SUPPLEMENTARY INFORMATION

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1 SUPPLEMENTARY INFORMATION Weakening of the equatorial Atlantic cold tongue over the past six decades Hiroki Tokinaga and Shang-Ping Xie International Pacific Research Center and Department of Meteorology, SOEST, University of Hawaii at Manoa Supplementary Notes 1. Warm tongue-like trend in observational datasets The weakening of the equatorial Atlantic cold tongue is examined using four widelyused SST products (Supplementary Fig. 1) including ERSST version 3b (Smith, et al. 2008), HadSST2 (Rayner, et al. 2006), Kaplan Extended SST version 2 (Kaplan, et al. 1998), and HadISST1 (Rayner, et al. 2003), and nighttime marine-air temperature (NMAT) archived in ICOADS (Supplementary Fig. 2a). The in-situ based ERSST, HadSST, and NMAT clearly exhibit a warm tongue-like trend pattern in the eastern equatorial Atlantic. The upward net surface flux trend also represents a tongue-like pattern acting to cool the ocean due to the evaporative damping of increased SST and a decrease in solar radiation (Supplementary Fig. 2b). On the other hand, HadISST shows an equatorial minimum in SST warming with much weaker SST trends than ERSST and HadSST (Note that color scales are different). Kaplan SST has not only a similar warm tongue-like trend pattern but also a warming maximum over the tropical North Atlantic as in HadISST. It is unclear why HadISST shows the equatorial minimum in SST warming, but a similar warming minimum can be found over the equatorial Pacific cold tongue (Deser, et al. 2010). Both HadISST and Kaplan SST merge highresolution satellite SST measurements for 1980s onward, which may be a possible cause for the disagreement with in-situ based SST and NMAT datasets. The weakening of SST annual cycle is also found in ERSST, HadSST, Kaplan SST, and NMAT, all of which successfully capture the warm tongue-like trend (not shown). This agreement between various SST products and independent NMAT measurements strongly supports the recent weakening of the equatorial Atlantic cold tongue revealed by the present study. 2. Ocean GCM hindcast nature geoscience 1

2 supplementary information To identify physical mechanisms for the weakening of the equatorial Atlantic cold tongue, we perform an ocean GCM experiment forced by our bias-corrected surface wind product (Tokinaga and Xie 2010) featuring the long-term relaxation of the equatorial trade winds. The ocean GCM used in this study is based on the Modular Ocean Model version 3 (Pacanowski and Griffies 2000). Details of the model settings are as follows: Resolution is 2.5 degrees in horizontal and 25 levels in vertical. Near the equator the meridional grid spacing is smoothly changed to 0.5 degrees to resolve equatorial waves. The model covers a near-global domains from 65 S to 65 N. This ocean GCM with similar settings successfully reproduces intraseasonal to interannual variabilities of dynamical and thermodynamical features in the tropical Indian-Pacific oceans (Ogata 2009). The model is first forced by climatological wind stresses for 28 years, and then driven by the monthly mean wind stresses from 1950 to SST is restored to the monthly mean observed value (ERSST) with a 30-day timescale. Surface salinity is also restored with the 30-day timescale to the observed monthly climatology. Sponge layers are applied poleward of 62 N/S. The ocean GCM hindcast successfully reproduces the climatological cold tongue, its weakening for the past six decades, and a local maximum in the interannual standard deviation of ocean mixed layer temperature (T M ) in the eastern equatorial Atlantic (Supplementary Fig. 3). To quantify the dynamical and thermodynamical effects on the weakening of the equatorial cold tongue, the mixed layer heat budget is estimated from the following equation (Niiler 1975): " T M " t = Q #C p H M $ U%&T M $ w ent (T M $ T ent ) H M + R,!!! (1) where Q is the net surface heat flux (positive into the ocean), H M is the mixed layer depth,! is the seawater density, C p is the heat capacity of the seawater, U is the horizontal velocity vector, w ent is the vertical entrainment rate, T ent is the water temperature below the base of the mixed layer, and R is the residual term including horizontal and vertical diffusion. The first and second terms on the right-hand side denote surface heat flux and horizontal heat advection, respectively. The third term represents vertical entrainment, a process containing 2 nature geoscience

3 supplementary information thermocline feedback effect. The vertical entrainment rate, w ent, can be determined as follows (Williams 1989): w ent = " H M " t + w M + U# $H M, (2) where w M is the vertical velocity at the base of the mixed layer, and U!H M is the horizontal advection. If w ent is negative, we assume w ent = 0. Supplementary Figure 4 compares 60-year trends in each term of Eq. (1) averaged during the developing phase of the observed warm tongue-like trend pattern (March July). The tongue-like trend in the temperature tendency can be mostly explained by the reduced vertical entrainment especially in the eastern equatorial Atlantic. The horizontal heat advection also shows a significant warming effect broadly in the tropical Atlantic but does not have a tongue-like structure. Consistent with the observations, the net surface heat flux acts to cool the ocean as a damping effect. These results support that the reduced thermocline feedback is a major cause for the weakening of the equatorial Atlantic cold tongue. To estimate how much of the reduced Atlantic Niño variability can be explained by each term of Eq. (1), we perform a composite analysis for Atlantic Niño events in two twenty-year periods ( and ). We define a warm (cold) Atlantic Niño event as when the June-August SST anomaly averaged in 5ºW 5ºE, 1ºS 1ºN is above 0.8 (below -0.8) sigma. The region is slightly east of the ATL3 region but corresponds to a local maximum in the simulated interannual standard deviation of T M (Supplementary Fig. 3b). For each twenty-year period, the Atlantic Niño composite includes a total of ten events (five warm and five cold events). We then calculate the epoch difference between the recent and earlier twenty-year periods. Supplementary Figure 5 shows the seasonal development of the epoch difference in each term of Eq. (1) averaged in 5ºW 5ºE, 1ºS 1ºN. The difference in T M tendency exhibits negative (positive) values during the developing (decay) phase of the Atlantic Niño with a significant peak of 0.4 ºC/month (+0.35 ºC/month) in May (August), indicative of the reduced seasonal development of Atlantic Niño events in the recent twentyyear period. The epoch difference in the vertical entrainment term shows a similar seasonal variation to the T M tendency with a large negative peak in May, twice the T M tendency difference. The other terms do not show such seasonality and are smaller. Therefore, the nature geoscience 3

4 supplementary information reduced amplitude of the Atlantic Niño can be mostly explained by the change in the vertical entrainment term, supporting that reduced thermocline feedback suppresses interannual Atlantic Niño variability in the recent twenty-year period. 3. Seasonal development of trends in marine cloud cover and land precipitation Trends in marine cloud cover and land precipitation have a quite similar seasonal development over the equatorial Atlantic and coastal West Africa (Supplementary Fig. 6). In May-June, marine cloud cover and land precipitation shows significant negative trends along the Guinea coast. An equatorial zonal band of increased marine cloud cover starts to develop in June, with significant positive trends over eastern equatorial Atlantic and significant positive land precipitation trends over equatorial West Africa. As the zonal band of increased marine cloud cover expands northward and southward in August, positive land precipitation trends become significant on the Guinea coast. In September, the significant positive trends in marine cloud cover and land precipitation both shrink. On the other hand, a zonal band of significant negative trends in marine cloud cover and land precipitation appears over the Sahel and tropical North Atlantic in July, and concurrently migrates southward from August to September. Given the climatological location of the intertropical convergence zone (ITCZ) around 5º 10ºN in August, these cloud/precipitation trends indicate a slight southward shift of the climatological ITCZ. 4. AMO influence on the equatorial Atlantic The Atlantic multidecadal oscillation (AMO) (Enfield, et al. 2001) is one of the dominant basin-wide modes in the Atlantic, characterized by an oscillation of warm and cold SST anomalies in the North Atlantic due to multidecadal changes in the thermohaline circulation. While recent studies suggest strong AMO influences on climate anomalies in the surrounding regions as well as over the North Atlantic, its relationship with the Atlantic Niño has still been unknown. The historical SST measurements along the major ship tracks indicate that AMO is strongly correlated with the SST anomaly in the western equatorial Atlantic (SSTA WEA ; r = 0.81), but weakly correlated with that in the eastern equatorial Atlantic (SSTA EEA ; r = 0.33) (Supplementary Fig. 7 and Supplementary Table 1). The weak correlation with SSTA EEA is probably due to a stronger thermocline feedback in the eastern 4 nature geoscience

5 supplementary information equatorial Atlantic. The!SST EQ time series, an index defined as SSTA EEA SSTA WEA, still has an upward trend even if the AMO signal is removed from both SSTA EEA and SSTA WEA by linear regression. This result implies another mechanism involved in the weakening of the equatorial Atlantic cold tongue over the last century. 5. Weakening of the zonal and meridional gradients of the tropical Atlantic SST in CMIP3 models. To examine the projected climate change over the tropical Atlantic, we analyzed the CMIP3 Climate of the 20th century experiments (20c3m) from 19 coupled GCMs forced with greenhouse gasses (GHGs) and sulfate aerosol effects. The 19 coupled GCMs include CNRM-CM3, CSIRO-MK3.0, CGCM3.1(T47), CGCM3.1(T63), GFDL-CM2.0, GFDL- CM2.1, GISS-AOGCM, GISS-EH, GISS-ER, FGOALS-g1.0, INM-CM3.0, IPSL-CM4, MIROC3.2-hires, MIROC3.2-medres, MIUB/ECHO-G, MPI/ECHAM5, MRI-CGCM2.3.2, UKMO-HadCM3, and UKMO-HadGEM1. Supplementary Figure 8 compares centennial trends in the equatorial zonal SST gradient (!xsst), meridional SST gradient across the tropical Atlantic (!ysst), and equatorial zonal (U EQ ) and meridional (V EQ ) surface winds for June August season.!xsst (!ysst) is defined as the zonal (meridional) difference in SST anomaly averaged over 20ºW 0º, 3ºS 3ºN (70º 15ºW, 0º 20ºN) and 25º 45ºW, 3ºS 3ºN (35ºW 15ºE, 0º 20ºS), while U EQ and V EQ anomalies are averaged over 30ºW 0º, 5ºS 5ºN. Observed SST shows a 0.57 ± 0.3ºC increase in!xsst and a 0.38 ± 0.28ºC decrease in!ysst over the last century, representing significant weakenings of the zonal and meridional SST gradient. Supporting the observed SST changes, CMIP3 models tend to have a positive (negative) trend in!xsst (!ysst) (Supplementary Fig. 8a) and capture the reduced annual cycle in the eastern equatorial Atlantic (Supplementary Fig. 9), although their magnitudes tend to be much weaker than the observed. This is probably because CMIP3 models fail to reproduce the climatological equatorial cold tongue (Richter and Xie 2008). The projected trend in!xsst negatively correlates with that in!ysst among CMIP3 models, with a significant correlation of 0.7 at 99% confidence level (Supplementary Fig. 8a). Interestingly, the weakenings of both zonal and meridional SST gradients are related to a weakened cross-equatorial southeasterly trade winds in CMIP3 models (Supplementary Figs. 8b-e), with significant nature geoscience 5

6 supplementary information correlations of 0.8 ( 0.57) between!xsst and U EQ (V EQ ) trends, and 0.9 ( 0.59) between!ysst and V EQ (U EQ ) trends. These correlations indicate a strong connection between the basin-wide zonal and meridional SST gradients through the relaxed cross-equatorial southeasterly trade winds. Such association between!ysst and V EQ is seen in the observed meridional mode of interannual variability (Chang, et al. 1997; Nobre and Shukla 1996). The connection between!xsst and V EQ is observed in the annual cycle (Mitchell and Wallace 1992) and interannual variability (Chiang, et al. 2001). While AMO may cause!ysst and V EQ to change, Supplementary Figure 7 shows that it is not correlated with!xsst. 6. Projected future trend patterns under the GHG emission scenario A1B Supplementary Figure 10 shows future trend patterns under the GHG emission scenario A1B predicted by a multi-model ensemble from 20 CMIP3 models (BCCR- BCM2.0, CNRM-CM3, CSIRO-MK3.5, CGCM3.1(T47), CGCM3.1(T63), GFDL-CM2.0, GFDL-CM2.1, GISS-AOGCM, GISS-EH, GISS-ER, FGOALS-g1.0, INM-CM3.0, IPSL- CM4, MIROC3.2-hires, MIROC3.2-medres, MIUB/ECHO-G, MPI/ECHAM5, MRI- CGCM2.3.2, UKMO-HadCM3, and UKMO-HadGEM1). Compared with the 20c3m experiments, the SST warming pattern is much broader in the tropical Atlantic, with local maxima at the equator and 10ºN. While the interhemispheric SST gradient is weakened in 20c3m experiments, it shows no obvious change or slightly strengthens in A1B experiments. As a result, neither the southward shift of ITCZ nor the relaxation of cross-equatorial southeasterly trades is found, although surface westerly trends are dominant over the whole domain. These differences between A1B and 20c3m experiments suggest that other climate forcing, rather than anthropogenic GHG, has forced the observed trend pattern for recent decades. 6 nature geoscience

7 supplementary information References used in Supplementary Information Chang, P., Ji, L. & Li, H. A decadal climate variation in the tropical Atlantic Ocean from thermodynamic air-sea interactions. Nature 385, , (1997). Chiang, J. C., Zebiak, S. E. & Cane, M. A. Relative roles of elevated heating and surface temperature gradients in driving anomalous surface winds over tropical oceans. J. Atmos. Sci. 58, , (2001). Clark, N. E., Eber, L., Laurs, R. M., Renner, J. A. & Saur, F. T. Heat exchange between ocean and atmosphere in the eastern North Pacific for NOAA Tech. Rep. NMFS SSRF-682, U.S. Dept. of Commerce, 108pp (1974). Deser, C., Phillips, A. & Alexander, M. A. Twentieth century tropical sea surface temperature trends revisited. Geophys. Res. Lett. 37, L10701, (2010). Enfield, D. B., Mestas-Nunez, A. M. & Trimble, P. J. The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental US. Geophys. Res. Lett. 28, , (2001). Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A. & Edson, J. B. Bulk parameterization of air-sea fluxes: Updates and verification for the COARE algorithm. J. Clim. 16, , (2003). Kaplan, A. et al. Analyses of global sea surface temperature J. Geophys. Res. 103, , (1998). Kendall, M. G. Rank Correlation Methods. 202 pp. (Griffin, 1975). Mitchell, T. P. & Wallace, J. M. The annual cycle in equatorial convection and sea surface temperature. J. Clim. 5, , (1992). Niiler, P. P. Deepening of the wind-mixed layer. J. Mar. Res. 33, , (1975). Nobre, P. & Shukla, J. Variations of sea surface temperature, wind stress, and rainfall over the tropical Atlantic and South America. J. Clim. 9, 64-79, (1996). Ogata, T. Interannual modulation of intraseasonal upper-ocean vriability in the Indo-Pacific warm water region. Ph. D. dissertation, 127pp (University of Tokyo, 2009). Pacanowski, R. C. & Griffies, S. M. MOM 3.0 manual. 680 pp (Geophysical Fluid Dynamics Laboratory/National Oceanic and Atmospheric Administration, 2000). Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407, (2003). nature geoscience 7

8 supplementary information Rayner, N. A. et al. Improved analyses of changes and uncertainties in sea surface temperature measured in situ sice the mid-nineteenth century: The HadSST2 dataset. J. Clim. 19, , (2006). Reed, R. K. On estimating insolation over the ocean. J. Phys. Oceanogr. 7, , (1977). Richter, I. & Xie, S.-P. On the origin of equatorial Atlantic biases in coupled general circulation models. Clim. Dyn. 31, , (2008). Sen, P. K. Estimates of the regression coefficient based on Kendall s tau. J. Amer. Stat. Assoc. 63, (1968). Smith, T. M., Reynolds, R. W., Peterson, T. C. & Lawrimore, J. Improvements to NOAA's historical merged land-ocean surface temperature analysis ( ). J. Clim. 21, , (2008). Tokinaga, H. & Xie, S.-P. Wave- and Anemometer-based Sea-surface Wind (WASWind) for climate change analysis. J. Clim.,, 7-285, doi: /2010JCLI3789.1, (2011). Williams, R. G. The influence of air-sea interaction on the ventilated thermocline. J. Phys. Oceanogr. 19, , (1989). 8 nature geoscience

9 supplementary information Supplementary Table 1. Correlation between the detrended SST time series for Significance for each correlation is tested by the two-tailed student-t test assuming that a degree of freedom is 5. Significant correlations are emboldened, and the numbers in parentheses indicate p-value for the student-t tests. AMO SSTA WEA SSTA EEA SSTA WEA EEA AMO 0.81 (5) SSTA WEA SSTA EEA 0.74 (0.1) SSTA WEA EEA! nature geoscience 9

10 supplementary information a ERSST b HadSST c 4W 2W 2E o C/60yr Kaplan SST d 4W 2W 2E o C/60yr HadISST 4W 2W 2E o C/60yr W 2W 2E o C/60yr Supplementary Figure 1. Trends in June-August mean SST for from (a) ERSST version 3b, (b) HadSST2, (c) Kaplan Extended SST version 2, and (d) HadISST1. Superimposed is the June-August mean climatology of each SST product (contours at 1ºC interval). Because Kaplan SST provides only anomaly data, the HadSST2 climatology is superimposed on the Kaplan SST trend. All trends are estimated based on the Sen median slope method. SST trends exceed 95% confidence level in most regions. 10 nature geoscience

11 a supplementary information b 4W 2W 2E 4W 2W 2E NMAT trend ( o C/60yr) Upward Q net trend (Wm -2 /60yr) Supplementary Figure 2. Trends in June-August nighttime marine-air temperature (NMAT) (a) and upward net surface heat flux (b) for NMAT is obtained from ICOADS. The upward trends of net surface heat flux, the sum of surface latent and sensible heat fluxes and shortwave and longwave radiations, are shown by positive values. Surface latent and sensible heat fluxes are calculated from bulk formulae depending on atmospheric stability (Fairall, et al. 2003), using the ICOADS SST, surface air temperature, specific humidity, and the WASWind surface wind speed. The net shortwave and longwave radiations are estimated from bulk formulae by Reed (1977) and Clark (1974), respectively, using the ICOADS cloud cover. All trends are estimated based on the Sen median slope method (Sen 1968). Grids marked with closed circles (open triangles) exceed 95% (90%) confidence level based on the Mann-Kendall test (Kendall 1975). nature geoscience 11

12 supplementary information a b W 2W 4W 2W T M trend ( o C/60yr) T M SD ( o C) Supplementary Figure 3. (a) Trend and (b) interannual standard deviation of June- August mixed layer temperature (T M ) anomaly for obtained from the ocean GCM hindcast. The trend is estimated based on the Sen median slope method (Sen 1968). Grids marked with closed circles indicate significant trends exceeding 95% confidence level based on the Mann-Kendall test (Kendall 1975). Superimposed on each panel is the June- August climatology of T M at 1ºC contour intervals. 12 nature geoscience

13 supplementary information a T M tendency 4W 2W o C mon -1 /60yr b Horizontal heat advection c Vertical entrainment 4W 2W 4W 2W d Net surface heat flux e Residual 4W 2W 4W 2W o C mon -1 /60yr Supplementary Figure 4. March-July trends in (a) T M tendency, (b) horizonal heat advection, (c) vertical entrainment, (d) net surface heat flux, and (e) residual in the heat budget equation. Each term is obtained from the ocean GCM hindcast for All trends are estimated based on the Sen median slope method (Sen 1968). Grids marked with closed circles indicate significant trends exceeding 95% confidence level based on the Mann- Kendall test (Kendall 1975). nature geoscience 13

14 supplementary information 0.4 T M tendency Vertical entrainment Residual Horizontal heat advection Net surfae heat flux 0.2 o C/mon J F M A M J J A S O N D Calendar month Supplementary Figure 5. Composite difference in heat balance between the Atlantic Niño events in and Each term is averaged in 5ºW 5ºE, 1ºS 1ºN. Circles (triangles) indicate significant difference exceeding 95% (90%) confidence level tested by the two-tailed student-t test. The shaded period denotes the mature phase of the Atlantic Niño. 14 nature geoscience

15 supplementary information May Aug 4W 2W 2E 4W 2W Jun Sep 4W 2W 4W 2W Jul Cloud cover trend (okta/60yr) Precip. trend (mm mon -1 /59yr) 4W 2W Supplementary Figure 6. Trends in marine cloud cover and land precipitation from May to September. Trend in marine cloud cover (land precipitation) is estimated for ( ) based on the Sen median slope method (Sen 1968). For cloud cover trend, grids marked with closed circles (open triangles) exceed 95% (90%) confidence level based on the Mann-Kendall test (Kendall 1975). For precipitation trend, only grids exceeding 95% confidence level are hatched. nature geoscience 15

16 supplementary information 0.2 a AMO index b SSTA EEA (solid) & SSTA WEA (dashed) c Detrended SSTA WEA d Detrended SSTA EEA e SSTA EEA SSTA WEA ( SST EQ ) Year Supplementary Figure 7. Time series of observed SST indices for (a) The Atlantic multidecadal oscillation (AMO) index (Enfield, et al. 2001), (b) the area-averaged SST anomalies in the western equatorial Atlantic (SST WEA ; dashed) and eastern equatorial Atlantic (SST EEA ; solid), and (c), (d) their detrended time series (colour) and those with AMO s signal removed by linear regression (black line). (e) The AMO-removed SST EEA minus SST WEA difference (!SST EQ ; black line) and its linear regression line (dashed red line). Each time series is smoothed with 121-month running average. 16 nature geoscience

17 supplementary information 0.3 b y SST trend ( o C/century) 0.3 a corr. = x SST trend ( o C/century) 0.3 c ERSST(obs) Ensemble mean CNRM-CM3 CSIRO-MK3.0 ECHO-G ECHAM5/MPI-OM CGCM3.1-T63 CGCM3.1 GISS-AOGCM GISS-ER GISS-EH FGOALS-g1.0 GFDL-CM2.0 GFDL-CM2.1 MIROC3.2-hires MIROC3.2-medres UKMO-HadGEM1 UKMO-HadCM3 INM-CM3.0 IPSL-CM4 MRI-CGCM2.3.2 y SST trend ( o C/century) corr. = corr. = d e x SST trend ( o C/century) corr. = corr. = V EQ trend (ms -1 /century) U EQ trend (ms -1 /century) Supplementary Figure 8. Scatter plots for each pair of SST and surface wind trends in 19 coupled GCM simulations for the Climate of the 20th Century experiment of CMIP3. (a) Equatorial zonal SST gradient (!xsst) vs the interhemispheric SST gradient (!ysst), (b) equatorial meridional wind (V EQ ) vs!ysst, (c) equatorial zonal wind (U EQ ) vs!ysst, (d) V EQ vs!xsst, and (e) U EQ vs!xsst. Trends are calculated for June-August anomalies from 1900 to 1999, using the Sen median slope method. Error bars for each trend indicate 95% confidence interval. The correlation coefficients for each pair are shown at the right bottom corner. Dashed lines in (b)-(c) and (d)-(e) indicate observed trends in!xsst and!ysst, respectively. All correlations are significant at 99% confidence level with the two-tailed student-t test. nature geoscience 17

18 supplementary information Calendar month D N O S A J J M A M F J 4W 3W 2W 1W 1E SST trend ( o C/100yr) Supplementary Figure 9. Longitude-month section of the climatology and trend in equatorial SST of the multi-model ensemble mean. 19 coupled GCM simulations for the Climate of the 20th Century experiment of CMIP3 are used for the multi-model ensemble mean. The SST trend is estimated for based on the Sen median slope method (Sen 1968). For the trend, grids marked with closed circles exceed 95% confidence level based on the Mann-Kendall test (Kendall 1975) nature geoscience

19 2N a supplementary information 2N b 1N 1N 1S 1S 2S 2S 6W 4W 2W 2E 6W 4W 2W 2E SST trend ( o C/century) Precip. trend (mm mon -1 /century) 0.4 ms -1 /century Supplementary Figure 10. Predicted trend patterns for under the GHG emission scenario A1B. (a) SST (colour; ºC century -1, and (b) surface wind (vectors; m s -1 century -1 ) and precipitation (colour; mm mon -1 century -1 ). The A1B experiments from 20 CMIP3 models are used. All trends are calculated from June August anomalies of the 20- model ensemble mean. nature geoscience 19