• European Marine Science
• Publicationsclose
• Other research productsclose
• US close
• CA close
• Atmospheric Measurement Techniques (AMT) close

Abstract. The 19-channel rotating shadowband radiometer GUVis-3511 built by Biospherical Instruments provides automated shipborne measurements of the direct, diffuse and global spectral irradiance components without a requirement for platform stabilization. Several direct sun products, including spectral direct beam transmittance, aerosol optical depth, Ångström exponent and precipitable water, can be derived from these observations. The individual steps of the data analysis are described, and the different sources of uncertainty are discussed. The total uncertainty of the observed direct beam transmittances is estimated to be about 4 % for most channels within a 95 % confidence interval for shipborne operation. The calibration is identified as the dominating contribution to the total uncertainty. A comparison of direct beam transmittance with those obtained from a Cimel sunphotometer at a land site and a manually operated Microtops II sunphotometer on a ship is presented. Measurements deviate by less than 3 and 4 % on land and on ship, respectively, for most channels and in agreement with our previous uncertainty estimate. These numbers demonstrate that the instrument is well suited for shipborne operation, and the applied methods for motion correction work accurately. Based on spectral direct beam transmittance, aerosol optical depth can be retrieved with an uncertainty of 0.02 for all channels within a 95 % confidence interval. The different methods to account for Rayleigh scattering and gas absorption in our scheme and in the Aerosol Robotic Network processing for Cimel sunphotometers lead to minor deviations. Relying on the cross calibration of the 940 nm water vapor channel with the Cimel sunphotometer, the column amount of precipitable water can be estimated with an uncertainty of ±0.034 cm.

During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed-wing uncrewed aircraft system (UAS). These in situ observations of the central Arctic atmosphere are some of the most extensive to date and provide unique insight into the atmospheric boundary layer (ABL) structure. The ABL is an important component of the Arctic climate, as it can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to manually identify the ABL height (ZABL) for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ZABL with ZABL identified by various previously published automated objective methods allows us to determine which objective methods are most successful at accurately identifying ZABL in the central Arctic environment and how the success of the methods differs based on stability regime. The objective methods we use are the Liu–Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ZABL determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ZABL, while the Liu–Liang method is least successful. The results of this study are expected to be beneficial for upcoming observational and modeling efforts regarding the central Arctic ABL.

Ground-based observations of 11.072 GHz atmospheric ozone (O3) emission have been made using the Ny-Ålesund Ozone in the Mesosphere Instrument (NAOMI) at the UK Arctic Research Station (latitude 78∘55′0′′ N, longitude 11∘55′59′′ E), Spitsbergen. Seasonally averaged O3 vertical profiles in the Arctic polar mesosphere–lower thermosphere region for night-time and twilight conditions in the period 15 August 2017 to 15 March 2020 have been retrieved over the altitude range 62–98 km. NAOMI measurements are compared with corresponding, overlapping observations by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite instrument. The NAOMI and SABER version 2.0 data are binned according to the SABER instrument 60 d yaw cycles into nominal 3-month “winter” (15 December–15 March), “autumn” (15 August–15 November), and “summer” (15 April–15 July) periods. The NAOMI observations show the same year-to-year and seasonal variabilities as the SABER 9.6 µm O3 data. The winter night-time (solar zenith angle, SZA ≥ 110∘) and twilight (75∘ ≤ SZA ≤ 110∘) NAOMI and SABER 9.6 µm O3 volume mixing ratio (VMR) profiles agree to within the measurement uncertainties. However, for autumn twilight conditions the SABER 9.6 µm O3 secondary maximum VMR values are higher than NAOMI over altitudes 88–97 km by 47 % and 59 %, respectively in 2017 and 2018. Comparing the two SABER channels which measure O3 at different wavelengths and use different processing schemes, the 9.6 µm O3 autumn twilight VMR data for the three years 2017–2019 are higher than the corresponding 1.27 µm measurements with the largest difference (58 %) in the 65–95 km altitude range similar to the NAOMI observation. The SABER 9.6 µm O3 summer daytime (SZA < 75∘) mesospheric O3 VMR is also consistently higher than the 1.27 µm measurement, confirming previously reported differences between the SABER 9.6 µm channel and measurements of mesospheric O3 by other satellite instruments.

Emissions of methane (CH4) from offshore oil and gas installations are poorly ground-truthed and quantification relies heavily on the use of emission factors and activity data. As part of the United Nations Climate and Clean Air Coalition (UN CCAC) objective to study and reduce short-lived climate pollutants (SLCP) a Twin Otter aircraft was used to survey CH4 emissions from UK and Dutch offshore oil and gas installations. The aims of the surveys were to i) identify installations that are significant CH4 emitters, ii) separate installation emissions from other emissions using carbon-isotopic fingerprinting and other chemical proxies, iii) estimate CH4 emission rates, and iv) improve flux estimation (and sampling) methodologies for rapid quantification of major gas leaks. In this paper, we detail the instrument and aircraft set up for two campaigns flown in the springs of 2018 and 2019 over the southern North Sea and describe the developments made in both planning and sampling methodology in order to maximise the quality and value of the data collected. We present example data collected from both campaigns to demonstrate the challenges encountered during offshore surveys, focussing on the complex meteorology of the marine boundary layer, and sampling discrete plumes from an airborne platform. The uncertainties of CH4 flux calculations from measurements under varying boundary layer conditions are considered, as well as recommendations for attribution of sources through either spot sampling for VOCs / δ13CCH4 or using in-situ instrumental data to determine C2H6-CH4 ratios. A series of recommendations for both planning and measurement techniques for future offshore work within the marine boundary layers are provided.

Low-level flights over tundra wetlands in Alaska and Canada have been conducted during the Airborne Measurements of Methane Emissions (AirMeth) campaigns to measure turbulent methane fluxes in the atmosphere. In this paper we describe the instrumentation and new calibration procedures for the essential pressure parameters required for turbulence sensing by aircraft that exploit suitable regular measurement flight legs without the need for dedicated calibration patterns. We estimate the accuracy of the mean wind and the turbulence measurements. We show that airborne measurements of turbulent fluxes of methane and carbon dioxide using cavity ring-down spectroscopy trace gas analysers together with established turbulence equipment achieve a relative accuracy similar to that of measurements of sensible heat flux if applied during low-level flights over natural area sources. The inertial subrange of the trace gas fluctuations cannot be resolved due to insufficient high-frequency precision of the analyser, but, since this scatter is uncorrelated with the vertical wind velocity, the covariance and thus the flux are reproduced correctly. In the covariance spectra the -7/3 drop-off in the inertial subrange can be reproduced if sufficient data are available for averaging. For convective conditions and flight legs of several tens of kilometres we estimate the flux detection limit to be about 4 mg m−2 d−1 for w′CH4′‾, 1.4 g m−2 d−1 for w′CO2′‾ and 4.2 W m−2 for the sensible heat flux.

Stable carbon isotope analysis of methane (δ13C of CH4) on atmospheric samples is one key method to constrain the current and past atmospheric CH4 budget. A frequently applied measurement technique is gas chromatography (GC) isotope ratio mass spectrometry (IRMS) coupled to a combustion-preconcentration unit. This report shows that the atmospheric trace gas krypton (Kr) can severely interfere during the mass spectrometric measurement, leading to significant biases in δ13C of CH4, if krypton is not sufficiently separated during the analysis. According to our experiments, the krypton interference is likely composed of two individual effects, with the lateral tailing of the doubly charged 86Kr peak affecting the neighbouring m/z 44 and partially the m/z 45 Faraday cups. Additionally, a broad signal affecting m/z 45 and especially m/z 46 is assumed to result from scattered ions of singly charged krypton. The introduced bias in the measured isotope ratios is dependent on the chromatographic separation, the krypton-to-CH4 mixing ratio in the sample, the focusing of the mass spectrometer as well as the detector configuration and can amount to up to several per mil in δ13C. Apart from technical solutions to avoid this interference, we present correction routines to a posteriori remove the bias.

Abstract. Water vapor is the most important greenhouse gas in the atmosphere with important implications not only for the Earth’s radiation and energy budget but also for various chemical, physical and dynamical processes in the stratosphere. The Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Radio Occultation (RO) dataset from 2007 through 2013 is used for the first time to study the distribution and variability water vapor in the upper troposphere and lower stratosphere (UTLS). The COSMIC data are compared to the Microwave Limb Sounder (MLS) data, and to two global reanalyses: The Modern-Era Retrospective analysis for Research and Application (MERRA) of the National Aeronautics and Space Administration (NASA); and, the latest reanalysis of the European Center for Medium-range Weather Forecast (ECMWF), the ERA-Interim. The MLS data have been assimilated into the MERRA, whereas the COSMIC data are used for the ERA-Interim. As a result, the MERRA agrees well with the MLS data and so does the ERA-Interim with the COSMIC data. While the monthly zonal mean distributions of water vapor from the four datasets show good agreements in northern mid-latitudes, large discrepancies exist in high southern latitudes and tropics. The MERRA shows overall a consistent seasonal cycle with MLS, but has too strong winter dehydration over the Antarctic, and is very weak in the interannual variations. The ERA-Interim fails to properly represent the winter dehydration over the Antarctic, and shows an unrealistic seasonal cycle in the tropical upper troposphere. The COSMIC data shows a good agreement with the MLS data except for the tropical "taper recorder" signal, where the COSMIC data suggest a faster upward motion than the MLS data. The COSMIC data are able to represent the moisture variabilities associated with the Quasi-Biennial Oscillation and the El Niño-Southern Oscillation.