Analysis of stable water isotopes in tropospheric moisture during the West African Monsoon

Der westafrikanische Monsun ist einer der markantesten Bestandteile des Klimas über Westafrika. Er ist die Hauptquelle für Regen über der semi-ariden Sahelzone und hat damit einen entscheidenden Einfluss auf die Sozioökonomie dieser Regionen, die großteils auf Landwirtschaft angewiesen sind. Allerdings stellt das komplexe Zusammenspiel der großräumigen Zirkulation mit kleinskaligen Wolken- und Regenprozessen eine große Herausforderung dar, die atmosphärischen Zweige des Wasserkreislaufs während des Monsuns verlässlich zu quantifizieren. Der Fokus der zugrundeliegenden Arbeit liegt daher auf der Analyse von troposphärischem Wasserdampf und seiner Einflussfaktoren während des westafrikanischen Monsuns. Für diesen Zweck werden Verteilungen der Wasserdampfisotopologe H$_2$O and HDO (standardmäßig als $\delta$D angegeben) gemeinsam betrachtet, da diese fundamentale Rückschlüsse über Feuchtepfade und -prozesse ermöglichen. In einem dreistufigen Konzept nutzt diese Arbeit beobachtungs- und modellgestützte {H$_2$O, $\delta$D} Verteilungen zur Analyse von Effekten von Transport- und Feuchteprozessen im Zusammenhang mit dem Monsun. Im ersten Schritt wird ein neuartiger Datensatz von troposphärischen {H$_2$O, $\delta$D}-Paaren auf der Basis von globalen and täglichen Fernerkundungsdaten des Satellitensensors Metop/IASI erzeugt. Um Isotopendaten aus Modellanalysen mit diesem neuen Datensatz vergleichbar zu machen, wird ein sogenannter Retrieval Simulator entwickelt. Der zweite Schritt zielt auf eine modellgestützte Prozessanalyse unter Verwendung von Luftmassen-Trajektorien, um eine aussagekräftige Interpretation von {H$_2$O, $\delta$D}-Verteilungen zu ermöglichen. Darauf aufbauend wird im dritten Schritt eine umfangreiche und mehrskalige Analyse der IASI {H$_2$O, $\delta$D}-Verteilungen über der Sahelzone mit Fokus auf den Monsun durchgeführt. Dies beinhaltet Simulationen mit den numerischen Wettermodellen ICON-ART$_\mathrm{iso}$ und COSMO$_\mathrm{iso}$ sowie Niederschlagsbeobachtungen von der NASA (GPM IMERG). Die Synthese dieser Datensätze und Methoden ermöglicht, charakteristische {H$_2$O, $\delta$D}-Signale über der Sahelzone zu identifizieren und diese auf eindeutige Effekte der Luftmassenmischung und mikrophysikalischen Prozesse wie Kondensation, Verdunstung und Äquilibrierung von Regentropfen zurückzuführen. Insgesamt verdeutlicht diese Studie das Potential von {H$_2$O, $\delta$D}-Verteilungen von IASI zusammen mit hoch aufgelösten Modellrechnungen sowie detaillierten Prozessanalysen zur Untersuchung des troposphärischen Feuchtebudgets. Damit unterstreicht diese Arbeit den grundsätzlichen Wert der Wasserdampfisotopologie für die Analyse des hydrologischen Kreislaufs

Nonevaporable getter-MEMS for generating UHV conditions in small volumina

The industrial use of quantum sensors requires further miniaturization of the experimental peripherals, i.e., the high vacuum chamber, laser technology, and control electronics. A central part of the high vacuum chamber is the maintenance of vacuum conditions. For this purpose, a prototype of a compact, i.e., miniaturized, ultrahigh vacuum pump in the form of a nonevaporable getter (NEG) pump at a wafer level (MEMS), is developed within the scope of this work. With regard to the basic conditions of the functionality of the NEG, a miniaturized heating plate with temperature sensors is analytically and numerically developed, constructed, and characterized in an ultrahigh vacuum test stand. This is followed by the integration of the NEG into the existing system, which, in connection with the characterization of material-specific parameters, enables a first correlation of heat input and pumping power. Thus, performance data of the getter-MEMS under high-vacuum confinement confirm its usability for quantum sensors. In addition, optimization potentials are shown with regard to all partial aspects of the MEMS

Potential of Mid-tropospheric Water Vapor Isotopes to Improve Large-Scale Circulation and Weather Predictability

Recent satellite techniques have uncovered detailed tropospheric water vapor isotope patterns on a daily basis, yet the significance of water isotopes on weather forecasting has remained largely unknown. Here, we perform a proof‐of‐concept observing system simulation experiment to show that mid‐tropospheric water isotopes observed by the Infrared Atmospheric Sounding Interferometer (IASI) can substantially improve weather forecasts through non‐local impacts on the convective heating structure and large‐scale circulation. Assimilating IASI isotopes can improve wind, humidity, and temperature fields by more than 10% at mid‐troposphere compared to only assimilating conventional non‐isotopic observations. These improvements are about two‐thirds of assimilating simultaneous IASI water vapor observations. The improvements can be attributed more to thermodynamic (phase change) effects than dynamic (transport) effects of water isotopes. Furthermore, isotopic observations produce additional 3%–4% improvements to the fields constrained by the conventional observations and simultaneous IASI water vapor observations, demonstrating the unique characteristics of water isotopes. Plain Language Summary Accurate weather forecasting has tremendous socio‐economic benefits by saving lives from natural hazards and affecting numerous sectors including water resources, energy, and agriculture. Although recent satellite techniques have enabled observing detailed water isotope patterns (e.g., HDΟ and Η$_{2}$$^{18}$O) in the atmosphere, it has not been incorporated in operational weather forecasting. Here, we show that water isotopes can substantially improve weather forecasts by improving the heating structure and large‐scale circulation. Satellite‐observed isotopes can improve wind, humidity, and temperature fields up to 3%–4% compared to utilizing conventional non‐isotopic observations and concurrent water vapor observations by the same satellite. We anticipate that our results will facilitate further modeling developments in isotopic processes and benefit the societal sectors by improving operational weather forecasting

The Influence of Convective Aggregation on the Stable Isotopic Composition of Water Vapor

Remote sensing datasets of water vapor isotopic composition are used along with objective measures of convective aggregation to better understand the impact of convective aggregation on the atmospheric hydrologic cycle in the global tropics (30°N to 30°S) for the period 2015–2020. When convection is unaggregated, vertical velocity profiles are top-heavy, mixing ratios increase and water vapor δD decreases as the mean precipitation rate increases, consistent with partial hydrometeor evaporation below anvils into a relatively humid atmospheric column. Aggregated convection is associated with bottom-heavy vertical velocity profiles and a positive correlation between mixing ratio and δD, a result that is consistent with isotopic enrichment from detrainment of shallow convection near the observation level. Intermediate degrees of aggregation do not display significant variation in δD with mixing ratio or precipitation rate. Convective aggregation provides a useful paradigm for understanding the relationships between mixing ratio and isotopic composition across a range of convective settings. The results presented here may have utility for a variety of applications including the interpretation of paleoclimate archives and the evaluation of numerical simulations of convection

Disentangling different moisture transport pathways over the eastern subtropical North Atlantic using multi-platform isotope observations and high-resolution numerical modelling

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, 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-based in situ measurements, ground-based and space-based remote sensing observations) from a field campaign in summer 2013 shows that COSMO$_{iso}$ can reproduce the observed variability of stable water vapour isotopes on time scales of hours to days, and thus allows studying the mechanisms that control the subtropical free-tropospheric humidity. Changes of isotopic signals along backward trajectories from the Canary Islands region reveal the physical processes behind the short-term isotope variability. We identify four predominant moisture transport pathways of mid-tropospheric air, each with distinct isotopic signatures: (1) Air parcels originating from the convective boundary layer of the Saharan heat low (SHL). These are characterised by a homogenous 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. (2) 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. (3) 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. (4) 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 to a large degree the observed high variability in humidity and δD on synoptic time scales. 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 time scales of hours to days in contrasting atmospheric conditions over the eastern subtropical North Atlantic

The global and multi-annual MUSICA IASI {H2O, δD} pair dataset

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) 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 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.This research has been supported by the Deutsche Forschungsgemeinschaft (grant no. 290612604, project MOTIV and grant no. 416767181, project TEDDY), the European Research Council, FP7 Ideas: European Research Council (MUSICA, grant no. 256961), the Bundesministerium für Bildung und Forschung (ForHLR supercomputer), the Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg (ForHLR supercomputer), and the Ministerio de Economía y Competitividad (grant no. CGL2016-80688-P, project INMENSE)

The MUSICA IASI {H2_{2}O, δD} pair product

We present a global and multi-annual space-borne dataset of tropospheric {H$_{2}$O, 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 H$_{2}$O 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 H$_{2}$O and δD. Here, this standard MUSICA method for deriving {H$_{2}$O, 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 {H$_{2}$O, 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 {H$_{2}$O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H$_{2}$O, 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 {H$_{2}$O, δD} pair data for atmospheric moisture pathway studiess. Finally, the dataset is referenced with the DOI 10.35097/415 (Diekmann et al., 2021)

Quantifying CH4_{4} emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method

In this study, we use satellite-based total column-averaged dry-air mole fraction of CH4 (XCH4) from the TROPOspheric Monitoring Instrument (TROPOMI) and tropospheric XCH$_{4}$ (TXCH$_{4}$) from the Infrared Atmospheric Sounding Interferometer (IASI). In addition, the high-resolution model forecasts, XCH$_{4}$ and TXCH$_{4}$, from the Copernicus Atmosphere Monitoring Service (CAMS) are used to estimate the CH$_{4}$ emission rate averaged over 3 years (November 2017–December 2020) in the USCB region (49.3–50.8$^\circ$ N and 18–20$^\circ$ E). The wind-assigned anomaly method is first validated using the CAMS forecast data (XCH$_{4}$ and TXCH$_{4}$), showing a good agreement with the CAMS GLOBal ANThropogenic emission (CAMS-GLOB-ANT) inventory. It indicates that the wind-assigned method works well. This wind-assigned method is further applied to the TROPOMI XCH$_{4}$ and TROPOMI + IASI TXCH$_{4}$ by using the Carbon dioxide and Methane (CoMet) inventory derived for the year 2018. The calculated averaged total CH$_{4}$ emissions over the USCB region is about 496 kt yr$^{-1}$ (5.9×10$^{26}$ molec. s$^{-1}$) for TROPOMI XCH$_{4}$ and 437 kt yr$^{-1}$ (5.2×10$^{26}$ molec. s$^{-1}$) for TROPOMI + IASI TXCH$_{4}$. These values are very close to the ones given in the E-PRTR inventory (448 kt yr$^{-1}$) and the ones in the CoMet inventory (555 kt yr$^{-1}$), and are thus in agreement with these inventories. The similar estimates of XCH$_{4}$ and TXCH$_{4}$ also imply that for a strong source, the dynamically induced variations of the CH$_{4}$ mixing ratio in the upper troposphere and lower stratosphere region are of secondary importance. Uncertainties from different error sources (background removal and noise in the data, vertical wind shear, wind field segmentation, and angle of the emission cone) are approximately 14.8 % for TROPOMI XCH$_{4}$ and 11.4 % for TROPOMI + IASI TXCH$_{4}$. These results suggest that our wind-assigned method is quite robust and might also serve as a simple method to estimate CH$_{4}$ or CO$_{2}$ emissions for other regions