Cited by 56Climate variability and modelsOceanographic and Atmospheric ProcessesMeteorological Phenomena and Simulations

On the relationship between Atlantic Niño variability and ocean dynamics.

Open access
Dippe, Tina, Greatbatch, Richard J., Ding, Hui·2018·Climate Dynamics

Abstract

The Atlantic Niño is the dominant mode of interannual sea surface temperature (SST) variability in the eastern equatorial Atlantic. Current coupled global climate models struggle to reproduce its variability. This is thought to be partly related to an equatorial SST bias that inhibits summer cold tongue growth. Here, we address the question whether the equatorial SST bias affects the ability of a coupled global climate model to produce realistic dynamical SST variability. We assess this by decomposing SST variability into dynamical and stochastic components. To compare our model results with observations, we employ empirical linear models of dynamical SST that, based on the Bjerknes feedback, use the two predictors sea surface height and zonal surface wind. We find that observed dynamical SST variance shows a pronounced seasonal cycle. It peaks during the active phase of the Atlantic Niño and is then roughly 4–7 times larger than stochastic SST variance. This indicates that the Atlantic Niño is a dynamical phenomenon that is related to the Bjerknes feedback. In the coupled model, the SST bias suppresses the summer peak in dynamical SST variance. Bias reduction, however, improves the representation of the seasonal cold tongue and enhances dynamical SST variability by supplying a background state that allows key feedbacks of the tropical ocean–atmosphere system to operate in the model. Due to the small zonal extent of the equatorial Atlantic, the observed Bjerknes feedback acts quasi-instantaneously during the dynamically active periods of boreal summer and early boreal winter. Then, all elements of the observed Bjerknes feedback operate simultaneously. The model cannot reproduce this, although it hints at a better performance when using bias reduction.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s00382-017-3943-z

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Poor representation of the AZM in many models appears related to the under-representation of the thermocline feedback associated with an overly deep mixed layer and too weak upwelling in the eastern Atlantic.

    “Poor representation of the AZM in many models appears related to the under-representation of the thermocline feedback associated with an overly deep mixed layer and too weak upwelling in the eastern Atlantic (Ding et al., 2015a,b;Deppenmeier et al., 2016;Dippe et al., 2018;Jouanno et al., 2017).”

    From The tropical atlantic observing system (2019) · cites this paper as Dippe et al., 2018

    The Introduction says biased simulations have a deeper thermocline and strongly reduced upwelling in the cold-tongue region, making the Atlantic Niño difficult to reproduce. Section 6 links the model bias to impaired feedback, but identifies the KCM’s main problem as the SST–wind relationship. The paper does not attribute that impairment to an overly deep mixed layer; thermocline depth is not mixed-layer depth. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 44

  1. Bjerknes J (1969) Atmospheric teleconnections from the equatorial pacic. Mon Weather Rev 97(3):163-172. doi:10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2 · DOI
  2. Burls NJ, Reason CJC, Penven P, Philander SG (2011) Similarities between the tropical Atlantic seasonal cycle and ENSO: an ener- getics perspective. J Geophys Res Oceans 116(C11):C11010. doi :10.1029/2011JC007164 · DOI
  3. Burls NJ, Reason CJC, Penven P, Philander SG (2012) Energetics of the Tropical Atlantic zonal mode. J Clim 25(21):7442-7466. doi:10.1175/JCLI-D-11-00602. · DOI
  4. C a n e M A ( 1 9 8 4 ) M o d e l i n g s e a l eve l N i ñ o . J P h y s O c e a n o g r 1 4 ( 1 2 ) : 1 8 6 4 -1 8 7 4 . doi:10.1175/1520-0485(1984)014<1864:MSLDEN>2.0.CO;2 · DOI
  5. Carton JA, Cao X, Giese BS, Da Silva AM (1996) Decadal and interannual SST variability in the tropical. Atlantic Ocean. doi:10.1175/1520-0485(1996)838026<1165:DAISVI>2.0.CO;2 · DOI
  6. Chang CY, Carton JA, Grodsky SA, Nigam S (2007) Seasonal cli- mate of the tropical Atlantic sector in the NCAR community climate system model 3: Error structure and probable causes of errors. J Clim 20(6):1053-1070. doi:10.1175/JCLI4047. · DOI
  7. Davey M et al (2002) STOIC: A study of coupled model climatol- ogy and variability 844 in tropical ocean regions. Clim Dyn 18(5):403-420. doi:10.1007/845 s00382-001-0188-6 · DOI
  8. Dee DP et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553-597. doi:10.1002/qj.828 · DOI · Paper page
  9. Deppenmeier AL, Haarsma RJ, Hazeleger W (2016) The Bjerknes feedback in the tropical Atlantic in CMIP5 models. Clim Dyn 1-17. doi:10.1007/s00382-016-2992-z · DOI · Paper page
  10. Ding H, Keenlyside NS, Latif M (2010) Equatorial Atlantic interan- nual variability: role of heat content. J Geophys Res Oceans 115(C9):C09020. doi:10.1029/2010JC006304 · DOI
  11. Ding H, Greatbatch RJ, Latif M, Park W, Gerdes R (2013) Hindcast of the 1976/77 and 1998/99 climate shifts in the Paciffic. J Clim 26(19):7650-7661. doi:10.1175/JCLI-D-12-00626. · DOI
  12. Ding H, Greatbatch RJ, Latif M, Park W (2015) The impact of sea surface temperature bias on equatorial Atlantic interannual vari- ability in partially coupled model experiments. Geophys Res Lett 42(13):5540-5546. doi:10.1002/2015GL064799 · DOI
  13. Draper NR, Smith H (1998) Applied regression analysis. 3rd edn. Wiley, Hoboken. doi:10.1002/9781118625590 · DOI
  14. Frankignoul C, Hasselman K, Hasselmann K (1977) Stochastic cli- mate models, Part II Application to sea-surface temperature anomalies and thermocline variability. Tellus 29(4):289-305. doi:10.1111/j.2153-3490.1977.tb00740.x · DOI
  15. Grodsky SA, Carton JA, Nigam S, Okumura YM (2012) Tropi- cal Atlantic biases in CCSM4. J Clim 25(11):3684-3701. doi:10.1175/JCLI-D-11-00315. · DOI
  16. Harlaß J, Latif M, Park W (2015) Improving climate model simula- tion of tropical Atlantic sea surface temperature: the importance of enhanced vertical atmosphere model resolution. Geophys Res Lett 42(7):2401-2408. doi:10.1002/2015GL063310 · DOI
  17. Hirst AC, Hastenrath S (1983) Atmosphere-ocean mecha- nisms of climate anomalies in the Angola-tropical Atlantic sector. J Phys Oceanogr 13(7):1146-1157. doi:10.1175/1520-0485(1983)013<1146:AOMOCA>2.0.CO;2 · DOI
  18. Hu Z-Z, Huang B (2007) The predictive skill and the most predict- able pattern in the tropical Atlantic: the effect of ENSO. Mon Weather Rev 135(5):1786-1806. doi:10.1175/MWR3393. · DOI
  19. Janicot S, Harzallah A, Fontaine B, Moron V (1998) West Afri- can monsoon dynamics and eastern equatorial Atlantic and Pacific SST anomalies (1970-88). J Clim 11(8):1874-1882. doi:10.1175/1520-0442(1998)011<1874:WAMDAE>2.0.CO;2 · DOI
  20. Kushnir Y, Robinson WA, Chang P, Robertson AW (2006) The phys- ical basis for predicting Atlantic sector seasonal-to-interannual climate variability. J Clim 19(23):5949-5970. doi:10.1175/ JCLI3943. · DOI
  21. Lübbecke JF, McPhaden MJ (2012) On the inconsistent relationship between Pacific and Atlantic Nifngos. J Clim 25(12):4294-4303. doi:10.1175/JCLI-D-11-00553. · DOI
  22. Lübbecke JF, McPhaden MJ (2013) A comparative stability analysis of Atlantic and Paciffic Niño modes. J Clim 26(16):5965-5980. doi: 10.1175/JCLI-D-12-00758. · DOI
  23. Lübbecke JF, McPhaden MJ (2017) Symmetry of the Atlantic Niño mode. Geophys Res Lett 44(2):965-973. doi:10.1002/201 · DOI
  24. 6GL071829 · DOI
  25. Lübbecke JF Burls NJ, Reason CJC, McPhaden MJ (2014) Variability in the South Atlantic Anticyclone and the Atlantic Nifñgo Mode. J Clim 27(21):8135-8150. doi:10.1175/JCLI-D-14-00202. · DOI
  26. Madec G, Delecluse P, Imbard M, Levy C (1998) OPA 8.1 general circulation model reference manual. Tech. rep. Paris: Institut Pierre-Simon Laplace Madec G (2008) NEMO ocean general circulation model reference mannuel. Tech. rep. Paris: Institut Pierre-Simon Laplace Marin F, Caniaux G, Giordani H, Bourlès B, Gouriou Y, Erica K (2009) Why were sea surface temperatures so different in the east- ern equatorial Atlantic in June 2005 and 2006? J Phys Oceanogr 39(6):1416-1431. doi:10.1175/2008JPO4030. · DOI · Paper page
  27. Mohino E, Losada T (2015) Impacts of the Atlantic equatorial mode in a warmer climate. Clim Dyn 45(7-8):2255-2271. doi:10.1007/ s00382-015-2471-y (English) · DOI
  28. Neelin JD, Battisti DS, Hirst AC, Jin F-F, Wakata Y, Yamagata T, Zebiak SE (1998) ENSO theory. J Geophys Res 103(C7):14261. doi:10.1029/97JC03424 · DOI
  29. Nnamchi HC, Li J, Kucharski F, Kang IS, Keenlyside NS, Chang P, Farneti R (2015) Thermodynamic controls of the Atlantic Niño. Nat Commun 6:8895. doi:10.1038/ncomms9895 · DOI
  30. Nnamchi HC, Li J, Kucharski F, Kang I-S, Keenlyside NS, Chang P, Farneti R (2016) An equatorial-extratropical dipole structure of the Atlantic Niño. J Clim 29(20):7295-7311. doi:10.1175/ JCLI-D-15-0894. · DOI
  31. Okumura Y, Xie SP (2006) Some overlooked features of tropical Atlantic climate leading to a new Nino-like phenomenon. J Clim 19(22):5859-5874
  32. Park W, Keenlyside N, Latif M, Ströh A, Redler R, Roeckner E, Madec G (2009) Tropical Paciffic climate and its response to globalwarm- ing in the Kiel climate model. J Clim 22(1):71-92. doi:10.1175 /2008JCLI2261.1 · DOI
  33. Rayner NA, Parker D, Horton E, Folland C, Alexander L, Rowell D, Kent E, Kaplan A (2003) Global analyses of sea surface tem- perature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108(D14):4407. doi:10.1029 /2002JD002670 · DOI
  34. Richter I, Behera SK, Masumoto Y, Taguchi B, Sasaki H, Yamagata T (2013) Multiple causes of interannual sea surface temperature variability in the equatorial Atlantic Ocean. Nat Geosci 6(1):43- 47. doi:10.1038/ngeo1660 · DOI
  35. Richter I, Xie SP, Behera SK, Doi T, Masumoto Y (2014a) Equatorial Atlantic variability and its relation to mean state biases in CMIP5. Clim Dyn 42(1-2):171-188. doi:10.1007/s00382-012-1624-5 · DOI
  36. Richter I, Behera SK, Doi T, Taguchi B, Masumoto Y, Xie SP (2014b) What controls equatorial Atlantic winds in boreal spring? Clim Dyn 43(11):3091-3104. doi:10.1007/s00382-014-2170-0 · DOI
  37. Richter I, Xie SP, Morioka Y, Doi T, Taguchi B, Behera S (2016) Phase locking of equatorial Atlantic variability through the seasonal migration of the ITCZ. Clim Dyn 1-15. doi:10.1007/ s00382-016-3289-y · DOI
  38. Roeckner E, Bäuml G, Bonaventura L, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kirchner I, Kornblueh L, Rhodin A, Schlese U, Schulzweida U, Tompkins A (2003) The atmospheric general circulation model ECHAM5: Part 1: Model description. MPI Rep 349:1-140. doi:10.1029/2010JD014036 · DOI
  39. Stockdale TN, Balmaseda MA, Vidard A (2006) Tropical Atlantic SST prediction with coupled Ocean-Atmosphere GCMs. J Clim 19(23):6047-6061. doi:10.1175/JCLI3947. · DOI · Paper page
  40. Thoma M, Greatbatch RJ, Kadow C, Gerdes R (2015) Decadal hind- casts initialized using observed surface wind stress: evaluation and prediction out to 2024. Geophys Res Lett. doi:10.1002/201 · DOI
  41. 5GL064833 · DOI
  42. Wang C, Zhang L, Lee S, Wu L, Mechoso CR (2014) A global perspec- tive on CMIP5 climate model biases. Nat Clim Change 4:201- 205. doi:10.1038/NCLIMATE2118 · DOI
  43. Xie SP, Carton JA (2004) Tropical Atlantic variability: patterns, mech- anisms, and impacts. Earth's Clim. American Geophysical Union 121-142. doi:10.1029/147GM07 Zebiak SE (1993) Air-sea interaction in the equato- r i a l At l a n t i c r e g i o n . J C l i m 6 ( 8 ) : 1 5 6 7 -1 5 8 6 . doi:10.1175/1520-0442(1993)006<1567:AIITEA>2.0.CO;2 · DOI · Paper page
  44. Zhu J, Huang B, Wu Z (2012) The role of ocean dynamics in the inter- action between the Atlantic meridional and equatorial modes. J Clim 25(10):3583-3598. doi:10.1175/JCLI-D-11-00364. · DOI

Cited by

Sorted by citations

Authors
Dippe, T., Greatbatch, R. J., & Ding, H.
Affiliations
  • GEOMAR Helmholtz Centre for Ocean Research Kiel (DE)
  • Christian-Albrechts-Universität zu Kiel (DE)
  • Cooperative Institute for Research in Environmental Sciences (US)
Corresponding author
Dippe, Tina
Venue
Climate Dynamics
Published
2017-10-28
Volume
51
Issue
1-2
Pages
597-612
ISSN
  • 0930-7575 (ISSN-L)
  • 1432-0894
OpenAlex
W2766729498
Cited by
56
References
3
Citations by year
2026: 2 · 2025: 2 · 2024: 7 · 2023: 4 · 2022: 4 · 2021: 5 · 2020: 17 · 2019: 10 · 2018: 5
FWCI
6.07
Type
journal article
Language
en
Open access
Locations
  • Climate Dynamics (publishedVersion, cc-by)
  • Helmholtz Centre for Ocean Research Kiel (GEOMAR) (acceptedVersion, other-oa)
  • NOAA Institutional Repository (submittedVersion)
  • EGUGA
Funders
  • German Ministry for Education and Research (01LP1517D, 03G0837A)
  • European Union 7th Framework Programme (603521)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
Keywords
Atlantic Niño, sea surface temperature variability, Bjerknes feedback, SST bias, equatorial Atlantic, cold tongue, sea surface height, ocean-atmosphere feedback, seasonal cycle

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review