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Abstract
The dynamical processes associated with block evolution are investigated by analyzing a GCM run, forced with perpetual January conditions. The core of the analysis lies on the temporal evolution of the blocks and on vorticity budget terms obtained from appropriate compositing procedures on a 350-mb model output. The results from the budget analysis are examined with barotropic model experiments, which allow the investigation of the influence of an individual dynamical process on block evolution.
Results are presented for two composite blocks, one close to the Atlantic storm track and the other farther downstream. Although these two blocks are found to develop differently, they share the following characteristics. During the decay linear processes dominate, and the high- and low-frequency eddy fluxes contribute equally toward prolonging the lifetime of the blocks by 2 to 3 days. While the time average of the budget yields results that are consistent with previous diagnostic studies, it is shown that such an approach exaggerates the role played by high-frequency eddies.
The barotropic model experiments show that the nonlinear self-interaction of the composite block anomaly plays a minimal role in the block evolution. It is the remaining part of the composite low-frequency eddy flux that contributes significantly toward the block evolution, indicating that case-to-case variability of the individual blocking events can be substantial, and that the nonlinearity of a slowly moving, nonsteady component of the flow plays an important role for the individual blocking events. The model experiments also demonstrate that the effect of divergence is crucial for correctly reproducing the structure of the blocking high. The implications of these results, as they apply to some of the prominent blocking theories, are also discussed.
Abstract
The dynamical processes associated with block evolution are investigated by analyzing a GCM run, forced with perpetual January conditions. The core of the analysis lies on the temporal evolution of the blocks and on vorticity budget terms obtained from appropriate compositing procedures on a 350-mb model output. The results from the budget analysis are examined with barotropic model experiments, which allow the investigation of the influence of an individual dynamical process on block evolution.
Results are presented for two composite blocks, one close to the Atlantic storm track and the other farther downstream. Although these two blocks are found to develop differently, they share the following characteristics. During the decay linear processes dominate, and the high- and low-frequency eddy fluxes contribute equally toward prolonging the lifetime of the blocks by 2 to 3 days. While the time average of the budget yields results that are consistent with previous diagnostic studies, it is shown that such an approach exaggerates the role played by high-frequency eddies.
The barotropic model experiments show that the nonlinear self-interaction of the composite block anomaly plays a minimal role in the block evolution. It is the remaining part of the composite low-frequency eddy flux that contributes significantly toward the block evolution, indicating that case-to-case variability of the individual blocking events can be substantial, and that the nonlinearity of a slowly moving, nonsteady component of the flow plays an important role for the individual blocking events. The model experiments also demonstrate that the effect of divergence is crucial for correctly reproducing the structure of the blocking high. The implications of these results, as they apply to some of the prominent blocking theories, are also discussed.
Abstract
California experienced record-setting drought from 2012 to 2017. Based on both seasonal forecast models and historical associations, there was widespread expectation that the major El Niño event of 2015/16 would result in increased winter-season precipitation and break the drought. However, the 2015/16 winter rainy season ultimately resulted in slightly below-average precipitation and the drought continued. In this work we analyze data from both observations and seasonal forecasts made as part of the North American Multi-Model Ensemble (NMME) to better understand the general relationship between El Niño and U.S. West Coast rainfall, focusing on Southern California (SOCAL) rainfall, Pacific Northwest (PNW) rainfall, and the 2015/16 event. We find that while there is a statistically significant positive correlation between El Niño events and the SOCAL and PNW rainfall anomalies, this relationship explains at most one-third of the observed variance. Examination of hindcasts from the NMME demonstrates that the models are capable of accurately reproducing this observed correlation between tropical Pacific sea surface temperatures and California rainfall when information from the individual ensemble members is retained. However, focusing on the multimodel ensemble mean, which deliberately reduces the influence of unpredicted variability, drastically overestimates the strength of this relationship. Our analysis demonstrates that much of the winter rainfall variability along the U.S. West Coast is dominated by unpredicted variations in the 200-hPa height field and that this same unpredicted variability was largely responsible for the unexpectedly dry conditions in 2015/16.
Abstract
California experienced record-setting drought from 2012 to 2017. Based on both seasonal forecast models and historical associations, there was widespread expectation that the major El Niño event of 2015/16 would result in increased winter-season precipitation and break the drought. However, the 2015/16 winter rainy season ultimately resulted in slightly below-average precipitation and the drought continued. In this work we analyze data from both observations and seasonal forecasts made as part of the North American Multi-Model Ensemble (NMME) to better understand the general relationship between El Niño and U.S. West Coast rainfall, focusing on Southern California (SOCAL) rainfall, Pacific Northwest (PNW) rainfall, and the 2015/16 event. We find that while there is a statistically significant positive correlation between El Niño events and the SOCAL and PNW rainfall anomalies, this relationship explains at most one-third of the observed variance. Examination of hindcasts from the NMME demonstrates that the models are capable of accurately reproducing this observed correlation between tropical Pacific sea surface temperatures and California rainfall when information from the individual ensemble members is retained. However, focusing on the multimodel ensemble mean, which deliberately reduces the influence of unpredicted variability, drastically overestimates the strength of this relationship. Our analysis demonstrates that much of the winter rainfall variability along the U.S. West Coast is dominated by unpredicted variations in the 200-hPa height field and that this same unpredicted variability was largely responsible for the unexpectedly dry conditions in 2015/16.
Abstract
A linear-stochastic model is applied to the 10-day low-pass streamfunction field at 300, 500, and 850 mb for 40 winter seasons of Northern Hemisphere NCEP–NCAR reanalysis data. The linear operator is derived from the observed multilevel covariances, allowing for statistical representation of nonlinear processes. While all empirical normal modes of the system are decaying, increase in the streamfunction variance is possible through nonmodal growth. When the evolution of the streamfunction field following the optimal perturbation is predicted, the Pacific–North American teleconnection pattern (PNA) is found to be the most probable state of the atmosphere. Sixty-eight percent (70%) of positive (negative) PNA events are found to follow high projections onto the leading optimal, suggesting the PNA arises through constructive interference between the decaying modes and may be treated as a linear response to Gaussian white noise stochastic forcing. Implications for PNA timescale and onset mechanisms are also discussed.
Abstract
A linear-stochastic model is applied to the 10-day low-pass streamfunction field at 300, 500, and 850 mb for 40 winter seasons of Northern Hemisphere NCEP–NCAR reanalysis data. The linear operator is derived from the observed multilevel covariances, allowing for statistical representation of nonlinear processes. While all empirical normal modes of the system are decaying, increase in the streamfunction variance is possible through nonmodal growth. When the evolution of the streamfunction field following the optimal perturbation is predicted, the Pacific–North American teleconnection pattern (PNA) is found to be the most probable state of the atmosphere. Sixty-eight percent (70%) of positive (negative) PNA events are found to follow high projections onto the leading optimal, suggesting the PNA arises through constructive interference between the decaying modes and may be treated as a linear response to Gaussian white noise stochastic forcing. Implications for PNA timescale and onset mechanisms are also discussed.
Abstract
The annular mode simulated by an atmospheric general circulation model with a zonally symmetric lower boundary is investigated. The annular mode, defined as the leading empirical orthogonal function (EOF) of the zonal-mean surface pressure, has a meridional structure consisting of a north–south dipole, similar to observations. The leading EOF of the zonally varying surface pressure has the same meridional structure and is also zonally symmetric. Because the lower boundary is zonally symmetric, composites of days with high projection onto the mode have, to within sampling error, no zonal structure. However, individual periods during which the zonal-mean surface pressure projects strongly onto the annular mode are dominated by zonally localized structures. Thus, the model annular mode represents a zonally homogeneous distribution of zonally localized events with a similar meridional structure, rather than a zonally symmetric mode of variability per se. Individual annular-mode events typically show a north–south teleconnection pattern whose meridional structure closely resembles the annular mode and whose zonal structure extends 60° to 90° in longitude, with a slight northwest–southeast offset between its centers of action. Similar structures are found for EOFs calculated over a subset of the domain corresponding to the width of the Atlantic basin. The spatial structure of both the teleconnection pattern and the regional EOFs resemble the observed North Atlantic Oscillation (NAO) pattern.
Abstract
The annular mode simulated by an atmospheric general circulation model with a zonally symmetric lower boundary is investigated. The annular mode, defined as the leading empirical orthogonal function (EOF) of the zonal-mean surface pressure, has a meridional structure consisting of a north–south dipole, similar to observations. The leading EOF of the zonally varying surface pressure has the same meridional structure and is also zonally symmetric. Because the lower boundary is zonally symmetric, composites of days with high projection onto the mode have, to within sampling error, no zonal structure. However, individual periods during which the zonal-mean surface pressure projects strongly onto the annular mode are dominated by zonally localized structures. Thus, the model annular mode represents a zonally homogeneous distribution of zonally localized events with a similar meridional structure, rather than a zonally symmetric mode of variability per se. Individual annular-mode events typically show a north–south teleconnection pattern whose meridional structure closely resembles the annular mode and whose zonal structure extends 60° to 90° in longitude, with a slight northwest–southeast offset between its centers of action. Similar structures are found for EOFs calculated over a subset of the domain corresponding to the width of the Atlantic basin. The spatial structure of both the teleconnection pattern and the regional EOFs resemble the observed North Atlantic Oscillation (NAO) pattern.
Abstract
The influence of zonally asymmetric boundary conditions on the leading modes of variability in a suite of atmospheric general circulation models is investigated. The set of experiments consists of nine model configurations, with varying degrees and types of zonal asymmetry in their boundary conditions. The structure of the leading EOF varies with the zonal asymmetry of the base state for each model configuration. In particular, a close relationship is found between the structure of the EOF and the model storm tracks. An approximately linear relationship is found to hold between the magnitude of the zonal asymmetry of the leading EOF and of the storm tracks in the models. It is shown that this linear relationship extends to the observations.
One-point correlation maps centered on the regions where the EOFs reach their maximum amplitude show similar structures for all configurations. These structures consist of a north–south dipole, resembling the observed structure of the North Atlantic Oscillation (NAO). They are significantly more zonally localized than the leading EOF, but do resemble one-point correlation maps and sector EOFs calculated for a simulation with zonally symmetric boundary conditions. Thus, the leading EOF for each simulation appears to represent the longitudinal distribution of zonally localized NAO-like patterns. This longitudinal distribution appears to be tied to the distribution of high-frequency eddies, as represented by the storm tracks. A detailed momentum budget for each case confirms that high-frequency eddies play a crucial role in producing the NAO-like patterns. Other dynamical processes also play an important role, but vary with the details of the simulation.
Abstract
The influence of zonally asymmetric boundary conditions on the leading modes of variability in a suite of atmospheric general circulation models is investigated. The set of experiments consists of nine model configurations, with varying degrees and types of zonal asymmetry in their boundary conditions. The structure of the leading EOF varies with the zonal asymmetry of the base state for each model configuration. In particular, a close relationship is found between the structure of the EOF and the model storm tracks. An approximately linear relationship is found to hold between the magnitude of the zonal asymmetry of the leading EOF and of the storm tracks in the models. It is shown that this linear relationship extends to the observations.
One-point correlation maps centered on the regions where the EOFs reach their maximum amplitude show similar structures for all configurations. These structures consist of a north–south dipole, resembling the observed structure of the North Atlantic Oscillation (NAO). They are significantly more zonally localized than the leading EOF, but do resemble one-point correlation maps and sector EOFs calculated for a simulation with zonally symmetric boundary conditions. Thus, the leading EOF for each simulation appears to represent the longitudinal distribution of zonally localized NAO-like patterns. This longitudinal distribution appears to be tied to the distribution of high-frequency eddies, as represented by the storm tracks. A detailed momentum budget for each case confirms that high-frequency eddies play a crucial role in producing the NAO-like patterns. Other dynamical processes also play an important role, but vary with the details of the simulation.
Abstract
Recent studies arising from both statistical analysis and dynamical disease models indicate that there is a link between the incidence of cholera, a paradigmatic waterborne bacterial illness endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). Cholera incidence typically increases following boreal winter El Niño events for the period 1973–2001. Observational and model analyses find that Bangladesh summer rainfall is enhanced following winter El Niño events, providing a plausible physical link between El Niño and cholera incidence. However, rainfall and cholera incidence do not increase following every winter El Niño event. Substantial variations in Bangladesh precipitation also occur in simulations in which identical sea surface temperature (SST) anomalies are prescribed in the central and eastern tropical Pacific. Bangladesh summer precipitation is thus not uniquely determined by forcing from the tropical Pacific, with significant implications for predictions of cholera risk.
Nonparametric statistical analysis is used to identify regions of SST anomalies associated with variations in Bangladesh rainfall in an ensemble of pacemaker simulations. The authors find that differences in the response of Bangladesh summer precipitation to winter El Niño events are strongly associated with the persistence of warm SST anomalies in the central Pacific. Also there are significant differences in the SST patterns associated with positive and negative Bangladesh rainfall anomalies, indicating that the response is not fully linear. SST anomalies in the Indian Ocean also modulate the influence of the tropical Pacific, with colder Indian Ocean SST tending to enhance Bangladesh precipitation relative to warm Indian Ocean SST for identical conditions in the central and eastern tropical Pacific. This influence is not fully linear. Forecasts of Bangladesh rainfall and cholera risk may thus be improved by considering the Niño-3 and Niño-4 indices separately, rather than the Niño-3.4 index alone. Additional skill may also be gained by incorporating information on the southeast Indian Ocean and by updating the forecast with information on the evolution of the SST anomalies into spring.
Abstract
Recent studies arising from both statistical analysis and dynamical disease models indicate that there is a link between the incidence of cholera, a paradigmatic waterborne bacterial illness endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). Cholera incidence typically increases following boreal winter El Niño events for the period 1973–2001. Observational and model analyses find that Bangladesh summer rainfall is enhanced following winter El Niño events, providing a plausible physical link between El Niño and cholera incidence. However, rainfall and cholera incidence do not increase following every winter El Niño event. Substantial variations in Bangladesh precipitation also occur in simulations in which identical sea surface temperature (SST) anomalies are prescribed in the central and eastern tropical Pacific. Bangladesh summer precipitation is thus not uniquely determined by forcing from the tropical Pacific, with significant implications for predictions of cholera risk.
Nonparametric statistical analysis is used to identify regions of SST anomalies associated with variations in Bangladesh rainfall in an ensemble of pacemaker simulations. The authors find that differences in the response of Bangladesh summer precipitation to winter El Niño events are strongly associated with the persistence of warm SST anomalies in the central Pacific. Also there are significant differences in the SST patterns associated with positive and negative Bangladesh rainfall anomalies, indicating that the response is not fully linear. SST anomalies in the Indian Ocean also modulate the influence of the tropical Pacific, with colder Indian Ocean SST tending to enhance Bangladesh precipitation relative to warm Indian Ocean SST for identical conditions in the central and eastern tropical Pacific. This influence is not fully linear. Forecasts of Bangladesh rainfall and cholera risk may thus be improved by considering the Niño-3 and Niño-4 indices separately, rather than the Niño-3.4 index alone. Additional skill may also be gained by incorporating information on the southeast Indian Ocean and by updating the forecast with information on the evolution of the SST anomalies into spring.
Abstract
Recent studies arising from both statistical analysis and dynamical disease models demonstrate a link between the incidence of cholera, a paradigmatic waterborne bacterial illness endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). The physical significance of this relationship was investigated by examining links between the regional climate of Bangladesh and western Pacific sea surface temperatures (SST) associated with ENSO using a pacemaker configuration of the Center for Ocean–Land–Atmosphere Studies atmospheric general circulation model. The global SST response to ENSO SST anomalies in the western Pacific alone is found to be relatively weak and unrealistic when compared to observations, indicating that the global response to ENSO is driven primarily by anomalies in the central and eastern tropical Pacific. Despite the weak global response to western Pacific SST anomalies, however, a signal is found in summer rainfall over India and Bangladesh. Specifically, reduced rainfall typically follows winter El Niño events. In the absence of warm SST anomalies in the eastern Pacific, cold anomalies in the western Pacific produce a La Niña–like response in the model circulation. Cold SST anomalies suppress convection over the western Pacific. Large-scale convergence shifts into the eastern Indian Ocean and modifies the summer monsoon circulation over India and Bangladesh.
The probabilistic relationship between Bangladesh rainfall and SST is also explored using a nonparametric statistical technique. Decreased rainfall is strongly associated with cold SST in the western Pacific, while associations between SST and enhanced rainfall are substantially weaker. Also found are strong associations between rainfall and SST in the Indian Ocean in the absence of differences in forcing from the western Pacific. It thus appears that the Indian Ocean may represent an independent source of predictability for the monsoon and cholera risk. Likewise, under certain circumstances, the western Pacific may also exert a significant influence on Bangladesh rainfall and cholera risk.
Abstract
Recent studies arising from both statistical analysis and dynamical disease models demonstrate a link between the incidence of cholera, a paradigmatic waterborne bacterial illness endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). The physical significance of this relationship was investigated by examining links between the regional climate of Bangladesh and western Pacific sea surface temperatures (SST) associated with ENSO using a pacemaker configuration of the Center for Ocean–Land–Atmosphere Studies atmospheric general circulation model. The global SST response to ENSO SST anomalies in the western Pacific alone is found to be relatively weak and unrealistic when compared to observations, indicating that the global response to ENSO is driven primarily by anomalies in the central and eastern tropical Pacific. Despite the weak global response to western Pacific SST anomalies, however, a signal is found in summer rainfall over India and Bangladesh. Specifically, reduced rainfall typically follows winter El Niño events. In the absence of warm SST anomalies in the eastern Pacific, cold anomalies in the western Pacific produce a La Niña–like response in the model circulation. Cold SST anomalies suppress convection over the western Pacific. Large-scale convergence shifts into the eastern Indian Ocean and modifies the summer monsoon circulation over India and Bangladesh.
The probabilistic relationship between Bangladesh rainfall and SST is also explored using a nonparametric statistical technique. Decreased rainfall is strongly associated with cold SST in the western Pacific, while associations between SST and enhanced rainfall are substantially weaker. Also found are strong associations between rainfall and SST in the Indian Ocean in the absence of differences in forcing from the western Pacific. It thus appears that the Indian Ocean may represent an independent source of predictability for the monsoon and cholera risk. Likewise, under certain circumstances, the western Pacific may also exert a significant influence on Bangladesh rainfall and cholera risk.
Abstract
In early 2018, due in part to a severe and extended meteorological drought, Cape Town was at risk of being one of the first major metropolitan areas in the world to run out of water. The magnitude of the crisis was exacerbated by the fact that such a prolonged and severe drought was both unanticipated and unpredicted. In this work, we analyze data from both observations and seasonal forecasts made as part of the North American Multimodel Ensemble (NMME) to better understand the predictability of rainfall in the Cape Town (CT) region. We find that there are statistically significant correlations between observed CT rainfall and sea surface temperatures in the tropical Atlantic (∼0.45) as well as a pattern of 200-mb geopotential height (z200) anomalies resembling the Southern Annular Mode (SAM; ∼0.4). Examination of hindcasts from the NMME demonstrates that the models accurately reproduce the observed correlation between CT rainfall and z200 anomalies. However, they fail to reproduce correlations between CT rainfall and the tropical South Atlantic. Decomposition of the correlations into contributions from predictable and unpredictable components indicates that CT rainfall in the models is dominated by unpredicted atmospheric variability (correlation ∼ 0.84) relative to predicted (correlation ∼ 0.14), which may be related to the failure to simulate the connection with the tropical Atlantic.
Significance Statement
Water crises are occurring with increasing severity and frequency around the globe. The ability to accurately forecast wet season rainfall would be invaluable to water managers and other decision-makers. Here, we explore the reasons behind the failure of a suite of operational seasonal forecast models to accurately predict rainfall in the Cape Town region of South Africa.
Abstract
In early 2018, due in part to a severe and extended meteorological drought, Cape Town was at risk of being one of the first major metropolitan areas in the world to run out of water. The magnitude of the crisis was exacerbated by the fact that such a prolonged and severe drought was both unanticipated and unpredicted. In this work, we analyze data from both observations and seasonal forecasts made as part of the North American Multimodel Ensemble (NMME) to better understand the predictability of rainfall in the Cape Town (CT) region. We find that there are statistically significant correlations between observed CT rainfall and sea surface temperatures in the tropical Atlantic (∼0.45) as well as a pattern of 200-mb geopotential height (z200) anomalies resembling the Southern Annular Mode (SAM; ∼0.4). Examination of hindcasts from the NMME demonstrates that the models accurately reproduce the observed correlation between CT rainfall and z200 anomalies. However, they fail to reproduce correlations between CT rainfall and the tropical South Atlantic. Decomposition of the correlations into contributions from predictable and unpredictable components indicates that CT rainfall in the models is dominated by unpredicted atmospheric variability (correlation ∼ 0.84) relative to predicted (correlation ∼ 0.14), which may be related to the failure to simulate the connection with the tropical Atlantic.
Significance Statement
Water crises are occurring with increasing severity and frequency around the globe. The ability to accurately forecast wet season rainfall would be invaluable to water managers and other decision-makers. Here, we explore the reasons behind the failure of a suite of operational seasonal forecast models to accurately predict rainfall in the Cape Town region of South Africa.
Abstract
Recent studies arising from both statistical analysis and dynamical disease models indicate that there is a link between incidence of cholera, a paradigmatic waterborne bacterial disease (WBD) endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). However, a physical mechanism explaining this relationship has not yet been established. A regionally coupled, or “pacemaker,” configuration of the Center for Ocean–Land–Atmosphere Studies atmospheric general circulation model is used to investigate links between sea surface temperature in the central and eastern tropical Pacific and the regional climate of Bangladesh. It is found that enhanced precipitation tends to follow winter El Niño events in both the model and observations, providing a plausible physical mechanism by which ENSO could influence cholera in Bangladesh.
The enhanced precipitation in the model arises from a modification of the summer monsoon circulation over India and Bangladesh. Westerly wind anomalies over land to the west of Bangladesh lead to increased convergence in the zonal wind field and hence increased moisture convergence and rainfall. This change in circulation results from the tropics-wide warming in the model following a winter El Niño event. These results suggest that improved forecasting of cholera incidence may be possible through the use of climate predictions.
Abstract
Recent studies arising from both statistical analysis and dynamical disease models indicate that there is a link between incidence of cholera, a paradigmatic waterborne bacterial disease (WBD) endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). However, a physical mechanism explaining this relationship has not yet been established. A regionally coupled, or “pacemaker,” configuration of the Center for Ocean–Land–Atmosphere Studies atmospheric general circulation model is used to investigate links between sea surface temperature in the central and eastern tropical Pacific and the regional climate of Bangladesh. It is found that enhanced precipitation tends to follow winter El Niño events in both the model and observations, providing a plausible physical mechanism by which ENSO could influence cholera in Bangladesh.
The enhanced precipitation in the model arises from a modification of the summer monsoon circulation over India and Bangladesh. Westerly wind anomalies over land to the west of Bangladesh lead to increased convergence in the zonal wind field and hence increased moisture convergence and rainfall. This change in circulation results from the tropics-wide warming in the model following a winter El Niño event. These results suggest that improved forecasting of cholera incidence may be possible through the use of climate predictions.
