Search Results
You are looking at 1 - 10 of 27 items for
- Author or Editor: Gerard H. Roe x
- Refine by Access: All Content x
Abstract
Baroclinic instability in two-level models is characterized by a critical vertical shear, for values above which the flow is unstable. Existing studies of nonlinear baroclinic equilibration in two-level models suggest that, while equilibration does occur, it does so for values of vertical shear that are supercritical. The criterion used for the critical shear, however, ignores nonlinear changes in barotropic (meridional) shear. The present note estimates, using the two-scale formalism, the effect of both jet scale and damping on the critical value of vertical shear. The results suggest the barotropic shear in the equilibrated states may be sufficient, in the presence of damping, to render the equilibrated states neutral. More generally, it appears important to take account of the nature of the evolved flow when assessing the stability properties of the equilibrated state.
Abstract
Baroclinic instability in two-level models is characterized by a critical vertical shear, for values above which the flow is unstable. Existing studies of nonlinear baroclinic equilibration in two-level models suggest that, while equilibration does occur, it does so for values of vertical shear that are supercritical. The criterion used for the critical shear, however, ignores nonlinear changes in barotropic (meridional) shear. The present note estimates, using the two-scale formalism, the effect of both jet scale and damping on the critical value of vertical shear. The results suggest the barotropic shear in the equilibrated states may be sufficient, in the presence of damping, to render the equilibrated states neutral. More generally, it appears important to take account of the nature of the evolved flow when assessing the stability properties of the equilibrated state.
Abstract
Patterns of orographic precipitation can vary significantly both in time and space, and such variations must ultimately be related to mountain geometry, cloud microphysics, and synoptic conditions. Here an extension of the classic upslope model is presented, which incorporates an explicit representation in the vertical dimension, represents the finite growth time of hydrometeors, their downwind advection by the prevailing wind, and also allows for evaporation. For a simple mountain geometry the authors derive an analytical solution for the precipitation rate, which can be understood in terms of four nondimensional parameters. The finite growth time and slanting hydrometeor trajectories give rise to some interesting possibilities: a precipitation rate that maximizes at intermediate values of the horizontal wind speed, localized precipitation efficiencies in excess of 100%, and a reverse rain shadow with more precipitation falling on the leeward flank than on the windward flank.
Abstract
Patterns of orographic precipitation can vary significantly both in time and space, and such variations must ultimately be related to mountain geometry, cloud microphysics, and synoptic conditions. Here an extension of the classic upslope model is presented, which incorporates an explicit representation in the vertical dimension, represents the finite growth time of hydrometeors, their downwind advection by the prevailing wind, and also allows for evaporation. For a simple mountain geometry the authors derive an analytical solution for the precipitation rate, which can be understood in terms of four nondimensional parameters. The finite growth time and slanting hydrometeor trajectories give rise to some interesting possibilities: a precipitation rate that maximizes at intermediate values of the horizontal wind speed, localized precipitation efficiencies in excess of 100%, and a reverse rain shadow with more precipitation falling on the leeward flank than on the windward flank.
Abstract
The language of feedbacks is ubiquitous in contemporary earth sciences, and the framework of feedback analysis is a powerful tool for diagnosing the relative strengths of the myriad mutual interactions that occur in complex dynamical systems. The ice albedo feedback is widely taught as the classic example of a climate feedback. Moreover, its potential to initiate a collapse to a completely glaciated snowball earth is widely taught as the classic example of a climate “tipping point.” A feedback analysis of the snowball earth phenomenon in simple, zonal mean energy balance models clearly reveals the physics of the snowball instability and its dependence on climate parameters. The analysis can also be used to illustrate some fundamental properties of climate feedbacks: how feedback strength changes as a function of mean climate state; how small changes in individual feedbacks can cause large changes in the system sensitivity; and last, how the strength and even the sign of the feedback is dependent on the climate variable in question.
Abstract
The language of feedbacks is ubiquitous in contemporary earth sciences, and the framework of feedback analysis is a powerful tool for diagnosing the relative strengths of the myriad mutual interactions that occur in complex dynamical systems. The ice albedo feedback is widely taught as the classic example of a climate feedback. Moreover, its potential to initiate a collapse to a completely glaciated snowball earth is widely taught as the classic example of a climate “tipping point.” A feedback analysis of the snowball earth phenomenon in simple, zonal mean energy balance models clearly reveals the physics of the snowball instability and its dependence on climate parameters. The analysis can also be used to illustrate some fundamental properties of climate feedbacks: how feedback strength changes as a function of mean climate state; how small changes in individual feedbacks can cause large changes in the system sensitivity; and last, how the strength and even the sign of the feedback is dependent on the climate variable in question.
Abstract
The climate feedback framework partitions the radiative response to climate forcing into contributions from individual atmospheric processes. The goal of this study is to understand the closure of the energy budget in as much detail and precision as possible, within as clean an experimental setup as possible. Radiative kernels and radiative forcing are diagnosed for an aquaplanet simulation under perpetual equinox conditions. The role of the meridional structure of feedbacks, heat transport, and nonlinearities in controlling the local climate response is characterized. Results display a combination of positive subtropical feedbacks and polar amplified warming. These two factors imply a critical role for transport and nonlinear effects, with the latter acting to substantially reduce global climate sensitivity. At the hemispheric scale, a rich picture emerges: anomalous divergence of heat flux away from positive feedbacks in the subtropics; nonlinear interactions among and within clear-sky feedbacks, which reinforce the pattern of tropical cooling and high-latitude warming tendencies; and strong ice-line feedbacks that drive further amplification of polar warming. These results have implications for regional climate predictability, by providing an indication of how spatial patterns in feedbacks combine to affect both the local and nonlocal climate response, and how constraining uncertainty in those feedbacks may constrain the climate response.
Abstract
The climate feedback framework partitions the radiative response to climate forcing into contributions from individual atmospheric processes. The goal of this study is to understand the closure of the energy budget in as much detail and precision as possible, within as clean an experimental setup as possible. Radiative kernels and radiative forcing are diagnosed for an aquaplanet simulation under perpetual equinox conditions. The role of the meridional structure of feedbacks, heat transport, and nonlinearities in controlling the local climate response is characterized. Results display a combination of positive subtropical feedbacks and polar amplified warming. These two factors imply a critical role for transport and nonlinear effects, with the latter acting to substantially reduce global climate sensitivity. At the hemispheric scale, a rich picture emerges: anomalous divergence of heat flux away from positive feedbacks in the subtropics; nonlinear interactions among and within clear-sky feedbacks, which reinforce the pattern of tropical cooling and high-latitude warming tendencies; and strong ice-line feedbacks that drive further amplification of polar warming. These results have implications for regional climate predictability, by providing an indication of how spatial patterns in feedbacks combine to affect both the local and nonlocal climate response, and how constraining uncertainty in those feedbacks may constrain the climate response.
Abstract
Characterizing the relationship between large-scale atmospheric circulation patterns and the shape of the daily precipitation distribution is fundamental to understanding how dynamical changes are manifest in the hydrological cycle, and it is also relevant to issues such as natural hazard mitigation and reservoir management. This relationship is pursued using ENSO variability and the American West as a case study. When considering the full range of wintertime precipitation and consistent with conventional wisdom, mean precipitation intensity is enhanced during El Niño relative to La Niña in the Southwest and vice versa in the Northwest. This change in mean is attributed to a shift in the distribution of daily precipitation toward more intense daily rainfall rates. In addition, fundamental changes in the shape of the precipitation distributions are observed, independent of shifts in the mean. Surprisingly, for intense precipitation, La Niña winters actually demonstrate a significant increase in intensity (but not frequency) across the Southwest. A main lesson from this analysis is that, in response to ENSO variability, changes in extreme events can be significantly different from changes in the mean. In some instances, even the sign of the change is reversed. This result suggests that patterns of large-scale variability have an effect on the precipitation distribution that is nuanced, and they cannot be regarded as simply causing a shift in climatic zones. It also raises interesting questions concerning how best to establish confidence in climate predictions.
Abstract
Characterizing the relationship between large-scale atmospheric circulation patterns and the shape of the daily precipitation distribution is fundamental to understanding how dynamical changes are manifest in the hydrological cycle, and it is also relevant to issues such as natural hazard mitigation and reservoir management. This relationship is pursued using ENSO variability and the American West as a case study. When considering the full range of wintertime precipitation and consistent with conventional wisdom, mean precipitation intensity is enhanced during El Niño relative to La Niña in the Southwest and vice versa in the Northwest. This change in mean is attributed to a shift in the distribution of daily precipitation toward more intense daily rainfall rates. In addition, fundamental changes in the shape of the precipitation distributions are observed, independent of shifts in the mean. Surprisingly, for intense precipitation, La Niña winters actually demonstrate a significant increase in intensity (but not frequency) across the Southwest. A main lesson from this analysis is that, in response to ENSO variability, changes in extreme events can be significantly different from changes in the mean. In some instances, even the sign of the change is reversed. This result suggests that patterns of large-scale variability have an effect on the precipitation distribution that is nuanced, and they cannot be regarded as simply causing a shift in climatic zones. It also raises interesting questions concerning how best to establish confidence in climate predictions.
Abstract
The oxygen isotope time series from ice cores in central Greenland [the Greenland Ice Sheet Project 2 (GISP2) and the Greenland Ice Core Project (GRIP)] and West Antarctica (Byrd) provide a basis for evaluating the behavior of the climate system on millennial time scales. These time series have been invoked as evidence for mechanisms such as an interhemispheric climate seesaw or a stochastic resonance process. Statistical analyses are used to evaluate the extent to which these mechanisms characterize the observed time series. Simple models in which the Antarctic record reflects the Greenland record or its integral are statistically superior to a model in which the two time series are unrelated. However, these statistics depend primarily on the large events in the earlier parts of the record (between 80 and 50 kyr BP). For the shorter, millennial-scale (Dansgaard–Oeschger) events between 50 and 20 kyr BP, a first-order autoregressive [AR(1)] stochastic climate model with a physical time scale of τ = 600 ± 300 yr is a self-consistent explanation for the Antarctic record. For Greenland, AR(1) with τ = 400 ± 200 yr, plus a simple threshold rule, provides a statistically comparable characterization to stochastic resonance (though it cannot account for the strong 1500-yr spectral peak). The similarity of the physical time scales underlying the millennial-scale variability provides sufficient explanation for the similar appearance of the Greenland and Antarctic records during the 50–20-kyr BP interval. However, it cannot be ruled out that improved cross dating for these records may strengthen the case for an interhemispheric linkage on these shorter time scales. Additionally, the characteristic time scales for the records are significantly shorter during the most recent 10 kyr. Overall, these results suggest that millennial-scale variability is determined largely by regional processes that change significantly between glacial and interglacial climate regimes, with little influence between the Southern and Northern Hemispheres except during those largest events that involve major reorganizations of the ocean thermohaline circulation.
Abstract
The oxygen isotope time series from ice cores in central Greenland [the Greenland Ice Sheet Project 2 (GISP2) and the Greenland Ice Core Project (GRIP)] and West Antarctica (Byrd) provide a basis for evaluating the behavior of the climate system on millennial time scales. These time series have been invoked as evidence for mechanisms such as an interhemispheric climate seesaw or a stochastic resonance process. Statistical analyses are used to evaluate the extent to which these mechanisms characterize the observed time series. Simple models in which the Antarctic record reflects the Greenland record or its integral are statistically superior to a model in which the two time series are unrelated. However, these statistics depend primarily on the large events in the earlier parts of the record (between 80 and 50 kyr BP). For the shorter, millennial-scale (Dansgaard–Oeschger) events between 50 and 20 kyr BP, a first-order autoregressive [AR(1)] stochastic climate model with a physical time scale of τ = 600 ± 300 yr is a self-consistent explanation for the Antarctic record. For Greenland, AR(1) with τ = 400 ± 200 yr, plus a simple threshold rule, provides a statistically comparable characterization to stochastic resonance (though it cannot account for the strong 1500-yr spectral peak). The similarity of the physical time scales underlying the millennial-scale variability provides sufficient explanation for the similar appearance of the Greenland and Antarctic records during the 50–20-kyr BP interval. However, it cannot be ruled out that improved cross dating for these records may strengthen the case for an interhemispheric linkage on these shorter time scales. Additionally, the characteristic time scales for the records are significantly shorter during the most recent 10 kyr. Overall, these results suggest that millennial-scale variability is determined largely by regional processes that change significantly between glacial and interglacial climate regimes, with little influence between the Southern and Northern Hemispheres except during those largest events that involve major reorganizations of the ocean thermohaline circulation.
Abstract
The great continental ice sheets of the Pleistocene represented significant obstacles to the Northern Hemisphere midlatitude westerlies. They must therefore have forced large changes in the atmospheric circulation, and consequently also in the patterns of accumulation and melting over the ice sheets themselves. A simplified three-dimensional coupled ice sheet–stationary wave model is developed in order to understand the ice sheet’s response to the circulation changes that it induces. Consistent with ice age climate simulations, the ice sheet topography induces an anticyclonic circulation over the ice sheet, causing a slight warming over the western slopes and a stronger cooling over the remainder. The modeled feedbacks significantly affect the ice sheet configuration, with the most important influences being the patterns of summer temperature, and the topographically induced precipitation field. The time evolution of the ice sheet is also changed by the atmospheric feedbacks and the results suggest the possibility of multiple equilibrium solutions.
Abstract
The great continental ice sheets of the Pleistocene represented significant obstacles to the Northern Hemisphere midlatitude westerlies. They must therefore have forced large changes in the atmospheric circulation, and consequently also in the patterns of accumulation and melting over the ice sheets themselves. A simplified three-dimensional coupled ice sheet–stationary wave model is developed in order to understand the ice sheet’s response to the circulation changes that it induces. Consistent with ice age climate simulations, the ice sheet topography induces an anticyclonic circulation over the ice sheet, causing a slight warming over the western slopes and a stronger cooling over the remainder. The modeled feedbacks significantly affect the ice sheet configuration, with the most important influences being the patterns of summer temperature, and the topographically induced precipitation field. The time evolution of the ice sheet is also changed by the atmospheric feedbacks and the results suggest the possibility of multiple equilibrium solutions.
Abstract
The framework of feedback analysis is used to explore the controls on the shape of the probability distribution of global mean surface temperature response to climate forcing. It is shown that ocean heat uptake, which delays and damps the temperature rise, can be represented as a transient negative feedback. This transient negative feedback causes the transient climate change to have a narrower probability distribution than that of the equilibrium climate response (the climate sensitivity). In this sense, climate change is much more predictable than climate sensitivity. The width of the distribution grows gradually over time, a consequence of which is that the larger the climate change being contemplated, the greater the uncertainty is about when that change will be realized. Another consequence of this slow growth is that further efforts to constrain climate sensitivity will be of very limited value for climate projections on societally relevant time scales. Finally, it is demonstrated that the effect on climate predictability of reducing uncertainty in the atmospheric feedbacks is greater than the effect of reducing uncertainty in ocean feedbacks by the same proportion. However, at least at the global scale, the total impact of uncertainty in climate feedbacks is dwarfed by the impact of uncertainty in climate forcing, which in turn is contingent on choices made about future anthropogenic emissions.
Abstract
The framework of feedback analysis is used to explore the controls on the shape of the probability distribution of global mean surface temperature response to climate forcing. It is shown that ocean heat uptake, which delays and damps the temperature rise, can be represented as a transient negative feedback. This transient negative feedback causes the transient climate change to have a narrower probability distribution than that of the equilibrium climate response (the climate sensitivity). In this sense, climate change is much more predictable than climate sensitivity. The width of the distribution grows gradually over time, a consequence of which is that the larger the climate change being contemplated, the greater the uncertainty is about when that change will be realized. Another consequence of this slow growth is that further efforts to constrain climate sensitivity will be of very limited value for climate projections on societally relevant time scales. Finally, it is demonstrated that the effect on climate predictability of reducing uncertainty in the atmospheric feedbacks is greater than the effect of reducing uncertainty in ocean feedbacks by the same proportion. However, at least at the global scale, the total impact of uncertainty in climate feedbacks is dwarfed by the impact of uncertainty in climate forcing, which in turn is contingent on choices made about future anthropogenic emissions.
Abstract
Glaciers are direct recorders of climate history and have come to be regarded as emblematic of climate change. They respond to variations in both accumulation and ablation, which can have separate atmospheric controls, leading to some ambiguity in interpreting the causes of glacier changes. Both climate change and climate variability have characteristic spatial patterns and time scales. The focus of this study is the regional-scale response of glaciers to natural patterns of climate variability. Using the Pacific Northwest of North America as the setting, the authors employ a simple linear glacier model to study how the combination of patterns of melt-season temperature and patterns of annual accumulation produce patterns of glacier length variations. Regional-scale spatial correlations in glacier length variations reflect three factors: the spatial correlations in precipitation and melt-season temperature, the geometry of a glacier and how it determines the relative importance of temperature and precipitation, and the climatic setting of the glaciers (i.e., maritime or continental). With the self-consistent framework developed here, the authors are able to evaluate the relative importance of these three factors. The results also highlight that, in order to understand the natural variability of glaciers, it is critically important to know the small-scale patterns of climate in mountainous terrain. The method can be applied to any area containing mountain glaciers and provides a baseline expectation for natural glacier variation against which the effects of climate changes can be evaluated.
Abstract
Glaciers are direct recorders of climate history and have come to be regarded as emblematic of climate change. They respond to variations in both accumulation and ablation, which can have separate atmospheric controls, leading to some ambiguity in interpreting the causes of glacier changes. Both climate change and climate variability have characteristic spatial patterns and time scales. The focus of this study is the regional-scale response of glaciers to natural patterns of climate variability. Using the Pacific Northwest of North America as the setting, the authors employ a simple linear glacier model to study how the combination of patterns of melt-season temperature and patterns of annual accumulation produce patterns of glacier length variations. Regional-scale spatial correlations in glacier length variations reflect three factors: the spatial correlations in precipitation and melt-season temperature, the geometry of a glacier and how it determines the relative importance of temperature and precipitation, and the climatic setting of the glaciers (i.e., maritime or continental). With the self-consistent framework developed here, the authors are able to evaluate the relative importance of these three factors. The results also highlight that, in order to understand the natural variability of glaciers, it is critically important to know the small-scale patterns of climate in mountainous terrain. The method can be applied to any area containing mountain glaciers and provides a baseline expectation for natural glacier variation against which the effects of climate changes can be evaluated.
