Xinhua Zhou, Tian Gao, E. Takle, Xiaojie Zhen, A. Suyker, T. Awada, J. Okalebo, Jiaojun Zhu
{"title":"Air temperature equation derived from sonic temperature and water vapor mixing ratio for air flow sampled through closed-path eddy-covariance flux systems","authors":"Xinhua Zhou, Tian Gao, E. Takle, Xiaojie Zhen, A. Suyker, T. Awada, J. Okalebo, Jiaojun Zhu","doi":"10.5194/amt-2021-160","DOIUrl":"https://doi.org/10.5194/amt-2021-160","url":null,"abstract":"Abstract. Air temperar (T) plays a fundamental role in many aspects of the flux exchanges between the atmosphere and ecosystems. Additionally, it is critical to know where (in relation to other essential measurements) and at what frequency T must be measured to accurately describe such exchanges. In closed-path eddy-covariance (CPEC) flux systems, T can be computed from the sonic temperature (Ts) and water vapor mixing ratio that are measured by the fast-response senosrs of three-dimensional sonic anemometer and infrared gas analyzer, respectively. T then is computed by use of either T = Ts (1 + 0.51q)−1, where q is specific humidity, or T = Ts (1 + 0.32e / P)−1, where e is water vapor pressure and P is atmospheric pressure. Converting q and e / P into the same water vapor mixing ratio analytically reveals the difference between these two equations. This difference in a CPEC system could reach ±0.18 K, bringing an uncertainty into the accuracy of T from both equations and raises the question of which equation is better. To clarify the uncertainty and to answer this question, the derivation of T equations in terms of Ts and H2O-related variables is thoroughly studied. The two equations above were developed with approximations. Therefore, neither of their accuracies were evaluated, nor was the question answered. Based on the first principles, this study derives the T equation in terms of Ts and water vapor molar mixing ratio (χH2O) without any assumption and approximation. Thus, this equation itself does not have any error and the accuracy in T from this equation (equation-computed T) depends solely on the measurement accuracies of Ts and χH2O. Based on current specifications for Ts and χH2O in the CPEC300 series and given their maximized measurement uncertainties, the accuracy in equation-computed T is specified within ±1.01 K. This accuracy uncertainty is propagated mainly (±1.00 K) from the uncertainty in Ts measurements and little (±0.03 K) from the uncertainty in χH2O measurements. Apparently, the improvement on measurement technologies particularly for Ts would be a key to narrow this accuracy range. Under normal sensor and weather conditions, the specified accuracy is overestimated and actual accuracy is better. Equation-computed T has frequency response equivalent to high-frequency Ts and is insensitive to solar contamination during measurements. As synchronized at a temporal scale of measurement frequency and matched at a spatial scale of measurement volume with all aerodynamic and thermodynamic variables, this T has its advanced merits in boundary-layer meteorology and applied meteorology.","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122100385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of Sulfur Dioxide by Broadband Cavity Enhanced Absorption Spectroscopy (BBCEAS)","authors":"R. Thalman, J. Hansen","doi":"10.5194/AMT-2021-172","DOIUrl":"https://doi.org/10.5194/AMT-2021-172","url":null,"abstract":"Abstract. Sulfur dioxide (SO2) is an important precursor for formation of atmospheric sulfate aerosol and acid rain. We present an instrument using Broad Band Cavity Enhanced Absorption Spectroscopy (BBCEAS) for the measurement of SO2 with a minimum limit of detection of 0.6 ppbv using the spectral range 305.5–312 nm and an averaging time of 60 seconds. The instrument consists of high reflectivity mirrors (0.9984 at 310 nm) and a deep UV light source. The effective absorption path length of the instrument is 610 m in a 0.957 m base length. Published reference absorption cross-sections were used to fit and retrieve the SO2 concentrations and were compared to a diluted standard for SO2. The comparison was well correlated, R2 = 0.9985 with a correlation slope of 1.01.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115335744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Gačnik, I. Živkovič, S. Ribeiro Guevara, R. Jacimovic, J. Kotnik, Gianmarco De Feo, Matthew A Dexter, W. Corns, M. Horvat
{"title":"Behaviour of KCl sorbent traps and KCl trapping solutions used for atmospheric mercury speciation: stability and specificity","authors":"J. Gačnik, I. Živkovič, S. Ribeiro Guevara, R. Jacimovic, J. Kotnik, Gianmarco De Feo, Matthew A Dexter, W. Corns, M. Horvat","doi":"10.5194/amt-2021-153","DOIUrl":"https://doi.org/10.5194/amt-2021-153","url":null,"abstract":"Abstract. Atmospheric mercury speciation is of paramount importance for understanding the behavior of mercury once it is emitted into the atmosphere as gaseous elemental (GEM), gaseous oxidized (GOM) and particulate-bound (PBM) mercury. GOM and PBM sampling are the most problematic steps in the analytical procedure. GOM sampling with speciation traps composed of KCl sorbent materials and KCl trapping solutions are commonly used sampling methods, although the work done at ambient air concentrations is limited. The results of the specificity test showed that the KCl sorbent traps are very specific when using new traps, while their specificity drops dramatically when they are reused. The results of the stability test showed that the highest Hg2+ losses (up to 5.5 % of Hg2+ loss) occur when low amounts of Hg2+ (< 1 ng) are loaded, due to a reduction of Hg2+ to Hg0. GOM losses should be taken into account when using KCl sorbent traps for atmospheric Hg speciation, especially at low ambient GOM concentrations. KCl trapping solutions have also been considered as a selective trapping media for GOM in atmospheric samples. A dimensionless Henry’s law constant was experimentally derived and was used to calculate the solubility of elemental Hg in KCl solution. The degree of GEM oxidation was established by purging elemental Hg calibration gas into a KCl solution and determining the GOM trapped using aqueous phase propylation liquid-liquid extraction GC-AFS. A positive GOM bias was observed due to the solubility and oxidation of GEM in KCl trapping solutions strongly suggesting that this approach is unsuitable for atmospheric mercury speciation measurements.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116906751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Lerot, F. Hendrick, M. Van Roozendael, L. Alvarado, A. Richter, I. de Smedt, N. Theys, J. Vlietinck, Huan Yu, J. van Gent, T. Stavrakou, J. Müller, P. Valks, D. Loyola, H. Irie, Vinod Kumar, T. Wagner, S. Schreier, V. Sinha, Ting Wang, Pucai C. Wang, C. Retscher
{"title":"Glyoxal tropospheric column retrievals from TROPOMI, multi-satellite intercomparison and ground-based validation","authors":"C. Lerot, F. Hendrick, M. Van Roozendael, L. Alvarado, A. Richter, I. de Smedt, N. Theys, J. Vlietinck, Huan Yu, J. van Gent, T. Stavrakou, J. Müller, P. Valks, D. Loyola, H. Irie, Vinod Kumar, T. Wagner, S. Schreier, V. Sinha, Ting Wang, Pucai C. Wang, C. Retscher","doi":"10.5194/amt-2021-158","DOIUrl":"https://doi.org/10.5194/amt-2021-158","url":null,"abstract":"Abstract. We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPOspheric Monitoring Instrument (TROPOMI) on board of the Sentinel-5 Precursor satellite. Atmospheric glyoxal results from the oxidation of other non-methane volatile organic compounds (NMVOCs) and from direct emissions caused by combustion processes. Therefore, this product is a useful indicator of VOC emissions. It is generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the Differential Optical Absorption Spectroscopy (DOAS) approach. Among the algorithmic updates, the DOAS fit now includes corrections to mitigate the impact of spectral misfits caused by scene brightness inhomogeneity and strong NO2 absorption. The product comes along with a full error characterization, which allows providing random and systematic error estimates for every observation. Systematic errors are typically in the range of 1–3 × 1014 molec/cm2 (~30–70 % in emission regimes). Random errors are larger (> 6 × 1014 molec/cm2) but can be reduced by averaging observations in space and/or time. Benefiting from a high signal-to-noise ratio and a large number of small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of details. Using the same retrieval algorithmic baseline, glyoxal column data sets are also generated from the Ozone Monitoring Instrument (OMI) on Aura and from the Global Ozone Monitoring Experiment-2 (GOME-2) on board of Metop-A and Metop-B. Those four data sets are intercompared over large-scale regions worldwide and show a high level of consistency. The satellite glyoxal columns are also compared to glyoxal columns retrieved from ground-based Multi-Axis (MAX-) DOAS instruments at nine stations in Asia and Europe. In general, the satellite and MAX-DOAS instruments provide consistent glyoxal columns both in terms of absolute values and variability. Correlation coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where satellite data appears low biased during wintertime. The mean absolute glyoxal columns from satellite and MAX-DOAS generally agree well for low/moderate columns with differences less than 1 × 1014 molec/cm2. A larger bias is identified at two sites where the MAX-DOAS columns are very large. Despite this systematic bias, the consistency of the satellite and MAX-DOAS glyoxal seasonal variability is excellent.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125781145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Atmospheric Carbon Dioxide Measurement from Aircraft and Comparison with OCO-2 and Carbon Tracker Model Data","authors":"Qin Wang, Farhan Mustafa, Lingbing Bu, Shouzheng Zhu, Jiqiao Liu, Weibiao Chen","doi":"10.5194/amt-2021-92","DOIUrl":"https://doi.org/10.5194/amt-2021-92","url":null,"abstract":"Abstract. Accurate monitoring of the atmospheric carbon dioxide (CO2) and its distribution is of great significance for studying the carbon cycle and predicting the future climate change. Compared to the ground observational sites, the airborne observations cover a wider area, and simultaneously observe a variety of surface types, which help in effectively monitoring the distribution of CO2 sources and sinks. In this work, an airborne experiment was carried out in March 2019 over Shanhaiguan area, China (39–41N,119–121E). An Integrated Path Differential Absorption (IPDA) Light Detection and Ranging (LIDAR) system and a commercial instrument, the Ultraportable Greenhouse Gas Analyzer (UGGA), were used installed on an aircraft to observe the CO2 distribution over various surface types. The Pulse Integration Method (PIM) algorithm was used to calculate the Differential Absorption Optical Depth (DAOD) from the LIDAR data. The CO2 column-averaged dry-air mixing ratio (XCO2) was calculated over different types of surfaces including mountain, ocean and urban areas. The concentrations of the XCO2 calculated from LIDAR measurements over ocean, mountain, and urban areas were 421.11, 427.67, and 430 ppm, respectively. Moreover, through the detailed analysis of the data obtained from the UGGA, the influence of pollution levels on the CO2 concentration was also studied. During the whole flight campaign, March 18 was heavily polluted with an Air Quality Index (AQI) of 175 and PM2.5 of 131. The Aerosol Optical Depth (AOD) reported by a sun photometer installed at the Funning ground station was 1.28. Compared to the other days, the CO2 concentration measured by UGGA at different heights was the largest on March 18 with an average value of 422.59 ppm, that was about 10 ppm higher than the measurements recorded on March 16. Moreover, the vertical profiles of Orbiting Carbon observatory-2 (OCO-2) OCO-2 and CarbonTracker were also compared with the aircraft measurements. All the datasets showed a similar variation trend with some differences in their CO2 concentrations, which proved the existence of a good agreement among them.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125601416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Konovalov, N. A. Golovushkin, M. Beekmann, M. Panchenko, M. Andreae
{"title":"Inferring the absorption properties of organic aerosol in biomass burning plumes from remote optical observations","authors":"I. Konovalov, N. A. Golovushkin, M. Beekmann, M. Panchenko, M. Andreae","doi":"10.5194/amt-2021-151","DOIUrl":"https://doi.org/10.5194/amt-2021-151","url":null,"abstract":"Abstract. Light-absorbing organic matter, known as brown carbon (BrC), has previously been found to significantly enhance the absorption of solar radiation by biomass burning (BB) aerosol. Previous studies also proposed methods aimed at constraining the BrC contribution to the overall aerosol absorption using the absorption Ångström exponents (AAEs) derived from the multi-wavelength remote observations at Aerosol Robotic Network (AERONET). However, representations of the BrC absorption in atmospheric models remain uncertain, particularly due to the high variability of the absorption properties of BB organic aerosol (OA). As a result, there is a need for stronger observational constraints on these properties. We extend the concept of the established AAE-based methods in the framework of our Bayesian method, which combines remote optical observations with Monte Carlo simulations of the aerosol absorption properties. We propose that the observational constraints on the absorption properties of BB OA can be enhanced by using the single scattering albedo (SSA) as part of the observation vector. The capabilities of our method were first examined by using synthetic data, which were intended to represent the absorption properties of BB aerosol originating from wildfires in Siberia. We found that observations of AAEs and SSA can provide efficient constraints not only on the BrC contribution to the total absorption but also on both the imaginary part of the refractive index and mass absorption efficiency of OA. As a result of the subsequent application of our method to the original multi-annual data from Siberian AERONET sites, we estimated that the average contribution of BrC to the overall light absorption by BB aerosol in Siberia at the 440 nm wavelength is about 15 %, although, in some cases, it can be more than 30 %. Based on the analysis of the AERONET data, we also derived simple nonlinear parameterizations for the absorption characteristics of BB OA in Siberia as functions of AAE.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117163657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Kalesse-Los, Willi Schimmel, E. Luke, P. Seifert
{"title":"Evaluating cloud liquid detection using cloud radar Doppler spectra in a pre-trained artificial neural network against Cloudnet liquid detection","authors":"H. Kalesse-Los, Willi Schimmel, E. Luke, P. Seifert","doi":"10.5194/amt-2021-60","DOIUrl":"https://doi.org/10.5194/amt-2021-60","url":null,"abstract":"Abstract. Detection of liquid-containing cloud layers in thick mixed-phase clouds or multi-layer cloud situations from ground-basedremote sensing instruments still pose observational challenges yet improvements are crucial since the existence of multi-layerliquid layers in mixed-phase cloud situations influences cloud radiative effects, cloud life time, and precipitation formationprocesses. Hydrometeor target classifications such as Cloudnet that require a lidar signal for the classification of liquid arelimited to the maximum height of lidar signal penetration and thus often lead to underestimations of liquid-containing cloudlayers. Here we evaluate the Cloudnet liquid detection against the approach of Luke et al. (2010) which extracts morphologicalfeatures in cloud-penetrating cloud radar Doppler spectra measurements in a artificial neural network (ANN) approach toclassify liquid beyond full lidar signal attenuation based on the simulation of the two lidar parameters particle backscattercoefficient and particle depolarization ratio. We show that the ANN of Luke et al. (2010) which was trained in Arctic conditionscan successfully be applied to observations in the mid-latitudes obtained during the seven-week long ACCEPT field experimentin Cabauw, the Netherlands, 2014. In a sensitivity study covering the whole duration of the ACCEPT campaign, different liquid-detectionthresholds for ANN-predicted lidar variables are applied and evaluated against the Cloudnet target classification.Independent validation of the liquid mask from the standard Cloudnet target classification against the ANN-based techniqueis realized by comparisons to observations of microwave radiometer liquid water path, ceilometer liquid-layer base altitude,and radiosonde relative humidity. Four conclusions were drawn from the investigation: First, it was found that the thresholdselection criteria of liquid-related lidar backscatter and depolarization alone control the liquid detection considerably. Second,nevertheless, all threshold values used in the ANN-framework were found to outperform the Cloudnet target classification fordeep or multi-layer cloud situations where the lidar signal is fully attenuated within low liquid layers and the cloud reflectivityin higher cloud layers was sufficiently high to be detectable by the cloud radar. Third, in convective situations for whichlidar data is available and for which the imprint of cloud microphysics on the radar Doppler spectrum is decreased, Cloudnetoutperforms the ANN retrieval. Fourth, in high-level clouds both approaches (Cloudnet and the ANN technique), are limited.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133610105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Latent heating profiles from GOES-16 and its comparison to heating from NEXRAD and GPM","authors":"Yoonjin Lee, C. Kummerow, M. Zupanski","doi":"10.5194/amt-2021-97","DOIUrl":"https://doi.org/10.5194/amt-2021-97","url":null,"abstract":"Abstract. Latent heating (LH) is an important quantity in both weather forecasting and climate analysis, being the essential factor driving convective systems. Yet, inferring LH rates from our current observing systems is challenging at best. For climate studies, LH has been retrieved from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) using model simulations in the look-up table (LUT) that relates instantaneous radar profiles to corresponding heating profiles. These radars, first on TRMM and then Global Precipitation Measurement (GPM), provide a continuous record of LH. However, with observations approximately 3 days apart, its temporal resolution is too coarse to be used to initiate convection in forecast models. In operational forecast models such as High-Resolution Rapid Refresh (HRRR), convection is initiated from LH derived from ground based radar. Despite the high spatial and temporal resolution of ground-based radars, one disadvantage of using it is that its data are only available over well observed land areas. This study suggests a method to derive LH from the Geostationary Operational-Environmental Satellite-16 (GOES-16) in near-real time. Even though the visible and infrared channels on the Advanced Baseline Imager (ABI) provide mostly cloud top information, rapid changes in cloud top visible and infrared properties, when coupled to a LUT similar to those used by the TRMM and GPM radars, can equally be used to derive LH profiles for convective regions using model simulations coupled to a convective classification scheme and channel 14 (11.2 μm) brightness temperature. Convective regions detected by GOES-16 are assigned LH from the LUT, and they are compared with LH from NEXRAD and one of Dual-frequency Precipitation Radar (DPR) products, Goddard Convective-Stratiform Heating (CSH). LH obtained from GOES-16 show similar magnitude with NEXRAD and CSH, and vertical distribution of LH is also very similar with CSH. Overall, GOES LH appear to have the ability to mimic LH from radars, although the area identified as convective is roughly 25 % smaller than the current HRRR model, while the heating is correspondingly higher.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125134053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Lieberherr, Kevin Auderset, B. Calpini, B. Clot, B. Crouzy, M. Gysel-Beer, T. Konzelmann, J. Manzano, A. Mihajlović, A. Moallemi, D. O’Connor, B. Šikoparija, Eric Sauvageat, F. Tummon, K. Vasilatou
{"title":"Assessment of Real-time Bioaerosol Particle Counters using Reference Chamber Experiments","authors":"G. Lieberherr, Kevin Auderset, B. Calpini, B. Clot, B. Crouzy, M. Gysel-Beer, T. Konzelmann, J. Manzano, A. Mihajlović, A. Moallemi, D. O’Connor, B. Šikoparija, Eric Sauvageat, F. Tummon, K. Vasilatou","doi":"10.5194/amt-2021-136","DOIUrl":"https://doi.org/10.5194/amt-2021-136","url":null,"abstract":"Abstract. This study presents the first reference calibrations of three commercially available bioaerosol detectors. The Droplet Measurement Technologies WIBS-NEO, Plair Rapid-E, and Swisens Poleno were compared with a primary standard for particle number concentrations at the Federal Institute for Metrology METAS. Polystyrene (PSL) spheres were used to assess absolute particle counts for diameters from 0.5 μm to 10 μm. For the three devices, counting efficiency was found to be strongly dependent on particle size. The results confirm the expected detection range for which the instruments were designed. While the WIBS-NEO achieves its highest efficiency at smaller particles, e.g. 90 % for 0.9 μm diameter, the Plair Rapid-E performs best for larger particles, with an efficiency of 58 % for particles with a diameter of 10 μm. The Swisens Poleno is also designed for larger particles, but operates well from 2 μm. However, the exact counting efficiency of the Poleno could not be evaluated as the cut-off diameter range of the integrated concentrator unit was not completely covered. In further experiments, three different types of fluorescent particles were tested to investigate the fluorescent detection capabilities of the Plair Rapid-E and the Swisens Poleno. Both instruments showed good agreement with the reference data. While the challenge to produce known concentrations of larger particles above 10 μm or even fresh pollen particles remain, the approach presented in this paper provides a potential standardised validation method that can be used to assess counting efficiency and fluorescence measurements of automatic bioaerosol monitoring devices.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128434634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Manninen, E. Jääskeläinen, Niilo Siljamo, A. Riihelä, K. Karlsson
{"title":"Cloud probability-based estimation of black-sky surface albedo from AVHRR data","authors":"T. Manninen, E. Jääskeläinen, Niilo Siljamo, A. Riihelä, K. Karlsson","doi":"10.5194/AMT-2021-143","DOIUrl":"https://doi.org/10.5194/AMT-2021-143","url":null,"abstract":"Abstract. Cloud cover constitutes a major challenge for the surface albedo estimation using Advanced Very High Resolution Radiometer AVHRR data for all possible conditions of cloud fraction and cloud type on any land cover type and solar zenith angle. Cloud masking has been the traditional way to estimate surface albedo from individual satellite images. Another approach to tackle cloudy conditions is presented in this study. Cloudy broadband albedo distributions were simulated first for theoretical cloud distributions and then using global cloud probability (CP) data of one month. A weighted mean approach based on the CP values was shown to produce very high accuracy black-sky surface albedo estimates for simulated data. The 90 % quantile for the error was 1.1 % (in absolute albedo percentage) and for the relative error it was 2.2 %. AVHRR based and in situ albedo distributions were in line with each other and also the monthly mean values were consistent. Comparison with binary cloud masking indicated that the developed method improves cloud contamination removal.\u0000","PeriodicalId":441110,"journal":{"name":"Atmospheric Measurement Techniques Discussions","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122124947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}