Articles | Volume 14, issue 4
https://doi.org/10.5194/amt-14-2827-2021
https://doi.org/10.5194/amt-14-2827-2021
Research article
 | 
12 Apr 2021
Research article |  | 12 Apr 2021

Spectroscopic imaging of sub-kilometer spatial structure in lower-tropospheric water vapor

David R. Thompson, Brian H. Kahn, Philip G. Brodrick, Matthew D. Lebsock, Mark Richardson, and Robert O. Green

Related authors

Brief communication: Not as dirty as they look, flawed airborne and satellite snow spectra
Edward H. Bair, Dar A. Roberts, David R. Thompson, Philip G. Brodrick, Brenton A. Wilder, Niklas Bohn, Chris J. Crawford, Nimrod Carmon, Carrie M. Vuyovich, and Jeff Dozier
EGUsphere, https://doi.org/10.5194/egusphere-2024-1681,https://doi.org/10.5194/egusphere-2024-1681, 2024
Short summary
The pitfalls of ignoring topography in snow retrievals: a case study with EMIT
Niklas Bohn, Edward H. Bair, Philip G. Brodrick, Nimrod Carmon, Robert O. Green, Thomas H. Painter, and David R. Thompson
EGUsphere, https://doi.org/10.2139/ssrn.4671920,https://doi.org/10.2139/ssrn.4671920, 2024
Short summary
Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts
María Gonçalves Ageitos, Vincenzo Obiso, Ron L. Miller, Oriol Jorba, Martina Klose, Matt Dawson, Yves Balkanski, Jan Perlwitz, Sara Basart, Enza Di Tomaso, Jerónimo Escribano, Francesca Macchia, Gilbert Montané, Natalie M. Mahowald, Robert O. Green, David R. Thompson, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8623–8657, https://doi.org/10.5194/acp-23-8623-2023,https://doi.org/10.5194/acp-23-8623-2023, 2023
Short summary
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
Boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021,https://doi.org/10.5194/amt-14-5555-2021, 2021
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024,https://doi.org/10.5194/amt-17-4065-2024, 2024
Short summary
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024,https://doi.org/10.5194/amt-17-3949-2024, 2024
Short summary
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024,https://doi.org/10.5194/amt-17-3439-2024, 2024
Short summary
Accounting for the effect of aerosols in GHGSat methane retrieval
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024,https://doi.org/10.5194/amt-17-3347-2024, 2024
Short summary
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024,https://doi.org/10.5194/amt-17-2937-2024, 2024
Short summary

Cited articles

Anderson, G., Clough, S., Kneizys, F., Chetwynd, J., and Shettle, E.: AFGL atmospheric constituent profiles (0–120 km), Tech. Rep., US Air Force Geophysics Laboratory, AFGL-TR, 86-0110, 1986. a, b
Bedka, K. M., Nehrir, A. R., Kavaya, M., Barton-Grimley, R., Beaubien, M., Carroll, B., Collins, J., Cooney, J., Emmitt, G. D., Greco, S., Kooi, S., Lee, T., Liu, Z., Rodier, S., and Skofronick-Jackson, G.: Airborne Lidar Observations of Wind, Water Vapor, and Aerosol Profiles During The NASA Aeolus Cal/Val Test Flight Campaign, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2020-475, in review, 2020. a, b
Berk, A. and Hawes, F.: Validation of MODTRAN®6 and its line-by-line algorithm, J. Quant. Spectrosc. Ra., 203, 542–556, 2017. a
Bretherton, C. S., Peters, M. E., and Back, L. E.: Relationships between Water Vapor Path and Precipitation over the Tropical Oceans, J. Climate, 17, 1517–1528, https://doi.org/10.1175/1520-0442(2004)017<1517:RBWVPA>2.0.CO;2, 2004. a
Bretherton, C. S., Blossey, P. N., and Khairoutdinov, M.: An Energy-Balance Analysis of Deep Convective Self-Aggregation above Uniform SST, J. Atmos. Sci., 62, 4273–4292, https://doi.org/10.1175/JAS3614.1, 2005. a
Download
Short summary
Concentrations of water vapor in the atmosphere vary dramatically over space and time. Mapping this variability can provide insights into atmospheric processes that help us understand atmospheric processes in the Earth system. Here we use a new measurement strategy based on imaging spectroscopy to map atmospheric water vapor concentrations at very small spatial scales. Experiments demonstrate the accuracy of this technique and some initial results from an airborne remote sensing experiment.