The direct analysis of atmospheric gravity waves (GWs) in temperature observations is difficult since the much stronger signal of large-scale temperature perturbations such as planetary waves obscure the perturbations due to GWs. The small-scale GW perturbations need to be isolated from the measurements by removing the large-scale temperature background, thereby revealing the object of analysis. In this study, the scale-separation via 2D spectral decomposition, which has the advantage of removing physical wave modes of zonal wavenumber up to 7 and wave frequency up to one cycle per day, is discussed. The technical implementation of this technique in a scale-separation Python-based toolbox, GLOFI (GLObal wave FIt), is detailed and demonstrated on a simulated satellite dataset for the ESA Earth Explorer 11 candidate CAIRT incorporating ECMWF ERA5 temperature data. Planetary wave spectra for the specified wavenumbers and frequencies are obtained by using a 28 d sliding window. These spectra are subsequently used to remove perturbations due to planetary waves from the measurements. This is followed by the removal of tides in a similar way but using a shorter 5 d sliding window and a fit of only stationary waves for ascending and descending orbits separately. For the considered dataset, the variances of the difference between reference and GLOFI-generated temperature background are an order of magnitude smaller than GW temperature variances, which suggests that the method removes the large-scale waves to a degree that enables the separation of the GW perturbations. Furthermore, the obtained spectra can be used to generate a global temperature background grid which approximately resembles the actual global temperature field. More importantly, the temperature background estimated by GLOFI at the satellite track coordinates is almost identical to the actual reference temperatures along the tracks. Regarding the performance on data including GW perturbations, the isolated small-scale temperature perturbations are virtually identical to the actual reference GW perturbations from the model. The GLOFI toolbox for scale separation of satellite observations is published as open access along this article.

The planned deployment of satellite mega-constellations will substantially increase the flux of anthropogenic space debris re-entering Earth’s atmosphere. A large fraction of this material is composed of aluminum, which will ablate during re-entry and form aluminum oxide (Al2O3) containing aerosols in the mesosphere and lower thermosphere. These particles represent a new, human-made metal aerosol source that may interact with natural meteoric smoke and potentially impact upper-and middle- atmospheric chemistry, radiative balance, polar mesospheric cloud, polar stratospheric cloud as well as stratospheric aerosol formation. However, observational constraints on the abundance and vertical distribution of such aluminum-bearing aerosols are currently very limited.Aluminum oxide exhibits characteristic spectral features in the mid-infrared, allowing detection via remote sensing spectroscopic measurements. In contrast to techniques based on scattering in the visible wavelength range, mid-infrared spectroscopic detection is independent of particle size as long as the particle radius remains small compared to the wavelength. This makes it particularly suited to constraining nanometer- to sub-micrometer-sized aluminum oxide aerosols expected from debris ablation. Moreover, spectrally resolved infrared limb measurements enable the quantification of total aerosol volume (and thus mass) profiles, providing a direct link between observed aerosol burdens and modeled debris input fluxes.In this work, we quantitatively assess the capability of a space-borne infrared limb-imaging instrument to detect and characterize aluminum oxide aerosols from re-entering space debris. We perform end-to-end simulations of atmospheric radiances and instrument response in the mid-infrared, incorporating realistic Al2O3 optical properties and assumed vertical profiles derived from debris model scenarios associated with upcoming mega-constellations. Radiative transfer calculations are used to compute infrared limb-emission spectra and sensitivities, which are then passed through an instrument simulator system representative of the CAIRT (Changing-Atmosphere Infra-Red Tomography) limb-imaging mission concept, studied as an EE11 candidate for ESA’s Earth Explorer program.We demonstrate that the characteristic mid-infrared absorption features of aluminum oxide remain detectable at realistic noise levels for CAIRT-like performance, over a range of plausible aerosol loads. Sensitivity analyses show that vertical profiles of total Al2O3 aerosol volume can be retrieved, even when particle sizes and shapes are not well constrained. Our results indicate that a CAIRT-type infrared limb-sounding mission could provide the first global, vertically resolved observational constraints on aluminum oxide aerosols from space debris.

Atmospheric gravity waves (GWs) generated by orography, commonly referred to as mountain waves (MWs), play a key role in driving atmospheric circulation and in modulating phenomena such as sudden stratospheric warmings (SSWs). Their contribution, however, is difficult to disentangle from the full spectrum of observed or simulated GWs. Here, we present a methodology to isolate the MW component of GW observations by combining simulated infrared limb imager measurements with backward ray tracing. This approach enables a systematic separation of GW momentum flux (GWMF) carried by MWs from the total observed signal. As a case study, we analyze the 2018/19 Northern Hemisphere New Year SSW period, presenting global distributions and time series of GWMF partitioned into orographic and residual components. The ensemble of backward ray trajectories shows a strong correspondence between inferred MW sources and surface topography, supporting the robustness of the method. On average, the identified MWs account for only a minor fraction of the observed GWMF, but episodically they can account for a major part of the GWMF, including prior to the onset of the SSW. These results highlight the potential of combining satellite observations with ray tracing to achieve source attribution of GWs. The method’s effectiveness depends on the accuracy of retrieved GW parameters, and we therefore include a sensitivity analysis of parameter uncertainties in the appendix.

Following the increase of greenhouse gas emissions, atmospheric models predict a strengthening of the middle atmospheric Brewer-Dobson circulation (BDC). Changes in the BDC, inferred from age of air (AoA) trends, can influence UTLS exchange processes, including stratosphere–troposphere transport of ozone. While models predict an acceleration of the BDC (i.e. a decrease of AoA), in-situ balloon observations suggest the opposite, although not significantly, given the limited number of observations and the substantial uncertainties (Garny et al., 2024a). Additionally, meteorological reanalyses disagree on the sign and magnitude of AoA trends, despite providing an optimized estimate of atmospheric circulation constrained by observations.The Changing Atmosphere Infrared Tomography explorer (CAIRT) was proposed for ESA’s Earth Explorer 11 to address these inconsistencies. CAIRT was foreseen to achieve a precision of 0.5 years on the age of air, a requirement to assess long-term trends. This contribution aims to evaluate the capability of CAIRT to achieve this precision. Synthetic CAIRT profiles of six long-lived species (SF6, CH4, N2O, CFC11, CFC12 and HCFC22) are simulated by the Belgian Assimilation System for Chemical ObsErvations (BASCOE) chemistry transport model, considering CAIRT’s expected measurement errors and spatial resolution. CAIRT AoA observations, derived from the six long-lived species using the method of Voet et al. (2025), are compared to clock tracer AoA, simulated by the BASCOE model, to evaluate the agreement. The analysis is repeated three times by driving the model with the meteorological reanalyses MERRA2, ERA5, and JRA-3Q, respectively, to check if CAIRT precision would be sufficient to evaluate meteorological reanalyses.

Abstract The Earth’s middle atmosphere spans the deep region from the upper troposphere/lower stratosphere at around 10 km altitude to the mesosphere/lower thermosphere at around 100 km altitude. It is being increasingly recognized for its role in driving extreme surface weather and regional climate change. Climate models predict large ongoing and future changes in the middle atmosphere composition and circulation. However, the observations needed to detect, attribute and understand these changes and their impacts, to test predictions, and thereby to improve our models, are lacking. Here we show the capacity of infrared limb-imaging tomography to provide the needed observations. This evaluation is based on studies performed within a recent satellite mission concept – the Changing-Atmosphere Infrared Tomography Explorer, CAIRT. Observing thermal infrared emissions simultaneously from the middle troposphere at about 4 km up to the lower thermosphere at about 115 km altitude this technique provides observations of temperature and an extensive range of trace gases with unprecedented spatial resolution of about 50 by 50 km horizontally and about 1 km vertically. We show how these observations would (a) help to quantify the changing atmospheric circulation, (b) allow characterization and quantification of the gravity waves that are critical in driving this circulation, (c) reveal how variability in solar radiation and energetic particles propagate downward to affect regional climate at the surface, (d) detect how volcanic eruptions and wildfires impact the middle atmosphere and climate, and (e) resolve how stratosphere-troposphere exchange affects ozone and water vapor in the crucial and climate-relevant tropopause region.

Abstract. Climate models predict changes in the Brewer-Dobson circulation under a changing climate, which could have profound effects on tracer distributions and the radiative budget. Age-of-Air is an important concept for describing transport in the stratosphere and to understand and quantify global atmospheric circulation patterns such as the Brewer-Dobson circulation. Being an unobservable quantity, it must be inferred from other, directly observable quantities such as long-lived trace gases. It is therefore essential to have accurate ways of determining Age-of-Air through observations. These observations are subject to measurement noise, which is a long-known source of uncertainty when deriving Age-of-Air, as such uncertainties can affect the derived Age-of-Air significantly. We present a novel approach of using neural networks to derive Age-of-Air from long-lived trace gases. Multi-layer perceptrons can be used to predict model Age-of-Air with accuracy as little as a single month. The networks can be optimally trained according to expected measurement uncertainties. An unsupervised autoencoder is presented which is capable of achieving similar predictability almost without relying on model Age-of-Air inputs. This study presents an overview of these new approaches and discusses their capabilities, their accuracies and precisions mostly from a technical perspective regarding input parameters, regularization and predictions outside the training domain. Our approach allows us to derive Age-of-Air with accuracy of up to a single month under considerable measurement noise and over a wide altitude range. This accuracy is even retained when predicting values from a completely different period.

Abstract. We develop and apply a novel method for estimating stratospheric mean age of air (AoA) from trace gases observed by the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS). The method combines SF6 with five additional long-lived tracers, N2O, CH4, CFC-11, CFC-12, and HCFC-22, and is evaluated for ACE-FTS dataset versions 3.6 and 5.2. A proof of concept using the Chemical Lagrangian Model of the Stratosphere (CLaMS) shows that the multi-tracer approach reduces the uncertainty of zonal-mean AoA by about 50 % relative to conventional methods based only on SF6 and yields AoA estimates at individual profiles with an average uncertainty of about 0.3 years. Applied to ACE-FTS data, the multi-tracer method produces smoother AoA fields and strongly suppresses noise in sparsely sampled regions compared with the conventional convolution method. Comparison with in situ AoA estimates from SF6 and CO2 generally favors the multi-tracer product, although some discrepancies remain. The method provides a precise and spatially resolved satellite-based AoA product and a promising basis for future studies of long-term changes in stratospheric circulation. Comparison of ERA5 AoA with the new satellite product indicates a slow bias in the reanalysis. The long-term AoA trend pattern over 2004–2021 shows increasing age in the Northern Hemisphere stratosphere between about 18–28 km and decreasing age in the tropics and Southern Hemisphere subtropics, largely consistent with ERA5. In particular, AoA increases in the Northern relative to the Southern Hemisphere.

The wave-driven Brewer–Dobson circulation plays a crucial role in determining the transport of trace gases and aerosols in the stratosphere. We examine the structure of the circulation based on reanalysis data (ERA5, ERA-Interim, MERRA2, and JRA55) and the Transformed Eulerian Mean and downward control framework, aiming for a dynamical separation of different circulation branches in terms of outflow generated by wave driving. The results show the existence of different circulation regimes, with a deep circulation branch mainly driven by planetary waves with wavenumbers 1–3, and a shallow circulation branch mainly driven by smaller-scale waves with wavenumbers greater than 3. We propose a definition of the separation level between shallow and deep branches as the lowest level where outflow from planetary waves is larger than outflow from smaller-scale waves. We show that this level occurs at approximately 22 km (43 hPa) with a weak annual cycle. This climatological structure is robust in various reanalyses. The variability of the circulation in the deep branch above the separation level is mainly related to planetary waves, while the variability in the shallow branch is related to both smaller-scale and planetary waves. Trends in the circulation over the period 1980–2017 show an upward shift of the deep branch related to planetary waves and a downward shift of the shallow branch related to both planetary and smaller-scale waves. The height of the separation level shows no significant trend. Taking into account differences in wave driving between the branches of the circulation could explain the spread in model inter-comparisons.

We present trace gas and aerosol measurements obtained by the airborne infrared imaging limb sounder GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) that has been operated onboard HALO (High Altitude and Long Range Research Aircraft) during the PHILEAS campaign (Probing High Latitude Export of air from the Asian Summer Monsoon ; August-September 2023). We measured outflow from the Asian Monsoon above the North Pacific, and the Mediterranean, as well as pollution plumes from biomass burning events in North America. In this contribution, we present retrieval results of ammonia (NH3), solid ammonium nitrate and other pollution trace gases (e.g. PAN) as two-dimensional distributions with high vertical resolution, derived from GLORIA observations in the UTLS (Upper Troposphere Lower Stratosphere).Our GLORIA observations reveal considerable abundances of solid ammonium nitrate, which is connected to the Asian Monsoon, in the lower stratosphere outside the Asian Monsoon Anticyclone. Measurements from a previous airborne campaign within the Asian Monsoon (StratoClim 2017) showed large enhancements of NH3 (precursor of ammonium nitrate), and solid ammonium nitrate in the Asian Monsoon upper troposphere.Further, GLORIA measured UTLS air masses heavily influenced by biomass burning during PHILEAS. Due to the ability of GLORIA to measure pollution trace gases with different atmospheric life times, we are able to estimate the age of individual plumes, based on their chemical composition. As an example, we show measurements from a PHILEAS flight, influenced by aged and fresh pollution.In a first analysis, we compare our measurements with atmospheric models to examine air mass origins. In particular, we use artificial tracers calculated by the ICON-ART (ICOsahedral Nonhydrostatic - Aerosol and Reactive Trace gases), one of the models that was also used in forecast configuration for flight planning.

The stratospheric overturning meridional circulation is an important element in the global climate system and observationally-based estimates of its strength and changes are important for model validation and process understanding. But such observational constraints are prone to significant uncertainties related to the low circulation velocities and uncertainties in available trace gas measurements. Here, we propose a method to calculate mean age of air, as a measure for the stratospheric circulation, from mixing ratios of multiple measurable trace gas species, like trichlorofluoromethane (CFC-11), dichlorodifluoromethane (CFC-12), chlorodifluoromethane (HCFC-22), methane (CH4), nitrous oxide (N2O) and sulfur hexafluoride (SF6 ). The method is based on the correlations of these trace gases with mean age. The involved methodological error includes uncertainties due to atmospheric variability and non-compactness of the correlation, and additional instrument uncertainties as would be inherent for e.g. satellite instruments. The age calculation method is evaluated, globally and seasonally, in a model environment and compared against the true model mean age. We show that the tracer-age correlations are, in general, sufficiently compact in the age range between about 1 and 4 to 5 years, depending on the given species. Combination of the six chosen species reduces the resulting uncertainty of the derived mean age to below 0.3 years throughout most regions in the lower stratosphere. Even smaller scale, seasonal features in the global age distribution can be reliably diagnosed from the multi tracer-based mean age. Hence, the proposed mean age calculation method shows promise to reduce the error in mean age estimates from satellite trace gas observations.

Abstract. The wave driven Brewer-Dobson circulation plays a crucial role in determining the transport of trace gases and aerosols in stratosphere. We examine the structure of the circulation based on reanalyses data (ERA5, ERA-Interim, MERRA2, JRA55), using the Transformed Eulerian Mean and downward control framework, aiming for a dynamical separation of different circulation branches in terms of outflow generated by wave driving. The results show the existence of different circulation regimes, with a deep circulation branch mainly driven by large-scale waves with wavenumbers 1–3, and a shallow circulation branch mainly driven by smaller-scale waves with wavenumbers 4–180. We propose a definition of the separation level between a shallow and deep branch as the lowest level where outflow from waves 1–3 is larger than from waves 4–180. We show that this level occurs at approximately 22 km (43 hPa) and exhibits a weak annual cycle. This climatological structure is robust in various reanalyses. The variability of the circulation in the deep branch above the separation level is mainly related to large-scale waves 1–3, while the variability in the shallow branch is related to both smaller-scale and large-scale waves. Trends in the circulation over the period 1980–2017 show an upward shift of the deep branch related to waves 1–3 and a downward shift of the shallow branch related to both large and smaller scale waves. The height of the separation level shows no significant trend. Taking into account differences in wave driving between the branches of the circulation could reduce the spread in model inter-comparisons.

Accurate observations of the vertical distribution and variability of atmospheric trace gases are essential for understanding chemical processes, validating atmospheric models, and monitoring the impact of anthropogenic emissions on climate and ozone. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is a limb-imaging Fourier-Transform Spectrometer (iFTS) designed to provide high-resolution mid-infrared spectra in the 780–1400 cm−1 wavenumber range. Originally developed for aircraft, the instrument has now been adapted for stratospheric balloon deployment (GLORIA-B) to extend its observational range from the middle troposphere to the middle stratosphere. GLORIA-B completed its first flight from Kiruna (Sweden) in August 2021 and a second from Timmins (Canada) in August 2022 as part of the EU Research Infrastructure HEMERA (Integrated access to balloon-borne platforms for innovative research and technology). The main objectives of these flights were technical qualification and the provision of a first imaging hyperspectral limb-emission dataset from 5 to 36 km altitude. Here, we present a characterization and validation of GLORIA-B performance using vertical volume mixing ratio (VMR) profiles retrieved from the August 2021 flight. Comparisons with in-situ measurements (ozonesonde, MegaAirCore, and cryosampler) show agreement within 10 % for O3, CH4, SF6, and CFC-12, and within 10 %–20 % for CFC-11, HCFC-22, and CFC-113 up to 18 km, with larger deviations above this altitude. Another objective is analyzing diurnal changes in photochemically active species (N2O5, NO2, ClONO2, BrONO2). Observed VMR variations align well with simulations from the EMAC (ECHAM5/MESSy Atmospheric Chemistry) chemistry-climate model, though absolute concentrations differ to a certain extent. Nighttime BrONO2 measurements allowed an estimate of lower stratospheric Bry (20.4 ± 2.5 pptv). These results demonstrate the suitability of balloon-borne limb-imaging spectroscopy for providing high-quality vertical trace gas profiles, offering valuable new data to improve our understanding of stratospheric composition and to support the validation of atmospheric models.

The stratospheric circulation is an important element in the climate system, but observational constraints are prone to significant uncertainties due to the low circulation velocities and uncertainties in available trace gas measurements. Here, we propose a method to calculate mean age of air as a measure of the circulation from observations of multiple trace gas species which are reliably measurable by satellite instruments, like trichlorofluoromethane (CFC-11), dichlorodifluoromethane (CFC-12), chlorodifluoromethane (HCFC-22), methane (CH4), nitrous oxide (N2O), and sulfur hexafluoride (SF6), and we show that this method works well in most of the lower stratosphere up to a height of about 25 km. The method is based on the compact correlations of these gases with mean age. Methodological uncertainties include effects of atmospheric variability, non-compactness of the correlation, and measurement related effects inherent for satellite instruments. The multi-species age calculation method is evaluated in a model environment and compared against the actual model age from an idealized clock tracer. We show that combination of the six chosen species reduces the resulting uncertainty of derived mean age to below 0.3 years throughout most regions in the lower stratosphere. Even small-scale, seasonal features in the global age distribution can be reliably diagnosed. The new correlation method is further applied to trace gas measurements with the balloon-borne Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA-B) instrument. The corresponding deduced mean age profiles agree reliably with SF6-based mean age below about 22 km and show significantly lower uncertainty ranges. Comparison between observation-based and model-simulated mean ages indicates a slow-biased circulation in the ERA5 reanalysis. Overall, the proposed mean age calculation method shows promise to substantially reduce the uncertainty in mean age estimates from satellite trace gas observations.

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is a limb-imaging Fourier-Transform spectrometer (iFTS) providing mid-infrared spectra with high spectral sampling (0.0625 cm-1 in the wavelength range 780-1400 cm-1). GLORIA, a demonstrator for the Changing-Atmosphere Infra-Red Tomography Explorer (CAIRT, one of the remaining two candidates for the ESA Earth Explorer 11 mission) was deployed on the Russian M55 Geophysica and is still being deployed on HALO, the German high-altitude research aircraft. In order to enhance the vertical range of GLORIA to observations in the middle stratosphere albeit still reaching down to the middle troposphere, the instrument was adapted to measurements from stratospheric balloon platforms. GLORIA-B performed its first flight from Kiruna (northern Sweden) in August 2021 and its second flight from Timmins (Ontario/Canada) in August 2022 in the framework of the EU Research Infrastructure HEMERA. The objectives of GLORIA-B observations for these campaigns have been its technical qualification and the provision of a first imaging hyperspectral limb-emission dataset from 5 to 36 km altitude. Further, scientific objectives, which are, amongst many others, the diurnal evolution of photochemically active species belonging to the nitrogen (e.g. N2O5, NO2), chlorine (e.g. ClONO2), and bromine (BrONO2) families are discussed. In this contribution we demonstrate the performance of GLORIA-B with regard to level-2 data of the flight in August 2021, consisting of retrieved altitude profiles of a variety of trace gases. We will show examples of selected results together with uncertainty estimations, altitude resolution as well as long-lived tracer comparisons to accompanying in-situ datasets. In addition, diurnal variations of photochemically active gases are compared to simulations of the chemistry climate model EMAC. Calculations largely reproduce the temporal variations of the species observed by GLORIA-B.

MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is a Swedish satellite designed to investigate atmospheric dynamics in the mesosphere and lower thermosphere (MLT). By observing structures in noctilucent clouds over polar regions and oxygen atmospheric-band (A-band) emissions globally, MATS will provide the research community with properties of the MLT atmospheric wave field. Individual A-band images taken by MATS's main instrument, a six-channel limb imager, are transformed through tomography and spectroscopy into three-dimensional temperature fields, within which the wave structures are embedded. To identify wave properties, particularly the gravity wave momentum flux, from the temperature field, smaller-scale perturbations (associated with the targeted waves) must be separated from large-scale background variations using a method of scale separation. This paper investigates the possibilities of employing a simple method based on smoothing polynomials to separate the smaller and larger scales. Using using synthetic tomography data based on the HIAMCM (HIgh Altitude Mechanistic general Circulation Model), we demonstrate that smoothing polynomials can be applied to MLT temperatures to obtain fields corresponding to global-scale separation at zonal wavenumber 18. The simplicity of the method makes it a promising candidate for studying wave dynamics in MATS temperature fields.

Abstract. 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 has been operated onboard the research aircraft Geophysica within the Asian Monsoon during the StratoClim campaign (July 2017) and onboard HALO (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. 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 reproduce the biomass burning plumes above the South Atlantic in general. However, NH3 concentrations are largely overestimated by the CAMS models within these plumes. We suggest that emission strengths used by CAMS models are of different accuracy for biomass burning and 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 mission to strengthen our understanding of this important trace gas in the atmosphere.

In the past, satellite climatologies of gravity waves (GWs) have initiated progress in their representation in global models. However, these could not provide the phase speed and direction distributions needed for a better understanding of the interaction between GWs and the large-scale winds directly. The ESA Earth Explorer 11 candidate CAIRT could provide such observations. CAIRT would use a limb-imaging Michelson interferometer resolving a wide spectral range, allowing temperature and trace gas mixing ratio measurements. With the proposed instrument design, a vertical resolution of 1 km, along-track sampling of 50 km, and across-track sampling of 25 km in a 400 km wide swath will be achieved. In particular, this allows for the observation of three-dimensional (3D), GW-resolving temperature fields throughout the middle atmosphere. In this work, we present the methodology for the GW analysis of CAIRT observations using a limited-volume 3D sinusoidal fit (S3D) wave analysis technique. We assess the capability of CAIRT to provide high-quality GW fields by the generation of synthetic satellite observations from high-resolution model data and comparison of the synthetic observations to the original model fields. For the assessment, wavelength spectra, phase speed spectra, horizontal distributions, and zonal means of GW momentum flux (GWMF) are considered. The atmospheric events we use to exemplify the capabilities of CAIRT are the 2006 sudden stratospheric warming (SSW) event, the quasi-biennial oscillation (QBO) in the tropics, and the mesospheric preconditioning phase of the 2019 SSW event. Our findings indicate that CAIRT would provide highly reliable observations not only of global-scale GW distributions and drag patterns but also of specific wave events and their associated wave parameters. Even under worse-than-expected noise levels of the instrument, the resulting GW measurements are highly consistent with the original model data. Furthermore, we demonstrate that the estimated GW parameters can be used for ray tracing, which physically extends the horizontal coverage of the observations beyond the orbit tracks.

During winter, the latitude belt at 60S is one of the most intense hotspots of stratospheric gravity wave (GW) activity. However, producing accurate representations of GW dynamics in this region in numerical models has proved exceptionally challenging. One reason for this is that questions remain regarding the relative contributions of different orographic and non-orographic sources of GWs here.We use 3-D satellite GW observations from the Atmospheric InfraRed Sounder (AIRS) from winter 2012 in combination with the Gravity-wave Regional Or Global Ray Tracer (GROGRAT) to backwards ray trace GWs to their sources. We trace over 14.2 million rays, which allows us to investigate GW propagation and to produce systematic estimates of the relative contribution of orographic and non-orographic sources to the total observed stratospheric GW momentum flux in this region.We find that in winter 56% of momentum flux (MF) traces back to the ocean and 44% to land, despite land representing less than a quarter of the region’s area. This demonstrates that, while orographic sources contribute much more momentum flux per unit area, the large spatial extent of non-orographic sources leads to a higher overall contribution. The small islands of Kerguelen and South Georgia specifically contribute up to 1.6% and 0.7% of average monthly stratospheric MF, and the intermittency of these sources suggests that their short-timescale contribution is even higher. These results provide the important insights needed to significantly advance our knowledge of the atmospheric momentum budget in the Southern polar region.

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.