Search Results
Results and recommendations from an intercomparison of six Hygroscopicity-TDMA systems
2011, Massling, A., Niedermeier, N., Hennig, T., Fors, E.O., Swietlicki, E., Ehn, M., Hämeri, K., Villani, P., Laj, P., Good, N., McFiggans, G., Wiedensohler, A.
The performance of six custom-built Hygrocopicity-Tandem Differential Mobility Analyser (H-TDMA) systems was investigated in the frame of an international calibration and intercomparison workshop held in Leipzig, February 2006. The goal of the workshop was to harmonise H-TDMA measurements and develop recommendations for atmospheric measurements and their data evaluation. The H-TDMA systems were compared in terms of the sizing of dry particles, relative humidity (RH) uncertainty, and consistency in determination of number fractions of different hygroscopic particle groups. The experiments were performed in an air-conditioned laboratory using ammonium sulphate particles or an external mixture of ammonium sulphate and soot particles. The sizing of dry particles of the six H-TDMA systems was within 0.2 to 4.2% of the selected particle diameter depending on investigated size and individual system. Measurements of ammonium sulphate aerosol found deviations equivalent to 4.5% RH from the set point of 90% RH compared to results from previous experiments in the literature. Evaluation of the number fraction of particles within the clearly separated growth factor modes of a laboratory generated externally mixed aerosol was done. The data from the H-TDMAs was analysed with a single fitting routine to investigate differences caused by the different data evaluation procedures used for each H-TDMA. The differences between the H-TDMAs were reduced from +12/−13% to +8/−6% when the same analysis routine was applied. We conclude that a common data evaluation procedure to determine number fractions of externally mixed aerosols will improve the comparability of H-TDMA measurements. It is recommended to ensure proper calibration of all flow, temperature and RH sensors in the systems. It is most important to thermally insulate the aerosol humidification unit and the second DMA and to monitor these temperatures to an accuracy of 0.2 °C. For the correct determination of external mixtures, it is necessary to take into account size-dependent losses due to diffusion in the plumbing between the DMAs and in the aerosol humidification unit.
Evaluation of wake influence on high-resolution balloon-sonde measurements
2019, Söder, J., Gerding, M., Schneider, A., Dörnbrack, A., Wilms, H., Wagner, J., Lübken, F.-J.
Balloons are used for various in situ measurements in the atmosphere. On turbulence measurements from rising balloons there is a potential for misinterpreting wake-created fluctuations in the trail of the balloon for atmospheric turbulence. These wake effects have an influence on temperature and humidity measurements from radiosondes as well. The primary aim of this study is to assess the likelihood for wake encounter on the payload below a rising balloon. Therefore, we present a tool for calculating this probability based on radiosonde wind data. This includes a retrieval of vertical winds from the radiosonde and an uncertainty analysis of the wake assessment. Our wake evaluation tool may be used for any balloon-gondola distance and provides a significant refinement compared to existing assessments. We have analysed wake effects for various balloon-gondola distances applying atmospheric background conditions from a set of 30 radiosondes. For a standard radiosonde we find an average probability for wake encounter of 28 %, pointing out the importance of estimating wake effects on sounding balloons. Furthermore, we find that even millimetre-sized objects in the payload can have significant effects on high-resolution turbulence measurements, if they are located upstream of the turbulence sensor. © Author(s) 2019. This work is distributed under.
Experimental techniques for the calibration of lidar depolarization channels in EARLINET
2018, Belegante, Livio, Bravo-Aranda, Juan Antonio, Freudenthaler, Volker, Nicolae, Doina, Nemuc, Anca, Ene, Dragos, Alados-Arboledas, Lucas, Amodeo, Aldo, Pappalardo, Gelsomina, D'Amico, Giuseppe, Amato, Francesco, Engelmann, Ronny, Baars, Holger, Wandinger, Ulla, Papayannis, Alexandros, Kokkalis, Panos, Pereira, Sérgio N.
Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol-typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components but only if the measurements are accurate enough. The accuracy related to the retrieval of particle depolarization ratios is the driving factor for assessing and improving the uncertainties of the depolarization products. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that have implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532-nm show values that fall within a range that is generally accepted in the literature.
Shortwave surface radiation network for observing small-scale cloud inhomogeneity fields
2016, Madhavan, Bomidi Lakshmi, Kalisch, John, Macke, Andreas
As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of 99 silicon photodiode pyranometers was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. In this paper, we provide the details of this unique setup of the pyranometer network, data processing, quality control, and uncertainty assessment under variable conditions. Some exemplary days with clear, broken cloudy, and overcast skies were explored to assess the spatiotemporal observations from the network along with other collocated radiation and sky imager measurements available during the HOPE period.
Mobility particle size spectrometers: Harmonization of technical standards and data structure to facilitate high quality long-term observations of atmospheric particle number size distributions
2012, Wiedensohler, A., Birmili, W., Nowak, A., Sonntag, A., Weinhold, K., Merkel, M., Wehner, B., Tuch, T., Pfeifer, S., Fiebig, M., Fjäraa, A.M., Asmi, E., Sellegri, K., Depuy, R., Venzac, H., Villani, P., Laj, P., Aalto, P., Ogren, J.A., Swietlick, E., Williams, P., Roldin, P., Quincey, P., Hüglin, C., Fierz-Schmidhauser, R., Gysel, M., Weingartner, E., Riccobono, F., Santos, S., Grüning, C., Faloon, K., Beddows, D., Harrison, R., Monahan, C., Jennings, S.G., O'Dowd, C.D., Marinoni, A., Horn, H.-G., Keck, L., Jiang, J., Scheckman, J., McMurry, P.H., Deng, Z., Zhao, C.S., Moerman, M., Henzing, B., de Leeuw, G., Löschau, G., Bastian, S.
Mobility particle size spectrometers often referred to as DMPS (Differential Mobility Particle Sizers) or SMPS (Scanning Mobility Particle Sizers) have found a wide range of applications in atmospheric aerosol research. However, comparability of measurements conducted world-wide is hampered by lack of generally accepted technical standards and guidelines with respect to the instrumental set-up, measurement mode, data evaluation as well as quality control. Technical standards were developed for a minimum requirement of mobility size spectrometry to perform long-term atmospheric aerosol measurements. Technical recommendations include continuous monitoring of flow rates, temperature, pressure, and relative humidity for the sheath and sample air in the differential mobility analyzer. We compared commercial and custom-made inversion routines to calculate the particle number size distributions from the measured electrical mobility distribution. All inversion routines are comparable within few per cent uncertainty for a given set of raw data. Furthermore, this work summarizes the results from several instrument intercomparison workshops conducted within the European infrastructure project EUSAAR (European Supersites for Atmospheric Aerosol Research) and ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) to determine present uncertainties especially of custom-built mobility particle size spectrometers. Under controlled laboratory conditions, the particle number size distributions from 20 to 200 nm determined by mobility particle size spectrometers of different design are within an uncertainty range of around ±10% after correcting internal particle losses, while below and above this size range the discrepancies increased. For particles larger than 200 nm, the uncertainty range increased to 30%, which could not be explained. The network reference mobility spectrometers with identical design agreed within ±4% in the peak particle number concentration when all settings were done carefully. The consistency of these reference instruments to the total particle number concentration was demonstrated to be less than 5%. Additionally, a new data structure for particle number size distributions was introduced to store and disseminate the data at EMEP (European Monitoring and Evaluation Program). This structure contains three levels: raw data, processed data, and final particle size distributions. Importantly, we recommend reporting raw measurements including all relevant instrument parameters as well as a complete documentation on all data transformation and correction steps. These technical and data structure standards aim to enhance the quality of long-term size distribution measurements, their comparability between different networks and sites, and their transparency and traceability back to raw data.
The effect of rapid relative humidity changes on fast filter-based aerosol-particle light-absorption measurements: Uncertainties and correction schemes
2019, Düsing, Sebastian, Wehner, Birgit, Müller, Thomas, Stöcker, Almond, Wiedensohler, Alfred
Measuring vertical profiles of the particle light-absorption coefficient by using absorption photometers may face the challenge of fast changes in relative humidity (RH). These absorption photometers determine the particle light-absorption coefficient due to a change in light attenuation through a particle-loaded filter. The filter material, however, takes up or releases water with changing relative humidity (RH in %), thus influencing the light attenuation. A sophisticated set of laboratory experiments was therefore conducted to investigate the effect of fast RH changes (dRH/dt) on the particle light-absorption coefficient (σabs in Mm-1) derived with two absorption photometers. The RH dependence was examined based on different filter types and filter loadings with respect to loading material and areal loading density. The Single Channel Tricolor Absorption Photometer (STAP) relies on quartz-fiber filter, and the microAeth® MA200 is based on a polytetrafluoroethylene (PTFE) filter band. Furthermore, three cases were investigated: clean filters, filters loaded with black carbon (BC), and filters loaded with ammonium sulfate. The filter areal loading densities (ρ∗) ranged from 3.1 to 99.6 mg m-2 in the case of the STAP and ammonium sulfate and 1.2 to 37.6 mg m-2 in the case the MA200. Investigating BC-loaded cases, M8 scroll mrow miBCm 15pt was in the range of 2.9 to 43.0 and 1.1 to 16.3 mg m-2 for the STAP and MA200, respectively. Both instruments revealed opposing responses to relative humidity changes ("RH) with different magnitudes. The STAP shows a linear dependence on relative humidity changes. The MA200 is characterized by a distinct exponential recovery after its filter was exposed to relative humidity changes. At a wavelength of 624 nm and for the default 60 s running average output, the STAP reveals an absolute change in σabs per absolute change of RH ("σabsĝ•"RH) of 0.14 Mm-1 %-1 in the clean case, 0.29 Mm-1 %-1 in the case of BC-loaded filters, and 0.21 Mm-1 %-1 in the case filters loaded with ammonium sulfate. The 60 s running average of the particle light-absorption coefficient at 625 nm measured with the MA200 revealed a response of around -0.4 Mm-1 %-1 for all three cases. Whereas the response of the STAP varies over the different loading materials, in contrast, the MA200 was quite stable. The response was, for the STAP, in the range of 0.17 to 0.24 Mm-1 %-1 and, in the case of ammonium sulfate loading and in the BC-loaded case, 0.17 to 0.62 Mm-1 %-1. In the ammonium sulfate case, the minimum response shown by the MA200 was -0.42 with a maximum of -0.36 Mm-1 %-1 and a minimum of -0.42 and maximum -0.37 Mm-1 %-1 in the case of BC. A linear correction function for the STAP was developed here. It is provided by correlating 1 Hz resolved recalculated particle light-absorption coefficients and RH change rates. The linear response is estimated at 10.08 Mm-1 s-1 %-1. A correction approach for the MA200 is also provided; however, the behavior of the MA200 is more complex. Further research and multi-instrument measurements have to be conducted to fully understand the underlying processes, since the correction approach resulted in different correction parameters across various experiments. However, the exponential recovery after the filter of the MA200 experienced a RH change could be reproduced. However, the given correction approach has to be estimated with other RH sensors as well, since each sensor has a different response time. And, for the given correction approaches, the uncertainties could not be estimated, which was mainly due to the response time of the RH sensor. Therefore, we do not recommend using the given approaches. But they point in the right direction, and despite the imperfections, they are useful for at least estimating the measurement uncertainties due to relative humidity changes. Due to our findings, we recommend using an aerosol dryer upstream of absorption photometers to reduce the RH effect significantly. Furthermore, when absorption photometers are used in vertical measurements, the ascending or descending speed through layers of large relative humidity gradients has to be low to minimize the observed RH effect. But this is simply not possible in some scenarios, especially in unmixed layers or clouds. Additionally, recording the RH of the sample stream allows correcting for the bias during post-processing of the data. This data correction leads to reasonable results, according to the given example in this study. © Author(s) 2019.
Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
2018, Dai, Guangyao, Althausen, Dietrich, Hofer, Julian, Engelmann, Ronny, Seifert, Patric, Bühl, Johannes, Mamouri, Rodanthi-Elisavet, Wu, Songhua, Ansmann, Albert
We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.
Do new sea spray aerosol source functions improve the results of a regional aerosol model?
2018, Barthel, Stefan, Tegen, Ina, Wolke, Ralf
Sea spray aerosol particle is a dominating part of the global aerosol mass load of natural origin. Thus, it strongly influences the atmospheric radiation balance and cloud properties especially over the oceans. Uncertainties of the estimated climate impacts by this aerosol type are partly caused by the uncertainties in the particle size dependent emission fluxes of sea spray aerosol particle. We present simulations with a regional aerosol transport model system in two domains, for three months and compared the model results to measurements at four stations using various sea spray aerosol particle source source functions. Despite these limitations we found the results using different source functions are within the range of most model uncertainties. Especially the model's ability to produce realistic wind speeds is crucial. Furthermore, the model results are more affected by a function correcting the emission flux for the effect of the sea surface temperature than by the use of different source functions. © 2018 The Authors