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In this work, a ∼21-year global dataset from four different satellite sensors with a mid-morning overpass (GOME/ERS-2, SCIAMACHY/ENVISAT, GOME-2/Metop-A, and GOME-2/Metop-B) is compiled to study the long-term tropospheric NO2 patterns and trends. The Global Ozone Monitoring Experiment (GOME) and GOME-2 data are “corrected” relative to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data to produce a self-consistent dataset that covers the period April 1996–September 2017. The highest tropospheric NO2 concentrations are seen over urban, industrialized, and highly populated areas and over ship tracks in the oceans. Tropospheric NO2 has generally decreased during the last 2 decades over the industrialized and highly populated regions of the western world (a total decrease of the order of ∼49 % over the US, the Netherlands, and the UK; ∼36 % over Italy and Japan; and ∼32 % over Germany and France) and increased over developing regions (a total increase of ∼160 % over China and ∼33 % over India). It is suggested here that linear trends cannot be used efficiently worldwide for such long periods. Tropospheric NO2 is very sensitive to socioeconomic changes (e.g., environmental protection policies, economic recession, warfare, etc.) which may cause either short-term changes or even a reversal of the trends. The application of a method capable of detecting the year when a reversal of trends happened shows that tropospheric NO2 concentrations switched from positive to negative trends and vice versa over several regions around the globe. A country-level analysis revealed clusters of countries that exhibit similar positive-to-negative or negative-to-positive trend reversals, while 29 out of a total of 64 examined megacities and large urban agglomerations experienced a trend reversal at some point within the last 2 decades.

The aerosol shortwave, direct radiative effects of smoke plumes from Chilean wildfires in 2017 and 2023 were derived from satellite observations in both cloud‐free and cloud scenes. At the top of the atmosphere, the aerosol DRE changes sign when aerosol overly clouds or open ocean, confirmed by both measurements and a simulation study. The cloud‐free daily‐mean DRE, computed using an offline radiative transfer model (RTM), was 66 W m−2 in 2023 and 42 W m−2 in 2017, due to absorption by smoke. However, the total radiative effects were larger in 2017 due to a larger plume size compared to 2023. The method presented here provides a new conceptual model to quickly assess the radiative effects of wildfire smoke plumes using satellite measurements and pre‐computed RTM results. The presented estimates are strongly affected by the uncertainty of aerosol optical thickness retrievals from satellite, which can be large in the presence of clouds. Plain Language Summary From 30 January to the end of February 2023, central Chile experienced over 400 individual wildfires, consuming over 430,000 ha of native sclerophyllous forests, with 25 fatalities as of 14 February. Wildfires are common in central Chile during dry periods, but seem intensified due to the mega‐drought since 2010. Next to health effects, the smoke from these wildfires has important climatic impacts through the change of solar insolation in the atmosphere: smoke strongly absorbs solar radiation and heats the atmosphere, changing the vertical stability. In this paper, the horizontal and vertical smoke distribution in the atmosphere is presented using satellite observations, and the radiative effects in the atmosphere and at the surface are quantified for the recent fires and as well as for the record‐breaking wildfires in 2017, which were the most devastating in the modern history of central‐Chile. Our results show that the radiative effects of the smoke from the recent wildfires were stronger in magnitude during the first few days, but confined to a smaller area, reducing their overall effect. Key Points The radiative effects of the recent 2023 Chilean wildfire smoke plumes are assessed and compared to the 2017 Chilean wildfires smoke plumes Pre‐computed radiative transfer model results can provide readily available aerosol direct radiative effects in clear‐sky for smoke Satellite measurements can further improve the aerosol direct effect and direct forcing estimates for both clear sky and cloud scenes

Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite retrievals in situations with enhanced trace gas concentrations in the lower troposphere. Structural uncertainty arises when different retrieval methodologies are applied within the scientific community to the same satellite observations. Here, we address the issue of AMF structural uncertainty via a detailed comparison of AMF calculation methods that are structurally different between seven retrieval groups for measurements from the Ozone Monitoring Instrument (OMI). We estimate the escalation of structural uncertainty in every sub-step of the AMF calculation process. This goes beyond the algorithm uncertainty estimates provided in state-of-the-art retrievals, which address the theoretical propagation of uncertainties for one particular retrieval algorithm only. We find that top-of-atmosphere reflectances simulated by four radiative transfer models (RTMs) (DAK, McArtim, SCIATRAN and VLIDORT) agree within 1.5%. We find that different retrieval groups agree well in the calculations of altitude resolved AMFs from different RTMs (to within 3%), and in the tropospheric AMFs (to within 6%) as long as identical ancillary data (surface albedo, terrain height, cloud parameters and trace gas profile) and cloud and aerosol correction procedures are being used. Structural uncertainty increases sharply when retrieval groups use their preference for ancillary data, cloud and aerosol correction. On average, we estimate the AMF structural uncertainty to be 42% over polluted regions and 31% over unpolluted regions, mostly driven by substantial differences in the a priori trace gas profiles, surface albedo and cloud parameters. Sensitivity studies for one particular algorithm indicate that different cloud correction approaches result in substantial AMF differences in polluted conditions (5 to 40% depending on cloud fraction and cloud pressure, and 11% on average) even for low cloud fractions (< 0.2) and the choice of aerosol correction introduces an average uncertainty of 50% for situations with high pollution and high aerosol loading. Our work shows that structural uncertainty in AMF calculations is significant and that it is mainly caused by the assumptions and choices made to represent the state of the atmosphere. In order to decide which approach and which ancillary data are best for AMF calculations, we call for well-designed validation exercises focusing on polluted conditions in which AMF structural uncertainty has the highest impact on NO2 and HCHO retrievals.

In this paper we introduce the new concept of directionally dependent Lambertian-equivalent reflectivity (DLER) of the Earth's surface retrieved from satellite observations. This surface DLER describes Lambertian (isotropic) surface reflection which is extended with a dependence on the satellite viewing geometry. We apply this concept to data of the GOME-2 satellite instruments to create a global database of the reflectivity of the Earth's surface, providing surface DLER for 26 wavelength bands between 328 and 772 nm as a function of the satellite viewing angle via a second-degree polynomial parameterisation. The resolution of the database grid is 0.25∘ by 0.25∘, but the real, intrinsic spatial resolution varies over the grid from 1.0∘ by 1.0∘ to 0.5∘ by 0.5∘ down to 0.25∘ by 0.25∘ by applying dynamic gridding techniques. The database is based on more than 10 years (2007–2018) of GOME-2 data from the MetOp-A and MetOp-B satellites. The relation between DLER and bi-directional reflectance distribution function (BRDF) surface reflectance is studied using radiative transfer simulations. For the shorter wavelengths (λ<500 nm), there are significant differences between the two. For instance, at 463 nm the difference can go up to 6 % at 30∘ solar zenith angle. The study also shows that, although DLER and BRDF surface reflectances have different properties, they are comparable for the longer wavelengths (λ>500 nm). Based on this outcome, the GOME-2 surface DLER is compared with MODIS surface BRDF data from MODIS band 1 (centred around 645 nm) using both case studies and global comparisons. The conclusion of this validation is that the GOME-2 DLER compares well to MODIS BRDF data and that it does so much better than the non-directional LER database. The DLER approach for describing surface reflectivity is therefore an important improvement over the standard isotropic (non-directional) LER approaches used in the past. The GOME-2 surface DLER database can be used for the retrieval of atmospheric properties from GOME-2 and from previous satellite instruments like GOME and SCIAMACHY. It will also be used to support retrievals from the future Sentinel-5 UVNS (ultraviolet, visible, near-infrared, and short-wave infrared) satellite instrument.

This study presents an analysis of TROPOMI cloud heights as a proxy for volcanic plume heights in the presence of absorbing aerosols and sulfur dioxide for the 19 February 2018 eruption plume of the Sinabung volcano on Sumatra, Indonesia. Comparison with CALIPSO satellite data shows that all three TROPOMI cloud height data products based on oxygen absorption which are considered here (FRESCO, ROCINN, O22CLD) provide volcanic ash cloud heights comparable to heights measured by CALIPSO for optically thick volcanic ash clouds. FRESCO and ROCINN heights are very similar, with the only differences for FRESCO cloud top heights above 14 km altitude. O22CLD cloud top heights unsurprisingly fall below those of FRESCO and ROCINN, as the O22CLD retrieval is less sensitive to cloud top heights above 10 km altitude. For optically thin volcanic ash clouds, i.e., when Earth's surface or clouds at lower altitudes shine through the volcanic ash cloud, retrieved heights fall below the volcanic ash cloud heights derived from CALIPSO data. Evaluation of corresponding Himawari-8 geostationary infrared (IR) brightness temperature differences (ΔBTs) – a signature for detection of volcanic ash clouds in geostationary satellite data and widely used as input for quantitative volcanic ash cloud retrievals – reveals that for this particular eruption the ΔBT volcanic ash signature changes to a ΔBT ice crystal signature for the part of the ash plume reaching the upper troposphere beyond 10 km altitude several hours after the start of the eruption and which TROPOMI clearly characterizes as volcanic (SO2 > 1 DU – Dobson units – and AAI > 4 – absorbing aerosol index – or, more conservatively, SO2 > 10). The presence of ice in volcanic ash clouds is known to prevent the detection of volcanic ash clouds based on broadband geostationary satellite data. TROPOMI does not suffer from this effect and can provide valuable and accurate information about volcanic ash clouds and ash top heights in cases where commonly used geostationary IR measurements of volcanic ash clouds fail.

In this study we present the retrieval of the column-averaged dry air mole fraction of carbon dioxide (XCO2) from the TanSat observations using the ACOS (Atmospheric CO2 Observations from Space) algorithm. The XCO2 product has been validated with collocated ground-based measurements from the Total Carbon Column Observing Network (TCCON) for 2 years of TanSat data from 2017 to 2018. Based on the correlation of the XCO2 error over land with goodness of fit in three spectral bands at 0.76, 1.61 and 2.06 μm, we applied an a posteriori bias correction to TanSat retrievals. For overpass averaged results, XCO2 retrievals show a standard deviation (SD) of ~2.45 ppm and a positive bias of ~0.27 ppm compared to collocated TCCON sites. The validation also shows a relatively higher positive bias and variance against TCCON over high-latitude regions. Three cases to evaluate TanSat target mode retrievals are investigated, including one field campaign at Dunhuang with measurements by a greenhouse gas analyzer deployed on an unmanned aerial vehicle and two cases with measurements by a ground-based Fourier-transform spectrometer in Beijing. The results show the retrievals of all footprints, except footprint-6, have relatively low bias (within ~2 ppm). In addition, the orbital XCO2 distributions over Australia and Northeast China between TanSat and the second Orbiting Carbon Observatory (OCO-2) on 20 April 2017 are compared. It shows that the mean XCO2 from TanSat is slightly lower than that of OCO-2 with an average difference of ~0.85 ppm. A reasonable agreement in XCO2 distribution is found over Australia and Northeast China between TanSat and OCO-2.

The angular distribution of the light reflected by the Earth's surface influences top-of-atmosphere (TOA) reflectance values. This surface reflectance anisotropy has implications for UV/Vis satellite retrievals of albedo, clouds, and trace gases such as nitrogen dioxide (NO2). These retrievals routinely assume the surface to reflect light isotropically. Here we show that cloud fractions retrieved from GOME-2A and OMI with the FRESCO and OMCLDO2 algorithms have an east–west bias of 10 % to 50 %, which are highest over vegetation and forested areas, and that this bias originates from the assumption of isotropic surface reflection. To interpret the across-track bias with the DAK radiative transfer model, we implement the bidirectional reflectance distribution function (BRDF) from the Ross–Li semi-empirical model. Testing our implementation against state-of-the-art RTMs LIDORT and SCIATRAN, we find that simulated TOA reflectance generally agrees to within 1 %. We replace the assumption of isotropic surface reflection in the equations used to retrieve cloud fractions over forested scenes with scattering kernels and corresponding BRDF parameters from a daily high-resolution database derived from 16 years' worth of MODIS measurements. By doing this, the east–west bias in the simulated cloud fractions largely vanishes. We conclude that across-track biases in cloud fractions can be explained by cloud algorithms that do not adequately account for the effects of surface reflectance anisotropy. The implications for NO2 air mass factor (AMF) calculations are substantial. Under moderately pollutedNO2 and backward-scattering conditions, clear-sky AMFs are up to 20 % higher and cloud radiance fractions up to 40 % lower if surface anisotropic reflection is accounted for. The combined effect of these changes is that NO2 total AMFs increase by up to 30 % for backward-scattering geometries (and decrease by up to 35 % for forward-scattering geometries), which is stronger than the effect of either contribution alone. In an unpolluted troposphere, surface BRDF effects on cloud fraction counteract (and largely cancel) the effect on the clear-sky AMF. Our results emphasise that surface reflectance anisotropy needs to be taken into account in a coherent manner for more realistic and accurate retrievals of clouds andNO2 from UV/Vis satellite sensors. These improvements will be beneficial for current sensors, in particular for the recently launched TROPOMI instrument with a high spatial resolution.

Clouds affected by solar eclipses could influence the reflection of sunlight back into space and might change local precipitation patterns. Satellite cloud retrievals have so far not taken into account the lunar shadow, hindering a reliable spaceborne assessment of the eclipse-induced cloud evolution. Here we use satellite cloud measurements during three solar eclipses between 2005 and 2016 that have been corrected for the partial lunar shadow together with large-eddy simulations to analyze the eclipse-induced cloud evolution. Our corrected data reveal that, over cooling land surfaces, shallow cumulus clouds start to disappear at very small solar obscurations (~15%). Our simulations explain that the cloud response was delayed and was initiated at even smaller solar obscurations. We demonstrate that neglecting the disappearance of clouds during a solar eclipse could lead to a considerable overestimation of the eclipse-related reduction of net incoming solar radiation. These findings should spur cloud model simulations of the direct consequences of sunlight-intercepting geoengineering proposals, for which our results serve as a unique benchmark.

The authors wish to make the following corrections to this paper [...]

The vulnerability of the (European) aviation system to the airborne hazards was evident during the Eyjafjallajökull volcanic eruption in 2010. For support of Air Traffic Control (ATC) many observations of the event were available from satellites, ground based instruments and airborne platforms, at pan-European scale. However, efficient use of the data for ATC proved difficult mainly due to sub-optimal aggregation and integrated assessment of the available information in near-real-time. The project EUNADICS-AV (European Natural Disaster Coordination and Information System for Aviation) aims to close this gap. The observational component of the project will make existing data products for airborne hazards more accessible, visible and used, and to foster tailored product development. Once assimilated into models and integrated in the EUNADICS-AV Data Portal these data can be the base to efficiently improve European airspace resilience to airborne hazards. Since 2010 new data products have become available specifically for for airborne hazard alerting and monitoring together with specific tailored products designed for replying to user needs and recommendations. This paper describes the EUNADICS-AV approach and will focus on the role of operational and research grade ground based lidars.