Articles | Volume 19, issue 6
https://doi.org/10.5194/acp-19-3733-2019
https://doi.org/10.5194/acp-19-3733-2019
Research article
 | 
22 Mar 2019
Research article |  | 22 Mar 2019

On the interpretation of upper-tropospheric humidity based on a second-order retrieval from infrared radiances

Klaus Gierens and Kostas Eleftheratos

Related authors

Machine learning for improvement of upper tropospheric relative humidity in ERA5 weather model data
Ziming Wang, Luca Bugliaro, Klaus Gierens, Michaela I. Hegglin, Susanne Rohs, Andreas Petzold, Stefan Kaufmann, and Christiane Voigt
EGUsphere, https://doi.org/10.5194/egusphere-2024-2012,https://doi.org/10.5194/egusphere-2024-2012, 2024
Short summary
How well can persistent contrails be predicted? An update
Sina Hofer, Klaus Gierens, and Susanne Rohs
Atmos. Chem. Phys., 24, 7911–7925, https://doi.org/10.5194/acp-24-7911-2024,https://doi.org/10.5194/acp-24-7911-2024, 2024
Short summary
Towards a more reliable forecast of ice supersaturation: concept of a one-moment ice-cloud scheme that avoids saturation adjustment
Dario Sperber and Klaus Gierens
Atmos. Chem. Phys., 23, 15609–15627, https://doi.org/10.5194/acp-23-15609-2023,https://doi.org/10.5194/acp-23-15609-2023, 2023
Short summary
The effect of ice supersaturation and thin cirrus on lapse rates in the upper troposphere
Klaus Gierens, Lena Wilhelm, Sina Hofer, and Susanne Rohs
Atmos. Chem. Phys., 22, 7699–7712, https://doi.org/10.5194/acp-22-7699-2022,https://doi.org/10.5194/acp-22-7699-2022, 2022
Short summary
Intercalibration between HIRS/2 and HIRS/3 channel 12 based on physical considerations
Klaus Gierens, Kostas Eleftheratos, and Robert Sausen
Atmos. Meas. Tech., 11, 939–948, https://doi.org/10.5194/amt-11-939-2018,https://doi.org/10.5194/amt-11-939-2018, 2018
Short summary

Related subject area

Subject: Gases | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Quantifying large methane emissions from the Nord Stream pipeline gas leak of September 2022 using IASI satellite observations and inverse modelling
Chris Wilson, Brian J. Kerridge, Richard Siddans, David P. Moore, Lucy J. Ventress, Emily Dowd, Wuhu Feng, Martyn P. Chipperfield, and John J. Remedios
Atmos. Chem. Phys., 24, 10639–10653, https://doi.org/10.5194/acp-24-10639-2024,https://doi.org/10.5194/acp-24-10639-2024, 2024
Short summary
Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data
Steffen Vanselow, Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Hartmut Boesch, and John P. Burrows
Atmos. Chem. Phys., 24, 10441–10473, https://doi.org/10.5194/acp-24-10441-2024,https://doi.org/10.5194/acp-24-10441-2024, 2024
Short summary
Biomass burning CO emissions: exploring insights through TROPOMI-derived emissions and emission coefficients
Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024,https://doi.org/10.5194/acp-24-10159-2024, 2024
Short summary
Measurement report: Combined use of MAX-DOAS and AERONET ground-based measurements in Montevideo, Uruguay, for the detection of distant biomass burning
Matías Osorio, Alejandro Agesta, Tim Bösch, Nicolás Casaballe, Andreas Richter, Leonardo M. A. Alvarado, and Erna Frins
Atmos. Chem. Phys., 24, 7447–7465, https://doi.org/10.5194/acp-24-7447-2024,https://doi.org/10.5194/acp-24-7447-2024, 2024
Short summary
Development of high spatial resolution annual emission inventory of greenhouse gases from open straw burning in Northeast China from 2001 to 2020
Zihan Song, Leiming Zhang, Chongguo Tian, Qiang Fu, Zhenxing Shen, Renjian Zhang, Dong Liu, and Song Cui
EGUsphere, https://doi.org/10.5194/egusphere-2024-980,https://doi.org/10.5194/egusphere-2024-980, 2024
Short summary

Cited articles

Abramowitz, M. and Stegun, I.: Handbook of mathematical functions, Dover, 9th Edn., 1972. a
Brogniez, H., Roca, R., and Picon, L.: A study of the free tropospheric humidity interannual variability using Meteosot data and an advection–condensation transport model, J. Climate, 22, 6773–6787, 2009. a
Chung, E.-S., Soden, B., Huang, X., Shi, L., and John, V.: An assessment of the consistency between satellite measurements of upper tropospheric water vapor, J. Geophys. Res., 121, 2874–2887, https://doi.org/10.1002/2015JD024496, 2016. a
Eleftheratos, K., Zerefos, C., Zanis, P., Balis, D., Tselioudis, G., Gierens, K., and Sausen, R.: A study on natural and manmade global interannual fluctuations of cirrus cloud cover for the period 184–2004, Atmos. Chem. Phys., 7, 2631–2642, https://doi.org/10.5194/acp-7-2631-2007, 2007. a
Gettelman, A., Fetzer, E., Elderling, A., and Irion, F.: The global distribution of supersaturation in the upper troposphere from the Atmospheric Infrared Sounder, J. Climate, 19, 6089–6103, 2006. a
Download
Short summary
We derive a new method to retrieve upper-tropospheric humidity (UTH) from High-resolution Infrared Radiation Sounder (HIRS) channel 12 brightness temperatures. With the new method we solve an old problem, namely that the wavelength change that occurred between HIRS 2 on NOAA 14 and HIRS 3 on NOAA 15 led to the retrieval of many more events with high UTH; that is, the time series shows strong jumps at high UTH values. This old problem is solved with the new retrieval.
Altmetrics
Final-revised paper
Preprint