ALBERT

Description: We report on applications of the ultraviolet-light-emitting-diode-based incoherent broadband cavity-enhanced absorption spectroscopy (UV-LED-IBBCEAS) technique for optical monitoring of HONO, NO2 and CH2O in a simulation chamber. Performance intercomparison of UV-LED-IBBCEAS with a wet chemistry-based NitroMAC sensor and a Fourier transform infrared (FTIR) spectrometer has been carried out on real-time simultaneous measurement of HONO, NO2 and CH2O concentrations during the reaction of NO2 with H2O vapour in CESAM (French acronym for Experimental Multiphasic Atmospheric Simulation Chamber). The 1σ (signal-to-noise ratio (SNR) = 1) detection limits of 112 pptv for NO2, 56 pptv for HONO and 41 ppbv for CH2O over 120 s were found for the UV-LED-IBBCEAS measurement. On the contrary to many set-ups where cavities are installed outside the simulation chamber, we describe here an original in situ permanent installation. The intercomparison results demonstrate that IBBCEAS is a very well suitable technique for in situ simultaneous measurements of multiple chemically reactive species with high sensitivity and high precision even if the absorption bands of these species are overlapped. It offers excellent capacity for non-invasive optical monitoring of chemical reactions without any perturbation. For the application to simulation chambers, it has the advantage to provide a spatially integrated measurement across the reactor and hence to avoid point-sampling-related artefacts.

Description: Assimilation of weather radar measurements including radar reflectivity and radial wind data has been operational at the Deutscher Wetterdienst, with a diagonal observation error (OE) covariance matrix. For an implementation of a full OE covariance matrix, the statistics of the OE have to be a priori estimated, for which the Desroziers method has been often used. However, the resulted statistics consists of contributions from different error sources and are difficult to interpret. In this work, we use an approach that is based on samples for truncation error in radar observation space to approximate the representation error due to unresolved scales and processes (RE) and compare its statistics with the OE statistics estimated by the Desroziers method. It is found that the statistics of the RE help the understanding of several important features in the variances and correlation length scales of the OE for both reflectivity and radial wind data and the other error sources from the microphysical scheme, radar observation operator and the superobbing technique may also contribute, for instance, to differences among different elevations and observation types. The statistics presented here can serve as a guideline for selecting which observations are assimilated and for assignment of the OE covariance matrix that can be diagonal or full and correlated.

Description: A method is proposed for determining the height of the turbulent mixing layer on the basis of the vertical profiles of the dissipation rate of turbulent energy, which is estimated from lidar measurements of the radial wind velocity using conical scanning by a probe beam around the vertical axis. The accuracy of the proposed method is discussed in detail. It is shown that for the estimation of the mixing layer height (MLH) with the acceptable relative error not exceeding 20 %, the signal-to-noise ratio should be no less than −16 dB, when the relative error of lidar estimation of the dissipation rate does not exceed 30 %. The method was tested in a 6 d experiment in which the wind velocity turbulence was estimated in smog conditions due to forest fires in Siberia in summer 2019. The results of the experiment reveal that the relative error of determination of the MLH time series obtained by this method does not exceed 10 % in the period of turbulence development. The estimates of the turbulent mixing layer height by the proposed method are in a qualitative agreement with the MLH estimated from the distributions of the Richardson number in height and time obtained during the comparison experiment in spring 2020.

Description: In urban areas, road traffic is a dominant source of nitrogen oxides (NOx=NO+NO2). Although the emissions from individual vehicles are regulated by the European emission standards, real driving emissions often exceed these limits. In this study, two multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments on opposite sides of the motorway were used to measure the NO2 absorption caused by road traffic at the A60 motorway close to Mainz, Germany. In combination with wind data, the total NOx emissions for the occurring traffic volume can be estimated. Hereto, the ozone-dependent photochemical equilibrium between NO and NO2 is considered. We show that for 10 May 2019 the measured emissions exceed the maximum expected emissions calculated from the European emission standards for standardised test cycles by a factor of 11±7. One major advantage of the method used here is that MAX-DOAS measurements are very sensitive to the integrated NO2 concentration close to the surface. Thus, all emitted NO2 molecules are detected independently from their altitude, and therefore the whole emission plume originating from the nearby motorway is captured, which is a key advantage compared to other approaches such as in situ measurements.

Description: Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.

Description: This work describes the latest design, calibration and application of a near-infrared laser diode-based photoacoustic (PA) hygrometer developed for total water content measurement in simulated atmospheric freezing precipitation and high ice water content conditions with relevance in fundamental icing research, aviation testing, and certification. The single-wavelength and single-pass PA absorption cell is calibrated for molar water vapor fractions with a two-pressure humidity generator integrated into the instrument. Laboratory calibration showed an estimated measurement accuracy better than 3.3 % in the water vapor mole fraction range of 510–12 360 ppm (5 % from 250–21 200 ppm) with a theoretical limit of detection (3σ) of 3.2 ppm. The hygrometer is examined in combination with a basic isokinetic evaporator probe (IKP) and sampling system designed for icing wind tunnel applications, for which a general description of total condensed water content (CWC) measurements and uncertainties are presented. Despite the current limitation of the IKP to a hydrometeor mass flux below 90 gm-2s-1, a CWC measurement accuracy better than 20 % is achieved by the instrument above a CWC of 0.14 g m−3 in cold air (−30 ∘C) with suitable background humidity measurement. Results of a comparison to the Cranfield University IKP instrument in freezing drizzle and rain show a CWC agreement of the two instruments within 20 %, which demonstrates the potential of PA hygrometers for water content measurement in atmospheric icing conditions.

Description: The comparative reactivity method (CRM) was developed more than a decade to measure OH reactivity (i.e., OH loss frequency) in both laboratory and field studies. However, accurate OH reactivity quantification remains challenging under real ambient conditions, especially for OH reactivity measurements in high-NOx (e.g., 〉 10 ppbv) environments, as ambient NO enhances the regeneration of OH radicals in the CRM reactor. To solve this problem, we design a new and improved CRM reactor (ICRM) and add NO into the system continuously so that the HO2 radical concentration is suppressed. We confirmed the appropriate level of NO by determining the maximum decrease in the pyrrole level caused by regenerated OH radicals from NO + HO2. RO2 radicals induced by volatile organic compounds (VOCs) in the ICRM reactor were also found to react with NO, which led to the regeneration of OH radicals and thus the underestimation of OH reactivity. This effect was quantified by the calibration of representative VOC species at different NO levels, and the correction coefficients obtained were used to correct the measured OH reactivity. All these efforts resulted in reducing the uncertainty of the NO-artifact correction by at least an order of magnitude compared to the original CRM system. Additionally, these technological improvements also considerably reduced the systematic errors from pyrrole photolysis in the original system. A new operation mode was proposed for the ICRM, which is able to avoid the interference resulting from OH radicals produced by photolysis of residual humidity and save time for ambient measurement. The ICRM system was employed in a field campaign to measure OH reactivity and performed well with ambient NO levels ranging from 0 to 50 ppbv, which are typically observed in the urban and suburban atmosphere.

Description: Precipitation is a crucial driver of hydrological processes. Ironically, a reliable characterization of its spatiotemporal variability is challenging. Ground-based rainfall measurement using rain gauges is more accurate. However, installing a dense gauging network to capture rainfall variability can be impractical. Satellite-based rainfall estimates (SREs) could be good alternatives, especially for data-scarce basins like in Ethiopia. However, SRE rainfall is plagued with uncertainties arising from many sources. The objective of this study was to evaluate the performance of the latest versions of several SRE products (i.e., CHIRPS2, IMERG6, TAMSAT3 and 3B42/3) for the Dhidhessa River Basin (DRB). Both statistical and hydrological modeling approaches were used for the performance evaluation. The Soil and Water Analysis Tool (SWAT) was used for hydrological simulations. The results showed that whereas all four SRE products are promising to estimate and detect rainfall for the DRB, the CHIRPS2 dataset performed the best at annual, seasonal and monthly timescales. The hydrological simulation-based evaluation showed that SWAT's calibration results are sensitive to the rainfall dataset. The hydrological response of the basin is found to be dominated by the subsurface processes, primarily by the groundwater flux. Overall, the study showed that both CHIRPS2 and IMERG6 products could be reliable rainfall data sources for the hydrological analysis of the DRB. Moreover, the climatic season in the DRB influences rainfall and streamflow estimation. Such information is important for rainfall estimation algorithm developers.

Description: Aerosol sulfate is a major component of submicron particulate matter (PM1). Sulfate can be present as inorganic (mainly ammonium sulfate, AS) or organosulfate (OS). Although OS is thought to be a smaller fraction of total sulfate in most cases, recent literature argues that this may not be the case in more polluted environments. Aerodyne aerosol mass spectrometers (AMSs) measure total submicron sulfate, but it has been difficult to apportion AS vs. OS as the detected ion fragments are similar. Recently, two new methods have been proposed to quantify OS separately from AS with AMS data. We use observations collected during several airborne field campaigns covering a wide range of sources and air mass ages (spanning the continental US, marine remote troposphere, and Korea) and targeted laboratory experiments to investigate the performance and validity of the proposed OS methods. Four chemical regimes are defined to categorize the factors impacting sulfate fragmentation. In polluted areas with high ammonium nitrate concentrations and in remote areas with high aerosol acidity, the decomposition and fragmentation of sulfate in the AMS is influenced by multiple complex effects, and estimation of OS does not seem possible with current methods. In regions with lower acidity (pH 〉 0) and ammonium nitrate (fraction of total mass

Description: The Brewer ozone spectrophotometer (the Brewer) was designed at Environment and Climate Change Canada (ECCC) in the 1970s to make accurate automated total ozone column measurements. Since the 1980s, the Brewer instrument has become a World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) standard ozone monitoring instrument. Now, more than 230 Brewers have been produced. To assure the quality of the Brewer measurements, a calibration chain is maintained, i.e., first, the reference instruments are independently absolutely calibrated, and then the calibration is transferred from the reference instrument to the travelling standard, and subsequently from the travelling standard to field instruments. ECCC has maintained the world Brewer reference instruments since the 1980s to provide transferable calibration to field instruments at monitoring sites. Three single-monochromator (Mark II) type instruments (serial numbers 008, 014, and 015) formed this world Brewer reference triad (BrT) and started their service in Toronto, Canada, in 1984. In the 1990s, the Mark III type Brewer (known as the double Brewer) was developed, which has two monochromators to reduce the internal instrumental stray light. The double-Brewer world reference triad (BrT-D) was formed in 2013 (serial numbers 145, 187 and 191), co-located with the BrT. The first assessment of the BrT's performance was made in 2005, covering the period between 1984 and 2004 (Fioletov et al., 2005). The current work provides an updated assessment of the BrT's performance (from 1999 to 2019) and the first comprehensive assessment of the BrT-D. The random uncertainties of individual reference instruments are within the WMO/GAW requirement of 1 % (WMO, 2001): 0.49 % and 0.42 % for BrT and BrT-D, respectively, as estimated in this study. The long-term stability of the reference instruments is also evaluated in terms of uncertainties of the key instrument characteristics: the extraterrestrial calibration constant (ETC) and effective ozone absorption coefficients (both having an effect of less than 2 % on total column ozone). Measurements from a ground-based instrument (Pandora spectrometer), satellites (11 datasets, including the most recent high-resolution satellite, TROPOspheric Monitoring Instrument), and reanalysis model (the second Modern-Era Retrospective analysis for Research and Applications, MERRA-2) are used to further assess the performance of world Brewer reference instruments and to provide a context for the requirements of stratospheric ozone observations during the last two decades.

Description: A primary mercury gas standard was developed at Van Swinden Laboratory (VSL) to establish an International System of Units (SI)-traceable reference point for mercury concentrations at emission and background levels in the atmosphere. The majority of mercury concentration measurements are currently made traceable to the empirically determined vapour pressure of mercury. The primary mercury gas standard can be used for the accurate and precise calibration of analytical systems used for measuring mercury concentrations in air. It has been especially developed to support measurements related to ambient air monitoring (1–2 ng m−3), indoor and workplace-related mercury concentration levels according to health standards (from 50 ng m−3 upwards) as well as stationary source emissions (from 1 µg m−3 upwards). The primary mercury gas standard is based on diffusion according to ISO 6154-8. Calibration gas mixtures are obtained by combining calibrated mass flows of nitrogen and air through a generator holding diffusion cells containing elemental mercury. In this paper, we present the results of comparisons between the primary gas standard and mercury calibration methods maintained by NPL (National Physical Laboratory in the United Kingdom), a National Metrology Institute (NMI), and the Jozef Stefan Institute (JSI), a Designated Institute (DI). The calibration methods currently used at NPL and JSI are based on the bell-jar calibration apparatus in combination with the Dumarey equation or a NIST (National Institute of Standards and Technology in the United States) reference material. For the comparisons, mercury was sampled on sorbent traps to obtain transfer standards with levels between 2 and 1000 ng with an expanded uncertainty not exceeding 3 % (k=2). The comparisons performed show that the results for the primary gas standard and the NIST reference material are comparable, whereas a difference of −8 % exists between results traceable to the primary gas standard and the Dumarey equation.

Description: In this paper, we compare column-averaged dry-air mole fractions of water vapor (XH2O) retrievals from the COllaborative Carbon Column Observing Network (COCCON) with retrievals from two co-located high-resolution Fourier transform infrared (FTIR) spectrometers as references at two boreal sites, Kiruna, Sweden, and Sodankylä, Finland, from 6 March 2017 to 20 September 2019. In the framework of the Network for the Detection of Atmospheric Composition Change (NDACC), an FTIR spectrometer is operated at Kiruna. The H2O product derived from these observations has been generated with the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) processor. In Sodankylä, a Total Carbon Column Observing Network (TCCON) spectrometer is operated, and the official XH2O data as provided by TCCON are used for this study. The datasets are in good overall agreement, with COCCON data showing a wet bias of (49.20±58.61) ppm ((3.33±3.37) %, R2=0.9992) compared with MUSICA NDACC and (56.32±45.63) ppm ((3.44±1.77) %, R2=0.9997) compared with TCCON. Furthermore, the a priori H2O volume mixing ratio (VMR) profiles (MAP) used as a priori information in the TCCON retrievals (also adopted for COCCON retrievals) are evaluated with respect to radiosonde (Vaisala RS41) profiles at Sodankylä. The MAP and radiosonde profiles show similar shapes and a good linear correlation of integrated XH2O, indicating that MAP is a reasonable approximation of the true atmospheric state and an appropriate choice for the scaling retrieval methods as applied by COCCON and TCCON. COCCON shows a reduced dry bias (−14.96 %) in comparison with TCCON (−19.08 %) with respect to radiosonde XH2O. Finally, we investigate the quality of satellite data at high latitudes. For this purpose, the COCCON XH2O is compared with retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) generated with the MUSICA processor (MUSICA IASI) and with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). Both paired datasets generally show good agreement and similar correlations at the two sites. COCCON measures 4.64 % less XH2O at Kiruna and 3.36 % less at Sodankylä with respect to MUSICA IASI, whereas COCCON measures 9.71 % more XH2O at Kiruna and 7.75 % more at Sodankylä compared with TROPOMI. Our study supports the assumption that COCCON also delivers a well-characterized XH2O data product. This emphasizes that this approach might complement the TCCON network with respect to satellite validation efforts. This is the first published study where COCCON XH2O has been compared with MUSICA NDACC and TCCON retrievals and has been used for MUSICA IASI and TROPOMI validation.

Description: Infrared spectroscopic observations have shown that crystalline ammonium nitrate (AN) particles are an abundant constituent of the upper tropospheric aerosol layer which is formed during the Asian summer monsoon period, the so-called Asian Tropopause Aerosol Layer (ATAL). At upper tropospheric temperatures, the thermodynamically stable phase of AN is different from that at 298 K, meaning that presently available room-temperature optical constants of AN, that is, the real and imaginary parts of the complex refractive index, cannot be applied for the quantitative analysis of these infrared measurements. In this work, we have retrieved the first low-temperature data set of optical constants for crystalline AN in the 800–6000 cm−1 wavenumber range with a spectral resolution of 0.5 cm−1. The optical constants were iteratively derived from an infrared extinction spectrum of 1 µm sized AN particles suspended in a cloud chamber at 223 K. The uncertainties of the new data set were carefully assessed in a comprehensive sensitivity analysis. We show that our data accurately fit aircraft-borne infrared measurements of ammonium nitrate particles in the ATAL.

Description: Although optical components in Fourier transform infrared (FTIR) spectrometers are preferably wedged, in practice, infrared spectra typically suffer from the effects of optical resonances (“channeling”) affecting the retrieval of weakly absorbing gases. This study investigates the level of channeling of each FTIR spectrometer within the Network for the Detection of Atmospheric Composition Change (NDACC). Dedicated spectra were recorded by more than 20 NDACC FTIR spectrometers using a laboratory mid-infrared source and two detectors. In the indium antimonide (InSb) detector domain (1900–5000 cm−1), we found that the amplitude of the most pronounced channeling frequency amounts to 0.1 ‰ to 2.0 ‰ of the spectral background level, with a mean of (0.68±0.48) ‰ and a median of 0.60 ‰. In the mercury cadmium telluride (HgCdTe) detector domain (700–1300 cm−1), we find even stronger effects, with the largest amplitude ranging from 0.3 ‰ to 21 ‰ with a mean of (2.45±4.50) ‰ and a median of 1.2 ‰. For both detectors, the leading channeling frequencies are 0.9 and 0.11 or 0.23 cm−1 in most spectrometers. The observed spectral frequencies of 0.11 and 0.23 cm−1 correspond to the optical thickness of the beam splitter substrate. The 0.9 cm−1 channeling is caused by the air gap in between the beam splitter and compensator plate. Since the air gap is a significant source of channeling and the corresponding amplitude differs strongly between spectrometers, we propose new beam splitters with the wedge of the air gap increased to at least 0.8∘. We tested the insertion of spacers in a beam splitter's air gap to demonstrate that increasing the wedge of the air gap decreases the 0.9 cm−1 channeling amplitude significantly. A wedge of the air gap of 0.8∘ reduces the channeling amplitude by about 50 %, while a wedge of about 2∘ removes the 0.9 cm−1 channeling completely. This study shows the potential for reducing channeling in the FTIR spectrometers operated by the NDACC, thereby increasing the quality of recorded spectra across the network.

Description: We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known January–February 2009 event. We first construct RO temperature, density, and bending angle anomaly profiles and estimate vertical-mean anomalies in selected altitude layers. These mean anomalies are then averaged into a daily updated 5∘ latitude × 20∘ longitude grid over 50–90∘ N. Based on the gridded mean anomalies, we employ the concept of threshold exceedance areas (TEAs), the geographic areas wherein the anomalies exceed predefined threshold values such as 40 K or 40 %. We estimate five basic TEAs for selected altitude layers and thresholds and use them to derive primary-, secondary-, and trailing-phase TEA metrics to detect SSWs and to monitor in particular their main-phase (primary- plus secondary-phase) evolution on a daily basis. As an initial setting, the main phase requires daily TEAs to exceed 3×106 km2, based on which main-phase duration, area, and overall event strength are recorded. Using the January–February 2009 SSW event for demonstration, and employing RO data plus cross-evaluation data from analysis fields of the European Centre for Medium-Range Weather Forecasts (ECMWF), we find the new approach has strong potential for detecting and monitoring SSW events. The primary-phase metric shows a strong SSW emerging on 20 January, reaching a maximum on 23 January and fading by 30 January. On 22–23 January, temperature anomalies over the middle stratosphere exceeding 40 K cover an area of more than 10×106 km2. The geographic tracking of the SSW showed that it was centered over east Greenland, covering Greenland entirely and extending from western Iceland to eastern Canada. The secondary- and trailing-phase metrics track the further SSW development, where the thermodynamic anomaly propagated downward and was fading with a transient upper stratospheric cooling, spanning until the end of February and beyond. Given the encouraging demonstration results, we expect the method to be very suitable for long-term monitoring of how SSW characteristics evolve under climate change and polar vortex variability, using both RO and reanalysis data.

Description: Pyrolysis is the first step in a series of chemical and physical processes that produce flammable organic gases from wildland fuels that can result in a wildland fire. We report results using a new time-resolved Fourier transform infrared (FTIR) method that correlates the measured FTIR spectrum with an infrared thermal image sequence, enabling the identification and quantification of gases within different phases of the fire process. The flame from burning fuel beds composed of pine needles (Pinus palustris) and mixtures of sparkleberry, fetterbush, and inkberry plants was the natural heat source for pyrolysis. Extractive gas samples were analyzed and identified in both static and dynamic modes synchronized to thermal infrared imaging: a total of 29 gases were identified including small alkanes, alkenes, aldehydes, nitrogen compounds, and aromatics, most previously measured by FTIR in wildland fires. This study presents one of the first identifications of phenol associated with both pre-combustion and combustion phases using ca. 1 Hz temporal resolution. Preliminary results indicate ∼2.5× greater phenol emissions from sparkleberry and inkberry compared to fetterbush, with differing temporal profiles.

Description: The suitability of a fibre-optic distributed temperature sensing (DTS) technique for observing atmospheric mixing profiles within and above a forest was quantified, and these profiles were analysed. The spatially continuous observations were made at a 125 m tall mast in a boreal pine forest. Airflows near forest canopies diverge from typical boundary layer flows due to the influence of roughness elements (i.e. trees) on the flow. Ideally, these complex flows should be studied with spatially continuous measurements, yet such measurements are not feasible with conventional micrometeorological measurements with, for example, sonic anemometers. Hence, the suitability of DTS measurements for studying canopy flows was assessed. The DTS measurements were able to discern continuous profiles of turbulent fluctuations and mean values of air temperature along the mast, providing information about mixing processes (e.g. canopy eddies and evolution of inversion layers at night) and up to third-order turbulence statistics across the forest–atmosphere interface. Turbulence measurements with 3D sonic anemometers and Doppler lidar at the site were also utilised in this analysis. The continuous profiles for turbulence statistics were in line with prior studies made at wind tunnels and large eddy simulations for canopy flows. The DTS measurements contained a significant noise component which was, however, quantified, and its effect on turbulence statistics was accounted for. Underestimation of air temperature fluctuations at high frequencies caused 20 %–30 % underestimation of temperature variance at typical flow conditions. Despite these limitations, the DTS measurements should prove useful also in other studies concentrating on flows near roughness elements and/or non-stationary periods, since the measurements revealed spatio-temporal patterns of the flow which were not possible to be discerned from single point measurements fixed in space.

Description: The Orbitrap mass spectrometer has recently been proved to be a powerful instrument to accurately measure gas-phase and particle-phase organic compounds with a greater mass resolving power than other widely used online mass spectrometers in atmospheric sciences. We develop an open-source software tool (Orbitool, https://orbitrap.catalyse.cnrs.fr, last access: 4 February 2021) to facilitate the analysis of long-term online Orbitrap data. Orbitool can average long-term data while improving the mass accuracy by re-calibrating each mass spectrum, assign molecular formulae of compounds and their isotopes to measured signals, and export time series and mass defect plots. The noise reduction procedure in Orbitool can separate signal peaks from noise and reduce the computational and storage expenses. Chemical ionization Orbitrap data from laboratory experiments on ozonolysis of monoterpenes and ambient measurements in urban Shanghai were used to test Orbitool. For the test dataset, the average mass accuracy was improved from 

Description: An operational data product available for both the Suomi National Polar-orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration-20 (NOAA-20) platforms provides high-spatial-resolution infrared (IR) absorption band radiances for Visible Infrared Imaging Radiometer Suite (VIIRS) based on a VIIRS and Crosstrack Infrared Sounder (CrIS) data fusion method. This study investigates the use of these IR radiances, centered at 4.5, 6.7, 7.3, 9.7, 13.3, 13.6, 13.9, and 14.2 µm, to construct atmospheric moisture products (e.g., total precipitable water and upper tropospheric humidity) and to evaluate their accuracy. Total precipitable water (TPW) and upper tropospheric humidity (UTH) retrieved from hyperspectral sounder CrIS measurements are provided at the associated VIIRS sensor's high spatial resolution (750 m) and are compared subsequently to collocated operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and S-NPP VIIRS moisture products. This study suggests that the use of VIIRS IR absorption band radiances will provide continuity with Aqua MODIS moisture products.

Description: Surface-based measurements of broadband shortwave (solar) and longwave (infrared) radiative fluxes using thermopile radiometers are made regularly around the globe for scientific and operational environmental monitoring. The occurrence of ice on sensor windows in cold environments – whether snow, rime, or frost – is a common problem that is difficult to prevent as well as difficult to correct in post-processing. The Baseline Surface Radiation Network (BSRN) community recognizes radiometer icing as a major outstanding measurement uncertainty. Towards constraining this uncertainty, the De-Icing Comparison Experiment (D-ICE) was carried out at the NOAA Atmospheric Baseline Observatory in UtqiaÄ¡vik (formerly Barrow), Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate existing ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational systems that are part of NOAA's Barrow BSRN station and the US Department of Energy Atmospheric Radiation Measurement (ARM) program North Slope of Alaska and Oliktok Point observatories. To detect icing, radiometers were monitored continuously using cameras, with a total of more than 1 million images of radiometer domes archived. Ventilator and ventilator–heater performance overall was skillful with the average of the systems mitigating ice formation 77 % (many 〉90 %) of the time during which icing conditions were present. Ventilators without heating elements were also effective and capable of providing heat through roughly equal contributions of waste energy from the ventilator fan and adiabatic heating downstream of the fan. This provided ∼0.6 ∘C of warming, enough to subsaturate the air up to a relative humidity (with respect to ice) of ∼105 %. Because the mitigation technologies performed well, a near complete record of verified ice-free radiometric fluxes was assembled for the duration of the campaign. This well-characterized data set is suitable for model evaluation, in particular for the Year of Polar Prediction (YOPP) first Special Observing Period (SOP1). We used the data set to calculate short- and long-term biases in iced sensors, finding that biases can be up to +60 W m−2 (longwave) and −211 to +188 W m−2 (shortwave). However, because of the frequency of icing, mitigation of ice by ventilators, cloud conditions, and the timing of icing relative to available sunlight, the biases in the monthly means were generally less than the aggregate uncertainty attributed to other conventional sources in both the shortwave and longwave.

Description: A new facility has been developed which allows for a stable and reproducible production of ambient-like model aerosols (PALMA) in the laboratory. The set-up consists of multiple aerosol generators, a custom-made flow tube homogeniser, isokinetic sampling probes, and a system to control aerosol temperature and humidity. Model aerosols containing elemental carbon, secondary organic matter from the ozonolysis of α-pinene, inorganic salts such as ammonium sulfate and ammonium nitrate, mineral dust particles, and water were generated under different environmental conditions and at different number and mass concentrations. The aerosol physical and chemical properties were characterised with an array of experimental methods, including scanning mobility particle sizing, ion chromatography, total reflection X-ray fluorescence spectroscopy and thermo-optical analysis. The facility is very versatile and can find applications in the calibration and performance characterisation of aerosol instruments monitoring ambient air. In this study, we performed, as proof of concept, an intercomparison of three different commercial PM (particulate matter) monitors (TEOM 1405, DustTrak DRX 8533 and Fidas Frog) with the gravimetric reference method under three simulated environmental scenarios. The results are presented and compared to previous field studies. We believe that the laboratory-based method for simulating ambient aerosols presented here could provide in the future a useful alternative to time-consuming and expensive field campaigns, which are often required for instrument certification and calibration.

Description: Visibility is an indicator of atmospheric transparency, and it is widely used in many research fields, including air pollution, climate change, ground transportation, and aviation. Although efforts have been made to improve the performance of visibility meters, a significant error exists in measured visibility data. This study conducts a well-designed simulation calibration of visibility meters, which proves that current methods of visibility measurement include a false assumption, leading to the long-term neglect of an important source of visibility error caused by erroneous values of Ångström exponents. This error has two characteristics, namely (1) independence, which means that the magnitude of the error is independent of the performance of the visibility meter. It is impossible to reduce this error by improving the performance of visibility meters. The second characteristic is (2) uncertainty, which means the magnitude of the error does not show a clear change pattern but can be substantially larger than the measurement error of visibility meters. It is impossible to accurately estimate the magnitude of this error or its influence on visibility measurements. Our simulations indicate that, as errors in visibility caused by erroneous values of Ångström exponents are inevitable using current methods of visibility measurement, reliable visibility data cannot be obtained without major adjustments to current measurement methods.

Description: In this work, a novel approach for the determination of the particle size distribution (PSD) parameters of stratospheric sulfate aerosols is presented. For this, ratios of extinction coefficients obtained from SAGE III/ISS (Stratospheric Aerosol and Gas Experiment III on the International Space Station) solar occultation measurements at 449, 756 and 1544 nm were used to retrieve the mode width and median radius of a size distribution assumed to be monomodal lognormal. The estimated errors at the peak of the stratospheric aerosol layer, on average, lie between 20 % and 25 % for the median radius and 5 % and 7 % for the mode width. The results are consistent in magnitude with other retrieval results from the literature, but a robust comparison is difficult, mainly because of differences in temporal and spatial coverage. Other quantities like number density and effective radius were also calculated. A major advantage of the described method over other retrieval techniques is that both the median radius and the mode width can be retrieved simultaneously, without having to assume one of them. This is possible due to the broad wavelength spectrum covered by the SAGE III/ISS measurements. Also, the presented method – being based on the analysis of three wavelengths – allows unique solutions for the retrieval of PSD parameters for almost all of the observed extinction spectra, which is not the case when using only two spectral channels. In addition, the extinction coefficients from SAGE III/ISS solar occultation measurements, on which the retrieval is based, are calculated without a priori assumptions about the PSD. For those reasons, the data produced with the presented retrieval technique may be a valuable contribution for a better understanding of the variability of stratospheric aerosol size distributions, e.g. after volcanic eruptions. While this study focuses on describing the retrieval method, and a future study will discuss the PSD parameter data set produced in depth, some exemplary results for background conditions in June 2017 are shown.

Description: This work describes key improvements made to the in situ laser-induced fluorescence instrument for measuring sulfur dioxide (SO2) that was originally described by Rollins et al. (2016). Here, we report measurements of the SO2 fluorescence emission spectrum. These measurements allow for the determination of the most appropriate bandpass filters to optimize the fluorescence signal, while reducing the instrumental background. Because many aromatic species fluoresce in the same spectral region as SO2, fluorescence spectra were also measured for naphthalene and anisole to determine if ambient SO2 measurements could be biased in the presence of such species. Improvement in the laser system resulted in better tunability, and a significant reduction in the 216.9 nm laser linewidth. This increases the online/offline signal ratio which, in turn, improves the precision and specificity of the measurement. The effects of these improvements on the instrumental sensitivity were determined by analyzing the signal and background of the instrument, using varying optical bandpass filter ranges and cell pressures and calculating the resulting limit of detection. As a result, we report an improvement to the instrumental sensitivity by as much as 50 %.

Description: The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. To investigate whether a regional-scale reduction of anthropogenic CO2 emissions during the COVID-19 pandemic can be detected using space-based observations of atmospheric CO2, we have analysed a small ensemble of OCO-2 and GOSAT satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2. We focus on East China and use a simple data-driven analysis method. We present estimates of the relative change of East China monthly emissions in 2020 relative to previous periods, limiting the analysis to October-to-May periods to minimize the impact of biogenic CO2 fluxes. The ensemble mean indicates an emission reduction by approximately 10 % ± 10 % in March and April 2020. However, our results show considerable month-to-month variability and significant differences across the ensemble of satellite data products analysed. For example, OCO-2 suggests a much smaller reduction (∼ 1 %–2 % ± 2 %). This indicates that it is challenging to reliably detect and to accurately quantify the emission reduction with current satellite data sets. There are several reasons for this, including the sparseness of the satellite data but also the weak signal; the expected regional XCO2 reduction is only on the order of 0.1–0.2 ppm. Inferring COVID-19-related information on regional-scale CO2 emissions using current satellite XCO2 retrievals likely requires, if at all possible, a more sophisticated analysis method including detailed transport modelling and considering a priori information on anthropogenic and natural CO2 surface fluxes.

Description: The Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) instrument operated from 25 October 1978 through 28 May 1979. Its version 6 (V6) profiles were processed and archived in 2002. We present several diagnostic examples of the quality of the V6 stratospheric species distributions based on their level 3 zonal Fourier coefficient products. In particular, we show that there are small differences in the ascending (A) minus descending (D) orbital temperature–pressure or T(p) profiles (their A−D values) that affect (A−D) species values. Systematic A−D biases in T(p) can arise from small radiance biases and/or from viewing anomalies along orbits. There can also be (A−D) differences in T(p) due to not resolving and correcting for all of the atmospheric temperature gradient along LIMS tangent view-paths. An error in T(p) affects species retrievals through (1) the Planck blackbody function in forward calculations of limb radiance that are part of the iterative retrieval algorithm of LIMS, and (2) the registration of the measured LIMS species radiance profiles in pressure altitude, mainly for the lower stratosphere. There are clear A−D differences for ozone, H2O, and HNO3 but not for NO2. Percentage differences are larger in the lower stratosphere for ozone and H2O because those species are optically thick. We evaluate V6 ozone profile biases in the upper stratosphere with the aid of comparisons against a monthly climatology of UV–ozone soundings from rocketsondes. We also provide results of time series analyses of V6 ozone, H2O, and potential vorticity for the middle stratosphere to show that their average (A+D) V6 level 3 products provide a clear picture of the evolution of those tracers during Northern Hemisphere winter. We recommend that researchers use the average V6 level 3 product for their science studies of stratospheric ozone and H2O, while keeping in mind that there are uncorrected nonlocal thermodynamic equilibrium effects in daytime ozone in the lower mesosphere and in daytime H2O in the uppermost stratosphere. We also point out that the present-day Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) experiment provides measurements and retrievals of temperature and ozone that are nearly free of anomalous diurnal variations and of effects from gradients at low and middle latitudes.

Description: A portable emission measurement system (PEMS) was used to measure the real-world driving emissions pertaining to a Japanese middle-sized heavy-duty vehicle. The testing was performed with the vehicle being driven in the metropolitan area of Tokyo in four seasons (January, June, August, and November) to analyze the seasonal dependence of NOx and CO2 emissions. The experimental results indicated that the amount of NOx emissions was particularly high in the cold season owing to the slow starting of the NOx after-treatment systems, which is to say the exhaust gas recirculation and urea-selective-catalytic-reduction systems, under low-ambient-temperature conditions. In real-world driving, a high acceleration pattern was observed in the low-speed region which is not considered in the world harmonized vehicle cycle, which is the worldwide official driving mode in the chassis dynamometer experiment. Finally, the transient emission tables for NOx and CO2 were constructed based on the PEMS measurement results and the classical mechanic theory. The constructed tables replicated well the experimental results in all the considered conditions involving different ambient temperatures and locations. The proposed approach can be used to evaluate emission inventories in the future.

Description: The LiDAR Statistical Barnes Objective Analysis (LiSBOA), presented in Letizia et al. (2021), is a procedure for the optimal design of lidar scans and calculations over a Cartesian grid of the statistical moments of the velocity field. Lidar data collected during a field campaign conducted at a wind farm in complex terrain are analyzed through LiSBOA for two different tests. For both case studies, LiSBOA is leveraged for the optimization of the azimuthal step of the lidar and the retrieval of the mean equivalent velocity and turbulence intensity fields. In the first case, the wake velocity statistics of four utility-scale turbines are reconstructed on a 3D grid, showing LiSBOA's ability to capture complex flow features, such as high-speed jets around the nacelle and the wake turbulent-shear layers. For the second case, the statistics of the wakes generated by four interacting turbines are calculated over a 2D Cartesian grid and compared to the measurements provided by the nacelle-mounted anemometers. Maximum discrepancies, as low as 3 % for the mean velocity (with respect to the free stream velocity) and turbulence intensity (in absolute terms), endorse the application of LiSBOA for lidar-based wind resource assessment and diagnostic surveys for wind farms.

Description: A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of lidar scans and retrieval of the velocity statistical moments is proposed. LiSBOA represents an adaptation of the classical Barnes scheme for the statistical analysis of unstructured experimental data in N-dimensional space, and it is a suitable technique for the evaluation over a structured Cartesian grid of the statistics of scalar fields sampled through scanning lidars. LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. This revisited theoretical framework for the Barnes objective analysis enables the formulation of guidelines for the optimal design of lidar experiments and efficient application of LiSBOA for the postprocessing of lidar measurements. The optimal design of lidar scans is formulated as a two-cost-function optimization problem, including the minimization of the percentage of the measurement volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field. The optimal design of the lidar scans also guides the selection of the smoothing parameter and the total number of iterations to use for the Barnes scheme. LiSBOA is assessed against a numerical data set generated using the virtual lidar technique applied to the data obtained from a large eddy simulation (LES). The optimal sampling parameters for a scanning Doppler pulsed wind lidar are retrieved through LiSBOA, and then the estimated statistics are compared with those of the original LES data set, showing a maximum error of about 4 % for both mean velocity and turbulence intensity.

Description: The new platforms for Earth observation from space are characterized by measurements made at great spatial and temporal resolutions. While this abundance of information makes it possible to detect and study localized phenomena, it may be difficult to manage this large amount of data for the study of global and large-scale phenomena. A particularly significant example is the use by assimilation systems of Level 2 products that represent gas profiles in the atmosphere. The models on which assimilation systems are based are discretized on spatial grids with horizontal dimensions of the order of tens of kilometres in which tens or hundreds of measurements may fall in the future. A simple procedure to overcome this problem is to extract a subset of the original measurements, but this involves a loss of information. Another option is the use of simple averages of the profiles, but this approach also has some limitations that we will discuss in the paper. A more advanced solution is to resort to the so-called fusion algorithms, capable of compressing the size of the dataset while limiting the information loss. A novel data fusion method, the Complete Data Fusion algorithm, was recently developed to merge a set of retrieved products in a single product a posteriori. In the present paper, we apply the Complete Data Fusion method to ozone profile measurements simulated in the thermal infrared and ultraviolet bands in a realistic scenario. Following this, the fused products are compared with the input profiles; comparisons show that the output products of data fusion have smaller total errors and higher information contents in general. The comparisons of the fused products with the fusing products are presented both at single fusion grid box scale and with a statistical analysis of the results obtained on large sets of fusion grid boxes of the same size. We also evaluate the grid box size impact, showing that the Complete Data Fusion method can be used with different grid box sizes even if this possibility is connected to the natural variability of the considered atmospheric molecule.

Description: The Japanese Greenhouse gases Observing SATellite-2 (GOSAT-2), in orbit since 29 October 2018, follows up the GOSAT mission, itself in orbit since 23 January 2009. GOSAT-2 monitors carbon dioxide and methane in order to increase our understanding of the global carbon cycle. It simultaneously measures carbon monoxide emitted from fossil fuel combustion and biomass burning and permits identification of the amount of combustion-related carbon. To do this, the satellite utilizes the Thermal and Near Infrared Sensor for Carbon Observation Fourier-Transform Spectrometer-2 (TANSO-FTS-2). This spectrometer detects gas absorption spectra of solar radiation reflected from the Earth's surface in the shortwave-infrared (SWIR) region as well as the emitted thermal infrared radiation (TIR) from the ground and the atmosphere. TANSO-FTS-2 can measure the oxygen A band (0.76 µm), weak and strong CO2 bands (1.6 and 2.0 µm), weak and strong CH4 bands (1.6 and 2.3 µm), a weak CO band (2.3 µm), a mid-wave TIR band (5.5–8.4 µm), and a long-wave TIR band (8.4–14.3 µm) with 0.2 cm−1 spectral sampling intervals. TANSO-FTS-2 is equipped with a solar diffuser target, a monochromatic light source, and a blackbody for spectral radiance calibration. These calibration sources permit characterization of time-dependent instrument changes in orbit. The onboard-recalibrated instrumental parameters are considered in operational level-1 processing and released as TANSO-FTS-2 level-1 version 102102 products, which were officially released on 25 May 2020. This paper provides an overview of the TANSO-FTS-2 instrument, the level-1 processing, and the first-year in-orbit performance. To validate the spectral radiance calibration during the first year of operation, the spectral radiance of the version 102102 product is compared at temporally coincident and spatially collocated points from February 2019 to March 2020 with TANSO-FTS on GOSAT for SWIR and with AIRS on Aqua and IASI on METOP-B for TIR. The spectral radiances measured by TANSO-FTS and TANSO-FTS-2 agree within 2 % of the averaged bias and 0.5 % standard deviation for SWIR bands. The agreement of brightness temperature between TANSO-FTS-2 and AIRS–IASI is better than 1 K in the range from 220 to 320 K. GOSAT-2 not only provides seamless global CO2 and CH4 observation but also observes local emissions and uptake with an additional CO channel, fully customized sampling patterns, higher signal-to-noise ratios, and wider pointing angles than GOSAT.

Description: The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (

Description: Nitrogen oxides (NOx≡NO+NO2) in the NOx-limited upper troposphere (UT) are long-lived and so have a large influence on the oxidizing capacity of the troposphere and formation of the greenhouse gas ozone. Models misrepresent NOx in the UT, and observations to address deficiencies in models are sparse. Here we obtain a year of near-global seasonal mean mixing ratios of NO2 in the UT (450–180 hPa) at 1∘×1∘ by applying cloud-slicing to partial columns of NO2 from TROPOMI. This follows refinement of the cloud-slicing algorithm with synthetic partial columns from the GEOS-Chem chemical transport model. TROPOMI, prior to cloud-slicing, is corrected for a 13 % underestimate in stratospheric NO2 variance and a 50 % overestimate in free-tropospheric NO2 determined by comparison to Pandora total columns at high-altitude free-tropospheric sites at Mauna Loa, Izaña, and Altzomoni and MAX-DOAS and Pandora tropospheric columns at Izaña. Two cloud-sliced seasonal mean UT NO2 products for June 2019 to May 2020 are retrieved from corrected TROPOMI total columns using distinct TROPOMI cloud products that assume clouds are reflective boundaries (FRESCO-S) or water droplet layers (ROCINN-CAL). TROPOMI UT NO2 typically ranges from 20–30 pptv over remote oceans to 〉80 pptv over locations with intense seasonal lightning. Spatial coverage is mostly in the tropics and subtropics with FRESCO-S and extends to the midlatitudes and polar regions with ROCINN-CAL, due to its greater abundance of optically thick clouds and wider cloud-top altitude range. TROPOMI UT NO2 seasonal means are spatially consistent (R=0.6–0.8) with an existing coarser spatial resolution (5∘ latitude × 8∘ longitude) UT NO2 product from the Ozone Monitoring Instrument (OMI). UT NO2 from TROPOMI is 12–26 pptv more than that from OMI due to increase in NO2 with altitude from the OMI pressure ceiling (280 hPa) to that for TROPOMI (180 hPa), but possibly also due to altitude differences in TROPOMI and OMI cloud products and NO2 retrieval algorithms. The TROPOMI UT NO2 product offers potential to evaluate and improve representation of UT NOx in models and supplement aircraft observations that are sporadic and susceptible to large biases in the UT.

Description: The demonstration satellite GHGSat-D, or “Claire”, launched on 21 June 2016, is the first in a planned constellation of small satellites designed and operated by GHGSat, Inc. to measure greenhouse gas emissions at the facility scale from space. Its instrument measures methane concentrations by collecting and spectrally decomposing solar backscattered radiation in the shortwave infrared using a compact fixed-cavity Fabry–Pérot imaging spectrometer. The effective spatial resolution of 50×50 m2 over targeted 12×12 km2 scenes is unprecedented for a space-based gas-sensing spectrometer. Here we report on the instrument design and forward model and retrieval procedure, and we present several examples of retrieved methane emissions observed over industrial facilities. We discuss the sources of error limiting the performance of GHGSat-D and identify improvements for our follow-on satellites. Claire's mission has proven that small satellites can be used to identify and quantify methane emissions from industrial facilities, enabling operators to take prompt corrective action.

Description: In August 2018, the first Doppler wind lidar, developed by the European Space Agency (ESA), was launched on board the Aeolus satellite into space. Providing atmospheric wind profiles on a global basis, the Earth Explorer mission is expected to demonstrate improvements in the quality of numerical weather prediction (NWP). For the use of Aeolus observations in NWP data assimilation, a detailed characterization of the quality and the minimization of systematic errors is crucial. This study performs a statistical validation of Aeolus observations, using collocated radiosonde measurements and NWP forecast equivalents from two different global models, the ICOsahedral Nonhydrostatic model (ICON) of Deutscher Wetterdienst (DWD) and the European Centre for Medium-Range Weather Forecast (ECMWF) Integrated Forecast System (IFS) model, as reference data. For the time period from the satellite's launch to the end of December 2019, comparisons for the Northern Hemisphere (23.5–65∘ N) show strong variations of the Aeolus wind bias and differences between the ascending and descending orbit phase. The mean absolute bias for the selected validation area is found to be in the range of 1.8–2.3 m s−1 (Rayleigh) and 1.3–1.9 m s−1 (Mie), showing good agreement between the three independent reference data sets. Due to the greater representativeness errors associated with the comparisons using radiosonde observations, the random differences are larger for the validation with radiosondes compared to the model equivalent statistics. To achieve an estimate for the Aeolus instrumental error, the representativeness errors for the comparisons are determined, as well as the estimation of the model and radiosonde observational error. The resulting Aeolus error estimates are in the range of 4.1–4.4 m s−1 (Rayleigh) and 1.9–3.0 m s−1 (Mie). Investigations of the Rayleigh wind bias on a global scale show that in addition to the satellite flight direction and seasonal differences, the systematic differences vary with latitude. A latitude-based bias correction approach is able to reduce the bias, but a residual bias of 0.4–0.6 m s−1 with a temporal trend remains. Taking additional longitudinal differences into account, the bias can be reduced further by almost 50 %. Longitudinal variations are suggested to be linked to land–sea distribution and tropical convection that influences the thermal emission of the earth. Since 20 April 2020 a telescope temperature-based bias correction scheme has been applied operationally in the L2B processor, developed by the Aeolus Data Innovation and Science Cluster (DISC).

Description: Important uncertainties remain in our understanding of the spatial and temporal variability of atmospheric hydroxyl radical concentration ([OH]). Carbon-14-containing carbon monoxide (14CO) is a useful tracer that can help in the characterization of [OH] variability. Prior measurements of atmospheric 14CO concentration ([14CO] are limited in both their spatial and temporal extent, partly due to the very large air sample volumes that have been required for measurements (500–1000 L at standard temperature and pressure, L STP) and the difficulty and expense associated with the collection, shipment, and processing of such samples. Here we present a new method that reduces the air sample volume requirement to ≈90 L STP while allowing for [14CO] measurement uncertainties that are on par with or better than prior work (≈3 % or better, 1σ). The method also for the first time includes accurate characterization of the overall procedural [14CO] blank associated with individual samples, which is a key improvement over prior atmospheric 14CO work. The method was used to make measurements of [14CO] at the NOAA Mauna Loa Observatory, Hawaii, USA, between November 2017 and November 2018. The measurements show the expected [14CO] seasonal cycle (lowest in summer) and are in good agreement with prior [14CO] results from another low-latitude site in the Northern Hemisphere. The lowest overall [14CO] uncertainties (2.1 %, 1σ) are achieved for samples that are directly accompanied by procedural blanks and whose mass is increased to ≈50 µgC (micrograms of carbon) prior to the 14C measurement via dilution with a high-CO 14C-depleted gas.

Description: Fast-response infrared gas analyzers (IRGAs) have been widely used over 3 decades in many ecosystems for long-term monitoring of water vapor fluxes in the surface layer of the atmosphere. While some of the early IRGA sensors are still used in these national and/or regional eco-flux networks, optically improved IRGA sensors are newly employed in the same networks. The purpose of this study was to evaluate the performance of water vapor density and flux data from three generations of IRGAs – LI-7500, LI-7500A, and LI-7500RS (LI-COR Bioscience, Inc., Nebraska, USA) – over the course of a growing season in Bushland, Texas, USA, in an irrigated maize canopy for 90 d. Water vapor density measurements were in generally good agreement, but temporal drift occurred in different directions and magnitudes. Means exhibited mostly shift changes that did not impact the flux magnitudes, while their variances of water vapor density fluctuations were occasionally in poor agreement, especially following rainfall events. LI-7500 cospectra were largest compared to LI-7500RS and LI-7500A, especially under unstable and neutral static stability. Agreement among the sensors was best under the typical irrigation-cooled boundary layer, with a 14 % interinstrument coefficient of variability under advective conditions. Generally, the smallest variances occurred with the LI-7500RS, and high-frequency spectral corrections were larger for these measurements, resulting in similar fluxes between the LI-7500A and LI-7500RS. Fluxes from the LI-7500 were best representative of growing season ET based on a world-class lysimeter reference measurement, but using the energy balance ratio as an estimate of systematic bias corrected most of the differences among measured fluxes.

Description: The distribution and dynamics of atmospheric pollutants are spatiotemporally heterogeneous due to variability in emissions, transport, chemistry, and deposition. To understand these processes at high spatiotemporal resolution and their implications for air quality and personal exposure, we present custom, low-cost air quality monitors that measure concentrations of contaminants relevant to human health and climate, including gases (e.g., O3, NO, NO2, CO, CO2, CH4, and SO2) and size-resolved (0.3–10 µm) particulate matter. The devices transmit sensor data and location via cellular communications and are capable of providing concentration data down to second-level temporal resolution. We produce two models: one designed for stationary (or mobile platform) operation and a wearable, portable model for directly measuring personal exposure in the breathing zone. To address persistent problems with sensor drift and environmental sensitivities (e.g., relative humidity and temperature), we present the first online calibration system designed specifically for low-cost air quality sensors to calibrate zero and span concentrations at hourly to weekly intervals. Monitors are tested and validated in a number of environments across multiple outdoor and indoor sites in New Haven, CT; Baltimore, MD; and New York City. The evaluated pollutants (O3, NO2, NO, CO, CO2, and PM2.5) performed well against reference instrumentation (e.g., r=0.66–0.98) in urban field evaluations with fast e-folding response times (≤ 1 min), making them suitable for both large-scale network deployments and smaller-scale targeted experiments at a wide range of temporal resolutions. We also provide a discussion of best practices on monitor design, construction, systematic testing, and deployment.

Description: Various instrumental or geophysical artifacts, such as saturation, stray light or obstruction of light (either coming from the instrument or related to solar eclipses), negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra and downstream retrievals of atmospheric and surface properties derived from these spectra. In addition, excessive noise such as from cosmic-ray impacts, prevalent within the South Atlantic Anomaly, can also degrade satellite radiance measurements. Saturation specifically pertains to observations of very bright surfaces such as sunglint over open water or thick clouds. When saturation occurs, additional photoelectric charge generated at the saturated pixel may overflow to pixels adjacent to a saturated area and be reflected as a distorted image in the final sensor output. When these effects cannot be corrected to an acceptable level for science-quality retrievals, flagging of the affected pixels is indicated. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm spectral range; our decorrelation index (DI for brevity) is simply defined as a DI of 1−r. DI increases with anomalous additive effects or excessive noise in either radiances, the most likely cause in data from the Ozone Monitoring Instrument (OMI), or irradiances. DI is relatively straightforward to use and interpret and can be computed for different wavelength intervals. We developed a set of DIs for two spectral channels of the OMI, a hyperspectral pushbroom imaging spectrometer. For each OMI spatial measurement, we define 14 wavelength-dependent DIs within the OMI visible channel (350–498 nm) and six DIs in its ultraviolet 2 (UV2) channel (310–370 nm). As defined, DIs reflect a continuous range of deviations of observed spectra from the reference irradiance spectrum that are complementary to the binary saturation possibility warning (SPW) flags currently provided for each individual spectral or spatial pixel in the OMI radiance data set. Smaller values of DI are also caused by a number of geophysical factors; this allows one to obtain interesting physical results on the global distribution of spectral variations.

Description: Aerial emission sampling of four natural gas boiler stack plumes was conducted using an unmanned aerial system (UAS) equipped with a lightweight sensor–sampling system (the “Kolibri”) for measurement of nitrogen oxide (NO), and nitrogen dioxide (NO2), carbon dioxide (CO2), and carbon monoxide (CO). Flights (n = 22) ranged from 11 to 24 min in duration at two different sites. The UAS was maneuvered into the plumes with the aid of real-time CO2 telemetry to the ground operators and, at one location, a second UAS equipped with an infrared–visible camera. Concentrations were collected and recorded at 1 Hz. The maximum CO2, CO, NO, and NO2 concentrations in the plume measured were 10 000, 7, 27, and 1.5 ppm, respectively. Comparison of the NOx emissions between the stack continuous emission monitoring systems and the UAS–Kolibri for three boiler sets showed an average of 5.6 % and 3.5 % relative difference for the run-weighted and carbon-weighted average emissions, respectively. To our knowledge, this is the first evidence of the accuracy performance of UAS-based emission factors against a source of known strength.

Description: We present a novel rocket-borne ion mass spectrometer named ROMARA (ROcket-borne MAss spectrometer for Research in the Atmosphere) for measuring atmospheric positive and negative ions (atomic, molecular and cluster ions) and positively and negatively charged meteor smoke particles. Our ROMARA instrument has, compared to previous rocket-borne ion mass spectrometers, a markedly larger mass range of up to m/z 2000 and a larger sensitivity, particularly for meteor smoke particle detection. The major objectives of this first ROMARA flight included the following: a functional test of the ROMARA instrument, measurements between 55 and 121 km in the mass range of atmospheric positive and negative ions, a first attempt to conduct mass spectrometric measurements in the mass range of meteor smoke particles with mass-to-charge ratios up to m/z 2000, and measurements inside a polar mesospheric winter echo layer as detected by ground-based radar. Our ROMARA measurements took place on the Arctic island of Andøya, Norway, at around noon in April 2018 and represented an integral part of the polar mesospheric winter radar echo (PMWE) rocket campaign. During the rocket flight, ROMARA was operated in a measurement mode, offering maximum sensitivity and the ability to qualitatively detect total ion signatures even beyond its mass-resolving mass range. On this first ROMARA flight we were able to meet all of our objectives. We detected atmospheric species including positive atomic, molecular and cluster ions along with negative molecular ions up to about m/z 100. Above m/z 2000, ROMARA measured strong negative-ion signatures, which are likely due to negatively charged meteor smoke particles.

Description: Atmospheric aerosols have been known to be a major source of uncertainties in CO2 concentrations retrieved from space. In this study, we investigate the added value of multi-angle polarimeter (MAP) measurements in the context of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. To this end, we compare aerosol-induced XCO2 errors from standard retrievals using a spectrometer only (without MAP) with those from retrievals using both MAP and a spectrometer. MAP observations are expected to provide information about aerosols that is useful for improving XCO2 accuracy. For the purpose of this work, we generate synthetic measurements for different atmospheric and geophysical scenes over land, based on which XCO2 retrieval errors are assessed. We show that the standard XCO2 retrieval approach that makes no use of auxiliary aerosol observations returns XCO2 errors with an overall bias of 1.12 ppm and a spread (defined as half of the 15.9–84.1 percentile range) of 2.07 ppm. The latter is far higher than the required XCO2 accuracy (0.5 ppm) and precision (0.7 ppm) of the CO2M mission. Moreover, these XCO2 errors exhibit a significantly larger bias and scatter at high aerosol optical depth, high aerosol altitude, and low solar zenith angle, which could lead to worse performance in retrieving XCO2 from polluted areas where CO2 and aerosols are co-emitted. We proceed to determine MAP instrument specifications in terms of wavelength range, number of viewing angles, and measurement uncertainties that are required to achieve XCO2 accuracy and precision targets of the mission. Two different MAP instrument concepts are considered in this analysis. We find that for either concept, MAP measurement uncertainties on radiance and degree of linear polarization should be no more than 3 % and 0.003, respectively. A retrieval exercise using MAP and spectrometer measurements of the synthetic scenes is carried out for each of the two MAP concepts. The resulting XCO2 errors have an overall bias of −0.004 ppm and a spread of 0.54 ppm for one concept, and a bias of 0.02 ppm and a spread of 0.52 ppm for the other concept. Both are compliant with the CO2M mission requirements; the very low bias is especially important for proper emission estimates. For the test ensemble, we find effectively no dependence of the XCO2 errors on aerosol optical depth, altitude of the aerosol layer, and solar zenith angle. These results indicate a major improvement in the retrieved XCO2 accuracy with respect to the standard retrieval approach, which could lead to a higher data yield, better global coverage, and a more comprehensive determination of CO2 sinks and sources. As such, this outcome underlines the contribution of, and therefore the need for, a MAP instrument aboard the CO2M mission.

Description: Fugitive emissions from tailings ponds contribute significantly to facility emissions in the Alberta oil sands, but details on chemical emission profiles and the temporal and spatial variability of emissions to the atmosphere are sparse, since flux measurement techniques applied for compliance monitoring have their limitations. In this study, open-path Fourier transform infrared spectroscopy was evaluated as a potential alternative method for quantifying spatially representative fluxes for various pollutants (methane, ammonia, and alkanes) from a particular pond, using vertical-flux-gradient and inverse-dispersion methods. Gradient fluxes of methane averaged 4.3 g m−2 d−1 but were 44 % lower than nearby eddy covariance measurements, while inverse-dispersion fluxes agreed to within 30 %. With the gradient fluxes method, significant NH3 emission fluxes were observed (0.05 g m−2 d−1, 42 t yr−1), and total alkane fluxes were estimated to be 1.05 g m−2 d−1 (881 t yr−1), representing 9.6 % of the facility emissions.

Description: Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

Description: In order to mitigate climate change, it is crucial to understand urban greenhouse gas (GHG) emissions precisely, as more than two-thirds of the anthropogenic GHG emissions worldwide originate from cities. Nowadays, urban emission estimates are mainly based on bottom-up calculation approaches with high uncertainties. A reliable and long-term top-down measurement approach could reduce the uncertainty of these emission inventories significantly. We present the Munich Urban Carbon Column network (MUCCnet), the world's first urban sensor network, which has been permanently measuring GHGs, based on the principle of differential column measurements (DCMs), since summer 2019. These column measurements and column concentration differences are relatively insensitive to vertical redistribution of tracer masses and surface fluxes upwind of the city, making them a favorable input for an inversion framework and, therefore, a well-suited candidate for the quantification of GHG emissions. However, setting up such a stationary sensor network requires an automated measurement principle. We developed our own fully automated enclosure systems for measuring column-averaged CO2, CH4 and CO concentrations with a solar-tracking Fourier transform spectrometer (EM27/SUN) in a fully automated and long-term manner. This also includes software that starts and stops the measurements autonomously and can be used independently from the enclosure system. Furthermore, we demonstrate the novel applications of such a sensor network by presenting the measurement results of our five sensor systems that are deployed in and around Munich. These results include the seasonal cycle of CO2 since 2015, as well as concentration gradients between sites upwind and downwind of the city. Thanks to the automation, we were also able to continue taking measurements during the COVID-19 lockdown in spring 2020. By correlating the CO2 column concentration gradients to the traffic amount, we demonstrate that our network is capable of detecting variations in urban emissions. The measurements from our unique sensor network will be combined with an inverse modeling framework that we are currently developing in order to monitor urban GHG emissions over years, identify unknown emission sources and assess how effective the current mitigation strategies are. In summary, our achievements in automating column measurements of GHGs will allow researchers all over the world to establish this approach for long-term greenhouse gas monitoring in urban areas.

Description: The recent development and improvement of commercial laser-based spectrometers have expanded in situ continuous observations of water vapour (H2O) stable isotope compositions (e.g. δ18O and δ2H) in a variety of sites worldwide. However, we still lack continuous observations in the Amazon, a region that significantly influences atmospheric and hydrological cycles on local to global scales. In order to achieve accurate on-site observations, commercial water isotope analysers require regular in situ calibration, which includes the correction of H2O concentration dependence ([H2O] dependence) of isotopic measurements. Past studies have assessed the [H2O] dependence for air with H2O concentrations of up to 35 000 ppm, a value that is frequently surpassed in tropical rainforest settings like the central Amazon where we plan continuous observations. Here we investigated the performance of two commercial analysers (L1102i and L2130i models, Picarro, Inc., USA) for measuring δ18O and δ2H in atmospheric moisture at four different H2O levels from 21 500 to 41 000 ppm. These H2O levels were created by a custom-built calibration unit designed for regular in situ calibration. Measurements on the newer analyser model (L2130i) had better precision for δ18O and δ2H and demonstrated less influence of H2O concentration on the measurement accuracy at each concentration level compared to the older L1102i. Based on our findings, we identified the most appropriate calibration strategy for [H2O] dependence, adapted to our calibration system. The best strategy required conducting a two-point calibration with four different H2O concentration levels, carried out at the beginning and end of the calibration interval. The smallest uncertainties in calibrating [H2O] dependence of isotopic accuracy of the two analysers were achieved using a linear surface fitting method and a 28 h calibration interval, except for the δ18O accuracy of the L1102i analyser for which the cubic fitting method gave the best results. The uncertainties in [H2O] dependence calibration did not show any significant difference using calibration intervals from 28 up to 196 h; this suggested that one [H2O] dependence calibration per week for the L2130i and L1102i analysers is sufficient. This study shows that the cavity ring-down spectroscopy (CRDS) analysers, appropriately calibrated for [H2O] dependence, allow the detection of natural signals of stable water vapour isotopes at very high humidity levels, which has promising implications for water cycle studies in areas like the central Amazon rainforest and other tropical regions.

Description: Continuous advancements in pulsed wind lidar technology have enabled compelling wind turbulence measurements within the atmospheric boundary layer with probe lengths shorter than 20 m and sampling frequency on the order of 10 Hz. However, estimates of the radial velocity from the back-scattered lidar signal are inevitably affected by an averaging process within each probe volume, generally modeled as a convolution between the true velocity projected along the lidar line-of-sight and an unknown weighting function representing the energy distribution of the laser pulse along the probe length. As a result, the spectral energy of the turbulent velocity fluctuations is damped within the inertial subrange, thus not allowing one to take advantage of the achieved spatio-temporal resolution of the lidar technology. We propose to correct the turbulent energy damping on the lidar measurements by reversing the effect of a low-pass filter, which can be estimated directly from the power spectral density of the along-beam velocity component. Lidar data acquired from three different field campaigns are analyzed to describe the proposed technique, investigate the variability of the filter parameters and, for one dataset, assess the corrected velocity variance against sonic anemometer data. It is found that the order of the low-pass filter used for modeling the energy damping on the lidar velocity measurements has negligible effects on the correction of the second-order statistics of the wind velocity. In contrast, the cutoff wavenumber plays a significant role in spectral correction encompassing the smoothing effects connected with the lidar probe length. Furthermore, the variability of the spatial averaging on wind lidar measurements is investigated for different wind speed, turbulence intensity, and sampling height. The results confirm that the effects of spatial averaging are enhanced with decreasing wind speed, smaller integral length scale and, thus, for smaller sampling height. The method proposed for the correction of the second-order turbulent statistics of wind-velocity lidar data is a compelling alternative to existing methods because it does not require any input related to the technical specifications of the used lidar system, such as the energy distribution over the laser pulse and lidar probe length. On the other hand, the proposed method assumes that surface-layer similarity holds.

Description: Methane is the second most important anthropogenic greenhouse gas in the Earth's atmosphere. To effectively reduce these emissions, a good knowledge of source locations and strengths is required. Airborne remote sensing instruments such as the Airborne Visible InfraRed Imaging Spectrometer – Next Generation (AVIRIS-NG) with meter-scale imaging capabilities are able to yield information about the locations and magnitudes of methane sources. In this study, we successfully applied the weighting function modified differential optical absorption spectroscopy (WFM-DOAS) algorithm to AVIRIS-NG data measured in Canada and the Four Corners region. The WFM-DOAS retrieval is conceptually located between the statistical matched filter (MF) and the optimal-estimation-based iterative maximum a posteriori DOAS (IMAP-DOAS) retrieval algorithm, both of which were already applied successfully to AVIRIS-NG data. The WFM-DOAS algorithm is based on a first order Taylor series approximation of the Lambert–Beer law using only one precalculated radiative transfer calculation per scene. This yields the fast quantitative processing of large data sets. We detected several methane plumes in the AVIRIS-NG images recorded during the Arctic-Boreal Vulnerability Experiment (ABoVE) Airborne Campaign and successfully retrieved a coal mine ventilation shaft plume observed during the Four Corners measurement campaign. The comparison between IMAP-DOAS, MF, and WFM-DOAS showed good agreement for the coal mine ventilation shaft plume. An additional comparison between MF and WFM-DOAS for a subset of plumes showed good agreement for one plume and some differences for the others. For five plumes, the emissions were estimated using a simple cross-sectional flux method. The retrieved fluxes originated from well pads, cold vents, and a coal mine ventilation shaft and ranged between (155 ± 71) kg (CH4) h−1 and (1220 ± 450) kg (CH4) h−1. The wind velocity was a significant source of uncertainty in all plumes, followed by the single pixel retrieval noise and the uncertainty due to atmospheric variability. The noise of the retrieved CH4 imagery over bright surfaces (〉1 µW cm−2 nm−1 sr−1 at 2140 nm) was typically ±2.3 % of the background total column of CH4 when fitting strong absorption lines around 2300 nm but could reach over ±5 % for darker surfaces (

Description: Lidar backscatter and wind retrievals of the planetary boundary layer height (PBLH) are assimilated into 22-hourly forecasts from the NASA Unified – Weather and Research Forecast (NU-WRF) model during the Plains Elevated Convection at Night (PECAN) campaign on 11 July 2015 in Greensburg, Kansas, using error statistics collected from the model profiles to compute the necessary covariance matrices. Two separate forecast runs using different PBL physics schemes were employed, and comparisons with six independent radiosonde profiles were made for each run. Both of the forecast runs accurately predicted the PBLH and the state variable profiles within the planetary boundary layer during the early morning, and the assimilation had a small impact during this time. In the late afternoon, the forecast runs showed decreased accuracy as the convective boundary layer developed. However, assimilation of the Doppler lidar PBLH observations was found to improve the temperature and V-velocity profiles relative to independent radiosonde profiles. Water vapor was overcorrected, leading to increased differences with independent data. Errors in the U velocity were made slightly larger. The computed forecast error covariances between the PBLH and state variables were found to rise in the late afternoon, leading to the larger improvements in the afternoon. This work represents the first effort to assimilate PBLH into forecast states using ensemble methods.

Description: Trace gases play a key role in the chemistry of urban atmospheres. Therefore, knowledge about their spatial distribution is needed to fully characterize air quality in urban areas. Using a new Multi-AXis Differential Optical Absorption Spectroscopy two-dimensional (MAXDOAS-2D) instrument, along with an inversion algorithm (bePRO), we report the first two-dimensional maps of nitrogen dioxide (NO2) and nitrous acid (HONO) concentrations in the city of Madrid, Spain. Measurements were made during 2 months (6 May–5 July 2019), and peak mixing ratios of 12 and 0.7 ppbv (parts per billion by volume) for NO2 and HONO, respectively, were observed in the early morning in the southern part of the downtown area. We found good general agreement between the MAXDOAS-2D mesoscale observations – which provide a typical spatial range of a few kilometers – and the in situ measurements provided by Madrid's air quality monitoring stations. In addition to vertical profiles, we studied the horizontal gradients of NO2 in the surface layer by applying the different horizontal light path lengths in the two spectral regions included in the NO2 spectral analysis: ultraviolet (UV, at 360 nm) and visible (VIS, 477 nm). We also investigate the sensitivity of the instrument to infer vertically distributed information on aerosol extinction coefficients and discuss possible future ways to improve the retrievals. The retrieval of two-dimensional distributions of trace gas concentrations reported here provides valuable spatial information for the study of air quality in the city of Madrid.

Description: The subgrid spatial variability of water vapor is an important geophysical parameter for modeling tropical convention and cloud processes in atmospheric models. This study maps sub-kilometer spatial structures in total atmospheric column water vapor with visible to shortwave infrared (VSWIR) imaging spectroscopy. We describe our inversion approach and validate its accuracy with coincident measurements by airborne imaging spectrometers and the AERONET ground-based observation network. Next, data from NASA's AVIRIS-NG spectrometer enable the highest-resolution measurement to date of water vapor's spatial variability and scaling properties. We find second-order structure function scaling exponents consistent with prior studies of convective atmospheres. Airborne lidar data show that this total column measurement provides information about variability in the lower troposphere. We conclude by discussing the implications of these measurements and paths toward future campaigns to build upon these results.

Description: We discuss an explicit and consistent aerosol correction for cloud and NO2 retrievals that are based on the mixed Lambertian-equivalent reflectivity (MLER) concept. We apply the approach to data from the Ozone Monitoring Instrument (OMI) for a case study over northeastern China. The cloud algorithm reports an effective cloud pressure, also known as cloud optical centroid pressure (OCP), from oxygen dimer (O2−O2) absorption at 477 nm after determining an effective cloud fraction (ECF) at 466 nm. The retrieved cloud products are then used as inputs to the standard OMI NO2 algorithm. A geometry-dependent Lambertian-equivalent reflectivity (GLER), which is a proxy of surface bidirectional reflectance, is used for the ground reflectivity in our implementation of the MLER approach. The current standard OMI cloud and NO2 algorithms implicitly account for aerosols by treating them as nonabsorbing particulate scatters within the cloud retrieval. To explicitly account for aerosol effects, we use a model of aerosol optical properties from a global aerosol assimilation system and radiative transfer computations. This approach allows us to account for aerosols within the OMI cloud and NO2 algorithms with relatively small changes. We compare the OMI cloud and NO2 retrievals with implicit and explicit aerosol corrections over our study area.

Description: Accurate estimation of the melting level (ML) is essential in radar rainfall estimation to mitigate the bright band enhancement, classify hydrometeors, correct for rain attenuation and calibrate radar measurements. This paper presents a novel and robust ML-detection algorithm based on either vertical profiles (VPs) or quasi-vertical profiles (QVPs) built from operational polarimetric weather radar scans. The algorithm depends only on data collected by the radar itself, and it is based on the combination of several polarimetric radar measurements to generate an enhanced profile with strong gradients related to the melting layer. The algorithm is applied to 1 year of rainfall events that occurred over southeast England, and the results were validated using radiosonde data. After evaluating all possible combinations of polarimetric radar measurements, the algorithm achieves the best ML detection when combining VPs of ZH, ρHV and the gradient of the velocity (gradV), whereas, for QVPs, combining profiles of ZH, ρHV and ZDR produces the best results, regardless of the type of rain event. The root mean square error in the ML detection compared to radiosonde data is ∼200 m when using VPs and ∼250 m when using QVPs.

Description: Obtaining precise continuous measurements of water vapor isotopic composition in dry places (polar or high-altitude regions) is an important challenge. The current limitation is the strong influence of humidity on the measured water isotopic composition by laser spectroscopy instruments for low humidity levels (below 3000 ppmv). This problem is addressed by determining the relationships between humidity and measured δ18O and δD of known water standards. Here, we present the development of a robust field instrument able to generate water vapor, down to 70 ppmv, at very stable humidity levels (average 1σ lower than 10 ppmv). This instrument, operated by a Raspberry interface, can be coupled to a commercial laser spectroscopy instrument. We checked the stability of the system as well as its accuracy when expressing the measured isotopic composition of water vapor on the VSMOW–SLAP (Vienna Standard Mean Ocean Water – Standard Light Antarctic Precipitation) scale. It proved to be highly stable during autonomous operation over more than 1 year at the East Antarctic Concordia and Dumont d'Urville stations.

Description: A major challenge for in situ observations in mixed-phase clouds remains the phase discrimination and sizing of cloud hydrometeors. In this work, we present a new method for determining the phase of individual cloud hydrometeors based on their angular-light-scattering behavior employed by the PHIPS (Particle Habit Imaging and Polar Scattering) airborne cloud probe. The phase discrimination algorithm is based on the difference of distinct features in the angular-scattering function of spherical and aspherical particles. The algorithm is calibrated and evaluated using a large data set gathered during two in situ aircraft campaigns in the Arctic and Southern Ocean. Comparison of the algorithm with manually classified particles showed that we can confidently discriminate between spherical and aspherical particles with a 98 % accuracy. Furthermore, we present a method for deriving particle size distributions based on single-particle angular-scattering data for particles in a size range from 100 µm ≤ D ≤ 700 µm and 20 µm ≤ D ≤ 700 µm for droplets and ice particles, respectively. The functionality of these methods is demonstrated in three representative case studies.

Description: The NOAA Global Monitoring Laboratory serves as the World Meteorological Organization Global Atmosphere Watch (WMO/GAW) Central Calibration Laboratory (CCL) for CO2 and is responsible for maintaining the WMO/GAW mole fraction scale used as a reference within the WMO/GAW program. The current WMO-CO2-X2007 scale is embodied by 15 aluminum cylinders containing modified natural air, with CO2 mole fractions determined using the NOAA manometer from 1995 to 2006. We have made two minor corrections to historical manometric records: fixing an error in the applied second virial coefficient of CO2 and accounting for loss of a small amount of CO2 to materials in the manometer during the measurement process. By incorporating these corrections, extending the measurement records of the original 15 primary standards through 2015, and adding four new primary standards to the suite, we define a new scale, identified as WMO-CO2-X2019. The new scale is 0.18 µmol mol−1 (ppm) greater than the previous scale at 400 ppm CO2. While this difference is small in relative terms (0.045 %), it is significant in terms of atmospheric monitoring. All measurements of tertiary-level standards will be reprocessed to WMO-CO2-X2019. The new scale is more internally consistent than WMO-CO2-X2007 owing to revisions in propagation and should result in an overall improvement in atmospheric data records traceable to the CCL.

Description: Atmospheric nitrogen oxides (NO + NO2 = NOx) have been measured at the Cape Verde Atmospheric Observatory (CVAO) in the tropical Atlantic (16∘51′ N, 24∘52′ W) since October 2006. These measurements represent a unique time series of NOx in the background remote troposphere. Nitrogen dioxide (NO2) is measured via photolytic conversion to nitric oxide (NO) by ultraviolet light-emitting diode arrays followed by chemiluminescence detection. Since the measurements began, a blue light converter (BLC) has been used for NO2 photolysis, with a maximum spectral output of 395 nm from 2006 to 2015 and of 385 nm from 2015 onwards. The original BLC used was constructed with a Teflon-like material and appeared to cause an overestimation of NO2 when illuminated. To avoid such interferences, a new additional photolytic converter (PLC) with a quartz photolysis cell (maximum spectral output also 385 nm) was implemented in March 2017. Once corrections are made for the NO2 artefact from the original BLC, the two NO2 converters are shown to give comparable NO2 mixing ratios (BLC = 0.99 × PLC + 0.7 ppt, linear least-squares regression), giving confidence in the quantitative measurement of NOx at very low levels. Data analysis methods for the NOx measurements made at CVAO have been developed and applied to the entire time series to produce an internally consistent and high-quality long-term data set. NO has a clear diurnal pattern with a maximum mixing ratio of 2–10 ppt during the day depending on the season and ∼ 0 ppt during the night. NO2 shows a fairly flat diurnal signal, although a small increase in daytime NOx is evident in some months. Monthly average mixing ratios of NO2 vary between 5 and 30 ppt depending on the season. Clear seasonal trends in NO and NO2 levels can be observed with a maximum in autumn and winter and a minimum in spring and summer.

Description: Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal-estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigão field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for the IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties) and that the combined IR + MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR + DIAL and MW + DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is a slight increase in the information content in the retrieved temperature profile using the IR + DIAL relative to the IR-only; this was not observed in the MW + DIAL retrieval.

Description: On 16–17 February 2020, dust within the Saharan Air Layer (SAL) from western Africa moved over the eastern Atlantic Ocean. Satellite imagery and products from the ABI on GOES-16, VIIRS on NOAA-20, and CALIOP on CALIPSO, along with retrieved values of layer and total precipitable water (TPW) from MIRS and NUCAPS, respectively, were used to identify dust within the SAL over the eastern Atlantic Ocean. Various satellite imagery and products were also used to characterize the distribution of water vapor within the SAL. There was a distinct pattern between dust detection and dust masking and values of precipitable water. Specifically, dust was detected when values of layer TPW were approximately 14 mm; in addition, dust was masked when values of layer TPW were approximately 28 mm. In other words, water vapor masked infrared dust detection if sufficient amounts of water vapor existed in a column. Results herein provide observational support to two recent numerical studies that concluded water vapor can mask infrared detection of airborne dust.

Description: The aerosol fine-mode fraction (FMF) is an important optical parameter of aerosols, and the FMF is difficult to accurately retrieve by traditional satellite remote sensing methods. In this study, FMF retrieval was carried out based on the multiangle polarization data of Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from Lidar (PARASOL), which overcame the shortcomings of the FMF retrieval algorithm in our previous research. In this research, FMF retrieval was carried out in China and compared with the AErosol RObotic NETwork (AERONET) ground-based observation results, Moderate Resolution Imaging Spectroradiometer (MODIS) FMF products, and Generalized Retrieval of Aerosol and Surface Properties (GRASP) FMF results. In addition, the FMF retrieval algorithm was applied, a new FMF dataset was produced, and the annual and quarterly average FMF results from 2006 to 2013 were obtained for all of China. The research results show that the FMF retrieval results of this study are comparable with the AERONET ground-based observation results in China and the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), and the proportion of results that fall within the expected error (Within EE) are 0.770, 0.143, 0.170, and 65.01 %, respectively. Compared with the MODIS FMF products, the FMF results of this study are closer to the AERONET ground-based observations. Compared with the FMF results of GRASP, the FMF results of this study are closer to the spatial variation in the ratio of PM2.5 to PM10 near the ground.

Description: An evaluation of the performance and relative accuracy of a Cavity Attenuated Phase-Shift Single Scattering Albedo Monitor (CAPS PMSSA; Aerodyne Research, Inc.) was conducted in an optical-closure study with proven technologies: Cavity Attenuated Phase-Shift Particle Extinction Monitor (CAPS PMex; Aerodyne Research, Inc.), three-wavelength integrating nephelometer (TSI Model 3563) and three-wavelength filter-based Particle Soot Absorption Photometer (PSAP; Radiance Research Inc.). The evaluation was conducted by connecting the instruments to a controlled aerosol generation system and comparing the measured scattering, extinction and absorption coefficients measured by the CAPS PMSSA with the independent measurements. Three different particle types were used to generate aerosol samples with single-scattering albedos (SSAs) ranging from 0.4 to 1.0 at 630 nm wavelength. The CAPS PMSSA measurements compared well with the proven technologies. Extinction measurement comparisons exhibited a slope of the linear regression line for the full dataset between 1.05 and 1.01, an intercept below ±1.5×10-6 m−1 (±1.5 Mm−1), and a regression coefficient R2〉0.99, whereas scattering measurements had a slope between 0.90 and 1.04, an intercept of less than ±2.0×10-6 m−1 (2.0 Mm−1), and a coefficient R2〉0.96. The derived CAPS PMSSA absorption compared well to the PSAP measurements for the small particle sizes and modest (0.4 to 0.6) SSA values tested, with a linear regression slope between 0.90 and 1.07, an intercept of ±3.0×10-6 m−1 (3.0 Mm−1), and a coefficient R2〉0.99. For the SSA measurements, agreement was highest (regression slopes within 1 %) for SSA =1.0 particles at extinction levels of per tens of inverse megameters and above; however, as extinctions approach 0, small uncertainties in the baseline can introduce larger errors. SSA measurements for absorbing particles exhibited absolute differences up to 18 %, though it is not clear which measurement had the best relative accuracy. For a given particle type, the CAPS PMSSA instrument exhibited the lowest scatter around the average. This study demonstrates that the CAPS PMSSA is a robust and reliable instrument for the direct measurement of the scattering and extinction coefficients and thus SSA. This conclusion also holds for the indirect measurement of the absorption coefficient with the constraint that the relative accuracy of this particular determination degrades as the SSA and particle size increases.

Description: Sea ice is difficult, expensive, and potentially dangerous to observe in nature. The remoteness of the Arctic Ocean and Southern Ocean complicates sampling logistics, while the heterogeneous nature of sea ice and rapidly changing environmental conditions present challenges for conducting process studies. Here, we describe the Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC), a laboratory facility designed to reproduce polar processes and overcome some of these challenges. The RvG-ASIC is an open-topped 3.5 m3 glass tank housed in a cold room (temperature range: −55 to +30 ∘C). The RvG-ASIC is equipped with a wide suite of instruments for ocean, sea ice, and atmospheric measurements, as well as visible and UV lighting. The infrastructure, available instruments, and typical experimental protocols are described. To characterise some of the technical capabilities of our facility, we have quantified the timescale over which our chamber exchanges gas with the outside, τl=(0.66±0.07) d, and the mixing rate of our experimental ocean, τm=(4.2±0.1) min. Characterising our light field, we show that the light intensity across the tank varies by less than 10 % near the centre of the tank but drops to as low as 60 % of the maximum intensity in one corner. The temperature sensitivity of our light sources over the 400 to 700 nm range (PAR) is (0.028±0.003) W m−2 ∘C−1, with a maximum irradiance of 26.4 W m−2 at 0 ∘C; over the 320 to 380 nm range, it is (0.16±0.1) W m−2 ∘C−1, with a maximum irradiance of 5.6 W m−2 at 0 ∘C. We also present results characterising our experimental sea ice. The extinction coefficient for PAR varies from 3.7 to 6.1 m−1 when calculated from irradiance measurements exterior to the sea ice and from 4.4 to 6.2 m−1 when calculated from irradiance measurements within the sea ice. The bulk salinity of our experimental sea ice is measured using three techniques, modelled using a halo-dynamic one-dimensional (1D) gravity drainage model, and calculated from a salt and mass budget. The growth rate of our sea ice is between 2 and 4 cm d−1 for air temperatures of (-9.2±0.9) ∘C and (-26.6±0.9) ∘C. The PAR extinction coefficients, vertically integrated bulk salinities, and growth rates all lie within the range of previously reported comparable values for first-year sea ice. The vertically integrated bulk salinity and growth rates can be reproduced well by a 1D model. Taken together, the similarities between our laboratory sea ice and observations in nature, as well as our ability to reproduce our results with a model, give us confidence that sea ice grown in the RvG-ASIC is a good representation of natural sea ice.

Description: The Compact Rayleigh Autonomous Lidar (CORAL) is the first fully autonomous middle atmosphere lidar system to provide density and temperature profiles from 15 to approximately 90 km altitude. From October 2019 to October 2020, CORAL acquired temperature profiles on 243 out of the 365 nights (66 %) above Río Grande, southern Argentina, a cadence which is 3–8 times larger as compared to conventional human-operated lidars. The result is an unprecedented data set with measurements on 2 out of 3 nights on average and high temporal (20 min) and vertical (900 m) resolution. The first studies using CORAL data have shown, for example, the evolution of a strong atmospheric gravity wave event and its impact on the stratospheric circulation. We describe the instrument and its novel software which enables automatic and unattended observations over periods of more than a year. A frequency-doubled diode-pumped pulsed Nd:YAG laser is used as the light source, and backscattered photons are detected using three elastic channels (532 nm wavelength) and one Raman channel (608 nm wavelength). Automatic tracking of the laser beam is realized by the implementation of the conical scan (conscan) method. The CORAL software detects blue sky conditions and makes the decision to start the instrument based on local meteorological measurements, detection of stars in all-sky images, and analysis of European Center for Medium-range Weather Forecasts Integrated Forecasting System data. After the instrument is up and running, the strength of the lidar return signal is used as additional information to assess sky conditions. Safety features in the software allow for the operation of the lidar even in marginal weather, which is a prerequisite to achieving the very high observation cadence.

Description: The microwave temperature profiler (MTP), an airborne passive microwave radiometer, measures radiances, recorded as counts and calibrated to brightness temperatures, in order to estimate temperature profiles around flight altitude. From these data, quantities such as potential temperature gradients and static stability, indicating the state of the atmosphere, can be derived and used to assess important dynamical processes (e.g., gravity waves or stability assessments). DLR has acquired a copy of the MTP from NASA–JPL, which was designed as a wing-canister instrument and is deployed on the German High Altitude LOng range research aircraft (HALO). For this instrument a thorough analysis of instrument characteristics has been made in order to correctly determine the accuracy and precision of MTP measurements. Using a laboratory setup, the frequency response function and antenna diagram of the instrument were carefully characterized. A cold chamber was used to simulate the changing in-flight conditions and to derive noise characteristics as well as reliable calibration parameters for brightness temperature calculations, which are compared to those calculated from campaign data. The MTP shows quite large changes in the instrument state, imposing considerable changes in calibration parameters over the course of a single measurement flight; using a built-in heated target for calibration may yield large errors in brightness temperatures due to a misinterpretation of the measured absolute temperature. Applying the corrections presented herein to the calibration parameter calculations, the measurement noise becomes the dominant source of uncertainty and it is possible to measure the brightness temperatures around flight level (closely related to the absolute temperature close to the instrument) with a precision of 0.38 K. Furthermore, radiative transfer simulations, using the Py4CAtS package in a pencil-beam approach, indicate that the altitude range of the sensitivity of the MTP instrument can be increased by applying a modified measurement strategy. This is the first time such an extensive characterization of an MTP instrument, including a thorough calibration strategy assessment, has been published. The presented results, relevant for the wing-canister design of the MTP instrument, are important when processing MTP data: knowledge of the relevant uncertainties and instrument characteristics is essential for retrieval setup and is mandatory to correctly identify and interpret significant atmospheric temperature fluctuations.

Description: Ozone (O3) plays a significant role in weather and climate on regional to global spatial scales. Most studies on the variability in the total column of O3 (TCO) are typically carried out using daytime data. Based on knowledge of the chemistry and transport of O3, significant deviations between daytime and night-time O3 are only expected either in the planetary boundary layer (PBL) or high in the stratosphere or mesosphere, with little effect on the TCO. Hence, we expect the daytime and night-time TCO to be very similar. However, a detailed evaluation of satellite measurements of daytime and night-time TCO is still lacking, despite the existence of long-term records of both. Thus, comparing daytime and night-time TCOs provides a novel approach to verifying the retrieval algorithms of instruments such as the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS). In addition, such a comparison also helps to assess the value of night-time TCO for scientific research. Applying this verification on the AIRS and the MLS data, we identified inconsistencies in observations of O3 from both satellite instruments. For AIRS, daytime–night-time differences were found over oceans resembling cloud cover patterns and over land, mostly over dry land areas, which is likely related to infrared surface emissivity. These differences point to issues with the representation of both processes in the AIRS retrieval algorithm. For MLS, a major issue was identified with the “ascending–descending” orbit flag, used to discriminate night-time and daytime MLS measurements. Disregarding this issue, MLS day–night differences were significantly smaller than AIRS day–night differences, providing additional support for the retrieval method origin of AIRS in stratospheric column ozone (SCO) day–night differences. MLS day–night differences are dominated by the upper-stratospheric and mesospheric diurnal O3 cycle. These results provide useful information for improving infrared O3 products.

Description: All-sky cameras are frequently used to detect cloud cover; however, this work explores the use of these instruments for the more complex purpose of extracting relative sky radiances. An all-sky camera (SONA202-NF model) with three colour filters narrower than usual for this kind of cameras is configured to capture raw images at seven exposure times. A detailed camera characterization of the black level, readout noise, hot pixels and linear response is carried out. A methodology is proposed to obtain a linear high dynamic range (HDR) image and its uncertainty, which represents the relative sky radiance (in arbitrary units) maps at three effective wavelengths. The relative sky radiances are extracted from these maps and normalized by dividing every radiance of one channel by the sum of all radiances at this channel. Then, the normalized radiances are compared with the sky radiance measured at different sky points by a sun and sky photometer belonging to the Aerosol Robotic Network (AERONET). The camera radiances correlate with photometer ones except for scattering angles below 10∘, which is probably due to some light reflections on the fisheye lens and camera dome. Camera and photometer wavelengths are not coincident; hence, camera radiances are also compared with sky radiances simulated by a radiative transfer model at the same camera effective wavelengths. This comparison reveals an uncertainty on the normalized camera radiances of about 3.3 %, 4.3 % and 5.3 % for 467, 536 and 605 nm, respectively, if specific quality criteria are applied.

Description: A 2-year measurement campaign of the ZephIR 300 vertical profiling continuous-wave (CW) focusing wind lidar has been carried out by the Royal Netherlands Meteorological Institute (KNMI) at the Cabauw site. We focus on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213 m tall meteorological mast. We find an overall availability of quality-controlled wind lidar data of 97 % to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm h−1 or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m s−1 with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. The mean bias in the wind direction is within 2∘, which is of the same order as the combined uncertainty in the alignment of the wind lidars and the mast wind vanes. The well-known 180∘ error in the wind direction output for this type of instrument occurs about 9 % of the time. A correction scheme based on data of an auxiliary wind vane at a height of 10 m is applied, leading to a reduction of the 180∘ error below 2 %. This scheme can be applied in real-time applications in the situation that a nearby freely exposed mast with wind direction measurements at a single height is available.

Description: A high-resolution (1.25 m) large eddy simulation (LES) of the nocturnal cloud-topped marine boundary layer is used to evaluate random error as a function of continuous track length L for virtual aircraft measurements of turbulent fluxes of sensible heat, latent heat, and horizontal momentum. Results are compared with the widely used formula of Lenschow and Stankov (1986). In support of these comparisons, the relevant integral length scales and correlations are evaluated and documented. It is shown that for heights up to approximately 100 m (z/zi=0.12), the length scales are accurately predicted by empirical expressions of the form If=Azb. The Lenschow and Stankov expression is found to be remarkably accurate at predicting the random error for shorter (7–10 km) flight tracks, but the empirically determined errors decay more rapidly with L than the L-1/2 relationship predicted from theory. Consistent with earlier findings, required track lengths to obtain useful precision increase sharply with altitude. In addition, an examination is undertaken of the role of uncertainties in empirically determined integral length scales and correlations in flux uncertainties as well as of the flux errors associated with crosswind and along-wind flight tracks. It is found that for 7.2 km flight tracks, flux errors are improved by factor of approximately 1.5 to 2 for most variables by making measurements in the crosswind direction.

Description: Precise and accurate hydroxyl radical (OH) measurements are essential to investigate mechanisms for oxidation and transformation of trace gases and processes leading to the formation of secondary pollutants like ozone (O3) in the troposphere. Laser-induced fluorescence (LIF) is a widely used technique for the measurement of ambient OH radicals and was used for the majority of field campaigns and chamber experiments. Recently, most LIF instruments in use for atmospheric measurements of OH radicals introduced chemical modulation to separate the ambient OH radical concentration from possible interferences by chemically removing ambient OH radicals before they enter the detection cell (Mao et al., 2012; Novelli et al., 2014a). In this study, we describe the application and characterization of a chemical modulation reactor (CMR) applied to the Forschungszentrum Jülich LIF (FZJ-LIF) instrument in use at the atmospheric simulation chamber SAPHIR (Simulation of Atmospheric PHotochemistry In a large Reaction Chamber). Besides dedicated experiments in synthetic air, the new technique was extensively tested during the year-round Jülich Atmospheric Chemistry Project (JULIAC) campaign, in which ambient air was continuously flowed into the SAPHIR chamber. It allowed for performing OH measurement comparisons with differential optical absorption spectroscopy (DOAS) and investigation of interferences in a large variety of chemical and meteorological conditions. Good agreement was obtained in the LIF–DOAS intercomparison within instrumental accuracies (18 % for LIF and 6.5 % for DOAS) which confirms that the new chemical modulation system of the FZJ-LIF instrument is suitable for measurement of interference-free OH concentrations under the conditions of the JULIAC campaign (rural environment). Known interferences from O3+H2O and the nitrate radical (NO3) were quantified with the CMR in synthetic air in the chamber and found to be 3.0×105 and 0.6×105 cm−3, respectively, for typical ambient-air conditions (O3=50 ppbv, H2O = 1 % and NO3=10 pptv). The interferences measured in ambient air during the JULIAC campaign in the summer season showed a median diurnal variation with a median maximum value of 0.9×106 cm−3 during daytime and a median minimum value of 0.4×106 cm−3 at night. The highest interference of 2×106 cm−3 occurred in a heat wave from 22 to 29 August, when the air temperature and ozone increased to 40 ∘C and 100 ppbv, respectively. All observed interferences could be fully explained by the known O3+H2O interference, which is routinely corrected in FZJ-LIF measurements when no chemical modulation is applied. No evidence for an unexplained interference was found during the JULIAC campaign. A chemical model of the CMR was developed and applied to estimate the possible perturbation of the OH transmission and scavenging efficiency by reactive atmospheric trace gases. These can remove OH by gas phase reactions in the CMR or produce OH by non-photolytic reactions, most importantly by the reaction of ambient HO2 with NO. The interfering processes become relevant at high atmospheric OH reactivities. For the conditions of the JULIAC campaign with OH reactivities below 20 s−1, the influence on the determination of ambient OH concentrations was small (on average: 2 %). However, in environments with high OH reactivities, such as in a rain forest or megacity, the expected perturbation in the currently used chemical modulation reactor could be large (more than a factor of 2). Such perturbations need to be carefully investigated and corrected for the proper evaluation of OH concentrations when applying chemical scavenging. This implies that chemical modulation, which was developed to eliminate interferences in ambient OH measurements, itself can be subject to interferences that depend on ambient atmospheric conditions.

Description: The ability of single-frequency, millimeter-wavelength radar reflectivity observations to provide useful constraints for retrieval of snow particle size distribution (PSD) parameters, snowfall rates, and snowfall accumulations is examined. An optimal estimation snowfall retrieval that allows analyses of retrieval uncertainties and information content is applied to observations of near-surface W-band reflectivities from multiple snowfall events during the 2006–2007 winter season in southern Ontario. Retrieved instantaneous snowfall rates generally have uncertainties greater than 100 %, but single-event and seasonal snow accumulations from the retrieval results match well with collocated measurements of accumulations. Absolute fractional differences are mainly below 30 % for individual events that have more substantial accumulations and, for the season, 12.6 %. Uncertainties in retrieved snowfall rates are driven mainly by uncertainties in the retrieved PSD parameters, followed by uncertainties in particle model parameters and, to a lesser extent, the uncertainties in the fall-speed model. Uncertainties attributable to assuming an exponential distribution are negligible. The results indicate that improvements to PSD and particle model a priori constraints provide the most impactful path forward for reducing uncertainties in retrieved snowfall rates. Information content analyses reveal that PSD slope is well-constrained by the retrieval. Given the sensitivity of PSD slope to microphysical transformations, the results show that such retrievals, when applied to radar reflectivity profiles, could provide information about microphysical transformations in the snowing column. The PSD intercept is less well-constrained by the retrieval. While applied to near-surface radar observations in this study, the retrieval is applicable as well to radar observations aloft, such as those provided by profiling ground-based, airborne, and satellite-borne radars under lighter snowfall conditions when attenuation and multiple scattering can be neglected.

Description: Smartphones are increasingly being equipped with atmospheric measurement sensors providing huge auxiliary resources for global observations. Although China has the highest number of cell phone users, there is little research on whether these measurements provide useful information for atmospheric research. Here, for the first time, we present the global spatial and temporal variation in smartphone pressure measurements collected in 2016 from the Moji Weather app. The data have an irregular spatiotemporal distribution with a high density in urban areas, a maximum in summer and two daily peaks corresponding to rush hours. With the dense dataset, we have developed a new bias-correction method based on a machine-learning approach without requiring users' personal information, which is shown to reduce the bias of pressure observation substantially. The potential application of the high-density smartphone data in cities is illustrated by a case study of a hailstorm that occurred in Beijing in which high-resolution gridded pressure analysis is produced. It is shown that the dense smartphone pressure analysis during the storm can provide detailed information about fine-scale convective structure and decrease errors from an analysis based on surface meteorological-station measurements. This study demonstrates the potential value of smartphone data and suggests some future research needs for their use in atmospheric science.

Description: Atmospheric ice-nucleating particles (INPs) play an important role in determining the phase of clouds, which affects their albedo and lifetime. A lack of data on the spatial and temporal variation of INPs around the globe limits our predictive capacity and understanding of clouds containing ice. Automated instrumentation that can robustly measure INP concentrations across the full range of tropospheric temperatures is needed in order to address this knowledge gap. In this study, we demonstrate the functionality and capacity of the new Portable Ice Nucleation Experiment (PINE) to study ice nucleation processes and to measure INP concentrations under conditions pertinent for mixed-phase clouds, with temperatures from about −10 to about −40 ∘C. PINE is a cloud expansion chamber which avoids frost formation on the cold walls and thereby omits frost fragmentation and related background ice signals during the operation. The development, working principle and treatment of data for the PINE instrument is discussed in detail. We present laboratory-based tests where PINE measurements were compared with those from the established AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber. Within experimental uncertainties, PINE agreed with AIDA for homogeneous freezing of pure water droplets and the immersion freezing activity of mineral aerosols. Results from a first field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory in Oklahoma, USA, from 1 October to 14 November 2019 with the latest PINE design (a commercially available PINE chamber) are also shown, demonstrating PINE's ability to make automated field measurements of INP concentrations at a time resolution of about 8 min with continuous temperature scans for INP measurements between −10 and −30 ∘C. During this field campaign, PINE was continuously operated for 45 d in a fully automated and semi-autonomous way, demonstrating the capability of this new instrument to also be used for longer-term field measurements and INP monitoring activities in observatories.

Description: Ground-based measurements of frozen precipitation are heavily influenced by interactions of surface winds with gauge-shield geometry. The Multi-Angle Snowflake Camera (MASC), which photographs hydrometeors in free-fall from three different angles while simultaneously measuring their fall speed, has been used in the field at multiple midlatitude and polar locations both with and without wind shielding. Here, we present an analysis of Arctic field observations – with and without a Belfort double Alter shield – and compare the results to computational fluid dynamics (CFD) simulations of the airflow and corresponding particle trajectories around the unshielded MASC. MASC-measured fall speeds compare well with Ka-band Atmospheric Radiation Measurement (ARM) Zenith Radar (KAZR) mean Doppler velocities only when winds are light (≤5ms-1) and the MASC is shielded. MASC-measured fall speeds that do not match KAZR-measured velocities tend to fall below a threshold value that increases approximately linearly with wind speed but is generally

Description: The OMPS Limb Profiler (LP) instrument is designed to provide high-vertical-resolution ozone and aerosol profiles from measurements of the scattered solar radiation in the 290–1000 nm spectral range. It collected its first Earth limb measurement on 10 January 2012 and continues to provide daily global measurements of ozone and aerosol profiles from the cloud top up to 60 and 40 km, respectively. The relatively high vertical and spatial sampling allow detection and tracking of sporadic events when aerosol particles are injected into the stratosphere, such as volcanic eruptions or pyrocumulonimbus (PyroCb) events. In this paper we discuss the newly released Version 2.0 OMPS multi-wavelength aerosol extinction coefficient retrieval algorithm. The algorithm now produces aerosol extinction profiles at 510, 600, 674, 745, 869 and 997 nm wavelengths. The OMPS LP Version 2.0 data products are compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies. The comparison shows significant improvements in the OMPS LP retrieval performance in the Southern Hemisphere (SH) and at lower altitudes. These improvements arise from use of the longer wavelengths, in contrast with the V1.0 and V1.5 OMPS aerosol retrieval algorithms, which used radiances only at 675 nm and therefore had limited sensitivity in those regions. In particular, the extinction coefficients at 745, 869 and 997 nm are shown to be the most accurate, with relative accuracies and precisions close to 10 % and 15 %, respectively, while the 675 nm relative accuracy and precision are on the order of 20 %. The 510 nm extinction coefficient is shown to have limited accuracy in the SH and is only recommended for use between 20–24 km and only in the Northern Hemisphere. The V2.0 retrieval algorithm has been applied to the complete set of OMPS LP measurements, and the new dataset is publicly available.

Description: Global climate change is one of the most important scientific, societal and economic contemporary challenges. Fundamental understanding of the major processes driving climate change is the key problem which is to be solved not only on a global but also on a regional scale. The accuracy of regional climate modelling depends on a number of factors. One of these factors is the adequate and comprehensive information on the anthropogenic impact which is highest in industrial regions and areas with dense population – modern megacities. Megacities are not only “heat islands”, but also significant sources of emissions of various substances into the atmosphere, including greenhouse and reactive gases. In 2019, the mobile experiment EMME (Emission Monitoring Mobile Experiment) was conducted within the St. Petersburg agglomeration (Russia) aiming to estimate the emission intensity of greenhouse (CO2, CH4) and reactive (CO, NOx) gases for St. Petersburg, which is the largest northern megacity. St. Petersburg State University (Russia), Karlsruhe Institute of Technology (Germany) and the University of Bremen (Germany) jointly ran this experiment. The core instruments of the campaign were two portable Bruker EM27/SUN Fourier transform infrared (FTIR) spectrometers which were used for ground-based remote sensing measurements of the total column amount of CO2, CH4 and CO at upwind and downwind locations on opposite sides of the city. The NO2 tropospheric column amount was observed along a circular highway around the city by continuous mobile measurements of scattered solar visible radiation with an OceanOptics HR4000 spectrometer using the differential optical absorption spectroscopy (DOAS) technique. Simultaneously, air samples were collected in air bags for subsequent laboratory analysis. The air samples were taken at the locations of FTIR observations at the ground level and also at altitudes of about 100 m when air bags were lifted by a kite (in case of suitable landscape and favourable wind conditions). The entire campaign consisted of 11 mostly cloudless days of measurements in March–April 2019. Planning of measurements for each day included the determination of optimal location for FTIR spectrometers based on weather forecasts, combined with the numerical modelling of the pollution transport in the megacity area. The real-time corrections of the FTIR operation sites were performed depending on the actual evolution of the megacity NOx plume as detected by the mobile DOAS observations. The estimates of the St. Petersburg emission intensities for the considered greenhouse and reactive gases were obtained by coupling a box model and the results of the EMME observational campaign using the mass balance approach. The CO2 emission flux for St. Petersburg as an area source was estimated to be 89 ± 28 ktkm-2yr-1, which is 2 times higher than the corresponding value in the EDGAR database. The experiment revealed the CH4 emission flux of 135 ± 68 tkm-2yr-1, which is about 1 order of magnitude greater than the value reported by the official inventories of St. Petersburg emissions (∼ 25 tkm-2yr-1 for 2017). At the same time, for the urban territory of St. Petersburg, both the EMME experiment and the official inventories for 2017 give similar results for the CO anthropogenic flux (251 ± 104 tkm-2yr-1 vs. 410 tkm-2yr-1) and for the NOx anthropogenic flux (66 ± 28 tkm-2yr-1 vs. 69 tkm-2yr-1).

Description: Oxidative stress can be used to evaluate not only adverse health effects but also adverse ecological effects, but limited research uses eco-toxicological assay to assess the risks posed by particle matters to non-human biomes. One important reason might be that the concentration of toxic components of atmospheric particles is far below the high detection limit of eco-toxic measurement. To solve the rapid detection problem, we extended a versatile aerosol concentration enrichment system (VACES) for ecotoxicity aerosol measurement and firstly used VACES to provide a comparison of ecotoxicity between non-concentrated and concentrated aerosols in ambient air. In this study, the total concentration (number or mass), the concentration of chemical components and the ecotoxicity were all increased by approximately 7 to 10 times in VACES, making the detection of ecotoxicity above the baseline. The comparison of ecotoxicity data and PM2.5 concentration showed that low concentration was not matched with ecotoxicity, although high concentration corresponded to higher ecotoxicity. In addition, the higher saturation temperature in VACES caused a loss of particulate matter, of which nitrate accounted for about 18 %.

Description: Correct, timely and meaningful interpretation of polarimetric weather radar observations requires an accurate understanding of hydrometeors and their associated microphysical processes along with well-developed techniques that automatize their recognition in both the spatial and temporal dimensions of the data. This study presents a novel technique for identifying different types of hydrometeors from quasi-vertical profiles (QVPs). In this new technique, the hydrometeor types are identified as clusters belonging to a hierarchical structure. The number of different hydrometeor types in the data is not predefined, and the method obtains the optimal number of clusters through a recursive process. The optimal clustering is then used to label the original data. Initial results using observations from the National Centre for Atmospheric Science (NCAS) X-band dual-polarization Doppler weather radar (NXPol) show that the technique provides stable and consistent results. Comparison with available airborne in situ measurements also indicates the value of this novel method for providing a physical delineation of radar observations. Although this demonstration uses NXPol data, the technique is generally applicable to similar multivariate data from other radar observations.

Description: A new methodology for performing long-term source apportionment (SA) using positive matrix factorization (PMF) is presented. The method is implemented within the SoFi Pro software package and uses the multilinear engine (ME-2) as a PMF solver. The technique is applied to a 1-year aerosol chemical speciation monitor (ACSM) dataset from downtown Zurich, Switzerland. The measured organic aerosol mass spectra were analyzed by PMF using a small (14 d) and rolling PMF window to account for the temporal evolution of the sources. The rotational ambiguity is explored and the uncertainties of the PMF solutions were estimated. Factor–tracer correlations for averaged seasonal results from the rolling window analysis are higher than those retrieved from conventional PMF analyses of individual seasons, highlighting the improved performance of the rolling window algorithm for long-term data. In this study four to five factors were tested for every PMF window. Factor profiles for primary organic aerosol from traffic (HOA), cooking (COA) and biomass burning (BBOA) were constrained. Secondary organic aerosol was represented by either the combination of semi-volatile and low-volatility organic aerosol (SV-OOA and LV-OOA, respectively) or by a single OOA when this separation was not robust. This scheme led to roughly 40 000 PMF runs. Full visual inspection of all these PMF runs is unrealistic and is replaced by predefined user-selected criteria, which allow factor sorting and PMF run acceptance/rejection. The selected criteria for traffic (HOA) and BBOA were the correlation with equivalent black carbon from traffic (eBCtr) and the explained variation of m/z 60, respectively. COA was assessed by the prominence of a lunchtime concentration peak within the diurnal cycle. SV-OOA and LV-OOA were evaluated based on the fractions of m/z 43 and 44 in their respective factor profiles. Seasonal pre-tests revealed a non-continuous separation of OOA into SV-OOA and LV-OOA, in particular during the warm seasons. Therefore, a differentiation between four-factor solutions (HOA, COA, BBOA and OOA) and five-factor solutions (HOA, COA, BBOA, SV-OOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4–0.7 µg m−3 (7.8 %–9.0 %) and 0.7–1.2 µg m−3 (12.2 %–15.7 %) on average throughout the year, respectively. BBOA shows a strong yearly cycle with the lowest mean concentrations in summer (0.6 µg m−3, 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 µg m−3, or 15.6 % and 18.6 %, respectively), and the highest mean concentrations during winter (1.9 µg m−3, 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 µg m−3 (26.5 %) and 2.2 µg m−3 (40.3 %), respectively. For the remaining seasons the seasonal concentrations of SV-OOA, LV-OOA and OOA range from 0.3 to 1.1 µg m−3 (3.4 %–15.9 %), from 0.6 to 2.2 µg m−3 (7.7 %–33.7 %) and from 0.9 to 3.1 µg m−3 (13.7 %–39.9 %), respectively. The relative PMF errors modeled for this study for HOA, COA, BBOA, LV-OOA, SV-OOA and OOA are on average ±34 %, ±27 %, ±30 %, ±11 %, ±25 % and ±12 %, respectively.

Description: In the frame of the EMEP/ACTRIS/COLOSSAL campaign in Milan during winter 2018, equivalent black carbon measurements using the Aethalometer 31 (AE31), the Aethalometer 33 (AE33), and a Multi-Angle Absorption Photometer (MAAP) were carried out together with levoglucosan analyses on 12 h resolved PM2.5 samples collected in parallel. From AE31 and AE33 data, the loading-corrected aerosol attenuation coefficients (bATN) were calculated at seven wavelengths (λ, where λ values are 370, 470, 520, 590, 660, 880, and 950 nm). The aerosol absorption coefficient at 637 nm (babs_MAAP) was determined by MAAP measurements. Furthermore, babs was also measured at four wavelengths (405, 532, 635, 780 nm) on the 12 h resolved PM2.5 samples by a polar photometer (PP_UniMI). After comparing PP_UniMI and MAAP results, we exploited PP_UniMI data to evaluate the filter multiple-scattering enhancement parameter at different wavelengths for AE31 and AE33. We obtained instrument- and wavelength-dependent multiple-scattering enhancement parameters by linear regression of the Aethalometer bATN against the babs measured by PP_UniMI. We found significant dependence of the multiple-scattering enhancement parameter on filter material, hence on the instrument, with a difference of up to 30 % between the AE31 and the AE33 tapes. The wavelength dependence and day–night variations were small – the difference between the smallest and largest value was up to 6 %. Data from the different instruments were used as input to the so-called “Aethalometer model” for optical source apportionment, and instrument dependence of the results was investigated. Inconsistencies among the source apportionment were found fixing the AE31 and AE33 multiple-scattering enhancement parameters to their usual values. In contrast, optimised multiple-scattering enhancement parameters led to a 5 % agreement among the approaches. Also, the component apportionment “MWAA model” (Multi-Wavelength Absorption Analyzer model) was applied to the dataset. It was less sensitive to the instrument and the number of wavelengths, whereas significant differences in the determination of the absorption Ångström exponent for brown carbon were found (up to 22 %).

Description: Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate atmospheric attenuation at relative transparent channels for radio propagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at channels other than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing 1 year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K- and V–W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at the V band (54–58 GHz). The retrieval coefficients are then applied to a 1-year dataset of real V-band observations, and the estimated TMR at the K and V–W band is compared with estimates from nearly colocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32 %–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10 %–20 % for K-band channels and ∼30 % for V–W-band channels.

Description: An ability to accurately detect convective regions is essential for initializing models for short-term precipitation forecasts. Radar data are commonly used to detect convection, but radars that provide high-temporal-resolution data are mostly available over land, and the quality of the data tends to degrade over mountainous regions. On the other hand, geostationary satellite data are available nearly anywhere and in near-real time. Current operational geostationary satellites, the Geostationary Operational Environmental Satellite-16 (GOES-16) and Satellite-17, provide high-spatial- and high-temporal-resolution data but only of cloud top properties; 1 min data, however, allow us to observe convection from visible and infrared data even without vertical information of the convective system. Existing detection algorithms using visible and infrared data look for static features of convective clouds such as overshooting top or lumpy cloud top surface or cloud growth that occurs over periods of 30 min to an hour. This study represents a proof of concept that artificial intelligence (AI) is able, when given high-spatial- and high-temporal-resolution data from GOES-16, to learn physical properties of convective clouds and automate the detection process. A neural network model with convolutional layers is proposed to identify convection from the high-temporal resolution GOES-16 data. The model takes five temporal images from channel 2 (0.65 µm) and 14 (11.2 µm) as inputs and produces a map of convective regions. In order to provide products comparable to the radar products, it is trained against Multi-Radar Multi-Sensor (MRMS), which is a radar-based product that uses a rather sophisticated method to classify precipitation types. Two channels from GOES-16, each related to cloud optical depth (channel 2) and cloud top height (channel 14), are expected to best represent features of convective clouds: high reflectance, lumpy cloud top surface, and low cloud top temperature. The model has correctly learned those features of convective clouds and resulted in a reasonably low false alarm ratio (FAR) and high probability of detection (POD). However, FAR and POD can vary depending on the threshold, and a proper threshold needs to be chosen based on the purpose.

Description: The retrieval of aerosol parameters from passive satellite instruments in cloudy scenes is challenging, partly because clouds and cloud-related processes may significantly modify aerosol optical depth (AOD) and particle size, a problem that is further compounded by 3D radiative processes. Recent advances in retrieval algorithms such as the “color ratio” method, which utilizes the measurements at a shorter (470 nm) and a longer (860 nm) wavelength, have demonstrated the simultaneous derivation of AOD and cloud optical depth (COD) for scenes in which absorbing aerosols are found to overlay low-level cloud decks. This study shows simultaneous retrievals of above-cloud aerosol optical depth (ACAOD) and aerosol-corrected cloud optical depth (COD) from airborne measurements of cloud-reflected and sky radiances using the color ratio method. These airborne measurements were taken over marine stratocumulus clouds with NASA's Cloud Absorption Radiometer (CAR) during the SAFARI 2000 field campaign offshore of Namibia. The ACAOD is partitioned between the AOD below-aircraft (AOD_cloudtop) and above-aircraft AOD (AOD_sky). The results show good agreement between AOD_sky and sun-photometer measurements of the above-aircraft AOD. The results also show that the use of aircraft-based sun-photometer measurements to validate satellite retrievals of the ACAOD is complicated by the lack of information on AOD below aircraft. Specifically, the CAR-retrieved AOD_cloudtop captures this “missing” aerosol layer caught between the aircraft and cloud top, which is required to quantify above-cloud aerosol loading and effectively validate satellite retrievals. In addition, the study finds a strong anticorrelation between the AOD_cloudtop and COD for cases in which COD  10, which may be associated with the uncertainties in the color ratio method at lower AODs and CODs. The influence of 3D radiative effects on the retrievals is examined, and the results show that at cloud troughs, 3D effects increase retrieved ACAOD by about 3 %–11 % and retrieved COD by about 25 %. The results show that the color ratio method has little sensitivity to 3D effects at overcast stratocumulus cloud decks. These results demonstrate a novel airborne measurement approach for assessing satellite retrievals of aerosols above clouds, thereby filling a major gap in global aerosol observations.

Description: We describe the change in operational instrument for the routine measurement of column-averaged dry-air mole fraction of several greenhouse gases (denoted Xgas) at the Lauder Total Carbon Column Observing Network (TCCON) site and the steps taken to demonstrate comparability between the two observation systems following a systematic methodology. Further, we intercompare retrieved Xgas values during an intensive intercomparison period during October and November 2018, when both instruments were performing optimally, and on subsequent, less frequent occasions. The average difference between the two observing systems was found to be well below the expected level of uncertainty for TCCON retrievals for all compared species. In the case of XCO2 the average difference was 0.0264±0.0465 % (0.11±0.19 µmol mol−1).

Description: In order to validate satellite measurements of atmospheric composition, it is necessary to understand the range of random and systematic uncertainties inherent in the measurements. On occasions where measurements from two different satellite instruments do not agree within those estimated uncertainties, a common explanation is that the difference can be assigned to geophysical variability, i.e., differences due to sampling the atmosphere at different times and locations. However, the expected geophysical variability is often left ambiguous and rarely quantified. This paper describes a case study where the geophysical variability of O3 between two satellite instruments – ACE-FTS (Atmospheric Chemistry Experiment – Fourier Transform Spectrometer) and OSIRIS (Optical Spectrograph and InfraRed Imaging System) – is estimated using simulations from climate models. This is done by sampling the models CMAM (Canadian Middle Atmosphere Model), EMAC (ECHAM/MESSy Atmospheric Chemistry), and WACCM (Whole Atmosphere Community Climate Model) throughout the upper troposphere and stratosphere at times and geolocations of coincident ACE-FTS and OSIRIS measurements. Ensemble mean values show that in the lower stratosphere, O3 geophysical variability tends to be independent of the chosen time coincidence criterion, up to within 12 h; and conversely, in the upper stratosphere geophysical variation tends to be independent of the chosen distance criterion, up to within 2000 km. It was also found that in the lower stratosphere, at altitudes where there is the greatest difference between air composition inside and outside the polar vortex, the geophysical variability in the southern polar region can be double of that in the northern polar region. This study shows that the ensemble mean estimates of geophysical variation can be used when comparing data from two satellite instruments to optimize the coincidence criteria, allowing for the use of more coincident profiles while providing an estimate of the geophysical variation within the comparison results.

Description: The presence of 3D cloud radiative effects in OCO-2 retrievals is demonstrated from an analysis of 2014–2019 OCO-2 XCO2 raw retrievals, bias-corrected XCO2bc data, ground-based Total Carbon Column Observation Network (TCCON) XCO2, and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud and radiance fields. In approximate terms, 40 % (quality flag – QF = 0, land or ocean) and 73 % (QF = 1, land or ocean) of the observations are within 4 km of clouds. 3D radiative transfer calculations indicate that 3D cloud radiative perturbations at this cloud distance, for an isolated low-altitude cloud, are larger in absolute value than those due to a 1 ppm increase in CO2. OCO-2 measurements are therefore susceptible to 3D cloud effects. Four 3D cloud metrics, based upon MODIS radiance and cloud fields as well as stand-alone OCO-2 measurements, relate XCO2bc–TCCON averages to 3D cloud effects. This analysis indicates that the operational bias correction has a nonzero residual 3D cloud bias for both QF = 0 and QF = 1 data. XCO2bc–TCCON averages at small cloud distances differ from those at large cloud distances by −0.4 and −2.2 ppm for the QF = 0 and QF = 1 data over the ocean. Mitigation of 3D cloud biases with a table lookup technique, which utilizes the nearest cloud distance (Distkm) and spatial radiance heterogeneity (CSNoiseRatio) 3D metrics, reduces QF = 1 ocean and land XCO2bc–TCCON averages from −1 ppm to near ±0.2 ppm. The ocean QF = 1 XCO2bc–TCCON averages can be reduced to the 0.5 ppm level if 60 % (70 %) of the QF = 1 data points are utilized by applying Distkm (CSNoiseRatio) metrics in a data screening process. Over land the QF = 1 XCO2bc–TCCON averages are reduced to the 0.5 (0.8) ppm level if 65 % (63 %) of the data points are utilized by applying Diastkm (CSNoiseRatio) data screening. The addition of more terms to the linear regression equations used in the current bias correction processing without data screening, however, did not introduce an appreciable improvement in the standard deviations of the XCO2bc–TCCON statistics.

Description: The Raman Lidar for Meteorological Observations (RALMO) is operated at the MeteoSwiss station of Payerne (Switzerland) and provides, amongst other products, continuous measurements of temperature since 2010. The temperature profiles are retrieved from the pure rotational Raman (PRR) signals detected around the 355 nm Cabannes line. The transmitter and receiver systems of RALMO are described in detail, and the reception and acquisition units of the PRR channels are thoroughly characterized. The FastCom P7888 card used to acquire the PRR signal, the calculation of the dead time and the desaturation procedure are also presented. The temperature profiles retrieved from RALMO PRR data during the period going from July 2017 to the end of December 2018 have been validated against two reference operational radiosounding systems (ORSs) co-located with RALMO, i.e. the Meteolabor SRS-C50 and the Vaisala RS41. The ORSs have also served to perform the calibration of the RALMO temperature during the validation period. The maximum bias (ΔTmax), mean bias (μ) and mean standard deviation (σ) of RALMO temperature Tral with respect to the reference ORS, Tors, are used to characterize the accuracy and precision of Tral along the troposphere. The daytime statistics provide information essentially about the lower troposphere due to lower signal-to-noise ratio. The ΔTmax, μ and σ of the differences ΔT=Tral-Tors are, respectively, 0.28, 0.02±0.1 and 0.62±0.03 K. The nighttime statistics provide information for the entire troposphere and yield ΔTmax=0.29 K, μ=0.05±0.34 K and σ=0.66±0.06 K. The small ΔTmax, μ and σ values obtained for both daytime and nighttime comparisons indicate the high stability of RALMO that has been calibrated only seven times over 18 months. The retrieval method can correct for the largest sources of correlated and uncorrelated errors, e.g. signal noise, dead time of the acquisition system and solar background. Especially the solar radiation (scattered into the field of view from the zenith angle Φ) affects the quality of PRR signals and represents a source of systematic error for the retrieved temperature. An imperfect subtraction of the background from the daytime PRR profiles induces a bias of up to 2 K at all heights. An empirical correction f(Φ) ranging from 0.99 to 1 has therefore been applied to the mean background of the PRR signals to remove the bias. The correction function f(Φ) has been validated against the numerical weather prediction model COSMO (Consortium for Small-scale Modelling), suggesting that f(Φ) does not introduce any additional source of systematic or random error to Tral. A seasonality study has been performed to help with understanding if the overall daytime and nighttime zero bias hides seasonal non-zero biases that cancel out when combined in the full dataset.

Description: Proton-transfer-reaction mass spectrometry (PTR-MS) is widely used in atmospheric sciences for measuring volatile organic compounds in real time. In the most widely used type of PTR-MS instruments, air is directly introduced into a chemical ionization reactor via an inlet capillary system. The reactor has a volumetric exchange time of ∼0.1 s, enabling PTR-MS analyzers to measure at a frequency of 10 Hz. The time response does, however, deteriorate if low-volatility analytes interact with surfaces in the inlet or in the instrument. Herein, we present the extended volatility range (EVR) PTR-MS instrument which mitigates this issue. In the EVR configuration, inlet capillaries are made of passivated stainless steel, and all wetted metal parts in the chemical ionization reactor are surface-passivated with a functionalized hydrogenated amorphous silicon coating. Heating the entire setup (up to 120 ∘C) further improves the time-response performance. We carried out time-response performance tests on a set of 29 analytes having saturation mass concentrations C0 in the range between 10−3 and 105 µg m−3. The 1/e-signal decay times after instant removal of the analyte from the sampling flow were between 0.2 and 90 s for gaseous analytes. We also tested the EVR PTR-MS instrument in combination with the chemical analysis of aerosols online (CHARON) particle inlet, and 1/e-signal decay times were in the range between 5 and 35 s for particulate analytes. We show on a set of example compounds that the time-response performance of the EVR PTR-MS instrument is comparable to that of the fastest flow tube chemical ionization mass spectrometers that are currently in use. The fast time response can be used for rapid (∼1 min equilibration time) switching between gas and particle measurements. The CHARON EVR PTR-MS instrument can thus be used for real-time monitoring of both gaseous and particulate organics in the atmosphere. Finally, we show that the CHARON EVR PTR-MS instrument also rapidly detects highly oxygenated species (with up to eight oxygen atoms) in particles formed by limonene ozonolysis.

Description: The humidified tandem differential mobility analyzer (HTDMA) is widely used to measure the hygroscopic properties of submicron particles. The size-resolved aerosol hygroscopicity κ measured by a HTDMA will be influenced by the contribution of multiply charged aerosols, but this effect on field measurements has seldom been discussed for previous field measurements. Our calculations demonstrate that the number ratio of multiply charged particles is quite considerable for some specific sizes between 100 and 300 nm, especially during a pollution episode. The presence of multiple charges will lead to a compression effect on the aerosol hygroscopicity in HTDMA measurements. Therefore, we propose a new algorithm that performs multi-charge correction of the size-resolved hygroscopicity κ, taking both the compression effect and the multi-charge number contribution into consideration. Application of the algorithm to field measurements showed that the relatively high hygroscopicity in the accumulation size range leads to the overestimation of the hygroscopicity of particles smaller than 200 nm. The low hygroscopicity of coarse-mode particles leads to the underestimation of the hygroscopicity of accumulation particles between 200 and 500 nm in size. The difference between the corrected and measured κ values can be as large as 0.05, highlighting that special attention must be paid to the multi-charge effect when a HTDMA is used for aerosol hygroscopicity measurements.

Description: Wind data collection in the atmospheric boundary layer benefits from short-term wind speed measurements using unmanned aerial vehicles. Fixed-wing and rotary-wing devices with diverse anemometer technology have been used in the past to provide such data, but the accuracy still has the potential to be increased. A lightweight drone for carrying an industry-standard precision sonic anemometer was developed. Accuracy tests have been performed with the isolated anemometer at high tilt angles in a calibration wind tunnel, with the drone flying in a large wind tunnel and with the full system flying at different heights next to a bistatic lidar reference. The propeller-induced flow deflects the air to some extent, but this effect is compensated effectively. The data fusion shows a substantial reduction of crosstalk (factor of 13) between ground speed and wind speed. When compared with the bistatic lidar in very turbulent conditions, with a 10 s averaging interval and with the unmanned aerial vehicle (UAV) constantly circling around the measurement volume of the lidar reference, wind speed measurements have a bias between −2.0 % and 4.2 % (root-mean-square error (RMSE) of 4.3 % to 15.5 %), vertical wind speed bias is between −0.05 and 0.07 m s−1 (RMSE of 0.15 to 0.4 m s−1), elevation bias is between −1 and 0.7∘ (RMSE of 1.2 to 6.3∘), and azimuth bias is between −2.6 and 7.2∘ (RMSE of 2.6 to 8.0∘). Key requirements for good accuracy under challenging and dynamic conditions are the use of a full-size sonic anemometer, a large distance between anemometer and propellers, and a suitable algorithm for reducing the effect of propeller-induced flow. The system was finally flown in the wake of a wind turbine, successfully measuring the spatial velocity deficit and downwash distribution during forward flight, yielding results that are in very close agreement to lidar measurements and the theoretical distribution. We believe that the results presented in this paper can provide important information for designing flying systems for precise air speed measurements either for short duration at multiple locations (battery powered) or for long duration at a single location (power supplied via cable). UAVs that are able to accurately measure three-dimensional wind might be used as a cost-effective and flexible addition to measurement masts and lidar scans.

Description: We describe the development, characterization, and first field deployments of a quantum cascade laser direct absorption spectrometer (QCLAS) for water vapor measurements in the upper troposphere and lower stratosphere (UTLS). The instrument is sufficiently small (30×23×11 cm3) and lightweight (3.9 kg) to be carried by meteorological balloons and used for frequent soundings in the UTLS. The spectrometer is a fully independent system, operating autonomously for the duration of a balloon flight. To achieve the required robustness, while satisfying stringent mass limitations, the concepts for optics and electronics have been fundamentally reconsidered compared to laboratory-based spectrometers. A significant enhancement of the mechanical and optical stability is achieved by integrating a newly designed segmented circular multipass cell which allows for 6 m optical path length in a very compact fashion. The H2O volume mixing ratio is retrieved by calibration-free evaluation of the spectral data, i.e., only relying on SI-traceable measurements and absorption line parameters. The open-path design reduces the risk of contamination and allows for fast response and thus high vertical resolution. Laboratory-based characterization experiments show an agreement within 2 % of reference measurements and a precision of 0.1 % under conditions comparable to the UTLS. The instrument successfully performed two balloon-borne test flights up to 28 km altitude. In the troposphere, the retrieved spectroscopic data show an excellent agreement with the accompanying measurements by a frost point hygrometer (CFH). At higher altitude, the quality of the spectral data remained unchanged, but outgassed water vapor within the instrument enclosure was hindering an accurate measurement of the atmospheric water vapor. Despite this limitation, these test flights demonstrated the operation of a compact laser spectrometer in the UTLS aboard a low-volume meteorological balloon, opening the perspective for future highly resolved, accurate, and cost-efficient soundings.

Description: Atmospheric black carbon (BC) is the strongest solar radiative absorber in the atmosphere, exerting significant influences on the earth's radiation budget. The mass absorption cross section (MAC) is a crucial parameter for converting the light absorption coefficient (σab) to the equivalent BC mass concentration (EBC). Traditional filter-based instruments, such as the AE33, use a constant MAC of 7.77 m2/g at 880 nm to derive the EBC, which may lead to uncertainty in the EBC. In this paper, a new method of converting σab to the EBC is proposed by incorporating the variations of the MAC attributed to the influences of the aerosol coating state. A Mie simulation showed that the MAC varied dramatically with different core sizes and shell thicknesses. We compared our new method with the traditional method during a field measurement at a site on the North China Plain. The results showed that the MAC at 880 nm was smaller (larger) than 7.77 m2/g for particles smaller (larger) than 280 nm, resulting in an EBC mass size distribution derived from the new method that was higher (lower) than the traditional method for particles smaller (larger) than 280 nm. The size-integrated EBC derived from the new method was 16 % higher than that derived from the traditional method. Sensitivity analysis indicated that the uncertainty in the EBC caused by the refractive index (RI) was within 35 %, and the imaginary part of the RI had dominant influence on the derived EBC. This study emphasizes the necessity to take variations of the MAC into account when deriving the EBC from σab and can help constrain the uncertainty in EBC measurements.