Nicola Zoppetti

We present a new ozone dataset generated using the Complete Data Fusion (CDF) algorithm, which combines limb observations from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard ESA's Envisat and nadir observations from the Infrared Atmospheric Sounding Interferometer (IASI) aboard EUMETSAT's MetOp satellites during their overlapping operational period (2008–2011). The fusion aims to enhance ozone profile information in the Upper Troposphere–Lower Stratosphere (UTLS), particularly over the Himalayas – a key region for stratospheric intrusion events. The fused dataset, mapped onto the IASI–MetOp grid, includes ozone partial columns with associated uncertainty estimates (covariance matrices-CMs, averaging kernels-AKs, and a priori profiles). After tuning the algorithm on 2008 data, the product was validated for the 2009–2011 period against ozonesondes from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) stations across multiple latitude bands. Results show that the fused profiles improve vertical information content and reduce uncertainty, successfully propagating MIPAS information to lower altitudes even in regions lacking direct limb observations. While the dataset initially exhibited altitude- and latitude-dependent biases, primarily inherited from IASI, these were significantly reduced through bias correction. The final product is suitable for data assimilation and model evaluation, offering valuable support for atmospheric reanalyses and studies of troposphere–stratosphere exchange processes.

We present a new ozone dataset generated using the Complete Data Fusion (CDF) algorithm, which combines limb observations from MIPAS-ENVISAT along with nadir observations from IASI during their overlapping operational period (2008–2011). The fusion aims to enhance ozone profile information in the Upper Troposphere–Lower Stratosphere (UTLS), particularly over the Himalayas—a key region for stratospheric intrusion events. The fused dataset, mapped onto the IASI- MetOp grid, includes ozone partial columns with associated uncertainty estimates (covariance matrices, averaging kernels, and a priori profiles). After tuning the algorithm on 2008 data, the product was validated for the 2009–2011 period against ozonesondes from WOUDC stations across multiple latitude bands. Results show that the fused profiles improve vertical information content (degrees of freedom) and reduce uncertainty, successfully propagating MIPAS information to lower altitudes even in regions lacking direct limb observations. While the dataset initially exhibited altitude- and latitude-dependent biases, primarily inherited from IASI, these were significantly reduced through bias correction. The final product is suitable for data assimilation and model evaluation, offering valuable support for atmospheric reanalyses and studies of troposphere–stratosphere exchange processes.

We present a new ozone dataset generated using the Complete Data Fusion (CDF) algorithm, which combines limb observations from MIPAS-ENVISAT along with nadir observations from IASI during their overlapping operational period (2008–2011). The fusion aims to enhance ozone profile information in the Upper Troposphere–Lower Stratosphere (UTLS), particularly over the Himalayas—a key region for stratospheric intrusion events. The fused dataset, mapped onto the IASI- MetOp grid, includes ozone partial columns with associated uncertainty estimates (covariance matrices, averaging kernels, and a priori profiles). After tuning the algorithm on 2008 data, the product was validated for the 2009–2011 period against ozonesondes from WOUDC stations across multiple latitude bands. Results show that the fused profiles improve vertical information content (degrees of freedom) and reduce uncertainty, successfully propagating MIPAS information to lower altitudes even in regions lacking direct limb observations. While the dataset initially exhibited altitude- and latitude-dependent biases, primarily inherited from IASI, these were significantly reduced through bias correction. The final product is suitable for data assimilation and model evaluation, offering valuable support for atmospheric reanalyses and studies of troposphere–stratosphere exchange processes.

We present a new ozone dataset generated using the Complete Data Fusion (CDF) algorithm, which combines limb observations from MIPAS-ENVISAT along with nadir observations from IASI during their overlapping operational period (2008–2011). The fusion aims to enhance ozone profile information in the Upper Troposphere–Lower Stratosphere (UTLS), particularly over the Himalayas—a key region for stratospheric intrusion events. The fused dataset, mapped onto the IASI- MetOp grid, includes ozone partial columns with associated uncertainty estimates (covariance matrices, averaging kernels, and a priori profiles). After tuning the algorithm on 2008 data, the product was validated for the 2009–2011 period against ozonesondes from WOUDC stations across multiple latitude bands. Results show that the fused profiles improve vertical information content (degrees of freedom) and reduce uncertainty, successfully propagating MIPAS information to lower altitudes even in regions lacking direct limb observations. While the dataset initially exhibited altitude- and latitude-dependent biases, primarily inherited from IASI, these were significantly reduced through bias correction. The final product is suitable for data assimilation and model evaluation, offering valuable support for atmospheric reanalyses and studies of troposphere–stratosphere exchange processes.

We present a new ozone dataset generated using the Complete Data Fusion (CDF) algorithm, which combines limb observations from MIPAS-ENVISAT along with nadir observations from IASI during their overlapping operational period (2008–2011). The fusion aims to enhance ozone profile information in the Upper Troposphere–Lower Stratosphere (UTLS), particularly over the Himalayas—a key region for stratospheric intrusion events. The fused dataset, mapped onto the IASI- MetOp grid, includes ozone partial columns with associated uncertainty estimates (covariance matrices, averaging kernels, and a priori profiles). After tuning the algorithm on 2008 data, the product was validated for the 2009–2011 period against ozonesondes from WOUDC stations across multiple latitude bands. Results show that the fused profiles improve vertical information content (degrees of freedom) and reduce uncertainty, successfully propagating MIPAS information to lower altitudes even in regions lacking direct limb observations. While the dataset initially exhibited altitude- and latitude-dependent biases, primarily inherited from IASI, these were significantly reduced through bias correction. The final product is suitable for data assimilation and model evaluation, offering valuable support for atmospheric reanalyses and studies of troposphere–stratosphere exchange processes.

We present a new ozone dataset generated using the Complete Data Fusion (CDF) algorithm, which combines limb observations from MIPAS-ENVISAT along with nadir observations from IASI during their overlapping operational period (2008–2011). The fusion aims to enhance ozone profile information in the Upper Troposphere–Lower Stratosphere (UTLS), particularly over the Himalayas—a key region for stratospheric intrusion events. The fused dataset, mapped onto the IASI- MetOp grid, includes ozone partial columns with associated uncertainty estimates (covariance matrices, averaging kernels, and a priori profiles). After tuning the algorithm on 2008 data, the product was validated for the 2009–2011 period against ozonesondes from WOUDC stations across multiple latitude bands. Results show that the fused profiles improve vertical information content (degrees of freedom) and reduce uncertainty, successfully propagating MIPAS information to lower altitudes even in regions lacking direct limb observations. While the dataset initially exhibited altitude- and latitude-dependent biases, primarily inherited from IASI, these were significantly reduced through bias correction. The final product is suitable for data assimilation and model evaluation, offering valuable support for atmospheric reanalyses and studies of troposphere–stratosphere exchange processes.

We present a new ozone dataset generated using the Complete Data Fusion (CDF) algorithm, which combines limb observations from MIPAS-ENVISAT along with nadir observations from IASI during their overlapping operational period (2008–2011). The fusion aims to enhance ozone profile information in the Upper Troposphere–Lower Stratosphere (UTLS), particularly over the Himalayas—a key region for stratospheric intrusion events. The fused dataset, mapped onto the IASI- MetOp grid, includes ozone partial columns with associated uncertainty estimates (covariance matrices, averaging kernels, and a priori profiles). After tuning the algorithm on 2008 data, the product was validated for the 2009–2011 period against ozonesondes from WOUDC stations across multiple latitude bands. Results show that the fused profiles improve vertical information content (degrees of freedom) and reduce uncertainty, successfully propagating MIPAS information to lower altitudes even in regions lacking direct limb observations. While the dataset initially exhibited altitude- and latitude-dependent biases, primarily inherited from IASI, these were significantly reduced through bias correction. The final product is suitable for data assimilation and model evaluation, offering valuable support for atmospheric reanalyses and studies of troposphere–stratosphere exchange processes.

The complete data fusion is a method that combines independent measurements of atmospheric vertical profiles. Recently a new formula for the complete data fusion, which does not contain matrices that can be singular and overcomes the generalized inverse approximation used when singular matrices have to be inverted, has been proposed. We show that the new formula is a generalization of the original one and analyze the analytical relationship between the two formulas when generalized inverse matrices are used for the inversion of singular matrices. We extend the new formula to include interpolation and coincidence errors, which must be considered when the profiles to be fused are measured on different vertical grids and at different times and/or locations. Finally, we use a real measurement of the Infrared Atmospheric Sounding Interferometer (IASI) instrument to show the improved performances of the new formula with respect to the original one.

The Complete Data Fusion is a method that combines independent measurements of an atmospheric vertical profile. Recently a new formula for the Complete Data Fusion, which does not contain matrices that can be singular and overcomes the generalized inverse approximation used when singular matrices have to be inverted, has been proposed. We show that the new formula is a generalization of the original one and analyze the analytical relationship between the two formulas when generalized inverse matrices are used for singular matrices. We extend the new formula to include interpolation and coincidence errors, which must be considered when the profiles to be fused are measured on different vertical grids and at either different times or locations. Finally, we use a real measurement of the IASI instrument to show the improved performances of the new formula with respect to the original one.

High quality long-term data sets of altitude-resolved measurements of the atmospheric composition are important because they can be used both to study the evolution of the atmosphere and as a benchmark for future missions. For the final ESA reprocessing of MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) on ENVISAT (ENViromental SATellite) data, numerous improvements were implemented in the Level 2 (L2) processor Optimised Retrieval Model (ORM) version 8.22 (V8) and its auxiliary data. The implemented changes involve all aspects of the processing chain, from the modelling of the measurements with the handling of the horizontal inhomogeneities along the line of sight to the use of the optimal estimation technique to retrieve the minor species, from a more sensitive approach to detecting the spectra affected by clouds to a refined method for identifying low quality products. Improvements in the modelling of the measurements were also obtained with an update of the used spectroscopic data and of the databases providing the a priori knowledge of the atmosphere. The HITRAN_mipas_pf4.45 spectroscopic database was finalised with new spectroscopic data verified with MIPAS measurements themselves, while recently measured cross-sections were used for the heavy molecules. The Level 2 Initial Guess (IG2) data set, containing the climatology used by the MIPAS L2 processor to generate the initial guess and interfering species profiles when the retrieved profiles from previous scans are not available, was improved taking into account the diurnal variation of the profiles defined using climatologies from both measurements and models. Horizontal gradients were generated using the ECMWF ERA-Interim data closest in time and space to the MIPAS data. Further improvements in the L2 V8 products derived from the use of the L1b V8 products, which were upgraded to reduce the instrumental temporal drift and to handle the abrupt changes in the calibration gain. The improvements introduced into the ORM V8 L2 processor and its upgraded auxiliary data, together with the use of the L1b V8 products, lead to the generation of the MIPAS L2 V8 products, which are characterised by an increased accuracy, better temporal stability and a greater number of retrieved species.