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- Author or Editor: Daniel M. Mitchell x
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Abstract
The mean state, variability, and extreme variability of the stratospheric polar vortices, with an emphasis on the Northern Hemisphere (NH) vortex, are examined using two-dimensional moment analysis and extreme value theory (EVT). The use of moments as an analysis tool gives rise to information about the vortex area, centroid latitude, aspect ratio, and kurtosis. The application of EVT to these moment-derived quantities allows the extreme variability of the vortex to be assessed. The data used for this study are 40-yr ECMWF Re-Analysis (ERA-40) potential vorticity fields on interpolated isentropic surfaces that range from 450 to 1450 K.
Analyses show that the most extreme vortex variability occurs most commonly in late January and early February, consistent with when most planetary wave driving from the troposphere is observed. Composites around sudden stratospheric warming (SSW) events reveal that the moment diagnostics evolve in statistically different ways between vortex splitting events and vortex displacement events, in contrast to the traditional diagnostics. Histograms of the vortex diagnostics on the 850-K (~10 hPa) surface over the 1958–2001 period are fitted with parametric distributions and show that SSW events constitute the majority of data in the tails of the distributions. The distribution of each diagnostic is computed on various surfaces throughout the depth of the stratosphere; it shows that in general the vortex becomes more circular with higher filamentation at the upper levels. The Northern and Southern Hemisphere (SH) vortices are also compared through the analysis of their respective vortex diagnostics, confirming that the SH vortex is less variable and lacks extreme events compared to the NH vortex. Finally, extreme value theory is used to statistically model the vortex diagnostics and make inferences about the underlying dynamics of the polar vortices.
Abstract
The mean state, variability, and extreme variability of the stratospheric polar vortices, with an emphasis on the Northern Hemisphere (NH) vortex, are examined using two-dimensional moment analysis and extreme value theory (EVT). The use of moments as an analysis tool gives rise to information about the vortex area, centroid latitude, aspect ratio, and kurtosis. The application of EVT to these moment-derived quantities allows the extreme variability of the vortex to be assessed. The data used for this study are 40-yr ECMWF Re-Analysis (ERA-40) potential vorticity fields on interpolated isentropic surfaces that range from 450 to 1450 K.
Analyses show that the most extreme vortex variability occurs most commonly in late January and early February, consistent with when most planetary wave driving from the troposphere is observed. Composites around sudden stratospheric warming (SSW) events reveal that the moment diagnostics evolve in statistically different ways between vortex splitting events and vortex displacement events, in contrast to the traditional diagnostics. Histograms of the vortex diagnostics on the 850-K (~10 hPa) surface over the 1958–2001 period are fitted with parametric distributions and show that SSW events constitute the majority of data in the tails of the distributions. The distribution of each diagnostic is computed on various surfaces throughout the depth of the stratosphere; it shows that in general the vortex becomes more circular with higher filamentation at the upper levels. The Northern and Southern Hemisphere (SH) vortices are also compared through the analysis of their respective vortex diagnostics, confirming that the SH vortex is less variable and lacks extreme events compared to the NH vortex. Finally, extreme value theory is used to statistically model the vortex diagnostics and make inferences about the underlying dynamics of the polar vortices.
Abstract
A strong link exists between stratospheric variability and anomalous weather patterns at the earth’s surface. Specifically, during extreme variability of the Arctic polar vortex termed a “weak vortex event,” anomalies can descend from the upper stratosphere to the surface on time scales of weeks. Subsequently the outbreak of cold-air events have been noted in high northern latitudes, as well as a quadrupole pattern in surface temperature over the Atlantic and western European sectors, but it is currently not understood why certain events descend to the surface while others do not. This study compares a new classification technique of weak vortex events, based on the distribution of potential vorticity, with that of an existing technique and demonstrates that the subdivision of such events into vortex displacements and vortex splits has important implications for tropospheric weather patterns on weekly to monthly time scales. Using reanalysis data it is found that vortex splitting events are correlated with surface weather and lead to positive temperature anomalies over eastern North America of more than 1.5 K, and negative anomalies over Eurasia of up to −3 K. Associated with this is an increase in high-latitude blocking in both the Atlantic and Pacific sectors and a decrease in European blocking. The corresponding signals are weaker during displacement events, although ultimately they are shown to be related to cold-air outbreaks over North America. Because of the importance of stratosphere–troposphere coupling for seasonal climate predictability, identifying the type of stratospheric variability in order to capture the correct surface response will be necessary.
Abstract
A strong link exists between stratospheric variability and anomalous weather patterns at the earth’s surface. Specifically, during extreme variability of the Arctic polar vortex termed a “weak vortex event,” anomalies can descend from the upper stratosphere to the surface on time scales of weeks. Subsequently the outbreak of cold-air events have been noted in high northern latitudes, as well as a quadrupole pattern in surface temperature over the Atlantic and western European sectors, but it is currently not understood why certain events descend to the surface while others do not. This study compares a new classification technique of weak vortex events, based on the distribution of potential vorticity, with that of an existing technique and demonstrates that the subdivision of such events into vortex displacements and vortex splits has important implications for tropospheric weather patterns on weekly to monthly time scales. Using reanalysis data it is found that vortex splitting events are correlated with surface weather and lead to positive temperature anomalies over eastern North America of more than 1.5 K, and negative anomalies over Eurasia of up to −3 K. Associated with this is an increase in high-latitude blocking in both the Atlantic and Pacific sectors and a decrease in European blocking. The corresponding signals are weaker during displacement events, although ultimately they are shown to be related to cold-air outbreaks over North America. Because of the importance of stratosphere–troposphere coupling for seasonal climate predictability, identifying the type of stratospheric variability in order to capture the correct surface response will be necessary.
Abstract
With extreme variability of the Arctic polar vortex being a key link for stratosphere–troposphere influences, its evolution into the twenty-first century is important for projections of changing surface climate in response to greenhouse gases. Variability of the stratospheric vortex is examined using a state-of-the-art climate model and a suite of specifically developed vortex diagnostics. The model has a fully coupled ocean and a fully resolved stratosphere. Analysis of the standard stratospheric zonal mean wind diagnostic shows no significant increase over the twenty-first century in the number of major sudden stratospheric warmings (SSWs) from its historical value of 0.7 events per decade, although the monthly distribution of SSWs does vary, with events becoming more evenly dispersed throughout the winter. However, further analyses using geometric-based vortex diagnostics show that the vortex mean state becomes weaker, and the vortex centroid is climatologically more equatorward by up to 2.5°, especially during early winter. The results using these diagnostics not only characterize the vortex structure and evolution but also emphasize the need for vortex-centric diagnostics over zonally averaged measures. Finally, vortex variability is subdivided into wave-1 (displaced) and -2 (split) components, and it is implied that vortex displacement events increase in frequency under climate change, whereas little change is observed in splitting events.
Abstract
With extreme variability of the Arctic polar vortex being a key link for stratosphere–troposphere influences, its evolution into the twenty-first century is important for projections of changing surface climate in response to greenhouse gases. Variability of the stratospheric vortex is examined using a state-of-the-art climate model and a suite of specifically developed vortex diagnostics. The model has a fully coupled ocean and a fully resolved stratosphere. Analysis of the standard stratospheric zonal mean wind diagnostic shows no significant increase over the twenty-first century in the number of major sudden stratospheric warmings (SSWs) from its historical value of 0.7 events per decade, although the monthly distribution of SSWs does vary, with events becoming more evenly dispersed throughout the winter. However, further analyses using geometric-based vortex diagnostics show that the vortex mean state becomes weaker, and the vortex centroid is climatologically more equatorward by up to 2.5°, especially during early winter. The results using these diagnostics not only characterize the vortex structure and evolution but also emphasize the need for vortex-centric diagnostics over zonally averaged measures. Finally, vortex variability is subdivided into wave-1 (displaced) and -2 (split) components, and it is implied that vortex displacement events increase in frequency under climate change, whereas little change is observed in splitting events.
Abstract
Given the Paris Agreement it is imperative there is greater understanding of the consequences of limiting global warming to the target 1.5° and 2°C levels above preindustrial conditions. It is challenging to quantify changes across a small increment of global warming, so a pattern-scaling approach may be considered. Here we investigate the validity of such an approach by comprehensively examining how well local temperatures and warming trends in a 1.5°C world predict local temperatures at global warming of 2°C. Ensembles of transient coupled climate simulations from multiple models under different scenarios were compared and individual model responses were analyzed. For many places, the multimodel forced response of seasonal-average temperatures is approximately linear with global warming between 1.5° and 2°C. However, individual model results vary and large contributions from nonlinear changes in unforced variability or the forced response cannot be ruled out. In some regions, such as East Asia, models simulate substantially greater warming than is expected from linear scaling. Examining East Asia during boreal summer, we find that increased warming in the simulated 2°C world relative to scaling up from 1.5°C is related to reduced anthropogenic aerosol emissions. Our findings suggest that, where forcings other than those due to greenhouse gas emissions change, the warming experienced in a 1.5°C world is a poor predictor for local climate at 2°C of global warming. In addition to the analysis of the linearity in the forced climate change signal, we find that natural variability remains a substantial contribution to uncertainty at these low-warming targets.
Abstract
Given the Paris Agreement it is imperative there is greater understanding of the consequences of limiting global warming to the target 1.5° and 2°C levels above preindustrial conditions. It is challenging to quantify changes across a small increment of global warming, so a pattern-scaling approach may be considered. Here we investigate the validity of such an approach by comprehensively examining how well local temperatures and warming trends in a 1.5°C world predict local temperatures at global warming of 2°C. Ensembles of transient coupled climate simulations from multiple models under different scenarios were compared and individual model responses were analyzed. For many places, the multimodel forced response of seasonal-average temperatures is approximately linear with global warming between 1.5° and 2°C. However, individual model results vary and large contributions from nonlinear changes in unforced variability or the forced response cannot be ruled out. In some regions, such as East Asia, models simulate substantially greater warming than is expected from linear scaling. Examining East Asia during boreal summer, we find that increased warming in the simulated 2°C world relative to scaling up from 1.5°C is related to reduced anthropogenic aerosol emissions. Our findings suggest that, where forcings other than those due to greenhouse gas emissions change, the warming experienced in a 1.5°C world is a poor predictor for local climate at 2°C of global warming. In addition to the analysis of the linearity in the forced climate change signal, we find that natural variability remains a substantial contribution to uncertainty at these low-warming targets.
Abstract
The vertical coupling between the stratosphere and the mesosphere is diagnosed from polar cap temperatures averaged over 60°–90°N with a new method: the joint occurrence of a warm stratosphere at 10 hPa and a cold mesosphere at 0.01 hPa. The investigation of an 11-yr-long dataset (2004–15) from Aura-MLS observations shows that such mesospheric coupling days appear in 7% of the winter. During major sudden stratospheric warming events mesospheric couplings are present with an enhanced average daily frequency of 22%. This daily frequency changes from event to event but broadly results in five of seven major warmings being classified as mesospheric couplings (2006, 2008, 2009, 2010, and 2013). The observed fraction of mesospheric coupling events (71%) is compared with simulations of the Kühlungsborn Mechanistic Circulation Model (KMCM), the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), and the Whole Atmosphere Community Climate Model (WACCM). The simulated fraction of mesospheric coupling events ranges between 57% and 94%, which fits the observations. In searching for causal relations weak evidence is found that major warming events with strong intensity or split vortices favor their coupling with the upper mesosphere. More evidence is found with a conceptual model: an effective vertical coupling between 10 and 0.01 hPa is provided by deep zonal-mean easterlies at 60°N, which are acting as a gravity-wave guide. The explained variance is above 40% in the four datasets, which indicates a near-realistic simulation of this process.
Abstract
The vertical coupling between the stratosphere and the mesosphere is diagnosed from polar cap temperatures averaged over 60°–90°N with a new method: the joint occurrence of a warm stratosphere at 10 hPa and a cold mesosphere at 0.01 hPa. The investigation of an 11-yr-long dataset (2004–15) from Aura-MLS observations shows that such mesospheric coupling days appear in 7% of the winter. During major sudden stratospheric warming events mesospheric couplings are present with an enhanced average daily frequency of 22%. This daily frequency changes from event to event but broadly results in five of seven major warmings being classified as mesospheric couplings (2006, 2008, 2009, 2010, and 2013). The observed fraction of mesospheric coupling events (71%) is compared with simulations of the Kühlungsborn Mechanistic Circulation Model (KMCM), the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), and the Whole Atmosphere Community Climate Model (WACCM). The simulated fraction of mesospheric coupling events ranges between 57% and 94%, which fits the observations. In searching for causal relations weak evidence is found that major warming events with strong intensity or split vortices favor their coupling with the upper mesosphere. More evidence is found with a conceptual model: an effective vertical coupling between 10 and 0.01 hPa is provided by deep zonal-mean easterlies at 60°N, which are acting as a gravity-wave guide. The explained variance is above 40% in the four datasets, which indicates a near-realistic simulation of this process.
Abstract
In the United Kingdom, where 90% of residents are projected to live in urban areas by 2050, projecting changes in urban heat islands (UHIs) is essential to municipal adaptation. Increased summer temperatures are linked to increased mortality. Using the new regional U.K. Climate Projections, UKCP18-regional, we estimate the 1981–2079 trends in summer urban and rural near-surface air temperatures and in UHI intensities during day and at night in the 10 most populous built-up areas in England. Summer temperatures increase by 0.45°–0.81°C per decade under RCP8.5, depending on the time of day and location. Nighttime temperatures increase more in urban than rural areas, enhancing the nighttime UHI by 0.01°–0.05°C per decade in all cities. When these upward UHI signals emerge from 2008–18 variability, positive summer nighttime UHI intensities of up to 1.8°C are projected in most cities. However, we can prevent most of these upward nighttime UHI signals from emerging by stabilizing climate to the Paris Agreement target of 2°C above preindustrial levels. In contrast, daytime UHI intensities decrease in nine cities, at rates between −0.004° and −0.05°C per decade, indicating a trend toward a reduced daytime UHI effect. These changes reflect different feedbacks over urban and rural areas and are specific to UKCP18-regional. Future research is important to better understand the drivers of these UHI intensity changes.
Abstract
In the United Kingdom, where 90% of residents are projected to live in urban areas by 2050, projecting changes in urban heat islands (UHIs) is essential to municipal adaptation. Increased summer temperatures are linked to increased mortality. Using the new regional U.K. Climate Projections, UKCP18-regional, we estimate the 1981–2079 trends in summer urban and rural near-surface air temperatures and in UHI intensities during day and at night in the 10 most populous built-up areas in England. Summer temperatures increase by 0.45°–0.81°C per decade under RCP8.5, depending on the time of day and location. Nighttime temperatures increase more in urban than rural areas, enhancing the nighttime UHI by 0.01°–0.05°C per decade in all cities. When these upward UHI signals emerge from 2008–18 variability, positive summer nighttime UHI intensities of up to 1.8°C are projected in most cities. However, we can prevent most of these upward nighttime UHI signals from emerging by stabilizing climate to the Paris Agreement target of 2°C above preindustrial levels. In contrast, daytime UHI intensities decrease in nine cities, at rates between −0.004° and −0.05°C per decade, indicating a trend toward a reduced daytime UHI effect. These changes reflect different feedbacks over urban and rural areas and are specific to UKCP18-regional. Future research is important to better understand the drivers of these UHI intensity changes.
The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice water path in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for their improvement.
Currently, there are significant discrepancies among the algorithms for ice clouds with very small optical depths (τ < 0.3) and those with 1 < τ < 5. The good news is that for thin clouds (0.3 < τ < 1), the algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.
The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice water path in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for their improvement.
Currently, there are significant discrepancies among the algorithms for ice clouds with very small optical depths (τ < 0.3) and those with 1 < τ < 5. The good news is that for thin clouds (0.3 < τ < 1), the algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.
