Martin Wirth

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).

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).

Cirrus clouds in the Arctic play a central role in the regional radiation budget, yet their formation pathways and properties remain poorly constrained, especially during Warm Air Intrusions (WAI). In this study, we analyse and contrast cirrus observed during WAI events (WAI cirrus) with those formed under undisturbed Arctic Conditions (AC cirrus) using remote sensing measurements from the HALO–(AC)³ campaign, combined with backward trajectory modelling with CLaMS-Ice and LAGRANTO. This allows us to connect the optical, macro- and microphysical properties measured via lidar and radar to the cloud origin and dynamics during their evolution. We find that WAI cirrus encountered stronger vertical transport along their trajectories compared to AC cirrus. At the time of detection, WAI cirrus were geometrically and optically thicker, exhibited higher depolarization ratios and ice supersaturation, and contained more numerous but smaller ice crystals, consistent with homogeneous ice nucleation at colder temperatures. AC cirrus, in contrast, showed larger ice crystals and a comparably greater contribution from heterogeneous ice nucleation. As WAI events are projected to become more frequent and long-lasting, a resulting increase in the formation of WAI cirrus may enhance their influence on the Arctic radiation budget leading to cooling. Our results provide observational constraints on cirrus variability in the Arctic and emphasize the need for their improved representation in weather and climate models.

Cirrus clouds in the Arctic play a central role in the regional radiation budget, yet their formation pathways and properties remain poorly constrained, especially during Warm Air Intrusions (WAI). In this study, we analyse and contrast cirrus observed during WAI events (WAI cirrus) with those formed under undisturbed Arctic Conditions (AC cirrus) using remote sensing measurements from the HALO–(AC)³ campaign, combined with backward trajectory modelling with CLaMS-Ice and LAGRANTO. This allows us to connect the optical, macro- and microphysical properties measured via lidar and radar to the cloud origin and dynamics during their evolution. We find that WAI cirrus encountered stronger vertical transport along their trajectories compared to AC cirrus. At the time of detection, WAI cirrus were geometrically and optically thicker, exhibited higher depolarization ratios and ice supersaturation, and contained more numerous but smaller ice crystals, consistent with homogeneous ice nucleation at colder temperatures. AC cirrus, in contrast, showed larger ice crystals and a comparably greater contribution from heterogeneous ice nucleation. As WAI events are projected to become more frequent and long-lasting, a resulting increase in the formation of WAI cirrus may enhance their influence on the Arctic radiation budget leading to cooling. Our results provide observational constraints on cirrus variability in the Arctic and emphasize the need for their improved representation in weather and climate models.

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 surface moisture flux is a large term in the surface energy balance and difficult to estimate remotely. The main difficulty for its remote estimation is a poor ability to measure near-surface humidity. Current methods to retrieve near-surface specific humidity approach the problem statistically and have errors of approximately 1 g kg ⁻¹ even in global, annual averages. Using extensive measurements from the EUREC ⁴ A field campaign (ElUcidating the RolE of Cloud-Circulation Coupling in Climate), we demonstrate that remote sensing measurements of cloud base height can provide useful estimates of near-surface humidity over convective oceanic regions where optically-thick clouds do not prevent lidar sampling. First applying the method to 171 coincident radiosonde and ceilometer pairings collected from a research vessel from 18 January to 14 February 2020 yields skillful predictions of near-surface specific humidity regarding the mean (mean bias 0.43 g kg ⁻¹ compared to observed) and its variability ( r =0.76). We then apply this method using an airborne lidar to estimate cloud base height from above. In two representative case studies, we find similar skill in the predicted humidity, with low mean biases (0.04 and −0.06 g kg ⁻¹ compared to observed) with substantial variability captured ( r =0.61 and r =0.57, respectively). Besides estimates of cloud base height, we highlight two main error sources: (i) the relative humidity lapse rate below cloud base and (ii) the temperature difference between the sea surface and near-surface air, which would need to be calibrated if using this method to develop an operational product to estimate the near-surface specific humidity from downward-looking spaceborne lidar. This proof of concept raises the potential for application over convective oceanic regions where lidar sampling of cloud base is possible. This method could provide a physics-based augmentation to existing, more empirical approaches and therefore provide an additional observational constraint on the surface energy budget.

The Earth Cloud, Aerosol, and Radiation Explors (EarthCARE) satellite mission aims to improve our understanding of cloud–aerosol–radiation interactions in the Earth's climate system. Its Atmospheric Lidar (ATLID) instrument aboard EarthCARE provides important observational data for determining the properties of clouds and aerosols; therefore, thorough validation of ATLID products is a prerequisite for their reliable scientific use. This study evaluates the reliability of selected parameters applicable to study cloud macrophysical properties of three ATLID single-sensor Level 2 products: The “simple classification” of the ATLID Target Classification (A-TC) product, the “feature mask” of the ATLID Feature Mask (A-FM) product, and the “cloud top height” of the ATLID Cloud Top Height (A-CTH) product. We present an independent validation using a comprehensive multi-campaign dataset of airborne high spectral resolution lidar (HSRL) backscatter ratio (BSR) measurements. During each flight at least one coordinated underpass underneath EarthCARE was conducted ensuring high spatial and temporal matching of the spaceborne and airborne lidars. The dataset spans a wide range of tropical and extratropical cloud regimes, enabling robust assessment under diverse atmospheric conditions. The evaluation addresses two main objectives: (i) assessing how well A-TC and A-FM represent the vertical cloud distribution compared to the airborne HSRL observations, and (ii) quantifying the accuracy of A-CTH cloud top heights for different classes of cloud regimes. In general, the vertical cloud distribution observed from the airborne data is well captured by both A-TC and A-FM. However, we found a systematic overestimation of ice cloud pixels by A-TC in Baseline BA. This overestimation is caused by ice clouds that are horizontally and vertically too large, but also, to a certain extent, by aerosol pixels incorrectly classified as ice clouds (at temperature > 0 °C), and to a spurious occurrence of stratospheric aerosol features near the tropopause. A-TC liquid clouds are in very good agreement with the airborne observations. A-CTH exhibits a consistent positive bias in cloud top height of almost 300 m across different cloud regimes, along with occasional low-altitude cloud top detections, particularly over ocean surfaces, suggesting issues in surface assignment. The presented results primarily reflect Baseline BA, while first comparisons with Baseline BC/BD indicate improvements in future processing baselines, including a reduction of low-cloud artefacts in A-CTH, improved cloud phase representation in A-TC, and a strong reduction of misclassified ice clouds in aerosol layers at temperatures > 0 °C. Altogether, the validated ATLID Level 2 products demonstrate a high ability to realistically represent key macrophysical cloud properties – including cloud cover and cloud top height – which confirms their suitability for scientific applications. The identified limitations in the performance of the BA and BC baselines can help users make optimal use of these datasets, point to expected improvements in the upcoming CA baseline, and may support the further refinement of the ATLID Level 2 products.

Cirrus clouds in the Arctic play a central role in the regional radiation budget, yet their formation pathways and properties remain poorly constrained, especially during Warm Air Intrusions (WAI). In this study, we analyse and contrast cirrus observed during WAI events (WAI cirrus) with those formed under undisturbed Arctic Conditions (AC cirrus) using remote sensing measurements from the HALO–(AC)³ campaign, combined with backward trajectory modelling with CLaMS-Ice and LAGRANTO. This allows us to connect the optical, macro- and microphysical properties measured via lidar and radar to the cloud origin and dynamics during their evolution. We find that WAI cirrus encountered stronger vertical transport along their trajectories compared to AC cirrus. At the time of detection, WAI cirrus were geometrically and optically thicker, exhibited higher depolarization ratios and ice supersaturation, and contained more numerous but smaller ice crystals, consistent with homogeneous ice nucleation at colder temperatures. AC cirrus, in contrast, showed larger ice crystals and a comparably greater contribution from heterogeneous ice nucleation. As WAI events are projected to become more frequent and long-lasting, a resulting increase in the formation of WAI cirrus may enhance their influence on the Arctic radiation budget leading to cooling. Our results provide observational constraints on cirrus variability in the Arctic and emphasize the need for their improved representation in weather and climate models.

The Earth Cloud, Aerosol, and Radiation Explors (EarthCARE) satellite mission aims to improve our understanding of cloud–aerosol–radiation interactions in the Earth’s climate system. The Atmospheric Lidar (ATLID) instrument aboard EarthCARE provides important observational data for determining the properties of clouds and aerosols; therefore, thorough validation of ATLID products is a prerequisite for their reliable scientific use. This study evaluates the reliability of selected parameters applicable to study cloud macrophysical properties of three ATLID single-sensor Level 2 products: The ‘simple classification’ of the ATLID Target Classification (A-TC) product, the ‘feature mask’ of the ATLID Feature Mask (A-FM) product, and the ‘cloud top height’ of the ATLID Cloud Top Height (A-CTH) product. We present an independent validation using a comprehensive multi-campaign dataset of airborne high spectral resolution lidar (HSRL) backscatter ratio (BSR) measurements. During each flight at least one coordinated underpass underneath EarthCARE ground track was conducted ensuring high spatial and temporal matching of the spaceborne and airborne lidars. The dataset spans a wide range of tropical and extratropical cloud regimes, enabling robust assessment under diverse atmospheric conditions. The evaluation addresses two main objectives: (i) assessing how well A-TC and A-FM represent the vertical cloud distribution compared to the airborne HSRL observations, and (ii) quantifying the accuracy of A-CTH cloud top heights for different classes of cloud regimes. In general, the vertical cloud distribution observed from the airborne data is well captured by both A-TC and A-FM products. However, we found a systematic overestimation of ice clouds by A-TC in Baseline BA. This overestimation is related to spreading effects in the retrieval, but also to some extent to misclassified aerosol pixels as ice clouds (at temperatures >0 °C), and to a spurious occurrence of stratospheric aerosol features near the tropopause. A-TC liquid cloud fractions show very good agreement with airborne observations. A-CTH exhibits a consistent positive bias in cloud top height of almost 300 m across different cloud regimes, along with occasional low-altitude cloud top detections, particularly over ocean surfaces, suggesting issues in surface assignment. The presented results primarily reflect Baseline BA, while first comparisons with Baseline BC and a prototype version of Baseline CA indicate improvements in future processing baselines, including a reduction of low-cloud artefacts in A-CTH, improved cloud phase representation in A-TC, and a strong reduction of misclassified ice clouds in aerosol layers at temperatures >0 °C. Altogether, the validated ATLID Level 2 products demonstrate a high ability to realistically represent key macrophysical cloud properties—including cloud cover and cloud top height—which confirms their suitability for scientific applications. The identified limitations in the performance of the BA and BC baselines can help users make optimal use of these datasets, point to expected improvements in the upcoming CA baseline, and may support the further refinement of the ATLID Level 2 products.

The Earth Cloud, Aerosol, and Radiation Explors (EarthCARE) satellite mission aims to improve our understanding of cloud–aerosol–radiation interactions in the Earth’s climate system. The Atmospheric Lidar (ATLID) instrument aboard EarthCARE provides important observational data for determining the properties of clouds and aerosols; therefore, thorough validation of ATLID products is a prerequisite for their reliable scientific use. This study evaluates the reliability of selected parameters applicable to study cloud macrophysical properties of three ATLID single-sensor Level 2 products: The ‘simple classification’ of the ATLID Target Classification (A-TC) product, the ‘feature mask’ of the ATLID Feature Mask (A-FM) product, and the ‘cloud top height’ of the ATLID Cloud Top Height (A-CTH) product. We present an independent validation using a comprehensive multi-campaign dataset of airborne high spectral resolution lidar (HSRL) backscatter ratio (BSR) measurements. During each flight at least one coordinated underpass underneath EarthCARE ground track was conducted ensuring high spatial and temporal matching of the spaceborne and airborne lidars. The dataset spans a wide range of tropical and extratropical cloud regimes, enabling robust assessment under diverse atmospheric conditions. The evaluation addresses two main objectives: (i) assessing how well A-TC and A-FM represent the vertical cloud distribution compared to the airborne HSRL observations, and (ii) quantifying the accuracy of A-CTH cloud top heights for different classes of cloud regimes. In general, the vertical cloud distribution observed from the airborne data is well captured by both A-TC and A-FM products. However, we found a systematic overestimation of ice clouds by A-TC in Baseline BA. This overestimation is related to spreading effects in the retrieval, but also to some extent to misclassified aerosol pixels as ice clouds (at temperatures >0 °C), and to a spurious occurrence of stratospheric aerosol features near the tropopause. A-TC liquid cloud fractions show very good agreement with airborne observations. A-CTH exhibits a consistent positive bias in cloud top height of almost 300 m across different cloud regimes, along with occasional low-altitude cloud top detections, particularly over ocean surfaces, suggesting issues in surface assignment. The presented results primarily reflect Baseline BA, while first comparisons with Baseline BC and a prototype version of Baseline CA indicate improvements in future processing baselines, including a reduction of low-cloud artefacts in A-CTH, improved cloud phase representation in A-TC, and a strong reduction of misclassified ice clouds in aerosol layers at temperatures >0 °C. Altogether, the validated ATLID Level 2 products demonstrate a high ability to realistically represent key macrophysical cloud properties—including cloud cover and cloud top height—which confirms their suitability for scientific applications. The identified limitations in the performance of the BA and BC baselines can help users make optimal use of these datasets, point to expected improvements in the upcoming CA baseline, and may support the further refinement of the ATLID Level 2 products.