Abstract. This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5 × 5.5 km2. This paper assesses the performances of the TROPOMI formaldehyde (HCHO) operational product compared to its predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favoured the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30 % in tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns (larger than 5 × 1015 molec. cm−2) the median bias between OMI and TROPOMI HCHO columns is not larger than 10 % (< 0.4 × 1015 molec. cm−2). For lower columns, OMI observations present a remaining positive bias of about 20 % (< 0.8 × 1015 molec. cm−2) compared to TROPOMI in midlatitude regions. Here, we also use a global network of 18 MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments to validate both satellite sensors for a large range of HCHO columns. This work complements the study by Vigouroux et al. (2020), where a global FTIR (Fourier transform infrared) network is used to validate the TROPOMI HCHO operational product. Consistent with the FTIR validation study, we find that for elevated HCHO columns, TROPOMI data are systematically low (−25 % for HCHO columns larger than 8 × 1015 molec. cm−2), while no significant bias is found for medium-range column values. We further show that OMI and TROPOMI data present equivalent biases for large HCHO levels. However, TROPOMI significantly improves the precision of the HCHO observations at short temporal scales and for low HCHO columns. We show that compared to OMI, the precision of the TROPOMI HCHO columns is improved by 25 % for individual pixels and by up to a factor of 3 when considering daily averages in 20 km radius circles. The validation precision obtained with daily TROPOMI observations is comparable to the one obtained with monthly OMI observations. To illustrate the improved performances of TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO column enhancements related to shipping emissions in the Indian Ocean. This is achieved by averaging data over a much shorter period (3 months) than required with previous sensors (5 years) and opens new perspectives to study shipping emissions of VOCs (volatile organic compounds) and related atmospheric chemical interactions.

Abstract. Measurements of the OH Meinel emissions in the terrestrial nightglow are one of the standard ground-based techniques to retrieve upper mesospheric temperatures. It is often assumed that the emission peak altitudes are not strongly dependent on the vibrational level, although this assumption is not based on convincing experimental evidence. In this study we use Envisat/SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY) observations in the near-IR spectral range to retrieve vertical volume emission rate profiles of the OH(3-1), OH(6-2) and OH(8-3) Meinel bands in order to investigate whether systematic differences in emission peak altitudes can be observed between the different OH Meinel bands. The results indicate that the emission peak altitudes are different for the different vibrational levels, with bands originating from higher vibrational levels having higher emission peak altitudes. It is shown that this finding is consistent with the majority of the previously published results. The SCIAMACHY observations yield differences in emission peak altitudes of up to about 4 km between the OH(3-1) and the OH(8-3) band.The observations are complemented by model simulations of the fractional population of the different vibrational levels and of the vibrational level dependence of the emission peak altitude. The model simulations reproduce the observed vibrational level dependence of the emission peak altitude well -both qualitatively and quantitatively -if quenching by atomic oxygen as well as multi-quantum collisional relaxation by O 2 is considered. If a linear relationship between emission peak altitude and vibrational level is assumed, then a peak altitude difference of roughly 0.5 km per vibrational level is inferred from both the SCIAMACHY observations and the model simulations.

Measurements of the OH Meinel emissions in the terrestrial nightglow are one of the standard ground-based techniques to retrieve upper mesospheric temperatures. It is often assumed that the emission peak altitudes are not strongly dependent on the vibrational level, although this assumption is not based on convincing experimental evidence. In this study we use Envisat/SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY) observations in the near-IR spectral range to retrieve vertical volume emission rate profiles of the OH(3-1), OH(6-2) and OH(8-3) Meinel bands in order to investigate, whether systematic differences in emission peak altitudes can be observed between the different OH Meinel bands. The results indicate that the emission peak altitudes are different for the different vibrational levels, with bands originating from higher vibrational levels having higher emission peak altitudes. It is shown that this finding is consistent with the majority of the previously published results. The SCIAMACHY observations yield differences in emission peak altitudes of up to about 4 km between the OH(3-1) and the OH(8-3) band.

The observations are complemented by model simulations of the fractional population of the different vibrational levels and of the vibrational level dependence of the emission peak altitude. The model simulations well reproduce the observed vibrational level dependence of the emission peak altitude – both qualitatively and quantitatively – if quenching by atomic oxygen as well as multi-quantum collisional relaxation by O₂ is considered. If a linear relationship between emission peak altitude and vibrational level is assumed, then a peak altitude difference of roughly 0.5 km per vibrational level is inferred from both the SCIAMACHY observations and the model simulations

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