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Atmos. Meas. Tech., 11, 1009-1017, 2018
https://doi.org/10.5194/amt-11-1009-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
20 Feb 2018
Importance of interpolation and coincidence errors in data fusion
Simone Ceccherini1, Bruno Carli1, Cecilia Tirelli1, Nicola Zoppetti1, Samuele Del Bianco1, Ugo Cortesi1, Jukka Kujanpää2, and Rossana Dragani3 1Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
2Finnish Meteorological Institute, Earth Observation Unit, P.O. Box 503, 00101 Helsinki, Finland
3European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
Abstract. The complete data fusion (CDF) method is applied to ozone profiles obtained from simulated measurements in the ultraviolet and in the thermal infrared in the framework of the Sentinel 4 mission of the Copernicus programme. We observe that the quality of the fused products is degraded when the fusing profiles are either retrieved on different vertical grids or referred to different true profiles. To address this shortcoming, a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors, is presented. This upgrade overcomes the encountered problems and provides products of good quality when the fusing profiles are both retrieved on different vertical grids and referred to different true profiles. The impact of the interpolation and coincidence errors on number of degrees of freedom and errors of the fused profile is also analysed. The approach developed here to account for the interpolation and coincidence errors can also be followed to include other error components, such as forward model errors.

Citation: Ceccherini, S., Carli, B., Tirelli, C., Zoppetti, N., Del Bianco, S., Cortesi, U., Kujanpää, J., and Dragani, R.: Importance of interpolation and coincidence errors in data fusion, Atmos. Meas. Tech., 11, 1009-1017, https://doi.org/10.5194/amt-11-1009-2018, 2018.
Publications Copernicus
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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...
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