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We introduce NitroNet, a deep learning model for the prediction of tropospheric NO2 profiles from satellite column measurements. NitroNet is a neural network trained on synthetic NO2 profiles from the regional chemistry and transport model WRF-Chem, which was operated on a European domain for the month of May 2019. This WRF-Chem simulation was constrained by in situ and satellite measurements, which were used to optimize important simulation parameters (e.g. the boundary layer scheme). The NitroNet model receives NO2 vertical column densities (VCDs) from the TROPOspheric Monitoring Instrument (TROPOMI) and ancillary variables (meteorology, emissions, etc.) as input, from which it reproduces NO2 concentration profiles. Training of the neural network is conducted on a filtered dataset, meaning that NO2 profiles showing strong disagreement (>20 %) with colocated TROPOMI column measurements are discarded. We present a first evaluation of NitroNet over a variety of geographical and temporal domains (Europe, the US West Coast, India, and China) and different seasons. For this purpose, we validate the NO2 profiles predicted by NitroNet against satellite, in situ, and MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) measurements. The training data were previously validated against the same datasets. During summertime, NitroNet shows small biases and strong correlations with all three datasets: a bias of +6.7% and R=0.95 for TROPOMI NO2 VCDs, a bias of -10.5% and R=0.75 for AirBase surface concentrations, and a bias of -34.3% to +99.6% with R=0.83 – 0.99 for MAX-DOAS measurements. In comparison to TROPOMI satellite data, NitroNet even shows significantly lower errors and stronger correlation than a direct comparison with WRF-Chem numerical results. During wintertime considerable low biases arise because the summertime/late-spring training data are not fully representative of all atmospheric wintertime characteristics (e.g. longer NO2 lifetimes). Nonetheless, the wintertime performance of NitroNet is surprisingly good and comparable to that of classic regional chemistry and transport models. NitroNet can demonstrably be used outside the geographic and temporal domain of the training data with only slight performance reductions. What makes NitroNet unique when compared to similar existing deep learning models is the inclusion of synthetic model data, which offers important benefits: due to the lack of NO2 profile measurements, models trained on empirical datasets are limited to the prediction of surface concentrations learned from in situ measurements. NitroNet, however, can predict full tropospheric NO2 profiles. Furthermore, in situ measurements of NO2 are known to suffer from biases, often larger than +20 %, due to cross-sensitivities to photooxidants, which other models trained on empirical data inevitably reproduce. [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]

Pioneering the use of the Geostationary Environment Monitoring Spectrometer's (GEMS) observation data in air quality modeling, we adjusted Asia's NOx emissions inventory by leveraging the instrument's unprecedented sampling frequency. GEMS tropospheric NO2 columns served as top-down constraints, guiding our Bayesian inversion to constrain NOx emissions in Asia during spring 2022. This enabled the model to better capture the diurnal variation in NOx emissions, such as its morning rush hour peak, particularly when more retrievals were available each day, improving the simulation accuracy to a certain extent. The GEMS-informed adjustment reduced the extent of model underestimation of surface NO2 concentrations from 17.38 to 5.58% in Korea and from 13.05 to 4.54% in China, showing about 9.40% and 5.77% greater improvements, respectively, compared to the adjustment based on the sun-synchronous low earth orbit observation proxy. Our findings highlight the potential of geostationary observation data in refining the diurnal cycle of inventoried NOx emissions, thereby more effectively improving the accuracy of air quality simulations. [ABSTRACT FROM AUTHOR]

This study presents new glyoxal (CHOCHO) products from the Ozone Monitoring Instrument (OMI) by utilizing updated level 1B irradiance/radiance data (Collection 4) and an updated glyoxal retrieval algorithm. The adoption of Collection 4 contributes to the reduction of artificial signals in differential glyoxal slant column densities (dSCDs) and improved fitting root mean square, and the updated retrieval settings result in fewer negative values of glyoxal dSCDs over oceans and less noisy dSCDs in the South Atlantic Anomaly. On‐line calculations of air mass factors consider interactive physical processes between input parameters. To address persistent trends in glyoxal SCDs over the Pacific Ocean that remain despite these updates, a trend correction is implemented. We evaluate the updated OMI glyoxal products using inter‐comparisons with GOME‐2A/2B glyoxal products. OMI glyoxal products exhibit good spatial and temporal agreement with GOME‐2A/2B, with correlation coefficients of 0.75–0.78 globally and 0.84–0.85 over source regions. Small biases are observed in OMI glyoxal vertical column densities, ranging from −0.2 ± 5.7% to 9 ± 3% in low and high glyoxal conditions, respectively, against GOME‐2A/2B. These advancements contribute to the reliability and accuracy of OMI glyoxal products, enhancing their utility for atmospheric studies and enabling a 20‐year‐long data record suitable for climate studies. Plain Language Summary: This research introduces new glyoxal (CHOCHO) products obtained from a satellite instrument called the Ozone Monitoring Instrument (OMI). For new glyoxal products, we use the updated OMI irradiance/radiance data and update the way we analyze the radiance data. As a result, new OMI glyoxal products show the reduction of errors caused by the instrument and consider interactive physical processes between the surface and atmosphere. The new data matches well with similar data from other satellite instruments (GOME‐2A/B), showing that the improvements are effective. This better data set helps scientists study the air quality over a long period of time. Key Points: We improve Ozone Monitoring Instrument (OMI) glyoxal column measurements with the new radiance data (Collection 4) and updated retrieval algorithmThe new glyoxal measurements show the stable spectral fitting through OMI's lifetimeCompared to GOME‐2A/B, OMI glyoxal products show good spatial (temporal) correlation coefficients of 0.75–0.78 (0.84–0.85), respectively [ABSTRACT FROM AUTHOR]

The Copernicus Atmosphere Monitoring Service (CAMS) provides daily analyses and forecasts of the composition of the atmosphere, including the reactive gases such as O3 , CO , NO2 , HCHO and SO2 ; aerosol species; and greenhouse gases. The global CAMS analysis system (IFS-COMPO) is based on the ECMWF Integrated Forecasting System (IFS) for numerical weather prediction (NWP) and assimilates a large number of composition satellite products on top of the meteorological observations ingested in IFS. The CAMS system receives regular upgrades, following the upgrades of IFS. The last upgrade, Cy48R1, operational since 27 June 2023, was major with a large number of code changes, both for IFS-COMPO and for NWP. The main IFS-COMPO innovations include the introduction of full stratospheric chemistry; a major update of the emissions; a major update of the aerosol model, including the representation of secondary organic aerosol; several updates of the dust life cycle and optics; updates to the inorganic chemistry in the troposphere; and the assimilation of Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth (AOD) and TROPOspheric Monitoring Instrument (TROPOMI) CO. The CAMS Cy48R1 upgrade was validated using a large number of independent measurement datasets, including surface in situ, surface remote sensing, routine aircraft, and balloon and satellite observations. In this paper we present the validation results for Cy48R1 by comparing them with the skill of the previous operational system (Cy47R3), with the independent observations as reference, for the period October 2022 to June 2023, during which daily forecasts from both cycles are available. Major improvements in skill are found for the ozone profile in the lower–middle stratosphere and for stratospheric NO2 due to the inclusion of full stratospheric chemistry. Stratospheric trace gases compare well with the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) observations between 10 and 200 hPa, with larger deviations between 1 and 10 hPa. The impact of the updated emissions is especially visible over East Asia and is beneficial for the trace gases O3 , NO2 and SO2. The CO column assimilation is now anchored by the Infrared Atmospheric Sounding Interferometer (IASI) instead of the Measurements Of Pollution in The Troposphere (MOPITT) instrument, which is beneficial for most of the CO comparisons, and the assimilation of TROPOMI CO data improves the model CO field in the troposphere. In general the aerosol optical depth has improved globally, but the dust evaluation shows more mixed results. The results of the 47 comparisons are summarised in a scorecard, which shows that 83 % of the evaluation datasets show a neutral or improved performance of Cy48R1 compared to the previous operational CAMS system, while 17 % indicate a (slight) degradation. This demonstrates the overall success of this upgrade. [ABSTRACT FROM AUTHOR]

The Geostationary Environment Monitoring Spectrometer (GEMS) over Asia is the first geostationary Earth orbit instrument in the virtual constellation of sensors for atmospheric chemistry and composition air quality research and applications. For the first time, the hourly observations enable studies of diurnal variation in several important trace gas and aerosol pollutants including nitrogen dioxide (NO2), which is the focus of this work. NO2 is a regulated pollutant and an indicator of anthropogenic emissions in addition to being involved in tropospheric ozone chemistry and particulate matter formation. We present new quantitative measures of NO2 tropospheric column diurnal variation which can be greater than 50 % of the column amount, especially in polluted environments. The NO2 distribution is seen to change hourly and can be quite different from what would be seen by a once-a-day low-Earth-orbit satellite observation. We use GEMS data in combination with TROPOspheric Monitoring Instrument (TROPOMI) satellite and Pandora ground-based remote sensing measurements and Multi-Scale Infrastructure for Chemistry and Aerosols (Version 0, MUSICAv0) 3D chemical transport model analysis to examine the NO2 diurnal variation in January and June 2023 over Northeast Asia and Seoul, South Korea, study regions to distinguish the different emissions, chemistry, and meteorological processes that drive the variation. Understanding the relative importance of these processes will be key to including pollutant diurnal variation in models aimed at determining true pollutant exposure levels for air quality studies. The work presented here also provides a path for investigating similar NO2 diurnal cycles in the new Earth Venture Instrument-1 Tropospheric Emissions: Monitoring Pollution (TEMPO) data over North America, and later over Europe with Sentinel-4. [ABSTRACT FROM AUTHOR]

Here, we present observations of temporal variability of sub-ice platelet layer over seasonal and diurnal timescales under Ice Shelf Water-influenced fast ice in McMurdo Sound. Electromagnetic induction (EM) sounding time-series measurements of the thicknesses of fast ice and sub-ice platelet layer were made in winter and late spring of 2018. Winter objectives were to measure the seasonal growth of fast ice and sub-ice platelet layer near the McMurdo Ice Shelf in the east, while in late spring we assessed the diurnal variability of sub-ice platelet layer with coincident EM time-series and oceanographic measurements collected in the main outflow path of supercooled Ice Shelf Water in the west. During winter, we observed when the sub-ice platelet layer formed beneath consolidated ice. Episodes of rapid sub-ice platelet layer growth (∼ 0.5–1 m) coincided with strong southerly wind events and polynya activity, suggesting wind-enhanced Ice Shelf Water circulation from the McMurdo–Ross Ice Shelf cavity. In late spring, we investigated how the tides and ocean properties influenced the sub-ice platelet layer. Over a 2-week neap–spring tidal cycle, changes in sub-ice platelet layer thickness were observed to correlate with the tides, increasing more during neap than spring tide cycles, and on diurnal timescales, more on ebb than flood tides. Neap and ebb tides correspond with stronger northward circulation out of the cavity, indicating that sub-ice platelet layer growth was driven by tidally enhanced Ice Shelf Water outflow. The observed variability indicated that wind-driven circulation and the tides influence Ice Shelf Water outflow in McMurdo Sound and, consequently, sub-ice platelet layer evolution over a range of timescales. [ABSTRACT FROM AUTHOR]

NOx is an important primary air pollutant of major environmental concern which is predominantly produced by anthropogenic combustion activities. NOx needs to be accounted for in national emission inventories, according to international treaties. Constructing accurate inventories requires substantial time and effort, resulting in reporting delays of 1 to 5 years. In addition to this, difficulties can arise from temporal and country-specific legislative and protocol differences. To address these issues, satellite-based atmospheric composition measurements offer a unique opportunity for the independent and large-scale estimation of emissions in a consistent, transparent, and comprehensible manner. Here we test the multi-source plume method (MSPM) to assess the NOx emissions over Germany in the COVID-19 period from 2019–2021. For the years where reporting is available, the differences between satellite estimates and inventory totals were within 75–100 kt (NO2) NOx (<10 % of inventory values). The large reduction in the NOx emissions (∼15 %) concurrent with the COVID-19 lockdowns was observed in both the inventory and satellite-derived emissions. The recent projections for the inventory emissions of 2021 pointed to a recovery of the 2021 emissions towards pre-COVID-19 levels. In the satellite-derived emissions, however, such an increase was not observed. While emissions from the larger power plants did rebound to pre-COVID-19 levels, other sectors such as road transport did not, and the change in emissions is likely due to a reduction in the number of heavier transport trucks compared to the pre-COVID-19 numbers. This again illustrates the value of having a consistent satellite-based methodology for faster emission estimates to guide and check the conventional emission inventory reporting. The method described in this work also meets the demand for independent verification of the official emission inventories, which will enable inventory compilers to detect potentially problematic reporting issues, bolstering transparency and comparability, which are two key values for emission reporting. [ABSTRACT FROM AUTHOR]

Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO 2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO 2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx , but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO 2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO 2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO 2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO 2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO 2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO 2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO 2 reflects a dynamic balance between emission and chemical loss. [ABSTRACT FROM AUTHOR]

We present a new method for estimating NOx emissions and effective lifetimes from large cities based on NO2 measurements from the TROPOspheric Monitoring Instrument (TROPOMI) (PAL dataset, May 2018–November 2021). As in previous studies, the estimate is based on the downwind plume evolution for different wind directions separately. The novelty of the presented approach lies in the simultaneous fit of downwind patterns for opposing wind directions, which makes the method far more robust (i.e., less prone to local minima with nonphysically high or low lifetimes) than a single exponential decay fit. In addition, the new method does not require the assumption of a city being a "point source" but also derives the spatial distribution of emissions. The method was successfully applied to 100 cities worldwide on a seasonal scale. Fitted emissions generally agree reasonably with the Emissions Database for Global Atmospheric Research (EDGAR) v6 (R=0.72) and are on average 14 % lower, while estimated uncertainties are still rather large (≈ 30 %–50 %). Lifetimes were found to be rather short (2.44 ± 0.68 h) and show no distinct dependency on season or latitude, which might be a consequence of discarding observations at high solar zenith angles (>65 °). The main limitations of this and similar methods are the underlying assumptions of steady state (meaning constant emissions, wind fields and chemical conditions) within about 100 km downwind from a city, which is probably a simplification that is too strong in order to reach higher accuracies. [ABSTRACT FROM AUTHOR]

Pioneering the use of the Geostationary Environment Monitoring Spectrometer's (GEMS) observation data in air quality modeling, we adjusted Asia's NO x emissions inventory by leveraging the instrument's unprecedented sampling frequency. GEMS tropospheric NO 2 columns served as top-down constraints, guiding our Bayesian inversion to constrain NO x emissions in Asia during spring 2022. This enabled the model to better capture the diurnal variation in NO x emissions, such as its morning rush hour peak, particularly when more retrievals were available each day, improving the simulation accuracy to a certain extent. The GEMS-informed adjustment reduced the extent of model underestimation of surface NO 2 concentrations from 17.38 to 5.58% in Korea and from 13.05 to 4.54% in China, showing about 9.40% and 5.77% greater improvements, respectively, compared to the adjustment based on the sun-synchronous low earth orbit observation proxy. Our findings highlight the potential of geostationary observation data in refining the diurnal cycle of inventoried NO x emissions, thereby more effectively improving the accuracy of air quality simulations., (© 2024. The Author(s).)

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Since the beginning of the aggression of the Russian Federation in Ukraine, education in many Ukrainian universities has been suspended due to security reasons for a certain period. But the war affected not only the forms of education, but also the content: military issues are increasingly reflected in educational courses and research projects. This applies directly to the bachelor's and master's training program in the field of Ecology of the National University of Kyiv–Mohyla Academy. Therefore, the practice of integrating new methodological approaches into educational courses related to the assessment of the impact of hostilities on the natural environment, the assessment of ecological damage, and the restoration of disturbed natural systems has become widespread. Students are also involved in conducting research as part of their bachelor's and master's theses. In this work, we present the results of the assessment of the impact of hostilities on atmospheric air, which was carried out as part of teaching the courses 'Meteorology and Climatology', 'Geoinformation Systems', 'Environmental Monitoring' and others. Faculty researchers and students extensively analyzed the profound direct and indirect environmental effects of the war in Ukraine. These effects can be attributed to changes in the optical characteristics of the atmosphere, atmospheric pollution caused by the emission of missile and shell detonation products, and the increasing release of greenhouse gases and gas-aerosol impurities. Satellite data were used for this purpose. Satellite observation of atmospheric concentrations of formaldehyde, aerosol, carbon monoxide, nitrogen oxide, and sulphur dioxide from the Sentinel–5P satellite was an important research method integrated into the educational process. Daily satellite observation data were analyzed using the Google Earth Engine platform for the period 2019–2022. Data were monthly and yearly averaged within the boundaries of rayons (second–level administrative units of Ukraine). It helped to register the dynamic of air pollution in the conditions of war. A full–scale war in Ukraine caused the suspension of many enterprises that were the main sources of gas emissions into the atmosphere, especially in the eastern and southern parts of Ukraine. Therefore, in recent months, the content of pollutants in the atmosphere over these regions is mainly tent to background values and as a result of hostilities. However, massive shelling, the use of military heavy equipment, and fires caused additional emissions of a number of pollutants into the atmosphere. It should be noted that in certain regions and certain months during the active phase of hostilities, these emissions were exceeded by several times compared to the average for the period 2019–2021. [ABSTRACT FROM AUTHOR]

The characteristics of the sea ice conditions in the seas of the Russian Arctic during the period of satellite measurements were studied, and quantitative estimates of their changes in the second half of the 21st century were obtained based on the results of the CMIP6 climate model ensemble using non-mitigation and moderate mitigation scenarios of anthropogenic impact, SSP585 and SSP245, respectively. It has been revealed that the dates of closing (DOC) of the sea ice cover and the length of the open water season (LOWS) are in general successfully reproduced by an ensemble of models. It is shown that DOC will be observed on the average about one month and ten days later under SSP245 scenario and two months later under the SSP585 scenario in 2061–2080 compared to period 1981–2020. At the same time, the increase of LOWS is more than 2.5 months under SSP245 scenario and almost four months under the SSP585 scenario. The most significant changes in DOC are expected in the northern parts of the Barents and Kara seas and in the northwestern part of the Laptev Sea: 2–2.5 months and 2.5–3 months later for the SSP245 and SSP585 scenarios, respectively. [ABSTRACT FROM AUTHOR]

We validate formaldehyde (HCHO) vertical column densities (VCDs) from Ozone Mapping and Profiler Suite Nadir Mapper (OMPS‐NM) instruments onboard the Suomi National Polar‐orbiting Partnership (Suomi NPP) satellite for 2012–2020 and National Oceanic and Atmospheric Administration‐20 (NOAA‐20) satellite for 2018–2020, hereafter referred to as OMPS‐NPP and OMPS‐N20, with ground‐based Fourier‐Transform Infrared (FTIR) observations of the Network for the Detection of Atmospheric Composition Change (NDACC). OMPS‐NPP/N20 HCHO products reproduce seasonal variability at 24 FTIR sites. Monthly variability of OMPS‐NPP/N20 has a very good agreement with FTIR, showing correlation coefficients of 0.83 and 0.88, respectively. OMPS‐NPP (N20) biases averaged over all sites are −0.9 (4) ± 3 (6)%. However, at clean sites (with VCDs < 4.0 × 1015 molecules cm−2), positive biases of 20 (32) ± 6 (18)% occur for OMPS‐NPP (N20). At sites with HCHO VCDs > 4.0 × 1015 molecules cm−2, negative biases of −15% ± 4% appear for OMPS‐NPP, but OMPS‐N20 shows smaller bias of 0.5% ± 6% due to its smaller ground pixel footprints. Therefore, smaller satellite footprint sizes are important in distinguishing small‐scale plumes. In addition, we discuss a bias correction and provide lower limit for the monthly uncertainty of OMPS‐NPP/N20 HCHO products. The total uncertainty for OMPS‐NPP (N20) at clean sites is 0.7 (0.8) × 1015 molecules cm−2, corresponding to a relative uncertainty of 32 (30)%. In the case of HCHO VCDs > 4.0 × 1015 molecules cm−2, however, the relative uncertainty in HCHO VCDs for OMPS‐NPP (N20) decreases to 31 (18)%. Plain Language Summary: Formaldehyde is a proxy for nonmethane volatile organic compounds (NMVOCs). Formaldehyde observations from satellites have been widely used to investigate NMVOC emissions, ozone production regime with NOx, and the production of secondary organic aerosols. We validate new publicly available satellite formaldehyde observations from two Ozone Mapping and Profiler Suite (OMPS) instruments onboard Suomi NPP and NOAA‐20 satellites, called OMPS‐NPP and OMPS‐N20 hereafter, with ground‐based Fourier‐Transform Infrared (FTIR) observations. OMPS‐NPP/N20 products show good correlation coefficients of 0.83 and 0.88 compared to FTIR and also capture seasonal variability at 24 sites. However, OMPS products have a bias depending on formaldehyde concentrations. In low formaldehyde concentrations, positive biases of 20 (32) ± 6 (18)% occur for OMPS‐NPP (N20). In high concentrations, negative biases of −15% ± 6% appear for OMPS‐NPP, but OMPS‐N20 products have a smaller bias of 0.5% ± 6% due to its smaller ground pixel footprints. This implies that smaller satellite footprint sizes are important in distinguishing small‐scale plumes. In addition, we provide a lower limit for the monthly uncertainty of OMPS‐NPP/N20 formaldehyde products. Key Points: Monthly mean OMPS‐NPP/N20 HCHO products have good agreement with Fourier‐Transform Infrared observations, showing correlation coefficients of 0.83 and 0.88The smaller pixel sizes of OMPS‐N20 as compared with OMPS‐NPP can help detect pollution sources on small scalesThe relative uncertainty of OMPS‐NPP (N20) HCHO monthly means is 31 (18)% with a bias of −15% ± 4% (0.5% ± 6%) in high HCHO vertical column densities [ABSTRACT FROM AUTHOR]

Landfast ice (LFI) plays a crucial role for both the climate and the ecosystem of the Antarctic coastal regions. We investigate the snow and LFI mass balance in Prydz Bay using observations from 11 sea ice mass balance buoys (IMBs). The buoys were deployed offshore from the Chinese Zhongshan Station (ZS) and Australian Davis Station (DS), with the measurements covering the ice seasons of 2009–2010, 2013–2016, and 2018. The observed annual maximum ice thickness and snow depth were 1.59 ± 0.17 and 0.11–0.76 m off ZS and 1.64 ± 0.08 and 0.11–0.38 m off DS, respectively. Early in the ice growth season (May–September), the LFI basal growth rate near DS (0.6 ± 0.2 cmd-1) was larger than that around ZS (0.5 ± 0.2 cmd-1). This is attributed to cooler air temperature (AT) and lower oceanic heat flux at that time in the DS region. Air temperature anomalies were more important in regulating the LFI growth rate at that time because of thinner sea ice having a weaker thermal inertia relative to thick ice in later seasons. Interannual and local spatial variabilities for the seasonality of LFI mass balance identified at ZS are larger than at DS due to local differences in topography and katabatic wind regime. Snow ice contributed up to 27 % of the LFI total ice thickness at the offshore site close to ground icebergs off ZS because of the substantial snow accumulation. Offshore from ZS, the supercooled water was observed at the sites close to the Dålk Glacier from July to October, which reduced the oceanic heat flux and promoted the LFI growth. During late austral spring and summer, the increased oceanic heat flux led to a reduction of LFI growth at all investigated sites. The variability of LFI properties across the study domain prevailed at interannual timescales, over any trend during the recent decades. Based on the results derived from this study, we argue that an increased understanding of snow (on LFI) processes, local atmospheric and oceanic conditions, as well as coastal morphology and bathymetry, are required to improve the Antarctic LFI modeling. [ABSTRACT FROM AUTHOR]

We report on airborne limb and nadir measurements of vertical profiles and total vertical column densities (VCDs) of glyoxal (C2H2O2) in the troposphere, which were performed aboard the German research aircraft HALO (High Altitude and LOng Range) in different regions and seasons around the globe between 2014 and 2019. The airborne nadir and integrated limb profiles agree excellently among each other. Our airborne observations are further compared to collocated glyoxal measurements of the TROPOspheric Monitoring Instrument (TROPOMI), with good agreement between both data sets for glyoxal observations in (1) pristine terrestrial, (2) pristine marine, (3) mixed polluted, and (4) biomass-burning-affected air masses with high glyoxal concentrations. Exceptions to the overall good agreement are observations of (1) faint and aged biomass burning plumes over the oceans and (2) of low-lying biomass burning or anthropogenic plumes in the terrestrial or marine boundary layer, both of which contain elevated glyoxal that is mostly not captured by TROPOMI. These differences in airborne and satellite-detected glyoxal are most likely caused by the overall small contribution of plumes of a limited extent to the total glyoxal absorption in the atmosphere and the difficulty in remotely detecting weak absorbers located close to low reflective surfaces (e.g. the ocean in the visible wavelength range) or within dense aerosol layers. Observations of glyoxal in aged biomass burning plumes (e.g. observed over the tropical Atlantic off the coast of West Africa in summer 2018, off the coast of Brazil by the end of the dry season 2019, and the East China Sea in spring 2018) could be traced back to related wildfires, such as a plume crossing over the Drake Passage that originated from the Australian bushfires in late 2019. Our observations of glyoxal in such aged biomass burning plumes confirm recent findings of enhanced glyoxal and presumably secondary organic aerosol (SOA) formation in aged wildfire plumes from yet-to-be-identified, longer-lived organic precursor molecules (e.g. aromatics, acetylene, or aliphatic compounds) co-emitted in the fires. Furthermore, elevated glyoxal (median 44 ppt – parts per trillion), as compared to other marine regions (median 10–19 ppt), is observed in the boundary layer over the tropical oceans, which is well in agreement with previous reports. The airborne data sets are further compared to glyoxal simulations performed with the global atmosphere chemistry model EMAC (ECHAM/MESSy Atmospheric Chemistry). When using an EMAC set up that resembles recent EMAC studies focusing on complex chemistry, reasonable agreement is found for pristine air masses (e.g. the unperturbed free and upper troposphere), but a notable glyoxal overestimation of the model exists for regions with high emissions of glyoxal and glyoxal-producing volatile organic compounds (VOCs) from the biosphere (e.g. the Amazon). In all other investigated regions, the model underpredicts glyoxal to varying degrees, in particular when probing mixed emissions from anthropogenic activities (e.g. over continental Europe, the Mediterranean, and East China Sea) and potentially from the sea (e.g. the tropical oceans). Also, the model tends to largely underpredict glyoxal in city plumes and aged biomass burning plumes. The potential causes for these differences are likely to be multifaceted, but they all point to missing glyoxal sources from the degradation of the mixture of potentially longer-chained organic compounds emitted from anthropogenic activities, biomass burning, and from the organic microlayer of the sea surface. [ABSTRACT FROM AUTHOR]

We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite. Atmospheric glyoxal results from the oxidation of other non-methane volatile organic compounds (NMVOCs) and from direct emissions caused by combustion processes. Therefore, this product is a useful indicator of VOC emissions. It is generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the differential optical absorption spectroscopy (DOAS) approach. Among the algorithmic updates, the DOAS fit now includes corrections to mitigate the impact of spectral misfits caused by scene brightness inhomogeneity and strong NO 2 absorption. The product comes along with a full error characterization, which allows for providing random and systematic error estimates for every observation. Systematic errors are typically in the range of 1 ×1014 –3 ×1014 molec. cm -2 (∼30% – 70% in emission regimes) and originate mostly from a priori data uncertainties and spectral interferences with other absorbing species. The latter may be at the origin, at least partly, of an enhanced glyoxal signal over equatorial oceans, and further investigation is needed to mitigate them. Random errors are large (>6×1014 molec. cm -2) but can be reduced by averaging observations in space and/or time. Benefiting from a high signal-to-noise ratio and a large number of small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of detail. Using the same retrieval algorithmic baseline, glyoxal column data sets are also generated from the Ozone Monitoring Instrument (OMI) on Aura and from the Global Ozone Monitoring Experiment-2 (GOME-2) on board Metop-A and Metop-B. Those four data sets are intercompared over large-scale regions worldwide and show a high level of consistency. The satellite glyoxal columns are also compared to glyoxal columns retrieved from ground-based Multi-AXis DOAS (MAX-DOAS) instruments at nine stations in Asia and Europe. In general, the satellite and MAX-DOAS instruments provide consistent glyoxal columns both in terms of absolute values and vari ability. Correlation coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where satellite data appear to be biased low during wintertime. The mean absolute glyoxal columns from satellite and MAX-DOAS generally agree well for low/moderate columns with differences of less than 1×1014 molec. cm -2. A larger bias is identified at two sites where the MAX-DOAS columns are very large. Despite this systematic bias, the consistency of the satellite and MAX-DOAS glyoxal seasonal variability is high. [ABSTRACT FROM AUTHOR]

Landfast sea ice (fast ice) is an important though poorly understood component of the cryosphere on the Antarctic continental shelf, where it plays a key role in atmosphere–ocean–ice-sheet interaction and coupled ecological and biogeochemical processes. Here, we present a first in-depth baseline analysis of variability and change in circum-Antarctic fast-ice distribution (including its relationship to bathymetry), based on a new high-resolution satellite-derived time series for the period 2000 to 2018. This reveals (a) an overall trend of -882±824 km 2 yr -1 (-0.19±0.18 % yr -1) and (b) eight distinct regions in terms of fast-ice coverage and modes of formation. Of these, four exhibit positive trends over the 18-year period and four negative. Positive trends are seen in East Antarctica and in the Bellingshausen Sea, with this region claiming the largest positive trend of +1198±359 km 2 yr -1 (+1.10±0.35 % yr -1). The four negative trends predominantly occur in West Antarctica, with the largest negative trend of -1206±277 km 2 yr -1 (-1.78±0.41 % yr -1) occurring in the Victoria and Oates Land region in the western Ross Sea. All trends are significant. This new baseline analysis represents a significant advance in our knowledge of the current state of both the global cryosphere and the complex Antarctic coastal system, which are vulnerable to climate variability and change. It will also inform a wide range of other studies. [ABSTRACT FROM AUTHOR]

Species extinction risk is accelerating due to anthropogenic climate change, making it urgent to protect vulnerable species through legal frameworks in order to facilitate conservation actions that help mitigate risk. Here, we discuss fundamental concepts for assessing climate change risks to species using the example of the emperor penguin (Aptenodytes forsteri), currently being considered for protection under the US Endangered Species Act (ESA). This species forms colonies on Antarctic sea ice, which is projected to significantly decline due to ongoing greenhouse gas (GHG) emissions. We project the dynamics of all known emperor penguin colonies under different GHG emission scenarios using a climate‐dependent meta‐population model including the effects of extreme climate events based on the observational satellite record of colonies. Assessments for listing species under the ESA require information about how species resiliency, redundancy and representation (3Rs) will be affected by threats within the foreseeable future. Our results show that if sea ice declines at the rate projected by climate models under current energy system trends and policies, the 3Rs would be dramatically reduced and almost all colonies would become quasi‐extinct by 2100. We conclude that the species should be listed as threatened under the ESA. [ABSTRACT FROM AUTHOR]

The outflow of supercooled Ice Shelf Water from the conjoined Ross and McMurdo ice shelf cavity augments fast ice thickness and forms a thick sub-ice platelet layer in McMurdo Sound. Here, we investigate whether the CryoSat-2 satellite radar altimeter can consistently detect the higher freeboard caused by the thicker fast ice combined with the buoyant forcing of a sub-ice platelet layer beneath. Freeboards obtained from CryoSat-2 were compared with 4 years of drill-hole-measured sea ice freeboard, snow depth, and sea ice and sub-ice platelet layer thicknesses in McMurdo Sound in November 2011, 2013, 2017 and 2018. The spatial distribution of higher CryoSat-2 freeboard concurred with the distributions of thicker ice-shelf-influenced fast ice and the sub-ice platelet layer. The mean CryoSat-2 freeboard was 0.07–0.09 m higher over the main path of supercooled Ice Shelf Water outflow, in the centre of the sound, relative to the west and east. In this central region, the mean CryoSat-2-derived ice thickness was 35 % larger than the mean drill-hole-measured fast ice thickness. We attribute this overestimate in satellite-altimeter-obtained ice thickness to the additional buoyant forcing of the sub-ice platelet layer which had a mean thickness of 3.90 m in the centre. We demonstrate the capability of CryoSat-2 to detect higher Ice Shelf Water-influenced fast ice freeboard in McMurdo Sound. Further development of this method could provide a tool to identify regions of ice-shelf-influenced fast ice elsewhere on the Antarctic coastline with adequate information on the snow layer. [ABSTRACT FROM AUTHOR]

Climate change and global warming strongly impact the cryosphere. The rise of air temperature and change of precipitation patterns lead to dramatic responses of snow and ice heat and mass balance. Sustainable field observations on lake air–snow–ice–water temperature regime have been carried out in Lake Orajärvi in the vicinity of the Finnish Space Centre, a Flagship Supersite in Sodankylä in Finnish Lapland since 2009. A thermistor-string-based snow and ice mass balance buoy called "Snow and ice mass balance apparatus (SIMBA)" was deployed in the lake at the beginning of each ice season. In this paper, we describe snow and ice temperature regimes, snow depth, ice thickness, and ice compositions retrieved from SIMBA observations as well as meteorological variables based on high-quality observations at the Finnish Space Centre. Ice thickness in Lake Orajärvi showed an increasing trend. During the decade of data collection (1) the November–May mean air temperature had an increasing trend of 0.16 ∘ C per year, and the interannual variations were highly correlated (r = 0.93) with the total seasonal accumulated precipitation; (2) the maximum granular ice thickness ranged from 15 % to 80 % of the maximum total ice thickness; and (3) the snow depth on lake ice was not correlated (r = 0.21) with the total precipitation. The data set can be applied to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and to improve the parameterization of snow to ice transformation in snow and ice models. The data are archived at 10.5281/zenodo.4559368 (Cheng et al., 2021). [ABSTRACT FROM AUTHOR]

Since May 2017 and August 2018, two ground-based MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments have been continuously recording daytime spectral UV–visible measurements in the northwest (University of Natural Resources and Life Sciences (BOKU) site) and south (Arsenal site), respectively, of the Vienna city center (Austria). In this study, vertical aerosol extinction (AE) profiles, aerosol optical depth (AOD), and near-surface AE are retrieved from MAX-DOAS measurements recorded on cloud-free days applying the Bremen Optimal estimation REtrieval for Aerosols and trace gaseS (BOREAS) algorithm. Measurements of atmospheric profiles of pressure and temperature obtained from routinely performed sonde ascents are used to calculate box-air-mass factors and weighting functions for different seasons. The performance of BOREAS was evaluated against co-located ceilometer, sun photometer, and in situ instrument observations covering all four seasons. The results show that the vertical AE profiles retrieved from the BOKU UV–visible MAX-DOAS observations are in very good agreement with data from the co-located ceilometer, reaching correlation coefficients (R) of 0.936–0.996 (UV) and 0.918–0.999 (visible) during the fall, winter, and spring seasons. Moreover, AE extracted using the lowest part of MAX-DOAS vertical profiles (up to 100 m above ground) is highly consistent with near-surface ceilometer AE (R>0.865 and linear regression slopes of 0.815–1.21) during the fall, winter, and spring seasons. A strong correlation is also found for the BOREAS-based AODs when compared to the AERONET ones. Notably, the highest correlation coefficients (R=0.953 and R=0.939 for UV and visible, respectively) were identified for the fall season. While high correlation coefficients are generally found for the fall, winter, and spring seasons, the results are less reliable for measurements taken during summer. For the first time, the spatial variability of AOD and near-surface AE over the urban environment of Vienna is assessed by analyzing the retrieved and evaluated BOREAS aerosol profiling products in terms of different azimuth angles of the two MAX-DOAS instruments and for different seasons. We found that the relative differences of averaged AOD between different azimuth angles are 7–13 % , depending on the season. Larger relative differences of up to 32 % are found for near-surface AE in the different azimuthal directions. This study revealed the strong capability of BOREAS to retrieve AE profiles, AOD, and near-surface AE over urban environments and demonstrated its use for identifying the spatial variability of aerosols in addition to the temporal variation. [ABSTRACT FROM AUTHOR]

The sub‐ice platelet layer (SIPL) is a highly porous, isothermal, friable layer of ice crystals and saltwater, that can develop to several meters in thickness under consolidated sea ice near Antarctic ice shelves. While the SIPL has been comprehensively described, details of its physics are rather poorly understood. In this contribution we describe the halo‐thermodynamic mechanisms driving the development and stability of the SIPL in mushy‐layer sea ice model simulations, forced by thermal atmospheric and oceanic conditions in McMurdo Sound, Ross Sea, Antarctica. The novelty of these simulations is that they predict a realistic model analogue for the SIPL. Two aspects of the model are essential: (a) a large initial brine fraction is imposed on newly forming ice, and (b) brine rejection via advective desalination. The SIPL appears once conductive heat fluxes become insufficient to remove latent heat required to freeze the highly porous new ice. Favorable conditions for SIPL formation include cold air, supercooled waters, and consolidated ice and snow that are thick enough to provide sufficient thermal insulation. Thermohaline properties resulting from large liquid fractions stabilize the SIPL, in particular a low thermal diffusivity. Intense convection within the isothermal SIPL generates the SIPL‐consolidated ice contrast without transporting heat. Using standard physical constants and free parameters, the model successfully predicts the SIPL and consolidated ice thicknesses at six locations. While most simulations were performed with 50 layers, an SIPL emerged with moderate accuracy in thickness for three layers proving a low‐cost representation of the SIPL in large‐scale climate models. Plain Language Summary: The sub‐ice platelet layer (SIPL) is a typical feature beneath sea ice near the Antarctic coast. The SIPL, made of ∼10 cm‐large ice crystals bathed in salt water, can be several meters thick and harbor exceptionally prolific micro‐algae. Much of coastal Antarctica is occupied by massive glaciers that float upon the ocean. We know that meltwater, released by glacial melting at depth, rises and refreezes on its ascent, sourcing ice to the SIPL. Yet many aspects of the growth and decay of an SIPL are poorly understood. Here, we present the first realistic simulations of the SIPL phenomenon near McMurdo Sound, Antarctica, based on a computer model encapsulating state‐of‐the‐art sea ice physics. The simulations inform us of features within the SIPL that are difficult to observe directly and help us understand why the SIPL is common, thick, and long‐lasting. In our simulations, the large volume of saltwater bathing the SIPL crystals buffers heat transfer and favors salt transfer, stabilizing the SIPL and generating a contrast with the consolidated sea ice above the SIPL. We also suggest a method of achieving an SIPL in climate models, which will help define its role in polar climate and ecology. Key Points: A realistic sub‐ice platelet layer (SIPL) emerges in a one‐dimensional thermodynamic sea ice model when suitably forcedKey influences are heat loss to water column, thermal insulation by ice and snow, and brine convection between platelet crystalsThe SIPL is stabilized by its high liquid content and isothermal character [ABSTRACT FROM AUTHOR]

This paper evaluates the ability of 35 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to simulate Arctic sea ice by comparing simulated results with observation from the aspects of spatial patterns and temporal variation. The simulation ability of each model is also quantified by the Taylor score and e score from these two aspects. Results show that biases between observed and simulated Arctic sea ice concentration (SIC) are mainly located in the East Greenland, Barents, and Bering Seas and the Sea of Okhotsk. The largest difference between the observed and simulated SIC spatial patterns occurs in September. Since the beginning of the twenty-first century, the ability of most models to simulate summer SIC spatial patterns has decreased. We also find that models with the Sea Ice Simulator (SIS) sea ice component in CMIP6 show a consistent larger positive simulation biases of SIC in the East Greenland and Barents Seas. In addition, for most models, the higher the model resolution is, the better the match between the simulated and observed spatial patterns of winter Arctic SIC is. Furthermore, this paper makes a detailed assessment for temporal variation of Arctic sea ice extent (SIE) with regard to climatological average, seasonal SIE, multiyear linear trend, and detrended standard deviation of SIE. The sensitivity of September Arctic SIE to a given change of Arctic surface air temperature over 1979–2014 in each model has also been investigated. Most models simulate a smaller loss of September Arctic SIE per degree of warming than is observed (1.37 × 106 km2 K−1). [ABSTRACT FROM AUTHOR]

Basal melting of ice shelves can result in the outflow of supercooled ice shelf water, which can lead to the formation of a sub-ice platelet layer (SIPL) below adjacent sea ice. McMurdo Sound, located in the southern Ross Sea, Antarctica, is well known for the occurrence of a SIPL linked to ice shelf water outflow from under the McMurdo Ice Shelf. Airborne, single-frequency, frequency-domain electromagnetic induction (AEM) surveys were performed in November of 2009, 2011, 2013, 2016, and 2017 to map the thickness and spatial distribution of the landfast sea ice and underlying porous SIPL. We developed a simple method to retrieve the thickness of the consolidated ice and SIPL from the EM in-phase and quadrature components, supported by EM forward modelling and calibrated and validated by drill-hole measurements. Linear regression of EM in-phase measurements of apparent SIPL thickness and drill-hole measurements of "true" SIPL thickness yields a scaling factor of 0.3 to 0.4 and rms error of 0.47 m. EM forward modelling suggests that this corresponds to SIPL conductivities between 900 and 1800 mSm-1 , with associated SIPL solid fractions between 0.09 and 0.47. The AEM surveys showed the spatial distribution and thickness of the SIPL well, with SIPL thicknesses of up to 8 m near the ice shelf front. They indicate interannual SIPL thickness variability of up to 2 m. In addition, they reveal high-resolution spatial information about the small-scale SIPL thickness variability and indicate the presence of persistent peaks in SIPL thickness that may be linked to the geometry of the outflow from under the ice shelf. [ABSTRACT FROM AUTHOR]

The radiative transfer of shortwave solar radiation through the sea ice cover of the polar oceans is a crucial aspect of energy partitioning at the atmosphere–ice–ocean interface. A detailed understanding of how sunlight is reflected and transmitted by the sea ice cover is needed for an accurate representation of critical processes in climate and ecosystem models, such as the ice–albedo feedback. Due to the challenges associated with ice internal measurements, most information about radiative transfer in sea ice has been gained by optical measurements above and below the sea ice. To improve our understanding of radiative transfer processes within the ice itself, we developed a new kind of instrument equipped with a number of multispectral light sensors that can be frozen into the ice. A first prototype consisting of a 2.3 m long chain of 48 sideward planar irradiance sensors with a vertical spacing of 0.05 m was deployed at the geographic North Pole in late August 2018, providing autonomous, vertically resolved light measurements within the ice cover during the autumn season. Here we present the first results of this instrument, discuss the advantages and application of the prototype, and provide first new insights into the spatiotemporal aspect of radiative transfer within the sea ice itself. In particular, we investigate how measured attenuation coefficients relate to the optical properties of the ice pack and show that sideward planar irradiance measurements are equivalent to measurements of total scalar irradiance. [ABSTRACT FROM AUTHOR]

Formaldehyde (HCHO) total column densities over the Mexico City metropolitan area (MCMA) were retrieved using two independent measurement techniques: multi-axis differential optical absorption spectroscopy (MAX-DOAS) and Fourier transform infrared (FTIR) spectroscopy. For the MAX-DOAS measurements, the software QDOAS was used to calculate differential slant column densities (dSCDs) from the measured spectra and subsequently the Mexican MAX-DOAS fit (MMF) retrieval code to convert from dSCDs to vertical column densities (VCDs). The direct solar-absorption spectra measured with FTIR were analyzed using the PROFFIT (PROFile FIT) retrieval code. Typically the MAX-DOAS instrument reports higher VCDs than those measured with FTIR, in part due to differences found in the ground-level sensitivities as revealed from the retrieval diagnostics from both instruments, as the FTIR and the MAX-DOAS information do not refer exactly to the same altitudes of the atmosphere. Three MAX-DOAS datasets using measurements conducted towards the east, west or both sides of the measurement plane were evaluated with respect to the FTIR results. The retrieved MAX-DOAS HCHO VCDs where 6 % , 8 % and 28 % larger than the FTIR measurements which, supported with satellite data, indicates a large horizontal inhomogeneity in the HCHO abundances. The temporal change in the vertical distribution of this pollutant, guided by the evolution of the mixing-layer height, affects the comparison of the two retrievals with different sensitivities (total column averaging kernels). In addition to the reported seasonal and diurnal variability of HCHO columns within the urban site, background data from measurements at a high-altitude station, located only 60 km away, are presented. [ABSTRACT FROM AUTHOR]

Airborne and ground-based Pandora spectrometer NO 2 column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO 2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO 2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2= 0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2=0.96) than Pandora measurements are with TROPOMI (r2=0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5 ∘) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4 %–11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19 %–33 % during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model–Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12 %–14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7 %–19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets. [ABSTRACT FROM AUTHOR]

Landfast sea ice (fast ice) attached to Antarctic (near-)coastal elements is a critical component of the local physical and ecological systems. Through its direct coupling with the atmosphere and ocean, fast-ice properties are also a potential indicator of processes related to a changing climate. However, in situ fast-ice observations in Antarctica are extremely sparse because of logistical challenges and harsh environmental conditions. Since 2010, a monitoring program observing the seasonal evolution of fast ice in Atka Bay has been conducted as part of the Antarctic Fast Ice Network (AFIN). The bay is located on the northeastern edge of Ekström Ice Shelf in the eastern Weddell Sea, close to the German wintering station Neumayer III. A number of sampling sites have been regularly revisited each year between annual ice formation and breakup to obtain a continuous record of sea-ice and sub-ice platelet-layer thickness, as well as snow depth and freeboard across the bay. Here, we present the time series of these measurements over the last 9 years. Combining them with observations from the nearby Neumayer III meteorological observatory as well as auxiliary satellite images enables us to relate the seasonal and interannual fast-ice cycle to the factors that influence their evolution. On average, the annual consolidated fast-ice thickness at the end of the growth season is about 2 m, with a loose platelet layer of 4 m thickness beneath and 0.70 m thick snow on top. Results highlight the predominately seasonal character of the fast-ice regime in Atka Bay without a significant interannual trend in any of the observed variables over the 9-year observation period. Also, no changes are evident when comparing with sporadic measurements in the 1980s and 1990s. It is shown that strong easterly winds in the area govern the year-round snow distribution and also trigger the breakup of fast ice in the bay during summer months. Due to the substantial snow accumulation on the fast ice, a characteristic feature is frequent negative freeboard, associated flooding of the snow–ice interface, and a likely subsequent snow ice formation. The buoyant platelet layer beneath negates the snow weight to some extent, but snow thermodynamics is identified as the main driver of the energy and mass budgets for the fast-ice cover in Atka Bay. The new knowledge of the seasonal and interannual variability of fast-ice properties from the present study helps to improve our understanding of interactions between atmosphere, fast ice, ocean, and ice shelves in one of the key regions of Antarctica and calls for intensified multidisciplinary studies in this region. [ABSTRACT FROM AUTHOR]

The results of Russian studies of climate and its changes (published in 2015–2018) are presented using a review prepared for the National Report on Meteorology and Atmospheric Sciences submitted to the 27th General Assembly of the International Union of Geodesy and Geophysics (Montreal, Canada, July 8–18, 2019). [ABSTRACT FROM AUTHOR]

Tropospheric NO2 and stratospheric NO2 vertical column densities are important TROPOspheric Monitoring Instrument (TROPOMI) data products. In order to validate the TROPOMI NO2 products, KNMI Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments have measured NO2 on ship cruises over the Atlantic and the Pacific oceans. The MAX-DOAS instruments have participated in five cruises on board RV Sonne (in 2017 and 2019) and RV Maria S. Merian (in 2018). The MAX-DOAS measurements were acquired over 7 months and spanned about 90 ∘ in latitude and 300 ∘ in longitude. During the cruises aerosol measurements from Microtops sun photometers were also taken. The MAX-DOAS measured stratospheric NO2 columns between 1.5×1015 and 3.5×1015 moleccm-2 and tropospheric NO2 up to 0.6×1015 moleccm-2. The MAX-DOAS stratospheric NO2 vertical column densities have been compared with TROPOMI stratospheric NO2 vertical column densities and the stratospheric NO2 vertical column densities simulated by the global chemistry Transport Model, version 5, Massively Parallel model (TM5-MP). Good correlation is found between the MAX-DOAS and TROPOMI and TM5 stratospheric NO2 vertical column densities, with a correlation coefficient of 0.93 or larger. The TROPOMI and TM5 stratospheric NO2 vertical column densities are about 0.4×1015 moleccm-2 (19 %) higher than the MAX-DOAS measurements. The TROPOMI tropospheric NO2 also has good agreement with the MAX-DOAS measurements. The tropospheric NO2 vertical column density is as low as 0.5×1015 moleccm-2 over remote oceans. [ABSTRACT FROM AUTHOR]

Variability in the volume of supercooled Ice Shelf Water outflow in McMurdo Sound is reflected in the thickness and distribution of fast ice and the sub‐ice platelet layer beneath. Ground‐based electromagnetic induction and drill hole surveys of the distribution and thickness of ice shelf‐influenced fast ice and the sub‐ice platelet layer in McMurdo Sound were carried out in late spring of 2011, 2013, 2016, and 2017. In 2011 and 2017, thicker sub‐ice platelet layers of up to 7.5 and 6 m were observed, respectively. Fast ice formation throughout the winters of 2011 and 2017 was influenced by a higher occurrence of strong southerly wind events and resultant activity of the Ross Sea Polynya. In contrast, lower wind conditions in 2016 led to largely undisturbed sea ice growth and anomalously extensive fast ice coverage. A thinner sub‐ice platelet layer of up to 4 m was observed in 2016. In 2011 and 2017, substantial and variable sub‐ice platelet layers were detected in a region of exchange of water masses between the Ross Sea and the McMurdo‐Ross ice shelf cavity, which were not observed in 2013 and 2016. We hypothesize that a higher frequency of strong southerly wind events, resultant polynya activity, and High Salinity Shelf Water production over winter accelerates circulation and increases melting in the proximal shallow McMurdo Ice Shelf and the deeper Ross Ice Shelf regions of the conjoined cavity. The outflow of supercooled Ice Shelf Water and sub‐ice platelet layer formation in McMurdo Sound are consequently promoted. Plain Language Summary: Ocean‐driven basal melting of ice shelves forms cold and fresh Ice Shelf Water (ISW) which can crystallize into platelet ice. Sea ice growth near an ice shelf is enhanced as the upper ocean is cooled and stabilized by ISW or by freezing of platelet ice into the sea ice. An unconsolidated mass of platelet ice called a sub‐ice platelet layer (SPL) can form beneath. To investigate variability in the influence of ISW, we measured sea ice and SPL thicknesses near McMurdo Ice Shelf in the Ross Sea, Antarctica with drill hole and geophysical surveys. Thicker SPLs were observed in years subject to a higher occurrence of strong offshore winds over winter as the sea ice was forming. Strong winds blow sea ice offshore and form regions of open water called polynyas. New ice is produced intensively within polynyas and the rejected salts form a very dense and saline water mass called High Salinity Shelf Water which can circulate into ice shelf cavities and drive basal melting and ISW formation at depth. We hypothesize that a higher occurrence of strong offshore winds results in more polynya activity, High Salinity Shelf Water production, and ISW formation which outflows into McMurdo Sound producing thicker SPLs. Key Points: Ice shelf‐influenced sea ice and the sub‐ice platelet layer were assessed with electromagnetic induction and drill hole thickness surveysThe sub‐ice platelet layer was thicker in years with more strong southerly wind events and polynya activity over winterIce Shelf Water outflow and sub‐ice platelet layer thickness in McMurdo Sound are connected to polynya‐driven HSSW circulation over winter [ABSTRACT FROM AUTHOR]

Glyoxal (CHOCHO) and formaldehyde (HCHO) are intermediate products in the tropospheric oxidation of the majority of volatile organic compounds (VOCs). CHOCHO is also a precursor of secondary organic aerosol (SOA) in the atmosphere. CHOCHO and HCHO are released from biogenic, anthropogenic, and pyrogenic sources. CHOCHO and HCHO tropospheric lifetimes are typically considered to be short during the daytime at mid-latitudes (e.g. several hours), as they are rapidly removed from the atmosphere by their photolysis, oxidation by OH, and uptake on particles or deposition. At night and at high latitudes, tropospheric lifetimes increase to many hours or even days. Previous studies demonstrated that CHOCHO and HCHO vertical column densities (VCDs) are well retrieved from space-borne observations using differential optical absorption spectroscopy (DOAS). In this study, we present CHOCHO and HCHO VCDs retrieved from measurements by TROPOMI (TROPOspheric Monitoring Instrument), launched on the Sentinel-5 Precursor (S5P) platform in October 2017. We observe strongly elevated amounts of CHOCHO and HCHO during the 2018 fire season in British Columbia, Canada, where a large number of fires occurred in August. CHOCHO and HCHO plumes from individual fire hot spots are observed in air masses travelling over distances of up to 1500 km , i.e. much longer than expected for the relatively short tropospheric lifetime expected for CHOCHO and HCHO. Comparison with simulations by the particle dispersion model FLEXPART (FLEXible PARTicle dispersion model) indicates that effective lifetimes of 20 h and more are needed to explain the observations of CHOCHO and HCHO if they decay in an effective first-order process. FLEXPART used in the study calculates accurately the transport. In addition an exponential decay, in our case assumed to be photochemical, of a species along the trajectory is added. We have used this simple approach to test our assumption that CHOCHO and HCHO are created in the fires and then decay at a constant rate in the plume as it is transported. This is clearly not the case and we infer that CHOCHO and HCHO are either efficiently recycled during transport or continuously formed from the oxidation of longer-lived precursors present in the plume, or possibly a mixture of both. We consider the best explanation of the observed CHOCHO and HCHO VCD in the plumes of the fire is that they are produced by oxidation of longer-lived precursors, which were also released by the fire and present in the plume. [ABSTRACT FROM AUTHOR]

An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parameterisation over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS (CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a clouds-as-layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current clouds-as-reflecting-boundaries (CRB) model, which assumes that the clouds are Lambertian reflectors. On average, improvements in the AMF calculation affect the tropospheric NO2 columns by ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and the aerosol-induced cloud parameters (implicit aerosol correction). Compared with the implicit aerosol correction utilising the CRB cloud parameters, the use of the CAL approach reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based multi-axis differential optical absorption spectroscopy (MAXDOAS) measurements at different BIRA-IASB stations. At the suburban Xianghe station, the improved tropospheric NO2 dataset shows better agreement with coincident ground-based measurements with a correlation coefficient of 0.94. [ABSTRACT FROM AUTHOR]

The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic models almost consistently reproduced a decreasing trend of sea ice cover, the reported results show a large distribution. To evaluate the performance of models for simulating Arctic sea ice cover and its potential role in climate change, this study constructed a reasonable metric by synthesizing both linear trends and anomalies of sea ice. This study particularly focused on the Barents Sea and the Kara Sea, where sea ice anomalies have the highest potential to affect the atmosphere. The investigated models can be grouped into three categories according to their normalized skill scores. The strong contrast among the multi-model ensemble means of different groups demonstrates the robustness and rationality of this method. Potential factors that account for the different performances of climate models are further explored. The results show that model performance depends more on the ozone datasets that are prescribed by the model rather than on the chemical representation of ozone. [ABSTRACT FROM AUTHOR]

Trace gas maps retrieved from satellite measurements show enhanced levels of the atmospheric volatile organic compounds formaldehyde (HCHO) and glyoxal (CHOCHO) over the Atlantic Ocean. To validate the spatial distribution of this continental outflow, ship-based measurements were taken during the Continental Outflow of Pollutants towards the MArine tRoposphere (COPMAR) project. A Multi-AXis Differential Optical Absorption Spectrometer (MAX-DOAS) was operated aboard the research vessel (RV) Maria S. Merian during cruise MSM58/2. This cruise was conducted in October 2016 from Ponta Delgada (Azores) to Cape Town (South Africa), crossing between Cabo Verde and the African continent. The instrument was continuously scanning the horizon, looking towards the African continent. Enhanced levels of HCHO and CHOCHO were found in the area of expected outflow during this cruise. The observed spatial gradients of HCHO and CHOCHO along the cruise track agree with the spatial distributions from satellite measurements and the Model for OZone and Related chemical Tracers version 4 (MOZART-4) model simulations. The continental outflow from the African continent is observed in an elevated layer, higher than 1000 m, and probably originates from biogenic emissions or biomass burning according to FLEXible PARTicle dispersion model (FLEXPART) emission sensitivities. [ABSTRACT FROM AUTHOR]

The paper discusses modelling uncertainties in climate models and how they can be addressed based on physical principles as well as based on how the models perform in light of empirical data. We argue that the reliability of climate models can be judged by three kinds of standards: striking confirmation, supplementing independent causal arguments, and judging the causal core of models by establishing model robustness. We also use model robustness for delimiting confirmational holism. We survey recent results of climate modelling and identify salient results that fulfil each of the three standards. Our conclusion is that climate models can be considered reliable for some qualitative gross features and some long-term tendencies of the climate system as well as for quantitative aspects of some smaller-scale mechanisms. The adequacy of climate models for other purposes is less convincing. Among the latter are probability estimates, in particular, those concerning rare events. On the whole, climate models suffer from important deficits and are difficult to verify, but are still better confirmed and more reliable than parts of the methodological literature suggest. [ABSTRACT FROM AUTHOR]

Abstract: Oceanographic and ice‐mass‐balance records are presented from two moorings deployed on landfast multiyear ice in the Wandel Sea (North Greenland) during June–August 2015. Here we show that the melting and drainage of >1 m of snow from June 14 to July 14 created a double‐diffusive vertical stratification which resulted in supercooling of water and enabled the formation of platelet crystals below the sea ice. Although the effect of supercooling, with temperatures up to 0.5°C below the freezing point, might be overestimated considerably in our records, this process led to the formation of ∼1.1–1.2 m‐thick subice platelet layer. While warm water temperatures lead to the complete loss of this layer at one mooring site, the layer persisted through summer and became incorporated into the congelation ice at the second site. The warm water that melted out the platelet layer can be ascribed to two different sources: (1) in situ heating from solar radiation resulting in a temperature increase up to 0.8°C in late July and (2) advection of warm surface water (with temperatures up to 3–4°C) from the ice‐free coastal regions in mid‐August. The combination of processes causing the seasonal growth of a platelet layer and either its subsequent ablation or incorporation into congelation ice is discussed with respect to the ice‐mass balance and stability of the landfast ice cover in the Wandel Sea. Furthermore, this study provides evidence for the formation of a platelet layer in the Arctic, a phenomenon that historically has only been observed in the Antarctic. [ABSTRACT FROM AUTHOR]

Abstract: Long‐term photographic recordings of animal populations provide unique insights into ecological and evolutionary processes. However, image acquisition at remote locations under harsh climatic conditions is highly challenging. We present a robust, energetically self‐sufficient and remote‐controlled observatory designed to operate year‐round in the Antarctic at temperatures below −50°C and wind speeds above 150 km/h. The observatory is equipped with multiple overview cameras and a high resolution steerable camera with a telephoto lens for capturing images with high spatial and temporal resolution. Our observatory has been in operation since 2013 to investigate an emperor penguin (Aptenodytes forsteri) colony at Atka Bay near the German Neumayer III research station. Data recorded by this observatory give novel biological insights in animal life cycle and demographic trends, but also in collective and individual behaviour. As an example, we present data showing how wind speed and direction influence movements of the entire colony and of individual penguins. We also estimate daily fluctuations in the total number of individuals present at the breeding site. Our results demonstrate that remote‐controlled observation systems can bridge the gap between remote sensing, simple time‐lapse recording setups, and on‐site observations by human investigators to collect unique biological datasets of undisturbed animal populations. [ABSTRACT FROM AUTHOR]