Volume 15, issue 17

Volume 15, issue 17

01 Sep 2022
Characterization of a modified printed optical particle spectrometer for high-frequency and high-precision laboratory and field measurements
Sabin Kasparoglu, Mohammad Maksimul Islam, Nicholas Meskhidze, and Markus D. Petters
Atmos. Meas. Tech., 15, 5007–5018, https://doi.org/10.5194/amt-15-5007-2022,https://doi.org/10.5194/amt-15-5007-2022, 2022
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01 Sep 2022
Real-world wintertime CO, N2O, and CO2 emissions of a central European village
László Haszpra, Zoltán Barcza, Zita Ferenczi, Roland Hollós, Anikó Kern, and Natascha Kljun
Atmos. Meas. Tech., 15, 5019–5031, https://doi.org/10.5194/amt-15-5019-2022,https://doi.org/10.5194/amt-15-5019-2022, 2022
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02 Sep 2022
GPROF-NN: a neural-network-based implementation of the Goddard Profiling Algorithm
Simon Pfreundschuh, Paula J. Brown, Christian D. Kummerow, Patrick Eriksson, and Teodor Norrestad​​​​​​​
Atmos. Meas. Tech., 15, 5033–5060, https://doi.org/10.5194/amt-15-5033-2022,https://doi.org/10.5194/amt-15-5033-2022, 2022
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05 Sep 2022
Comprehensive detection of analytes in large chromatographic datasets by coupling factor analysis with a decision tree
Sungwoo Kim, Brian M. Lerner, Donna T. Sueper, and Gabriel Isaacman-VanWertz
Atmos. Meas. Tech., 15, 5061–5075, https://doi.org/10.5194/amt-15-5061-2022,https://doi.org/10.5194/amt-15-5061-2022, 2022
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06 Sep 2022
Top-of-the-atmosphere reflected shortwave radiative fluxes from GOES-R
Rachel T. Pinker, Yingtao Ma, Wen Chen, Istvan Laszlo, Hongqing Liu, Hye-Yun Kim, and Jaime Daniels
Atmos. Meas. Tech., 15, 5077–5094, https://doi.org/10.5194/amt-15-5077-2022,https://doi.org/10.5194/amt-15-5077-2022, 2022
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07 Sep 2022
Passive ground-based remote sensing of radiation fog
Heather Guy, David D. Turner, Von P. Walden, Ian M. Brooks, and Ryan R. Neely
Atmos. Meas. Tech., 15, 5095–5115, https://doi.org/10.5194/amt-15-5095-2022,https://doi.org/10.5194/amt-15-5095-2022, 2022
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08 Sep 2022
Characterization of inexpensive metal oxide sensor performance for trace methane detection
Daniel Furuta, Tofigh Sayahi, Jinsheng Li, Bruce Wilson, Albert A. Presto, and Jiayu Li
Atmos. Meas. Tech., 15, 5117–5128, https://doi.org/10.5194/amt-15-5117-2022,https://doi.org/10.5194/amt-15-5117-2022, 2022
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09 Sep 2022
Validation of Copernicus Sentinel-3/OLCI Level 2 Land Integrated Water Vapour product
Niilo Kalakoski, Viktoria F. Sofieva, René Preusker, Claire Henocq, Matthieu Denisselle, Steffen Dransfeld, and Silvia Scifoni
Atmos. Meas. Tech., 15, 5129–5140, https://doi.org/10.5194/amt-15-5129-2022,https://doi.org/10.5194/amt-15-5129-2022, 2022
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13 Sep 2022
Ice crystal images from optical array probes: classification with convolutional neural networks
Louis Jaffeux, Alfons Schwarzenböck, Pierre Coutris, and Christophe Duroure
Atmos. Meas. Tech., 15, 5141–5157, https://doi.org/10.5194/amt-15-5141-2022,https://doi.org/10.5194/amt-15-5141-2022, 2022
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13 Sep 2022
Extending water vapor measurement capability of photon-limited differential absorption lidars through simultaneous denoising and inversion
Willem J. Marais and Matthew Hayman
Atmos. Meas. Tech., 15, 5159–5180, https://doi.org/10.5194/amt-15-5159-2022,https://doi.org/10.5194/amt-15-5159-2022, 2022
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14 Sep 2022
Segmentation-based multi-pixel cloud optical thickness retrieval using a convolutional neural network
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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