Articles | Volume 14, issue 1
https://doi.org/10.5194/amt-14-391-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-391-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Jan 2021
Research article |
| 18 Jan 2021
| 18 Jan 2021
Classification of lidar measurements using supervised and unsupervised machine learning methods
Ghazal Farhani
Department of Physics and Astronomy, The University of Western Ontario, 1151 Richmond St., London, ON, N6A 3K7, Canada
Department of Physics and Astronomy, The University of Western Ontario, 1151 Richmond St., London, ON, N6A 3K7, Canada
Mark Joseph Daley
Department of Computer Science, The Vector Institute for Artificial Intelligence, The University of Western Ontario, 1151 Richmond St., London, ON, N6A 3K7, Canada
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Atmos. Meas. Tech., 18, 1461–1469, https://doi.org/10.5194/amt-18-1461-2025, https://doi.org/10.5194/amt-18-1461-2025, 2025
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Our study presents a new method, the solar background calibration method, which improves temperature determinations in rotational Raman lidar systems. By utilizing background solar radiation, this technique offers more continuous and reliable temperatures independent of external measuring instruments. This new method enhances our ability to monitor and understand atmospheric trends and their association with climate change with greater accuracy.
Shannon Hicks-Jalali, Robert J. Sica, Giovanni Martucci, Eliane Maillard Barras, Jordan Voirin, and Alexander Haefele
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We have calculated an 11.5-year water vapour climatology using the Raman Lidar for Meteorological Observations (RALMO), located in Payerne, Switzerland. The climatology shows that the highest water vapour concentrations are in the summer months and the lowest in the winter months. We present for the first time height-resolved water vapour trends, which show that water vapour increases specific humidity by between 5 % and 15 % per decade depending on the altitude.
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Atmos. Meas. Tech., 12, 5801–5816, https://doi.org/10.5194/amt-12-5801-2019, https://doi.org/10.5194/amt-12-5801-2019, 2019
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We present a new method for retrieving temperature from pure rotational Raman (PRR) lidar measurements using an optimal estimation method. We show that the error due to calibration can be reduced significantly using our method. The new method is tested on PRR temperature measurements from the MeteoSwiss Raman Lidar for Meteorological Observations system in different sky conditions. The next step is to assimilate the temperature profiles into models to help improve weather forecasts.
Ali Jalali, Shannon Hicks-Jalali, Robert J. Sica, Alexander Haefele, and Thomas von Clarmann
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Atmos. Meas. Tech., 12, 2097–2111, https://doi.org/10.5194/amt-12-2097-2019, https://doi.org/10.5194/amt-12-2097-2019, 2019
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-381, https://doi.org/10.5194/amt-2018-381, 2019
Publication in AMT not foreseen
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A satellite retrieval for water vapour column was adapted for use over different surfaces in the wintertime Arctic. The retrieval was validated at multiple locations where there was excellent agreement. Reanalyses were found to be 10–15 % drier compared to our water vapour retrieval. Reanalyses represent the present day understanding of the atmosphere so this discrepancy between reanalyses and our retrieval could have implications for the current understanding of the climate.
Ali Jalali, Robert J. Sica, and Alexander Haefele
Atmos. Meas. Tech., 11, 6043–6058, https://doi.org/10.5194/amt-11-6043-2018, https://doi.org/10.5194/amt-11-6043-2018, 2018
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We use 16 years of lidar (laser radar) temperature measurements of the middle atmosphere to form a climatology for use in studying atmospheric temperature change using an optimal estimation method (OEM). Using OEM allows us to calculate a complete systematic and random uncertainty budget and allows for an additional 10–15 km in altitude for the measurement to be used, improving our ability to detect atmospheric temperature change up to 100 km of altitude.
Emily M. McCullough, Robert J. Sica, James R. Drummond, Graeme J. Nott, Christopher Perro, and Thomas J. Duck
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Measuring the phase (liquid and ice) of Arctic clouds is essential for understanding the changing global climate. Using a lidar, two polarized signals are usually needed. At CRL lidar, one of these signals is small, so phase measurements have low resolution. Another method can use a large unpolarized signal in place of the small polarized signal. We show how to use the original low-resolution measurement to calibrate the new high-resolution method. At CRL, this gives 20 times higher resolution.
Emily M. McCullough, Robert J. Sica, James R. Drummond, Graeme Nott, Christopher Perro, Colin P. Thackray, Jason Hopper, Jonathan Doyle, Thomas J. Duck, and Kaley A. Walker
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CRL lidar in the Canadian High Arctic uses lasers and a telescope to study polar clouds, essential for understanding the changing global climate. Hardware added to CRL allows it to measure the polarization of returned laser light, indicating whether cloud particles are liquid or frozen. Calibrations show that traditional analysis methods work well, although CRL was not originally set up to make this type of measurement. CRL can now measure cloud particle phase every 5 min, every 37.5 m, 24h/day.
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Thierry Leblanc, Robert J. Sica, Joanna A. E. van Gijsel, Alexander Haefele, Guillaume Payen, and Gianluigi Liberti
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A. Moss, R. J. Sica, E. McCullough, K. Strawbridge, K. Walker, and J. Drummond
Atmos. Meas. Tech., 6, 741–749, https://doi.org/10.5194/amt-6-741-2013, https://doi.org/10.5194/amt-6-741-2013, 2013
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Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Accurate KDP estimates are crucial in radar-based applications. We quantify the uncertainties of several publicly available KDP estimation methods for multiple rainfall intensities. We use C-band weather radar observations and employed a self-consistency KDP, estimated from reflectivity and differential reflectivity, as a framework for the examination. Our study provides guidance for the performance, uncertainties, and optimisation of the methods, focusing mainly on accuracy and robustness.
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Tropospheric gradients provide information on the moisture distribution, whereas ZTDs provide the absolute amount of moisture through integrated water vapor. When TGs are assimilated with ZTDs, it helps the model actuate the moisture fields, correcting its dynamics. In our research, we show evidence that in particular regions with very few GNSS stations, the assimilation of gradients on top of ZTDs can provide the same impact as the assimilation of only ZTDs with dense coverage of GNSS stations.
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Commercial microwave links (CMLs), part of mobile phone networks, transmit comparable signals as instruments specially designed to estimate evaporation. Therefore, we investigate if CMLs could be used to estimate evaporation, even though they have not been designed for this purpose. Our results illustrate the potential of using CMLs to estimate evaporation, especially given their global coverage, but also outline some major drawbacks, often a consequence of unfavourable design choices for CMLs.
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 7169–7181, https://doi.org/10.5194/amt-17-7169-2024, https://doi.org/10.5194/amt-17-7169-2024, 2024
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Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. We present a method based on a selection of specific frequencies and elevation angles from microwave radiometer observations. A comparison with a numerical weather prediction model shows the presented method allows low-level temperature profiles during rain to be resolved, with rain rates of up to 2.5 mm h−1,, which was not possible before with state-of-the-art retrievals.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
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The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm that produces Aeolus lidar surface returns (LSRs), containing useful information for measuring UV reflectivity. Aeolus LSRs matched well with existing UV reflectivity data from other satellites, like GOME-2 and TROPOMI, and demonstrated excellent sensitivity to modeled snow cover.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
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The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
Atmos. Meas. Tech., 17, 7007–7026, https://doi.org/10.5194/amt-17-7007-2024, https://doi.org/10.5194/amt-17-7007-2024, 2024
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This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft), are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024, https://doi.org/10.5194/amt-17-6913-2024, 2024
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Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose optimized post-processing for error reduction.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Yunfan Yang, Wei Han, Haofei Sun, Jun Li, Jiapeng Yan, and Zhiqiu Gao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-175, https://doi.org/10.5194/amt-2024-175, 2024
Revised manuscript accepted for AMT
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Our research improves satellite-based precipitation monitoring by using deep learning to reconstruct radar observations from passive microwave radiances. Active radar is costly, so we focus on a more accessible approach. Using data from the FengYun-3G satellite, we successfully tracked severe weather like Typhoon Khanun and heavy rainfall in Beijing in 2023. This method enhances global precipitation data and helps better understand extreme weather.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Tessa E. Rosenberger, Thijs Heus, Girish N. Raghunathan, David D. Turner, Timothy J. Wagner, and Julia M. Simonson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2894, https://doi.org/10.5194/egusphere-2024-2894, 2024
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Entrainment is key in understanding temperature and moisture changes within the boundary layer, but it is difficult to observe using ground-based observations. This work used simulations to verify an assumption that simplifies entrainment estimations from ground-based observational data, recognizing that entrainment is the combination of the transfer of heat and moisture from above the boundary layer into it and the change in concentration of heat and moisture as boundary layer depth changes.
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
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The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Ollie Lewis, Chris Brunt, Malcolm Kitchen, Neill E. Bowler, and Edmund K. Stone
EGUsphere, https://doi.org/10.5194/egusphere-2024-2273, https://doi.org/10.5194/egusphere-2024-2273, 2024
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Humidity observations are crucial for an accurate weather forecast. We propose a new way to measure humidity by measuring how radio signals from commercial aircraft are refracted by the atmosphere. Humidity affects the refractive index of air, allowing its presence to be detected. With thousands of flights in the airspace over the United Kingdom every day, there is the potential for a large increase in the number of humidity measurements for use in weather forecasting models.
Dianrun Zhao, Shanshan Du, Chu Zou, Longfei Tian, Meng Fan, Yulu Du, and Liangyun Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3118, https://doi.org/10.5194/egusphere-2024-3118, 2024
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The TanSat-2 satellite is designed for global carbon monitoring. It provides high-resolution, dual-band observations of solar-induced chlorophyll fluorescence, a key indicator of plant photosynthesis. Through simulations, we optimized the satellite's data processing and found it can retrieve this fluorescence with great accuracy. These findings suggest that TanSat-2 will enhance global monitoring of carbon cycles and vegetation health, offering valuable insights for climate change research.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
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We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Xiaoye Wang, Jing Xu, Songhua Wu, Qichao Wang, Guangyao Dai, Peizhi Zhu, Zhizhong Su, Sai Chen, Xiaomeng Shi, and Mengqi Fan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-156, https://doi.org/10.5194/amt-2024-156, 2024
Revised manuscript accepted for AMT
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In this paper, we proposed a data fusion method to obtain the no-blind zone wind speed profiles covering the whole Atmospheric Boundary Layer based on the joint measurements of coherent Doppler lidar (CDL), radar wind profiler (RWP) and automatic weather station (AWS). Since above instruments are widely deployed in China, we believe this method has broad application prospects on the improvement of the boundary layer parameterization scheme in numerical forecast models.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
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This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
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A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
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Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
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We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
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A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
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We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
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Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
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Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Bing Cao, Jennifer S. Haase, Michael J. Murphy Jr., and Anna M. Wilson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-119, https://doi.org/10.5194/amt-2024-119, 2024
Revised manuscript accepted for AMT
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This paper describes an Airborne Radio Occultation (ARO) observation system installed on reconnaissance aircraft that uses GPS signal refraction in the atmosphere to retrieve information about the temperature and moisture in the storm environment as far away as 400 km surrounding the flight track. The characteristics and quality of 1700 ARO refractivity profiles were assessed. These observations are collected to help understand atmospheric rivers and improve their forecasting.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
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The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Qihou Zhou, Yanlin Li, and Yun Gong
Atmos. Meas. Tech., 17, 4197–4209, https://doi.org/10.5194/amt-17-4197-2024, https://doi.org/10.5194/amt-17-4197-2024, 2024
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We discuss several robust estimators to compute the variance of a normally distributed random variable to deal with interference. Compared to rank-based estimators, the methods based on the geometric mean are more accurate and are computationally more efficient. We apply three robust estimators to incoherent scatter power and velocity processing, along with the traditional sample mean estimator. The best estimator is a hybrid estimator that combines the sample mean and a robust estimator.
Zhao Shi, Yuxiang Wen, and Jianxin He
Atmos. Meas. Tech., 17, 4121–4135, https://doi.org/10.5194/amt-17-4121-2024, https://doi.org/10.5194/amt-17-4121-2024, 2024
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The squall line is a type of convective system. Squall lines are often associated with damaging weather, so identifying and tracking squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines within the radar scanning range with an accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking results for each squall line.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
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Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
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The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024, https://doi.org/10.5194/amt-17-3829-2024, 2024
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The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the mesosphere and lower thermosphere. These waves perturb the temperature field, and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
Cited articles
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, 2002. a
Burges, C. J.: A tutorial on support vector machines
for pattern recognition, Data Mining Knowledge Discovery, 2, 121–167, 1998. a
Christian, K., Wang, J., Ge, C., Peterson, D., Hyer, E., Yorks, J., and McGill, M.: Radiative Forcing and Stratospheric Warming of Pyrocumulonimbus Smoke Aerosols: First Modeling Results With Multisensor (EPIC, CALIPSO, and CATS) Views from Space, Geophys. Res. Lett., 46, 10061–10071, 2019. a
Feurer, M. and Hutter, F.:
Hyperparameter optimization, in: Automated Machine Learning, Springer, Cham, 3–33, 2019. a
Foody, G. M. and Mathur, A.: A relative evaluation of multiclass image classification by support vector machines, IEEE T. Geosci. Remote Sens., 42,
1335–1343, 2004. a
Hastie, T., Tibshirani, R., and Friedman, J.: Unsupervised learning, in: The elements of statistical learning, Springer Series in Statistics, New York, Chap. 14, 485–585, 2009. a
Lerman, R. I. and Yitzhaki, S.: A note on the
calculation and interpretation of the Gini index, Econ. Lett., 15, 363–368, 1984. a
Maaten, L. and Hinton, G.: Visualizing
data using t-SNE, J. Machine Learn. Res., 9, 2579–2605, 2008. a
Mantero, P., Moser, G., and
Serpico, S. B.: Partially supervised classification of remote sensing images through SVM-based
probability density estimation, IEEE T. Geosci. Remote Sens., 43, 559–570, 2005. a
NDACC: NDACC Measurements at the London, Ontario, Canada Station, NDACC, available at: https://www.ndaccdemo.org/stations/london-ontario-canada or via ftp at:
http://ftp.cpc.ncep.noaa.gov/ndacc/station/londonca/hdf/lidar/, last access: 8 January 2021. a
Nicolae, D., Vasilescu, J., Talianu, C., Binietoglou, I., Nicolae, V., Andrei, S., and Antonescu, B.: A neural network aerosol-typing algorithm based on lidar data, Atmos. Chem. Phys., 18, 14511–14537, https://doi.org/10.5194/acp-18-14511-2018, 2018. a, b
Quinlan, J. R.: Induction of decision trees, Machine
Learn., 1, 81–106, 1986. a
Robert, C. P. and Casella, G.: Monte Carlo Statistical
Methods, Springer Texts in Statistics, Springer science & business media, New York, NY, 2004. a
Schapire, R. E.: The strength of weak learnability,
Machine Learn., 5, 197–227, 1990. a
Shannon, C.: A mathematical theory of
communication, Bell Syst. Techn. J., 27, 379–423, 1948. a
Sica, R., Sargoytchev, S., Argall, P. S., Borra, E. F., Girard, L.,
Sparrow, C. T., and Flatt, S.: Lidar measurements taken with a large-aperture liquid
mirror. 1. Rayleigh-scatter system, Appl. Opt., 34, 6925–6936, 1995. a
Vapnik, V.: The nature of statistical learning theory,
Springer Science & Business Media, Springer-Verlag New York, 2013. a
Wing, R., Hauchecorne, A., Keckhut, P., Godin-Beekmann, S., Khaykin, S., McCullough, E. M., Mariscal, J.-F., and d'Almeida, É.: Lidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidars, Atmos. Meas. Tech., 11, 5531–5547, https://doi.org/10.5194/amt-11-5531-2018, 2018. a, b
Zeng, S., Vaughan, M., Liu, Z., Trepte, C., Kar, J., Omar, A., Winker, D., Lucker, P., Hu, Y., Getzewich, B., and Avery, M.: Application of high-dimensional fuzzy k-means cluster analysis to CALIOP/CALIPSO version 4.1 cloud–aerosol discrimination, Atmos. Meas. Tech., 12, 2261–2285, https://doi.org/10.5194/amt-12-2261-2019, 2019. a, b
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
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.
While it is relatively straightforward to automate the processing of lidar signals, it is...
