Articles | Volume 8, issue 8
Atmos. Meas. Tech., 8, 3163–3175, 2015
https://doi.org/10.5194/amt-8-3163-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 8, 3163–3175, 2015
https://doi.org/10.5194/amt-8-3163-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 10 Aug 2015
Research article | 10 Aug 2015
Accounting for the effects of sastrugi in the CERES clear-sky Antarctic shortwave angular distribution models
J. Corbett and W. Su
Related authors
W. Su, J. Corbett, Z. Eitzen, and L. Liang
Atmos. Meas. Tech., 8, 3297–3313, https://doi.org/10.5194/amt-8-3297-2015, https://doi.org/10.5194/amt-8-3297-2015, 2015
W. Su, J. Corbett, Z. Eitzen, and L. Liang
Atmos. Meas. Tech., 8, 611–632, https://doi.org/10.5194/amt-8-611-2015, https://doi.org/10.5194/amt-8-611-2015, 2015
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The top-of-atmosphere (TOA) radiative fluxes are critical components to advancing our understanding of the Earth's radiative energy balance. The Clouds and Earth's Radiant Energy System (CERES) instruments provide broadband shortwave and longwave radiance measurements. These radiances are converted to fluxes by using scene-type-dependent angular distribution models (ADMs). This paper describes the next-generation CERES ADMs that are developed for TOA radiative flux inversion.
Wenying Su, Patrick Minnis, Lusheng Liang, David P. Duda, Konstantin Khlopenkov, Mandana M. Thieman, Yinan Yu, Allan Smith, Steven Lorentz, Daniel Feldman, and Francisco P. J. Valero
Atmos. Meas. Tech., 13, 429–443, https://doi.org/10.5194/amt-13-429-2020, https://doi.org/10.5194/amt-13-429-2020, 2020
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The Deep Space Climate Observatory (DSCOVR) provides continuous full-disk global broadband irradiance measurements over most of the sunlit side of the Earth. The three active cavity radiometers measure the total radiant energy from the sunlit side of the Earth in shortwave (SW; 0.2–4 µm), total (0.4–100 µm), and near-infrared (NIR; 0.7–4 µm) channels. In this paper, the algorithm used to derive daytime shortwave and longwave fluxes from NISTAR measurements is presented.
Yuekui Yang, Kerry Meyer, Galina Wind, Yaping Zhou, Alexander Marshak, Steven Platnick, Qilong Min, Anthony B. Davis, Joanna Joiner, Alexander Vasilkov, David Duda, and Wenying Su
Atmos. Meas. Tech., 12, 2019–2031, https://doi.org/10.5194/amt-12-2019-2019, https://doi.org/10.5194/amt-12-2019-2019, 2019
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The physical basis of the EPIC cloud product algorithms and an initial evaluation of their performance are presented. EPIC cloud products include cloud mask, effective height, and optical depth. Comparison with co-located retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the NASA Langley Atmospheric Sciences Data Center.
Wenying Su, Lusheng Liang, Walter F. Miller, and Victor E. Sothcott
Atmos. Meas. Tech., 10, 4001–4011, https://doi.org/10.5194/amt-10-4001-2017, https://doi.org/10.5194/amt-10-4001-2017, 2017
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The footprint size of NPP CERES is larger than that of Aqua CERES, because the altitude of the NPP orbit is higher than that of the Aqua orbit. Additionally, the cloud retrievals from VIIRS and MODIS, the imagers that fly alongside NPP CERES and Aqua CERES, are also different. This paper outlined a simulation study using the MODIS pixel-level data to address the impact of these differences on the NPP CERES fluxes inverted using the Aqua CERES angular distribution models.
W. Su, J. Corbett, Z. Eitzen, and L. Liang
Atmos. Meas. Tech., 8, 3297–3313, https://doi.org/10.5194/amt-8-3297-2015, https://doi.org/10.5194/amt-8-3297-2015, 2015
W. Su, J. Corbett, Z. Eitzen, and L. Liang
Atmos. Meas. Tech., 8, 611–632, https://doi.org/10.5194/amt-8-611-2015, https://doi.org/10.5194/amt-8-611-2015, 2015
Short summary
Short summary
The top-of-atmosphere (TOA) radiative fluxes are critical components to advancing our understanding of the Earth's radiative energy balance. The Clouds and Earth's Radiant Energy System (CERES) instruments provide broadband shortwave and longwave radiance measurements. These radiances are converted to fluxes by using scene-type-dependent angular distribution models (ADMs). This paper describes the next-generation CERES ADMs that are developed for TOA radiative flux inversion.
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Integrated water vapor and liquid water path retrieval using a single-channel radiometer
Improving atmospheric path attenuation estimates for radio propagation applications by microwave radiometric profiling
A new global grid-based weighted mean temperature model considering vertical nonlinear variation
Monitoring sudden stratospheric warmings using radio occultation: a new approach demonstrated based on the 2009 event
LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 1: Theoretical framework
LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 2: Applications to lidar measurements of wind turbine wakes
Estimation of the height of the turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam
Spectral correction of turbulent energy damping on wind lidar measurements due to spatial averaging
Improvement in tropospheric moisture retrievals from VIIRS through the use of infrared absorption bands constructed from VIIRS and CrIS data fusion
Hydrometeor classification of quasi-vertical profiles of polarimetric radar measurements using a top-down iterative hierarchical clustering method
Assimilation of lidar planetary boundary layer height observations
Detection of anomalies in the UV–vis reflectances from the Ozone Monitoring Instrument
What millimeter-wavelength radar reflectivity reveals about snowfall: an information-centric analysis
Generalized canonical transform method for radio occultation sounding with improved retrieval in the presence of horizontal gradients
Linking rain into ice microphysics across the melting layer in stratiform rain: a closure study
Classification of lidar measurements using supervised and unsupervised machine learning methods
Consistency of total column ozone measurements between the Brewer and Dobson spectroradiometers of the LKO Arosa and PMOD/WRC Davos
The development of rainfall retrievals from radar at Darwin
Assimilation of DAWN Doppler Wind Lidar Data During the 2017 Convective Processes Experiment (CPEX): Impact on the Precipitation and Flow Structure
Retrieved wind speed from the Orbiting Carbon Observatory-2
Probabilistic analysis of ambiguities in radar echo direction of arrival from meteors
Detecting the melting layer with a micro rain radar using a neural network approach
Statistical analyzing the effect of ionospheric irregularity on GNSS radio occultation atmospheric measurement
Detecting turbulent structures on single Doppler lidar large datasets: an automated classification method for horizontal scans
Real-time estimation of airflow vector based on lidar observations for preview control
Filtering of pulsed lidar data using spatial information and a clustering algorithm
Variability of the Brunt–Väisälä frequency at the OH∗-airglow layer height at low and midlatitudes
Eddies in motion: visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videos
Insights into wind turbine reflectivity and RCS and their variability using X-band weather radar observations
Intra-annual variations of spectrally resolved gravity wave activity in the upper mesosphere/lower thermosphere (UMLT) region
Detection of the freezing level with polarimetric weather radar
RainForest: A random forest algorithm for quantitative precipitation estimation over Swizerland
Ground-based Temperature and Humidity Profiling: Combining Active and Passive Remote Sensors
Removing spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methods
Resolving ambiguous direction of arrival of weak meteor radar trail echoes
Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation
Towards improved turbulence estimation with Doppler wind lidar velocity-azimuth display (VAD) scans
Comparison of Single Doppler and Multiple Doppler Wind Retrievals in Hurricane Matthew (2016)
Optimised degradation correction for SCIAMACHY satellite solar measurements from 330 to 1600 nm by using the internal white light source
Rain event detection in commercial microwave link attenuation data using convolutional neural networks
Preliminary investigation of the relationship between differential phase shift and path-integrated attenuation at the X band frequency in an Alpine environment
Observation of sensible and latent heat flux profiles with lidar
Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar
Update of Infrared Atmospheric Sounding Interferometer (IASI) channel selection with correlated observation errors for numerical weather prediction (NWP)
Learning about the vertical structure of radar reflectivity using hydrometeor classes and neural networks in the Swiss Alps
Toward a variational assimilation of polarimetric radar observations in a convective-scale numerical weather prediction (NWP) model
Estimating raindrop size distributions using microwave link measurements: potential and limitations
An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions
Analysis of flow in complex terrain using multi-Doppler lidar retrievals
Unsupervised classification of vertical profiles of dual polarization radar variables
Anne-Claire Billault-Roux and Alexis Berne
Atmos. Meas. Tech., 14, 2749–2769, https://doi.org/10.5194/amt-14-2749-2021, https://doi.org/10.5194/amt-14-2749-2021, 2021
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In the context of climate studies, understanding the role of clouds on a global and local scale is of paramount importance. One aspect is the quantification of cloud liquid water, which impacts the Earth’s radiative balance. This is routinely achieved with radiometers operating at different frequencies. In this study, we propose an approach that uses a single-frequency radiometer and that can be applied at any location to retrieve vertically integrated quantities of liquid water and water vapor.
Ayham Alyosef, Domenico Cimini, Lorenzo Luini, Carlo Riva, Frank S. Marzano, Marianna Biscarini, Luca Milani, Antonio Martellucci, Sabrina Gentile, Saverio T. Nilo, Francesco Di Paola, Ayman Alkhateeb, and Filomena Romano
Atmos. Meas. Tech., 14, 2737–2748, https://doi.org/10.5194/amt-14-2737-2021, https://doi.org/10.5194/amt-14-2737-2021, 2021
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Telecommunication is based on the propagation of radio signals through the atmosphere. The signal power diminishes along the path due to atmospheric attenuation, which needs to be estimated to be accounted for. In a study funded by the European Space Agency, we demonstrate an innovative method improving atmospheric attenuation estimates from ground-based radiometric measurements by 10–30 %. More accurate atmospheric attenuation estimates imply better telecommunication services in the future.
Peng Sun, Suqin Wu, Kefei Zhang, Moufeng Wan, and Ren Wang
Atmos. Meas. Tech., 14, 2529–2542, https://doi.org/10.5194/amt-14-2529-2021, https://doi.org/10.5194/amt-14-2529-2021, 2021
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In GPS or Global navigation satellite systems (GNSS) meteorology, precipitable water vapor (PWV) at a station is obtained from a conversion of the GNSS signal zenith wet delay (ZWD) using a conversion factor which is a function of weighted mean temperature (Tm) over the site. We developed a new global grid-based empirical Tm model using ERA5 reanalysis data. The model-predicted Tm value has significance for applications needing real-time or near real-time PWV converted from GNSS signals.
Ying Li, Gottfried Kirchengast, Marc Schwärz, Florian Ladstädter, and Yunbin Yuan
Atmos. Meas. Tech., 14, 2327–2343, https://doi.org/10.5194/amt-14-2327-2021, https://doi.org/10.5194/amt-14-2327-2021, 2021
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We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known Jan.–Feb. 2009 event. We found that RO data are capable of SSW monitoring. Based on our method, a SSW event can be detected and tracked, and the duration and the strength of the event can be recorded. The results are consistent with other research on the 2009 event.
Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 2065–2093, https://doi.org/10.5194/amt-14-2065-2021, https://doi.org/10.5194/amt-14-2065-2021, 2021
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A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of lidar scans and retrieval of velocity statistics is proposed. The LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. The optimal design of lidar scans is formulated as a two-cost-function optimization problem, including the minimization of the volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field.
Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 2095–2113, https://doi.org/10.5194/amt-14-2095-2021, https://doi.org/10.5194/amt-14-2095-2021, 2021
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The LiDAR Statistical Barnes Objective Analysis (LiSBOA) is applied to lidar data collected in the wake of wind turbines to reconstruct mean wind speed and turbulence intensity. Various lidar scans performed during a field campaign for a wind farm in complex terrain are analyzed. The results endorse the application of the LiSBOA for lidar-based wind resource assessment and farm diagnosis.
Viktor A. Banakh, Igor N. Smalikho, and Andrey V. Falits
Atmos. Meas. Tech., 14, 1511–1524, https://doi.org/10.5194/amt-14-1511-2021, https://doi.org/10.5194/amt-14-1511-2021, 2021
Matteo Puccioni and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 1457–1474, https://doi.org/10.5194/amt-14-1457-2021, https://doi.org/10.5194/amt-14-1457-2021, 2021
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A procedure for correcting the turbulent-energy damping connected with spatial averaging of wind lidars is proposed. This effect of the lidar measuring process is modeled through a low-pass filter, whose order and cut-off frequency are estimated directly from the lidar data. The proposed procedure is first assessed through simultaneous and colocated lidar and sonic-anemometer measurements. Then it is applied to several datasets collected at sites with different terrain roughness.
E. Eva Borbas, Elisabeth Weisz, Chris Moeller, W. Paul Menzel, and Bryan A. Baum
Atmos. Meas. Tech., 14, 1191–1203, https://doi.org/10.5194/amt-14-1191-2021, https://doi.org/10.5194/amt-14-1191-2021, 2021
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As the VIIRS satellite sensor has no infrared (IR) H2O absorption bands, we construct the missing bands through the fusion of imager (VIIRS) and sounder (CrIS) data in an attempt to improve derivation of moisture products. This study clearly demonstrates the positive impact by adding fusion IR absorption spectral bands and the potential for continuing the moisture record from MODIS and the previous generations of polar-orbiting satellite sensors.
Maryna Lukach, David Dufton, Jonathan Crosier, Joshua M. Hampton, Lindsay Bennett, and Ryan R. Neely III
Atmos. Meas. Tech., 14, 1075–1098, https://doi.org/10.5194/amt-14-1075-2021, https://doi.org/10.5194/amt-14-1075-2021, 2021
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This paper presents a novel technique of data-driven hydrometeor classification (HC) from quasi-vertical profiles, where the hydrometeor types are identified from an optimal number of hierarchical clusters, obtained recursively. This data-driven HC approach is capable of providing an optimal number of classes from dual-polarimetric weather radar observations. The embedded flexibility in the extent of granularity is the main advantage of this technique.
Andrew Tangborn, Belay Demoz, Brian J. Carroll, Joseph Santanello, and Jeffrey L. Anderson
Atmos. Meas. Tech., 14, 1099–1110, https://doi.org/10.5194/amt-14-1099-2021, https://doi.org/10.5194/amt-14-1099-2021, 2021
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Accurate prediction of the planetary boundary layer is essential to both numerical weather prediction (NWP) and pollution forecasting. This paper presents a methodology to combine these measurements with the models through a statistical data assimilation approach that calculates the correlation between the PBLH and variables like temperature and moisture in the model. The model estimates of these variables can be improved via this method, and this will enable increased forecast accuracy.
Nick Gorkavyi, Zachary Fasnacht, David Haffner, Sergey Marchenko, Joanna Joiner, and Alexander Vasilkov
Atmos. Meas. Tech., 14, 961–974, https://doi.org/10.5194/amt-14-961-2021, https://doi.org/10.5194/amt-14-961-2021, 2021
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Various instrumental or geophysical artifacts, such as saturation, stray light or obstruction of light, negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm spectral range; our decorrelation index (DI for brevity) is simply defined as DI of 1–r.
Norman B. Wood and Tristan S. L'Ecuyer
Atmos. Meas. Tech., 14, 869–888, https://doi.org/10.5194/amt-14-869-2021, https://doi.org/10.5194/amt-14-869-2021, 2021
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Although millimeter-wavelength radar reflectivity observations are used to investigate snowfall properties, their ability to constrain specific properties has not been well-quantified. An information-focused retrieval
method shows how well snowfall properties, including rate and size distribution, are constrained by reflectivity. Sources of uncertainty in snowfall rate are dominated by uncertainties in the retrieved size distribution properties rather than by other retrieval assumptions.
Michael Gorbunov, Gottfried Kirchengast, and Kent B. Lauritsen
Atmos. Meas. Tech., 14, 853–867, https://doi.org/10.5194/amt-14-853-2021, https://doi.org/10.5194/amt-14-853-2021, 2021
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Currently, the canonical transform (CT) approach to the processing of radio occultation observations is widely used. For the spherically symmetric atmosphere, the applicability of this method can be strictly proven. However, in the presence of horizontal gradients, this approach may not work. Here we introduce a generalization of the CT method in order to reduce the errors due to horizontal gradients.
Kamil Mróz, Alessandro Battaglia, Stefan Kneifel, Leonie von Terzi, Markus Karrer, and Davide Ori
Atmos. Meas. Tech., 14, 511–529, https://doi.org/10.5194/amt-14-511-2021, https://doi.org/10.5194/amt-14-511-2021, 2021
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The article examines the relationship between the characteristics of rain and the properties of the ice cloud from which the rain originated. Our results confirm the widely accepted assumption that the mass flux through the melting zone is well preserved with an exception of extreme aggregation and riming conditions. Moreover, it is shown that the mean (mass-weighted) size of particles above and below the melting zone is strongly linked, with the former being on average larger.
Ghazal Farhani, Robert J. Sica, and Mark Joseph Daley
Atmos. Meas. Tech., 14, 391–402, https://doi.org/10.5194/amt-14-391-2021, https://doi.org/10.5194/amt-14-391-2021, 2021
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While it is relatively straightforward to automate the processing of lidar signals, it is difficult to automatically preprocess the measurements to distinguish between
goodand
badscans. It is easy to train humans to perform the task; however, considering the growing number of measurements, it is a time-consuming, on-going process. We have tested some machine learning algorithms for lidar signal classification and had success with both supervised and unsupervised methods.
Julian Gröbner, Herbert Schill, Luca Egli, and René Stübi
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-497, https://doi.org/10.5194/amt-2020-497, 2021
Revised manuscript accepted for AMT
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The world's longest continuous total column ozone time series was initiated in 1926 at the Lichtklimatisches Observatorium (LKO), at Arosa, in the Swiss Alps. The measurements between Dobson and Brewer spectroradiometers have shown seasonal variations of the order of 2 %. The results of the study show that the consistency between the two instrument types can be significantly improved when the ozone cross-sections from Serdyuchenko et al. (2013) and the measured slit functions are used.
Robert Jackson, Scott Collis, Valentin Louf, Alain Protat, Die Wang, Scott Giangrande, Elizabeth J. Thompson, Brenda Dolan, and Scott W. Powell
Atmos. Meas. Tech., 14, 53–69, https://doi.org/10.5194/amt-14-53-2021, https://doi.org/10.5194/amt-14-53-2021, 2021
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About 4 years of 2D video disdrometer data in Darwin are used to develop and validate rainfall retrievals for tropical convection in C- and X-band radars in Darwin. Using blended techniques previously used for Colorado and Manus and Gan islands, with modified coefficients in each estimator, provided the most optimal results. Using multiple radar observables to develop a rainfall retrieval provided a greater advantage than using a single observable, including using specific attenuation.
Svetla Hristova-Veleva, Sara Q. Zhang, F. Joseph Turk, Ziad S. Haddad, and Randy C. Sawaya
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-503, https://doi.org/10.5194/amt-2020-503, 2020
Revised manuscript accepted for AMT
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The assimilation of airborne-based 3-dimensional winds into a mesoscale weather forecast model resulted in better agreement with airborne radar-derived precipitation 3-D structure at later model time steps. More importantly, there was also a discernible impact to the resultant wind and moisture structure, in accord with independent analysis of the wind structure and external satellite observations.
Robert R. Nelson, Annmarie Eldering, David Crisp, Aronne J. Merrelli, and Christopher W. O'Dell
Atmos. Meas. Tech., 13, 6889–6899, https://doi.org/10.5194/amt-13-6889-2020, https://doi.org/10.5194/amt-13-6889-2020, 2020
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Measurements of surface wind speed over oceans are scientifically useful. Here we show that the Orbiting Carbon Observatory-2 (OCO-2), originally designed to measure carbon dioxide using reflected sunlight, can also accurately and precisely measure wind speed. OCO-2's high spatial resolution means that it can observe close to coastlines and therefore be used to study coastal wind processes and inform related economic sectors.
Daniel Kastinen and Johan Kero
Atmos. Meas. Tech., 13, 6813–6835, https://doi.org/10.5194/amt-13-6813-2020, https://doi.org/10.5194/amt-13-6813-2020, 2020
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The behaviour of position determination with interferometric radar systems and possible ambiguities therein depends on the spatial configuration of the radar-receiving antennas and their individual characteristics. We have simulated the position determination performance of five different radar systems. These simulations showed that ambiguities are dynamic and need to be examined on a case-by-case basis. However, the simulations can be used to analyse and understand previously ambiguous data.
Maren Brast and Piet Markmann
Atmos. Meas. Tech., 13, 6645–6656, https://doi.org/10.5194/amt-13-6645-2020, https://doi.org/10.5194/amt-13-6645-2020, 2020
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An artificial neural network was trained to identify melting layers in micro rain radar data. It was successfully tested on simple and complex cases, which are difficult to identify using classical approaches, and also provided information on the melting layer width.
Mingzhe Li and Xinan Yue
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-440, https://doi.org/10.5194/amt-2020-440, 2020
Revised manuscript accepted for AMT
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In this study, we have analyzed the correlation between the ionospheric irregularity and the quality of the GNSS atmospheric radio occultation (RO) products statistically. Results show that the ionospheric irregularity could affect the GNSS atmospheric RO in terms of causing failed inverted RO events and the bending angle oscillation. Awareness of the ionospheric irregularity effect on RO could be beneficial to improve the RO data quality for weather and climate research.
Ioannis Cheliotis, Elsa Dieudonné, Hervé Delbarre, Anton Sokolov, Egor Dmitriev, Patrick Augustin, and Marc Fourmentin
Atmos. Meas. Tech., 13, 6579–6592, https://doi.org/10.5194/amt-13-6579-2020, https://doi.org/10.5194/amt-13-6579-2020, 2020
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The current study presents an automated method to classify coherent structures near the surface, based on the observations recorded by a single scanning Doppler lidar. This methodology combines texture analysis with a supervised machine-learning algorithm in order to study large datasets. The algorithm classified correctly about 91 % of cases of a training ensemble (150 scans). Furthermore the results of a 2-month classified dataset (4577 scans) by the algorithm are presented.
Ryota Kikuchi, Takashi Misaka, Shigeru Obayashi, and Hamaki Inokuchi
Atmos. Meas. Tech., 13, 6543–6558, https://doi.org/10.5194/amt-13-6543-2020, https://doi.org/10.5194/amt-13-6543-2020, 2020
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The control technique in a gust-alleviation system using the airborne Doppler lidar is expected to minimize the risks of turbulence-related accidents. Accurate estimation of the vertical wind is important in the successful implementation of a gust-alleviation system. An estimation algorithm of the airflow vector based on the lidars is proposed for preview control. The estimation performance and the computational cost of the proposed method can satisfy the performance demand for preview control.
Leonardo Alcayaga
Atmos. Meas. Tech., 13, 6237–6254, https://doi.org/10.5194/amt-13-6237-2020, https://doi.org/10.5194/amt-13-6237-2020, 2020
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Wind lidars present advantages over meteorological masts, including simultaneous multipoint observations, flexibility in measuring geometry, and reduced installation cost. But wind lidars come with the cost of increased complexity in terms of data quality and analysis. The common carrier-to-noise ratio and median filters are compared to the DBSCAN clustering algorithm to find improved data quality and recovery rate.
Sabine Wüst, Michael Bittner, Jeng-Hwa Yee, Martin G. Mlynczak, and James M. Russell III
Atmos. Meas. Tech., 13, 6067–6093, https://doi.org/10.5194/amt-13-6067-2020, https://doi.org/10.5194/amt-13-6067-2020, 2020
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With airglow spectrometers, the temperature in the upper mesosphere/lower thermosphere can be derived each night. The data allow to estimate the amount of energy which is transported by small-scale atmospheric waves, known as gravity waves. In order to do this, information about the Brunt–Väisälä frequency and its evolution during the year is necessary. This is provided here for low and midlatitudes based on 18 years of satellite data.
Pavel Alekseychik, Gabriel Katul, Ilkka Korpela, and Samuli Launiainen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-382, https://doi.org/10.5194/amt-2020-382, 2020
Revised manuscript accepted for AMT
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Drone with a thermal camera is a powerful new tool with potential to provide new insights into the atmospheric turbulence and heat fluxes. In a pioneering experiment, a Matrice 210 drone equipped with a Zenmuse XT2 thermal camera was used to record 10–20 min thermal videos over the Siikaneva natural peatland in southern Finland. A method to visualize the turbulent structures and derive their parameters from thermal videos is developed. The study provides a novel approach for turbulence analysis.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-384, https://doi.org/10.5194/amt-2020-384, 2020
Revised manuscript accepted for AMT
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We show results from two unique measurement campaigns aiming at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross section of the wind turbines. The findings are useful for wind turbine interference mitigation measures on radar systems.
René Sedlak, Alexandra Zuhr, Carsten Schmidt, Sabine Wüst, Michael Bittner, Goderdzi G. Didebulidze, and Colin Price
Atmos. Meas. Tech., 13, 5117–5128, https://doi.org/10.5194/amt-13-5117-2020, https://doi.org/10.5194/amt-13-5117-2020, 2020
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Gravity wave (GW) activity in the UMLT in the period range 6-480 min is calculated by applying a wavelet analysis to nocturnal temperature time series derived from OH* airglow spectrometers. We analyse measurements from eight different locations at different latitudes.
GW activity shows strong period dependence. We find hardly any seasonal variability for periods below 60 min and a semi-annual cycle for periods longer than 60 min that evolves into an annual cycle around a period of 200 min.
Daniel Sanchez-Rivas and Miguel Angel Rico-Ramirez
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-375, https://doi.org/10.5194/amt-2020-375, 2020
Revised manuscript accepted for AMT
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In our paper, we propose a robust and operational algorithm to determine the height of the Fre ezing level that can be applied to either Quasi-Vertical Profiles (QVPs) or Vertical profiles (VPs) of polarimetric radar variables. The algorithm is applied over one year of rainfall events collected by a C-Band operational weather radar located in the UK and validated using measured FLs from radiosonde. The results confirm that the algorithm estimates the FL accurately.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-284, https://doi.org/10.5194/amt-2020-284, 2020
Revised manuscript accepted for AMT
David D. Turner and Ulrich Löhnert
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-352, https://doi.org/10.5194/amt-2020-352, 2020
Revised manuscript accepted for AMT
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Temperature and humidity profiles in the lowest couple kilometers near the surface are very important for many applications. Passive spectral radiometers are commercially available, and observations from these instruments have been used to get these profiles. However, new active lidar systems are able to measure partial profiles of water vapor. This paper investigates how the derived profiles of water vapor and temperature are improved with the active and passive observations are combined.
Cornelia Strube, Manfred Ern, Peter Preusse, and Martin Riese
Atmos. Meas. Tech., 13, 4927–4945, https://doi.org/10.5194/amt-13-4927-2020, https://doi.org/10.5194/amt-13-4927-2020, 2020
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We present how inertial instabilities affect gravity wave background removal filters on different temperature data sets. Vertical filtering has to remove a part of the gravity wave spectrum to eliminate inertial instability remnants, while horizontal filtering leaves typical gravity wave scales untouched. In addition, we show that it is possible to separate inertial instabilities from gravity wave perturbations for infrared limb-sounding satellite profiles using a cutoff zonal wavenumber of 6.
Daniel Kastinen, Johan Kero, Alexander Kozlovsky, and Mark Lester
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-220, https://doi.org/10.5194/amt-2020-220, 2020
Revised manuscript accepted for AMT
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When a meteor enters the atmosphere it causes a trail of diffusing plasma that moves with the neutral wind. An interferometric radar system can measure such trails and determine its location. However, there is a chance of determining the wrong position due to noise. We simulate this behavior and use the simulations to successfully determine the true location of ambiguous events. We also successfully test a simple temporal integration method for avoiding such erroneous determinations.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech., 13, 4295–4315, https://doi.org/10.5194/amt-13-4295-2020, https://doi.org/10.5194/amt-13-4295-2020, 2020
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With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2018 to track worldwide changes in photosynthetic activity by vegetation.
Norman Wildmann, Eileen Päschke, Anke Roiger, and Christian Mallaun
Atmos. Meas. Tech., 13, 4141–4158, https://doi.org/10.5194/amt-13-4141-2020, https://doi.org/10.5194/amt-13-4141-2020, 2020
Ting-Yu Cha and Michael M. Bell
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-240, https://doi.org/10.5194/amt-2020-240, 2020
Revised manuscript accepted for AMT
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Doppler radar provides high-resolution wind measurements within tropical cyclones (TCs) for real-time monitoring and weather forecasting. Hurricane Matthew (2016) was observed by the ground-based single Doppler and NOAA P-3 Hurricane Hunter airborne radar simultaneously, providing a novel opportunity to compare single and multiple Doppler wind retrieval techniques. Here we improve the single Doppler wind retrieval algorithm, and show the pros and cons of each technique for studying TC structure.
Tina Hilbig, Klaus Bramstedt, Mark Weber, John P. Burrows, and Matthijs Krijger
Atmos. Meas. Tech., 13, 3893–3907, https://doi.org/10.5194/amt-13-3893-2020, https://doi.org/10.5194/amt-13-3893-2020, 2020
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One of the main limitations for long-term space-based measurements is
instrument degradation. We present an optimisation of the
degradation correction approach (Krijger et al. 2014) for SCIAMACHY
on-board Envisat, focusing on the improvement of the solar spectral
irradiance data. The main achievement of this study is the
successful integration of SCIAMACHY’s internal white light source
(WLS) into the existing degradation model and the
characterisation of WLS ageing in space.
Julius Polz, Christian Chwala, Maximilian Graf, and Harald Kunstmann
Atmos. Meas. Tech., 13, 3835–3853, https://doi.org/10.5194/amt-13-3835-2020, https://doi.org/10.5194/amt-13-3835-2020, 2020
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Commercial microwave link (CML) networks can be used to estimate path-averaged rain rates. This study evaluates the ability of convolutional neural networks to distinguish between wet and dry periods in CML time series data and the ability to transfer this detection skill to sensors not used for training. Our data set consists of several months of data from 3904 CMLs covering all of Germany. Compared to a previously used detection method, we could show a significant increase in performance.
Guy Delrieu, Anil Kumar Khanal, Nan Yu, Frédéric Cazenave, Brice Boudevillain, and Nicolas Gaussiat
Atmos. Meas. Tech., 13, 3731–3749, https://doi.org/10.5194/amt-13-3731-2020, https://doi.org/10.5194/amt-13-3731-2020, 2020
Andreas Behrendt, Volker Wulfmeyer, Christoph Senff, Shravan Kumar Muppa, Florian Späth, Diego Lange, Norbert Kalthoff, and Andreas Wieser
Atmos. Meas. Tech., 13, 3221–3233, https://doi.org/10.5194/amt-13-3221-2020, https://doi.org/10.5194/amt-13-3221-2020, 2020
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In order to understand how solar radiation energy hitting the ground is distributed into the atmosphere, we use a new combination of laser-based remote-sensing techniques to quantify these energy fluxes up to heights of more than 1 km above ground. Before, similar techniques had already been presented for determining the energy flux component regarding the exchange of humidity but not the warm air itself. Now, we show that this can also be measured by remote sensing with low uncertainties.
Pyry Pentikäinen, Ewan James O'Connor, Antti Juhani Manninen, and Pablo Ortiz-Amezcua
Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, https://doi.org/10.5194/amt-13-2849-2020, 2020
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We provide a methodology for obtaining a function describing how the Doppler lidar telescope configuration
impacts the measurements. Together with the function itself, we also provide the uncertainties in the function, which propagate through to provide uncertainties in the geophysical quantities obtained from the measurements. The method can be used to determine how stable the instrument is over time and also identify if changes have been made in the instrument setup.
Olivier Coopmann, Vincent Guidard, Nadia Fourrié, Béatrice Josse, and Virginie Marécal
Atmos. Meas. Tech., 13, 2659–2680, https://doi.org/10.5194/amt-13-2659-2020, https://doi.org/10.5194/amt-13-2659-2020, 2020
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The objective of this paper is to make a new selection of IASI channels by taking into account inter-channel observation-error correlations. Our selection further reduces the analysis error by 3 % in temperature, 1.8 % in humidity and 0.9 % in ozone compared to Collard’s selection, when using the same number of channels. A selection of 400 IASI channels is proposed at the end of the paper which is able to further reduce analysis errors.
Floor van den Heuvel, Loris Foresti, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 13, 2481–2500, https://doi.org/10.5194/amt-13-2481-2020, https://doi.org/10.5194/amt-13-2481-2020, 2020
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In areas with reduced visibility at the ground level, radar precipitation measurements higher up in the atmosphere need to be extrapolated to the ground and be corrected for the vertical change (i.e. growth and transformation) of precipitation. This study proposes a method based on hydrometeor proportions and machine learning (ML) to apply these corrections at smaller spatiotemporal scales. In comparison with existing techniques, the ML methods can make predictions from higher altitudes.
Guillaume Thomas, Jean-François Mahfouf, and Thibaut Montmerle
Atmos. Meas. Tech., 13, 2279–2298, https://doi.org/10.5194/amt-13-2279-2020, https://doi.org/10.5194/amt-13-2279-2020, 2020
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This paper presents the potential of a polarimetric weather radar observation operator for hydrometeor content initialization. The non-linear operator allows to simulate ZHH, ZDR, KDP and ρHV, using the T-Matrix method, prognostic variables forecasted by the AROME-France NWP model and a one-moment microphysical scheme. After sensitivity studies, it has been found that ZHH and ZDR are good candidates for hydrometeor initialization and that KDP seems useful for rain content only.
Thomas C. van Leth, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 13, 1797–1815, https://doi.org/10.5194/amt-13-1797-2020, https://doi.org/10.5194/amt-13-1797-2020, 2020
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We present a method of using collocated microwave link instruments to estimate the average size distribution of raindrops along a path of several kilometers. Our method is validated using simulated fields as well as five laser disdrometers installed along a path. We also present preliminary results from an experimental setup measuring at 26 and 38 GHz along a 2.2 km path. We show that a retrieval on the basis of microwave links can be highly accurate, provided the base power level is stable.
Philipp Gasch, Andreas Wieser, Julie K. Lundquist, and Norbert Kalthoff
Atmos. Meas. Tech., 13, 1609–1631, https://doi.org/10.5194/amt-13-1609-2020, https://doi.org/10.5194/amt-13-1609-2020, 2020
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We present an airborne Doppler lidar simulator (ADLS) based on high-resolution atmospheric wind fields (LES). The ADLS is used to evaluate the retrieval accuracy of airborne wind profiling under turbulent, inhomogeneous wind field conditions inside the boundary layer. With the ADLS, the error due to the violation of the wind field homogeneity assumption used for retrieval can be revealed. For the conditions considered, flow inhomogeneities exert a dominant influence on wind profiling error.
Tyler M. Bell, Petra Klein, Norman Wildmann, and Robert Menke
Atmos. Meas. Tech., 13, 1357–1371, https://doi.org/10.5194/amt-13-1357-2020, https://doi.org/10.5194/amt-13-1357-2020, 2020
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This study investigates the utility of using multi-Doppler retrievals during the Perdigão 2017 campaign. By combining scans from the multitude of Doppler lidars, it was possible to derive virtual towers that greatly extend the range of traditional in situ meteorological towers. Uncertainties from the measurements are analyzed and discussed. Despite multiple sources of error, it was found that the virtual towers are useful for analyzing the complex flows observed during the campaign.
Jussi Tiira and Dmitri Moisseev
Atmos. Meas. Tech., 13, 1227–1241, https://doi.org/10.5194/amt-13-1227-2020, https://doi.org/10.5194/amt-13-1227-2020, 2020
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Modern weather radars are sensitive for properties of precipitating snow particles, such as their sizes, shapes and number concentration. Vertical profiles of such radar measurements can be used for studying the processes through which snow is formed. We created a profile classification method for this purpose, and we show how it can be used for automatic identification of snow growth processes. Being able to identify the processes is expected to improve radar-based precipitation estimation.
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Short summary
Sastrugi are surface roughness elements on Antarctica that modify the anisotropy of reflected shortwave solar radiation. This can create biases in the shortwave flux inverted from radiances measured by the satellite-borne Clouds and the Earths's Radiant Energy System instruments. Here we provide a detailed description of the methodology we use to account for their effect and examples of the reduction in bias from using our new method.
Sastrugi are surface roughness elements on Antarctica that modify the anisotropy of reflected...
