Cirrus evolution from nucleation to cloud breakup can be investigated with a novel classification scheme based on airborne lidar data. Applying it to a case study from the ML-CIRRUS campaign, we investigate the impact of large-scale dynamics and small-scale gravity lee waves on the detailed spatial distribution of evolution stages in individual clouds. Our scheme may help to gain more insights in optical and radiative properties of cirrus under various formation and life cycle conditions.

This paper presents retrieval results of NO₂ vertical column densities mapped at high spatial resolution over three Belgian cities, based on the DOAS analysis of Airborne APEX observations. A major objective of the study is to assess the technical and operational capabilities of the APEX hyperspectral pushbroom imager to map the NO₂ horizontal distribution field over urbanised areas.

The use of ground-based GNSS data for climate research is an emerging field. The reprocessing activity under EUREF has been a huge effort, generating homogeneous tropospheric products to be used as a data set for monitoring trends in atmospheric water vapour. EPN-Repro2 data have been evaluated against RS and ERA-Interim data as well as in terms of ZTD trends. The obtained results show that they can be used for ZTD trend detection over Europe in areas where other data are not available.

XPIA is a study held in 2015 at NOAA's Boulder Atmospheric Observatory facility, aimed at assessing remote-sensing capabilities for wind energy applications. We use well-defined reference systems to validate temperature retrieved by two microwave radiometers (MWRs) and virtual temperature measured by wind profiling radars with radio acoustic sounding systems (RASSs). Water vapor density and relative humidity by the MWRs were also compared with similar measurements from the reference systems.

We have developed an instrument which can be deployed on ships in the remote oceans to measure optical properties of the atmosphere. These optical properties are key to understanding how light and heat are transmitted, absorbed and reflected within the atmosphere. This has consequences for how the wider climate system works. The oceans, covering 70 % of the planet, are chronically under-sampled for such optical properties. Such instruments, when widely deployed, should help rectify this problem.

Wind turbines in the line of sight of a weather radar can have a negative impact on the quality of the radar's measurements. Wind turbine echoes have proven difficult to filter due to their complex and time-varying nature. In this work we present recordings of high-resolution low-level data from a Swedish weather radar. A characteristic and robust signature from wind turbines is found. A simple wind turbine filter is presented and applied to the recorded data.

The goal of the paper is to understand what the optimal cloud radar settings for drizzle detection are. The number of cloud radars in the world has increased in the last 10 years and it is important to develop strategies to derive optimal settings which can be applied to all radar systems. The study is part of broader research focused on better understanding the microphysical process of drizzle growth using ground-based observations.

We present a comparison of CO measurements performed with a portable OF-CEAS laser spectrometer against a high-performance gas chromatograph. For both surface and airborne measurements, the instruments show an excellent agreement very close to the 2 ppb World Meteorological Organization recommendation for CO inter-laboratory comparison. This work establishes that this laser technique allows for the development of sensitive, compact, robust and reliable instruments for in situ trace-gas analysis.

This study focused on the extraction of the atmospheric excess phases using the non-difference processing strategy. The COSMIC POD processing is used to accurately determine the position and velocity of the centre of mass of the satellite and the receiver offset based on PANDA software. Finally, the bending angle, refractive and dry temperature profiles are taken from AEP using ROPP software.

Knowing the size and elemental composition of airborne particles is necessary to understand their impact on human health. A widely used instrument for collecting size-segregated particles is the multi-orifice uniform deposit impactor (MOUDI). Laser ablation ICP-MS in imaging mode provided multi-elemental analysis of size-segregated particles with excellent sensitivity. The maps generated offered insights regarding the uniformity of the elemental distribution.

We present airborne remote sensing measurements of NO₂ in the urban area of Bucharest. NO₂ is a harmful pollutant, which is emitted in combustion processes. The measurements presented here enable the creation of maps, showing the horizontal NO₂ distribution across the whole city within a relatively short time window of 1.5 h. These data provide new insight into urban pollution levels and their spatial distribution.

Deterministic and probabilistic CI detection models based on decision trees (DT), random forest (RF), and logistic regression (LR) were developed using Himawari-8 AHI data obtained over the Korean Peninsula. We used a total of 12 interest fields including time trends to develop the models. We identified contributing variables for CI detection. DT showed a higher hit rate, while RF produced a higher critical success index. The mean lead times by the four models were in the range of 20–40 min.

This study applies horizontal concentration gradient measurements and inverse dispersion modelling to evaluate ammonia emissions from cattle grazing. The results can contribute to an emission factor for cattle grazing, where emissions where found to be towards the lower end of the range found in the limited number of existing studies. The influences of ammonia deposition, uneven urine patch distribution and climate conditions are discussed.

To know how air pollution moves away from their sources, we need to know the height of the pollution. We use a laser instrument that detects particles of air pollution to precisely measure the height of the particles. Now we want to detect the layer where the pollution is. As the height of this layer changes with time it is difficult to automatically follow the correct layer. Pathfinder, which works like route planners that find the shortest way, improves this task.

The accurate detection of reactive nitrogen species (NO_y) is key to understanding tropospheric ozone production. Typically, NO_y is detected by thermal conversion to NO₂, followed by NO₂ detection. Here, we assess the conversion efficiency of several NO_y species to NO₂ in a thermal dissociation cavity ring-down spectrometer and discuss how this conversion efficiency is affected by certain experimental conditions, such as oven residence time, and interferences from non-NO_y species.

The study presents the first systematic use of ground-based remote-sensing data from the Network for the Detection of Atmospheric Composition Change (NDACC) to validate satellite-based Measurements of Pollution in the Troposphere (MOPITT) total column carbon monoxide (CO). MOPITT generally shows low bias with respect to the ground-based instruments. The geographic and temporal dependence of validation results are determined. Our findings inform some recommendations for using MOPITT measurements.

The Ozone Monitoring Instrument (OMI) has been flying on NASA’s EOS Aura satellite since July 15, 2004. It has measured the concentration of trace gasses in the atmosphere, like ozone, NO₂ and SO₂. This article describes the trend in performance and calibration parameters of OMI during 12 years of flight. The degradation of the CCD detectors, solar diffusers, spectral calibration and row anomaly are shown. The instrument shows overall degradation that is better than expected.