Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a Ceilometer and Microwave Radiometer
Jae-Sik Min, Moon-Soo Park, Jung-Hoon Chae, and Minsoo Kang
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-18,2020
Preprint under review for AMT (discussion: open, 0 comments)
An algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained by a ceilometer and a microwave radiometer in Seoul City, Korea.
The ISABLE algorithm could find an optimal ABLH from post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques.
The ABLH determined by ISABLE exhibited better performances than those obtained by most conventional methods.
High-humidity tandem differential mobility analyzer for accurate determination of aerosol hygroscopic growth, microstructure, and activity coefficients over a wide range of relative humidity
Eugene F. Mikhailov and Sergey S. Vlasenko
Atmos. Meas. Tech., 13, 2035–2056, https://doi.org/10.5194/amt-13-2035-2020, 2020
Here we present the high-humidity tandem differential hygroscopicity analyzer (HHTDMA) and a new method to measure the hygroscopic growth of aerosol particles with in situ restructuring to minimize the influence of particle shape. Our results demonstrate that the HHTDMA system described in this work allows us to determine the thermodynamic characteristics of aqueous solutions with an accuracy close to that obtained by bulk methods.
The influence of the signal-to-noise ratio upon radio occultation inversion quality
Michael Gorbunov
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-114,2020
Preprint under review for AMT (discussion: open, 0 comments)
In this paper, we investigate the influence of the signal-to-noise ratio (SNR) upon the radio occultation (RO) retrieval quality. We perform two series of numerical simulations: (1) with artificial RO data and, (2) with real COSMIC observations. We superimpose the simulated white noise with varying magnitudes upon both types of the observation data and evaluate the response in the statistics. The statistics use the reference fields of the analyses of European Centre for Medium-Range Weather Forecasts (ECMWF). Our simulations indicate that the effect of additive white noise has a threshold character: the influence of the noise is very low up to some threshold, but when the threshold is exceeded, the influence increases dramatically. Another conclusion is that, given RO observations of fair quality, the enhancement of the SNR cannot be expected to provide significant improvement in retrieval quality.
Integrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a Ceilometer and Microwave Radiometer
Jae-Sik Min, Moon-Soo Park, Jung-Hoon Chae, and Minsoo Kang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-18,2020
Preprint under review for AMT (discussion: open, 0 comments)
An algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained by a ceilometer and a microwave radiometer in Seoul City, Korea.
The ISABLE algorithm could find an optimal ABLH from post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques.
The ABLH determined by ISABLE exhibited better performances than those obtained by most conventional methods.
Sources of error in open-path FTIR measurements of N2O and CO2 emitted from agricultural fields
Cheng-Hsien Lin, Richard H. Grant, Albert J. Heber, and Cliff T. Johnston
Atmos. Meas. Tech., 13, 2001–2013, https://doi.org/10.5194/amt-13-2001-2020, 2020
Gas quantification using the open-path Fourier transform infrared spectrometer (OP-FTIR) is subject to interferences of environmental variables, leading to errors in gas concentration calculations. This study investigated the effects of ambient water vapour content, temperature, path lengths, and wind speed on the quantification of N2O and CO2 concentrations, which can help the OP-FTIR users to avoid these errors and improve the precision and accuracy of the atmospheric gas quantification.
Sources of error in open-path FTIR measurements of N2O and CO2 emitted from agricultural fields
Cheng-Hsien Lin, Richard H. Grant, Albert J. Heber, and Cliff T. Johnston
Atmos. Meas. Tech., 13, 2001–2013, https://doi.org/10.5194/amt-13-2001-2020, 2020
Gas quantification using the open-path Fourier transform infrared spectrometer (OP-FTIR) is subject to interferences of environmental variables, leading to errors in gas concentration calculations. This study investigated the effects of ambient water vapour content, temperature, path lengths, and wind speed on the quantification of N2O and CO2 concentrations, which can help the OP-FTIR users to avoid these errors and improve the precision and accuracy of the atmospheric gas quantification.
On the estimation of vertical air velocity and detection of atmospheric turbulence from the ascent rate of balloon soundings
Hubert Luce and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 13, 1989–1999, https://doi.org/10.5194/amt-13-1989-2020, 2020
Vertical ascent rate Vb of meteorological balloons is sometimes used for retrieving vertical air velocity, an important parameter for meteorological applications. Comparisons with concurrent radar and unmanned aerial vehicle (UAV) measurements of atmospheric turbulence showed that Vb can be increased in turbulent layers due to the probable decrease in the drag coefficient of the balloon. We conclude that Vb can also potentially be used for the detection of atmospheric turbulence.
Characterization and first results from LACIS-T: a moist-air wind tunnel to study aerosol–cloud–turbulence interactions
Dennis Niedermeier, Jens Voigtländer, Silvio Schmalfuß, Daniel Busch, Jörg Schumacher, Raymond A. Shaw, and Frank Stratmann
Atmos. Meas. Tech., 13, 2015–2033, https://doi.org/10.5194/amt-13-2015-2020, 2020
In this paper, we present the new moist-air wind tunnel LACIS-T (Turbulent Leipzig Aerosol Cloud Interaction Simulator). It is used to study cloud physical processes in general and interactions between turbulence and cloud microphysical processes in particular. The operating principle of LACIS-T is explained, and the first results are depicted from deliquescence and droplet formation experiments observing clear indications on the effect of turbulence on these microphysical processes.
Evaluation of the reflectivity calibration of W-band radars based on observations in rain
Alexander Myagkov, Stefan Kneifel, and Thomas Rose
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-133,2020
Preprint under review for AMT (discussion: open, 0 comments)
This study shows two methods to evaluate the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first method is based on spectral polarimetric observations and requires a polarimetric cloud radar with a scanner. The second method utilizes disdrometer observations and can be applied to scanning and vertically pointed radars. Both methods show consistent results and can be applied for the operational monitoring of the measurement quality.
On the estimation of vertical air velocity and detection of atmospheric turbulence from the ascent rate of balloon soundings
Hubert Luce and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 13, 1989–1999, https://doi.org/10.5194/amt-13-1989-2020, 2020
Vertical ascent rate Vb of meteorological balloons is sometimes used for retrieving vertical air velocity, an important parameter for meteorological applications. Comparisons with concurrent radar and unmanned aerial vehicle (UAV) measurements of atmospheric turbulence showed that Vb can be increased in turbulent layers due to the probable decrease in the drag coefficient of the balloon. We conclude that Vb can also potentially be used for the detection of atmospheric turbulence.
Characterization and first results from LACIS-T: a moist-air wind tunnel to study aerosol–cloud–turbulence interactions
Dennis Niedermeier, Jens Voigtländer, Silvio Schmalfuß, Daniel Busch, Jörg Schumacher, Raymond A. Shaw, and Frank Stratmann
Atmos. Meas. Tech., 13, 2015–2033, https://doi.org/10.5194/amt-13-2015-2020, 2020
In this paper, we present the new moist-air wind tunnel LACIS-T (Turbulent Leipzig Aerosol Cloud Interaction Simulator). It is used to study cloud physical processes in general and interactions between turbulence and cloud microphysical processes in particular. The operating principle of LACIS-T is explained, and the first results are depicted from deliquescence and droplet formation experiments observing clear indications on the effect of turbulence on these microphysical processes.
Evaluation of the reflectivity calibration of W-band radars based on observations in rain
Alexander Myagkov, Stefan Kneifel, and Thomas Rose
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-133,2020
Preprint under review for AMT (discussion: open, 0 comments)
This study shows two methods to evaluate the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first method is based on spectral polarimetric observations and requires a polarimetric cloud radar with a scanner. The second method utilizes disdrometer observations and can be applied to scanning and vertically pointed radars. Both methods show consistent results and can be applied for the operational monitoring of the measurement quality.
Calibration of global MODIS cloud amount using CALIOP cloud
profiles
Andrzej Z. Kotarba
Atmos. Meas. Tech. Discuss., https//doi.org/10.5194/amt-2020-111,2020
Preprint under review for AMT (discussion: open, 2 comments)
Paper evaluates the operational approach for producing global (Level3 product) cloud amount based on MODIS cloud masks (Level2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 % and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/ local scale. A methods is suggested how to correct/calibrate MODIS global data using CALIPSO detections.
Calibration of global MODIS cloud amount using CALIOP cloud
profiles
Andrzej Z. Kotarba
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-111,2020
Preprint under review for AMT (discussion: open, 2 comments)
Paper evaluates the operational approach for producing global (Level3 product) cloud amount based on MODIS cloud masks (Level2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 % and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/ local scale. A methods is suggested how to correct/calibrate MODIS global data using CALIPSO detections.
Studying boundary layer methane isotopy and vertical mixing processes at a rewetted peatland site using an unmanned aircraft system
Astrid Lampert, Falk Pätzold, Magnus O. Asmussen, Lennart Lobitz, Thomas Krüger, Thomas Rausch, Torsten Sachs, Christian Wille, Denis Sotomayor Zakharov, Dominik Gaus, Stephan Bansmer, and Ellen Damm
Atmos. Meas. Tech., 13, 1937–1952, https://doi.org/10.5194/amt-13-1937-2020, 2020
Methane has high climate warming potential. Sources of methane can be distinguished by the isotopic composition. To investigate the origin of methane, an airborne sampling system has been developed that can take air samples worldwide and at various altitudes. The article shows the performance of the overall system, from taking samples to laboratory analyses. As known methane source, a rewetted peatland site, was studied, and the vertical distribution of the isotopic composition is investigated.
SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Wanyi Xie, Dong Liu, Ming Yang, Shaoqing Chen, Benge Wang, Zhenzhu Wang, Yingwei Xia, Yong Liu, Yiren Wang, and Chaofang Zhang
Atmos. Meas. Tech., 13, 1953–1961, https://doi.org/10.5194/amt-13-1953-2020, 2020
Cloud detection and cloud properties have substantial applications in weather forecast, signal attenuation analysis, and other cloud-related fields. Cloud image segmentation is the fundamental and important step in deriving cloud cover. However, traditional segmentation methods rely on low-level visual features of clouds and often fail to achieve satisfactory performance. Deep convolutional neural networks (CNNs) can extract high-level feature information of objects and have achieved remarkable success in many image segmentation fields. On this basis, a novel deep CNN model named SegCloud is proposed and applied for accurate cloud segmentation based on ground-based observation. Architecturally, SegCloud possesses a symmetric encoder–decoder structure. The encoder network combines low-level cloud features to form high-level, low-resolution cloud feature maps, whereas the decoder network restores the obtained high-level cloud feature maps to the same resolution of input images. The Softmax classifier finally achieves pixel-wise classification and outputs segmentation results. SegCloud has powerful cloud discrimination capability and can automatically segment whole-sky images obtained by a ground-based all-sky-view camera. The performance of SegCloud is validated by extensive experiments, which show that SegCloud is effective and accurate for ground-based cloud segmentation and achieves better results than traditional methods do. The accuracy and practicability of SegCloud are further proven by applying it to cloud cover estimation.
Studying boundary layer methane isotopy and vertical mixing processes at a rewetted peatland site using an unmanned aircraft system
Astrid Lampert, Falk Pätzold, Magnus O. Asmussen, Lennart Lobitz, Thomas Krüger, Thomas Rausch, Torsten Sachs, Christian Wille, Denis Sotomayor Zakharov, Dominik Gaus, Stephan Bansmer, and Ellen Damm
Atmos. Meas. Tech., 13, 1937–1952, https://doi.org/10.5194/amt-13-1937-2020, 2020
Methane has high climate warming potential. Sources of methane can be distinguished by the isotopic composition. To investigate the origin of methane, an airborne sampling system has been developed that can take air samples worldwide and at various altitudes. The article shows the performance of the overall system, from taking samples to laboratory analyses. As known methane source, a rewetted peatland site, was studied, and the vertical distribution of the isotopic composition is investigated.
SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Wanyi Xie, Dong Liu, Ming Yang, Shaoqing Chen, Benge Wang, Zhenzhu Wang, Yingwei Xia, Yong Liu, Yiren Wang, and Chaofang Zhang
Atmos. Meas. Tech., 13, 1953–1961, https://doi.org/10.5194/amt-13-1953-2020, 2020
Cloud detection and cloud properties have substantial applications in weather forecast, signal attenuation analysis, and other cloud-related fields. Cloud image segmentation is the fundamental and important step in deriving cloud cover. However, traditional segmentation methods rely on low-level visual features of clouds and often fail to achieve satisfactory performance. Deep convolutional neural networks (CNNs) can extract high-level feature information of objects and have achieved remarkable success in many image segmentation fields. On this basis, a novel deep CNN model named SegCloud is proposed and applied for accurate cloud segmentation based on ground-based observation. Architecturally, SegCloud possesses a symmetric encoder–decoder structure. The encoder network combines low-level cloud features to form high-level, low-resolution cloud feature maps, whereas the decoder network restores the obtained high-level cloud feature maps to the same resolution of input images. The Softmax classifier finally achieves pixel-wise classification and outputs segmentation results. SegCloud has powerful cloud discrimination capability and can automatically segment whole-sky images obtained by a ground-based all-sky-view camera. The performance of SegCloud is validated by extensive experiments, which show that SegCloud is effective and accurate for ground-based cloud segmentation and achieves better results than traditional methods do. The accuracy and practicability of SegCloud are further proven by applying it to cloud cover estimation.
Flow-induced errors in airborne in situ measurements of aerosols and clouds
Antonio Spanu, Maximilian Dollner, Josef Gasteiger, T. Paul Bui, and Bernadett Weinzierl
Atmos. Meas. Tech., 13, 1963–1987, https://doi.org/10.5194/amt-13-1963-2020, 2020
This study investigates how the airflow around wing-mounted instruments on fast-flying aircraft affects aerosol and cloud measurements. It combines airborne data with numerical simulations and shows that particle speed, particle concentration, and shape of water droplets are modified by the airflow. The proposed correction strategy for optical particle counters and optical array probes considers airflow effects and significantly reduces errors of derived ambient aerosol and cloud properties.
Flow-induced errors in airborne in situ measurements of aerosols and clouds
Antonio Spanu, Maximilian Dollner, Josef Gasteiger, T. Paul Bui, and Bernadett Weinzierl
Atmos. Meas. Tech., 13, 1963–1987, https://doi.org/10.5194/amt-13-1963-2020, 2020
This study investigates how the airflow around wing-mounted instruments on fast-flying aircraft affects aerosol and cloud measurements. It combines airborne data with numerical simulations and shows that particle speed, particle concentration, and shape of water droplets are modified by the airflow. The proposed correction strategy for optical particle counters and optical array probes considers airflow effects and significantly reduces errors of derived ambient aerosol and cloud properties.
