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Daniel Mitchell
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Daniel M. Mitchell, Andrew J. Charlton-Perez, and Lesley J. Gray

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.

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Dániel Topál, Qinghua Ding, Jonathan Mitchell, Ian Baxter, Mátyás Herein, Tímea Haszpra, Rui Luo, and Qingquan Li

Abstract

Arctic sea ice melting processes in summer due to internal atmospheric variability have recently received considerable attention. A regional barotropic atmospheric process over Greenland and the Arctic Ocean in summer (June–August), featuring either a year-to-year change or a low-frequency trend toward geopotential height rise, has been identified as an essential contributor to September sea ice loss, in both observations and the CESM1 Large Ensemble (CESM-LE) of simulations. This local melting is further found to be sensitive to remote sea surface temperature (SST) variability in the east-central tropical Pacific Ocean. Here, we utilize five available large “initial condition” Earth system model ensembles and 31 CMIP5 models’ preindustrial control simulations to show that the same atmospheric process, resembling the observed one and the one found in the CESM-LE, also dominates internal sea ice variability in summer on interannual to interdecadal time scales in preindustrial, historical, and future scenarios, regardless of the modeling environment. However, all models exhibit limitations in replicating the magnitude of the observed local atmosphere–sea ice coupling and its sensitivity to remote tropical SST variability in the past four decades. These biases call for caution in the interpretation of existing models’ simulations and fresh thinking about models’ credibility in simulating interactions of sea ice variability with the Arctic and global climate systems. Further efforts toward identifying the causes of these model limitations may provide implications for alleviating the biases and improving interannual- and decadal-time-scale sea ice prediction and future sea ice projection.

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Daniel M. Mitchell, Lesley J. Gray, James Anstey, Mark P. Baldwin, and Andrew J. Charlton-Perez

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.

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Daniel M. Mitchell, Scott M. Osprey, Lesley J. Gray, Neal Butchart, Steven C. Hardiman, Andrew J. Charlton-Perez, and Peter Watson

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.

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Daniel M. Mitchell, Scott M. Osprey, Lesley J. Gray, Neal Butchart, Steven C. Hardiman, Andrew J. Charlton-Perez, and Peter Watson
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Andrew D. King, Reto Knutti, Peter Uhe, Daniel M. Mitchell, Sophie C. Lewis, Julie M. Arblaster, and Nicolas Freychet

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.

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Christoph Zülicke, Erich Becker, Vivien Matthias, Dieter H. W. Peters, Hauke Schmidt, Han-Li Liu, Laura de la Torre Ramos, and Daniel M. Mitchell

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.

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Y. T. Eunice Lo, Daniel M. Mitchell, Sylvia I. Bohnenstengel, Mat Collins, Ed Hawkins, Gabriele C. Hegerl, Manoj Joshi, and Peter A. Stott

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.

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John C. Lin, Logan Mitchell, Erik Crosman, Daniel L. Mendoza, Martin Buchert, Ryan Bares, Ben Fasoli, David R. Bowling, Diane Pataki, Douglas Catharine, Courtenay Strong, Kevin R. Gurney, Risa Patarasuk, Munkhbayar Baasandorj, Alexander Jacques, Sebastian Hoch, John Horel, and Jim Ehleringer

Abstract

Urban areas are responsible for a substantial proportion of anthropogenic carbon emissions around the world. As global populations increasingly reside in cities, the role of urban emissions in determining the future trajectory of carbon emissions is magnified. Consequently, a number of research efforts have been started in the United States and beyond, focusing on observing atmospheric carbon dioxide (CO2) and relating its variations to carbon emissions in cities. Because carbon emissions are intimately tied to socioeconomic activity through the combustion of fossil fuels, and many cities are actively adopting emission reduction plans, such urban carbon research efforts give rise to opportunities for stakeholder engagement and guidance on other environmental issues, such as air quality.

This paper describes a research effort centered in the Salt Lake City, Utah, metropolitan region, which is the locus for one of the longest-running urban CO2 networks in the world. The Salt Lake City area provides a rich environment for studying anthropogenic emissions and for understanding the relationship between emissions and socioeconomic activity when the CO2 observations are enhanced with a) air quality observations, b) novel mobile observations from platforms on light-rail public transit trains and a news helicopter, c) dense meteorological observations, and d) modeling efforts that include atmospheric simulations and high-resolution emission inventories.

Carbon dioxide and other atmospheric observations are presented, along with associated modeling work. Examples in which the work benefited from and contributed to the interests of multiple stakeholders (e.g., policymakers, air quality managers, municipal government, urban planners, industry, and the general public) are discussed.

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