Experimental assessment of a micro-pulse lidar system in comparison with reference lidar measurements for aerosol optical properties retrieval

Simultaneous observations of a polarized micro-pulse lidar (P-MPL) system and two reference European Aerosol Research Lidar Network lidars running at the Leipzig site Germany, 51.4∘ N, 12.4∘ E; 125 m a.s.l.) were performed during a comprehensive 2-month field intercomparison campaign in summer 2019. An experimental assessment regarding both the overlap (OVP) correction of the P-MPL signal profiles and the volume linear depolarization ratio (VLDR) analysis, together with its impact on the retrieval of the aerosol optical properties, is achieved; the experimental procedure used is also described. The optimal lidar-specific OVP function is experimentally determined, highlighting that the one delivered by the P-MPL manufacturer cannot be used long. Among the OVP functions examined, the averaged function between those obtained from the comparison of the P-MPL observations with those of the other two reference lidars seems to be the best proxy at both near- and far-field ranges. In addition, the impact of the OVP function on the accuracy of the retrieved profiles of the total particle backscatter coefficient (PBC) and the particle linear depolarization ratio (PLDR) is examined. The VLDR profile is obtained and compared with that derived from the reference lidar, showing that it needs to be corrected by a small offset value with good accuracy. Once P-MPL measurements are optimally (OVP, VLDR) corrected, both the PBC and PLDR profiles can be accurately derived and are in good agreement with reference aerosol retrievals. Overall, as a systematic requirement for lidar systems, an adequate OVP function determination and VLDR testing analysis needs to be performed on a regular basis to correct the P-MPL measurements in order to derive suitable aerosol products. A dust event observed in Leipzig in June 2019 is used for illustration.

Airborne extractive electrospray mass spectrometry measurements of the chemical composition of organic aerosol

We deployed an extractive electrospray ionization time-of-flight mass spectrometer (EESI-MS) for airborne measurements of biomass burning aerosol during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) study onboard the NASA DC-8 research aircraft. Through optimization of the electrospray working solution, active control of the electrospray region pressure, and precise control of electrospray capillary position, we achieved 1 Hz quantitative measurements of aerosol nitrocatechol and levoglucosan concentrations up to pressure altitudes of 7 km. The EESI-MS response to levoglucosan and nitrocatechol was calibrated for each flight, with flight-to-flight calibration variability of 60 % (1σ). Laboratory measurements showed no aerosol size dependence in EESI-MS sensitivity below particle geometric diameters of 400 nm, covering 82 % of accumulation-mode aerosol mass during FIREX-AQ. We also present a first in-field intercomparison of EESI-MS with a chemical analysis of aerosol online proton-transfer-reaction mass spectrometer (CHARON PTR-MS) and a high-resolution Aerodyne aerosol mass spectrometer (AMS). EESI-MS and CHARON PTR-MS levoglucosan concentrations were well correlated, with a regression slope of 0.94 (R2=0.77). AMS levoglucosan-equivalent concentrations and EESI-MS levoglucosan showed a greater difference, with a regression slope of 1.36 (R2=0.96), likely indicating the contribution of other compounds to the AMS levoglucosan-equivalent measurement. The total EESI-MS signal showed correlation (R2=0.9) with total organic aerosol measured by AMS, and the EESI-MS bulk organic aerosol sensitivity was 60 % of the sensitivity to levoglucosan standards.

Airborne Extractive Electrospray Mass Spectrometry Measurements of the Chemical Composition of Organic Aerosol

We deployed an extractive electrospray ionization time-of-flight mass spectrometer (EESI-MS) for airborne measurements of biomass burning aerosol during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) study onboard the NASA DC-8 research aircraft. Through optimization of the electrospray working solution, active control of the electrospray region pressure, and precise control of electrospray capillary position, we achieved 1 Hz quantitative measurements of aerosol nitrocatechol and levoglucosan concentrations up to pressure altitudes of 7 km. EESI-MS response to levoglucosan and nitrocatechol was calibrated for each flight, with flight-to-flight calibration variability of 60 % (1σ). Laboratory measurements showed no aerosol size dependence in EESI-MS sensitivity below particle geometric diameters of 400 nm, covering 82 % of accumulation mode aerosol mass during FIREX-AQ. We also present a first in-field intercomparison of EESI-MS with a chemical analysis of aerosol online proton-transfer-reaction mass spectrometer (CHARON PTR-MS) and a high-resolution Aerodyne aerosol mass spectrometer (AMS). EESI-MS and CHARON PTR-MS levoglucosan concentrations were well correlated, with a regression slope of 0.94, R2 = 0.77. AMS levoglucosan-equivalent concentrations and EESI-MS levoglucosan showed greater difference, with a regression slope of 1.36, R2 = 0.96, likely indicating the contribution of other compounds to the AMS levoglucosan-equivalent measurement. Total EESI-MS signal showed correlation (R2 = 0.9) with total organic aerosol measured by AMS, and the EESI-MS bulk organic aerosol sensitivity was 60 % of the sensitivity to levoglucosan standards.

Field Intercomparison of Radiometer Measurements for Ocean Colour Validation

A field intercomparison was conducted at the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea, from 9 to 19 July 2018 to assess differences in the accuracy of in- and above-water radiometer measurements used for the validation of ocean colour products. Ten measurement systems were compared. Prior to the intercomparison, the absolute radiometric calibration of all sensors was carried out using the same standards and methods at the same reference laboratory. Measurements were performed under clear sky conditions, relatively low sun zenith angles, moderately low sea state and on the same deployment platform and frame (except in-water systems). The weighted average of five above-water measurements was used as baseline reference for comparisons. For downwelling irradiance ( E d ), there was generally good agreement between sensors with differences of <6% for most of the sensors over the spectral range 400 nm–665 nm. One sensor exhibited a systematic bias, of up to 11%, due to poor cosine response. For sky radiance ( L s k y ) the spectrally averaged difference between optical systems was <2.5% with a root mean square error (RMS) <0.01 mWm−2 nm−1 sr−1. For total above-water upwelling radiance ( L t ), the difference was <3.5% with an RMS <0.009 mWm−2 nm−1 sr−1. For remote-sensing reflectance ( R r s ), the differences between above-water TriOS RAMSES were <3.5% and <2.5% at 443 and 560 nm, respectively, and were <7.5% for some systems at 665 nm. Seabird-Hyperspectral Surface Acquisition System (HyperSAS) sensors were on average within 3.5% at 443 nm, 1% at 560 nm, and 3% at 665 nm. The differences between the weighted mean of the above-water and in-water systems was <15.8% across visible bands. A sensitivity analysis showed that E d accounted for the largest fraction of the variance in R r s , which suggests that minimizing the errors arising from this measurement is the most important variable in reducing the inter-group differences in R r s . The differences may also be due, in part, to using five of the above-water systems as a reference. To avoid this, in situ normalized water-leaving radiance ( L w n ) was therefore compared to AERONET-OC SeaPRiSM L w n as an alternative reference measurement. For the TriOS-RAMSES and Seabird-HyperSAS sensors the differences were similar across the visible spectra with 4.7% and 4.9%, respectively. The difference between SeaPRiSM L w n and two in-water systems at blue, green and red bands was 11.8%. This was partly due to temporal and spatial differences in sampling between the in-water and above-water systems and possibly due to uncertainties in instrument self-shading for one of the in-water measurements.

Field Intercomparison of Radiometers Used for Satellite Validation in the 400–900 nm Range

An intercomparison of radiance and irradiance ocean color radiometers (the second laboratory comparison exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8–13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: (1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; (2) indoor, laboratory intercomparison using stable radiance and irradiance sources in a controlled environment; (3) outdoor, field intercomparison of natural radiation sources over a natural water surface. The aim of the experiment was to provide a link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the third phase of LCE-2: The results of the field experiment. The calibration of radiometers and laboratory comparison experiment are presented in a related paper of the same journal issue. Compared to the laboratory comparison, the field intercomparison has demonstrated substantially larger variability between freshly calibrated sensors, because the targets and environmental conditions during radiometric calibration were different, both spectrally and spatially. Major differences were found for radiance sensors measuring a sunlit water target at viewing zenith angle of 139° because of the different fields of view. Major differences were found for irradiance sensors because of imperfect cosine response of diffusers. Variability between individual radiometers did depend significantly also on the type of the sensor and on the specific measurement target. Uniform SI traceable radiometric calibration ensuring fairly good consistency for indoor, laboratory measurements is insufficient for outdoor, field measurements, mainly due to the different angular variability of illumination. More stringent specifications and individual testing of radiometers for all relevant systematic effects (temperature, nonlinearity, spectral stray light, etc.) are needed to reduce biases between instruments and better quantify measurement uncertainties.

Field intercomparison of prevailing sonic anemometers

Three-dimensional sonic anemometers are the core component of eddy covariance systems, which are widely used for micrometeorological and ecological research. In order to characterize the measurement uncertainty of these instruments we present and analyse the results from a field intercomparison experiment of six commonly used sonic anemometer models from four major manufacturers. These models include Campbell CSAT3, Gill HS-50 and R3, METEK uSonic-3 Omni, R. M. Young 81000 and 81000RE. The experiment was conducted over a meadow at the TERENO/ICOS site DE-Fen in southern Germany over a period of 16 days in June of 2016 as part of the ScaleX campaign. The measurement height was 3 m for all sensors, which were separated by 9 m from each other, each on its own tripod, in order to limit contamination of the turbulence measurements by adjacent structures as much as possible. Moreover, the high-frequency data from all instruments were treated with the same post-processing algorithm. In this study, we compare the results for various turbulence statistics, which include mean horizontal wind speed, standard deviations of vertical wind velocity and sonic temperature, friction velocity, and the buoyancy flux. Quantitative measures of uncertainty, such as bias and comparability, are derived from these results. We find that biases are generally very small for all sensors and all computed variables, except for the sonic temperature measurements of the two Gill sonic anemometers (HS and R3), confirming a known transducer-temperature dependence of the sonic temperature measurement. The best overall agreement between the different instruments was found for the mean wind speed and the buoyancy flux.

Field intercomparison of prevailing sonic anemometers

Three-dimensional sonic anemometers are the core component of eddy-covariance systems, which are widely used for micrometeorological and ecological research. In order to characterize the measurement uncertainty of these instruments we present and analyse the results from a field intercomparison experiment of six commonly used sonic anemometer models from four major manufacturers. These models include Campbell CSAT3, Gill HS-50 and R3, METEK uSonic-3 Omni, R.M. Young 81000 and 81000RE. The experiment was conducted over a meadow at the TERENO/ICOS site De-Fen in southern Germany over a period of 16 days in June of 2016 as part of the ScaleX campaign. The measurement height was 3 m for all sensors, which were separated by 9 m from each other, each on its own tripod, in order to limit contamination of the turbulence measurements by adjacent structures as much as possible. Moreover, the high-frequency data from all instruments were treated with the same post-processing algorithm. In this study, we compare the results for various turbulence statistics, which include mean horizontal wind speed, standard deviations of vertical wind velocity and sonic temperature, friction velocity and the buoyancy flux. Quantitative measures of uncertainty, such as bias and comparability, are derived from these results. We find that biases are generally very small for all sensors and all computed variables, except for the sonic temperature measurements of the two Gill sonic anemometers (HS and R3), confirming a known transducer-temperature dependence of the sonic temperature measurement. The best overall agreement between the different instruments was found for the mean wind speed and the buoyancy flux.