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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]

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]