Articles | Volume 13, issue 2
https://doi.org/10.5194/amt-13-537-2020
© Author(s) 2020. 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-13-537-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Feb 2020
Research article |
| 07 Feb 2020
| 07 Feb 2020
Improved fuzzy logic method to distinguish between meteorological and non-meteorological echoes using C-band polarimetric radar data
Shuai Zhang
Key Laboratory of Meteorological Disaster of Ministry of Education,
Nanjing University of Information Science and Technology, Nanjing, China
Xingyou Huang
CORRESPONDING AUTHOR
Key Laboratory of Meteorological Disaster of Ministry of Education,
Nanjing University of Information Science and Technology, Nanjing, China
Jinzhong Min
Key Laboratory of Meteorological Disaster of Ministry of Education,
Nanjing University of Information Science and Technology, Nanjing, China
Zhigang Chu
Key Laboratory of Meteorological Disaster of Ministry of Education,
Nanjing University of Information Science and Technology, Nanjing, China
Xiaoran Zhuang
Key Laboratory of Meteorological Disaster of Ministry of Education,
Nanjing University of Information Science and Technology, Nanjing, China
Hengheng Zhang
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Related authors
No articles found.
Qian Liu, Bing Gong, Xiaoran Zhuang, Xiaohui Zhong, Zhiming Kang, and Hao Li
EGUsphere, https://doi.org/10.5194/egusphere-2024-3183, https://doi.org/10.5194/egusphere-2024-3183, 2024
Preprint withdrawn
Short summary
Short summary
This paper presents a machine learning-based data compression method for weather and climate research, addressing the computational challenges posed by large datasets in weather applications. We propose a novel VAE framework that compresses three years of 1 km resolution data from 8.61 TB to 204 GB. This reduction significantly lowers computational resource requirements. We also demonstrate the compressed data's effectiveness by downscaling the Fuxi AI forecast model.
Haixia Xiao, Yaqiang Wang, Yu Zheng, Yuanyuan Zheng, Xiaoran Zhuang, Hongyan Wang, and Mei Gao
Geosci. Model Dev., 16, 3611–3628, https://doi.org/10.5194/gmd-16-3611-2023, https://doi.org/10.5194/gmd-16-3611-2023, 2023
Short summary
Short summary
Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CG nowcasting has remained unattainable. Here, we developed a deep learning model — namely CGsNet — for 0—2 h of quantitative CG nowcasting, first achieving minute—kilometer-level forecasts. Based on the CGsNet model, the average surface wind speed (ASWS) and peak wind gust speed (PWGS) predictions are obtained. Experiments indicate that CGsNet exhibits higher accuracy than the traditional method.
Yuefei Zeng, Tijana Janjic, Yuxuan Feng, Ulrich Blahak, Alberto de Lozar, Elisabeth Bauernschubert, Klaus Stephan, and Jinzhong Min
Atmos. Meas. Tech., 14, 5735–5756, https://doi.org/10.5194/amt-14-5735-2021, https://doi.org/10.5194/amt-14-5735-2021, 2021
Short summary
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 Retrieval
Global Navigation Satellite System (GNSS) radio occultation climatologies mapped by machine learning and Bayesian interpolation
Determination of low-level temperature profiles from microwave radiometer observations during rain
Aeolus lidar surface return (LSR) at 355 nm as a new Aeolus Level-2A product
Sampling the diurnal and annual cycles of the Earth's energy imbalance with constellations of satellite-borne radiometers
Retrieval of top-of-atmosphere fluxes from combined EarthCARE lidar, imager, and broadband radiometer observations: the BMA-FLX product
Analysis of the measurement uncertainty for a 3D wind lidar
Improving solution availability and temporal consistency of an optimal-estimation physical retrieval for ground-based thermodynamic boundary layer profiling
An improved geolocation methodology for spaceborne radar and lidar systems
Combining low- and high-frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products
HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and TEmporal Resolution
Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT
Retrieval of pseudo-BRDF-adjusted surface reflectance at 440 nm from the Geostationary Environmental Monitoring Spectrometer (GEMS)
Benchmarking KDP in Rainfall: A Quantitative Assessment of Estimation Algorithms Using C-Band Weather Radar Observations
Drop size distribution retrieval using dual-polarization radar at C-band and S-band
Thermal tides in the middle atmosphere at mid-latitudes measured with a ground-based microwave radiometer
Mitigating Radome Induced Bias in X-Band Weather Radar Polarimetric moments using Adaptive DFT Algorithm
Global sensitivity analysis of simulated remote sensing polarimetric observations over snow
Improving the Gaussianity of radar reflectivity departures between observations and simulations using symmetric rain rates
On the temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique
Limitations in wavelet analysis of non-stationary atmospheric gravity wave signatures in temperature profiles
A new non-linearity correction method for the spectrum from the Geostationary Inferometric Infrared Sounder on board Fengyun-4 satellites and its preliminary assessments
Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data
Unfiltering of the EarthCARE Broadband Radiometer (BBR) observations: the BM-RAD product
Variance estimations in the presence of intermittent interference and their applications to incoherent scatter radar signal processing
A clustering-based method for identifying and tracking squall lines
A multi-instrument fuzzy logic boundary-layer-top detection algorithm
Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models
Scale separation for gravity wave analysis from 3D temperature observations in the mesosphere and lower thermosphere (MLT) region
Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation
Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms
Noise filtering options for conically scanning Doppler lidar measurements with low pulse accumulation
Comparative experimental validation of microwave hyperspectral atmospheric soundings in clear-sky conditions
GNSS-RO Residual Ionospheric Error (RIE): A New Method and Assessment
Measuring rainfall using microwave links: the influence of temporal sampling
Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground
Mid-Atlantic Nocturnal Low-Level Jet Characteristics: A machine learning analysis of radar wind profiles
The High lAtitude sNowfall Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS): a new algorithm for snowfall retrieval at high latitudes
Next-generation radiance unfiltering process for the Clouds and the Earth's Radiant Energy System instrument
Improved rain event detection in commercial microwave link time series via combination with MSG SEVIRI data
A directional surface reflectance climatology determined from TROPOMI observations
Investigation of gravity waves using measurements from a sodium temperature/wind lidar operated in multi-direction mode
An improved BRDF hotspot model and its use in VLIDORT for studying the impact of atmospheric scattering on hotspot directional signatures in the atmosphere
A multi-decadal time series of upper stratospheric temperature profiles from Odin-OSIRIS limb-scattered spectra
Observations of Tall-Building Wakes Using a Scanning Doppler Lidar
CALOTRITON: a convective boundary layer height estimation algorithm from ultra-high-frequency (UHF) wind profiler data
Enhancing consistency of microphysical properties of precipitation across the melting layer in dual-frequency precipitation radar data
Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer
Forward operator for polarimetric radio occultation measurements
Assessing atmospheric gravity wave spectra in the presence of observational gaps
Endrit Shehaj, Stephen Leroy, Kerri Cahoy, Alain Geiger, Laura Crocetti, Gregor Moeller, Benedikt Soja, and Markus Rothacher
Atmos. Meas. Tech., 18, 57–72, https://doi.org/10.5194/amt-18-57-2025, https://doi.org/10.5194/amt-18-57-2025, 2025
Short summary
Short summary
This work investigates whether machine learning (ML) can offer an alternative to existing methods to map radio occultation (RO) products, allowing the extraction of information not visible in direct observations. ML can further improve the results of Bayesian interpolation, a state-of-the-art method to map RO observations. The results display improvements in horizontal and temporal domains, at heights ranging from the planetary boundary layer up to the lower stratosphere, and for all seasons.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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).
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-155, https://doi.org/10.5194/amt-2024-155, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
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 framework for the examination. Our study provides guidance in the performance, uncertainties and optimisation of the methods, focusing mainly on accuracy and robustness.
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
Short summary
Short summary
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
Short summary
Short summary
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).
Thiruvengadam Padmanabhan, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-117, https://doi.org/10.5194/amt-2024-117, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study explores how the joints in a weather radar's protective cover affect its measurements. We developed a new method to correct these errors, improving the accuracy of the radar's data. Our method was tested during an intense cyclone on Reunion Island, demonstrating significant improvements in data accuracy. This research is crucial for enhancing weather predictions and understanding, particularly in challenging terrains.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, https://doi.org/10.5194/amt-17-3605-2024, 2024
Short summary
Short summary
This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
Short summary
Short summary
This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024, https://doi.org/10.5194/amt-17-3377-2024, 2024
Short summary
Short summary
We have created a new method to better identify enhanced features in radar data from winter storms. Unlike the clear-cut features seen in warm-season storms, features in winter storms are often fuzzier with softer edges. Our technique is unique because it uses two adaptive thresholds that change based on the background radar values. It can identify both strong and subtle features in the radar data and takes into account uncertainties in the detection process.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech., 17, 3187–3217, https://doi.org/10.5194/amt-17-3187-2024, https://doi.org/10.5194/amt-17-3187-2024, 2024
Short summary
Short summary
Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed both by means of assessing the filter results and by comparing retrieved turbulence variables versus independent measurements.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
EGUsphere, https://doi.org/10.5194/egusphere-2024-1045, https://doi.org/10.5194/egusphere-2024-1045, 2024
Short summary
Short summary
This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground-airborne synergy between the two instruments yielded optimal-sounding results.
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae H. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-51, https://doi.org/10.5194/amt-2024-51, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Radio occultation (RO) observations play an important role in monitoring climate changes and numerical weather forecasts. The residual ionospheric error (RIE) in RO measurements is critical to accurately retrieve atmospheric temperature and refractivity. This study shows that RIF impacts on temperature analysis are mainly confined to the polar stratosphere with amplitude of 1–4 K. These results further highlight the need for RO RIE correction in the modern data assimilation systems.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
Short summary
Short summary
Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, https://doi.org/10.5194/amt-17-2539-2024, 2024
Short summary
Short summary
This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail on the ground to estimate hail size distributions (HSDs). Traditional hail sensors' limited areas complicate the full HSD retrieval. The HSD of a supercell event on 20 June 2021 is retrieved and contains > 18 000 hailstones. The HSD is compared to automatic hail sensor measurements and those of weather-radar-based MESHS. Investigations into ground hail melting are performed by five drone flights.
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-37, https://doi.org/10.5194/amt-2024-37, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This paper introduces a machine-learning approach to automatically isolate Nocturnal Low-Level Jets (NLLJs) using observations from Maryland’s Radar Wind Profiler (RWP) network. Initial findings identify 90 south-westerly NLLJs from May to September 2017–2021, showcasing core parameters and jet morphology. The research aims to establish a foundation for understanding the formation mechanisms of Mid-Atlantic NLLJs and their impact on air quality.
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech., 17, 2195–2217, https://doi.org/10.5194/amt-17-2195-2024, https://doi.org/10.5194/amt-17-2195-2024, 2024
Short summary
Short summary
The paper describes a new machine-learning-based snowfall retrieval algorithm for Advanced Technology Microwave Sounder observations developed to retrieve high-latitude snowfall events. The main novelty of the approach is the radiometric characterization of the background surface at the time of the overpass, which is ancillary to the retrieval process. The algorithm shows a unique capability to retrieve snowfall in the environmental conditions typical of high latitudes.
Lusheng Liang, Wenying Su, Sergio Sejas, Zachary Eitzen, and Norman G. Loeb
Atmos. Meas. Tech., 17, 2147–2163, https://doi.org/10.5194/amt-17-2147-2024, https://doi.org/10.5194/amt-17-2147-2024, 2024
Short summary
Short summary
This paper describes an updated process to obtain unfiltered radiation from CERES satellite instruments by incorporating the most recent developments in radiative transfer modeling and ancillary input datasets (e.g., realistic representation of land surface radiation and climatology of surface temperatures and aerosols) during the past 20 years. The resulting global mean of instantaneous SW and LW fluxes is changed by less than 0.5 W m−2 with regional differences as large as 2.0 W m−2.
Maximilian Graf, Andreas Wagner, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, Harald Kunstmann, and Christian Chwala
Atmos. Meas. Tech., 17, 2165–2182, https://doi.org/10.5194/amt-17-2165-2024, https://doi.org/10.5194/amt-17-2165-2024, 2024
Short summary
Short summary
Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is a crucial processing step. We investigate the usage of rainfall data from MSG SEVIRI for this task, compare this approach with existing methods, and introduce a novel combined approach. The results show certain advantages for SEVIRI-based methods, particularly for CMLs where existing methods perform poorly. Our novel combination yields the best performance.
Lieuwe G. Tilstra, Martin de Graaf, Victor J. H. Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, https://doi.org/10.5194/amt-17-2235-2024, 2024
Short summary
Short summary
This paper introduces a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by TROPOMI on the Sentinel-5 Precursor satellite. The database contains monthly fields of DLER for 21 wavelength bands at a relatively high spatial resolution of 0.125 by 0.125 degrees. The anisotropy of the surface reflection is handled by parameterisation of the viewing angle dependence.
Bing Cao and Alan Z. Liu
Atmos. Meas. Tech., 17, 2123–2146, https://doi.org/10.5194/amt-17-2123-2024, https://doi.org/10.5194/amt-17-2123-2024, 2024
Short summary
Short summary
A narrow-band sodium lidar measures atmospheric waves but is limited to vertical variations. We propose to utilize phase shifts among observations from different laser beams to derive horizontal wave information. Two gravity wave packets were identified by this method. Both waves were found to interact with thin evanescent layers, partially reflected, but transmitted energy to higher altitudes. The method can detect more medium-frequency gravity waves for similar lidar systems worldwide.
Xiaozhen Xiong, Xu Liu, Robert Spurr, Ming Zhao, Qiguang Yang, Wan Wu, and Liqiao Lei
Atmos. Meas. Tech., 17, 1965–1978, https://doi.org/10.5194/amt-17-1965-2024, https://doi.org/10.5194/amt-17-1965-2024, 2024
Short summary
Short summary
The term “hotspot” refers to the sharp increase in reflectance occurring when incident (solar) and reflected (viewing) directions coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications, but current models typically require large values of computations to represent the hotspot accurately. This paper provides a numerically improved hotspot BRDF model that converges much faster and is used in VLIDORT.
Daniel Zawada, Kimberlee Dubé, Taran Warnock, Adam Bourassa, Susann Tegtmeier, and Douglas Degenstein
Atmos. Meas. Tech., 17, 1995–2010, https://doi.org/10.5194/amt-17-1995-2024, https://doi.org/10.5194/amt-17-1995-2024, 2024
Short summary
Short summary
There remain large uncertainties in long-term changes of stratospheric–atmospheric temperatures. We have produced a time series of more than 20 years of satellite-based temperature measurements from the OSIRIS instrument in the upper–middle stratosphere. The dataset is publicly available and intended to be used for a better understanding of changes in stratospheric temperatures.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
EGUsphere, https://doi.org/10.5194/egusphere-2024-937, https://doi.org/10.5194/egusphere-2024-937, 2024
Short summary
Short summary
A doppler lidar was placed in highly built-up area in London to measure wakes from tall buildings during a period of one year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Alban Philibert, Marie Lothon, Julien Amestoy, Pierre-Yves Meslin, Solène Derrien, Yannick Bezombes, Bernard Campistron, Fabienne Lohou, Antoine Vial, Guylaine Canut-Rocafort, Joachim Reuder, and Jennifer K. Brooke
Atmos. Meas. Tech., 17, 1679–1701, https://doi.org/10.5194/amt-17-1679-2024, https://doi.org/10.5194/amt-17-1679-2024, 2024
Short summary
Short summary
We present a new algorithm, CALOTRITON, for the retrieval of the convective boundary layer depth with ultra-high-frequency radar measurements. CALOTRITON is partly based on the principle that the top of the convective boundary layer is associated with an inversion and a decrease in turbulence. It is evaluated using ceilometer and radiosonde data. It is able to qualify the complexity of the vertical structure of the low troposphere and detect internal or residual layers.
Kamil Mroz, Alessandro Battaglia, and Ann M. Fridlind
Atmos. Meas. Tech., 17, 1577–1597, https://doi.org/10.5194/amt-17-1577-2024, https://doi.org/10.5194/amt-17-1577-2024, 2024
Short summary
Short summary
In this study, we examine the extent to which radar measurements from space can inform us about the properties of clouds and precipitation. Surprisingly, our analysis showed that the amount of ice turning into rain was lower than expected in the current product. To improve on this, we came up with a new way to extract information about the size and concentration of particles from radar data. As long as we use this method in the right conditions, we can even estimate how dense the ice is.
Volker Wulfmeyer, Christoph Senff, Florian Späth, Andreas Behrendt, Diego Lange, Robert M. Banta, W. Alan Brewer, Andreas Wieser, and David D. Turner
Atmos. Meas. Tech., 17, 1175–1196, https://doi.org/10.5194/amt-17-1175-2024, https://doi.org/10.5194/amt-17-1175-2024, 2024
Short summary
Short summary
A simultaneous deployment of Doppler, temperature, and water-vapor lidar systems is used to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of weather forecast and climate models.
Daisuke Hotta, Katrin Lonitz, and Sean Healy
Atmos. Meas. Tech., 17, 1075–1089, https://doi.org/10.5194/amt-17-1075-2024, https://doi.org/10.5194/amt-17-1075-2024, 2024
Short summary
Short summary
Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a new type of GNSS observations that can detect heavy precipitation along the ray path between the emitter and receiver satellites. As a first step towards using these observations in numerical weather prediction (NWP), we developed a computer code that simulates GNSS-PRO observations from forecast fields produced by an NWP model. The quality of the developed simulator is evaluated with a number of case studies.
Mohamed Mossad, Irina Strelnikova, Robin Wing, and Gerd Baumgarten
Atmos. Meas. Tech., 17, 783–799, https://doi.org/10.5194/amt-17-783-2024, https://doi.org/10.5194/amt-17-783-2024, 2024
Short summary
Short summary
This numerical study addresses observational gaps' impact on atmospheric gravity wave spectra. Three methods, fast Fourier transform (FFT), generalized Lomb–Scargle periodogram (GLS), and Haar structure function (HSF), were tested on synthetic data. HSF is best for spectra with negative slopes. GLS excels for flat and positive slopes and identifying dominant frequencies. Accurately estimating these aspects is crucial for understanding gravity wave dynamics and energy transfer in the atmosphere.
Cited articles
Bringi, V. N. and Chandrasekar, V.: Polarimetric Doppler Weather Radar,
Cambridge University Press, Cambridge, UK, 2001.
Cho, Y. H., Lee, G., Kim, K. E., and Zawadzki, I.: Identification and
Removal of Ground Echoes and Anomalous Propagation Using the Characteristics
of Radar Echoes, J. Atmos. Ocean. Tech., 23, 1206–1222, 2006.
Crum, T. D. and Alberty, R. L.: The WSR-88D and the WSR-88D Operational
Support Facility, B. Am. Meteorol. Soc., 74, 1669–1688, 1993.
Doswell III, C. A., Davies-Jones, R., and Keller, D. L.: On summary measures
of skill in rare event forecasting based on contingency tables, Weather Forecast., 5, 576–585, 1990.
Doviak, R. J. and Zrnić, D. S.: Doppler radar and weather observations,
Academic Press, Mineola, NY, 2nd edn., Dover Publications, Mineola, N.Y., 2006.
Fang, M., Doviak, R. J., and Melnikov, V.: Spectrum Width Measured by
WSR-88D: Error Sources and Statistics of Various Weather Phenomena, J.
Atmos. Ocean. Tech., 21, 888–904, 2004.
Giangrande, S. E. and Ryzhkov, A. V.: Estimation of Rainfall Based on the
Results of Polarimetric Echo Classification, J. Appl. Meteorol. Clim., 47, 2445–2462, 2008.
Giangrande, S. E., Krause, J., and Ryzhkov, A. V: Automatic detection of the
melting layer with a polarimetric prototype of the WSR-88D radar, J. Appl. Meteorol. Clim., 47, 1354–1364, 2008.
Gourley, J. J., Tabary, P., and Chatelet, J. P. D.: Data Quality of the
Meteo-France C-Band Polarimetric Radar, J. Atmos. Ocean. Tech., 23, 1340–1356, 2006.
Gourley, J. J., Tabary, P., and Parent du Chatelet, J.: A Fuzzy Logic
Algorithm for the Separation of Precipitating from Nonprecipitating Echoes
Using Polarimetric Radar Observations, J. Atmos. Ocean. Tech., 24, 1439–1451, 2007.
Hubbert, J. C., Dixon, M., Ellis, S. M., and Meymaris, G.: Weather radar
ground clutter. Part I: Identification, modeling, and simulation, J. Atmos. Ocean. Tech., 26, 1165–1180, 2009a.
Hubbert, J. C., Dixon, M., and Ellis, S. M.: Weather radar ground clutter.
Part II: Real-time identification and filtering, J. Atmos. Ocean. Tech., 26, 1181–1197, 2009b.
Islam, T., Rico-Ramirez, M. A., Han, D., and Srivastava, P. K.: Artificial
intelligence techniques for clutter identification with polarimetric radar
signatures, Atmos. Res., 109–110, 95–113, 2012.
Jung, Y., Zhang, G., and Xue, M.: Assimilation of simulated polarimetric
radar data for a convective storm using the ensemble Kalman filter. Part I:
Observation Operators for Reflectivity and Polarimetric Variables, Mon.
Weather Rev., 136, 2228–2245, 2008a.
Jung, Y., Zhang, G., and Xue, M.: Assimilation of simulated polarimetric
radar data for a convective storm using the ensemble Kalman filter. Part II:
Impact of polarimetric data on storm analysis, Mon. Weather Rev., 136,
2246–2260, 2008b.
Krause, J. M.: A Simple Algorithm to Discriminate between Meteorological and
Nonmeteorological Radar Echoes, J. Atmos. Ocean. Tech., 33, 1875–1885, 2016.
Kumjian, M. R.: Principles and Applications of Dual-Polarization Weather
Radar. Part I: Description of the Polarimetric Radar Variables, Journal of
Operational Meteorology, 1, 226–242, 2013a.
Kumjian, M. R.: Principles and Applications of Dual-Polarization Weather
Radar. Part II: Warm-and Cold-Season Applications, Journal of Operational
Meteorology, 1, 243–264, 2013b.
Kumjian, M. R.: Principles and Applications of Dual-Polarization Weather
Radar. Part III: Artifacts, Journal of Operational Meteorology, 1, 265–274,
2013c.
Lakshmanan, V., Fritz, A., Smith, T., Hondl, K., and Stumpf, G.: An
Automated Technique to Quality Control Radar Reflectivity Data, J. Appl. Meteorol. Clim., 46, 288–305, 2007.
Lakshmanan, V., Karstens, C., Krause, J., and Tang, L.: Quality Control of
Weather Radar Data Using Polarimetric Variables, J. Atmos. Ocean. Tech., 31, 1234–1249, 2014.
Lakshmanan, V., Karstens, C., Krause, J., Elmore, K., Ryzhkov, A., and
Berkseth, S.: Which Polarimetric Variables Are Important for
Weather/No-Weather Discrimination?, J. Atmos. Ocean. Tech., 32, 1209–1223, 2015.
Lin, P. F., Chang, P. L., Jou, J. D., Wilson, J. W., and Roberts, R. D.:
Objective Prediction of Warm Season Afternoon Thunderstorms in Northern
Taiwan Using a Fuzzy Logic Approach, Weather Forecast., 27, 1178–1197, 2012.
Liu, H. and Chandrasekar, V.: Classification of hydrometeors based on
polarimetric radar measurements: Development of fuzzy logic and neuro-fuzzy
systems, and in situ verification, J. Atmos. Ocean. Tech., 17, 140–164,
2000.
Park, H., Ryzhkov, A. V., Zrnic, D. S., and Kim, K. E.: The Hydrometeor
Classification Algorithm for the Polarimetric WSR-88D: Description and
Application to an MCS, Weather Forecast., 24, 730–748, 2009.
Rico-Ramirez, M. A. and Cluckie, I. D.: Classification of Ground Clutter
and Anomalous Propagation Using Dual-Polarization Weather Radar, IEEE
T. Geosci. Remote, 46, 1892–1904, 2008.
Ryzhkov, A. V., Giangrande, S. E., Melnikov, V. M., and Schuur, T. J.:
Calibration Issues of Dual-Polarization Radar Measurements, J. Atmos. Ocean. Tech., 22, 1138–1155, 2005.
Schuur, T., Ryzhkov, A., Heinselman, P., Zrnic, D., Burgess, D., and
Scharfenberg, K.: Observations and classification of echoes with the
polarimetric WSR-88D radar, Report of the National Severe Storms Laboratory,
Norman, OK, 73069, 46 pp., 2003.
Stumpf, G. J., Witt, A., Mitchell, D. W., Spencer, P. L., and Burgess, D.
W.: The National Severe Storms Laboratory Mesocyclone Detection Algorithm
for the WSR-88D, Weather Forecast., 13, 304–326, 1998.
Tang, L., Zhang, J., Langston, C., Krause, J., Howard, K., and Lakshmanan,
V.: A Physically Based Precipitation-Nonprecipitation Radar Echo Classifier
Using Polarimetric and Environmental Data in a Real-Time National System,
Weather Forecast., 29, 1106-1119, 2014.
Torres, S. M. and Warde, D. A.: Ground clutter mitigation for weather
radars using the autocorrelation spectral density, J. Atmos. Ocean. Tech., 31, 2049–2066, 2014.
Wang, Y. T. and Chandrasekar, V.: Algorithm for estimation of the specific
differential phase, J. Atmos. Ocean. Tech., 26, 2565–2578, 2009.
Wilson, J. W., Weckwerth, T. M., Vivekanandan, J., Wakimoto, R. M., and
Russell, R. W.: Boundary Layer Clear-Air Radar Echoes: Origin of Echoes and
Accuracy of Derived Winds, J. Atmos. Ocean. Tech., 11, 1184–1206, 1994.
Zhang, J. and Qi, Y. C.: A real-time algorithm for the correction of
brightband effects in radar-derived QPE, J. Hydrometeorol., 11, 1157–1171, 2010.
Zhang, J., Langston, C., and Howard, K.: Brightband Identification Based on
Vertical Profiles of Reflectivity from the WSR-88D, J. Atmos. Ocean. Tech., 25, 1859–1872, 2008.
Zhang, J., Howard, K., Langston, C., Vasiloff, S., Kaney, B., Arthur, A.,
Cooten, S. V., Kelleher, K., Kitzmiller, D., and Feng, D.: National Mosaic
and Multi-Sensor QPE (NMQ) System: Description, Results, and Future Plans,
B. Am. Meteorol. Soc., 92, 1321–1338, 2011.
Zrnić, D. S., Ryzhkov, A., Straka, J., Liu, Y., and Vivekanandan, J.:
Testing a Procedure for Automatic Classification of Hydrometeor Types,
J. Atmos. Ocean. Tech., 18, 892–913, 2001.
Zrnić, D. S., Melnikov, V. M., and Ryzhkov, A. V.: Correlation Coefficients between Horizontally and Vertically Polarized Returns from Ground Clutter, J. Atmos. Ocean. Tech., 23, 381–394, 2006.
Short summary
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...
