Articles | Volume 16, issue 23
https://doi.org/10.5194/amt-16-5749-2023
© 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-16-5749-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Dec 2023
Research article |
| 01 Dec 2023
| 01 Dec 2023
Performance evaluation of three bio-optical models in aerosol and ocean color joint retrievals
Neranga K. Hannadige
Department of Physics, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
Peng-Wang Zhai
CORRESPONDING AUTHOR
Department of Physics, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Science Systems and Applications, Inc., Greenbelt, MD 20706, USA
Yongxiang Hu
NASA Langley Research Center, 1 Nasa Dr, Hampton, VA 23666, USA
P. Jeremy Werdell
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Kirk Knobelspiesse
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Brian Cairns
NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025, USA
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This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
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Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
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Emily D. Lenhardt, Lan Gao, Jens Redemann, Feng Xu, Sharon P. Burton, Brian Cairns, Ian Chang, Richard A. Ferrare, Chris A. Hostetler, Pablo E. Saide, Calvin Howes, Yohei Shinozuka, Snorre Stamnes, Mary Kacarab, Amie Dobracki, Jenny Wong, Steffen Freitag, and Athanasios Nenes
Atmos. Meas. Tech., 16, 2037–2054, https://doi.org/10.5194/amt-16-2037-2023, https://doi.org/10.5194/amt-16-2037-2023, 2023
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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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André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Thomas Jackson, Andrei Chuprin, Malcolm Taberner, Ruth Airs, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Robert J. W. Brewin, Elisabetta Canuti, Francisco P. Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Afonso Ferreira, Scott Freeman, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Ralf Goericke, Richard Gould, Nathalie Guillocheau, Stanford B. Hooker, Chuamin Hu, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Steven Lohrenz, Hubert Loisel, Antonio Mannino, Victor Martinez-Vicente, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Enrique Montes, Frank Muller-Karger, Aimee Neeley, Michael Novak, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Rüdiger Röttgers, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Crystal Thomas, Rob Thomas, Gavin Tilstone, Andreia Tracana, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Bozena Wojtasiewicz, Simon Wright, and Giuseppe Zibordi
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A compiled set of in situ data is vital to evaluate the quality of ocean-colour satellite data records. Here we describe the global compilation of bio-optical in situ data (spanning from 1997 to 2021) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba
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The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.
Santiago Gassó and Kirk D. Knobelspiesse
Atmos. Chem. Phys., 22, 13581–13605, https://doi.org/10.5194/acp-22-13581-2022, https://doi.org/10.5194/acp-22-13581-2022, 2022
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Atmospheric particles interact with light resulting in observable optical polarization. Thus, we can learn about their composition from space. New satellite sensor technology measures full polarization of reflected sunlight. This paper considers circular polarization, an overlooked category of polarization with distinctive features that could bring new insights. We review existing literature and make novel computations to consider this previously underappreciated category of polarization.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Dongwei Fu, Larry Di Girolamo, Robert M. Rauber, Greg M. McFarquhar, Stephen W. Nesbitt, Jesse Loveridge, Yulan Hong, Bastiaan van Diedenhoven, Brian Cairns, Mikhail D. Alexandrov, Paul Lawson, Sarah Woods, Simone Tanelli, Sebastian Schmidt, Chris Hostetler, and Amy Jo Scarino
Atmos. Chem. Phys., 22, 8259–8285, https://doi.org/10.5194/acp-22-8259-2022, https://doi.org/10.5194/acp-22-8259-2022, 2022
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Satellite-retrieved cloud microphysics are widely used in climate research because of their central role in water and energy cycles. Here, we provide the first detailed investigation of retrieved cloud drop sizes from in situ and various satellite and airborne remote sensing techniques applied to real cumulus cloud fields. We conclude that the most widely used passive remote sensing method employed in climate research produces high biases of 6–8 µm (60 %–80 %) caused by 3-D radiative effects.
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.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252, https://doi.org/10.5194/amt-14-3233-2021, https://doi.org/10.5194/amt-14-3233-2021, 2021
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We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Andrew M. Dzambo, Tristan L'Ecuyer, Kenneth Sinclair, Bastiaan van Diedenhoven, Siddhant Gupta, Greg McFarquhar, Joseph R. O'Brien, Brian Cairns, Andrzej P. Wasilewski, and Mikhail Alexandrov
Atmos. Chem. Phys., 21, 5513–5532, https://doi.org/10.5194/acp-21-5513-2021, https://doi.org/10.5194/acp-21-5513-2021, 2021
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This work highlights a new algorithm using data collected from the 2016–2018 NASA ORACLES field campaign. This algorithm synthesizes cloud and rain measurements to attain estimates of cloud and precipitation properties over the southeast Atlantic Ocean. Estimates produced by this algorithm compare well against in situ estimates. Increased rain fractions and rain rates are found in regions of atmospheric instability. This dataset can be used to explore aerosol–cloud–precipitation interactions.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
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Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Adeyemi A. Adebiyi, Paquita Zuidema, Ian Chang, Sharon P. Burton, and Brian Cairns
Atmos. Chem. Phys., 20, 11025–11043, https://doi.org/10.5194/acp-20-11025-2020, https://doi.org/10.5194/acp-20-11025-2020, 2020
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Over the southeast Atlantic, interactions between the low-level clouds and the overlying smoke aerosols have previously been highlighted, but no study has yet focused on the presence of the mid-level clouds that complicate the aerosol–cloud interactions. Here we show that these optically thin super-cooled mid-level clouds are relatively common, and they frequently occur at the top of the smoke layer between August and October with significant radiative impacts on the low-level clouds.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
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The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Melody A. Avery, Robert A. Ryan, Brian J. Getzewich, Mark A. Vaughan, David M. Winker, Yongxiang Hu, Anne Garnier, Jacques Pelon, and Carolus A. Verhappen
Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, https://doi.org/10.5194/amt-13-4539-2020, 2020
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CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6 %–9 % for high-confidence cloud phases and 1 %–2 % for all cloudy bins, including cloud fringes and unknown cloud phases. In V4 there are many fewer cloud layers identified as horizontally oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Daniel J. Miller, Michal Segal-Rozenhaimer, Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Mikhail Alexandrov, Bastiaan van Diedenhoven, and Andrzej Wasilewski
Atmos. Meas. Tech., 13, 3447–3470, https://doi.org/10.5194/amt-13-3447-2020, https://doi.org/10.5194/amt-13-3447-2020, 2020
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A neural network (NN) is developed and used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. The NN is applied to research scanning polarimeter (RSP) observations obtained during the ORACLES field campaign and compared to other co-located remote sensing retrievals of cloud effective radius and optical thickness. A NN approach can advance more complex iterative search retrieval algorithms by providing a quick initial guess.
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020, https://doi.org/10.5194/amt-13-1575-2020, 2020
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Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
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In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Wenbo Sun, Yongxiang Hu, Rosemary R. Baize, Gorden Videen, Sungsoo S. Kim, Young-Jun Choi, Kyungin Kang, Chae Kyung Sim, Minsup Jeong, Ali Omar, Snorre A. Stamnes, David G. MacDonnell, and Evgenij Zubko
Atmos. Chem. Phys., 19, 15583–15586, https://doi.org/10.5194/acp-19-15583-2019, https://doi.org/10.5194/acp-19-15583-2019, 2019
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Dusts have a significant impact on climate and environment. Detecting dust using satellite instruments is generally conducted by measuring at multiple observation angles due to the uncertainty of the surface reflection. This report shows that the degree of polarization of reflected light can be used for retrieving the optical depth of dust at backscatter angles only, regardless of surface conditions. This simple method is suitable for surveying dust aerosols over oceans with low-cost satellites.
Andrew M. Sayer and Kirk D. Knobelspiesse
Atmos. Chem. Phys., 19, 15023–15048, https://doi.org/10.5194/acp-19-15023-2019, https://doi.org/10.5194/acp-19-15023-2019, 2019
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Data about the Earth are routinely obtained from satellite observations, model simulations, and ground-based or other measurements. These are at different space and timescales, and it is common to average them to reduce gaps and increase ease of use. The question of how the data should be averaged depends on the underlying distribution of the quantity. This study presents a method for determining how to appropriately aggregate data and applies it to data sets about atmospheric aerosol levels.
Kristina Pistone, Jens Redemann, Sarah Doherty, Paquita Zuidema, Sharon Burton, Brian Cairns, Sabrina Cochrane, Richard Ferrare, Connor Flynn, Steffen Freitag, Steven G. Howell, Meloë Kacenelenbogen, Samuel LeBlanc, Xu Liu, K. Sebastian Schmidt, Arthur J. Sedlacek III, Michal Segal-Rozenhaimer, Yohei Shinozuka, Snorre Stamnes, Bastiaan van Diedenhoven, Gerard Van Harten, and Feng Xu
Atmos. Chem. Phys., 19, 9181–9208, https://doi.org/10.5194/acp-19-9181-2019, https://doi.org/10.5194/acp-19-9181-2019, 2019
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Understanding how smoke particles interact with sunlight is important in calculating their effects on climate, since some smoke is more scattering (cooling) and some is more absorbing (heating). Knowing this proportion is important for both satellite observations and climate models. We measured smoke properties in a recent aircraft-based field campaign off the west coast of Africa and present a comparison of these properties as measured using the six different, independent techniques available.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Yongxiang Hu, Kirk Knobelspiesse, P. Jeremy Werdell, Amir Ibrahim, Brian Cairns, and Alison Chase
Atmos. Meas. Tech., 12, 3921–3941, https://doi.org/10.5194/amt-12-3921-2019, https://doi.org/10.5194/amt-12-3921-2019, 2019
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford B. Hooker, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Hubert Loisel, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 11, 1037–1068, https://doi.org/10.5194/essd-11-1037-2019, https://doi.org/10.5194/essd-11-1037-2019, 2019
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A compiled set of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2018) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Shan Zeng, Mark Vaughan, Zhaoyan Liu, Charles Trepte, Jayanta Kar, Ali Omar, David Winker, Patricia Lucker, Yongxiang Hu, Brian Getzewich, and Melody Avery
Atmos. Meas. Tech., 12, 2261–2285, https://doi.org/10.5194/amt-12-2261-2019, https://doi.org/10.5194/amt-12-2261-2019, 2019
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We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol discrimination (CAD) algorithm to correctly distinguish between clouds and aerosols detected in the CALIPSO lidar backscatter signals. FKM is an unsupervised learning algorithm, so the classifications it derives are wholly independent from those reported by the CAD scheme. For a full month of measurements, the two techniques agree in ~ 95 % of all cases, providing strong evidence for CAD correctness.
Meloë S. Kacenelenbogen, Mark A. Vaughan, Jens Redemann, Stuart A. Young, Zhaoyan Liu, Yongxiang Hu, Ali H. Omar, Samuel LeBlanc, Yohei Shinozuka, John Livingston, Qin Zhang, and Kathleen A. Powell
Atmos. Chem. Phys., 19, 4933–4962, https://doi.org/10.5194/acp-19-4933-2019, https://doi.org/10.5194/acp-19-4933-2019, 2019
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Significant efforts are required to estimate the direct radiative effects of aerosols above clouds (DAREcloudy). We have used a combination of passive and active A-Train satellite sensors and derive mainly positive global and regional DAREcloudy values (e.g., global seasonal values between 0.13 and 0.26 W m-2). Despite differences in methods and sensors, the DAREcloudy values in this study are generally higher than previously reported. We discuss the primary reasons for these higher estimates.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
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The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
Man-Hae Kim, Ali H. Omar, Jason L. Tackett, Mark A. Vaughan, David M. Winker, Charles R. Trepte, Yongxiang Hu, Zhaoyan Liu, Lamont R. Poole, Michael C. Pitts, Jayanta Kar, and Brian E. Magill
Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, https://doi.org/10.5194/amt-11-6107-2018, 2018
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This paper discusses recent advances made in distinguishing among different aerosols species detected in the CALIPSO lidar measurements. A new classification algorithm now classifies four different aerosol types in the stratosphere, and the number of aerosol types recognized in the troposphere has increased from six to seven. The lidar ratios characterizing each type have been updated and the effects of these changes on CALIPSO retrievals of aerosol optical depth are examined in detail.
Kirk Knobelspiesse and Sreeja Nag
Atmos. Meas. Tech., 11, 3935–3954, https://doi.org/10.5194/amt-11-3935-2018, https://doi.org/10.5194/amt-11-3935-2018, 2018
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We test if small satellites flying in formation can be used for multi-angle aerosol remote sensing. So far, this has only been done with multiple views on one satellite. Single-view angle satellites flying in formation are a technically feasible alternative, although with different geometries. Using Bayesian information content analysis, we find such satellites equally capable. For aerosol remote sensing, the number of viewing angles is the most important.
Daniel J. Miller, Zhibo Zhang, Steven Platnick, Andrew S. Ackerman, Frank Werner, Celine Cornet, and Kirk Knobelspiesse
Atmos. Meas. Tech., 11, 3689–3715, https://doi.org/10.5194/amt-11-3689-2018, https://doi.org/10.5194/amt-11-3689-2018, 2018
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Prior satellite comparisons of bispectral and polarimetric cloud droplet size retrievals exhibited systematic biases. However, similar airborne instrument retrievals have been found to be quite similar to one another. This study explains this discrepancy in terms of differing sensitivity to vertical profile, as well as spatial and angular resolution. This is accomplished by using a satellite retrieval simulator – an LES cloud model coupled to radiative transfer and cloud retrieval algorithms.
Xiaomei Lu, Yongxiang Hu, Yuekui Yang, Mark Vaughan, Zhaoyan Liu, Sharon Rodier, William Hunt, Kathy Powell, Patricia Lucker, and Charles Trepte
Atmos. Meas. Tech., 11, 3281–3296, https://doi.org/10.5194/amt-11-3281-2018, https://doi.org/10.5194/amt-11-3281-2018, 2018
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This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. The surface bidirectional reflectances retrieved from CALIOP measurements contribute complementary data for existing MODIS standard data products and could be used to detect and monitor seasonal surface reflectance changes in high latitude regions where passive MODIS measurements are limited.
Antonio Di Noia, Otto P. Hasekamp, Lianghai Wu, Bastiaan van Diedenhoven, Brian Cairns, and John E. Yorks
Atmos. Meas. Tech., 10, 4235–4252, https://doi.org/10.5194/amt-10-4235-2017, https://doi.org/10.5194/amt-10-4235-2017, 2017
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In this paper an algorithm for the retrieval of aerosol properties from NASA Research Scanning Polarimeter (RSP) data is presented. An artificial neural network is used to produce a first estimate of the aerosol properties, which is then improved using an iterative retrieval scheme based on Phillips–Tikhonov regularization. Using the neural network retrievals as a first guess for the Phillips–Tikhonov improved the retrieval convergence, confirming results previously found on ground-based data.
Kenneth Sinclair, Bastiaan van Diedenhoven, Brian Cairns, John Yorks, Andrzej Wasilewski, and Matthew McGill
Atmos. Meas. Tech., 10, 2361–2375, https://doi.org/10.5194/amt-10-2361-2017, https://doi.org/10.5194/amt-10-2361-2017, 2017
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We present a multi-angular contrast approach to retrieve cloud top height (CTH) using photogrammetry. We demonstrate the method’s ability to retrieve heights of multiple cloud layers within single footprints, using the multiple views available for each footprint. This paper provides an in-depth description and performance analysis of the CTH retrieval technique and the retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar.
Sharon P. Burton, Eduard Chemyakin, Xu Liu, Kirk Knobelspiesse, Snorre Stamnes, Patricia Sawamura, Richard H. Moore, Chris A. Hostetler, and Richard A. Ferrare
Atmos. Meas. Tech., 9, 5555–5574, https://doi.org/10.5194/amt-9-5555-2016, https://doi.org/10.5194/amt-9-5555-2016, 2016
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Retrievals of aerosol microphysics exist for ground-based, airborne, and future space-borne lidar measurements. We investigate the information content of a lidar measurement system, using only a forward model but no explicit inversion. The simplified aerosol used here is applicable as a best case for all retrievals in the absence of additional constraints. We report (1) information content of the measurements; (2) uncertainties on the retrieved parameters; and (3) sources of compensating errors.
Feng Xu, Oleg Dubovik, Peng-Wang Zhai, David J. Diner, Olga V. Kalashnikova, Felix C. Seidel, Pavel Litvinov, Andrii Bovchaliuk, Michael J. Garay, Gerard van Harten, and Anthony B. Davis
Atmos. Meas. Tech., 9, 2877–2907, https://doi.org/10.5194/amt-9-2877-2016, https://doi.org/10.5194/amt-9-2877-2016, 2016
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We developed an algorithm for aerosol and water-leaving radiance retrieval in a simultaneous way.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Hervé Claustre, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford Hooker, Mati Kahru, Holger Klein, Susanne Kratzer, Hubert Loisel, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Alex J. Poulton, Michel Repecaud, Timothy Smyth, Heidi M. Sosik, Michael Twardowski, Kenneth Voss, Jeremy Werdell, Marcel Wernand, and Giuseppe Zibordi
Earth Syst. Sci. Data, 8, 235–252, https://doi.org/10.5194/essd-8-235-2016, https://doi.org/10.5194/essd-8-235-2016, 2016
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A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2012) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Joel McCorkel, Brian Cairns, and Andrzej Wasilewski
Atmos. Meas. Tech., 9, 955–962, https://doi.org/10.5194/amt-9-955-2016, https://doi.org/10.5194/amt-9-955-2016, 2016
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The transfer and maintenance of international radiometric standards to satellite remote-sensing instruments is a labor-intensive and costly one. The goal is to provide specific examples for calibration implementation for a potential instrument mission and, with this, advance debate on the roles that the various satellite calibration techniques play in providing the best radiometric standards for Earth-observing sensors.
B. Nechad, K. Ruddick, T. Schroeder, K. Oubelkheir, D. Blondeau-Patissier, N. Cherukuru, V. Brando, A. Dekker, L. Clementson, A. C. Banks, S. Maritorena, P. J. Werdell, C. Sá, V. Brotas, I. Caballero de Frutos, Y.-H. Ahn, S. Salama, G. Tilstone, V. Martinez-Vicente, D. Foley, M. McKibben, J. Nahorniak, T. Peterson, A. Siliò-Calzada, R. Röttgers, Z. Lee, M. Peters, and C. Brockmann
Earth Syst. Sci. Data, 7, 319–348, https://doi.org/10.5194/essd-7-319-2015, https://doi.org/10.5194/essd-7-319-2015, 2015
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The CoastColour Round Robin (CCRR) project (European Space Agency) was designed to set up the first database for remote-sensing algorithm testing and accuracy assessment of water quality parameter retrieval in coastal waters, from satellite imagery. This paper analyses the CCRR database, which includes in situ bio-geochemical and optical measurements in various water types, match-up reflectance products from the MEdium Resolution Imaging Spectrometer (MERIS), and radiative transfer simulations.
W. Sun, R. R. Baize, G. Videen, Y. Hu, and Q. Fu
Atmos. Chem. Phys., 15, 11909–11918, https://doi.org/10.5194/acp-15-11909-2015, https://doi.org/10.5194/acp-15-11909-2015, 2015
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A method is reported for retrieving super-thin cloud optical depth with polarized light. It is found that near-backscatter p-polarized light is sensitive to clouds, but not to ocean conditions. Near-backscatter p-polarized intensity linearly relates to super-thin cloud optical depth. Based on these findings, super-thin cloud optical depth can be retrieved with little effect from surface reflection.
M. Ottaviani, B. van Diedenhoven, and B. Cairns
The Cryosphere, 9, 1933–1942, https://doi.org/10.5194/tc-9-1933-2015, https://doi.org/10.5194/tc-9-1933-2015, 2015
W. Sun, R. R. Baize, C. Lukashin, and Y. Hu
Atmos. Chem. Phys., 15, 7725–7734, https://doi.org/10.5194/acp-15-7725-2015, https://doi.org/10.5194/acp-15-7725-2015, 2015
L. Wu, O. Hasekamp, B. van Diedenhoven, and B. Cairns
Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, https://doi.org/10.5194/amt-8-2625-2015, 2015
Z. Liu, D. Winker, A. Omar, M. Vaughan, J. Kar, C. Trepte, Y. Hu, and G. Schuster
Atmos. Chem. Phys., 15, 1265–1288, https://doi.org/10.5194/acp-15-1265-2015, https://doi.org/10.5194/acp-15-1265-2015, 2015
S. Zeng, J. Riedi, C. R. Trepte, D. M. Winker, and Y.-X. Hu
Atmos. Chem. Phys., 14, 7125–7134, https://doi.org/10.5194/acp-14-7125-2014, https://doi.org/10.5194/acp-14-7125-2014, 2014
S. Rodier, Y. Hu, and M. Vaughan
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4681-2013, https://doi.org/10.5194/tcd-7-4681-2013, 2013
Revised manuscript has not been submitted
B. van Diedenhoven, B. Cairns, A. M. Fridlind, A. S. Ackerman, and T. J. Garrett
Atmos. Chem. Phys., 13, 3185–3203, https://doi.org/10.5194/acp-13-3185-2013, https://doi.org/10.5194/acp-13-3185-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Measuring rainfall using microwave links: the influence of temporal sampling
Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground
The High lAtitude sNowfall Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS): a new algorithm for snowfall retrieval at high latitudes
Next-generation radiance unfiltering process for the Clouds and the Earth's Radiant Energy System instrument
Improved rain event detection in commercial microwave link time series via combination with MSG SEVIRI data
A directional surface reflectance climatology determined from TROPOMI observations
Investigation of gravity waves using measurements from a sodium temperature/wind lidar operated in multi-direction mode
An improved BRDF hotspot model and its use in VLIDORT for studying the impact of atmospheric scattering on hotspot directional signatures in the atmosphere
A multi-decadal time series of upper stratospheric temperature profiles from Odin-OSIRIS limb-scattered spectra
CALOTRITON: a convective boundary layer height estimation algorithm from ultra-high-frequency (UHF) wind profiler data
Enhancing consistency of microphysical properties of precipitation across the melting layer in dual-frequency precipitation radar data
Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer
Forward operator for polarimetric radio occultation measurements
Assessing atmospheric gravity wave spectra in the presence of observational gaps
Joint 1DVar retrievals of tropospheric temperature and water vapor from Global Navigation Satellite System radio occultation (GNSS-RO) and microwave radiometer observations
Mispointing characterization and Doppler velocity correction for the conically scanning WIVERN Doppler radar
Scale separation for gravity wave analysis from 3D temperature observations in the MLT region
Radar and environment-based hail damage estimates using machine learning
Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms
A new power-law model for μ–Λ relationships in convective and stratiform rainfall
Suppression of precipitation bias in wind velocities from continuous-wave Doppler lidars
Difference spectrum fitting of the ion–neutral collision frequency from dual-frequency EISCAT measurements
Observation of horizontal temperature variations by a spatial heterodyne interferometer using single-sided interferograms
Version 8 IMK–IAA MIPAS temperatures from 12–15 µm spectra: Middle and Upper Atmosphere modes
GNSS radio occultation excess-phase processing for climate applications including uncertainty estimation
Impact analysis of processing strategies for long-term GPS zenith tropospheric delay (ZTD)
Irradiance and cloud optical properties from solar photovoltaic systems
Single field-of-view sounder atmospheric product retrieval algorithm: establishing radiometric consistency for hyper-spectral sounder retrievals
Higher-order calibration on WindRAD (Wind Radar) scatterometer winds
On the polarimetric backscatter by a still or quasi-still wind turbine
OH airglow observations with two identical spectrometers: benefits of increased data homogeneity in the identification of variations induced by the 11-year solar cycle, the QBO, and other factors
Broadband radiative quantities for the EarthCARE mission: the ACM-COM and ACM-RT products
HSRL-2 Retrievals of Ocean Surface Wind Speeds
Long-term multi-source precipitation estimation with high resolution (RainGRS Clim)
Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations
Unfiltering of the EarthCARE Broadband Radiometer (BBR) observations: the BM–RAD product
Using optimal estimation to retrieve winds from velocity-azimuth display (VAD) scans by a Doppler lidar
Angular sampling of a monochromatic, wide-field-of-view camera to augment next-generation Earth radiation budget satellite observations
Noise filtering options for conically scanning Doppler LiDAR measurements with low pulse accumulation
Estimating the refractivity bias of Formosat-7/COSMIC-II GNSS Radio Occultation in the planetary boundary layer
Efficient collocation of global navigation satellite system radio occultation soundings with passive nadir microwave soundings
Analysis of 2D airglow imager data with respect to dynamics using machine learning
Estimation of extreme precipitation events in Estonia and Italy using dual-polarization weather radar quantitative precipitation estimations
Detection and localization of F-layer ionospheric irregularities with the back-propagation method along the radio occultation ray path
Observations of anomalous propagation over waters near Sweden
Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence
Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach
High-resolution 3D winds derived from a modified WISSDOM synthesis scheme using multiple Doppler lidars and observations
Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations
Assessing and mitigating the radar–radar interference in the German C-band weather radar network
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
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Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, https://doi.org/10.5194/amt-17-2539-2024, 2024
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This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail on the ground to estimate hail size distributions (HSDs). Traditional hail sensors' limited areas complicate the full HSD retrieval. The HSD of a supercell event on 20 June 2021 is retrieved and contains > 18 000 hailstones. The HSD is compared to automatic hail sensor measurements and those of weather-radar-based MESHS. Investigations into ground hail melting are performed by five drone flights.
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech., 17, 2195–2217, https://doi.org/10.5194/amt-17-2195-2024, https://doi.org/10.5194/amt-17-2195-2024, 2024
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The paper describes a new machine-learning-based snowfall retrieval algorithm for Advanced Technology Microwave Sounder observations developed to retrieve high-latitude snowfall events. The main novelty of the approach is the radiometric characterization of the background surface at the time of the overpass, which is ancillary to the retrieval process. The algorithm shows a unique capability to retrieve snowfall in the environmental conditions typical of high latitudes.
Lusheng Liang, Wenying Su, Sergio Sejas, Zachary Eitzen, and Norman G. Loeb
Atmos. Meas. Tech., 17, 2147–2163, https://doi.org/10.5194/amt-17-2147-2024, https://doi.org/10.5194/amt-17-2147-2024, 2024
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This paper describes an updated process to obtain unfiltered radiation from CERES satellite instruments by incorporating the most recent developments in radiative transfer modeling and ancillary input datasets (e.g., realistic representation of land surface radiation and climatology of surface temperatures and aerosols) during the past 20 years. The resulting global mean of instantaneous SW and LW fluxes is changed by less than 0.5 W m−2 with regional differences as large as 2.0 W m−2.
Maximilian Graf, Andreas Wagner, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, Harald Kunstmann, and Christian Chwala
Atmos. Meas. Tech., 17, 2165–2182, https://doi.org/10.5194/amt-17-2165-2024, https://doi.org/10.5194/amt-17-2165-2024, 2024
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Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is a crucial processing step. We investigate the usage of rainfall data from MSG SEVIRI for this task, compare this approach with existing methods, and introduce a novel combined approach. The results show certain advantages for SEVIRI-based methods, particularly for CMLs where existing methods perform poorly. Our novel combination yields the best performance.
Lieuwe G. Tilstra, Martin de Graaf, Victor J. H. Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, https://doi.org/10.5194/amt-17-2235-2024, 2024
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This paper introduces a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by TROPOMI on the Sentinel-5 Precursor satellite. The database contains monthly fields of DLER for 21 wavelength bands at a relatively high spatial resolution of 0.125 by 0.125 degrees. The anisotropy of the surface reflection is handled by parameterisation of the viewing angle dependence.
Bing Cao and Alan Z. Liu
Atmos. Meas. Tech., 17, 2123–2146, https://doi.org/10.5194/amt-17-2123-2024, https://doi.org/10.5194/amt-17-2123-2024, 2024
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A narrow-band sodium lidar measures atmospheric waves but is limited to vertical variations. We propose to utilize phase shifts among observations from different laser beams to derive horizontal wave information. Two gravity wave packets were identified by this method. Both waves were found to interact with thin evanescent layers, partially reflected, but transmitted energy to higher altitudes. The method can detect more medium-frequency gravity waves for similar lidar systems worldwide.
Xiaozhen Xiong, Xu Liu, Robert Spurr, Ming Zhao, Qiguang Yang, Wan Wu, and Liqiao Lei
Atmos. Meas. Tech., 17, 1965–1978, https://doi.org/10.5194/amt-17-1965-2024, https://doi.org/10.5194/amt-17-1965-2024, 2024
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The term “hotspot” refers to the sharp increase in reflectance occurring when incident (solar) and reflected (viewing) directions coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications, but current models typically require large values of computations to represent the hotspot accurately. This paper provides a numerically improved hotspot BRDF model that converges much faster and is used in VLIDORT.
Daniel Zawada, Kimberlee Dubé, Taran Warnock, Adam Bourassa, Susann Tegtmeier, and Douglas Degenstein
Atmos. Meas. Tech., 17, 1995–2010, https://doi.org/10.5194/amt-17-1995-2024, https://doi.org/10.5194/amt-17-1995-2024, 2024
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There remain large uncertainties in long-term changes of stratospheric–atmospheric temperatures. We have produced a time series of more than 20 years of satellite-based temperature measurements from the OSIRIS instrument in the upper–middle stratosphere. The dataset is publicly available and intended to be used for a better understanding of changes in stratospheric temperatures.
Alban Philibert, Marie Lothon, Julien Amestoy, Pierre-Yves Meslin, Solène Derrien, Yannick Bezombes, Bernard Campistron, Fabienne Lohou, Antoine Vial, Guylaine Canut-Rocafort, Joachim Reuder, and Jennifer K. Brooke
Atmos. Meas. Tech., 17, 1679–1701, https://doi.org/10.5194/amt-17-1679-2024, https://doi.org/10.5194/amt-17-1679-2024, 2024
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We present a new algorithm, CALOTRITON, for the retrieval of the convective boundary layer depth with ultra-high-frequency radar measurements. CALOTRITON is partly based on the principle that the top of the convective boundary layer is associated with an inversion and a decrease in turbulence. It is evaluated using ceilometer and radiosonde data. It is able to qualify the complexity of the vertical structure of the low troposphere and detect internal or residual layers.
Kamil Mroz, Alessandro Battaglia, and Ann M. Fridlind
Atmos. Meas. Tech., 17, 1577–1597, https://doi.org/10.5194/amt-17-1577-2024, https://doi.org/10.5194/amt-17-1577-2024, 2024
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In this study, we examine the extent to which radar measurements from space can inform us about the properties of clouds and precipitation. Surprisingly, our analysis showed that the amount of ice turning into rain was lower than expected in the current product. To improve on this, we came up with a new way to extract information about the size and concentration of particles from radar data. As long as we use this method in the right conditions, we can even estimate how dense the ice is.
Volker Wulfmeyer, Christoph Senff, Florian Späth, Andreas Behrendt, Diego Lange, Robert M. Banta, W. Alan Brewer, Andreas Wieser, and David D. Turner
Atmos. Meas. Tech., 17, 1175–1196, https://doi.org/10.5194/amt-17-1175-2024, https://doi.org/10.5194/amt-17-1175-2024, 2024
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A simultaneous deployment of Doppler, temperature, and water-vapor lidar systems is used to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of weather forecast and climate models.
Daisuke Hotta, Katrin Lonitz, and Sean Healy
Atmos. Meas. Tech., 17, 1075–1089, https://doi.org/10.5194/amt-17-1075-2024, https://doi.org/10.5194/amt-17-1075-2024, 2024
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Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a new type of GNSS observations that can detect heavy precipitation along the ray path between the emitter and receiver satellites. As a first step towards using these observations in numerical weather prediction (NWP), we developed a computer code that simulates GNSS-PRO observations from forecast fields produced by an NWP model. The quality of the developed simulator is evaluated with a number of case studies.
Mohamed Mossad, Irina Strelnikova, Robin Wing, and Gerd Baumgarten
Atmos. Meas. Tech., 17, 783–799, https://doi.org/10.5194/amt-17-783-2024, https://doi.org/10.5194/amt-17-783-2024, 2024
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This numerical study addresses observational gaps' impact on atmospheric gravity wave spectra. Three methods, fast Fourier transform (FFT), generalized Lomb–Scargle periodogram (GLS), and Haar structure function (HSF), were tested on synthetic data. HSF is best for spectra with negative slopes. GLS excels for flat and positive slopes and identifying dominant frequencies. Accurately estimating these aspects is crucial for understanding gravity wave dynamics and energy transfer in the atmosphere.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
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In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Filippo Emilio Scarsi, Alessandro Battaglia, Frederic Tridon, Paolo Martire, Ranvir Dhillon, and Anthony Illingworth
Atmos. Meas. Tech., 17, 499–514, https://doi.org/10.5194/amt-17-499-2024, https://doi.org/10.5194/amt-17-499-2024, 2024
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The WIVERN mission, one of the two candidates to be the ESA's Earth Explorer 11 mission, aims at providing measurements of horizontal winds in cloud and precipitation systems through a conically scanning W-band Doppler radar. This work discusses four methods that can be used to characterize and correct the Doppler velocity error induced by the antenna mispointing. The proposed methodologies can be extended to other Doppler concepts featuring conically scanning or slant viewing Doppler systems.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
EGUsphere, https://doi.org/10.5194/egusphere-2024-136, https://doi.org/10.5194/egusphere-2024-136, 2024
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The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the Mesosphere and the lower Thermosphere. The waves perturb the temperature field and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
Luis Ackermann, Joshua Soderholm, Alain Protat, Rhys Whitley, Lisa Ye, and Nina Ridder
Atmos. Meas. Tech., 17, 407–422, https://doi.org/10.5194/amt-17-407-2024, https://doi.org/10.5194/amt-17-407-2024, 2024
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The paper addresses the crucial topic of hail damage quantification using radar observations. We propose a new radar-derived hail product that utilizes a large dataset of insurance hail damage claims and radar observations. A deep neural network was employed, trained with local meteorological variables and the radar observations, to better quantify hail damage. Key meteorological variables were identified to have the most predictive capability in this regard.
Laura Mary Tomkins, Sandra E. Yuter, and Matthew A. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2023-2888, https://doi.org/10.5194/egusphere-2023-2888, 2024
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We have created a new method to better identify enhanced features in radar data from winter storms. Unlike the clear-cut features seen in warm season storms, features in winter storms are often fuzzier with softer edges. Our technique is unique because it uses two adaptive thresholds that change based on the background radar values. It can identify both strong and subtle features in the radar data, and takes into account uncertainties in the detection process.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 17, 235–245, https://doi.org/10.5194/amt-17-235-2024, https://doi.org/10.5194/amt-17-235-2024, 2024
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A common method to retrieve important information about the microphysical structure of rain (DSD retrievals) requires a constrained relationship between the drop size distribution parameters. The most widely accepted empirical relationship is between μ and Λ. The relationship shows variability across the different types of rainfall (convective or stratiform). The new proposed power-law model to represent the μ–Λ relation provides a better physical interpretation of the relationship coefficients.
Liqin Jin, Jakob Mann, Nikolas Angelou, and Mikael Sjöholm
Atmos. Meas. Tech., 16, 6007–6023, https://doi.org/10.5194/amt-16-6007-2023, https://doi.org/10.5194/amt-16-6007-2023, 2023
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By sampling the spectra from continuous-wave Doppler lidars very fast, the rain-induced Doppler signal can be suppressed and the bias in the wind velocity estimation can be reduced. The method normalizes 3 kHz spectra by their peak values before averaging them down to 50 Hz. Over 3 h, we observe a significant reduction in the bias of the lidar data relative to the reference sonic data when the largest lidar focus distance is used. The more it rains, the more the bias is reduced.
Florian Günzkofer, Gunter Stober, Dimitry Pokhotelov, Yasunobu Miyoshi, and Claudia Borries
Atmos. Meas. Tech., 16, 5897–5907, https://doi.org/10.5194/amt-16-5897-2023, https://doi.org/10.5194/amt-16-5897-2023, 2023
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Electric currents in the ionosphere can impact both satellite and ground-based infrastructure. These currents depend strongly on the collisions of ions and neutral particles. Measuring ion–neutral collisions is often only possible via certain assumptions. The direct measurement of ion–neutral collision frequencies is possible with multifrequency incoherent scatter radar measurements. This paper presents one analysis method of such measurements and discusses its advantages and disadvantages.
Konstantin Ntokas, Jörn Ungermann, Martin Kaufmann, Tom Neubert, and Martin Riese
Atmos. Meas. Tech., 16, 5681–5696, https://doi.org/10.5194/amt-16-5681-2023, https://doi.org/10.5194/amt-16-5681-2023, 2023
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A nanosatellite was developed to obtain 1-D vertical temperature profiles in the mesosphere and lower thermosphere, which can be used to derive wave parameters needed for atmospheric models. A new processing method is shown, which allows one to extract two 1-D temperature profiles. The location of the two profiles is analyzed, as it is needed for deriving wave parameters. We show that this method is feasible, which however will increase the requirements of an accurate calibration and processing.
Maya García-Comas, Bernd Funke, Manuel López-Puertas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Belén Martínez-Mondéjar, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 5357–5386, https://doi.org/10.5194/amt-16-5357-2023, https://doi.org/10.5194/amt-16-5357-2023, 2023
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We have released version 8 of MIPAS IMK–IAA temperatures and pointing information retrieved from MIPAS Middle and Upper Atmosphere mode version 8.03 calibrated spectra, covering 20–115 km altitude. We considered non-local thermodynamic equilibrium emission explicitly for each limb scan, essential to retrieve accurate temperatures above the mid-mesosphere. Comparisons of this temperature dataset with SABER measurements show excellent agreement, improving those of previous MIPAS versions.
Josef Innerkofler, Gottfried Kirchengast, Marc Schwärz, Christian Marquardt, and Yago Andres
Atmos. Meas. Tech., 16, 5217–5247, https://doi.org/10.5194/amt-16-5217-2023, https://doi.org/10.5194/amt-16-5217-2023, 2023
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Atmosphere remote sensing using GNSS radio occultation provides a highly valuable basis for atmospheric and climate science. For the highest-quality demands, the Wegener Center set up a rigorous system for processing low-level measurement data. This excess-phase processing setup includes integrated quality control and uncertainty estimation. It was successfully evaluated and inter-compared, ensuring the capability of producing reliable long-term data records for climate applications.
Jingna Bai, Yidong Lou, Weixing Zhang, Yaozong Zhou, Zhenyi Zhang, Chuang Shi, and Jingnan Liu
Atmos. Meas. Tech., 16, 5249–5259, https://doi.org/10.5194/amt-16-5249-2023, https://doi.org/10.5194/amt-16-5249-2023, 2023
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Homogenized atmospheric water vapor data are an important prerequisite for climate analysis. Compared to other techniques, GPS has an inherent homogeneity advantage but requires reprocessing and homogenization to eliminate impacts of applied strategy and observation environmental changes. The low-elevation cut-off angles are suggested for the best estimates of zenith tropospheric delay (ZTD) reprocessing time series when compared to homogenized radiosonde data or ERA5 reference time series.
James Barry, Stefanie Meilinger, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Christopher Schirrmeister, Rone Yousif, Tina Buchmann, Johannes Grabenstein, Hartwig Deneke, Jonas Witthuhn, Claudia Emde, Felix Gödde, Bernhard Mayer, Leonhard Scheck, Marion Schroedter-Homscheidt, Philipp Hofbauer, and Matthias Struck
Atmos. Meas. Tech., 16, 4975–5007, https://doi.org/10.5194/amt-16-4975-2023, https://doi.org/10.5194/amt-16-4975-2023, 2023
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Measured power data from solar photovoltaic (PV) systems contain information about the state of the atmosphere. In this work, power data from PV systems in the Allgäu region in Germany were used to determine the solar irradiance at each location, using state-of-the-art simulation and modelling. The results were validated using concurrent measurements of the incoming solar radiation in each case. If applied on a wider scale, this algorithm could help improve weather and climate models.
Wan Wu, Xu Liu, Liqiao Lei, Xiaozhen Xiong, Qiguang Yang, Qing Yue, Daniel K. Zhou, and Allen M. Larar
Atmos. Meas. Tech., 16, 4807–4832, https://doi.org/10.5194/amt-16-4807-2023, https://doi.org/10.5194/amt-16-4807-2023, 2023
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We present a new operational physical retrieval algorithm that is used to retrieve atmospheric properties for each single field-of-view measurement of hyper-spectral IR sounders. The physical scheme includes a cloud-scattering calculation in its forward-simulation part. The data product generated using this algorithm has an advantage over traditional IR sounder data production algorithms in terms of improved spatial resolution and minimized error due to cloud contamination.
Zhen Li, Ad Stoffelen, Anton Verhoef, Zhixiong Wang, Jian Shang, and Honggang Yin
Atmos. Meas. Tech., 16, 4769–4783, https://doi.org/10.5194/amt-16-4769-2023, https://doi.org/10.5194/amt-16-4769-2023, 2023
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WindRAD (Wind Radar) is the first dual-frequency rotating fan-beam scatterometer in orbit. We observe non-linearity in the backscatter distribution. Therefore, higher-order calibration (HOC) is proposed, which removes the non-linearities per incidence angle. The combination of HOC and NOCant is discussed. It can remove not only the non-linearity but also the anomalous harmonic azimuth dependencies caused by the antenna rotation; hence the optimal winds can be achieved with this combination.
Marco Gabella, Martin Lainer, Daniel Wolfensberger, and Jacopo Grazioli
Atmos. Meas. Tech., 16, 4409–4422, https://doi.org/10.5194/amt-16-4409-2023, https://doi.org/10.5194/amt-16-4409-2023, 2023
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A still wind turbine observed with a fixed-pointing radar antenna has shown distinctive polarimetric signatures: the correlation coefficient between the two orthogonal polarization states was persistently equal to 1. The differential reflectivity and the radar reflectivity factors were also stable in time. Over 2 min (2000 Hz, 128 pulses were used; consequently, the sampling time was 64 ms), the standard deviation of the differential backscattering phase shift was only a few degrees.
Carsten Schmidt, Lisa Küchelbacher, Sabine Wüst, and Michael Bittner
Atmos. Meas. Tech., 16, 4331–4356, https://doi.org/10.5194/amt-16-4331-2023, https://doi.org/10.5194/amt-16-4331-2023, 2023
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Two identical instruments in a parallel setup were used to observe the mesospheric OH airglow for more than 10 years (2009–2020) at 47.42°N, 10.98°E. This allows unique analyses of data quality aspects and their impact on the obtained results. During solar cycle 24 the influence of the sun was strong (∼6 K per 100 sfu). A quasi-2-year oscillation (QBO) of ±1 K is observed mainly during the maximum of the solar cycle. Unlike the stratospheric QBO the variation has a period of or below 24 months.
Jason N. S. Cole, Howard W. Barker, Zhipeng Qu, Najda Villefranque, and Mark W. Shephard
Atmos. Meas. Tech., 16, 4271–4288, https://doi.org/10.5194/amt-16-4271-2023, https://doi.org/10.5194/amt-16-4271-2023, 2023
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Measurements from the EarthCARE satellite mission will be used to retrieve profiles of cloud and aerosol properties. These retrievals are combined with auxiliary information about surface properties and atmospheric state, e.g., temperature and water vapor. This information allows computation of 1D and 3D solar and thermal radiative transfer for small domains, which are compared with coincident radiometer observations to continually assess EarthCARE retrievals.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
EGUsphere, https://doi.org/10.5194/egusphere-2023-1943, https://doi.org/10.5194/egusphere-2023-1943, 2023
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This study introduces and evaluates a new ocean surface wind speed product from NASA Langley Research Center’s (LARC’s) airborne High Spectral Resolution Lidar – generation 2 (HSRL-2) using NASA ACTIVATE field data. We show that HSRL-2 wind speed retrievals have small errors when compared to wind speeds directly measured by NCAR AVAPS dropsondes. This novel retrieval method provides a way to obtain accurate, high resolution wind speed data in airborne field campaigns.
Anna Jurczyk, Katarzyna Ośródka, Jan Szturc, Magdalena Pasierb, and Agnieszka Kurcz
Atmos. Meas. Tech., 16, 4067–4079, https://doi.org/10.5194/amt-16-4067-2023, https://doi.org/10.5194/amt-16-4067-2023, 2023
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A data-processing algorithm, RainGRS Clim, has been developed to work on precipitation accumulations such as daily or monthly totals. The algorithm makes the most of additional opportunities: access to high-quality data that are not operationally available and greater efficiency of the algorithms for data quality control and merging for longer accumulations. Monthly accumulations estimated by RainGRS Clim were found to be significantly more reliable than accumulations generated operationally.
Sophie Rosenburg, Charlotte Lange, Evelyn Jäkel, Michael Schäfer, André Ehrlich, and Manfred Wendisch
Atmos. Meas. Tech., 16, 3915–3930, https://doi.org/10.5194/amt-16-3915-2023, https://doi.org/10.5194/amt-16-3915-2023, 2023
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Snow layer melting and melt pond formation on Arctic sea ice are important seasonal processes affecting the surface reflection and energy budget. Sea ice reflectivity was surveyed by airborne imaging spectrometers in May–June 2017. Adapted retrieval approaches were applied to find snow layer liquid water fraction, snow grain effective radius, and melt pond depth. The retrievals show the potential and limitations of spectral airborne imaging to map melting snow layer and melt pond properties.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-170, https://doi.org/10.5194/amt-2023-170, 2023
Revised manuscript accepted for AMT
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The BBR measures shortwave and totalwave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, it is needed to correct for the effect of the spectral response. This is done within the BM-RAD processor. Errors in the unfiltering are propagated into the fluxes, thus, an accurate unfiltering is required for a proper estimation of the fluxes (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the SW and <0.1 % for the LW.
Sunil Baidar, Timothy J. Wagner, David D. Turner, and W. Alan Brewer
Atmos. Meas. Tech., 16, 3715–3726, https://doi.org/10.5194/amt-16-3715-2023, https://doi.org/10.5194/amt-16-3715-2023, 2023
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This paper provides a new method to retrieve wind profiles from coherent Doppler lidar (CDL) measurements. It takes advantage of layer-to-layer correlation in wind profiles to provide continuous profiles of up to 3 km by filling in the gaps where the CDL signal is too small to retrieve reliable results by itself. Comparison with the current method and collocated radiosonde wind measurements showed excellent agreement with no degradation in results where the current method gives valid results.
Jake J. Gristey, K. Sebastian Schmidt, Hong Chen, Daniel R. Feldman, Bruce C. Kindel, Joshua Mauss, Mathew van den Heever, Maria Z. Hakuba, and Peter Pilewskie
Atmos. Meas. Tech., 16, 3609–3630, https://doi.org/10.5194/amt-16-3609-2023, https://doi.org/10.5194/amt-16-3609-2023, 2023
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The concept of a satellite-based camera is demonstrated for sampling the angular distribution of outgoing radiance from Earth needed to generate data products for new radiation budget spectral channels.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-153, https://doi.org/10.5194/amt-2023-153, 2023
Revised manuscript accepted for AMT
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Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed, both, by means of assessing the filter results, and by comparing retrieved turbulence variables versus independent measurements.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng-Yung Huang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1246, https://doi.org/10.5194/egusphere-2023-1246, 2023
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This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and their dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We proposed methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the bias under different atmospheric conditions and thus improves the applications of the GNSS RO data in the planetary boundary layer.
Alex Meredith, Stephen Leroy, Lucy Halperin, and Kerri Cahoy
Atmos. Meas. Tech., 16, 3345–3361, https://doi.org/10.5194/amt-16-3345-2023, https://doi.org/10.5194/amt-16-3345-2023, 2023
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We developed a new efficient algorithm leveraging orbital dynamics to collocate radio occultation soundings with microwave radiance soundings. This new algorithm is 99 % accurate and is much faster than traditional collocation-finding approaches. Speeding up collocation finding is useful for calibrating and validating microwave radiometers and for data assimilation into numerical weather prediction models. Our algorithm can also be used to predict collocation yield for new satellite missions.
René Sedlak, Andreas Welscher, Patrick Hannawald, Sabine Wüst, Rainer Lienhart, and Michael Bittner
Atmos. Meas. Tech., 16, 3141–3153, https://doi.org/10.5194/amt-16-3141-2023, https://doi.org/10.5194/amt-16-3141-2023, 2023
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We show that machine learning can help in classifying images of the OH* airglow, a thin layer in the middle atmosphere (ca. 86 km height) emitting infrared radiation, in an efficient way. By doing this,
dynamicepisodes of strong movement in the OH* airglow caused predominantly by waves can be extracted automatically from large data sets. Within these dynamic episodes, turbulent wave breaking can also be found. We use these observations of turbulence to derive the energy released by waves.
Roberto Cremonini, Tanel Voormansik, Piia Post, and Dmitri Moisseev
Atmos. Meas. Tech., 16, 2943–2956, https://doi.org/10.5194/amt-16-2943-2023, https://doi.org/10.5194/amt-16-2943-2023, 2023
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Extreme rainfall for a specific location is commonly evaluated when designing stormwater management systems. This study investigates the use of quantitative precipitation estimations (QPEs) based on polarimetric weather radar data, without rain gauge corrections, to estimate 1 h rainfall total maxima in Italy and Estonia. We show that dual-polarization weather radar provides reliable QPEs and effective estimations of return periods for extreme rainfall in climatologically homogeneous regions.
Vinícius Ludwig-Barbosa, Joel Rasch, Thomas Sievert, Anders Carlström, Mats I. Pettersson, Viet Thuy Vu, and Jacob Christensen
Atmos. Meas. Tech., 16, 1849–1864, https://doi.org/10.5194/amt-16-1849-2023, https://doi.org/10.5194/amt-16-1849-2023, 2023
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In this paper, the back-propagation method's capabilities and limitations regarding the location of irregularity regions in the ionosphere, e.g. equatorial plasma bubbles, are evaluated. The assessment was performed with simulations in which different scenarios were assumed. The results showed that the location estimate is possible if the amplitude of the ionospheric disturbance is stronger than the instrument noise level. Further, multiple patches can be located if regions are well separated.
Lars Norin
Atmos. Meas. Tech., 16, 1789–1801, https://doi.org/10.5194/amt-16-1789-2023, https://doi.org/10.5194/amt-16-1789-2023, 2023
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The atmosphere can cause radar beams to bend more or less towards the ground. When the atmosphere differs from standard atmospheric conditions, the propagation is considered anomalous. Radars affected by anomalous propagation can observe ground clutter far beyond the radar horizon. Here, 4.5 years' worth of data from five operational Swedish weather radars are presented. Analyses of the data reveal a strong seasonal cycle and weaker diurnal cycle in ground clutter from across nearby waters.
Mathieu Ratynski, Sergey Khaykin, Alain Hauchecorne, Robin Wing, Jean-Pierre Cammas, Yann Hello, and Philippe Keckhut
Atmos. Meas. Tech., 16, 997–1016, https://doi.org/10.5194/amt-16-997-2023, https://doi.org/10.5194/amt-16-997-2023, 2023
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Aeolus is the first spaceborne wind lidar providing global wind measurements since 2018. This study offers a comprehensive analysis of Aeolus instrument performance, using ground-based wind lidars and meteorological radiosondes, at tropical and mid-latitudes sites. The analysis allows assessing the long-term evolution of the satellite's performance for more than 3 years. The results will help further elaborate the understanding of the error sources and the behavior of the Doppler wind lidar.
Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
Atmos. Meas. Tech., 16, 911–940, https://doi.org/10.5194/amt-16-911-2023, https://doi.org/10.5194/amt-16-911-2023, 2023
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Better understanding and modeling snowfall properties and processes is relevant to many fields, ranging from weather forecasting to aircraft safety. Meteorological radars can be used to gain insights into the microphysics of snowfall. In this work, we propose a new method to retrieve snowfall properties from measurements of radars with different frequencies. It relies on an original deep-learning framework, which incorporates knowledge of the underlying physics, i.e., electromagnetic scattering.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and GyuWon Lee
Atmos. Meas. Tech., 16, 845–869, https://doi.org/10.5194/amt-16-845-2023, https://doi.org/10.5194/amt-16-845-2023, 2023
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Since the winds in clear-air conditions usually play an important role in the initiation of various weather systems and phenomena, the modified Wind Synthesis System using Doppler Measurements (WISSDOM) synthesis scheme was developed to derive high-quality and high-spatial-resolution 3D winds under clear-air conditions. The performance and accuracy of derived 3D winds from this modified scheme were evaluated with an extreme strong wind event over complex terrain in Pyeongchang, South Korea.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Michael Frech, Cornelius Hald, Maximilian Schaper, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 16, 295–309, https://doi.org/10.5194/amt-16-295-2023, https://doi.org/10.5194/amt-16-295-2023, 2023
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Weather radar data are the backbone of a lot of meteorological products. In order to obtain a better low-level coverage with radar data, additional systems have to be included. The frequency range in which radars are allowed to operate is limited. A potential radar-to-radar interference has to be avoided. The paper derives guidelines on how additional radars can be included into a C-band weather radar network and how interferences can be avoided.
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Short summary
We evaluated the impact of three ocean optical models with different numbers of free parameters on the performance of an aerosol and ocean color remote sensing algorithm using the multi-angle polarimeter (MAP) measurements. It was demonstrated that the three- and seven-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the one-parameter model has smaller retrieval uncertainty over open water.
We evaluated the impact of three ocean optical models with different numbers of free parameters...
