Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.400 IF 3.400
  • IF 5-year value: 3.841 IF 5-year
    3.841
  • CiteScore value: 3.71 CiteScore
    3.71
  • SNIP value: 1.472 SNIP 1.472
  • IPP value: 3.57 IPP 3.57
  • SJR value: 1.770 SJR 1.770
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 70 Scimago H
    index 70
  • h5-index value: 49 h5-index 49
AMT | Articles | Volume 11, issue 12
Atmos. Meas. Tech., 11, 6617–6626, 2018
https://doi.org/10.5194/amt-11-6617-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 11, 6617–6626, 2018
https://doi.org/10.5194/amt-11-6617-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Dec 2018

Research article | 17 Dec 2018

Radiometric correction of observations from microwave humidity sounders

Isaac Moradi et al.

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Discrete-wavelength DOAS NO2 slant column retrievals from OMI and TROPOMI
Cristina Ruiz Villena, Jasdeep S. Anand, Roland J. Leigh, Paul S. Monks, Claire E. Parfitt, and Joshua D. Vande Hey
Atmos. Meas. Tech., 13, 1735–1756, https://doi.org/10.5194/amt-13-1735-2020,https://doi.org/10.5194/amt-13-1735-2020, 2020
Short summary
Estimates of lightning NOx production based on high-resolution OMI NO2 retrievals over the continental US
Xin Zhang, Yan Yin, Ronald van der A, Jeff L. Lapierre, Qian Chen, Xiang Kuang, Shuqi Yan, Jinghua Chen, Chuan He, and Rulin Shi
Atmos. Meas. Tech., 13, 1709–1734, https://doi.org/10.5194/amt-13-1709-2020,https://doi.org/10.5194/amt-13-1709-2020, 2020
Short summary
S5P TROPOMI NO2 slant column retrieval: method, stability, uncertainties and comparisons with OMI
Jos van Geffen, K. Folkert Boersma, Henk Eskes, Maarten Sneep, Mark ter Linden, Marina Zara, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020,https://doi.org/10.5194/amt-13-1315-2020, 2020
Short summary
Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements
Diego G. Loyola, Jian Xu, Klaus-Peter Heue, and Walter Zimmer
Atmos. Meas. Tech., 13, 985–999, https://doi.org/10.5194/amt-13-985-2020,https://doi.org/10.5194/amt-13-985-2020, 2020
Short summary
Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003–2018) for carbon and climate applications
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020,https://doi.org/10.5194/amt-13-789-2020, 2020
Short summary

Cited articles

Berg, W., Bilanow, S., Chen, R., Datta, S., Draper, D., Ebrahimi, H., Farrar, S., Jones, W. L., Kroodsma, R., McKague, D., Payne, V., Wang, J., Wilheit, T., and Yang, J. X.: Intercalibration of the GPM Microwave Radiometer Constellation, J. Atmos. Ocean. Tech., 33, 2639–2654, https://doi.org/10.1175/JTECH-D-16-0100.1, 2016. a
Buehler, S. A., Kuvatov, M., Sreerekha, T. R., John, V. O., Rydberg, B., Eriksson, P., and Notholt, J.: A cloud filtering method for microwave upper tropospheric humidity measurements, Atmos. Chem. Phys., 7, 5531–5542, https://doi.org/10.5194/acp-7-5531-2007, 2007. a
Cao, C., Weinreb, M., and Xu, H.: Predicting Simultaneous Nadir Overpasses among Polar-Orbiting Meteorological Satellites for the Intersatellite Calibration of Radiometers, J. Atmos. Ocean. Techn., 21, 537–542, https://doi.org/10.1175/1520-0426(2004)021<0537:PSNOAP>2.0.CO;2, 2004. a
Chander, G., Hewison, T., Fox, N., Wu, X., Xiong, X., and Blackwell, W.: Overview of intercalibration of satellite instruments, IEEE T. Geosci. Remote, 51, 1056–1080, https://doi.org/10.1109/TGRS.2012.2228654, 2013. a
Ferraro, R., Weng, F., C. Grody, N., Zhao, L., Meng, H., Kongoli, C., Pellegrino, P., Qiu, S., and Dean, C.: NOAA operational hydrological products derived from the AMSU, IEEE T. Geosci. Remote, 43, 1036–1049, 2005. a
Publications Copernicus
Download
Short summary
Microwave (MW) satellite instruments are used for a variety of applications such as retrieving geophysical variables such as temperature and humidity. They are also assimilated into NWP models to improve the weather forecast. However, MW instruments are subject to radiometric and geometric errors. This study evaluates the observations from several MW instruments for radiometric errors and provides correction coefficients for the data that are biased.
Microwave (MW) satellite instruments are used for a variety of applications such as retrieving...
Citation