZ) by prescribing the preindustrial and contemporary amounts of riverine and atmospheric N fluxes into the Arctic Ocean. The experiment forced by ANFs represents the increase in ocean N inventory and chlorophyll concentrations in present and projected future Arctic Ocean relative to the experiment forced by preindustrial N flux inputs. The enhanced chlorophyll concentrations by ANFs reinforce shortwave attenuation in the upper ocean, generating additional warming in the Arctic Ocean. The strongest responses are simulated in the Eurasian shelf seas (Kara, Barents, and Laptev Seas; 65°–90°N, 20°–160°E) due to increased N fluxes, where the annual mean surface temperature increase by 12% and the annual mean sea ice concentration decrease by 17% relative to the future projection, forced by preindustrial N inputs.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jong-Seong Kug, jskug1@gmail.com

Abstract

Human activities such as fossil fuel combustion, land-use change, nitrogen (N) fertilizer use, emission of livestock, and waste excretion accelerate the transformation of reactive N and its impact on the marine environment. This study elucidates that anthropogenic N fluxes (ANFs) from atmospheric and river deposition exacerbate Arctic warming and sea ice loss via physical–biological feedback. The impact of physical–biological feedback is quantified through a suite of experiments using a coupled climate–ocean–biogeochemical model (GFDL-CM2.1-TOPAZ) by prescribing the preindustrial and contemporary amounts of riverine and atmospheric N fluxes into the Arctic Ocean. The experiment forced by ANFs represents the increase in ocean N inventory and chlorophyll concentrations in present and projected future Arctic Ocean relative to the experiment forced by preindustrial N flux inputs. The enhanced chlorophyll concentrations by ANFs reinforce shortwave attenuation in the upper ocean, generating additional warming in the Arctic Ocean. The strongest responses are simulated in the Eurasian shelf seas (Kara, Barents, and Laptev Seas; 65°–90°N, 20°–160°E) due to increased N fluxes, where the annual mean surface temperature increase by 12% and the annual mean sea ice concentration decrease by 17% relative to the future projection, forced by preindustrial N inputs.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jong-Seong Kug, jskug1@gmail.com
Save
  • Anav, A., and Coauthors, 2013: Evaluating the land and ocean components of the global carbon cycle in the CMIP5 Earth system models. J. Climate, 26, 68016843, https://doi.org/10.1175/JCLI-D-12-00417.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anderson, D. M., P. M. Glibert, and J. M. Burkholder, 2002: Harmful algal blooms and eutrophication: Nutrient sources, composition, and consequences. Estuaries, 25, 704726, https://doi.org/10.1007/BF02804901.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anderson, J. L., V. Balaji, A. J. Broccoli, and W. F. Cooke, 2004: The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations. J. Climate, 17, 46414673, https://doi.org/10.1175/JCLI-3223.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anderson, W., A. Gnanadesikan, and A. Wittenberg, 2009: Regional impacts of ocean color on tropical Pacific variability. Ocean Sci., 5, 313327, https://doi.org/10.5194/os-5-313-2009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Antonov, J., R. Locarnini, T. Boyer, A. Mishonov, and H. Garcia, 2006: Salinity. Vol. 2, World Ocean Atlas 2005, NOAA Atlas NESDIS 62, 182 pp.

  • Armstrong, R. A., C. Lee, J. I. Hedges, S. Honjo, and S. G. Wakeham, 2002: A new, mechanistic model for organic carbon fluxes in the ocean based on the quantitative association of POC with ballast minerals. Deep-Sea Res. II, 49, 219236, https://doi.org/10.1016/S0967-0645(01)00101-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arneth, A., and Coauthors, 2010: Terrestrial biogeochemical feedbacks in the climate system. Nat. Geosci., 3, 525532, https://doi.org/10.1038/ngeo905.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arrigo, K. R., and G. L. van Dijken, 2011: Secular trends in Arctic Ocean net primary production. J. Geophys. Res., 116, C09011, https://doi.org/10.1029/2011JC007151.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arrigo, K. R., and G. L. van Dijken, 2015: Continued increases in Arctic Ocean primary production. Prog. Oceanogr., 136, 6070, https://doi.org/10.1016/j.pocean.2015.05.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arrigo, K. R., and Coauthors, 2012: Massive phytoplankton blooms under Arctic sea ice. Science, 336, 1408, https://doi.org/10.1126/science.1215065.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boyer, E. W., R. W. Howarth, J. N. Galloway, F. J. Dentener, P. A. Green, and C. J. Vörösmarty, 2006: Riverine nitrogen export from the continents to the coasts. Global Biogeochem. Cycles, 20, GB1S91, https://doi.org/10.1029/2005GB002537.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bring, A., and Coauthors, 2015: Implications of freshwater flux data from the CMIP5 multimodel output across a set of Northern Hemisphere drainage basins. Earth’s Future, 3, 206217, https://doi.org/10.1002/2014EF000296.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brüchert, V., and Coauthors, 2018: Carbon mineralization in Laptev and East Siberian Sea shelf and slope sediment. Biogeosciences, 15, 471490, https://doi.org/10.5194/bg-15-471-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cabré, A., I. Marinov, and S. Leung, 2015: Consistent global responses of marine ecosystems to future climate change across the IPCC AR5 Earth system models. Climate Dyn., 45, 12531280, https://doi.org/10.1007/s00382-014-2374-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delworth, T. L., and Coauthors, 2006: GFDL’s CM2 global coupled climate models. Part I: Formulation and simulation characteristics. J. Climate, 19, 643674, https://doi.org/10.1175/JCLI3629.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., R. Tomas, M. Alexander, and D. Lawrence, 2010: The seasonal atmospheric response to projected Arctic sea ice loss in the late twenty-first century. J. Climate, 23, 333351, https://doi.org/10.1175/2009JCLI3053.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Diaz, R. J., and R. Rosenberg, 2008: Spreading dead zones and consequences for marine ecosystems. Science, 321, 926929, https://doi.org/10.1126/science.1156401.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duce, R. A., and Coauthors, 2008: Impacts of atmospheric anthropogenic nitrogen on the open ocean. Science, 320, 893897, https://doi.org/10.1126/science.1150369.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunne, J. P., R. A. Armstrong, A. Gnanadesikan, and J. L. Sarmiento, 2005: Empirical and mechanistic models for the particle export ratio. Global Biogeochem. Cycles, 19, GB4026, https://doi.org/10.1029/2004GB002390.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunne, J. P., A. Gnanadesikan, J. L. Sarmiento, and R. D. Slater, 2010: Technical description of the prototype version (v0) of Tracers of Phytoplankton with Allometric Zooplankton (TOPAZ) ocean biogeochemical model as used in the Princeton IFMIP model. Biogeosciences, 7, 122, https://doi.org/10.5194/bg-7-3593-2010.

    • Search Google Scholar
    • Export Citation
  • Dunne, J. P., B. Hales, and J. R. Toggweiler, 2012a: Global calcite cycling constrained by sediment preservation controls. Global Biogeochem. Cycles, 26, GB3023, https://doi.org/10.1029/2010GB003935.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunne, J. P., and Coauthors, 2012b: GFDL’s ESM2 global coupled climate–carbon Earth system models. Part I: Physical formulation and baseline simulation characteristics. J. Climate, 25, 66466665, https://doi.org/10.1175/JCLI-D-11-00560.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunne, J. P., and Coauthors, 2013: GFDL’s ESM2 global coupled climate–carbon Earth system models. Part II: Carbon system formulation and baseline simulation characteristics. J. Climate, 26, 22472267, https://doi.org/10.1175/JCLI-D-12-00150.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Evans, S., P. Ginoux, S. Malyshev, and E. Shevliakova, 2016: Climate–vegetation interaction and amplification of Australian dust variability. Geophys. Res. Lett., 43, 11 82311 830, https://doi.org/10.1002/2016GL071016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fan, S.-M., W. J. Moxim, and H. Levy, 2006: Aeolian input of bioavailable iron to the ocean. Geophys. Res. Lett., 33, L07602, https://doi.org/10.1029/2005GL024852.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frey, K. E., J. W. McClelland, R. M. Holmes, and L. C. Smith, 2007: Impacts of climate warming and permafrost thaw on the riverine transport of nitrogen and phosphorus to the Kara Sea. J. Geophys. Res. Biogeosci., 112, G04S58, https://doi.org/10.1029/2006JG000369.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fritz, M., J. Vonk, and H. Lantuit, 2017: Collapsing Arctic coastlines. Nat. Climate Change, 7, 67, https://doi.org/10.1038/nclimate3188.

  • Galloway, J. N., J. D. Aber, J. W. Erisman, S. P. Seitzinger, R. W. Howarth, E. B. Cowling, and B. J. Cosby, 2003: The nitrogen cascade. BioScience, 53, 341356, https://doi.org/10.1641/0006-3568(2003)053[0341:TNC]2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Galloway, J. N., and Coauthors, 2004: Nitrogen cycles: Past, present, and future. Biogeochemistry, 70, 153226, https://doi.org/10.1007/s10533-004-0370-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Galloway, J. N., and Coauthors, 2008: Transformation of the nitrogen cycle: Recent trends, questions, and potential solutions. Science, 320, 889892, https://doi.org/10.1126/science.1136674.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garcia, H., R. Locarnini, T. Boyer, and J. Antonov, 2006a: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation. Vol. 3, World Ocean Atlas 2005, NOAA Atlas NESDIS 63, 342 pp.

  • Garcia, H., R. Locarnini, T. Boyer, J. Antonov, and S. Levitus, 2006b: Nutrients (Phosphate, Nitrate, Silicate). Vol. 4, World Ocean Database 2005, NOAA Atlas NESDIS 64, 396 pp.

  • Garcia, H., and Coauthors, 2014: Dissolved Inorganic Nutrients (Phosphate, Nitrate, Silicate). Vol. 4, World Ocean Atlas 2013, NOAA Atlas NESDIS 76, 25 pp.

  • Geider, R., H. MacIntyre, and T. Kana, 1997: Dynamic model of phytoplankton growth and acclimation: Responses of the balanced growth rate and the chlorophyll a:carbon ratio to light, nutrient-limitation and temperature. Mar. Ecol. Prog. Ser., 148, 187200, https://doi.org/10.3354/meps148187.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giese, B. S., and S. Ray, 2011: El Niño variability in Simple Ocean Data Assimilation (SODA), 1871–2008. J. Geophys. Res., 116, C02024, https://doi.org/10.1029/2010JC006695.

    • Search Google Scholar
    • Export Citation
  • Green, P. A., C. J. Vörösmarty, M. Meybeck, J. N. Galloway, B. J. Peterson, and E. W. Boyer, 2004: Pre-industrial and contemporary fluxes of nitrogen through rivers: A global assessment based on typology. Biogeochemistry, 68, 71105, https://doi.org/10.1023/B:BIOG.0000025742.82155.92.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffies, S. M., 2012: Elements of the Modular Ocean Model (MOM). NOAA Geophysical Fluid Dynamics Laboratory/GFDL Ocean Group Tech. Rep. 7, 632 pp.

  • Griffies, S. M., and Coauthors, 2011: The GFDL CM3 coupled climate model: Characteristics of the ocean and sea ice simulations. J. Climate, 24, 35203544, https://doi.org/10.1175/2011JCLI3964.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gruber, N., and J. L. Sarmiento, 1997: Global patterns of marine nitrogen fixation and denitrification. Global Biogeochem. Cycles, 11, 235266, https://doi.org/10.1029/97GB00077.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gruber, N., and J. N. Galloway, 2008: An Earth-system perspective of the global nitrogen cycle. Nature, 451, 293296, https://doi.org/10.1038/nature06592.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hegglin, M., D. Kinnison, and J.-F. Lamarque, 2016: CCMI nitrogen surface fluxes in support of CMIP6–version 2.0. Earth System Grid Federation, accessed 2018, https://doi.org/10.22033/ESGF/input4MIPs.1125.

    • Crossref
    • Export Citation
  • Holmes, R. M., B. J. Peterson, V. V. Gordeev, A. V. Zhulidov, M. Meybeck, R. B. Lammers, and C. J. Vörösmarty, 2000: Flux of nutrients from Russian rivers to the Arctic Ocean: Can we establish a baseline against which to judge future changes? Water Resour. Res., 36, 23092320, https://doi.org/10.1029/2000WR900099.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holmes, R. M., and Coauthors, 2001: Nutrient chemistry of the Ob’ and Yenisey Rivers, Siberia: Results from June 2000 expedition and evaluation of long-term data sets. Mar. Chem., 75, 219227, https://doi.org/10.1016/S0304-4203(01)00038-X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holmes, R. M., J. W. McClelland, P. A. Raymond, B. B. Frazer, B. J. Peterson, and M. Stieglitz, 2008: Lability of DOC transported by Alaskan rivers to the Arctic Ocean. Geophys. Res. Lett., 35, L03402, https://doi.org/10.1029/2007GL032837.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holmes, R. M., and Coauthors, 2012: Seasonal and annual fluxes of nutrients and organic matter from large rivers to the Arctic Ocean and surrounding seas. Estuaries Coasts, 35, 369382, https://doi.org/10.1007/s12237-011-9386-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Horowitz, L. W., and Coauthors, 2003: A global simulation of tropospheric ozone and related tracers: Description and evaluation of MOZART, version 2. J. Geophys. Res., 108, 4784, https://doi.org/10.1029/2002JD002853.

    • Search Google Scholar
    • Export Citation
  • Hyun, S.-H., S.-W. Yeh, and J. Yoon, 2017: Reduction of internal climate variability in surface temperature due to sea-ice loss since the mid-21st century. Int. J. Climatol., 37, 52115216, https://doi.org/10.1002/joc.5146.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hyun, S.-H., S.-W. Yeh, S.-Y. Song, H.-S. Park, and B. P. Kirtman, 2020: Understanding intermodel diversity when simulating the time of emergence in CMIP5 climate models. Geophys. Res. Lett., 47, e2020GL087923, https://doi.org/10.1029/2020GL087923.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jakobsson, M., 2002: Hypsometry and volume of the Arctic Ocean and its constituent seas. Geochem. Geophys. Geosyst., 3, 118, https://doi.org/10.1029/2001GC000302.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C. D., and Coauthors, 2016: The C4MIP experimental protocol for CMIP6. Geosci. Model Dev., 9, 28532880, https://doi.org/10.5194/gmd-9-2853-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jun, S.-Y., S.-J. Choi, and B.-M. Kim, 2018: Dynamical core in atmospheric model does matter in the simulation of Arctic climate. Geophys. Res. Lett., 45, 28052814, https://doi.org/10.1002/2018GL077478.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Key, R. M., and Coauthors, 2004: A global ocean carbon climatology: Results from global data analysis project (GLODAP). Global Biogeochem. Cycles, 18, GB4031, https://doi.org/10.1029/2004GB002247.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, G. E., A. Gnanadesikan, and M.-A. Pradal, 2016: Increased surface ocean heating by colored detrital matter (CDM) linked to greater Northern Hemisphere ice formation in the GFDL CM2Mc ESM. J. Climate, 29, 90639076, https://doi.org/10.1175/JCLI-D-16-0053.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, I.-N., K. Lee, N. Gruber, D. M. Karl, J. L. Bullister, S. Yang, and T.-W. Kim, 2014: Increasing anthropogenic nitrogen in the North Pacific Ocean. Science, 346, 11021106, https://doi.org/10.1126/science.1258396.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krishnamurthy, A., J. K. Moore, C. S. Zender, and C. Luo, 2007: Effects of atmospheric inorganic nitrogen deposition on ocean biogeochemistry. J. Geophys. Res. Biogeosci., 112, G02019, https://doi.org/10.1029/2006JG000334.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kwon, Y.-O., A. Camacho, C. Martinez, and H. Seo, 2018: North Atlantic winter eddy-driven jet and atmospheric blocking variability in the Community Earth System Model version 1 Large Ensemble simulations. Climate Dyn., 51, 32753289, https://doi.org/10.1007/s00382-018-4078-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamarque, J. F., and Coauthors, 2012: CAM-chem: Description and evaluation of interactive atmospheric chemistry in the Community Earth System Model. Geosci. Model Dev., 5, 369411, https://doi.org/10.5194/gmd-5-369-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lantuit, H., W. H. Pollard, N. Couture, M. Fritz, L. Schirrmeister, H. Meyer, and H. W. Hubberten, 2012: Modern and late Holocene retrogressive thaw slump activity on the Yukon coastal plain and Herschel Island, Yukon territory, Canada. Permafr. Periglac. Process., 23, 3951, https://doi.org/10.1002/ppp.1731.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Large, W. G., and S. G. Yeager, 2004: Diurnal to decadal global forcing for ocean and sea-ice models: The data sets and flux climatologies. NCAR Tech. Note NCAR/TN-460+STR, 112 pp., http://doi.org/10.5065/D6KK98Q6.

    • Crossref
    • Export Citation
  • Laufkötter, C., and Coauthors, 2015: Drivers and uncertainties of future global marine primary production in marine ecosystem models. Biogeosciences, 12, 69556984, https://doi.org/10.5194/bg-12-6955-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lauvset, S. K., and Coauthors, 2016: New global interior ocean mapped climatology: the 1° × 1° GLODAP version 2. Earth Syst. Sci. Data, 8, 325340, https://doi.org/10.5194/essd-8-325-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, M., E. Shevliakova, C. A. Stock, S. Malyshev, and P. C. D. Milly, 2019: Prominence of the tropics in the recent rise of global nitrogen pollution. Nat. Commun., 10, 1437, https://doi.org/10.1038/s41467-019-09468-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, Y. J., and Coauthors, 2016: Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models. J. Geophys. Res. Oceans, 121, 86358669, https://doi.org/10.1002/2016JC011993.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Le Fouest, V., M. Babin, and J. É. Tremblay, 2013: The fate of riverine nutrients on Arctic shelves. Biogeosciences, 10, 36613677, https://doi.org/10.5194/bg-10-3661-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Le Fouest, V., M. Manizza, B. Tremblay, and M. Babin, 2015: Modelling the impact of riverine DON removal by marine bacterioplankton on primary production in the Arctic Ocean. Biogeosciences, 12, 33853402, https://doi.org/10.5194/bg-12-3385-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lengaigne, M., G. Madec, L. Bopp, C. Menkes, O. Aumont, and P. Cadule, 2009: Bio-physical feedbacks in the Arctic Ocean using an Earth system model. Geophys. Res. Lett., 36, L21602, https://doi.org/10.1029/2009GL040145.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lim, H.-G., J.-Y. Park, and J.-S. Kug, 2018: Impact of chlorophyll bias on the tropical Pacific mean climate in an Earth system model. Climate Dyn., 51, 26812694, https://doi.org/10.1007/s00382-017-4036-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lim, H.-G., J.-S. Kug, and J.-Y. Park, 2019a: Biogeophysical feedback of phytoplankton on the Arctic climate. Part I: Impact of nonlinear rectification of interactive chlorophyll variability in the present-day climate. Climate Dyn., 52, 53835396, https://doi.org/10.1007/s00382-018-4450-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lim, H.-G., J.-S. Kug, and J.-Y. Park, 2019b: Biogeophysical feedback of phytoplankton on Arctic climate. Part II: Arctic warming amplified by interactive chlorophyll under greenhouse warming. Climate Dyn., 53, 31673180, https://doi.org/10.1007/s00382-019-04693-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, S.-J., 2004: A “vertically Lagrangian” finite-volume dynamical core for global models. Mon. Wea. Rev., 132, 22932307, https://doi.org/10.1175/1520-0493(2004)132<2293:AVLFDC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, X., J. P. Dunne, C. A. Stock, M. J. Harrison, A. Adcroft, and L. Resplandy, 2019: Simulating water residence time in the coastal ocean: A global perspective. Geophys. Res. Lett., 46, 13 91013 919, https://doi.org/10.1029/2019GL085097.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Locarnini, R., and Coauthors, 2006: Temperature. Vol. 1, World Ocean Atlas 2005, NOAA Atlas NESDIS 61, 182 pp.

  • Manizza, M., C. Le Quéré, A. J. Watson, and E. T. Buitenhuis, 2005: Bio-optical feedbacks among phytoplankton, upper ocean physics and sea-ice in a global model. Geophys. Res. Lett., 32, L05603, https://doi.org/10.1029/2004GL020778.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marzeion, B., A. Timmermann, R. Murtugudde, and F.-F. Jin, 2005: Biophysical feedbacks in the tropical Pacific. J. Climate, 18, 5870, https://doi.org/10.1175/JCLI3261.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McClelland, J. W., R. M. Holmes, B. J. Peterson, and M. Stieglitz, 2004: Increasing river discharge in the Eurasian Arctic: Consideration of dams, permafrost thaw, and fires as potential agents of change. J. Geophys. Res., 109, D18102, https://doi.org/10.1029/2004JD004583.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McClelland, J. W., and Coauthors, 2016: Particulate organic carbon and nitrogen export from major Arctic rivers. Global Biogeochem. Cycles, 30, 629643, https://doi.org/10.1002/2015GB005351.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Middelburg, J. J., K. Soetaert, P. M. J. Herman, and C. H. R. Heip, 1996: Denitrification in marine sediments: A model study. Global Biogeochem. Cycles, 10, 661673, https://doi.org/10.1029/96GB02562.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Milly, P. C. D., and A. B. Shmakin, 2002: Global modeling of land water and energy balances. Part I: The Land Dynamics (LaD) model. J. Hydrometeor., 3, 283299, https://doi.org/10.1175/1525-7541(2002)003<0283:GMOLWA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Min, S.-K., X. Zhang, and F. Zwiers, 2008: Human-induced Arctic moistening. Science, 320, 518520, https://doi.org/10.1126/science.1153468.

  • Morel, A., 1988: Optical modeling of the upper ocean in relation to its biogenous matter content (case I waters). J. Geophys. Res., 93, 10 74910 768, https://doi.org/10.1029/JC093iC09p10749.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morel, A., and D. Antoine, 1994: Heating rate within the upper ocean in relation to its bio-optical state. J. Phys. Oceanogr., 24, 16521665, https://doi.org/10.1175/1520-0485(1994)024<1652:HRWTUO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mori, M., M. Watanabe, H. Shiogama, J. Inoue, and M. Kimoto, 2014: Robust Arctic sea-ice influence on the frequent Eurasian cold winters in past decades. Nat. Geosci., 7, 869873, https://doi.org/10.1038/ngeo2277.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mori, M., Y. Kosaka, M. Watanabe, H. Nakamura, and M. Kimoto, 2019: A reconciled estimate of the influence of Arctic sea-ice loss on recent Eurasian cooling. Nat. Climate Change, 9, 123129, https://doi.org/10.1038/s41558-018-0379-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Müller, D., and Coauthors, 2015: The Ocean Colour Climate Change Initiative: I. A methodology for assessing atmospheric correction processors based on in-situ measurements. Remote Sens. Environ., 162, 242256, https://doi.org/10.1016/j.rse.2013.11.026.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murray, R. J., 1996: Explicit generation of orthogonal grids for ocean models. J. Comput. Phys., 126, 251273, https://doi.org/10.1006/jcph.1996.0136.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pabi, S., G. L. van Dijken, and K. R. Arrigo, 2008: Primary production in the Arctic Ocean, 1998–2006. J. Geophys. Res., 113, C08005, https://doi.org/10.1029/2007JC004578.

    • Search Google Scholar
    • Export Citation
  • Park, J. Y., J. S. Kug, J. Badera, R. Rolph, and M. Kwon, 2015: Amplified Arctic warming by phytoplankton under greenhouse warming. Proc. Natl. Acad. Sci. USA, 112, 59215926, https://doi.org/10.1073/pnas.1416884112.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Paulot, F., D. Paynter, M. Winton, P. Ginoux, M. Zhao, and L. W. Horowitz, 2020: Revisiting the impact of sea salt on climate sensitivity. Geophys. Res. Lett., 47, e2019GL085601, https://doi.org/10.1029/2019GL085601.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peterson, B. J., and Coauthors, 2002: Increasing river discharge to the Arctic Ocean. Science, 298, 21712173, https://doi.org/10.1126/science.1077445.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Popova, E. E., and Coauthors, 2012: What controls primary production in the Arctic Ocean? Results from an intercomparison of five general circulation models with biogeochemistry. J. Geophys. Res., 117, C00D12, https://doi.org/10.1029/2011JC007112.

    • Search Google Scholar
    • Export Citation
  • Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Redfield, A. C., 1963: The influence of organisms on the composition of seawater. The Sea, Vol. 2, M. N. Hill, Ed., Wiley-Interscience, 2677.

    • Search Google Scholar
    • Export Citation
  • Regnier, P., and Coauthors, 2013: Anthropogenic perturbation of the carbon fluxes from land to ocean. Nat. Geosci., 6, 597607, https://doi.org/10.1038/ngeo1830.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodgers, K. B., J. Lin, and T. L. Frölicher, 2015: Emergence of multiple ocean ecosystem drivers in a large ensemble suite with an Earth system model. Biogeosciences, 12, 33013320, https://doi.org/10.5194/bg-12-3301-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sánchez-García, L., J. E. Vonk, A. N. Charkin, D. Kosmach, O. V. Dudarev, I. P. Semiletov, and Ö. Gustafsson, 2014: Characterisation of three regimes of collapsing Arctic ice complex deposits on the SE Laptev sea coast using biomarkers and dual carbon isotopes. Permafrost Periglacial Process., 25, 172183, https://doi.org/10.1002/ppp.1815.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schlunegger, S., K. B. Rodgers, J. L. Sarmiento, T. L. Frölicher, J. P. Dunne, M. Ishii, and R. Slater, 2019: Emergence of anthropogenic signals in the ocean carbon cycle. Nat. Climate Change, 9, 719725, https://doi.org/10.1038/s41558-019-0553-2.

    • Crossref
    • Search Google Scholar
    • Export Citation