Abstract. Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10 %. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30 ‰ for the ratio between the two isotopologues HD 16 O and H 16 2 O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO 2 retrievals and use them for demonstrating the MUSICA network-wide data consistency.In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multiyear mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.
Abstract. In the lower/middle troposphere, {H 2 O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUltiplatform 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 {H 2 O,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 {H 2 O,δD} data pairs.First, we briefly resume the particularities of an {H 2 O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H 2 O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H 2 O,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 {H 2 O,δD} pair distributions due to incomplete processing of the remote sensing products.
Abstract. Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground-and space-based remote sensing as well as in situ data sets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing data set is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale.Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, midlatitudes, and Arctic), and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remotesensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier Transform InfraRed) remote-sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change).We confirm that IASI is able to measure tropospheric H 2 O profiles with a vertical resolution of about 4 km and a random error of about 10 %. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H 2 O observations. Our study presents theoretical and empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes.
Abstract. We present two years of in situ measurements of water vapour (H 2 O) and its isotopologue ratio (δD, the standardized ratio between H 2 16 O and HD 16 O), made at two remote mountain sites on Tenerife in the subtropical North Atlantic. We show that the data -if measured during night-time -are well representative for the lower/middle free troposphere. We use the measured H 2 O-δD pairs, together with dust measurements and back trajectory modelling for analysing the moisture pathways to this region. We can identify four principally different transport pathways. The air mass transport from high altitudes and high latitudes shows two different scenarios. The first scenario brings dry air masses to the stations, as the result of condensation events occurring at low temperatures. The second scenario brings humid air masses to the stations, due to cross-isentropic mixing with lower-level and more humid air during transport since last condensation (LC). The third pathway is transportation from lower latitudes and lower altitudes, whereby we can identify rain re-evaporation as an occasional source of moisture. The fourth pathway is linked to the African continent, where during summer, dry convection processes over the Sahara very effectively inject humidity from the boundary layer to higher altitudes. This so-called Saharan Air Layer (SAL) is then advected westward over the Atlantic and contributes to moisten the free troposphere. We demonstrate that the different pathways leave distinct fingerprints on the measured H 2 O-δD pairs.
Abstract. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) integrates tropospheric water vapour isotopologue remote sensing and in situ observations. This paper presents a first empirical validation of MUSICA's H 2 O and δD remote sensing products, generated from groundbased FTIR (Fourier transform infrared), spectrometer and space-based IASI (infrared atmospheric sounding interferometer) observation. The study is made in the area of the Canary Islands in the subtropical northern Atlantic. As reference we use well calibrated in situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers.The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the variations in the water vapour isotopologues, and the scatter with respect to the in situ references suggests a δD random uncertainty for the FTIR product of much better than 45 ‰ in the lower troposphere and of about 15 ‰ for the middle troposphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15 ‰. In both remote sensing data sets we find a positive δD bias of 30-70 ‰.Complementing H 2 O observations with δD data allows moisture transport studies that are not possible with H 2 O observations alone. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data. We document that the δD-H 2 O curves obtained from the different in situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere.
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