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Model-based climatology of diurnal variability in stratospheric ozone as adata analysis tool

We use the NASA GEOS-GMI chemistry climate model to construct a climatology of stratospheric ozone diurnal variations as a function of latitude, pressure and month, which can be used in a variety of data analysis tasks involving ozone observations made at different times of the day. The climatology compares well with previous modeling simulations and available observations, and to the authors’ knowledge is the first characterization of the diurnal cycle available for general ozone data analyses.

Simultaneous measurements of the relative-humidity-dependent aerosol lightextinction, scattering, absorption, and single-scattering albedo with ahumidified cavity-enhanced albedometer

We report the first demonstration of a humidified cavity-enhanced albedometer (H-CEA) that combines a broadband cavity-enhanced aerosol albedometer with a humidigraph system for simultaneous and accurate measurements of multiple optical hygroscopic parameters ( f (RH)ext,scat,abs,ω) at λ = 532 nm. The instrument is suitable for operating under high RH-conditions and has sampling advantages over independent measurements of different parameters with different instruments.

Microwave and submillimeter wave scattering of oriented ice particles

Microwave dual-polarization observations consistently show that larger atmospheric ice particles tend to have a preferred orientation. We provide a publicly available database of microwave and submillimeter wave scattering properties of oriented ice particles based on discrete dipole approximation scattering calculations. Detailed radiative transfer simulations, recreating observed polarization patterns, are additionally presented in this study.

A machine-learning-based cloud detection and thermodynamic-phaseclassification algorithm using passive spectral observations

A machine-learning (ML)-based approach that can be used for cloud mask and phase detection is developed. An all-day model that uses infrared (IR) observations and a daytime model that uses shortwave and IR observations from a passive instrument are trained separately for different surface types. The training datasets are selected by using reference pixel types from collocated space lidar. The ML approach is validated carefully and the overall performance is better than traditional methods.

Intercomparison of wind observations from the European Space Agency’s Aeolus satellite mission and the ALADIN Airborne Demonstrator

This work reports on the first airborne validation campaign of ESA’s Earth Explorer mission Aeolus, conducted in central Europe during the commissioning phase in November 2018. After presenting the methodology used to compare the data sets from the satellite, the airborne wind lidar and the ECWMF model, the wind results from the underflights performed are analyzed and discussed, providing a first assessment of the accuracy and precision of the preliminary Aeolus wind data.

ALADIN Airborne Demonstrator">Read more

Real-time pollen monitoring using digital holography

We present the first validation of the only operational automatic pollen monitoring system based on holography, the Swisens Poleno. The device produces real-time images of coarse aerosols, and by applying a machine learning algorithm we identify a range of pollen taxa with accuracy >90 %. The device was further validated in controlled chamber experiments to verify the counting ability and the performance of additional fluorescence measurements, which can further be used in pollen identification.

Quantifying hail size distributions from the sky – application of drone aerial photogrammetry

Collecting measurements of hail size and shape is difficult due to the infrequent and dangerous nature of hailstorms. To improve upon this, a new technique called HailPixel is introduced for measuring hail using aerial imagery collected by a drone. A combination of machine learning and computer vision methods is used to extract the shape of thousands of hailstones from the aerial imagery. The improved statistics from the much larger HailPixel dataset show significant benefits.

First data set of H2O/HDO columns from the Tropospheric Monitoring Instrument (TROPOMI)

This paper presents a new H ₂ O/HDO data set from TROPOMI short-wave infrared measurements. It is validated against recent ground-based FTIR measurements from the TCCON network. A bias in TCCON HDO (which is not verified) is corrected by fitting a correction factor for the HDO column to match MUSICA δD for common observations. The use of the new TROPOMI data set is demonstrated using a case study of a blocking anticyclone over Europe in July 2018.

TROPOMI)">Read more

Low-temperature triple-capillary cryostat for ice crystal growth studies

We have built a triple-capillary cryostat designed to reduce potential instrumental effects that may have influenced earlier measurements and to improve our understanding of the processes responsible for ice crystal shapes and sizes. In this cryostat, a crystal forms on one of three well-separated and ultrafine capillaries. In this paper we describe the new instrument and present several observations made using the instrument to illustrate the instrument’s advantages.

Description of a formaldehyde retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS)

The Geostationary Environment Monitoring Spectrometer (GEMS) will be launched by South Korea in 2019, and it will measure radiances ranging from 300 to 500 nm every hour with a fine spatial resolution of 7 km x 8 km over Seoul in South Korea to monitor column concentrations of air pollutants including O₃, NO₂, SO₂, and HCHO, as well as aerosol optical properties. This paper describes a GEMS formaldehyde retrieval algorithm including a number of sensitivity tests for algorithm evaluation.

GEMS)">Read more

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