Revised and Resubmitted to Journal of Climate November 2005 Abstract




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Figure Caption


Figure 1. Retrospective forecasts of ENSO from 1857 to 2003. a) Niño 3.4 time series (red: observed; blue: predicted at lead time 6 months). b) Composite ENSO events. (From Chen et al. 2004.)


Figure 2. Comparison between ENSO (left) and epoch difference (right) patterns of SST (top) and cloudiness (bottom) anomalies during boreal winter. The ENSO patterns are based upon linear regression of the anomaly fields upon the CTI during 1947-1997, and the epoch difference maps are obtained by subtracting the period 1947-1976 from the period 1977-1997. The color bar scale for the SST (cloudiness) anomalies is given on the right-hand side of the figure in units of °C (oktas). Note that the ENSO-related anomalies are per unit standard deviation of the CTI. (From Deser et al. 2004.)


Figure 3. The period (A) and growth rate (B) of the most unstable coupled mode as a function of mean thermocline depth (H) and strength of the trade winds () (From Fedorov and Philander 2000.)


Figure 4. Schematic sketch of the hypotheses of STC-induced decadal changes in the tropical Pacific mean state by (Gu and Philander 1997) and (Kleeman et al. 1999). The Gu-Philander’s mechanism emphasizes the advection of thermal anomalies by the STCs, while Kleeman et al.’s mechanism emphasizes changes in STCs. Note the sketch shows a zonally averaged view of the STCs. In reality, much of the equatorward geostrophic transport probably occurs in the western boundary current.


Figure 5. Decadal differences in SST and winds in the tropical Pacific (From McPhaden and Zhang 2004.)


Figure 6. Leading EOFs of the low-passed SST from the coupled GCM experiments of Yeh and Kirtman (2004b). The leading EOF has a low correlation with the Niño-3.4 SSTA Variance, while EOF 2 has a high correlation. Note the similarity of the EOF1 pattern with the observed changes from McPhaden and Zhang (2004.)


Figure 7. The dominant pattern of surface ocean-atmosphere variability in the tropical Atlantic region during boreal spring (left panel) and boreal summer (right panel). The black contours depict the first EOF of the regional March-April and of June-August rainfall anomaly (from GPCP data 1979-2001) in units of mm/day. The EOFs explain 33% and 23% of the seasonal variance in the boreal spring and summer, respectively. The colored field is the March-April and June-August SST anomaly regressed on the principal component time series of the rainfall EOF (units are °C, see scale below; white contours every 0.2° are added for further clarity). Arrows depict the seasonal mean surface wind vector in m/sec, regressed on the same time series (see arrow scale below frame). (From Kushnir et al. 2004)


Figure 8. Correlation between SST, pseudostresses and the Atl-3 index, respectively. The Atl-3 index is defined as area-averaged SST anomaly over 3°S-3°N, 20°W-0°. The SST and pseudostress data derive from the analysis by Servain et al (1987), on a 2° by 2° grid for the period 1964-1988 (From Zebiak 1993).


Figure 9. Regression of zonally averaged surface wind stresses (vector), surface heat flux (contour) and SST anomalies onto Niño-3 (a) and negative NAO (b) indices as a function latitude and time lag (from the winter to the summer). The zonal average was taken between 40° and 20° W. The Niño-3 index is defined as area-averaged SST anomaly over 5°S-5°N, 90°-150°W during boreal winter (December-January-February) and the NAO index is based on the winter (December-January-February-March) sea level pressure index of Hurrell (1995). (From Czaja et al. 2002).


Figure 10. Correlation maps of a cross-equatorial wind stress index against wind stress curl and SST anomaly. (From Joyce et al. 2004)


Figure 11. Propagation of salinity compensated temperature anomalies on isopycnal  25.5, within the thermocline along the Brazilian coast and then within the equatorial undercurrent (EUC) as seen in an ocean GCM forced at the surface by NCEP-NCAR Reanalysis data (see Lazar et al. 2001).


Figure 12. Change in surface air temperature during year 20-30 after the shutdown of the thermohaline circulation in HadCM3. (From Vellinga and Wood 2002)


Figure 13. Lag-correlation between the zonal wind index from equatorial Indian Ocean in June-August, and the SST anomalies derived from GISST (Rayner et al. 2003) and heat content anomalies derived from SODA (Carton et al. 2000) in September-November. The correlation coefficients with the anomalies of SST (heat content) are shaded (contoured). b) Same as in a) but for concurrent correlation in September-November.


Figure 14. Composite of SST anomalies for a) all IOD events, b) pure IOD events, c) all ENSO events and d) pure ENSO events. Adapted from the Yamagata et al. 2004.


Figure 15. Schematic diagram of IOD (top panel) and ENSO (bottom panel) teleconnections based on the partial correlations/pure composite of Saji and Yamagata (2003b) and Yamagata et al. (2004). The orange (blue) shade indicates warm (cold) conditions during positive IOD or El Niño. Clouds (grey shade) represent rainy (dry) conditions during positive IOD or El Niño. The opposite is true during negative IOD and La Nina events.


Figure 16. Same as in Fig. 14 but for the zonal mass flux anomalies that represent anomalous Walker circulation (from Yamagata et al. 2003a).


Figure 17. Schematic triangular relation among three key regions: the eastern Indian Ocean, Eastern Europe/the Mediterranean Sea and the Far East. Warm (cold) colors denote anomalously dry (wet) conditions. See details in the text. (From Yamagata et al. 2004.)


Figure 18. Wavelet spectrum of zonal wind anomalies showing the ISO activity for six strongest IOD years. (From Rao and Yamagata 2004.)


Figure 19. TACE Observational Strategy. The proposed observing system components include (see legend): Continuation of PIRATA moorings, PIRATA extensions along 23 º W and 5-10º E, equatorial subsurface (non-realtime) moorings along 23 ºE and at 10º W, island meteorological and tide gauge stations, enhanced float/drifter coverage in the eastern TA, repeated atmospheric soundings along 23 º W, ship-of-opportunity XBT lines, and selected glider transects.


Figure 20. The evolving design of a sustained observing system for the Indian Ocean.The systems includes 3x3 Argo profiling float array, 5x5 surface drifting bouy arrays and a real time tide guage network.



Figure 1. Retrospective forecasts of ENSO from 1857 to 2003. a) Niño 3.4 time series (red: observed; blue: predicted at lead time 6 months). b) Composite ENSO events. (From Chen et al. 2004.)





Figure 2: Comparison between ENSO (left) and epoch difference (right) patterns of SST (top) and cloudiness (bottom) anomalies during boreal winter. The ENSO patterns are based upon linear regression of the anomaly fields upon the CTI during 1947-1997, and the epoch difference maps are obtained by subtracting the period 1947-1976 from the period 1977-1997. The color bar scale for the SST (cloudiness) anomalies is given on the right-hand side of the figure in units of °C (oktas). Note that the ENSO-related anomalies are per unit standard deviation of the CTI. (From Deser et al. 2004)





Figure 3. The period (A) and growth rate (B) of the most unstable coupled mode as a function of mean thermocline depth (H) and strength of the trade winds () (From Fedorov and Philander 2000).





Figure 4. Schematic sketch of the hypotheses of STC-induced decadal changes in the tropical Pacific mean state by (Gu and Philander 1997) and (Kleeman et al. 1999). The Gu-Philander’s mechanism emphasizes the advection of thermal anomalies by the STCs, while Kleeman et al.’s mechanism emphasizes changes in STCs. Note the sketch shows a zonally averaged view of the STCs. In reality, much of the equatorward geostrophic transport probably occurs in the western boundary current.



Figure 5. Decadal differences in SST and winds in the tropical Pacific (From McPhaden and Zhang 2004).




Figure 6. Leading EOFs of the low-passed SST from the coupled GCM experiments of Yeh and Kirtman (2004b). The leading EOF has a low correlation with the Niño-3.4 SSTA Variance, while EOF 2 has a high correlation. Note the similarity of the EOF1 pattern with the observed changes from McPhaden and Zhang (2004).




Figure 7. The dominant pattern of surface ocean-atmosphere variability in the tropical Atlantic region during boreal spring (left panel) and boreal summer (right panel). The black contours depict the first EOF of the regional March-April and of June-August rainfall anomaly (from GPCP data 1979-2001) in units of mm/day. The EOFs explain 33% and 23% of the seasonal variance in the boreal spring and summer, respectively. The colored field is the March-April and June-August SST anomaly regressed on the principal component time series of the rainfall EOF (units are °C, see scale below; white contours every 0.2° are added for further clarity). Arrows depict the seasonal mean surface wind vector in m/sec, regressed on the same time series (see arrow scale below frame). (From Kushnir et al. 2004)





Figure 8. Correlation between SST, pseudostresses and the Atl-3 index, respectively. The Atl-3 index is defined as area-averaged SST anomaly over 3°S-3°N, 20°W-0°. The SST and pseudostress data derive from the analysis by Servain et al (1987), on a 2° by 2° grid for the period 1964-1988 (From Zebiak 1993).





Figure 9. Regression of zonally averaged surface wind stresses (vector), surface heat flux (contour) and SST anomalies onto Niño-3 (a) and negative NAO (b) indices as a function latitude and time lag (from the winter to the summer). The zonal average was taken between 40° and 20° W. The Niño-3 index is defined as area-averaged SST anomaly over 5°S-5°N, 90°-150°W during boreal winter (December-January-February) and the NAO index is based on the winter (December-January-February-March) sea level pressure index of Hurrell (1995). (From Czaja et al. 2002). .





Figure 10. Correlation maps of a cross-equatorial wind stress index against wind stress curl and SST anomaly. (From Joyce et al. 2004)






Figure 11. Propagation of salinity compensated temperature anomalies on isopycnal  25.5, within the thermocline along the Brazilian coast and then within the equatorial undercurrent (EUC) as seen in an ocean GCM forced at the surface by NCEP-NCAR Reanalysis data (see Lazar et al. 2001).




Figure 12. Change in surface air temperature during year 20-30 after the shutdown of the thermohaline circulation in HadCM3. (From Vellinga and Wood 2002)




a) b) c) d)



Figure 14. Composite of SST anomalies for a) all IOD events, b) pure IOD events, c) all ENSO events and d) pure ENSO events. Adapted from the Yamagata et al. 2004.







Figure 15. Schematic diagram of IOD (top panel) and ENSO (bottom panel) teleconnections based on the partial correlations/pure composite of Saji and Yamagata (2003b) and Yamagata et al. (2004). The orange (blue) shade indicates warm (cold) conditions during positive IOD or El Niño. Clouds (grey shade) represent rainy (dry) conditions during positive IOD or El Niño. The opposite is true during negative IOD and La Nina events.



Figure 16. Same as in Fig. 14 but for the zonal mass flux anomalies that represent anomalous Walker circulation (from Yamagata et al. 2003a).




Figure 17. Schematic triangular relation among three key regions: the eastern Indian Ocean, Eastern Europe/the Mediterranean Sea and the Far East. Warm (cold) colors denote anomalously dry (wet) conditions. See details in the text. From Yamagata et al. (2004).




Figure 18. Wavelet spectrum of zonal wind anomalies showing the ISO activity for six strongest IOD years. From Rao and Yamagata 2004.





Figure 19. TACE Observational Strategy. The proposed observing system components include (see legend): Continuation of PIRATA moorings, PIRATA extensions along 23 º W and 5-10º E, equatorial subsurface (non-realtime) moorings along 23 ºE and at 10º W, island meteorological and tide gauge stations, enhanced float/drifter coverage in the eastern TA, repeated atmospheric soundings along 23 º W, ship-of-opportunity XBT lines, and selected glider transects.





Figure 20. The evolving design of a sustained observing system for the Indian Ocean.The systems includes 3x3 Argo profiling float array, 5x5 surface drifting bouy arrays and a real time tide guage network.

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