bluuebunny/crossref_metadata_2025 huggingface dataset:
In-situ, U-Pb dating of titanite in phonolitic dykes from the Dolomites area (Southern Alps, Italy): new insights on the timing of the Middle Triassic magmatism
Authors: Coltorti Massimo , Nardini Nicolò , Casetta Federico , Tavazzani Lorenzo , Peres Stefano , Ntaflos Theodoros , Dellantonio Elio
Published: February 2023

Due to the complex geodynamic framework and the excellent state of preservation of the stratigraphic relationships towards the host metamorphic and sedimentary rocks, the Permo-Triassic magmatic sequences of the Southern Alps (Italy) are intensely studied. Throughout the Southalpine domain, the main peaks of the volcano-plutonic activity are both pre- and post-dated by the emplacement of small volume of magmas with variable chemical affinity. These magmas, preserved as dykes and veins intruded into the plutonic bodies and/or the overlying volcanites, are powerful tools for tracing the evolution of the magma source and reconstructing the temporal evolution of the magmatic episode. Here, we present a detailed geochemical and geochronological study of phonolitic dykes (SiO2 from 56.8 to 57.8 wt.%; Na2O + K2O from 11.1 to 15.3 wt.%) cropping out near Predazzo (Southern Alps; Italy) and intruded into the basaltic to trachyandesitic Middle Triassic lavas. The phonolites are mostly aphyric with a porphyricity index <10%. The main mineral phases are concentric-zoned clinopyroxene, ranging in composition from diopside-hedenbergite, to aegirine (Wo13-51; En2-29; Fs20-85), K-feldspar and rare sodalite. Accessory phases are titanite, apatite and magnetite embedded in a aphyric matrix. Titanite has a highly variable U-Th concentration (U from 24 to 478 ppm and Th from 170 to 4328 ppm) and is characterized by a chondrite-normalized REE pattern with a convex-upward shape (La/YbN from 18.9 to 41.5) with enrichment in LREE and depletion in HREE. Thermometry through Zr-in-Titanite calculations (Hayden et al., 2008) indicate crystallisation temperatures between 860.3 and 942.8 ± 57 °C. In-situ, U-Pb dating on titanite phenocrysts performed by laser ablation-inductively coupled-mass spectrometry (LA-ICP-MS) shows that the age of phonolite dykes is comprised between 240.4 ± 3.2 Ma and 242.0 ± 3.6 Ma, partially overlapping with the emplacement of the Middle-Triassic plutonic bodies of the Dolomites (238.190 ± 0.050 - 238.075 ± 0.087; Storck et al. 2019).These results provide new insights into the timing of the Middle Triassic magmatic event in the Southern Alps, fostering the debates about the temporal and chemical evolution of the magmatism in between the Variscan orogeny and the opening of the Alpine Tethys.References:Hayden, L. A., Watson, E. B., & Wark, D. A. (2008). A thermobarometer for sphene (titanite). Contributions to Mineralogy and Petrology, 155(4), 529-540.Storck, J. C., Brack, P., Wotzlaw, J. F., & Ulmer, P. (2019). Timing and evolution of Middle Triassic magmatism in the Southern Alps (northern Italy). Journal of the Geological Society, 176(2), 253-268.
Automated detection and monitoring of methane super-emitters using satellite data
Authors: Schuit Berend J. , Maasakkers Joannes D. , Bijl Pieter , Mahapatra Gourav , Van den Berg Anne-Wil , Yaakoub Mohamed , Pandey Sudhanshu , Lorente Alba , Borsdorff Tobias , Houweling Sander , Varon Daniel J. , McKeever Jason , Jervis Dylan , Girard Marianne , Irakulis-Loitxate Itziar , Gorroño Javier , Guanter Luis , Cusworth Daniel H. , Aben Ilse
Published: February 2023

A reduction in anthropogenic methane emissions is vital to limit near-term global warming. A small number of so-called super-emitters is responsible for a disproportionally large fraction of total methane emissions. Since late 2017, the TROPOspheric Monitoring Instrument (TROPOMI) has been in orbit providing daily global coverage of methane mixing ratios at a resolution of up to 7x5.5 km2, enabling the detection of these super-emitters for the first time at global scale. However, TROPOMI produces millions of observations each day, which together with the complexity of the methane data, makes manual inspection infeasible. We have therefore designed a two-step machine learning approach using a Convolutional Neural Network to detect plume-like structures in the methane data and subsequently apply a Support Vector Classifier to distinguish emission plumes from retrieval artefacts. The models are trained on pre-2021 data, and subsequently applied to all 2021 observations. We detect 2974 plumes in 2021 with a mean estimated source rate of 44 t h-1 and 5-95th percentile range of 8-122 t h-1. These emissions originate from 94 persistent emission clusters and hundreds of transient sources. Based on bottom-up emission inventories, we find that most detected plumes are related to urban areas / landfills (35%), followed by plumes from gas infrastructure (24%), oil infrastructure (21%) and coal mines (20%). For twelve (clusters of) TROPOMI detections, we "tip-and-cue" targeted observations and analysis of high-resolution satellite instruments to identify the exact sources responsible for these plumes. Using the high-resolution observations from GHGSat, PRISMA and Sentinel-2, we detect and analyze both persistent and transient facility-level emissions underlying the TROPOMI detections. We will show observations of emissions from landfills and fossil fuel exploitation facilities, for the latter we find up to ten facilities contributing to one TROPOMI detection. In addition to our examination of 2021, we will show results from applying our automated machine learning pipeline continuously on TROPOMI data from as recently as three days ago. Our automated TROPOMI-based monitoring system in combination with high-resolution satellite data allows for the detection, precise identification and monitoring of these methane super-emitters, which is essential for mitigating their emissions and reaching the goals of the Global Methane Pledge of reducing global anthropogenic methane emissions with 30% by 2030.
Interactive stratospheric aerosol simulations of the Hunga-Tonga aerosol cloud re: stronger than expected observed mid-visible stratospheric AOD
Authors: Mann Graham , Dhomse Sandip , Shallcross Sarah , Bellouin Nicholas , Abraham Luke , Hatcher Rosalyn , Lister Grenville , Taha Ghassan , Baron Alexandre , Duflot Valentin , Lopes Fabio , Landulfo Eduardo
Published: February 2023

In this presentation we present findings from a series of interactive stratospheric aerosol simulations of the Hunga-Tonga volcanic aerosol cloud with the UM-UKCA composition-climate model.   The model experiments apply the same version of the UM-UKCA model published for the Agung, El Chichon and Pinatubo aerosol clouds (Dhomse et al., 2020), those runs aligned with the Historical Eruption SO2 emissions Assessment experiment within ISA-MIP (Timmreck et al., 2018).A consistent feature of interactive stratospheric aerosol simulations of Pinatubo (e.g. Dhomse et al., 2014; Sheng et al., 2015; Mills et al., 2016) is an over-prediction of stratospheric AOD, for a given emission of SO2, requiring a downward-adjustment of emitted SO2 (e.g. Timmreck et al., 2018). Dhomse et al. (2020) indicated models may be missing an important removal process such as heterogeneous uptake of SO2 onto fine ash particles, the process recently demonstrated to have removed ~43% more sulphate than SO2-only simulations for the Kelut aerosol cloud (Zhu et al., 2020).For Hunga-Tonga, any volcanic ash was likely removed within the initial days (Sellitto et al., 2022) and the co-emission of ~100Tg of water vapour (e.g. Carn et al., 2022) has been shown by Zhu et al. (2022) to increase the scattering efficiency of the Hunga-Tonga cloud, both via hygroscopic growth and changes in coagulation, leading to a potential systematic underestimation of stratospheric AOD among interactive stratospheric aerosol models.In a series of UM-UKCA model experiments, we explore the unexpectedly strong optical depth from Hunga-Tonga aerosol via SO2-only simulations, increasing by a factor 2 and 3 the observed 0.4-0.5Tg of SO2 (Carn et al., 2022), and aligning with the protocol from a multi-model Hunga-Tonga aerosol intercomparison co-ordinated by the University of Colorado (Clyne et al., 2021).  The Tonga-MIP protocol emits 0.5Tg of SO2 at 25-30km, within a 6-hour period, with models also enacting a meridional emission spread between 22S and 14S, matching approaches used to account for unresolved early-phase plume transport for Pinatubo (see e.g. Quaglia et al., 2022).We evaluate the strength of the simulated Hunga-Tonga aerosol cloud in these SO2-only emission runs, comparing to the magnitude and timing of maximum strat-AOD observed from OMPS (Taha et al., 2022), and the altitude of the progressing aerosol cloud compared to ground-based lidar measurements from Reunion Island (Baron et al., 2022) and Sao Paulo (Landulfo et al., 2022).
Global Model of Chorus Waves and Electron Lifetime Derived From Juno Observations
Authors: Hao Yixin , Wang Dedong , Shprits Yuri , Menietti John , Drozdov Alexander
Published: February 2023

Gyroresonant wave-particle interactions with whistler mode chorus waves plays a dual role in the precipitating loss and acceleration of energetic electrons in Jovian magnetosphere, which plays fundamental role in both Jovian radiation belt dynamics and auroral emission. Knowledge of the chorus wave power as a function of multi-dimensional spatial location and their spectral distribution are critical inputs for Jovian radiation belt modeling. In this work we present a global, analytical model of the typical Jovian chorus waves (0.1fce<f<0.8fce) based on the measurements made by Juno spacecraft in orbits 1 through 45, with which the whole nightside sector is covered. The radial, latitudal and local time dependence of the chorus wave intensity are derived. Mean-squared and most-probable spectral distributions are also statistically in separated M-shell and magnetic latitude sectors. With the updated chorus wave model, the wave-particle interaction is further quantified in terms of pitch angle, energy and mixed diffusion coefficients. We present an estimation of electron loss rate due to pitch angle scattering and henceforth precipitating to Jovian atmosphere in the format of electron lifetime as a function of energy and M-shell.
GEOBEST2020+ baseline seismic monitoring workflow and network performance evaluation for deep geothermal projects in Switzerland
Authors: Antunes Verónica , Kraft Toni , Roth Philippe , Toledo Tania , Wiemer Stefan
Published: February 2023

Deep geothermal is a clean and renewable source of energy with a high potential for heat and electricity production which can help Switzerland meet its energy and climate objectives. Worldwide, several geothermal projects have been successfully operated for decades. Unfortunately, some projects have also been suspended due to unexpected levels of induced seismicity. Thus, adequate risk management is essential to establish safe and economically viable geothermal projects.In Switzerland, the subsurface is under the sovereignty of the cantonal authorities. Within the GEOBEST2020+ project, the Swiss Seismological Service (SED) supports the cantons in adequately handling the risk of induced seismicity associated with deep geothermal projects. Funded by the Federal Office of Energy (SFOE) in the scope of its SwissEnergy program, the GEOBEST2020+ program aims to provide operator-independent seismological consulting and baseline seismic monitoring services to the cantonal authorities.In this framework, we deploy dedicated seismic networks in the vicinity of the monitored projects. These networks must be sensitive enough to follow the evolution of microseismicity and allow the operators to run traffic-light systems and take action before larger events occur. Before the station installation, we perform a careful site survey analysis, considering the background noise conditions and evaluating the signal-to-noise ratio at each site. To evaluate beforehand the detection sensibility of a seismic network, we estimate the Bayesian Magnitude of Completeness (BMC), optimized for Switzerland. We additionally estimate the theoretical location uncertainties inside the network considering the background noise level at the stations and the network geometry.Here we show the comparison results between our methodology to the ground truths of several years of continuous monitoring data at Lavey-les-Bains, canton of Vaud. We use a combination of three types of detection methods: Machine Learning combined with migration methods (MALMI), coherence (Pyrocko/Lassie) and template matching (QuakeMatch), to produce a high-quality, manually revised seismic catalog. We compare our theoretical methods of network performance to the real data measured at the geothermal site.
Revealing the importance of transpiration from trees and non-tree vegetation to moisture recycling over Africa
Authors: te Wierik Sofie , Keune Jessica , Miralles Diego , Cammeraat Erik , Gupta Joyeeta , Artzy Yael , van Loon Emiel
Published: February 2023

The redistribution of biological (transpiration) and non-biological (interception loss, soil evaporation) fluxes of terrestrial evaporation via atmospheric circulation and precipitation is an important Earth system process. Overall, vegetation is the main contributor to terrestrial evaporation and subsequent precipitation over land. Yet, the specific contribution of different vegetation classes remains understudied. Here, we investigate how different vegetation classes (trees and non-tree vegetation) contribute to precipitation patterns through moisture recycling over African watersheds. Our study is based on simulated daily atmospheric moisture trajectories derived from the Lagrangian model FLEXPART, driven by 1° resolution reanalysis data over 1981–2019, aggregated at the monthly level. The data is constrained by evaporation and precipitation products, and unravels the annual and seasonal contribution from trees and non-tree vegetation to precipitation, employing fractional vegetation cover data. Our findings show that trees provide a higher water flux to precipitation over Africa compared to non-tree cover, with contributions of 777 mm year-1 versus  342 mm year-1  respectively. However, the large extent of non-tree vegetation over the continent compensates for this difference and many watersheds depend even largely on non-tree vegetation for precipitation. As non-tree vegetation appears to be important for precipitation over Africa, its current contribution to water availability should not be overlooked and requires further research, particularly in relation to ongoing land use and land cover change that may affect hydrology. Providing an outlook on existing and projected land use and land cover change, we highlight the spatial heterogeneous impact on local and regional water availability over the continent.
Uncertainty in aerosol-cloud radiative forcing is driven by clean conditions
Authors: Gryspeerdt Edward , Povey Adam C. , Grainger Roy G. , Hasekamp Otto , Hsu N. Christina , Mulcahy Jane P. , Sayer Andrew M. , Sorooshian Armin
Published: February 2023

Atmospheric aerosols and their interaction with clouds are the largest uncertainty in the human forcing of the climate system. Anthropogenic emissions have increased aerosol concentrations, increasing the concentration of cloud droplets and leading to reductions in droplet size and increases in cloud reflectivity (a negative radiative forcing). Central to this climate impact is the susceptibility of cloud droplet number to aerosol. This susceptibility varies widely with the method and data used to estimate it and within global climate models, explaining much of the variation in estimates of the radiative forcing from aerosol-cloud interactions (RFaci). Better constraints on the susceptibility have been a key target for recent observation-based constraints on the aerosol forcing.                                                                                                                                                 Previous work has shown that the aerosol burden of the clean, pre-industrial atmosphere has been demonstrated as a key uncertainty for the aerosol forcing. Here we show that the behaviour of clouds under these clean conditions is of equal importance for understanding the spread in radiative forcing estimates between models and observations. This means that the uncertainty in the aerosol impact on clouds is, counterintuitively, driven by situations with little aerosol. Removing these clean conditions from observational estimates of the susceptibility produces a close agreement between different model and observational estimates of the cloud response to aerosol, but does not provide a strong constraint on the RFaci. If we are to produce tighter constraints on the radiative forcing from aerosol-cloud interactions, better constraints on the behaviour of cloud in keen conditions are vital.
Subsurface Structure Regulates Water Storage in the Alpine Critical Zone on the Qinghai-Tibet Plateau
Authors: Zuo Fenglin , Li Xiaoyan
Published: February 2023

The subsurface critical zone (CZ) structure in alpine regions has a profound influence on water storage. The primary focus of this work is to reveal that the organic layer (A), leaching-deposit layer (B), saprolite layer (C) and freeze–thaw processes regulate changes in subsurface liquid water storage (CSWS). Here, we selected six representative ecosystems along an elevation gradient (4221~3205 m) in the Qinghai Lake Basin Critical Zone Observatory (QLBCZO) on the Qinghai-Tibet Plateau. We performed in situ field surveys, ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) measurements to investigate the subsurface CZ structure and liquid water storage (SWS). The results showed that the saprolite layer (thickness of 0.84~41.85 m) was the main subsurface liquid water storage reservoir, with a monthly average value of 595.49 mm. It occupied 82.12% of the total water storage of layers A, B and C. The average seasonal frozen thickness (SFT) ranged from 0.33 m to 1.60 m. SFT contributed most to CSWS, with 27.95% during the thawing period, and precipitation contributed most, with 19.87% during the freezing period. The SWS of the saprolite layers compared to that of layers A and B increased the most, by 39.41 mm and 45.88 mm in the thawing and nonfreezing periods, respectively, and that of layer B decreased maximally by 52.50 mm in the freezing period. This study contributes to advancing the mechanistic understanding of the interactions between the subsurface CZ structure and water storage processes and provides high-quality data with which coupled ecohydrological models can be developed.
Climate mitigation using wood in the Netherlands: a modelling approach from family home to national scale
Authors: Bos Jaap , van Wijnen Jikke , Lansu Angelique , Leenes-Gerbens Winnie
Published: February 2023

AbstractForests mitigate climate change by storing CO2 as wood and providing wood for products with a long economic residence time. This study examined the extent to which common Dutch homogeneous forests can contribute to climate mitigation if the harvested wood is processed into products. A model was set up which calculates the CO2 stock in the atmosphere for varying residence times of harvested wood in the economy and also determines the influence of this residence time on the optimal harvest age. Existing yield tables of Dutch homogenous forest were used as input data. This study showed that homogeneous forests in the Netherlands can extract a maximum of between 7 and 17 Mg of CO2 per hectare annually, depending on the tree species. For all tree species, the CO2 extracted from the atmosphere approaches this maximum as the residence time in the economy increases. The optimum felling age is not fixed, but varies depending on the economic residence time. The construction of 660,000 wooded single-family homes until 2050 with a lifetime of 150 years will remove an average of 1,5 Tg from the atmosphere annually. If the total forest area in the Netherlands is used to store wood in the economy for 150 years, an average of almost 6 Tg will be extracted annually. This is relatively low compared to the annual Dutch CO2 emissions of 150 Tg, but it is an option that fits well into the mix of other options that can contribute to climate change mitigation.
PETRARCH: Pinpointing Earth-System Thresholds for Anoxia with new Reconstructions of the Cretaceous Hothouse
Authors: Henehan Michael
Published: February 2023

Oxygen levels in Earth’s oceans are dropping fast due to anthropogenic nutrient input and CO2 release, and the consequences of this for marine ecosystems are difficult to predict. The Cretaceous Period (66- 145 million years ago) witnessed numerous extreme ocean anoxic events (OAEs) – some regional, some global in scale – that are thought to have been caused by pulses of volcanism and CO2 release. If we knew the exact mechanisms by which volcanism triggered these Cretaceous OAEs, and the role of feedbacks and boundary conditions, they could provide vital information as to where potential future tipping points in the Earth system lie. Presently, however, our estimates of climate, atmospheric CO2 and carbon cycling in the Cretaceous are qualitative at best, preventing OAEs from being useful analogues. In this poster, I will introduce the planned PETRARCH project, funded through UKRI matching of an ERC Consolidator Grant, that will aim to fill that gap. PETRARCH will combine new and proven geochemical proxy archives with cutting-edge Earth system modelling to look at how marine life and changes in marine pelagic ecosystems may have interacted with environmental changes to drive pervasive global anoxia. To do this, we will calibrate boron isotopes in the silica shells of radiolarians as a new proxy archive for ocean pH and atmospheric CO2, combine this new radiolarian data with new measurements of carbonate microfossils to reconstruct Cretaceous marine carbon cycling, and use Earth System modelling, tuned to these data, to test what exact biogeochemical feedbacks and climate forcings tipped the Cretaceous Earth into profound, and sometimes global, ocean anoxia.
NASA’s Science Discovery Engine: An Interdisciplinary, Open Science Data and Information Discovery Service
Authors: Bugbee Kaylin , Acharya Ashish , Davis Carson , Foshee Emily , Ramachandran Rahul , Li Xiang , Ramasubramanian Muthukumaran
Published: February 2023

NASA’s Science Plan includes a strategy to advance discovery by leveraging cross-disciplinary opportunities between scientific disciplines. In addition, NASA is committed to building an inclusive, open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI supports many activities to promote open science including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to NASA’s open science data and information and promotes interdisciplinary scientific discovery. In this presentation, we describe our work to develop the Science Discovery Engine in Sinequa, a Cognitive Search capability. We also share lessons learned about data governance, curation and information access.
Can soil moisture sensors support smart irrigation decision making in mountain terrace agriculture?
Authors: Bruggeman Adriana , Eliades Marinos , Djuma Hakan , Siakou Melpo , Sofokleous Ioannis , Zoumides Christos
Published: February 2023

While our planet is heating up, mountain terraces may be able to maintain agricultural production systems in a cooler environment than the agricultural plains. Mountain terraces are, however, characterised by diverse growing environments, with highly variable, stony soils, variable plant spacing and canopy cover. This limits the effectiveness of sensor-based technologies for efficient agricultural resource management. The objective of this research is to provide guidelines for informed irrigation decision making in mountain terrace orchards. Over the past four years, we have cooperated with four farmers with irrigated fruit trees on traditional dry-stone terraces in the Troodos Mountains of Cyprus. We installed soil moisture sensors at a different number of locations and soil depths, depending on the soil and terrace characteristics. In the stony soils of the apple terraces we installed sensors 3 locations and 2 depths (10 and 30 cm). In the cherry terraces, we installed 12 sensors at 4 locations and 3 depths (10, 30 and 45 cm) and 2 additional sensors at 10 cm. In the deep soils of the nectarine terraces, we installed sensors at 2 locations and 7 depths (10-70-cm depth). In the stony plum terraces, we installed sensors at 2 locations and 3 depths (10, 25 and 50 cm). We analysed the variability of the soil moisture observations and the effect of the uncertainty of the soil moisture observations on irrigation decision making. In the cherry terrace, results of more than 3600 hourly observations for 14 sensors showed that the average difference between the driest and wettest sensors amounted to 11.6% volumetric soil moisture at 10-cm depth, 6.7% at 30-cm depth and 7.6% at 45-cm depth. The maximum difference between the soil moisture sensors was observed immediately after one of the irrigation events (12 May 2022), showing a difference of 187 mm water in the rootzone between the driest and wettest set of sensors at the 3 depths. Based on the depth-weighted average of all 14 sensors, this event showed a drainage loss of approximately 38 mm of the 55-mm applied irrigation, below the 55-cm rootzone. The sensor-based irrigation advice would have suggested that the farmer should have irrigated maximum 17 mm. If the driest set of sensors at the 3 depths would have been used, the irrigation advice would have been the same, whereas based on the the wettest set of 3 sensors, the advice would have been to irrigate maximum 22 mm. This indicates that even though the the irrigation advice can have a 29% error, 33-mm drainage loss could have been saved with sensor-based irrigation scheduling for this event.   
Robustness of the nitrate transfer model NIT-DRAIN in an artificially drained agricultural area
Authors: Henine Hocine , Chelil Samy , Chaumont Cedric , Tournebize Julien
Published: February 2023

Nitrate leaching due to excessive agricultural fertilization affects the quality of both surface and ground water. The presence of subsurface drains in agricultural areas introduces significant modifications to the hydrological behavior and results in the increase of nutrients and fertilizers losses from farmland to surface water. The recent development of the NIT-DRAIN conceptual model allows the simulation of nitrate transfer at the agricultural drainage system outlet and the estimation of the initial prewinter nitrogen pool (PWNP), equivalent to the remaining nitrogen pool at the start of winter season. This model was applied to three representative drained agricultural areas in France (La Jaillière, 1 ha; Gobard, 36 ha and Rampillon, 355 ha). The hourly drainage discharge and nitrate concentration data are recorded over a period of several years. The objective of this study is to evaluate of the spatiotemporal robustness of the NIT-DRAIN model, by testing the functioning of the model regarding a single or a generic set of model parameters for the three study sites.The results showed that the model estimation of the PWNP is more precise at the small scale (Jailliere site). At the large scale, the PWNP estimation is slightly different from the measurement (<10kgN/ha). The model calibration for each study site shows high model performance for nitrate fluxes and concentrations, with Nash-Sutcliffe criterion greater than 0.6. These performances are preserved when calibrating a generic set of parameters to all the three sites. These results validate the robustness of the NIT-Drain model. This study present a simplified and operational approach for the quantification of PWNP applied to the subsurface drained agricultural lands by measuring nitrate concentration at outlet instead of soil core sampling.
An Analysis of Spectral Simulation Methods for Laser Heterodyne Radiometry for the Vertical Profiling of Greenhouse Gas (GHG) Mixing Ratios
Authors: Miller J. Houston , Flores Monica , Bomse David , Gomez Anthony
Published: February 2023

George Washington University and Mesa Photonics are developing and deploying a Laser Heterodyne Radiometer (LHR) that simultaneously measures CO2, CH4, H2O, and O2 mixing ratios throughout the troposphere and lower stratosphere. Spectral fits are constrained by fitting the oxygen spectral line shape – which depends only on pressure and temperature – to improve GHG retrieval precision and provide dry-air corrections. This constraint is achieved by fitting pressure and temperature profiles obtained from the meteorology data measured by radiosondes (vertical resolution ranging from 5-500 m) as part of NOAA’s Integrated Global Radiosonde Archive (IGRA).Atmospheric spectra are simulated for the column using a spectral simulation package (“LahetraSim”) that uses parameters from the HITRAN spectral database to model spectra through the HITRAN Application Programming Interface (HAPI). Integrated path absorption spectra are calculated using the initial sun angle and estimated radiosonde pressure and temperature profiles. Concentration profiles for CO2, CH4, and H2O can then be iterated on their vertical distributions and refining the pressure and temperature profiles to best fit the oxygen spectrum.Here we present a comparison of our spectral simulation software to that of an alternative method that has been presented for LHR data processing which makes use of the Planetary Spectrum Generator (PSG) API. Spectral simulations are generated using several atmospheric databases, templates, and transfer models. This tool allows for the extraction of Modern Era Retrospective Analysis, Version 2 (MERRA-2) vertical profiles of pressure and temperature and species abundances from HITRAN. Two limitations of the MERRA-2 database are the latency of approximately 2 months for the latest data availability and the coarse vertical resolution (~1 km) of the available data.  Another benefit of our approach is that approximation of both Planetary Boundary Layer (PBL) and Tropopause Heights can be extracted from the temperature and pressure profiles and these heights can be iterated to refine atmospheric layers; thus increasing their relevance of LHR to GHG modeling.
Iceland: mantle plume or microcontinent? A zircon study
Authors: Peace Alexander , Phethean Jordan , Li Yang , Foulger Gillian
Published: February 2023

In recent years, unexpected continental crust in areas presumed to be purely oceanic in nature has been discovered, indicated by the presence of Paleozoic zircons in rock samples. Notable examples include the Rio Grande Rise, Mauritius, and potentially also the Comoros islands, which have all previously been interpreted as mantle plume edifices. Iceland is also often interpreted as a hotspot of mantle plume origin, however the presence of a deep seated consistent thermal anomaly with depth has long been challenged, with implications for the wider regional geodynamic evolution.
Previous reports of Mesozoic and Paleozoic zircons from Iceland may allude to the presence of continental material at depth, although these are sometimes suggested to be the result of contamination. Nonetheless, geochemical evidence from erupted material at Öræfajökull may indicate a continental contribution to melts beneath SE Iceland, and the nearby Jan Mayen microcontinent readily demonstrates the ability of continental material to make its way to the ocean interior, coincident with hotspot volcanism. Furthermore, continental material in the NE Atlantic Ocean is perhaps more common than previously thought, with recent work suggesting that substantial components of the Greenland-Iceland-Faeroes region may be continental in nature.
Here, we test the hypothesis that the basaltic upper crust of Iceland is underlain by older continental crust. To do this, we have undertaken extensive, targeted sampling of Icelandic rocks and sediments using robust collection approaches to eliminate the possibility of contamination. Over a 3-week period in summer 2022, we collected samples from across the entirety of Iceland. We sampled both intrusive and extrusive rocks with a wide range of ages (both felsic and mafic, but with an emphasis on felsic rocks), as well as river sediments from above 250 m elevation (to avoid potential contamination from Greenland glacial debris). Zircons will be separated from these samples using contamination-safe approaches, and then U-Pb and Hf isotopic age analysis will be completed. The results from this preliminary study will be used to guide further sampling in summer 2023, allowing evaluation of the competing hypothesises for the origin of Iceland.
Towards semi-quantification of DOM: isomer separation with LC-FT-ICR-MS combined with a post-column infusion of standard.
Authors: Rodrigues Matos Rebecca , Jennings Elaine , Koch Boris , Lechtenfeld Oliver
Published: February 2023

Ultrahigh-resolution mass spectrometry like FT-ICR MS has greatly expanded our view of the complexity and reactivity of complex dissolved organic matter (DOM) in the environment. However, both the structural characterization and (semi)-quantification DOM are methodologically not fully resolved, despite recent advances with coupling liquid chromatography (LC) to FT-ICR-MS that allows isomeric separation. Likewise, matrix effects and the existence of multiple isomers with largely varying – but unknown – ionization efficiencies that are simultaneously ionized and detected in direct infusion (DI)-FT-ICR MS prevents (semi)-quantification of DOM compounds and has limited the comparability of samples. Finally, common normalization strategies applied for non-targeted DOM analysis with DI cannot be easily transferred to LC-type DOM data. Here we present a new method that combines a post-column infusion of internal standard (PCI-IS) with LC-FT-ICR MS in order to reduce and compensate matrix effects as well as to provide a robust and reliable way to normalize MS peak intensities and compare samples measured with LC-FT-ICR MS. To this end, DOM samples were analyzed and the peak intensity data normalized by the internal standard and other frequently used normalization methods (e.g. sum of intensity, base peak), and absolute intensity indicating that PCI-IS normalization provides superior precision and accuracy. The potential of this method to provide semi-quantitative information on polarity fractions of DOM is assessed by testing the precision, accuracy, and linearity of PCI-IS normalization of model compounds spiked into DOM samples. Our results indicate that the use of LC separation reduced matrix effects (as compared to DI) and, in combination with the internal standard, improved to potential to obtain reliable peak intensity information.
Perfect storm for green economy and fossil fuels alike
Authors: Dubitsky Will
Published: February 2023

Fuel prices, inflation and war have created the perfect storm for the green economy and fossil fuels alike.  The presentation is special in its global focus on the perfect storm interconnections of components, much like a huge jigsaw puzzle for which all the pieces fit together, but in a complicated way.Renewables are expected to represent 90% of newly installed electrical generation capacity between 2022 and 2027, overtaking coal in the process. Electric vehicle (EV) sales are growing hastily in China and Europe.  By contrast, North American targets are weak, leaving much room for automakers to continue to favour the more profitable gas-powered vehicles.  Another constraint is the lack of availability of many EV models, with delivery wait times as long as 2 years or more.The U.S. Inflation Reduction Act (IRA) and the Bipartisan Infrastructure Law (BIL) combined, will catapult U.S. clean energy production plus close American EV and clean tech gaps with China and Europe.  There was a mind-boggling momentum for green economy projects, existing, under construction and planned, prior to the IRA and BIL.  The new legislative initiatives promise to stimulate massive investments green economy research, applications and R & D unparalleled elsewhere, with the possible exception of China.The IRA and BIL are complex and likely to give the U.S. a North American green advantage at the expense of Canada.Concurrently, with trillions in profits, the oil and gas sector is headed for gargantuan fossil fuel agenda.  Though the sector was writing off tens of billions of dollars in 2020 and all signs point to peak oil and gas nearby, the short-term sector view has taken precedence. This oil and gas industry tunnel vision perspective is propelled by executive bonuses linked to production increases, 41% in the case of ExxonMobil and 20% for Shell.  While the bonus criteria include transition positive elements, many of these elements may actually increase production and/or are greenwashing.  Such is the case with characterizations of natural gas as a bridge fuel, howbeit shale gas methane emissions could render this fuel as bad as coal.  Notwithstanding, greater production trumps all other considerations.This is what it is like in a transition, the path is bumpy with much tugging in opposite directions.  Not unlike the long history of the struggle for women’s rights.  The green transition shakedown is tramping ahead, but gamechangers are only noticed when tide is omnipresent.There are reasons that give hope for a green metamorphosis, but the foundation is shaky.
Spatio-temporal analysis of soil surface hydraulic properties in a semi-arid agroforestry system of the Senegalese groundnut basin
Authors: Faye Waly , Orange Didier , Talla Seydou , Do Frederic , Jourdan Christophe , Roupsard Olivier , Faty Abdoulaye , Niang Awa , Kane Alioune , Di prima Simone , Angulo-Jaramillo Raphael , Lassabatere Laurent
Published: February 2023

In Senegal, the groundnut basin is the main agricultural region under a semi-arid climate, heavily cultivated in an agrarian system combining agricultural rotation and agroforestry dominated by Faidherbia albida trees. The soils of the groundnut basin, essentially sandy, have a low water retention capacity. In this area, water is a limiting factor, and the climate variability represents an additional constraint on an already precarious agricultural production system. It is therefore essential to improve knowledge on water saving practices and soil humidity dynamics. The management of water resources in agricultural fields requires reliable information about soil hydraulic properties, which control the partition of rainfall into infiltration and runoff, and their spatio-temporal variability.
To investigate the variability of soil hydraulic parameters we have carried out infiltration measurement in open space without tree and below tree canopies. A total of 24 infiltration measurements were carried out using an automatic single-ring infiltrometer in the nearby of each plot (4 measurements × 6 plots), and after removing the first 10 cm of uncompacted sand. The infiltration tests were carried out in June, October and December, respectively before, during and after the crop season. We used the Beerkan Estimation of Soil Transfer Parameters (BEST) method to retrieve the soil hydraulic parameters from infiltrometer data and field measurements of soil porosity, initial and saturated soil water contents and soil bulk density.
The statistical analysis of the data showed a high variability during the cultivating period, both in time and space, especially of the saturated soil hydraulic conductivity Ks. However, the Ks seems higher under tree cover, around 0.186 mm/s, for 0.167mm/s without any tree canopy influence.  Despite the expected homogeneity of the investigated sandy soil, the presence of the perennials triggered a patchy distribution of soil hydraulic conditions. These preliminary results evidenced the importance of taking into account parameters variability and landscape structure when simulating soil water dynamics in the Senegalese groundnut basin.
Mapping Hazard to Extreme Temperature Events Over the Indian Subcontinent
Authors: Shilin Anokha , Sudharsan Naveen , Mondal Arpita , Kalbar Pradip , Karmakar Subhankar
Published: February 2023

The recent AR6 report of the Intergovernmental Panel on Climate Change (IPCC) explicitly shows that the observed change in hot extremes (including heatwaves) with high confidence in human contribution to the observed changes has highly increased in the South Asian (SAS) domain which comprises the Indian subcontinent. Extreme heat events are more frequent and intense across the globe since the 1950s and have adverse societal and economic impacts. Considering current warming trends and projections, heatwaves are becoming a serious problem in India. Exposure to extreme heat in the population is increasing due to climate change. Also, observed temperatures are increasing globally as well as regionally as an effect of global warming. As heat stress occurs when the human body cannot get rid of the excess heat, it can be considered a good proxy for the heatwave hazard. Heat stress results in heat stroke, exhaustion, cramps, or rashes. Exposure to extreme heat can result in occupational illnesses and injuries. An agrarian country like India will have large economic damage when climate-related heat stress increases the occurrence of droughts and exacerbate water scarcity for irrigation. Hence the impact of the heat stress hazard is spotted and largely discussed both in the academic and political domains. In this study, Universal Thermal Climate Index (UTCI) based hazard map is developed for India with a non-parametric multivariate approach. The prominent heat stress hazard areas are identified and mapped with reference to the UTCI assessment scale which is categorized based on thermal stress. The probability of occurrence is also mapped using the exceedance probability with the UTCI reference. Heat stress hazard map provides the basis for a wide range of applications in public and individual precautionary planning such as heatwave action plans, urban and regional planning, the tourism industry, and climate research. Hence a country-level extreme temperature hazard map is of dire necessity.Keywords: Exceedance probability, hazard map, heat stress, multivariate approach, non-parametric method
Danish national early warning system for flash floods based on a gradient boosting machine learning framework
Authors: Martinsen Grith , Sweeney Yann , Pedersen Jonas Wied , Alexandru Roxana , Capape Sergi , Harris Charlotte , Butts Michael , Diaz Maria
Published: February 2023

Fluvial and flash floods can have devastating effects if they occur without warning. In Denmark, management of flood risk and performing preventative emergency service actions has been the sole responsibility of local municipalities. However, motivated by the disastrous 2021 floods in Central Europe, the Danish government has recently appointed the Danish Meteorological Institute (DMI) as the national authority for flood warnings in Denmark, and DMI is in the process of building capacity to fulfill this role. One of the most cost-effective ways to mitigate flood damages is a well-functioning early warning system. Flood warning systems can rely on various methods ranging from human interpretation of meteorological and hydrological data to advanced hydrological modelling. The aim of this study is to generate short-range streamflow predictions in Danish river systems with lead times of 4-12 hours. To do so, we train and test models with hourly data on 172 catchments. Machine learning (ML) models have in many cases been shown to outperform traditional hydrological models and offer efficient ways to learn patterns in historical data. Here, we investigate streamflow predictions with LightGBM, which is a gradient boosting framework that employs tree-based ML algorithms and is developed and maintained by Microsoft (Ke et al., 2017). The main argument for choosing a tree-based algorithm is its inherent ability to represent rapid dynamics often observed during flash floods. The main advantages of LightGBM over other tree-based algorithms are efficiency in training and lower memory consumption. We benchmark LightGBM’s performance against persistence, linear regression and various LSTM setups from the Neural Hydrology library (Kratzert et al., 2022). We evaluate the algorithm trained using different input features. This analysis include model explainability, such as SHAP, and the results indicate that simply using lagged real-time observations of streamflow together with precipitation leads to the best performing and most parsimonious models. The results show that the LightGBM setup outperforms the benchmarks and is able to generate predictions with high Klinge-Gupta Efficiency scores > 0.9 in most catchments. Compared to the persistence benchmark it especially shows strong improvements on peak timing errors.
Ice-rain interaction determining the erosional-depositional behavior of adjacent drainages at Cotopaxi volcano (Ecuador)
Authors: Andrade S. Daniel , Povea María José , Saltos Emilia , Vásconez Francisco Javier
Published: February 2023

Cotopaxi is a glacier-clad volcano located in the Andes of Ecuador (South America). Since its last big eruption, occurred in June 1877, alluvial fans have developed in the lower flanks of the volcanic edifice due to water-related erosional-depositional processes. Two of those fans can be identified in the adjacent Pucarumi and Jatabamba drainages, whose source zones are closely located in the upper north-east flank of Cotopaxi volcano. Geological, ground-penetrating radar and sediment-componentry and granulometry data show that both fans have been deposited after the 1877 eruption and are similar in size, thickness and composition. These measurements thus suggest that the medium- to long-term development of the adjacent fans was controlled by similar processes affecting both drainages. However, when the current deposition in both drainages was surveyed during a one-year period using drone ortho-photogrammetry, the Jatabamba drainage proved to be much more active than the Pucarumi drainage. Although the observed depositional activity at Jatabamba can be broadly correlated to the year-round rain-pattern, the contrasting behavior observed at the adjacent Pucarumi drainage strongly suggest that rainfall alone is unable to entirely explain the erosional processes occurring at Cotopaxi volcano. Instead, recent satellite imagery shows that the source zone of the strongly active Jatabamba drainage currently displays a glacier tongue, which is absent in the case of the weakly active Pucarumi drainage. It is thus concluded that erosional processes occurring at Cotopaxi volcano are mostly driven by water originated by an interaction between rainfall and ice at the glacier border. The precise nature of such interaction remains to be determined.