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Abstract
It is a simple truism that public policy must be guided by an objective analysis of the physical and economic consequences of climate change. It is equally true that policy making is an inherently value-laden endeavor. While these two threads are interconnected, the relative weight given to each depends on the certainty that the technical analyses can deliver. For climate change, the envelope of uncertainty is best understood at the global scale, and there are some well known and formidable challenges to reducing it. This uncertainty must in turn be compounded with much more poorly constrained uncertainties in regional climate, climate impacts, and future economic costs. The case can be made that technical analyses have reached the point of diminishing returns. Should meaningful action on climate change await greater analytical certainty? This paper argues that policy makers should give greater weight to moral arguments, in no small part because that is where the heart of the debate really lies.
Abstract
It is a simple truism that public policy must be guided by an objective analysis of the physical and economic consequences of climate change. It is equally true that policy making is an inherently value-laden endeavor. While these two threads are interconnected, the relative weight given to each depends on the certainty that the technical analyses can deliver. For climate change, the envelope of uncertainty is best understood at the global scale, and there are some well known and formidable challenges to reducing it. This uncertainty must in turn be compounded with much more poorly constrained uncertainties in regional climate, climate impacts, and future economic costs. The case can be made that technical analyses have reached the point of diminishing returns. Should meaningful action on climate change await greater analytical certainty? This paper argues that policy makers should give greater weight to moral arguments, in no small part because that is where the heart of the debate really lies.
Abstract
The mass balance of a glacier is a complex consequence of the combination of atmospheric variables that control it. However, the understanding of past, present, and future glacier states is often predicated on very simplified representations of the mass balance–climate relationship. Here, a full surface energy and mass balance (SEMB) model is developed to explore the relationship between glacier equilibrium-line altitudes (ELAs) and climate at a regional scale. This model is applied to central Asia because of the diverse climate regimes and glacier history. The model captures the pattern in ELAs well; the seasonal cycle in energy balance terms are comparable to studies on individual glaciers in central Asia, and the proportionality factor relating melt to temperature is within the range of those reported for individual glaciers within the area. In regions where precipitation is low, ablation at the ELA is dominated by sublimation. Conversely, where precipitation is high, ablation at the ELA is dominated by melt and surface runoff. In turn, the sensitivity of the ELA to changes in climate is strongly tied to the dominant ablation process. In particular, ELAs in melt-dominated regions are most sensitive to interannual variability in air temperature, while ELAs in sublimation-dominated regions are most sensitive to interannual variability in precipitation. Glaciers in sublimation-dominated regions are acutely sensitive to even small changes in atmospheric variables. Finally, changes in clouds are shown to be important in all regions through their influence on the shortwave and longwave radiative fluxes, which dominate the surface energy balance at the ELA.
Abstract
The mass balance of a glacier is a complex consequence of the combination of atmospheric variables that control it. However, the understanding of past, present, and future glacier states is often predicated on very simplified representations of the mass balance–climate relationship. Here, a full surface energy and mass balance (SEMB) model is developed to explore the relationship between glacier equilibrium-line altitudes (ELAs) and climate at a regional scale. This model is applied to central Asia because of the diverse climate regimes and glacier history. The model captures the pattern in ELAs well; the seasonal cycle in energy balance terms are comparable to studies on individual glaciers in central Asia, and the proportionality factor relating melt to temperature is within the range of those reported for individual glaciers within the area. In regions where precipitation is low, ablation at the ELA is dominated by sublimation. Conversely, where precipitation is high, ablation at the ELA is dominated by melt and surface runoff. In turn, the sensitivity of the ELA to changes in climate is strongly tied to the dominant ablation process. In particular, ELAs in melt-dominated regions are most sensitive to interannual variability in air temperature, while ELAs in sublimation-dominated regions are most sensitive to interannual variability in precipitation. Glaciers in sublimation-dominated regions are acutely sensitive to even small changes in atmospheric variables. Finally, changes in clouds are shown to be important in all regions through their influence on the shortwave and longwave radiative fluxes, which dominate the surface energy balance at the ELA.
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 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.
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
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 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.
