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Diagnosing carbon dioxide ( ) and methane ( ) fluxes at subcontinental scales is complicated by sparse observations, limited knowledge of prior fluxes and their uncertainties, and background and transport errors. Multispecies measurements in flasks sampled during the wintertime ACT‐America campaign were used for background characterization and source apportionment of regional anthropogenic and fluxes when ecosystem exchange is likely to be least active. Continental background trace gas mole fractions for regional enhancements are defined using samples from the upper troposphere and assessed using model products. Trace gas enhancements taken from flask samples in the lower troposphere with background levels subtracted out are then interpreted to inform and enhancement variability in the eastern United States. Strong correlations between and enhancements in the Midwestern and Mid‐Atlantic United States indicated colocated anthropogenic sources. Oil and natural gas influence was also broadly observed throughout the entire observational domain. In the Midwestern United States, agricultural influence on and enhancement variability was evident during above‐average wintertime temperatures. Weaker correlations between and anthropogenic tracer enhancements in the Southeastern United States indicated potentially nonnegligible wintertime ecosystem exchange, with biogenic tracers indicating more active surface processing than other regions. These whole‐air flask samples illuminated significant regional and sources or sinks during Atmospheric Carbon and Transport‐America (ACT‐America) and can provide additional information for informing regional inverse modeling efforts.
Ground-based Doppler-lidar instrumentation provides atmospheric wind data at dramatically improved accuracies and spatial/temporal resolutions. These capabilities have provided new insights into atmospheric flow phenomena, but they also should have a strong role in NWP model improvement. Insight into the nature of model errors can be gained by studying recurrent atmospheric flows, here a regional summertime diurnal sea breeze and subsequent marine-air intrusion into the arid interior of Oregon–Washington, where these winds are an important wind-energy resource. These marine intrusions were sampled by three scanning Doppler lidars in the Columbia River basin as part of the Second Wind Forecast Improvement Project (WFIP2), using data from summer 2016. Lidar time–height cross sections of wind speed identified 8 days when the diurnal flow cycle (peak wind speeds at midnight, afternoon minima) was obvious and strong. The 8-day composite time–height cross sections of lidar wind speeds are used to validate those generated by the operational NCEP–HRRR model. HRRR simulated the diurnal wind cycle, but produced errors in the timing of onset and significant errors due to a premature nighttime demise of the intrusion flow, producing low-bias errors of 6 m s−1. Day-to-day and in the composite, whenever a marine intrusion occurred, HRRR made these same errors. The errors occurred under a range of gradient wind conditions indicating that they resulted from the misrepresentation of physical processes within a limited region around the measurement locations. Because of their generation within a limited geographical area, field measurement programs can be designed to find and address the sources of these NWP errors.
Surface albedo can be highly variable in both space and time. The Department of Energy's Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems (HI‐SCALE) field study provides a unique opportunity to characterize the variability over the Southern Great Plains of the United States using integrated tower, aircraft, and satellite observations of surface albedo. The primary advantage of the aircraft and satellite observations is the ability to examine the spatial distribution of surface albedo over a large area, while the tower measurements have the ability to examine both diurnal and day‐to‐day variability at a single location. In general, consistency was found between the broadband (BB) albedo measured from the surface, air and space. There was a small increase from 0.186 to 0.194 in the aircraft BB surface albedo between May and September (about 4% change), while the MODIS black‐sky BB surface albedo increased from 0.151 to 0.166 over the same period (about 10% change) while the standard deviations in the aircraft and MODIS BB albedo were similar. The largest seasonal differences in the aircraft BB albedo were found for areas with winter wheat or forest, while areas with pasture or grasses showed a smaller seasonal diversity. The Weather Research and Forecasting (WRF) model was used to simulate the BB surface albedo. In comparison with the aircraft and satellite observations, the WRF‐simulated BB surface albedo had no seasonal change and a much narrower distribution.
Earth's atmosphere oxidizes the greenhouse gas methane and other gases, thus determining their lifetimes and oxidation products. Much of this oxidation occurs in the remote, relatively clean free troposphere above the planetary boundary layer, where the oxidation chemistry is thought to be much simpler and better understood than it is in urban regions or forests. The NASA airborne Atmospheric Tomography study (ATom) was designed to produce cross sections of the detailed atmospheric composition in the remote atmosphere over the Pacific and Atlantic Oceans during four seasons. As part of the extensive ATom data set, measurements of the atmosphere's primary oxidant, hydroxyl (OH), and hydroperoxyl (HO2) are compared to a photochemical box model to test the oxidation chemistry. Generally, observed and modeled median OH and HO2 agree to within combined uncertainties at the 2σ confidence level, which is ~±40%. For some seasons, this agreement is within ~±20% below 6‐km altitude. While this test finds no significant differences, OH observations increasingly exceeded modeled values at altitudes above 8 km, becoming ~35% greater, which is near the combined uncertainties. Measurement uncertainty and possible unknown measurement errors complicate tests for unknown chemistry or incorrect reaction rate coefficients that would substantially affect the OH and HO2 abundances. Future analysis of detailed comparisons may yield additional discrepancies that are masked in the median values.
Abstract. The uptake of water by atmospheric aerosols has a pronounced effect on particle light scattering properties which in turn are strongly dependent on the ambient relative humidity (RH). Earth system models need to account for the aerosol water uptake and its influence on light scattering in order to properly capture the overall radiative effects of aerosols. Here we present a comprehensive model-measurement evaluation of the particle light scattering enhancement factor f(RH), defined as the particle light scattering coefficient at elevated RH (here set to 85 %) divided by its dry value. The comparison uses simulations from 10 Earth system models and a global dataset of surface-based in situ measurements. In general, we find a large diversity in the magnitude of predicted f(RH) amongst the different models which can not be explained by the site types. There is strong indication that differences in the model parameterizations of hygroscopicity and perhaps mixing state are driving at least some of the observed diversity in simulated f(RH). An important finding is that the models show a significantly larger discrepancy with the observations if RHref = 0 % is chosen as the model reference RH compared to when RHref = 40 % is used. The multi-site average ratio between model outputs and measurements is 1.64 in the former case and 1.16 in the latter. The overestimation by the models is believed to originate from the hygroscopicity parameterizations at the lower RH range which may not implement all phenomena taking place (i.e. not fully dried particles and hysteresis effects). Our results emphasize the need to consider the measurement conditions in such comparisons and recognize that measurements referred to as
dry may not be dry in model terms.
Abstract. Detecting a tropospheric ozone trend from sparsely sampled ozonesonde profiles (typically once per week) is challenging due to the noise in the time series resulting from ozone's high temporal variability. To enhance trend detection we have developed a sophisticated statistical approach that utilizes a geoadditive model to assess ozone variability across a time series of vertical profiles. Treating the profile time series as a set of individual time series on discrete pressure surfaces, a class of smoothing spline ANOVA (analysis of variance) models is used for the purpose of jointly modeling multiple correlated time series (on separate pressure surfaces) by their associated seasonal and interannual variabilities. This integrated fit method filters out the unstructured noise through a statistical regularization (i.e. a roughness penalty), by taking advantage of the additional correlated data points available on the pressure surfaces above and below the surface of interest. We have applied this technique to the trend analysis of the vertically correlated time series of tropospheric ozone observations from 1) IAGOS (In-service Aircraft for a Global Observing System) commercial aircraft profiles above Europe and China, and 2) NOAA GMD's (Global Monitoring Division) ozonesonde records at Hilo, Hawaii and Trinidad Head, California. We illustrate the ability of this technique to detect a consistent trend estimate, and its effectiveness for reducing the associated uncertainty in the noisy profile data due to low sampling frequency. We also conducted a sensitivity analysis of frequent IAGOS profiles above Europe (approximately 120 profiles per month) to determine how many profiles in a month are required for reliable long-term trend detection. When ignoring the vertical correlation we found that a typical sampling strategy of 4 profiles-per-month results in 7 % of sampled trends falling outside the 2-sigma uncertainty interval derived from the full data set, with associated 10 % of mean absolute percentage error. We determined that an optimal sampling frequency is 14 profiles per month when using the integrated fit method for calculating trends; when the integrated fit method is not applied, the sampling frequency had to be increased to 18 profiles per month to achieve the same result. While our method improves trend detection from sparse data sets, the key to substantially reducing the uncertainty is to increase the sampling frequency.
Dichloromethane (CH2Cl2) and perchloroethylene (C2Cl4) are chlorinated very short lived substances (Cl‐VSLS) with anthropogenic sources. Recent studies highlight the increasing influence of such compounds, particularly CH2Cl2, on the stratospheric chlorine budget and therefore on ozone depletion. Here, a multiyear global‐scale synthesis inversion was performed to optimize CH2Cl2 (2006–2017) and C2Cl4 (2007–2017) emissions. The approach combines long‐term surface observations from global monitoring networks, output from a three‐dimensional chemical transport model (TOMCAT), and novel bottom‐up information on prior industry emissions. Our posterior results show an increase in global CH2Cl2 emissions from 637 ± 36 Gg yr−1 in 2006 to 1,171 ± 45 Gg yr−1 in 2017, with Asian emissions accounting for 68% and 89% of these totals, respectively. In absolute terms, Asian CH2Cl2 emissions increased annually by 51 Gg yr−1 over the study period, while European and North American emissions declined, indicating a continental‐scale shift in emission distribution since the mid‐2000s. For C2Cl4, we estimate a decrease in global emissions from 141 ± 14 Gg yr−1 in 2007 to 106 ± 12 Gg yr−1 in 2017. The time‐varying posterior emissions offer significant improvements over the prior. Utilizing the posterior emissions leads to modeled tropospheric CH2Cl2 and C2Cl4 abundances and trends in good agreement to those observed (including independent observations to the inversion). A shorter C2Cl4 lifetime, from including an uncertain Cl sink, leads to larger global C2Cl4 emissions by a factor of ~1.5, which in some places improves model‐measurement agreement. The sensitivity of our findings to assumptions in the inversion procedure, including CH2Cl2 oceanic emissions, is discussed.
Abstract. In order to assess the global evolution of aerosol parameters affecting climate change, a long-term trend analyses of aerosol optical properties were performed on time series from 52 stations situated across five continents. The time series of measured scattering, backscattering and absorption coefficients as well as the derived single scattering albedo, backscattering fraction, scattering and absorption Ångström exponents covered at least 10 years and up to 40 years for some stations. The non-parametric seasonal Mann–Kendall (MK) statistical test associated with several prewhitening methods and with the Sen's slope were used as main trend analysis methods. Comparisons with General Least Mean Square associated with Autoregressive Bootstrap (GLS/ARB) and with standard Least Mean Square analysis (LMS) enabled confirmation of the detected MK statistically significant trends and the assessment of advantages and limitations of each method. Currently, scattering and backscattering coefficients trends are mostly decreasing in Europe and North America and are not statistically significant in Asia, while polar stations exhibit a mix of increasing and decreasing trends. A few increasing trends are also found at some stations in North America and Australia. Absorption coefficients time series also exhibit primarily decreasing trends. For single scattering albedo, 52 % of the sites exhibit statistically significant positive trends, mostly in Asia, Eastern/Northern Europe and Arctic, 18 % of sites exhibit statistically significant negative trends, mostly in central Europe and central North America, while the remaining 30 % of sites have trends, which are not statistically significant. In addition to evaluating trends for the overall time series, the evolution of the trends in sequential 10 year segments was also analyzed. For scattering and backscattering, statistically significant increasing 10 year trends are primarily found for earlier periods (10 year trends ending in 2010–2015) for polar stations and Mauna Loa. For most of the stations, the present-day statistically significant decreasing 10 year trends of the single scattering albedo were preceded by not statistically significant and statistically significant increasing 10 year trends. The effect of air pollution abatement policies in continental North America is very obvious in the 10 year trends of the scattering coefficient – there is a shift to statistically significant negative trends in 2010–2011 for all stations in the eastern and central US. This long-term trend analysis of aerosol radiative properties with a broad spatial coverage enables a better global view of potential aerosol effects on climate changes.
Extracting globally representative trend information from lower tropospheric ozone observations is extremely difficult due to the highly variable distribution and interannual variability of ozone, and the ongoing shift of ozone precursor emissions from high latitudes to low latitudes. Here we report surface ozone trends at 27 globally distributed remote locations (20 in the Northern Hemisphere, 7 in the Southern Hemisphere), focusing on continuous time series that extend from the present back to at least 1995. While these sites are only representative of less than 25% of the global surface area, this analysis provides a range of regional long-term ozone trends for the evaluation of global chemistry-climate models. Trends are based on monthly mean ozone anomalies, and all sites have at least 20 years of data, which improves the likelihood that a robust trend value is due to changes in ozone precursor emissions and/or forced climate change rather than naturally occurring climate variability. Since 1995, the Northern Hemisphere sites are nearly evenly split between positive and negative ozone trends, while 5 of 7 Southern Hemisphere sites have positive trends. Positive trends are in the range of 0.5-2 ppbv decade-1, with ozone increasing at Mauna Loa by roughly 50% since the late 1950s. Two high elevation Alpine sites, discussed by previous assessments, exhibit decreasing ozone trends in contrast to the positive trend observed by IAGOS commercial aircraft in the European lower free-troposphere. The Alpine sites frequently sample polluted European boundary layer air, especially in summer, and can only be representative of lower free tropospheric ozone if the data are carefully filtered to avoid boundary layer air. The highly variable ozone trends at these 27 surface sites are not necessarily indicative of free tropospheric trends, which have been overwhelmingly positive since the mid-1990s, as shown by recent studies of ozonesonde and aircraft observations.
Permafrost and methane hydrates are large, climate-sensitive old carbon reservoirs that have the potential to emit large quantities of methane, a potent greenhouse gas, as the Earth continues to warm. We present ice core isotopic measurements of methane (Δ C, δ C, and δD) from the last deglaciation, which is a partial analog for modern warming. Our results show that methane emissions from old carbon reservoirs in response to deglacial warming were small (<19 teragrams of methane per year, 95% confidence interval) and argue against similar methane emissions in response to future warming. Our results also indicate that methane emissions from biomass burning in the pre-Industrial Holocene were 22 to 56 teragrams of methane per year (95% confidence interval), which is comparable to today.
In this paper, we compare model calculations of ozone profiles and their variability for the period 1998 to 2016 with satellite and lidar profiles at five ground-based stations. Under the investigation is the temporal impact of the stratospheric halogen reduction (chemical processes) and increase in greenhouse gases (i.e., global warming) on stratospheric ozone changes. Attention is given to the effect of greenhouse gases on ultraviolet-B radiation at ground level. Our chemistry transport and chemistry climate models (Oslo CTM3 and EMAC CCM) indicate that (a) the effect of halogen reduction is maximized in ozone recovery at 1–7 hPa and observed at all lidar stations; and (b) significant impact of greenhouse gases on stratospheric ozone recovery is predicted after the year 2050. Our study indicates that solar ultraviolet-B irradiance that produces DNA damage would increase after the year 2050 by +1.3% per decade. Such change in the model is driven by a significant decrease in cloud cover due to the evolution of greenhouse gases in the future and an insignificant trend in total ozone. If our estimates prove to be true, then it is likely that the process of climate change will overwhelm the effect of ozone recovery on UV-B irradiance in midlatitudes.
Abstract. Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the present day modelling of aerosol optical properties has been assessed using simulated data representative for the year 2010, from 14 global aerosol models participating in the Phase III Control experiment. The model versions are close or equal to those used for CMIP6 and AerChemMIP and inform also on bias in state of the art ESMs. Modelled column optical depths (total, fine and coarse mode AOD) and Angstrom Exponents (AE) were compared both with ground based observations from the Aerosol Robotic Network (AERONET, version 3) as well as space based observations from AATSR-SU instruments. In addition, the modelled AODs were compared with MODIS (Aqua and Terra) data and a satellite AOD data-set (MERGED-FMI) merged from 12 different individual AOD products. Furthermore, for the first time, the modelled near surface scattering (under dry conditions) and absorption coefficients were evaluated against measurements made at low relative humidity at surface in-situ GAW sites.
Statistics are based mainly on normalised mean biases and Pearson correlation coefficients from colocated model and observation data in monthly resolution. Hence, the results are mostly representative for the regions covered by each of the observation networks. Model biases established against satellite data yield insights into remote continental areas and oceans, where ground-based networks lack site coverage. The satellite data themselves are evaluated against AERONET observations, to test our aggregation and re-gridding routines, suggesting relative AOD biases of −5 %, −6 %, +9 % and +18 % for AATSR-SU, MERGED-FMI, MODIS-aqua and MODIS-terra, respectively, with high correlations exceeding 0.8. Biases of fine and coarse AOD and AE in AATSR are found to be +2 %, −16 % and +14.7 % respectively, at AERONET sites, with correlations of the order of 0.8.
The AeroCom MEDIAN and most of the participating models underestimate the optical properties investigated, relative to remote sensing observations. AERONET AOD is underestimated by 21 % ± 17 %. Against satellite data, the model AOD biases range from −38 % (MODIS-terra) to −17 % (MERGED-FMI). Correlation coefficients of model AODs with AERONET, MERGED-FMI and AATSR-SU are high (0.8–0.9) and slightly lower against the two MODIS data-sets (0.6–0.8). Investigation of fine and coarse AODs from the MEDIAN model reveals biases of −10% ± 20 % and −41 % ± 29 % against AERONET and −13 % and −24 % against AATSR-SU, respectively. The differences in bias against AERONET and AATSR-SU are in agreement with the established satellite bias against AERONET. These results indicate that most of the AOD bias is due to missing coarse AOD in the regions covered by these observations.
Underestimates are also found when comparing the models against the surface GAW observations, showing AeroCom MEDIAN mean bias and inter-model variation of −44 % ± 22 % and −32 % ± 34 % for scattering and absorption coefficients, respectively. Dry scattering shows higher underestimation than AOD at ambient relative humidity and is in agreement with recent findings that suggest that models tend to overestimate scattering enhancement due to hygroscopic growth. Broadly consistent negative bias in AOD and scattering suggest a general underestimate in aerosol effects in current global aerosol models.
The large diversity in the surface absorption results suggests differences in the model treatment of light absorption by black carbon (BC), dust (DU) and to a minor degree, organic aerosol (OA). Considerable diversity is found among the models in the simulated near surface absorption coefficients, particularly in regions associated with dust (e.g. Sahara, Tibet), biomass burning (e.g. Amazonia, Central Australia) and biogenic emissions (e.g. Amazonia). Regions associated with high anthropogenic BC emissions such as China and India exhibit comparatively good agreement for all models.
Evaluation of modelled column AEs shows an underestimation of 9 % ± 24 % against AERONET and −21 % against AATSR-SU. This suggests that overall, models tend to overestimate particle size, with implications for lifetime and radiative transfer calculations.
An investigation of modelled emissions, burdens and lifetimes, mass-specific-extinction coefficients (MECs) and optical depths (ODs) for each species and model reveals considerable diversity in most of these parameters. These are discussed in detail for each model individually. Inter-model spread of aerosol species lifetime appears to be similar to that of mass extinction coefficients, suggesting that AOD uncertainties are still associated to a broad spectrum of parameterised aerosol processes.
Atmospheric methane (CH4) is a potent greenhouse gas, and its mole fraction has more than doubled since the preindustrial era1. Fossil fuel extraction and use are among the largest anthropogenic sources of CH4 emissions, but the precise magnitude of these contributions is a subject of debate2,3. Carbon-14 in CH4 (14CH4) can be used to distinguish between fossil (14C-free) CH4 emissions and contemporaneous biogenic sources; however, poorly constrained direct 14CH4 emissions from nuclear reactors have complicated this approach since the middle of the 20th century4,5. Moreover, the partitioning of total fossil CH4 emissions (presently 172 to 195 teragrams CH4 per year)2,3 between anthropogenic and natural geological sources (such as seeps and mud volcanoes) is under debate; emission inventories suggest that the latter account for about 40 to 60 teragrams CH4 per year6,7. Geological emissions were less than 15.4 teragrams CH4 per year at the end of the Pleistocene, about 11,600 years ago8, but that period is an imperfect analogue for present-day emissions owing to the large terrestrial ice sheet cover, lower sea level and extensive permafrost. Here we use preindustrial-era ice core 14CH4 measurements to show that natural geological CH4 emissions to the atmosphere were about 1.6 teragrams CH4 per year, with a maximum of 5.4 teragrams CH4 per year (95 per cent confidence limit)—an order of magnitude lower than the currently used estimates. This result indicates that anthropogenic fossil CH4 emissions are underestimated by about 38 to 58 teragrams CH4 per year, or about 25 to 40 per cent of recent estimates. Our record highlights the human impact on the atmosphere and climate, provides a firm target for inventories of the global CH4 budget, and will help to inform strategies for targeted emission reductions9,10.
In situ and remote‐sensing observations of water vapor are analyzed to assess the evidence for direct convective hydration of the lower stratosphere. We have examined several hundred balloon‐borne and airborne in situ measurements of lower stratospheric humidity in the tropics and northern midlatitudes. We find that the tropical lower‐stratospheric H2O enhancements above the background occur quite infrequently, and the height of the enhancements is within about 1 km of the cold‐point tropopause. Following Schwartz et al. (2013),, we examine the anomalously high (above 8 ppmv) water vapor mixing ratios retrieved by the Aura Microwave Limb Sounder (MLS) at 100 and 82 hPa pressure levels, and we determine their vertical location relative to the local tropopause based on both GFS operational analysis and the ERA5 reanalysis temperature data. We find that essentially all of the >8 ppmv MLS water vapor measurements over the extratropical north American monsoon region are above the relatively low lapse‐rate tropopause in the region, and most are above the local cold‐point tropopause. Over the Asian monsoon region, most (80/90%) of the high H2O values occur below the relatively high‐altitude local lapse‐rate/cold‐point tropopause. Anomalously high MLS water vapor retrievals at 100 and 82 hPa almost never occur in the deep tropics. We show that this result is consistent with the in situ observations given the broad vertical averaging kernel of the MLS measurement. The available evidence suggests that direct hydration of the lower stratosphere is important over north America during the monsoon season, but likely has limited impact in the tropics.
Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generation, cloud screening must be balanced, so both false cloud-free and false cloudy retrievals are minimized. Many methods used in recent CDRs show signs of clear-conservative cloud screening leading to overestimated cloudiness. This study presents a new cloud screening approach for Advanced Very-High-Resolution Radiometer (AVHRR) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery based on the Bayesian discrimination theory. The method is trained on high-quality cloud observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The method delivers results designed for optimally balanced cloud screening expressed as cloud probabilities together with information on for which clouds (minimum cloud optical thickness) the probabilities are valid. Cloud screening characteristics over 28 different Earth surface categories were estimated. Using independent CALIOP observations (including all observed clouds) in 2010 for validation, the total global hit rates for AVHRR data and the SEVIRI full disk were 82% and 85%, respectively. High-latitude oceans had the best performance, with a hit rate of approximately 93%. The results were compared to the CM SAF cLoud, Albedo, and surface RAdiation dataset from AVHRR data–second edition (CLARA-A2) CDR and showed general improvements over most global regions. Notably, the Kuipers’ Skill Score improved, verifying a more balanced cloud screening. The new method will be used to prepare the new CLARA-A3 and CLAAS-3 (CLoud property dAtAset using SEVIRI, Edition 3) CDRs in the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project.
Abstract. Aerosol particles are essential constituents of the Earth’s atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence time resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in-situ near-surface segment of the atmospheric observations system. This paper will provide the widest effort so far to document variability of climate-relevant in-situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High quality data from more than 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single scattering albedo and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information including data provision procedures, quality control and analysis, data policy and usage of the ground-based aerosol measurements network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully-characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.
Chlorofluorocarbon (CFC) banks from uses such as air conditioners or foams can be emitted after global production stops. Recent reports of unexpected emissions of CFC-11 raise the need to better quantify releases from these banks, and associated impacts on ozone depletion and climate change. Here we develop a Bayesian probabilistic model for CFC-11, 12, and 113 banks and their emissions, incorporating the broadest range of constraints to date. We find that bank sizes of CFC-11 and CFC-12 are larger than recent international scientific assessments suggested, and can account for much of current estimated CFC-11 and 12 emissions (with the exception of increased CFC-11 emissions after 2012). Left unrecovered, these CFC banks could delay Antarctic ozone hole recovery by about six years and contribute 9 billion metric tonnes of equivalent CO2 emission. Derived CFC-113 emissions are subject to uncertainty, but are much larger than expected, raising questions about its sources.
Abstract. This study presents a multi-parameter analysis of aerosol trends over the last two decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical composition and mass aerosol properties by using the observations of several ground-based networks. From these regional time series the aerosol trends have been derived for different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases of aerosol optical depth (AOD) are found in Europe, North America, South America and North Africa, ranging from −1.3 %/yr to −3.1 %/yr. An error and representativity analysis of the incomplete observational data has been performed using model data subsets in order to investigate how likely the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of the climate models and their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, column Angstrom exponent, sulfate and particulate matter well (except in North Africa), but show larger discrepancies for coarse mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from the one depicted by solely relying on ground based observations. Using a model with complete diagnostics (NorESM2) we find a global increase of AOD of about 0.2 %/yr between 2000 and 2014, primarily caused by an increase of the loads of organic aerosol, sulfate and black carbon.
A meeting of experts in shortwave (SW) spectral measurements was held in February 2019 to discuss the current state of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility instrumentation and the potential scientific impact of these measurements. Instrument mentors and users reported significant progress in hyperspectral measurement quality, with good-quality data sets now possible at several field campaigns and fixed sites. Ongoing filter-based measurement improvements, including addition of the 1.6-micron channel to the multifilter rotating shadowband radiometer (MFRSR) and lunar tracking mode of the Cimel sun photometers, were also lauded as exciting developments to improve retrievals of aerosol radiative properties and size distributions.
Group discussion focused primarily on two scientific applications of hyperspectral measurements that could provide ground-breaking advances with current measurements. First, SW spectral measurements have the potential to provide new constraints on cloud microphysical processes, particularly related to aerosol-cloud interactions, which are a key uncertainty in climate feedback and sensitivity. Examples were given in how SW spectral measurements are currently being used to better understand and model the feedback between cloud optical properties and ice and snow melt in high latitudes; provide quantitative constraints on accumulation and accretion processes in warm-cloud precipitation formation; and identify mixing regime at cloud edges and thereby separate aerosol-cloud impacts from cloud dynamics in broken cloud conditions. While filter-based measurements can provide constraints in some of these conditions in combination with other sensors, hyperspectral measurements have the potential to retrieve the needed cloud microphysical and optical properties in new environments such as giving more accurate effective radius retrievals, identifying thermodynamic phase, and more accurately and flexibly separating aerosol, surface albedo, and cloud optical properties in heterogeneous environments.
Second, the emerging understanding of how hyperspectral measurements provide inherent information about three-dimensional (3D) radiative effects has the potential to constrain and improve estimates of cloud and aerosol radiative effects in new complex environments such as broken cloud conditions and complex aerosol and cloud scenes such as aerosol layers above clouds. This exciting new area of research has the potential to produce new parameterizations to account for phenomena such as the inherent biases in plane parallel radiative transfer calculations of shallow cumulus conditions modeled by the LES ARM Symbiotic Simulation and Observation (LASSO) workflow.
For the most strategic future investment in advancing scientific knowledge from these measurements, the group’s highest-priority recommendations (more details in Section 5) were:
1. Provide data epochs of good-quality hyperspectral measurements with consistent calibration from several campaigns to give the community a testbed for science applications and retrieval development.
2. Invest in cloud retrieval development from hyperspectral measurements based on new approaches that take advantage of slopes and shapes of the spectra and are less sensitive to absolute calibration. Providing an initial product based on methods in the literature would allow the broader atmospheric science community access to the potential of these measurements for process studies.
L Riihimaki et al., February 2020, DOE/SC-ARM-20-003
3. Update aerosol retrievals of optical properties and size distributions to better leverage multi-instrument synergies and filter-based instrument upgrades.
4. Promote the availability and maturity of ARM’s SW spectral measurements through a Bulletin of the American Meteorological Society (BAMS) article to engage a wider community of researchers with this rich data set
A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July‐October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) is presented. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find the main reasons for the modeled differences in the SEB components are a direct consequence of the RCMs treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their over‐ or under‐estimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully‐coupled ocean‐ice‐atmosphere model. Despite the biases in over‐estimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully‐coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully‐coupled climate system.
An international effort to improve ozonesonde data quality and to reevaluate historical records has made significant improvements in the accuracy of global network data. However, between 2014 and 2016, ozonesonde total column ozone (TCO; O3) at 14 of 37 regularly reporting stations exhibited a sudden dropoff relative to satellite measurements. The ozonesonde TCO drop is 3–7% compared to satellite and ground‐based TCO, and 5–10% or more compared to satellite stratospheric O3 profiles, compromising the use of recent data for trends, although they remain reliable for other uses. Hardware changes in the ozonesonde instrument are likely a major factor in the O3 dropoff, but no single property of the ozonesonde explains the findings. The bias remains in recent data. Research to understand the dropoff is in progress; this letter is intended as a caution to users of the data. Our findings underscore the importance of regular ozonesonde data evaluation.
Balloon‐borne ozonesondes provide accurate measurements of atmospheric ozone (O3) from the surface to above 30 km with high vertical resolution. Dozens of global stations have regularly launched ozonesondes for decades, and they provide vital information for improving O3‐measuring satellite algorithms, tracking recovery of the stratospheric O3 layer, and our understanding of surface to lower stratospheric O3 changes in an evolving climate. We present the discovery of an apparent instrument artifact that has caused total column O3 measurements from about a third of global stations to drop by 3–7% starting in 2014–2016, limiting their suitability for calculating O3 trends. Work is underway to solve the problem, but the exact cause of the drop is still unknown. This letter serves as a caution to the community of ozonesonde data users.
The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was launched on 19 February 2017 and began routine operation in June 2017. The first 2 years of SAGE III/ISS (v5.1) solar occultation ozone data were evaluated by using correlative satellite and ground‐based measurements. Among the three (MES, AO3, and MLR) SAGE III/ISS retrieved solar ozone products, AO3 ozone shows the smallest bias and best precision, with mean biases less than 5% for altitudes ~15–55 km in the midlatitudes and ~20–55 km in the tropics. In the lower stratosphere and upper troposphere, AO3 ozone shows high biases that increase with decreasing altitudes and reach ~10% near the tropopause. Preliminary studies indicate that those high biases primarily result from the contributions of the oxygen dimer (O4) not being appropriately removed within the ozone channel. The precision of AO3 ozone is estimated to be ~3% for altitudes between 20 and 40 km. It degrades to ~10–15% in the lower mesosphere (~55 km) and ~20–30% near the tropopause. There could be an altitude registration error of ~100 m in the SAGE III/ISS auxiliary temperature and pressure profiles. This, however, does not affect retrieved ozone profiles in native number density on geometric altitude coordinates. In the upper stratosphere and lower mesosphere (~40–55 km), the SAGE III/ISS (and SAGE II) retrieved ozone values show sunrise/sunset differences of ~5–8%, which are almost twice as large as what was observed by other satellites or model predictions. This feature needs further study.
Abstract. Within the framework of the International Arctic Systems for Observing the Atmosphere (IASOA), we report a modelling-based study on surface ozone across the Arctic. We use surface ozone from six sites: Summit (Greenland), Pallas (Finland), Barrow (USA), Alert (Canada), Tiksi (Russia), and Villum Research Station (VRS) at Station Nord (North Greenland, Danish Realm), and ozonesonde data from three Canadian sites: Resolute, Eureka, and Alert. Two global chemistry models: a global chemistry transport model (p-TOMCAT) and a global chemistry climate model (UKCA), are used for model-data comparisons. Remotely sensed data of BrO from the GOME-2 satellite instrument and ground-based Multi-axis Differential Optical Absorption Spectroscopy (MAX-DOAS) at Eureka, Canada are used for model validation.
The observed climatology data show that spring surface ozone at coastal sites is heavily depleted, making ozone seasonality at Arctic coastal sites distinctly different from that at inland sites. Model simulations show that surface ozone can be greatly reduced by bromine chemistry. In April, bromine chemistry can cause a net ozone loss (monthly mean) of 10–20 ppbv, with almost half attributable to open-ocean-sourced bromine and the rest to sea-ice-sourced bromine. However, the open-ocean-sourced bromine, via sea spray bromide depletion, cannot by itself produce ozone depletion events (ODEs) (defined as ozone volume mixing ratios VMRs < 10 ppbv). In contrast, sea-ice-sourced bromine, via sea salt aerosol (SSA) production from blowing snow, can produce ODEs even without bromine from sea spray, highlighting the importance of sea ice surface in polar boundary layer chemistry.
Model bromine is sensitive to model configuration, e.g., under the same bromine loading, the total inorganic bromine (BrY) in the Arctic spring boundary layer in the p-TOMCAT base run (i.e., with all bromine emissions) can be 2 times larger than that in the UKCA base run. Despite the model differences, both model base runs can successfully reproduce large bromine explosion events (BEEs) in polar spring. Model-integrated tropospheric column BrO generally matches GOME-2 tropospheric columns within ~50 % (in the UKCA base run) and factors of 2–3 (in the p-TOMCAT base run). The success of the models in reproducing both ODEs and BEEs in the Arctic indicates that the relevant parameterizations implemented in the models work reasonably well, which supports the proposed mechanism of SSA and bromine production from blowing snow on sea ice. Given that sea ice is a large source of SSA and halogens, changes in sea ice type and extent in a warming climate will influence Arctic boundary layer chemistry, including the oxidation of atmospheric elemental mercury.