bluuebunny/crossref_metadata_2025 huggingface dataset:
Seasonally Resolved Age Scale based on Oxygen Isotope Record from SE-Dome II Ice Core, Greenland
Authors: Hamamoto Saaya , Matoba Sumito , Kawakami Kaoru , Sasage Mahiro , Matsumoto Mai , Yoshimura Kei , Okazaki Atsushi , Bong Hayoung , Iizuka Yoshinori , Uemura Ryu
Published: March 2024

Ice core ages have been typically determined by counting the layer boundaries of various proxies that represent annual cycles. Some studies in Greenland have identified winter and summer layers, but it is difficult to identify them at higher resolutions (several months resolution) in ice cores drilled at sites with low accumulation rates due to diffusion. Furukawa et al. (2017) proposed a precise age model by matching the oxygen isotope (δ18O) pattern of precipitation isotope between ice core record and isotope-incorporated general circulation models. They applied this dating method to the SE-Dome I (SE1) ice core drilled from a high snow accumulation area (1.02 m w.e. a-1) in southeast Greenland. However, the SE1 core covered for the past 60 years only. Here, we report the age scale based on δ18O data of the SE-Dome II (SE2) ice core (length: 250.79 m) drilled in 2021 in southeast Greenland. The δ18O was analyzed using a cavity ring-down spectrometer (L2130-i, Picarro) with a precision (1σ) of ±0.04‰. The SE2 core δ18O highly correlated with the SE1 core δ18O (r = 0.90), suggesting that the within-year peaks in the SE core are climatic signals. The age scale was created using the SE1 core method, but for this study, we used iso-GSM nudged to historical reanalysis data (20CRv2) for 1870-1979 and created a longer age scale. There was a high correlation between the ice core data and the model (r = 0.76), and by matching the within-year patterns (typically negative peaks during the warm season). Based on this age scale, we analyzed the day on which the maximum and minimum peaks of the mean H2O2 concentration data (Kawakami et al., 2023). The maximum and minimum of H2O2 concentrations for 1980-2020 were estimated on July 20 and January 7, respectively. REFERENCESFurukawa, R. et al. , Seasonal-Scale Dating of a Shallow Ice Core From Greenland Using Oxygen Isotope Matching Between Data and Simulation, Journal of Geophys. Res. Atmospheres, 122, 20, 10,873-10,887, 2017, https://doi.org/10.1002/2017JD026716Kawakami, K., et al., SE-Dome II Ice Core Dating With Half-Year Precision: Increasing Melting Events From 1799 to 2020 in Southeastern Greenland, Journal of Geophys. Res.  Atmospheres, 128, 20, 2023, https://doi.org/10.1029/2023JD038874
The Construction of Multi-Channel Wells and Analysis of Related Hydraulic Tests to Explore the Physical Mechanism behind Land Subsidence in Changhua and Yunlin, Taiwan.
Authors: Lee Jhe-Wei , Lo Wei-Cheng , Peng Syue-Hong
Published: March 2024

To enhance the density and precision of groundwater level observations, this study installed two 300-meter multi-channel wells (MCW) in XiHu (Changhua) and YuanChang (Yunlin). These wells can concurrently monitor water levels in 15 layers within the protective tubing. Fifteen sets of 1-inch groundwater observation wells, varying in depths, were placed in the protective pipe. The groundwater level observation equipment utilized two sets with different principles—electronic and optical fiber—to record water levels. The objective was to compare the accuracy and stability of the optical fiber water level measuring equipment. Despite the potential simplification of well construction processes for fiber-optic water pressure gauges, a pressure issue still needs to be addressed. Therefore, the electronic water level meter remains the more reliable option between the two.
Pumping tests were conducted at two sites to observe the flow characteristics of each layer in the multi-channel well and the depth changes of the magnetic ring in the multi-level compaction monitoring well (MLCW). During pumping in XiHu #1, the water level in the shallow layer rose due to additional groundwater recharge caused by pumping. The rise in water level in the sub-deep layers is attributed to the gravel composition of the stratum at this depth, facilitating better groundwater flow.The YuanChang standard observation well is divided into five depths. The pumping test results indicate that the aquifer at each depth is less influenced by the upper and lower layers. Water level changes in the MCW, affected by the pumping test, can be categorized into three groups: MCW#1~#5, MCW#6~#12, and MCW#13~#15. The depth changes of the magnetic ring in the MLCW were analyzed during water pumping and recovery. The changing trend of the magnetic ring in the XiHu pumping test site aligns with the pumping and recovery process. The magnetic rings of YuanChang, specifically NO.1 to NO.5 comprising unconfined aquifer layers, exhibit minimal rebound during the recovery stage of Yuanchang #1. The trends in magnetic rings NO.18 to NO.26 align with water pumping and recovery, indicating characteristics typical of a confined aquifer. The water pumping and recovery in YuanChang#3 and YuanChang#4 display a hysteresis effect on the changing trend of magnetic rings NO.1 to NO.7.
The MCWs established in this study, along with the pumping test results, can provide more accurate on-site survey data. Coupled with the comparison of MLCW observation results, this can serve as a demonstration site for studying stratigraphic subsidence, significantly contributing to improving scientific research demonstrations.
Air Quality in Mexico-City: Emissions, Transport, and Chemical Transformation
Authors: Rappenglück Bernhard , Akther Tanzina , Ahmad Mateen , Alam Jahirul , Osibanjo Olabosipo , Retama Armando , Rivera-Hernández Olivia
Published: March 2024

During the period March 12-17, 2016, Mexico-City experienced its most severe smog episode since 2007. The Metropolitan Index of Air Quality (IMECA) for Mexico-City surpassed the value of 200, indicating an extremely bad situation. Hourly peak values for both, NO2 and O3, exceeded 200 ppb, while for CO more than 2 ppm were observed. Restrictions on traffic and industrial activities, among other emergency measures, were imposed. We describe results from Positive Matrix Factorization (PMF) for source apportionment based on a commixture of gasphase compounds (VOCs, CO, NO, NO2, SO2, NH3) along with equivalent black carbon (eBC), and ions (Na+, Mg2+, Ca2+, NO3-, NH4+) in combination with an analysis of regional meteorological processes and boundary layer conditions retrieved from continuous microwave radiometer measurements. Apart from more traditional emission sources, the PMF analysis also deciphered a geogenic source. Continuous boundary layer height data was used to normalize mixing ratios of pollutants representative for each source factor. This procedure allowed the retrieval of diurnal variations of pollutants predominantly determined by emissions and removal mechanisms. The results show prolonged daytime emissions of O3 precursors beyond the typical morning rush hour, an important information to optimize O3 mitigation strategies. Propylene Equivalent and Maximum Incremental Reactivity (MIR) methods identified isoprene and ethylene as the highest oxidant and O3 forming species which indicates some interchange of individual top VOC contributors to ozone formation in that city over the last decades. This presentation concludes with results from air quality modeling including Machine Learning approaches. While the Deep Neural Network, Random Forest and Gradient Tree Boosting models are depicting diurnal O3 levels nicely, as long as O3 mixing ratios are at moderate levels (≤120 ppb) only the Deep Neural Network may capture peak ozone values (>160 ppb), which are most critical with regard to public health.
Nonlinear Viscoelastic Model for Ice and Olivine, Constrained by Experimental Data using MCMC
Authors: Maor Ron , Hansen Lars , Goldsby David
Published: March 2024

Mechanisms of energy dissipation in ice and olivine have been studied experimentally in the past, with an observed strain-amplitude dependence that indicates nonlinear viscoelastic behavior resulting from the presence and motion of dislocations. In a range of low to moderate stress amplitudes, dislocations can ”bow out” between pinning points. If the resolved shear stress is sufficiently large, dislocations may escape their pinning points and elastically interact with each other. The transition from pinned to unpinned motion, along with the subsequent interactions and recovery processes, are associated with the shift from anelastic to steady-state viscous behavior. This transition forms the basis of a viscoelastic model. Despite the experimental evidence of nonlinear mechanisms, the availability of comprehensive nonlinear viscoelastic models for geological materials is limited. In this work, we propose a nonlinear viscoelastic model that captures the effect of dislocation dynamics on energy dissipation. The model is based on the well-known linear Burgers model, modified to incorporate non-linear steady-state viscous flow, and enhanced by the integration of fabric and grain-size evolution dynamics. The proposed model is tested against data from constant strain-rate and forced oscillation experiments, and the parameters are constrained using Markov Chain Monte Carlo (MCMC) methods. The model successfully reproduces data from deformation experiments in the dislocation creep regime and can be extended to experiments involving other deformation mechanisms as well.
Cascading impacts of extreme events across an interconnected and warming world
Authors: Huning Laurie , Brunner Manuela
Published: March 2024

Extreme events (e.g., heatwaves, wildfires, droughts, floods, etc.) are anticipated to become more severe, persistent, and frequent throughout many parts of the world due to warming. Such extreme events occur across a diverse set of ecosystems and climatic regions and their multifaceted impacts cascade in space, time, and across sectors (e.g., water, energy, agriculture, economic, human health). To better understand the cascading impacts of extreme events and their feedbacks, we draw on recent examples such as the 2023 heatwaves and wildfires in Canada. In addition, we also examine other extreme events (e.g., droughts, floods) around the world and their feedbacks and interactions that pose challenges for modeling, monitoring, and managing associated risks. For example, we quantify how snowpack changes and drought across agricultural regions have wide-reaching impacts that affect remote areas. Our study highlights that the impacts of extreme events have important feedbacks that should be considered in resource and risk models and management as well as remote impacts that are not yet fully understood or well-tracked. Furthermore, we identify other challenges, existing knowledge gaps, and future directions to guide global monitoring and modeling of impact cascades for improved mitigation, adaptation, and climate change resilient policy advancements.
Recruitment at treeline in the Central Rocky Mountains shifts in favor of a drought-tolerant species as climate water deficit increases
Authors: Sindewald Laurel , Tomback Diana
Published: March 2024

Treeline elevation is expected to shift upward in response to climate warming. However, over half of alpine treelines worldwide appear to be lagging, possibly due to moisture limitations. Seedling niches tend to have narrower climate envelopes than those of mature, established trees, and regeneration requirements can vary substantially among species. We examined the density and species composition of recruitment at alpine treeline sites west and east of the Continental Divide, Central Rocky Mountains.  In the arid Colorado Front Range, the Divide results in a rain shadow on the east side due to orographic uplift. We stratified our sampling effort by proximity to subalpine limber pine (Pinus flexilis), a generalist, drought-tolerant conifer with a patchy metapopulation distribution in the Front Range. We expected to find higher abundance of limber pine regeneration than that of drought-averse Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) in two regeneration height categories (≤ 100 cm and ≤ 20 cm). Regeneration occurred at low densities on both sides of the Continental Divide and did not differ significantly between sites east and west of the Divide. Regeneration density also did not differ significantly between communities dominated by limber pine and communities dominated by Engelmann spruce and subalpine fir. However, the quadrats with highest regeneration densities were east of the Divide where limber pine was the dominant conifer. These sites were also in the rain shadow and associated with higher climate water deficit and lower growing season precipitation. Limber pine also comprised the majority of this regeneration. The site with the highest observed regeneration rates also had high rates of viable limber pine seed production at treeline. We observed a significantly higher proportional abundance of limber pine in the 100 cm regeneration class (relative to established trees) in quadrats east of the Divide, corresponding to establishment roughly in the last 30-70 years. The greater proportional abundance in limber pine regeneration at these treeline study sites occurred despite increasing temperatures, reduced growing season precipitation, and increased climate water deficit over the past 30 years. Drought-tolerant limber pine may therefore be the best-suited conifer in this region to persist and to migrate to higher elevations as temperatures continue to increase. Our findings underscore the importance of considering differences in seedling tolerances (niches) among different species in alpine treeline systems when aiming to predict landscape-scale treeline responses to climate warming.
Green Soil Stabilisation:  Harnessing Microbes from Fermented Vegetables and PET Bottle Plastics Waste as Reinforcement
Authors: Baharuddin Intan Nor Zuliana , Che Omar Rohayu , Abdul Azam Farah ‘Atiqah , Mohamad Zakaria
Published: March 2024

This research focused on the integration of biological and mechanical grouting methods in soil stabilization. In this research, soil reinforcement was achieved using a bio-mediated technique involving microbes derived from vegetable waste, along with the incorporation of PET strips sourced from plastic bottle waste. The silty sand types of soil treated with 15 wt.% of fermented vegetable liquid (vege-grout) were mixed with different sizes and percentages of PET plastic waste. After curing for 21 days, the finding shows that 0.75% of PET is the optimum percentage of PET reinforcement with an unconfined compressive strength of 20.80kPa. Increasing higher amount of PET 1 wt.% reduces the shear strength of the soil by 18.75%. The longer size of PET strips exhibited superior strength, providing more effective reinforcement. The result demonstrated that the utilization of vegetable and plastic wastes holds substantial importance from both economic and environmental perspectives in the future. 
Simple parasequences in a medial shelf setting: Albian Sikanni Formation, Northwest Territories, Canada
Authors: Abi Daoud Angelina A. , Bhattacharya Janok P.
Published: March 2024

We document medial shelf parasequences in the Upper Albian Sikanni Formation in the Liard Basin, Northwest Territories, Canada, deposited during a greenhouse climate in the Western Interior Cretaceous Seaway. It is characterised as a fine-grained glauconitic sandstone with argillaceous shales, ranging approximately 100 to 300 metres in thickness. We measured 111 metres of section, passing from sandier to more distal shale facies towards the contact with the conformably overlying Sully shale, indicating an overall deepening. The sandier section shows well-organised upward coarsening facies successions, transitioning from wave to hummocky cross stratified sandstones to pervasively bioturbated sandstones, dominated by Zoophycos to distal Cruziana ichnofacies, interpreted as a medial shelf environment. There are at least 8 well-expressed parasequences in the sandier lower part of the section, transitioning into more uniform shalier units near the contact of the Sully Formation. The sandier parasequences are sharply bounded by shales forming well-expressed ‘simple parasequences’. Simple parasequences are defined as upward-coarsening facies successions lacking evidence of key bounding surfaces indicating bypass or subaerial exposure, such as lag deposits, roots, or transgressive erosion. These are distinguished from ‘complex parasequences’, commonly containing these features. The changing environment of the more uniform muddier facies can be distinguished using increases and decreases in bioturbation, corresponding to lower and higher sedimentation rates, respectively. The Sikanni units lack evidence of subaerial exposure, indicating that it is unlikely the parasequences shallowed up to the shoreline. Nevertheless, these cycles are well-expressed, suggesting that simple parasequences can be identified in medial shelf environments. Additionally, a guiding framework based on Dene (First Nations) principles was developed as a basis for this project. The phases on the framework are: (1) Decolonisation of the Self, (2) Building Relationships and Community Consultation, (3) Community Entry and Data Collection, (4) Data Analysis, and (5) Knowledge Translation and Dissemination. A special thanks to Acho Dene Koe First Nation in the community of Acho Dene Koe, Northwest Territories, for graciously welcoming us onto their lands, into their community, and allowing us to share the geologic stories of the rocks they have coexisted with since time immemorial.
Using Digital Soil Mapping to identify where best to store soil carbon
Authors: van Zadelhoff Feiko , McNally Sam , Kumar Kishor , Ekanayake Jagath , McNeill Stephen , Triantafilis John
Published: March 2024

Soil has the potential to store large amounts of soil organic carbon (SOC). The mineral surface area (MSA - m2 g-1) indicates this capability. Given the cost of laboratory analysis and the heterogeneous nature of soil, a digital soil mapping (DSM) approach may enable a farmer to determine where best to sequester SOC. Herein we create DSM’s of MSA at the Lincoln University Dairy Farm (LUDF) on the South Island of Aotearoa (New Zealand). We compare ordinary kriging (OK) of topsoil (0-0.15 m) MSA, with DSM’s created using various digital data either or alone or in combination, including remote (i.e., Light Detection and Ranging [LiDAR]) and/or proximal (i.e., gamma-ray [γ-ray] and electromagnetic [EM] induction) sensed data. We compare various approaches; stepwise multiple-linear regression (MLR), geostatistical (i.e., regression kriging [RK]), and a hybrid machine learning and geostatistical (i.e., Random Forest [RK] with RK [RFRK]) models. In all cases, a prediction sample size (n = 160-10) was evaluated against a validation (n = 40) dataset, considering prediction agreement (Lin's concordance correlation coefficient [LCCC]) and accuracy (root mean square error [RMSE]). We also compare which digital data is best and whether used on its own or in combination. When n = 160, OK produced moderate (Lin’s = 0.78) agreement. When predicting with digital data (i.e., g-ray [K], EM [1mPcon] and DEM [SWI]), RK (0.88), RFRK (0.82) and MLR (0.80) produced substantial agreement. When considering the minimum number of samples, OK maintains near substantial (i.e., > 0.8) agreement when n = 100 (0.79), while RK (0.84) and RFRK (0.8) need n = 20, with MLR (0.79) as few as n = 10. We conclude that with digital data (i.e., SWI, g-ray K and 1mPcon) and using RK was optimal, with as few as 1 sample required every 8 hectares for calibration, but we recommend 1 sample be taken every 4 hectares. Moreover, to improve prediction additional soil samples should be taken where MSA was large (i.e., > 30 m2 g-1). When considering which digital data might be useful on its own or in various combinations, we found that in terms of agreement and considering models developed using RK, using DEM + EM (0.88) was best in terms of agreement, followed by EM only and DEM, g-ray + EM (0.86), with DEM only (0.83) and DEM + g-ray (0.81) also having substantial agreement. The final DSM of RK, indicate where soil capability would be greatest to store SOC, and this was where the most suitable soil conditions (i.e., MSA) were present in the southern part of the LUDF, associated with the larger clay content of the Glay soil profiles.
Deciphering Seismogenic Patterns in Hydraulic Fracturing: A Machine Learning Approach in the Southern Montney Play
Authors: Wang Bei , Kao Honn , Yu Hongyu , Li Ge , M.H. Dokht Ramin , Visser Ryan
Published: March 2024

The burgeoning development of hydraulic fracturing (HF) for unconventional resource extraction has been paralleled by a rise in injection-induced earthquakes (IIEs), posing significant seismic hazards. A critical challenge in mitigating these hazards is the accurate assessment of the seismogenic potential and earthquake productivity of individual HF pads. We addresses this challenge by analyzing over 35,000 earthquakes in the Southern Montney Play (SMP), Western Canada, from 2014 to 2022, and associating them with 357 HF pads. We employed the eXtreme Gradient Boosting (XGBoost) machine-learning algorithm, integrating fifteen geological and operational factors to evaluate their influence on IIE occurrence and intensity. We also utilized Shapley Additive Explanations (SHAP) values for a nuanced interpretation of the model outputs, providing insights into the relative importance and interaction of these factors. Our analysis reveals that the cumulative injected volume and the location of HF pads within the Fort St. John Graben (FSJG) are the primary determinants of seimogenic potential (occurrence of IIE). In contrast, the number of HF stages targeting the Lower Middle Montney formation, cumulative volume from preceding injections, and the HF pad's location within the FSJG predominantly influence the seismogenic productivity (number of IIE). These findings suggest that both operational and geological factors are critical in determining the seismogenic productivity of HF pads. The XGBoost model demonstrated high predictive accuracy (R2 ~0.90), although its performance is constrained by the dataset's size and potential overfitting issues. The study challenges the conventional understanding that proximity to known faults is a major factor in IIE occurrence, instead highlighting the significance of cumulative injection volumes and specific geological settings. The analysis also underscores the complex interplay between various factors, such as the correlation between the location fo the HF pads and the targed formation during HF stimulations, which may influence seismogenic patterns. Overall, our result provides a comprehensive assessment of the factors influencing seismogenic behavior in HF-related IIEs, paving the way for more accurate forecasting of IIE activity levels for individual HF pads in the SMP. The findings have significant implications for seismic hazard assessment and risk mitigation strategies in regions undergoing HF operations. The application of machine learning in this context not only enhances our understanding of induced seismicity but also demonstrates the potential of such techniques in addressing complex geoscientific challenges.
Proton energy spectra of energetic storm particle events and magnetic field turbulent fluctuations nearby the associated interplanetary shocks
Authors: Lepreti Fabio , Chiappetta Federica , Laurenza Monica , Benella Simone , Consolini Giuseppe
Published: March 2024

Interplanetary shocks are efficient sources of accelerated particles and are often associated with high-energy proton/ion flux enhancements known as energetic storm particle (ESP) events. In situ spacecraft observations of particle fluxes near the shocks can be used to obtain energy spectra, providing very useful information for the investigation of the acceleration mechanisms. In this work we analysed the kinetic energy spectra of proton flux enhancements associated with ESP events observed by various spacecraft. ESP events associated with diverse shock conditions and geometries (e.g. quasi-perpendicular and quasi-parallel) were investigated. In addition, some of the events occurred during intervals in which Solar Energetic Particle (SEP) events were also ongoing, providing a background of pre-accelerated particles. The analysis of the shape of the observed spectra was used to identify which are the most plausible acceleration mechanisms at work. The turbulent magnetic field fluctuations upstream and downstream of the shocks were also studied to the aim of obtaining information about their possible role in particle acceleration.This research has been carried out in the framework of the CAESAR (Comprehensive spAce wEather Studies for the ASPIS prototype Realization) project, supported by the Italian Space Agency and the National Institute of Astrophysics through the ASI-INAF n. 2020-35-HH.0 agreement for the development of the ASPIS (ASI Space weather InfraStructure) prototype of scientific data centre for Space Weather.
Contrasting Responses of Heat Mitigation Strategies on Surface and Air Temperature and on Thermal-Stress Indices Deduced from Mesoscale Modelling
Authors: Leroyer Sylvie , Bélair Stéphane , Alavi Nasim , Nikiema Oumarou , Munoz-Alpizar Rodrigo , Popadic Ivana
Published: March 2024

With recent advances in subkilometric numerical weather prediction (NWP) for urban areas1, it has become possible to develop numerical platforms to assess landscape modifications and in particular heat mitigation scenarios in urban areas. One of the major barriers that exist for urban planners and health institutes to rely on such data is that they might be reluctant to consider the large amount of data produced by such numerical simulations.  This study aims at analyzing results in a more holistic approach, with the objectives of developing training data for statistical assessment of the impact of heat mitigation strategies in a particular city.In a recent study2, evaluations of scenarios for the urban landscape modifications were performed in Canada for Montreal and Toronto metropolitan areas with the Global Environmental Multiscale (GEM) atmospheric model with grid spacing of 250 m (with the Town Energy Balance TEB and the Interactions between the Soil, the Biosphere and the Atmosphere ISBA surface schemes) and applied during two overheating periods in 2010 when large impacts on the mortality rate were observed. More than 20 scenarios were assessed with realistic but ambitious scenarios, including increase of vegetation fraction with or without irrigation, and of thermal reflectivities. Various responses on the temperature reduction were found with an overall improvement, and down to -3 oC during the daytime, but negative effects were also found on the thermal stress during daytime when increasing albedo values.More insights into the results are provided in this study, using various normalized efficiency metrics, as for example those based on previous work3 and extended to the mean radiant temperature and to thermal stress indices computed in these experiments (UTCI and WBGT4).  Dependencies of the measures on the various environmental conditions will be presented and greening strategies will be analyzed in combination with the soil water availability. References:1.Leroyer, S., et al., 2022, https://doi.org/10.3390/atmos130710302.Leroyer, S., et al., 2019, https://doi.org/10.5281/zenodo.70757893.Krayenhoff, E.S., et al., 2021, https://doi.org/10.1088/1748-9326/abdcf14.Leroyer, S., et al., 2018, https://doi.org/10.1016/j.uclim.2018.05.003
Forecasting future volcanic activity in long time series orbital infrared data using machine learning
Authors: Thompson James , Ramsey Michael , Corradino Claudia
Published: March 2024

Well established baseline data are critical for volcanic change detection and forecasting associated hazards. High resolution thermal infrared (TIR) data captured synoptically over the entire volcanic system and spanning a long time period provide this forecasting capability for many volcanoes around the world. Foundational to these patterns is the subtle (1-2 K) thermal changes, which are easily overlooked using the current lower spatial resolution (1-2 km) TIR data. Therefore, despite decades of spaceborne data acquisition, orbital volcano science still lacks the fundamental ability to forecast a new eruption. Fortunately, several high spatial resolution TIR missions are planned for the coming decade and their data will be crucial to constrain volcanic activity patterns throughout the pre- and post-eruption phases. One of these is the Surface Biology and Geology (SBG) TIR instrument being jointly developed between NASA in the US and ASI in Italy. It is planned to have high spatial (~ 60 m) and much improved temporal (1-3 days) resolutions with the regular production of volcano-specific data products. In preparation for the data from these new missions, we conducted the first study using the entire data record of higher spatial, lower temporal resolution TIR data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. ASTER data are the most similar to SBG TIR and most critically, ASTER’s twenty-two-year archive presents a unique opportunity to quantify low-level temperature anomalies to establish baseline behavior. We developed a new statistical algorithm to automatically detect the full range of thermal activity and applied it to >5000 ASTER scenes of five volcanoes with well-documented eruptions. Unique to this algorithm is its ability to use both day and night data, account for clouds, and quantify accurate background temperatures by dynamically scaling depending on the anomaly size. Despite the less frequent temporal coverage of ASTER, the results are an improvement over prior studies that used lower spatial resolution data and show that high spatial resolution TIR data are more effective. Most significant was the finding that the smaller, subtle thermal detections served as precursory signals in ~81% of eruptions. These results also create a framework for classifying future eruptive styles and produced a labeled dataset for use with more advanced machine learning (ML) modeling. Using ML trained on the ASTER results, data from a sixth volcano that was not part of the original study were modeled and the thermally-elevated pixels accurately identified. This thermal anomaly detection approach will be incorporated into the SBG data processing stream to produce crucial daily orbital forecasting of the volcanic activity across the world.
The changing role of dust PM2.5  and its impact on Africa's air quality and human health
Authors: Aboagye-Okyere Adwoa
Published: March 2024

Aerosol pollution events pose serious threats to humans and ecosystems. Emissions from dust, fossil fuels and wildfires have increased in many places since preindustrial times globally in both urban and rural regions. Aerosol particles in these emissions directly alter the radiative budget of the atmosphere and modify snow and ice surface albedos when deposited on the surface. Aerosols also indirectly impact climate by modifying cloud properties and changing land and ocean biogeochemistry. In addition to these impacts, aerosols from dust, fossil fuels and wildfires pose major air quality and health concerns. Near-surface particulate matter (PM ) from aerosols are associated with negative health impacts, including premature mortality. Most studies have focused on anthropogenic emissions and their impacts on air quality. Natural aerosols are much less studied for their airquality impacts, even though dust and wildfires have likely changed because of anthropogenic activities and such changes have the potential to impact global mortality.This study seeks to understand how emissions of dust and wildfireaerosols (often referred to as natural aerosols) have changed over the African continent since the preindustrial era to the present day and how much they may signifcantly change in the future under the Coupled ModelInter comparison Project (CMIP) scenarios. Some studies have shown that global dust mass loading have increased by 55% since preindustrial times, with North Africa and Asia as the main drivers, while the frequency and severity of wild res has decreased signifcantly in recent decades, at least globally. The indirect effects of these changes on human health have not yet been adequately estimated. We will specifically consider the impact of changing aerosols on premature deaths and outdoor air quality, but do not consider potentially important changes to indoor air quality. This current study will use the latest Community Earth System Model (CESM) Community Atmosphere Model version 6 (CAM6) to simulate estimated preindustrial, present, and future scenarios of aerosol PM concentrations, including changes in dust and wildfires and apply a long-term concentration response function from epidemiological studies to estimate which aerosol sources are most important for changes in African mortality due to exposure. This study will also assess mortality changes due to differences in PM exposure between people in rural and urban communities. 
Mortality burden in 35 European countries attributed to anthropogenic warming during the record-breaking summer of 2022 
Authors: Beck Thessa M , Schumacher Dominik L , Vicedo Cabrera Ana M , Seneviratne Sonia I , Achebak Hicham , Ballester Joan
Published: March 2024

More than 61,000 heat-related deaths were associated with the record-breaking temperatures in Europe during the summer of 2022. In this study, we quantify the number of heat-related deaths that would have been avoided in the absence of anthropogenic warming.For this study, we utilize epidemiological models calibrated for the period 2015–2019 to estimate the heat-related mortality burden in the summer of 2022 for the factual and counterfactual scenario. We derive a counterfactual scenario by removing the regional summer mean warming that arises in response to rising global mean temperatures from the factual temperatures. We use ERA5-Land temperature data and mortality counts from the Eurostat database to estimate the heat-related deaths across 823 distinct administrative regions spanning 35 European countries. At 1.15 °C of global warming since pre-industrial times, we obtain a population-weighted median increase over all regions in Europe of more than 2 °C in summer mean temperatures, with the Mediterranean regions being most affected by the increase. By comparing the factual and counterfactual heat-related mortality, we estimate that approx. 70% [95th CI 53.33%– 82.17%] of the total heat-related deaths would not have occurred without anthropogenic warming. Southern Europe has been the most affected by dangerous heat and consequently features the highest number of heat-related deaths attributable to climate change [64.19% of the climate change-attributable deaths]. In relative terms, however, the impact of anthropogenic warming is strongest in Central Europe where approx. 78% of the heat-related deaths are attributable to anthropogenic warming.
Reduced terrestrial evaporation increases atmospheric water vapor by generating cloud feedbacks
Authors: Lague Marysa
Published: March 2024

Reduced terrestrial evaporation directly warms the surface by reducing latent cooling, but also indirectly modifies surface climate by altering atmospheric processes. We use a global climate model to explore two end cases of terrestrial evaporation, comparing the climate of SwampLand, a world where land is always fully saturated with water, to that of DesertLand, where land is always completely lacking in soil moisture. When we suppress evaporation to create a desert-like planet, we find that temperatures increase and precipitation decreases in the global mean. We find an increase in atmospheric water vapor over both land and ocean in the DesertLand simulation. Suppressing evaporative cooling over the continents reduces continental cloud cover, allowing more energy input to the surface and increasing surface moist static energy over land. The residence time of atmospheric water vapor increases by about 50 percent. Atmospheric feedbacks such as changes in air temperatures and cloud cover contribute larger changes to the terrestrial surface energy budget than the direct effect of suppressed evaporation alone. Without the cloud feedback, the land surface still warms with suppressed land evaporation, but total atmospheric water vapor decreases, and the anomalous atmospheric circulations over the continents are much shallower than in simulations with cloud changes; that is, the cloud feedback changes the sign of the water vapor response. This highlights the importance of accounting for atmospheric feedbacks when exploring land surface change impacts on the climate system.
Impact of landslide on the water supply capacity of the Shihmen Reservoir in Taiwan under climate change
Authors: Yeh Chia-Yen , Tung Ching-Pin
Published: March 2024

Climate change has altered precipitation patterns, significantly affecting water resources management and supply systems. Reservoirs, including Shihmen Reservoir in Taiwan, are particularly vulnerable due to changes in rainfall distribution and topographic factors, leading to sedimentation from events such as landslides and debris flows. These events pose direct and indirect threats to the water quality and supply capacity of reservoirs.The frequency of heavy rainfall events has increased, resulting in heightened soil and rock erosion. Consequently, a larger amount of sediment is entering the reservoir, degrading its water quality. Currently, Shimen Reservoir is operating at only 2/3 of its storage capacity, with 1/3 of the reservoir now filled with deposited silt. This situation poses a significant risk to future water supply.
To assess future rainfall trends at Shihmen Reservoir, we compared TCCIP statistical downscaling data for Taiwan with weather generation data. Our analysis focused on understanding the impact of landslide sediments on the storage capacity of Shihmen Reservoir and identifying potential risk indicators, including resilience, reliability, and vulnerability.
This study underscores the profound impact of climate change on Shihmen Reservoir, specifically highlighting the repercussions of rainfall failure on water quality and supply capacity.
A multiannual and global synergetic satellite product of tropospheric CH4
Authors: Shahzadi kanwal , Schnider Matthias , Ying Lo Nga , Mayer Jörg , Ugur Cayoglu , Hase Frank , Braesicke Peter , Borsdorff Tobias , Velarte Mari Martinez
Published: March 2024

Data products of atmospheric methane with improved vertical sensitivity in the lower troposphere are crucial for gaining a more comprehensive understanding of the impact of anthropogenic emissions. This study presents a methane data product derived from the synergistic combination of TROPOMI (Tropospheric Monitoring Instrument) total column and IASI (Infrared Atmospheric Sounding Interferometer) profiles, utilizing level 2 data spanning the period from 2018 to 2021. IASI enables high-quality retrievals in the upper troposphere-lower stratosphere, while TROPOMI observations excel in providing sensitivity to total-column-averaged CH4. The combined product retains the information from individual datasets and therefore enhances sensitivity to lower tropospheric signals independently of the upper troposphere, which is not achievable by using IASI or TROPOMI data alone.We present a method for optimally combining the IASI and TROPOMI level 2 data. Firstly, the products from the individual satellites are collocated in time and space (geomatching). Subsequently, the collocated data are optimally merged by fully considering the individual data characteristics (uncertainties and sensitivities) by the application of a Kalman filter. We show that the procedure is robust and computationally cheap, which allows the efficient combination of billions of IASI and TROPOMI observations, and the combined product offers good global coverage.The combined product is validated by comparison to reference datasets such as 14 globally distributed TCCON (Total Carbon Column Observing Network) stations, CH4 profile measurements made by 36 individual AirCore soundings, and tropospheric CH4 data derived from continuous ground-based in situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. These comparisons confirm the theoretically predicted quality of the combined data product, in particular the increased quality of the tropospheric CH4 data.Following the procedure outlined above, the final data product will consist of CH4 partial columns below and above 6000 m a.s.l. together with their respective averaging kernels and uncertainties and it will be made available as netCDF files that are compliant with version 1.7 of the CF metadata convention. 
Resuspension of intertidal cohesive sediment during the passage of extreme typhoons 
Authors: Ha Ho Kyung , Jeong Seong Woon , Ha Hun Jun , Khim Jong Seong
Published: March 2024

Typhoon is an extreme tropical storm, severely disturbing the coastal environments with strong winds and heavy precipitations. At the shallow intertidal flat, in particular, the typhoon can vigorously stir up the benthic sediment layers. To understand the effect of typhoons on the resuspension of intertidal cohesive sediment and phytoplankton, two in-situ moorings were installed at mud (M1) and mixed (M2) flats, the Muui Island. During the mooring period, four sediment erodibility experiments were conducted using Gust erosion microcosm system (GEMS). Two successive typhoons (Maysak and Haishen) generated strong wind stress up to 0.5 Pa, resulting in high suspended sediment concentration (SSC) (M1: 614 mg/l; M2: 434 mg/l), which is three times higher than that under fair weather. The Chl-a, as a proxy of phytoplankton, maintained low (< 6 mg/l) during the combined period of typhoon and neap tide. However, it drastically increased to 19 mg/l at the early stage of the spring tide. The response of SSC at the mud flat was different from that at the mixed flat because of the sediment composition. The GEMS experiments showed that the sediment erodibility of M2 (Erosion rate (E): 89.98 mg/m2 s; erosion threshold (tce): 0.0520 Pa) was higher than M1 (E: 4.08 mg/m2 s; tce: 0.2433 Pa). After the typhoon, the mud flat showed an abrupt increase and rapid recovery of SSC, whereas the mixed flat showed a gradual increase of SSC, and it maintained high SSC for relatively longer than the mud flat. The outcomes from this study suggest that the successive typhoons flushed out surface sediments, resulting in the tidal flat's ecologically “reset” condition. The low solar radiation and continuous high SSC prohibited phytoplankton from photosynthesizing, resulting in low Chl-a during the typhoons.
Creating a community testbed to strengthen the research to operations pathway for hydrologic prediction in the US
Authors: Wood Andy , Sturtevant Joshua , Van Werkhoven Katie , Denno Matthew , Hogue Terri
Published: March 2024

The US NOAA Cooperative Institute for Research to Operations in Hydrology (CIROH) is a consortium of several dozen US institutions (academic, private, non-profit) that collectively partner with the US National Water Center (NWC) to conduct research to advance operational hydrologic forecasting services.  This presention describes the new CIROH Hydrologic Prediction Testbed (CHPT), a community-oriented initiative to establish rigorous, quantitative intercomparison and benchmarking of US operational hydrologic forecasts, and particularly the multiple elements – models, methods, datasets – involved in producing them.  The Testbed’s overarching goal is to address the problematic lack of coherence of research into fundamental challenges and needs for operational prediction systems, which is a significant impediment to intercomparison, benchmarking, and synergistic learning across diverse investments into forecasting research and development. Hundreds of localized, one-off studies are published, yet few of the resulting potential advances ever become operational. The CHPT promotes a benchmark-oriented paradigm through facilitating the use of multiple community-based experimental protocols with standardized evaluation tools, targeting different forecasting and forecasting sub-component objectives. Examples of forecasting sub-components include the models, model parameterizations (e.g., glacier physics, channel routing), input datasets, and techniques (e.g., data assimilation, post-processing, ensemble methods), across time scales from nowcasting to multi-season prediction. This paradigm is essential to produce a consistent intercomparison and evaluation of innovations arising from distinct forecast-related research projects across the community.  This in turn supports a rational assessment of the potential gains of each innovation against current operational baseline capabilities. As it matures, the CHPT will enable the US to quantify and track the current performance of its hydrologic forecasting capabilities – for the first time – enabling evidence-driven decisions regarding the adoption of new forecast elements into operational practice. The core concepts of CHPT are generalizable to forecasting research and development activities in countries and communities globally.  
Links between seasonal precipitation intermittency and soil moisture variability
Authors: Kim Woon Mi , Simpson Isla , Deser Clara , Lehner Flavio , Pendergrass Angeline
Published: March 2024

Precipitation is an important control of soil moisture on land. Thus, many studies have focused on understanding the influences of mean or total precipitation variability on soil moisture. However, the relationship between precipitation intermittency (the temporal distribution of rainfall events) and soil moisture variability remains largely underexplored. This question requires more attention as climate models are known to be deficient in their representation of precipitation intermittency (PI), and PI is projected to increase in a future warmer climate, potentially affecting soil moisture variability. In this study, we examine the associations between seasonal PI and soil moisture (SM) across the globe in observation-based datasets (ERA5, MSWEP, and GLEAM) and model simulations (CESM2 Large Ensembles – LENS2) for the period 1981–2020. As a methodology to quantify the associations between PI and SM, we use a conditional regression analysis of 10cm soil moisture onto a metric of PI (reverted number of wet days in a season) after the removal of the influence of total seasonal precipitation from each variable. The result suggests that in many regions, higher PI leads to decreases in SM under the same amount of seasonal precipitation. These associations are explained by increased runoff under higher PI. Therefore, the spatial patterns of the magnitude and sign of the linkage between PI and SM align with the global patterns of PI-runoff interactions. Additionally, the regions where evapotranspiration (ET)–SM correlations are high (>0.5) present higher SM sensitivity to changes in PI. CESM2 exhibits spatial consistency in the PI–SM associations with ERA5, although noticeable differences exist in the magnitudes of the regression coefficients between the two datasets. In general, the PI–SM associations are weaker in CESM2. This disparity is attributed to the different runoff sensitivity to changes in precipitation and PI. CESM2 exhibits reduced runoff sensitivity to PI than ERA5 over the entire globe. This finding implies that how runoff is modeled and constrained in climate models will affect future projections of soil moisture.