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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/amt-2019-436
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-436
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  18 Dec 2019

18 Dec 2019

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This preprint is currently under review for the journal AMT.

The Complete Data Fusion for a Full Exploitation of Copernicus Atmospheric Sentinel Level 2 Products

Nicola Zoppetti1, Simone Ceccherini1, Bruno Carli1, Samuele Del Bianco1, Marco Gai1, Cecilia Tirelli1, Flavio Barbara1, Rossana Dragani2, Antti Arola3, Jukka Kujanpää4, Jacob C. A. van Peet5,6, Ronald van der A5, and Ugo Cortesi1 Nicola Zoppetti et al.
  • 1Istituto di Fisica Applicata "Nello Carrara" del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
  • 2European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
  • 3Finnish Meteorological Institute, Atmospheric Research Centre of Eastern Finland, P.O.Box 1627, 70211 Kuopio, Finland
  • 4Finnish Meteorological Institute, Space and Earth Observation Centre, P.O. Box 503, FI-00101 Helsinki, Finland
  • 5Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, The Netherlands
  • 6Vrije Universiteit Amsterdam, Department of Earth Sciences, Amsterdam, The Netherlands

Abstract. The new platforms for Earth observation from space are characterized by measurements made with great spatial and temporal resolution. While this abundance of information makes it possible to detect and study localized phenomena, on the other hand it may be difficult to manage this large amount of data in the study of global and large scale phenomena.

A particularly significant example is the use by assimilation systems of level 2 products that represent gas profiles in the atmosphere. The models on which assimilation systems are based are discretized on spatial grids with horizontal dimensions of the order of tens of kilometres in which tens or hundreds of measurements may fall.

A simple procedure to overcome this problem is to extract a subset of the original measurements. However, this procedure involves a loss of information and is therefore justifiable only as a temporary solution. A more refined solution is to resort to the so-called fusion algorithms, capable of compressing the size of the dataset limiting the information loss. A novel data fusion method, the Complete Data Fusion, was recently developed to merge a-posteriori a set of retrieved products in a single one. In the present paper, the Complete Data Fusion method is applied to ozone profile measurements simulated in the thermal infrared and ultraviolet bands, in a realistic scenario, according to the specifications of the Sentinel 4 and 5 missions of the Copernicus programme. Then the fused products are compared with the input profiles; comparisons show that the output products of data fusion have in general smaller errors and higher information contents. The most significant improvement is an increased vertical resolution together with a reduction of the errors. The comparisons of the fused with the fusing products are presented both at single fusion grid-box scale and with a statistical analysis. The grid box size impact was also evaluated, showing that the Complete Data Fusion method can be used with a wide range of grid-box size, the quality of the products improving with larger grid boxes.

Nicola Zoppetti et al.

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Nicola Zoppetti et al.

Nicola Zoppetti et al.

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Latest update: 04 Aug 2020
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Short summary
The atmospheric Sentinels will provide an enormous amount of data that can be hard to exploit as a whole. The Complete Data Fusion algorithm is able to reduce the data volume while retaining the information of the full data set. In this work, the Complete Data Fusion is applied to simulated ozone profiles and the results show that the fused products are characterized by higher information content compared to individual L2 products.
The atmospheric Sentinels will provide an enormous amount of data that can be hard to exploit as...
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