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- Author or Editor: Thomas Reichler x
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Abstract
Sudden stratospheric warmings (SSWs) are rare in the Southern Hemisphere (SH), making it difficult to study possible precursors or subsequent impacts. Using a multimillennial coupled climate model simulation producing 161 SSWs in the SH, we present a detailed study of their life cycle. We show that SH SSWs are predominantly displacement events forced by wave-1 planetary waves, and that a surface signature similar to the negative phase of the Southern Annular Mode (SAM) is detectable up to two months before the onset date, but there is a tendency for a transition from wave 1 before to zonally symmetric anomalies after onset. We identify a strong weakening of the Amundsen Sea low as one of the most prominent precursors, which weakens the climatological wave-2 and wave-3 stationary waves and strengthens wave-1 forcing. Compared to their northern counterparts, SH SSWs generally have a longer time scale, and while there is evidence of pre-onset forcing related to tropical sea surface temperatures, the Indian Ocean dipole is more important than El Niño–Southern Oscillation.
Significance Statement
Sudden stratospheric warmings (SSWs) are extreme events where the winter polar stratosphere warms within a few days to temperatures usually only experienced in summer. These events are rare in the Southern Hemisphere. Therefore, both the observational record and standard climate model simulations are not enough to understand how SSWs develop, or how they might change surface weather. Here we use very long global climate simulations that produce a large number of SSWs in the Southern Hemisphere to study the development and impact of these events. This includes possible precursors as well as the influence they have on surface weather after they occur.
Abstract
Sudden stratospheric warmings (SSWs) are rare in the Southern Hemisphere (SH), making it difficult to study possible precursors or subsequent impacts. Using a multimillennial coupled climate model simulation producing 161 SSWs in the SH, we present a detailed study of their life cycle. We show that SH SSWs are predominantly displacement events forced by wave-1 planetary waves, and that a surface signature similar to the negative phase of the Southern Annular Mode (SAM) is detectable up to two months before the onset date, but there is a tendency for a transition from wave 1 before to zonally symmetric anomalies after onset. We identify a strong weakening of the Amundsen Sea low as one of the most prominent precursors, which weakens the climatological wave-2 and wave-3 stationary waves and strengthens wave-1 forcing. Compared to their northern counterparts, SH SSWs generally have a longer time scale, and while there is evidence of pre-onset forcing related to tropical sea surface temperatures, the Indian Ocean dipole is more important than El Niño–Southern Oscillation.
Significance Statement
Sudden stratospheric warmings (SSWs) are extreme events where the winter polar stratosphere warms within a few days to temperatures usually only experienced in summer. These events are rare in the Southern Hemisphere. Therefore, both the observational record and standard climate model simulations are not enough to understand how SSWs develop, or how they might change surface weather. Here we use very long global climate simulations that produce a large number of SSWs in the Southern Hemisphere to study the development and impact of these events. This includes possible precursors as well as the influence they have on surface weather after they occur.
Abstract
Projections of future climate change are increasingly based on the output of many different models. Typically, the mean over all model simulations is considered as the optimal prediction, with the underlying assumption that different models provide statistically independent information evenly distributed around the true state. However, there is reason to believe that this is not the best assumption. Coupled models are of comparable complexity and are constructed in similar ways. Some models share parts of the same code and some models are even developed at the same center. Therefore, the limitations of these models tend to be fairly similar, contributing to the well-known problem of common model biases and possibly to an unrealistically small spread in the outcomes of model predictions.
This study attempts to quantify the extent of this problem by asking how many models there effectively are and how to best determine this number. Quantifying the effective number of models is achieved by evaluating 24 state-of-the-art models and their ability to simulate broad aspects of twentieth-century climate. Using two different approaches, the amount of unique information in the ensemble is calculated and the effective ensemble size is found to be much smaller than the actual number of models. As more models are included in an ensemble, the amount of new information diminishes in proportion. Furthermore, this reduction is found to go beyond the problem of “same center” models and systemic similarities are seen to exist across all models. The results suggest that current methodologies for the interpretation of multimodel ensembles may lead to overly confident climate predictions.
Abstract
Projections of future climate change are increasingly based on the output of many different models. Typically, the mean over all model simulations is considered as the optimal prediction, with the underlying assumption that different models provide statistically independent information evenly distributed around the true state. However, there is reason to believe that this is not the best assumption. Coupled models are of comparable complexity and are constructed in similar ways. Some models share parts of the same code and some models are even developed at the same center. Therefore, the limitations of these models tend to be fairly similar, contributing to the well-known problem of common model biases and possibly to an unrealistically small spread in the outcomes of model predictions.
This study attempts to quantify the extent of this problem by asking how many models there effectively are and how to best determine this number. Quantifying the effective number of models is achieved by evaluating 24 state-of-the-art models and their ability to simulate broad aspects of twentieth-century climate. Using two different approaches, the amount of unique information in the ensemble is calculated and the effective ensemble size is found to be much smaller than the actual number of models. As more models are included in an ensemble, the amount of new information diminishes in proportion. Furthermore, this reduction is found to go beyond the problem of “same center” models and systemic similarities are seen to exist across all models. The results suggest that current methodologies for the interpretation of multimodel ensembles may lead to overly confident climate predictions.
Abstract
The frequency of stratospheric sudden warming events (SSWs) is an important characteristic of the coupled stratosphere–troposphere system. However, many modern climate models are unable to reproduce the observed SSW frequency. A previous study suggested that one of the reasons could be the momentum damping at the surface. The goal of the present study is to understand what determines the climatological SSW frequency and how the surface damping comes into play. To this end, we conduct a parameter sweep with an idealized model, using a wide range of values for the surface damping. It is found that the SSW frequency is a strong and nonlinear function of the surface damping. Various tropospheric and stratospheric factors are identified to link the surface damping to the SSW frequency. The factors include the magnitude of the surface winds, the meridional and vertical wind shear, the synoptic eddy activity in the troposphere, the transient wave activity flux at the lower stratosphere, and the strength of the stratospheric polar vortex. Mathematical–statistical modeling, informed by the parameter sweep, is used to quantify how the different factors relate to each other. This successfully reproduces the complex variations of the SSW frequency with the surface damping seen in the parameter sweep. The results may help in explaining some of the difficulties that climate models have in simulating the observed SSW frequency.
Abstract
The frequency of stratospheric sudden warming events (SSWs) is an important characteristic of the coupled stratosphere–troposphere system. However, many modern climate models are unable to reproduce the observed SSW frequency. A previous study suggested that one of the reasons could be the momentum damping at the surface. The goal of the present study is to understand what determines the climatological SSW frequency and how the surface damping comes into play. To this end, we conduct a parameter sweep with an idealized model, using a wide range of values for the surface damping. It is found that the SSW frequency is a strong and nonlinear function of the surface damping. Various tropospheric and stratospheric factors are identified to link the surface damping to the SSW frequency. The factors include the magnitude of the surface winds, the meridional and vertical wind shear, the synoptic eddy activity in the troposphere, the transient wave activity flux at the lower stratosphere, and the strength of the stratospheric polar vortex. Mathematical–statistical modeling, informed by the parameter sweep, is used to quantify how the different factors relate to each other. This successfully reproduces the complex variations of the SSW frequency with the surface damping seen in the parameter sweep. The results may help in explaining some of the difficulties that climate models have in simulating the observed SSW frequency.
Abstract
The sensitivity to initial and boundary conditions of monthly mean tropical long-range forecasts (1–14 weeks) during Northern Hemisphere winter is studied with a numerical model. Five predictability experiments with different combinations of initial conditions and prescribed ocean boundary conditions are conducted in order to investigate the temporal and spatial characteristics of the perfect model forecast skill. It is shown that initial conditions dominate a tropical forecast during the first 3 weeks and that they influence a forecast for at least 8 weeks. The initial condition effect is strongest over the Eastern Hemisphere and during years when the El Niño–Southern Oscillation (ENSO) phenomenon is weak. The relatively long sensitivity to initial conditions is related to a complex combination of dynamic and thermodynamic effects, and to positive internal feedbacks of large-scale convective anomalies. At lead times of more than 3 weeks, boundary forcing is the main contributor to tropical predictability. This effect is particularly strong over the Western Hemisphere and during ENSO. Using persisted instead of observed sea surface temperatures leads to useful forecast results only over the Western Hemisphere and during ENSO.
Abstract
The sensitivity to initial and boundary conditions of monthly mean tropical long-range forecasts (1–14 weeks) during Northern Hemisphere winter is studied with a numerical model. Five predictability experiments with different combinations of initial conditions and prescribed ocean boundary conditions are conducted in order to investigate the temporal and spatial characteristics of the perfect model forecast skill. It is shown that initial conditions dominate a tropical forecast during the first 3 weeks and that they influence a forecast for at least 8 weeks. The initial condition effect is strongest over the Eastern Hemisphere and during years when the El Niño–Southern Oscillation (ENSO) phenomenon is weak. The relatively long sensitivity to initial conditions is related to a complex combination of dynamic and thermodynamic effects, and to positive internal feedbacks of large-scale convective anomalies. At lead times of more than 3 weeks, boundary forcing is the main contributor to tropical predictability. This effect is particularly strong over the Western Hemisphere and during ENSO. Using persisted instead of observed sea surface temperatures leads to useful forecast results only over the Western Hemisphere and during ENSO.
Abstract
It is suggested that the slow evolution of the tropical Madden–Julian oscillation (MJO) has the potential to improve the predictability of tropical and extratropical circulation systems at lead times beyond 2 weeks. In practice, however, the MJO phenomenon is extremely difficult to predict because of the lack of good observations, problems with ocean forecasts, and well-known model deficiencies. In this study, the potential skill in forecasting tropical intraseasonal variability is investigated by eliminating all those errors. This is accomplished by conducting five ensemble predictability experiments with a complex general circulation model and by verifying them under the perfect model assumption. The experiments are forced with different combinations of initial and boundary conditions to explore their sensitivity to uncertainties in those conditions.
When “perfect” initial and boundary conditions are provided, the model produces a realistic climatology and variability as compared to reanalysis, although the spectral peak of the simulated MJO is too broad. The effect of initial conditions is noticeable out to about 40 days. The quality of the boundary conditions is crucial at all lead times. The small but positive correlations at very long lead times are related to intraseasonal variability of tropical sea surface temperatures (SSTs). When model, initial, and boundary conditions are all perfect, the useful forecast skill of intraseasonal variability is about 4 weeks. Predictability is insensitive to the El Niño–Southern Oscillation (ENSO) phenomenon, but it is enhanced during years when the intraseasonal oscillation is more active.
The results provide evidence that the MJO must be understood as a coupled system. As a consequence, it is concluded that further progress in the long-range predictability effort may require the use of fully interactive ocean models.
Abstract
It is suggested that the slow evolution of the tropical Madden–Julian oscillation (MJO) has the potential to improve the predictability of tropical and extratropical circulation systems at lead times beyond 2 weeks. In practice, however, the MJO phenomenon is extremely difficult to predict because of the lack of good observations, problems with ocean forecasts, and well-known model deficiencies. In this study, the potential skill in forecasting tropical intraseasonal variability is investigated by eliminating all those errors. This is accomplished by conducting five ensemble predictability experiments with a complex general circulation model and by verifying them under the perfect model assumption. The experiments are forced with different combinations of initial and boundary conditions to explore their sensitivity to uncertainties in those conditions.
When “perfect” initial and boundary conditions are provided, the model produces a realistic climatology and variability as compared to reanalysis, although the spectral peak of the simulated MJO is too broad. The effect of initial conditions is noticeable out to about 40 days. The quality of the boundary conditions is crucial at all lead times. The small but positive correlations at very long lead times are related to intraseasonal variability of tropical sea surface temperatures (SSTs). When model, initial, and boundary conditions are all perfect, the useful forecast skill of intraseasonal variability is about 4 weeks. Predictability is insensitive to the El Niño–Southern Oscillation (ENSO) phenomenon, but it is enhanced during years when the intraseasonal oscillation is more active.
The results provide evidence that the MJO must be understood as a coupled system. As a consequence, it is concluded that further progress in the long-range predictability effort may require the use of fully interactive ocean models.
Abstract
The climatological frequency of stratospheric sudden warming events (SSWs) is an important dynamical characteristic of the extratropical stratosphere. However, modern climate models have difficulties in simulating this frequency, with many models either considerably under- or overestimating the observational estimates. Past research has found that models with a higher upper lid tend to simulate a higher and more realistic number of SSWs. The present study revisits this issue and investigates causes for biases in the simulated SSW frequency from the CMIP5 and CMIP6 models. It is found that variations in the frequency are closely related to 1) the strength of the polar vortex and 2) the upward-propagating wave activity in the stratosphere. While it is difficult to explain the variations in the polar vortex strength from the available model output, the stratospheric wave activity is influenced by different aspects of the climatological mean state of the atmosphere in the lower stratosphere. We further find that models with a finer vertical resolution in the stratosphere are overall more realistic: vertical resolution is associated with a smaller cold bias above the extratropical tropopause, more upward-propagating wave activity in the lower stratosphere, and a higher frequency of SSWs. We conclude that not only a high model lid but also a fine vertical resolution in the stratosphere is important for simulating the dynamical variability of the stratosphere.
Abstract
The climatological frequency of stratospheric sudden warming events (SSWs) is an important dynamical characteristic of the extratropical stratosphere. However, modern climate models have difficulties in simulating this frequency, with many models either considerably under- or overestimating the observational estimates. Past research has found that models with a higher upper lid tend to simulate a higher and more realistic number of SSWs. The present study revisits this issue and investigates causes for biases in the simulated SSW frequency from the CMIP5 and CMIP6 models. It is found that variations in the frequency are closely related to 1) the strength of the polar vortex and 2) the upward-propagating wave activity in the stratosphere. While it is difficult to explain the variations in the polar vortex strength from the available model output, the stratospheric wave activity is influenced by different aspects of the climatological mean state of the atmosphere in the lower stratosphere. We further find that models with a finer vertical resolution in the stratosphere are overall more realistic: vertical resolution is associated with a smaller cold bias above the extratropical tropopause, more upward-propagating wave activity in the lower stratosphere, and a higher frequency of SSWs. We conclude that not only a high model lid but also a fine vertical resolution in the stratosphere is important for simulating the dynamical variability of the stratosphere.
Abstract
This study investigates the climatological frequency distribution of sudden stratospheric warmings (SSWs). General circulation models (GCMs) tend to produce SSW maxima later in winter than observations, which has been considered as a model deficiency. However, the observed record is short, calling into question the representativeness of the observational record. To study the seasonality of SSWs and the factors behind it, the authors use observations, a long control simulation with a stratosphere resolving GCM, and also a simple statistical model that is based on the climatological seasonal cycle of the polar vortex winds. From the combined analysis, the authors conclude that the late-winter SSW maximum seen in most climate models is realistic and that observations would also have a late-winter SSW maximum if more data were available. The authors identify the seasonally varying strengths of the polar vortex and stratospheric wave driving as the two main factors behind the seasonal SSW distribution. The statistical model also indicates that there exists a continuum of weak polar vortex states and that SSWs simply form the tail of normally distributed stratospheric winds.
Abstract
This study investigates the climatological frequency distribution of sudden stratospheric warmings (SSWs). General circulation models (GCMs) tend to produce SSW maxima later in winter than observations, which has been considered as a model deficiency. However, the observed record is short, calling into question the representativeness of the observational record. To study the seasonality of SSWs and the factors behind it, the authors use observations, a long control simulation with a stratosphere resolving GCM, and also a simple statistical model that is based on the climatological seasonal cycle of the polar vortex winds. From the combined analysis, the authors conclude that the late-winter SSW maximum seen in most climate models is realistic and that observations would also have a late-winter SSW maximum if more data were available. The authors identify the seasonally varying strengths of the polar vortex and stratospheric wave driving as the two main factors behind the seasonal SSW distribution. The statistical model also indicates that there exists a continuum of weak polar vortex states and that SSWs simply form the tail of normally distributed stratospheric winds.
Abstract
The authors identify an interdecadal oscillatory mode of the North Atlantic atmosphere–ocean system in a general circulation model (GFDL CM2.1) via a linear inverse model (LIM). The oscillation mechanism is mostly embedded in the subpolar gyre: anomalous advection generates density anomalies in the eastern subpolar gyre, which propagate along the mean gyre circulation and reach the subpolar gyre center around 10 years later, when associated anomalous advection of the opposite sign starts the other half cycle. As density anomalies reach the Labrador Sea deep convection region, Atlantic meridional overturning circulation (AMOC) anomalies are also induced. Both the gyre and AMOC anomalies then propagate equatorward slowly, following the advection of density anomalies. The oscillation is further demonstrated to be more likely an ocean-only mode while excited by the atmospheric forcing; in particular, it can be approximated as a linearly driven damped oscillator that is partly excited by the North Atlantic Oscillation (NAO). The slowly evolving interdecadal oscillation significantly improves and prolongs the LIM’s prediction skill of sea surface temperature (SST) evolution.
Abstract
The authors identify an interdecadal oscillatory mode of the North Atlantic atmosphere–ocean system in a general circulation model (GFDL CM2.1) via a linear inverse model (LIM). The oscillation mechanism is mostly embedded in the subpolar gyre: anomalous advection generates density anomalies in the eastern subpolar gyre, which propagate along the mean gyre circulation and reach the subpolar gyre center around 10 years later, when associated anomalous advection of the opposite sign starts the other half cycle. As density anomalies reach the Labrador Sea deep convection region, Atlantic meridional overturning circulation (AMOC) anomalies are also induced. Both the gyre and AMOC anomalies then propagate equatorward slowly, following the advection of density anomalies. The oscillation is further demonstrated to be more likely an ocean-only mode while excited by the atmospheric forcing; in particular, it can be approximated as a linearly driven damped oscillator that is partly excited by the North Atlantic Oscillation (NAO). The slowly evolving interdecadal oscillation significantly improves and prolongs the LIM’s prediction skill of sea surface temperature (SST) evolution.
Abstract
Tropospheric circulation shifts have strong potential to impact surface climate. However, the magnitude of these shifts in a changing climate and the attending regional hydrological changes are difficult to project. Part of this difficulty arises from the lack of understanding of the physical mechanisms behind the circulation shifts themselves. To better delineate circulation shifts and their respective causes the circulation response is decomposed into 1) the “direct” response to radiative forcings themselves and 2) the “indirect” response to changing sea surface temperatures. Using ensembles of 90-day climate model simulations with immediate switch-on forcings, including perturbed greenhouse gas concentrations, stratospheric ozone concentrations, and sea surface temperatures, this paper documents the direct and indirect transient responses of the zonal-mean general circulation, and investigates the roles of previously proposed mechanisms in shifting the midlatitude jet. It is found that both the direct and indirect wind responses often begin in the lower stratosphere. Changes in midlatitude eddies are ubiquitous and synchronous with the midlatitude zonal wind response. Shifts in the critical latitude of wave absorption on either flank of the jet are not indicted as primary factors for the poleward-shifting jet, although some evidence for increasing equatorward wave reflection over the Southern Hemisphere in response to sea surface warming is seen. Mechanisms for the Northern Hemisphere jet shift are less clear.
Abstract
Tropospheric circulation shifts have strong potential to impact surface climate. However, the magnitude of these shifts in a changing climate and the attending regional hydrological changes are difficult to project. Part of this difficulty arises from the lack of understanding of the physical mechanisms behind the circulation shifts themselves. To better delineate circulation shifts and their respective causes the circulation response is decomposed into 1) the “direct” response to radiative forcings themselves and 2) the “indirect” response to changing sea surface temperatures. Using ensembles of 90-day climate model simulations with immediate switch-on forcings, including perturbed greenhouse gas concentrations, stratospheric ozone concentrations, and sea surface temperatures, this paper documents the direct and indirect transient responses of the zonal-mean general circulation, and investigates the roles of previously proposed mechanisms in shifting the midlatitude jet. It is found that both the direct and indirect wind responses often begin in the lower stratosphere. Changes in midlatitude eddies are ubiquitous and synchronous with the midlatitude zonal wind response. Shifts in the critical latitude of wave absorption on either flank of the jet are not indicted as primary factors for the poleward-shifting jet, although some evidence for increasing equatorward wave reflection over the Southern Hemisphere in response to sea surface warming is seen. Mechanisms for the Northern Hemisphere jet shift are less clear.
Abstract
This study investigates the meteorological conditions associated with multidecadal drought cycles as revealed by lake level fluctuation of the Great Salt Lake (GSL). The analysis combined instrumental, proxy, and simulation datasets, including the Twentieth Century Reanalysis version 2, the North American Drought Atlas, and a 2000-yr control simulation of the GFDL Coupled Model, version 2.1 (CM2.1). Statistical evidence from the spectral coherence analysis points to a phase shift amounting to 6–9 yr between the wet–dry cycles in the Great Basin and the warm–cool phases of the interdecadal Pacific oscillation (IPO). Diagnoses of the sea surface temperature and atmospheric circulation anomalies attribute such a phase shift to a distinctive teleconnection wave train that develops during the transition points between the IPO’s warm and cool phases. This teleconnection wave train forms recurrent circulation anomalies centered over the southeastern Gulf of Alaska; this directs moisture flux across the Great Basin and subsequently drives wet–dry conditions over the Great Basin and the GSL watershed. The IPO life cycle therefore modulates local droughts–pluvials in a quarter-phase manner.
Abstract
This study investigates the meteorological conditions associated with multidecadal drought cycles as revealed by lake level fluctuation of the Great Salt Lake (GSL). The analysis combined instrumental, proxy, and simulation datasets, including the Twentieth Century Reanalysis version 2, the North American Drought Atlas, and a 2000-yr control simulation of the GFDL Coupled Model, version 2.1 (CM2.1). Statistical evidence from the spectral coherence analysis points to a phase shift amounting to 6–9 yr between the wet–dry cycles in the Great Basin and the warm–cool phases of the interdecadal Pacific oscillation (IPO). Diagnoses of the sea surface temperature and atmospheric circulation anomalies attribute such a phase shift to a distinctive teleconnection wave train that develops during the transition points between the IPO’s warm and cool phases. This teleconnection wave train forms recurrent circulation anomalies centered over the southeastern Gulf of Alaska; this directs moisture flux across the Great Basin and subsequently drives wet–dry conditions over the Great Basin and the GSL watershed. The IPO life cycle therefore modulates local droughts–pluvials in a quarter-phase manner.
