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Recent studies show that the Asian summer monsoon anticyclone (ASMA) transports emissions from the rapidly industrializing nations in Asia into the tropical upper troposphere. Here, we present a unique set of measurements on over 100 air samples collected on multiple flights of the M55 Geophysica high altitude research aircraft over the Mediterranean, Nepal, and Northern India during the summers of 2016 and 2017 as part of the European Union project StratoClim. These air samples were measured for 27 ozone‐depleting substances (ODSs), many of which were enhanced above expected levels, including the chlorinated very short‐lived substances, dichloromethane (CH2Cl2), 1,2‐dichloroethane (CH2ClCH2Cl), and chloroform (CHCl3). CH2Cl2 mixing ratios in the tropopause region were 65–136 parts per trillion (ppt) in comparison to previous estimates of mixing ratios in the tropical tropopause layer of 30–44 ppt in 2013–2014. Backward trajectories, calculated with the trajectory module of the chemistry‐transport model CLaMS and driven by the ERA5 reanalysis, indicate possible source regions of CH2Cl2 in South Asia. We derived total equivalent chlorine (ECl), and equivalent effective stratospheric chlorine (EESC) and found that these quantities were substantially higher than previous estimates in the literature. EESC at mean age‐of‐air of 3 years based on the 2016 measurements was 1,861–1,872 ppt in comparison to a previously estimated EESC of 1,646 ppt. Our findings show that the ASMA transports larger than expected mixing ratios of long‐lived and very short‐lived ODSs into the upper troposphere and lower stratosphere, likely leading to an impact on the stratospheric ozone layer.
The record of downwelling solar irradiance and other surface radiation budget components for the U.S. has been extended through 2019 using SURFRAD Network data. Brightening of surface solar irradiance of +7.36 Wm−2/decade occurred from 1996 through 2012. In 2013, surface solar radiation sharply decreased to the long-term mean (representing 1996–2019) and remained near that level through 2017. Successive decreases in 2018 and 2019 yielded a dimming trend of −3.90 Wm−2/decade after 2012, but with a high uncertainty owing to the observed variability and brief period covered. Individually, all stations but Penn State showed brightening trends consistent with the network average, and surface solar irradiance decreased at all stations after 2012. Total surface net radiation showed similar tendencies but the reversal from increasing to decreasing was more gradual because of the response of surface net longwave to the changing solar input. Aerosol optical depth decreased continuously throughout the tenure of the network but accounted for only 3% of the variability of surface solar irradiance, while cloud fraction explained 62%. The mean cloud fraction was 2.4% greater during the dimming period than the brightening period but showed no trends due to high interannual variability. However, annual anomalies of direct-normal solar radiation, which relate to sun duration and clouds, generally increased to 2012 and then decreased thereafter. Collectively, these results indicate that changing cloud cover was the primary source of brightening and dimming over the U.S. from 1996 to 2019.
There is ample evidence that Black Carbon (BC) is harmful to the Arctic. BC can darken the otherwise highly reflective surfaces of snow and ice and increase atmospheric and ice surface temperatures. Because of the importance of BC to the Arctic, this work was designed to resolve the most significant source regions of Arctic BC as measured by monitoring stations in the Arctic. Using a bottom‐up approach, it is shown for the first time that there is one particular BC transport pathway from lower latitudes into the Arctic that registers at all but one of the Arctic surface monitoring stations included in this study. Through this pathway, pollutants are transported from the Indo‐Gangetic plane over Central Asia into the high Arctic in as little as 7 days. The measurement sites and BC pathways in this study are shown to be well representative of the Arctic as a whole.
Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.
Abstract. The rapidly warming Arctic is sensitive to perturbations in the surface energy budget, which can be caused by clouds and aerosols. However, the interactions between clouds and aerosols are poorly quantified in the Arctic, in part due to (1) limited observations of vertical structure of aerosols relative to clouds and (2) ground-based observations often being inadequate for assessing aerosol impacts on cloud formation in the characteristically stratified Arctic atmosphere. Here, we present a novel evaluation of Arctic aerosol vertical distributions using almost 3 years' worth of tethered balloon system (TBS) measurements spanning multiple seasons. The TBS was deployed at the U.S. Department of Energy Atmospheric Radiation Measurement Program's facility at Oliktok Point, Alaska. Aerosols were examined in tandem with atmospheric stability and ground-based remote sensing of cloud macrophysical properties to specifically address the representativeness of near-surface aerosols to those at cloud base. Based on a statistical analysis of the TBS profiles, ground-based aerosol number concentrations were unequal to those at cloud base 86 % of the time. Intermittent aerosol layers were observed 63 % of the time due to poorly mixed below-cloud environments, mostly found in the spring, causing a decoupling of the surface from the cloud layer. A uniform distribution of aerosol below cloud was observed only 14 % of the time due to a well-mixed below-cloud environment, mostly during the fall. The equivalent potential temperature profiles of the below-cloud environment reflected the aerosol profile 89 % of the time, whereby a mixed or stratified below-cloud environment was observed during a uniform or layered aerosol profile, respectively. In general, a combination of aerosol sources, thermodynamic structure, and wet removal processes from clouds and precipitation likely played a key role in establishing observed aerosol vertical structures. Results such as these could be used to improve future parameterizations of aerosols and their impacts on Arctic cloud formation and radiative properties.
Abstract. Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc. Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.
Abstract. The NOAA Global Monitoring Laboratory serves as the World Meteorological Organization Global Atmosphere Watch (WMO/GAW) Central Calibration Laboratory (CCL) for CO2 and is responsible for maintaining the WMO/GAW mole fraction scale used as a reference within the WMO/GAW program. The current WMO-CO2-X2007 scale is embodied by 15 aluminum cylinders containing modified natural air, with CO2 mole fractions determined using the NOAA manometer from 1995 to 2006. We have made two minor corrections to historical manometric records: fixing an error in the applied second virial coefficient of CO2 and accounting for loss of a small amount of CO2 to materials in the manometer during the measurement process. By incorporating these corrections, extending the measurement records of the original 15 primary standards through 2015, and adding four new primary standards to the suite, we define a new scale, identified as WMO-CO2-X2019. The new scale is 0.18 µmol mol−1 (ppm) greater than the previous scale at 400 ppm CO2. While this difference is small in relative terms (0.045 %), it is significant in terms of atmospheric monitoring. All measurements of tertiary-level standards will be reprocessed to WMO-CO2-X2019. The new scale is more internally consistent than WMO-CO2-X2007 owing to revisions in propagation and should result in an overall improvement in atmospheric data records traceable to the CCL.
Abstract. Carbonyl sulfide (COS) has the potential to be used as a climate diagnostic due to its close coupling to the biospheric uptake of CO2 and its role in the formation of stratospheric aerosol. The current understanding of the COS budget, however, lacks COS sources, which have previously been allocated to the tropical ocean. This paper presents a first attempt at global inverse modelling of COS within the 4-dimensional variational data-assimilation system of the TM5 chemistry transport model (TM5-4DVAR) and a comparison of the results with various COS observations. We focus on the global COS budget, including COS production from its precursors carbon disulfide (CS2) and dimethyl sulfide (DMS). To this end, we implemented COS uptake by soil and vegetation from an updated biosphere model (Simple Biosphere Model – SiB4). In the calculation of these fluxes, a fixed atmospheric mole fraction of 500 pmol mol−1 was assumed. We also used new inventories for anthropogenic and biomass burning emissions. The model framework is capable of closing the COS budget by optimizing for missing emissions using NOAA observations in the period 2000–2012. The addition of 432 Gg a−1 (as S equivalents) of COS is required to obtain a good fit with NOAA observations. This missing source shows few year-to-year variations but considerable seasonal variations. We found that the missing sources are likely located in the tropical regions, and an overestimated biospheric sink in the tropics cannot be ruled out due to missing observations in the tropical continental boundary layer. Moreover, high latitudes in the Northern Hemisphere require extra COS uptake or reduced emissions. HIPPO (HIAPER Pole-to-Pole Observations) aircraft observations, NOAA airborne profiles from an ongoing monitoring programme and several satellite data sources are used to evaluate the optimized model results. This evaluation indicates that COS mole fractions in the free troposphere remain underestimated after optimization. Assimilation of HIPPO observations slightly improves this model bias, which implies that additional observations are urgently required to constrain sources and sinks of COS. We finally find that the biosphere flux dependency on the surface COS mole fraction (which was not accounted for in this study) may substantially lower the fluxes of the SiB4 biosphere model over strong-uptake regions. Using COS mole fractions from our inversion, the prior biosphere flux reduces from 1053 to 851 Gg a−1, which is closer to 738 Gg a−1 as was found by Berry et al. (2013). In planned further studies we will implement this biosphere dependency and additionally assimilate satellite data with the aim of better separating the role of the oceans and the biosphere in the global COS budget.
Abstract. Land surface modellers need measurable proxies to constrain the quantity of carbon dioxide (CO2) assimilated by continental plants through photosynthesis, known as gross primary production (GPP). Carbonyl sulfide (COS), which is taken up by leaves through their stomates and then hydrolysed by photosynthetic enzymes, is a candidate GPP proxy. A former study with the ORCHIDEE land surface model used a fixed ratio of COS uptake to CO2 uptake normalised to respective ambient concentrations for each vegetation type (leaf relative uptake, LRU) to compute vegetation COS fluxes from GPP. The LRU approach is known to have limited accuracy since the LRU ratio changes with variables such as photosynthetically active radiation (PAR): while CO2 uptake slows under low light, COS uptake is not light limited. However, the LRU approach has been popular for COS–GPP proxy studies because of its ease of application and apparent low contribution to uncertainty for regional-scale applications. In this study we refined the COS–GPP relationship and implemented in ORCHIDEE a mechanistic model that describes COS uptake by continental vegetation. We compared the simulated COS fluxes against measured hourly COS fluxes at two sites and studied the model behaviour and links with environmental drivers. We performed simulations at a global scale, and we estimated the global COS uptake by vegetation to be −756 Gg S yr−1, in the middle range of former studies (−490 to −1335 Gg S yr−1). Based on monthly mean fluxes simulated by the mechanistic approach in ORCHIDEE, we derived new LRU values for the different vegetation types, ranging between 0.92 and 1.72, close to recently published averages for observed values of 1.21 for C4 and 1.68 for C3 plants. We transported the COS using the monthly vegetation COS fluxes derived from both the mechanistic and the LRU approaches, and we evaluated the simulated COS concentrations at NOAA sites. Although the mechanistic approach was more appropriate when comparing to high-temporal-resolution COS flux measurements, both approaches gave similar results when transporting with monthly COS fluxes and evaluating COS concentrations at stations. In our study, uncertainties between these two approaches are of secondary importance compared to the uncertainties in the COS global budget, which are currently a limiting factor to the potential of COS concentrations to constrain GPP simulated by land surface models on the global scale.
The atmospheric concentration of trichlorofluoromethane (CFC-11) has been in decline since the production of ozone-depleting substances was phased out under the Montreal Protocol1,2. Since 2013, the concentration decline of CFC-11 slowed unexpectedly owing to increasing emissions, probably from unreported production, which, if sustained, would delay the recovery of the stratospheric ozone layer1,2,3,4,5,6,7,8,9,10,11,12. Here we report an accelerated decline in the global mean CFC-11 concentration during 2019 and 2020, derived from atmospheric concentration measurements at remote sites around the world. We find that global CFC-11 emissions decreased by 18 ± 6 gigagrams per year (26 ± 9 per cent; one standard deviation) from 2018 to 2019, to a 2019 value (52 ± 10 gigagrams per year) that is similar to the 2008−2012 mean. The decline in global emissions suggests a substantial decrease in unreported CFC-11 production. If the sharp decline in unexpected global emissions and unreported production is sustained, any associated future ozone depletion is likely to be limited, despite an increase in the CFC-11 bank (the amount of CFC-11 produced, but not yet emitted) by 90 to 725 gigagrams by the beginning of 2020.
Emissions of ozone-depleting substances, including trichlorofluoromethane (CFC-11), have decreased since the mid-1980s in response to the Montreal Protocol1,2. In recent years, an unexpected increase in CFC-11 emissions beginning in 2013 has been reported, with much of the global rise attributed to emissions from eastern China3,4. Here we use high-frequency atmospheric mole fraction observations from Gosan, South Korea and Hateruma, Japan, together with atmospheric chemical transport-model simulations, to investigate regional CFC-11 emissions from eastern China. We find that CFC-11 emissions returned to pre-2013 levels in 2019 (5.0 ± 1.0 gigagrams per year in 2019, compared to 7.2 ± 1.5 gigagrams per year for 2008–2012, ±1 standard deviation), decreasing by 10 ± 3 gigagrams per year since 2014–2017. Furthermore, we find that in this region, carbon tetrachloride (CCl4) and dichlorodifluoromethane (CFC-12) emissions—potentially associated with CFC-11 production—were higher than expected after 2013 and then declined one to two years before the CFC-11 emissions reduction. This suggests that CFC-11 production occurred in eastern China after the mandated global phase-out, and that there was a subsequent decline in production during 2017–2018. We estimate that the amount of the CFC-11 bank (the amount of CFC-11 produced, but not yet emitted) in eastern China is up to 112 gigagrams larger in 2019 compared to pre-2013 levels, probably as a result of recent production. Nevertheless, it seems that any substantial delay in ozone-layer recovery has been avoided, perhaps owing to timely reporting3,4 and subsequent action by industry and government in China5,6.
Trends and variability in tropospheric hydroxyl (OH) radicals influence budgets of many greenhouse gases, air pollutant species, and ozone depleting substances. Estimations of tropospheric OH trends and variability based on budget analysis of methyl chloroform (CH3CCl3) and process‐based chemistry transport models often produce conflicting results. Here we use a previously tested transport model to simulate atmospheric CH3CCl3 for the period 1985–2018. Based on mismatches between model output and observations, we derive consistent anomalies in the inverse lifetime of CH3CCl3 (KG) using measurements from two independent observational networks (National Oceanic and Atmospheric Administration and Advanced Global Atmospheric Gases Experiment). Our method allows a separation between “physical” (transport, temperature) and “chemical” (i.e., abundance) influences on OH + CH3CCl3 reaction rate in the atmosphere. Small increases in KG due to “physical” influences are mostly driven by increases in the temperature‐dependent reaction between OH and CH3CCl3 and resulted in a smoothly varying increase of 0.80% decade−1. Chemical effects on KG, linked to global changes in OH sources and sinks, show larger year‐to‐year variations (∼2%–3%), and have a negative correlation with the El Niño Southern Oscillation. A significant positive trend in KG can be derived after 2001, but it persists only through 2015 and only if we assume that CH3CCl3 emissions decayed more slowly over time than our best estimate suggests. If global CH3CCl3 emissions dropped below 3 Gg year−1 after 2015, recent CH3CCl3 measurements indicate that the 2015–2018 loss rate of CH3CCl3 due to reaction with OH is comparable to its value 2 decades ago.
Understanding the activation properties of aerosol particles as cloud condensation nuclei (CCN) is important for the climate and hydrological cycle, but their properties are not fully understood. In this study, the CCN activation properties of aerosols are investigated at two different sites in southern Spain: an urban background station in Granada and a high altitude mountain station in the Sierra Nevada National Park, with a horizontal separation of 21 km and vertical separation of 1820 m.
CCN activity at the urban environment is driven by primary sources, mainly road traffic. Maximum CCN concentrations occurred during traffic rush hours, although this is also when the activation fraction is lowest. This is due to the characteristics of the rush hour aerosol consisting of ultrafine and less hygroscopic particles. In contrast, the mountain site exhibited larger and more hygroscopic particles, with CCN activity driven by the joint effect of new particle formation (NPF) and vertical transport of anthropogenic particles from Granada urban area by orographic buoyant upward flow. This led to the maximum concentrations of CCN and aerosol particles occurring at midday at the mountain site. Clear differences in the diurnal evolution of CCN between NPF events and non-event days were observed at the Sierra Nevada station, demonstrating the large contribution of NPF to CCN concentrations, especially at high supersaturations. The isolated contribution of NPF to CCN concentration has been estimated to be 175% higher at SS = 0.5% relative to what it would be without NPF. We conclude that NPF could be the major source of CCN at this mountain site.
Finally, two empirical models were used to parameterize CCN concentration in terms of aerosol optical or physical parameters. The models can explain measurements satisfactorily at the urban station. At the mountain site both models cannot reproduce satisfactorily the observations at low SS.
Abstract. Clear-sky periods across the high latitudes have profound impacts on the surface energy budget and lower atmospheric stratification; however an understanding of the atmospheric processes leading to low-level cloud dissipation and formation events is limited. A method to identify clear periods at Utqiaġvik (formerly Barrow), Alaska, during a 5-year period (2014–2018) is developed. A suite of remote sensing and in situ measurements from the high-latitude observatory are analyzed; we focus on comparing and contrasting atmospheric properties during low-level (below 2 km) cloud dissipation and formation events to understand the processes controlling clear-sky periods. Vertical profiles of lidar backscatter suggest that aerosol presence across the lower atmosphere is relatively invariant during the periods bookending clear conditions, which suggests that a sparsity of aerosol is not frequently a cause for cloud dissipation on the North Slope of Alaska. Further, meteorological analysis indicates two active processes ongoing that appear to support the formation of low clouds after a clear-sky period: namely, horizontal advection, which was dominant in winter and early spring, and quiescent air mass modification, which was dominant in the summer. During summer, the dominant mode of cloud formation is a low cloud or fog layer developing near the surface. This low cloud formation is driven largely by air mass modification under relatively quiescent synoptic conditions. Near-surface aerosol particles concentrations changed by a factor of 2 around summer formation events. Thermodynamic adjustment and increased aerosol presence under quiescent atmospheric conditions are hypothesized as important mechanisms for fog formation.
Various methods have been developed to characterize cloud type, otherwise referred to as cloud regime. These include manual sky observations, combining radiative and cloud vertical properties observed from satellite, surface-based remote sensing, and digital processing of sky imagers. While each method has inherent advantages and disadvantages, none of these cloud-typing methods actually includes measurements of surface shortwave or longwave radiative fluxes. Here, a method that relies upon detailed, surface-based radiation and cloud measurements and derived data products to train a random-forest machine-learning cloud classification model is introduced. Measurements from five years of data from the ARM Southern Great Plains site were compiled to train and independently evaluate the model classification performance. A cloud-type accuracy of approximately 80% using the random-forest classifier reveals that the model is well suited to predict climatological cloud properties. Furthermore, an analysis of the cloud-type misclassifications is performed. While physical cloud types may be misreported, the shortwave radiative signatures are similar between misclassified cloud types. From this, we assert that the cloud-regime model has the capacity to successfully differentiate clouds with comparable cloud–radiative interactions. Therefore, we conclude that the model can provide useful cloud-property information for fundamental cloud studies, inform renewable energy studies, and be a tool for numerical model evaluation and parameterization improvement, among many other applications.
Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (≈4 nmol/mol) below the 2000–2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere contributed less than one‐quarter of the observed tropospheric anomaly. The observed anomaly is consistent with recent chemistry‐climate model simulations, which assume emissions reductions similar to those caused by the COVID‐19 crisis. COVID‐19 related emissions reductions appear to be the major cause for the observed reduced free tropospheric ozone in 2020.