Articles | Volume 17, issue 22
https://doi.org/10.5194/acp-17-13625-2017
https://doi.org/10.5194/acp-17-13625-2017
Research article
 | 
15 Nov 2017
Research article |  | 15 Nov 2017

Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications

Claudia J. Stubenrauch, Artem G. Feofilov, Sofia E. Protopapadaki, and Raymond Armante

Related authors

Relationship between latent and radiative heating fields of Tropical cloud systems using synergistic satellite observations
Xiaoting Chen, Claudia J. Stubenrauch, and Giulio Mandorli
EGUsphere, https://doi.org/10.5194/egusphere-2024-3434,https://doi.org/10.5194/egusphere-2024-3434, 2024
Short summary
Assessment of object-based indices to identify convective organization
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024,https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Convective organization and 3D structure of tropical cloud systems deduced from synergistic A-Train observations and machine learning
Claudia J. Stubenrauch, Giulio Mandorli, and Elisabeth Lemaitre
Atmos. Chem. Phys., 23, 5867–5884, https://doi.org/10.5194/acp-23-5867-2023,https://doi.org/10.5194/acp-23-5867-2023, 2023
Short summary
3D radiative heating of tropical upper tropospheric cloud systems derived from synergistic A-Train observations and machine learning
Claudia J. Stubenrauch, Giacomo Caria, Sofia E. Protopapadaki, and Friederike Hemmer
Atmos. Chem. Phys., 21, 1015–1034, https://doi.org/10.5194/acp-21-1015-2021,https://doi.org/10.5194/acp-21-1015-2021, 2021
Short summary
Diurnal variation of high-level clouds from the synergy of AIRS and IASI space-borne infrared sounders
Artem G. Feofilov and Claudia J. Stubenrauch
Atmos. Chem. Phys., 19, 13957–13972, https://doi.org/10.5194/acp-19-13957-2019,https://doi.org/10.5194/acp-19-13957-2019, 2019
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height
Mengyuan Wang, Min Min, Jun Li, Han Lin, Yongen Liang, Binlong Chen, Zhigang Yao, Na Xu, and Miao Zhang
Atmos. Chem. Phys., 24, 14239–14256, https://doi.org/10.5194/acp-24-14239-2024,https://doi.org/10.5194/acp-24-14239-2024, 2024
Short summary
Observing convective activities in complex convective organizations and their contributions to precipitation and anvil cloud amounts
Zhenquan Wang and Jian Yuan
Atmos. Chem. Phys., 24, 13811–13831, https://doi.org/10.5194/acp-24-13811-2024,https://doi.org/10.5194/acp-24-13811-2024, 2024
Short summary
Weak liquid water path response in ship tracks
Anna Tippett, Edward Gryspeerdt, Peter Manshausen, Philip Stier, and Tristan W. P. Smith
Atmos. Chem. Phys., 24, 13269–13283, https://doi.org/10.5194/acp-24-13269-2024,https://doi.org/10.5194/acp-24-13269-2024, 2024
Short summary
Lightning declines over shipping lanes following regulation of fuel sulfur emissions
Chris J. Wright, Joel A. Thornton, Lyatt Jaeglé, Yang Cao, Yannian Zhu, Jihu Liu, Randall Jones II, Robert H. Holzworth, Daniel Rosenfeld, Robert Wood, Peter Blossey, and Daehyun Kim
EGUsphere, https://doi.org/10.48550/arXiv.2408.07207,https://doi.org/10.48550/arXiv.2408.07207, 2024
Short summary
Air mass history linked to the development of Arctic mixed-phase clouds
Rebecca J. Murray-Watson and Edward Gryspeerdt
Atmos. Chem. Phys., 24, 11115–11132, https://doi.org/10.5194/acp-24-11115-2024,https://doi.org/10.5194/acp-24-11115-2024, 2024
Short summary

Cited articles

Aires, F., Prigent, C., and Rossow, W. B.: Temporal interpolation of global surface skin temperature diurnal cycle over land under clear and cloudy conditions, J. Geophys. Res., 109, D04313, https://doi.org/10.1019/2003JD003527, 2004.
AIRS Science Team/Chahine, M.: AIRS/Aqua L1B Infrared (IR) geolocated and calibrated radiances V005, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), available at: https://disc.gsfc.nasa.gov/datacollection/AIRIBRAD_005.html, 2007.
AIRS Science Team/Joao Texeira: AIRS/Aqua L2 Standard Physical Retrieval (AIRS + AMSU) V006, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/AQUA/AIRS/DATA201, 2013.
Blackwell, W. J., Milstein, A. B., Zavodsky, B., and Blankenship, C. B.: Neural Network Estimation of Atmospheric Thermodynamic State for Weather Forecasting Applications, Foundations of Augmented Cognition. Advancing Human Performance and Decision-Making through Adaptive Systems: 8th International Conference, AC 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, 22–27 June, 93–103, Springer International Publishing, https://doi.org/10.1007/978-3-319-07527-3_9, 2014.
Download
Short summary
We present multi-year cloud climatologies from the advanced IR sounders AIRS and IASI. These data are particularly sensitive to cirrus. Cloud emissivity allows to distinguish between high opaque, thick cirrus and thin cirrus. By comparing tropical geographical change patterns of these cloud types with respect to changing tropical mean surface temperature, it is demonstrated that their response to climate change may be different, with potential consequences on the atmospheric circulation.
Altmetrics
Final-revised paper
Preprint