Volume 15, issue 1

Volume 15, issue 1

03 Jan 2022
Wind speed and direction estimation from wave spectra using deep learning
Haoyu Jiang
Atmos. Meas. Tech., 15, 1–9, https://doi.org/10.5194/amt-15-1-2022,https://doi.org/10.5194/amt-15-1-2022, 2022
Short summary
03 Jan 2022
A study on the fragmentation of sulfuric acid and dimethylamine clusters inside an atmospheric pressure interface time-of-flight mass spectrometer
Dina Alfaouri, Monica Passananti, Tommaso Zanca, Lauri Ahonen, Juha Kangasluoma, Jakub Kubečka, Nanna Myllys, and Hanna Vehkamäki
Atmos. Meas. Tech., 15, 11–19, https://doi.org/10.5194/amt-15-11-2022,https://doi.org/10.5194/amt-15-11-2022, 2022
Short summary
03 Jan 2022
Towards operational multi-GNSS tropospheric products at GFZ Potsdam
Karina Wilgan, Galina Dick, Florian Zus, and Jens Wickert
Atmos. Meas. Tech., 15, 21–39, https://doi.org/10.5194/amt-15-21-2022,https://doi.org/10.5194/amt-15-21-2022, 2022
Short summary
04 Jan 2022
Dealing with spatial heterogeneity in pointwise-to-gridded- data comparisons
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022,https://doi.org/10.5194/amt-15-41-2022, 2022
Short summary
05 Jan 2022
Biomass burning aerosol heating rates from the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2017 experiments
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Michal Segal Rozenhaimer, Meloë Kacenelenbogen, Yohei Shinozuka, Connor Flynn, Rich Ferrare, Sharon Burton, Chris Hostetler, Marc Mallet, and Paquita Zuidema
Atmos. Meas. Tech., 15, 61–77, https://doi.org/10.5194/amt-15-61-2022,https://doi.org/10.5194/amt-15-61-2022, 2022
Short summary
05 Jan 2022
Design and characterization of a semi-open dynamic chamber for measuring biogenic volatile organic compound (BVOC) emissions from plants
Jianqiang Zeng, Yanli Zhang, Huina Zhang, Wei Song, Zhenfeng Wu, and Xinming Wang
Atmos. Meas. Tech., 15, 79–93, https://doi.org/10.5194/amt-15-79-2022,https://doi.org/10.5194/amt-15-79-2022, 2022
Short summary
05 Jan 2022
Air temperature equation derived from sonic temperature and water vapor mixing ratio for turbulent airflow sampled through closed-path eddy-covariance flux systems
Xinhua Zhou, Tian Gao, Eugene S. Takle, Xiaojie Zhen, Andrew E. Suyker, Tala Awada, Jane Okalebo, and Jiaojun Zhu
Atmos. Meas. Tech., 15, 95–115, https://doi.org/10.5194/amt-15-95-2022,https://doi.org/10.5194/amt-15-95-2022, 2022
Short summary
05 Jan 2022
New sampling strategy mitigates a solar-geometry-induced bias in sub-kilometre vapour scaling statistics derived from imaging spectroscopy
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022,https://doi.org/10.5194/amt-15-117-2022, 2022
Short summary
05 Jan 2022
Inter-comparison of wind measurements in the atmospheric boundary layer and the lower troposphere with Aeolus and a ground-based coherent Doppler lidar network over China
Songhua Wu, Kangwen Sun, Guangyao Dai, Xiaoye Wang, Xiaoying Liu, Bingyi Liu, Xiaoquan Song, Oliver Reitebuch, Rongzhong Li, Jiaping Yin, and Xitao Wang
Atmos. Meas. Tech., 15, 131–148, https://doi.org/10.5194/amt-15-131-2022,https://doi.org/10.5194/amt-15-131-2022, 2022
Short summary
06 Jan 2022
A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data
Alberto Sorrentino, Alessia Sannino, Nicola Spinelli, Michele Piana, Antonella Boselli, Valentino Tontodonato, Pasquale Castellano, and Xuan Wang
Atmos. Meas. Tech., 15, 149–164, https://doi.org/10.5194/amt-15-149-2022,https://doi.org/10.5194/amt-15-149-2022, 2022
Short summary
11 Jan 2022
On the quality of RS41 radiosonde descent data
Bruce Ingleby, Martin Motl, Graeme Marlton, David Edwards, Michael Sommer, Christoph von Rohden, Holger Vömel, and Hannu Jauhiainen
Atmos. Meas. Tech., 15, 165–183, https://doi.org/10.5194/amt-15-165-2022,https://doi.org/10.5194/amt-15-165-2022, 2022
Short summary
11 Jan 2022
Optimization of Aeolus' aerosol optical properties by maximum-likelihood estimation
Frithjof Ehlers, Thomas Flament, Alain Dabas, Dimitri Trapon, Adrien Lacour, Holger Baars, and Anne Grete Straume-Lindner
Atmos. Meas. Tech., 15, 185–203, https://doi.org/10.5194/amt-15-185-2022,https://doi.org/10.5194/amt-15-185-2022, 2022
Short summary
CC BY 4.0