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  • Atmospheric Measurement Techniques

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Thomas von Clarmann; Norbert Glatthor; Udo Grabowski; Bernd Funke; +5 Authors

    This paper describes the error estimation for temperature and trace gas mixing ratios retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb emission spectra. The following error sources are taken into account: measurement noise, propagated temperature and pointing noise, uncertainties in the abundances of spectrally interfering species, instrument line shape errors, and spectroscopic data uncertainties in terms of line intensities and broadening coefficients. Furthermore, both the direct impact of volatile and persistent gain calibration uncertainties, offset calibration, and spectral calibration uncertainties, as well as their impact through propagated calibration-related temperature and pointing uncertainties, are considered. An error source specific to the MIPAS upper atmospheric observation mode is the propagation of the smoothing error crosstalk of the combined NO and temperature retrieval. Whenever non-local thermodynamic equilibrium modelling is used in the retrieval, related kinetic constants and mixing ratios of species involved in the modelling of populations of excitational states also contribute to the error budget. Both generalized Gaussian error propagation and perturbation studies are used to estimate the error components. Error correlations are taken into account. Estimated uncertainties are provided for a multitude of atmospheric conditions. Some error sources were found to contribute both to the random and the systematic component of the total estimated error. The sequential nature of the MIPAS retrievals gives rise to entangled errors. These are caused by error sources that affect the uncertainty in the final data product via multiple pathways, i.e., on the one hand, directly, and, on the other hand, via errors caused in a preceding retrieval step. These errors tend to partly compensate for each other. The hard-to-quantify effect of the horizontally non-homogeneous atmosphere and unknown error correlations of spectroscopic data are considered to be the major limitations of the MIPAS error estimation. © Author(s) 2022. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. This research has been supported by the Agencia Estatal de Investigación (grant no. PID2019-110689RB-I00). The article processing charges for this open-access publication were covered by the Karlsruhe Institute of Technology (KIT). With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709. Peer reviewed

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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    KITopen
    Article . 2022
    License: CC BY
    Data sources: KITopen
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    https://doi.org/10.5445/ir/100...
    Article . 2022
    License: CC BY
    Data sources: Datacite
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      KITopen
      Article . 2022
      License: CC BY
      Data sources: KITopen
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      https://doi.org/10.5445/ir/100...
      Article . 2022
      License: CC BY
      Data sources: Datacite
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    Authors: Ridolfi; M.; Tirelli; C.; +8 Authors

    In the frame of Earth observation remote-sensing data analysis, synergistic retrieval (SR) and complete data fusion (CDF) are techniques used to exploit the complementarity of the information carried by different measurements sounding the same air mass and/or ground pixel. While more difficult to implement due to the required simultaneous access to measurements originating from different instruments, the SR method is sometimes preferred over the CDF method as the latter relies on a linear approximation of the retrieved states as functions of the true atmospheric and/or surface state. In this work, we study the performance of the SR and CDF techniques when applied to simulated measurements of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) and the Infrared Atmospheric Sounding Interferometer – New Generation (IASI-NG) missions that will be operational in a few years, from two polar-orbiting satellites. The study is based on synthetic measurements generated for the two missions in clear-sky atmospheres. The target parameters of the inversion are the vertical profiles of temperature, water vapor and ozone mixing ratios, surface temperature, and spectral emissivity. We find that for exact matching of the measurements, the results of the SR and CDF techniques differ by less than 1/10 of their errors estimated through the propagation of measurement noise. For measurements with a realistic mismatch in space and time, the two methods provide more different results. Still in this case, however, the differences between the results are within the error bars due to measurement noise. We conclude that, when applied to FORUM and IASI-NG missions, the two methods are equivalent from an accuracy point of view.

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    Atmospheric Measurement Techniques; CNR ExploRA
    Article . 2022 . Peer-reviewed
    License: CC BY
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      Atmospheric Measurement Techniques; CNR ExploRA
      Article . 2022 . Peer-reviewed
      License: CC BY
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    Authors: D. Summa; D. Summa; F. Madonna; N. Franco; +3 Authors

    This paper reports results from an inter-comparison effort involving different sensors and models used to measure the atmospheric boundary layer height (ABLH). The effort took place in the framework of the first Special Observing Period of the Hydrological Cycle in the Mediterranean Experiment (HyMeX-SOP1), with the Raman lidar system BASIL deployed in Candillargues (southern France) and operating in almost continuous mode over the time period September–November 2012. ABLH estimates were obtained based on the application of the Richardson number technique to Raman lidar and radiosonde measurements and to ECMWF-ERA5 reanalysis data. In the effort we considered radiosondes launched in the proximity of the lidar site, as well as radiosondes launched from the closest radiosonde station included in the Integrated Global Radiosonde Archive (IGRA). The inter-comparison effort also includes ABLH measurements from the wind profiler, which rely on the turbulence method, as well as measurements obtained from elastic backscatter lidar signals. The Richardson number approach applied to the on-site radiosonde data is taken as reference. Measurements were carried out throughout the month of October 2012. The inter-comparison is extended to both daytime and night-time data. Results reveal a very good agreement between the different approaches, with values of the correlation coefficient R2 for all compared data pairs in the range 0.94–0.98. Values of the slope of the fitting line in the regression analysis are in the range 0.91–1.08 for daytime comparisons and in the range 0.95–1.03 for night-time comparisons, which testifies to the presence of the very small biases affecting all five ABLH estimates with respect to the reference ABLH estimate, with slightly smaller bias values found at night. Results also confirm that the combined application of different methods to the sensors and model data allows us to get accurate and cross-validated estimates of the ABL height in a variety of weather conditions. Correlations between the ABLH measurements and other atmospheric dynamic and thermodynamic variables, such as CAPE (convective available potential energy), friction velocity and relative humidity, are also evaluated to infer possible mutual dependences.

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    CNR ExploRA
    Article . 2022
    Data sources: CNR ExploRA
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    Authors: S. Noël; M. Reuter; M. Buchwitz; J. Borchardt; +38 Authors

    We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context. International audience

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    https://doi.org/10.5445/ir/100...
    Article . 2022
    License: CC BY
    Data sources: Datacite
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    MPG.PuRe
    Article . 2022
    Data sources: MPG.PuRe
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    KITopen
    Article . 2022
    License: CC BY
    Data sources: KITopen
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    Atmospheric Measurement Techniques
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      https://doi.org/10.5445/ir/100...
      Article . 2022
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      KITopen
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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    Authors: S. Kotthaus; J. A. Bravo-Aranda; J. A. Bravo-Aranda; J. A. Bravo-Aranda; +17 Authors

    The atmospheric boundary layer (ABL) defines the volume of air adjacent to the Earth’s surface for the dilution of heat, moisture, and trace substances. Quantitative knowledge on the temporal and spatial variations in the heights of the ABL and its sub-layers is still scarce, despite their importance for a series of applications (including, for example, air quality, numerical weather prediction, greenhouse gas assessment, and renewable energy production). Thanks to recent advances in ground-based remote-sensing measurement technology and algorithm development, continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution is increasingly possible. Dense measurement networks of autonomous ground-based remote-sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers are hence emerging across Europe and other parts of the world. This review summarises the capabilities and limitations of various instrument types for ABL monitoring and provides an overview on the vast number of retrieval methods developed for the detection of ABL sublayer heights from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, pointing out where instrumental or methodological synergy are considered particularly promising. The review highlights the fact that harmonised data acquisition across carefully designed sensor networks as well as tailored data processing are key to obtaining high-quality products that are again essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe. Marie Sklodowska-Curie Action Cofund 2016 EU project - Athenea3i national Portuguese funds through FCT - Fundacao para a Ciencia e Tecnologia, I.P. CA18235 871115 101036245 ANR-20-CE22-0013 PID2020-120015RB-I00 PID2020.117825GB.C21 P18-RT-3820 P20-00136 A-RNM-430-UGR20 754446 UIDB/04683/2020 European Cooperation in Science and Technology (COST) PTDC/CTAMET/29678/2017 European Commission University of Granada, Programa Operativo FEDER Andalucia 2014-2020 French National Research Agency (ANR) Region Ile-de-France Earth System Excellence Units Program Spanish Government Junta de Andalucia

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    CNR ExploRA
    Article . 2023
    Data sources: CNR ExploRA
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    https://doi.org/10.5194/amt-20...
    Preprint . 2022 . Peer-reviewed
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    Data sources: Sygma; Crossref
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      CNR ExploRA
      Article . 2023
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      https://doi.org/10.5194/amt-20...
      Preprint . 2022 . Peer-reviewed
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    Authors: B. Debus; A. T. Weakley; S. Takahama; K. M. George; +9 Authors

    To enable chemical speciation, monitoring networks collect particulate matter (PM) on different filter media, each subjected to one or more analytical techniques to quantify PM composition present in the atmosphere. In this work, we propose an alternate approach that uses one filter type (teflon or polytetrafluoroethylene, PTFE, commonly used for aerosol sampling) and one analytical method, Fourier transform infrared (FT-IR) spectroscopy to measure almost all of the major constituents in the aerosol. In the proposed method, measurements using the typical multi-filter, multi-analytical techniques are retained at a limited number of sites and used as calibration standards. At all remaining sites, only sampling on PTFE and analysis by FT-IR is performed. This method takes advantage of the sensitivity of the mid-IR domain to various organic and inorganic functional groups and offers a fast and inexpensive way of exploring sample composition. As a proof of concept, multiple years of samples collected within the Interagency Monitoring of PROtected Visual Environment network (IMPROVE) are explored with the aim of retaining high quality predictions for a broad range of atmospheric compounds including mass, organic (OC), elemental (EC), and total (TC) carbon, sulfate, nitrate, and crustal elements. Findings suggest that models based on only 21 sites, covering spatial and seasonal trends in atmospheric composition, are stable over a 3 year period within the IMPROVE network with acceptable prediction accuracy (R2 > 0.9, median bias less than 3 %) for most constituents. The major limitation is measuring nitrate as it is known to volatilize off of PTFE filters. Incorporating additional sites at low cost, partially replacing existing, more time- and cost-intensive techniques, or using the FT-IR data for quality control or substitute for missing data, are among the potential benefits of the one-filter, one-method approach.

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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    https://amt.copernicus.org/pre...
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
      Preprint . 2021 . Peer-reviewed
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      https://amt.copernicus.org/pre...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
      License: CC BY
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    Authors: Sang-Wook Lee; Sunghun Kim; Young-Suk Lee; Jae-Keun Yoo; +5 Authors

    A dual thermistor radiosonde (DTR) comprising two (aluminium-coated and black) sensors with different emissivities was developed to correct the effects of solar radiation on temperature probes based on in situ radiation measurements. Herein, the DTR performance is characterised in terms of the uncertainty via a series of ground-based facilities and an intercomparison radiosounding test. The DTR characterisation procedure using laboratory facilities is as follows: individually calibrate the temperature of the thermistors in a climate chamber from −70 to 30 ∘C to evaluate the uncertainty of raw temperature measurement before radiation correction; test the effect of temperature on the resistance reading using radiosonde boards in the climate chamber from −70 to 20 ∘C to identify a potential source of errors owing to the boards, especially at cold temperatures; individually perform radiation tests on thermistors at room temperature to investigate the degree of heating of aluminium-coated and black sensors (the average ratio = 1 : 2.4) and use the result for obtaining unit-specific radiation correction formulas; and perform parameterisation of the radiation measurement and correction formulas with five representative pairs of sensors in terms of temperature, pressure, ventilation speed, and irradiance using an upper air simulator. These results are combined and applied to the DTR sounding test conducted in July 2021. Thereafter, the effective irradiance is measured using the temperature difference between the aluminium-coated and black sensors of the DTR. The measured irradiance is then used for the radiation correction of the DTR aluminium-coated sensor. The radiation-corrected temperature of the DTR is mostly consistent with that of a commercial radiosonde (Vaisala, RS41) within the expanded uncertainty (∼ 0.35 ∘C) of the DTR at the coverage factor k = 2. Furthermore, the components contributing to the uncertainty of the radiation measurement and correction are analysed. The DTR methodology can improve the accuracy of temperature measurement in the upper air within the framework of the traceability to the International System of Units.

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    Atmospheric Measurement Techniques
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    https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
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      https://doi.org/10.5194/amt-20...
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    Authors: Ashley S. Bittner; Eben S. Cross; David H. Hagan; Carl Malings; +2 Authors

    Low-cost gas and particulate matter sensor packages offer a compact, lightweight, and easily transportable solution to address global gaps in air quality (AQ) observations. However, regions that would benefit most from widespread deployment of low-cost AQ monitors often lack the reference-grade equipment required to reliably calibrate and validate them. In this study, we explore approaches to calibrating and validating three integrated sensor packages before a 1-year deployment to rural Malawi using colocation data collected at a regulatory site in North Carolina, USA. We compare the performance of five computational modeling approaches to calibrate the electrochemical gas sensors: k-nearest neighbors (kNN) hybrid, random forest (RF) hybrid, high-dimensional model representation (HDMR), multilinear regression (MLR), and quadratic regression (QR). For the CO, Ox, NO, and NO2 sensors, we found that kNN hybrid models returned the highest coefficients of determination and lowest error metrics when validated. Hybrid models were also the most transferable approach when applied to deployment data collected in Malawi. We compared kNN hybrid calibrated CO observations from two regions in Malawi to remote sensing data and found qualitative agreement in spatial and annual trends. However, ARISense monthly mean surface observations were 2 to 4 times higher than the remote sensing data, partly due to proximity to residential biomass combustion activity not resolved by satellite imaging. We also compared the performance of the integrated Alphasense OPC-N2 optical particle counter to a filter-corrected nephelometer using colocation data collected at one of our deployment sites in Malawi. We found the performance of the OPC-N2 varied widely with environmental conditions, with the worst performance associated with high relative humidity (RH >70 %) conditions and influence from emissions from nearby residential biomass combustion. We did not find obvious evidence of systematic sensor performance decay after the 1-year deployment to Malawi. Data recovery (30 %–80 %) varied by sensor and season and was limited by insufficient power and access to resources at the remote deployment sites. Future low-cost sensor deployments to rural, low-income settings would benefit from adaptable power systems, standardized sensor calibration methodologies, and increased regional regulatory-grade monitoring infrastructure.

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    https://doi.org/10.5194/amt-20...
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    Atmospheric Measurement Techniques
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      Atmospheric Measurement Techniques
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    Authors: Michael Schäfer; Kevin Wolf; André Ehrlich; Christoph Hallbauer; +8 Authors

    The new airborne thermal infrared (TIR) imager VELOX (Video airbornE Longwave Observations within siX channels) is introduced. VELOX is a commercially available TIR camera system that has been adapted extensively for atmospheric applications, which are introduced in this paper. The system covers six spectral bands with centre wavelengths between 7.7 and 12 µm. Currently, VELOX is installed on board the German High Altitude and Long Range Research Aircraft (HALO) to observe cloud and surface properties. It provides observations of two-dimensional (2D) fields of upward terrestrial spectral radiance with a horizontal resolution of approximately 10 m×10 m at a target distance of 10 km. Atmospheric temperature values are rather low compared to the originally intended commercial applications of VELOX and range close to the detection limit of the sensor. This challenge requires additional calibration efforts to enable atmospheric applications of VELOX. Therefore, required sophisticated calibration and correction procedures, including radiometric calibrations, non-uniformity corrections, bad-pixel replacements, and window corrections, are presented. Furthermore, first observations of cloud properties acquired by VELOX during the EUREC4A (ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte) campaign are discussed, including an analysis of the cloud top brightness temperature, cloud mask/fraction, and cloud top altitude data. The data reveal the potential of VELOX to resolve the cloud top temperature with a resolution of better than 0.1 K, which translates into a resolution of approximately 40 m in cloud top altitude.

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    Atmospheric Measurement Techniques
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    Authors: Benjamin Witschas; Christian Lemmerz; Oliver Lux; Uwe Marksteiner; +7 Authors

    In August 2018, the European Space Agency (ESA) launched the first Doppler wind lidar into space, which has since then been providing continuous profiles of the horizontal line-of-sight wind component at a global scale. Aeolus data have been successfully assimilated into several numerical weather prediction (NWP) models and demonstrated a positive impact on the quality of the weather forecasts. To provide valuable input data for NWP models, a detailed characterization of the Aeolus instrumental performance as well as the realization and minimization of systematic error sources is crucial. In this paper, Aeolus interferometer spectral drifts and their potential as systematic error sources for the aerosol and wind products are investigated by means of instrument spectral registration (ISR) measurements that are performed on a weekly basis. During these measurements, the laser frequency is scanned over a range of 11 GHz in steps of 25 MHz and thus spectrally resolves the transmission curves of the Fizeau interferometer and the Fabry–Pérot interferometers (FPIs) used in Aeolus. Mathematical model functions are derived to analyze the measured transmission curves by means of non-linear fit procedures. The obtained fit parameters are used to draw conclusions about the Aeolus instrumental alignment and potentially ongoing drifts. The introduced instrumental functions and analysis tools may also be applied for upcoming missions using similar spectrometers as for instance EarthCARE (ESA), which is based on the Aeolus FPI design. International audience

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    https://amt.copernicus.org/pre...
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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
      Preprint . 2021 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Thomas von Clarmann; Norbert Glatthor; Udo Grabowski; Bernd Funke; +5 Authors

    This paper describes the error estimation for temperature and trace gas mixing ratios retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb emission spectra. The following error sources are taken into account: measurement noise, propagated temperature and pointing noise, uncertainties in the abundances of spectrally interfering species, instrument line shape errors, and spectroscopic data uncertainties in terms of line intensities and broadening coefficients. Furthermore, both the direct impact of volatile and persistent gain calibration uncertainties, offset calibration, and spectral calibration uncertainties, as well as their impact through propagated calibration-related temperature and pointing uncertainties, are considered. An error source specific to the MIPAS upper atmospheric observation mode is the propagation of the smoothing error crosstalk of the combined NO and temperature retrieval. Whenever non-local thermodynamic equilibrium modelling is used in the retrieval, related kinetic constants and mixing ratios of species involved in the modelling of populations of excitational states also contribute to the error budget. Both generalized Gaussian error propagation and perturbation studies are used to estimate the error components. Error correlations are taken into account. Estimated uncertainties are provided for a multitude of atmospheric conditions. Some error sources were found to contribute both to the random and the systematic component of the total estimated error. The sequential nature of the MIPAS retrievals gives rise to entangled errors. These are caused by error sources that affect the uncertainty in the final data product via multiple pathways, i.e., on the one hand, directly, and, on the other hand, via errors caused in a preceding retrieval step. These errors tend to partly compensate for each other. The hard-to-quantify effect of the horizontally non-homogeneous atmosphere and unknown error correlations of spectroscopic data are considered to be the major limitations of the MIPAS error estimation. © Author(s) 2022. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. This research has been supported by the Agencia Estatal de Investigación (grant no. PID2019-110689RB-I00). The article processing charges for this open-access publication were covered by the Karlsruhe Institute of Technology (KIT). With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709. Peer reviewed

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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    KITopen
    Article . 2022
    License: CC BY
    Data sources: KITopen
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    https://doi.org/10.5445/ir/100...
    Article . 2022
    License: CC BY
    Data sources: Datacite
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      KITopen
      Article . 2022
      License: CC BY
      Data sources: KITopen
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      https://doi.org/10.5445/ir/100...
      Article . 2022
      License: CC BY
      Data sources: Datacite
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    Authors: Ridolfi; M.; Tirelli; C.; +8 Authors

    In the frame of Earth observation remote-sensing data analysis, synergistic retrieval (SR) and complete data fusion (CDF) are techniques used to exploit the complementarity of the information carried by different measurements sounding the same air mass and/or ground pixel. While more difficult to implement due to the required simultaneous access to measurements originating from different instruments, the SR method is sometimes preferred over the CDF method as the latter relies on a linear approximation of the retrieved states as functions of the true atmospheric and/or surface state. In this work, we study the performance of the SR and CDF techniques when applied to simulated measurements of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) and the Infrared Atmospheric Sounding Interferometer – New Generation (IASI-NG) missions that will be operational in a few years, from two polar-orbiting satellites. The study is based on synthetic measurements generated for the two missions in clear-sky atmospheres. The target parameters of the inversion are the vertical profiles of temperature, water vapor and ozone mixing ratios, surface temperature, and spectral emissivity. We find that for exact matching of the measurements, the results of the SR and CDF techniques differ by less than 1/10 of their errors estimated through the propagation of measurement noise. For measurements with a realistic mismatch in space and time, the two methods provide more different results. Still in this case, however, the differences between the results are within the error bars due to measurement noise. We conclude that, when applied to FORUM and IASI-NG missions, the two methods are equivalent from an accuracy point of view.

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    Atmospheric Measurement Techniques; CNR ExploRA
    Article . 2022 . Peer-reviewed
    License: CC BY
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      Atmospheric Measurement Techniques; CNR ExploRA
      Article . 2022 . Peer-reviewed
      License: CC BY
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: D. Summa; D. Summa; F. Madonna; N. Franco; +3 Authors

    This paper reports results from an inter-comparison effort involving different sensors and models used to measure the atmospheric boundary layer height (ABLH). The effort took place in the framework of the first Special Observing Period of the Hydrological Cycle in the Mediterranean Experiment (HyMeX-SOP1), with the Raman lidar system BASIL deployed in Candillargues (southern France) and operating in almost continuous mode over the time period September–November 2012. ABLH estimates were obtained based on the application of the Richardson number technique to Raman lidar and radiosonde measurements and to ECMWF-ERA5 reanalysis data. In the effort we considered radiosondes launched in the proximity of the lidar site, as well as radiosondes launched from the closest radiosonde station included in the Integrated Global Radiosonde Archive (IGRA). The inter-comparison effort also includes ABLH measurements from the wind profiler, which rely on the turbulence method, as well as measurements obtained from elastic backscatter lidar signals. The Richardson number approach applied to the on-site radiosonde data is taken as reference. Measurements were carried out throughout the month of October 2012. The inter-comparison is extended to both daytime and night-time data. Results reveal a very good agreement between the different approaches, with values of the correlation coefficient R2 for all compared data pairs in the range 0.94–0.98. Values of the slope of the fitting line in the regression analysis are in the range 0.91–1.08 for daytime comparisons and in the range 0.95–1.03 for night-time comparisons, which testifies to the presence of the very small biases affecting all five ABLH estimates with respect to the reference ABLH estimate, with slightly smaller bias values found at night. Results also confirm that the combined application of different methods to the sensors and model data allows us to get accurate and cross-validated estimates of the ABL height in a variety of weather conditions. Correlations between the ABLH measurements and other atmospheric dynamic and thermodynamic variables, such as CAPE (convective available potential energy), friction velocity and relative humidity, are also evaluated to infer possible mutual dependences.

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    CNR ExploRA
    Article . 2022
    Data sources: CNR ExploRA
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    Authors: S. Noël; M. Reuter; M. Buchwitz; J. Borchardt; +38 Authors

    We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context. International audience

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    https://doi.org/10.5445/ir/100...
    Article . 2022
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    KITopen
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    Atmospheric Measurement Techniques
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      https://doi.org/10.5445/ir/100...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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    Authors: S. Kotthaus; J. A. Bravo-Aranda; J. A. Bravo-Aranda; J. A. Bravo-Aranda; +17 Authors

    The atmospheric boundary layer (ABL) defines the volume of air adjacent to the Earth’s surface for the dilution of heat, moisture, and trace substances. Quantitative knowledge on the temporal and spatial variations in the heights of the ABL and its sub-layers is still scarce, despite their importance for a series of applications (including, for example, air quality, numerical weather prediction, greenhouse gas assessment, and renewable energy production). Thanks to recent advances in ground-based remote-sensing measurement technology and algorithm development, continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution is increasingly possible. Dense measurement networks of autonomous ground-based remote-sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers are hence emerging across Europe and other parts of the world. This review summarises the capabilities and limitations of various instrument types for ABL monitoring and provides an overview on the vast number of retrieval methods developed for the detection of ABL sublayer heights from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, pointing out where instrumental or methodological synergy are considered particularly promising. The review highlights the fact that harmonised data acquisition across carefully designed sensor networks as well as tailored data processing are key to obtaining high-quality products that are again essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe. Marie Sklodowska-Curie Action Cofund 2016 EU project - Athenea3i national Portuguese funds through FCT - Fundacao para a Ciencia e Tecnologia, I.P. CA18235 871115 101036245 ANR-20-CE22-0013 PID2020-120015RB-I00 PID2020.117825GB.C21 P18-RT-3820 P20-00136 A-RNM-430-UGR20 754446 UIDB/04683/2020 European Cooperation in Science and Technology (COST) PTDC/CTAMET/29678/2017 European Commission University of Granada, Programa Operativo FEDER Andalucia 2014-2020 French National Research Agency (ANR) Region Ile-de-France Earth System Excellence Units Program Spanish Government Junta de Andalucia

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    https://doi.org/10.5194/amt-20...
    Preprint . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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    Authors: B. Debus; A. T. Weakley; S. Takahama; K. M. George; +9 Authors

    To enable chemical speciation, monitoring networks collect particulate matter (PM) on different filter media, each subjected to one or more analytical techniques to quantify PM composition present in the atmosphere. In this work, we propose an alternate approach that uses one filter type (teflon or polytetrafluoroethylene, PTFE, commonly used for aerosol sampling) and one analytical method, Fourier transform infrared (FT-IR) spectroscopy to measure almost all of the major constituents in the aerosol. In the proposed method, measurements using the typical multi-filter, multi-analytical techniques are retained at a limited number of sites and used as calibration standards. At all remaining sites, only sampling on PTFE and analysis by FT-IR is performed. This method takes advantage of the sensitivity of the mid-IR domain to various organic and inorganic functional groups and offers a fast and inexpensive way of exploring sample composition. As a proof of concept, multiple years of samples collected within the Interagency Monitoring of PROtected Visual Environment network (IMPROVE) are explored with the aim of retaining high quality predictions for a broad range of atmospheric compounds including mass, organic (OC), elemental (EC), and total (TC) carbon, sulfate, nitrate, and crustal elements. Findings suggest that models based on only 21 sites, covering spatial and seasonal trends in atmospheric composition, are stable over a 3 year period within the IMPROVE network with acceptable prediction accuracy (R2 > 0.9, median bias less than 3 %) for most constituents. The major limitation is measuring nitrate as it is known to volatilize off of PTFE filters. Incorporating additional sites at low cost, partially replacing existing, more time- and cost-intensive techniques, or using the FT-IR data for quality control or substitute for missing data, are among the potential benefits of the one-filter, one-method approach.

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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    https://amt.copernicus.org/pre...
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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    Authors: Sang-Wook Lee; Sunghun Kim; Young-Suk Lee; Jae-Keun Yoo; +5 Authors

    A dual thermistor radiosonde (DTR) comprising two (aluminium-coated and black) sensors with different emissivities was developed to correct the effects of solar radiation on temperature probes based on in situ radiation measurements. Herein, the DTR performance is characterised in terms of the uncertainty via a series of ground-based facilities and an intercomparison radiosounding test. The DTR characterisation procedure using laboratory facilities is as follows: individually calibrate the temperature of the thermistors in a climate chamber from −70 to 30 ∘C to evaluate the uncertainty of raw temperature measurement before radiation correction; test the effect of temperature on the resistance reading using radiosonde boards in the climate chamber from −70 to 20 ∘C to identify a potential source of errors owing to the boards, especially at cold temperatures; individually perform radiation tests on thermistors at room temperature to investigate the degree of heating of aluminium-coated and black sensors (the average ratio = 1 : 2.4) and use the result for obtaining unit-specific radiation correction formulas; and perform parameterisation of the radiation measurement and correction formulas with five representative pairs of sensors in terms of temperature, pressure, ventilation speed, and irradiance using an upper air simulator. These results are combined and applied to the DTR sounding test conducted in July 2021. Thereafter, the effective irradiance is measured using the temperature difference between the aluminium-coated and black sensors of the DTR. The measured irradiance is then used for the radiation correction of the DTR aluminium-coated sensor. The radiation-corrected temperature of the DTR is mostly consistent with that of a commercial radiosonde (Vaisala, RS41) within the expanded uncertainty (∼ 0.35 ∘C) of the DTR at the coverage factor k = 2. Furthermore, the components contributing to the uncertainty of the radiation measurement and correction are analysed. The DTR methodology can improve the accuracy of temperature measurement in the upper air within the framework of the traceability to the International System of Units.

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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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    https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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    Authors: Ashley S. Bittner; Eben S. Cross; David H. Hagan; Carl Malings; +2 Authors

    Low-cost gas and particulate matter sensor packages offer a compact, lightweight, and easily transportable solution to address global gaps in air quality (AQ) observations. However, regions that would benefit most from widespread deployment of low-cost AQ monitors often lack the reference-grade equipment required to reliably calibrate and validate them. In this study, we explore approaches to calibrating and validating three integrated sensor packages before a 1-year deployment to rural Malawi using colocation data collected at a regulatory site in North Carolina, USA. We compare the performance of five computational modeling approaches to calibrate the electrochemical gas sensors: k-nearest neighbors (kNN) hybrid, random forest (RF) hybrid, high-dimensional model representation (HDMR), multilinear regression (MLR), and quadratic regression (QR). For the CO, Ox, NO, and NO2 sensors, we found that kNN hybrid models returned the highest coefficients of determination and lowest error metrics when validated. Hybrid models were also the most transferable approach when applied to deployment data collected in Malawi. We compared kNN hybrid calibrated CO observations from two regions in Malawi to remote sensing data and found qualitative agreement in spatial and annual trends. However, ARISense monthly mean surface observations were 2 to 4 times higher than the remote sensing data, partly due to proximity to residential biomass combustion activity not resolved by satellite imaging. We also compared the performance of the integrated Alphasense OPC-N2 optical particle counter to a filter-corrected nephelometer using colocation data collected at one of our deployment sites in Malawi. We found the performance of the OPC-N2 varied widely with environmental conditions, with the worst performance associated with high relative humidity (RH >70 %) conditions and influence from emissions from nearby residential biomass combustion. We did not find obvious evidence of systematic sensor performance decay after the 1-year deployment to Malawi. Data recovery (30 %–80 %) varied by sensor and season and was limited by insufficient power and access to resources at the remote deployment sites. Future low-cost sensor deployments to rural, low-income settings would benefit from adaptable power systems, standardized sensor calibration methodologies, and increased regional regulatory-grade monitoring infrastructure.

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    https://doi.org/10.5194/amt-20...
    Preprint . 2021 . Peer-reviewed
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    Atmospheric Measurement Techniques
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/amt-20...
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      Atmospheric Measurement Techniques
      Article . 2022 . Peer-reviewed
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    Authors: Michael Schäfer; Kevin Wolf; André Ehrlich; Christoph Hallbauer; +8 Authors

    The new airborne thermal infrared (TIR) imager VELOX (Video airbornE Longwave Observations within siX channels) is introduced. VELOX is a commercially available TIR camera system that has been adapted extensively for atmospheric applications, which are introduced in this paper. The system covers six spectral bands with centre wavelengths between 7.7 and 12 µm. Currently, VELOX is installed on board the German High Altitude and Long Range Research Aircraft (HALO) to observe cloud and surface properties. It provides observations of two-dimensional (2D) fields of upward terrestrial spectral radiance with a horizontal resolution of approximately 10 m×10 m at a target distance of 10 km. Atmospheric temperature values are rather low compared to the originally intended commercial applications of VELOX and range close to the detection limit of the sensor. This challenge requires additional calibration efforts to enable atmospheric applications of VELOX. Therefore, required sophisticated calibration and correction procedures, including radiometric calibrations, non-uniformity corrections, bad-pixel replacements, and window corrections, are presented. Furthermore, first observations of cloud properties acquired by VELOX during the EUREC4A (ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte) campaign are discussed, including an analysis of the cloud top brightness temperature, cloud mask/fraction, and cloud top altitude data. The data reveal the potential of VELOX to resolve the cloud top temperature with a resolution of better than 0.1 K, which translates into a resolution of approximately 40 m in cloud top altitude.

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    MPG.PuRe
    Article . 2022
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    MPG.PuRe
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    Atmospheric Measurement Techniques
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    Authors: Benjamin Witschas; Christian Lemmerz; Oliver Lux; Uwe Marksteiner; +7 Authors

    In August 2018, the European Space Agency (ESA) launched the first Doppler wind lidar into space, which has since then been providing continuous profiles of the horizontal line-of-sight wind component at a global scale. Aeolus data have been successfully assimilated into several numerical weather prediction (NWP) models and demonstrated a positive impact on the quality of the weather forecasts. To provide valuable input data for NWP models, a detailed characterization of the Aeolus instrumental performance as well as the realization and minimization of systematic error sources is crucial. In this paper, Aeolus interferometer spectral drifts and their potential as systematic error sources for the aerosol and wind products are investigated by means of instrument spectral registration (ISR) measurements that are performed on a weekly basis. During these measurements, the laser frequency is scanned over a range of 11 GHz in steps of 25 MHz and thus spectrally resolves the transmission curves of the Fizeau interferometer and the Fabry–Pérot interferometers (FPIs) used in Aeolus. Mathematical model functions are derived to analyze the measured transmission curves by means of non-linear fit procedures. The obtained fit parameters are used to draw conclusions about the Aeolus instrumental alignment and potentially ongoing drifts. The introduced instrumental functions and analysis tools may also be applied for upcoming missions using similar spectrometers as for instance EarthCARE (ESA), which is based on the Aeolus FPI design. International audience

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