Due to the complex spatiotemporal and physical properties of clouds, their quantitative depictions in different atmospheric reanalysis datasets are still highly uncertain. A radiance-based evaluation approach is developed to evaluate the quality of cloud properties by directly comparing them with satellite radiance observations. ERA5 and CRA are found to have great capability in representing the cloudy atmosphere over East Asia, and MERRA-2 tends to slightly overestimate clouds over the region.

The prime source of the temperature sensitivity of Z_DR can be attributed to the antenna assembly. This result is based on over 2000 solar box scans. These data also reveal that there is a 0.6 dB decrease in gain for a 10 °C temperature increase, which directly relates to a bias of the radar reflectivity factor Z, which has not been not accounted for previously. The Z_DR variability in and Z_DR calibration performance of the German weather radar network are shown.

This paper shows the importance of the nature of the aerosol phase function used in the retrieval of the stratospheric aerosol extinction from limb scattering measurements. The aerosol phase function is derived from the parameters using either a unimodal lognormal or gamma aerosol size distribution. These two distributions were fitted to the same aerosol concentration measurements at two altitudes, and depending on the nature of the measurements, each distribution shows its strengths.

The reliability of remotely sensed cloud variables from space depends on the horizontal resolution of the instrument. This study presents and evaluates several candidate approaches for increasing the spatial resolution of observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) from the native 3 km scale to a horizontal resolution of 1 km. It is shown that uncertainties in the derived cloud products can be significantly mitigated by applying an appropriate downscaling scheme.

Cirrus clouds consist of crystals (plates, needles) that can orient themselves in space as a result of free fall. This leads to the appearance of various types of optical halo and to specular reflection of solar radiation. The presence of such particles significantly affects the passage of thermal radiation through the mid- and high-level ice clouds. Using the properties of polarization, a scanning lidar makes it possible to identify cloud areas with oriented crystals.

Here, we evaluate a ground-based remote sensing method (MAX-DOAS) for measuring total pollutant loading and vertical profiles of pollution in the lower atmosphere by comparing our method to a variety of other measurement methods (lidar, sunphotometer, active DOAS, and aircraft measurements). Measurements were made in the Athabasca Oil Sands Region in Alberta, Canada. The complex dataset provided a rare opportunity to evaluate the performance of MAX-DOAS under varying atmospheric conditions.

The procedure for preparing electrochemical concentration cell (ECC) ozonesondes are considered to be standardized, but there remains the question of actual measurement accuracy, believed to be 5–10 %. It would be ideal to include a reference instrument on the balloon flight to aid in checking ECC accuracy and reliability. Balloon-borne reference instruments are not usually available, mostly because they are too expensive for other than occasional use.

The paper addresses the need for automatic quality control of a whole series of Earth observation (EO) time series extending a period of over 40 years. Such a dataset is valuable and may provide important information about trends related to geo-physical processes. Furthermore, as the dataset is that large, there is a need to completely automate the processes, as otherwise the effort would become impracticable. The result is a system with a high probability of detection and low false alarm rate.

There is considerable interest in using low-cost optical particle counters (OPCs) for particle mass measurements; however, there is no agreed upon method with respect to calibration. Here we exploit a number of datasets globally to demonstrate that particle composition and relative humidity are the key factors affecting measured concentrations from a low-cost OPC, and we present a simple correction methodology that corrects for this influence.

This study analyzed the aerosol optical properties derived by SKYRAD.pack versions 5.0 and 4.2 using the radiometer measurements over Qionghai and Yucheng in China, which are two new sites of SKYNET. The seasonal variability of the aerosol properties over the two sites were investigated based on SKYRAD.pack V5.0. The validation results provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks.

A novel gap-filling method called the diurnal-cycle-constrained empirical orthogonal function (DCCEOF) is proposed. Cross validation indicates that this method gives high accuracy in predicting missing values in daily PM_2.5 time series by accounting for the local diurnal phases, especially by reconstructing daily extrema that cannot be accurately restored by other approaches. The DCCEOF method can be easily applied to other data sets because of its self-consistent capability.

Modern weather radars are sensitive for properties of precipitating snow particles, such as their sizes, shapes and number concentration. Vertical profiles of such radar measurements can be used for studying the processes through which snow is formed. We created a profile classification method for this purpose, and we show how it can be used for automatic identification of snow growth processes. Being able to identify the processes is expected to improve radar-based precipitation estimation.

In this paper we study the cloud top height derived from MIPAS measurements. Previous studies showed contradictory results with respect to MIPAS, both underestimating and overestimating cloud top height. We used simulations and found that overestimation and/or underestimation depend on cloud extinction. To support our findings we compared MIPAS cloud top heights of volcanic sulfate aerosol with measurements from CALIOP, ground-based lidar, and ground-based twilight measurements.

Directly measured shape and fall speed are two important parameters needed for models and remote sensing. This can be done by the new Dual Ice Crystal Imager (D-ICI) instrument, which takes two high-resolution pictures of falling snow crystals from two different angles. Fall speed is measured by doubly exposing the side-view picture. Size and shape are determined from the second picture providing the top view of the snow crystal. D-ICI has been tested on the ground in Kiruna, northern Sweden.

We present a validation of O₃ data from the SAGE III-ISS instrument using ground-based lidars and ozonesondes from Hohenpeißenberg and Lauder as well as O₃ data from the ACE-FTS instrument. Average differences in the O₃ concentration between SAGE III-ISS and the lidar and sonde observations are < 10 % over much of the lower and middle stratosphere. The ACE comparisons are < 5 % from 20 to 45 km. These results provide confidence in the SAGE III measurements of global stratospheric O₃ profiles.

In this study we thoroughly address the calibration and validation of the new polarimetric radio occultation (PRO) observables. These represent an innovative way to obtain vertical profiles of precipitation along with thermodynamic observations of the same scene. First we perform the on-orbit calibration of the measurement. Then, we show how the PRO observables are sensitive to the presence and intensity of rain by looking for coincident precipitation measurements from independent missions.

The Tropospheric Monitoring Instrument (TROPOMI) provides atmospheric trace gase and cloud and aerosol property measurements at unprecedented spatial resolution. This study focusses on the TROPOMI NO₂ slant column density (SCD) retrieval: the retrieval method used, the stability of and uncertainties in the SCDs, and a comparison with Ozone Monitoring Instrument (OMI) NO₂ SCDs. TROPOMI shows a superior performance compared to OMI/QA4ECV and operates as anticipated from instrument specifications.

This study investigates the utility of using multi-Doppler retrievals during the Perdigão 2017 campaign. By combining scans from the multitude of Doppler lidars, it was possible to derive virtual towers that greatly extend the range of traditional in situ meteorological towers. Uncertainties from the measurements are analyzed and discussed. Despite multiple sources of error, it was found that the virtual towers are useful for analyzing the complex flows observed during the campaign.

We retrieve the eddy dissipation rate (EDR) from the derived equivalent vertical gust included in the Aircraft Meteorological Data Relay data for more reliable and consistent observations of aviation turbulence globally with the single preferred EDR metric. We convert the DEVG to the EDR using two methods (lognormal mapping scheme and best-fit curve between EDR and DEVG), and the DEVG-derived EDRs are evaluated against in situ EDR data reported by US-operated carriers.

Reliable reference measurements over ocean are essential for the evaluation and improvement of satellite- and model-based aerosol datasets. Here, a uniqe set of shipborne reference aerosol products obtained from Microtops sunphotometer and GUVis-3511 shadowband radiometer observations are compared to aerosol products from the MODIS and SEVIRI satellite sensors, and the CAMS reanalysis over the Atlantic Ocean. The present evaluation highlights the importance of an aerosol-type based analysis.

The comparison of shipborne MAX-DOAS and TROPOMI NO₂ products is important for the evaluation of the TROPOMI products. The ship cruises were mainly over remote oceans, thus we only measured background tropospheric NO₂. Stratospheric NO₂ was measured more accurately because there was almost no contamination from tropospheric NO₂. We found that the TROPOMI stratospheric NO₂ vertical column densities were slightly higher than the MAX-DOAS measurements.

This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.

The current work summarizes a long-term effort to provide an open-source code for the analysis of turbulent fluctuations of trace gases in the atmosphere by eddy covariance and disjunct eddy covariance, with a special focus on reactive gases that participate in atmospheric chemistry. The performance of the code is successfully evaluated based on measurements of minute fluxes of non-methane volatile organic compounds into the urban atmosphere.

Methane is a potent greenhouse gas, with large flux uncertainties from facility-scale sources, such as natural gas extraction infrastructure. A recently developed flux quantification method was successfully tested by flying an unmanned aerial vehicle (UAV) downwind of 22 controlled atmospheric methane releases. The UAVs were used to derive high-precision atmospheric methane measurements. The UAV methodology was successful in both detecting the release and providing a rough flux estimate.

A combination of ground-based active and passive observations is used to partition cloud and precipitation liquid water path in precipitating stratocumulous clouds. Results show that neglecting scattering effects from drizzle drops leads to 8–15 % overestimation of the liquid amount in the cloud. In closed-cell systems only ~20 % of the available drizzle in the cloud falls below the cloud base, compared to ~40 % in open-cell systems.

The article presents a powerful atmospheric instrument based on a laser radar (lidar), capable of measuring horizontal wind velocity at a wide range of altitudes. In this study, we evaluate the performance of the wind lidar at Observatoire de Haute-Provence and demonstrate the application of its measurements for studies of atmospheric dynamical processes. Finally, we present an example of early validation of the ESA Aeolus space-borne wind lidar using its ground-based predecessor.

Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.

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.

We developed a nanoparticle sizer (NPS), consisting of a multi-port differential mobility analyzer (MP-DMA) with 12 sampling ports and multi-condensation particle counters (M-CPCs) for fast measurement of particle size distribution. The NPS can successfully capture the changes in particle size distribution under fast-changing particle concentration conditions. In this study, particle emissions from cooking activity are analyzed as an exemplary real-world application.

Most observations of the atmosphere are point observations, which only measure a small area around the sensor. This limitation creates problems for a number of disciplines, especially those that focus on how the surface and atmosphere exchange heat, mass, and momentum. We used distributed temperature sensing with fiber optics to demonstrate a key breakthrough in observing wind direction in a distributed way, i.e., not at a point, using small structures attached to the fiber-optic cables.

Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.

Objective identification of deep convection outflow boundaries (OFBs) in next-generation geostationary satellite imagery is explored here using motion derived from a tuned advanced optical flow algorithm. Motion discontinuity preservation within the derivation is found crucial for successful OFB tracking between images, which yields new meteorological data for objective systems to use. These results provide the first step towards a fully automated satellite-based OFB identification algorithm.

We present an airborne Doppler lidar simulator (ADLS) based on high-resolution atmospheric wind fields (LES). The ADLS is used to evaluate the retrieval accuracy of airborne wind profiling under turbulent, inhomogeneous wind field conditions inside the boundary layer. With the ADLS, the error due to the violation of the wind field homogeneity assumption used for retrieval can be revealed. For the conditions considered, flow inhomogeneities exert a dominant influence on wind profiling error.

We compare total ozone columns from the satellite-based GOME-type Total Ozone Essential Climate Variable record and the adjusted Modern Era Retrospective Analysis for Research and Applications version 2 reanalysis during their overlap period from 1995 to 2018. Ozone columns and anomalies show a very good agreement in terms of spatial and temporal patterns. In the tropics the interannual variability is assessed by means of an EOF analysis and both data records show a remarkable consistency.

Ozone is a key atmospheric pollutant formed through chemical processing of natural and anthropogenic emissions and removed by reaction with organic compounds emitted by plants. We describe a new instrument – the Total Ozone Reactivity System or TORS – that measures the total loss of ozone in the troposphere. The objective of the TORS instrument is to provide an estimate of the organic compounds emitted by plants which are not measured and thus to improve our understanding of the ozone budget.