Airborne or spaceborne Integral Path Differential Absorption (IPDA) lidar has the potential to deliver the highly accurate column measurements of trace gases that are needed to reduce the uncertainties on the surface fluxes of anthropogenic greenhouse gases. Among its advantages over passive remote sensing is the very narrow field of view, which makes it possible to exploit “cloud holes” at all spatial scales to increase the coverage. Moreover, in a broken cloud field scenario, it is possible to turn the IPDA lidar into a pseudo-range-resolved lidar and retrieve the average trace gas concentration in the atmospheric layer below the clouds by combining partial columns down to the cloud tops and total columns down to the ground. This is usually referred to as “cloud slicing”. Here we report on an attempt to apply cloud slicing on methane data from DLR's airborne IPDA lidar, CHARM-F. The data was acquired on the 23rd of August 2021 over the northern Scandinavian wetlands in the frame of the MAGIC 2021 campaign. We show that cloud slicing enables to overcome some issues with the instrument's performance during the campaign and that the retrieved methane concentration in the boundary layer matches well with vertical in-situ profiles acquired during the same flight.

Validation of the MERLIN data products by the airborne demonstrator CHARM-F is regarded a key mission element. Deployment of this instrument on the German HALO or French ATR aircrafts during several scientific campaigns enabled to improve the measurement performance and data reduction capability, enormously. Thus CHARM-F is on the right track to meet the stringent measurement requirements for MERLIN. It is found that the systematic error of CHARM-F can be kept smaller than 3 ppb which is the target performance requirement for MERLIN. Preliminary direct comparisons to WMO certified In-Situ measurements, however, show still an almost constant bias of about 1.5 % which is subject to further investigations.

Abstract. Regulating the emission of methane (CH4) from anthropogenic sources plays an important role in global climate mitigation strategies. The waste sector is responsible for some of the strongest localized sources and therefore its control has the potential for high impact reduction measures. As shown in a related preceding publication, airborne lidar and imaging spectrometer data provide reliable measurements of CH4 columns and can be used to estimate CH4 fluxes from sources such as landfills. However, incomplete knowledge of the transport of greenhouse gases from the source to the measurement point is one of the main sources of uncertainty in flux determination. In this paper, we improve the accuracy over previous emission estimates by applying a new analysis method, based on high-resolution regional-scale weather simulations to describe the atmospheric transport. We use this model to perform a combined fit to the CH4 measurements from airborne lidar and passive remote sensing, as well as in situ measurements. The key improvement over previous estimates comes from explicitly accounting for the complex, time-varying wind field on the measurement day, which caused significant CH4 accumulation that biased earlier cross-sectional flux estimates. This investigation focuses on two waste facilities close to Madrid, Spain, which were overflown by the German research aircraft HALO during a flight of the CoMet 2.0 Arctic mission. The estimated emission rates for the two sites were determined to be 4.0 ± 1.2 t h-1 (Pinto landfill) and 4.7 ± 0.7 t h-1 (Valdemingómez waste site).

The airborne Integrated Path Differential Absorption Lidar CHARM-F for accurate column concentration measurements of CH4 and CO2 has been very successfully deployed on a HALO aircraft campaign over Canada in late summer 2022. The scientific target areas, apart from natural sources (wetlands and thawing permafrost areas), included a variety of anthropogenic sources (oil and gas industry, coal mining, landfills and power plants). Using selected examples, we show the capabilities, but also the challenges, of trying to quantify methane fluxes from such measurements.

Nitrous oxide, N 2 O is the third most important anthropogenic greenhouse gas after carbon dioxide and methane. The major source is nitrogen fertilization in croplands. Differential absorption lidar is very demanding since suitable absorption lines exist only in the infrared, which challenges lidar transmitter and detector options. Spectroscopic investigations and lidar instrumental noise simulations show that in the 4.5 µm band a trough position between two strong N 2 O lines is likely the best option for an airborne lidar. A second option exists in the 3.9 µm band, at the cost of higher laser frequency stability constraints. Independently on the 3.9 versus 4.5 µm question an airborne lidar is expected to fulfill the N 2 O measurement requirements for regional gradient or hot spot detection with technically realizable and affordable transmitter (100 mW average laser power) and receiver (20 cm telescope) characteristics. However, such a system would benefit from progress in infrared transmitter and detector technology.

Abstract. Methane (CH4) is the second most important greenhouse gas with an atmospheric lifetime of approximately 10 years. Due to its relatively short lifetime, it offers substantial mitigation potential with reduction in emissions. Lakes and wetlands constitute major natural CH4 sources, and offshore oil and gas production is a dominant anthropogenic source over open water. However, passive remote sensors have observational gaps over water due to low surface reflectance and challenging sun-glint measurement geometry, and in-situ observations also remain sparse. Active remote sensing using CO2 and CH4 Atmospheric Remote Monitoring – Flugzeug (CHARM-F) Integrated Path Differential Absorption (IPDA) lidar provides column-averaged methane mixing ratio (XCH4) over water bodies and wetlands independent of solar illumination and largely independent of surface reflectance. However, understanding how the lidar signal to noise ratio (SNR) varies with different surface types, and how this variability propagates into retrieval uncertainties is critical to fully exploit the potential of IPDA lidar over water bodies and wetlands. In this study, we analyze airborne CHARM-F IPDA lidar observations acquired during two Carbon dioxide and Methane (CoMet) field campaigns over heterogeneous land and water surfaces in Europe and North America. This lidar serves as the airborne demonstrator for the future space borne MEthane Remote sensing Lidar missioN (MERLIN) which will deliver global methane emission maps and reduce uncertainties in methane emission estimates. Here, we study the averaging biases of the lidar XCH4 retrievals and propagate SNR-derived uncertainties to the final XCH4 estimates building on the work of Tellier et al. (2018). An independent analysis of surface reflectance measurements from the hyperspectral imaging spectrometer of the Munich Aerosol Cloud Scanner (specMACS) against CHARM-F signal strength and SNR provides a direct observational link between surface properties, signal statistics, and retrieval performance. The lidar signals over dry land exhibit Gaussian distributions associated with high surface reflectance, high SNR and low non-correctable residual XCH4 uncertainties below 1 ppb. In contrast, wetlands and open water surfaces display weaker and broader signal distributions with SNR reduced by a factor of about 2 as compared to dry land. However, the retrieval uncertainty over water bodies remains below 1 ppb when using an appropriate water mask and SNR-weighted averaging of the lidar signals. These findings provide the first observationally constrained characterization of how surface type is related to lidar SNR, averaging bias, and retrieval uncertainty in airborne IPDA methane measurements. The results highlight the capability of IPDA to robustly measure methane over water, relevant for the MERLIN mission.

In 2018, the CoMet series of airborne missions was launched under the auspices of the German Aerospace Center (DLR). From this point onward, large-scale field campaigns are organized regularly every few years, in collaboration with partner institutions, to understand the anthropogenic and natural fluxes of the greenhouse gases CO2 and CH4, using the German research aircraft HALO. In addition to scientific objectives, the CoMet field campaigns aim to promote technological developments necessary for new and future Earth observation satellites, validate current greenhouse gas satellite measurements, and prepare new satellite missions, in particular the upcoming German-French methane lidar mission MERLIN. One of the core instruments of CoMet is the IPDA lidar CHARM-F, which was developed at DLR as an airborne demonstrator, testbed, and validation tool for MERLIN.

Nitrous oxide, N2O is the third most important anthropogenic greenhouse gas after carbon dioxide and methane. The major source is nitrogen fertilization in croplands. Differential absorption lidar is very demanding since suitable absorption lines exist only in the infrared, which challenges lidar transmitter and detector options. Spectroscopic investigations and lidar instrumental noise simulations show that in the 4.5 µm band a trough position between two strong N2O lines is likely the best option for an airborne lidar. A second option exists in the 3.9 µm band, at the cost of higher laser frequency stability constraints. Independently on the 3.9 versus 4.5 µm question an airborne lidar is expected to fulfill the N2O measurement requirements for regional gradient or hot spot detection with technically realizable and affordable transmitter (100 mW average laser power) and receiver (20 cm telescope) characteristics. However, such a system would benefit from progress in infrared transmitter and detector technology.

Water vapor is the key trace gas component of the air and involved in virtually all relevant atmospheric processes. To know the vertical profile with decent resolution is crucial in all cases. For example, there are several regions of the atmosphere where numerical weather prediction models show biases which are not understood. So, after aerosol/cloud and wind lidars have been very successfully applied within space missions, the natural next step would be the profiling of water vapor by a Differential Absorption Lidar (DIAL) from a satellite in a low Earth orbit. About 20 years ago the ESA EarthExplorer Proposal WALES went through phase A, but was not further selected due to the identified technological risks and the corresponding financial efforts. Thanks to the European spaceborne lidar missions Aeolus/2, EarthCare, and MERLIN now the major building blocks for a such water vapor DIAL have reached the necessary technological readiness to realize such a program within the financial limits of a typical Earth observation mission. We will review the benefits of water vapor profiling by lidar as compared to passive sensors for different applications and then present an updated system design based on the current European space lidar component pool. Finally, results from end-to-end performance simulations will be presented. This presentation is thought as an invitation to the community to think about possible applications of space-borne H2O-lidar data and the corresponding observational requirements.

Airborne and satellite based lidar remote sensing combines the advantages of high measurement accuracy, large-area coverage and low-ambient-light measurement capability. The Merlin airborne demonstrator CHARM-F is an Integrated-Path Differential-Absorption (IPDA) lidar providing vertical column concentrations of carbon dioxide and methane up to the flight altitude along the flight track. It operated onboard the German HALO (high-altitude long-range) research aircraft during the CoMet 2.0 Arctic campaign in August and September 2022 over natural and anthropogenic sources of CO2 and CH4 in Canada. Natural methane fluxes from wetlands generally produce weak atmospheric concentration enhancements of the measured atmospheric column (

The Arctic Methane and Permafrost Challenge (AMPAC) is an ESA and NASA collaborative community initiative to help tackle the scientific challenges in estimating current and future methane fluxes from the Arctic region. Under this umbrella, AMPAC-Net is an ESA funded project to foster collaborations and scientific exchange on the Arctic methane challenge. The six guiding goals are: (1) Engaging the community, workshops, dialogue (2) Advancing EO products, novel methods, algorithms (3) Reconciling bottom-up & top-down approaches (4) Data catalogues, open science and data sharing (5) Summer schools, training, outreach and education and (6) Networking, including supporting scientific exchanges. The initiative is further supported through the ESA funded project MethaneCamp with focus on improvement of satellite retrievals of methane concentrations in the Arctic. As part of AMPAC-Net, relevant already published datasets have been included into a catalogue (https://apgc.awi.de/group/about/ampac) including datasets for methane (in situ, satellite derived concentrations, airborne campaign data, inversions etc.) and landcover/wetlands. Bottom-up estimates rely on accurate representation of Arctic landcover, especially wetlands as potential methane source. The heterogeneity of Arctic landcover requires high spatial resolution and appropriate thematic content. Existing circumpolar landcover data and a range of in situ data have been investigated with respect to wetlands and heterogeneity supporting AMPAC goals, especially the new landcover units derived from Copernicus Sentinel-1 (Synthetic Aperture Radar) and Sentinel-2 (multispectral) satellite missions (ESA Permafrost_CCI, 10 m). Further on, the potential of new, approved European satellite missions for AMPAC goals is discussed. https://www.ampac-net.info/ https://methanecamp.fmi.fi/

The Integrated Greenhouse Gas Monitoring System for Germany (ITMS) is a national initiative to establish an operational service for the provision of independent estimates of GHG fluxes for Germany. The main aim is to enhance transparency in reporting of emissions and natural fluxes on the path to net zero emissions. ITMS is a highly interdisciplinary project, bringing together diverse scientific communities involved in atmospheric observations, satellite observations, biosphere and agriculture research, inventory experts, and atmospheric transport and inverse modelling. ITMS utilizes observational datastreams from research infrastructures such as ICOS and IAGOS, and tailored remote sensing products, to constrain Germany’s GHG fluxes into the atmosphere using inverse atmospheric transport modelling. Detailed a priori emissions are generated consistent with UNFCCC reported emissions, while priors for natural fluxes are based on various process based as well as diagnostic models. Inverse modelling is deployed at mesoscale resolution, using the CarboScope-Regional (CSR) inversion system operated at the MPI-BGC as a back-bone and reference system, while developing ICON-ART based data assimilation for future operational services. The presentation will give an overview of recent progress and show some research highlights achieved so far.

Permafrost degradation in the Arctic is accelerating and is forecast to enhance greenhouse gas (GHG) emissions from the large permafrost carbon pool. Earth observation has a key role in determining GHG sources and sinks, and multiple current and future missions are useful to track baseline parameters for determining GHG fluxes. NASA and ESA have initialized the Arctic Methane and Permafrost Challenge (AMPAC) as a transatlantic networking action that strives to promote related scientific work and improve observation capabilities. Key variables observable from space include methane concentrations as well as landcover properties to inform process-based models as proxy for sources as well as temperature-related constraints for microbial activity. Upcoming missions are expected to advance these capabilities significantly with increased sampling intervals through future synthetic aperture radar missions and constellations of multiple multispectral sensors. This will allow better representation of seasonality and advance methane source attribution in general. In addition, continuity of current missions, which provide GHG observations, including methane, is crucial. Hyperspectral and superspectral sensors targeting primarily landsurface observation are expected to complement methane retrievals through the identification of emission hotspots. Arctic monitoring also requires active optical instruments for concentration retrieval, a type of instrumentation that is still novel for satellite-based observations. A comprehensive portfolio of hyperspectral, passive microwave, synthetic aperture radar, altimeter and landsurface temperature, and lidar measurements in addition to imaging spectrometers will be available by 2032/2033, at the time of the International Polar Year. This will allow for advanced experiments when also accompanying in situ observations become available.

The CoMet 2.0 Arctic airborne measurement campaign of 2022 targeted a variety of natural as well as anthropogenic sources of CH4, mostly in Canada, such as landfills, coal mines, power plants or fossil fuel exploitation sites. Many anthropogenic emission targets consist of a few strong emitters with small or negligible spatial extension. In these cases, emission plumes can readily be observed by passive imaging spectrometers, through the observed enhancement in column averaged CH4. However, over oil and gas fields such as the Lloydminster area at the Alberta/Saskatchewan border, with numerous individual wells extending over large areas, this is much more difficult since individual plumes are lower in magnitude and may even overlap. In such cases it may not be possible to resolve plumes from individual sources, but the total flux can still be estimated using a budget approach. Nevertheless, limitations arise from spatial and temporal variations in the wind field, regarding proper quantification of the source strengths. In this contribution we present our strategy for source attribution, combining measurements by the airborne CHARM-F greenhouse-gas lidar and the MAMAP2DL imaging spectrometer with emission inventories and inverse modeling. A similar approach has already been successfully applied to CHARM-F data recorded over the Upper Silesian Coal Basin during the CoMet 1.0 campaign. CHARM-F is an Integrated-Path Differential-Absorption (IPDA) lidar that provides vertical column concentrations of CO2 and CH4 up to the flight altitude along the flight track. The advantages of lidar are the insensitivity to illumination conditions and a low intrinsic bias. MAMAP2DL is a passive airborne push broom imaging spectrometer that measures spatially resolved changes in relative column concentrations of CH4 and CO2. During the CoMet 2.0 Arctic campaign in August and September 2022, CHARM-F and MAMAP2DL have been deployed onboard the German research aircraft HALO, alongside a suite of complementary instruments for in-situ measurements of CH4, CO2 and other trace gases. We introduce our methods for data treatment and inverse modelling and show first results from this approach.

To reduce and mitigate anthropogenic greenhouse gas surface fluxes from industrial sites, their sources must be, firstly, identified or localized and, secondly, accurately quantified. For methane (CH4), the second most important anthropogenic greenhouse gas, the quantification of its diverse emitters is still a challenge. Due to their nature, these emitters can reach dimensions from point sources to hundreds of square kilometres for fossil fuel (gas, oil, coal) exploitation sites or up to several square kilometres in case of waste disposal sites. Although, CH4 emissions from, e.g., waste disposal sites can be computed from activity data combined with landfill models, a high potential for unintended and poorly quantified leakages remain due to, e.g., potential ruptures in the landfill cover. Consequently, the exact localization and quantification of those leakages is a necessary step towards reducing CH4 emissions from waste disposal sites. To have better knowledge and insights into anthropogenic and natural greenhouse gas emissions, a team of scientists has assembled a comprehensive suite of instruments aboard the German Research aircraft HALO (High Altitude and Long Range Research Aircraft) during the CoMet 2.0 Arctic mission conducted in Canada in August and September 2022. Although the campaign was primarily intended to observe and quantify CH4 and CO2 emissions and disentangle anthropogenic from natural sources at the high northern latitudes of Canada, a test flight over Spain revealed unexpectedly high and still persistent emissions from two landfills in Madrid - Valdemingomez and Pinto, previously also pointed out in an ESA story based on satellite observations. Both were investigated by means of passive and active remote sensing, as well as in situ airborne techniques. The measurements of the passive airborne remote sensing instrument MAMAP2D-Light, developed at the University of Bremen, delivers atmospheric concentration anomaly maps of CH4 and CO2. Here, its imaging capabilities are used to pin-point the origin of the CH4 emissions across the targeted landfills and to quantify their emissions. MAMAP2D-Light’s concentration maps are combined with highly accurate CH4 column concentration measurements from the integrated-path differential-absorption lidar CHARM-F (CO2 and CH4 Remote Monitoring-Flugzeug), developed by German Aerospace Center (DLR) in Oberpfaffenhofen. Additionally, airborne CH4 in situ mole fractions were measured by the Jena Instrument for Greenhouse Gases (JIG) and supplemented with wind data within the emission plume in order to complement the remote sensing observations. This contribution will present top-down emission estimates from measurements of all aforementioned instruments, operated quasi-simultaneously, i.e. within a time span of approximate 2 hours, over the targeted area in Madrid in August 2022.

Airborne and spaceborne integral-path differential absorption (IPDA) lidar has the potential to deliver column measurements of the major greenhouse gases influenced by human activity with the high accuracy that is required to significantly reduce the uncertainties in our estimations of surface fluxes of methane and carbon dioxide by inverse modelling. A prerequisite is the highly accurate knowledge of the emitted wavelengths, especially for carbon dioxide in the 1.6-µm region, where a long-term optical frequency knowledge accuracy of the online channel down to a few tens of kHz is required. Deutsches Zentrum für Luft- und Raumfahrt's airborne IPDA lidar for simultaneous measurements of carbon dioxide at 1.57 µm and methane at 1.64 µm, CHARM-F, uses a specifically developed frequency reference unit based on optimized wavelength modulation spectroscopy which can reach the required accuracy in a stabilized laboratory environment, but whose in-flight performance in the more challenging aircraft environment could not be independently validated. In the frame of the Carbon Dioxide and Methane Mission (CoMet) field campaigns in 2018 and 2022, CoMet 1.0 and CoMet 2.0 Arctic, respectively, a cooperation with Menlo Systems GmbH made it possible to bring a prototype of a new generation of portable and rugged self-referenced frequency combs (SRFCs) on board the German research aircraft HALO. This airborne frequency comb served as an independent frequency reference to characterize the performance of the carbon dioxide channel of CHARM-F's frequency reference system in flight. We report here on the frequency stability measurements carried out during the CoMet 2.0 Arctic campaign and demonstrate the potential of such portable SRFCs as next-generation frequency references for atmospheric lidars.

Methane (CH4), alongside carbon dioxide (CO2), is a key driver of anthropogenic climate change. Reducing CH4 is crucial for short-term climate mitigation. Waste-related activities, such as landfills, are a major CH4 source, even in developed countries. Atmospheric concentration measurements using remote sensing (RS) offer a powerful way to quantify these emissions. We study waste facilities near Madrid, Spain, where satellite data indicated high CH4 emissions. For the first time, we combine passive imaging (Methane Airborne Mapper 2D – Light, MAMAP2DL) and active lidar (CO2 and CH4 Atmospheric Remote Monitoring – Flugzeug, CHARM-F) remote sensing aboard the German High Altitude and Long Range Research Aircraft (HALO), supported by in situ instruments, to quantify CH4 emissions. Using the CH4 column data and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis v5 (ERA5) model wind information validated by airborne measurements, we estimate landfill emissions through a cross-sectional mass balance approach. Strong emission plumes are traced up to 20 km downwind on 4 August 2022, with the highest CH4 column anomalies observed over active landfill areas in the vicinity of Madrid, Spain. Total emissions are estimated to be up to ∼ 13 t h−1. Single co-located plume crossings from both instruments agree well within 1.2 t h−1 (or 13 %). Flux errors range from ∼ 25 % to 40 %, mainly due to boundary layer (BL) and wind speed variability. This case study not only showcases the capabilities of applying a simple but fast cross-sectional mass balance approach, along with its limitations due to challenging atmospheric boundary layer conditions, but also demonstrates, to our knowledge, the first successful use of both active and passive airborne remote sensing to quantify methane emissions from hotspots and independently verify their emissions.

Nitrous oxide (N2O) is the third most important greenhouse gas modified by human activities after carbon dioxide and methane. This study examines the feasibility of airborne differential absorption lidar to measure N2O concentration enhancements over agricultural, fossil fuel combustion, industrial, and biomass burning sources. The mid-infrared spectral region, where suitably strong N2O absorption lines exist, challenges passive remote sensing by means of spectroscopy due to both low solar radiation and thermal emission. Lidar remote sensing is principally possible thanks to the laser as an independent radiation source but has not yet been realized due to technological challenges. Mid-infrared N2O absorption bands suitable for remote sensing are investigated. Simulations show that a spectral trough position between two strong N2O lines in the 4.5 mu m band is the favored option. A second option exists in the 3.9 mu m band at the cost of higher laser frequency stability constraints and less measurement sensitivity. Both options fulfill the N2O measurement requirements for agricultural areal or point-source emission quantification (0.5 % measurement precision, 500 m spatial resolution) with technically realizable and affordable transmitter (100 mW average laser power) and receiver (20 cm telescope) characteristics for integrated-path differential absorption lidar that measures the column concentration beneath the aircraft. The development of an airborne N2O lidar is feasible yet would benefit from progress in infrared laser transmitter and low-noise-detection technology. It will also serve as a precursor to space versions, which are still out of reach due to the lack of space technology.

Power plants and large industrial facilities contribute more than half of global anthropogenic CO2 emissions. Quantifying the emissions of these point sources is therefore one of the main goals of the planned constellation of anthropogenic CO2 monitoring satellites (CO2M) of the European Copernicus program. Atmospheric transport models may be used to study the capabilities of such satellites through observing system simulation experiments and to quantify emissions in an inverse modeling framework. How realistically the CO2 plumes of power plants can be simulated and how strongly the results may depend on model type and resolution, however, is not well known due to a lack of observations available for benchmarking. Here, we use the unique data set of aircraft in situ and remote sensing observations collected during the CoMet (Carbon Dioxide and Methane Mission) measurement campaign downwind of the coal-fired power plants at Bełchatów in Poland and Jänschwalde in Germany in 2018 to evaluate the simulations of six different atmospheric transport models. The models include three large-eddy simulation (LES) models, two mesoscale numerical weather prediction (NWP) models extended for atmospheric tracer transport, and one Lagrangian particle dispersion model (LPDM) and cover a wide range of model resolutions from 200 m to 2 km horizontal grid spacing. At the time of the aircraft measurements between late morning and early afternoon, the simulated plumes were slightly (at Jänschwalde) to highly (at Bełchatów) turbulent, consistent with the observations, and extended over the whole depth of the atmospheric boundary layer (ABL; up to 1800 m a.s.l. (above sea level) in the case of Bełchatów). The stochastic nature of turbulent plumes puts fundamental limitations on a point-by-point comparison between simulations and observations. Therefore, the evaluation focused on statistical properties such as plume amplitude and width as a function of distance from the source. LES and NWP models showed similar performance and sometimes remarkable agreement with the observations when operated at a comparable resolution. The Lagrangian model, which was the only model driven by winds observed from the aircraft, quite accurately captured the location of the plumes but generally underestimated their width. A resolution of 1 km or better appears to be necessary to realistically capture turbulent plume structures. At a coarser resolution, the plumes disperse too quickly, especially in the near-field range (0–8 km from the source), and turbulent structures are increasingly smoothed out. Total vertical columns are easier to simulate accurately than the vertical distribution of CO2, since the latter is critically affected by profiles of vertical stability, especially near the top of the ABL. Cross-sectional flux and integrated mass enhancement methods applied to synthetic CO2M data generated from the model simulations with a random noise of 0.5–1.0 ppm (parts per million) suggest that emissions from a power plant like Bełchatów can be estimated with an accuracy of about 20 % from single overpasses. Estimates of the effective wind speed are a critical input for these methods. Wind speeds in the middle of the ABL appear to be a good approximation for plumes in a well-mixed ABL, as encountered during CoMet.

The distribution of H2O and O3 in the midlatitude UTLS is of key relevance for the Earth’s weather and climate. Tropospheric and stratospheric dynamical processes, acting on different time-scales, interact with chemistry and determine the composition of the UTLS and the extratropical transition layer (ExTL) therein. In this study, we investigate how strongly the fine-scale trace gas distribution in the UTLS/ExTL is related to interacting, tropospheric weather systems on synoptic time scales, which shape transport and mixing.We present range-resolved, collocated lidar H2O and O3 measurements from a research flight during the Wave-driven ISentropic Exchange (WISE) campaign, which was conducted across a jet stream located over the eastern North Atlantic on 1 October 2017. The observations are combined with 10-day backward trajectories along which meteorological parameters and turbulence diagnostics are traced. The derived transport and mixing characteristics are projected to the vertical cross sections of the lidar measurements and to the H2O–O3 phase space (Tracer-Tracer space) to explore linkages with the evolution of synoptic-scale weather systems and their interaction.We find that the formation of H2O and O3 filaments in the troposphere and stratosphere, the high variability of tropospheric H2O and the formation of the ExTL mixing layer can, to a large extent, be explained by transport and mixing associated with interacting tropical, midlatitude and arctic weather systems in the region of the jet stream on synoptic time scales. The mixed ExTL air exhibits a strong influence of turbulent mixing in the jet stream during the two days before the flight. The diagnosed non-local and transient character of mixing points to the complexity of the formation and interpretation of mixing lines in T–T space. The presented work is accepted for publication in ACP:Schäfler, A., Sprenger, M., Wernli, H., Fix, A., and Wirth, M.: Case study on the influence of synoptic-scale processes on the paired H2O-O3 distribution in the UTLS across a North Atlantic jet stream, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-692, accepted, 2022.