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Abstract
Upper-ocean zonal currents in the western equatorial Pacific are remarkably variable, changing direction both with time and depth. As a part of the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment, an enhanced monitoring array of moorings measured the upper-ocean velocity, temperature, salinity, and, surface meteorological conditions in the western equatorial Pacific for two years (March 1992–April 1994). Data from this array are used to evaluate the zonal momentum balance. Although nonlinear terms (zonal, meridional, and vertical advection) were at times large, reversing jets were primarily due to an interplay between wind forcing and compensating pressure gradients. In the weakly stratified surface layer, the flow is to a large extent directly forced by local winds. Eastward acceleration associated with westerly wind bursts and westward accelerations associated with easterly trades lead to frequent reversals in the surface-layer flow. However, pressure gradients set up by the wind bursts partially compensate the local wind forcing in the surface layer. Below the surface layer, these pressure gradients tend to accelerate the upper-thermocline flow in a direction opposing the local winds. Consequently, during westerly wind bursts, a reversing jet structure can develop, with a surface eastward current overlying a westward intermediate layer flow, overlaying the eastward Equatorial Undercurrent.
Abstract
Upper-ocean zonal currents in the western equatorial Pacific are remarkably variable, changing direction both with time and depth. As a part of the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment, an enhanced monitoring array of moorings measured the upper-ocean velocity, temperature, salinity, and, surface meteorological conditions in the western equatorial Pacific for two years (March 1992–April 1994). Data from this array are used to evaluate the zonal momentum balance. Although nonlinear terms (zonal, meridional, and vertical advection) were at times large, reversing jets were primarily due to an interplay between wind forcing and compensating pressure gradients. In the weakly stratified surface layer, the flow is to a large extent directly forced by local winds. Eastward acceleration associated with westerly wind bursts and westward accelerations associated with easterly trades lead to frequent reversals in the surface-layer flow. However, pressure gradients set up by the wind bursts partially compensate the local wind forcing in the surface layer. Below the surface layer, these pressure gradients tend to accelerate the upper-thermocline flow in a direction opposing the local winds. Consequently, during westerly wind bursts, a reversing jet structure can develop, with a surface eastward current overlying a westward intermediate layer flow, overlaying the eastward Equatorial Undercurrent.
Abstract
This paper investigates the structure and dynamics of the Equatorial Undercurrent (EUC) of the Indian Ocean by analyzing in situ observations and reanalysis data and performing ocean model experiments using an ocean general circulation model and a linear continuously stratified ocean model. The results show that the EUC regularly occurs in each boreal winter and spring, particularly during February and April, consistent with existing studies. The EUC generally has a core depth near the 20°C isotherm and can be present across the equatorial basin. The EUC reappears during summer–fall of most years, with core depth located at different longitudes and depths. In the western basin, the EUC results primarily from equatorial Kelvin and Rossby waves directly forced by equatorial easterly winds. In the central and eastern basin, however, reflected Rossby waves from the eastern boundary play a crucial role. While the first two baroclinic modes make the largest contribution, intermediate modes 3–8 are also important. The summer–fall EUC tends to occur in the western basin but exhibits obvious interannual variability in the eastern basin. During positive Indian Ocean dipole (IOD) years, the eastern basin EUC results largely from Rossby waves reflected from the eastern boundary, with directly forced Kelvin and Rossby waves also having significant contributions. However, the eastern basin EUC disappears during negative IOD and normal years because westerly wind anomalies force a westward pressure gradient force and thus westward subsurface current, which cancels the eastward subsurface flow induced by eastern boundary–reflected Rossby waves. Interannual variability of zonal equatorial wind that drives the EUC variability is dominated by the zonal sea surface temperature (SST) gradients associated with IOD and is much less influenced by equatorial wind associated with Indian monsoon rainfall strength.
Abstract
This paper investigates the structure and dynamics of the Equatorial Undercurrent (EUC) of the Indian Ocean by analyzing in situ observations and reanalysis data and performing ocean model experiments using an ocean general circulation model and a linear continuously stratified ocean model. The results show that the EUC regularly occurs in each boreal winter and spring, particularly during February and April, consistent with existing studies. The EUC generally has a core depth near the 20°C isotherm and can be present across the equatorial basin. The EUC reappears during summer–fall of most years, with core depth located at different longitudes and depths. In the western basin, the EUC results primarily from equatorial Kelvin and Rossby waves directly forced by equatorial easterly winds. In the central and eastern basin, however, reflected Rossby waves from the eastern boundary play a crucial role. While the first two baroclinic modes make the largest contribution, intermediate modes 3–8 are also important. The summer–fall EUC tends to occur in the western basin but exhibits obvious interannual variability in the eastern basin. During positive Indian Ocean dipole (IOD) years, the eastern basin EUC results largely from Rossby waves reflected from the eastern boundary, with directly forced Kelvin and Rossby waves also having significant contributions. However, the eastern basin EUC disappears during negative IOD and normal years because westerly wind anomalies force a westward pressure gradient force and thus westward subsurface current, which cancels the eastward subsurface flow induced by eastern boundary–reflected Rossby waves. Interannual variability of zonal equatorial wind that drives the EUC variability is dominated by the zonal sea surface temperature (SST) gradients associated with IOD and is much less influenced by equatorial wind associated with Indian monsoon rainfall strength.
Abstract
Three sets of horizontal velocity measurements obtained within 3 miles of each other at 0°, 140°W are compared. Measurements were taken by acoustic Doppler current Profilers (ADCPs) on different platforms, with different tracking filter configurations, and were processed by three different groups. A veraged over more than 12 days, mean velocity measurements differ by less than 1 cm s−1 at most depths. This discrepancy is about the same as the skew error of ADCP measurements. The rms value of residual velocity components for measurements averaged over 5–6 min is 0(5 cm s−1). These residuals are due to the combined effects of navigational errors and spatial variability in the oceanic velocity field. The estimated navigational error has an rms value of 2–3 cm s−1 for each velocity component. Meridional gradients of the Equatorial Undercurrent estimated from transient velocity differences and ship-buoy separations agree with those estimated from meridional transect data.
Abstract
Three sets of horizontal velocity measurements obtained within 3 miles of each other at 0°, 140°W are compared. Measurements were taken by acoustic Doppler current Profilers (ADCPs) on different platforms, with different tracking filter configurations, and were processed by three different groups. A veraged over more than 12 days, mean velocity measurements differ by less than 1 cm s−1 at most depths. This discrepancy is about the same as the skew error of ADCP measurements. The rms value of residual velocity components for measurements averaged over 5–6 min is 0(5 cm s−1). These residuals are due to the combined effects of navigational errors and spatial variability in the oceanic velocity field. The estimated navigational error has an rms value of 2–3 cm s−1 for each velocity component. Meridional gradients of the Equatorial Undercurrent estimated from transient velocity differences and ship-buoy separations agree with those estimated from meridional transect data.
Abstract
There was an opportunity to compare 10 months of collocated National Aeronautics and Space Administration scatterometer (NSCAT) wind vectors with those from the Tropical Atmosphere Ocean (TAO) buoy array, located in the tropical Pacific Ocean. Over 5500 data pairs, from nearly 70 buoys, were collocated in the calibration/validation effort for NSCAT. These data showed that the wind speeds produced from the NSCAT-1 model function were low by about 7%–8% compared with TAO buoy winds. The revised model function, NSCAT-2, produces wind speeds with a bias of about 1%. The scatterometer directions were within 20° (rms), meeting accuracy requirements, when compared to TAO data. The mean direction bias between the TAO and the NSCAT vectors (regardless of model function) is about 9° with the scatterometer winds to the right of the TAO winds, which may be due to swell. The statistics of the two datasets are discussed, using component biases in lieu of the speed bias, which is naturally skewed. Using ocean currents and buoy winds measured along the equator, it is shown that the scatterometer measures the wind relative to the moving ocean surface. In addition, a systematic effect of rain on the NSCAT wind retrievals is noted. In all analyses presented here, winds less than 3 m s−1 are removed, due to the difficulty in making accurate low wind measurements.
Abstract
There was an opportunity to compare 10 months of collocated National Aeronautics and Space Administration scatterometer (NSCAT) wind vectors with those from the Tropical Atmosphere Ocean (TAO) buoy array, located in the tropical Pacific Ocean. Over 5500 data pairs, from nearly 70 buoys, were collocated in the calibration/validation effort for NSCAT. These data showed that the wind speeds produced from the NSCAT-1 model function were low by about 7%–8% compared with TAO buoy winds. The revised model function, NSCAT-2, produces wind speeds with a bias of about 1%. The scatterometer directions were within 20° (rms), meeting accuracy requirements, when compared to TAO data. The mean direction bias between the TAO and the NSCAT vectors (regardless of model function) is about 9° with the scatterometer winds to the right of the TAO winds, which may be due to swell. The statistics of the two datasets are discussed, using component biases in lieu of the speed bias, which is naturally skewed. Using ocean currents and buoy winds measured along the equator, it is shown that the scatterometer measures the wind relative to the moving ocean surface. In addition, a systematic effect of rain on the NSCAT wind retrievals is noted. In all analyses presented here, winds less than 3 m s−1 are removed, due to the difficulty in making accurate low wind measurements.
Abstract
The investigation of the consequences of trying to blend tropical Pacific observations from the Tropical Atmosphere–Ocean (TAO) array into the dynamical framework of an intermediate coupled ocean–atmosphere model is continued. In a previous study it was found that the model dynamics, the prior estimates of uncertainty in the observations, and the estimates of the errors in the dynamical equations of the model could not be reconciled with data from the 1994–95 period. The error estimates and the data forced the rejection of the model physics as being unacceptably in error. In this work, data from two periods (1995–96 and 1997–98) were used when the tropical Pacific was in states very different from the previous study. The consequences of increasing the prior error estimates were explored in an effort to find out if it is possible at least to use the intermediate model physics to assist in mapping the observations into fields in a statistically consistent way.
It was found that such a result is possible for the new data periods, with larger prior error assumptions. However, examination of the behavior of the mapped fields indicates that they have no dynamical utility. The model dynamical residuals, that is, the size of the quantity that is left after evaluating all of the terms in each intermediate model equation, dominate the terms themselves. Evidently the intermediate model is not able to add insight into the processes that caused the tropical Pacific to behave as it was observed to, during these time intervals.
The inverse techniques described here together with the relatively dense TAO dataset have made it possible for the unambiguous rejection of the nonlinear intermediate model dynamical system. This is the first time that data have been able to provide such a clear-cut appraisal of simplified dynamics.
Abstract
The investigation of the consequences of trying to blend tropical Pacific observations from the Tropical Atmosphere–Ocean (TAO) array into the dynamical framework of an intermediate coupled ocean–atmosphere model is continued. In a previous study it was found that the model dynamics, the prior estimates of uncertainty in the observations, and the estimates of the errors in the dynamical equations of the model could not be reconciled with data from the 1994–95 period. The error estimates and the data forced the rejection of the model physics as being unacceptably in error. In this work, data from two periods (1995–96 and 1997–98) were used when the tropical Pacific was in states very different from the previous study. The consequences of increasing the prior error estimates were explored in an effort to find out if it is possible at least to use the intermediate model physics to assist in mapping the observations into fields in a statistically consistent way.
It was found that such a result is possible for the new data periods, with larger prior error assumptions. However, examination of the behavior of the mapped fields indicates that they have no dynamical utility. The model dynamical residuals, that is, the size of the quantity that is left after evaluating all of the terms in each intermediate model equation, dominate the terms themselves. Evidently the intermediate model is not able to add insight into the processes that caused the tropical Pacific to behave as it was observed to, during these time intervals.
The inverse techniques described here together with the relatively dense TAO dataset have made it possible for the unambiguous rejection of the nonlinear intermediate model dynamical system. This is the first time that data have been able to provide such a clear-cut appraisal of simplified dynamics.
Abstract
Surface wind analyses from three data assimilation systems are compared with independent wind observations from six buoys located in the Pacific within 8 deg of the equator. The period of comparison is 6 months (February to July 1987), with daily sampling.
The agreement between the assimilation systems and the independent buoy data is disappointing. The longterm mean differences between the buoy and the assimilated zonal and meridional winds are as large as 3.1 m s−1, which is comparable to the size of the means themselves. The zonal and meridional daily wind correlations range between 0.66 and 0.17. The wind field agreement was actually better among the different systems than between any system and the buoys. However, the agreement among the analysis products was usually better for the zonal winds than for the meridional winds. For the time period and locations presented, the comparisons with the independent data show that no assimilation system is clearly superior to any of the others.
Abstract
Surface wind analyses from three data assimilation systems are compared with independent wind observations from six buoys located in the Pacific within 8 deg of the equator. The period of comparison is 6 months (February to July 1987), with daily sampling.
The agreement between the assimilation systems and the independent buoy data is disappointing. The longterm mean differences between the buoy and the assimilated zonal and meridional winds are as large as 3.1 m s−1, which is comparable to the size of the means themselves. The zonal and meridional daily wind correlations range between 0.66 and 0.17. The wind field agreement was actually better among the different systems than between any system and the buoys. However, the agreement among the analysis products was usually better for the zonal winds than for the meridional winds. For the time period and locations presented, the comparisons with the independent data show that no assimilation system is clearly superior to any of the others.
Abstract
Current coupled global climate models have biases in their simulations of the tropical Pacific mean-state conditions as well as the El Niño–Southern Oscillation (ENSO) phenomenon. Specifically, in the Community Earth System Model (CESM version 1.2.2), the tropical Pacific mean state has overly weak sea surface temperature (SST) gradients in both the zonal and meridional directions, ENSO is too strong and too regular, and El Niño and La Niña events are too symmetrical. A previous study with a slab-ocean model showed that a higher elevation of the Andes can improve the tropical Pacific mean-state simulation by adjusting the atmospheric circulation and increasing the east–west and north–south SST gradients. Motivated by the link between the mean tropical Pacific climate and ENSO variations shown in previous studies, here we explored the influence of the Andes on the simulation of ENSO using the CESM 1.2.2 under full atmosphere–ocean coupling. In addition to improving the simulated tropical Pacific mean state by increasing the strength of the surface easterly and cross-equatorial southerly winds, the Higher Andes experiment decreases the amplitude of ENSO, increases the phase asymmetry, and makes ENSO events less regular, resulting in a simulated ENSO that is more consistent with observations. The weaker ENSO cycle is related to stronger damping in the Higher Andes experiment according to an analysis of the Bjerknes index. Our overall results suggest that increasing the height of the Andes reduces biases in the mean state and improves the representation of ENSO in the tropical Pacific.
Abstract
Current coupled global climate models have biases in their simulations of the tropical Pacific mean-state conditions as well as the El Niño–Southern Oscillation (ENSO) phenomenon. Specifically, in the Community Earth System Model (CESM version 1.2.2), the tropical Pacific mean state has overly weak sea surface temperature (SST) gradients in both the zonal and meridional directions, ENSO is too strong and too regular, and El Niño and La Niña events are too symmetrical. A previous study with a slab-ocean model showed that a higher elevation of the Andes can improve the tropical Pacific mean-state simulation by adjusting the atmospheric circulation and increasing the east–west and north–south SST gradients. Motivated by the link between the mean tropical Pacific climate and ENSO variations shown in previous studies, here we explored the influence of the Andes on the simulation of ENSO using the CESM 1.2.2 under full atmosphere–ocean coupling. In addition to improving the simulated tropical Pacific mean state by increasing the strength of the surface easterly and cross-equatorial southerly winds, the Higher Andes experiment decreases the amplitude of ENSO, increases the phase asymmetry, and makes ENSO events less regular, resulting in a simulated ENSO that is more consistent with observations. The weaker ENSO cycle is related to stronger damping in the Higher Andes experiment according to an analysis of the Bjerknes index. Our overall results suggest that increasing the height of the Andes reduces biases in the mean state and improves the representation of ENSO in the tropical Pacific.
Abstract
The highly temporally resolved time series from the Tropical Atmosphere-Ocean moored buoy array are used to evaluate the scales of thermal variability in the upper equatorial Pacific. The TAO array consists of nearly 70 deep-ocean moorings arranged nominally 15° longitude and 2°–3° latitude apart across the equatorial Pacific. The bulk of the data from the array consists of daily averages telemetered in real time, with some records up to 15 years long. However, at several sites more finely resolved data exist, in some cases with resolution of 1 minute. These data form the basis for spectral decomposition spanning virtually all scales of variability from the Brunt-Väiälä frequency to the El Niño-Southern Oscillation timescale. The spectra are used to define the signal to noise ratio as a function of sample rate and frequency, and to investigate the effects of aliasing that results from sparser sampling, such as ship-based observational techniques. The results show that the signal to noise ratio is larger in the east, mostly because the low-frequency signals are larger there. The noise level for SST varies by as much as a factor of 10 among the locations studied, while noise in thermocline depth is relatively more homogeneous over the region. In general, noise due to aliased high-frequency variability increases by roughly a factor of 10 as the sample rate decreases from daily to 100-day sampling. The highly resolved spectra suggest a somewhat more optimistic estimate of overall signal-to-noise ratios for typical ship of opportunity (VOS) XBT sampling (generally about 2) than had been found in previous studies using sparser data. Time scales were estimated for various filtered versions of the time series by integration of the autocorrelation functions. For high-passed data (periods longer than about 150 days removed), the timescale is about 5 days for both surface and subsurface temperatures everywhere in the region. Conversely, for low-passed data (the annual cycle and periods shorter than 150 days removed), the timescale is roughly 100 days. Horizontal space scales were estimated from cross-correlations among the buoys. Zonal scales of low-frequency SST variations along the equator were half the width of the Pacific, larger than those of thermocline depth (about 30°–40° longitude). In the cast, meridional scales of low-frequency SST were large (greater than about 15° latitude), associated with the coherent waxing and waning of the equatorial cold tongue, whereas in the west these scales were shorter. Thermocline depth variations had meridional scales associated with the equatorial waves, particularly in the east. Spatial scale estimates reported here are generally consistent with those found from the VOS datasets when the ENSO signals in the records of each dataset are taken into account. However, if signals with periods of 1 to 2 months are to be properly sampled, then sampling scales of 1°–2° latitude by 8°–10° longitude, with a 5-day timescale, are needed.
Abstract
The highly temporally resolved time series from the Tropical Atmosphere-Ocean moored buoy array are used to evaluate the scales of thermal variability in the upper equatorial Pacific. The TAO array consists of nearly 70 deep-ocean moorings arranged nominally 15° longitude and 2°–3° latitude apart across the equatorial Pacific. The bulk of the data from the array consists of daily averages telemetered in real time, with some records up to 15 years long. However, at several sites more finely resolved data exist, in some cases with resolution of 1 minute. These data form the basis for spectral decomposition spanning virtually all scales of variability from the Brunt-Väiälä frequency to the El Niño-Southern Oscillation timescale. The spectra are used to define the signal to noise ratio as a function of sample rate and frequency, and to investigate the effects of aliasing that results from sparser sampling, such as ship-based observational techniques. The results show that the signal to noise ratio is larger in the east, mostly because the low-frequency signals are larger there. The noise level for SST varies by as much as a factor of 10 among the locations studied, while noise in thermocline depth is relatively more homogeneous over the region. In general, noise due to aliased high-frequency variability increases by roughly a factor of 10 as the sample rate decreases from daily to 100-day sampling. The highly resolved spectra suggest a somewhat more optimistic estimate of overall signal-to-noise ratios for typical ship of opportunity (VOS) XBT sampling (generally about 2) than had been found in previous studies using sparser data. Time scales were estimated for various filtered versions of the time series by integration of the autocorrelation functions. For high-passed data (periods longer than about 150 days removed), the timescale is about 5 days for both surface and subsurface temperatures everywhere in the region. Conversely, for low-passed data (the annual cycle and periods shorter than 150 days removed), the timescale is roughly 100 days. Horizontal space scales were estimated from cross-correlations among the buoys. Zonal scales of low-frequency SST variations along the equator were half the width of the Pacific, larger than those of thermocline depth (about 30°–40° longitude). In the cast, meridional scales of low-frequency SST were large (greater than about 15° latitude), associated with the coherent waxing and waning of the equatorial cold tongue, whereas in the west these scales were shorter. Thermocline depth variations had meridional scales associated with the equatorial waves, particularly in the east. Spatial scale estimates reported here are generally consistent with those found from the VOS datasets when the ENSO signals in the records of each dataset are taken into account. However, if signals with periods of 1 to 2 months are to be properly sampled, then sampling scales of 1°–2° latitude by 8°–10° longitude, with a 5-day timescale, are needed.
Abstract
Unusually high western Pacific Ocean oceanic heat content often leads to El Niño about 1 year later, while unusually low heat content leads to La Niña. Here, we investigate if El Niño–Southern Oscillation (ENSO) predictability also depends on the initial state recharge, and we discuss the underlying mechanisms. To that end, we use the CNRM-CM5 model, which has a reasonable representation of the main observed ENSO characteristics, asymmetries, and feedbacks. Observations and a 1007-yr-long CNRM-CM5 simulation indicate that discharged states evolve more systematically into La Niña events than recharged states into neutral states or El Niño events. We ran 70-member ensemble experiments in a perfect-model setting, initialized in boreal autumn from either recharged or discharged western Pacific heat content, sampling the full range of corresponding ENSO phases. Predictability measures based both on spread and signal-to-noise ratio confirm that discharged states yield a more predictable ENSO outcome one year later than recharged states. As expected from recharge oscillator theory, recharged states evolve into positive central Pacific sea surface temperature anomalies in boreal spring, inducing stronger and more variable westerly wind event activity and a fast growth of the ensemble spread during summer and autumn. This also enhances the positive wind stress feedback in autumn, but the effect is offset by changes in thermocline and heat flux feedbacks. The state-dependent component of westerly wind events is thus the most likely cause for the predictability asymmetry in CNRM-CM5, although changes in the low-frequency wind stress feedback may also contribute.
Abstract
Unusually high western Pacific Ocean oceanic heat content often leads to El Niño about 1 year later, while unusually low heat content leads to La Niña. Here, we investigate if El Niño–Southern Oscillation (ENSO) predictability also depends on the initial state recharge, and we discuss the underlying mechanisms. To that end, we use the CNRM-CM5 model, which has a reasonable representation of the main observed ENSO characteristics, asymmetries, and feedbacks. Observations and a 1007-yr-long CNRM-CM5 simulation indicate that discharged states evolve more systematically into La Niña events than recharged states into neutral states or El Niño events. We ran 70-member ensemble experiments in a perfect-model setting, initialized in boreal autumn from either recharged or discharged western Pacific heat content, sampling the full range of corresponding ENSO phases. Predictability measures based both on spread and signal-to-noise ratio confirm that discharged states yield a more predictable ENSO outcome one year later than recharged states. As expected from recharge oscillator theory, recharged states evolve into positive central Pacific sea surface temperature anomalies in boreal spring, inducing stronger and more variable westerly wind event activity and a fast growth of the ensemble spread during summer and autumn. This also enhances the positive wind stress feedback in autumn, but the effect is offset by changes in thermocline and heat flux feedbacks. The state-dependent component of westerly wind events is thus the most likely cause for the predictability asymmetry in CNRM-CM5, although changes in the low-frequency wind stress feedback may also contribute.
Abstract
The Atlantic multidecadal oscillation (AMO) has been shown to play a major role in the multidecadal variability of the Northern Hemisphere, impacting temperature and precipitation, including intertropical convergence zone (ITCZ)-driven precipitation across Africa and South America. Studies into the location of the intertropical convergence zone have suggested that it resides in the warmer hemisphere, with the poleward branch of the Hadley cell acting to transport energy from the warmer hemisphere to the cooler one. Given the impact of the Atlantic multidecadal oscillation on Northern Hemisphere temperatures, we expect the Atlantic multidecadal oscillation to have an impact on the location of the intertropical convergence zone. We find that the positive phase of the Atlantic multidecadal oscillation warms the Northern Hemisphere, resulting in a northward shift of the intertropical convergence zone, which is evident in the Pacific climate proxy record. Using a coupled climate model, we further find that the shift in the intertropical convergence zone is consistent with the surface energy imbalance generated by the Atlantic multidecadal oscillation. In this model, the Pacific changes are driven in large part by the warming of the tropical Atlantic and not the extratropical Atlantic.
Abstract
The Atlantic multidecadal oscillation (AMO) has been shown to play a major role in the multidecadal variability of the Northern Hemisphere, impacting temperature and precipitation, including intertropical convergence zone (ITCZ)-driven precipitation across Africa and South America. Studies into the location of the intertropical convergence zone have suggested that it resides in the warmer hemisphere, with the poleward branch of the Hadley cell acting to transport energy from the warmer hemisphere to the cooler one. Given the impact of the Atlantic multidecadal oscillation on Northern Hemisphere temperatures, we expect the Atlantic multidecadal oscillation to have an impact on the location of the intertropical convergence zone. We find that the positive phase of the Atlantic multidecadal oscillation warms the Northern Hemisphere, resulting in a northward shift of the intertropical convergence zone, which is evident in the Pacific climate proxy record. Using a coupled climate model, we further find that the shift in the intertropical convergence zone is consistent with the surface energy imbalance generated by the Atlantic multidecadal oscillation. In this model, the Pacific changes are driven in large part by the warming of the tropical Atlantic and not the extratropical Atlantic.