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- Author or Editor: Michelle L'Heureux x
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Abstract
There is increasing evidence that the Madden–Julian oscillation (MJO) modifies the mid- to high-latitude circulation and, in particular, appears to have a relationship to the leading mode of extratropical variability, the Arctic Oscillation (AO). In this study, new insights into the observed similarities between the MJO and the AO are explored. It is shown that the eastward progression of the convectively active phase of the MJO is associated with a corresponding shift in the tendency and sign of the AO index. Moreover, the AO and the MJO share several analogous features not only in the global circulation, but also in surface temperature fields. Also, the AO is linked to a pattern of eastward-propagating MJO-like variability in the tropics that is partially reproduced in free runs of the NCEP Climate Forecast System (CFS) model. Finally, it is shown that the structure of the AO, as defined by the leading mode in the 1000-hPa geopotential height field, is significantly altered based on the phase of the MJO.
Abstract
There is increasing evidence that the Madden–Julian oscillation (MJO) modifies the mid- to high-latitude circulation and, in particular, appears to have a relationship to the leading mode of extratropical variability, the Arctic Oscillation (AO). In this study, new insights into the observed similarities between the MJO and the AO are explored. It is shown that the eastward progression of the convectively active phase of the MJO is associated with a corresponding shift in the tendency and sign of the AO index. Moreover, the AO and the MJO share several analogous features not only in the global circulation, but also in surface temperature fields. Also, the AO is linked to a pattern of eastward-propagating MJO-like variability in the tropics that is partially reproduced in free runs of the NCEP Climate Forecast System (CFS) model. Finally, it is shown that the structure of the AO, as defined by the leading mode in the 1000-hPa geopotential height field, is significantly altered based on the phase of the MJO.
Abstract
There is increasing evidence indicating that the climate response to variations in the El Niño–Southern Oscillation (ENSO) includes not only thermally forced zonal wind anomalies in the subtropics but also eddy-driven zonal wind anomalies that extend into the mid–high latitudes of both hemispheres. In this study, new insights into the observed seasonally varying signature of ENSO in the extratropical zonal-mean circulation are provided and the associated linkages with the dominant patterns of extratropical variability are examined.
The zonal-mean extratropical atmospheric response to ENSO is characterized by two principal features: an equivalent barotropic dipole in the Southern Hemisphere (SH) zonal-mean zonal flow with centers of action located near ∼40° and ∼60° during austral summer, and a weaker, but analogous, dipole in the Northern Hemisphere (NH) with centers of action located near ∼25° and ∼45° during early and late boreal winter. Both structures are accompanied by eddy momentum flux anomalies that exhibit a remarkable degree of hemispheric symmetry. In the SH, the extratropical signature of ENSO projects strongly onto the primary mode of large-scale variability, the southern annular mode (SAM). During the austral summer, roughly 25% of the temporal variability in the SAM is linearly related to fluctuations in the ENSO cycle. An analogous relationship is not observed in association with the principal mode of climate variability in the NH, the northern annular mode (NAM).
It is argued that the seasonally varying impact of ENSO on the extratropical circulation is consistent with the impact of the thermally forced subtropical wind anomalies on the dissipation of equatorward-propagating wave activity at subtropical latitudes.
Abstract
There is increasing evidence indicating that the climate response to variations in the El Niño–Southern Oscillation (ENSO) includes not only thermally forced zonal wind anomalies in the subtropics but also eddy-driven zonal wind anomalies that extend into the mid–high latitudes of both hemispheres. In this study, new insights into the observed seasonally varying signature of ENSO in the extratropical zonal-mean circulation are provided and the associated linkages with the dominant patterns of extratropical variability are examined.
The zonal-mean extratropical atmospheric response to ENSO is characterized by two principal features: an equivalent barotropic dipole in the Southern Hemisphere (SH) zonal-mean zonal flow with centers of action located near ∼40° and ∼60° during austral summer, and a weaker, but analogous, dipole in the Northern Hemisphere (NH) with centers of action located near ∼25° and ∼45° during early and late boreal winter. Both structures are accompanied by eddy momentum flux anomalies that exhibit a remarkable degree of hemispheric symmetry. In the SH, the extratropical signature of ENSO projects strongly onto the primary mode of large-scale variability, the southern annular mode (SAM). During the austral summer, roughly 25% of the temporal variability in the SAM is linearly related to fluctuations in the ENSO cycle. An analogous relationship is not observed in association with the principal mode of climate variability in the NH, the northern annular mode (NAM).
It is argued that the seasonally varying impact of ENSO on the extratropical circulation is consistent with the impact of the thermally forced subtropical wind anomalies on the dissipation of equatorward-propagating wave activity at subtropical latitudes.
Abstract
Two questions are addressed in this paper: whether ENSO can be adequately characterized by simple, seasonally invariant indices and whether the time series of a single component—SST or OLR—provides a sufficiently complete representation of ENSO for the purpose of quantifying U.S. climate impacts. Here, ENSO is defined as the leading mode of seasonally varying canonical correlation analysis (CCA) between anomalies of tropical Pacific SST and outgoing longwave radiation (OLR). The CCA reveals that the strongest regions of coupling are mostly invariant as a function of season and correspond to an OLR region located in the central Pacific Ocean (CP-OLR) and an SST region in the eastern Pacific that coincides with the Niño-3 region. In a linear context, the authors explore whether the use of a combined index of these SST and OLR regions explains additional variance of North American temperature and precipitation anomalies beyond that described by using a single index alone. Certain seasons and regions benefit from the use of a combined index. In particular, a combined index describes more variability in winter/spring precipitation and summer temperature.
Abstract
Two questions are addressed in this paper: whether ENSO can be adequately characterized by simple, seasonally invariant indices and whether the time series of a single component—SST or OLR—provides a sufficiently complete representation of ENSO for the purpose of quantifying U.S. climate impacts. Here, ENSO is defined as the leading mode of seasonally varying canonical correlation analysis (CCA) between anomalies of tropical Pacific SST and outgoing longwave radiation (OLR). The CCA reveals that the strongest regions of coupling are mostly invariant as a function of season and correspond to an OLR region located in the central Pacific Ocean (CP-OLR) and an SST region in the eastern Pacific that coincides with the Niño-3 region. In a linear context, the authors explore whether the use of a combined index of these SST and OLR regions explains additional variance of North American temperature and precipitation anomalies beyond that described by using a single index alone. Certain seasons and regions benefit from the use of a combined index. In particular, a combined index describes more variability in winter/spring precipitation and summer temperature.
Abstract
The relation between the El Niño–Southern Oscillation (ENSO) and California precipitation has been studied extensively and plays a prominent role in seasonal forecasting. However, a wide range of precipitation outcomes on seasonal time scales are possible, even during extreme ENSO states. Here, we investigate prediction skill and its origins on subseasonal time scales. Model predictions of California precipitation are examined using Subseasonal Experiment (SubX) reforecasts for the period 1999–2016, focusing on those from the Flow-Following Icosahedral Model (FIM). Two potential sources of subseasonal predictability are examined: the tropical Pacific Ocean and upper-level zonal winds near California. In both observations and forecasts, the Niño-3.4 index exhibits a weak and insignificant relationship with daily to monthly averages of California precipitation. Likewise, model tropical sea surface temperature and outgoing longwave radiation show only minimal relations with California precipitation forecasts, providing no evidence that flavors of El Niño or tropical modes substantially contribute to the success or failure of subseasonal forecasts. On the other hand, an index for upper-level zonal winds is strongly correlated with precipitation in observations and forecasts, across averaging windows and lead times. The wind index is related to ENSO, but the correlation between the wind index and precipitation remains even after accounting for ENSO phase. Intriguingly, the Niño-3.4 index and California precipitation show a slight but robust negative statistical relation after accounting for the wind index.
Abstract
The relation between the El Niño–Southern Oscillation (ENSO) and California precipitation has been studied extensively and plays a prominent role in seasonal forecasting. However, a wide range of precipitation outcomes on seasonal time scales are possible, even during extreme ENSO states. Here, we investigate prediction skill and its origins on subseasonal time scales. Model predictions of California precipitation are examined using Subseasonal Experiment (SubX) reforecasts for the period 1999–2016, focusing on those from the Flow-Following Icosahedral Model (FIM). Two potential sources of subseasonal predictability are examined: the tropical Pacific Ocean and upper-level zonal winds near California. In both observations and forecasts, the Niño-3.4 index exhibits a weak and insignificant relationship with daily to monthly averages of California precipitation. Likewise, model tropical sea surface temperature and outgoing longwave radiation show only minimal relations with California precipitation forecasts, providing no evidence that flavors of El Niño or tropical modes substantially contribute to the success or failure of subseasonal forecasts. On the other hand, an index for upper-level zonal winds is strongly correlated with precipitation in observations and forecasts, across averaging windows and lead times. The wind index is related to ENSO, but the correlation between the wind index and precipitation remains even after accounting for ENSO phase. Intriguingly, the Niño-3.4 index and California precipitation show a slight but robust negative statistical relation after accounting for the wind index.
ABSTRACT
The relationship between the warm water volume (WWV) ENSO precursor and ENSO SST weakened substantially after ~2000, coinciding with a degradation in dynamical model ENSO prediction skill. It is important to understand the drivers of the equatorial thermocline temperature variations and their linkage to ENSO onsets. In this study, a set of ocean reanalyses is employed to assess factors responsible for the variation of the equatorial Pacific Ocean thermocline during 1982–2019. Off-equatorial thermocline temperature anomalies carried equatorward by the mean meridional currents associated with Pacific tropical cells are shown to play an important role in modulating the central equatorial thermocline variations, which is rarely discussed in the literature. Further, ENSO events are delineated into two groups based on precursor mechanisms: the western equatorial Pacific type (WEP) ENSO, when the central equatorial thermocline is mainly influenced by the zonal propagation of anomalies from the western Pacific, and the off-equatorial central Pacific (OCP) ENSO, when off-equatorial central thermocline anomalies play the primary role. WWV is found to precede all WEP ENSO events by 6–9 months, while the correlation is substantially lower for OCP ENSO events. In contrast, the central tropical Pacific (CTP) precursor, which includes off-equatorial thermocline signals, has a very robust lead correlation with the OCP ENSO. Most OCP ENSO events are found to follow the same ENSO conditions, and the number of OCP ENSO events increases substantially since the start of the twenty-first century. These results highlight the importance of monitoring off-equatorial subsurface preconditions for ENSO prediction and to understand multiyear ENSO.
ABSTRACT
The relationship between the warm water volume (WWV) ENSO precursor and ENSO SST weakened substantially after ~2000, coinciding with a degradation in dynamical model ENSO prediction skill. It is important to understand the drivers of the equatorial thermocline temperature variations and their linkage to ENSO onsets. In this study, a set of ocean reanalyses is employed to assess factors responsible for the variation of the equatorial Pacific Ocean thermocline during 1982–2019. Off-equatorial thermocline temperature anomalies carried equatorward by the mean meridional currents associated with Pacific tropical cells are shown to play an important role in modulating the central equatorial thermocline variations, which is rarely discussed in the literature. Further, ENSO events are delineated into two groups based on precursor mechanisms: the western equatorial Pacific type (WEP) ENSO, when the central equatorial thermocline is mainly influenced by the zonal propagation of anomalies from the western Pacific, and the off-equatorial central Pacific (OCP) ENSO, when off-equatorial central thermocline anomalies play the primary role. WWV is found to precede all WEP ENSO events by 6–9 months, while the correlation is substantially lower for OCP ENSO events. In contrast, the central tropical Pacific (CTP) precursor, which includes off-equatorial thermocline signals, has a very robust lead correlation with the OCP ENSO. Most OCP ENSO events are found to follow the same ENSO conditions, and the number of OCP ENSO events increases substantially since the start of the twenty-first century. These results highlight the importance of monitoring off-equatorial subsurface preconditions for ENSO prediction and to understand multiyear ENSO.
Abstract
Using multiple observational and model datasets, the authors document a strengthening relationship between boreal winter sea surface temperature anomalies (SSTAs) in the western North Pacific (WNP) and the development of the El Niño–Southern Oscillation (ENSO) in the following year. The increased WNP–ENSO association emerged in the mid-twentieth century and has grown through the present, reaching correlation coefficients as high as ~0.70 in recent decades. Fully coupled climate experiments with the Community Earth System Model, version 1 (CESM1), replicate the WNP–ENSO association and indicate that greenhouse gases (GHGs) are largely responsible for this observed increase. The authors speculate that shifts in the location of the largest positive SST trends between the subtropical and tropical western Pacific impact the low-level circulation in a manner that reinforces the link between the WNP and the development of ENSO. A strengthened GHG-driven relationship with the WNP provides an example of how anthropogenic climate change may directly influence one of the most prominent patterns of natural climate variability, ENSO, and potentially improve the skill of intraseasonal-to-interannual climate prediction.
Abstract
Using multiple observational and model datasets, the authors document a strengthening relationship between boreal winter sea surface temperature anomalies (SSTAs) in the western North Pacific (WNP) and the development of the El Niño–Southern Oscillation (ENSO) in the following year. The increased WNP–ENSO association emerged in the mid-twentieth century and has grown through the present, reaching correlation coefficients as high as ~0.70 in recent decades. Fully coupled climate experiments with the Community Earth System Model, version 1 (CESM1), replicate the WNP–ENSO association and indicate that greenhouse gases (GHGs) are largely responsible for this observed increase. The authors speculate that shifts in the location of the largest positive SST trends between the subtropical and tropical western Pacific impact the low-level circulation in a manner that reinforces the link between the WNP and the development of ENSO. A strengthened GHG-driven relationship with the WNP provides an example of how anthropogenic climate change may directly influence one of the most prominent patterns of natural climate variability, ENSO, and potentially improve the skill of intraseasonal-to-interannual climate prediction.
Abstract
Forecast climatologies are used to remove systematic errors from forecasts and to express forecasts as departures from normal. Forecast climatologies are computed from hindcasts by various averaging, smoothing, and interpolation procedures. Here the Climate Forecast System, version 2 (CFSv2), monthly forecast climatology provided by the NCEP Environmental Modeling Center (EMC) is shown to be biased in the sense of systematically differing from the hindcasts that are used to compute it. These biases, which are unexpected, are primarily due to fitting harmonics to hindcast data that have been organized in a particular format, which on careful inspection is seen to introduce discontinuities. Biases in the monthly near-surface temperature forecast climatology reach 2°C over North America for March targets and start times at the end of January. Biases in the monthly Niño-3.4 forecast climatology are also largest for start times near calendar-month boundaries. A further undesirable consequence of this fitting procedure is that the EMC forecast climatology varies discontinuously with lead time for fixed target month. Two alternative methods for computing the forecast climatology are proposed and illustrated. The proposed methods more accurately fit the hindcast data and provide a clearer representation of the CFSv2 model climate drift toward lower Niño-3.4 values for starts in March and April and toward higher Niño-3.4 values for starts in June, July, and August.
Abstract
Forecast climatologies are used to remove systematic errors from forecasts and to express forecasts as departures from normal. Forecast climatologies are computed from hindcasts by various averaging, smoothing, and interpolation procedures. Here the Climate Forecast System, version 2 (CFSv2), monthly forecast climatology provided by the NCEP Environmental Modeling Center (EMC) is shown to be biased in the sense of systematically differing from the hindcasts that are used to compute it. These biases, which are unexpected, are primarily due to fitting harmonics to hindcast data that have been organized in a particular format, which on careful inspection is seen to introduce discontinuities. Biases in the monthly near-surface temperature forecast climatology reach 2°C over North America for March targets and start times at the end of January. Biases in the monthly Niño-3.4 forecast climatology are also largest for start times near calendar-month boundaries. A further undesirable consequence of this fitting procedure is that the EMC forecast climatology varies discontinuously with lead time for fixed target month. Two alternative methods for computing the forecast climatology are proposed and illustrated. The proposed methods more accurately fit the hindcast data and provide a clearer representation of the CFSv2 model climate drift toward lower Niño-3.4 values for starts in March and April and toward higher Niño-3.4 values for starts in June, July, and August.
Real-time model predictions of ENSO conditions during the 2002–11 period are evaluated and compared to skill levels documented in studies of the 1990s. ENSO conditions are represented by the Niño- 3.4 SST index in the east-central tropical Pacific. The skills of 20 prediction models (12 dynamical, 8 statistical) are examined. Results indicate skills somewhat lower than those found for the less advanced models of the 1980s and 1990s. Using hindcasts spanning 1981–2011, this finding is explained by the relatively greater predictive challenge posed by the 2002–11 period and suggests that decadal variations in the character of ENSO variability are a greater skill-determining factor than the steady but gradual trend toward improved ENSO prediction science and models. After adjusting for the varying difficulty level, the skills of 2002–11 are slightly higher than those of earlier decades. Unlike earlier results, the average skill of dynamical models slightly, but statistically significantly, exceeds that of statistical models for start times just before the middle of the year when prediction has proven most difficult. The greater skill of dynamical models is largely attributable to the subset of dynamical models with the most advanced, highresolution, fully coupled ocean–atmosphere prediction systems using sophisticated data assimilation systems and large ensembles. This finding suggests that additional advances in skill remain likely, with the expected implementation of better physics, numeric and assimilation schemes, finer resolution, and larger ensemble sizes.
Real-time model predictions of ENSO conditions during the 2002–11 period are evaluated and compared to skill levels documented in studies of the 1990s. ENSO conditions are represented by the Niño- 3.4 SST index in the east-central tropical Pacific. The skills of 20 prediction models (12 dynamical, 8 statistical) are examined. Results indicate skills somewhat lower than those found for the less advanced models of the 1980s and 1990s. Using hindcasts spanning 1981–2011, this finding is explained by the relatively greater predictive challenge posed by the 2002–11 period and suggests that decadal variations in the character of ENSO variability are a greater skill-determining factor than the steady but gradual trend toward improved ENSO prediction science and models. After adjusting for the varying difficulty level, the skills of 2002–11 are slightly higher than those of earlier decades. Unlike earlier results, the average skill of dynamical models slightly, but statistically significantly, exceeds that of statistical models for start times just before the middle of the year when prediction has proven most difficult. The greater skill of dynamical models is largely attributable to the subset of dynamical models with the most advanced, highresolution, fully coupled ocean–atmosphere prediction systems using sophisticated data assimilation systems and large ensembles. This finding suggests that additional advances in skill remain likely, with the expected implementation of better physics, numeric and assimilation schemes, finer resolution, and larger ensemble sizes.
