bluuebunny/crossref_metadata_2025_split huggingface dataset:
Magnitude and Interevent Time Statistics of Strombolian Activity of Villarrica Volcano and Inference Regarding the Flow Regime
Authors: Lehr Johanna , Rabbel Wolfgang 
Published: September 2021

AbstractThe different flow regimes of two‐phase gas‐in‐liquid flow—as it occurs in the shallow conduit of basaltic volcanoes—are characterized by distinct frequency‐size distributions of the liquid and gaseous slugs. Assuming that the ascent of gaseous bubbles is indicated by seismic events, we explore the possibility of inferring the flow regime from the frequency distributions of magnitudes and interevent times. Our data set consists of 20,000 volcanic seismic events recorded in early March 2012 at Villarrica Volcano (Chile), which are commonly attributed to Strombolian activity. One crucial factor is the completeness of the catalog in terms of detectable amplitudes, which we assess using a stochastic simulation of the network output based on statistical properties of the ambient seismicity. Magnitudes, at which we consider the catalog complete, show an exponential occurrence. Yet, the simulation approach indicates that low magnitude events occur indeed more sparsely than expected for an exponential distribution, and that the magnitude distribution does not obey the Gutenberg‐Richter law. Interevent times are log‐normally distributed, which implies a preferred recurrence interval. The distributions are consistent with a slug flow regime. They correlate weakly with the preceding magnitude, suggesting that slugs coalesce while ascending.
Seismoelectric and Electroseismic Modeling in Stratified Porous Media With a Shallow or Ground Surface Source
Authors: Zheng Xu‐Zhen , Ren Hengxin , Butler Karl E. , Zhang Haiming , Sun Yao‐Chong , Zhang Wei , Huang Qinghua , Chen Xiaofei 
Published: September 2021

AbstractFor a shallow or ground surface source and receiver at the same level or close depth, it is very difficult or computationally inefficient to simulate seismoelectric or electroseismic wave‐fields in stratified porous media by current reflectivity methods, such as the Luco‐Apsel‐Chen generalized reflection and transmission method (LAC GRTM). In this work, the peak‐trough averaging method which has been proved effective and efficient in dealing with this kind of computational problem is adopted to update the seismoelectric and electroseismic modeling algorithm based on LAC GRTM. After thoroughly verifying the accuracy and computational efficiency of the updated algorithm, we utilize it to numerically investigate both the electroseismic and seismoelectric couplings. Snapshots of electroseismic wave‐fields indicate evanescent electroseismic conversion, a reverse process of evanescent seismoelectric conversion, dominates at relatively larger ratios of seismic wavelength to interface depth, whereas the interfacial radiation electroseismic conversion is more prominent for the opposite situation. Our seismoelectric modeling results demonstrate that electric signals can arrive at the ground surface a few milliseconds earlier than their causative seismic signals due to evanescent seismoelectric conversion. This is the first modeling result considering source‐receiver geometries on the surface capable of explaining similar phenomena reported in geophysical field observations of seismically induced electrokinetic effects over a long history. The updated algorithm offers an accurate and efficient tool for forward modeling and will benefit interpretations of field observations as well as future inversion studies.
Analyzing Explosive Volcanic Deposits From Satellite‐Based Radar Backscatter, Volcán de Fuego, 2018
Authors: Dualeh E. W. , Ebmeier S. K. , Wright T. J. , Albino F. , Naismith A. , Biggs J. , Ordoñez P. A. , Boogher R. M. , Roca A. 
Published: September 2021

AbstractSatellite radar backscatter has the potential to provide useful information about the progression of volcanic eruptions when optical, ground‐based, or radar phase‐based measurements are limited. However, backscatter changes are complex and challenging to interpret: explosive deposits produce different signals depending on pre‐existing ground cover, radar parameters and eruption characteristics. We use high temporal‐ and spatial‐resolution backscatter imagery to examine the emplacement and alteration of pyroclastic density currents (PDCs), lahar and ash deposits from the June 2018 eruption of Volcán de Fuego, Guatemala, using observatory reports and rainfall gauge data to ground truth our observations. We use a temporally dense time series of backscatter data to reduce noise and extract deposit areas. We observe backscatter changes in six drainages, the largest deposit was 11.9‐km‐long that altered an area of 6.3 and had a thickness of 10.5 2 m in the lower sections as estimated from radar shadows. The 3 June eruption also produced backscatter signal over an area of 40 , consistent with reported ashfall. We use transient patterns in backscatter time series to identify nine periods of high lahar activity in a single drainage system between June and October 2018. We find that the characterization of subtle backscatter signals associated with explosive eruptions are best observed with (1) radiometric terrain calibration, (2) speckle correction, and (3) consideration of pre‐existing scattering properties. Our observations demonstrate that SAR backscatter can capture the emplacement and subsequent alteration of a range of explosive deposits, allowing the progression of an explosive eruption to be monitored.
Future Climatic Projections and Hydrological Responses in the Upper Beijiang River Basin of South China Using Bias‐Corrected RegCM 4.6 Data
Authors: Chen Xiaoli , Chen Wenjie , Huang Guoru 
Published: September 2021

AbstractThe adverse effects of climate change on future extreme rainfall‐runoff events are posing severe challenges to flood control departments. Aimed at projecting future extreme rainfall‐runoff events over the Upper Beijiang River Basin of South China, regional climate model (RegCM 4.6) was used for dynamic downscaling three global climate models (GCMs) with two representative concentration pathways (RCP4.5 and RCP8.5) in two future periods (F1: 2016–2035 and F2: 2066–2085). Precipitation bias correction was carried out using an improved quantile mapping method. The future extreme precipitation events were analyzed using four extreme precipitation indices. The Soil and Water Assessment Tool model was established to simulate historical runoff and project future runoff. Three extreme runoff indices were defined to analyze future extreme runoff. The results showed that the bias correction effect was obvious, and the ability of the RegCM outputs driven by GCMs to capture the precipitation characteristics was obviously enhanced. Future extreme precipitation events will be more intense with almost all the four extreme precipitation indices showing increasing trends in future periods. Moreover, the future monthly runoff have basically increased and almost all the extreme runoff indices have increased in future periods with the average annual runoff, the total runoff in very wet days and the number of very heavy runoff days increasing by about 7%, 25%, and 35% respectively. Overall, responses and mitigation strategies should be developed regarding future extreme rainfall‐runoff events.
Impact of Prior Terrestrial Carbon Fluxes on Simulations of Atmospheric CO2 Concentrations
Authors: Fu Yu , Liao Hong , Tian XiangJun , Gao Hao , Jia Binghao , Han Rui 
Published: September 2021

AbstractTerrestrial ecosystems have a significant role in shaping the distribution of atmospheric CO2, but it is uncertain how much they affect CO2 concentrations. We assessed the impact of terrestrial fluxes derived from different biosphere models in the Multi‐scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) on atmospheric CO2 estimations based on a global chemical transport model (GEOS‐Chem) when these fluxes were applied as prior information. We examined the spatiotemporal uncertainty in terrestrial flux estimations from 15 MsTMIP terrestrial fluxes. We found high uncertainties in the terrestrial fluxes for temperate North America, tropical and temperate South America, southern Africa, Europe and tropical Asia. Sensitivity simulations showed that the annual mean CO2 concentration changed by 6.0–8.0 ppmv with the spread of the terrestrial fluxes. The interannual trend in the terrestrial fluxes could significantly affect the simulated trend of atmospheric CO2 concentrations. As a result of the spread in the prior terrestrial fluxes, large differences in the daily mean CO2 anomalies changed with an interquartile range of −1.0 to +1.0 ppmv and the magnitude of change in the sub‐daily CO2 concentrations was in the range 4.0–6.0 ppmv for China, the USA and Europe. Our results suggest an urgent need to increase the reliability of terrestrial flux estimates in CO2 simulations. Surface seasonal CO2 concentrations were simulated to change by ±2.0 ppmv in most regions of the world due to the differences in the ensemble mean fluxes, reflecting the impact of the uncertainties in the existing optimized terrestrial fluxes on CO2 simulations.
Seasonality in Prediction Skill of the Madden‐Julian Oscillation and Associated Dynamics in Version 2 of NASA's GEOS‐S2S Forecast System
Authors: Lim Young‐Kwon , Arnold Nathan P. , Molod Andrea M. , Pawson Steven 
Published: September 2021

AbstractThe prediction skill of the Madden‐Julian Oscillation (MJO) in Version 2 of NASA's Global Earth Observing System Subseasonal to Seasonal (GEOS‐S2S) forecast system is investigated for winter and summer focusing on moistening‐related processes crucial for eastward propagating MJO activity. It is found that the annual bivariate correlation of the Real‐time Multivariate MJO time series between prediction and observation is ∼0.70, ∼0.57, and ∼0.50 at 20‐, 25‐, and 30‐day forecast leads. Correlation at long‐leads (>30 days) is noticeably higher for boreal summer initial conditions (June‐September [JJAS]), with correlations remaining above 0.5 at 35–40 days leads. Correlations are lower for boreal winter initial conditions from January through March (JFM), dropping to ∼0.5 at 25‐day lead, still comparable to the skills in the other reliable S2S forecast systems.The predicted eastward MJO propagation across the Indo‐western Pacific sector is well captured in JJAS, but is slower than observed in JFM. Investigations of the moisture field and advection and moisture sink, moist static energy (MSE) budget, and tropical circulation/pressure responses to the MJO convective heating reveal that, in JFM, those responses and moistening processes, especially the vertical MSE advection, are underestimated over and to the east of the Maritime Continent when the MJO anomaly approaches from the west. In contrast, those processes are well represented in JJAS, although moistening is overestimated due to large surface evaporation. This study suggests that improvement of the moistening tendency over that region in the boreal winter could contribute to further increases in MJO prediction skill of the GEOS‐S2S system.
New Estimation of the NOx Snow‐Source on the Antarctic Plateau
Authors: Barbero A. , Savarino J. , Grilli R. , Blouzon C. , Picard G. , Frey M. M. , Huang Y. , Caillon N. 
Published: September 2021

AbstractTo fully decipher the role of nitrate photolysis on the atmospheric oxidative capacity in snow‐covered regions, NOx flux must be determined with more precision than existing estimates. Here, we introduce a method based on dynamic flux chamber measurements for evaluating the NOx production by photolysis of snowpack nitrate in Antarctica. Flux chamber experiments were conducted for the first time in Antarctica, at the French‐Italian station Concordia, Dome C (75°06'S, 123°20’E, 3233 m a.s.l) during the 2019–2020 summer campaign. Measurements were gathered with several snow samples of different ages ranging from newly formed drifted snow to 6‐year‐old firn. Contrary to existing literature expectations, the daily average photolysis rate coefficient, , did not significantly vary between differently aged snow samples, suggesting that the photolabile nitrate in snow behaves as a single‐family source with common photochemical properties, where a = (2.37 0.35) × 10−8 s−1 (1) has been calculated from December 10th 2019 to January 7th 2020. At Dome C summer daily average NOx flux, , based on measured NOx production rates was estimated to be (4.3 1.2) × 108 molecules cm−2 s−1, which is 1.5–7 times less than the net NOx flux observed previously above snow at Dome C using the gradient flux method. Using these results, we extrapolated an annual continental snow sourced NOx budget of 0.017 0.003 TgN y−1, 2 times the nitrogen budget, (N‐budget), of the stratospheric denitrification previously estimated for Antarctica. These quantifications of nitrate photolysis using flux chamber experiments provide a road‐map toward a new parameterization of the product that can improve future global and regional models of atmospheric chemistry.
Accessing the Subsurface Biosphere Within Rocks Undergoing Active Low‐Temperature Serpentinization in the Samail Ophiolite (Oman Drilling Project)
Authors: Templeton Alexis S. , Ellison Eric T. , Glombitza Clemens , Morono Yuki , Rempfert Kaitlin R. , Hoehler Tori M. , Zeigler Spencer D. , Kraus Emily A. , Spear John R. , Nothaft Daniel B. , Fones Elizabeth M. , Boyd Eric S. , Munro‐Ehrlich Mason , Mayhew Lisa E. , Cardace Dawn , Matter Juerg M. , Kelemen Peter B. ,   the Oman Drilling Project Science Party
Published: September 2021

AbstractThe Oman Drilling Project established an “Active Alteration” multi‐borehole observatory in peridotites undergoing low‐temperature serpentinization in the Samail Ophiolite. The highly serpentinized rocks are in contact with strongly reducing fluids. Distinct hydrological regimes, governed by differences in rock porosity and fracture density, give rise to steep redox (Eh +200 to −750 mV) and pH (pH range 8.5–11.2) gradients within the 300–400 m deep boreholes. The serpentinites and fluids host an active subsurface ecosystem. Microbial cell abundances in serpentinite vary at least six orders of magnitude, from ≤3.5 × 101 to 2.9 × 107 cells/g. Low levels of biological sulfate reduction (2–1,000 fmol/cm3/day) can be detected in rock cores, particularly in rocks in contact with reduced groundwaters with pH < 10.5. Thermodesulfovibrio is the predominant sulfate reducer identified via metagenomic sequencing of adjacent groundwater communities. We infer that transport and reaction of microbially generated sulfide with the serpentine and brucite assemblages gives rise to optical darkening and sulfide overprinting, including the formation of tochilinite‐vallerite group minerals, potentially serving as an indicator that this system is inhabited by microbial life. Olivine mesh‐cores replaced with ferroan brucite and minor awaruite, abundant veins containing hydroandradite garnet and polyhedral serpentine, and late‐stage carbonate veins are suggested as targets for future spatially resolved life‐detection investigations. The high‐quality whole‐round core samples that have been preserved can be further probed to define how life distributes itself and functions within a system where chemical disequilibria are sustained by low‐temperature water/rock interaction, and how biosignatures of in situ microbial activity are generated.
Semi‐Coupling of a Field‐Scale Resolving Land‐Surface Model and WRF‐LES to Investigate the Influence of Land‐Surface Heterogeneity on Cloud Development
Authors: Simon Jason S. , Bragg Andrew D. , Dirmeyer Paul A. , Chaney Nathaniel W. 
Published: September 2021

AbstractContemporary Earth system models mostly ignore the sub‐grid scale (SGS) heterogeneous coupling between the land surface and atmosphere. To aid in the development of coupled land and atmosphere SGS parameterizations for global models, we present a study of different aspects of highly realistic sub‐100 km scale land‐surface heterogeneity. The primary experiment is a set of simulations of September 24, 2017 over the Southern Great Plains (SGP) site using the Weather Research and Forecasting (WRF) model with 100‐m horizontal resolution. The overall impact of land‐surface heterogeneity is evaluated by comparing cloud and turbulent kinetic energy (TKE) production in large‐eddy simulations (LESs) using heterogeneous and homogeneous surface fields (namely sensible and latent heat fluxes) specified by an offline field‐scale resolving land‐surface model (LSM). The heterogeneous land surface leads to significantly more cloud and TKE production. We then isolate specific sources of heterogeneity by using selectively domain‐wide averaged fields in the LSM. It is found that heterogeneity in the land surface created by precipitation is effectively responsible for the increases in cloud and TKE production, while rivers and soil type have a negligible impact and land cover has only a small impact. Additional experiments modify the Bowen ratio in the surface fields and the initial wind profile of the heterogeneous case to clarify the results seen. Finally two additional days at the SGP site are simulated showing a similar increase in cloud production in heterogeneous cases.
Attribution of Snowpack Errors to Simulated Temperature and Precipitation in E3SMv1 Over the Contiguous United States
Authors: Brunke Michael A. , Welty Joshua , Zeng Xubin 
Published: September 2021

AbstractSnow water equivalent (SWE), temperature, and precipitation biases and trends are evaluated in the atmosphere‐land simulations of the Energy Exascale Earth System Model version 1 (E3SMv1) in comparison to the Community Earth System Model version 2 (CESM2) and two other models using the ground measurement‐based University of Arizona (UA) snow product. SWE, temperature, and precipitation biases are highest in magnitude in the Western contiguous United States (CONUS). SWE errors are attributed to temperature and precipitation through multiple linear regressions of normalized errors, the coefficients of which represent the sensitivities to temperature and precipitation errors. SWE errors are more sensitive to temperature errors throughout the CONUS. Model SWE and temperature trends are generally opposite from UA product trends in the Western CONUS. SWE trend errors are also attributed to temperature and precipitation trend errors using multiple linear regressions of normalized trend errors. SWE trend errors are more sensitive to those of precipitation at higher elevations (>1,500 m) in the Western CONUS in these simulations. Thus, the sensitivity to temperature and precipitation differ for SWE errors and its trend errors. Furthermore, the SWE trend errors are more sensitive to temperature and precipitation in the atmosphere‐ocean coupled simulations in which the atmosphere‐land is coupled to an active ocean model. These results suggest that both errors in simulated temperature and precipitation contribute to SWE errors.
Historical Reconstruction of Astronaut Cancer Risk: Context for Recent Solar Minima
Authors: Slaba Tony C. 
Published: September 2021

AbstractAs NASA prepares for longer duration missions beyond the geomagnetic field, the possibility of intensifying galactic cosmic ray (GCR) exposure raises possible concerns for mission planning and crew health and safety. Spaceborne satellite measurements have exhibited increasing GCR intensities and dose‐rates over the past few solar minima, consistent with related heliospheric magnetic field data. Surrogate measures of solar activity (e.g., sunspot number records and radionuclide yields from ice cores and/or tree rings) combined with model predictions have also been used to infer that the Sun may be entering into a quiet period similar to the Dalton or Gleissberg minima when GCR fluences reached historically high levels. Using the most up‐to‐date models for characterizing the ambient GCR environment, physical interactions with shielding, and cancer risk, it is found that projected risks vary by only ±10% over all historical minima since 1750. To provide additional context for this level of variation, two different nuclear interaction models are used within the radiation transport algorithms used to propagate GCR ions and secondary particles through shielding and tissue. It is shown that switching the nuclear interaction model also introduces 10% difference, on average, in projected risks over all historical minima. Furthermore, it is noted that the quantified historical variation is within combined environmental and physics uncertainties already accounted for in the probabilistic cancer risk model used by NASA for crew health and safety considerations.
Stochastic Rainwater Harvesting System Modeling Under Random Rainfall Features and Variable Water Demands
Authors: Cheng Guanhui , Huang Guohe (Gordon) , Guo Yiping , Baetz Brian W. , Dong Cong 
Published: September 2021

AbstractA stochastic rainwater harvesting system modeling (StRaHaS) method is developed to enhance both accurateness and applicability of hydrologic modeling in guiding extensive applications of individual rainwater harvesting (RWH) systems (especially over large data‐scarce regions). The reliability of a RWH system is characterized as the fraction of time water demands being satisfied by a rainwater storage unit (RWSU). The variations of water balances, the post‐rainfall RWSU full‐storage probability, and the system reliability with random rainfall features, variable water demands, and the other RWH system characteristics are derived as analytical, accurate, and easily applied models through stochastic integration. StRaHaS is applied to three domestic RWH systems in Toronto, Canada. Due to high accurateness and low complexity in modeling, designing, assessing, and analyzing the RWH systems, StRaHaS outperforms existing methods (e.g., inaccurate water‐balance estimation, complicated continuous simulation, and simplified stochastic simulation). Based on StRaHaS, we quantitatively expound the increases in the reliability of the systems with higher rainwater supplies (corresponding to higher rainfall depths, and lower rainfall losses and first‐flush depths), lower water demands (in shorter wet and dry periods), and higher RWSU capacities. Long dry periods are lengthened by climate change and play dominant roles in low, spatially heterogeneous reliability of the systems. Synchronic changes and extremely high values of rainfall features do not significantly affect the reliability. Overall, StRaHaS is a promising method in modeling RWH systems, revealing RWH mechanisms, scientizing RWH applications, and facilitating the Sustainable Development Goals for addressing global water issues.