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National audience; This article is the first step of a complex process of measuring fine particle concentrations by spectral cameras. To do this, an accurate and fast classification of all pixels from a hyperspectral image is crucial to determine the nature of the objects and their optical properties. The methods traditionally used rely on the richness of the spectral information in measurements with hundreds of wavelengths. However, neglecting the spatial dimension during the classification can lead to situations where the resulting classes may not be spatially consistent. Here, we propose a classification method (Spatial Spectral Optimised Classification) based on learning, which takes into account spectral features but also spatial information via neighbouring pixels.; Cet article est la première étape d'un processus complexe de mesure de la concentration de particules fines par des caméras spectrales. Pour ce faire, une classification précise et rapide de tous les pixels d'une image hyperspectrale est cruciale pour déterminer la nature des objets et leurs propriétés optiques. Les méthodes traditionnellement utilisées reposent sur la richesse de l'information spectrale avec des centaines de longueurs d'onde habituellement mesurées par les caméras. Cependant, négliger la dimension spatiale durant une classification conduit à certaines situations où les classes obtenues ne sont pas spatialement cohérentes. Nous proposons ici une méthode de classification optimisée pour la mesure de la qualité de l'air (Spatial Spectral Optimised Classification) basée sur l'apprentissage, qui prend en compte les caractéristiques spectrales mais aussi l'information spatiale via les pixels voisins.

In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.

In the lower/middle troposphere H2O-δD pairs are good proxies for moisture pathways, however their observation is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating remote sensing with in-situ measurement techniques. The aim is to retrieve accurate tropospheric H2O-δD pairs from the middle infrared spectra measured from ground by the FTIR (Fourier Transform InfraRed) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper we review the MUSICA framework, present the final MUSICA products, and outline the NDACC/FTIR’s and METOP/IASI’s potential for observing accurate and consistent H2O-δD data pairs. First, we briefly resume the particularities of an H2O-δD pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in-situ profile references measured in the subtropics, between 0 and 7 km. Third, we empirically demonstrate that the calibrated remote sensing H2O-δD pairs can identify different lower/middle tropospheric moisture pathways and advert to the risk of misinterpretations caused by an incorrect processing of such remote sensing data. Fourth, we reveal that the different sensors (NDACC/FTIR instruments, MetOp/IASI-A, and MetOp/IASI-B) provide consistent H2O-δD pairs for very distinct atmospheric clear sky conditions. Fifth, we document the unique possibilities of the NDACC/FTIR instruments for providing long-term records (important for climatological studies) and of the MetOp/IASI sensors for observing diurnal signals on quasi global scale and with high horizontal resolution. This study has been conducted in the framework of the project MUSICA which is funded by the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013) / ERC Grant agreement number 256961. E. Sepúlveda is supported by the Ministerio de Economía and Competitividad of Spain for the project NOVIA (CGL2012-37505). The aircraft campaign has been co-funded by the project MUSICA and the Spanish national project AMISOC (CGL2011-24891). The AERONET sun photometer at Izaña (PI: Dr. Emilio Cuevas) has been calibrated within AERONET EUROPE TNA supported by the European Community Research Infrastructure Action under the FP7 Capacities program for Integrating Activities, ACTRIS grant agreement number 262254. The Izaña aerosol in-situ measurements are part of the project POLLINDUST (CGL2011-26259) funded by the Minister of Economy and Competitiveness of Spain.

In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.

Tropospheric {H2O,δD} pairs can be observed by remote sensing techniques, but the data quality strongly depends on a comprehensive consideration of the complex nature and a careful calibration of the remote sensing data pairs. This paper reviews the quality assurance/documentation activities of the MUSICA project and demonstrates that MUSICA’s ground-based FTIR and space-based IASI {H2O,δD} pair products are accurate and can be generated at a global scale with high resolution and for long periods. This study has been conducted in the framework of the project MUSICA which is funded by the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013) / ERC Grant agreement number 256961. E. Sepúlveda is supported by the Ministerio de Economía and Competitividad of Spain for the project NOVIA (CGL2012-37505). The aircraft campaign has been co-funded by the project MUSICA and the Spanish national project AMISOC (CGL2011-24891). The AERONET sun photometer at Izaña (PI: Dr. Emilio Cuevas) has been calibrated within AERONET EUROPE TNA supported by the European Community Research Infrastructure Action under the FP7 Capacities program for Integrating Activities, ACTRIS grant agreement number 262254. The Izaña aerosol in-situ measurements are part of the project POLLINDUST (CGL2011-26259) funded by the Minister of Economy and Competitiveness of Spain.

Memoria para optar al título de doctor en Ciencias Físicas, Universidad Autónoma de Madrid. Departamento de Física aplicada

Comunicación presentada en: V Reunión Española de Ciencia y Tecnología de Aerosoles – RECTA 2011 celebrada del 27 al 29 de junio de 2011 en CIEMAT, Madrid.

In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.

Measurements on 27 June 2011 were performed over the Southern Iberian Peninsula at Granada EARLINET station, using active and passive remote sensing and airborne and surface in-situ data in order to study the entrainment processes between aerosols in the free troposphere and those in the planetary boundary layer (PBL). To this aim the temporal evolution of the lidar depolarisation, backscatter-related Angström exponent and potential temperature profiles were used in combination with the PBL contribution to the aerosol optical depth (AOD). Our results show that the mineral dust entrainment in the PBL was caused by the convective processes which ‘trapped’ the lofted mineral dust layer, distributing the mineral dust particles within the PBL. The temporal evolution of ground-based in-situ data evidenced the impact of this process at surface level. Finally, the amount of mineral dust in the atmospheric column available to be dispersed into the PBL was estimated by means of POLIPHON (Polarizing Lidar Photometer Networking). The dust mass concentration derived from POLIPHON was compared with the coarse-mode mass concentration retrieved with airborne in-situ measurements. Comparison shows differences below 50 µg/m³ (30% relative difference) indicating a relative good agreement between both techniques.