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Ammonia (NH3) is the major alkaline species in the atmosphere and plays an important role in aerosol formation, which affects local air quality and the radiation budget. NH3 in the upper troposphere and lower stratosphere (UTLS) is difficult to detect, and only limited observations are available. We present two-dimensional trace gas measurements of NH3 obtained by the airborne infrared imaging limb sounder GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) that was operated on board the research aircraft Geophysica within the Asian monsoon anticyclone during the StratoClim campaign (July 2017) and on board HALO (the High Altitude and LOng Range research aircraft) above the South Atlantic during the SouthTRAC campaign (September–November 2019). We compare these GLORIA measurements in the UTLS with results of the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis and forecast model to evaluate its performance. The GLORIA observations reveal large enhancements of NH3 of more than 1 ppbv in the Asian monsoon upper troposphere but no clear indication of NH3 in biomass burning plumes in the upper troposphere above the South Atlantic above the instrument's detection limit of around 20 pptv. In contrast, CAMS reanalysis and forecast simulation results indicate strong enhancements of NH3 in both measured scenarios. Comparisons of other retrieved pollution gases, such as peroxyacetyl nitrate (PAN), show the ability of CAMS models to generally reproduce the biomass burning plumes above the South Atlantic. However, NH3 concentrations are largely overestimated by the CAMS models within these plumes. We suggest that emission strengths used by CAMS models are of lower accuracy for biomass burning in comparison to agricultural sources in the Asian monsoon. Further, we suggest that loss processes of NH3 during transport to the upper troposphere may be underestimated for the biomass burning cases above the South Atlantic. Since NH3 is strongly undersampled, in particular at higher altitudes, we hope for regular vertically resolved measurements of NH3 from the proposed CAIRT (Changing-Atmosphere Infra-Red Tomography Explorer) mission to strengthen our understanding of this important trace gas in the atmosphere.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was a limb-viewing infrared Fourier transform spectrometer that operated from 2002 to 2012 aboard the Environmental Satellite (ENVISAT). The final re-processing of the full MIPAS mission Level 2 data was performed with the ESA operational version 8 (v8) processor. This MIPAS dataset includes not only the retrieval results of pressure–temperature and the standard species H2O, O3, HNO3, CH4, N2O, and NO2 but also vertical profiles of volume mixing ratios of the more difficult-to-retrieve molecules N2O5, ClONO2, CFC-11, CFC-12 (included since v6 processing), HCFC-22, CCl4, CF4, COF2, and HCN (included since v7 processing). Finally, vertical profiles of the species C2H2, C2H6, COCl2, OCS, CH3Cl, and HDO were additionally retrieved by the v8 processor. The balloon-borne limb-emission sounder MIPAS-B was a precursor of the MIPAS satellite instrument. Several flights with MIPAS-B were carried out during the 10-year operational phase of ENVISAT at different latitudes and seasons, including both operational periods when MIPAS measured with full spectral resolution (FR mode) and with optimised spectral resolution (OR mode). All MIPAS operational products (except HDO) were compared to results inferred from dedicated validation limb sequences of MIPAS-B. To enhance the statistics of vertical profile comparisons, a trajectory match method has been applied to search for MIPAS coincidences along the 2 d forward and backward trajectories running from the MIPAS-B measurement geolocations. This study gives an overview of the validation results based on the ESA operational v8 data comprising the MIPAS FR and OR observation periods. This includes an assessment of the data agreement of both sensors, taking into account the combined errors of the instruments. The differences between the retrieved temperature profiles of both MIPAS instruments generally stays within ±2 K in the stratosphere. For most gases – namely H2O, O3, HNO3, CH4, N2O, NO2, N2O5, ClONO2, CFC-11, CFC-12, HCFC-22, CCl4, CF4, COF2, and HCN – we find a 5 %–20 % level of agreement for the retrieved vertical profiles of both MIPAS instruments in the lower stratosphere. For the species C2H2, C2H6, COCl2, OCS, and CH3Cl, however, larger differences (within 20 %–50 %) appear in this altitude range.

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an infrared imaging FTS (Fourier transform spectrometer) with a 2-D infrared detector that is operated on two high-flying research aircraft. It has flown on eight campaigns and measured along more than 300 000 km of flight track. This paper details our instrument calibration and characterization efforts, which, in particular, almost exclusively leverage in-flight data. First, we present the framework of our new calibration scheme, which uses information from all three available calibration sources (two blackbodies and upward-pointing “deep space” measurements). Part of this scheme is a new algorithm for correcting the erratically changing nonlinearity of a subset of detector pixels and the identification of the remaining bad pixels. Using this new calibration, we derive a 1σ bound of 1 % on the instrument gain error and a bound of 30 nW cm−2 sr−1 cm on the instrument offset error. We show how we can examine the noise and spectral accuracy for all measured atmospheric spectra and derive a spectral accuracy of 5 ppm on average. All these errors are compliant with the initial instrument requirements. We also discuss, for the first time, the pointing system of the GLORIA instrument. Combining laboratory calibration efforts with the measurement of astronomical bodies during the flight, we can achieve a pointing accuracy of 0.032∘, which corresponds to one detector pixel. The paper concludes with a brief study of how these newly characterized instrument parameters affect temperature and ozone retrievals. We find that the pointing uncertainty and, to a lesser extent, the instrument gain uncertainty are the main contributors to the error in the result.

In this study, we present simultaneous airborne measurements of peroxyacetyl nitrate (PAN), ethane (C2H6), formic acid (HCOOH), methanol (CH3OH), and ethylene (C2H4) above the South Atlantic in September and October 2019. Observations were obtained from the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA), as two-dimensional altitude cross sections along the flight path. The flights were part of the SouthTRAC (Transport and Composition in the Southern Hemisphere Upper Troposphere/Lower Stratosphere) campaign with the German High Altitude and Long Range Research Aircraft (HALO). On two flights (8 September 2019 and 7 October 2019), large enhancements of all these substances were found between 7 and 14 km altitude with maximum volume mixing ratios (VMRs) of 1000 pptv for PAN, 1400 pptv for C2H6, 800 pptv for HCOOH, 4500 pptv for CH3OH, and 200 pptv for C2H4. One flight showed a common filamentary structure in the trace gas distributions, while the second flight is characterized by one large plume. Using backward trajectories, we show that measured pollutants likely reached upper troposphere and lower stratosphere (UTLS) altitudes above South America and central Africa, where elevated PAN VMRs are visible at the surface layer of the Copernicus Atmosphere Monitoring Service (CAMS) model during the weeks before both measurements. In comparison to results of the CAMS reanalysis interpolated onto the GLORIA measurement geolocations, we show that the model is able to reproduce the overall structure of the measured pollution trace gas distributions. For PAN, the absolute VMRs are in agreement with the GLORIA measurements. However, C2H6 and HCOOH are generally underestimated by the model, while CH3OH and C2H4, the species with the shortest atmospheric lifetimes of the pollution trace gases discussed, are overestimated by CAMS. The good agreement between model and observations for PAN suggests that the general transport pathways and emissions locations are well captured by the model. The poorer agreement for other species is therefore most likely linked to model deficiencies in the representation of loss processes and emission strength.

Water vapour and ozone are important for the thermal and radiative balance of the upper troposphere (UT) and lowermost stratosphere (LMS). Both species are modulated by transport processes. Chemical and microphysical processes affect them differently. Thus, representing the different processes and their interactions is a challenging task for dynamical cores, chemical modules and microphysical parameterisations of state-of-the-art atmospheric model components. To test and improve the models, high-resolution measurements of the UT–LMS are required. Here, we use measurements taken in a flight of the GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) instrument on HALO (High Altitude and LOng Range Research Aircraft). The German research aircraft HALO performed a research flight on 26 February 2016 that covered deeply subsided air masses of the aged 2015/16 Arctic vortex, high-latitude LMS air masses, a highly textured region affected by troposphere-to-stratosphere exchange and high-altitude cirrus clouds. Therefore, it provides a challenging multifaceted case study for comparing GLORIA observations with state-of-the-art atmospheric model simulations in a complex UT–LMS region at a late stage of the Arctic winter 2015/16. Using GLORIA observations in this manifold scenario, we test the ability of the numerical weather prediction (NWP) model ICON (ICOsahedral Nonhydrostatic) with the extension ART (Aerosols and Reactive Trace gases) and the chemistry–climate model (CCM) EMAC (ECHAM5/MESSy Atmospheric Chemistry – fifth-generation European Centre Hamburg general circulation model/Modular Earth Submodel System) to model the UT–LMS composition of water vapour (H2O), ozone (O3), nitric acid (HNO3) and clouds. Within the scales resolved by the respective model, we find good overall agreement of both models with GLORIA. The applied high-resolution ICON-ART set-up involving an R2B7 nest (local grid refinement with a horizontal resolution of about 20 km), covering the HALO flight region, reproduces mesoscale dynamical structures well. Narrow moist filaments in the LMS observed by GLORIA at tropopause gradients in the context of a Rossby wave breaking event and in the vicinity of an occluded Icelandic low are clearly reproduced by the model. Using ICON-ART, we show that a larger filament in the west was transported horizontally into the Arctic LMS in connection with a jet stream split associated with poleward breaking of a cyclonically sheared Rossby wave. Further weaker filaments are associated with an older tropopause fold in the east. Given the lower resolution (T106) of the nudged simulation of the EMAC model, we find that this model also reproduces these features well. Overall, trace gas mixing ratios simulated by both models are in a realistic range, and major cloud systems observed by GLORIA are mostly reproduced. However, we find both models to be affected by a well-known systematic moist bias in the LMS. Further biases are diagnosed in the ICON-ART O3, EMAC H2O and EMAC HNO3 distributions. Finally, we use sensitivity simulations to investigate (i) short-term cirrus cloud impacts on the H2O distribution (ICON-ART), (ii) the overall impact of polar winter chemistry and microphysical processing on O3 and HNO3 (ICON-ART and EMAC), (iii) the impact of the model resolution on simulated parameters (EMAC), and (iv) consequences of scavenging processes by cloud particles (EMAC). We find that changing the horizontal model resolution results in notable systematic changes for all species in the LMS, while scavenging processes play a role only in the case of HNO3. We discuss the model biases and deficits found in this case study that potentially affect forecasts and projections (adversely) and provide suggestions for further model improvements.