Articles | Volume 18, issue 1
https://doi.org/10.5194/os-18-51-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-51-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Arctic sea level variability from high-resolution model simulations and implications for the Arctic observing system
School of Oceanography, Shanghai Jiao Tong University, Shanghai,
China
Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany
Nuno Serra
Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany
Meng Zhou
School of Oceanography, Shanghai Jiao Tong University, Shanghai,
China
Detlef Stammer
Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany
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Cited articles
AMAP: AMAP Climate Change Update 2019: An Update to Key Findings of Snow, Water, Ice and Permafrost in the Arctic (SWIPA) 2017, AMAP – Arctic
Monitoring and Assessment Programme, Oslo, Norway, 12 pp., 2019.
Armitage, T. W., Bacon, S., Ridout, A. L., Thomas, S. F., Aksenov, Y., and
Wingham, D. J.: Arctic sea surface height variability and change from satellite radar altimetry and grace, 2003–2014, J. Geophys. Res.-Oceans, 121, 4303–4322, https://doi.org/10.1002/2015JC011579, 2016.
Behrendt, A., Sumata, H., Rabe, B., and Schauer, U.: A comprehensive, quality-controlled and up-to-date data set of temperature and salinity data for the Arctic Mediterranean Sea (Version 1.0), links to data files, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.872931, 2017.
Behrendt, A., Sumata, H., Rabe, B., and Schauer, U.: Udash – unified
database for arctic and subarctic hydrography, Earth Syst. Sci. Data, 10,
1119–1138, https://doi.org/10.5194/essd-10-1119-2018, 2018.
Boyer, T., Levitus, S., Garcia, H., Locarnini, R. A., Stephens, C., and
Antonov, J.: Objective analyses of annual, seasonal, and monthly temperature
and salinity for the world ocean on a 0.25 grid, Int. J. Climatol., 25, 931–945, https://doi.org/10.1002/joc.1173, 2005.
Brakstad, A., Våge, K., Håvik, L., and Moore, G. W. K.: Water mass
transformation in the greenland sea during the period 1986–2016, J. Phys. Oceanogr., 49, 121–140, https://doi.org/10.1175/jpo-d-17-0273.1, 2019.
Calafat, F., Chambers, D., and Tsimplis, M.: Inter-annual to decadal sea-level variability in the coastal zones of the norwegian and siberian seas: The role of atmospheric forcing, J. Geophys. Res.-Oceans, 118, 1287–1301, https://doi.org/10.1002/jgrc.20106, 2013.
Chambers, D. P. and Bonin, J. A.: Evaluation of release-05 grace time-variable gravity coefficients over the ocean, Ocean Sci., 8, 859-868,
10.5194/os-8-859-2012, 2012.
Chambers, D. P. and Willis, J. K.: A global evaluation of ocean bottom
pressure from grace, omct, and steric-corrected altimetry, J. Atmos. Ocean. Tech., 27, 1395–1402, https://doi.org/10.1175/2010jtecho738.1, 2010.
Cheng, L. and Zhu, J.: Benefits of cmip5 multimodel ensemble in reconstructing historical ocean subsurface temperature variations, J. Climate, 29, 5393–5416, https://doi.org/10.1175/jcli-d-15-0730.1, 2016.
Dee, D. P., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M., Balsamo, G., and d. Bauer, P.: The era-interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Evensen, G.: The ensemble kalman filter: Theoretical formulation and practical implementation, Ocean Dynam., 53, 343–367,
https://doi.org/10.1007/s10236-003-0036-9, 2003.
Fekete, B. M., Vörösmarty, C. J., and Grabs, W.: High-resolution fields of global runoff combining observed river discharge and simulated water balances, Global Biogeochem. Cy., 16, 15-11–15-10, https://doi.org/10.1029/1999GB001254, 2002.
Forget, G., Campin, J.-M., Heimbach, P., Hill, C. N., Ponte, R. M., and Wunsch, C.: ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation, Geosci. Model Dev., 8, 3071–3104, https://doi.org/10.5194/gmd-8-3071-2015, 2015.
Fukumori, I., Raghunath, R., and Fu, L.-L.: Nature of global large-scale sea
level variability in relation to atmospheric forcing: A modeling study, J. Geophys. Res.-Oceans, 103, 5493–5512, https://doi.org/10.1029/97JC02907, 1998.
Giles, K. A., Laxon, S. W., Ridout, A. L., Wingham, D. J., and Bacon, S.:
Western arctic ocean freshwater storage increased by wind-driven spin-up of
the beaufort gyre, Nat. Geosci., 5, 194–197, https://doi.org/10.1038/ngeo1379, 2012.
Haine, T. W. N., Curry, B., Gerdes, R., Hansen, E., Karcher, M., Lee, C.,
Rudels, B., Spreen, G., de Steur, L., Stewart, K. D., and Woodgate, R.: Arctic freshwater export: Status, mechanisms, and prospects, Global Planet. Change, 125, 13-35, https://doi.org/10.1016/j.gloplacha.2014.11.013, 2015.
Häkkinen, S. and Proshutinsky, A.: Freshwater content variability in the arctic ocean, J. Geophys. Res.-Oceans, 109, C03051, https://doi.org/10.1029/2003JC001940, 2004.
Hibler, W. D.: A dynamic thermodynamic sea ice model, J. Phys. Oceanogr., 9, 815–846, https://doi.org/10.1175/1520-0485(1979)009<0815:adtsim>2.0.co;2, 1979.
Hibler, W. D.: Modeling a variable thickness sea ice cover, Mon. Weather Rev., 108, 1943–1973, https://doi.org/10.1175/1520-0493(1980)108<1943:mavtsi>2.0.co;2, 1980.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., and Woollen, J.: The ncep/ncar 40-year
reanalysis project, B. Am. Meteorol. Soc., 77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Köhl, A.: Evaluation of the GECCO2 Ocean Synthesis: Transports of Volume, Heat and Freshwater in the Atlantic, Q. J. Roy. Meteorol. Soc., 141, 166–181, https://doi.org/10.1002/qj.2347, 2015.
Köhl, A. and Serra, N.: Causes of decadal changes of the freshwater content in the arctic ocean, J. Climate, 27, 3461–3475,
https://doi.org/10.1175/jcli-d-13-00389.1, 2014.
Koldunov, N. V., Serra, N., Köhl, A., Stammer, D., Henry, O., Cazenave,
A., Prandi, P., Knudsen, P., Andersen, O. B., and Gao, Y.: Multimodel
simulations of arctic ocean sea surface height variability in the period 1970–2009, J. Geophys. Res.-Oceans, 119, 8936–8954,
https://doi.org/10.1002/2014JC010170, 2014.
Lee, C. M., Starkweather, S., Eicken, H., Timmermans, M.-L., Wilkinson, J.,
Sandven, S., Dukhovskoy, D., Gerland, S., Grebmeier, J., Intrieri, J. M.,
Kang, S.-H., McCammon, M., Nguyen, A. T., Polyakov, I., Rabe, B., Sagen, H.,
Seeyave, S., Volkov, D., Beszczynska-Möller, A., Chafik, L., Dzieciuch,
M., Goni, G., Hamre, T., King, A. L., Olsen, A., Raj, R. P., Rossby, T.,
Skagseth, Ø., Søiland, H., and Sørensen, K.: A framework for the
development, design and implementation of a sustained arctic ocean observing
system, Front. Mar. Sci., 6, 451, https://doi.org/10.3389/fmars.2019.00451, 2019.
Llovel, W., Willis, J. K., Landerer, F. W., and Fukumori, I.: Deep-ocean
contribution to sea level and energy budget not detectable over the past
decade, Nat. Clim. Change, 4, 1031–1035, https://doi.org/10.1038/nclimate2387, 2014.
Losch, M., Menemenlis, D., Campin, J.-M., Heimbach, P., and Hill, C.: On the
formulation of sea-ice models. Part 1: Effects of different solver implementations and parameterizations, Ocean Model., 33, 129–144,
https://doi.org/10.1016/j.ocemod.2009.12.008, 2010.
Ludwigsen, C. A. and Andersen, O. B.: Contributions to arctic sea level
from 2003 to 2015, Adv. Space Res., 68, 703–710, https://doi.org/10.1016/j.asr.2019.12.027, 2021.
Lyu, G., Wang, H., Zhu, J., Wang, D., Xie, J., and Liu, G.: Assimilating the
along-track sea level anomaly into the regional ocean modeling system using
the ensemble optimal interpolation, Acta Oceanolog. Sin., 33, 72–82,
https://doi.org/10.1007/s13131-014-0469-7, 2014.
Lyu, G., Serra, N., Koehl, A., Zhou M., and Stammer, D.: Arctic sea level variability from high-resolution model simulations and implications for the Arctic observing system, Institute of Oceanography, University of Hamburg, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.912255, 2020.
Lyu, G., Koehl, A., Serra, N., and Stammer, D.: Assessing the current and
future arctic ocean observing system with observing system simulating
experiments, Q. J. Roy. Meteorol. Soc., 147, 2670–2690, https://doi.org/10.1002/qj.4044, 2021.
Marshall, J., Adcroft, A., Hill, C., Perelman, L., and Heisey, C.: A finite-volume, incompressible navier stokes model for studies of the ocean
on parallel computers, J. Geophys. Res.-Oceans, 102, 5753–5766, https://doi.org/10.1029/96JC02775, 1997.
Morison, J., Wahr, J., Kwok, R., and Peralta-Ferriz, C.: Recent trends in Arctic Ocean mass distribution revealed by GRACE, Geophys. Res. Lett., 34, L07602, https://doi.org/10.1029/2006GL029016, 2007.
Morison, J., Kwok, R., Peralta-Ferriz, C., Alkire, M., Rigor, I., Andersen,
R., and Steele, M.: Changing arctic ocean freshwater pathways, Nature, 481,
66–70, https://doi.org/10.1038/nature10705, 2012.
Nguyen, A. T., Heimbach, P., Garg, V. V., Ocaña, V., Lee, C., and Rainville, L.: Impact of synthetic arctic argo-type floats in a coupled
ocean–sea ice state estimation framework, J. Atmos. Ocean. Tech., 37, 1477–1495, https://doi.org/10.1175/jtech-d-19-0159.1, 2020.
Nurser, A. J. G. and Bacon, S.: The rossby radius in the arctic ocean, Ocean Sci., 10, 967–975, https://doi.org/10.5194/os-10-967-2014, 2014.
Overland, J. E., Ballinger, T. J., Cohen, J., Francis, J. A., Hanna, E., Jaiser, R., Kim, B. M., Kim, S. J., Ukita, J., Vihma, T., Wang, M., and Zhang, X.: How do intermittency and simultaneous processes obfuscate the
arctic influence on midlatitude winter extreme weather events?, Environ. Res. Lett., 16, 043002, https://doi.org/10.1088/1748-9326/abdb5d, 2021.
Pawlowicz, R., Beardsley, B., and Lentz, S.: Classical tidal harmonic analysis including error estimates in matlab using t_tide, Comput. Geosci., 28, 929–937, https://doi.org/10.1016/S0098-3004(02)00013-4, 2002.
Peralta-Ferriz, C. and Morison, J.: Understanding the annual cycle of the
arctic ocean bottom pressure, Geophys. Res. Lett., 37, L10603, https://doi.org/10.1029/2010gl042827, 2010.
Perovich, D., Meier, W., Tschudi, M., Hendricks, S., Petty, A., Divine, D.,
Farrell, S., Gerland, S., Haas, C., and Kaleschke, L.: Arctic report card 2020: Sea ice, https://doi.org/10.25923/n170-9h57, 2020.
Polyakov, I. V., Alexeev, V. A., Belchansky, G. I., Dmitrenko, I. A., Ivanov, V. V., Kirillov, S. A., Korablev, A. A., Steele, M., Timokhov, L. A., and Yashayaev, I.: Arctic ocean freshwater changes over the past 100 years and their causes, J. Climate, 21, 364–384, https://doi.org/10.1175/2007jcli1748.1, 2008.
Polyakov, I. V., Pnyushkov, A. V., Alkire, M. B., Ashik, I. M., Baumann, T.
M., Carmack, E. C., Goszczko, I., Guthrie, J., Ivanov, V. V., Kanzow, T.,
Krishfield, R., Kwok, R., Sundfjord, A., Morison, J., Rember, R., and Yulin,
A.: Greater role for atlantic inflows on sea-ice loss in the eurasian basin
of the arctic ocean, Science, 356, 285–291, https://doi.org/10.1126/science.aai8204, 2017.
Polyakov, I. V., Alkire, M. B., Bluhm, B. A., Brown, K. A., Carmack, E. C.,
Chierici, M., Danielson, S. L., Ellingsen, I., Ershova, E. A., Gårdfeldt, K., Ingvaldsen, R. B., Pnyushkov, A. V., Slagstad, D., and Wassmann, P.: Borealization of the arctic ocean in response to anomalous advection from sub-arctic seas, Front. Mar. Sci., 7, 491, https://doi.org/10.3389/fmars.2020.00491, 2020.
Ponte, R. M.: A preliminary model study of the large-scale seasonal cycle in
bottom pressure over the global ocean, J. Geophys. Res.-Oceans, 104, 1289–1300, https://doi.org/10.1029/1998JC900028, 1999.
Proshutinsky, A., Bourke, R., and McLaughlin, F.: The role of the beaufort
gyre in arctic climate variability: Seasonal to decadal climate scales, Geophys. Res. Lett., 29, 2100, https://doi.org/10.1029/2002GL015847, 2002.
Proshutinsky, A., Ashik, I., Häkkinen, S., Hunke, E., Krishfield, R.,
Maltrud, M., Maslowski, W., and Zhang, J.: Sea level variability in the
arctic ocean from aomip models, J. Geophys. Res.-Oceans., 112, C04S08, https://doi.org/10.1029/2006jc003916, 2007.
Proshutinsky, A., Krishfield, R., Toole, J. M., Timmermans, M.-L., Williams,
W., Zimmermann, S., Yamamoto-Kawai, M., Armitage, T. W. K., Dukhovskoy, D.,
Golubeva, E., Manucharyan, G. E., Platov, G., Watanabe, E., Kikuchi, T.,
Nishino, S., Itoh, M., Kang, S.-H., Cho, K.-H., Tateyama, K., and Zhao, J.:
Analysis of the beaufort gyre freshwater content in 2003–2018, J. Geophys. Res.-Oceans, 124, 9658–9689, https://doi.org/10.1029/2019jc015281, 2019.
Proshutinsky, A. Y. and Johnson, M. A.: Two circulation regimes of the wind-driven arctic ocean, J. Geophys. Res.-Oceans, 102, 12493–12514, https://doi.org/10.1029/97JC00738, 1997.
Rabe, B., Karcher, M., Schauer, U., Toole, J. M., Krishfield, R. A., Pisarev, S., Kauker, F., Gerdes, R., and Kikuchi, T.: An assessment of arctic ocean freshwater content changes from the 1990s to the 2006–2008 period, Deep-Sea Research Pt. I, 58, 173–185, https://doi.org/10.1016/j.dsr.2010.12.002, 2011.
Rabe, B., Karcher, M., Kauker, F., Schauer, U., Toole, J. M., Krishfield, R.
A., Pisarev, S., Kikuchi, T., and Su, J.: Arctic ocean basin liquid freshwater storage trend 1992–2012, Geophys. Res. Lett., 41, 961–968, https://doi.org/10.1002/2013GL058121, 2014.
Ronski, S. and Budéus, G.: Time series of winter convection in the
greenland sea, J. Geophys. Res.-Oceans, 110, C04015, https://doi.org/10.1029/2004JC002318, 2005.
Rose, S. K., Andersen, O. B., Passaro, M., Ludwigsen, C. A., and Schwatke, C.: Arctic ocean sea level record from the complete radar altimetry era: 1991–2018, Remote Sens., 11, 1672, https://doi.org/10.3390/rs11141672, 2019.
Sandu, I., Massonnet, F., van Achter, G., Acosta Navarro, J. C., Arduini, G., Bauer, P., Blockley, E., Bormann, N., Chevallier, M., Day, J., Dahoui, M., Fichefet, T., Flocco, D., Jung, T., Hawkins, E., Laroche, S., Lawrence, H., Kristianssen, J., Moreno-Chamarro, E., Ortega, P., Poan, E., Ponsoni, L., and Randriamampianina, R.: The potential of numerical prediction systems to support the design of arctic observing systems: Insights from the applicate and yopp projects, Q. J. Roy. Meteorol. Soc., 147, 3863–3877, https://doi.org/10.1002/qj.4182, 2021.
Schauer, U. and Losch, M.: “Freshwater” in the ocean is not a useful parameter in climate research, J. Phys. Oceanogr., 49, 2309–2321, https://doi.org/10.1175/jpo-d-19-0102.1, 2019.
Smith, W. H. F. and Sandwell, D. T.: Global sea floor topography from satellite altimetry and ship depth soundings, Science, 277, 1956–1962,
https://doi.org/10.1126/science.277.5334.1956, 1997.
Solomon, A., Heuzé, C., Rabe, B., Bacon, S., Bertino, L., Heimbach, P.,
Inoue, J., Iovino, D., Mottram, R., Zhang, X., Aksenov, Y., McAdam, R.,
Nguyen, A., Raj, R. P., and Tang, H.: Freshwater in the arctic ocean 2010–2019, Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, 2021.
Stammer, D., Wunsch, C., and Ponte, R. M.: De-aliasing of global high frequency barotropic motions in altimeter observations, Geophys. Res. Lett., 27, 1175–1178, https://doi.org/10.1029/1999gl011263, 2000.
Stammer, D., Cazenave, A., Ponte, R. M., and Tamisiea, M. E.: Causes for
contemporary regional sea level changes, Annu. Rev. Mar. Sci., 5, 21–46, https://doi.org/10.1146/annurev-marine-121211-172406, 2013.
Steele, M., Morley, R., and Ermold, W.: Phc: A global ocean hydrography with a high-quality arctic ocean, J. Climate, 14, 2079-2087,
https://doi.org/10.1175/1520-0442(2001)014<2079:pagohw>2.0.co;2, 2001.
Toole, J. M. and Krishfield, R.: Woods Hole Oceanographic Institution Ice-Tethered Profiler Program, Ice-Tethered Profiler observations: Vertical
profiles of temperature, salinity, oxygen, and ocean velocity from an
Ice-Tethered Profiler buoy system, NOAA National Centers for Environmental
Information [data set], https://doi.org/10.7289/v5mw2f7x, 2016.
Vinogradova, N. T., Ponte, R. M., and Stammer, D.: Relation between sea
level and bottom pressure and the vertical dependence of oceanic variability, Geophys. Res. Lett., 34, L03608, https://doi.org/10.1029/2006GL028588, 2007.
Volkov, D. L. and Landerer, F. W.: Nonseasonal fluctuations of the arctic
ocean mass observed by the grace satellites, J. Geophys. Res.-Oceans, 118, 6451–6460, https://doi.org/10.1002/2013jc009341, 2013.
Volkov, D. L., Landerer, F. W., and Kirillov, S. A.: The genesis of sea level variability in the barents sea, Cont. Shelf Res., 66, 92–104, https://doi.org/10.1016/j.csr.2013.07.007, 2013.
Woodgate, R. A., Weingartner, T. J., and Lindsay, R.: Observed increases in
bering strait oceanic fluxes from the pacific to the arctic from 2001 to 2011 and their impacts on the arctic ocean water column, Geophys. Res. Lett., 39, L24603, https://doi.org/10.1029/2012GL054092, 2012.
Zhang, J. and Rothrock, D. A.: Modeling arctic sea ice with an efficient plastic solution, J. Geophys. Res.-Oceans, 105, 3325–3338,
https://doi.org/10.1029/1999JC900320, 2000.
Short summary
This study explores the Arctic sea level variability depending on different timescales and the relation to temperature, salinity and mass changes, identifying key parameters and regions that need to be observed coordinately. The decadal sea level variability reflects salinity changes. But it can only reflect salinity change at periods of greater than 1 year, highlighting the requirement for enhancing in situ hydrographic observations and complicated interpolation methods.
This study explores the Arctic sea level variability depending on different timescales and the...