Surveys in Geophysics

, Volume 38, Issue 1, pp 349–383

Testing the Quality of Sea-Level Data Using the GECCO Adjoint Assimilation Approach

  • Martin G. Scharffenberg
  • Armin Köhl
  • Detlef Stammer
Article
  • 298 Downloads

Abstract

Besides providing an estimate of the changing ocean state, an important result of the dynamically consistent estimating the circulation and climate of the ocean (ECCO) state estimate approach is the provision of a posterior model–data residuals which contain important information about elements in the assimilated observations that are inconsistent with the model dynamics or with the information present in other ocean data sets that are being used as constraints in the assimilation procedure. Based on decreased GECCO2 model–data residuals, upon using the altimeter data through the ESA climate change initiative (cci) sea-level (SL) project, we show here that the recently reprocessed ESA SL_cci altimeter data set (SL1) has been improved relative to the earlier AVISO altimetry data set and is now more consistent with the GECCO2 estimate and with the information about the changing ocean state embedded in other ocean data sets. The improvement can be shown to exist separately for both TOPEX/POSEIDON and ERS data sets. The study reveals that especially in regions characterized by small sea surface height (SSH) variability and small signal-to-noise ratio in the SSH data, improvements can be on the order of 30% of previously existing model–data residuals. However, in some regions we can find degradations, particulary in those where GECCO2 has little skill in representing the altimeter data and where evaluation of the products with GECCO2 is thus not advisable. Upon the assimilation of the new SL1 data set, the GECCO2 synthesis was further improved. However, adding the sea surface temperature (SST) from the SST_cci project as additional constrain, no further impact can be identified.

Keywords

Altimeter observations Data assimilation Ocean state estimate Ocean Modeling 

References

  1. Ablain M, Cazenave A, Larnicol G, Balmaseda M, Cipollini P, Faugère Y, Fernandes MJ, Henry O, Johannessen JA, Knudsen P, Andersen O, Legeais J, Meyssignac B, Picot N, Roca M, Rudenko S, Scharffenberg MG, Stammer D, Timms G, Benveniste J (2015) Improved sea level record over the satellite altimetry era (1993–2010) from the climate change initiative project. Ocean Sci 11:67–82. doi:10.5194/os-11-67-2015 CrossRefGoogle Scholar
  2. Andersen OB, Knudsen P, Stenseng L (2015) The DTU13 MSS (mean sea surface) and MDT (mean dynamic topography) from 20 years of satellite altimetry. International Association of Geodesy Symposia. Springer, Berlin, pp 1–10. doi:10.1007/1345_2015_182 Google Scholar
  3. Cazenave A, Larnicol G, Legeais J-F, Ablain M, Faugère Y, Mbajon Njiche S, Timms G, Meyssignac B, Balmaseda M, Zuo H, Johannessen J, Scharffenberg MG, Stammer D, Andersen O, Knudsen P, Zawadzki L, Thibaut P, Poisson J-C, Picard B, Carrre L, Mertz F, Lauret O, Rudenko S, Farquhar C, Pechorro E, Roca M, Nilo P, Cipollini P, Calafat F, Fernandes J, Lazaro C, Quartly G, Kurekin A, Nencioli F, Fenoglio-Marc L, Benveniste J, Lucas B, Dinardo S, Ambrozio A (2014) ESA sea level climate change initiative (ESA SL_cci): sea level essential climate variable products, version 1.1., December 2014. doi:10.5270/esa-sea_level_cci-1993_2013-v_1.1-201412
  4. Flato G, Marotzke J, Abiodun B, Braconnot P, Chou SC, Collins W, Cox P, Driouech F, Emori S, Eyring V, Forest Chr, Gleckler P, Guilyardi E, Jakob Chr, Kattsov V, Reason Chr, Rummukainen M (2013) Evaluation of climate models. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM, (eds) Climatic change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  5. Ingleby B, Huddleston M (2007) Quality control of ocean temperature and salinity profiles—historical and real-time data. J Mar Syst 65(1):158–175. doi:10.1016/j.jmarsys.2005.11.019 CrossRefGoogle Scholar
  6. Köhl A (2015) Evaluation of the GECCO2 ocean synthesis: transports of volume, heat and freshwater in the Atlantic. Q J R Meteorol Soc 141:166–181. doi:10.1002/qj.2347 CrossRefGoogle Scholar
  7. Köhl A, Stammer D (2008) Decadal sea level changes in the 50-year GECCO ocean synthesis. J Clim 21(9):1876–1890. doi:10.1175/2007JCLI2081.1 CrossRefGoogle Scholar
  8. Menemenlis D, Fukumori I, Lee T (2005) Using Greens functions to calibrate an ocean general circulation model. Mon Weather Rev 133:1224–1240CrossRefGoogle Scholar
  9. Merchant CJ, Embury O, Roberts-Jones J, Fiedler E, Bulgin CE, Corlett GK, Good S, McLaren A, Rayner N, Morak-Bozzo S, Donlon C (2014) Sea surface temperature datasets for climate applications from phase 1 of the European space agency climate change initiative (SST CCI). Geosci Data J 1:179–191. doi:10.1002/gdj3.20 CrossRefGoogle Scholar
  10. Stammer D, Tokmakian R, Semtner A, Wunsch C (1996) How well does a 1/4\(^{\circ }\) global circulation model simulate large-scale oceanic observations? J Geophys Res 101(C11):25779. doi:10.1029/96JC01754 CrossRefGoogle Scholar
  11. Stammer D, Ueyoshi K, Köhl A, Large WG, Josey SA, Wunsch C (2004) Estimating air-sea fluxes of heat, freshwater and momentum through global ocean data assimilation. J Geophys Res 109:C05023. doi:10.1029/2003JC002082 CrossRefGoogle Scholar
  12. Stammer D, Köhl A, Wunsch C (2007) Impact of accurate geoid fields on estimates of the ocean circulation. J Atmos Ocean Technol 24(8):1464–1478. doi:10.1175/JTECH2044.1 CrossRefGoogle Scholar
  13. Stammer D, Balmaseda M, Heimbach P, Köhl A, Weaver A (2016) Ocean data assimilation in support of climate applications: status and perspectives. Ann Rev Mar Sci 8:491–518. doi:10.1146/annurev-marine-122414-034113

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Martin G. Scharffenberg
    • 1
  • Armin Köhl
    • 1
  • Detlef Stammer
    • 1
  1. 1.Universität HamburgHamburgGermany

Personalised recommendations