Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000–2016 period

The modeling study presented here aims to estimate how uncertainties in global hydroxyl radical (OH) distributions, variability, and trends may contribute to resolving discrepancies between simulated and observed methane (CH4) changes since 2000. A multi-model ensemble of 14 OH fields was analyzed and aggregated into 64 scenarios to force the offline atmospheric chemistry transport model LMDz (Laboratoire de Meteorologie Dynamique) with a standard CH4 emission scenario over the period 2000–2016. The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000–2010 ranges between 8:7*10^5 and 12:8*10^5 molec cm-3. The inter-model differences in tropospheric OH burden and vertical distributions are mainly determined by the differences in the nitrogen oxide (NO) distributions, while the spatial discrepancies between OH fields are mostly due to differences in natural emissions and volatile organic compound (VOC) chemistry. From 2000 to 2010, most simulated OH fields show an increase of 0.1–0:3*10^5 molec cm-3 in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960–2000. Once ingested into the LMDz model, these OH changes translated into a 5 to 15 ppbv reduction in the CH4 mixing ratio in 2010, which represents 7%–20% of the model-simulated CH4 increase due to surface emissions. Between 2010 and 2016, the ensemble of simulations showed that OH changes could lead to a CH4 mixing ratio uncertainty of > 30 ppbv. Over the full 2000–2016 time period, using a common stateof- the-art but nonoptimized emission scenario, the impact of [OH] changes tested here can explain up to 54% of the gap between model simulations and observations. This result emphasizes the importance of better representing OH abundance and variations in CH4 forward simulations and emission optimizations performed by atmospheric inversions

Future global mortality from changes in air pollution attributable to climate change

Ground-level ozone and fine particulate matter (PM2.5) are associated with premature human mortality1-4; their future concentrations depend on changes in emissions, which dominate the near-term5, and on climate change6,7. Previous global studies of the air quality-related health effects of future climate change8,9 used single atmospheric models. However, in related studies, mortality results differ among models10-12. Here we use an ensemble of global chemistry-climate models13 to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.514, is likely positive. We estimate 3,340 (-30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (-195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM2.5, we estimate 55,600 (-34,300 to 164,000) deaths in 2030 and 215,000 (-76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation will likely reduce air pollution-related mortality

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

Regional evaluation of the performance of the global CAMS chemical modeling system over the United States (IFS cycle 47r1)

International audienceAbstract. The Copernicus Atmosphere Monitoring Service (CAMS) provides routine analyses and forecasts of trace gases and aerosols on a global scale. The core is the European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), where modules for atmospheric chemistry and aerosols have been introduced and which allows for data assimilation of satellite retrievals of composition. We have updated both the homogeneous and heterogeneous NOx chemistry applied in the three independent tropospheric–stratospheric chemistry modules maintained within CAMS, referred to as IFS(CB05BASCOE), IFS(MOCAGE) and IFS(MOZART). Here we focus on the evaluation of main trace gas products from these modules that are of interest as markers of air quality, namely lower-tropospheric O3, NO2 and CO, with a regional focus over the contiguous United States. Evaluation against lower-tropospheric composition reveals overall good performance, with chemically induced biases within 10 ppb across species for regions within the US with respect to a range of observations. The versions show overall equal or better performance than the CAMS reanalysis, which includes data assimilation. Evaluation of surface air quality aspects shows that annual cycles are captured well, albeit with variable seasonal biases. During wintertime conditions there is a large model spread between chemistry schemes in lower-tropospheric O3 (∼ 10 %–35 %) and, in turn, oxidative capacity related to NOx lifetime differences. Analysis of differences in the HNO3 and PAN formation, which act as reservoirs for reactive nitrogen, revealed a general underestimate in PAN formation over polluted regions, likely due to too low organic precursors. Particularly during wintertime, the fraction of NO2 sequestered into PAN has a variability of 100 % across chemistry modules, indicating the need for further constraints. Notably, a considerable uncertainty in HNO3 formation associated with wintertime N2O5 conversion on wet particle surfaces remains. In summary, this study has indicated that the chemically induced differences in the quality of CAMS forecast products over the United States depends on season, trace gas, altitude and region. While analysis of the three chemistry modules in CAMS provide a strong handle on uncertainties associated with chemistry modeling, the further improvement of operational products additionally requires coordinated development involving emissions handling, chemistry and aerosol modeling, complemented with data-assimilation efforts

Effect of climate change on surface ozone over North America, Europe, and East Asia.

The effect of future climate change on surface ozone over North America, Europe, and East Asia is evaluated using present-day (2000s) and future (2100s) hourly surface ozone simulated by four global models. Future climate follows RCP8.5, while methane and anthropogenic ozone precursors are fixed at year-2000 levels. Climate change shifts the seasonal surface ozone peak to earlier in the year and increases the amplitude of the annual cycle. Increases in mean summertime and high-percentile ozone are generally found in polluted environments, while decreases are found in clean environments. We propose climate change augments the efficiency of precursor emissions to generate surface ozone in polluted regions, thus reducing precursor export to neighboring downwind locations. Even with constant biogenic emissions, climate change causes the largest ozone increases at high percentiles. In most cases, air quality extreme episodes become larger and contain higher ozone levels relative to the rest of the distribution

Effect of climate change on surface ozone over North America, Europe, and East Asia.

The effect of future climate change on surface ozone over North America, Europe, and East Asia is evaluated using present-day (2000s) and future (2100s) hourly surface ozone simulated by four global models. Future climate follows RCP8.5, while methane and anthropogenic ozone precursors are fixed at year-2000 levels. Climate change shifts the seasonal surface ozone peak to earlier in the year and increases the amplitude of the annual cycle. Increases in mean summertime and high-percentile ozone are generally found in polluted environments, while decreases are found in clean environments. We propose climate change augments the efficiency of precursor emissions to generate surface ozone in polluted regions, thus reducing precursor export to neighboring downwind locations. Even with constant biogenic emissions, climate change causes the largest ozone increases at high percentiles. In most cases, air quality extreme episodes become larger and contain higher ozone levels relative to the rest of the distribution

Effect of climate change on surface ozone over North America, Europe, and East Asia

The effect of future climate change on surface ozone over North America, Europe, and East Asia is evaluated using present-day (2000s) and future (2100s) hourly surface ozone simulated by four global models. Future climate follows RCP8.5, while methane and anthropogenic ozone precursors are fixed at year-2000 levels. Climate change shifts the seasonal surface ozone peak to earlier in the year and increases the amplitude of the annual cycle. Increases in mean summertime and high-percentile ozone are generally found in polluted environments, while decreases are found in clean environments. We propose climate change augments the efficiency of precursor emissions to generate surface ozone in polluted regions, thus reducing precursor export to neighboring downwind locations. Even with constant biogenic emissions, climate change causes the largest ozone increases at high percentiles. In most cases, air quality extreme episodes become larger and contain higher ozone levels relative to the rest of the distribution

Modelling the volcanic ash plume from Eyjafjallajökull eruption (May 2010) over Europe: evaluation of the benefit of source term improvements and of the assimilation of aerosol measurements

International audienceAbstract. Numerical dispersion models are used operationally worldwide to mitigate the effect of volcanic ash on aviation. In order to improve the representation of the horizontal dispersion of ash plumes and of the 3D concentration of ash, a study was conducted using the MOCAGE model during the European Natural Airborne Disaster Information and Coordination System for Aviation (EUNADICS-AV) project. Source term modelling and assimilation of different data were investigated. A sensitivity study of source term formulation showed that a resolved source term, using the FPLUME plume rise model in MOCAGE, instead of a parameterised source term, induces a more realistic representation of the horizontal dispersion of the ash plume. The FPLUME simulation provides more concentrated and focused ash concentrations in the horizontal and the vertical dimensions than the other source term. The assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth has an impact on the horizontal dispersion of the plume, but this effect is rather low and local compared to source term improvement. More promising results are obtained with the continuous assimilation of ground-based lidar profiles, which improves the vertical distribution of ash and helps in reaching realistic values of ash concentrations. Using this configuration, the effect of assimilation may last for several hours and it may propagate several hundred kilometres downstream of the lidar profiles

Stratospheric impact of the anomalous 2023 Canadian wildfires

International audienceThe frequency of extreme wildfires has increased as a response to the regional and global warming trends and there is an emerging realization of their impact on climate through emissions of smoke aerosols into the stratosphere. The 2023 wildfire season in Canada was unprecedented in terms of its duration, burned area and cumulative fire power, rendering it the most destructive ever recorded.  Here we use various satellite observations (TROPOMI, OMPS-LP, OMPS-NM, MLS, CALIPSO, SAGE III) to quantify the stratospheric emissions of smoke aerosols and carbon monoxide by the 2023 Canadian wildfires and to characterize the long-range transport of smoke plumes in the stratosphere. Using multiwavelength lidar observations in Northern France, we show systematically distinct microphysical properties of UTLS smoke aerosols compared to their free-tropospheric counterparts. The analysis of satellite data reveals multiple episodes of smoke intrusions into the stratosphere through pyroconvection (PyroCb) and synoptic-scale processes (warm conveyor belt, WCB). Model simulations using MOCAGE chemistry-transport model, which included emission data from GFAS (Global Fire Assimilation System) are shown to accurately capture the synoptic-scale uplift of smoke into the UTLS and reproduce the spatial evolution of the aerosol plumes. We show that the multiple episodes of wildfire-driven stratospheric intrusions during Boreal Summer 2023 through PyroCb and WCB mechanisms are altogether responsible for the record-high and persistent season-wide smoke pollution at the commercial aircraft cruising altitudes and the lowermost stratosphere.The frequency of extreme wildfires has increased as a response to the regional and global warming trends and there is an emerging realization of their impact on climate through emissions of smoke aerosols into the stratosphere. The 2023 wildfire season in Canada was unprecedented in terms of its duration, burned area and cumulative fire power, rendering it the most destructive ever recorded. Here we use various satellite observations (TROPOMI, OMPS-LP, OMPS-NM, MLS, CALIPSO, SAGE III) to quantify the stratospheric emissions of smoke aerosols and carbon monoxide by the 2023 Canadian wildfires and to characterize the long-range transport of smoke plumes in the stratosphere. Using multiwavelength lidar observations in Northern France, we show systematically distinct microphysical properties of UTLS smoke aerosols compared to their free-tropospheric counterparts.The analysis of satellite data reveals multiple episodes of smoke intrusions into the stratosphere through pyroconvection (PyroCb) and synoptic-scale processes (warm conveyor belt, WCB). Model simulations using MOCAGE chemistry-transport model, which included emission data from GFAS (Global Fire Assimilation System) are shown to accurately capture the synoptic-scale uplift of smoke into the UTLS and reproduce the spatial evolution of the aerosol plumes.We show that the multiple episodes of wildfire-driven stratospheric intrusions during Boreal Summer 2023 through PyroCb and WCB mechanisms are altogether responsible for the record-high and persistent season-wide smoke pollution at the commercial aircraft cruising altitudes and the lowermost stratosphere