Synergy between middle infrared and millimeter-wave limb sounding of atmospheric temperature and minor constituents

Abstract

Abstract. Synergistic exploitation of redundant and complementary information from independent observations of the same target remains a major issue in atmospheric remote sounding and increasing attention is devoted to investigate optimized or innovative methods for the combination of two or more measured data sets. This paper focuses on the synergy between middle infrared and millimeterwave limb sounding measurements of atmospheric composition and temperature and reports the results of a study conducted as part of the preparatory activities of the PRE-MIER (Process Exploration through Measurements of Infrared and millimeter-wave Emitted Radiation) mission candidate to the Core Missions of the European Space Agency (ESA) Earth Explorer 7. The activity was based on data acquired by the MIPAS-STR (Michelson Interferometer for Passive Atmospheric Sounding -STRatospheric aircraft) and MARSCHALS (Millimetre-wave Airborne Receivers for Spectroscopic CHaracterisation in Atmospheric Limb Sounding) instruments on-board the high-altitude research aircraft M-55 Geophysica during the flight of the PremierEx (PREMIER Experiment) campaign on 10 March 2010 from Kiruna, Sweden, for observation of the Arctic upper troposphere and lower stratosphere. The cloud coverage observed along the flight provided representative test cases to evaluate the synergy in three different scenarios: low clouds in the first part, no clouds in the central part and high tropospheric clouds at the end. The calculation of synergistic profiles of four atmospheric targets (i.e., O 3 , HNO 3 , H 2 O and temperature) was performed using a posteriori combination of individual retrieved profiles, i.e., Level 2 (L2) data rather than simultaneous inversion of observed radiances, i.e., Level 1 (L1) data. An innovative method of data fusion, based on the Measurement Space Solution (MSS) was applied along with the standard approach of inversion of MARSCHALS spectral radiances using MIPAS-STR retrieval products as a priori information (L1 + L2 method). A quantitative estimate and cross-check of the results of MSS data fusion and (L1 + L2) method was achieved based on a specific set of quantifiers including the total retrieval error, the number of degrees of freedom, the relative information distribution and the synergy factor.

The cost function of the data fusion process and its application

“…The CDF method was proved (Ceccherini, 2016) to be equivalent to the measurement space solution data fusion method (Ceccherini et al, 2009) and the latter was successfully applied to the data fusion of MIPAS-ENVISAT and IASI-METOP measurements (Ceccherini et al, 2010a;Ceccherini et al, 2010b) and of MIPAS-STR and MARSCHALS measurements (Cortesi et al, 2016).…”

Importance of interpolation and coincidence errors in data fusion

“…About the fusion of data provided by different instruments, it has been proved (Ceccherini, 2016) that the CDF method is completely equivalent to the measurement space solution (MSS) data fusion method (Ceccherini et al, 2009). The latter was successfully applied to the data fusion of MIPAS-ENVISAT and IASI-METOP measurements (Ceccherini et al, 2010a, b) and of MIPAS-STR and MARSCHALS measurements (Cortesi et al, 2016). However, since in these cases the measurements to be fused (referred to as fusing profiles hereafter) carried information about basically complementary altitude ranges, their possible inconsistency did not result in unrealistic fused profiles.…”

Reply to referee #1

“…About the fusion of data provided by different instruments, it has been proved (Ceccherini, 2016) that the CDF method is completely equivalent to the measurement space solution (MSS) data fusion method (Ceccherini et al, 2009). The latter was successfully applied to the data fusion of MIPAS-ENVISAT and IASI-METOP measurements (Ceccherini et al, 2010a, b) and of MIPAS-STR and MARSCHALS measurements (Cortesi et al, 2016). However, since in these cases the measurements to be fused (referred to as fusing profiles hereafter) carried information about basically complementary altitude ranges, their possible inconsistency did not result in unrealistic fused profiles.…”

“…eu/main/sentinels). The advantages in using a multispectral approach for observing ozone profiles from space have been studied, using simulated measurements, by Landgraf and Hasekamp (2007), Worden et al (2007), Natraj et al 2011, Hache et al (2014) and Costantino et al (2017), and, using real measurements, by Fu et al (2013) and Cuesta et al (2013). Two review papers on this subject are Lahoz et al (2012) and Timmermans et al (2015).…”