The Met Office HadGEM3-ES chemistry–climate model: evaluation of stratospheric dynamics and its impact on ozone

Free-running and nudged versions of a Met Office chemistry–climate model are evaluated and used to investigate the impact of dynamics versus transport and chemistry within the model on the simulated evolution of stratospheric ozone. Metrics of the dynamical processes relevant for simulating stratospheric ozone are calculated, and the free-running model is found to outperform the previous model version in 10 of the 14 metrics. In particular, large biases in stratospheric transport and tropical tropopause temperature, which existed in the previous model version, are substantially reduced, making the current model more suitable for the simulation of stratospheric ozone. The spatial structure of the ozone hole, the area of polar stratospheric clouds, and the increased ozone concentrations in the Northern Hemisphere winter stratosphere following sudden stratospheric warmings, were all found to be sensitive to the accuracy of the dynamics and were better simulated in the nudged model than in the free-running model. Whilst nudging can, in general, provide a useful tool for removing the influence of dynamical biases from the evolution of chemical fields, this study shows that issues can remain in the climatology of nudged models. Significant biases in stratospheric vertical velocities, age of air, water vapour, and total column ozone still exist in the Met Office nudged model. Further, these can lead to biases in the downward flux of ozone into the troposphere

Simulations of Arctic ozone depletion with current and doubled levels of CO2

Results from idealized 3-D simulations of a dynamical-radiative-photochemical model of the stratosphere are presented for the Northern Hemisphere winter and spring. For a simulation of a quiescent winter, it is found that with current levels of CO2 only modest polar ozone depletion occurs, consistent with observations. For a second simulation with the same planetary wave amplitudes in the upper troposphere but with doubled CO2, the model predicts a northern hemisphere ozone hole comparable to that observed in Antarctica with almost complete ozone destruction at 20 km. Reasons for the marked difference between the simulations are identified

Climate change projections and stratosphere–troposphere interaction

Climate change is expected to increase winter rainfall and flooding in many extratropical regions as evaporation and precipitation rates increase, storms become more intense and storm tracks move polewards. Here, we show how changes in stratospheric circulation could play a significant role in future climate change in the extratropics through an additional shift in the tropospheric circulation. This shift in the circulation alters climate change in regional winter rainfall by an amount large enough to significantly alter regional climate change projections. The changes are consistent with changes in stratospheric winds inducing a change in the baroclinic eddy growth rate across the depth of the troposphere. A change in mean wind structure and an equatorward shift of the tropospheric storm tracks relative to models with poor stratospheric resolution allows coupling with surface climate. Using the Atlantic storm track as an example, we show how this can double the predicted increase in extreme winter rainfall over Western and Central Europe compared to other current climate projection

Evidence for changes in stratospheric transport and mixing over the past three decades based on multiple data sets and tropical leaky pipe analysis

Variability in the strength of the stratospheric Lagrangian mean meridional or Brewer-Dobson circulation and horizontal mixing into the tropics over the past three decades are examined using observations of stratospheric mean age of air and ozone. We use a simple representation of the stratosphere, the tropical leaky pipe (TLP) model, guided by mean meridional circulation and horizontal mixing changes in several reanalyses data sets and chemistry climate model (CCM) simulations, to help elucidate reasons for the observed changes in stratospheric mean age and ozone. We find that the TLP model is able to accurately simulate multiyear variability in ozone following recent major volcanic eruptions and the early 2000s sea surface temperature changes, as well as the lasting impact on mean age of relatively short-term circulation perturbations. We also find that the best quantitative agreement with the observed mean age and ozone trends over the past three decades is found assuming a small strengthening of the mean circulation in the lower stratosphere, a moderate weakening of the mean circulation in the middle and upper stratosphere, and a moderate increase in the horizontal mixing into the tropics. The mean age trends are strongly sensitive to trends in the horizontal mixing into the tropics, and the uncertainty in the mixing trends causes uncertainty in the mean circulation trends. Comparisons of the mean circulation and mixing changes suggested by the measurements with those from a recent suite of CCM runs reveal significant differences that may have important implications on the accurate simulation of future stratospheric climate

Air quality evaluation of London Paddington train station

Enclosed railway stations hosting diesel trains are at risk of reduced air quality as a result of exhaust emissions that may endanger passengers and workers. Air quality measurements were conducted inside London Paddington Station, a semi-enclosed railway station where 70% of trains are powered by diesel engines. Particulate matter (PM2.5) mass was measured at five station locations. PM size, PM number, oxides of nitrogen (NOx), and sulfur dioxide (SO2) were measured at two station locations. Paddington Station’s hourly mean PM2.5 mass concentrations averaged 16 μg/m3 [min 2, max 68]. Paddington Station’s hourly mean NO2 concentrations averaged 73 ppb [49, 120] and SO2 concentrations averaged 25 ppb [15, 37]. While UK train stations are not required to comply with air quality standards, there were five instances where the hourly mean NO2 concentrations exceeded the EU hourly mean limits (106 ppb) for outdoor air quality. PM2.5, SO2, and NO2 concentrations were compared against Marylebone, a busy London roadside 1.5 km from the station. The comparisons indicated that train station air quality was more polluted than the nearby roadside. PM2.5 for at least one measurement location within Paddington Station was shown to be statistically higher (P-value < 0.05) than Marylebone on 3 out of 4 days. Measured NO2 within Paddington Station was statistically higher than Marylebone on 4 out of 5 days. Measured SO2 within Paddington Station was statistically higher than Marylebone on all 3 days.We thank the Engineering and Physical Sciences Research Council (EP/F034350/1) for funding the Energy Efficient Cities Initiative and the Schiff Foundation for doctoral studentship funding.This is the final version of the article. It first appeared from IOP via http://dx.doi.org/10.1088/1748-9326/10/9/09401

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models

Stratosphere‐troposphere coupling and annular mode variability in chemistry‐climate models

The internal variability and coupling between the stratosphere and troposphere in CCMVal‐2 chemistry‐climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models’ annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well‐simulated stratosphere can improve simulation of tropospheric intraseasonal variability

Aeolus wind lidar observations of the 2019/2020 Quasi-Biennial Oscillation disruption with comparison to radiosondes and reanalysis

The quasi-biennial oscillation (QBO) was unexpectedly disrupted for only the second time in the historical record during the 2019/20 boreal winter. As the dominant mode of atmospheric variability in the tropical stratosphere, and a significant source of seasonal predictability globally, understanding the drivers behind this unusual behaviour is very important. Here, novel data from Aeolus, the first Doppler wind lidar in space, is used to observe the 2019/20 QBO disruption. Aeolus is the first satellite able to observe winds at high resolution on a global scale, and is therefore a uniquely capable platform for studying the evolution of the disruption and the broader circulation changes triggered by it. This study therefore contains the first direct wind observations of the QBO from space, and exploits measurements from a special Aeolus scanning mode, implemented to observe this disruption as it happened. Aeolus observes easterly winds of up to 20 ms&minus;1 in the core of the disruption jet during July 2020. By co-locating with radiosonde measurements from Singapore and ERA5 reanalysis, like-for-like comparisons of the observed wind structures in the tropical stratosphere are produced, showing equatorial Kelvin wave activity and key parts of the Walker Circulation during the disruption period. The onset of the disruption easterly jet occurs 5 days earlier in Aeolus observations compared with the reanalysis. This analysis highlights how Aeolus and future Doppler wind lidar satellites can deepen our understanding of the QBO, its disruptions, and the tropical upper-troposphere lower-stratosphere region more generally.</p

Chemistry–climate model simulations of twenty-first century stratospheric climate and circulation changes

The response of stratospheric climate and circulation to increasing amounts of greenhouse gases (GHGs) and ozone recovery in the twenty-first century is analyzed in simulations of 11 chemistry–climate models using near-identical forcings and experimental setup. In addition to an overall global cooling of the stratosphere in the simulations (0.59 6 0.07 K decade21 at 10 hPa), ozone recovery causes a warming of the Southern Hemisphere polar lower stratosphere in summer with enhanced cooling above. The rate of warming correlates with the rate of ozone recovery projected by the models and, on average, changes from 0.8 to 0.48 Kdecade21 at 100 hPa as the rate of recovery declines from the first to the second half of the century. In the winter northern polar lower stratosphere the increased radiative cooling from the growing abundance of GHGs is, in most models, balanced by adiabatic warming from stronger polar downwelling. In the Antarctic lower stratosphere the models simulate an increase in low temperature extremes required for polar stratospheric cloud (PSC) formation, but the positive trend is decreasing over the twenty-first century in all models. In the Arctic, none of the models simulates a statistically significant increase in Arctic PSCs throughout the twenty-first century. The subtropical jets accelerate in response to climate change and the ozone recovery produces awestward acceleration of the lower-stratosphericwind over theAntarctic during summer, though this response is sensitive to the rate of recovery projected by the models. There is a strengthening of the Brewer–Dobson circulation throughout the depth of the stratosphere, which reduces the mean age of air nearly everywhere at a rate of about 0.05 yr decade21 in those models with this diagnostic. On average, the annual mean tropical upwelling in the lower stratosphere (;70 hPa) increases by almost 2% decade21, with 59% of this trend forced by the parameterized orographic gravity wave drag in the models. This is a consequence of the eastward acceleration of the subtropical jets, which increases the upward flux of (parameterized) momentum reaching the lower stratosphere in these latitudes

Aeolus wind lidar observations of the 2019/2020 quasi-biennial oscillation disruption with comparison to radiosondes and reanalysis

The quasi-biennial oscillation (QBO) was unexpectedly disrupted for only the second time in the historical record during the 2019/2020 boreal winter. As the dominant mode of atmospheric variability in the tropical stratosphere and a significant source of seasonal predictability globally, understanding the drivers behind this unusual behaviour is very important. Here, novel data from Aeolus, the first Doppler wind lidar (DWL) in space, are used to observe the 2019/2020 QBO disruption. Aeolus is the first satellite able to observe winds at high resolution on a global scale, and it is therefore a uniquely capable platform for studying the evolution of the disruption and the broader circulation changes triggered by it. This study therefore contains the first direct wind observations of the QBO from space, and it exploits measurements from a special Aeolus scanning mode, implemented to observe this disruption as it happened. Aeolus observes easterly winds of up to 20 m s−1 in the core of the disruption jet during July 2020. By co-locating with radiosonde measurements from Singapore and the ERA5 reanalysis, comparisons of the observed wind structures in the tropical stratosphere are produced, showing differences in equatorial wave activity during the disruption period. Local zonal wind biases are found in both Aeolus and ERA5 around the tropopause, and the average Aeolus-ERA5 Rayleigh horizontal line-of-sight random error is found to be 7.58 m s−1. The onset of the QBO disruption easterly jet occurs 5 d earlier in Aeolus observations compared with the reanalysis. This discrepancy is linked to Kelvin wave variances that are 3 to 6 m2 s−2 higher in Aeolus compared with ERA5, centred on regions of maximum vertical wind shear in the tropical tropopause layer that are up to twice as sharp. The enhanced lower-stratospheric westerly winds which are known to help disrupt the QBO, perhaps with increasing frequency as the climate changes, are also stronger in Aeolus observations, with important implications for the future predictability of such disruptions. An investigation into differences in the equivalent depth of the most dominant Kelvin waves suggests that slower, shorter-vertical-wavelength waves break more readily in Aeolus observations compared with the reanalysis. This analysis therefore highlights how Aeolus and future DWL satellites can deepen our understanding of the QBO, its disruptions and the tropical upper-troposphere lower-stratosphere region more generally