Articles | Volume 12, issue 11
https://doi.org/10.5194/amt-12-6037-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-12-6037-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Retrieval of cloud properties from spectral zenith radiances observed by sky radiometers
Pradeep Khatri
CORRESPONDING AUTHOR
Center for Atmospheric and Oceanic Studies, Graduate School of
Science, Tohoku University, Sendai, Japan
Hironobu Iwabuchi
Center for Atmospheric and Oceanic Studies, Graduate School of
Science, Tohoku University, Sendai, Japan
Tadahiro Hayasaka
Center for Atmospheric and Oceanic Studies, Graduate School of
Science, Tohoku University, Sendai, Japan
Hitoshi Irie
Center for Environmental Remote Sensing, Chiba University, Chiba,
Japan
Tamio Takamura
Center for Environmental Remote Sensing, Chiba University, Chiba,
Japan
Akihiro Yamazaki
Climate Research Department, Meteorological Research Institute, Tsukuba, Japan
Alessandro Damiani
Center for Environmental Remote Sensing, Chiba University, Chiba,
Japan
Husi Letu
Institute of Remote Sensing and Digital Earth, Chinese Academy of
Sciences, Beijing, China
School of Environment Science and Spatial Informatics, China University of Mining
and Technology, Xuzhou, China
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Preprint withdrawn
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Hossain M. S. Hoque, Kengo Sudo, Hitoshi Irie, Alessandro Damiani, and Al Mashroor Fatmi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-815, https://doi.org/10.5194/acp-2021-815, 2021
Revised manuscript not accepted
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Isabelle De Smedt, Gaia Pinardi, Corinne Vigouroux, Steven Compernolle, Alkis Bais, Nuria Benavent, Folkert Boersma, Ka-Lok Chan, Sebastian Donner, Kai-Uwe Eichmann, Pascal Hedelt, François Hendrick, Hitoshi Irie, Vinod Kumar, Jean-Christopher Lambert, Bavo Langerock, Christophe Lerot, Cheng Liu, Diego Loyola, Ankie Piters, Andreas Richter, Claudia Rivera Cárdenas, Fabian Romahn, Robert George Ryan, Vinayak Sinha, Nicolas Theys, Jonas Vlietinck, Thomas Wagner, Ting Wang, Huan Yu, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 12561–12593, https://doi.org/10.5194/acp-21-12561-2021, https://doi.org/10.5194/acp-21-12561-2021, 2021
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This paper assess the performances of the TROPOMI formaldehyde observations compared to its predecessor OMI at different spatial and temporal scales. We also use a global network of MAX-DOAS instruments to validate both satellite datasets for a large range of HCHO columns. The precision obtained with daily TROPOMI observations is comparable to monthly OMI observations. We present clear detection of weak HCHO column enhancements related to shipping emissions in the Indian Ocean.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, Bo Qiu, Jun Ge, Kai Qin, Yong Xue, and Jian Peng
Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, https://doi.org/10.5194/hess-25-4209-2021, 2021
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Rei Kudo, Henri Diémoz, Victor Estellés, Monica Campanelli, Masahiro Momoi, Franco Marenco, Claire L. Ryder, Osamu Ijima, Akihiro Uchiyama, Kouichi Nakashima, Akihiro Yamazaki, Ryoji Nagasawa, Nozomu Ohkawara, and Haruma Ishida
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Mizuo Kajino, Makoto Deushi, Tsuyoshi Thomas Sekiyama, Naga Oshima, Keiya Yumimoto, Taichu Yasumichi Tanaka, Joseph Ching, Akihiro Hashimoto, Tetsuya Yamamoto, Masaaki Ikegami, Akane Kamada, Makoto Miyashita, Yayoi Inomata, Shin-ichiro Shima, Pradeep Khatri, Atsushi Shimizu, Hitoshi Irie, Kouji Adachi, Yuji Zaizen, Yasuhito Igarashi, Hiromasa Ueda, Takashi Maki, and Masao Mikami
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This study compares performance of aerosol representation methods of the Japan Meteorological Agency's regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). It indicates separate treatment of sea salt and dust in coarse mode and that of light-absorptive and non-absorptive particles in fine mode could provide accurate assessments on aerosol feedback processes.
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
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This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Nicolas Theys, Nader Abuhassan, Alkiviadis Bais, Folkert Boersma, Alexander Cede, Jihyo Chong, Sebastian Donner, Theano Drosoglou, Anatoly Dzhola, Henk Eskes, Udo Frieß, José Granville, Jay R. Herman, Robert Holla, Jari Hovila, Hitoshi Irie, Yugo Kanaya, Dimitris Karagkiozidis, Natalia Kouremeti, Jean-Christopher Lambert, Jianzhong Ma, Enno Peters, Ankie Piters, Oleg Postylyakov, Andreas Richter, Julia Remmers, Hisahiro Takashima, Martin Tiefengraber, Pieter Valks, Tim Vlemmix, Thomas Wagner, and Folkard Wittrock
Atmos. Meas. Tech., 13, 6141–6174, https://doi.org/10.5194/amt-13-6141-2020, https://doi.org/10.5194/amt-13-6141-2020, 2020
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We validate several GOME-2 and OMI tropospheric NO2 products with 23 MAX-DOAS and 16 direct sun instruments distributed worldwide, highlighting large horizontal inhomogeneities at several sites affecting the validation results. We propose a method for quantification and correction. We show the application of such correction reduces the satellite underestimation in almost all heterogeneous cases, but a negative bias remains over the MAX-DOAS and direct sun network ensemble for both satellites.
Mengyao Liu, Jintai Lin, Hao Kong, K. Folkert Boersma, Henk Eskes, Yugo Kanaya, Qin He, Xin Tian, Kai Qin, Pinhua Xie, Robert Spurr, Ruijing Ni, Yingying Yan, Hongjian Weng, and Jingxu Wang
Atmos. Meas. Tech., 13, 4247–4259, https://doi.org/10.5194/amt-13-4247-2020, https://doi.org/10.5194/amt-13-4247-2020, 2020
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Nitrogen oxides (NOx = NO + NO2) are important air pollutants in the troposphere and play crucial roles in the formation of ozone and particulate matter. The recently launched TROPOspheric Monitoring Instrument (TROPOMI) provides an opportunity to retrieve tropospheric concentrations of nitrogen dioxide (NO2) at an unprecedented high horizontal resolution. This work presents a new NO2 retrieval product over East Asia and further quantifies key factors affecting the retrieval, including aerosol.
Teruyuki Nakajima, Monica Campanelli, Huizheng Che, Victor Estellés, Hitoshi Irie, Sang-Woo Kim, Jhoon Kim, Dong Liu, Tomoaki Nishizawa, Govindan Pandithurai, Vijay Kumar Soni, Boossarasiri Thana, Nas-Urt Tugjsurn, Kazuma Aoki, Sujung Go, Makiko Hashimoto, Akiko Higurashi, Stelios Kazadzis, Pradeep Khatri, Natalia Kouremeti, Rei Kudo, Franco Marenco, Masahiro Momoi, Shantikumar S. Ningombam, Claire L. Ryder, Akihiro Uchiyama, and Akihiro Yamazaki
Atmos. Meas. Tech., 13, 4195–4218, https://doi.org/10.5194/amt-13-4195-2020, https://doi.org/10.5194/amt-13-4195-2020, 2020
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This paper overviews the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. The paper also discusses current issues of SKYNET to provide better information for the community.
Masahiro Momoi, Rei Kudo, Kazuma Aoki, Tatsuhiro Mori, Kazuhiko Miura, Hiroshi Okamoto, Hitoshi Irie, Yoshinori Shoji, Akihiro Uchiyama, Osamu Ijima, Matsumi Takano, and Teruyuki Nakajima
Atmos. Meas. Tech., 13, 2635–2658, https://doi.org/10.5194/amt-13-2635-2020, https://doi.org/10.5194/amt-13-2635-2020, 2020
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The water vapor channel of sun photometers, such as a sky radiometer, has been calibrated at limited observation sites (e.g., Mauna Loa) in previous studies, but our procedure has made on-site calibration possible by using sky radiances in addition to direct solar irradiance. The retrieved precipitable water vapor values correspond well to those derived from a global-navigation-satellite-system–global-positioning-system receiver, a microwave radiometer, and an AERONET sun–sky radiometer.
Karin Kreher, Michel Van Roozendael, Francois Hendrick, Arnoud Apituley, Ermioni Dimitropoulou, Udo Frieß, Andreas Richter, Thomas Wagner, Johannes Lampel, Nader Abuhassan, Li Ang, Monica Anguas, Alkis Bais, Nuria Benavent, Tim Bösch, Kristof Bognar, Alexander Borovski, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Henning Finkenzeller, David Garcia-Nieto, Clio Gielen, Laura Gómez-Martín, Nan Hao, Bas Henzing, Jay R. Herman, Christian Hermans, Syedul Hoque, Hitoshi Irie, Junli Jin, Paul Johnston, Junaid Khayyam Butt, Fahim Khokhar, Theodore K. Koenig, Jonas Kuhn, Vinod Kumar, Cheng Liu, Jianzhong Ma, Alexis Merlaud, Abhishek K. Mishra, Moritz Müller, Monica Navarro-Comas, Mareike Ostendorf, Andrea Pazmino, Enno Peters, Gaia Pinardi, Manuel Pinharanda, Ankie Piters, Ulrich Platt, Oleg Postylyakov, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Alfonso Saiz-Lopez, Anja Schönhardt, Stefan F. Schreier, André Seyler, Vinayak Sinha, Elena Spinei, Kimberly Strong, Frederik Tack, Xin Tian, Martin Tiefengraber, Jan-Lukas Tirpitz, Jeroen van Gent, Rainer Volkamer, Mihalis Vrekoussis, Shanshan Wang, Zhuoru Wang, Mark Wenig, Folkard Wittrock, Pinhua H. Xie, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 13, 2169–2208, https://doi.org/10.5194/amt-13-2169-2020, https://doi.org/10.5194/amt-13-2169-2020, 2020
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In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants during an instrument intercomparison campaign (CINDI-2) at Cabauw, the Netherlands. Here we report on the outcome of this intercomparison exercise. The three major goals were to characterise the differences between the participating instruments, to define a robust methodology for performance assessment, and to contribute to the harmonisation of the measurement settings and retrieval methods.
Zhe Jiang, Minzheng Duan, Huizheng Che, Wenxing Zhang, Teruyuki Nakajima, Makiko Hashimoto, Bin Chen, and Akihiro Yamazaki
Atmos. Meas. Tech., 13, 1195–1212, https://doi.org/10.5194/amt-13-1195-2020, https://doi.org/10.5194/amt-13-1195-2020, 2020
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This study analyzed the aerosol optical properties derived by SKYRAD.pack versions 5.0 and 4.2 using the radiometer measurements over Qionghai and Yucheng in China, which are two new sites of SKYNET. The seasonal variability of the aerosol properties over the two sites were investigated based on SKYRAD.pack V5.0. The validation results provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks.
Bin Yao, Chao Liu, Yan Yin, Zhiquan Liu, Chunxiang Shi, Hironobu Iwabuchi, and Fuzhong Weng
Atmos. Meas. Tech., 13, 1033–1049, https://doi.org/10.5194/amt-13-1033-2020, https://doi.org/10.5194/amt-13-1033-2020, 2020
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Due to the complex spatiotemporal and physical properties of clouds, their quantitative depictions in different atmospheric reanalysis datasets are still highly uncertain. A radiance-based evaluation approach is developed to evaluate the quality of cloud properties by directly comparing them with satellite radiance observations. ERA5 and CRA are found to have great capability in representing the cloudy atmosphere over East Asia, and MERRA-2 tends to slightly overestimate clouds over the region.
Akihiro Uchiyama, Masataka Shiobara, Hiroshi Kobayashi, Tsuneo Matsunaga, Akihiro Yamazaki, Kazunori Inei, Kazuhiro Kawai, and Yoshiaki Watanabe
Atmos. Meas. Tech., 12, 6465–6488, https://doi.org/10.5194/amt-12-6465-2019, https://doi.org/10.5194/amt-12-6465-2019, 2019
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The majority of aerosol data are obtained from daytime measurements using the Sun as a light source, and there are few datasets available for studying nighttime aerosol characteristics. To estimate the aerosol optical depth (AOD) during the nighttime using the moon as a light source, a radiometer for the daytime was modified, and a new calibration method was developed. As a result, the estimations of the nighttime AOD were made with the same degree of precision and accuracy during the daytime.
Xianyi Yang, Huizheng Che, Hitoshi Irie, Quanliang Chen, Ke Gui, Ying Cai, Yu Zheng, Linchang An, Hujia Zhao, Lei Li, Yuanxin Liang, Yaqiang Wang, Hong Wang, and Xiaoye Zhang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-339, https://doi.org/10.5194/amt-2019-339, 2019
Preprint withdrawn
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This study assesses the performance of SKYNET in comparison to AERONET (Aerosol Robotic Network) for retrieving aerosol optical properties (AOPs) in Beijing, China. SKYNET data retrieved by SR-CEReS analysis package are used to analyze a serious pollution event in winter over Beijing. The AOPs under three weather conditions (clean, dusty, haze) in Beijing are discussed. Measurements from the SKYNET skyradiometer can be used to analyze the AOPs over Beijing reasonably.
Pavle Arsenovic, Alessandro Damiani, Eugene Rozanov, Bernd Funke, Andrea Stenke, and Thomas Peter
Atmos. Chem. Phys., 19, 9485–9494, https://doi.org/10.5194/acp-19-9485-2019, https://doi.org/10.5194/acp-19-9485-2019, 2019
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Low-energy electrons (LEE) are the dominant source of odd nitrogen, which destroys ozone, in the mesosphere and stratosphere in polar winter in the geomagnetically active periods. However, the observed stratospheric ozone anomalies can be reproduced only when accounting for both low- and middle-range energy electrons (MEE) in the chemistry-climate model. Ozone changes may induce further dynamical and thermal changes in the atmosphere. We recommend including both LEE and MEE in climate models.
Hitoshi Irie, Hossain Mohammed Syedul Hoque, Alessandro Damiani, Hiroshi Okamoto, Al Mashroor Fatmi, Pradeep Khatri, Tamio Takamura, and Thanawat Jarupongsakul
Atmos. Meas. Tech., 12, 599–606, https://doi.org/10.5194/amt-12-599-2019, https://doi.org/10.5194/amt-12-599-2019, 2019
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The first intensive multicomponent observation by sky radiometer and MAX-DOAS was performed in Thailand during the 2016 dry season. We found that the concentration of formaldehyde (HCHO) was a useful tracer for biomass burning plumes. With the HCHO enhancement, the ratio of gaseous glyoxal to HCHO concentrations decreased and the aerosol absorption optical depths (AAODs) increased. The wavelength dependence of AAODs was quantified, providing evidence for the presence of brown carbon aerosols.
K. Folkert Boersma, Henk J. Eskes, Andreas Richter, Isabelle De Smedt, Alba Lorente, Steffen Beirle, Jos H. G. M. van Geffen, Marina Zara, Enno Peters, Michel Van Roozendael, Thomas Wagner, Joannes D. Maasakkers, Ronald J. van der A, Joanne Nightingale, Anne De Rudder, Hitoshi Irie, Gaia Pinardi, Jean-Christopher Lambert, and Steven C. Compernolle
Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, https://doi.org/10.5194/amt-11-6651-2018, 2018
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This paper describes a new, improved data record of 22+ years of coherent nitrogen dioxide (NO2) pollution measurements from different satellite instruments. Our work helps to ensure that climate data are of sufficient quality to draw reliable conclusions and shape decisions. It shows how dedicated intercomparisons of retrieval sub-steps have led to improved NO2 measurements from the GOME, SCIAMACHY, GOME-2(A), and OMI sensors, and how quality assurance of the new data product is achieved.
X. Han, G. Tana, K. Qin, and H. Letu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 9–15, https://doi.org/10.5194/isprs-archives-XLII-3-W5-9-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-9-2018, 2018
H. Shang, H. Letu, Z. Peng, and Z. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 61–66, https://doi.org/10.5194/isprs-archives-XLII-3-W5-61-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-61-2018, 2018
X. Shi, C. Zhao, K. Qin, Y. Yang, K. Zhang, and H. Fan
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 73–76, https://doi.org/10.5194/isprs-archives-XLII-3-W5-73-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-73-2018, 2018
J. Zou, K. Qin, J. Xu, and X. Han
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W5, 83–88, https://doi.org/10.5194/isprs-archives-XLII-3-W5-83-2018, https://doi.org/10.5194/isprs-archives-XLII-3-W5-83-2018, 2018
Akihiro Uchiyama, Tsuneo Matsunaga, and Akihiro Yamazaki
Atmos. Meas. Tech., 11, 5363–5388, https://doi.org/10.5194/amt-11-5363-2018, https://doi.org/10.5194/amt-11-5363-2018, 2018
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Atmospheric aerosols are an important constituent of the atmosphere. Measurement networks using radiometers such as SKYNET have been developed. There are two constants that we must determine to make accurate measurements. One of them is the calibration constant. The accuracy of the current method to determine this was investigated and the new method for water vapor and near-infrared channels was developed. Utilizing the results of this paper, SKYNET measurement data will become more reliable.
Akihiro Uchiyama, Tsuneo Matsunaga, and Akihiro Yamazaki
Atmos. Meas. Tech., 11, 5389–5402, https://doi.org/10.5194/amt-11-5389-2018, https://doi.org/10.5194/amt-11-5389-2018, 2018
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Atmospheric aerosols are an important constituent of the atmosphere. Measurement networks using radiometers such as SKYNET have been developed. There are two constants that we must determine. One of them is the solid view angle (SVA) of the radiometer. The problems related to SVA were investigated. It was shown that the conventional method can cause a systematic underestimation, and an improved method was proposed. Utilizing the results of this paper, SKYNET data will become more reliable.
Q. Gao, D. Dong, X. Yang, L. Husi, and H. Shang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 363–370, https://doi.org/10.5194/isprs-archives-XLII-3-363-2018, https://doi.org/10.5194/isprs-archives-XLII-3-363-2018, 2018
Alessandro Damiani, Hitoshi Irie, Takashi Horio, Tamio Takamura, Pradeep Khatri, Hideaki Takenaka, Takashi Nagao, Takashi Y. Nakajima, and Raul R. Cordero
Atmos. Meas. Tech., 11, 2501–2521, https://doi.org/10.5194/amt-11-2501-2018, https://doi.org/10.5194/amt-11-2501-2018, 2018
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The Tohoku Earthquake of March 2011 stressed the need for energy source diversity, and the governmental policy in Japan has been stimulating a broader use of
renewable energy. Solar power is potentially able to mitigate climate change triggered by greenhouse gas emissions, but its instability caused by cloudiness
is a critical issue for suppliers. To develop an appropriate control system, surface solar radiation data must be made available as accurately as possible.
Jungbin Mok, Nickolay A. Krotkov, Omar Torres, Hiren Jethva, Zhanqing Li, Jhoon Kim, Ja-Ho Koo, Sujung Go, Hitoshi Irie, Gordon Labow, Thomas F. Eck, Brent N. Holben, Jay Herman, Robert P. Loughman, Elena Spinei, Seoung Soo Lee, Pradeep Khatri, and Monica Campanelli
Atmos. Meas. Tech., 11, 2295–2311, https://doi.org/10.5194/amt-11-2295-2018, https://doi.org/10.5194/amt-11-2295-2018, 2018
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Measuring aerosol absorption from the shortest ultraviolet (UV) to the near-infrared (NIR) wavelengths is important for studies of climate, tropospheric photochemistry, human health, and agricultural productivity. We estimate the accuracy and demonstrate consistency of aerosol absorption retrievals from different instruments, after accounting for spectrally varying surface albedo and gaseous absorption.
Tomohiro O. Sato, Takao M. Sato, Hideo Sagawa, Katsuyuki Noguchi, Naoko Saitoh, Hitoshi Irie, Kazuyuki Kita, Mona E. Mahani, Koji Zettsu, Ryoichi Imasu, Sachiko Hayashida, and Yasuko Kasai
Atmos. Meas. Tech., 11, 1653–1668, https://doi.org/10.5194/amt-11-1653-2018, https://doi.org/10.5194/amt-11-1653-2018, 2018
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Air pollution is one of the world's greatest environmental health risks. Ozone adversely affects human health and agricultural production, and the tropospheric ozone has been increasing globally over the past few decades. We report an advanced method to derive the ozone amount in the lowermost troposphere using multi-spectral measurements (UV, thermal infrared and microwave). Combining the MW measurement with the UV and thermal infrared measurements certainly increased the sensitivity.
Rintaro Okamura, Hironobu Iwabuchi, and K. Sebastian Schmidt
Atmos. Meas. Tech., 10, 4747–4759, https://doi.org/10.5194/amt-10-4747-2017, https://doi.org/10.5194/amt-10-4747-2017, 2017
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Three-dimensional (3-D) radiative transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. Multi-pixel, multispectral approaches based on deep learning are proposed for retrieval of cloud optical thickness and droplet effective radius. A feasibility test shows that proposed retrieval methods are effective to obtain accurate cloud properties. Use of the convolutional neural network is effective to reduce 3-D radiative transfer effects.
K. L. Chan and K. Qin
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 29–36, https://doi.org/10.5194/isprs-archives-XLII-2-W7-29-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-29-2017, 2017
Osamu Uchino, Tetsu Sakai, Toshiharu Izumi, Tomohiro Nagai, Isamu Morino, Akihiro Yamazaki, Makoto Deushi, Keiya Yumimoto, Takashi Maki, Taichu Y. Tanaka, Taiga Akaho, Hiroshi Okumura, Kohei Arai, Takahiro Nakatsuru, Tsuneo Matsunaga, and Tatsuya Yokota
Atmos. Chem. Phys., 17, 1865–1879, https://doi.org/10.5194/acp-17-1865-2017, https://doi.org/10.5194/acp-17-1865-2017, 2017
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To validate products of GOSAT, we observed vertical profiles of aerosols, thin cirrus clouds, and tropospheric ozone with a mobile lidar system that consisted of a two-wavelength (532 and 1064 nm) polarization lidar and tropospheric ozone differential absorption lidar (DIAL). We used these lidars to make continuous measurements over Saga (33.24° N, 130.29° E) during 20–31 March 2015. High ozone and high aerosol concentrations were observed almost simultaneously and impacted surface air quality.
Shi Song, K. Sebastian Schmidt, Peter Pilewskie, Michael D. King, Andrew K. Heidinger, Andi Walther, Hironobu Iwabuchi, Gala Wind, and Odele M. Coddington
Atmos. Chem. Phys., 16, 13791–13806, https://doi.org/10.5194/acp-16-13791-2016, https://doi.org/10.5194/acp-16-13791-2016, 2016
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The radiative effects of spatially complex cloud fields are notoriously difficult to estimate and are afflicted with errors up to ±50 % of the incident solar radiation. We find that horizontal photon transport, the leading cause for these three-dimensional effects, manifests itself through a spectral fingerprint – a new observable that holds promise for reducing the errors associated with spatial complexity by moving the problem to the spectral dimension.
Husi Letu, Hiroshi Ishimoto, Jerome Riedi, Takashi Y. Nakajima, Laurent C.-Labonnote, Anthony J. Baran, Takashi M. Nagao, and Miho Sekiguchi
Atmos. Chem. Phys., 16, 12287–12303, https://doi.org/10.5194/acp-16-12287-2016, https://doi.org/10.5194/acp-16-12287-2016, 2016
Lixin Wu, Shuo Zheng, Angelo De Santis, Kai Qin, Rosa Di Mauro, Shanjun Liu, and Mario Luigi Rainone
Nat. Hazards Earth Syst. Sci., 16, 1859–1880, https://doi.org/10.5194/nhess-16-1859-2016, https://doi.org/10.5194/nhess-16-1859-2016, 2016
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Many anomalies before the 2009 L'Aquila earthquake were reported but not synergically analyzed referring to geosystem coupling. We investigated changes of multiple hydrothermal parameters in coversphere and atmosphere and studied 3-D evolution of b value in lithosphere. Quasi-synchronism of pre-earthquake anomalies georelating to particular thrusts and local topography are revealed. A geosphere coupling mode is proposed interpreting the function of CO2-rich crust fluids on local LCA coupling.
U. Frieß, H. Klein Baltink, S. Beirle, K. Clémer, F. Hendrick, B. Henzing, H. Irie, G. de Leeuw, A. Li, M. M. Moerman, M. van Roozendael, R. Shaiganfar, T. Wagner, Y. Wang, P. Xie, S. Yilmaz, and P. Zieger
Atmos. Meas. Tech., 9, 3205–3222, https://doi.org/10.5194/amt-9-3205-2016, https://doi.org/10.5194/amt-9-3205-2016, 2016
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This article describes the first direct comparison of aerosol extinction profiles from Multi-Axis DOAS measurements of the oxygen collision complex using five different retrieval algorithms. A comparison of the retrieved profiles with co-located aerosol measurements shows good agreement with respect to profile shape and aerosol optical thickness. This study shows that MAX-DOAS is a simple, versatile and cost-effective method for the measurement of aerosol properties in the lower troposphere.
H. Ohyama, S. Kawakami, T. Tanaka, I. Morino, O. Uchino, M. Inoue, T. Sakai, T. Nagai, A. Yamazaki, A. Uchiyama, T. Fukamachi, M. Sakashita, T. Kawasaki, T. Akaho, K. Arai, and H. Okumura
Atmos. Meas. Tech., 8, 5263–5276, https://doi.org/10.5194/amt-8-5263-2015, https://doi.org/10.5194/amt-8-5263-2015, 2015
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We derived time series of column-averaged dry-air mole fractions of carbon dioxide and methane (XCO2 and XCH4) at Saga, Japan, with a ground-based high-resolution Fourier transform spectrometer (g-b FTS). The g-b FTS XCO2 and XCH4 data were compared with those derived from a satellite-based instrument (TANSO-FTS onboard GOSAT). Using aerosol information measured simultaneously with a sky radiometer and a lidar at Saga, we evaluated the influence of aerosols on the satellite observations.
M. Saito and H. Iwabuchi
Atmos. Meas. Tech., 8, 4295–4311, https://doi.org/10.5194/amt-8-4295-2015, https://doi.org/10.5194/amt-8-4295-2015, 2015
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A new algorithm for aerosol retrievals from twilight photographs taken by a digital single reflex-lens camera is developed. A radiative transfer model taking spherical-shell atmosphere, multiple scattering and refraction into account is used as a forward model, and the optimal estimation is used as an inversion calculation to infer the aerosol optical and radiative properties. The AOTs are inferred with small uncertainties and agree very well with that from the skyradiometer.
H. Irie, T. Nakayama, A. Shimizu, A. Yamazaki, T. Nagai, A. Uchiyama, Y. Zaizen, S. Kagamitani, and Y. Matsumi
Atmos. Meas. Tech., 8, 2775–2788, https://doi.org/10.5194/amt-8-2775-2015, https://doi.org/10.5194/amt-8-2775-2015, 2015
L. N. Lamsal, N. A. Krotkov, E. A. Celarier, W. H. Swartz, K. E. Pickering, E. J. Bucsela, J. F. Gleason, R. V. Martin, S. Philip, H. Irie, A. Cede, J. Herman, A. Weinheimer, J. J. Szykman, and T. N. Knepp
Atmos. Chem. Phys., 14, 11587–11609, https://doi.org/10.5194/acp-14-11587-2014, https://doi.org/10.5194/acp-14-11587-2014, 2014
K. Noguchi, A. Richter, V. Rozanov, A. Rozanov, J. P. Burrows, H. Irie, and K. Kita
Atmos. Meas. Tech., 7, 3497–3508, https://doi.org/10.5194/amt-7-3497-2014, https://doi.org/10.5194/amt-7-3497-2014, 2014
Y. Kanaya, H. Irie, H. Takashima, H. Iwabuchi, H. Akimoto, K. Sudo, M. Gu, J. Chong, Y. J. Kim, H. Lee, A. Li, F. Si, J. Xu, P.-H. Xie, W.-Q. Liu, A. Dzhola, O. Postylyakov, V. Ivanov, E. Grechko, S. Terpugova, and M. Panchenko
Atmos. Chem. Phys., 14, 7909–7927, https://doi.org/10.5194/acp-14-7909-2014, https://doi.org/10.5194/acp-14-7909-2014, 2014
M. Campanelli, T. Nakajima, P. Khatri, T. Takamura, A. Uchiyama, V. Estelles, G. L. Liberti, and V. Malvestuto
Atmos. Meas. Tech., 7, 1075–1087, https://doi.org/10.5194/amt-7-1075-2014, https://doi.org/10.5194/amt-7-1075-2014, 2014
S. Itahashi, I. Uno, H. Irie, J.-I. Kurokawa, and T. Ohara
Atmos. Chem. Phys., 14, 3623–3635, https://doi.org/10.5194/acp-14-3623-2014, https://doi.org/10.5194/acp-14-3623-2014, 2014
J.-T. Lin, R. V. Martin, K. F. Boersma, M. Sneep, P. Stammes, R. Spurr, P. Wang, M. Van Roozendael, K. Clémer, and H. Irie
Atmos. Chem. Phys., 14, 1441–1461, https://doi.org/10.5194/acp-14-1441-2014, https://doi.org/10.5194/acp-14-1441-2014, 2014
Y. Kanaya, H. Akimoto, Z.-F. Wang, P. Pochanart, K. Kawamura, Y. Liu, J. Li, Y. Komazaki, H. Irie, X.-L. Pan, F. Taketani, K. Yamaji, H. Tanimoto, S. Inomata, S. Kato, J. Suthawaree, K. Okuzawa, G. Wang, S. G. Aggarwal, P. Q. Fu, T. Wang, J. Gao, Y. Wang, and G. Zhuang
Atmos. Chem. Phys., 13, 8265–8283, https://doi.org/10.5194/acp-13-8265-2013, https://doi.org/10.5194/acp-13-8265-2013, 2013
K. Qin, L. X. Wu, X. Y. Ouyang, X. H. Shen, and S. Zheng
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-1-2439-2013, https://doi.org/10.5194/nhessd-1-2439-2013, 2013
Revised manuscript has not been submitted
K. Kawamura, K. Okuzawa, S. G. Aggarwal, H. Irie, Y. Kanaya, and Z. Wang
Atmos. Chem. Phys., 13, 5369–5380, https://doi.org/10.5194/acp-13-5369-2013, https://doi.org/10.5194/acp-13-5369-2013, 2013
H. Irie, K. Yamaji, K. Ikeda, I. Uno, S. Itahashi, T. Ohara, and J. Kurokawa
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-14037-2013, https://doi.org/10.5194/acpd-13-14037-2013, 2013
Preprint withdrawn
G. Pinardi, M. Van Roozendael, N. Abuhassan, C. Adams, A. Cede, K. Clémer, C. Fayt, U. Frieß, M. Gil, J. Herman, C. Hermans, F. Hendrick, H. Irie, A. Merlaud, M. Navarro Comas, E. Peters, A. J. M. Piters, O. Puentedura, A. Richter, A. Schönhardt, R. Shaiganfar, E. Spinei, K. Strong, H. Takashima, M. Vrekoussis, T. Wagner, F. Wittrock, and S. Yilmaz
Atmos. Meas. Tech., 6, 167–185, https://doi.org/10.5194/amt-6-167-2013, https://doi.org/10.5194/amt-6-167-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
A cloud-by-cloud approach for studying aerosol-cloud interaction in satellite observations
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product
Insights into 3D cloud radiative transfer effects for the Orbiting Carbon Observatory
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation
Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar
The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations
Near-global distributions of overshooting tops derived from Terra and Aqua MODIS observations
Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy
Optimizing cloud motion estimation on the edge with phase correlation and optical flow
A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations
The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission
High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow
Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product
Retrieval of terahertz ice cloud properties from airborne measurements based on the irregularly shaped Voronoi ice scattering models
Latent heating profiles from GOES-16 and its impacts on precipitation forecasts
A CO2-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications
Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network
Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals
Improved spectral processing for a multi-mode pulse compression Ka–Ku-band cloud radar system
Uncertainty-bounded estimates of ash cloud properties using the ORAC algorithm: application to the 2019 Raikoke eruption
Ice water path retrievals from Meteosat-9 using quantile regression neural networks
An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties
Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
Segmentation-based multi-pixel cloud optical thickness retrieval using a convolutional neural network
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
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The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
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We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
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The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
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Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
EGUsphere, https://doi.org/10.5194/egusphere-2023-2773, https://doi.org/10.5194/egusphere-2023-2773, 2023
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We present a novel method for studying aerosol-cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to one year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
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Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
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The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
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The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
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The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-109, https://doi.org/10.5194/amt-2023-109, 2023
Revised manuscript accepted for AMT
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We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals is always decreasing with the increasing distance from the cloud far edge. The decreasing is the direct consequence of the fact that the forward peak of particles phase functions is much larger than the receiver field of view.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
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The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
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This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
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This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
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We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
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We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
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Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn
Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, https://doi.org/10.5194/amt-16-1683-2023, 2023
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The Virga-Sniffer, a new modular open-source Python package tool to characterize full precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically pointing cloud radar reflectivity time–height fields, is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in January–February 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.
Yulan Hong, Stephen W. Nesbitt, Robert J. Trapp, and Larry Di Girolamo
Atmos. Meas. Tech., 16, 1391–1406, https://doi.org/10.5194/amt-16-1391-2023, https://doi.org/10.5194/amt-16-1391-2023, 2023
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Deep convective updrafts form overshooting tops (OTs) when they extend into the upper troposphere and lower stratosphere. An OT often indicates hazardous weather conditions. The global distribution of OTs is useful for understanding global severe weather conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra satellites provides 2 decades of records on the Earth–atmosphere system with stable orbits, which are used in this study to derive 20-year OT climatology.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
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Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Bhupendra A. Raut, Paytsar Muradyan, Rajesh Sankaran, Robert C. Jackson, Seongha Park, Sean A. Shahkarami, Dario Dematties, Yongho Kim, Joseph Swantek, Neal Conrad, Wolfgang Gerlach, Sergey Shemyakin, Pete Beckman, Nicola J. Ferrier, and Scott M. Collis
Atmos. Meas. Tech., 16, 1195–1209, https://doi.org/10.5194/amt-16-1195-2023, https://doi.org/10.5194/amt-16-1195-2023, 2023
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We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
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Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
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This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
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In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
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SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
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Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
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Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022, https://doi.org/10.5194/amt-15-6653-2022, 2022
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With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
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This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
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The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
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In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
Andrew T. Prata, Roy G. Grainger, Isabelle A. Taylor, Adam C. Povey, Simon R. Proud, and Caroline A. Poulsen
Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, https://doi.org/10.5194/amt-15-5985-2022, 2022
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Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret,
aggregate and utilise the data.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
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Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
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This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
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A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
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Short summary
In an attempt to make cloud retrievals from the surface more common and convenient, we developed a cloud retrieval algorithm applicable for sky radiometers. It is based on an optimum method by fitting measured transmittances with modeled values. Further, a cost-effective and easy-to-use calibration procedure is proposed and validated using data obtained from the standard method. A detailed error analysis and quality assessment are also performed.
In an attempt to make cloud retrievals from the surface more common and convenient, we developed...