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Abstract. Accurate simulation of atmospheric circulation,particularly in the lower stratosphere, is challenging due to unresolvedwave–mean flow interactions and limited high-resolution observations for validation. Gravity-induced pressure gradients lead to a small butmeasurable separation of heavy and light gases by molecular diffusion in thestratosphere. Because the relative abundance of Ar to N2 is exclusivelycontrolled by physical transport, the argon-to-nitrogen ratio (Ar∕N2)provides an additional constraint on circulation and the age of air (AoA),i.e., the time elapsed since entry of an air parcel into the stratosphere. Here we use airborne measurements of N2O and Ar∕N2 from ninecampaigns with global coverage spanning 2008–2018 to calculate AoA and toquantify gravitational separation in the lowermost stratosphere. To thisend, we develop a new N2O–AoA relationship using a Markov chain Monte Carlo algorithm. We observe that gravitational separation increases systematically with increasing AoA for samples with AoA between 0 and 3 years. These observations are compared to a simulation of the TOMCAT/SLIMCAT 3-D chemical transport model, which has been updated to includegravitational fractionation of gases. We demonstrate that although AoA atold ages is slightly underestimated in the model, the relationship betweenAr∕N2 and AoA is robust and agrees with the observations. Thishighlights the potential of Ar∕N2 to become a new AoA tracer that is subject only to physical transport phenomena and can supplement the suite of available AoA indicators.

Abstract. Accurate simulation of atmospheric circulation, particularly in the lower stratosphere, is challenging due to unresolved wave-mean flow interactions and limited high-resolution observations for validation. Gravity-induced pressure gradients lead to a small but measurable separation of heavy and light gases by molecular diffusion in the stratosphere. Because the relative abundance of Ar to N2 is exclusively controlled by physical transport, the argon-to-nitrogen ratio (Ar/N2) provides an additional constraint on circulation and the age of air (AoA), i.e. the time elapsed since entry of an air parcel into the stratosphere. Here we use airborne measurements of N2O and Ar/N2 from nine campaigns with global coverage spanning 2008–2018 to calculate AoA and to quantify gravitational separation in the lowermost stratosphere. To this end, we develop a new N2O-AoA relationship using a Markov Chain Monte Carlo algorithm. We observe that gravitational separation increases systematically with increasing AoA for samples with AoA between 0 to 3 years. These observations are compared to a simulation of the TOMCAT/SLIMCAT 3-D chemical transport model, which has been updated to include gravitational fractionation of gases. We demonstrate that although AoA at old ages is slightly underestimated in the model, the relationship between Ar/N2 and AoA is robust and agrees with the observations. This highlights the potential of Ar/N2 to become a new AoA tracer that is subject only to physical transport phenomena and can supplement the suite of available AoA indicators.

Using model projections to study the emergence of observable climate signals presumes omniscient knowledge about the climate system. In reality, observational knowledge suffers from data quality and availability issues, for instance data gaps, changes in instrumentation, issues due to gridding and retrieval algorithms. Overlooking such deficiencies leads to misrepresentations of the time of emergence (ToE). We introduce a new definition of ToE that accounts for observational limitations, and show that significant corrections to the ToE may be necessary to achieve the same statistical confidence as would be afforded by omniscient knowledge. We also show how our method can inform future observational needs and observing systems design. Plain Language Summary: Long‐term planning for climate change adaptation requires accurate forecasts of climate impacts. Such forecasts are produced using computer models, which provide omniscient knowledge of the climate states they simulate. However, real‐world knowledge is based on incomplete and sometimes flawed observational data. Ignoring these flaws yields a distorted view of the timing of observable climate impacts. We propose a method to address this issue by accounting for observational limitations such as data gaps, changes in measuring equipment, data post‐processing, etc. We also show how to use the method to plan future data collection. Key Points: The degree of confidence placed in observed climate trends is misrepresented when overlooking observational limitationsWe provide a nonparametric method to account for such limitationsThe method can also inform the design of future observing platforms [ABSTRACT FROM AUTHOR]

The study of mixing in the stratosphere is important for understanding the transport of chemical species and the dynamics of the atmosphere. How best to quantify this mixing is not settled, however. In recent years, Lagrangian Coherent Structures (LCSs) have emerged as a valuable tool for examining mixing in fluid flows, and in this work we present a stratospheric mixing metric based on the LCS framework. We identify LCSs associated with the transport of air masses and quantify the amount of mixing between different regions of the atmosphere in the Whole Atmosphere Community Climate Model (WACCM). Our results show that LCSs provide a powerful approach to analyze mixing in the stratosphere and can be used to identify regions of high and low mixing as well as to study the dynamics of the atmosphere. The results are compared with those obtained two other tools to quantify mixing: the commonly used effective diffusivity and the recently introduced isentropic eddy diffusivity. We find qualitative agreement between these metrics for much of the stratosphere, although there are regions where they clearly disagree. A significant advantage of the LCS mixing metric is that it reflects Lagrangian transport in physical latitude rather than the equivalent latitude coordinate needed to calculate effective diffusivity, and we discuss other advantages and disadvantages of these methods. [ABSTRACT FROM AUTHOR]

Observational monitoring of the stratospheric transport circulation, the Brewer–Dobson circulation (BDC), is crucial to estimate any decadal to long-term changes therein, a prerequisite to interpret trends in stratospheric composition and to constrain the consequential impacts on climate. The transport time along the BDC (i.e. the mean stratospheric age of air, AoA) can best be deduced from trace gas measurements of tracers which increase linearly with time and are chemically passive. The gas sulfur hexafluoride (SF 6) is often used to deduce AoA because it has been increasing monotonically since the ∼ 1950s, and previously its chemical sinks in the mesosphere have been assumed to be negligible for AoA estimates. However, recent studies have shown that the chemical sinks of SF 6 are stronger than assumed and become increasingly relevant with rising SF 6 concentrations. To adjust biases in AoA that result from the chemical SF 6 sinks, we here propose a simple correction scheme for SF 6 -based AoA estimates accounting for the time-dependent effects of chemical sinks. The correction scheme is based on theoretical considerations with idealized assumptions, resulting in a relation between ideal AoA and apparent AoA which is a function of the tropospheric reference time series of SF 6 and of the AoA-dependent effective lifetime of SF 6. The correction method is thoroughly tested within a self-consistent data set from a climate model that includes explicit calculation of chemical SF 6 sinks. It is shown within the model that the correction successfully reduces biases in SF 6 -based AoA to less than 5 % for mean ages below 5 years. Tests using only subsampled data for deriving the fit coefficients show that applying the correction scheme even with imperfect knowledge of the sink is far superior to not applying a sink correction. Furthermore, we show that based on currently available measurements, we are not able to constrain the fit parameters of the correction scheme based on observational data alone. However, the model-based correction curve lies within the observational uncertainty, and we thus recommend using the model-derived fit coefficients until more high-quality measurements are able to further constrain the correction scheme. The application of the correction scheme to AoA from satellites and in situ data suggests that it is highly beneficial to reconcile different observational estimates of mean AoA. [ABSTRACT FROM AUTHOR]

Studying temperature probability distributions and the physical processes that shape them is important for understanding extreme temperature events. Previous work has used a conditional mean temperature framework to reveal whether horizontal temperature advection drives temperature to extreme or median values at a specific location as a method to dynamically interpret temperature probability distributions. In this paper, we generalize this method to study how other processes shape temperature probability distributions and explore the diverse effects of horizontal temperature advection on temperature probability distributions at different locations and different temperature percentiles. We apply this generalized method to several representative regions to demonstrate its use. We find that temperature advection drives temperatures toward more extreme values over most land in the midlatitudes (i.e., cold air advection occurs during cold anomalies and warm air advection occurs during warm anomalies). In contrast, we find that horizontal temperature advection dampens temperature anomalies in some coastal summer monsoon regions, where extreme temperatures result from other processes, such as horizontal humidity advection and vertical temperature advection. By calculating the mean of processes conditioned on the temperature percentile, this method enables composite analysis of processes that contribute to events for all percentiles and a range of processes. We show examples of composites at different percentiles for certain processes and regions to illustrate the conditional mean analysis. This general approach may benefit future studies related to temperature probability distributions and extreme events. [ABSTRACT FROM AUTHOR]

Lagrangian trajectories have previously been used to reconstruct water vapor variability in the lower stratosphere, where the sensitivity of surface radiation to changes in the water vapor concentration is strongest, by obtaining temperature histories of air parcels that ascend from the troposphere to the stratosphere through the tropical tropopause layer (TTL). Models and theory predict an acceleration of the Brewer-Dobson Circulation (BDC) and deceleration of the Walker Circulation (WC) with surface warming, and both of these will drive future changes to transport across the TTL. Here, we examine the response of TTL transport during boreal winter to idealized changes in the BDC and WC by comparing the temperature histories of trajectories computed with ERA5 data to those calculated using the same data but with altered vertical and zonal wind velocities. We find that lower stratospheric water vapor mixing ratios calculated from trajectories' cold point temperatures can increase by about 1.6 ppmv (about 50 %) when only zonal winds are slowed, while changes to vertical winds have a negligible impact on water vapor concentrations. This change follows from a decrease in zonal sampling of the temperature field by trajectories, which weakens the 'cold trap' mechanism of dehydration as TTL transport evolves. As the zonal winds of the TTL decrease, the fraction of air that passes through the cold trap while ascending to the stratosphere will decrease and the coldest average temperature experienced by parcels will increase. Some of the resultant moistening may be negated by a decreased rate of temperature change following the cold point, which will allow more ice to gravitationally settle before sublimating outside of the cold trap. This result presents a mechanism for a stratospheric water vapor feedback that can exist without changes to TTL temperatures. [ABSTRACT FROM AUTHOR]

As the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to proliferate across the globe, it is a struggle to predict and prevent its spread. The successes of mobility interventions demonstrate how policies can help limit the person-to-person interactions that are essential to infection. With significant community spread, experts predict this virus will continue to be a threat until safe and effective vaccines have been developed andwidely deployed. We aimto understand mobility changes during the first major quarantine period in the United States, measured via mobile device tracking, by assessing how people changed their behavior in response to policies and to weather. Here, we show that consistent national messaging was associated with consistent national behavioral change, regardless of local policy. Furthermore, although human behavior did vary with outdoor air temperature, these variations were not associated with variations in a proxy for the rate of encounters between people. The independence of encounters and temperatures suggests that weather-related behavioral changes will, in many cases, be of limited relevance for SARS-CoV-2 transmission dynamics. Both of these results are encouraging for the potential of clear national messaging to help contain any future pandemics, and possibly to help contain COVID-19. [ABSTRACT FROM AUTHOR]

Accurate simulation of atmospheric circulation, particularly in the lower stratosphere, is challenging due to unresolved wave-mean flow interactions and limited high-resolution observations for validation. Gravity-induced pressure gradients lead to a small but measurable separation of heavy and light gases by molecular diffusion in the stratosphere. Because the relative abundance of Ar to N2 is exclusively controlled by physical transport, the argon-to-nitrogen ratio (Ar/N2) provides an additional constraint on circulation and the age of air (AoA), i.e. the time elapsed since entry of an air parcel into the stratosphere. Here we use airborne measurements of N2O and Ar/N2 from nine campaigns with global coverage spanning 2008–2018 to calculate AoA and to quantify gravitational separation in the lowermost stratosphere. To this end, we develop a new N2O-AoA relationship using a Markov Chain Monte Carlo algorithm. We observe that gravitational separation increases systematically with increasing AoA for samples with AoA between 0 to 3 years. These observations are compared to a simulation of the TOMCAT/SLIMCAT 3-D chemical transport model, which has been updated to include gravitational fractionation of gases. We demonstrate that although AoA at old ages is slightly underestimated in the model, the relationship between Ar/N2 and AoA is robust and agrees with the observations. This highlights the potential of Ar/N2 to become a new AoA tracer that is subject only to physical transport phenomena and can supplement the suite of available AoA indicators. [ABSTRACT FROM AUTHOR]

The circulation of the stratosphere, also known as the Brewer-Dobson circulation, transports water vapor and ozone, with implications for radiative forcing and climate. This circulation is typically quantified from model output by calculating the tropical upwelling vertical velocity in the residual circulation framework, and it is estimated from observations by using time series of tropical water vapor to infer a vertical velocity. Recent theory has introduced a method to calculate the global mean diabatic circulation strength through isentropes from satellite measurements of long-lived tracers. In this paper, we explore this global diabatic circulation as it relates to the residual circulation vertical velocity, stratospheric water vapor, and ozone at interannual timescales. We use a comprehensive climate model, three reanalysis data products, and satellite ozone data. The different metrics for the circulation have different properties, especially with regards to the vertical autocorrelation. In the model, the different residual circulation metrics agree closely and are well correlated with the global diabatic circulation, except in the lowermost stratosphere. In the reanalysis products however, there are more differences throughout, indicating the dynamical inconsistencies of these products. The vertical velocity derived from the time series of water vapor in the tropics is significantly correlated with the diabatic circulation, but this relationship is not as strong as that between the diabatic circulation and the residual circulation vertical velocity. We find that the diabatic circulation in the lower to middle stratosphere (up to 500 K) is correlated with the total column ozone in the high latitudes and in the tropics. The upper level circulation is also correlated with the total column ozone, primarily in the subtropics, and we show that this is due to the correlation of both the circulation and the ozone with upper level temperatures. [ABSTRACT FROM AUTHOR]