This study introduces a novel method to detect horizontally oriented ice crystals (HOICs) using two ground-based polarization lidars at different zenith angles, based on a yearlong dataset collected in Beijing. Combined with cloud radar and reanalysis data, the fine categorization results reveal HOICs occur in calm winds and moderately cold temperatures and are influenced by turbulence near cloud bases. The results enhance our understanding of cloud processes and improve atmospheric models.

This study evaluates a remote calibration tool, referred to as MOment MAtching (MOMA), for calibrating PurpleAir PM_2.5 sensors, especially for varying PM sources, and compares it with the Environmental Protection Agency (EPA) correction. MOMA improved the accuracy of PurpleAir sensor data comparable to the EPA correction. Although reliant on nearby reference sites, MOMA offers valuable insights into potential PM sources, thereby increasing the overall value of PurpleAir sensor networks.

TanSat-2 is designed for global carbon monitoring, offering high-resolution dual-band observations of solar-induced chlorophyll fluorescence – a key indicator of photosynthesis. Simulations show its data processing can retrieve fluorescence with high accuracy. These results suggest TanSat-2 will enhance global tracking of the carbon cycle and vegetation health, providing valuable insights for climate change research.

We present an analysis of high-resolution remote sensing measurements of nitrogen-containing trace gases emitted by wildfires. The measurements were made using an instrument on the NASA ER-2 aircraft in the summer of 2019. We find that time-resolved fire intensity is critical to quantify trace gas emissions over a fire's entire lifespan. These findings have implications for improving air pollution forecasts downwind of wildfires using computer models of atmospheric chemistry and meteorology.

Clumped-isotope signals obtained through gas source mass spectrometry are typically small and require pressure baseline corrections. While such corrections have been developed for square-shaped peaks, we present an approach for correcting peaks with complex shapes. Our method is demonstrated using oxygen clumped isotopes measured in pure oxygen, where the peak tops are linearly increasing and/or negatively curved.

Simulations of storm characteristics and associated radar signatures were improved, especially under the freezing level, using an advanced cloud scheme. Discrepancies between observations and forecasts at and above the melting layer highlighted issues in both the radar forward operator and the microphysics. To overcome some of these issues, different parameterizations of the operator were suggested. This work aligns with the future integration of polarimetric data into assimilation systems.

The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over Asia, e.g., NO₂. GEMS provides hourly data, improving the time resolution compared to the daily overpasses by other satellites. For the prediction of hourly surface NO₂ over South Korea from GEMS observations and meteorological data, this study shows that machine learning models benefit from this higher time resolution. This is achieved by using observations from previous hours as additional inputs.

This study analyzed NaCl and CaCl₂ powder-type hygroscopic materials for cloud seeding, using the Korea Cloud Physics Experimental Chamber (K-CPEC) in South Korea. The aerosol chamber enabled particle analysis in an extremely dry environment, while the cloud chamber, with precise pressure and temperature control, facilitated droplet growth through quasi-adiabatic expansion. Our study provides valuable insights for the development of new seeding materials and advanced cloud seeding experiments.

Nitryl chloride (ClNO₂) is a reservoir of chlorine atoms and nitrogen oxides, both of which play important roles in atmospheric chemistry. However, all ambient ClNO₂ observations so far have been made by a single technique, mass spectrometry, which needs complex calibrations. Here, we present a laser-based method that detects ClNO₂ (TD-TILDAS – thermal dissociation–tunable infrared laser direct absorption spectrometry) without the need for complicated calibrations. The results show excellent agreement between these two methods from both laboratory and ambient samples.

One important property of a cloud is the concentration of cloud drops. This property is relevant to how the cloud interacts with sunlight and how easily the cloud forms precipitation. Measuring this property from satellite observations is one important source of data, but it does require making some assumptions. This study evaluates the accuracy of satellite-derived drop concentration by a comparison with aircraft measurements.

The topic is finding methods to extend climate data records from single-instrument satellite observations, in this case the Advanced Very High Resolution Radiometer (AVHRR). Several modern instruments include AVHRR-heritage channels, but some corrections are necessary to account for some differences. We have simulated AVHRR data from the Visible Infrared Imaging Radiometer Suite (VIIIRS) sensor on National Oceanic and Atmospheric Administration (NOAA) polar satellites. We find that methods based on machine learning are capable of performing these corrections.

This study presents a data processing scheme for the detection and quantification of methane emissions using the MethaneAIR airborne spectrometer. We show that the proposed methods enable the detection of smaller plumes (compared with those detectable using other existing methods) and improve the potential of MethaneAIR to survey methane point sources across large regions.

The study highlights how aerosol measurements from aircraft can be used in synergy with ground-based observations to validate the European Space Agency's Aeolus satellite aerosol product above the tropical Atlantic. For the first time, collocated sections of the troposphere up to 626 km long are crossed. Combining measurements from satellite, aircraft, and ground-based instruments allows characterization of the optical properties of the observed dust particles emitted from the Sahara.