Articles | Volume 11, issue 2
https://doi.org/10.5194/amt-11-1009-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-1009-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Feb 2018
Research article |
| 20 Feb 2018
| 20 Feb 2018
Importance of interpolation and coincidence errors in data fusion
Simone Ceccherini
CORRESPONDING AUTHOR
Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Bruno Carli
Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Cecilia Tirelli
Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Nicola Zoppetti
Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Samuele Del Bianco
Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Ugo Cortesi
Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
Jukka Kujanpää
Finnish Meteorological Institute, Earth Observation Unit, P.O. Box 503, 00101 Helsinki, Finland
Rossana Dragani
European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
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Cited
13 citations as recorded by crossref.
- A Distributed Modular Data Processing Chain Applied to Simulated Satellite Ozone Observations M. Gai et al. 10.3390/rs13020210
- Benefit of ozone observations from Sentinel-5P and future Sentinel-4 missions on tropospheric composition S. Quesada-Ruiz et al. 10.5194/amt-13-131-2020
- An improved formula for the complete data fusion S. Ceccherini et al. 10.5194/amt-15-7039-2022
- Advanced Ultraviolet Radiation and Ozone Retrieval for Applications—Surface Ultraviolet Radiation Products A. Lipponen et al. 10.3390/atmos11040324
- Synergistic retrieval and complete data fusion methods applied to simulated FORUM and IASI-NG measurements M. Ridolfi et al. 10.5194/amt-15-6723-2022
- Advanced Ultraviolet Radiation and Ozone Retrieval for Applications (AURORA): A Project Overview U. Cortesi et al. 10.3390/atmos9110454
- Application of the Complete Data Fusion algorithm to the ozone profiles measured by geostationary and low-Earth-orbit satellites: a feasibility study N. Zoppetti et al. 10.5194/amt-14-2041-2021
- Interpolation uncertainty of atmospheric temperature profiles A. Fassò et al. 10.5194/amt-13-6445-2020
- Harmonization and comparison of vertically resolved atmospheric state observations: methods, effects, and uncertainty budget A. Keppens et al. 10.5194/amt-12-4379-2019
- Generalization of the complete data fusion to multi-target retrieval of atmospheric parameters and application to FORUM and IASI-NG simulated measurements C. Tirelli et al. 10.1016/j.jqsrt.2021.107925
- The cost function of the data fusion process and its application S. Ceccherini et al. 10.5194/amt-12-2967-2019
- Data Fusion Analysis of Sentinel-4 and Sentinel-5 Simulated Ozone Data C. Tirelli et al. 10.1175/JTECH-D-19-0063.1
- Removing Prior Information from Remotely Sensed Atmospheric Profiles by Wiener Deconvolution Based on the Complete Data Fusion Framework A. Keppens et al. 10.3390/rs14092197
13 citations as recorded by crossref.
- A Distributed Modular Data Processing Chain Applied to Simulated Satellite Ozone Observations M. Gai et al. 10.3390/rs13020210
- Benefit of ozone observations from Sentinel-5P and future Sentinel-4 missions on tropospheric composition S. Quesada-Ruiz et al. 10.5194/amt-13-131-2020
- An improved formula for the complete data fusion S. Ceccherini et al. 10.5194/amt-15-7039-2022
- Advanced Ultraviolet Radiation and Ozone Retrieval for Applications—Surface Ultraviolet Radiation Products A. Lipponen et al. 10.3390/atmos11040324
- Synergistic retrieval and complete data fusion methods applied to simulated FORUM and IASI-NG measurements M. Ridolfi et al. 10.5194/amt-15-6723-2022
- Advanced Ultraviolet Radiation and Ozone Retrieval for Applications (AURORA): A Project Overview U. Cortesi et al. 10.3390/atmos9110454
- Application of the Complete Data Fusion algorithm to the ozone profiles measured by geostationary and low-Earth-orbit satellites: a feasibility study N. Zoppetti et al. 10.5194/amt-14-2041-2021
- Interpolation uncertainty of atmospheric temperature profiles A. Fassò et al. 10.5194/amt-13-6445-2020
- Harmonization and comparison of vertically resolved atmospheric state observations: methods, effects, and uncertainty budget A. Keppens et al. 10.5194/amt-12-4379-2019
- Generalization of the complete data fusion to multi-target retrieval of atmospheric parameters and application to FORUM and IASI-NG simulated measurements C. Tirelli et al. 10.1016/j.jqsrt.2021.107925
- The cost function of the data fusion process and its application S. Ceccherini et al. 10.5194/amt-12-2967-2019
- Data Fusion Analysis of Sentinel-4 and Sentinel-5 Simulated Ozone Data C. Tirelli et al. 10.1175/JTECH-D-19-0063.1
- Removing Prior Information from Remotely Sensed Atmospheric Profiles by Wiener Deconvolution Based on the Complete Data Fusion Framework A. Keppens et al. 10.3390/rs14092197
Latest update: 24 Apr 2024
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.
Data fusion is an important tool to reduce data volume and to improve data quality.
This paper...
