Articles | Volume 16, issue 23
https://doi.org/10.5194/amt-16-5811-2023
© Author(s) 2023. 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-16-5811-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Dec 2023
Research article |
| 05 Dec 2023
| 05 Dec 2023
Thundercloud structures detected and analyzed based on coherent Doppler wind lidar
Kenan Wu
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
Tianwen Wei
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China
Jinlong Yuan
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China
Hefei National Laboratory for Physical Sciences at the Microscale, Hefei 230026, China
Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China
Aerosol-Cloud-Precipitation Key Laboratory, NUIST, CMA, Beijing 100081, China
Xin Huang
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
Gaopeng Lu
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
Yunpeng Zhang
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
Feifan Liu
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
Baoyou Zhu
School of Earth and Space Science, University of Science and Technology of China, Hefei 230026, China
Weidong Ding
Anhui Meteorological Observatory, Hefei 230031, China
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Tianwen Wei, Mengya Wang, Kenan Wu, Jinlong Yuan, Haiyun Xia, and Simone Lolli
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-178, https://doi.org/10.5194/amt-2024-178, 2024
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This study uses three years of wind lidar measurements to investigate the dynamics of the urban PBL in Hefei, China. Results show that nocturnal low-level jets occur most frequently in spring and intensify in summer, significantly increasing turbulence and shear intensity near the ground level, especially during the night. Cloud cover raises the MLH by around 100 m during the night due to the greenhouse effect and decreases it by up to 200 m in the afternoon by obstructing solar radiation.
Pu Jiang, Jinlong Yuan, Kenan Wu, Lu Wang, and Haiyun Xia
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-288, https://doi.org/10.5194/amt-2021-288, 2021
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To analyse the atmospheric turbulence in high resolution, we proposed a new method by combining the advantages of two remote sensing instruments. A contrastive experiment was conducted horizontally to verify the method. Based on the result, we obtained and analyzed the continuous Cn2 and other turbulence profiles with high temporal and spatial resolution simultaneously. It is significant for studying the complex and fast-changing atmospheric environment.
Tianwen Wei, Mengya Wang, Kenan Wu, Jinlong Yuan, Haiyun Xia, and Simone Lolli
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This study uses three years of wind lidar measurements to investigate the dynamics of the urban PBL in Hefei, China. Results show that nocturnal low-level jets occur most frequently in spring and intensify in summer, significantly increasing turbulence and shear intensity near the ground level, especially during the night. Cloud cover raises the MLH by around 100 m during the night due to the greenhouse effect and decreases it by up to 200 m in the afternoon by obstructing solar radiation.
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Atmos. Chem. Phys., 24, 10947–10963, https://doi.org/10.5194/acp-24-10947-2024, https://doi.org/10.5194/acp-24-10947-2024, 2024
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The cold downhill airflow of the Tibetan Plateau leading to the low-level jet weakens the height and intensity of the inversion layer, which reduces the energy demand for the broken inversion layer. The low-level jet causes dust aerosols to accumulate near the ground. The material conditions for the development of the desert atmospheric boundary layer can be quickly transformed into thermal conditions.
Shican Qiu, Zhe Wang, Gaopeng Lu, Zeren Zhima, Willie Soon, Victor Manuel Velasco Herrera, and Peng Ju
Atmos. Chem. Phys., 24, 8519–8527, https://doi.org/10.5194/acp-24-8519-2024, https://doi.org/10.5194/acp-24-8519-2024, 2024
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We focus on the interactions among TLEs, lightning, and the ionospheric electric field. The SNR of the Schumann resonance at the first and second modes dropped during the TLEs. A significant enhancement of the energy in ULF occurred. Distinct lightning whistler waves were found in the VLF band. Our results indicate that the observations of electric fields from the satellite could possibly be utilized to monitor lower-atmospheric lightning and its impact on the space environment.
Nan Sun, Gaopeng Lu, and Yunfei Fu
Atmos. Chem. Phys., 24, 7123–7135, https://doi.org/10.5194/acp-24-7123-2024, https://doi.org/10.5194/acp-24-7123-2024, 2024
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Microphysical characteristics of convective overshooting are essential but poorly understood, and we examine them by using the latest data. (1) Convective overshooting events mainly occur over NC (Northeast China) and northern MEC (Middle and East China). (2) Radar reflectivity of convective overshooting over NC accounts for a higher proportion below the zero level, while the opposite is the case for MEC and SC (South China). (3) Droplets of convective overshooting are large but sparse.
Lian Zong, Yuanjian Yang, Haiyun Xia, Meng Gao, Zhaobin Sun, Zuofang Zheng, Xianxiang Li, Guicai Ning, Yubin Li, and Simone Lolli
Atmos. Chem. Phys., 22, 6523–6538, https://doi.org/10.5194/acp-22-6523-2022, https://doi.org/10.5194/acp-22-6523-2022, 2022
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Heatwaves (HWs) paired with higher ozone (O3) concentration at surface level pose a serious threat to human health. Taking Beijing as an example, three unfavorable synoptic weather patterns were identified to dominate the compound HW and O3 pollution events. Under the synergistic stress of HWs and O3 pollution, public mortality risk increased, and synoptic patterns and urbanization enhanced the compound risk of events in Beijing by 33.09 % and 18.95 %, respectively.
Dawei Tang, Tianwen Wei, Jinlong Yuan, Haiyun Xia, and Xiankang Dou
Atmos. Meas. Tech., 15, 2819–2838, https://doi.org/10.5194/amt-15-2819-2022, https://doi.org/10.5194/amt-15-2819-2022, 2022
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During 11–20 March 2020, three aerosol transport events were investigated by a lidar system and an online bioaerosol detection system in Hefei, China.
Observation results reveal that the events not only contributed to high particulate matter pollution but also to the transport of external bioaerosols, resulting in changes in the fraction of fluorescent biological aerosol particles.
This detection method improved the time resolution and provided more parameters for aerosol detection.
Pu Jiang, Jinlong Yuan, Kenan Wu, Lu Wang, and Haiyun Xia
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-288, https://doi.org/10.5194/amt-2021-288, 2021
Revised manuscript not accepted
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To analyse the atmospheric turbulence in high resolution, we proposed a new method by combining the advantages of two remote sensing instruments. A contrastive experiment was conducted horizontally to verify the method. Based on the result, we obtained and analyzed the continuous Cn2 and other turbulence profiles with high temporal and spatial resolution simultaneously. It is significant for studying the complex and fast-changing atmospheric environment.
Shican Qiu, Ning Wang, Willie Soon, Gaopeng Lu, Mingjiao Jia, Xingjin Wang, Xianghui Xue, Tao Li, and Xiankang Dou
Atmos. Chem. Phys., 21, 11927–11940, https://doi.org/10.5194/acp-21-11927-2021, https://doi.org/10.5194/acp-21-11927-2021, 2021
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Our results suggest that lightning strokes would probably influence the ionosphere and thus give rise to the occurrence of a sporadic sodium layer (NaS), with the overturning of the electric field playing an important role. Model simulation results show that the calculated first-order rate coefficient could explain the efficient recombination of Na+→Na in this NaS case study. A conjunction between the lower and upper atmospheres could be established by these inter-connected phenomena.
Mingjiao Jia, Jinlong Yuan, Chong Wang, Haiyun Xia, Yunbin Wu, Lijie Zhao, Tianwen Wei, Jianfei Wu, Lu Wang, Sheng-Yang Gu, Liqun Liu, Dachun Lu, Rulong Chen, Xianghui Xue, and Xiankang Dou
Atmos. Chem. Phys., 19, 15431–15446, https://doi.org/10.5194/acp-19-15431-2019, https://doi.org/10.5194/acp-19-15431-2019, 2019
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Gravitational waves (GWs) with periods ranging from 10 to 30 min over 10 h and 20 wave cycles are detected within a 2 km height in the atmospheric boundary layer (ABL) by a coherent Doppler wind lidar. Observations and computational fluid dynamics (CFD) simulations lead to a conclusion that the GWs are excited by the wind shear of a low-level jet under the condition of light horizontal wind. The GWs are trapped in the ABL due to a combination of thermal and Doppler ducts.
Chong Wang, Mingjiao Jia, Haiyun Xia, Yunbin Wu, Tianwen Wei, Xiang Shang, Chengyun Yang, Xianghui Xue, and Xiankang Dou
Atmos. Meas. Tech., 12, 3303–3315, https://doi.org/10.5194/amt-12-3303-2019, https://doi.org/10.5194/amt-12-3303-2019, 2019
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To investigate the relationship between BLH and air pollution under different conditions, a compact micro-pulse lidar integrating both direct-detection lidar and coherent Doppler wind lidar is built. Evolution of atmospheric boundary layer height (BLH), aerosol layer and fine structure in cloud base are well retrieved. Negative correlation exists between BLH and PM2.5. Different trends show that the relationship between PM2.5 and BLH should be considered in different boundary layer categories.
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Consideration of the cloud motion for aircraft-based stereographically derived cloud geometry and cloud top heights
Exploring the characteristics of Fengyun-4A Advanced Geostationary Radiation Imager (AGRI) visible reflectance using the China Meteorological Administration Mesoscale (CMA-MESO) forecasts and its implications for data assimilation
Validating global horizontal irradiance retrievals from Meteosat SEVIRI at increased spatial resolution against a dense network of ground-based observations
Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES
Synergistic approach of frozen hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework
An evaluation of microphysics in a numerical model using Doppler velocity measured by ground-based radar for application to the EarthCARE satellite
Investigation of cirrus cloud properties in the tropical tropopause layer using high-altitude limb-scanning near-IR spectroscopy during NASA-ATTREX
Comparing FY-2F/CTA products to ground-based manual total cloud cover observations in Xinjiang under complex underlying surfaces and different weather conditions
Model-based evaluation of cloud geometry and droplet size retrievals from two-dimensional polarized measurements of specMACS
Improved RepVGG ground-based cloud image classification with attention convolution
An intercomparison of EarthCARE cloud, aerosol, and precipitation retrieval products
First results of cloud retrieval from the Geostationary Environmental Monitoring Spectrometer
Assessing Arctic low-level clouds and precipitation from above – a radar perspective
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The Education and Research 3D Radiative Transfer Toolbox (EaR3T) – towards the mitigation of 3D bias in airborne and spaceborne passive imagery cloud retrievals
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Consistency test of precipitating ice cloud retrieval properties obtained from the observations of different instruments operating at Dome C (Antarctica)
Sizing ice hydrometeor populations using the dual-wavelength radar ratio
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Horizontal geometry of trade wind cumuli – aircraft observations from a shortwave infrared imager versus a radar profiler
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Atmos. Meas. Tech., 17, 6659–6675, https://doi.org/10.5194/amt-17-6659-2024, https://doi.org/10.5194/amt-17-6659-2024, 2024
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Satellite remote sensing retrievals of cloud droplet size are used to understand clouds and their interactions with aerosols and radiation but require many simplifying assumptions. Evaluation of these retrievals typically is done by comparing against direct measurements of droplets from airborne cloud probes. This paper details an evaluation of proxy airborne remote sensing droplet size retrievals against several cloud probes and explores the impact of key assumptions on retrieval agreement.
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Atmos. Meas. Tech., 17, 3567–3582, https://doi.org/10.5194/amt-17-3567-2024, https://doi.org/10.5194/amt-17-3567-2024, 2024
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In cloudy situations, infrared and microwave observations are complementary, with infrared being sensitive to cloud tops and microwave sensitive to precipitation. However, infrared satellite observations are underused. This study aims to quantify if the inconsistencies in the modelling of clouds prevent the use of cloudy infrared observations in the process of weather forecasting. It shows that the synergistic use of infrared and microwave observations is beneficial, despite inconsistencies.
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Atmos. Meas. Tech., 17, 3455–3466, https://doi.org/10.5194/amt-17-3455-2024, https://doi.org/10.5194/amt-17-3455-2024, 2024
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The advantage of the use of Doppler velocity in the categorization of the hydrometeors is that Doppler velocities suffer less impact from the attenuation of rain and wet attenuation on an antenna. The ground Cloud Profiling Radar observation of the radar reflectivity for the precipitation case is limited because of wet attenuation on an antenna. We found the main contribution to Doppler velocities is the terminal velocity of hydrometeors by analysis of simulation results.
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Atmos. Meas. Tech., 17, 2367–2385, https://doi.org/10.5194/amt-17-2367-2024, https://doi.org/10.5194/amt-17-2367-2024, 2024
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Cirrus clouds are poorly understood components of the climate system, in part due to the challenge of observing thin, sub-visible ice clouds. We address this issue with a new observational approach that uses the remote sensing of near-infrared ice water absorption features from a high-altitude aircraft. We describe the underlying principle of this approach and present a new procedure to retrieve ice concentration in cirrus clouds. Our retrievals compare well with in situ observations.
Shuai Li, Hua Zhang, Yonghang Chen, Zhili Wang, Xiangyu Li, Yuan Li, and Yuanyuan Xue
Atmos. Meas. Tech., 17, 2011–2024, https://doi.org/10.5194/amt-17-2011-2024, https://doi.org/10.5194/amt-17-2011-2024, 2024
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Lea Volkmer, Veronika Pörtge, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 17, 1703–1719, https://doi.org/10.5194/amt-17-1703-2024, https://doi.org/10.5194/amt-17-1703-2024, 2024
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Three-dimensional radiative transfer simulations are used to evaluate the performance of retrieval algorithms in the derivation of cloud geometry (cloud top heights) and cloud droplet size distributions from two-dimensional polarized radiance measurements of the airborne spectrometer of the Munich Aerosol Cloud Scanner. The cloud droplet size distributions are derived for the effective radius and variance. The simulations are based on cloud data from highly resolved large-eddy simulations.
Chaojun Shi, Leile Han, Ke Zhang, Hongyin Xiang, Xingkuan Li, Zibo Su, and Xian Zheng
Atmos. Meas. Tech., 17, 979–997, https://doi.org/10.5194/amt-17-979-2024, https://doi.org/10.5194/amt-17-979-2024, 2024
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This article mainly studies the problem of ground cloud classification and significantly improves the accuracy of ground cloud classification by applying an improved deep-learning method. The research results show that the method proposed in this article has a significant impact on the classification results of ground cloud images. These conclusions have important implications for providing new insights and future research directions in the field of ground cloud classification.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Bo-Ram Kim, Gyuyeon Kim, Minjeong Cho, Yong-Sang Choi, and Jhoon Kim
Atmos. Meas. Tech., 17, 453–470, https://doi.org/10.5194/amt-17-453-2024, https://doi.org/10.5194/amt-17-453-2024, 2024
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This study introduces the GEMS cloud algorithm and validates its results using data from GEMS and other environmental satellites. The GEMS algorithm is able to detect the lowest cloud heights among the four satellites, and its effective cloud fraction and cloud centroid pressure are well reflected in the retrieval results. The study highlights the algorithm's usefulness in correcting errors in trace gases caused by clouds in the East Asian region.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes
Atmos. Meas. Tech., 16, 3531–3546, https://doi.org/10.5194/amt-16-3531-2023, https://doi.org/10.5194/amt-16-3531-2023, 2023
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In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.
Kameswara S. Vinjamuri, Marco Vountas, Luca Lelli, Martin Stengel, Matthew D. Shupe, Kerstin Ebell, and John P. Burrows
Atmos. Meas. Tech., 16, 2903–2918, https://doi.org/10.5194/amt-16-2903-2023, https://doi.org/10.5194/amt-16-2903-2023, 2023
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Clouds play an important role in Arctic amplification. Cloud data from ground-based sites are valuable but cannot represent the whole Arctic. Therefore the use of satellite products is a measure to cover the entire Arctic. However, the quality of such cloud measurements from space is not well known. The paper discusses the differences and commonalities between satellite and ground-based measurements. We conclude that the satellite dataset, with a few exceptions, can be used in the Arctic.
Hong Chen, K. Sebastian Schmidt, Steven T. Massie, Vikas Nataraja, Matthew S. Norgren, Jake J. Gristey, Graham Feingold, Robert E. Holz, and Hironobu Iwabuchi
Atmos. Meas. Tech., 16, 1971–2000, https://doi.org/10.5194/amt-16-1971-2023, https://doi.org/10.5194/amt-16-1971-2023, 2023
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We introduce the Education and Research 3D Radiative Transfer Toolbox (EaR3T) and propose a radiance self-consistency approach for quantifying and mitigating 3D bias in legacy airborne and spaceborne imagery retrievals due to spatially inhomogeneous clouds and surfaces.
Kumar Abhijeet, Thota Narayana Rao, Nidamanuri Rama Rao, and Kasimahanthi Amar Jyothi
Atmos. Meas. Tech., 16, 871–888, https://doi.org/10.5194/amt-16-871-2023, https://doi.org/10.5194/amt-16-871-2023, 2023
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The present study focuses on retrieving and validating raindrop size distribution (DSD) relations for monsoonal rainfall, which are required for retrieving DSDs with polarimetric radar measurements. The seasonal variation in DSD is quite large and significant, and as a result the coefficients also vary considerably between the seasons and from those existing elsewhere. Among the existing DSD methods, the N-gamma method performs better than the other methods.
Gianluca Di Natale, David D. Turner, Giovanni Bianchini, Massimo Del Guasta, Luca Palchetti, Alessandro Bracci, Luca Baldini, Tiziano Maestri, William Cossich, Michele Martinazzo, and Luca Facheris
Atmos. Meas. Tech., 15, 7235–7258, https://doi.org/10.5194/amt-15-7235-2022, https://doi.org/10.5194/amt-15-7235-2022, 2022
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In this paper, we describe a new approach to test the consistency of the precipitating ice cloud optical and microphysical properties in Antarctica, Dome C, retrieved from hyperspectral measurements in the far-infrared, with the reflectivity detected by a co-located micro rain radar operating at 24 GHz. The retrieved ice crystal sizes were found in accordance with the direct measurements of an optical imager, also installed at Dome C, which can collect the falling ice particles.
Sergey Y. Matrosov, Alexei Korolev, Mengistu Wolde, and Cuong Nguyen
Atmos. Meas. Tech., 15, 6373–6386, https://doi.org/10.5194/amt-15-6373-2022, https://doi.org/10.5194/amt-15-6373-2022, 2022
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A remote sensing method to retrieve sizes of particles in ice clouds and precipitation from radar measurements at two wavelengths is described. This method is based on relating the particle size information to the ratio of radar signals at these two wavelengths. It is demonstrated that this ratio is informative about different characteristic particle sizes. Knowing atmospheric ice particle sizes is important for many applications such as precipitation estimation and climate modeling.
Andrzej Z. Kotarba
Atmos. Meas. Tech., 15, 4307–4322, https://doi.org/10.5194/amt-15-4307-2022, https://doi.org/10.5194/amt-15-4307-2022, 2022
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Space profiling lidars offer a unique insight into cloud properties in Earth’s atmosphere, and are considered the most reliable source of cloud information. However, lidar-based cloud climatologies are infrequently sampled: every 7 to 91 d, and only along the ground track. This study evaluated how accurate are the cloud data from existing (CALIPSO, ICESat-2, Aeolus) and planned (EarthCARE) space lidars, when compared to a cloud climatology obtained with observations taken every day.
Edward Gryspeerdt, Daniel T. McCoy, Ewan Crosbie, Richard H. Moore, Graeme J. Nott, David Painemal, Jennifer Small-Griswold, Armin Sorooshian, and Luke Ziemba
Atmos. Meas. Tech., 15, 3875–3892, https://doi.org/10.5194/amt-15-3875-2022, https://doi.org/10.5194/amt-15-3875-2022, 2022
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Droplet number concentration is a key property of clouds, influencing a variety of cloud processes. It is also used for estimating the cloud response to aerosols. The satellite retrieval depends on a number of assumptions – different sampling strategies are used to select cases where these assumptions are most likely to hold. Here we investigate the impact of these strategies on the agreement with in situ data, the droplet number climatology and estimates of the indirect radiative forcing.
Henning Dorff, Heike Konow, and Felix Ament
Atmos. Meas. Tech., 15, 3641–3661, https://doi.org/10.5194/amt-15-3641-2022, https://doi.org/10.5194/amt-15-3641-2022, 2022
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This study elaborates how aircraft-based horizontal geometries of trade wind cumuli differ whether a one-dimensional profiling radar or a two-dimensional imager is used. Cloud size distributions are examined in terms of sensitivity to sample size, resolution, and instrument field of view. While the radar cannot reproduce the double power law distribution due to coarse resolution and restriction to vertical transects, the imager also reveals the elliptic cloud structure enhancing with wind speed.
Qing Yue, Eric J. Fetzer, Likun Wang, Brian H. Kahn, Nadia Smith, John M. Blaisdell, Kerry G. Meyer, Mathias Schreier, Bjorn Lambrigtsen, and Irina Tkatcheva
Atmos. Meas. Tech., 15, 2099–2123, https://doi.org/10.5194/amt-15-2099-2022, https://doi.org/10.5194/amt-15-2099-2022, 2022
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The self-consistency and continuity of cloud retrievals from infrared sounders and imagers aboard Aqua and SNPP (Suomi National Polar-orbiting Partnership) are examined at the pixel scale. Cloud products are found to be consistent with each other. Differences between sounder products are mainly due to cloud clearing and the treatment of clouds in scenes with unsuccessful atmospheric retrievals. The impact of algorithm and instrument differences is clearly seen in the imager cloud retrievals.
Pradeep Khatri, Tadahiro Hayasaka, Hitoshi Irie, Husi Letu, Takashi Y. Nakajima, Hiroshi Ishimoto, and Tamio Takamura
Atmos. Meas. Tech., 15, 1967–1982, https://doi.org/10.5194/amt-15-1967-2022, https://doi.org/10.5194/amt-15-1967-2022, 2022
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Cloud properties observed by the Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite are evaluated using surface observation data. The study finds that SGLI-observed cloud properties are qualitative enough, although water cloud properties are suggested to be more qualitative, and both water and ice cloud properties can reproduce surface irradiance quite satisfactorily. Thus, SGLI cloud products are very useful for different studies.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, Rodrigo Guzman, Cyprien Gindre, Po-Lun Ma, and Marjolaine Chiriaco
Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, https://doi.org/10.5194/amt-15-1055-2022, 2022
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Space-borne lidars have been providing invaluable information of atmospheric optical properties since 2006, and new lidar missions are on the way to ensure continuous observations. In this work, we compare the clouds estimated from space-borne ALADIN and CALIOP lidar observations. The analysis of collocated data shows that the agreement between the retrieved clouds is good up to 3 km height. Above that, ALADIN detects 40 % less clouds than CALIOP, except for polar stratospheric clouds (PSCs).
Gregor Köcher, Tobias Zinner, Christoph Knote, Eleni Tetoni, Florian Ewald, and Martin Hagen
Atmos. Meas. Tech., 15, 1033–1054, https://doi.org/10.5194/amt-15-1033-2022, https://doi.org/10.5194/amt-15-1033-2022, 2022
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We present a setup for systematic characterization of differences between numerical weather models and radar observations for convective weather situations. Radar observations providing dual-wavelength and polarimetric variables to infer information about hydrometeor shapes and sizes are compared against simulations using microphysics schemes of varying complexity. Differences are found in ice and liquid phase, pointing towards issues of some schemes in reproducing particle size distributions.
Simon Pfreundschuh, Stuart Fox, Patrick Eriksson, David Duncan, Stefan A. Buehler, Manfred Brath, Richard Cotton, and Florian Ewald
Atmos. Meas. Tech., 15, 677–699, https://doi.org/10.5194/amt-15-677-2022, https://doi.org/10.5194/amt-15-677-2022, 2022
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We test a novel method to remotely measure ice particles in clouds. This is important because such measurements are required to improve climate and weather models. The method combines a radar with newly developed sensors measuring microwave radiation at very short wavelengths. We use observations made from aircraft flying above the cloud and compare them to real measurements from inside the cloud. This works well given that one can model the ice particles in the cloud sufficiently well.
David Painemal, Douglas Spangenberg, William L. Smith Jr., Patrick Minnis, Brian Cairns, Richard H. Moore, Ewan Crosbie, Claire Robinson, Kenneth L. Thornhill, Edward L. Winstead, and Luke Ziemba
Atmos. Meas. Tech., 14, 6633–6646, https://doi.org/10.5194/amt-14-6633-2021, https://doi.org/10.5194/amt-14-6633-2021, 2021
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Cloud properties derived from satellite sensors are critical for the global monitoring of climate. This study evaluates satellite-based cloud properties over the North Atlantic using airborne data collected during NAAMES. Satellite observations of droplet size and cloud optical depth tend to compare well with NAAMES data. The analysis indicates that the satellite pixel resolution and the specific viewing geometry need to be taken into account in research applications.
Charles H. White, Andrew K. Heidinger, and Steven A. Ackerman
Atmos. Meas. Tech., 14, 3371–3394, https://doi.org/10.5194/amt-14-3371-2021, https://doi.org/10.5194/amt-14-3371-2021, 2021
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Automated detection of clouds in satellite imagery is an important practice that is useful for predicting and understanding both weather and climate. Cloud detection is often difficult at night and over cold surfaces. In this paper, we discuss how a complex statistical model (a neural network) can more accurately detect clouds compared to currently used approaches. Overall, our results suggest that our approach could result in more reliable assessments of global cloud cover.
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
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In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Jędrzej S. Bojanowski and Jan P. Musiał
Atmos. Meas. Tech., 13, 6771–6788, https://doi.org/10.5194/amt-13-6771-2020, https://doi.org/10.5194/amt-13-6771-2020, 2020
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Satellites such as NOAA's Advanced Very High Resolution Radiometer can uniquely observe changes in cloud cover but are affected by orbital drift that results in shifted image acquisition times, which in turn lead to spurious trends in cloud cover detected during climatological analyses. Providing a detailed quantification of these trends, we show that climate data records must be analysed with caution, as for some periods and regions they do not comply with the requirements for climate data.
Andrzej Z. Kotarba
Atmos. Meas. Tech., 13, 4995–5012, https://doi.org/10.5194/amt-13-4995-2020, https://doi.org/10.5194/amt-13-4995-2020, 2020
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This paper evaluates the operational approach for producing global (Level 3) cloud amount based on MODIS cloud masks (Level 2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 %, and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/local scale. A method of how to correct and calibrate MODIS global data using CALIPSO detections is suggested.
Benjamin Marchant, Steven Platnick, Kerry Meyer, and Galina Wind
Atmos. Meas. Tech., 13, 3263–3275, https://doi.org/10.5194/amt-13-3263-2020, https://doi.org/10.5194/amt-13-3263-2020, 2020
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Multilayer cloud scenes (such as an ice cloud overlapping a liquid cloud) are common in the Earth's atmosphere and are quite difficult to detect from space. The detection of multilayer clouds is important to better understand how they interact with the light and their impact on the climate. So, for the instrument MODIS an algorithm has been developed to detect those clouds, and this paper presents an evaluation of this algorithm by comparing it with
other instruments.
Alexis Hunzinger, Joseph C. Hardin, Nitin Bharadwaj, Adam Varble, and Alyssa Matthews
Atmos. Meas. Tech., 13, 3147–3166, https://doi.org/10.5194/amt-13-3147-2020, https://doi.org/10.5194/amt-13-3147-2020, 2020
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The calibration of weather radars is one of the most dominant sources of errors hindering their use. This work takes a technique for tracking the changes in radar calibration using the radar clutter from the ground and extends it to higher-frequency research radars. It demonstrates that after modifications the technique is successful but that special care needs to be taken in its application at high frequencies. The technique is verified using data from multiple DOE ARM field campaigns.
Dieter R. Poelman and Wolfgang Schulz
Atmos. Meas. Tech., 13, 2965–2977, https://doi.org/10.5194/amt-13-2965-2020, https://doi.org/10.5194/amt-13-2965-2020, 2020
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The objective of this work is to quantify the similarities and contrasts between the lightning observations from the Lightning Imaging Sensor (LIS) on the International Space Station (ISS) and the ground-based European Cooperation for Lightning Detection (EUCLID) network. This work is timely, given that the Meteosat Third Generation (MTG), which has a lightning imager (LI) on board, is going to be launched in 2 years.
Manfred Brath, Robin Ekelund, Patrick Eriksson, Oliver Lemke, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 2309–2333, https://doi.org/10.5194/amt-13-2309-2020, https://doi.org/10.5194/amt-13-2309-2020, 2020
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Microwave dual-polarization observations consistently show that larger atmospheric ice particles tend to have a preferred orientation. We provide a publicly available database of microwave and submillimeter wave scattering properties of oriented ice particles based on discrete dipole approximation scattering calculations. Detailed radiative transfer simulations, recreating observed polarization patterns, are additionally presented in this study.
Erin A. Riley, Jessica M. Kleiss, Laura D. Riihimaki, Charles N. Long, Larry K. Berg, and Evgueni Kassianov
Atmos. Meas. Tech., 13, 2099–2117, https://doi.org/10.5194/amt-13-2099-2020, https://doi.org/10.5194/amt-13-2099-2020, 2020
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Discrepancies in hourly shallow cumuli cover estimates can be substantial. Instrument detection differences contribute to long-term bias in shallow cumuli cover estimates, whereas narrow field-of-view configurations impact measurement uncertainty as averaging time decreases. A new tool is introduced to visually assess both impacts on sub-hourly cloud cover estimates. Accurate shallow cumuli cover estimation is needed for model–observation comparisons and studying cloud-surface interactions.
Robin Ekelund, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 13, 501–520, https://doi.org/10.5194/amt-13-501-2020, https://doi.org/10.5194/amt-13-501-2020, 2020
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Atmospheric ice particles (e.g. snow and ice crystals) are an important part of weather, climate, and the hydrological cycle. This study investigates whether combined satellite measurements by radar and radiometers at microwave wavelengths can be used to find the most likely shape of such ice particles. The method was limited when using only currently operating sensors (CloudSat radar and the GPM Microwave Imager) but shows promise if the upcoming Ice Cloud Imager is also considered.
Juan Huo, Daren Lu, Shu Duan, Yongheng Bi, and Bo Liu
Atmos. Meas. Tech., 13, 1–11, https://doi.org/10.5194/amt-13-1-2020, https://doi.org/10.5194/amt-13-1-2020, 2020
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Cloud top height (CTH) is one of the important cloud parameters providing information about the vertical structure of cloud water content. To better understand the accuracy of CTH derived from passive satellite data, 2 years of ground-based Ka-band radar measurements are compared with CTH inferred from Terra/Aqua MODIS and Himawari AHI. It is found that MODIS and AHI underestimate CTH relative to radar by −1.10 km. Both MODIS and AHI CTH retrieval accuracy depend strongly on cloud depth.
Vladimir S. Kostsov, Anke Kniffka, Martin Stengel, and Dmitry V. Ionov
Atmos. Meas. Tech., 12, 5927–5946, https://doi.org/10.5194/amt-12-5927-2019, https://doi.org/10.5194/amt-12-5927-2019, 2019
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Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms. The LWP data delivered by the satellite instruments SEVIRI and AVHRR together with the data provided by the ground-based radiometer RPG-HATPRO near St. Petersburg, Russia, have been compared. Our study revealed considerable differences between LWP data from SEVIRI and AVHRR in winter over ice-covered relatively small water bodies in this region.
Jonathan K. P. Shonk, Jui-Yuan Christine Chiu, Alexander Marshak, David M. Giles, Chiung-Huei Huang, Gerald G. Mace, Sally Benson, Ilya Slutsker, and Brent N. Holben
Atmos. Meas. Tech., 12, 5087–5099, https://doi.org/10.5194/amt-12-5087-2019, https://doi.org/10.5194/amt-12-5087-2019, 2019
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Retrievals of cloud optical depth made using AERONET radiometers in “cloud mode” rely on the assumption that all cloud is liquid. The presence of ice cloud therefore introduces errors in the retrieved optical depth, which can be over 25 in optically thick ice clouds. However, such clouds are not frequent and the long-term mean optical depth error is about 3 for a sample of real clouds. A correction equation could improve the retrieval further, although this would require extra instrumentation.
Chaojun Shi, Yatong Zhou, Bo Qiu, Jingfei He, Mu Ding, and Shiya Wei
Atmos. Meas. Tech., 12, 4713–4724, https://doi.org/10.5194/amt-12-4713-2019, https://doi.org/10.5194/amt-12-4713-2019, 2019
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Cloud segmentation plays a very important role in astronomical observatory site selection. At present, few researchers segment cloud in nocturnal all-sky imager (ASI) images. We propose a new automatic cloud segmentation algorithm to segment cloud pixels from diurnal and nocturnal ASI images called an enhancement fully convolutional network (EFCN). Experiments showed that the proposed EFCN was much more accurate in cloud segmentation for diurnal and nocturnal ASI images.
Maximilian Maahn, Fabian Hoffmann, Matthew D. Shupe, Gijs de Boer, Sergey Y. Matrosov, and Edward P. Luke
Atmos. Meas. Tech., 12, 3151–3171, https://doi.org/10.5194/amt-12-3151-2019, https://doi.org/10.5194/amt-12-3151-2019, 2019
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Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Here, we present three novel methods for calibrating vertically pointing cloud radars. These calibration methods are based on microphysical processes of liquid clouds, such as the transition of cloud droplets to drizzle drops. We successfully apply the methods to cloud radar data from the North Slope of Alaska (NSA) and Oliktok Point (OLI) ARM sites.
Florian Ewald, Silke Groß, Martin Hagen, Lutz Hirsch, Julien Delanoë, and Matthias Bauer-Pfundstein
Atmos. Meas. Tech., 12, 1815–1839, https://doi.org/10.5194/amt-12-1815-2019, https://doi.org/10.5194/amt-12-1815-2019, 2019
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This study gives a summary of lessons learned during the absolute calibration of the airborne, high-power Ka-band cloud radar HAMP MIRA on board the German research aircraft HALO. The first part covers the internal calibration of the instrument where individual instrument components are characterized in the laboratory. In the second part, the internal calibration is validated with external reference sources like the ocean surface backscatter and different air- and spaceborne cloud radars.
Stuart Fox, Jana Mendrok, Patrick Eriksson, Robin Ekelund, Sebastian J. O'Shea, Keith N. Bower, Anthony J. Baran, R. Chawn Harlow, and Juliet C. Pickering
Atmos. Meas. Tech., 12, 1599–1617, https://doi.org/10.5194/amt-12-1599-2019, https://doi.org/10.5194/amt-12-1599-2019, 2019
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Airborne observations of ice clouds are used to validate radiative transfer simulations using a state-of-the-art database of cloud ice optical properties. Simulations at these wavelengths are required to make use of future satellite instruments such as the Ice Cloud Imager. We show that they can generally reproduce observed cloud signals, but for a given total ice mass there is considerable sensitivity to the cloud microphysics, including the particle shape and distribution of ice mass.
Katrin Lonitz and Alan J. Geer
Atmos. Meas. Tech., 12, 405–429, https://doi.org/10.5194/amt-12-405-2019, https://doi.org/10.5194/amt-12-405-2019, 2019
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Permittivity models for microwave frequencies of liquid water below 0°C are poorly constrained due to limited laboratory experiments and observations, especially for high microwave frequencies. This uncertainty translates directly into errors in retrieved liquid water paths of up to 80 %. This study investigates the effect of different liquid water permittivity models including models based on the most recent observations.
Vladimir S. Kostsov, Anke Kniffka, and Dmitry V. Ionov
Atmos. Meas. Tech., 11, 5439–5460, https://doi.org/10.5194/amt-11-5439-2018, https://doi.org/10.5194/amt-11-5439-2018, 2018
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Clouds are a very important component of the climate system and of the hydrological cycle in the Arctic and sub-Arctic. A joint analysis of the cloud parameters obtained remotely from satellite and ground-based observations near St Petersburg, Russia, has been made. Our study has revealed considerable differences between the cloud properties over land and over water areas in the region under investigation.
Fanny Jeanneret, Giovanni Martucci, Simon Pinnock, and Alexis Berne
Atmos. Meas. Tech., 11, 4153–4170, https://doi.org/10.5194/amt-11-4153-2018, https://doi.org/10.5194/amt-11-4153-2018, 2018
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Above mountainous regions, satellites may have difficulty in discriminating snow from clouds: this study proposes a new method that combines different ground-based measurements to assess the sky cloudiness with high temporal resolution. The method's output is used as input to a model capable of identifying false satellite cloud detections. Results show that 62 ± 13 % of these false detections can be identified by the model when applied to the AVHRR-PM and MODIS Aqua data sets of the Cloud_cci.
Céline Cornet, Laurent C.-Labonnote, Fabien Waquet, Frédéric Szczap, Lucia Deaconu, Frédéric Parol, Claudine Vanbauce, François Thieuleux, and Jérôme Riédi
Atmos. Meas. Tech., 11, 3627–3643, https://doi.org/10.5194/amt-11-3627-2018, https://doi.org/10.5194/amt-11-3627-2018, 2018
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Simulations of total and polarized cloud reflectance angular signatures such as the ones measured by the multi-angular and polarized radiometer POLDER3/PARASOL are used to evaluate cloud heterogeneity effects on cloud parameter retrievals. Effects on optical thickness, albedo of the cloudy scenes, effective radius and variance of the cloud droplet size distribution, cloud top pressure and aerosol above cloud are analyzed.
Cited articles
Baars, H., Seifert, P., Engelmann, R., and Wandinger, U.: Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements, Atmos. Meas. Tech., 10, 3175–3201, https://doi.org/10.5194/amt-10-3175-2017, 2017.
Banakh, V. A. and Smalikho, I. N.: Lidar Studies of Wind Turbulence in the Stable Atmospheric Boundary Layer, Remote Sens.-Basel, 10, 1219, https://doi.org/10.3390/rs10081219, 2018.
Banakh, V. A., Brewer, A., Pichugina, E. L., and Smalikho, I. N.: Measurements of wind velocity and direction with coherent Doppler lidar in conditions of a weak echo signal, Atmospheric and Oceanic Optics, 23, 381–388, https://doi.org/10.1134/S1024856010050076, 2010.
Banakh, V. A., Smalikho, I. N., and Falits, A. V.: Estimation of the turbulence energy dissipation rate in the atmospheric boundary layer from measurements of the radial wind velocity by micropulse coherent Doppler lidar, Opt. Express, 25, 22679–22692, https://doi.org/10.1364/OE.25.022679, 2017.
Banakh, V. A., Smalikho, I. N., and Falits, A. V.: Estimation of the height of the turbulent mixing layer from data of Doppler lidar measurements using conical scanning by a probe beam, Atmos. Meas. Tech., 14, 1511–1524, https://doi.org/10.5194/amt-14-1511-2021, 2021.
Beard, K. V.: Terminal Velocity and Shape of Cloud and Precipitation Drops Aloft, J. Atmos. Sci., 33, 851–864, https://doi.org/10.1175/1520-0469(1976)033<0851:TVASOC>2.0.CO;2, 1976.
Bian, Y., Liu, L., Zheng, J., Wu, S., and Dai, G.: Classification of Cloud Phase Using Combined Ground-Based Polarization Lidar and Millimeter Cloud Radar Observations Over the Tibetan Plateau, IEEE T. Geosci. Remote, 61, 1–13, https://doi.org/10.1109/TGRS.2023.3313798, 2023.
Bruning, E. C., Rust, W. D., Schuur, T. J., MacGorman, D. R., Krehbiel, P. R., and Rison, W.: Electrical and Polarimetric Radar Observations of a Multicell Storm in TELEX, Mon. Weather Rev., 135, 2525–2544, https://doi.org/10.1175/MWR3421.1, 2007.
Bruning, E. C., Rust, W. D., MacGorman, D. R., Biggerstaff, M. I., and Schuur, T. J.: Formation of Charge Structures in a Supercell, Mon. Weather Rev., 138, 3740–3761, https://doi.org/10.1175/2010mwr3160.1, 2010.
Bruning, E. C., Weiss, S. A., and Calhoun, K. M.: Continuous variability in thunderstorm primary electrification and an evaluation of inverted-polarity terminology, Atmos. Res., 135–136, 274–284, https://doi.org/10.1016/j.atmosres.2012.10.009, 2014.
Bryan, G. H., Wyngaard, J. C., and Fritsch, J. M.: Resolution Requirements for the Simulation of Deep Moist Convection, Mon. Weather Rev., 131, 2394–2416, https://doi.org/10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2, 2003.
Calhoun, K. M., Mansell, E. R., MacGorman, D. R., and Dowell, D. C.: Numerical Simulations of Lightning and Storm Charge of the 29–30 May 2004 Geary, Oklahoma, Supercell Thunderstorm Using EnKF Mobile Radar Data Assimilation, Mon. Weather Rev., 142, 3977–3997, https://doi.org/10.1175/mwr-d-13-00403.1, 2014.
Carey, L. D. and Buffalo, K. M.: Environmental Control of Cloud-to-Ground Lightning Polarity in Severe Storms, Mon. Weather Rev., 135, 1327–1353, https://doi.org/10.1175/MWR3361.1, 2007.
Carey, L. D. and Rutledge, S. A.: The Relationship between Precipitation and Lightning in Tropical Island Convection: A C-Band Polarimetric Radar Study, Mon. Weather Rev., 128, 2687–2710, https://doi.org/10.1175/1520-0493(2000)128<2687:TRBPAL>2.0.CO;2, 2000.
Chen, Z., Sun, J., Qie, X., Zhang, Y., Ying, Z., Xiao, X., and Cao, D.: A Method to Update Model Kinematic States by Assimilating Satellite-Observed Total Lightning Data to Improve Convective Analysis and Forecasting, J. Geophys. Res.-Atmos., 125, e2020JD033330, https://doi.org/10.1029/2020JD033330, 2020.
Cheng, S., Wang, J., Cai, L., Zhou, M., Su, R., Huang, Y., and Li, Q.: Characterising the dynamic movement of thunderstorms using very low- and low-frequency (VLF/LF) total lightning data over the Pearl River Delta region, Atmos. Chem. Phys., 22, 10045–10059, https://doi.org/10.5194/acp-22-10045-2022, 2022.
Chmielewski, V. C., Bruning, E. C., and Ancell, B. C.: Variations of Thunderstorm Charge Structures in West Texas on 4 June 2012, J. Geophys. Res.-Atmos., 123, 9502–9523, https://doi.org/10.1029/2018JD029006, 2018.
Cooray, V.: Charge Generation in Thunderclouds and Different Forms of Lightning Flashes, in: An Introduction to Lightning, Springer Netherlands, Dordrecht, 79–89, https://doi.org/10.1007/978-94-017-8938-7_6, 2015.
Coquillat, S., Pont, V., Lambert, D., Houel, R., Pardé, M., Kreitz, M., Ricard, D., Gonneau, E., de Guibert, P., and Prieur, S.: Six years of electrified convection over the island of Corsica monitored by SAETTA: General trends and anomalously electrified thunderstorms during African dust south flow events, Atmos. Res., 275, 106227, https://doi.org/10.1016/j.atmosres.2022.106227, 2022.
Dye, J. E., Winn, W. P., Jones, J. J., and Breed, D. W.: The electrification of New Mexico thunderstorms: 1. Relationship between precipitation development and the onset of electrification, J. Geophys. Res.-Atmos., 94, 8643–8656, https://doi.org/10.1029/JD094iD06p08643, 1989.
Erdmann, F., Defer, E., Caumont, O., Blakeslee, R. J., Pédeboy, S., and Coquillat, S.: Concurrent satellite and ground-based lightning observations from the Optical Lightning Imaging Sensor (ISS-LIS), the low-frequency network Meteorage and the SAETTA Lightning Mapping Array (LMA) in the northwestern Mediterranean region, Atmos. Meas. Tech., 13, 853–875, https://doi.org/10.5194/amt-13-853-2020, 2020.
Fan, J., Rosenfeld, D., Zhang, Y., Giangrande, S. E., Li, Z., Machado, L. A. T., Martin, S. T., Yang, Y., Wang, J., Artaxo, P., Barbosa, H. M. J., Braga, R. C., Comstock, J. M., Feng, Z., Gao, W., Gomes, H. B., Mei, F., Pöhlker, C., Pöhlker, M. L., Pöschl, U., and Souza, R. A. F. D.: Substantial convection and precipitation enhancements by ultrafine aerosol particles, Science, 359, 411–418, https://doi.org/10.1126/science.aan8461, 2018.
Fan, Y., Lu, G., Zhang, Y., Lyu, W., Zheng, D., Fan, X., Li, X., and Zhang, Y.: Characterizing Radio Frequency Magnetic Radiation of Initial Upward Leader Stepping in Triggered Lightning With Interferometric Lightning Mapping, Geophys. Res. Lett., 47, e2020GL089392, https://doi.org/10.1029/2020GL089392, 2020.
Feist, M. M., Westbrook, C. D., Clark, P. A., Stein, T. H. M., Lean, H. W., and Stirling, A. J.: Statistics of convective cloud turbulence from a comprehensive turbulence retrieval method for radar observations, Q. J. Roy. Meteor. Soc., 145, 727–744, https://doi.org/10.1002/qj.3462, 2019.
FengYun Satellite Data Center: http://satellite.nsmc.org.cn/portalsite/default.aspx (last access: 30 November 2023), 2023.
Figueras i Ventura, J., Pineda, N., Besic, N., Grazioli, J., Hering, A., van der Velde, O. A., Romero, D., Sunjerga, A., Mostajabi, A., Azadifar, M., Rubinstein, M., Montanyà, J., Germann, U., and Rachidi, F.: Analysis of the lightning production of convective cells, Atmos. Meas. Tech., 12, 5573–5591, https://doi.org/10.5194/amt-12-5573-2019, 2019a.
Figueras i Ventura, J., Pineda, N., Besic, N., Grazioli, J., Hering, A., van der Velde, O. A., Romero, D., Sunjerga, A., Mostajabi, A., Azadifar, M., Rubinstein, M., Montanyà, J., Germann, U., and Rachidi, F.: Polarimetric radar characteristics of lightning initiation and propagating channels, Atmos. Meas. Tech., 12, 2881–2911, https://doi.org/10.5194/amt-12-2881-2019, 2019b.
Fuchs, B. R., Rutledge, S. A., Bruning, E. C., Pierce, J. R., Kodros, J. K., Lang, T. J., MacGorman, D. R., Krehbiel, P. R., and Rison, W.: Environmental controls on storm intensity and charge structure in multiple regions of the continental United States, J. Geophys. Res.-Atmos., 120, 6575–6596, https://doi.org/10.1002/2015JD023271, 2015.
Fuchs, B. R., Bruning, E. C., Rutledge, S. A., Carey, L. D., Krehbiel, P. R., and Rison, W.: Climatological analyses of LMA data with an open-source lightning flash-clustering algorithm, J. Geophys. Res.-Atmos., 121, 8625–8648, https://doi.org/10.1002/2015JD024663, 2016.
Fuchs, B. R., Rutledge, S. A., Dolan, B., Carey, L. D., and Schultz, C.: Microphysical and Kinematic Processes Associated With Anomalous Charge Structures in Isolated Convection, J. Geophys. Res.-Atmos., 123, 6505–6528, https://doi.org/10.1029/2017JD027540, 2018.
Goodman, S. J., Buechler, D. E., Wright, P. D., and Rust, W. D.: Lightning and precipitation history of a microburst-producing storm, Geophys. Res. Lett., 15, 1185–1188, https://doi.org/10.1029/GL015i011p01185, 1988.
Hallett, J., Sax, R. I., Lamb, D., and Murty, A. S. R.: Aircraft measurements of ice in Florida cumuli, Q. J. Roy. Meteor. Soc., 104, 631–651, https://doi.org/10.1002/qj.49710444108, 1978.
He, G., Li, G., Zou, X., and Ray, P. S.: Applications of a Velocity Dealiasing Scheme to Data from the China New Generation Weather Radar System (CINRAD), Weather Forecast., 27, 218–230, https://doi.org/10.1175/WAF-D-11-00054.1, 2012.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate, Copernicus Climate Change Service (C3S) Data Store (CDS), https://doi.org/10.24381/cds.143582cf, 2017.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Jayaratne, E. R., Saunders, C. P. R., and Hallett, J.: Laboratory studies of the charging of soft-hail during ice crystal interactions, Q. J. Roy. Meteor. Soc., 109, 609–630, https://doi.org/10.1002/qj.49710946111, 1983.
Jia, M., Yuan, J., Wang, C., Xia, H., Wu, Y., Zhao, L., Wei, T., Wu, J., Wang, L., Gu, S.-Y., Liu, L., Lu, D., Chen, R., Xue, X., and Dou, X.: Long-lived high-frequency gravity waves in the atmospheric boundary layer: observations and simulations, Atmos. Chem. Phys., 19, 15431–15446, https://doi.org/10.5194/acp-19-15431-2019, 2019.
Khanal, S. and Wang, Z.: Uncertainties in MODIS-Based Cloud Liquid Water Path Retrievals at High Latitudes Due to Mixed-Phase Clouds and Cloud Top Height Inhomogeneity, J. Geophys. Res.-Atmos., 123, 11154–11172, https://doi.org/10.1029/2018JD028558, 2018.
Lang, T. J. and Rutledge, S. A.: A Framework for the Statistical Analysis of Large Radar and Lightning Datasets: Results from STEPS 2000, Mon. Weather Rev., 139, 2536–2551, https://doi.org/10.1175/mwr-d-10-05000.1, 2011.
Lang, T. J., Miller, L. J., Weisman, M., Rutledge, S. A., Barker, L. J., Bringi, V. N., Chandrasekar, V., Detwiler, A., Doesken, N., Helsdon, J., Knight, C., Krehbiel, P., Lyons, W. A., MacGorman, D., Rasmussen, E., Rison, W., Rust, W. D., and Thomas, R. J.: The Severe Thunderstorm Electrification and Precipitation Study, B. Am. Meteorol. Soc., 85, 1107–1126, https://doi.org/10.1175/bams-85-8-1107, 2004.
Li, Y., Zhang, G., and Zhang, Y.: Evolution of the Charge Structure and Lightning Discharge Characteristics of a Qinghai-Tibet Plateau Thunderstorm Dominated by Negative Cloud-to-Ground Flashes, J. Geophys. Res.-Atmos., 125, e2019JD031129, https://doi.org/10.1029/2019JD031129, 2020.
Liu, F., Zhu, B., Lu, G., Qin, Z., Lei, J., Peng, K.-M., Chen, A. B., Huang, A., Cummer, S. A., Chen, M., Ma, M., Lyu, F., and Zhou, H.: Observations of Blue Discharges Associated With Negative Narrow Bipolar Events in Active Deep Convection, Geophys. Res. Lett., 45, 2842–2851, https://doi.org/10.1002/2017GL076207, 2018.
Liu, F., Lu, G., Neubert, T., Lei, J., Chanrion, O., Østgaard, N., Li, D., Luque, A., Gordillo-Vázquez, F. J., Reglero, V., Lyu, W., and Zhu, B.: Optical emissions associated with narrow bipolar events from thunderstorm clouds penetrating into the stratosphere, Nat. Commun., 12, 6631, https://doi.org/10.1038/s41467-021-26914-4, 2021a.
Liu, F., Zhu, B., Lu, G., Lei, J., Shao, J., Chen, Y., Huang, A., Ma, M., Qin, Z., Zhong, J., Ren, H., Wang, Z., Wan, Z., Liu, G., Peng, C., Peng, K.-M., and Zhou, H.: Meteorological and Electrical Conditions of Two Mid-latitude Thunderstorms Producing Blue Discharges, J. Geophys. Res.-Atmos., 126, e2020JD033648, https://doi.org/10.1029/2020JD033648, 2021b.
Lottman, B. T. and Frehlich, R.: Extracting vertical winds from simulated clouds with ground-based coherent Doppler lidar, Appl. Optics, 37, 8297–8305, https://doi.org/10.1364/AO.37.008297, 1998.
Low, T. B. and List, R.: Collision, Coalescence and Breakup of Raindrops. Part I: Experimentally Established Coalescence Efficiencies and Fragment Size Distributions in Breakup, J. Atmos. Sci., 39, 1591–1606, https://doi.org/10.1175/1520-0469(1982)039<1591:CCABOR>2.0.CO;2, 1982.
Marshall, T. C. and Winn, W. P.: Measurements of charged precipitation in a New Mexico thunderstorm: lower positive charge centers, J. Geophys. Res., 87, 7141–7157, https://doi.org/10.1029/JC087iC09p07141, 1982.
Mecikalski, R. M. and Carey, L. D.: Radar Reflectivity and Altitude Distributions of Lightning as a Function of IC, CG, and HY Flashes: Implications for LNOx Production, J. Geophys. Res.-Atmos., 123, 12796–12813, https://doi.org/10.1029/2018JD029263, 2018.
Medina, B. L., Carey, L. D., Lang, T. J., Bitzer, P. M., Deierling, W., and Zhu, Y.: Characterizing Charge Structure in Central Argentina Thunderstorms During RELAMPAGO Utilizing a New Charge Layer Polarity Identification Method, Earth and Space Science, 8, e2021EA001803, https://doi.org/10.1029/2021EA001803, 2021.
Qie, X., Yuan, S., Chen, Z., Wang, D., Liu, D., Sun, M., Sun, Z., Srivastava, A., Zhang, H., Lu, J., Xiao, H., Bi, Y., Feng, L., Tian, Y., Xu, Y., Jiang, R., Liu, M., Xiao, X., Duan, S., Su, D., Sun, C., Xu, W., Zhang, Y., Lu, G., Zhang, D.-L., Yin, Y., and Yu, Y.: Understanding the dynamical-microphysical-electrical processes associated with severe thunderstorms over the Beijing metropolitan region, Sci. China Earth Sci., 64, 10–26, https://doi.org/10.1007/s11430-020-9656-8, 2021.
Qiu, J., Xia, H., Shangguan, M., Dou, X., Li, M., Wang, C., Shang, X., Lin, S., and Liu, J.: Micro-pulse polarization lidar at 1.5 µm using a single superconducting nanowire single-photon detector, Opt. Lett., 42, 4454–4457, https://doi.org/10.1364/OL.42.004454, 2017.
Reynolds, S. E., Brook, M., and Gourley, M. F.: THUNDERSTORM CHARGE SEPARATION, J. Atmos. Sci., 14, 426–436, https://doi.org/10.1175/1520-0469(1957)014<0426:Tcs>2.0.Co;2, 1957.
Sassen, K. and Wang, Z.: Classifying clouds around the globe with the CloudSat radar: 1 year of results, Geophys. Res. Lett., 35, L04805, https://doi.org/10.1029/2007GL032591, 2008.
Sathe, A. and Mann, J.: A review of turbulence measurements using ground-based wind lidars, Atmos. Meas. Tech., 6, 3147–3167, https://doi.org/10.5194/amt-6-3147-2013, 2013.
Saunders, C.: Charge Separation Mechanisms in Clouds, Space Sci. Rev., 137, 335, https://doi.org/10.1007/s11214-008-9345-0, 2008.
Smalikho, I. N. and Banakh, V. A.: Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer, Atmos. Meas. Tech., 10, 4191–4208, https://doi.org/10.5194/amt-10-4191-2017, 2017.
Stolzenburg, M., Rust, W. D., and Marshall, T. C.: Electrical structure in thunderstorm convective regions: 3. Synthesis, J. Geophys. Res.-Atmos., 103, 14097–14108, https://doi.org/10.1029/97JD03545, 1998.
Stolzenburg, M., Marshall, T. C., Rust, W. D., and Bartels, D. L.: Two simultaneous charge structures in thunderstorm convection, J. Geophys. Res.-Atmos., 107, ACL 5-1–ACL 5-12, https://doi.org/10.1029/2001JD000904, 2002.
Stolzenburg, M., Marshall, T. C., and Krehbiel, P. R.: Initial electrification to the first lightning flash in New Mexico thunderstorms, J. Geophys. Res.-Atmos., 120, 11253–11276, https://doi.org/10.1002/2015JD023988, 2015.
Stough, S. M., Carey, L. D., Schultz, C. J., and Cecil, D. J.: Examining Conditions Supporting the Development of Anomalous Charge Structures in Supercell Thunderstorms in the Southeastern United States, J. Geophys. Res.-Atmos., 126, e2021JD034582, https://doi.org/10.1029/2021JD034582, 2021.
Sun, M., Liu, D., Qie, X., Mansell, E. R., Yair, Y., Fierro, A. O., Yuan, S., Chen, Z., and Wang, D.: Aerosol effects on electrification and lightning discharges in a multicell thunderstorm simulated by the WRF-ELEC model, Atmos. Chem. Phys., 21, 14141–14158, https://doi.org/10.5194/acp-21-14141-2021, 2021.
Takahashi, T.: Riming electrification as a charge generation mechanism in thunderstorms, J. Atmos. Sci., 35, 1536–1548, https://doi.org/10.1175/1520-0469(1978)035<1536:REAACG>2.0.CO;2, 1978.
Takahashi, T., Sugimoto, S., Kawano, T., and Suzuki, K.: Riming Electrification in Hokuriku Winter Clouds and Comparison with Laboratory Observations, J. Atmos. Sci., 74, 431–447, https://doi.org/10.1175/JAS-D-16-0154.1, 2017.
Tang, D., Wei, T., Yuan, J., Xia, H., and Dou, X.: Observation of bioaerosol transport using wideband integrated bioaerosol sensor and coherent Doppler lidar, Atmos. Meas. Tech., 15, 2819–2838, https://doi.org/10.5194/amt-15-2819-2022, 2022.
Tokay, A., Wolff, D. B., and Petersen, W. A.: Evaluation of the New Version of the Laser-Optical Disdrometer, OTT Parsivel2, J. Atmos. Ocean. Tech., 31, 1276–1288, https://doi.org/10.1175/jtech-d-13-00174.1, 2014.
Wang, C., Xia, H., Shangguan, M., Wu, Y., Wang, L., Zhao, L., Qiu, J., and Zhang, R.: 1.5 µm polarization coherent lidar incorporating time-division multiplexing, Opt. Express, 25, 20663–20674, https://doi.org/10.1364/oe.25.020663, 2017.
Wang, C., Xia, H., Wu, Y., Dong, J., Wei, T., Wang, L., and Dou, X.: Meter-scale spatial-resolution-coherent Doppler wind lidar based on Golay coding, Opt. Lett., 44, 311–314, https://doi.org/10.1364/OL.44.000311, 2019a.
Wang, C., Jia, M., Xia, H., Wu, Y., Wei, T., Shang, X., Yang, C., Xue, X., and Dou, X.: Relationship analysis of PM2.5 and boundary layer height using an aerosol and turbulence detection lidar, Atmos. Meas. Tech., 12, 3303–3315, https://doi.org/10.5194/amt-12-3303-2019, 2019b.
Wang, D., Stachlewska, I. S., Delanoë, J., Ene, D., Song, X., and Schüttemeyer, D.: Spatio-temporal discrimination of molecular, aerosol and cloud scattering and polarization using a combination of a Raman lidar, Doppler cloud radar and microwave radiometer, Opt. Express, 28, 20117–20134, https://doi.org/10.1364/OE.393625, 2020.
Wang, F., Liu, H., Dong, W., Zhang, Y., Yao, W., and Zheng, D.: Radar Reflectivity of Lightning Flashes in Stratiform Regions of Mesoscale Convective Systems, J. Geophys. Res.-Atmos., 124, 14114–14132, https://doi.org/10.1029/2019JD031238, 2019.
Wang, H., Liu, Y., Duan, J., Shi, Y., Lou, X., and Li, J.: Assimilation of Radar Reflectivity Using a Time-Lagged Ensemble Based Ensemble Kalman Filter With the “Cloud-Dependent” Background Error Covariances, J. Geophys. Res.-Atmos., 127, e2021JD036207, https://doi.org/10.1029/2021JD036207, 2022.
Wang, L., Qiang, W., Xia, H., Wei, T., Yuan, J., and Jiang, P.: Robust Solution for Boundary Layer Height Detections with Coherent Doppler Wind Lidar, Adv. Atmos. Sci., 38, 1920–1928, https://doi.org/10.1007/s00376-021-1068-0, 2021.
Wang, L., Yuan, J., Xia, H., Zhao, L., and Wu, Y.: Marine Mixed Layer Height Detection Using Ship-Borne Coherent Doppler Wind Lidar Based on Constant Turbulence Threshold, Remote Sens.-Basel, 14, 745, https://doi.org/10.3390/rs14030745, 2022.
Wei, T., Xia, H., Hu, J., Wang, C., Shangguan, M., Wang, L., Jia, M., and Dou, X.: Simultaneous wind and rainfall detection by power spectrum analysis using a VAD scanning coherent Doppler lidar, Opt. Express, 27, 31235–31245, https://doi.org/10.1364/oe.27.031235, 2019.
Wei, T., Xia, H., Wu, Y., Yuan, J., Wang, C., and Dou, X.: Inversion probability enhancement of all-fiber CDWL by noise modeling and robust fitting, Opt. Express, 28, 29662–29675, https://doi.org/10.1364/oe.401054, 2020.
Wei, T., Xia, H., Yue, B., Wu, Y., and Liu, Q.: Remote sensing of raindrop size distribution using the coherent Doppler lidar, Opt. Express, 29, 17246–17257, https://doi.org/10.1364/OE.426326, 2021.
Wei, T., Xia, H., Wu, K., Yang, Y., Liu, Q., and Ding, W.: Dark/bright band of a melting layer detected by coherent Doppler lidar and micro rain radar, Opt. Express, 30, 3654–3664, https://doi.org/10.1364/oe.450714, 2022.
Williams, E. R.: The Electrification of Thunderstorms, Sci. Am., 259, 88–99, https://www.jstor.org/stable/24989265 (last access: 30 November 2023), 1988.
Williams, E. R.: The tripole structure of thunderstorms, J. Geophys. Res.-Atmos., 94, 13151–13167, https://doi.org/10.1029/JD094iD11p13151, 1989.
Williams, E. R.: The Electrification of Severe Storms, in: Severe Convective Storms, edited by: Doswell, C. A., American Meteorological Society, Boston, MA, 527–561, https://doi.org/10.1007/978-1-935704-06-5_13, 2001.
Wu, K.: A thundercloud lidar results during the experiment, figshare [data set], https://doi.org/10.6084/m9.figshare.20326350.v2, 2022a.
Wu, K.: A thundercloud rader results during the experiment, figshare [data set], https://doi.org/10.6084/m9.figshare.20326377.v1, 2022b.
Wu, K.: Lightning data detected by lightning location array, figshare [data set], https://doi.org/10.6084/m9.figshare.20588385.v4, 2022c.
Wu, K.: raw data and Converted data video of CDWL during this experiment, figshare [data set], https://doi.org/10.6084/m9.figshare.21590433.v3, 2022d.
Wu, K.: raindrop spectrometer data, figshare [data set], https://doi.org/10.6084/m9.figshare.22256617.v1, 2023.
Yang, J., Zhang, Z., Wei, C., Lu, F., and Guo, Q.: Introducing the New Generation of Chinese Geostationary Weather Satellites, Fengyun-4, B. Am. Meteorol. Soc., 98, 1637–1658, https://doi.org/10.1175/bams-d-16-0065.1, 2017.
Yang, J., Zhao, K., Zheng, Y., Chen, H., and Chen, G.: Microphysical Structure of Thunderstorms and Their Lightning Activity During the mei-yu and Post-mei-yu Periods Over Nanjing, Yangtze River Delta, Geophys. Res. Lett., 49, e2022GL100952, https://doi.org/10.1029/2022GL100952, 2022.
Yuan, J., Xia, H., Wei, T., Wang, L., Yue, B., and Wu, Y.: Identifying cloud, precipitation, windshear, and turbulence by deep analysis of the power spectrum of coherent Doppler wind lidar, Opt. Express, 28, 37406–37418, https://doi.org/10.1364/oe.412809, 2020.
Yuan, J., Wu, K., Wei, T., Wang, L., Shu, Z., Yang, Y., and Xia, H.: Cloud Seeding Evidenced by Coherent Doppler Wind Lidar, Remote Sens.-Basel, 13, 3815, https://doi.org/10.3390/rs13193815, 2021.
Yuan, J., Su, L., Xia, H., Li, Y., Zhang, M., Zhen, G., and Li, J.: Microburst, Windshear, Gust Front, and Vortex Detection in Mega Airport Using a Single Coherent Doppler Wind Lidar, Remote Sens.-Basel, 14, https://doi.org/10.3390/rs14071626, 2022a.
Yuan, J., Wu, Y., Shu, Z., Su, L., Tang, D., Yang, Y., Dong, J., Yu, S., Zhang, Z., and Xia, H.: Real-Time Synchronous 3-D Detection of Air Pollution and Wind Using a Solo Coherent Doppler Wind Lidar, Remote Sens.-Basel, 14, 2809, https://doi.org/10.3390/rs14122809, 2022b.
Zhang, Y., Zhang, Y., Zou, M., Wang, J., Li, Y., Tan, Y., Feng, Y., Zhang, H., and Zhu, S.: Advances in Lightning Monitoring and Location Technology Research in China, Remote Sens.-Basel, 14, 1293, https://doi.org/10.3390/rs14051293, 2022.
Zhao, C., Zhang, Y., Zheng, D., Zhou, Y., Xiao, H., and Zhang, X.: An improved hydrometeor identification method for X-band dual-polarization radar and its application for one summer Hailstorm over Northern China, Atmos. Res., 245, 105075, https://doi.org/10.1016/j.atmosres.2020.105075, 2020.
Short summary
A compact all-fiber coherent Doppler wind lidar (CDWL) working at the 1.5 µm wavelength is applied to probe the dynamics and microphysics structure of thunderstorms. It was found that thunderclouds below the 0 ℃ isotherm have significant spectrum broadening and an increase in skewness, and that lightning affects the microphysics structure of the thundercloud. It is proven that the precise spectrum of CDWL is a promising indicator for studying the charge structure of thunderstorms.
A compact all-fiber coherent Doppler wind lidar (CDWL) working at the 1.5 µm wavelength is...
