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Abstract
Regional interdecadal variability, on subbasin to basin scales, is shown to be a robust feature of the post–World War II (WWII) historical temperature record, even after a recently proposed bias correction to XBT fall rates is applied. This study shows that the previously reported strong regional variability is generally unaffected by this correction, even though the interdecadal variability in the most recently published estimates of global ocean heat content is much reduced after a correction is applied. Following methods used in previous trend analysis work, estimates of interdecadal trends are calculated for individual regions of the global ocean where there are sufficient data. Spatial maps of temperature trends for the surface and three subsurface depths (50, 100, and 300 m) are presented, with both bias-corrected and uncorrected data trends at 100 and 300 m shown for comparison. In the upper two depths and at the surface, interdecadal variability is shown to be present and strong in most of the analysis regions. At 100 m, the differences between trends based on bias-corrected versus uncorrected data are small, and barely distinguishable for much of the ocean analyzed. There are more differences at 300 m between the two data treatments, but large-scale patterns are still present in the bias-corrected trends, especially where the trends are stronger.
Given the sampling issues discussed in previous works, the presence of strong interdecadal variability on smaller scales raises concerns that global interdecadal variability in the historical record still may not be properly resolved.
Abstract
Regional interdecadal variability, on subbasin to basin scales, is shown to be a robust feature of the post–World War II (WWII) historical temperature record, even after a recently proposed bias correction to XBT fall rates is applied. This study shows that the previously reported strong regional variability is generally unaffected by this correction, even though the interdecadal variability in the most recently published estimates of global ocean heat content is much reduced after a correction is applied. Following methods used in previous trend analysis work, estimates of interdecadal trends are calculated for individual regions of the global ocean where there are sufficient data. Spatial maps of temperature trends for the surface and three subsurface depths (50, 100, and 300 m) are presented, with both bias-corrected and uncorrected data trends at 100 and 300 m shown for comparison. In the upper two depths and at the surface, interdecadal variability is shown to be present and strong in most of the analysis regions. At 100 m, the differences between trends based on bias-corrected versus uncorrected data are small, and barely distinguishable for much of the ocean analyzed. There are more differences at 300 m between the two data treatments, but large-scale patterns are still present in the bias-corrected trends, especially where the trends are stronger.
Given the sampling issues discussed in previous works, the presence of strong interdecadal variability on smaller scales raises concerns that global interdecadal variability in the historical record still may not be properly resolved.
Abstract
The unexpected halt of warm sea surface temperature anomaly (SSTA) growth in 2014 and development of a major El Niño in 2015 has drawn attention to our ability to understand and predict El Niño development. Wind stress–forced ocean model studies have satisfactorily reproduced observed equatorial Pacific SSTAs during periods when data return from the TAO/TRITON buoy network was high. Unfortunately, TAO/TRITON data return in 2014 was poor. To study 2014 SSTA development, the observed wind gaps must be filled. The hypothesis that subseasonal wind events provided the dominant driver of observed waveguide SSTA development in 2014 and 2015 is used along with the available buoy winds to construct an oceanic waveguide-wide surface stress field of westerly wind events (WWEs) and easterly wind surges (EWSs). It is found that the observed Niño-3.4 SSTA development in 2014 and 2015 can thereby be reproduced satisfactorily. Previous 2014 studies used other wind fields and reached differing conclusions about the importance of WWEs and EWSs. Experiment results herein help explain these inconsistencies, and clarify the relative importance of WWEs and EWSs. It is found that the springtime surplus of WWEs and summertime balance between WWEs and EWSs (yielding small net wind stress anomaly) accounts for the early development and midyear reversal of El Niño–like SSTA development in 2014. A strong abundance of WWEs in 2015 accounts for the rapid SSTA warming observed then. Accurately forecasting equatorial Pacific SSTA in years like 2014 and 2015 may require learning to predict WWE and EWS occurrence characteristics.
Abstract
The unexpected halt of warm sea surface temperature anomaly (SSTA) growth in 2014 and development of a major El Niño in 2015 has drawn attention to our ability to understand and predict El Niño development. Wind stress–forced ocean model studies have satisfactorily reproduced observed equatorial Pacific SSTAs during periods when data return from the TAO/TRITON buoy network was high. Unfortunately, TAO/TRITON data return in 2014 was poor. To study 2014 SSTA development, the observed wind gaps must be filled. The hypothesis that subseasonal wind events provided the dominant driver of observed waveguide SSTA development in 2014 and 2015 is used along with the available buoy winds to construct an oceanic waveguide-wide surface stress field of westerly wind events (WWEs) and easterly wind surges (EWSs). It is found that the observed Niño-3.4 SSTA development in 2014 and 2015 can thereby be reproduced satisfactorily. Previous 2014 studies used other wind fields and reached differing conclusions about the importance of WWEs and EWSs. Experiment results herein help explain these inconsistencies, and clarify the relative importance of WWEs and EWSs. It is found that the springtime surplus of WWEs and summertime balance between WWEs and EWSs (yielding small net wind stress anomaly) accounts for the early development and midyear reversal of El Niño–like SSTA development in 2014. A strong abundance of WWEs in 2015 accounts for the rapid SSTA warming observed then. Accurately forecasting equatorial Pacific SSTA in years like 2014 and 2015 may require learning to predict WWE and EWS occurrence characteristics.
Abstract
El Niño and La Niña seasonal weather anomaly associations provide a useful basis for winter forecasting over the North American regions where they are sufficiently strong in amplitude and consistent in character from one event to another. When the associations during La Niña are different than El Niño, however, the obvious quasi-linear-statistical approach to modeling them has serious shortcomings. The linear approach of L’Heureux et al. is critiqued here based on observed land surface temperature and tropospheric circulation associations over North America. The La Niña associations are quite different in pattern from their El Niño counterparts. The El Niño associations dominate the statistics. This causes the linear approach to produce results that are inconsistent with the observed La Niña–averaged associations. Further, nearly all the useful North American associations have been contributed by the subset of El Niño and La Niña years that are identifiable by an outgoing longwave radiation (OLR) El Niño index and a distinct OLR La Niña index. The remaining “non-OLR events” exhibit winter weather anomalies with large event-to-event variability and contribute very little statistical utility to the composites. The result is that the linear analysis framework is sufficiently unable to fit the observations as to question its utility for studying La Niña and El Niño seasonal temperature and atmospheric circulation relationships. An OLR-event based approach that treats La Niña and El Niño separately is significantly more consistent with, and offers an improved statistical model for, the observed relationships.
Abstract
El Niño and La Niña seasonal weather anomaly associations provide a useful basis for winter forecasting over the North American regions where they are sufficiently strong in amplitude and consistent in character from one event to another. When the associations during La Niña are different than El Niño, however, the obvious quasi-linear-statistical approach to modeling them has serious shortcomings. The linear approach of L’Heureux et al. is critiqued here based on observed land surface temperature and tropospheric circulation associations over North America. The La Niña associations are quite different in pattern from their El Niño counterparts. The El Niño associations dominate the statistics. This causes the linear approach to produce results that are inconsistent with the observed La Niña–averaged associations. Further, nearly all the useful North American associations have been contributed by the subset of El Niño and La Niña years that are identifiable by an outgoing longwave radiation (OLR) El Niño index and a distinct OLR La Niña index. The remaining “non-OLR events” exhibit winter weather anomalies with large event-to-event variability and contribute very little statistical utility to the composites. The result is that the linear analysis framework is sufficiently unable to fit the observations as to question its utility for studying La Niña and El Niño seasonal temperature and atmospheric circulation relationships. An OLR-event based approach that treats La Niña and El Niño separately is significantly more consistent with, and offers an improved statistical model for, the observed relationships.
Abstract
The fundamental importance of near-equatorial zonal wind stress in the evolution of the tropical Pacific Ocean’s seasonal cycle and El Niño–Southern Oscillation (ENSO) events is well known. It has been two decades since the TAO/TRITON buoy array was deployed, in part to provide accurate surface wind observations across the Pacific waveguide. It is timely to revisit the impact of TAO/TRITON winds on our ability to simulate and thereby understand the evolution of sea surface temperature (SST) in this region. This work shows that forced ocean model simulations of SST anomalies (SSTAs) during the periods with a reasonably high buoy data return rate can reproduce the major elements of SSTA variability during ENSO events using a wind stress field computed from TAO/TRITON observations only. This demonstrates that the buoy array usefully fulfills its waveguide-wind-measurement purpose. Comparison of several reanalysis wind fields commonly used in recent ENSO studies with the TAO/TRITON observations reveals substantial biases in the reanalyses that cause substantial errors in the variability and trends of the reanalysis-forced SST simulations. In particular, the negative trend in ERA-Interim is much larger and the NCEP–NCAR Reanalysis-1 and NCEP–DOE Reanalysis-2 variability much less than seen in the TAO/TRITON wind observations. There are also mean biases. Thus, even with the TAO/TRITON observations available for assimilation into these wind products, there remain oceanically important differences. The reanalyses would be much more useful for ENSO and tropical Pacific climate change study if they would more effectively assimilate the TAO/TRITON observations.
Abstract
The fundamental importance of near-equatorial zonal wind stress in the evolution of the tropical Pacific Ocean’s seasonal cycle and El Niño–Southern Oscillation (ENSO) events is well known. It has been two decades since the TAO/TRITON buoy array was deployed, in part to provide accurate surface wind observations across the Pacific waveguide. It is timely to revisit the impact of TAO/TRITON winds on our ability to simulate and thereby understand the evolution of sea surface temperature (SST) in this region. This work shows that forced ocean model simulations of SST anomalies (SSTAs) during the periods with a reasonably high buoy data return rate can reproduce the major elements of SSTA variability during ENSO events using a wind stress field computed from TAO/TRITON observations only. This demonstrates that the buoy array usefully fulfills its waveguide-wind-measurement purpose. Comparison of several reanalysis wind fields commonly used in recent ENSO studies with the TAO/TRITON observations reveals substantial biases in the reanalyses that cause substantial errors in the variability and trends of the reanalysis-forced SST simulations. In particular, the negative trend in ERA-Interim is much larger and the NCEP–NCAR Reanalysis-1 and NCEP–DOE Reanalysis-2 variability much less than seen in the TAO/TRITON wind observations. There are also mean biases. Thus, even with the TAO/TRITON observations available for assimilation into these wind products, there remain oceanically important differences. The reanalyses would be much more useful for ENSO and tropical Pacific climate change study if they would more effectively assimilate the TAO/TRITON observations.
Abstract
This study shows that, since 1979 when outgoing longwave radiation (OLR) observations became reliably available, most of the useful U.S. seasonal weather impact of El Niño events is associated with the few events identified by the behavior of outgoing longwave radiation (OLR) over the eastern equatorial Pacific (“OLR–El Niño events”). These events produce composite seasonal regional weather anomalies that are 95% statistically significant and robust (associated with almost all events). Results also show that there are very few statistically significant seasonal weather anomalies, even at the 80% level, associated with the non-OLR–El Niño events. A major enhancement of statistical seasonal forecasting skill over the contiguous United States appears possible by incorporating these results. It is essential to respect that not all events commonly labeled as El Niño events lead to statistically useful U.S. seasonal forecast skill.
Abstract
This study shows that, since 1979 when outgoing longwave radiation (OLR) observations became reliably available, most of the useful U.S. seasonal weather impact of El Niño events is associated with the few events identified by the behavior of outgoing longwave radiation (OLR) over the eastern equatorial Pacific (“OLR–El Niño events”). These events produce composite seasonal regional weather anomalies that are 95% statistically significant and robust (associated with almost all events). Results also show that there are very few statistically significant seasonal weather anomalies, even at the 80% level, associated with the non-OLR–El Niño events. A major enhancement of statistical seasonal forecasting skill over the contiguous United States appears possible by incorporating these results. It is essential to respect that not all events commonly labeled as El Niño events lead to statistically useful U.S. seasonal forecast skill.
Abstract
The processes responsible for the onset of La Niña events have not received the same attention as those responsible for the onset of El Niño events, for which westerly wind events (WWEs) in the tropical Pacific have been identified as important contributors. Results here show that synoptic-scale surface easterly wind surges (EWSs) play an important role in the onset of La Niña events, akin to the role of WWEs in the onset of El Niño events. It is found that EWSs are a substantial component of zonal wind stress variance along the equatorial Pacific. Using reanalysis wind stress fields, validated against buoy measurements, 340 EWS events are identified between 1986 and 2012. Their distributions in space, time, and El Niño–Southern Oscillation (ENSO) state are described. About 150 EWSs occur during ENSO-neutral conditions, during the months associated with La Niña initiation and growth (April–December). Composites of changes in sea surface temperature anomaly (SSTA) following these ~150 events show statistically significant cooling (0.1°–0.4°C) along the oceanic waveguide that persists for 2–3 months following the EWSs. Experiments with EWS forcing of an ocean general circulation model show SSTA patterns like those in the observations. It is suggested that EWSs play an important role in the onset of La Niña waveguide surface cooling and deserve additional study.
Abstract
The processes responsible for the onset of La Niña events have not received the same attention as those responsible for the onset of El Niño events, for which westerly wind events (WWEs) in the tropical Pacific have been identified as important contributors. Results here show that synoptic-scale surface easterly wind surges (EWSs) play an important role in the onset of La Niña events, akin to the role of WWEs in the onset of El Niño events. It is found that EWSs are a substantial component of zonal wind stress variance along the equatorial Pacific. Using reanalysis wind stress fields, validated against buoy measurements, 340 EWS events are identified between 1986 and 2012. Their distributions in space, time, and El Niño–Southern Oscillation (ENSO) state are described. About 150 EWSs occur during ENSO-neutral conditions, during the months associated with La Niña initiation and growth (April–December). Composites of changes in sea surface temperature anomaly (SSTA) following these ~150 events show statistically significant cooling (0.1°–0.4°C) along the oceanic waveguide that persists for 2–3 months following the EWSs. Experiments with EWS forcing of an ocean general circulation model show SSTA patterns like those in the observations. It is suggested that EWSs play an important role in the onset of La Niña waveguide surface cooling and deserve additional study.
Abstract
El Niño–Southern Oscillation (ENSO) events are associated with particular seasonal weather anomalies in many regions around the planet. When the statistical links are sufficiently strong, ENSO state information can provide useful seasonal forecasts with varying lead times. However, using conventional sea surface temperature or sea level pressure indices to characterize ENSO state leads to many instances of limited forecast skill (e.g., years identified as El Niño or La Niña with weather anomalies unlike the average), even in regions where there is considerable ENSO-associated anomaly, on average. Using outgoing longwave radiation (OLR) conditions to characterize ENSO state identifies a subset of the conventional ENSO years, called OLR El Niño and OLR La Niña years herein. Treating the OLR-identified subset of years differently can both usefully strengthen the level of statistical significance in the average (composite) and also greatly reduce the year-to-year deviations in the composite precipitation anomalies. On average, over most of the planet, the non-OLR El Niño and non-OLR La Niña years have much more limited statistical utility for precipitation. The OLR El Niño and OLR La Niña indices typically identify years in time to be of use to boreal wintertime and later seasonal forecasting efforts, meaning that paying attention to tropical Pacific OLR conditions may offer more than just a diagnostic tool. Understanding better how large-scale environmental conditions during ENSO events determine OLR behavior (and deep atmospheric convection) will lead to improved seasonal precipitation forecasts for many areas.
Abstract
El Niño–Southern Oscillation (ENSO) events are associated with particular seasonal weather anomalies in many regions around the planet. When the statistical links are sufficiently strong, ENSO state information can provide useful seasonal forecasts with varying lead times. However, using conventional sea surface temperature or sea level pressure indices to characterize ENSO state leads to many instances of limited forecast skill (e.g., years identified as El Niño or La Niña with weather anomalies unlike the average), even in regions where there is considerable ENSO-associated anomaly, on average. Using outgoing longwave radiation (OLR) conditions to characterize ENSO state identifies a subset of the conventional ENSO years, called OLR El Niño and OLR La Niña years herein. Treating the OLR-identified subset of years differently can both usefully strengthen the level of statistical significance in the average (composite) and also greatly reduce the year-to-year deviations in the composite precipitation anomalies. On average, over most of the planet, the non-OLR El Niño and non-OLR La Niña years have much more limited statistical utility for precipitation. The OLR El Niño and OLR La Niña indices typically identify years in time to be of use to boreal wintertime and later seasonal forecasting efforts, meaning that paying attention to tropical Pacific OLR conditions may offer more than just a diagnostic tool. Understanding better how large-scale environmental conditions during ENSO events determine OLR behavior (and deep atmospheric convection) will lead to improved seasonal precipitation forecasts for many areas.
Abstract
Globally, the seasonal cycle is the largest single component of observed sea surface temperature (SST) variability, yet it is still not fully understood. Herein, the degree to which the structure of the seasonal cycle of Southern Hemisphere SST can be explained by the present understanding of surface fluxes and upper-ocean physics is examined. It has long been known that the annual range of Southern Hemisphere SST is largest in the midlatitudes, despite the fact that the annual range of net surface heat flux peaks well poleward of the SST peak. The reasons for this discrepancy (“falloff of the annual range of SST”) are determined here through analysis of net surface heat flux estimates, observed SST, and mixed layer depth data, and results from experiments using two different one-dimensional ocean models. Results show that (i) the classical explanations for the structure of the annual range of SST in the Southern Hemisphere are incomplete, (ii) current estimates of surface heat flux and mixed layer depth can be used to accurately reproduce the observed annual range of SST, and (iii) the prognostic mixed layer models used here often fail to adequately reproduce the seasonal cycle at higher latitudes, despite performing remarkably well in other regions. This suggests that more work is necessary to understand the changes of upper-ocean dynamics that occur with latitude.
Abstract
Globally, the seasonal cycle is the largest single component of observed sea surface temperature (SST) variability, yet it is still not fully understood. Herein, the degree to which the structure of the seasonal cycle of Southern Hemisphere SST can be explained by the present understanding of surface fluxes and upper-ocean physics is examined. It has long been known that the annual range of Southern Hemisphere SST is largest in the midlatitudes, despite the fact that the annual range of net surface heat flux peaks well poleward of the SST peak. The reasons for this discrepancy (“falloff of the annual range of SST”) are determined here through analysis of net surface heat flux estimates, observed SST, and mixed layer depth data, and results from experiments using two different one-dimensional ocean models. Results show that (i) the classical explanations for the structure of the annual range of SST in the Southern Hemisphere are incomplete, (ii) current estimates of surface heat flux and mixed layer depth can be used to accurately reproduce the observed annual range of SST, and (iii) the prognostic mixed layer models used here often fail to adequately reproduce the seasonal cycle at higher latitudes, despite performing remarkably well in other regions. This suggests that more work is necessary to understand the changes of upper-ocean dynamics that occur with latitude.
Abstract
It is shown that space–time smoothed outgoing longwave radiation (OLR) indices of equatorial Pacific seasonal variability can give an interestingly different perspective on El Niño than is obtained from sea surface temperature (SST) indices or the Southern Oscillation index (SOI). In particular, the index defined by averaging over an eastern-central region exhibits strong event like character—more so than in any other El Niño–Southern Oscillation (ENSO) warm-phase index known to the authors. Although the historical record for OLR is much shorter than for SST or SOI, OLR offers a direct connection to anomalous atmospheric heating. It is suggested that the years identified as events by this OLR index deserve particular recognition; and it is noteworthy that they all meet the criteria for “El Niño” years. Other years, whose warm-ENSO status differs depending upon the index favored, are not particularly distinctive from an OLR perspective, and a case could be made that either the other years do not deserve special classification or that they should be identified as different from the OLR-distinguished El Niño years.
Abstract
It is shown that space–time smoothed outgoing longwave radiation (OLR) indices of equatorial Pacific seasonal variability can give an interestingly different perspective on El Niño than is obtained from sea surface temperature (SST) indices or the Southern Oscillation index (SOI). In particular, the index defined by averaging over an eastern-central region exhibits strong event like character—more so than in any other El Niño–Southern Oscillation (ENSO) warm-phase index known to the authors. Although the historical record for OLR is much shorter than for SST or SOI, OLR offers a direct connection to anomalous atmospheric heating. It is suggested that the years identified as events by this OLR index deserve particular recognition; and it is noteworthy that they all meet the criteria for “El Niño” years. Other years, whose warm-ENSO status differs depending upon the index favored, are not particularly distinctive from an OLR perspective, and a case could be made that either the other years do not deserve special classification or that they should be identified as different from the OLR-distinguished El Niño years.
Abstract
Based on examination of 10 yr of 10-m winds and wind anomalies from European Centre for Medium-Range Weather Forecasts (ECWMF) analysis, definitions for westerly wind events (WWEs) of eight different types are proposed. The authors construct a composite for each type of event, show that a simple propagating Gaussian model satisfactorily describes the evolution of zonal wind anomaly for each type of event, and determine the scales of each composite event by fitting the model to each composite. The authors discuss the WWEs that occurred during the Tropical Oceans Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) intensive observing period (IOP) and show the extent to which these composite events are able to reproduce the major westerly wind features of the IOP. The frequency of occurrence of each type of WWE for each year of this record and by calendar month are described; the authors find several types of events are negatively correlated with the annual mean troup Southern Oscillation index (SOI), and that the stronger WWEs often have a statistically significant seasonality. Several instances of widespread westerly wind anomaly are identified and described, but these “mega”-WWEs have few features in common. Although the authors’ composites underestimate the peak amplitude of many WWEs and cannot always accurately represent the time evolution of each WWE, the authors believe that they offer a useful framework for representing the sort of westerly wind variability that occurs in the western and central tropical Pacific and can provide a basis for further study of the importance of such winds in the climatological and interannual variability of this part of the World Ocean.
Abstract
Based on examination of 10 yr of 10-m winds and wind anomalies from European Centre for Medium-Range Weather Forecasts (ECWMF) analysis, definitions for westerly wind events (WWEs) of eight different types are proposed. The authors construct a composite for each type of event, show that a simple propagating Gaussian model satisfactorily describes the evolution of zonal wind anomaly for each type of event, and determine the scales of each composite event by fitting the model to each composite. The authors discuss the WWEs that occurred during the Tropical Oceans Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) intensive observing period (IOP) and show the extent to which these composite events are able to reproduce the major westerly wind features of the IOP. The frequency of occurrence of each type of WWE for each year of this record and by calendar month are described; the authors find several types of events are negatively correlated with the annual mean troup Southern Oscillation index (SOI), and that the stronger WWEs often have a statistically significant seasonality. Several instances of widespread westerly wind anomaly are identified and described, but these “mega”-WWEs have few features in common. Although the authors’ composites underestimate the peak amplitude of many WWEs and cannot always accurately represent the time evolution of each WWE, the authors believe that they offer a useful framework for representing the sort of westerly wind variability that occurs in the western and central tropical Pacific and can provide a basis for further study of the importance of such winds in the climatological and interannual variability of this part of the World Ocean.
