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We present the CHORA (Cloud Height Ozone Reference Algorithm) for retrieving tropospheric-ozone columns from S5P-TROPOMI (Sentinel-5 Precursor–TROPOspheric Monitoring Instrument). The method uses a local-cloud reference sector (CLC – CHORA Local Cloud) to determine the stratospheric (above-cloud) column, which is subtracted from the total column in clear-sky scenes in the same zonal band to retrieve the tropospheric column. The standard CCD (convective cloud differential) approach uses cloud data from the Pacific region (CPC – CHORA Pacific Cloud) instead. An important assumption for the standard method is the zonal invariance of stratospheric ozone. The local-cloud approach is the first step to diminish this constraint in order to extend the CCD method to mid-latitudes, where stratospheric-ozone variability is larger. An iterative approach has been developed for the automatic selection of an optimal local-cloud reference sector around each retrieval grid box varying latitudinally by ± 1° and longitudinally between ± 5 and ± 50°. The optimised CLCT (CHORA Local Cloud Theil–Sen) algorithm, a follow-up from the CLC, employs a homogeneity criterion for total ozone from the cloud reference sector in order to overcome the inhomogeneities in stratospheric ozone. It directly estimates the above-cloud column ozone for a common reference altitude of 270 hPa using the Theil–Sen regression. The latter allows for the combination of the CCD method with the cloud-slicing algorithm that retrieves upper-tropospheric ozone volume mixing ratios. Monthly averaged tropospheric-column ozone (TCO) using the Pacific cloud reference sector (CPC) and the local-cloud reference sector (CLC, CLCT) has been determined over the tropics and subtropics (26° S–22° N) using TROPOMI for the time period from 2018 to 2022. The accuracy of the various methods was investigated by means of comparisons with spatially collocated NASA/GSFC SHADOZ (Southern Hemisphere Additional Ozonesondes) measurements and the ESA TROPOMI level-2 tropospheric-ozone product. At eight out of nine tropical stations, tropospheric-ozone columns using the CLCT yield better agreement with ozonesondes than the CPC. In the tropical region (20° S–20° N), the CLCT shows a significantly lower overall mean bias and dispersion of 1 ± 7 %, outperforming both the CPC (12 ± 10 %) and CCD-ESA (22 ± 10 %). The CLCT surpasses the ESA operational product, providing more accurate tropospheric-ozone retrievals at eight out of nine stations in the tropics. For the Hilo station, with a larger stratospheric-ozone variability due to its proximity to the subtropics, the bias of + 30 % (CPC) is effectively reduced to -5 % (CLCT). Similarly, in the subtropics (Reunion, Irene, Hanoi, and King's Park), the CLCT algorithm provides an overall bias and scatter of - 11 ± 9 % with respect to sondes. The CLCT effectively reduces the impact of stratospheric-ozone inhomogeneity, typically at higher latitudes. These results demonstrate the advantage of the local-cloud reference sector in the subtropics. The algorithm is therefore an important basis for subsequent systematic applications in current and future missions of geostationary satellites, like GEMS (Geostationary Environment Monitoring Spectrometer, Korea), ESA Sentinel-4, and NASA TEMPO (Tropospheric Emissions: Monitoring of POllution), predominantly covering the middle latitudes. [ABSTRACT FROM AUTHOR]

Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation in important air pollutants such as nitrogen dioxide (NO2). The South Korean instrument GEMS (Geostationary Environmental Monitoring Spectrometer), launched in February 2020, is the first geostationary instrument that is able to observe the diurnal variation in NO2. The measurements have a spatial resolution of 3.5 km × 8 km and cover a large part of Asia. This study compares 1 year of tropospheric NO2 vertical column density (VCD) observations from the operational GEMS L2 product, the scientific GEMS IUP-UB (Institute of Environmental Physics at the University of Bremen) product, the operational TROPOspheric Monitoring Instrument (TROPOMI) product, and ground-based differential optical absorption spectroscopy (DOAS) measurements in South Korea. The GEMS L2 tropospheric NO2 VCDs overestimate the ground-based tropospheric NO2 VCDs with a median relative difference of + 61 % and a correlation coefficient of 0.76. The median relative difference is - 2 % for the GEMS IUP-UB product and - 16 % for the TROPOMI product, with correlation coefficients of 0.83 and 0.89, respectively. The scatter in the GEMS products can be reduced when observations are limited to the TROPOMI overpass time. Diurnal variations in tropospheric NO2 VCDs differ by the pollution level of the analyzed site but with good agreement between the GEMS IUP-UB and ground-based observations. Low-pollution sites show weak or almost no diurnal variation. In summer, the polluted sites show a minimum around noon, indicating the large influence of photochemical loss. Most variation is seen in spring and autumn, with increasing NO2 in the morning, a maximum close to noon, and a decrease towards the afternoon. Winter observations show rather flat or slightly decreasing NO2 throughout the day. Winter observations under low-wind-speed conditions at high-pollution sites show enhancements of NO2 throughout the day. This indicates that under calm conditions, dilution and the less effective chemical loss in winter do not balance the accumulating emissions. Diurnal variation observed at a low-pollution site follows seasonal wind patterns. A weekday–weekend effect analysis shows good agreement between the different products. However, the GEMS L2 product, while agreeing with the other data sets on weekdays, shows significantly less reduction on weekends. The influence of the stratospheric contribution and the surface reflectivity product on the satellite tropospheric NO2 VCD products is investigated. While the TM5 model's stratospheric VCDs, used in the TROPOMI product, are too high, resulting in tropospheric NO2 VCDs that are too low and even negative, when used in the GEMS IUP-UB retrieval, the GEMS L2 stratospheric VCD is too low. Surface reflectivity comparisons indicate that the GEMS L2 reflectivity makes a large contribution to the observed overestimation and scatter. [ABSTRACT FROM AUTHOR]

The genus Asparagus arose ∼9 to 15 million years ago (Ma), and transitions from hermaphroditism to dioecy (separate sexes) occurred ∼3 to 4 Ma. Roughly 27% of extant Asparagus species are dioecious, while the remaining are bisexual with monoclinous flowers. As such, Asparagus is an ideal model taxon for studying the early stages of dioecy and sex chromosome evolution in plants. Until now, however, understanding of diversification and shifts from hermaphroditism to dioecy in Asparagus has been hampered by the lack of robust species tree estimates for the genus. In this study, a genus-wide phylogenomic analysis including 1,726 nuclear loci and comprehensive species sampling supports two independent origins of dioecy in Asparagus —first in a widely distributed Eurasian clade and then in a clade restricted to the Mediterranean Basin. Modeling of ancestral biogeography indicates that both dioecy origins were associated with range expansion out of southern Africa. Our findings also reveal several bursts of diversification across the phylogeny, including an initial radiation in southern Africa that gave rise to 12 major clades in the genus, and more recent radiations that have resulted in paraphyly and polyphyly among closely related species, as expected given active speciation processes. Lastly, we report that the geographic origin of domesticated garden asparagus (Asparagus officinalis L.) was likely in western Asia near the Mediterranean Sea. The presented phylogenomic framework for Asparagus is foundational for ongoing genomic investigations of diversification and functional trait evolution in the genus and contributes to its utility for understanding the origin and early evolution of dioecy and sex chromosomes. [ABSTRACT FROM AUTHOR]

Methane (CH4) is an important anthropogenic greenhouse gas, and its rising concentration in the atmosphere contributes significantly to global warming. A comparatively small number of highly emitting persistent methane sources are responsible for a large share of global methane emissions. The identification and quantification of these sources, which often show large uncertainties regarding their emissions or locations, are important to support mitigating climate change. Daily global column-averaged dry air mole fractions of atmospheric methane (XCH4) are retrieved from radiance measurements of the TROPOspheric Monitoring Instrument (TROPOMI) on board on the Sentinel-5 Precursor (S5P) satellite with a moderately high spatial resolution, enabling the detection and quantification of localized methane sources. We developed a fully automated algorithm to detect regions with persistent methane enhancement and to quantify their emissions using a monthly TROPOMI XCH4 dataset from the years 2018–2021. We detect 217 potential persistent source regions (PPSRs), which account for approximately 20% of the total bottom-up emissions. By comparing the PPSRs in a spatial analysis with anthropogenic and natural emission databases, we conclude that 7.8% of the detected source regions are dominated by coal, 7.8% by oil and gas, 30.4% by other anthropogenic sources like landfills or agriculture, 7.3% by wetlands, and 46.5% by unknown sources. Many of the identified PPSRs are in well-known source regions, like the Permian Basin in the USA, which is a large production area for oil and gas; the Bowen Basin coal mining area in Australia; or the Pantanal Wetlands in Brazil. We perform a detailed analysis of the PPSRs with the 10 highest emission estimates, including the Sudd Wetland in South Sudan, an oil- and gas-dominated area on the west coast in Turkmenistan, and one of the largest coal production areas in the world, the Kuznetsk Basin in Russia. The calculated emission estimates of these source regions are in agreement within the uncertainties in results from other studies but are in most of the cases higher than the emissions reported by emission databases. We demonstrate that our algorithm is able to automatically detect and quantify persistent localized methane sources of different source type and shape, including larger-scale enhancements such as wetlands or extensive oil- and gas-production basins. [ABSTRACT FROM AUTHOR]

Large-scale meteorological events (e.g. cyclones), referred to as synoptic events, strongly influence weather predictability but still cannot be fully characterised in the Arctic region because of the sparse coverage of measurements. Due to the fact that atmospheric dynamics in the lower stratosphere and troposphere influence the ozone field, one approach to analyse these events further is the use of space-borne measurements of ozone vertical distributions and total columns in addition to conventional parameters such as pressure or wind speed. In this study we investigate the link between cyclones and changes in stratospheric ozone by using a combination of unique measurements during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) ship expedition, ozone profile and total column observations by satellite instruments (OMPS-LP, TROPOMI), and ERA5 reanalysis data. The final goal of the study is to assess whether the satellite ozone data can be used to obtain information about cyclones and provide herewith an additional value in the assimilation by numerical weather prediction models. Three special cases during the MOSAiC expedition were selected and classified for the analysis. They are one "normal" cyclone, where a low surface pressure coincides with a minimum in tropopause height, and two "untypical" cyclones, where this is not observed. The influence of cyclone events on ozone in the upper-troposphere lower-stratosphere (UTLS) region was investigated, using the fact that both are correlated with tropopause height changes. The negative correlation between tropopause height from ERA5 and ozone columns was investigated in the Arctic region for the 3-month period from June to August 2020. This was done using total ozone columns and sub-columns from TROPOMI, OMPS-LP, and MOSAiC ozonesonde data. The greatest influence of tropopause height changes on ozone contour levels occurs at an altitude between 10 and 20 km. Moreover, the lowering of the 250 ppb ozonopause (at about 11 km altitude) below 9 km was used to detect cyclones using OMPS-LP ozone observations. The potential of this approach was demonstrated in two case studies where the boundaries of cyclones could be determined using ozone observations. The results of this study can help improve our understanding of the relationship between cyclones, tropopause height, and ozone in the Arctic and demonstrate the usability of satellite ozone data in addition to the conventional parameters for investigating cyclones in the Arctic. [ABSTRACT FROM AUTHOR]

Global crude steel production is expected to continue to increase in the coming decades to meet the demands of the growing world population. Currently, the dominant steelmaking technology worldwide is the conventional highly CO2 -intensive blast furnace–basic oxygen furnace production route (also known as the Linz–Donawitz process), which uses iron ore as raw material and coke as a reducing agent. As a result, large quantities of special gases that are rich in carbon monoxide (CO) are by-products of the various stages of the steelmaking process. Given the challenges associated with satellite-based estimates of carbon dioxide (CO2) emissions at the scale of emitting installations due to significant background levels, co-emitted CO may serve as a valuable indicator of the carbon footprint of steel plants. We show that regional CO release from steel production sites can be monitored from space using 5 years of measurements (2018–2022) from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite, benefiting from its relatively high spatial resolution and daily global coverage. We analyse all German steel plants with blast furnaces and basic oxygen furnaces and obtain associated CO emissions in the range of 50–400 kt yr -1 per site. A comparison with the respective CO2 emissions on the level of emitting installations available from emissions trading data of the European Union Emissions Trading System yields a linear relationship with a sector-specific CO/CO2 emission ratio for the analysed steelworks of 3.24 % [2.73–3.89; 1 σ ], suggesting the feasibility of using CO as a proxy for CO2 emissions from comparable steel production sites. An evaluation at other steel production sites indicates that the derived CO/CO2 emission ratio is also representative of other highly optimised state-of-the-art Linz–Donawitz steelworks outside Germany and that the emission ratio is potentially valuable for estimating sector-specific CO2 emissions from remotely sensed CO emissions, provided that the underlying CO emission estimate is not affected by other sources. [ABSTRACT FROM AUTHOR]

Stratospheric aerosols play a key role in atmospheric chemistry and climate. Their particle size is a crucial factor controlling the microphysical, radiative, and chemical aerosol processes in the stratosphere. Despite its importance, available observations on aerosol particle size are rather sparse. This limits our understanding and knowledge about the mechanisms and importance of chemical and climate aerosol feedbacks. The retrieval described by provides the stratospheric particle size distribution (PSD) from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) limb observations in the tropics. This algorithm has now been improved and extended to work on the entire globe. Two PSD parameters of a unimodal lognormal PSD, the median radius and the geometric standard deviation, are retrieved between 18 and 35 km altitude from SCIAMACHY limb observations by a multiwavelength nonlinear regularized inversion. The approach assumes an aerosol particle number density profile that does not change during the retrieval. The effective Lambertian surface albedo pre-retrieved from coinciding SCIAMACHY nadir observations is integrated into the retrieval algorithm to mitigate the influence of the surface albedo on the retrieval results. The extinction coefficient and the effective radius are calculated from the PSD parameters. The aerosol characteristics from SCIAMACHY are compared with in situ balloon-borne measurements from Laramie, Wyoming, and retrievals from the satellite instruments of the Stratospheric Aerosol and Gas Experiment series (SAGE II and SAGE III) and Optical Spectrograph and InfraRed Imager System (OSIRIS). In the Northern Hemisphere, the median radius differs by less than 27 % and the geometric standard deviation by less than 11 % from both balloon-borne and SAGE III data. Differences are mainly attributed to errors in the assumed a priori number density profile. Globally, the SCIAMACHY extinction coefficient at 750 nm deviates by less than 35 % from SAGE II, SAGE III, and OSIRIS data. The effective radii from SCIAMACHY, balloon-borne measurements, and SAGE III agree within about 18 %, while the effective radius based on SAGE II measurements is systematically larger. The novel data set containing the PSD parameters, the effective radius, and the aerosol extinction coefficients at 525, 750, and 1020 nm from SCIAMACHY observations is publicly available. [ABSTRACT FROM AUTHOR]

The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of - 12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is - 10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by - 9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period. [ABSTRACT FROM AUTHOR]

The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4). [ABSTRACT FROM AUTHOR]

Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation of important air pollutants such as nitrogen dioxide (NO2) over large areas. The South Korean instrument GEMS on the GK2B satellite was launched in February 2020 and is the first instrument in geostationary orbit that delivers hourly daytime observations of NO2. The measurements with a spatial resolution of 3.5 km x 8 km cover a large part of Asia. This study compares one year of tropospheric NO2 vertical column density (VCD) observations of the operational GEMS L2 product, the scientific GEMS IUP-UB product, the operational TROPOMI product, and ground-based DOAS measurements in South Korea. The GEMS L2 tropospheric NO2 VCDs overestimate the VCDs retrieved from the ground-based observations with a median relative difference of +64 % and a correlation coefficient of 0.75. The median relative difference is -1 % for the GEMS IUP-UB product and -14 % for the TROPOMI product. The evaluation of the GEMS IUP-UB product and the operational TROPOMI product with ground-based measurements is in good agreement with correlation coefficients of 0.82 and 0.88. The scatter in the GEMS products can be reduced when observations are limited to the TROPOMI overpass time. The observed diurnal variations of the tropospheric NO2 VCDs show a maximum of NO2 during the late morning for urban sites, whereas rural sites show weak or almost no diurnal changes. Investigations of the seasonal diurnal variability show with a minimum in the observed tropospheric NO2 VCDs around noon the importance of chemical loss of NO2 in summer. Most variability is seen in spring and autumn, which dominate the average annual diurnal cycle. Observations under low wind conditions show strong enhancements of NO2 over the day, especially at polluted sites during winter. This indicates that under calm conditions, dilution and the less effective chemical loss in winter do not balance the accumulating emissions. The impact of transport processes is illustrated by the diurnal variability at a rural site following mean wind patterns for specific seasons and observation times. Analyzing the weekday-weekend effect, good agreement was found between the different products. However, the GEMS L2 product while agreeing with the other data sets during weekdays shows significantly less reduction on weekends. Our investigations show that the observed diurnal evolution of NO2 varies significantly at the different measurement sites, with good agreement between the GEMS IUP-UB and ground-based observations. The diurnal variability of tropospheric NO2 VCDs depends on chemistry, emissions, and transport into and out of the measurement region. To interpret the sources and sinks of NO2 requires that all of these factors are considered. [ABSTRACT FROM AUTHOR]

Climate-related studies need information about the distribution of stratospheric aerosols, which influence the energy balance of the Earth's atmosphere. In this work, we present a merged dataset of vertically resolved stratospheric aerosol extinction coefficients, which is derived from data by six limb and occultation satellite instruments: SAGE II on ERBS, GOMOS and SCIAMACHY on Envisat, OSIRIS on Odin, OMPS on Suomi-NPP, and SAGE III on the International Space Station. The merging of aerosol profiles is performed by transformation of the aerosol datasets from individual satellite instruments to the same wavelength 750 nm and their de-biasing and homogenization by adjusting the seasonal cycles. After such homogenization, the data from individual satellite instruments are in good agreement. The merged aerosol extinction coefficient is computed as the median of the adjusted data from the individual instruments. The merged time series of vertically resolved monthly mean aerosol extinction coefficients at 750 nm is provided in 10° latitudinal bins from 90° S to 90° N, in the altitude range from 8.5 km to 39.5 km. The time series of the stratospheric aerosol optical depth (SAOD) is created by integration of aerosol extinction profiles from the tropopause to 39.5 km; it is also provided as monthly mean data in 10° latitudinal bins. The created aerosol climate record covers the period from October 1984 until May 2022, and it is intended to be extended in the future. It can be used in various climate-related studies. [ABSTRACT FROM AUTHOR]

A tropospheric ozone column (TrOC) dataset from the Ozone Mapping and Profiler Suite (OMPS) observations was generated by combining the retrieved total ozone column from OMPS – Nadir Mapper (OMPS-NM) and limb profiles from OMPS – Limb Profiler (OMPS-LP) data. All datasets were generated at the University of Bremen, and the TrOC product was obtained by applying the limb–nadir matching technique (LNM). The retrieval algorithm and a comprehensive analysis of the uncertainty budget are presented here. The OMPS-LNM-TrOC dataset (2012–2018) is analysed and validated through comparison with ozonesondes, tropospheric ozone residual (TOR) data from the combined Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) observations, and the TROPOspheric Monitoring Instrument (TROPOMI) Convective Cloud Differential technique (CCD) dataset. The OMPS-LNM TrOC is generally lower than the other datasets. The average bias with respect to ozonesondes is -1.7 DU with no significant latitudinal dependence identified. The mean difference with respect to OMI/MLS TOR and TROPOMI CCD is -3.4 and -1.8 DU, respectively. The seasonality and inter-annual variability are in good agreement with all comparison datasets. [ABSTRACT FROM AUTHOR]

We present the CHORA (Cloud Height Ozone Reference Algorithm) algorithm for retrieving tropospheric ozone columns from S5P/TROPOMI. The method uses a local cloud reference sector (CLC, CHORA Local Cloud) to determine the stratospheric (above cloud) column, which is subtracted from the total column in clear-sky scenes in the same zonal band to retrieve the tropospheric column. The standard CCD (Convective Cloud Differential) approach uses cloud data from the Pacific region (CPC, CHORA Pacific Cloud) instead. An important assumption for the standard method is the zonal invariance of stratospheric ozone. The local cloud approach is the first step to diminish this constraint in order to extend the CCD method to middle latitudes, where stratospheric ozone variability is larger. An iterative approach has been developed for the automatic selection of an optimal local cloud reference sector around each retrieval grid box varying longitudinally between ±5° and ±50° and latitudinally by ±1°. The optimised CLCT (CHORA-Local Cloud Theil-Sen algorithm) algorithm, a follow-up from CLC, employs a homogeneity criterion for total ozone from the cloud reference sector in order to overcome the inhomogeneities in stratospheric ozone. It directly estimates the above cloud column ozone for a common reference altitude of 270 hPa using the Theil-Sen regression. The latter allows combining the CCD method with the cloud slicing algorithm that retrieves upper tropospheric ozone volume mixing ratios. Monthly averaged Tropospheric Column Ozone (TCO) using the Pacific cloud reference sector (CPC) and local cloud reference sector (CLC, CLCT) have been determined over the tropics and subtropics (26° S–21° N) from TROPOMI for the time period from 2018 to 2022. The accuracy of the various methods was investigated by comparisons with collocated NASA/GSFC SHADOZ ozonesonde measurements and the ESA TROPOMI Level 2 tropospheric ozone product. At eleven out of twelve stations, tropospheric ozone columns using CLCT yield better agreement with ozonesondes than CPC. The overall statistical dispersion is effectively reduced from 4 DU (CPC) to 2 DU (CLCT). In the tropical region (20° S–20° N), CLCT shows a significantly lower overall mean bias and dispersion of -1±8 %, outperforming both CPC (12±9 %) and CCD-ESA (22±10 %). CLCT surpasses the ESA operational product, providing more accurate tropospheric ozone retrievals at eight out of nine stations in the tropics. For the Hilo station, with a larger stratospheric ozone variability due to its proximity to the subtropics, the bias of +25 % (CPC) is effectively reduced to -12 % (CLCT). Similarly, in the subtropics (Reunion, Irene, and Hanoi), the CLCT algorithm provides an improved overall bias and scatter (-11±8 %) compared to CPC (-17±13 %) with respect to sondes but the bias remains negative. The CLCT effectively reduces the impact of stratospheric ozone inhomogeneity, typically at higher latitudes. These results demonstrate the advantage of the local cloud reference sector in the subtropics. The algorithm, thereby, is an important basis for subsequent systematic applications in current and future missions of geostationary satellites, like GEMS (Geostationary Environment Monitoring Spectrometer, Korea), ESA Sentinel-4, and NASA TEMPO (Tropospheric Emissions: Monitoring of POllution) covering predominantly middle latitudes. [ABSTRACT FROM AUTHOR]

We present the CHORA (Cloud Height Ozone Reference Algorithm) algorithm for retrieving tropospheric ozone columns from S5P/TROPOMI. The method uses a local cloud reference sector (CLC, CHORA Local Cloud) to determine the stratospheric (above cloud) column, which is subtracted from the total column in clear-sky scenes in the same zonal band to retrieve the tropospheric column. The standard CCD (Convective Cloud Differential) approach uses cloud data from the Pacific region (CPC, CHORA Pacific Cloud) instead. An important assumption for the standard method is the zonal invariance of stratospheric ozone. The local cloud approach is the first step to diminish this constraint in order to extend the CCD method to middle latitudes, where stratospheric ozone variability is larger. An iterative approach has been developed for the automatic selection of an optimal local cloud reference sector around each retrieval grid box varying longitudinally between ±5° and ±50° and latitudinally by ±1°. The optimised CLCT (CHORA-Local Cloud Theil-Sen algorithm) algorithm, a follow-up from CLC, employs a homogeneity criterion for total ozone from the cloud reference sector in order to overcome the inhomogeneities in stratospheric ozone. It directly estimates the above cloud column ozone for a common reference altitude of 270 hPa using the Theil-Sen regression. The latter allows combining the CCD method with the cloud slicing algorithm that retrieves upper tropospheric ozone volume mixing ratios. Monthly averaged Tropospheric Column Ozone (TCO) using the Pacific cloud reference sector (CPC) and local cloud reference sector (CLC, CLCT) have been determined over the tropics and subtropics (26° S–21° N) from TROPOMI for the time period from 2018 to 2022. The accuracy of the various methods was investigated by comparisons with collocated NASA/GSFC SHADOZ ozonesonde measurements and the ESA TROPOMI Level 2 tropospheric ozone product. At eleven out of twelve stations, tropospheric ozone columns using CLCT yield better agreement with ozonesondes than CPC. The overall statistical dispersion is effectively reduced from 4 DU (CPC) to 2 DU (CLCT). In the tropical region (20° S–20° N), CLCT shows a significantly lower overall mean bias and dispersion of -1±8 %, outperforming both CPC (12±9 %) and CCD-ESA (22±10 %). CLCT surpasses the ESA operational product, providing more accurate tropospheric ozone retrievals at eight out of nine stations in the tropics. For the Hilo station, with a larger stratospheric ozone variability due to its proximity to the subtropics, the bias of +25 % (CPC) is effectively reduced to -12 % (CLCT). Similarly, in the subtropics (Reunion, Irene, and Hanoi), the CLCT algorithm provides an improved overall bias and scatter (-11±8 %) compared to CPC (-17±13 %) with respect to sondes but the bias remains negative. The CLCT effectively reduces the impact of stratospheric ozone inhomogeneity, typically at higher latitudes. These results demonstrate the advantage of the local cloud reference sector in the subtropics. The algorithm, thereby, is an important basis for subsequent systematic applications in current and future missions of geostationary satellites, like GEMS (Geostationary Environment Monitoring Spectrometer, Korea), ESA Sentinel-4, and NASA TEMPO (Tropospheric Emissions: Monitoring of POllution) covering predominantly middle latitudes. [ABSTRACT FROM AUTHOR]

The central Arctic cryosphere is influenced by the Arctic Amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) data sets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during the Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterised by long-range transport of anthropogenic aerosols in the Arctic, the GC underestimates the AOD in the vicinity of Alaska. At the same time, it overestimates the AOD along the Bering Strait, Northern Europe, and the Siberian central Arctic sea ice regions, with differences of -12.3 % and 21.7 %, respectively. In contrast, the GC consistently underestimates AOD compared to AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea ice region, where it is -10.6 %. Conversely, the GC tends to overestimate AOD along the Siberian and Greenland marginal sea ice zones by 19.5 %, but underestimates AOD along the Canadian Archipelago by -9.3 %. The differences in summer AOD between AEROSNOW data products and GC simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models to constrain its effects on cloud condensation nuclei, ice nucleating particles, and any effects on the radiation budget over central Arctic sea ice during the developing AA period. [ABSTRACT FROM AUTHOR]

The central Arctic cryosphere is influenced by the Arctic Amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) data sets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during the Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterised by long-range transport of anthropogenic aerosols in the Arctic, the GC underestimates the AOD in the vicinity of Alaska. At the same time, it overestimates the AOD along the Bering Strait, Northern Europe, and the Siberian central Arctic sea ice regions, with differences of -12.3% and 21.7%, respectively. In contrast, the GC consistently underestimates AOD compared to AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70°N. This underestimation is particularly pronounced over the central Arctic sea ice region, where it is -10.6%. Conversely, the GC tends to overestimate AOD along the Siberian and Greenland marginal sea ice zones by 19.5%, but underestimates AOD along the Canadian Archipelago by -9.3%. The differences in summer AOD between AEROSNOW data products and GC simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models to constrain its effects on cloud condensation nuclei, ice nucleating particles, and any effects on the radiation budget over central Arctic sea ice during the developing AA period. [ABSTRACT FROM AUTHOR]

Methane (CH4) is an important anthropogenic greenhouse gas and its rising concentration in the atmosphere contributes significantly to global warming. A comparatively small number of highly emitting persistent methane sources is responsible for a large share of global methane emissions. The identification and quantification of these sources, which often show large uncertainties regarding their emissions or locations, is important to support mitigating climate change. The TROPOspheric Monitoring Instrument (TROPOMI) onboard on the Sentinel-5 Precursor (S5P) satellite, launched in October 2017, provides measurements of the column-averaged dry-air mole fraction of atmospheric methane (XCH4) with a daily global coverage and a high spatial resolution of up to km2, enabling the detection and quantification of localized methane sources. We developed a fully automated algorithm to detect regions with persistent methane enhancement and to quantify their emissions using a monthly TROPOMI XCH4 dataset from the years 2018–2021. We detect 217 potential persistent source regions (PPSRs), which account for approximately 20 % of the total bottom-up emissions. By comparing the PPSRs in a spatial analysis with anthropogenic and natural emission databases we conclude that 7.8 % of the detected source regions are dominated by coal, 7.8 % by oil and gas, 30.4 % by other anthropogenic sources like landfills or agriculture, 7.3 % by wetlands and 46.5 % by unknown sources. Many of the identified PPSRs are well-known source regions, like the Permian Basin in the USA, which is a large production area for oil and gas, the Bowen Basin coal mining area in Australia, or the Pantanal wetlands in Brazil. We perform a detailed analysis of the PPSRs with the 10 highest emission estimates, including the Sudd Wetland in South Sudan, an oil and gas dominated area on the west coast in Turkmenistan, and one of the largest coal production areas in the world, the Kuznetsk Basin in Russia. The calculated emission estimates of these source regions are in agreement within the uncertainties with results from other studies, but are in most of the cases higher than the emissions reported by emission databases. We demonstrate that our algorithm is able to automatically detect and quantify persistent localized methane sources of different source type and shape, including larger-scale enhancements such as wetlands or extensive oil and gas production basins. [ABSTRACT FROM AUTHOR]

Methane (CH4) is an important anthropogenic greenhouse gas and its rising concentration in the atmosphere contributes significantly to global warming. A comparatively small number of highly emitting persistent methane sources is responsible for a large share of global methane emissions. The identification and quantification of these sources, which often show large uncertainties regarding their emissions or locations, is important to support mitigating climate change. The TROPOspheric Monitoring Instrument (TROPOMI) onboard on the Sentinel-5 Precursor (S5P) satellite, launched in October 2017, provides measurements of the column-averaged dry-air mole fraction of atmospheric methane (XCH4) with a daily global coverage and a high spatial resolution of up to 5.5 × 7km², enabling the detection and quantification of localized methane sources. We developed a fully automated algorithm to detect regions with persistent methane enhancement and to quantify their emissions using a monthly TROPOMI XCH4 dataset from the years 2018-2021. We detect 217 potential persistent source regions (PPSRs), which account for approximately 20% of the total bottom-up emissions. By comparing the PPSRs in a spatial analysis with anthropogenic and natural emission databases we conclude that 7.8% of the detected source regions are dominated by coal, 7.8% by oil and gas, 30.4% by other anthropogenic sources like landfills or agriculture, 7.3% by wetlands and 46.5% by unknown sources. Many of the identified PPSRs are well-known source regions, like the Permian Basin in the USA, which is a large production area for oil and gas, the Bowen Basin coal mining area in Australia, or the Pantanal wetlands in Brazil. We perform a detailed analysis of the PPSRs with the 10 highest emission estimates, including the Sudd Wetland in South Sudan, an oil and gas dominated area on the west coast in Turkmenistan, and one of the largest coal production areas in the world, the Kuznetsk Basin in Russia. The calculated emission estimates of these source regions are in agreement within the uncertainties with results from other studies, but are in most of the cases higher than the emissions reported by emission databases. We demonstrate that our algorithm is able to automatically detect and quantify persistent localized methane sources of different source type and shape, including larger-scale enhancements such as wetlands or extensive oil and gas production basins. [ABSTRACT FROM AUTHOR]

A new retrieval algorithm to obtain vertical profiles of the aerosol extinction coefficient from the measurements of the scattered solar light in the limb viewing geometry made by the OMPS-LP instrument is presented. The method employs the normalization of the limb radiances to the solar irradiance in contrast to the normalization by a limb measurement at an upper tangent height, which is used by most of the other published limb-scatter retrievals. The main advantage of this approach is a nearly complete elimination of the dependence of the retrieval results on the prior aerosol extinction profile used in the retrieval. This makes the retrieval well suitable to analyze the observation scenes with highly elevated aerosol plumes as occurred after the Hunga Tonga–Hunga Ha'apai volcanic eruption in January 2022. The results from the new approach were compared to independent data from SAGE III/ISS and OSIRIS. In general, an agreement within 25% between the different data products was observed although larger differences were seen after very strong volcanic eruptions and wildfires. The new data product was used to investigate the evolution of the aerosol plume after the Hunga Tonga–Hunga Ha'apai volcanic eruption. [ABSTRACT FROM AUTHOR]

A new retrieval algorithm to obtain vertical profiles of the aerosol extinction coefficient from the measurements of the scattered solar light in the limb viewing geometry made by the OMPS-LP instrument is presented. The method employs the normalization of the limb radiances to the solar irradiance in contrast to the normalization by a limb measurement at an upper tangent height, which is used by most of the other published limb-scatter retrievals. The main advantage of this approach is a nearly complete elimination of the dependence of the retrieval results on the prior aerosol extinction profile used in the retrieval. This makes the retrieval well suitable to analyze the observation scenes with highly elevated aerosol plumes as occurred after the Hunga Tonga-Hunga Ha'apai volcanic eruption in January 2022. The results from the new approach were compared to independent data from SAGE III/ISS and OSIRIS. In general, an agreement within 25 % between the different data products was observed although larger differences were seen after very strong volcanic eruptions and wildfires. The new data product was used to investigate the evolution of the aerosol plume after the Hunga Tonga-Hunga Ha'apai volcanic eruption. [ABSTRACT FROM AUTHOR]

Global crude steel production is expected to continue to increase in the coming decades to meet the demands of the growing world population. Currently, the dominant steelmaking technology worldwide is the conventional highly CO2-intensive Blast Furnace – Basic Oxygen Furnace production route (also known as the Linz-Donawitz process) using iron ore as raw material and coke as a reducing agent. As a result, large quantities of special gases that are rich in carbon monoxide (CO) are by-products of the various stages of the steelmaking process. Given the challenges associated with satellite-based estimates of carbon dioxide (CO2) emissions at the scale of emitting installations due to significant background levels, co-emitted CO may serve as a valuable indicator of the carbon footprint of steel plants. We show that regional CO release from steel production sites can be monitored from space using 5 years of measurements (2018–2022) from the TROPOspheric monitoring instrument (TROPOMI) on board the Sentinel-5 Precursor satellite benefiting from its relatively high spatial resolution and daily global coverage. We analyse all German steel plants with blast furnaces and basic oxygen furnaces and obtain associated CO emissions in the range of 50–400 kt yr-1 per site. A comparison with the respective CO2 emissions on the level of emitting installations available from emissions trading data of the European Union Emissions Trading System yields a linear relationship with a sector-specific CO/CO2 emission ratio for the analysed steelworks of 3.24 % [2.73–3.89; 1 σ ] suggesting the feasibility of using CO as a proxy for CO2 emissions from comparable steel production sites. [ABSTRACT FROM AUTHOR]

Global crude steel production is expected to continue to increase in the coming decades to meet the demands of the growing world population. Currently, the dominant steelmaking technology worldwide is the conventional highly CO2-intensive Blast Furnace – Basic Oxygen Furnace production route (also known as the Linz-Donawitz process) using iron ore as raw material and coke as a reducing agent. As a result, large quantities of special gases that are rich in carbon monoxide (CO) are by-products of the various stages of the steelmaking process. Given the challenges associated with satellite-based estimates of carbon dioxide (CO2) emissions at the scale of emitting installations due to significant background levels, co-emitted CO may serve as a valuable indicator of the carbon footprint of steel plants. We show that regional CO release from steel production sites can be monitored from space using 5 years of measurements (2018–2022) from the TROPOspheric monitoring instrument (TROPOMI) on board the Sentinel-5 Precursor satellite benefiting from its relatively high spatial resolution and daily global coverage. We analyse all German steel plants with blast furnaces and basic oxygen furnaces and obtain associated CO emissions in the range of 50–400 kt yr-1 per site. A comparison with the respective CO2 emissions on the level of emitting installations available from emissions trading data of the European Union Emissions Trading System yields a linear relationship with a sector-specific CO/CO2 emission ratio for the analysed steelworks of 3.24 % [2.73–3.89; 1σ] suggesting the feasibility of using CO as a proxy for CO2 emissions from comparable steel production sites. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Its atmospheric concentration has increased by almost 50 % since the beginning of the industrial era, causing climate change. Fossil fuel combustion is responsible for most of the atmospheric CO2 increase, which originates to a large extent from localized sources such as power stations. Independent estimates of the emissions from these sources are key to tracking the effectiveness of implemented climate policies to mitigate climate change. We developed an automatic procedure to quantify CO2 emissions from localized sources based on a cross-sectional mass-balance approach and applied it to infer CO2 emissions from the Bełchatów Power Station (Poland) using atmospheric observations from the Orbiting Carbon Observatory 3 (OCO-3) in its snapshot area map (SAM) mode. As a result of the challenge of identifying CO2 emission plumes from satellite data with adequate accuracy, we located and constrained the shape of emission plumes using TROPOspheric Monitoring Instrument (TROPOMI) NO2 column densities. We automatically analysed all available OCO-3 overpasses over the Bełchatów Power Station from July 2019 to November 2022 and found a total of nine that were suitable for the estimation of CO2 emissions using our method. The mean uncertainty in the obtained estimates was 5.8 Mt CO 2 yr -1 (22.0 %), mainly driven by the dispersion of the cross-sectional fluxes downwind of the source, e.g. due to turbulence. This dispersion uncertainty was characterized using a semivariogram, made possible by the OCO-3 imaging capability over a target region in SAM mode, which provides observations containing plume information up to several tens of kilometres downwind of the source. A bottom-up emission estimate was computed based on the hourly power-plant-generated power and emission factors to validate the satellite-based estimates. We found that the two independent estimates agree within their 1σ uncertainty in eight out of nine analysed overpasses and have a high Pearson's correlation coefficient of 0.92. Our results confirm the potential to monitor large localized CO2 emission sources from space-based observations and the usefulness of NO2 estimates for plume detection. They also illustrate the potential to improve CO2 monitoring capabilities with the planned Copernicus Anthropogenic CO2 Monitoring (CO2M) satellite constellation, which will provide simultaneously retrieved XCO2 and NO2 maps. [ABSTRACT FROM AUTHOR]

Premise: Dioecy (separate sexes) has independently evolved numerous times across the angiosperm phylogeny and is recently derived in many lineages. However, our understanding is limited regarding the evolutionary mechanisms that drive the origins of dioecy in plants. The recent and repeated evolution of dioecy across angiosperms offers an opportunity to make strong inferences about the ecological, developmental, and molecular factors influencing the evolution of dioecy, and thus sex chromosomes. The genus Asparagus (Asparagaceae) is an emerging model taxon for studying dioecy and sex chromosome evolution, yet estimates for the age and origin of dioecy in the genus are lacking. Methods: We use plastome sequences and fossil time calibrations in phylogenetic analyses to investigate the age and origin of dioecy in the genus Asparagus. We also review the diversity of sexual systems present across the genus to address contradicting reports in the literature. Results: We estimate that dioecy evolved once or twice approximately 2.78−3.78 million years ago in Asparagus, of which roughly 27% of the species are dioecious and the remaining are hermaphroditic with monoclinous flowers. Conclusions: Our findings support previous work implicating a young age and the possibility of two origins of dioecy in Asparagus, which appear to be associated with rapid radiations and range expansion out of Africa. Lastly, we speculate that paleoclimatic oscillations throughout northern Africa may have helped set the stage for the origin(s) of dioecy in Asparagus approximately 2.78−3.78 million years ago. [ABSTRACT FROM AUTHOR]

Large-scale meteorologic events (e.g. cyclones), referred to as synoptic events, strongly influence weather predictability but still cannot be fully characterised in the Arctic region because of the sparse coverage of measurements. Due to the fact that atmospheric dynamics in the lower stratosphere and troposphere influence the ozone field, an approach to analyse these events further is the use of space-borne measurements of ozone vertical distributions and total columns. In this study we investigate the link between cyclones and changes in stratospheric ozone by using a combination of unique measurements during the MOSAiC ship expedition, ozone profile and total column observations by satellite instruments (OMPS-LP, TROPOMI), and ERA5 reanalysis data. Three special cases during the MOSAiC expedition were selected and classified for the analysis. They consist of one 'normal' cyclone, where a low surface pressure coincides with a minimum in tropopause height, and two 'untypical' cyclones, where this is not observed. The influence of cyclone events on ozone in the upper-troposphere lower-stratosphere (UTLS) region was investigated, using the fact that both are correlated with tropopause height changes. The negative correlation between tropopause height from ERA5 and ozone columns was investigated in the Arctic region for the three-month period from June to August 2020. This was done using total ozone columns and subcolumns from TROPOMI, OMPS-LP and MOSAiC ozonesonde data. The greatest influence of tropopause height changes on ozone contour levels occurs at an altitude between 10 and 20 km. Moreover, the lowering of the 250 ppb ozonopause (about 11 km altitude) below 9 km was used to identify and track cyclones using OMPS-LP ozone observations. The potential of this approach was demonstrated in two case studies where the boundaries of cyclones could be determined using ozone observations. The results of this study can help improve our understanding of the relationship between cyclones, tropopause height, and ozone in the Arctic and demonstrate the usability of satellite ozone data for investigating cyclones in the Arctic. [ABSTRACT FROM AUTHOR]

Large-scale meteorologic events (e.g. cyclones), referred to as synoptic events, strongly influence weather predictability but still cannot be fully characterised in the Arctic region because of the sparse coverage of measurements. Due to the fact that atmospheric dynamics in the lower stratosphere and troposphere influence the ozone field, an approach to analyse these events further is the use of space-borne measurements of ozone vertical distributions and total columns. In this study we investigate the link between cyclones and changes in stratospheric ozone by using a combination of unique measure- ments during the MOSAiC ship expedition, ozone profile and total column observations by satellite instruments (OMPS-LP, TROPOMI), and ERA5 reanalysis data. Three special cases during the MOSAiC expedition were selected and classified for the analysis. They consist of one 'normal' cyclone, where a low surface pressure coincides with a minimum in tropopause height, and two 'untypical' cyclones, where this is not observed. The influence of cyclone events on ozone in the upper-troposphere lower-stratosphere (UTLS) region was investigated, using the fact that both are correlated with tropopause height changes. The negative correlation between tropopause height from ERA5 and ozone columns was investigated in the Arctic region for the three-month period from June to August 2020. This was done using total ozone columns and subcolumns from TROPOMI, OMPS-LP and MOSAiC ozonesonde data. The greatest influence of tropopause height changes on ozone contour levels occurs at an altitude between 10 and 20 km. Moreover, the lowering of the 250 ppb ozonopause (about 11 km altitude) below 9 km was used to identify and track cyclones using OMPS-LP ozone observations. The potential of this approach was demonstrated in two case studies where the boundaries of cyclones could be determined using ozone observations. The results of this study can help improve our understanding of the relationship between cyclones, tropopause height, and ozone in the Arctic and demonstrate the usability of satellite ozone data for investigating cyclones in the Arctic. [ABSTRACT FROM AUTHOR]

The Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) satellite is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, which enables the calculation of daily globally averaged CH4 concentrations. To investigate changes in atmospheric methane, the background CH4 level (i.e. the CH4 concentration without seasonal and short-term variations) has to be determined. CH4 growth rates vary in a complex manner and high-latitude zonal averages may have gaps in the time series, and thus simple fitting methods do not produce reliable results. In this paper we present an approach based on fitting an ensemble of dynamic linear models (DLMs) to TROPOMI data, from which the best model is chosen with the help of cross-validation to prevent overfitting. This method is computationally fast and is not dependent on additional inputs, allowing for fast and continuous analysis of the most recent time series data. We present results of global annual methane increases (AMIs) for the first 4.5 years of S5P/TROPOMI data, which show good agreement with AMIs from other sources. Additionally, we investigated what information can be derived from zonal bands. Due to the fast meridional mixing within hemispheres, we use zonal growth rates instead of AMIs, since they provide a higher temporal resolution. Clear differences can be observed between Northern Hemisphere and Southern Hemisphere growth rates, especially during 2019 and 2022. The growth rates show similar patterns within the hemispheres and show no short-term variations during the years, indicating that air masses within a hemisphere are well-mixed during a year. Additionally, the growth rates derived from S5P/TROPOMI data are largely consistent with growth rates derived from Copernicus Atmospheric Monitoring Service (CAMS) global-inversion-optimized (CAMS/INV) data, which use surface observations. In 2019 a reduction in growth rates can be observed for the Southern Hemisphere, while growth rates in the Northern Hemisphere stay stable or increase. During 2020 a strong increase in Southern Hemisphere growth rates can be observed, which is in accordance with recently reported increases in Southern Hemisphere wetland emissions. In 2022 the reduction in the global AMI can be attributed to decreased growth rates in the Northern Hemisphere, while growth rates in the Southern Hemisphere remain high. Investigations of fluxes from CAMS/INV data support these observations and suggest that the Northern Hemisphere decrease is mainly due to the decrease in anthropogenic fluxes, while in the Southern Hemisphere, wetland fluxes continued to rise. While the continued increase in Southern Hemisphere wetland fluxes agrees with existing studies about the causes of observed methane trends, the difference between Northern Hemisphere and Southern Hemisphere methane increases in 2022 has not been discussed before and calls for further research. [ABSTRACT FROM AUTHOR]

The climate in the Arctic has warmed much more quickly in the last 2 to 3 decades than at the mid-latitudes, i.e., during the Arctic amplification (AA) period. Radiative forcing in the Arctic is influenced both directly and indirectly by aerosols. However, their observation from ground or airborne instruments is challenging, and thus measurements are sparse. In this study, total aerosol optical depth (AOD) is determined from top-of-atmosphere reflectance measurements by the Advanced Along-Track Scanning Radiometer (AATSR) on board ENVISAT over snow and ice in the Arctic using a retrieval called AEROSNOW for the period 2003 to 2011. AEROSNOW incorporates an existing aerosol retrieval algorithm with a cloud-masking algorithm, alongside a novel quality-flagging methodology specifically designed for implementation in the high Arctic region (≥ 72 ∘ N). We use the dual-viewing capability of the AATSR instrument to accurately determine the contribution of aerosol to the reflection at the top of the atmosphere for observations over the bright surfaces of the cryosphere in the Arctic. The AOD is retrieved assuming that the surface reflectance observed by the satellite can be well parameterized by a bidirectional snow reflectance distribution function (BRDF). The spatial distribution of AOD shows that high values in spring (March, April, May) and lower values in summer (June, July, August) are observed. The AEROSNOW AOD values are consistent with those from collocated Aerosol Robotic Network (AERONET) measurements, with no systematic bias found as a function of time. The AEROSNOW AOD in the high Arctic was validated by comparison with ground-based measurements at the PEARL, OPAL, Hornsund, and Thule stations. The AEROSNOW AOD value is less than 0.15 on average, and the linear regression of AEROSNOW and AERONET total AOD yields a slope of 0.98, a Pearson correlation coefficient of R=0.86 , and a root mean square error (RMSE) of =0.01 for the monthly scale in both spring and summer. The AEROSNOW observation of increased AOD values over the high Arctic cryosphere during spring confirms clearly that Arctic haze events were well captured by this dataset. In addition, the AEROSNOW AOD results provide a novel and unique total AOD data product for the springtime and summertime from 2003 to 2011. These AOD values, retrieved from spaceborne observation, provide a unique insight into the high Arctic cryospheric region at high spatial resolution and temporal coverage. [ABSTRACT FROM AUTHOR]

Satellite data records of stratospheric water vapour have been compared to balloon-borne frost point hygrometer (FP) profiles that are coincident in space and time. The satellite data records of 15 different instruments cover water vapour data available from January 2000 through December 2016. The hygrometer data are from 27 stations all over the world in the same period. For the comparison, real or constructed averaging kernels have been applied to the hygrometer profiles to adjust them to the measurement characteristics of the satellite instruments. For bias evaluation, we have compared satellite profiles averaged over the available temporal coverage to the means of coincident FP profiles for individual stations. For drift determinations, we analysed time series of relative differences between spatiotemporally coincident satellite and hygrometer profiles at individual stations. In a synopsis we have also calculated the mean biases and drifts (and their respective uncertainties) for each satellite record over all applicable hygrometer stations in three altitude ranges (10–30 hPa, 30–100 hPa, and 100 hPa to tropopause). Most of the satellite data have biases <10 % and average drifts <1 % yr -1 in at least one of the respective altitude ranges. Virtually all biases are significant in the sense that their uncertainty range in terms of twice the standard error of the mean does not include zero. Statistically significant drifts (95 % confidence) are detected for 35 % of the ≈ 1200 time series of relative differences between satellites and hygrometers. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Its atmospheric concentration has increased by almost 50% since the beginning of the industrial era, causing climate change. Fossil fuel combustion is responsible for most of the atmospheric CO2 increase, which originates to a large extent from localized sources such as power stations. Independent estimates of the emissions from these sources are key to tracking the effectiveness of implemented climate policies to mitigate climate change. We developed a procedure to quantify CO2 emissions from localized sources based on a cross-sectional mass-balance approach and applied it to infer CO2 emissions from the Bełchatów Power Station, in Poland, using atmospheric observations from the Orbiting Carbon Observatory 3 (OCO-3) in its Snapshot Area Map (SAM) mode. As a result of the challenge of identifying CO2 emission plumes from satellite data with adequate accuracy, we located and constrained the shape of emission plumes using TROPOspheric Monitoring Instrument (TROPOMI) NO2 column densities. We analysed all available OCO-3 overpasses over the Bełchatów Power Station from July 2019 to November 2022 and found a total of 9 that were suitable for the estimation of CO2 emissions using our method. The mean uncertainty of the obtained estimates was 5.8 Mt CO2y-1 (22.0%), mainly driven by the dispersion of the cross-sectional fluxes downwind of the source, e.g. due to turbulence. This dispersion uncertainty was characterized using a semivariogram, possible thanks to the OCO-3 imaging capability over a target region in SAM mode, which provides observations containing plume information up to several tens of kilometres downwind of the source. A bottom-up emission estimate was computed based on the hourly power plant generated power and emission factors to validate the satellite-based estimates. We found that the two independent estimates agree within their 1σ uncertainty in 8 out of 9 analysed overpasses and have a high Pearson's correlation coefficient of 0.92. Our results confirm the potential for monitoring large localized CO2 emission sources from space-based observations and the usefulness of NO2 estimates for plume detection. They illustrate as well the potential to improve CO2 monitoring capabilities with the planned Copernicus Anthropogenic CO2 Monitoring (CO2M) satellite constellation, which will provide simultaneously retrieved XCO2 and NO2 maps. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Its atmospheric concentration has increased by almost 50 % since the beginning of the industrial era, causing climate change. Fossil fuel combustion is responsible for most of the atmospheric CO2 increase, which originates to a large extent from localized sources such as power stations. Independent estimates of the emissions from these sources are key to tracking the effectiveness of implemented climate policies to mitigate climate change. We developed a procedure to quantify CO2 emissions from localized sources based on a cross-sectional mass-balance approach and applied it to infer CO2 emissions from the Bełchatów Power Station, in Poland, using atmospheric observations from the Orbiting Carbon Observatory 3 (OCO-3) in its Snapshot Area Map (SAM) mode. As a result of the challenge of identifying CO2 emission plumes from satellite data with adequate accuracy, we located and constrained the shape of emission plumes using TROPOspheric Monitoring Instrument (TROPOMI) NO2 column densities. We analysed all available OCO-3 overpasses over the Bełchatów Power Station from July 2019 to November 2022 and found a total of 9 that were suitable for the estimation of CO2 emissions using our method. The mean uncertainty of the obtained estimates was 5.8 Mt CO2 y−1 (22.0 %), mainly driven by the dispersion of the cross-sectional fluxes downwind of the source, e.g. due to turbulence. This dispersion uncertainty was characterized using a semivariogram, possible thanks to the OCO-3 imaging capability over a target region in SAM mode, which provides observations containing plume information up to several tens of kilometres downwind of the source. A bottom-up emission estimate was computed based on the hourly power plant generated power and emission factors to validate the satellite-based estimates. We found that the two independent estimates agree within their 1 sigma uncertainty in 8 out of 9 analysed overpasses and have a high Pearson's correlation coefficient of 0.92. Our results confirm the potential for monitoring large localized CO2 emission sources from space-based observations and the usefulness of NO2 estimates for plume detection. They illustrate as well the potential to improve CO2 monitoring capabilities with the planned Copernicus Anthropogenic CO2 Monitoring (CO2M) satellite constellation, which will provide simultaneously retrieved XCO2 and NO2 maps. [ABSTRACT FROM AUTHOR]

The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties) which were taken from model data for the year 2015. We consider instrument noise and systematic errors due to the retrieval method but have not considered additional error sources due to e.g. instrumental issues, spectroscopy, or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (Multi Angle Polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data confidence is gained that the FOCAL method is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias = 0.5 ppm for XCO2 and = 5 ppb for XCH4). [ABSTRACT FROM AUTHOR]

During polar spring, ozone depletion events (ODEs) are often observed in combination with bromine explosion events (BEEs) in Ny-Ålesund. In this study, two long-term ozone data sets (2010–2021) from ozonesonde launches and in situ ozone measurements have been evaluated between March and May of each year to study ODEs in Ny-Ålesund. Ozone concentrations below 15 ppb were marked as ODEs. We applied a composite analysis to evaluate tropospheric BrO retrieved from satellite data and the prevailing meteorological conditions during these events. During ODEs, both data sets show a blocking situation with a low-pressure anomaly over the Barents Sea and anomalously high pressure in the Icelandic Low area, leading to transport of cold polar air from the north to Ny-Ålesund with negative temperature and positive BrO anomalies found around Svalbard. In addition, a higher wind speed and a higher, less stable boundary layer are noticed, supporting the assumption that ODEs often occur in combination with polar cyclones. Applying a 20 ppb ozone threshold value to tag ODEs resulted in only a slight attenuation of the BrO and meteorological anomalies compared to the 15 ppb threshold. Monthly analysis showed that BrO and meteorological anomalies are weakening from March to May. Therefore, ODEs associated with low-pressure systems, high wind speeds, and blowing snow more likely occur in early spring, while ODEs associated with low wind speed and stable boundary layer meteorological conditions seem to occur more often in late spring. Annual evaluations showed similar weather patterns for several years, matching the overall result of the composite analysis. However, some years show different meteorological patterns deviating from the results of the mean analysis. Finally, an ODE case study from the beginning of April 2020 in Ny-Ålesund is presented, where ozone was depleted for 2 consecutive days in combination with increased BrO values. The meteorological conditions are representative of the results of the composite analysis. A low-pressure system arrived from the northeast to Svalbard, resulting in high wind speeds with blowing snow and transport of cold polar air from the north. [ABSTRACT FROM AUTHOR]

The Tropospheric Monitoring Instrument (TROPOMI) on-board the satellite Sentinel-5 Precursor (S5P) is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, which enable the calculation of daily globally averaged CH4 concentrations. To investigate changes of atmospheric methane, the background CH4 level (i.e. the CH4 concentration without seasonal and short-term variations) has to be determined. CH4 growth rates vary in a complex manner and high-latitude zonal averages may have gaps in the time series, thus simple fitting methods don't produce reliable results. In this manuscript we present an approach based on fitting an ensemble of Dynamic Linear Models (DLMs) to TROPOMI data, from which the best model is chosen with the help of cross-validation to prevent overfitting. We present results of global annual methane increases (AMIs) for the first 4.5 years of S5P/TROPOMI data which show good agreement with AMIs from other sources. Additionally, we investigated what information can be derived from zonal bands. Due to the fast meridional mixing within hemispheres we use zonal growth rates instead of AMIs, since they provide a daily temporal resolution. Clear differences can be observed between Northern and Southern Hemisphere growth rates, especially during 2019 and 2022. The growth rates show similar patterns within the hemispheres and show no short-term variations during the years, indicating that air masses within a hemisphere are well-mixed during a year. Additionally, the growth rates derived from S5P/TROPOMI data are largely consistent with growth rates derived from CAMS global inversion optimized (CAMS/INV) data. In 2019 a reduction in growth rates can be observed for the Southern Hemisphere, while growth rates in the Northern Hemisphere stay stable or increase. During 2020 a strong increase in Southern Hemisphere growth rates can be observed, which is in accordance with recently reported increases in Southern Hemisphere wetland emissions. In 2022 the reduction of the global AMI can be attributed to decreased growth rates in the Northern Hemisphere, while growth rates in the Southern Hemisphere remain high. Investigations of fluxes from CAMS/INV data support these observations and suggest that the Northern Hemisphere decrease is mainly due to the decrease in anthropogenic fluxes while in the Southern Hemisphere wetland fluxes continued to rise. [ABSTRACT FROM AUTHOR]

The Tropospheric Monitoring Instrument (TROPOMI) on-board the satellite Sentinel-5 Precursor (S5P) is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, which enable the calculation of daily globally averaged CH4 concentrations. To investigate changes of atmospheric methane, the background CH4 level (i.e. the CH4 concentration without seasonal and short-term variations) has to be determined. CH4 growth rates vary in a complex manner and high-latitude zonal averages may have gaps in the time series, thus simple fitting methods don't produce reliable results. In this manuscript we present an approach based on fitting an ensemble of Dynamic Linear Models (DLMs) to TROPOMI data, from which the best model is chosen with the help of cross-validation to prevent overfitting. We present results of global annual methane increases (AMIs) for the first 4.5 years of S5P/TROPOMI data which show good agreement with AMIs from other sources. Additionally, we investigated what information can be derived from zonal bands. Due to the fast meridional mixing within hemispheres we use zonal growth rates instead of AMIs, since they provide a daily temporal resolution. Clear differences can be observed between Northern and Southern Hemisphere growth rates, especially during 2019 and 2022. The growth rates show similar patterns within the hemispheres and show no short-term variations during the years, indicating that air masses within a hemisphere are well-mixed during a year. Additionally, the growth rates derived from S5P/TROPOMI data are largely consistent with growth rates derived from CAMS global inversion-optimized (CAMS/INV) data. In 2019 a reduction in growth rates can be observed for the Southern Hemisphere, while growth rates in the Northern Hemisphere stay stable or increase. During 2020 a strong increase in Southern Hemisphere growth rates can be observed, which is in accordance with recently reported increases in Southern Hemisphere wetland emissions. In 2022 the reduction of the global AMI can be attributed to decreased growth rates in the Northern Hemisphere, while growth rates in the Southern Hemisphere remain high. Investigations of fluxes from CAMS/INV data support these observations and suggest that the Northern Hemisphere decrease is mainly due to the decrease in anthropogenic fluxes while in the Southern Hemisphere wetland fluxes continued to rise. [ABSTRACT FROM AUTHOR]

Stratospheric aerosols play a key role in atmospheric chemistry and climate. Their particle size is a crucial factor controlling the microphysical, radiative, and chemical aerosol processes in the stratosphere. Despite its importance, available observations on aerosol particle size are rather sparse. This limits our understanding and knowledge about the mechanisms and importance of chemical and climate aerosol feedbacks. The retrieval described by Malinina et al. (2018) provides the stratospheric particle size distribution (PSD) from SCIAMACHY limb observations in the tropics. This algorithm has now been improved and extended to work on the entire globe. Two PSD parameters of a unimodal lognormal PSD, the median radius and the geometric standard deviation, are retrieved between 18 and 35 km altitude from SCIAMACHY limb observations by a multi-wavelength non-linear regularized inversion. This assumes a fixed number density profile. The extinction coefficient and the effective radius are calculated. The effective Lambertian surface albedo pre-retrieved from coinciding SCIAMACHY nadir observations is integrated into the retrieval algorithm to mitigate the influence of the surface albedo on the retrieval results. The aerosol characteristics from SCIAMACHY are compared with in-situ balloon-borne measurements from Laramie, Wyoming, and retrievals from the satellite instruments SAGE II, SAGE III, and OSIRIS. In the northern hemisphere, the median radius differs by less than 27% and the geometric standard deviation by less than 11% from both balloon-borne and SAGE III data. Differences are mainly attributed to errors in the assumed a priori number density profile. Globally, the SCIAMACHY extinction coefficients at 750 nm deviate by less than 35% from SAGE II, SAGE III, and OSIRIS data. The effective radius from SCIAMACHY, balloon-borne measurements, and SAGE III agree within about 18% while the effective radius based on SAGE II measurements is systematically larger. The novel data set containing the effective radius and the aerosol extinction coefficient at 525, 750, and 1020 nm from SCIAMACHY observations is publicly available. [ABSTRACT FROM AUTHOR]

In this study, airborne measurements of the sum of hydroperoxyl (HO2) and organic peroxy (RO2) radicals that react with nitrogen monoxide (NO) to produce nitrogen dioxide (NO2), coupled with actinometry and other key trace gases measurements, have been used to test the current understanding of the fast photochemistry in the outflow of major population centres. The measurements were made during the airborne campaign of the EMeRGe (Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales) project in Europe on board the High Altitude and Long Range Research Aircraft (HALO). The measurements of RO 2∗ on HALO were made using the in situ instrument Peroxy Radical Chemical Enhancement and Absorption Spectrometer (PeRCEAS). RO 2∗ is to a good approximation the sum of peroxy radicals reacting with NO to produce NO2. RO 2∗ mixing ratios up to 120 pptv were observed in air masses of different origins and composition under different local actinometric conditions during seven HALO research flights in July 2017 over Europe. Radical production rates were estimated using knowledge of the photolysis frequencies and the RO2∗ precursor concentrations measured on board, as well as the relevant rate coefficients. Generally, high RO2∗ concentrations were measured in air masses with high production rates. In the air masses investigated, RO2∗ is primarily produced by the reaction of O 1 D with water vapour and the photolysis of nitrous acid (HONO) and of the oxygenated volatile organic compounds (OVOCs, e.g. formaldehyde (HCHO) and glyoxal (CHOCHO)). Due to their short lifetime in most environments, the RO 2∗ concentrations are expected to be in a photostationary steady state (PSS), i.e. a balance between production and loss rates is assumed. The RO2∗ production and loss rates and the suitability of PSS assumptions to estimate the RO2∗ mixing ratios and variability during the airborne observations are discussed. The PSS assumption for RO2∗ is considered robust enough to calculate RO2∗ mixing ratios for most conditions encountered in the air masses measured. The similarities and discrepancies between measured and PSS calculated RO2∗ mixing ratios are discussed. The dominant terminating processes for RO2∗ in the pollution plumes measured up to 2000 m are the formation of nitrous acid, nitric acid, and organic nitrates. Above 2000 m, HO2 – HO2 and HO2 – RO2 reactions dominate the RO2∗ removal. RO2∗ calculations by the PSS analytical expression inside the pollution plumes probed often underestimated the measurements. The underestimation is attributed to the limitations of the PSS equation used for the analysis. In particular, this expression does not account for the yields of RO2∗ from the oxidation and photolysis of volatile organic compounds, VOCs, and OVOCs other than those measured during the EMeRGe research flights in Europe. In air masses with NO mixing ratios ≤50 pptv and low VOC/NO ratios, the RO2∗ measured is overestimated by the analytical expression. This may be caused by the formation of H 2 O and O 2 from OH and HO2 , being about 4 times faster than the rate of the OH oxidation reaction of the dominant OVOCs considered. [ABSTRACT FROM AUTHOR]

The Arctic is a unique part of the Earth system that is currently undergoing a warming phase called the Arctic Amplification (AA). Changes in aerosol abundance and composition are under the influence of the AA and may be, in turn, important drivers to the AA. However, their ground and space observations are particularly difficult and spatio-temporally sparse in this region, limiting the knowledge and ability to model their variability. In this study, we have used the total aerosol optical depth (AOD) determined by the AEROSNOWalgorithm using data from the AATSR satellite instrument over snow- and ice-covered regions of the Arctic. This data is then used to evaluate the global GEOS-Chem 3D chemical transport model for the period 2003-2011. Thus, the main drivers of monthly and seasonal variations in spaceborne AOD were determined by using the GEOS-Chem model-simulated aerosol components. By comparing these two AOD datasets, we examined the spring and summer AOD over Arctic snow and ice for the period of space-borne observations. The space-borne and modelled AOD show consistent spatiotemporal distributions in both seasons, with a pronounced chemical speciation in GEOS-Chem. This behaviour is attributed to the different seasonal sources of AOD. In spring, Arctic aerosols originate from long-range pollution transport from low and mid-latitudes as well as from local sources, whereas in summer natural local sources within the Arctic Circle (here defined as > 60°N) dominate. Arctic AOD is generally highest in spring and lowest in summer due to wet scavenging. In addition, carbonaceous aerosols (black carbon, BC, and organic carbon, OC) are an increasingly important contributor to total AOD over Arctic sea ice in summer due to the expected increase in boreal forest fires. The relative contribution of sulfate to total AOD over Arctic sea ice decreases while that of carbonaceous aerosols increases during the spring-summer transition. This suggests that boreal wildfires are penetrating more deeply into Arctic sea ice at higher latitudes during this study period. GEOSChem showed a systematically smaller AOD value compared to AEROSNOW over the Arctic sea ice region in summer. The promising results of AEROSNOW could also serve as the baseline for the evaluation and improvement of aerosol forecasts for various chemical transport models, especially over Arctic sea ice. [ABSTRACT FROM AUTHOR]

The Arctic is a unique part of the Earth system that is currently undergoing a warming phase called the Arctic Amplification (AA). Changes in aerosol abundance and composition are under the influence of the AA and may be, in turn, important drivers to the AA. However, their ground and space observations are particularly difficult and spatio-temporally sparse in this region, limiting the knowledge and ability to model their variability. In this study, we have used the total aerosol optical depth (AOD) determined by the AEROSNOW algorithm using data from the AATSR satellite instrument over snow- and ice-covered regions of the Arctic. This data is then used to evaluate the global GEOS-Chem 3D chemical transport model for the period 2003–2011. Thus, the main drivers of monthly and seasonal variations in spaceborne AOD were determined by using the GEOS-Chem model-simulated aerosol components. By comparing these two AOD datasets, we examined the spring and summer AOD over Arctic snow and ice for the period of space-borne observations. The space-borne and modelled AOD show consistent spatio-temporal distributions in both seasons, with a pronounced chemical speciation in GEOS-Chem. This behaviour is attributed to the different seasonal sources of AOD. In spring, Arctic aerosols originate from long-range pollution transport from low and mid-latitudes as well as from local sources, whereas in summer natural local sources within the Arctic Circle (here defined as > 60° N) dominate. Arctic AOD is generally highest in spring and lowest in summer due to wet scavenging. In addition, carbonaceous aerosols (black carbon, BC, and organic carbon, OC) are an increasingly important contributor to total AOD over Arctic sea ice in summer due to the expected increase in boreal forest fires. The relative contribution of sulfate to total AOD over Arctic sea ice decreases while that of carbonaceous aerosols increases during the spring-summer transition. This suggests that boreal wildfires are penetrating more deeply into Arctic sea ice at higher latitudes during this study period. GEOS-Chem showed a systematically smaller AOD value compared to AEROSNOW over the Arctic sea ice region in summer. The promising results of AEROSNOW could also serve as the baseline for the evaluation and improvement of aerosol forecasts for various chemical transport models, especially over Arctic sea ice. [ABSTRACT FROM AUTHOR]

Cavity ring-down spectroscopy (CRDS) has been applied to retrieve accurate Rayleigh scattering cross-sections, σ Rayl. for a set of atmospheric gases at ~ 408 nm. Step pressure changes and pressure ramps were used in three different but similar optical cavities to measure light extinction by N2, O2, Ar, CO, CO2, N2O, CH4 and synthetic air (SA). The experimentally determined σ Rayl. were compared with σ Rayl. values calculated for these atmospheric gases using knowledge of extrapolated literature values of the refractive index (n) and King correction factors measured in different spectral regions. The difference between measured and calculated σ Rayl. using the most recently published dispersion relationship for N2O and CH4 is ~ 0.6%. This confirms the improved accuracy of the new dispersion relationship. The calculated and measured σ Rayl. agreed on average within 0.6%, 2.4%, 1.2%, 2.2%, and 1.5% for the gases CO2, N2 O2, SA, and Ar at ~ 408 nm. However, for CO, the difference is 4.1%, i.e. more than twice the error. This implies that improved knowledge of the dispersion relationship for CO, and thus the refractive index and King correction factors, would be of value to calculate σ Rayl. in the blue spectral region. [ABSTRACT FROM AUTHOR]

The role of clouds in the Arctic radiation budget is not well understood. Ground-based and airborne measurements provide valuable data to test and improve our understanding. However, the ground-based measurements are intrinsically sparse, and the airborne observations are snapshots in time and space. Passive remote sensing measurements from satellite sensors offer high spatial coverage and an evolving time series, having lengths potentially of decades. However, detecting clouds by passive satellite remote sensing sensors is challenging over the Arctic because of the brightness of snow and ice in the ultraviolet and visible spectral regions and because of the small brightness temperature contrast to the surface. Consequently, the quality of the resulting cloud data products needs to be assessed quantitatively. In this study, we validate the cloud data products retrieved from the Advanced Very High Resolution Radiometer (AVHRR) post meridiem (PM) data from the polar-orbiting NOAA-19 satellite and compare them with those derived from the ground-based instruments during the sunlit months. The AVHRR cloud data products by the European Space Agency (ESA) Cloud Climate Change Initiative (Cloud_CCI) project uses the observations in the visible and IR bands to determine cloud properties. The ground-based measurements from four high-latitude sites have been selected for this investigation: Hyytiälä (61.84 ∘ N, 24.29 ∘ E), North Slope of Alaska (NSA; 71.32 ∘ N, 156.61 ∘ W), Ny-Ålesund (Ny-Å; 78.92 ∘ N, 11.93 ∘ E), and Summit (72.59 ∘ N, 38.42 ∘ W). The liquid water path (LWP) ground-based data are retrieved from microwave radiometers, while the cloud top height (CTH) has been determined from the integrated lidar–radar measurements. The quality of the satellite products, cloud mask and cloud optical depth (COD), has been assessed using data from NSA, whereas LWP and CTH have been investigated over Hyytiälä, NSA, Ny-Å, and Summit. The Cloud_CCI COD results for liquid water clouds are in better agreement with the NSA radiometer data than those for ice clouds. For liquid water clouds, the Cloud_CCI COD is underestimated roughly by 3 optical depth (OD) units. When ice clouds are included, the underestimation increases to about 5 OD units. The Cloud_CCI LWP is overestimated over Hyytiälä by ≈7 g m -2 , over NSA by ≈16 g m -2 , and over Ny-Å by ≈24 g m -2. Over Summit, CCI LWP is overestimated for values ≤20 g m -2 and underestimated for values >20 g m -2. Overall the results of the CCI LWP retrievals are within the ground-based instrument uncertainties. To understand the effects of multi-layer clouds on the CTH retrievals, the statistics are compared between the single-layer clouds and all types (single-layer + multi-layer). For CTH retrievals, the Cloud_CCI product overestimates the CTH for single-layer clouds. When the multi-layer clouds are included (i.e., all types), the observed CTH overestimation becomes an underestimation of about 360–420 m. The CTH results over Summit station showed the highest biases compared to the other three sites. To understand the scale-dependent differences between the satellite and ground-based data, the Bland–Altman method is applied. This method does not identify any scale-dependent differences for all the selected cloud parameters except for the retrievals over the Summit station. In summary, the Cloud_CCI cloud data products investigated agree reasonably well with those retrieved from ground-based measurements made at the four high-latitude sites. [ABSTRACT FROM AUTHOR]

A Tropospheric Ozone Column (TrOC) dataset from the Ozone Mapping and Profiler Suite (OMPS) observations was generated by combining the retrieved total ozone column from OMPS - Nadir Mapper (OMPS-NM) and limb profiles from OMPS Limb Profiler (OMPS-LP) data. All datasets were generated at the University of Bremen, and the TrOC product was obtained by applying the Limb-Nadir Matching technique (LNM). The retrieval algorithm and a comprehensive analysis of the uncertainty budget are presented here. The OMPS-LNM-TrOC dataset (2012-2018) is analysed and validated by comparing with ozonesondes, tropospheric ozone residual (TOR) data from the combined Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) observations, and the TROPOspheric Monitoring Instrument (TROPOMI) Convective Cloud Differential technique (CCD) dataset. The OMPS-LNM TrOC is generally lower than the other datasets. The average bias with respect to ozonesondes is -1.7 DU with no significant latitudinal dependence identified. The mean difference with respect to OMI/MLS TOR and TROPOMI CCD is -3.4 and -1.8 DU, respectively. The seasonality and inter-annual variability are in good agreement with all comparison datasets. [ABSTRACT FROM AUTHOR]

The Arctic climate has changed significantly over the past two to three decades. Aerosols play various roles in the radiative forcing in the Arctic, both directly and indirectly, depending on the changes in loading and composition. However, their observation from the ground or with airborne instruments is challenging and thus measurements are sparse. In this study, total Aerosol Optical Depth (AOD) is determined from top-of-atmosphere reflectance measurements by the Advanced AlongTrack Scanning Radiometer (AATSR) aboard ENVISAT over snow and ice in the Arctic using a retrieval called AEROSNOW for the period 2003 to 2011. We use the dual-viewing capability of the AATSR instrument to reduce the impact of surface reflectance on the accuracy of AOD. The AOD is retrieved assuming that the surface reflectance observed by the satellite can be well-parametrized by a bidirectional snow reflectance distribution function, BRDF. The spatial distribution of AODs shows that high values in spring (March, April, May) and lower AOD values in summer (June, July, August) are well captured. Spaceborne AOD values are consistent with colocated AERONET measurements, with no systematic bias as a function of time. The AEROSNOW AOD in the high Arctic ( ≥ 72°N) was validated by comparison with ground-based measurements at the PEARL, OPAL, Hornsund, and Thule stations. The AEROSNOW AOD value is less than 0.15 on average and the regression to AERONET yields a slope of 0.98, a Pearson correlation coefficient of R = 0.86, and an RMSE = 0.01 at a monthly scale, both in spring and summer. These AOD results provide, for the first time, observational insights into the central Arctic with significant spatial and temporal coverage. [ABSTRACT FROM AUTHOR]

Satellite data records of stratospheric water vapour have been compared to balloon-borne frost point hygrometer (FP) profiles that are coincident in space and time. The satellite data records of 15 different instruments cover water vapour data available from January 2000 through December 2016. The hygrometer data are from 27 stations all over the world in the same period. For the comparison, real or constructed averaging kernels have been applied to the hygrometer profiles to adjust them to the measurement characteristics of the satellite instruments. For bias evaluation, we have compared satellite profiles averaged over the available temporal coverage to the means of coincident FP profiles for individual stations. For drift determinations, we analyzed timeseries of relative differences between spatiotemporally coincident satellite and hygrometer profiles at individual stations. In a synopsis we have also calculated the mean biases and drifts (and their respective uncertainties) for each satellite record over all applicable hygrometer stations in three altitude ranges (10 - 30 hPa, 30 - 100 hPa, and 100 hPa to tropopause). Most of the satellite data have biases < 10% and average drifts < 1%yr-1 in at least one of the respective altitude ranges. Virtually all biases are significant in the sense that their uncertainty range in terms of twice the standard error of the mean does not include zero. Statistically significant drifts (95% confidence) are detected for 35% of the -1200 timeseries of relative differences between satellites and hygrometers. [ABSTRACT FROM AUTHOR]

Inland ships are an important source of NOx , especially for cities along busy waterways. The amount and effect of such emissions depend on the traffic density and NOx emission rates of individual vessels. Ship emission rates are typically derived using in situ land measurements in relation to NOx emission factors (e.g. the number of pollutants emitted by ships per unit of burnt fuel). In this study, a different approach is taken, and NOx emission rates are obtained (in gs-1). Within the EU LIFE project, CLean INland SHipping (CLINSH), a new approach to calculating the NOx emission rates from data of in situ measurement stations has been developed and is presented in this study. Peaks (i.e. elevated concentrations) of NOx were assigned to the corresponding source ships, using the AIS (automated identification system) signals they transmit. Each ship passage was simulated, using a Gaussian puff model, in order to derive the emission rate of the respective source ship. In total, over 32 900 ship passages have been monitored over the course of 4 years. The emission rates of NOx were investigated with respect to ship speed, ship size, and direction of travel. Comparisons of the onshore-derived emission rates and those on board for selected CLINSH ships show good agreement. The derived emission rates are of a similar magnitude to emission factors from previous studies. Most ships comply with existing limits due to grandfathering. The emission rates (in gs-1) can be directly used to investigate the effect of ship traffic on air quality, as the absolute emitted number of pollutants per unit of time is known. In contrast, for relative emission factors (in gkg-1 fuel), further knowledge about the fuel consumption of the individual ships is needed to calculate the number of pollutants emitted per unit of time. [ABSTRACT FROM AUTHOR]

During polar spring, Ozone Depletion Events (ODEs) are often observed in combination with Bromine Explosion Events (BEEs) in Ny-Ålesund. In this study, two long term ozone data sets (2010-2021) from ozone sonde launches and insitu ozone measurements have been evaluated between March and May of each year, to study ODEs in Ny-Ålesund. Ozone concentrations below 15 ppb were marked as ODE. We applied a composite analysis to evaluate tropospheric BrO retrieved from satellite data and the prevailing meteorological conditions during these events. During ODEs, both data sets show a blocking situation with a low pressure anomaly over the Barents Sea and anomalously high pressure in the Icelandic low area, leading to transport of cold polar air from the north to Ny-Ålesund with negative temperature and positive BrO anomalies found around Svalbard. Also higher wind speed and a higher, less stable boundary layer are noticed, supporting the assumption that ODEs often occur in combination with polar cyclones. Applying a 20 ppb ozone threshold value to tag ODEs resulted in only a slight attenuation of the BrO and meteorological anomalies compared to the 15 ppb threshold. Monthly analysis showed that BrO and meteorological anomalies are weakening from March to May. Therefore, ODEs associated with low pressure systems, high wind speeds and blowing snow more likely occur in early spring, while ODEs associated with low wind speed and stable boundary layer meteorological conditions seem to occur more often in late spring. In an annual evaluation, similar prevailing meteorological conditions were found for several years as well as in the overall result of the composite analysis. However, some years show different meteorological patterns deviating from the results of the mean analysis. Finally, an ODE case study from the beginning of April 2020 in Ny-Ålesund is presented, where ozone was depleted for two consecutive days in combination with increased BrO values. The meteorological conditions are representative of the results of the composite analysis. A low pressure system arrived from the north-east to Svalbard resulting in high wind speeds with blowing snow and transport of cold polar air from the north. [ABSTRACT FROM AUTHOR]

During polar spring, Ozone Depletion Events (ODEs) are often observed in combination with Bromine Explosion Events (BEEs) in Ny-Ålesund. In this study, two long term ozone data sets (2010–2021) from ozone sonde launches and in-situ ozone measurements have been evaluated between March and May of each year, to study ODEs in Ny-Ålesund. Ozone concentrations below 15 ppb were marked as ODE. We applied a composite analysis to evaluate tropospheric BrO retrieved from satellite data and the prevailing meteorological conditions during these events. During ODEs, both data sets show a blocking situation with a low pressure anomaly over the Barents Sea and anomalously high pressure in the Icelandic low area, leading to transport of cold polar air from the north to Ny-Ålesund with negative temperature and positive BrO anomalies found around Svalbard. Also higher wind speed and a higher, less stable boundary layer are noticed, supporting the assumption that ODEs often occur in combination with polar cyclones. Applying a 20 ppb ozone threshold value to tag ODEs resulted in only a slight attenuation of the BrO and meteorological anomalies compared to the 15 ppb threshold. Monthly analysis showed that BrO and meteorological anomalies are weakening from March to May. Therefore, ODEs associated with low pressure systems, high wind speeds and blowing snow more likely occur in early spring, while ODEs associated with low wind speed and stable boundary layer meteorological conditions seem to occur more often in late spring. In an annual evaluation, similar prevailing meteorological conditions were found for several years as well as in the overall result of the composite analysis. However, some years show different meteorological patterns deviating from the results of the mean analysis. Finally, an ODE case study from the beginning of April 2020 in Ny-Ålesund is presented, where ozone was depleted for two consecutive days in combination with increased BrO values. The meteorological conditions are representative of the results of the composite analysis. A low pressure system arrived from the north-east to Svalbard resulting in high wind speeds with blowing snow and transport of cold polar air from the north. [ABSTRACT FROM AUTHOR]

Since the initiation of development at the Institute of Environmental Physics (IUP), University of Bremen, in 1994, the radiative transfer model SCIATRAN (formerly GOMETRAN) has been continuously improved and new versions have been released. In the course of development, the SCIATRAN software package became capable of simulating radiative transfer processes through the Earth's atmosphere or coupled atmosphere–ocean system with a variety of approaches to treat the sphericity of the atmosphere (plane-parallel, pseudo-spherical, approximately spherical and full-spherical solutions) in both scalar and vector modes. Supported by a variety of built-in databases and parameterizations, these capabilities made SCIATRAN widely used for various remote-sensing applications related to the retrieval of atmospheric trace gases and characteristics of aerosols, clouds and surfaces. This paper presents an overview of the cloud, aerosol and surface (CAS) databases and models implemented in the SCIATRAN software package (V4.6) and provides some recommendations on their usage. The new implementations offer potential users a flexible interface to perform radiative transfer simulations: (1) accounting for multilayer liquid water, ice and mixed-phase clouds; (2) employing typical aerosol-type parameterizations (including vertical variability) used in the satellite and model communities as well as updated databases; (3) including various surface bidirectional reflectance distribution function (BRDF) and albedo models for land, vegetation, ocean, snow and melt ponds on sea ice. The most recent version of the radiative transfer model SCIATRAN is freely available at the website of the IUP, University of Bremen: http://www.iup.physik.uni-bremen.de/sciatran (last access: November 2022). [ABSTRACT FROM AUTHOR]

Two decades of measurements of spectral reflectance of solar radiation at the top of the atmosphere and a complementary record of cloud properties from satellite passive remote sensing have been analyzed for their pan-Arctic, regional, and seasonal changes. The pan-Arctic loss of brightness, which is explained by the retreat of sea ice during the current warming period, is not compensated by a corresponding increase in cloud cover. A systematic change in the thermodynamic phase of clouds has taken place, shifting towards the liquid phase at the expense of the ice phase. Without significantly changing the total cloud optical thickness or the mass of condensed water in the atmosphere, liquid water content has increased, resulting in positive trends in liquid cloud optical thickness and albedo. This leads to a cooling trend by clouds being superimposed on top of the pan-Arctic amplified warming, induced by the anthropogenic release of greenhouse gases, the ice–albedo feedback, and related effects. Except over the permanent and parts of the marginal sea ice zone around the Arctic Circle, the rate of surface cooling by clouds has increased, both in spring (- 32 % in total radiative forcing for the whole Arctic) and in summer (- 14 %). The magnitude of this effect depends on both the underlying surface type and changes in the regional Arctic climate. [ABSTRACT FROM AUTHOR]