A consensus estimate for the ice thickness distribution of all glaciers on Earth

Knowledge of the ice thickness distribution of the world’s glaciers is a fundamental prerequisite for a range of studies. Projections of future glacier change, estimates of the available freshwater resources or assessments of potential sea-level rise all need glacier ice thickness to be accurately constrained. Previous estimates of global glacier volumes are mostly based on scaling relations between glacier area and volume, and only one study provides global-scale information on the ice thickness distribution of individual glaciers. Here we use an ensemble of up to five models to provide a consensus estimate for the ice thickness distribution of all the about 215,000 glaciers outside the Greenland and Antarctic ice sheets. The models use principles of ice flow dynamics to invert for ice thickness from surface characteristics. We find a total volume of 158 ± 41 × 103 km3, which is equivalent to 0.32 ± 0.08 m of sea-level change when the fraction of ice located below present-day sea level (roughly 15%) is subtracted. Our results indicate that High Mountain Asia hosts about 27% less glacier ice than previously suggested, and imply that the timing by which the region is expected to lose half of its present-day glacier area has to be moved forward by about one decade

Patients with chronic mucocutaneous candidiasis exhibit reduced production of Th17-associated cytokines IL-17 and IL-22

Chronic mucocutaneous candidiasis (CMC) constitutes a selective inability to clear infection with the yeast Candida, resulting in persistent debilitating inflammation of skin, nails, and mucous membranes. The underlying defect is unknown. Only recently, IL-17-producing T cells have been reported to be involved in clearing Candida infections. In order to characterize T cellular immune response to Candida, we analyzed T-cell cytokine secretion to Candida antigen and mitogenic stimuli in CMC patients, immunocompetent patients suffering from acute Candida infection, and healthy volunteers. Peripheral blood mononuclear cells (PBMCs) from CMC patients produced significantly lower amounts of IL-17 and IL-22 mRNA and protein when stimulated with Candida albicans or mitogen in vitro compared with that in matched healthy individuals. Additionally, PBMCs from immunocompetent Candida-infected patients secreted more IL-17 and IL-22 than those of both CMC patients and healthy, non-infected controls. Flow cytometry revealed a decreased number of CCR6+ IL-17-producing T cells in CMC patients, whereas the amount of CCR6+/CCR4+ cells was not altered. Levels of differentiating cytokines for human Th17 cells, IL-1β and IL-6, tended to be higher in CMC patients. The inability to clear C. albicans in CMC patients could be due to a defect in the immune response of IL-17-producing T cells

Cyanoborates: Syntheses, Ionic Liquids and coordination compounds and the chemistry of the boron-centred nucleophile B(CN)3_32^2−^-

Diese Arbeit beschäftigt sich mit der Synthese, Reaktivität und den physikalischen Eigenschaften verschiedener Cyanoborate. Es gelang die optimierte Synthese des Tricyanofluoroborates M[BF(CN)3] (M = Na, K) mittels Lewis-Säure-Katalyse. Aus diesem Borat wurde mittels Reduktion das Bor-zentrierte Nukleophil B(CN)3 2− hergestellt, welches ebenfalls über die äußerst ungewöhnliche Depronotierung des [BH(CN)3]− -Anions zugänglich ist. Das B(CN)3 2− -Dianion wurde erfolgreich mit diversen Elektrophilen wie z.B. Alkylhalogeniden, CO2, CN+-Quellen sowie per- und teilfluorierten Aromaten umgesetzt. Darüber hinaus ergibt die Synthese mit Tricyanohalogenoborat-Anionen das ungewöhnlich stabile gekoppelte Diborat-Dianion [B2(CN)6]2−, welches über einen SN2-Mechanismus entsteht und eine elektronenpräzise B-B-Bindung aufweist. Ferner wurden Ionische Flüssigkeiten mit Perfluoraklylcyanoboraten hergestellt und die physikalischen Parameter systematisch und ausführlich untersucht.In this work the syntheses, reactivity and physical properties of different cyanoborates are presented. The synthesis of the tricyanofluoroborates M[BF(CN)3] (M = Na, K) was optimized via a Lewis-acid-catalysis. Reducing this anion resulted in the formation of the boron-centered nucleophile B(CN)3 2−, which is accessible by the highly unusual deprotonation of [BH(CN)3]−, too. The B(CN)3 2− -dianion was successfully treated with various electrophiles such as alkylhalides, CO2, CN+ -sources as well as partly and perfluorinated arenes. Moreover, the synthesis with halidotricyanoborate anions provide the unusually stable coupled diborat-dianion [B2 (CN)6]2−, which is formed via a SN2-mechanismusm and exhibits an electron-precise B-B-bond. Furthermore, Ionic Liquids based on perlfuorocyanoborates were synthesized and their physical properties were studied systematically in detail

Near-Real-Time Monitoring, Modelling, and Data Assimilation of Glacier Mass Balance

Glaciers are among the most prominent indicators of climate change, since their behavior is directly linked to climatic variables such as temperature, precipitation, and solar radiation. Under the longterm trend of shrinkage due to recent and future climate warming, near-real-time glacier mass balance information and its prediction play a particular role: on scales of days to months, glaciers fulfill important functions concerning water supply, planning for hydroelectricity production, ecology, and mountain tourism. Due to this importance, near-real-time glacier mass balance information is also of interest to the broad media. However, supplying such near-real-time information, for example on glacier mass balance, is not simple. This is mainly for two reasons: first, acquiring up-to-date glacier observations comes with a high cost, because glaciers are often located in remote areas and a considerable amount of time and humanpower is required to access and observe them in situ. Second, there is the uncertainty that affects glacier mass balance models, which are often justified by physics, but still parametrized by statistical relations between mass change and meteorological variables. As a consequence of sparse and uncertain observations, model parameters are often not uniquely identifiable, or their spatial and temporal variability cannot be accounted for. A lack of observations thus associates the calculation of near-real-time glacier mass balance with high uncertainties. This thesis aims at treating the issue of uncertain observations and models by making use of available observations and their respective uncertainties. It does so by presenting Cryospheric Monitoring and Prediction Online (CRAMPON), a Bayesian framework that allows determining near-real-time glacier mass balances in an optimal fashion, i.e. by using all available direct and indirect mass balance information and by minimizing the uncertainties. Bayesian methods are widely used in fields like meteorology, hydrology, snow sciences, and oceanography, but applications in glaciology are sparse to date. CRAMPON builds upon a Sequential Importance Resampling (SIR) scheme, also known as Particle Filtering, which comprises three steps: first, a prior estimate of a glacier’s mass balance on a particular day is given through forward integration of a mass balance model ensemble. The forward integration is driven by gridded meteorological data, and accounts for the corresponding uncertainty. Second, this prior estimate is updated with observations. This is done by using various measurements, including daily point mass balance observations from cameras, as well as surface albedo and transient snow lines derived from optical satellites. The combination of observations ensures that both temporally frequent point observations and less frequent but spatially comprehensive observations complement each other. This second step results in a so-called posterior mass balance estimate. Third, a resampling technique is applied to ensure temporal stability of the particle filter. Here, CRAMPON focuses on (1) making the resampling technique compatible with an ensemble modeling approach, and (2) using the filter to estimate model parameter distributions. This statistical data assimilation approach ensures that, at any instance, the framework delivers an optimal estimate of the current mass balance of a glacier, given all observations and respecting all observation uncertainties. Special focus is put on handling variables in a probabilistic fashion. This allows calculating uncertainties for the near-real-time glacier mass balance estimates during model runtime. The daily estimates and their uncertainties are then used for predicting the glacier mass balances into the near future. This is achieved by using Consortium for Small-Scale Modelling (COSMO) numerical weather predictions with lead times of up to five days, and European Centre for Medium-Range Weather Forecasts (ECMWF) extended-range forecasts for lead times of up to one month. Analyses of the results show that (1) CRAMPON delivers up to 95% more accurate results than conventional approaches that model mass balance deterministically and with constant parameters, (2) the produced mass balances are in line with seasonal, glacier-wide mass balances obtained from interpolation of in situ observations, and (3) the combination of point mass balances and satellite information is helpful to reduce the uncertainty. The thesis also explores other options for improving near-real-time glacier mass balances. In particular, the possibility of (i) extrapolating glacier mass balance signals in space to otherwise unobserved glaciers, (ii) using short-term geodetic volume changes, (iii) predicting model parameters through machine learning, (iv) acquiring glacier melt observations with Unmanned Aerial Vehicles (UAVs), and (v) using Bayesian calibration for cases where model parameters cannot be uniquely identified, are tested and discussed. The daily, near-real-time estimates calculated by CRAMPON are provided at the resolution of individual glaciers, the results being summarized on an interactive web site.Während sich die Gletscher auf lange Sicht gesehen zurückziehen, spielen auch Nah-Echtzeitanalysen und -prognosen von Gletschermassenbilanzen eine wesentliche Rolle: Gletscher erfüllen wichtige Funktionen im Zusammenhang mit Wasserversorgung, Wasserressourcenplanung für die Stromproduktion, Ökologie und Bergtourismus. Weiter zählen Gletscher zu den wichtigsten Indikatoren des Klimawandels, denn ihre Massenbilanz ist direkt mit klimatischen Variablen wie Temperatur, Niederschlage und solarer Einstrahlung verknüpft. Obwohl Nah-Echtzeitanalysen daher auch auf ein breites Medieninteresse stoßen, gestaltet sich die Berechnung von Nah-Echtzeitanalysen für Gletscher jedoch aus hauptsächlich zwei Gründen als schwierig: Zunächst ist zu sagen, dass die Beschaffung von Gletscher-Nahechtzeitbeobachtungen oftmals beschwerlich ist, da Gletscher meist in abgelegenen Regionen liegen. Der Zugang zu Gletschern für Beobachtungen vor Ort erfordert daher viel Zeit und Arbeitskraft. Darüber hinaus sind glaziologische Massenbilanzmodelle unsicher, insofern als diese zwar physikalisch gerechtfertigt sind, aber durch statistische Beziehungen zwischen Massenänderung und meteorologischen Variablen parametrisiert sind. Als eine Folge von seltenen und unsicheren Beobachtungen können Modellparameter oft nicht eindeutig identifiziert werden, und ihre räumliche und zeitliche Variabilität kann nicht hinreichend aufgelöst werden. Diese Doktorarbeit, die das Projekt mit dem Akronym Cryospheric Monitoring and Prediction Online (CRAMPON) (zu deutsch: Kryosphärische Überwachung und Vorhersagen im Internet) vorstellt, zielt darauf ab die Schwierigkeiten im Zusammenhang mit unsicheren Beobachtungen und Modellen zu adressieren. CRAMPON ist ein Bayesianisches Modellierungsprojekt, welches es erlaubt Nahechtzeit-Massenbilanzen auf eine “optimale” Art und Weise zu berechnen (mit allen verfügbaren direkten und indirekten Massenbilanzinformationen) und dabei Unsicherheiten zu minimieren. Der Grad der Optimaltität ist dabei durch eine Bayesianische Herangehensweise gegeben, durch welche Unsicherheiten minimiert werden. Bayesianische Methoden haben sich im Bereich der Meteorologie, Hydrologie, Schneewissenschaften und Ozeanographie zu Standardmethoden entwickelt, sind aber im Bereich der Glaziologie kaum anzutreffen. Als konkrete Implementierung einer Bayesianischen Methode baut diese Doktorarbeit daher auf der so genannten Sequential Importance Resampling (SIR)-Methode (zu deutsch: Sequentielle Stichprobenentnahme nach Wichtigkeit) auf, die auch als Partikelfilter bezeichnet wird. Der Partikelfilter umfasst generell drei Schritte, die hier wie folgt implementiert werden: Zunächst wird im Vorhersageschritt eine a priori-Schätzung der Massenbilanz eines Gletscher an einem gewissen Tag durch Vorwärtsintegration eines Massenbilanzmodellensembles berechnet. Dieses Ensemble wird durch meteorologische Gitterdaten angetrieben, deren Unsicherheit durch den Datenversorger bestimmt wurde. Um diese a priori-Schätzung mit Beobachtungen zu verbessern, werden in einem zweiten Schritt Beobachtungen mit einbezogen. Diese sind zum Beispiel tägliche Punktbeoachtungen von Massenbilanz aus Kamerabeobachtungen, sowie Albedo- und Schneelinienbeobachtungen aus optischen Fernerkundungsdaten. CRAMPON setzt bei letzteren Beobachtungen einen Schwerpunkt darauf Wolken und Wolkenschatten in den Satellitenbildern richtig zu klassifizieren und auszuschließen. Die Kombination aus in situ- und Fernerkundungsbeobachtungen ermöglicht, dass sowohl zeitlich häufige Punktbeobachtungen als auch weniger häufige, aber dafür flächige Aufnahmen sich gegenseitig ergänzen. Auf diese Weise wird erhält man eine a posteriori-Schätzung der Nahechtzeit-Gletschermassenbilanz. Im dritten Schritt wird ein Resampling (Stichprobenwiederholung) angewendet, was die so genannte Filterdegeneration verhindern soll, d.h. eine zeitliche Instabilität des Filters. CRAMPON setzt hier besonderen Wert darauf (1) dieses Resampling mit einer Ensemblemodellierung kompatibel zu halten, und (2) den Partikelfilter dazu zu benutzen neben der Massenbilanz auch Massenbilanzmodellparameter zu schätzen. Ein spezieller Fokus ist dabei darauf gerichtet Variablen probabilistisch zu behandeln. Diese probabilistische Herangehensweise erlaubt eine flexible und echtzeittreue Berechnung der Unsicherheiten von Nah-Echtzeitmassenbilanzen. Diese täglichen Schätzungen und ihre Unsicherheit werden im Weiteren auch aus Ausgangsbedingungen für eine Massenbilanzvorhersage in die Zukunft benutzt. Dazu werden die Massenbilanzmodelle sowohl mit Vorhersagen des Consortium for Small-Scale Modelling (COSMO) (zu deutsch: Konsortium für kleinskalige Modellierung) mit einem Vorhersagezeitraum von bis zu fünf Tagen als auch mit Monatsvorhersagen des European Centre for Medium-Range Weather Forecasts (ECMWF) (zu deutsch: Europäisches Zentrum für mittelfristige Wettervorhersagen) angetrieben. In Anwendungsstudien kann belegt werden, dass (1) CRAMPON bis zu 95% bessere Massenbilanzwerte berechnen kann als konventionelle, deterministische Berechnungsmethoden mit konstanten Parametern, (2) die produzierten Massenbilanzen mit saisonalen, gletscherweit interpolierten Massenbilanzen aus in situ Beobachtungen übereinstimmen, und (3) es einen Mehrwert gibt Punktbeobachtungen von Gletschermassenbilanzen und Satelliteninformation zu verbinden, um eine Reduktion der Gesamtunsicherheit zu erreichen. Diese Doktorarbeit untersucht auch inwiefern man Nahechtzeit-Gletschermassenbilanzen sowie deren Beobachtungen einfacher beschaffen kann. Dies geschieht zum Beispiel durch (i) Extrapolation von Gletschermassenbilanzem im Raum, (ii) die Modellierung von Schnee- und Firndichten zur besseren Bestimmung von Volume-zu-Masse Umrechnungen im Zusammenhang mit kurzzeitlichen, geodätischen Volumenänderungen, (iii) die Vorhersage von Massenbilanz-Modellparametern im Raum durch maschinelles Lernen, (iv) die Möglichkeit Gletscherbeobachtungen mit autonomen Drohnen zu beschaffen, sowie (v) Bayesianische Ansätze zu verwenden, wenn in Kalibrierungsvorgängen Modellparameter nicht eindeutig identifiziert werden können. Die täglichen Nahechtzeit-Massenbilanzen aus CRAMPON werden für individuelle Gletscher bereitgestellt, und eine Karte erlaubt es sich einen Überblick über den Status aller berechneten Gletscher zu verschaffen. Um die Ergebnisse von CRAMPON besser zugänglich zu machen, werden sie auf einer Webseite präsentiert

Borylation of fluorinated arenes using the boron centred nucleophile B(CN)3_{3}2−^{2-} - a unique entry to aryltricyanoborates

The potassium salt of the boron-centred nucleophile B(CN)$_{3}$$^{2-}$(1) readily reacts with perfluorinated arenes, such as hexafluorobenzene, decafluorobiphenyl, octafluoronaphthalene and pentafluoropyridine, which results in KF and the K$^{+}$ salts of the respective borate anions with one {B(CN)$_{3}$} unit bonded to the (hetero)arene. An excess of K$_{2}$1 leads to the successive reaction of two or, in the case of perfluoropyridine, even three C–F moieties and the formation of di- and trianions, respectively. Moreover, all of the 11 partially fluorinated benzene derivatives, C$_{6}$F$_{6-n}$H$_{n}$ (n = 1–5), generally react with K$_{2}$1 to give new tricyano(phenyl)borate anions with high chemo- and regioselectivity. A decreasing number of fluorine substituents on benzene results in a decrease in the reaction rate. In the cases of partially fluorinated benzenes, the addition of LiCl is advantageous or even necessary to facilitate the reaction. Also, pentafluorobenzenes R–C$_{6}$F$_{5}$ (R = –CN, –OMe, –Me, or –CF$_{3}$) react via C–F/C–B exchange that mostly occurs in the para position and to a lesser extent in the meta or ortho positions. Most of the reactions proceed via an S$_{N}$Ar mechanism. The reaction of 1,4-F$_{2}$C$_{6}$H$_{4}$ with K$_{2}$1 shows that an aryne mechanism has to be considered in some cases as well. In summary, a wealth of new stable tricyano(aryl)borates have been synthesised and fully characterized using multi-NMR spectroscopy and most of them were characterised using single-crystal X-ray diffraction

Worldwide version-controlled database of glacier thickness observations

. Although worldwide inventories of glacier area have been coordinated internationally for several decades, a similar effort for glacier ice thicknesses was only initiated in 2013. Here, we present the third version of the Glacier Thickness Database (GlaThiDa v3), which includes 3 854 279 thickness measurements distributed over roughly 3000 glaciers worldwide. Overall, 14 % of global glacier area is now within 1 km of a thickness measurement (located on the same glacier) – a significant improvement over GlaThiDa v2, which covered only 6 % of global glacier area and only 1100 glaciers. Improvements in measurement coverage increase the robustness of numerical interpolations and model extrapolations, resulting in better estimates of regional to global glacier volumes and their potential contributions to sea-level rise. In this paper, we summarize the sources and compilation of glacier thickness data and the spatial and temporal coverage of the resulting database. In addition, we detail our use of open-source metadata formats and software tools to describe the data, validate the data format and content against this metadata description, and track changes to the data following modern data management best practices. Archived versions of GlaThiDa are available from the World Glacier Monitoring Service (e.g., v3.1.0, from which this paper was generated: https://doi.org/10.5904/wgms-glathida-2020-10; GlaThiDa Consortium, 2020), while the development version is available on GitLab (https://gitlab.com/wgms/glathida, last access: 9 November 2020)

European heat waves 2022: contribution to extreme glacier melt in Switzerland inferred from automated ablation readings

Accelerating glacier melt rates were observed during the last decades. Substantial ice loss occurs particularly during heat waves that are expected to intensify in the future. Because measuring and modelling glacier mass balance on a daily scale remains challenging, short-term mass balance variations, including extreme melt events, are poorly captured. Here, we present a novel approach based on computer-vision techniques for automatically determining daily mass balance variations at the local scale. The approach is based on the automated recognition of colour-taped ablation stakes from camera images and is tested and validated at six stations installed on three Alpine glaciers during the summers of 2019-2022. Our approach produces daily mass balance with an uncertainty of ±0.81 cm w.e. d-1, which is about half of the accuracy obtained from visual readouts. The automatically retrieved daily mass balances at the six sites were compared to average daily mass balances over the last decade derived from seasonal in situ observations to detect and assess extreme melt events. This allows analysing the impact that the summer heat waves which occurred in 2022 had on glacier melt. Our results indicate 23 d with extreme melt, showing a strong correspondence between the heat wave periods and extreme melt events. The combination of below-average winter snowfall and a suite of summer heat waves led to unprecedented glacier mass loss. The Switzerland-wide glacier storage change during the 25 d of heat waves in 2022 is estimated as 1.27 ± 0.10 km3 of water, corresponding to 35 % of the overall glacier mass loss during that summer. The same 25 d of heat waves caused a glacier mass loss that corresponds to 56 % of the average mass loss experienced over the entire melt season during the summers 2010-2020, demonstrating the relevance of heat waves for seasonal melt.ISSN:1994-0416ISSN:1994-042

Assimilating near-real-time mass balance stake readings into a model ensemble using a particle filter

Short-term glacier variations can be important for water supplies or hydropower production, and glaciers are important indicators of climate change. This is why the interest in near-real-time mass balance nowcasting is considerable. Here, we address this interest and provide an evaluation of continuous observations of point mass balance based on online cameras transmitting images every 20 min. The cameras were installed on three Swiss glaciers during summer 2019, provided 352 near-real-time point mass balances in total, and revealed melt rates of up to 0.12 m water equivalent per day (mw.e.d−1) and of more than 5 mw.e. in 81 d. By means of a particle filter, these observations are assimilated into an ensemble of three TI (temperature index) and one simplified energy-balance mass balance models. State augmentation with model parameters is used to assign temporally varying weights to individual models. We analyze model performance over the observation period and find that the probability for a given model to be preferred by our procedure is 39 % for an enhanced TI model, 24 % for a simple TI model, 23 %, for a simplified energy balance model, and 14 % for a model employing both air temperature and potential solar irradiation. When compared to reference forecasts produced with both mean model parameters and parameters tuned on single mass balance observations, the particle filter performs about equally well on the daily scale but outperforms predictions of cumulative mass balance by 95 %–96 %. A leave-one-out cross-validation on the individual glaciers shows that the particle filter is also able to reproduce point observations at locations not used for model calibration. Indeed, the predicted mass balances is always within 9 % of the observations. A comparison with glacier-wide annual mass balances involving additional measurements distributed over the entire glacier mostly shows very good agreement, with deviations of 0.02, 0.07, and 0.24 mw.e.ISSN:1994-0416ISSN:1994-042

Dynamic Disorder and Electronic Structures of Electron-Precise Dianionic Diboranes: Insights from Solid-State Multinuclear Magnetic Resonance Spectroscopy

The <i>J</i>(¹¹B,¹¹B) coupling constants of various salts of the electron-precise hexacyanodiborane(6) dianion, [B₂(CN)₆]^2–, were obtained using ¹¹B double-quantum-filtered (DQF) <i>J</i>-resolved solid-state nuclear magnetic resonance (SSNMR) spectroscopy. Our results show that the magnitude of the DQF <i>J</i> splitting is influenced by both the crystallographic symmetry of the system and the presence of dynamics. The splittings are amplified by a factor of 3 as compared to the corresponding theoretical <i>J</i> coupling constants for cases where (1) there is an absence of dynamics but the boron pairs are crystallographically equivalent or (2) the boron pairs are crystallographically inequivalent but are rendered magnetically equivalent on the time scale of the experiment due to dynamic disorder, which was identified by ¹¹B and ¹³C SSNMR experiments. Consequently, molecular motions need to be taken into consideration when interpreting the results of DQF <i>J</i>-resolved experiments, and conversely, these experiments may be used to identify dynamic disorder. Variable-temperature NMR data support the notion of three different motional processes with correlation times ranging from 10² to 10⁶ s^–1 over the temperature range of 248–306 K. When molecular motion and crystallographic symmetry are both accounted for, the <i>J</i>(¹¹B,¹¹B) coupling constants for various [B₂(CN)₆]^2– salts were measured to range from 29.4 to 35.8 Hz, and their electronic origins were determined using natural localized molecular orbital and natural bond orbital analyses. The coupling constants were found to strongly correlate to the hybridization states of the boron orbitals that form the B–B bonds and to the strength of the B–B bonds. This study provides a novel tool to study dynamics in ordered and disordered solids and provides new perspectives on electron-precise dianionic diboranes featuring two-center–two-electron bonds in the context of related compounds featuring multiply and singly bonded boron spin pairs