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At least 55 records · Page 3

Effect of tectonic processes on biosphere–geosphere feedbacks across a convergent margin

The subsurface is among Earth’s largest biomes, but the extent to which microbial communities vary across tectonic plate boundaries or interact with subduction-scale geological processes remains unknown. Here we compare bacterial community composition with deep-subsurface geochemistry from 21 hot springs across the Costa Rican convergent margin. We find that cation and anion compositions of the springs reflect the dip angle and position of the underlying tectonic structure and also correlate with the bacterial community. Co-occurring microbial cliques related to cultured chemolithoautotrophs that use the reverse tricarboxylic acid cycle (rTCA) as well as abundances of metagenomic rTCA genes correlate with concentrations of slab-volatilized carbon. This, combined with carbon isotope evidence, suggests that fixation of slab-derived CO2 into biomass may support a chemolithoautotrophy-based subsurface ecosystem. We calculate that this forearc subsurface biosphere could sequester 1.4 × 10 9 to 1.4 × 10 10 mol of carbon per year, which would decrease estimates of the total carbon delivered to the mantle by 2 to 22%. Furthermore, based on the observed correlations, we suggest that distribution and composition of the subsurface bacterial community are probably affected by deep tectonic processes across the Costa Rican convergent margin and that, by sequestering carbon volatilized during subduction, these chemolithoautotrophic communities could in turn impact the geosphere.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.

Huntzinger, D. N.↗

94 {beta}-Decay Half-Lives of Neutron-Rich 55Cs to 67Ho: Experimental Feedback and Evaluation of the r-Process Rare-Earth Peak Formation

The β-decay half-lives of 94 neutron-rich nuclei 144$-$151 Cs, 146$-$154 Ba, 148$-$156 La, 150$-$158 Ce, 153$-$160 Pr, 156$-$162 Nd, 159$-$163 Pm, 160$-$166 Sm, 161$-$168 Eu, 165$-$170 Gd, 166$-$172 Tb, 169$-$173 Dy, 172$-$175 Ho, and two isomeric states 174m Er, 172m Dy were measured at the Radioactive Isotope Beam Factory, providing a new experimental basis to test theoretical models. Strikingly large drops of β-decay half-lives are observed at neutron-number N = 97 for 58 Ce, 59 Pr, 60 Nd, and 62 Sm, and N = 105 for 63 Eu, 64 Gd, 65 Tb, and 66 Dy. Lastly, features in the data mirror the interplay between pairing effects and microscopic structure. r-process network calculations performed for a range of mass models and astrophysical conditions show that the 57 half-lives measured for the first time play an important role in shaping the abundance pattern of rare-earth elements in the solar system

Wu, J.↗

Feedback and Oscillations: Constructing Feedback Systems for Root Cause Analysis of Oscillations in Power Grids

Dynamic phenomena linked to inverter-based resources (IBRs) have gained global attention. Several IBR-induced dynamics have caused bulk power system-connected wind or solar power plants to trip, and some have even led to widespread outages. In addition, many oscillations have been observed involving IBR power plants. In 2023, the IEEE Power & Energy Society (PES) IBR Subsynchronous Oscillations (SSO) task force published a journal article, “Real-World Subsynchronous Oscillation Events in Power Grids With High Penetrations of Inverter-Based Resources,” in which 19 IBR oscillation events were examined for their causation. Earlier in 2020, another PES task force article, “Definition and Classification of Power System Stability-Revisited & Extended,” authored by prominent academics, introduced converter-driven stability as a new category of stability. The international power grid industry community also took action by publishing the CIGRE Green Book, Power System Dynamic Modelling and Analysis in Evolving Networks (led by Babak Badrzadeh and Zia Emin) in 2024. In August 2024, the Energy Systems Integration Group (ESIG) released a practical guide led by Nick Miller, “Diagnosis and Mitigation of Observed Oscillations in IBR-Dominant Power System: A Practical Guide.” The goal of the guide is to assist practicing engineers in making initial judgments and conducting detailed analyses about oscillations. Finally, when addressing the classification of stability and oscillations, the guide emphasizes a causality-based taxonomy for grouping, such as voltage control-induced oscillations, synchronization-induced oscillations, and frequency or active power control-induced oscillations.

Fan, Lingling [Univ. of South Florida, Tampa, FL (↗

Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks

The complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the C fate and persistence under future climate scenarios. As these proxies are used at increasingly larger scales, the C pools and processes that proxies represent must be thoughtfully considered in order to minimize uncertainties in empirical understanding, as well as in model parameters and in model outcomes. The importance of these uncertainties is further amplified by the current need to make predictions of the C cycle for the non steady state environmental conditions resulting from global climate change. To clarify the appropriate uses of proxy variables, we provide specific examples of proxy variables that could improve decision making, adaptation choices, and modeling skill, while not foreclosing on – and also encouraging – continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil organic matter: metabolic quotient, clay content, and physical fractionation. We also consider emerging data types, specifically genome-sequence data, and how these serve as proxies for microbial community activities. We opine that the demand for increasing mechanistic detail, and the flood of data from new imaging and genetic techniques, does not replace the value of correlative and integrative proxies--variables that are simpler, easier, or cheaper to measure. By closely examining the current knowledge gaps and broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.

Bailey, Vanessa L.↗

Rapid feedback of chemical vapor deposition growth mechanisms by operando X-ray diffraction

An operando x-ray diffraction system is presented for elucidating optimal laser assisted chemical vapor deposition growth conditions. The technique is utilized to investigate deposition dynamics of boron-carbon materials using trimethyl borate precursor. Trimethyl borate exhibits vastly reduced toxicological and flammability hazards compared to existing precursors, but has previously not been applied to boron carbide growth. Crystalline boron-rich carbide material is produced in a narrow growth regime on addition of hydrogen during the growth phase at high temperature. Finally, the use of the operando x-ray diffraction system allows for the exploration of highly nonequilibrium conditions and rapid process control, which are not possible using ex situ diagnostics.

36 MATERIALS SCIENCE↗

Modeling UV Radiation Feedback from Massive Stars. I. Implementation of Adaptive Ray-tracing Method and Tests [Modeling UV Radiation Feedback from Massive Stars: I. Implementation of Adaptive Ray Tracing Algorithm]

Here, we present an implementation of an adaptive ray-tracing (ART) module in the Athena hydrodynamics code that accurately and efficiently handles the radiative transfer involving multiple point sources on a three-dimensional Cartesian grid. We adopt a recently proposed parallel algorithm that uses nonblocking, asynchronous MPI communications to accelerate transport of rays across the computational domain. We validate our implementation through several standard test problems, including the propagation of radiation in vacuum and the expansions of various types of H II regions. Additionally, scaling tests show that the cost of a full ray trace per source remains comparable to that of the hydrodynamics update on up to $\sim {10}^{3}$ processors. To demonstrate application of our ART implementation, we perform a simulation of star cluster formation in a marginally bound, turbulent cloud, finding that its star formation efficiency is 12% when both radiation pressure forces and photoionization by UV radiation are treated. We directly compare the radiation forces computed from the ART scheme with those from the M 1 closure relation. Although the ART and M 1 schemes yield similar results on large scales, the latter is unable to resolve the radiation field accurately near individual point sources.

79 ASTRONOMY AND ASTROPHYSICS↗

The Cloud Feedback Model Intercomparison Project (CFMIP) Diagnostic Codes Catalogue – metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models

The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from general circulation model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. Here, this paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided into the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments will also be facilitated by the sharing of diagnostic codes via this catalogue. Any code which implements diagnostics relevant to analysing clouds – including cloud–circulation interactions and the contribution of clouds to estimates of climate sensitivity in models – and which is documented in peer-reviewed studies, can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.

58 GEOSCIENCES↗

Mid-latitude clouds contribute to Arctic amplification via interactions with other climate feedbacks

Abstract Traditional feedback analyses, which assume that individual climate feedback mechanisms act independently and add linearly, suggest that clouds do not contribute to Arctic amplification. However, feedback locking experiments, in which the cloud feedback is disabled, suggest that clouds, particularly outside of the Arctic, do contribute to Arctic amplification. Here, we reconcile these two perspectives by introducing a framework that quantifies the interactions between radiative feedbacks, radiative forcing, ocean heat uptake, and atmospheric heat transport. We show that including the cloud feedback in a comprehensive climate model can result in Arctic amplification because of interactions with other radiative feedbacks. The surface temperature change associated with including the cloud feedback is amplified in the Arctic by the surface-albedo, Planck, and lapse-rate feedbacks. A moist energy balance model with a locked cloud feedback exhibits similar behavior as the comprehensive climate model with a disabled cloud feedback and further indicates that the mid-latitude cloud feedback contributes to Arctic amplification via feedback interactions. Feedback locking in the moist energy balance model also suggests that the mid-latitude cloud feedback contributes substantially to the intermodel spread in Arctic amplification across comprehensive climate models. These results imply that constraining the mid-latitude cloud feedback will greatly reduce the intermodel spread in Arctic amplification. Furthermore, these results highlight a previously unrecognized non-local pathway for Arctic amplification.

58 GEOSCIENCES↗

Extrapolar Cloud Feedbacks as a Driver of Arctic Amplification

The role of cloud feedbacks in Arctic amplification (AA) of anthropogenic warming remains unclear. Traditional feedback analysis diagnoses the net cloud feedback as strongly positive in the tropics but either weak or negative in the Arctic, suggesting that AA would be amplified if cloud feedbacks were suppressed. However, in cloud-locking experiments using the slab ocean version of the Energy Exascale Earth System Model (E3SM), we find that suppressing cloud feedbacks results in a substantial decrease in AA under greenhouse gas forcing. We show that the increase in AA from cloud feedbacks arises from two main mechanisms: 1) the additional energy contributed by positive cloud feedbacks in the tropics leads to increased poleward moist atmospheric heat transport (AHT) which then amplifies Arctic warming; and 2) the additional Arctic warming is amplified by positive noncloud feedbacks in the region, together making extrapolar cloud feedbacks amplify AA. We also find that cloud changes can modify the strength of noncloud feedback, but that modification has a small effect on Arctic warming. We further examine the role of cloud feedbacks in AA using a moist energy balance model, which demonstrates that interactions of cloud feedbacks with moist AHT and other positive feedbacks dominate the influence of clouds on the pattern of surface warming. However, the contribution of cloud-induced changes in noncloud feedbacks on AA is relatively minor. Furthermore, these results demonstrate that traditional attributions of AA, that are based on local feedback analysis, overlook key interactions between extrapolar cloud changes, poleward AHT, and noncloud feedbacks in the Arctic.

58 GEOSCIENCES↗