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Abstract
The authors examine global statistical relationships between westerly wind events (WWEs) and sea surface temperature anomaly (SSTA) variability, using a compositing technique for the period 1986–98. The authors describe the extent to which equatorial WWEs are associated with central and eastern equatorial Pacific waveguide warming and with local SSTA changes under the WWE. Their goal is to quantify the extent to which equatorial WWEs are fundamental to the onset and maintenance of warm El Niño–Southern Oscillation conditions. In order to understand the effect of WWEs on SSTA evolution, they begin by examining how SSTA changes in the absence of equatorial WWEs. They find that SSTA tends toward mean climate values in the absence of equatorial WWEs, whether the eastern equatorial Pacific has close to normal SSTA or warmer than normal SSTA.
The two equatorial WWE types whose main surface wind anomalies are west of the date line are associated with weak local surface cooling. The equatorial WWE type that has equatorial westerly wind anomalies east of the date line is associated with weak warming under those anomalies, when the eastern equatorial Pacific SSTA is close to normal.
When the tropical Pacific has near-normal eastern equatorial Pacific SST, each of the equatorial WWE types is followed by substantial equatorial waveguide warming in the central and eastern Pacific (composite warming as large as 1.0°C); also more than 50% of the large-amplitude WWEs were followed by Niño-3 SSTA warming in excess of 0.5°C. These changes are of similar amplitude and spatial structure as those seen in the onset of El Niño and are consistent with the predicted oceanic response to WWE forcing. When the eastern equatorial Pacific is initially warmer than usual, the two westernmost equatorial WWE types are associated with the maintenance of warm El Niño eastern and central Pacific SSTA; these warm anomalies tend to disappear in the absence of those WWE types. WWEs, or some mechanism strongly correlated with WWEs, represent a fundamental process for waveguide warming in the onset of El Niño and for eastern and central Pacific warm SSTA maintenance during El Niño.
Abstract
The authors examine global statistical relationships between westerly wind events (WWEs) and sea surface temperature anomaly (SSTA) variability, using a compositing technique for the period 1986–98. The authors describe the extent to which equatorial WWEs are associated with central and eastern equatorial Pacific waveguide warming and with local SSTA changes under the WWE. Their goal is to quantify the extent to which equatorial WWEs are fundamental to the onset and maintenance of warm El Niño–Southern Oscillation conditions. In order to understand the effect of WWEs on SSTA evolution, they begin by examining how SSTA changes in the absence of equatorial WWEs. They find that SSTA tends toward mean climate values in the absence of equatorial WWEs, whether the eastern equatorial Pacific has close to normal SSTA or warmer than normal SSTA.
The two equatorial WWE types whose main surface wind anomalies are west of the date line are associated with weak local surface cooling. The equatorial WWE type that has equatorial westerly wind anomalies east of the date line is associated with weak warming under those anomalies, when the eastern equatorial Pacific SSTA is close to normal.
When the tropical Pacific has near-normal eastern equatorial Pacific SST, each of the equatorial WWE types is followed by substantial equatorial waveguide warming in the central and eastern Pacific (composite warming as large as 1.0°C); also more than 50% of the large-amplitude WWEs were followed by Niño-3 SSTA warming in excess of 0.5°C. These changes are of similar amplitude and spatial structure as those seen in the onset of El Niño and are consistent with the predicted oceanic response to WWE forcing. When the eastern equatorial Pacific is initially warmer than usual, the two westernmost equatorial WWE types are associated with the maintenance of warm El Niño eastern and central Pacific SSTA; these warm anomalies tend to disappear in the absence of those WWE types. WWEs, or some mechanism strongly correlated with WWEs, represent a fundamental process for waveguide warming in the onset of El Niño and for eastern and central Pacific warm SSTA maintenance during El Niño.
Abstract
ENSO cold (La Niña) events are shown to exhibit a distinctive life cycle. The first near-global description of ENSO cold (La Niña)–event anomaly features is described using ocean surface data. It is found that cold-event anomalies are not simply the mirror image of warm (El Niño) events. The Comprehensive Ocean–Atmosphere Data Set marine surface record [SST, sea level pressure (SLP), and wind] is used to identify the statistically significant features of the nine cold-event periods during 1946–95 and to focus on the large-scale elements that are typical of most events. By examining time series, the most robust features of the composite that have occurred during nearly all of the post–World War II cold events are identified.
These robust cold-event features are more numerous and cover more of the globe than their warm-event counterparts. Of the 90 composite features examined, 57 (63%) are found to be robust. Most of these are located in the Tropics (70%) and in the Pacific (65%). However, robust elements are found in all the ocean basins (Indian—14%; Atlantic—21%) and in both hemispheres (Northern—18%; Southern—12%), making cold events truly global. In addition, a true life cycle for the cold event is found, with different anomalies occurring at different phases of the evolution of the event and not just during the peak (largest amplitude) phase. The evolution and simulation of these characteristic features of cold events offer as important a challenge to coupled models as the more familiar warm-event anomalies.
Abstract
ENSO cold (La Niña) events are shown to exhibit a distinctive life cycle. The first near-global description of ENSO cold (La Niña)–event anomaly features is described using ocean surface data. It is found that cold-event anomalies are not simply the mirror image of warm (El Niño) events. The Comprehensive Ocean–Atmosphere Data Set marine surface record [SST, sea level pressure (SLP), and wind] is used to identify the statistically significant features of the nine cold-event periods during 1946–95 and to focus on the large-scale elements that are typical of most events. By examining time series, the most robust features of the composite that have occurred during nearly all of the post–World War II cold events are identified.
These robust cold-event features are more numerous and cover more of the globe than their warm-event counterparts. Of the 90 composite features examined, 57 (63%) are found to be robust. Most of these are located in the Tropics (70%) and in the Pacific (65%). However, robust elements are found in all the ocean basins (Indian—14%; Atlantic—21%) and in both hemispheres (Northern—18%; Southern—12%), making cold events truly global. In addition, a true life cycle for the cold event is found, with different anomalies occurring at different phases of the evolution of the event and not just during the peak (largest amplitude) phase. The evolution and simulation of these characteristic features of cold events offer as important a challenge to coupled models as the more familiar warm-event anomalies.
Abstract
Previous studies by the authors have described the composite global marine surface anomalies of ENSO warm (El Niño) events and cold (La Niña) events. Here the similarities and differences in these life cycles are examined. Qualitatively different behavior between warm events and cold events exists in the tropical Indian and Atlantic Oceans and in the extratropical Pacific. Even in the tropical Pacific statistically significantly different behavior is found in some variables for particular regions and phases of the life cycles. A single-mode regression analysis of the ENSO signal is done; the patterns are very similar to those of previously published ENSO EOF and regression analyses. The authors describe how the regression patterns obscure many of the interesting life cycles and life cycle differences of cold events and warm events. Most of the regression structures outside of the tropical Pacific are not statistically significant because of such differences. ENSO models should be evaluated against their ability to reproduce the observed cold event and warm event life cycles and not just single EOF or regression mode patterns.
Abstract
Previous studies by the authors have described the composite global marine surface anomalies of ENSO warm (El Niño) events and cold (La Niña) events. Here the similarities and differences in these life cycles are examined. Qualitatively different behavior between warm events and cold events exists in the tropical Indian and Atlantic Oceans and in the extratropical Pacific. Even in the tropical Pacific statistically significantly different behavior is found in some variables for particular regions and phases of the life cycles. A single-mode regression analysis of the ENSO signal is done; the patterns are very similar to those of previously published ENSO EOF and regression analyses. The authors describe how the regression patterns obscure many of the interesting life cycles and life cycle differences of cold events and warm events. Most of the regression structures outside of the tropical Pacific are not statistically significant because of such differences. ENSO models should be evaluated against their ability to reproduce the observed cold event and warm event life cycles and not just single EOF or regression mode patterns.
Abstract
The Indian southwest monsoon directly affects the lives of over one billion people, providing almost 90% of the annual precipitation to the Indian subcontinent. An important characteristic of the southwest monsoon is variability on subseasonal timescales, with “active” periods of heavy rain interrupted by drier “break” periods. Both the number of monsoon breaks in a season and the timing of these breaks profoundly impact agricultural output from the Indian subcontinent. Most research on monsoon breaks has emphasized possible atmospheric mechanisms. However, new satellite data reveal large-amplitude basin-scale subseasonal sea surface temperature (SST) variability in the Bay of Bengal (BoB), in which northern BoB cooling precedes monsoon breaks by about 1 week. The relationship is statistically significant at the 95% level over the 3 yr examined, and so offers a potential statistical predictor for short-term monsoon variability. The basinwide averaged amplitude of SST changes is 1°–2°C and local changes can exceed 3°C over 2 weeks; these changes are as large as those seen in the local climatological seasonal cycle. This raises the possibility that air–sea interaction may be a significant factor in monsoon variability; the SST variability is coherent with monsoon variability with a phase relationship consistent with a coupled oscillation. A schematic coupled air–sea oscillator mechanism is offered for further study, in which oceanic changes play a dynamical role in monsoon variability.
Abstract
The Indian southwest monsoon directly affects the lives of over one billion people, providing almost 90% of the annual precipitation to the Indian subcontinent. An important characteristic of the southwest monsoon is variability on subseasonal timescales, with “active” periods of heavy rain interrupted by drier “break” periods. Both the number of monsoon breaks in a season and the timing of these breaks profoundly impact agricultural output from the Indian subcontinent. Most research on monsoon breaks has emphasized possible atmospheric mechanisms. However, new satellite data reveal large-amplitude basin-scale subseasonal sea surface temperature (SST) variability in the Bay of Bengal (BoB), in which northern BoB cooling precedes monsoon breaks by about 1 week. The relationship is statistically significant at the 95% level over the 3 yr examined, and so offers a potential statistical predictor for short-term monsoon variability. The basinwide averaged amplitude of SST changes is 1°–2°C and local changes can exceed 3°C over 2 weeks; these changes are as large as those seen in the local climatological seasonal cycle. This raises the possibility that air–sea interaction may be a significant factor in monsoon variability; the SST variability is coherent with monsoon variability with a phase relationship consistent with a coupled oscillation. A schematic coupled air–sea oscillator mechanism is offered for further study, in which oceanic changes play a dynamical role in monsoon variability.
Abstract
The North Atlantic hurricane seasons of 2005 and 2006 were dramatically different for the Gulf Coast and eastern seaboard of the United States. The 2005 hurricane season was one of the most destructive seasons in history, whereas there was limited impact in 2006. Hurricane activity had been forecast to be above normal in 2006, but it was not. One of the conspicuous differences in environmental conditions between these two years was sea surface temperature anomaly (SSTA) over a region of the western Atlantic and Caribbean (15°–30°N, 70°–40°W), which is important for hurricane formation and intensification. SSTA was more than 1.5 standard deviations warmer during the 2005 hurricane season, but it was much less in 2006 through most of its hurricane season. The intent of this study is to determine the mechanisms responsible for this SSTA difference. It is shown that the difference can be reproduced using a simple one-dimensional (1D) ocean mixed layer model forced with surface fluxes from the NCEP–NCAR reanalysis project. It is found that there are two causes of SSTA difference over this region during July through September: the first is latent heat flux variability caused by wind speed effects, and the second is nonlinear ocean warming caused by submonthly atmospheric variability. The observed SSTA difference is reproduced by our model even though solar forcing damps the observed difference, contrary to previous hypotheses.
Abstract
The North Atlantic hurricane seasons of 2005 and 2006 were dramatically different for the Gulf Coast and eastern seaboard of the United States. The 2005 hurricane season was one of the most destructive seasons in history, whereas there was limited impact in 2006. Hurricane activity had been forecast to be above normal in 2006, but it was not. One of the conspicuous differences in environmental conditions between these two years was sea surface temperature anomaly (SSTA) over a region of the western Atlantic and Caribbean (15°–30°N, 70°–40°W), which is important for hurricane formation and intensification. SSTA was more than 1.5 standard deviations warmer during the 2005 hurricane season, but it was much less in 2006 through most of its hurricane season. The intent of this study is to determine the mechanisms responsible for this SSTA difference. It is shown that the difference can be reproduced using a simple one-dimensional (1D) ocean mixed layer model forced with surface fluxes from the NCEP–NCAR reanalysis project. It is found that there are two causes of SSTA difference over this region during July through September: the first is latent heat flux variability caused by wind speed effects, and the second is nonlinear ocean warming caused by submonthly atmospheric variability. The observed SSTA difference is reproduced by our model even though solar forcing damps the observed difference, contrary to previous hypotheses.
Abstract
There is great interest in World Ocean temperature trends, yet the historical global ocean database has very uneven coverage in space and time. Previous work on 50-yr upper ocean temperature trends from the NOAA ocean data archive is extended here. Trends at depths from 50 to 1000 m are examined, based on observations gridded over larger regions than in the earlier study. Despite the use of larger grid boxes, most of the ocean does not have significant 50-yr trends at the 90% confidence level (CL). In fact only 30% of the ocean at 50 m has 90% CL trends, and the percentage decreases significantly with increasing depth. As noted in the previous study, there is much spatial structure in 50-yr trends, with areas of strong warming and strong cooling. These trend results are compared with trends calculated from data interpolated to standard levels and from a highly horizontally interpolated version of the dataset that has been used in previous heat content trend studies. The regional trend results can differ substantially, even in the areas with statistically significant trends. Trends based on the more interpolated analyses show more warming. Together with major temporal and spatial sampling limitations, the previously described strong interdecadal and spatial variability of trends makes it very difficult to formally estimate uncertainty in World Ocean averages, but these results suggest that upper ocean heat content integrals and integral trends may be substantially more uncertain than has yet been acknowledged. Further exploration of uncertainties is needed.
Abstract
There is great interest in World Ocean temperature trends, yet the historical global ocean database has very uneven coverage in space and time. Previous work on 50-yr upper ocean temperature trends from the NOAA ocean data archive is extended here. Trends at depths from 50 to 1000 m are examined, based on observations gridded over larger regions than in the earlier study. Despite the use of larger grid boxes, most of the ocean does not have significant 50-yr trends at the 90% confidence level (CL). In fact only 30% of the ocean at 50 m has 90% CL trends, and the percentage decreases significantly with increasing depth. As noted in the previous study, there is much spatial structure in 50-yr trends, with areas of strong warming and strong cooling. These trend results are compared with trends calculated from data interpolated to standard levels and from a highly horizontally interpolated version of the dataset that has been used in previous heat content trend studies. The regional trend results can differ substantially, even in the areas with statistically significant trends. Trends based on the more interpolated analyses show more warming. Together with major temporal and spatial sampling limitations, the previously described strong interdecadal and spatial variability of trends makes it very difficult to formally estimate uncertainty in World Ocean averages, but these results suggest that upper ocean heat content integrals and integral trends may be substantially more uncertain than has yet been acknowledged. Further exploration of uncertainties is needed.
Abstract
Westerly wind events (WWEs) in the western equatorial Pacific have previously been shown to cause significant warming of sea surface temperature (SST) in the eastern equatorial Pacific. Observational statistics compiled during and prior to the large El Niño event of 1997/98 link WWEs to substantial (up to 3°C) warming in the eastern Pacific cold tongue region. Since 1998, however, relatively little WWE-related cold tongue warming has been observed, and warm equatorial Pacific SST anomalies (SSTAs) have tended to be trapped near the date line rather than extending to the American coast as in a classical El Niño–Southern Oscillation (ENSO) composite. Here, the relationship between WWEs and cold tongue warming is revisited using in situ and operational forecast winds and in situ and satellite-based SST. Significant differences are found in the basin-scale zonal wind anomalies associated with WWEs that occurred before and after 1997/98. Although the post-1997/98 composite WWE westerly anomalies are very similar to their predecessors within the WWE regions, conditions east of the WWE regions are different; there are enhanced equatorial easterlies in the post-1997/98 cases. General ocean circulation model experiments are conducted to explore the extent to which the observed changes in the character of post-1997/98 WWEs can explain the recent behavior of cold tongue SSTAs. It is found that the wind differences can account for the changes in the average cold tongue warming associated with pre- and post-1997/98 WWEs.
Abstract
Westerly wind events (WWEs) in the western equatorial Pacific have previously been shown to cause significant warming of sea surface temperature (SST) in the eastern equatorial Pacific. Observational statistics compiled during and prior to the large El Niño event of 1997/98 link WWEs to substantial (up to 3°C) warming in the eastern Pacific cold tongue region. Since 1998, however, relatively little WWE-related cold tongue warming has been observed, and warm equatorial Pacific SST anomalies (SSTAs) have tended to be trapped near the date line rather than extending to the American coast as in a classical El Niño–Southern Oscillation (ENSO) composite. Here, the relationship between WWEs and cold tongue warming is revisited using in situ and operational forecast winds and in situ and satellite-based SST. Significant differences are found in the basin-scale zonal wind anomalies associated with WWEs that occurred before and after 1997/98. Although the post-1997/98 composite WWE westerly anomalies are very similar to their predecessors within the WWE regions, conditions east of the WWE regions are different; there are enhanced equatorial easterlies in the post-1997/98 cases. General ocean circulation model experiments are conducted to explore the extent to which the observed changes in the character of post-1997/98 WWEs can explain the recent behavior of cold tongue SSTAs. It is found that the wind differences can account for the changes in the average cold tongue warming associated with pre- and post-1997/98 WWEs.
Abstract
It is well known that some austral summertime subtropical Indian Ocean sea surface temperature (SST) variability correlates with rainfall over certain regions of Africa that depend on rainfall for their economic well-being. Recent studies have determined that this SST variability is at least partially driven by latent heat flux variability, but the mechanism has not been fully described. Here, the mechanism that drives this SST variability is reexamined using analyses of operational air–sea fluxes, ocean mixed layer modeling, and simple atmospheric boundary layer physics. The SST variability of interest is confirmed to be mainly driven by latent heat flux variability, which is shown, for the first time, to be mainly caused by near-surface humidity variability. This humidity variability is then shown to be fundamentally driven by the anomalous meridional advection of water vapor. The meridional wind anomalies of interest are subsequently found to occur when the subtropical atmospheric anticyclone is preferentially located toward one of the sides (east/west) of the basin.
Abstract
It is well known that some austral summertime subtropical Indian Ocean sea surface temperature (SST) variability correlates with rainfall over certain regions of Africa that depend on rainfall for their economic well-being. Recent studies have determined that this SST variability is at least partially driven by latent heat flux variability, but the mechanism has not been fully described. Here, the mechanism that drives this SST variability is reexamined using analyses of operational air–sea fluxes, ocean mixed layer modeling, and simple atmospheric boundary layer physics. The SST variability of interest is confirmed to be mainly driven by latent heat flux variability, which is shown, for the first time, to be mainly caused by near-surface humidity variability. This humidity variability is then shown to be fundamentally driven by the anomalous meridional advection of water vapor. The meridional wind anomalies of interest are subsequently found to occur when the subtropical atmospheric anticyclone is preferentially located toward one of the sides (east/west) of the basin.
Abstract
Multidecadal time series of surface wind observations from tropical Pacific islands have been examined in order to investigate the space and time scales of variability. Climatological monthly means and variances are compared with comparable means and variances derived from ship observations; usually the means agree to within ∼1 m s−1 in speed and ∼10 degrees in direction. Annual and semiannual cycles differ in detail. Island zonal wind variances are often significantly larger, by up to 10 m2 s−2 near the equator between September and December; because of the spatial coherence of the island results, these discrepancies are believed to result from the poor high-frequency sampling typical of ship data. A substantial near-equatorial zonal wind variance maximum is shown to be related to ENSO period variability; excluding ENSO time periods leaves a relatively spatially uniform variance of ∼5 m2 s−2 over a broad region.
The frequency distribution of variance, derived from daily-averaged data, exhibits considerable geographical variation. Within a few degrees of the equator the most energetic zonal wind variability is found in a broad band extending from about 3- to 60-day periods, with maximum at about 10 days; there is also significant interannual power in records located west of 170°W. There is occasionally a local variance maximum in the range of 30- to 60-day periods. Within this near-equatorial region, the meridional wind variance is roughly half the zonal wind variance and is found primarily between about 3-day and 6-day periods and at the annual period. Poleward of about 5 degrees of latitude, the interannual variability in zonal wind diminishes sharply, and the zonal and meridional wind variances become increasingly comparable. The zonal wind energy level in the 3- to 60-day band decreases as one moves farther from the equator, until the more energetic winds typical of subtropical latitudes arise. Coherence calculations typically show zonal wind coherence significant at the 95% level at all energetic periods when islands axe within 200–300 km of each other meridionally, and within 1000–1500 km zonally. The meridional wind tends to be less coherent. A minimal sampling array for tropical surface wind variability in this region should have meridional sampling about every 2° and zonal sampling about every 15° for the zonal wind, and perhaps half these distances for the meridional wind.
Abstract
Multidecadal time series of surface wind observations from tropical Pacific islands have been examined in order to investigate the space and time scales of variability. Climatological monthly means and variances are compared with comparable means and variances derived from ship observations; usually the means agree to within ∼1 m s−1 in speed and ∼10 degrees in direction. Annual and semiannual cycles differ in detail. Island zonal wind variances are often significantly larger, by up to 10 m2 s−2 near the equator between September and December; because of the spatial coherence of the island results, these discrepancies are believed to result from the poor high-frequency sampling typical of ship data. A substantial near-equatorial zonal wind variance maximum is shown to be related to ENSO period variability; excluding ENSO time periods leaves a relatively spatially uniform variance of ∼5 m2 s−2 over a broad region.
The frequency distribution of variance, derived from daily-averaged data, exhibits considerable geographical variation. Within a few degrees of the equator the most energetic zonal wind variability is found in a broad band extending from about 3- to 60-day periods, with maximum at about 10 days; there is also significant interannual power in records located west of 170°W. There is occasionally a local variance maximum in the range of 30- to 60-day periods. Within this near-equatorial region, the meridional wind variance is roughly half the zonal wind variance and is found primarily between about 3-day and 6-day periods and at the annual period. Poleward of about 5 degrees of latitude, the interannual variability in zonal wind diminishes sharply, and the zonal and meridional wind variances become increasingly comparable. The zonal wind energy level in the 3- to 60-day band decreases as one moves farther from the equator, until the more energetic winds typical of subtropical latitudes arise. Coherence calculations typically show zonal wind coherence significant at the 95% level at all energetic periods when islands axe within 200–300 km of each other meridionally, and within 1000–1500 km zonally. The meridional wind tends to be less coherent. A minimal sampling array for tropical surface wind variability in this region should have meridional sampling about every 2° and zonal sampling about every 15° for the zonal wind, and perhaps half these distances for the meridional wind.
