Advertisement

Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Northern hemisphere atmospheric response to changes of atlantic ocean SST on decadal time scales: a GCM experiment

  • 74 Accesses

  • 13 Citations

Abstract

Analyses indicate that the Atlantic Ocean seasurface temperature (SST) was considerably colder at the beginning than in the middle of the century. In parallel, a systematic change in the North Atlantic sea-level pressure (SLP) pattern was observed. To find out whether the SST and SLP changes analyzed are consistent, which would indicate that the SST change was real and not an instrumental artifact, a response experiment with a low-resolution (T21) atmospheric GCM was performed. Two perpetual January simulations were conducted, which differ solely in the Atlantic Ocean (40° S-60° N) SST: the “cold” simulation utilizes the SSTs for the period 1904–1913; the “warm” simulation uses the SSTs for the period 1951–1960. Also, a “control” run with the model's standard SST somewhat between the “cold” and “warm” SST was made. For the response analysis, a rigorous statistical approach was taken. First, the null hypothesis of identical horizontal distributions was subjected to a multivariate significance test. Second, the level of recurrence was estimated. The multivariate statistical approaches are based on hierarchies of test models. We examined three different hierarchies: a scale-dependent hierarchy based on spherical harmonics (S), and two physically motivated ones, one based on the barotropic normal modes of the mean 300 hPa flow (B) and one based on the eigenmodes of the advection diffusion operator at 1000 hPa (A). The intercomparison of the “cold” and “warm” experiments indicates a signal in the geostrophic stream function that in the S-hierarchy is significantly nonzero and highly recurrent. In the A-hierarchy, the low level temperature field is identified as being significantly and recurrently affected by the altered SST distribution. The SLP signal is reasonably similar to the SLP change observed. Unexpectedly, the upper level stream-function signal does not appear to be significantly nonzero in the B-hierarchy. If, however, the pairs of experiments “warm versus control” and “cold versus control” are examined in the B-hierarchy, a highly significant and recurrent signal emerges. We conclude that the “cold versus warm” response is not a “small disturbance” that would allow the signal to be described by eigenmodes of the linear system. An analysis of the three-dimensional structure of the signal leads to the hypothesis that two different mechanisms are acting to modify the model's mean state. At low levels, local heating and advection are dominant, but at upper levels the extratropical signal is a remote responce to modifications of the tropical convection.

This is a preview of subscription content, log in to check access.

References

  1. Alexander RC, Mobley RL (1976) Monthly average sea-surface temperatures and ice-pack limits on a 1° global grid. Mon Weather Rev 104:143–148

  2. Barnett TP, Preisendorfer RW, Goldstein LM, Hasselmann K (1981) Significance tests for regression model hierarchies. J Phys Oceanogr 11:1150–1154

  3. Barnett TP, Heinz HD, Hasselmann K (1984) Statistical prediction of seasonal air temperatures over Eurasia. Tellus 36A:132–146

  4. Branstator G (1985a) Analysis of general circulation model sea-surface temperature anomaly simulations using a linear model. Part I. Forced solutions. J Atmos Sci 42:2225–2241

  5. Branstator G (1985b) Analysis of general circulation model seasurface temperature anomaly simulations using a linear model. Part II. Eigenanalysis. J Atmos Sci 42:2242–2254

  6. Chervin RM, Kutzbach JE, Houghton DD, Gallimore RG (1989) Response of the NCAR general circulation model to prescribed changes in ocean surface temperature. Part II. Midlatitude and subtropical changes. J Atmos Sci 37:308–322

  7. Egger J (1977) On the linear theory of the atmospheric response to sea surface temperature anomalies. J Atmos Sci 34:603–614

  8. Fischer G (ed) (1987) Climate simulations with the ECMWF T21 Model in Hamburg. Meteorologisches Institut der Unversität Hamburg. Large Scale Atmospheric Modelling Report 1

  9. Folland CK, Palmer TN, Parker DE (1986) Sahel rainfall and worldwide sea temperatures 1901–85. Nature 320:602–607

  10. Frankignoul C, Molin A (1988a) Response of the GISS general circulation model to a midlatitude sea surface temperature anomaly in the North Pacific. J Atmos Sci 45:95–108

  11. Frankignoul C, Molin A (1988b) Analysis of the GISS GCM response to a subtropical sea surface temperature anomaly using a linear model. J Atmos Sci 45:3833–3845

  12. Glowienka R (1985) Studies on the variability of Icelandic low and Azores high between 1881 and 1982. Beitr Phys Atmos 58:160–170

  13. Glowienka-Hense R (1988) Performance of the ECMWF T21 model in simulating the North Atlantic oscillation (NAO). Climate simulations with the ECMWF T21-model in Hamburg, Part II. In: Storch H von (ed) Meteorologisches Institut der Universität Hamburg Large Scale Atmospheric Modelling Report 4:35–51

  14. HannoschÖck G, Frankignoul C (1985) Multivariate statistical analysis of a sea surface temperature anomaly experiment with the GISS general circulation model. J Atmos Sci 42:1430–1450

  15. Hasselmann K (1979) On the signal- to-noise problem in atmospheric response studies. Meteorology over the tropical oceans. R Met Soc London, pp 251–259

  16. Held I, Kang I-S (1987) Barotropic models of the extratropical response to El Niño. J Atmos Sci 44:1433–1452

  17. Hense A (1986) Multivariate statistical analysis of the Northern Hemisphere circulation during the El Niño 1982/83. Tellus 38A:189–204

  18. Höflich W (1974) The seasonal and secular variations of the meteorological parameters on both sides of the ITCZ in the Atlantic ocean. GARP Report 2

  19. Jones PD, Raper SCB, Sauter BS, Cherry BSG, Goodess C, Bradley RS, Diaz HF, Kelly PM, Wigley TML (1985) A gridpoint surface air temperature data set for the Northern Hemisphere, 1851–1984. -DoE technical Report No. 22 US Department of Energy Carbon Dioxide Research Division, Washington DC, 251 pp

  20. Lautenschlager M, Schlese U, Ponater M, Mai W, Ulbrich U, Speth P (1988) Atmospheric response to Ice Age January conditions. Climate Simulations with the ECMWF T21-model in Hamburg, Part 11, H v Storch (ed) Meteorologisches Institut der Universität Hamburg Large Scale Atmospheric Modelling Report 4:191–230

  21. Loon van H, Rogers J (1978) The seesaw in winter temperature between Greenland and northern Europe. Part I: General description. Mon Weather Rev 106:296–310

  22. Loon van H, Madden RA (1983) Interannual variations of monthly mean sea-level pressure in January. J Climate Appl Met 22:687–692

  23. Navarra A, Miyakoda K (1988) Anomaly general circulation models. J Atmos Sci 45:1509–1530

  24. Okamoto M (1963) An asymptotic expansion for the distribution of the linear discriminant function. Ann Math Stat 34:1286–1301

  25. Page JT (1985) Error rate estimation in discriminant analysis. Technometrics 27:189–198

  26. Palmer TN, Sun Zhaobao (1985) A modelling and observational study of the relationship between sea surface temperature in the north-west Atlantic and the atmospheric general circulation. Quart J R Met Soc 111:947–975

  27. Pitcher EJ, Blackmon ML, Bates GT, Munoz S (1988) The effect of North Pacific sea surface temperature anomalies on the January climate of a general circulation model. J Atmos Sci 45:173–188

  28. Rogers JC (1985) Atmospheric circulation changes associated with the warming over the northern North Atlantic in the 1920s. J Climate Appl Met 24:1303–1310

  29. Rowntree, PR (1979) The effects of changes in ocean temperatures on the atmosphere. Dyn Atmosph Oceans 3:373–390

  30. Sardeshmukh P, Hoskins BJ (1988) The generation of global rotational flow by steady idealized tropical divergence. J Atmos Sci 45:1228–1252

  31. Schneider EK (1988) A formulation for diagnostic anomaly models. Pageoph 126:137–140

  32. Simmons AJ, Wallace JM, Branstator G (1983) Barotropic wavepropagation and instability, and atmospheric teleconnection patterns. J Atmos Sci 40:1363–1392

  33. Storch H von, Kruse H (1985) The extratropical atmospheric response to El Niño events. Tellus 37a:361–377

  34. Storch H von (1987) A statistical comparison with observations of control and El Niño simulations using the NCAR CCM. Beitr Phys Atmosph 60:464–477

  35. Storch H von, Zwiers F (1988) Recurrence analysis of Climate sensitivity experiments. J Climat 1:157–171

  36. Storch H von (ed) (1988) Climate simulations with the ECMWF T21-Model in Hamburg Part II: Climatology and sensitivity experiments. Meteorologisches Institut der Universität Hamburg Large Scale Atmospheric Modelling Report 4:265 pp

  37. Webster PJ (1981) Mechanism determining the atmospheric response to sea surface temperature anomalies. J Atmos Sci 38:554–571

  38. Zwiers F, Boer GJ (1987) A comparison of climates simulated by a general circulation model when run in the annual cycle and perpetual modes. Mon Wea Rev 115:2626–2644

  39. Zwiers F, Storch H von (1989) Multivariate Recurrence Analysis. J Climat 2:1538–1553

Download references

Author information

Correspondence to Andreas Hense.

Additional information

This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. Dilmenil.

AWI Publication no. 254

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Hense, A., Glowienka-Hense, R., von Storch, H. et al. Northern hemisphere atmospheric response to changes of atlantic ocean SST on decadal time scales: a GCM experiment. Climate Dynamics 4, 157–174 (1990). https://doi.org/10.1007/BF00209519

Download citation

Keywords

  • Decadal Time Scale
  • Multivariate Statistical Approach
  • Advection Diffusion
  • Instrumental Artifact
  • Rigorous Statistical Approach