bluuebunny/crossref_metadata_2025 huggingface dataset:
A new post-hoc method to improve the eddy-covariance-based evapotranspiration measurements
Authors: Zhang Weijie , Nelson Jacob , Miralles Diego , Mauder Matthias , Migliavacca Mirco , Poyatos Rafael , Reichstein Markus , Jung Martin
Published: March 2024

Terrestrial evapotranspiration (ET) is the nexus of the water, energy and carbon cycles, and therefore accurate quantification of ET is important for understanding the climate and the Earth system. However, current ET estimates derived from process-based models and remotely sensed observations are subject to significant uncertainty, a major reason for which is the limited availability and quality of ground validation data. The eddy covariance (EC) technique provides an excellent opportunity for continuous ET measurements at ecosystem scales with high temporal resolution (half-hourly or hourly resolution), and nowadays eddy towers are deployed in almost all types of terrestrial ecosystems and climatic conditions. Most EC-based ET estimates, however, suffer from an energy imbalance: the sum of sensible and latent heat fluxes is often lower than the available energy (i.e. the difference between net radiation and soil heat flux). The general consensus on the causes includes instrumental bias, missing stored fluxes, different footprints for different variables, and imperfect assumptions in the eddy covariance approach.In this presentation, we propose a generalised correction method (Zhang et al., 2023, 2024) across the site network. The method, statistical in nature, can improve the energy imbalance from ~80% to ~98% across the site network. The results are markedly better than those by the standard correction method implemented in the dataset processed by the ONEFlux pipeline, which tends to over-correct turbulent flux measurements. We further evaluate the corrected ET by comparing it with independent regional measurements in terms of spatial patterns and temporal variations, after upscaling the ecosystem-level data to the global scale using the latest FLUXCOM framework. The results show that the corrected ET-based upscaled estimates are closer to the ET derived from the water balance perspective and from the balloon-sounding observations. Our method provides a state-of-the-art alternative to improve the energy balance closure by correcting the site-level ET, and the improved global ET estimates can be of great value for water cycle studies and for model development.References:Zhang, W., Jung, M., Migliavacca, M., Poyatos, R., Miralles, D. G., El-Madany, T. S., . . . Nelson, J. A. (2023). The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation. Agric. For. Meteorol., 330, 109305. doi:10.1016/j.agrformet.2022.109305Zhang, W., Nelson, J. A., Miralles, D. G., Mauder, M., Migliavacca, M., Poyatos, R., Reichstein, M., Jung, M. (2024). A new post-hoc method to reduce the energy imbalance in eddy covariance measurements. Geophys. Res. Lett., (accecpted)
Characteristics and Results of Cloud Retrieval Algorithm for Geostationary Environment Monitoring Spectrometer
Authors: Kim Bo-Ram , Kim Gyuyeon , Cho Minjeong , Choi Yong-Sang
Published: March 2024

The cloud retrieval algorithm used by the Geostationary Environment Monitoring Spectrometer (GEMS) to monitor atmospheric conditions over East Asia is presented in this paper. In the UV-VIS range, cloud increase radiance and shorten the beam bath length. We defined cloud products as the effective cloud fraction, which represents the reflecting impact of clouds, and the cloud centroid pressure, which indicates the height at which clouds reflect. The absorption in the O2-O2 absorption band, which results from collisions of oxygen molecules in the atmosphere with generally constant concentrations, is used by the algorithm to determine the characteristics of clouds. Input data include observed radiance, irradiance, observation geometry, and surface information (reflectance and pressure). We evaluate the algorithm’s sensitivity to each input data. Moreover, we perform a monthly comparison and analysis of the actual cloud retrieval products acquired from GEMS with TROPOMI (Tropospheric Monitoring Instrument), investigating the algorithm's seasonality. Additionally, events showcasing prominent cloud features, such as high concentrations of air pollutants, typhoons, and sea fog, are chosen for performance evaluation through comparisons between GEMS results and those from TROPOMI, Advanced Meteorology Imager, and Cloud-Aerosol Lidar with Orthogonal Polarization. In comparing GEMS cloud retrieval results with those of other satellites, distinct variations based on land and ocean surfaces were observed, overshadowing the impact of seasonal differences. However, the CCP exhibited reduced accuracy during thick cloud in the summer season. This feature was consistently seen in event analysis, especially in cases of typhoons with diverse cloud shapes. In thin-cloud regions, CCP was comparable to other satellites; in thick-cloud regions, significant differences were seen. Besides, the investigation showed that GEMS had a tendency to identify clouds over highly reflective, low-altitude sea fog, resulting in CCP values that were comparable to surface pressure. This special quality made it possible to accurately characterize the characteristics of sea fog.
Tracing glacial weathering and pyrite oxidation using rare earth elements in sedimentary iron oxides
Authors: Jang Kwangchul , Bayon Germain , Pourret Olivier , Joe Young Jin , Kim Jung-Hyun , Byun Eunji , Forwick Matthias , León Rafael , Nam Seung-Il
Published: March 2024

Sulfide weathering plays a crucial role in driving the long-term carbon cycle on Earth, and thus its historical reconstruction is essential for a better understanding of the global carbon-climate feedback. In this study, we analyzed the abundance of rare earth elements (REE) within authigenic Fe-(oxyhydr)oxide phases in glacimarine sediments retrieved from the continental shelf offshore northern Svalbard, spanning over the last 16,300 years, to evaluate their potential as a novel tracer of sulfide weathering in source areas. The shale-normalized REE concentrations mostly showed strong mid-REE enrichment patterns over the entire period, characterized by a concavity index (CI) greater than 2.5. Such a high CI value distinctly deviates from typical measurements in authigenic phases of global marine/river sediments (1.0 < CI < 2.5) and exclusively occurs in acid mine drainage, minesoil leachates, or some authigenic river sediments known to be affected by intense sulfide weathering. In this context, we argue that the pronounced mid-REE enrichments with CI > 2.5 observed in northern Svalbard have resulted from prevailing sulfide oxidation linked to glacial weathering. This finding underscores a new approach of REE signatures in the authigenic phases of marine sediments for the past reconstruction of sulfide weathering over the geological time scale.
Characterizing life influence on Earth's mineralogy via mineral network analysis
Authors: Morrison Shaunna , Prabhu Anirudh , Hazen Robert , Wong Michael , Giovannelli Donato , Eleish Ahmed
Published: March 2024

Determining the habitability of planets remains a fundamental question in science and society. In this study, we harness network theory to explore the unique patterns exhibited by minerals and their mineralizing environments in both biotic and abiotic contexts throughout the evolution of Earth and other terrestrial bodies in our solar system [1-. By examining mineralogical networks across diverse planetary systems, including early solar system bodies, the early Hadean Earth (closely related to modern-day Mars), plate tectonics, and modern Earth, we gain valuable insights into Earth's history and the factors that have shaped the development and sustainability of life. Our investigation reveals distinct characteristics within biotic networks, setting them apart from their abiotic counterparts.This research significantly advances our understanding of the intricate interplay between Earth and life. Network analysis offers deeper insights into the connections between minerals and living systems, providing invaluable perspectives on the emergence and co-evolution of life on our planet. Moreover, our findings contribute to identifying and characterizing planetary biosignatures, essential for the search for extraterrestrial life. Recognizing these unique patterns within biotic networks lays the groundwork for developing targeted exploration strategies for detecting potential biosignatures and interpreting the complexities of planetary environments.Our innovative network analysis of minerals and mineralizing environments sheds new light on the relationships between Earth and life. By delving into the intricate connections within biotic and abiotic systems, we deepen our understanding of Earth's dynamic history and enhance our knowledge of potential habitats for life beyond our planet.
Evaluation of the applicability of simulation tools for conjunctive water management with a focus on induced groundwater recharge
Authors: Hernandez Hernandez Mario Alberto , Navarro Farfán María del Mar , García Ledesma Israel Alejandro , Correa Gonzalez Alejandra
Published: March 2024

Water availability in sufficient quantity and quality is increasingly challenging in countries with limited water resources, such as Mexico. The present work takes as a case study the Río Grande in the Morelia Basin (Michoacán), widely studied in the functioning of its surface hydrology and with less detail in the groundwater. A review of potential sites for the implementation of induced recharge zones is presented, considering different methods, including the use of excess rainfall peaks, their conduction and temporary storage in infiltration ponds, the estimation of induced recharge volumes that micro-basins, irrigation returns and treated wastewater can capture. All induced recharge options are evaluated in a pre-existing conjunctive water management tool, and the improvement in water availability conditions in the water system of the study basin is discussed. A base scenario and induced recharge proposals are evaluated by quantifying the costs associated with their implementation.
Assessing the Influenced Zone of Debris Flow Using Numerical Simulation
Authors: Wei Kai-Lun , Liao Kuo-Wei , Lin Guan-Yu , Lin Poshuan , Hsieh Tsungyu
Published: March 2024

Taiwan is located at the boundary between the Philippine Sea Plate and the Eurasian Plate, characterized by steep terrain and high river gradients. Combined with frequent events such as typhoons leading to substantial rainfall, this has resulted in disasters like debris flows. Several available tools such as HEC-RAS two-dimensional hydraulic, SRH-2D, FLO-2D and FLOW-3D are used to analyze the area of flooding and the impact of debris flow in the watershed. The simulation results are compared with historical disaster data to validate the feasibility of model. Furthermore, the results are used to evaluate the suitability of current government-designated evacuation locations and routes.Among several analysis tools, the debris flow modeling in HEC-RAS two-dimensional hydraulic is considered as the best platform to analyze debris risk. The results show the sections of evacuation routes on the left bank of the downstream area near the estuary pass through the debris flow impact area. However, there is no suitable evacuation facility in the vicinity. Therefore, during warning issuance, residents need to be cautious and evacuate promptly. On the other hand, collaboration with government authorities can be pursued to establish new shelters or activity centers nearby, serving as alternative evacuation sites.
Fast and Accurate Calculation of Wet-bulb Temperature for Humid-Heat Extremes
Authors: Rogers Cassandra , Warren Robert
Published: March 2024

It is well known that heat extremes have increased in frequency, intensity, and duration over recent decades. However, since extreme heat is typically examined using dry-bulb temperature, the reported changes do not fully reflect the impacts these events may have on human health. By accounting for humidity in measures of extreme heat, we can gain a better understanding of the health risk associated with these events in current and future climates.  

  

A variety of indices are used to examine humid heat. One of the simplest is wet-bulb temperature (Tw), which is defined as the temperature of a parcel of air cooled to saturation by the evaporation of water into it. Tw is typically calculated using empirical equations (e.g., Stull 2011, Davies-Jones 2008); however, these can be inaccurate for extreme values or slow due to the need for iterations in the solution. Here, we present a fast and highly accurate calculation of Tw, which we call NEWT (Noniterative Evaluation of Wet-bulb Temperature). This method follows the diagrammatic approach to evaluating Tw, where a parcel is lifted dry adiabatically to its lifting condensation level (LCL) and then brought pseudoadiabatically back to its original level. To avoid the need for iterations, NEWT uses exact equations for the LCL from Romps (2017) and a modified version of the high-order polynomial fits to pseudoadiabats from Moisseeva and Stull (2017).  

  

A comparison of NEWT with three other methods for calculating Tw (Stull, MetPy, and Davies-Jones) reveals a marked improvement in accuracy, with maximum errors of ~0.01°C (cf. ~1.3°C for Stull, ~0.4°C for MetPy, and ~0.05°C for Davies-Jones). The accuracy of each method is further assessed using Automatic Weather Station data from the Bureau of Meteorology, with a focus on extreme values. 
Decoding Cryptic Population Structures using Stable Isotope Markers
Authors: Bowen Gabriel , Brennan Kyle , Brennan Sean , Cline Timothy
Published: March 2024

Life-history diversity has been shown to contribute to the resilience of species but can be challenging to quantify, particularly where intra-population genetic structure is lacking. Such is the case for salmon within many fisheries of the North American Pacific Northwest, where the resolution of genetic markers is variable and limited. For Sockeye salmon (Oncorhynchus nerka) within the U.S.-Canada transboundary Taku Watershed, for example, single-nucleotide polymorphisms have successfully distinguished populations associated with specific inland lakes but allocates many individuals to an undifferentiated “River Type” stock. The extent and dynamics of geographic structure within this stock, and thus its potential contribution to the fishery’s resilience, remain unresolved.In such cases, intrinsic non-genetic markers that record key aspects of life history, such as the isotope ratios of body tissues, can provide valuable information on population structure and diversity. We combined a recently published stream network model for strontium stable isotopes (87Sr/86Sr) with otolith (ear stone) microchemistry data to infer the geographic natal origins of 45 adult fish captured during the 2019 run. Our analysis was implemented in a Bayesian framework and leveraged radio tag data as a source of prior information. We distinguish 4 previously undifferentiated sub-populations within the River Type stock, characterized by groups of fish with distinct natal 87Sr/86Sr values and, by inference, natal habitat locations. Although data from additional years will be needed to assess the persistence of these patterns, the result implies potential for previously unrecognized geographic structure within the River Type stock as a contributor to resilience within the population. The lack of genetic differentiation among the subpopulations may suggest that plasticity of habitat use is prevalent and contributes to adaptation. Alternatively, individuals may exhibit strong site fidelity, but differentiation of these sub-populations may be relatively recent or obscured by gene flow. Distinction between these hypotheses should be resolvable by applying the Sr-isotope method to fish recovered across multiple years.
Unbiased fully nonlinear data assimilation: the Stochastic Particle Flow Filter
Authors: Yeh Hao-Lun , van Leeuwen Peter Jan
Published: March 2024

Nonlinearities in numerical models for the geosciences and in observation operators that map model states to observation space have become so strong that they can no longer be ignored. The particle flow filter (PFF) is a fully nonlinear and efficient sequential Monte Carlo filter that removes the weight degeneracy problem in particle filters by iteratively transporting the equal-weighted particles from the prior to the posterior distribution. The deterministic version of the PPF has been successfully applied to high-dimensional systems and is unbiased in the limit of an infinite number of particles. However, with a small number of particles, the ensemble spread can be biased low, especially in the observed part of the state space. This can be partly alleviated by using a so-called matrix-valued kernel in the algorithm, but the fundamental issue remains. To address this challenge, we propose a novel approach, the Stochastic Particle Flow Filter (SPFF), which includes a Gaussian noise in the Stein Variational Gradient Descent dynamics, the amplitude and covariance of which follow directly from theory. With this additional repulsive force between particles, the SPFF guarantees an unbiased posterior pdf, even with a finite number of particles.We demonstrate the performance of the SPFF using detailed experiments with the 1000-dimensional Loreanz-96 model. Our results demonstrate that SPFF successfully avoids particle collapse of the marginal distributions and accurately captures the evolutions of particles Additionally, and initially unexpectedly, the SPFF exhibits faster convergence than the deterministic PFF and thus improves analysis accuracy compared to the PFF with a matrix-valued kernel at the computational cost. We also show results of its performance on a high-dimensional ocean model demonstrating that we, as a community, are very close to solving the nonlinear data assimilation problem.
Impacts of hydrological extremes in a mountainous forest catchment: Experiences from the Harz mountains, Germany
Authors: Wagner Paul , Fohrer Nicola
Published: March 2024

The Harz mountains in Germany have experienced floods and droughts in recent years. On the one hand, a major flood event affected the city of Goslar in 2017, and on the other hand, drought conditions since 2018 have led to tree mortality in the forested catchment area upstream. The frequency of such extreme events is expected to increase as a result of climate change. Here, we aim at assessing the impacts of the ongoing tree mortality on hydrology. To this end, we employ the ecohydrological model SWAT+ to assess changes in water balance components. The model is specifically calibrated for extreme conditions by evaluating the model performance for different segments of the flow duration curve. Satellite-derived changes in forest cover are used to assess the impact on water balance components. The analysis of the model performance indicates that the calibration strategy improved model performance for drought conditions. Furthermore, first model results indicate that tree mortality led to a decrease in evapotranspiration and an increase in surface runoff. The spatial assessment suggests stronger effects at the sub-catchment scale than at the catchment scale. However, the faster response of the catchment due to tree mortality potentially increases the severity of flood events and the flood risk in downstream areas. Therefore, afforestation with climate-resilient trees is needed to improve both flood and drought resilience in the Harz mountains.
Combining mechanistic modelling and observations to characterize carbon and water fluxes in mainland Southeast Asia
Authors: Ren Jianning , Luo Zhaoyang , Galelli Stefano , Fatichi Simone
Published: March 2024

Tropical forests account for approximately one-fourth of the global terrestrial carbon sink, playing an important role in the Earth’s carbon cycle. Importantly, mainland Southeast Asia has the densest vegetation surface but its ecohydrology is historically understudied due to the paucity of field observations and modelling studies. Leveraging on existing flux tower data, remote sensing products, and the mechanistic ecohydrological model T&C, we provide an enhanced understanding of carbon and water exchanges in mainland Southeast Asia. The T&C model is tested to reproduce various ecosystem types of Southeast Asia, including tropical evergreen forests, subtropical deciduous forests, savannas, rubber plantations, and rice fields. The flux tower data including gross primary productivity (GPP) and evapotranspiration (ET) along with remote sensing data of leaf area index and other vegetation indexes, allow us to better refine and constrain model simulations.  With the integration of data and model, we provide a comprehensive picture of spatiotemporal patterns and key drivers of carbon and water fluxes in mainland Southeast Asia. Our findings highlight a strong latitudinal gradient in carbon fluxes and ET associated with seasonality of rainfall as well as an important role of vapour pressure deficit (VPD) and soil moisture content with different responses in wet and dry years. Direct effects of temperature and precipitation are relatively smaller when compared to VPD and soil moisture in driving changes of carbon and water fluxes. These findings, combined with our model framework, pave the road to more accurate predictions of ecohydrological variables in the relatively understudied region of mainland Southeast Asia.
Potential of diatoms in sediments as seeds for autumn blooms in the Pacific Arctic shelf
Authors: Fukai Yuri , Fujiwara Amane , Nishino Shigeto , Matsuno Kohei , Suzuki Koji
Published: March 2024

The Pacific gateway to the Arctic has a vast continental shelf spanning the northern Bering and the Chukchi Seas. Within this shelf region, diatoms are crucial in sustaining high primary production and facilitating the sinking particulate organic carbon flux from spring to summer. Consequently, the bottom sediments have abundant viable diatoms, including resting stages. Despite the importance of diatoms, our understanding of the dynamics of this organism in sediments and their capacity to initiate primary production in the Pacific Arctic shelf remains limited.In this study, we delved into the photophysiological capabilities of diatoms in the surface sediments collected from the Chukchi Sea in autumn through a laboratory incubation experiment at 3°C under the light conditions of 300 or 30 µmol photons m-2 s-1 for seven days. This experiment revealed that diatoms, mainly Chaetoceros, quickly resumed photosynthesis after light exposure and reached the maximum photosynthetic carbon fixation rates within only several days. These results suggest that diatoms in sediments have a significant potential to function as “seeds” for bloom formation in the sunlit water column. We further examined diatom communities, including resting spores, in the water column of the Chukchi Sea during autumn using scanning electron microscopy (SEM) and DNA metabarcoding techniques, as well as environmental parameters. Consequently, intense winds and subsequent water turbulence in the shallow Chukchi caused the predominance of Chaetoceros resting spores, probably derived from the sediments, in the diatom assemblages. As speculated from the incubation experiment mentioned above, diatom resting spores from the sediments can germinate immediately in the water column. Thus, settled diatoms could work as seeds for subsequent autumn blooms by being supplied from the seafloor along with nutrient-rich water.The recent delayed sea ice formation in the autumn Arctic leads to increased storm occurrence over open water and enhanced vertical mixing, resulting in more frequent autumn blooms. Therefore, diatoms in sediments could be one of the critical contributors to autumn blooms in the shallow Pacific Arctic.
Spatiotemporal Variation of DOM Concentration and Composition along the Subtropical Small River Continuum in Taiwan
Authors: Lee Li-Chin , Huang Jr-Chuan , Weigelhofer Gabriele , Hein Thomas , Yu Yu-Lin , Chen Pei-Hao
Published: March 2024

The fate and reactivity of dissolved organic matter (DOM) in river networks is critical to understanding carbon cycling in inland water systems, and is highly regulated by physio-geographic factors and water residence time (WRT). In this study, we investigate the spatiotemporal variation of DOM concentration and composition in two SMRs in Taiwan with different landscapes and anthropogenic impacts. The WRT for these two rivers, the Keelung and Lanyang River, are around 34 and 23 hours, respectively. Dissolved organic carbon (DOC) concentration measurements and optical analyses (absorbance and fluorescence) were used to examine DOM quantity and quality along the river continuum. The comparative results showed that, along the SMR continuum, the DOC concentrations and optical indexes exhibited slight changes, with significant increases observed only at downstream sites influenced by human activities. Meanwhile, the higher biological index (BIX) and lower humification index (HIX) indicated an increase in autochthonous sources and a decrease in the degree of humic characters. In addition, we observed a positive correlation between WRT and DOC concentration variability, yet not significant for DOM compositions. When comparing the two rivers, the one with steeper topography and less human influence shows lower levels of DOC concentration and degree of humification. Overall, the SMRs seem to have lower DOC concentrations (0.26 - 1.65 mg-C L-1), lower HIX (0.28 - 0.76), and slightly higher BIX (0.8 - 1.9) on a global scale, which might be attributed to Taiwan's steep landscape and shorter water residence time, limiting soil organic carbon (SOC) production and in-stream processes rates. Through our investigation, DOC concentration and DOM composition across river networks will be better understood and potentially improve the assessment of the global carbon cycle.
How remote sensing contributes to flux upscaling in natural bog ecosystems – a case study in Estonia
Authors: Schindler Thomas , Brovkina Olga , Machacova Katerina , Mander Ülo , Soosaar Kaido
Published: March 2024

The research potential to investigate and monitor a peatland site is often limited by difficult accessibility to the site, and a heterogeneous surface with diverse topography, hydrological features, and vegetation. Satellite remote sensing (RS) methods offer the advantage of past-to-present repeating cover research areas compared to field studies. Our case study examined the potential usability of applied satellite RS methods to determine greenhouse gas (GHG) fluxes in natural peatlands. Specifically, we tested several landscape indices on their correlation to GHG fluxes and basic environmental parameters. The field campaign was carried out from 13.7.2018 to 24.7.2019 in a natural raised bog covered with young pine trees in central Estonia, measuring carbon dioxide (CO2) and methane (CH4) fluxes with manual static chambers, soil temperature, soil moisture, and the water table. The measured air temperature was provided by the nearest meteorological station.  Land surface temperature (LST) was calculated from satellite Landsat-8 data using open-source code in Google Earth Engine cloud-based service. Normalized Difference Vegetation Index (NDVI), Water Index (NDWI), and Snow Index (NDSI) were calculated from Sentinel-2 data. The relationships between LST and indices with field-measured parameters were explored. Peatland site land covers were mapped using Sentinel-2 data supervised classification into dense trees, sphagnum mosses and grasses, and open water classes. The dynamics of open water locations were estimated based on the distribution of land covers for each month of study period. Our correlation analysis reflected different in-situ GHG dynamics throughout the investigated period and the micro-spatial heterogeneity of the land surface, with naturally wetter and dryer spots. The preliminary results show a close relationship between the in-situ measured CO2 fluxes and LST. The CO2 fluxes were further correlated with CH4 fluxes. Distribution of land covers from RS can significantly improve the GHG flux upscaling process. Thus, the obtained results can further help to identify locations in peatlands with the highest risks and priorities to provide detailed in situ monitoring.Acknowledgements:This work was supported by the Ministry of Education, Youth and Sports of CR within the CzeCOS program (grant number LM2023048) and project AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation (CZ.02.01.01/00/22_008/0004635).
Deep learning to predict time to failure of lab foreshocks and earthquakes from fault zone raw acoustic emissions
Authors: Laurenti Laura , Johnson Christopher , Tinti Elisa , Galasso Fabio , Johnson Paul , Marone Chris
Published: March 2024

Earthquake forecasting and prediction are going through achievements in short-term early warning systems, hazard assessment of natural and human-induced seismicity, and prediction of laboratory earthquakes.In laboratory settings, frictional stick-slip events serve as an analog for the complete seismic cycle. These experiments have been pivotal in comprehending the initiation of failure and the dynamics of earthquake rupture. Additionally, lab earthquakes present optimal opportunities for the application of machine learning (ML) techniques, as they can be generated in long sequences and with variable seismic cycles under controlled conditions. Indeed, recent ML studies demonstrate the predictability of labquakes through acoustic emissions (AE). In particular, Time to Failure (TTF) (defined as the time remaining before the next main labquake and retrieved from recorded shear stress) has been predicted for the main lab-event considering simple AE features as the variance.A step forward in the state of the art is the prediction of Time To Failure (TTF) by using raw AE waveforms. Here we use deep learning (DL) to predict not only the TTF of the mainshock with raw AE time series but also the TTF of all the labquakes, foreshocks or aftershocks, above a certain amplitude. This is a great finding for several reasons, mainly: 1) we can predict TTF by using traces that don’t contain EQ (but only noise); 2) we can improve our knowledge of seismic cycle predicting also TTF of foreshocks and aftershocks.This work is promising and opens new opportunities for the study of natural earthquakes just by analyzing the continuous raw seismogram. In general laboratory data studies underscore the significance of subtle deformation signals and intricate patterns emanating from slipping and/or locked faults before major earthquakes. Insights gained from laboratory experiments, coupled with the exponential growth in seismic data recordings worldwide, are diving into a new era of earthquake comprehension.
Quantifying leaks with a field-deployable, fast, sensitive hydrogen instrument
Authors: Lunny Elizabeth , Wehr Richard , Roscioli Joseph , Daube Conner , Shorter Joanne , Sun Tianyi , Long William , Momeni Ahmad , Albertson John , Herndon Scott , Nelson David
Published: March 2024

Accurate quantification of leaks associated with hydrogen transport and storage infrastructure is vital to evaluate the environmental benefit associated with the transition from fossil fuels to hydrogen as an energy source. Understanding the locations and magnitudes of leaks is critical in efforts to mitigate the indirect climate impact of transitioning to a hydrogen economy. Quantification of hydrogen leaks requires a field-deployable, fast, sensitive measurement technology which, until recently, has not existed. We have developed a novel inlet system which couples to an Aerodyne tunable infrared laser direct absorption spectrometer (TILDAS) to measure hydrogen with
Exploring dynamics of Indian summer monsoon rainfall trends asymmetry: An event in early twentieth century warming and mid-twentieth century cooling episode
Authors: Chakra Swagatika , Oza Harsh , Ganguly Akash , Pandey Amit , Padhya Virendra , Deshpande Rajendrakumar Dattatraya
Published: March 2024

The shifting pattern of Indian summer monsoon rainfall (ISMR) holds paramount importance on a global scale, demanding urgent attention due to its profound impact on freshwater availability, food production, and the economy of India, which is home to ~18% of the global population. The notable decline and subsequent recovery of ISMR during recent global warming and subsequent hiatus (from the 1970s onwards) have been associated with diminished and amplified land-sea thermal contrast, resulting from accelerated anthropogenic interventions. A similar global warming trend followed by a hiatus is also present in history called Early Twentieth Century Warming (ETCW) and Mid-Twentieth Century Cooling (MTCC), respectively. Examining the spatial variability of ISMR trends during this period and comprehending the dynamics behind such variability is crucial for understanding the current and future climate.
To achieve this objective, the analysis focuses on district-wise summer monsoon rainfall patterns in four rainfall homogeneous regions across India (South Peninsula, Central, Northwest, Northeast), employing the established method of Chakra et al. 2023. Notable increasing rainfall trends are observed in the South Peninsula and Northwest India, contrasting with an opposite trend in Northeast India, covering more than one-third of the regions between the 1930s and 1960s. Central India also experiences an increasing trend during this period but over a limited area. This spatial heterogeneity in rainfall trends contributes to an east-west rainfall trend asymmetry in India, prompting further exploration for understanding causal processes.
An increase in wind strength is noted in the Arabian Sea and the southern Bay of Bengal, while a decrease is observed in the Northern Bay of Bengal. The wind updraft rate varies across the Indian region, with a higher rate over the Arabian Sea and southern Bay of Bengal, and a lower rate in northern India and the Tibetan Plateau. Analysis of surface temperature trends reveals a higher warming rate in the northern tropical Indian Ocean compared to the southern tropical Indian Ocean. This difference resulted in a meridional thermal contrast conducive to a stronger Hadley circulation, bringing increased rainfall to the western part of the Indian region. Concurrently, the cooling trend over northern India and the Tibetan plateau led to weak updraft and increased downdraft, ultimately reducing wind strength over the northern Bay of Bengal, and creating unfavorable conditions for rainfall over the Northeast region. Hence, the east-west asymmetry in the trend of ISMR is linked to the latitudinal disparity in temperature trends during the periods of Early Twentieth Century Warming and Mid-Twentieth Century Cooling.
Landscape and Burn Severity Controls on Post-fire Snowpack Response in Montane Forests 
Authors: Rey David , Sexstone Graham
Published: March 2024

Wildfire is becoming a more common landscape disturbance in snow-dominated watersheds as burned area extents have increased within high elevation areas that store key snow-water resources for down-stream communities. In snow-dominated watersheds, fire modifies the surface-energy budget that controls, in part, the magnitude and timing of snow accumulation and ablation. While there is growing recognition of fire-induced changes to seasonal snowpack dynamics, post-fire hydrologic studies have generally focused on changes in water quality or stream discharge as opposed to downstream impacts of fire-modified accumulation and ablation. To bridge these gaps, we use a combination of remotely sensed (i.e., satellite, fixed-wing), continuous plot-scale radiative and meteorological observations, and synoptic snow surveys to evaluate snowpack response to wildfire across a range of elevations, aspects, and canopy disturbances at several snapshots in time, and at eight continuously monitored north-south paired study sites. This approach demonstrated that topographic controls on snow distribution such as elevation and aspect still exhibit a stronger control on post-fire accumulation and ablation than wildfire induced changes. Nuanced radiative feedbacks also drove non-intuitive snow distribution patterns across burn-severities, particularly in areas where canopy was only partially combusted. In contrast, regions of lower burn severities where canopy remained unaffected, experienced insignificant changes in post-fire snow accumulation and ablation. Given the rising prominence of wildfire as a key land surface disturbance in snow-dominated watersheds, this work addresses key knowledge gaps currently inhibiting seasonal and long-term prediction of fire’s impact on snow water resources across burn-severities. 
Saltwater intrusion may aggravate carbon loss from tropical peatlands
Authors: Akhtar Hasan , Jaafar Salwana M. , Sukri Rahayu S. , Lupascu Massimo
Published: March 2024

Tropical peatlands, covering approximately 23 million hectares, constitute 6% of the global peatlands, predominantly situated in low-lying coastal regions of Indonesia, Malaysia, Borneo, and Papua. Unfortunately, due to land-use change and accompanying subsidence, these low-lying coastal peatlands may be inundated with seawater due to sea level rise in response to climate warming in the coming decades. This would not only result in carbon losses in fluvial form but may also alter the biogeochemistry of peat, thereby affecting the peat decomposition process. Therefore, in this peat incubation study, we attempted to simulate the effect of saltwater intrusion on CO2 emissions under a factorial setup of two salinity levels (15 ppt, 30 ppt), tidal cycle (high tide as flooded peat vs low tide as mesic peat), and labile carbon mimicking plant root exudates (in the form of glucose addition @ 0.1 mgC/g of peat/day) with peat incubated at 28 °C (the long-term average temperature at site).            We found that salinity and carbon addition significantly (p < 0.01) affected the rate of CO2 emissions with the highest mean values for treatment with 30 ppt salinity (251.7 ± 61.3 mgCO2/g of peat/hr), which was approximately three times higher than the control (72.3 ± 9.3 mgCO2/g of peat/hr). Similarly, we found that the mesic peat (reflecting low tide) showed almost twice the mean CO2 values (150 ± 36 mgCO2/g of peat/hr) compared to flooded peat (79.9 ± 15.1 mgCO2/g of peat/hr). These results underscore the vulnerability of these ecosystems to future sea level rise, potentially transforming them into a significant carbon source. The urgency to conserve these vital terrestrial carbon reserves is further emphasized by the implications of our study, emphasizing the need for proactive measures to mitigate the impact of land use and climate change on tropical peatlands.
Understanding cloud structures with machine learning- An algorithm to represent sub-grid scale variability in stratocumulus clouds 
Authors: Allwayin Nithin , Larsen Michael , Shaw Alexander , Chandrakar Kamal Kant , Glienke Susanne , Shaw Raymond
Published: March 2024

Changes to low-level cloud properties and their associated feedback in a warming climate are a significant source of uncertainty in global climate models (GCMs). “Local’’ processes at the droplet scales, such as drizzle growth by collision-coalescence, are not well represented in GCMs and constitute a significant uncertainty in model predictions. Parameterization schemes often derived from empirical fits to spatially averaged cloud size distributions have been used to represent clouds and hence do not fully account for the subgrid-scale variabilities. We hypothesize that inhomogeneities in cloud microphysical properties may be captured by a small number of distinct droplet size distributions called “characteristic distributions” and developed an algorithm capable of retrieving them.To do this, we developed an algorithm by combining hypothesis testing with a machine-learning clustering algorithm. The test does not presume any specific distribution shape, is parameter-free, and avoids biases from binning. Importantly, for the clustering algorithm, the number of clusters is not an input parameter but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the hypothesis test results, and hence spatial correlation is not fundamental for members classified to a characteristic distribution. To validate the algorithm's robustness, we test it on a synthetic dataset that mimics cloud drop distributions. The algorithm successfully identifies the predefined distributions at plausible noise levels.When implemented on cm-scale cloud samples taken using Holographic Detector for Clouds (HOLODEC) deployed during Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), the algorithm reveals that local characteristic distribution types are ubiquitous in stratocumulus clouds. These distribution types are generally narrow with distinct modes and do not resemble the averaged size distribution shape. Each characteristic distribution represents identical-looking local cloud volumes which tend to occur in spatial blocks of varying extent, usually of order 1s to 10s of km. These observations have implications for understanding small-scale cloud properties and can guide the development of novel parameterizations of sub-grid-scale variability for coarse-resolution models. Subsequently, we show the first results from an investigation of characteristic distributions for LESs. The algorithm is general and helps in finding similarities in data representable as CDFs and is expected to have broader applicability in earth sciences.
Counting the contributions of tides and surges to changing coastal flooding
Authors: Palmer Karen , Watson Christopher , Power Hannah , Hunter John
Published: March 2024

Globally, the frequency of high tide exceedances is increasing with sea level rise. However, the rate of mean sea level (MSL) alone is not enough for estimating changes in coastal flooding. Understanding the drivers of changing exceedance frequency must also factor in additional contributions from tides and surges, accounting for the importance of local variability and interactions. Our novel Joint Probability of Maxima Method represents these complex processes nonparametrically, efficiently enabling the estimation of exceedance thresholds at user defined average recurrence intervals (ARIs). We compared exceedance levels between two recent 19-year epochs for 166 widely distributed coastal tide gauge sites, at 1, 5, and 10 year ARIs. We then quantified the specific contributions of MSL, tide, and skew surge components to the net changes in exceedance levels in metric terms, relating them directly to the height of coastal protections. Our approach demonstrates that high water exceedance levels are, on average, increasing more than MSL alone, and that changing exceedance frequency can depend significantly on local characteristics of sea level variability. On average, exceedance frequency doubled over the epochs assessed.
Quantitative attribution of Northern Hemisphere summer temperaturesover the past 2000 years
Authors: Shi Feng
Published: March 2024

Quantitative assessment of natural internal variability and externally forced responses of Northern Hemisphere (NH) temperatures is necessary for understanding and attributing climate change signals during past warm and cold periods. However, it remains a challenge to distinguish the robust internally generated variability from the observed variability. Here, large-ensemble (70 member) simulations, Energy Balance Model simulation, temperature ensemble reconstruction, and three dominant external forcings (volcanic, solar, and greenhouse gas) were combined to estimate the internal variability of NH summer (June–August) temperatures over the past 2000 years (1–2000 CE). Results indicate that the Medieval Climate Anomaly was predominantly attributed to centennial-scale internal oscillation, accounting for an estimated 104% of the warming anomaly. In contrast, the Current Warm Period is influenced mainly by external forcing, contributing up to 90% of the warming anomaly. Internal temperature variability offsets cooling by volcanic eruptions during the Late Antique Little Ice Age. Ultimately, this study indicates that the dominant internal climate factor driving centennial-scale fluctuations in NH summer temperatures over the last two millennia has been the AMOC, and that the primary external forcing agent is volcanic activity. These findings have important implications for the attribution of past climate variability and improvement of future climate projections.
Cooling effect of mesoscale SST perturbations induced rotational wind in the Kuroshio Extension
Authors: Wei Yanzhou
Published: March 2024

Mesoscale SST perturbations induced wind stress field perturbations have feedback effect on the ocean through influencing air-sea heat and momentum fluxes. Unlike the thermal feedback mechanism that is well understood, momentum feedback still needs to be studied, especially about the respective roles of divergent and rotational wind components. In this study, momentum feedback was examined using an ocean model and an empirical equation, which solved wind stress field perturbations from their divergence and curl that were estimated from time-evolving downwind and crosswind SST gradients. Through several numerical experiments, it was found that the divergent wind can induce positive and negative SST changes at varying regions and depths. On the contrary, the rotational wind can cool the upper ocean and reduce SST by 0.1°C on average.