ALBERT

Description: Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget,

Description: The hydroxyl radical (OH), which is the dominant sink of methane (CH4), plays a key role in closing the global methane budget. Current top-down estimates of the global and regional CH4 budget using 3D models usually apply prescribed OH fields and attribute model–observation mismatches almost exclusively to CH4 emissions, leaving the uncertainties due to prescribed OH fields less quantified. Here, using a variational Bayesian inversion framework and the 3D chemical transport model LMDz, combined with 10 different OH fields derived from chemistry–climate models (Chemistry–Climate Model Initiative, or CCMI, experiment), we evaluate the influence of OH burden, spatial distribution, and temporal variations on the global and regional CH4 budget. The global tropospheric mean CH4-reaction-weighted [OH] ([OH]GM-CH4) ranges 10.3–16.3×105 molec cm−3 across 10 OH fields during the early 2000s, resulting in inversion-based global CH4 emissions between 518 and 757  Tg yr−1. The uncertainties in CH4 inversions induced by the different OH fields are similar to the CH4 emission range estimated by previous bottom-up syntheses and larger than the range reported by the top-down studies. The uncertainties in emissions induced by OH are largest over South America, corresponding to large inter-model differences of [OH] in this region. From the early to the late 2000s, the optimized CH4 emissions increased by 22±6  Tg yr−1 (17–30  Tg yr−1), of which ∼25  % (on average) offsets the 0.7  % (on average) increase in OH burden. If the CCMI models represent the OH trend properly over the 2000s, our results show that a higher increasing trend of CH4 emissions is needed to match the CH4 observations compared to the CH4 emission trend derived using constant OH. This study strengthens the importance of reaching a better representation of OH burden and of OH spatial and temporal distributions to reduce the uncertainties in the global and regional CH4 budgets.

Description: The stratospheric contribution to tropospheric ozone (O3) has been a subject of much debate in recent decades but is known to have an important influence. Recent improvements in diagnostic and modelling tools provide new evidence that the stratosphere has a much larger influence than previously thought. This study aims to characterise the seasonal and geographical distribution of tropospheric ozone, its variability, and its changes and provide quantification of the stratospheric influence on these measures. To this end, we evaluate hindcast specified-dynamics chemistry–climate model (CCM) simulations from the European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model and the Canadian Middle Atmosphere Model (CMAM), as contributed to the International Global Atmospheric Chemistry – Stratosphere-troposphere Processes And their Role in Climate (IGAC-SPARC) (IGAC–SPARC) Chemistry Climate Model Initiative (CCMI) activity, together with satellite observations from the Ozone Monitoring Instrument (OMI) and ozone-sonde profile measurements from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) over a period of concurrent data availability (2005–2010). An overall positive, seasonally dependent bias in 1000–450 hPa (∼0–5.5 km) sub-column ozone is found for EMAC, ranging from 2 to 8 Dobson units (DU), whereas CMAM is found to be in closer agreement with the observations, although with substantial seasonal and regional variation in the sign and magnitude of the bias (∼±4 DU). Although the application of OMI averaging kernels (AKs) improves agreement with model estimates from both EMAC and CMAM as expected, comparisons with ozone-sondes indicate a positive ozone bias in the lower stratosphere in CMAM, together with a negative bias in the troposphere resulting from a likely underestimation of photochemical ozone production. This has ramifications for diagnosing the level of model–measurement agreement. Model variability is found to be more similar in magnitude to that implied from ozone-sondes in comparison with OMI, which has significantly larger variability. Noting the overall consistency of the CCMs, the influence of the model chemistry schemes and internal dynamics is discussed in relation to the inter-model differences found. In particular, it is inferred that CMAM simulates a faster and shallower Brewer–Dobson circulation (BDC) compared to both EMAC and observational estimates, which has implications for the distribution and magnitude of the downward flux of stratospheric ozone over the most recent climatological period (1980–2010). Nonetheless, it is shown that the stratospheric influence on tropospheric ozone is significant and is estimated to exceed 50 % in the wintertime extratropics, even in the lower troposphere. Finally, long-term changes in the CCM ozone tracers are calculated for different seasons. An overall statistically significant increase in tropospheric ozone is found across much of the world but particularly in the Northern Hemisphere and in the middle to upper troposphere, where the increase is on the order of 4–6 ppbv (5 %–10 %) between 1980–1989 and 2001–2010. Our model study implies that attribution from stratosphere–troposphere exchange (STE) to such ozone changes ranges from 25 % to 30 % at the surface to as much as 50 %–80 % in the upper troposphere–lower stratosphere (UTLS) across some regions of the world, including western Eurasia, eastern North America, the South Pacific and the southern Indian Ocean. These findings highlight the importance of a well-resolved stratosphere in simulations of tropospheric ozone and its implications for the radiative forcing, air quality and oxidation capacity of the troposphere.

Description: The representation of upper tropospheric–lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution – for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry–climate models.

Description: The stratospheric circulation determines the transport and lifetime of key trace gases in a changing climate, including water vapor and ozone, which radiatively impact surface climate. The unusually warm El Niño–Southern Oscillation (ENSO) event aligned with a disrupted Quasi-Biennial Oscillation (QBO) caused an unprecedented perturbation to this circulation in 2015–2016. Here, we quantify the impact of the alignment of these two phenomena in 2015–2016 on lower stratospheric water vapor and ozone from satellite observations. We show that the warm ENSO event substantially increased water vapor and decreased ozone in the tropical lower stratosphere. The QBO disruption significantly decreased global lower stratospheric water vapor and tropical ozone from early spring to late autumn. Thus, this QBO disruption reversed the lower stratosphere moistening triggered by the alignment of the warm ENSO event with westerly QBO in early boreal winter. Our results suggest that the interplay of ENSO events and QBO phases will be crucial for the distributions of radiatively active trace gases in a changing future climate, when increasing El Niño-like conditions and a decreasing lower stratospheric QBO amplitude are expected.

Description: Stratospheric transport in global circulation models and chemistry–climate models is an important component in simulating the recovery of the ozone layer as well as changes in the climate system. The Brewer–Dobson circulation is not well constrained by observations and further investigation is required to resolve uncertainties related to the mechanisms driving the circulation. This study has assessed the specified dynamics mode of the Canadian Middle Atmosphere Model (CMAM30) by comparing to the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) profile measurements of CFC-11 (CCl3F), CFC-12 (CCl2F2), and N2O. In the CMAM30 specified dynamics simulation, the meteorological fields are nudged using the ERA-Interim reanalysis and a specified tracer was employed for each species, with hemispherically defined surface measurements used as the boundary condition. A comprehensive sampling technique along the line of sight of the ACE-FTS measurements has been utilized to allow for direct comparisons between the simulated and measured tracer concentrations. The model consistently overpredicts tracer concentrations of CFC-11, CFC-12, and N2O in the lower stratosphere, particularly in the northern hemispheric winter and spring seasons. The three mixing barriers investigated, including the polar vortex, the extratropical tropopause, and the tropical pipe, show that there are significant inconsistencies between the measurements and the simulations. In particular, the CMAM30 simulation underpredicts mixing efficiency in the tropical lower stratosphere during the June–July–August season.

Description: Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields.The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses.In contrast to O3, reanalysis estimates of stratospheric WV are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore mainly dependent on the reanalyses' representation of the physical drivers that influence stratospheric WV, such as temperatures in the tropical tropopause layer, methane oxidation, and the stratospheric overturning circulation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.

Description: 〉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 (±20 DU 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: The climate research community uses atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics. The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. The project focuses predominantly on differences among reanalyses, although studies that include operational analyses and studies comparing reanalyses with observations are also included when appropriate. The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. This paper summarizes the motivation and goals of the S-RIP activity and extensively reviews key technical aspects of the reanalysis data sets that are the focus of this activity. The special issue The SPARC Reanalysis Intercomparison Project (S-RIP) in this journal serves to collect research with relevance to the S-RIP in preparation for the publication of the planned two (interim and full) S-RIP reports.

Description: 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 8.7×105 and 12.8×105 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 0.1–0.3×105 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 state-of-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.