Atmospheric rivers (ARs) are recognized as significant contributors to extreme precipitation at mid-latitudes and may increase in frequency and intensity due to climate change. This timely study is the first the show the potential value of GNSS radio occultation (GNSS RO) remote sensing to the study of ARs and in particular how the high vertical resolution of GNSS RO provides information that is complementary to other techniques. The combination of GNSS-RO data with mesoscale models, particularly through assimilation, could further improve our understanding of AR dynamics and the processes leading to extreme precipitation and flooding. This is an important direction for future studies.

Accurate atmospheric measurements of ice nucleating particles (INPs) are needed for improving understanding of their role in affecting cloud properties and climate. Prior international workshops on comparing INP measuring systems were conducted mainly in the laboratory, where high concentrations of INPs were typically employed. This workshop established a template for the conduct of comparisons in an atmospheric setting where low number concentrations of INPs typically exist, representing a very small fraction of all particles. Overall, this study stimulates advances of important but challenging INP measurements and strengthens confidence in their use to understand ice formation in clouds.

The manuscript presents an approach for enabling direct flux measurements of greenhouse gases to already existing tall tower networks by simply adding a 3D sonic anemometer to each station. This way, the spatial information density about the land surface exchange and quantifying temporal sources and sinks of greenhouse gases would be significantly improved with little extra instrumental effort. Slower-response analyzers may be used for flux measurements as the relevant frequency ranges at tall towers differ from those closer to the land surface. Tall tower measurements have larger footprints than classical eddy-covariance ecosystem sites, which further amplify spatial coverage of observations. Still, detailed knowledge of surrounding footprints is needed. The presented concept is of high relevance within the scientific greenhouse gas community and may act as a blueprint for bridging scales between atmospheric and ecosystem networks.

I agree with the handling aditor that this is a very useful and comprehensive study and deserves wide attention.

I fully support the justification given by the handling editor

This is an important manuscript documenting performances of MethaneAIR imaging spectrometer for accurately measure emissions of CH4 from oil and gas production and processing facilities The MethaneAIR is a precursor of MethaneSAT, a small satellite intended to revolutionize measurements and modeling of emissions of CH4 at regional (100s of km) and fine scales (< 1 km), across the globe. Its deployment onboard the NSF Gulfsteam-V aircraft is an important step for validation and demonstration of MethaneSAT. The paper demonstrates the instrument's ability to quantify methane emission at various scale and concludes successfully the pre-launch validation phase of MethaneSat.

Air pollution is one of the greatest threats to human health, and many of the adverse health effects can be attributed to aerosols. In addition, aerosols play an important role in regulating climate, both through direct effects and through cloud formation. Aerosols can be detected using satellite-based instruments, but due to the broad range of characteristics and their variability in space and time, aerosol retrieval by remote sensing is not trivial. This highlight paper presents the combination of data from six satellite instruments that complement each other. Three of the satellites are in sun-synchronous orbits (observing the whole Earth once per day) and three in geo-stationary orbit (observing a portion of the Earth several times per hour). The paper shows that by combining data from the six instruments a high-quality, consistent data set can be created with a higher combined spatio-temporal resolution and less gaps than existing data sets. The freely available new aerosol data product is provided at 30 minute resolution and on a 0.25 degree grid in a format convenient for use in satellite studies or ingestion by models, providing data that will further advance the field of aerosol studies.

This manuscript provides a detailed overview of aerosol and cloud products to be expected from the upcoming EarthCARE mission. In documenting the basic steps of processing of the data from the ATLID instrument it will be a very valuable source of information for users of the resulting products.

Chemical ionization mass-spectrometry (CIMS) has been widely used in atmospheric chemistry research to detect oxygenated organic compounds. However, accurate quantification of species which do not have generic standards remains a major challenge for CIMS application, and semi-quantitative methods which have been developed to solve this dilemma usually have very large uncertainties. This work introduced a novel classification approach which greatly enhances the accuracy of semi-quantitative methods and effectively reduces their uncertainties. Although the approach was developed in this work specifically for toluene oxidation products, the concept can also be applied to other oxygenated organic compounds and may significantly enhance the quantification ability of CIMS.

Although the paper is very technical, I agree with the handling editor that this is an important paper and deserves broader awareness.

This is a very thorough quantification of uncertainties in hydrometeor retrieval from synergistic retrievals. This is rare (and difficult) both in that a thorough uncertainty analysis, and multi-sensor synergy retrievals, are both uncommon - let alone together. This analysis can be a pathfinder for this community and for others seeking to achieve similar goals. Uncertainty analyses are becoming increasingly important as sensors and retrievals improve, and as models are being more sophisticated about use of this information for assimilation or analysis.

Following the handling editor recommendation, the manuscript presents innovative analysis of a ground-based imaging experiment using a shortwave infrared spectral camera to quantify carbon dioxide (CO2) emissions from a coal-fired power plant. The innovation of the manuscript is to use low spectral resolution (7nm) imaging spectroscopy to measure CO2 plume structure and estimate emission amounts from chimneys by the ground-based observation. The methodology has potential important applications for fine-scale estimates of CO2 and other GHG emissions

This paper presents a detailed analysis about the methane emissions leakage event in the UK in 2023 by multiple approaches, which is highly available for the GHG emission, climate change, as well as the air quality communities, and highly concerned by the public and society.

This paper demonstrates that lidar CO₂ measurements can substantially complement current passive remote sensors by providing measurements above clouds and within cloud gaps. Furthermore, lidar provides data at high latitudes where spectroscopy suffers from low solar illumination and challenging albedo variations. This is of particular importance in the context of "Arctic amplification". The paper paves the way for future CO₂ and also CH₄ lidar measurements from satellites.

Tornadoes are having impact on peoples live and are in a general interest.

This is the first time showing that long-term polarization observations with a Doppler lidar are possible. Second, the methodology could be applied to other HALO lidars and thus expand the capabilities for observing atmospheric aerosol. Third: It shows that Finland (any maybe whole Scandinavia) is during summer time most of the time dominated by Pollen or other biogenic aerosol, something which is maybe attributed to the continental background class used in CALIPSO, and not yet fully understood.

This work validates retrievals from the latest operational version of the NASA Goddard Profiling Algorithm (GPROF), currently version 7, and it quantitatively demonstrates the performance improvements with respect to previous versions (GPROF v05) at various spatial and temporal resolutions. It also presents new, not yet operationally implemented, machine learning based versions of GPROF (GPROF-NN).

Aerosol properties are usually retrieved on scales of 300-1000m, which is more than enough considering the spatial variability of aerosols. However, a higher spatial resolution is needed in some specific cases (volcanic eruptions, technogenic catastrophes, dust storms, military operations, and industrial pollution). Various parameters of the aerosol plume are needed, including the direction of propagation, spatial coverage, plume height, chemical composition and microstructure parameters. Such information is required for practical applications, including population warning systems. This paper is one of the first studies retrieving aerosol properties using spaceborne PRISMA hyperspectral 30m spatial resolution measurements. It opens the way for developing automatic procedures for monitoring aerosol plumes. The hyperspectral instrumentation can also be installed on airborne platforms and used to monitor particulate matter and gaseous components of pollution plumes.

I agree with the reviewer's assessment

As the Editor states does this manuscript describe application of long-path absorption spectroscopy to detection of gas leak plumes. The technique uses an unmanned aerial vehicle (UAV) carrying a retroreflector as the endpoint of the absorption path, which allows for rapid discovery of plume location and quantification of plume cross section for emissions rate determination. The technique works at a safe standoff distance and through the use of the UAV doesn't need two fixed end locations. It would be of interest to many seeking to find and quantify gas leaks, which is important for safety and minimizing greenhouse gas and reactive gas emissions.

From the handling editor : I think this paper is of particular interest to the geoscience community (following peer review) though likely too arcane for broader public/media. There's been a lot of discussion of the potential for preferentially oriented dust particles and this has impacts for remote sensing and modeling. So this seems to be an important step towards real characterisation of them. I agree with the authors' provided comment here so reproduce it below: Atmospheric dust particles with irregular shapes may present a preferential orientation in the Earth's atmosphere. This alignment can be detected from the resulting dichroic extinction of the transmitted sunlight through the elevated dust layers. Since mineral dust is one of the most abundant atmospheric aerosols and plays a significant role to the radiative forcing of the global climate, the somewhat elusive observation of particle orientation will be a game changer to existing remote sensing measurement techniques and the implementation of particle dynamics in desert dust transport models. With our research, we utilize a specifically designed direct sun Solar Polarimeter (SolPol), installed and operated on a remote observatory in Greece, and report on unique observations of enhanced linear polarization during dust events. We aim to interpret our measurements as the first observations of atmospheric dust particle orientation by measuring direct sunlight.

Measuring water vapour in the UTLS region has been challenging for decades. The method presented here provides a breakthrough for future high precision measurements at the low concentrations and under the conditions found in the UTLS region. Such measurements are essential given the critical role of water vapour in this region for the Earth's radiative balance.

The study makes a substantial promise with direct benefits for the society at large.

The paper provides the general overview on the upcoming EarthCARE mission, which carries a unique suite of active and passive instruments for aerosol, cloud and radiation observations. It is thought to be the introductory paper for the AMT Special Issue "EarthCARE Level 2 algorithms and data products".

These are important first results of carbon monoxide from the GEO perspective which gives the diurnal variation of a critical atmospheric pollutant.

The paper introduces a machine learning based retrieval algorithm for Aura/MLS, which could lead to a major update of the Aura/MLS NRT L2 products.

This study evaluates many currently available conventional and polarimetric radar-based remote-sensing retrievals of ice water content, total number concentration and mean diameter of ice hydrometeors. It has the potential to become a reference for the assessment of measurement uncertainties from radar observations for which no in-situ reference data are available.

I agree with the handling editor that the technique described is a breakthrough in analytical capability with potential wide ranging applications.

I agree with the handling editor that this paper covers a very good study that would be a very useful for the community, especially for measurements of reactive gases.

I agree with the handling editor Dr. Laura Bianco and the reviewer Dr. Frank Beyrich that this is a very good paper and that it is of general interest and relevance.

Accurate detection and quantification of methane emissions are urgently needed for climate change mitigation. Multiple observations and measurement approaches can contribute to this challenge. This study shows how Sentinel-2 can provide useful coverage and spatial resolution for methane plumes, despite limited spectral sensitivity for methane absorption.

The manuscript gives exceptional good insight into true eddy accumulation.

Next to tackling the fundamental problem in the representativeness of point measurements of particles and retrieving the surface flux in a turbulent atmosphere, this manuscript provides a general framework to plan sampling strategies for aerosol field campaigns and provides tools to quantify related uncertainties.

This manuscript discusses the basis and uncertainties of the Aeolus mission performance and its improvement over time. Aeolus is a key ESA mission for atmospheric dynamics, greatly beneficial for numerical weather prediction and Earth system dynamics studies. The lessons learned in understanding and improving the atmospheric measurement technique described here will be of great importance for the Aeolus follow-on mission, now being planned by EUMETSAT and ESA in Europe.