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We present a global and multi-annual space-borne dataset of tropospheric { H2O , δ D } pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) on board the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in. From the independently retrieved H2O and δ D proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset, we generate an optimal estimation product for pairs of H2O and δ D. Here, this standard MUSICA method for deriving { H2O , δ D } pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a { H2O , δ D } pair dataset for the whole period from October 2014 to December 2020 with global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1500 million individually processed observations. The retrievals are most sensitive to variations in { H2O , δ D } pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the { H2O , δ D } pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but higher latitudes also show a considerable amount of reliable data. Exemplary time series over the tropical Atlantic and West Africa are chosen to illustrate the potential of the MUSICA IASI { H2O , δ D } pair data for atmospheric moisture pathway studies. Furthermore, in order to facilitate the application of this rather comprehensive MUSICA IASI { H2O , δ D } pair dataset (referred to as Level-2), we additionally provide the data in a re-gridded and simplified format (Level-3) with focus on the quality-filtered { H2O , δ D } pairs in the free troposphere. A technical documentation for guiding the use of both datasets is attached as the Supplement. Finally, the Level-2 dataset is referenced with the DOI 10.35097/415 and the Level-3 dataset with DOI 10.35097/495. [ABSTRACT FROM AUTHOR]

Due to its dryness, the subtropical free troposphere plays a critical role in the radiative balance of the Earth's climate system. But the complex interactions of the dynamical and physical processes controlling the variability in the moisture budget of this sensitive region of the subtropical atmosphere are still not fully understood. Stable water isotopes can provide important information about several of the latter processes, namely subsidence drying, turbulent mixing, and dry and moist convective moistening. In this study, we use high-resolution simulations of the isotope-enabled version of the regional weather and climate prediction model of the Consortium for Small-Scale Modelling (COSMO iso) to investigate predominant moisture transport pathways in the Canary Islands region in the eastern subtropical North Atlantic. Comparison of the simulated isotope signals with multi-platform isotope observations (aircraft, ground- and space-based remote sensing) from a field campaign in summer 2013 shows that COSMO iso can reproduce the observed variability of stable water vapour isotopes on timescales of hours to days, thus allowing us to study the mechanisms that control the subtropical free-tropospheric humidity. Changes in isotopic signals along backward trajectories from the Canary Islands region reveal the physical processes behind the synoptic-scale isotope variability. We identify four predominant moisture transport pathways of mid-tropospheric air, each with distinct isotopic signatures: air parcels originating from the convective boundary layer of the Saharan heat low (SHL) – these are characterised by a homogeneous isotopic composition with a particularly high δD (median mid-tropospheric δD=-122‰), which results from dry convective mixing of low-level moisture of diverse origin advected into the SHL; air parcels originating from the free troposphere above the SHL – although experiencing the largest changes in humidity and δD during their subsidence over West Africa, these air parcels typically have lower δD values (median δD=-148‰) than air parcels originating from the boundary layer of the SHL; air parcels originating from outside the SHL region, typically descending from tropical upper levels south of the SHL, which are often affected by moist convective injections from mesoscale convective systems in the Sahel – their isotopic composition is much less enriched in heavy isotopes (median δD=-175‰) than those from the SHL region; air parcels subsiding from the upper-level extratropical North Atlantic – this pathway leads to the driest and most depleted conditions (median δD=-255‰) in the middle troposphere near the Canary Islands. The alternation of these transport pathways explains the observed high variability in humidity and δD on synoptic timescales to a large degree. We further show that the four different transport pathways are related to specific large-scale flow conditions. In particular, distinct differences in the location of the North African mid-level anticyclone and of extratropical Rossby wave patterns occur between the four transport pathways. Overall, this study demonstrates that the adopted Lagrangian isotope perspective enhances our understanding of air mass transport and mixing and offers a sound interpretation of the free-tropospheric variability of specific humidity and isotope composition on timescales of hours to days in contrasting atmospheric conditions over the eastern subtropical North Atlantic. [ABSTRACT FROM AUTHOR]

We present a Lagrangian framework for identifying mechanisms that control the isotopic composition of mid‐tropospheric water vapor in the Sahel region during the West African Monsoon 2016. In this region mixing between contrasting air masses, strong convective activity, as well as surface and rain evaporation lead to high variability in the distribution of stable water isotopologues. Using backward trajectories based on high‐resolution isotope‐enabled model data, we obtain information not only about the source regions of Sahelian air masses, but also about the evolution of H2O and its isotopologue HDO (expressed as δD) along the pathways of individual air parcels. We sort the full trajectory ensemble into groups with similar transport pathways and hydro‐meteorological properties, such as precipitation and relative humidity, and investigate the evolution of the corresponding paired {H2O, δD} distributions. The use of idealized process curves in the {H2O, δD} phase space allows us to attribute isotopic changes to contributions from (a) air mass mixing, (b) Rayleigh condensation during convection, and (c) microphysical processes depleting the vapor beyond the Rayleigh prediction, i.e., partial rain evaporation in unsaturated and isotopic equilibration in saturated conditions. Different combinations of these processes along the trajectory ensembles are found to determine the final isotopic composition in the Sahelian troposphere during the monsoon. The presented Lagrangian framework is a powerful tool for interpreting tropospheric water vapor distributions. In the future, it will be applied to satellite observations of {H2O, δD} over Africa and other regions in order to better quantify characteristics of the hydrological cycle. Key Points: New Lagrangian framework to attribute variability in {H2O, δD} distributions to air mass mixing and phase changes of waterApplication to West African Monsoon season 2016 shows characteristic mixing and precipitation effects along trajectoriesNew framework can be used for the interpretation of satellite and in‐situ observations, and for model validation in future work [ABSTRACT FROM AUTHOR]

We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) onboard the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to June 2019 with a global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1200 million individually processed observations. The retrievals are most sensitivity to variations of {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but also for higher latitudes there is a considerable amount of reliable data. Exemplary time-series over the Tropical Atlantic and West Africa are chosen to illustrates the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studies. Finally, the dataset is referenced with the DOI 10.35097/415 (Diekmann et al., 2021). [ABSTRACT FROM AUTHOR]