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MIPAS-ENVISAT and IASI-METOP data fusion using the Measurement Space Solution method

Ugo Cortesi(1), Simone Ceccherini(1), Samuele Del Bianco(1), Piera Raspollini(1) and Bruno Carli(1)

(1) Istituto di Fisica Applicata N. Carrara (IFAC-CNR), Via Madonna del Piano, 10, 50019 Sesto Fiorentino (Firenze), Italy

Abstract

The goal of data fusion techniques is to combine independent measurements of the same target in order to exploit the complementarities of different observations. In principle data fusion can be obtained by analyzing simultaneously the observations made by different instruments (L1-L1 data fusion), but often this is impracticable because of either the too large amount of data, or the different forward models required. The data fusion of retrieved quantities can be alternatively used (L2-L2 data fusion). In this case, when the different measurements are represented on different grids (defined by the different observation strategies and retrieval methods), the combination implies some interpolation that produces a loss of information. It is possible to avoid the problem of interpolation by using some a-priori information in the L2 products, which however may introduce a bias in the fused data. Interpolations and biases are the two main problems encountered in data fusion applications. These problems can be overcome using the measurement space solution (MSS) method for the representation of the retrieval products and for the subsequent data fusion. In this work we present the application of the MSS method to the data fusion of the ozone profiles measured by MIPAS-ENVISAT and IASI-METOP spectrometers. Advantages of the MIPAS-IASI ozone data fusion are demonstrated by comparing the performances of quality of the fused ozone profiles with that of the individual products in retrieval test conducted on simulated measurements. An example of O3 data fusion in case of real MIPAS and IASI measurements is given.