This paper describes the algorithm for O₃ and SO₂ retrievals from DSCOVR EPIC. Algorithm advances, including the improved O₃ profile representation and the regulated direct fitting inversion technique, improve the accuracy of O₃ and SO₂ from the multi-channel measurements of DSCOVR EPIC. A thorough error analysis is provided to quantify O₃ and SO₂ retrieval uncertainties due to various error sources and simplified algorithm physics treatments.

GRUAN data products (GDPs) from Meisei iMS-100 and Vaisala RS92 were compared with 59 dual sounding data. For daytime observations, the iMS-100 temperature is around 0.5 K lower than RS92-GDP in the stratosphere, but for nighttime observations, the difference is around −0.1 K, and data are mostly in agreement. For relative humidity (RH), iMS-100 is around 1–2 % RH higher in the troposphere and 1 % RH smaller in the stratosphere than RS92, but both GDPs are in agreement for most of the profile.

This paper characterizes the uncertainties affecting the ozone profiles retrieved at the University of Bremen through OMPS limb satellite observations. An accurate knowledge of the uncertainties is relevant for the validation of the product and to correctly interpret the retrieval results. We investigate several sources of uncertainties, estimate a total random and systematic component, and verify the consistency of the combined OMPS-MLS total uncertainty.

The CO₂ concentration in a cylinder is affected by carbon dioxide (CO₂) adsorption to a cylinder’s internal surface and fractionation of CO₂ and air in the preparation of standard mixtures. We demonstrate that the effects make the CO₂ molar fractions deviate in standard mixtures prepared by diluting pure CO₂ with air three times. This means that CO₂ standard gases are difficult to gravimetrically prepare through multistep dilution.

Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret, aggregate and utilise the data.

The NYS Mesonet Profiler Network is comprised of 17 profiler sites, each equipped with a Doppler lidar, microwave radiometer, and sun photometer. This study presents a multi-year, multi-station evaluation based on well-defined reference measurements. Results demonstrate robust technologies that can aid real-time weather operations and a network test bed that can be used for further expansion, evaluation, and integration of such technologies at a large scale.

Under warmer global temperatures, precipitation patterns are expected to shift substantially, with critical impact on the global water-energy budget. In this work, we develop a deep learning model for predicting snow and rain accumulation based on surface radar observations of the lower atmosphere. Our model demonstrates improved skill over traditional methods and provides new insights into the regions of the atmosphere that provide the most significant contributions to high model accuracy.

We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.

This study deals with the dynamic error estimates of the aerosol-retrieved properties by the GRASP algorithm, which are provided for directly retrieved and derived parameters. Moreover, GRASP provides full covariance matrices that appear to be a useful approach for optimizing observation schemes and retrieval set-ups. The validation of the retrieved dynamic error estimates is done through real and synthetic measurements using sun photometer and lidar observations.

We develop a new algorithm to get the vertical mass concentration profiles of fine aerosol components based on the synergy of ground-based remote sensing for the first time. The comparisons with in situ observations and chemistry transport models validate the performance of the algorithm. Uncertainties caused by input parameters are also assessed in this paper. We expected that the algorithm can provide a new idea for lidar inversion and promote the development of aerosol component profiles.

We use a global atmospheric chemistry model simulation to generate scaling factors that account for the daily cycle of NO₂ and ozone. These factors facilitate comparisons between sunrise and sunset observations from SAGE III/ISS and observations from other instruments. We provide the scaling factors as monthly zonal means for different latitudes and altitudes. We find that applying these factors yields more consistent comparisons between observations from SAGE III/ISS and other instruments.

Satellite observations are important for monitoring changes in atmospheric composition. Here we describe an improved version of the NO₂ retrieval for the Optical Spectrograph and InfraRed Imager System. The resulting NO₂ profiles are compared to those from the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer and the Stratospheric Aerosol and Gas Experiment III on the International Space Station. All datasets agree within 20 % throughout the stratosphere.

In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.

A new bubble-generating glass chamber design with an extensive set of aerosol production experiments is presented to re-evaluate bubble-bursting-mediated aerosol production as a function of water parameters: bubbling air flow, water salinity, and temperature. Our main findings suggest modest dependence of aerosol production on the water salinity and a strong dependence on temperature below ~ 10 °C.

3D cloud envelope and development velocity are retrieved from realistic simulations of multi-view CLOUD (C3IEL) images. Cloud development velocity is derived by finding matching features between acquisitions separated by 20 s. The tie points are then mapped from image to space via 3D reconstruction of the cloud envelope obtained from 2 simultaneous images. The retrieved cloud topography as well as the velocities are in good agreement with the estimates obtained from the physical models.

This paper provides a new way to estimate uncertainties and error correlations. The method is a generalization of a known method called the three-cornered hat: Instead of calculating uncertainties from assumed knowledge about the observation method, uncertainties and error correlations are estimated statistically from tree independent observation series, measuring the same variable. The results are useful for future estimation of atmospheric-specific humidity from the bending of radio waves.