Articles | Volume 11, issue 2
Atmos. Meas. Tech., 11, 1009–1017, 2018
https://doi.org/10.5194/amt-11-1009-2018
Atmos. Meas. Tech., 11, 1009–1017, 2018
https://doi.org/10.5194/amt-11-1009-2018
Research article
20 Feb 2018
Research article | 20 Feb 2018

Importance of interpolation and coincidence errors in data fusion

Simone Ceccherini et al.

Related authors

Level 2 processor and auxiliary data for ESA Version 8 final full mission analysis of MIPAS measurements on ENVISAT
Piera Raspollini, Enrico Arnone, Flavio Barbara, Massimo Bianchini, Bruno Carli, Simone Ceccherini, Martyn P. Chipperfield, Angelika Dehn, Stefano Della Fera, Bianca Maria Dinelli, Anu Dudhia, Jean-Marie Flaud, Marco Gai, Michael Kiefer, Manuel López-Puertas, David P. Moore, Alessandro Piro, John J. Remedios, Marco Ridolfi, Harjinder Sembhi, Luca Sgheri, and Nicola Zoppetti
Atmos. Meas. Tech., 15, 1871–1901, https://doi.org/10.5194/amt-15-1871-2022,https://doi.org/10.5194/amt-15-1871-2022, 2022
Short summary
The ESA MIPAS/Envisat level2-v8 dataset: 10 years of measurements retrieved with ORM v8.22
Bianca Maria Dinelli, Piera Raspollini, Marco Gai, Luca Sgheri, Marco Ridolfi, Simone Ceccherini, Flavio Barbara, Nicola Zoppetti, Elisa Castelli, Enzo Papandrea, Paolo Pettinari, Angelika Dehn, Anu Dudhia, Michael Kiefer, Alessandro Piro, Jean-Marie Flaud, Manuel López-Puertas, David Moore, John Remedios, and Massimo Bianchini
Atmos. Meas. Tech., 14, 7975–7998, https://doi.org/10.5194/amt-14-7975-2021,https://doi.org/10.5194/amt-14-7975-2021, 2021
Short summary
Phosgene distribution derived from MIPAS ESA v8 data: intercomparisons and trends
Paolo Pettinari, Flavio Barbara, Simone Ceccherini, Bianca Maria Dinelli, Marco Gai, Piera Raspollini, Luca Sgheri, Massimo Valeri, Gerald Wetzel, Nicola Zoppetti, and Marco Ridolfi
Atmos. Meas. Tech., 14, 7959–7974, https://doi.org/10.5194/amt-14-7959-2021,https://doi.org/10.5194/amt-14-7959-2021, 2021
Short summary
Comment on “Synergetic use of IASI and TROPOMI space borne sensors for generating a tropospheric methane profile product”
Simone Ceccherini
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-98,https://doi.org/10.5194/amt-2021-98, 2021
Revised manuscript accepted for AMT
Short summary
Application of the Complete Data Fusion algorithm to the ozone profiles measured by geostationary and low-Earth-orbit satellites: a feasibility study
Nicola Zoppetti, Simone Ceccherini, Bruno Carli, Samuele Del Bianco, Marco Gai, Cecilia Tirelli, Flavio Barbara, Rossana Dragani, Antti Arola, Jukka Kujanpää, Jacob C. A. van Peet, Ronald van der A, and Ugo Cortesi
Atmos. Meas. Tech., 14, 2041–2053, https://doi.org/10.5194/amt-14-2041-2021,https://doi.org/10.5194/amt-14-2041-2021, 2021
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Improved ozone monitoring by ground-based FTIR spectrometry
Omaira Elena García, Esther Sanromá, Matthias Schneider, Frank Hase, Sergio Fabián León-Luis, Thomas Blumenstock, Eliezer Sepúlveda, Alberto Redondas, Virgilio Carreño, Carlos Torres, and Natalia Prats
Atmos. Meas. Tech., 15, 2557–2577, https://doi.org/10.5194/amt-15-2557-2022,https://doi.org/10.5194/amt-15-2557-2022, 2022
Short summary
On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases
Edward Malina, Ben Veihelmann, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, and Isamu Morino
Atmos. Meas. Tech., 15, 2377–2406, https://doi.org/10.5194/amt-15-2377-2022,https://doi.org/10.5194/amt-15-2377-2022, 2022
Short summary
The MOPITT Version 9 CO product: sampling enhancements and validation
Merritt Deeter, Gene Francis, John Gille, Debbie Mao, Sara Martínez-Alonso, Helen Worden, Dan Ziskin, James Drummond, Róisín Commane, Glenn Diskin, and Kathryn McKain
Atmos. Meas. Tech., 15, 2325–2344, https://doi.org/10.5194/amt-15-2325-2022,https://doi.org/10.5194/amt-15-2325-2022, 2022
Short summary
Retrieving H2O/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI)
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022,https://doi.org/10.5194/amt-15-2251-2022, 2022
Short summary
Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data
Jos van Geffen, Henk Eskes, Steven Compernolle, Gaia Pinardi, Tijl Verhoelst, Jean-Christopher Lambert, Maarten Sneep, Mark ter Linden, Antje Ludewig, K. Folkert Boersma, and J. Pepijn Veefkind
Atmos. Meas. Tech., 15, 2037–2060, https://doi.org/10.5194/amt-15-2037-2022,https://doi.org/10.5194/amt-15-2037-2022, 2022
Short summary

Cited articles

Aires, F., Aznay, O., Prigent, C., Paul, M., and Bernardo, F.: Synergistic multi-wavelength remote sensing versus a posteriori combination of retrieved products: Application for the retrieval of atmospheric profiles using MetOp-A, J. Geophys. Res., 117, D18304, https://doi.org/10.1029/2011JD017188, 2012. 
Calisesi, Y., Soebijanta, V. T., and Oss, R. V.: Regridding of remote soundings: formulation and application to ozone profile comparison, J. Geophys. Res., 110, D23306, https://doi.org/10.1029/2005JD006122, 2005. 
Ceccherini, S.: Equivalence of measurement space solution data fusion and complete fusion, J. Quant. Spectrosc. Ra., 182, 71–74, 2016. 
Ceccherini, S. and Ridolfi, M.: Technical Note: Variance–covariance matrix and averaging kernels for the Levenberg–Marquardt solution of the retrieval of atmospheric vertical profiles, Atmos. Chem. Phys., 10, 3131–3139, https://doi.org/10.5194/acp-10-3131-2010, 2010. 
Ceccherini, S., Carli, B., Pascale, E., Prosperi, M., Raspollini, P., and Dinelli, B. M.: Comparison of measurements made with two different instruments of the same atmospheric vertical profile, Appl. Optics, 42, 6465–6473, 2003. 
Download
Short summary
Data fusion is an important tool to reduce data volume and to improve data quality. This paper introduces a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors. This upgraded algorithm extends the applicability of the technique to a wider range of cases. In fact, it also makes it possible to fuse vertical profiles of atmospheric parameters when they are represented on different altitude grids and refer to different true profiles.