In this paper we describe the implementation of an interpolation–prediction estimator applied to cloud properties derived from CloudSat observations. The objective is to evaluate the uncertainty associated with the estimated quantity. The model developed in this study can be valuable for satellite applications (GPS, telecommunication) as well as for cloud product comparisons. This paper is didactic and beneficial for anyone interested in kriging estimators.

This paper details laboratory-based and field developments of a cost-effective and compacted UAV CO₂ sensor system to address the challenge of measuring CO₂ with sufficient precision and acquisition frequency. We assess its performance extensively through laboratory and field tests and provide a case study in an urban area (Nicosia, Cyprus). We therefore expect that this portable system will be widely used for measuring CO₂ emission and distribution in natural or urban environments.

Aeolus is the first satellite that provides global wind profile measurements. The mission aims to improve the weather forecasts in the tropics, but also, potentially, in the polar regions. We evaluate the performance of the instrument over the Canadian North and the Arctic by comparing its measured winds in both cloudy and non-cloudy layers to wind data from forecasts, reanalysis, and ground-based instruments. Overall, good agreement was seen, but Aeolus winds have greater dispersion.

Water vapor absorption in the near-UV region is essential to describe the energy budget of Earth; however, there is little spectroscopic information available. And accurate near-UV water absorption is also required in both ground-based observations and satellite missions for trace gas species. Here, we provide the high-resolution spectra of water vapor around 415 nm measured with cavity ring-down spectroscopy. These absorption lines have never been experimentally verified before.

We describe our vibration-resistant instrument for measuring ambient NO₃, NO₂, and H₂O based on cavity-enhanced absorption spectroscopy. By simultaneous retrieval of H₂O with the other species using a measured H₂O absorption spectrum, direct quantifications among all species are possible without any pre-treatment for H₂O. Our instrument achieves the effective light path to ~101.5 km, which allows the sensitive measurements of NO₃ and NO₂ as 1.41 pptv and 6.92 ppbv (1σ) in 1 s.

NOAA’s Geostationary Extended Observations (GeoXO) constellation is planned to consist of an atmospheric composition instrument (ACX) to support air quality forecasting and monitoring. As design trade-offs are being studied, we investigated one parameter, the polarization sensitivity, which has yet to be fully documented for NO₂ retrievals. Our simulation study explores these impacts to inform the ACX’s development and better understand polarization’s role in trace gas retrievals.

A total of 2 years of dual-scan ground-based MAX-DOAS measurements of tropospheric NO₂ and aerosols in Uccle (Belgium) have been used to develop a new optimal-estimation-based inversion approach to retrieve horizontal profiles of surface NO₂ concentration and aerosol extinction profiles. We show that the combination of an appropriate sampling of TROPOMI pixels by ground-based measurements and an adequate a priori NO₂ profile shape in TROPOMI retrievals improves the agreement between datasets.

This investigation demonstrates how useful ionospheric parameters can be extracted from existing high-frequency radars that are used for oceanographic research. The methodology presented can be used by scientists and radio amateurs to understand ionospheric dynamics.

Retrieving high-precision concentrations of atmospheric trace gases from FTIR (Fourier transform infrared) spectrometry requires a precise knowledge of the instrumental performance. In this context, this paper examines the impact on the ozone (O₃) retrievals of several approaches used to characterise the instrumental line shape (ILS) function of ground-based FTIR spectrometers within NDACC (Network for the Detection of Atmospheric Composition Change).

Accurate long-term measurement of aerosol light absorption is vital for assessing direct aerosol radiative forcing. Light absorption by aerosols at the US Department of Energy long-term climate monitoring SGP site is measured using the Particle Soot Absorption Photometer (PSAP), which suffers from artifacts and biases difficult to quantify. Machine learning offers a promising path forward to correct for biases in the long-term absorption dataset at the SGP site and similar Class-I areas.

Our work investigates the behavior of errors in remote-sensing wind lidar measurements due to turbulence. Using a virtual instrument, we measured winds in simulated atmospheric flows and decomposed the resulting error. Dominant error mechanisms, particularly vertical velocity variations and interactions with shear, were identified in ensemble data over three test cases. By analyzing the underlying mechanisms, the response of the error behavior to further varying flow conditions may be projected.

HALO is a multi-functional lidar that measures CH₄ columns and profiles of H₂O mixing ratio and aerosol/cloud optical properties. HALO supports carbon cycle, weather dynamics, and radiation science suborbital research and is a technology testbed for future space-based differential absorption lidar missions. In 2019 HALO collected CH₄ columns and aerosol/cloud profiles during the ACT-America campaign. Here we assess HALO's CH₄ accuracy and precision compared to co-located in situ observations.

A rapid, sensitive, and precise analytical method was developed for measuring the fractional amounts of the (−) and (+) forms of chiral enantiomeric forms of monoterpenes in air containing biogenic plant emissions. The method uses passive air sampling onto adsorption–thermal desorption (ATD) gas sampling cartridge tubes; this is followed by automatable thermal desorption onto a chiral gas chromatography (GC) column, followed by detection with mass spectrometry (MS).