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- Author or Editor: Shuting Yang x
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Abstract
An objective break criterion is utilized to investigate the manner in which the slowly varying component of the atmosphere ( 10-90 day frequency band) actually varies. It is found that a great deal of the behavior appears to be made up of relatively infrequent large amplitude transitions between quasi-persistent states. The most frequent time interval over which these transition events occur is between five and six days. The rapid speed of these events strongly suggests that some type of baroclinic instability mechanism is involved in the transition process.
Abstract
An objective break criterion is utilized to investigate the manner in which the slowly varying component of the atmosphere ( 10-90 day frequency band) actually varies. It is found that a great deal of the behavior appears to be made up of relatively infrequent large amplitude transitions between quasi-persistent states. The most frequent time interval over which these transition events occur is between five and six days. The rapid speed of these events strongly suggests that some type of baroclinic instability mechanism is involved in the transition process.
Abstract
Transition of weather regimes is examined in a highly simplified model. Two completely distinct internal methods of transition are identified. The first is a synoptically triggered large-scale instability, while the second is an energy inconsistency between the large-scale and synoptic scales that does not allow the two scales to equilibrate. In the atmosphere, the first case appears as a sudden propagation and damping (or vice versa) of the large-scale pattern with no obvious warning, while the second is consistent with the synoptician's description of a regime being disrupted by a single catastrophic event such as explosive cyclogenesis. The first method is always fast (on a synoptic time scale), while the second does not have to be, though often is. By examining what causes the regimes to fail, one can better understand the role of the transients during all phases of weather regimes.
Abstract
Transition of weather regimes is examined in a highly simplified model. Two completely distinct internal methods of transition are identified. The first is a synoptically triggered large-scale instability, while the second is an energy inconsistency between the large-scale and synoptic scales that does not allow the two scales to equilibrate. In the atmosphere, the first case appears as a sudden propagation and damping (or vice versa) of the large-scale pattern with no obvious warning, while the second is consistent with the synoptician's description of a regime being disrupted by a single catastrophic event such as explosive cyclogenesis. The first method is always fast (on a synoptic time scale), while the second does not have to be, though often is. By examining what causes the regimes to fail, one can better understand the role of the transients during all phases of weather regimes.
Abstract
Systematically recurrent, geographically fixed weather regimes forced by a single isolated mountain in a two-layer, high-resolution, quasigeostrophic model modified for the sphere are found to be robust phenomena. While the climatological stationary wave is often confined to (or has maximum amplitude in) the region just downstream of the orography, giving the appearance of a wave train propagating into the Tropics, the regional maximum centers of low-frequency variance appear around the hemisphere, giving the appearance of zonal resonance or some type of zonally confined propagation. This result is not anticipated in light of Rossby wave dispersion theory on the sphere. On the other hand, baroclinic disturbances developing on a meridional temperature gradient of finite extent force subtropical and polar easterlies as well as a sharpened midlatitude westerly jet, which provides a zonal waveguide (by refraction and/or reflection) for the Rossby waves. These conditions are favorable for the establishment of multiple weather regimes. The baroclinicity of the atmosphere is then continuously forcing a mean state that favors forced zonal propagation, counteracting the meridional dispersion generated by the spherical geometry alone. These ideas suggest that the multiple-equilibria theories may be more applicable to the atmosphere than originally suggested by linear dispersion theory on the sphere. It may also help explain why channel models work as well as they do even for the largest scales.
Abstract
Systematically recurrent, geographically fixed weather regimes forced by a single isolated mountain in a two-layer, high-resolution, quasigeostrophic model modified for the sphere are found to be robust phenomena. While the climatological stationary wave is often confined to (or has maximum amplitude in) the region just downstream of the orography, giving the appearance of a wave train propagating into the Tropics, the regional maximum centers of low-frequency variance appear around the hemisphere, giving the appearance of zonal resonance or some type of zonally confined propagation. This result is not anticipated in light of Rossby wave dispersion theory on the sphere. On the other hand, baroclinic disturbances developing on a meridional temperature gradient of finite extent force subtropical and polar easterlies as well as a sharpened midlatitude westerly jet, which provides a zonal waveguide (by refraction and/or reflection) for the Rossby waves. These conditions are favorable for the establishment of multiple weather regimes. The baroclinicity of the atmosphere is then continuously forcing a mean state that favors forced zonal propagation, counteracting the meridional dispersion generated by the spherical geometry alone. These ideas suggest that the multiple-equilibria theories may be more applicable to the atmosphere than originally suggested by linear dispersion theory on the sphere. It may also help explain why channel models work as well as they do even for the largest scales.
Abstract
We investigate the forced response of the North Atlantic Oscillation (NAO)—calculated as the ensemble mean—in different large ensembles of climate models including simulations with historical forcings and initialized decadal hindcasts. The forced NAO in the CMIP6 historical ensemble correlates significantly with observations after 1970. However, the forced NAO shows an apparent nonstationarity with significant correlations to observations only in the period after 1970 and in the period before 1890. We demonstrate that such apparent nonstationarity can be due to chance even when models and observations are independent. For the period after 1970 the correlation to the observed NAO continues to increase while the amplitude of the forced signal continues to decrease—although both with some signs of saturation—when the ensemble size grows. This behavior can be explained by a simple statistical model assuming a very small signal-to-noise ratio in the models. We find only rather weak evidence that initialization improves the skill of the NAO on decadal time scales. The NAO in the historical ensembles including only natural forcings, well-mixed greenhouse gases, or anthropogenic aerosols show skill that is not significantly different from zero. The same holds for a large single-model ensemble. The skills of these ensembles, except for the well-mixed greenhouse gas ensemble, are also significantly different from the skill of the larger full historical ensemble even though their ensemble sizes are smaller. Taken together, our results challenge the possibility of useful NAO predictions on decadal time scales.
Abstract
We investigate the forced response of the North Atlantic Oscillation (NAO)—calculated as the ensemble mean—in different large ensembles of climate models including simulations with historical forcings and initialized decadal hindcasts. The forced NAO in the CMIP6 historical ensemble correlates significantly with observations after 1970. However, the forced NAO shows an apparent nonstationarity with significant correlations to observations only in the period after 1970 and in the period before 1890. We demonstrate that such apparent nonstationarity can be due to chance even when models and observations are independent. For the period after 1970 the correlation to the observed NAO continues to increase while the amplitude of the forced signal continues to decrease—although both with some signs of saturation—when the ensemble size grows. This behavior can be explained by a simple statistical model assuming a very small signal-to-noise ratio in the models. We find only rather weak evidence that initialization improves the skill of the NAO on decadal time scales. The NAO in the historical ensembles including only natural forcings, well-mixed greenhouse gases, or anthropogenic aerosols show skill that is not significantly different from zero. The same holds for a large single-model ensemble. The skills of these ensembles, except for the well-mixed greenhouse gas ensemble, are also significantly different from the skill of the larger full historical ensemble even though their ensemble sizes are smaller. Taken together, our results challenge the possibility of useful NAO predictions on decadal time scales.
Abstract
A considerable part of the skill in decadal forecasts often comes from the forcings, which are present in both initialized and uninitialized model experiments. This makes the added value from initialization difficult to assess. We investigate statistical tests to quantify if initialized forecasts provide skill over the uninitialized experiments. We consider three correlation-based statistics previously used in the literature. The distributions of these statistics under the null hypothesis that initialization has no added values are calculated by a surrogate data method. We present some simple examples and study the statistical power of the tests. We find that there can be large differences in both the values and power for the different statistics. In general, the simple statistic defined as the difference between the skill of the initialized and uninitialized experiments behaves best. However, for all statistics the risk of rejecting the true null hypothesis is too high compared to the nominal value. We compare the three tests on initialized decadal predictions (hindcasts) of near-surface temperature performed with a climate model and find evidence for a significant effect of initializations for small lead times. In contrast, we find only little evidence for a significant effect of initializations for lead times longer than 3 years when the experience from the simple experiments is included in the estimation.
Abstract
A considerable part of the skill in decadal forecasts often comes from the forcings, which are present in both initialized and uninitialized model experiments. This makes the added value from initialization difficult to assess. We investigate statistical tests to quantify if initialized forecasts provide skill over the uninitialized experiments. We consider three correlation-based statistics previously used in the literature. The distributions of these statistics under the null hypothesis that initialization has no added values are calculated by a surrogate data method. We present some simple examples and study the statistical power of the tests. We find that there can be large differences in both the values and power for the different statistics. In general, the simple statistic defined as the difference between the skill of the initialized and uninitialized experiments behaves best. However, for all statistics the risk of rejecting the true null hypothesis is too high compared to the nominal value. We compare the three tests on initialized decadal predictions (hindcasts) of near-surface temperature performed with a climate model and find evidence for a significant effect of initializations for small lead times. In contrast, we find only little evidence for a significant effect of initializations for lead times longer than 3 years when the experience from the simple experiments is included in the estimation.
Abstract
The surface of the world’s oceans has been warming since the beginning of industrialization. In addition to this, multidecadal sea surface temperature (SST) variations of internal origin exist. Evidence suggests that the North Atlantic Ocean exhibits the strongest multidecadal SST variations and that these variations are connected to the overturning circulation.
This work investigates the extent to which these internal multidecadal variations have contributed to enhancing or diminishing the trend induced by the external radiative forcing, globally and in the North Atlantic. A model study is carried out wherein the analyses of a long control simulation with constant radiative forcing at preindustrial level and of an ensemble of simulations with historical forcing from 1850 until 2005 are combined. First, it is noted that global SST trends calculated from the different historical simulations are similar, while there is a large disagreement between the North Atlantic SST trends. Then the control simulation is analyzed, where a relationship between SST anomalies and anomalies in the Atlantic meridional overturning circulation (AMOC) for multidecadal and longer time scales is identified. This relationship enables the extraction of the AMOC-related SST variability from each individual member of the ensemble of historical simulations and then the calculation of the SST trends with the AMOC-related variability excluded. For the global SST trends this causes only a little difference while SST trends with AMOC-related variability excluded for the North Atlantic show closer agreement than with the AMOC-related variability included. From this it is concluded that AMOC variability has contributed significantly to North Atlantic SST trends since the mid nineteenth century.
Abstract
The surface of the world’s oceans has been warming since the beginning of industrialization. In addition to this, multidecadal sea surface temperature (SST) variations of internal origin exist. Evidence suggests that the North Atlantic Ocean exhibits the strongest multidecadal SST variations and that these variations are connected to the overturning circulation.
This work investigates the extent to which these internal multidecadal variations have contributed to enhancing or diminishing the trend induced by the external radiative forcing, globally and in the North Atlantic. A model study is carried out wherein the analyses of a long control simulation with constant radiative forcing at preindustrial level and of an ensemble of simulations with historical forcing from 1850 until 2005 are combined. First, it is noted that global SST trends calculated from the different historical simulations are similar, while there is a large disagreement between the North Atlantic SST trends. Then the control simulation is analyzed, where a relationship between SST anomalies and anomalies in the Atlantic meridional overturning circulation (AMOC) for multidecadal and longer time scales is identified. This relationship enables the extraction of the AMOC-related SST variability from each individual member of the ensemble of historical simulations and then the calculation of the SST trends with the AMOC-related variability excluded. For the global SST trends this causes only a little difference while SST trends with AMOC-related variability excluded for the North Atlantic show closer agreement than with the AMOC-related variability included. From this it is concluded that AMOC variability has contributed significantly to North Atlantic SST trends since the mid nineteenth century.
Abstract
While a rapid sea ice retreat in the Arctic has become ubiquitous, the potential weakening of the Atlantic meridional overturning circulation (AMOC) in response to global warming is still under debate. As deep mixing occurs in the open ocean close to the sea ice edge, the strength and vertical extent of the AMOC is likely to respond to ongoing and future sea ice retreat. Here, we investigate the link between changes in Arctic sea ice cover and AMOC strength in a long simulation with the EC-Earth–Parallel Ice Sheet Model (PISM) climate model under the emission scenario RCP8.5. The extended duration of the experiment (years 1850–2300) captures the disappearance of summer sea ice in 2060 and the removal of winter sea ice in 2165. By introducing a new metric, the Arctic meridional overturning circulation (ArMOC), we document changes beyond the Greenland–Scotland ridge and into the central Arctic. We find an ArMOC strengthening as the areas of deep mixing move north, following the retreating winter sea ice edge into the Nansen Basin. At the same time, mixing in the Labrador and Greenland Seas reduces and the AMOC weakens. As the winter sea ice edge retreats farther into the regions with high surface freshwater content in the central Arctic Basin, the mixing becomes shallower and the ArMOC weakens. Our results suggest that the location of deep-water formation plays a decisive role in the structure and strength of the ArMOC; however, the intermittent strengthening of the ArMOC and convection north of the Greenland–Scotland ridge cannot compensate for the progressive weakening of the AMOC.
Abstract
While a rapid sea ice retreat in the Arctic has become ubiquitous, the potential weakening of the Atlantic meridional overturning circulation (AMOC) in response to global warming is still under debate. As deep mixing occurs in the open ocean close to the sea ice edge, the strength and vertical extent of the AMOC is likely to respond to ongoing and future sea ice retreat. Here, we investigate the link between changes in Arctic sea ice cover and AMOC strength in a long simulation with the EC-Earth–Parallel Ice Sheet Model (PISM) climate model under the emission scenario RCP8.5. The extended duration of the experiment (years 1850–2300) captures the disappearance of summer sea ice in 2060 and the removal of winter sea ice in 2165. By introducing a new metric, the Arctic meridional overturning circulation (ArMOC), we document changes beyond the Greenland–Scotland ridge and into the central Arctic. We find an ArMOC strengthening as the areas of deep mixing move north, following the retreating winter sea ice edge into the Nansen Basin. At the same time, mixing in the Labrador and Greenland Seas reduces and the AMOC weakens. As the winter sea ice edge retreats farther into the regions with high surface freshwater content in the central Arctic Basin, the mixing becomes shallower and the ArMOC weakens. Our results suggest that the location of deep-water formation plays a decisive role in the structure and strength of the ArMOC; however, the intermittent strengthening of the ArMOC and convection north of the Greenland–Scotland ridge cannot compensate for the progressive weakening of the AMOC.
Abstract
We present a model intercomparison project, LongRunMIP, the first collection of millennial-length (1,000+ years) simulations of complex coupled climate models with a representation of ocean, atmosphere, sea ice, and land surface, and their interactions. Standard model simulations are generally only a few hundred years long. However, modeling the long-term equilibration in response to radiative forcing perturbation is important for understanding many climate phenomena, such as the evolution of ocean circulation, time- and temperature-dependent feedbacks, and the differentiation of forced signal and internal variability. The aim of LongRunMIP is to facilitate research into these questions by serving as an archive for simulations that capture as much of this equilibration as possible. The only requirement to participate in LongRunMIP is to contribute a simulation with elevated, constant CO2 forcing that lasts at least 1,000 years. LongRunMIP is an MIP of opportunity in that the simulations were mostly performed prior to the conception of the archive without an agreed-upon set of experiments. For most models, the archive contains a preindustrial control simulation and simulations with an idealized (typically abrupt) CO2 forcing. We collect 2D surface and top-of-atmosphere fields and 3D ocean temperature and salinity fields. Here, we document the collection of simulations and discuss initial results, including the evolution of surface and deep ocean temperature and cloud radiative effects. As of October 2019, the collection includes 50 simulations of 15 models by 10 modeling centers. The data of LongRunMIP are publicly available. We encourage submissions of more simulations in the future.
Abstract
We present a model intercomparison project, LongRunMIP, the first collection of millennial-length (1,000+ years) simulations of complex coupled climate models with a representation of ocean, atmosphere, sea ice, and land surface, and their interactions. Standard model simulations are generally only a few hundred years long. However, modeling the long-term equilibration in response to radiative forcing perturbation is important for understanding many climate phenomena, such as the evolution of ocean circulation, time- and temperature-dependent feedbacks, and the differentiation of forced signal and internal variability. The aim of LongRunMIP is to facilitate research into these questions by serving as an archive for simulations that capture as much of this equilibration as possible. The only requirement to participate in LongRunMIP is to contribute a simulation with elevated, constant CO2 forcing that lasts at least 1,000 years. LongRunMIP is an MIP of opportunity in that the simulations were mostly performed prior to the conception of the archive without an agreed-upon set of experiments. For most models, the archive contains a preindustrial control simulation and simulations with an idealized (typically abrupt) CO2 forcing. We collect 2D surface and top-of-atmosphere fields and 3D ocean temperature and salinity fields. Here, we document the collection of simulations and discuss initial results, including the evolution of surface and deep ocean temperature and cloud radiative effects. As of October 2019, the collection includes 50 simulations of 15 models by 10 modeling centers. The data of LongRunMIP are publicly available. We encourage submissions of more simulations in the future.
Abstract
As climate change accelerates, societies and climate-sensitive socioeconomic sectors cannot continue to rely on the past as a guide to possible future climate hazards. Operational decadal predictions offer the potential to inform current adaptation and increase resilience by filling the important gap between seasonal forecasts and climate projections. The World Meteorological Organization (WMO) has recognized this and in 2017 established the WMO Lead Centre for Annual to Decadal Climate Predictions (shortened to “Lead Centre” below), which annually provides a large multimodel ensemble of predictions covering the next 5 years. This international collaboration produces a prediction that is more skillful and useful than any single center can achieve. One of the main outputs of the Lead Centre is the Global Annual to Decadal Climate Update (GADCU), a consensus forecast based on these predictions. This update includes maps showing key variables, discussion on forecast skill, and predictions of climate indices such as the global mean near-surface temperature and Atlantic multidecadal variability. it also estimates the probability of the global mean temperature exceeding 1.5°C above preindustrial levels for at least 1 year in the next 5 years, which helps policy-makers understand how closely the world is approaching this goal of the Paris Agreement. This paper, written by the authors of the GADCU, introduces the GADCU, presents its key outputs, and briefly discusses its role in providing vital climate information for society now and in the future.
Abstract
As climate change accelerates, societies and climate-sensitive socioeconomic sectors cannot continue to rely on the past as a guide to possible future climate hazards. Operational decadal predictions offer the potential to inform current adaptation and increase resilience by filling the important gap between seasonal forecasts and climate projections. The World Meteorological Organization (WMO) has recognized this and in 2017 established the WMO Lead Centre for Annual to Decadal Climate Predictions (shortened to “Lead Centre” below), which annually provides a large multimodel ensemble of predictions covering the next 5 years. This international collaboration produces a prediction that is more skillful and useful than any single center can achieve. One of the main outputs of the Lead Centre is the Global Annual to Decadal Climate Update (GADCU), a consensus forecast based on these predictions. This update includes maps showing key variables, discussion on forecast skill, and predictions of climate indices such as the global mean near-surface temperature and Atlantic multidecadal variability. it also estimates the probability of the global mean temperature exceeding 1.5°C above preindustrial levels for at least 1 year in the next 5 years, which helps policy-makers understand how closely the world is approaching this goal of the Paris Agreement. This paper, written by the authors of the GADCU, introduces the GADCU, presents its key outputs, and briefly discusses its role in providing vital climate information for society now and in the future.
