This article presents a novel technique to estimate liquid water content (LWC) profiles in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.

In the Observed Composition Trends And Variability in the UTLS (OCTAV-UTLS) Stratosphere-troposphere Processes And their Role in Climate (SPARC) activity, we have mapped multiplatform ozone datasets into coordinate systems to systematically evaluate the influence of these coordinates on binned climatological variability. This effort unifies the work of studies that focused on individual coordinate system variability. Our goal was to create the most comprehensive assessment of this topic.

This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.

This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.

In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA²RSE) campaign.

This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.

The 2022 Hunga Tonga eruption injected a large amount of water into the stratosphere. Ozone depletion was observed inside the volcanic plume. Chlorine and water vapor injected by this eruption exceeded the normal range, which made the ozone chemistry during this event occur at a higher temperature than polar ozone depletion. Unlike polar ozone chemistry where chlorine nitrate is more important, hypochlorous acid plays a large role in the in-plume chlorine balance and heterogeneous processes.

In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.

The determination of atmospheric composition trends in the upper troposphere and lower stratosphere (UTLS) is still highly uncertain. We present the creation of dynamical diagnostics to map several ozone datasets (ozonesondes, lidars, aircraft, and satellite measurements) in geophysically based coordinate systems. The diagnostics can also be used to analyze other greenhouse gases relevant to surface climate and UTLS chemistry.

The algorithm that produces the near-real-time data products of the Aura Microwave Limb Sounder has been updated. The new algorithm is based on machine learning techniques and yields data products with much improved accuracy. It is shown that the new algorithm outperforms the previous versions, even when it is trained on only a few years of satellite observations. This confirms the potential of applying machine learning to the near-real-time efforts of other current and future mission concepts.

The upper troposphere–lower stratosphere is one of the most variable regions in the atmosphere. To improve our understanding of water vapour and ozone concentrations in this region, climatologies have been developed from 14 years of measurements from three Canadian satellite instruments. Horizontal and vertical coordinates have been chosen to minimize the effects of variability. To aid in analysis, model simulations have been used to characterize differences between instrument climatologies.

We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.

We analyze satellite-derived distributions of chlorine monoxide (ClO) and hypochlorous acid (HOCl) in the upper atmosphere. For 2005–2020, from 50°S to 50°N and over ~30 to 45 km, ClO and HOCl decreased by −0.7 % and −0.4 % per year, respectively. A detailed model of chemistry and dynamics agrees with the results. These decreases confirm the effectiveness of the 1987 Montreal Protocol, which limited emissions of chlorine- and bromine-containing source gases, in order to protect the ozone layer.

Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that smears 2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is towards or away from the Sun, so calculating across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.

The Microwave Limb Sounder (MLS), an instrument on NASA's Aura mission launched in 2004, measures vertical profiles of the temperature and composition of Earth's "middle atmosphere" (the region from ~12 to ~100 km altitude). We describe how, among the 16 trace gases measured by MLS, the measurements of water vapor (H₂O) and nitrous oxide (N₂O) have started to drift since ~2010. The paper also discusses the origins of this drift and work to ameliorate it in a new version of the MLS dataset.

This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.