Search Results
Abstract
During the 1990s there was a major change in the state of the world's oceans. In particular, the North Atlantic underwent a rapid warming, with sea surface temperatures (SSTs) in the subpolar gyre region increasing by 1°C in just a few years. Associated with the changes in SST patterns were changes in the surface climate, in particular, a tendency for warm and dry conditions over areas of North America in all seasons, and warm springs and wet summers over areas of Europe. Here, the extent to which a climate prediction system initialized using observations of the ocean state is able to capture the observed changes in seasonal mean surface climate is investigated. Rather than examining predictions of the mid-1990s North Atlantic warming event itself, this study compares hindcasts started before and after the warming, relative to hindcasts that do not assimilate information. It is demonstrated that the hindcasts capture many aspects of the observed changes in seasonal mean surface climate, especially in North, South, and Central America and in Europe. Furthermore, the prediction system retains skill beyond the first year. Finally, it is shown that, in addition to memory of Atlantic SSTs, successfully predicting Pacific SSTs was likely important for the hindcasts to predict surface climate over North America.
Abstract
During the 1990s there was a major change in the state of the world's oceans. In particular, the North Atlantic underwent a rapid warming, with sea surface temperatures (SSTs) in the subpolar gyre region increasing by 1°C in just a few years. Associated with the changes in SST patterns were changes in the surface climate, in particular, a tendency for warm and dry conditions over areas of North America in all seasons, and warm springs and wet summers over areas of Europe. Here, the extent to which a climate prediction system initialized using observations of the ocean state is able to capture the observed changes in seasonal mean surface climate is investigated. Rather than examining predictions of the mid-1990s North Atlantic warming event itself, this study compares hindcasts started before and after the warming, relative to hindcasts that do not assimilate information. It is demonstrated that the hindcasts capture many aspects of the observed changes in seasonal mean surface climate, especially in North, South, and Central America and in Europe. Furthermore, the prediction system retains skill beyond the first year. Finally, it is shown that, in addition to memory of Atlantic SSTs, successfully predicting Pacific SSTs was likely important for the hindcasts to predict surface climate over North America.
Abstract
A Bayesian statistical model is proposed that combines information from a multimodel ensemble of atmosphere–ocean general circulation models (AOGCMs) and observations to determine probability distributions of future temperature change on a regional scale. The posterior distributions derived from the statistical assumptions incorporate the criteria of bias and convergence in the relative weights implicitly assigned to the ensemble members. This approach can be considered an extension and elaboration of the reliability ensemble averaging method. For illustration, the authors consider the output of mean surface temperature from nine AOGCMs, run under the A2 emission scenario from the Synthesis Report on Emission Scenarios (SRES), for boreal winter and summer, aggregated over 22 land regions and into two 30-yr averages representative of current and future climate conditions. The shapes of the final probability density functions of temperature change vary widely, from unimodal curves for regions where model results agree (or outlying projections are discounted) to multimodal curves where models that cannot be discounted on the basis of bias give diverging projections. Besides the basic statistical model, the authors consider including correlation between present and future temperature responses, and test alternative forms of probability distributions for the model error terms. It is suggested that a probabilistic approach, particularly in the form of a Bayesian model, is a useful platform from which to synthesize the information from an ensemble of simulations. The probability distributions of temperature change reveal features such as multimodality and long tails that could not otherwise be easily discerned. Furthermore, the Bayesian model can serve as an interdisciplinary tool through which climate modelers, climatologists, and statisticians can work more closely. For example, climate modelers, through their expert judgment, could contribute to the formulations of prior distributions in the statistical model.
Abstract
A Bayesian statistical model is proposed that combines information from a multimodel ensemble of atmosphere–ocean general circulation models (AOGCMs) and observations to determine probability distributions of future temperature change on a regional scale. The posterior distributions derived from the statistical assumptions incorporate the criteria of bias and convergence in the relative weights implicitly assigned to the ensemble members. This approach can be considered an extension and elaboration of the reliability ensemble averaging method. For illustration, the authors consider the output of mean surface temperature from nine AOGCMs, run under the A2 emission scenario from the Synthesis Report on Emission Scenarios (SRES), for boreal winter and summer, aggregated over 22 land regions and into two 30-yr averages representative of current and future climate conditions. The shapes of the final probability density functions of temperature change vary widely, from unimodal curves for regions where model results agree (or outlying projections are discounted) to multimodal curves where models that cannot be discounted on the basis of bias give diverging projections. Besides the basic statistical model, the authors consider including correlation between present and future temperature responses, and test alternative forms of probability distributions for the model error terms. It is suggested that a probabilistic approach, particularly in the form of a Bayesian model, is a useful platform from which to synthesize the information from an ensemble of simulations. The probability distributions of temperature change reveal features such as multimodality and long tails that could not otherwise be easily discerned. Furthermore, the Bayesian model can serve as an interdisciplinary tool through which climate modelers, climatologists, and statisticians can work more closely. For example, climate modelers, through their expert judgment, could contribute to the formulations of prior distributions in the statistical model.
Abstract
Decadal climate predictions exhibit large biases, which are often subtracted and forgotten. However, understanding the causes of bias is essential to guide efforts to improve prediction systems, and may offer additional benefits. Here the origins of biases in decadal predictions are investigated, including whether analysis of these biases might provide useful information. The focus is especially on the lead-time-dependent bias tendency. A “toy” model of a prediction system is initially developed and used to show that there are several distinct contributions to bias tendency. Contributions from sampling of internal variability and a start-time-dependent forcing bias can be estimated and removed to obtain a much improved estimate of the true bias tendency, which can provide information about errors in the underlying model and/or errors in the specification of forcings. It is argued that the true bias tendency, not the total bias tendency, should be used to adjust decadal forecasts.
The methods developed are applied to decadal hindcasts of global mean temperature made using the Hadley Centre Coupled Model, version 3 (HadCM3), climate model, and it is found that this model exhibits a small positive bias tendency in the ensemble mean. When considering different model versions, it is shown that the true bias tendency is very highly correlated with both the transient climate response (TCR) and non–greenhouse gas forcing trends, and can therefore be used to obtain observationally constrained estimates of these relevant physical quantities.
Abstract
Decadal climate predictions exhibit large biases, which are often subtracted and forgotten. However, understanding the causes of bias is essential to guide efforts to improve prediction systems, and may offer additional benefits. Here the origins of biases in decadal predictions are investigated, including whether analysis of these biases might provide useful information. The focus is especially on the lead-time-dependent bias tendency. A “toy” model of a prediction system is initially developed and used to show that there are several distinct contributions to bias tendency. Contributions from sampling of internal variability and a start-time-dependent forcing bias can be estimated and removed to obtain a much improved estimate of the true bias tendency, which can provide information about errors in the underlying model and/or errors in the specification of forcings. It is argued that the true bias tendency, not the total bias tendency, should be used to adjust decadal forecasts.
The methods developed are applied to decadal hindcasts of global mean temperature made using the Hadley Centre Coupled Model, version 3 (HadCM3), climate model, and it is found that this model exhibits a small positive bias tendency in the ensemble mean. When considering different model versions, it is shown that the true bias tendency is very highly correlated with both the transient climate response (TCR) and non–greenhouse gas forcing trends, and can therefore be used to obtain observationally constrained estimates of these relevant physical quantities.
Abstract
In the North Atlantic, there are pronounced gyre-scale changes in ocean heat content on interannual-to-decadal time scales, which are associated with changes in both sea surface temperature and thermocline thickness; the subtropics are often warm with a thick thermocline when the subpolar gyre is cool with a thin thermocline, and vice versa. This climate variability is investigated using a semidiagnostic dynamical analysis of historical temperature and salinity data from 1962 to 2011 together with idealized isopycnic model experiments. On time scales of typically 5 yr, the tendencies in upper-ocean heat content are not simply explained by the area-averaged atmospheric forcing for each gyre but instead dominated by heat convergences associated with the meridional overturning circulation. In the subtropics, the most pronounced warming events are associated with an increased influx of tropical heat driven by stronger trade winds. In the subpolar gyre, the warming and cooling events are associated with changes in western boundary density, where increasing Labrador Sea density leads to an enhanced overturning and an influx of subtropical heat. Thus, upper-ocean heat content anomalies are formed in a different manner in the subtropical and subpolar gyres, with different components of the meridional overturning circulation probably excited by the local imprint of atmospheric forcing.
Abstract
In the North Atlantic, there are pronounced gyre-scale changes in ocean heat content on interannual-to-decadal time scales, which are associated with changes in both sea surface temperature and thermocline thickness; the subtropics are often warm with a thick thermocline when the subpolar gyre is cool with a thin thermocline, and vice versa. This climate variability is investigated using a semidiagnostic dynamical analysis of historical temperature and salinity data from 1962 to 2011 together with idealized isopycnic model experiments. On time scales of typically 5 yr, the tendencies in upper-ocean heat content are not simply explained by the area-averaged atmospheric forcing for each gyre but instead dominated by heat convergences associated with the meridional overturning circulation. In the subtropics, the most pronounced warming events are associated with an increased influx of tropical heat driven by stronger trade winds. In the subpolar gyre, the warming and cooling events are associated with changes in western boundary density, where increasing Labrador Sea density leads to an enhanced overturning and an influx of subtropical heat. Thus, upper-ocean heat content anomalies are formed in a different manner in the subtropical and subpolar gyres, with different components of the meridional overturning circulation probably excited by the local imprint of atmospheric forcing.
Abstract
Basin-scale thermal anomalies in the North Atlantic, extending to depths of 1–2 km, are more pronounced than the background warming over the last 60 years. A dynamical analysis based on reanalyses of historical data from 1965 to 2000 suggests that these thermal anomalies are formed by ocean heat convergences, augmented by the poorly known air–sea fluxes. The heat convergence is separated into contributions from the horizontal circulation and the meridional overturning circulation (MOC), the latter further separated into Ekman and MOC transport minus Ekman transport (MOC-Ekman) cells. The subtropical thermal anomalies are mainly controlled by wind-induced changes in the Ekman heat convergence, while the subpolar thermal anomalies are controlled by the MOC-Ekman heat convergence; the horizontal heat convergence is generally weaker, only becoming significant within the subpolar gyre. These thermal anomalies often have an opposing sign between the subtropical and subpolar gyres, associated with opposing changes in the meridional volume transport driving the Ekman and MOC-Ekman heat convergences. These changes in gyre-scale convergences in heat transport are probably induced by the winds, as they correlate with the zonal wind stress at gyre boundaries.
Abstract
Basin-scale thermal anomalies in the North Atlantic, extending to depths of 1–2 km, are more pronounced than the background warming over the last 60 years. A dynamical analysis based on reanalyses of historical data from 1965 to 2000 suggests that these thermal anomalies are formed by ocean heat convergences, augmented by the poorly known air–sea fluxes. The heat convergence is separated into contributions from the horizontal circulation and the meridional overturning circulation (MOC), the latter further separated into Ekman and MOC transport minus Ekman transport (MOC-Ekman) cells. The subtropical thermal anomalies are mainly controlled by wind-induced changes in the Ekman heat convergence, while the subpolar thermal anomalies are controlled by the MOC-Ekman heat convergence; the horizontal heat convergence is generally weaker, only becoming significant within the subpolar gyre. These thermal anomalies often have an opposing sign between the subtropical and subpolar gyres, associated with opposing changes in the meridional volume transport driving the Ekman and MOC-Ekman heat convergences. These changes in gyre-scale convergences in heat transport are probably induced by the winds, as they correlate with the zonal wind stress at gyre boundaries.
Abstract
The role of the atmospheric jet stream in driving patterns of surface heat flux, changes in sea surface temperature, and sea ice fraction is explored for the winter North Atlantic. Seasonal time-scale ensemble hindcasts from the Met Office Hadley Centre are analyzed for each winter from 1980 to 2014, which for each year includes 40 ensemble members initialized at the start of November. The spread between ensemble members that develops during a season is interpreted to represent the ocean response to stochastic atmospheric variability. The seasonal coupling between the winter atmosphere and the ocean over much of the North Atlantic reveals anomalies in surface heat loss driving anomalies in the tendency of sea surface temperature. The atmospheric jet, defined either by its speed or latitude, strongly controls the winter pattern of air–sea latent and sensible heat flux anomalies, and subsequent sea surface temperature anomalies. On time scales of several months, the effect of jet speed is more pronounced than that of jet latitude on the surface ocean response, although the effect of jet latitude is important in altering the extent of the ocean subtropical and subpolar gyres. A strong jet or high jet latitude increases sea ice fraction over the Labrador Sea due to the enhanced transport of cold air from west Greenland, while sea ice fraction decreases along the east side of Greenland due either to warm air advection or a strong northerly wind along the east Greenland coast blowing surface ice away from the Fram Strait.
Abstract
The role of the atmospheric jet stream in driving patterns of surface heat flux, changes in sea surface temperature, and sea ice fraction is explored for the winter North Atlantic. Seasonal time-scale ensemble hindcasts from the Met Office Hadley Centre are analyzed for each winter from 1980 to 2014, which for each year includes 40 ensemble members initialized at the start of November. The spread between ensemble members that develops during a season is interpreted to represent the ocean response to stochastic atmospheric variability. The seasonal coupling between the winter atmosphere and the ocean over much of the North Atlantic reveals anomalies in surface heat loss driving anomalies in the tendency of sea surface temperature. The atmospheric jet, defined either by its speed or latitude, strongly controls the winter pattern of air–sea latent and sensible heat flux anomalies, and subsequent sea surface temperature anomalies. On time scales of several months, the effect of jet speed is more pronounced than that of jet latitude on the surface ocean response, although the effect of jet latitude is important in altering the extent of the ocean subtropical and subpolar gyres. A strong jet or high jet latitude increases sea ice fraction over the Labrador Sea due to the enhanced transport of cold air from west Greenland, while sea ice fraction decreases along the east side of Greenland due either to warm air advection or a strong northerly wind along the east Greenland coast blowing surface ice away from the Fram Strait.
Abstract
Daily maximum and minimum summer temperatures have increased throughout the majority of Europe over the past few decades, along with the frequency and intensity of heat waves. It is essential to learn whether this rise is expected to continue in the future for adaptation purposes. A study of predictability of European temperature indices with the Met Office Hadley Centre Decadal Prediction System (DePreSys) has revealed significant skill in predictions of 5- and 10-yr average indices of the summer mean and maximum 5-day average temperatures based on daily maximum and minimum temperatures for a large area of Europe, particularly in the Mediterranean. In contrast, the decadal forecasts of winter mean/minimum 5-day average temperature indices show poorer skill than the summer indices. Significant skill is shown for the United Kingdom in some cases but less than for the European/Mediterranean regions.
Comparison of two parallel ensembles, one initialized with observations and one without initialization, has shown that the skill largely originates from external forcing. However, there were a few cases with hints of additional skill in forecasts of decadal mean indices due to the initialization.
Model realizations of extreme indices can have large biases compared to observations that are different from those of the mean climate indices. Several methods were tested for correcting biases, as well as for testing the significance and quantifying uncertainty of the results to rule out cases of spurious skill. Bias correction of each index individually is required as biases vary across different extremes.
Abstract
Daily maximum and minimum summer temperatures have increased throughout the majority of Europe over the past few decades, along with the frequency and intensity of heat waves. It is essential to learn whether this rise is expected to continue in the future for adaptation purposes. A study of predictability of European temperature indices with the Met Office Hadley Centre Decadal Prediction System (DePreSys) has revealed significant skill in predictions of 5- and 10-yr average indices of the summer mean and maximum 5-day average temperatures based on daily maximum and minimum temperatures for a large area of Europe, particularly in the Mediterranean. In contrast, the decadal forecasts of winter mean/minimum 5-day average temperature indices show poorer skill than the summer indices. Significant skill is shown for the United Kingdom in some cases but less than for the European/Mediterranean regions.
Comparison of two parallel ensembles, one initialized with observations and one without initialization, has shown that the skill largely originates from external forcing. However, there were a few cases with hints of additional skill in forecasts of decadal mean indices due to the initialization.
Model realizations of extreme indices can have large biases compared to observations that are different from those of the mean climate indices. Several methods were tested for correcting biases, as well as for testing the significance and quantifying uncertainty of the results to rule out cases of spurious skill. Bias correction of each index individually is required as biases vary across different extremes.
Abstract
In the mid-1990s, the subpolar gyre of the North Atlantic underwent a remarkable rapid warming, with sea surface temperatures increasing by around 1°C in just 2 yr. This rapid warming followed a prolonged positive phase of the North Atlantic Oscillation (NAO) but also coincided with an unusually negative NAO index in the winter of 1995/96. By comparing ocean analyses and carefully designed model experiments, it is shown that this rapid warming can be understood as a delayed response to the prolonged positive phase of the NAO and not simply an instantaneous response to the negative NAO index of 1995/96. Furthermore, it is inferred that the warming was partly caused by a surge and subsequent decline in the meridional overturning circulation and northward heat transport of the Atlantic Ocean. These results provide persuasive evidence of significant oceanic memory on multiannual time scales and are therefore encouraging for the prospects of developing skillful predictions.
Abstract
In the mid-1990s, the subpolar gyre of the North Atlantic underwent a remarkable rapid warming, with sea surface temperatures increasing by around 1°C in just 2 yr. This rapid warming followed a prolonged positive phase of the North Atlantic Oscillation (NAO) but also coincided with an unusually negative NAO index in the winter of 1995/96. By comparing ocean analyses and carefully designed model experiments, it is shown that this rapid warming can be understood as a delayed response to the prolonged positive phase of the NAO and not simply an instantaneous response to the negative NAO index of 1995/96. Furthermore, it is inferred that the warming was partly caused by a surge and subsequent decline in the meridional overturning circulation and northward heat transport of the Atlantic Ocean. These results provide persuasive evidence of significant oceanic memory on multiannual time scales and are therefore encouraging for the prospects of developing skillful predictions.
Abstract
The atmospheric response to Arctic and Antarctic sea ice changes typical of the present day and coming decades is investigated using the Hadley Centre global climate model (HadGEM3). The response is diagnosed from ensemble simulations of the period 1979 to 2009 with observed and perturbed sea ice concentrations. The experimental design allows the impacts of ocean–atmosphere coupling and the background atmospheric state to be assessed. The modeled response can be very different to that inferred from statistical relationships, showing that the response cannot be easily diagnosed from observations. Reduced Arctic sea ice drives a local low pressure response in boreal summer and autumn. Increased Antarctic sea ice drives a poleward shift of the Southern Hemisphere midlatitude jet, especially in the cold season. Coupling enables surface temperature responses to spread to the ocean, amplifying the atmospheric response and revealing additional impacts including warming of the North Atlantic in response to reduced Arctic sea ice, with a northward shift of the Atlantic intertropical convergence zone and increased Sahel rainfall. The background state controls the sign of the North Atlantic Oscillation (NAO) response via the refraction of planetary waves. This could help to resolve differences in previous studies, and potentially provides an “emergent constraint” to narrow the uncertainties in the NAO response, highlighting the need for future multimodel coordinated experiments.
Abstract
The atmospheric response to Arctic and Antarctic sea ice changes typical of the present day and coming decades is investigated using the Hadley Centre global climate model (HadGEM3). The response is diagnosed from ensemble simulations of the period 1979 to 2009 with observed and perturbed sea ice concentrations. The experimental design allows the impacts of ocean–atmosphere coupling and the background atmospheric state to be assessed. The modeled response can be very different to that inferred from statistical relationships, showing that the response cannot be easily diagnosed from observations. Reduced Arctic sea ice drives a local low pressure response in boreal summer and autumn. Increased Antarctic sea ice drives a poleward shift of the Southern Hemisphere midlatitude jet, especially in the cold season. Coupling enables surface temperature responses to spread to the ocean, amplifying the atmospheric response and revealing additional impacts including warming of the North Atlantic in response to reduced Arctic sea ice, with a northward shift of the Atlantic intertropical convergence zone and increased Sahel rainfall. The background state controls the sign of the North Atlantic Oscillation (NAO) response via the refraction of planetary waves. This could help to resolve differences in previous studies, and potentially provides an “emergent constraint” to narrow the uncertainties in the NAO response, highlighting the need for future multimodel coordinated experiments.
Abstract
The impact of initial conditions relative to external forcings in decadal integrations from an ensemble of state-of-the-art prediction models has been assessed using specifically designed sensitivity experiments (SWAP experiments). They consist of two sets of 10-yr-long ensemble hindcasts for two initial dates in 1965 and 1995 using either the external forcings from the “correct” decades or swapping the forcings between the two decades. By comparing the two sets of integrations, the impact of external forcing versus initial conditions on the predictability over multiannual time scales was estimated as the function of lead time of the hindcast. It was found that over time scales longer than about 1 yr, the predictability of sea surface temperatures (SSTs) on a global scale arises mainly from the external forcing. However, the correct initialization has a longer impact on SST predictability over specific regions such as the North Atlantic, the northwestern Pacific, and the Southern Ocean. The impact of initialization is even longer and extends to wider regions when below-surface ocean variables are considered. For the western and eastern tropical Atlantic, the impact of initialization for the 700-m heat content (HTC700) extends to as much as 9 years for some of the models considered. In all models the impact of initial conditions on the predictability of the Atlantic meridional overturning circulation (AMOC) is dominant for the first 5 years.
Abstract
The impact of initial conditions relative to external forcings in decadal integrations from an ensemble of state-of-the-art prediction models has been assessed using specifically designed sensitivity experiments (SWAP experiments). They consist of two sets of 10-yr-long ensemble hindcasts for two initial dates in 1965 and 1995 using either the external forcings from the “correct” decades or swapping the forcings between the two decades. By comparing the two sets of integrations, the impact of external forcing versus initial conditions on the predictability over multiannual time scales was estimated as the function of lead time of the hindcast. It was found that over time scales longer than about 1 yr, the predictability of sea surface temperatures (SSTs) on a global scale arises mainly from the external forcing. However, the correct initialization has a longer impact on SST predictability over specific regions such as the North Atlantic, the northwestern Pacific, and the Southern Ocean. The impact of initialization is even longer and extends to wider regions when below-surface ocean variables are considered. For the western and eastern tropical Atlantic, the impact of initialization for the 700-m heat content (HTC700) extends to as much as 9 years for some of the models considered. In all models the impact of initial conditions on the predictability of the Atlantic meridional overturning circulation (AMOC) is dominant for the first 5 years.
