Articles | Volume 13, issue 2
Research article 07 Feb 2020
Research article | 07 Feb 2020
Improved fuzzy logic method to distinguish between meteorological and non-meteorological echoes using C-band polarimetric radar data
Shuai Zhang et al.
No articles found.
Yuefei Zeng, Tijana Janjic, Yuxuan Feng, Ulrich Blahak, Alberto de Lozar, Elisabeth Bauernschubert, Klaus Stephan, and Jinzhong Min
Atmos. Meas. Tech., 14, 5735–5756,Short summary
Observation errors (OEs) of radar measurements are correlated. The Desroziers method has been often used to estimate statistics of OE in data assimilation. However, the resulting statistics consist of contributions from different sources and are difficult to interpret. Here, we use an approach based on samples for truncation error to approximate the representation error due to unresolved scales and processes (RE) and compare its statistics with OE statistics estimated by the Desroziers method.
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information RetrievalHigh-temporal-resolution wet delay gradients estimated from multi-GNSS and microwave radiometer observationsBoundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopyGNSS-based water vapor estimation and validation during the MOSAiC expeditionMeteor radar observations of polar mesospheric summer echoes over SvalbardAnalysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radarsEvaluation of micro rain radar-based precipitation classification algorithms to discriminate between stratiform and convective precipitationOn the estimation of boundary layer heights: a machine learning approachIMK/IAA MIPAS temperature retrieval version 8: nominal measurementsResolving the ambiguous direction of arrival of weak meteor radar trail echoesComparison of single-Doppler and multiple-Doppler wind retrievals in Hurricane Matthew (2016)Insights into wind turbine reflectivity and radar cross-section (RCS) and their variability using X-band weather radar observationsEddies in motion: visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videosAssimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structureConsistency of total column ozone measurements between the Brewer and Dobson spectroradiometers of the LKO Arosa and PMOD/WRC DavosRainForest: a random forest algorithm for quantitative precipitation estimation over SwitzerlandGround-based temperature and humidity profiling: combining active and passive remote sensorsStatistically analyzing the effect of ionospheric irregularity on GNSS radio occultation atmospheric measurementDetection of the melting level with polarimetric weather radarIntegrated water vapor and liquid water path retrieval using a single-channel radiometerImproving atmospheric path attenuation estimates for radio propagation applications by microwave radiometric profilingUsing Vertical Phase Differences to Better Resolve 3D Gravity Wave StructureA new global grid-based weighted mean temperature model considering vertical nonlinear variationMonitoring sudden stratospheric warmings using radio occultation: a new approach demonstrated based on the 2009 eventLiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 1: Theoretical frameworkLiSBOA (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 wakesEstimation of the height of the turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beamSpectral correction of turbulent energy damping on wind lidar measurements due to spatial averagingImprovement in tropospheric moisture retrievals from VIIRS through the use of infrared absorption bands constructed from VIIRS and CrIS data fusionHydrometeor classification of quasi-vertical profiles of polarimetric radar measurements using a top-down iterative hierarchical clustering methodAssimilation of lidar planetary boundary layer height observationsDetection of anomalies in the UV–vis reflectances from the Ozone Monitoring InstrumentWhat millimeter-wavelength radar reflectivity reveals about snowfall: an information-centric analysisGeneralized canonical transform method for radio occultation sounding with improved retrieval in the presence of horizontal gradientsLinking rain into ice microphysics across the melting layer in stratiform rain: a closure studyClassification of lidar measurements using supervised and unsupervised machine learning methodsThe development of rainfall retrievals from radar at DarwinRetrieved wind speed from the Orbiting Carbon Observatory-2Probabilistic analysis of ambiguities in radar echo direction of arrival from meteorsDetecting the melting layer with a micro rain radar using a neural network approachDetecting turbulent structures on single Doppler lidar large datasets: an automated classification method for horizontal scansReal-time estimation of airflow vector based on lidar observations for preview controlFiltering of pulsed lidar data using spatial information and a clustering algorithmVariability of the Brunt–Väisälä frequency at the OH∗-airglow layer height at low and midlatitudesIntra-annual variations of spectrally resolved gravity wave activity in the upper mesosphere/lower thermosphere (UMLT) regionRemoving spurious inertial instability signals from gravity wave temperature perturbations using spectral filtering methodsImproved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradationTowards improved turbulence estimation with Doppler wind lidar velocity-azimuth display (VAD) scansOptimised degradation correction for SCIAMACHY satellite solar measurements from 330 to 1600 nm by using the internal white light sourceRain event detection in commercial microwave link attenuation data using convolutional neural networksPreliminary investigation of the relationship between differential phase shift and path-integrated attenuation at the X band frequency in an Alpine environment
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 14, 5593–5605,Short summary
We have estimated horizontal gradients of the propagation delay caused by water vapour in the atmosphere using two independent techniques, namely global navigation satellite systems (GNSS) and microwave radiometry. The highest resolution was 5 min. We found that the sampling of the atmosphere in different directions is an important factor for high correlations between the two techniques and that GNSS data can be used to detect large short-lived gradients, however, with increased formal errors.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576,Short summary
Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Benjamin Männel, Florian Zus, Galina Dick, Susanne Glaser, Maximilian Semmling, Kyriakos Balidakis, Jens Wickert, Marion Maturilli, Sandro Dahlke, and Harald Schuh
Atmos. Meas. Tech., 14, 5127–5138,Short summary
Within the MOSAiC expedition, GNSS was used to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked data, coordinates and hourly zenith total delays (ZTDs) were determined using kinematic precise point positioning. The derived ZTD values agree within few millimeters with ERA5 and terrestrial GNSS and VLBI stations. The derived integrated water vapor corresponds to the frequently launched radiosondes (0.08 ± 0.04 kg m−2, rms of the differences of 1.47 kg m−2).
Joel P. Younger, Iain M. Reid, Chris L. Adami, Chris M. Hall, and Masaki Tsutsumi
Atmos. Meas. Tech., 14, 5015–5027,Short summary
A radar in Svalbard usually used to study meteor trails was used to observe a thin icy layer in the upper atmosphere. New methods used the layer to measure wind speed over short periods of time and found that the layer is most reflective within 6.8 ± 3.3° of vertical. Analysis of meteor trail radar echo durations found that the layer may shorten meteor trail echoes, but more data are needed. This study shows new uses for data collected by meteor radars for other purposes.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913,Short summary
Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Andreas Foth, Janek Zimmer, Felix Lauermann, and Heike Kalesse-Los
Atmos. Meas. Tech., 14, 4565–4574,Short summary
In this paper, we present two micro rain radar-based approaches to discriminate between stratiform and convective precipitation. One is based on probability density functions and the other one is an artificial neural network classification. Both methods agree well, giving similar results. However, the results of the artificial neural network are more reasonable since it is also able to distinguish an inconclusive class, in turn making the stratiform and convective classes more reliable.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424,Short summary
Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Anne Kleinert, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, Daniel R. Marsh, and Gabriele P. Stiller
Atmos. Meas. Tech., 14, 4111–4138,Short summary
An improved dataset of vertical temperature profiles of the Earth's atmosphere in the altitude range 5–70 km is presented. These profiles are derived from measurements of the MIPAS instrument onboard ESA's Envisat satellite. The overall improvements are based on upgrades in the input data and several improvements in the data processing approach. Both of these are discussed, and an extensive error discussion is included. Enhancements of the new dataset are demonstrated by means of examples.
Daniel Kastinen, Johan Kero, Alexander Kozlovsky, and Mark Lester
Atmos. Meas. Tech., 14, 3583–3596,Short summary
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 behaviour and use the simulations to successfully determine the true location of ambiguous events. We also successfully test two simple temporal integration methods for avoiding such erroneous determinations.
Ting-Yu Cha and Michael M. Bell
Atmos. Meas. Tech., 14, 3523–3539,Short summary
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 method for studying TC structure.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech., 14, 3541–3560,Short summary
We show results from two unique measurement campaigns aimed 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 in radar systems.
Pavel Alekseychik, Gabriel Katul, Ilkka Korpela, and Samuli Launiainen
Atmos. Meas. Tech., 14, 3501–3521,Short summary
Drones with thermal cameras are powerful new tools with the potential to provide new insights into atmospheric turbulence and heat fluxes. In a pioneering experiment, a Matrice 210 drone with a Zenmuse XT2 thermal camera was used to record 10–20 min thermal videos at 500 m a.g.l. over the Siikaneva 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.
Svetla Hristova-Veleva, Sara Q. Zhang, F. Joseph Turk, Ziad S. Haddad, and Randy C. Sawaya
Atmos. Meas. Tech., 14, 3333–3350,Short summary
The assimilation of airborne-based three-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 on the resultant wind and moisture structure, in accord with independent analysis of the wind structure and external satellite observations.
Julian Gröbner, Herbert Schill, Luca Egli, and René Stübi
Atmos. Meas. Tech., 14, 3319–3331,Short summary
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.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193,Short summary
In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
David D. Turner and Ulrich Löhnert
Atmos. Meas. Tech., 14, 3033–3048,Short summary
Temperature and humidity profiles in the lowest couple of 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 when the active and passive observations are combined.
Mingzhe Li and Xinan Yue
Atmos. Meas. Tech., 14, 3003–3013,Short summary
In this study, we statistically analyzed the correlation between the ionospheric irregularity and the quality of the GNSS atmospheric radio occultation (RO) products. The 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.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 14, 2873–2890,Short summary
In our paper, we propose a robust and operational algorithm to determine the height of the melting level that can be applied to either quasi-vertical profiles (QVPs) or vertical profiles (VPs) of polarimetric radar variables. The algorithm is applied to 1 year of rainfall events that occurred over southeast England and validated using radiosonde data. The algorithm proves to be accurate as the errors (mean absolute error and root mean square error) are close to 200 m.
Anne-Claire Billault-Roux and Alexis Berne
Atmos. Meas. Tech., 14, 2749–2769,Short summary
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,Short summary
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.
Corwin J. Wright, Neil P. Hindley, M. Joan Alexander, Laura A. Holt, and Lars Hoffmann
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
Measuring atmospheric gravity waves in low-vertical-resolution data is technically challenging, especially when the waves are significantly longer in the vertical than the length of the measurement domain. We introduce and demonstrate a modification to the existing Stockwell-Transform methods of characterising these waves that addresses these problems, with no apparent reduction in the other capabilities of the technique.
Peng Sun, Suqin Wu, Kefei Zhang, Moufeng Wan, and Ren Wang
Atmos. Meas. Tech., 14, 2529–2542,Short summary
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,Short summary
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,Short summary
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,Short summary
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,
Matteo Puccioni and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 1457–1474,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
While it is relatively straightforward to automate the processing of lidar signals, it is difficult to automatically preprocess the measurements to distinguish between
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.
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,Short summary
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.
Robert R. Nelson, Annmarie Eldering, David Crisp, Aronne J. Merrelli, and Christopher W. O'Dell
Atmos. Meas. Tech., 13, 6889–6899,Short summary
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,Short summary
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,Short summary
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.
Ioannis Cheliotis, Elsa Dieudonné, Hervé Delbarre, Anton Sokolov, Egor Dmitriev, Patrick Augustin, and Marc Fourmentin
Atmos. Meas. Tech., 13, 6579–6592,Short summary
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,Short summary
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.
Atmos. Meas. Tech., 13, 6237–6254,Short summary
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,Short summary
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.
René Sedlak, Alexandra Zuhr, Carsten Schmidt, Sabine Wüst, Michael Bittner, Goderdzi G. Didebulidze, and Colin Price
Atmos. Meas. Tech., 13, 5117–5128,Short summary
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.
Cornelia Strube, Manfred Ern, Peter Preusse, and Martin Riese
Atmos. Meas. Tech., 13, 4927–4945,Short summary
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.
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,Short summary
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,
Tina Hilbig, Klaus Bramstedt, Mark Weber, John P. Burrows, and Matthijs Krijger
Atmos. Meas. Tech., 13, 3893–3907,Short summary
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,Short summary
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,
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The discrimination between meteorological and non-meteorological echoes is necessary to obtain better meteorological application performance. However, the widely used algorithms have high expectations for polarimetric data, which have similar characteristics between meteorological and non-meteorological echoes in the weak-signal regions. Therefore, an improved fuzzy logic method is proposed in this paper to improve the classification performance in weak-signal regions.
The discrimination between meteorological and non-meteorological echoes is necessary to obtain...