A 1D RCE study of factors affecting the tropical tropopause layer and surface climate

There are discrepancies between global climate models regarding the evolution of the tropical tropopause layer (TTL) and also whether changes in ozone impact the surface under climate change. We use a 1D clear-sky radiative–convective equilibrium model to determine how a variety of factors can affect the TTL and how they influence surface climate. We develop a new method of convective adjustment, which relaxes the temperature profile toward the moist adiabat and allows for cooling above the level of neutral buoyancy. The TTL temperatures in our model are sensitive to CO2 concentration, ozone profile, the method of convective adjustment, and the upwelling velocity, which is used to calculate a dynamical cooling rate in the stratosphere. Moreover, the temperature response of the TTL to changes in each of the above factors sometimes depends on the others. The surface temperature response to changes in ozone and upwelling at and above the TTL is also strongly amplified by both stratospheric and tropospheric water vapor changes. With all these influencing factors, it is not surprising that global models disagree with regard to TTL structure and evolution and the influence of ozone changes on surface temperatures. On the other hand, the effect of doubling CO2 on the surface, including just radiative, water vapor, and lapse-rate feedbacks, is relatively robust to changes in convection, upwelling, or the applied ozone profile

Improvements to stratospheric chemistry scheme in the UM-UKCA (v10.7) model: solar cycle and heterogeneous reactions

Improvements are made to two areas of the United Kingdom Chemistry and Aerosol (UKCA) module, which forms part of the Met Office Unified Model (UM) used for weather and climate applications. Firstly, a solar cycle is added to the photolysis scheme. The effect on total column ozone of this addition was found to be around 1–2% in mid-latitude and equatorial regions in phase with the solar cycle. Secondly, reactions occurring on the surfaces of polar stratospheric clouds and sulfate aerosol are updated and extended by modification of the uptake coefficients of five existing reactions and the addition of a further eight reactions involving bromine species. These modifications are shown to reduce the overabundance of modeled total-column ozone in the Arctic during October to February, southern mid-latitudes during August, and the Antarctic during September. Antarctic springtime ozone depletion is shown to be enhanced by 25 DU on average, which now causes the ozone hole to be somewhat too deep compared to observations. We show that this is in part due to a cold bias of the Antarctic polar vortex in the model

Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence

Calculating a multi-model mean, a commonly used method for ensemble averaging, assumes model independence and equal model skill. Sharing of model components amongst families of models and research centres, conflated by growing ensemble size, means model independence cannot be assumed and is hard to quantify. We present a methodology to produce a weighted-model ensemble projection, accounting for model performance and model independence. Model weights are calculated by comparing model hindcasts to a selection of metrics chosen for their physical relevance to the process or phenomena of interest. This weighting methodology is applied to the Chemistry-Climate Model Initiative (CCMI) ensemble to investigate Antarctic ozone depletion and subsequent recovery. The weighted mean projects an ozone recovery to 1980 levels, by 2056 with a 95 % confidence interval (2052-2060), 4 years earlier than the most recent study. Perfect-model testing and out-of-sample testing validate the results and show a greater projective skill than a standard multi-model mean. Interestingly, the construction of a weighted mean also provides insight into model performance and dependence between the models. This weighting methodology is robust to both model and metric choices and therefore has potential applications throughout the climate and chemistry-climate modelling communities

Reconciling the climate and ozone response to the 1257 CE Mount Samalas eruption.

The 1257 CE eruption of Mount Samalas (Indonesia) is the source of the largest stratospheric injection of volcanic gases in the Common Era. Sulfur dioxide emissions produced sulfate aerosols that cooled Earth's climate with a range of impacts on society. The coemission of halogenated species has also been speculated to have led to wide-scale ozone depletion. Here we present simulations from HadGEM3-ES, a fully coupled Earth system model, with interactive atmospheric chemistry and a microphysical treatment of sulfate aerosol, used to assess the chemical and climate impacts from the injection of sulfur and halogen species into the stratosphere as a result of the Mt. Samalas eruption. While our model simulations support a surface air temperature response to the eruption of the order of -1°C, performing well against multiple reconstructions of surface temperature from tree-ring records, we find little evidence to support significant injections of halogens into the stratosphere. Including modest fractions of the halogen emissions reported from Mt. Samalas leads to significant impacts on the composition of the atmosphere and on surface temperature. As little as 20% of the halogen inventory from Mt. Samalas reaching the stratosphere would result in catastrophic ozone depletion, extending the surface cooling caused by the eruption. However, based on available proxy records of surface temperature changes, our model results support only very minor fractions (1%) of the halogen inventory reaching the stratosphere and suggest that further constraints are needed to fully resolve the issue.DTP-1502139 NE/S000887/1 NE/N006038/1 ACSIS UKC

Cloud impacts on photochemistry: Building a climatology of photolysis rates from the Atmospheric Tomography mission

Abstract. Measurements from actinic flux spectroradiometers on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission provide an extensive set of statistics on how clouds alter photolysis rates (J values) throughout the remote Pacific and Atlantic Ocean basins. J values control tropospheric ozone and methane abundances, and thus clouds have been included for more than three decades in tropospheric chemistry modeling. ATom made four profiling circumnavigations of the troposphere capturing each of the seasons during 2016–2018. This work examines J values from the Pacific Ocean flights of the first deployment, but publishes the complete Atom-1 data set (29 July to 23 August 2016). We compare the observed J values (every 3 s along flight track) with those calculated by nine global chemistry–climate/transport models (globally gridded, hourly, for a mid-August day). To compare these disparate data sets, we build a commensurate statistical picture of the impact of clouds on J values using the ratio of J-cloudy (standard, sometimes cloudy conditions) to J-clear (artificially cleared of clouds). The range of modeled cloud effects is inconsistently large but they fall into two distinct classes: (1) models with large cloud effects showing mostly enhanced J values aloft and or diminished at the surface and (2) models with small effects having nearly clear-sky J values much of the time. The ATom-1 measurements generally favor large cloud effects but are not precise or robust enough to point out the best cloud-modeling approach. The models here have resolutions of 50–200 km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average scattered sunlight over a mixed cloud field, but only out to scales of tens of kilometers. A primary uncertainty remains in the role of clouds in chemistry, in particular, how models average over cloud fields, and how such averages can simulate measurements. NERC ACSIS LTSM projec

Direct and ozone-mediated forcing of the Southern Annular Mode by greenhouse gases

We assess the roles of long-lived greenhouse gases and ozone depletion in driving meridional surface pressure gradients in the southern extratropics; these gradients are a defining feature of the Southern Annular Mode. Stratospheric ozone depletion is thought to have caused a strengthening of this mode during summer, with increasing long-lived greenhouse gases playing a secondary role. Using a coupled atmosphere-ocean chemistry-climate model, we show that there is cancelation between the direct, radiative effect of increasing greenhouse gases by the also substantial indirect—chemical and dynamical—feedbacks that greenhouse gases have via their impact on ozone. This sensitivity of the mode to greenhouse gas-induced ozone changes suggests that a consistent implementation of ozone changes due to long-lived greenhouse gases in climate models benefits the simulation of this important aspect of Southern Hemisphere 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

Top-Charm Associated Production in High Energy e+e−e^+e^- Collisions

The possibility of exploring the flavor changing neutral current $tcZ/tc\gamma$ couplings in the production vertex for the reaction \epem\to t\bar c + \bar tc is examined. Using a model independent parameterization for the effective Lagrangian to describe the most general three-point interactions, production cross sections are found to be relatively small at LEP II, but potentially sizeable at higher energy \epem colliders. The kinematic characteristics of the signal are studied and a set of cuts are devised for clean separation of the signal from background. The resulting sensitivity to anomalous flavor changing couplings at LEP II with an integrated luminosity of $4\times 500$ pb$^{-1}$ is found to be comparable to their present indirect constraints from loop processes, while at higher energy colliders with $0.5-1$ TeV center-of-mass energy and 50-200 fb$^{-1}$ luminosity, one expects to reach a sensitivity at or below the percentage level.Comment: Latex, 22 page

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

Description and evaluation of the UKCA stratosphere-troposphere chemistry scheme (StratTrop vn 1.0) implemented in UKESM1

Abstract. Here we present a description of the UKCA StratTrop chemical mechanism, which is used in the UKESM1 Earth system model for CMIP6. The StratTrop chemical mechanism is a merger of previously well-evaluated tropospheric and stratospheric mechanisms, and we provide results from a series of bespoke integrations to assess the overall performance of the model. We find that the StratTrop scheme performs well when compared to a wide array of observations. The analysis we present here focuses on key components of atmospheric composition, namely the performance of the model to simulate ozone in the stratosphere and troposphere and constituents that are important for ozone in these regions. We find that the results obtained for tropospheric ozone and its budget terms from the use of the StratTrop mechanism are sensitive to the host model; simulations with the same chemical mechanism run in an earlier version of the MetUM host model show a range of sensitivity to emissions that the current model does not fall within. Whilst the general model performance is suitable for use in the UKESM1 CMIP6 integrations, we note some shortcomings in the scheme that future targeted studies will address. NERC (NE/M00273X/1), NERC (NE/P016383/1), National Centre for Atmospheric Science (NERC) (via University of Leeds) (R8/H12/83/003