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At least 307 records · Page 17

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U. S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics parameterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRT Center to select NOAA/NWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boundary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage of lightning activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, E. W., Jr.↗

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

McCaul, Eugene W., Jr.↗

Equation of State and Spin Crossover of (Al, Fe)–Phase H

The transport of hydrogen into Earth's deep interior may have an impact on lower mantle dynamics as well as on the seismic signature of subducted material. Due to the stability of the hydrous phases δ-AlOOH (delta phase), MgSiO 2 (OH) 2 (phase H), and ε-FeOOH at high temperatures and pressures, their solid solutions may transport significant amounts of hydrogen as deep as the core-mantle boundary. Here we have constrained the equation of state, including the effects of a spin crossover in the Fe 3+ atoms, of (Al, Fe)-phase H: Al 0.84 Fe 3+ 0.07 Mg 0.02 Si 0.06 OOH, using powder X-ray diffraction measurements to 125 GPa, supported by synchrotron Mössbauer spectroscopy measurements on (Al, Fe)-phase H and δ-(Al, Fe)OOH. The changes in spin state of Fe 3+ in (Al, Fe)-phase H results in a significant decrease in bulk sound velocity and occurs over a different pressure range (48–62 GPa) compared with δ-(Al, Fe)OOH (32–40 GPa). Changes in axial compressibilities indicate a decrease in the compressibility of hydrogen bonds in (Al, Fe)-phase H near 30 GPa, which may be associated with hydrogen bond symmetrization. The formation of (Al, Fe)-phase H in subducted oceanic crust may contribute to scattering of seismic waves in the mid-lower mantle (~1,100–1,550 km). Accumulation of 1–4 wt.% (Al, Fe)-phase H could reproduce some of the seismic signatures of large, low seismic-velocity provinces. Our results suggest that changes in the electronic structure of phases in the (δ-AlOOH)-(MgSiO 2 (OH) 2 )-(ε-FeOOH) solid solution are sensitive to composition and that the presence of these phases in subducted oceanic crust could be seismically detectable throughout the lower mantle.

58 GEOSCIENCES↗

Deep Minima in the Triply Differential Cross Section for Ionization of Atomic Hydrogen by Electron and Positron Impact

We investigate ionization of atomic hydrogen by electron- and positron-impact. We apply the Coulomb–Born (CB1) approximation, various modified CB1 approximations, the three body distorted wave (3DW) approximation, and the time-dependent close-coupling (TDCC) method to electron-impact ionization of hydrogen. For electron-impact ionization of hydrogen for an incident energy of approximately 76.45 eV, we obtain a deep minimum in the CB1 triply differential cross section (TDCS). However, the TDCC for 74.45 eV and the 3DW for 74.46 eV gave a dip in the TDCS. For positron-hydrogen ionization (breakup) we apply the CB1 approximation and a modified CB1 approximation. We obtain a deep minimum in the TDCS and a zero in the CB1 transition matrix element for an incident energy of 100 eV with a gun angle of 56.13 °. Corresponding to a zero in the CB1 transition matrix element, there is a vortex in the velocity field associated with this element. For both electron- and positron-impact ionization of hydrogen the velocity field rotates in the same direction, which is anticlockwise. All calculations are performed for a doubly symmetric geometry; the electron-impact ionization is in-plane and the positron-impact ionization is out-of-plane.

74 ATOMIC AND MOLECULAR PHYSICS↗

First discovery of the organic materials in deep-sea iron cosmic spherule

The dust impact mass analyzer (PUMA) carried by the spacecraft Vega 1, Vega 2 and Giotto has provided the first direct measurements of the physical and chemical properties of cometary dust. The results indicate that most of the cometary dust particles are rich in light elements such as H, C, N, and O, suggesting the validity of models that describe the cometary dust as including organic material. Up to now, there were none found with the organic material from the deep-sea cosmic spherules. We have determined this from the deep-sea iron cosmic spherules collected from the North Pacific. An iron cosmic spherule (382 microns in diameter) was determined by the Laser Raman Microprobe.

Hanchang, Peng↗

Effect of Ice Sheet Thickness on Formation of the Hiawatha Impact Crater

The discovery of a large putative impact crater buried beneath Hiawatha Glacier along the margin of the northwestern Greenland Ice Sheet has reinvigorated interest into the nature of large impacts into thick ice masses. This circular structure is relatively shallow and exhibits a small central uplift, whereas a peak-ring morphology is expected. This discrepancy may be due to long-term and ongoing subglacial erosion but may also be explained by a relatively recent impact through the Greenland Ice Sheet, which is expected to alter the final crater morphology. Here we model crater formation using hydrocode simulations, varying pre-impact ice thickness and impactor composition over crystalline target rock. We find that an ice-sheet thickness of 1.5 or 2 km results in a crater morphology that is consistent with the present morphology of this structure. Further, an ice sheet that thick substantially inhibits ejection of rocky material, which might explain the absence of rocky ejecta in most existing Greenland deep ice cores if the impact occurred during the late Pleistocene. From the present morphology of the putative Hiawatha impact crater alone, we cannot distinguish between an older crater formed by a pre-Pleistocene impact into ice-free bedrock or a younger, Pleistocene impact into locally thick ice, but based on our modeling we conclude that latter scenario is possible.

Elizabeth A. Silber↗

Probing the state of hydrogen in δ − AlOOH at mantle conditions with machine learning potential

Hydrous and nominally anhydrous minerals are a fundamental class of solids of enormous significance to geophysics. They are the water carriers in the deep geological water cycle and impact structural, elastic, plastic, and thermodynamic properties and phase relations in Earth's forming aggregates (rocks). They play a critical role in the geochemical and geophysical processes that shape the planet. Their complexity has prevented predictive calculations of their properties, but progress in materials simulations ushered by machine-learning potentials is transforming this state of affairs. Here, we adopt a hybrid approach that combines deep learning potentials (DPs) with the strongly constrained and appropriately normed meta-generalized gradient approximation functional to simulate a prototypical hydrous system. We illustrate the success of this approach to simulate δ − AlOOH ( δ ) , a phase capable of transporting water down to near the core-mantle boundary of the Earth ( ∼ 2900 km depth and ∼ 135 GPa ) in subducting slabs. A high-throughput sampling of phase space using molecular dynamics simulations with DPs sheds light on the hydrogen-bond behavior and proton diffusion at geophysical conditions. These simulations provide a pathway for a deeper understanding of these crucial components that shape Earth's internal state. Published by the American Physical Society 2024

Luo, Chenxing (ORCID:0000000341166851)↗

Physical and hydrodynamic properties of deep sea mining-generated, abyssal sediment plumes in the Clarion Clipperton Fracture Zone (eastern-central Pacific)

The anthropogenic impact of polymetallic nodule harvesting in the Clarion-Clipperton Fracture Zone is expected to strongly affect the benthic ecosystem. To predict the long-term, industrial-scale impact of nodule mining on the deep-sea environment and to improve the reliability of the sediment plume model, information about the specific characteristics of deep-sea particles is needed. Discharge simulations of mining-related fine-grained (median diameter ≈ 20 µm) sediment plumes at concentrations of 35–500 mg L –1 (dry weight) showed a propensity for rapid flocculation within 10 to 135 min, resulting in the formation of large aggregates up to 1100 µm in diameter. The results indicated that the discharge of elevated plume concentrations (500 mg L –1 ) under an increased shear rate (G ≥ 2.4 s –1 ) would result in improved efficiency of sediment flocculation. Furthermore, particle transport model results suggested that even under typical deep-sea flow conditions (G ≈ 0.1 s –1 ), rapid deposition of particles could be expected, which would restrict heavy sediment blanketing (several centimeters) to a smaller fall-out area near the source, unless subsequent flow events resuspended the sediments. Planning for in situ tests of these model projections is underway.

42 ENGINEERING↗

Multi-objective automatic discovery of optimized metamaterials for varying velocity impact protection

Mechanical metamaterials have demonstrated exceptional impact performance while remaining lightweight. Impact resistance has traditionally been investigated using quasi-static simulations, often with the assumption that performance will translate to high-velocity impact scenarios. However, critical crash protection parameters—such as peak stress and absorbed energy—are highly sensitive to impact velocity, leading to inconsistent performance under dynamic loading. To address this, we introduce a strain-rate-aware, active deep learning framework that enables multi-objective optimization of impact protection metrics across a wide range of impact velocities. Our framework captures the strain-rate sensitivity of architected lattices by learning to control spatial gradation in cellular metamaterials, resulting in over 200 % enhancement in impact protection relative to state-of-the-art designs such as Voronoi and re-entrant lattices. We demonstrate its practical utility by designing next-generation lattice structures for automotive bumper systems that satisfy multiple, velocity-specific safety criteria—capabilities beyond those of conventional designs. More than just a predictive tool, this framework marks the first step towards enabling adaptable impact-resistant structures across dynamic regimes.

Deep learning↗

Applying Deep Learning for Wildfire Identification: Economical and Accessible Solutions Leveraging Small Datasets

Wildfires significantly impact human health, air quality, visibility, weather, and climate change and cause substantial economic losses. While state and county-operated air quality monitors provide critical insights during wildfires, they are not available in all regions. This highlights the need for affordable, accessible tools that allow the general public to assess air quality impacts. In this study, we apply machine learning with deep neural networks to diagnose air quality rapidly from sky images taken at the Pacific Northwest National Laboratory in Richland, WA, USA. Using a convolutional neural network (CNN) framework, we trained a deep learning model to classify air quality indices based on sky images. By leveraging transfer learning, our approach fine-tunes a pre-trained model on a small dataset of sky images, significantly reducing training time while maintaining high accuracy. Our results demonstrate the potential of deep learning to provide rapid air quality diagnostics during wildfire episodes, offering early warnings to the public and enabling timely mitigation strategies, particularly for vulnerable populations. Additionally, we show that lower respiratory infections pose the highest health risk during acute smoke exposures. Reactive oxygen species (ROS) from wildfire particles further exacerbate health risks by triggering inflammation and other adverse effects.

54 ENVIRONMENTAL SCIENCES↗

Geomechanical models of impact cratering: Puchezh-Katunki structure

Impact cratering is a complex natural phenomenon that involves various physical and mechanical processes. Simulating these processes may be improved using the data obtained during the deep drilling at the central mound of the Puchezh-Katunki impact structure. A research deep drillhole (named Vorotilovskaya) has been drilled in the Puchezh-Katunki impact structure (European Russia, 57 deg 06 min N, 43 deg 35 min E). The age of the structure is estimated at about 180 to 200 m.y. The initial rim crater diameter is estimated at about 40 km. The central uplift is composed of large blocks of crystalline basement rocks. Preliminary study of the core shows that crystalline rocks are shock metamorphosed by shock pressure from 45 GPa near the surface to 15-20 GPa at a depth of about 5 km. The drill core allows the possibility of investigating many previously poorly studied cratering processes in the central part of the impact structure. As a first step one can use the estimates of energy for the homogeneous rock target. The diameter of the crater rim may be estimated as 40 km. The models elaborated earlier show that such a crater may be formed after collapse of a transient cavity with a radius of 10 km. The most probable range of impact velocities from 11.2 to 30 km/s may be inferred for the asteroidal impactor. For the density of a projectile of 2 g/cu cm the energy of the impact is estimated as 1E28 to 3E28 erg. In the case of vertical impact, the diameter of an asteroidal projectile is from 1.5 to 3 km for the velocity range from 11 to 30 km/s. For the most probable impact angle of 45 deg, the estimated diameter of an asteroid is slightly larger: from 2 to 4 km. Numerical simulation of the transient crater collapse has been done using several models of rock rheology during collapse. Results show that the column at the final position beneath the central mound is about 5 km in length. This value is close to the shock-pressure decay observed along the drill core. Further improvement of the model needs to take into account the blocky structure of target rocks revealed by drilling.

Ivanov, B. A.↗

Diagnostic Clast-Texture Criteria for Recognition of Impact Deposits

It is difficult to find definitive evidence for impact in the geological record because there are many endogenous geological processes that can produce diamictites similar to those generated by impact ejecta. The classic impact criteria of shock fabrics in certain minerals, and iridium layers, for example, may be either difficult to find, or long-since erased from the impact site (shock fabrics also anneal with time). It is important to be able to recognize impact-generated materials in order to understand earth's crustal development and biological evolution. In future exploration of Mars and other solar-system bodies, recognition of impact materials will be important for elucidating planetary evolution, planetary volatile inventories, and exobiological issues. The cobble depicted is typical of many that have been found in diamictite deposits in Belize generated by the Chicxulub K-T impact event. The pebbles are roughly-hewn in general shape with smoothed corners and edges. Surfaces are almost uniformly frosted (on both protuberances and hollows), but some asperities are glazed. Optical microscopy and thin-section petrographic microscopy reveal the frosting to be only a few microns thick, with a well-defined granular structure; grains are the same size as those composing the bulk of the limestone, but their clearer appearance may represent annealing. One or two adjacent pebble faces are often decorated with striated gouges and closely-spaced hemispherical depressions representing indentation hollows produced by well-rounded impacting clasts of up to 0.5 cm in diameter. Some of the impactors are still embedded in the cobble surface. Non-destructive x-ray diffraction techniques showed the impactors to be of the same mineralogy as the target cobble. We believe this unusual glazing and frosting to be related to the impact event, but this must be reconciled with its survival for over 60 my. since it is composed of one of the most alterable substances, CaCO3. We focus, however, on the non-fractured rounded pebbles that appear to have impacted the larger cobble as a swarm of clasts, probably encountered during ballistic flight. It cannot be defined whether the cobble swept through the pebble cloud, or the pebbles rained upon a slowermoving cobble. Two interesting questions arise: (1) Where did large numbers of such well rounded pebbles come from in the ejecta curtain?, and (2) How did they embed themselves in a nominally brittle rock without suffering damage? Are the well-rounded pebbles crystalline (devitrified) melt spherules? Further investigations are in progress. If the cobble was cold and brittle, impact of well-rounded pebbles would have produced Hertzian fracture patterns (a) in the virtually elastically isotropic cobble target. For penetration depths of about 0.5 of the impactor diameter, the pebbles would require a relative impact velocity sufficient to cause pebble fragmentation and crushing, and the development of a complex Hertzian-Boussinesq fracture field (b) involving deep fracturing and lateral surface spalling (impact velocities > 50 m/s). The existing relationship could only evolve by the impact of cold, hard pebbles into a soft, plastic cobble surface (c). For limestone to have been plastic, it must have been at elevated temperature, but to prevent calcification of the material, the ambient pressure must also have been elevated. This would be possible either in the impact's gas plume, or within the confines of a thin aerodynamically-produced shock bow generated by supersonic ballistic motion of the cobble. In the latter case, it is implied that the cobble swept through the pebbles rather than vice-versa. Although there are high T-P conditions associated with volcanism, such textures have not been reported on volcaniclastic materials, nor from other high T-P environments; e.g., metamorphic (as far as the authors are aware). We propose that this very easily recognizable embedding and indentation surface texture can be used as a diagnostic criterion for the recognition of impact ejecta. The term "peening texture" is suggested, because it is absolutely analogous to the plastic-deformation induced, metal-surface textures generated by ball-bearing bombardment used in engineering metallurgy to work-harden metal surfaces. Additional information is contained in the original (Figures).

Marshall, J. R.↗

Effective structural impact detection and localization using convolutional neural network and Bayesian information fusion with limited sensors

Due to their unpredictable nature, many impact events (e.g., overheight vehicles striking on bridges) go unnoticed or get reported many hours later. However, they can induce structural failures or hidden damage that accelerates the structure’s long-term degradation. Therefore, prompt impact detection and localization strategies are essential for early warning of impact events and rapid maintenance of structures. Most existing impact detection strategies are developed for aircraft composite panels utilizing high-rate synchronized measurement from densely deployed sensors. Limited efforts have been made for infrastructure or human habitats which generally require large-scale but low-rate measurement. In particular, due to harsh environments (e.g., deep space habitats under meteoroids), structural impact localization must be robust to limited sensors (e.g., sensor damage during impacts) and multi-source errors (e.g., measurement errors). In this study, an effective impact detection and localization strategy is proposed using a limited number of vibration measurements, especially in harsh environments (e.g. in deep space). Convolutional neural networks are trained for each sensor node and are fused using Bayesian theory to improve the accuracy of impact localization. Special considerations are paid to evaluate the effect of both measurement error and modeling error in the analysis. The proposed strategy is illustrated using 1D structure, and further validated in 3D geodesic dome structure numerically. The results demonstrate that it can detect and localize impact events accurately and robustly on structures.

Yuguang Fu↗

Change Agent: Energy Storage as a Driver of Regulatory Evolution

Purpose of Review Dividing the electric grid into the functions of generation, transmission, anddistribution enabled the drawing of jurisdictional lines and the application of the U.S.Constitution’s federalist system to energy regulation. Energy storage technologies,which can be placed throughout the grid to increase flexibility, can provide serviceacross all three of those functions. But the jurisdictional boundaries that have beendrawn around those functions have created barriers that restrict energy storagetechnologies from achieving their full potential. This review analyzes regulatory changes made to reduce barriers to storage deployment and their broader impacts on energy regulation in the U.S. Recent Findings Major energy regulations promulgated at the state and federal levels have generally focused on liberalizing the U.S. electric system through deregulation and increased competition. Paradoxically, however, these efforts have erected strict regulatory barriers that prevent energy storage technologies from providing service across multiple functions. A new wave of regulations in recent years has endeavored to reduce and remove those barriers. Summary Energy regulations adopted in recent years to reduce barriers to energy storage functionality in recent years have had deep and far-reaching impacts on U.S. electric regulation. These impacts go beyond storage and affect all energy technologies. This paper traces the development of energy regulation in U.S., the functional barriers that they created that impede energy storage functionality, recent efforts to remove those barriers, and the broader effects of those efforts. It concludes with a brief discussion of remaining barriers that prevent energy storage from reaching their full potential on the U.S. electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimization and Evaluation of Stochastic Unified Convection Using Single-Column Model Simulations at Multiple Observation Sites

We extend the previously developed stochastic unified convection scheme (UNICON) for shallow convection to deep convection by parameterizing the impact of mesoscale organized flow on updraft properties. The extended stochastic UNICON parameterizes thermodynamic properties of updrafts at the near-surface as a multivariate Gaussian distribution, where the variances of the distribution are the summation of variances from non-organized turbulence and mesoscale organized flow. The distribution of updraft radius is parameterized as a power-law distribution with a scale break which is parameterized as a linear function of the strength of mesoscale organized flow. The proposed parameterization is validated using a series of large-eddy simulations of deep convection. The free parameters introduced in the formulation of stochastic UNICON are optimized using 10 cases of single-column model simulations over the ocean. Stochastic UNICON with the optimized parameters significantly reduces the biases of thermodynamic profiles and surface precipitation rates simulated in the original UNICON for tropical convection cases. The simulation of the variation in anomalies of temperature and moisture associated with the Madden-Julian oscillation is also improved. The overall improvements in simulated thermodynamic profiles are found to be due to the increased heating and drying tendencies by convective processes in stochastic UNICON. An additional simulation of an idealized deep convection case shows that stochastic UNICON produces enhanced cloud variabilities with dependency on updraft radius, indicating its ability to represent the coexistence of shallow and deep convection.

54 ENVIRONMENTAL SCIENCES↗

Climatic controls on soil and saprock nitrogen distribution and persistence in the Sierra Nevada

Nitrogen (N) is an essential nutrient in soil that regulates plant growth, terrestrial sequestration of atmospheric carbon dioxide, and persistence of organic compounds. However, major knowledge gaps remain about how climate change may impact N accumulation and persistence, especially in deep soil and saprock (friable weakly weathered bedrock). Our objective was to understand how climate impacts the accumulation of N in soil and saprock and how climate impacts soil N distribution, persistence, and mechanisms of N persistence. We investigated N concentration in bulk soil and density fractions. We estimated N persistence along a bio-climatic sequence—sites range from a low-elevation oak savannah, mid-elevation pine-oak/mixed-conifer forest, to a high-elevation subalpine forest—in the southern Sierra Nevada in California. A combination of radiocarbon and elemental composition measurements along with a first-order kinetic model was used. The N concentration in the bulk soil and density fractions declined with depth, and there was a relatively greater mineral-associated heavy fraction (HF) N in deeper samples. The cooler/wetter mixed conifer site held 37% of profile N in saprock, which was greater than that of the entire soil profile at the drier/hotter oak savannah. The majority of N in soil, which was in the HF, was not influenced by climate proxies tested. However, both unprotected and occluded fractions of N were strongly influenced by climate. Soil N mean residence time (MRT) showed that drier/hotter climates have a shorter MRT, compared to mid-elevation sites with cooler/wetter climates. The effect of climate on deep saprock N storage might be indirect, primarily through climatic influence on the thickness of saprock. Overall, our findings suggest the mineral-associated HF N pool will not be vulnerable to changes in climate and will continue to contribute to the persistent soil N pool. The amount of topsoil and subsoil unprotected and occluded N can be explained by gross primary productivity and mean annual precipitation indicating that changes in climate can influence N partitioning. N stored in deep soil and saprock may be less vulnerable to climate than N stored in drier/hotter climates with less deeply stored N. It is critical to dig deeper to understand terrestrial ecosystems’ response to climate.

58 GEOSCIENCES↗

Deep in the Sierra Nevada critical zone: saprock represents a large terrestrial organic carbon stock

Large uncertainty remains in the spatial distribution of deep soil organic carbon (OC) storage and how climate controls belowground OC. This research aims to quantify OC stocks, characterize soil OC age and chemical composition, and evaluate climatic impacts on OC storage from the soil surface through the deep critical zone to bedrock. These objectives were carried out at four sites along a bio-climosequence in the Sierra Nevada, California. On average, 74% of OC was stored below the A horizon, and up to 30% of OC was stored in saprock (friable weakly weathered bedrock). Radiocarbon, spectroscopic, and isotopic analyses revealed the coexistence of very old organic matter (OM) (mean radiocarbon age = 20 300 years) with relatively recent OM (mean radiocarbon age = 4800 years) and highly decomposed organic compounds with relatively less decomposed material in deep soil and saprock. This co-mingling of OM suggests OC is prone to both active cycling and long-term protection from degradation. In addition to having direct effects on OC cycling, climate indirectly controls deep OC storage through its impact on the degree of regolith weathering (e.g. thickening). Although deep OC concentrations are low relative to soil, thick saprock represents a large, previously unrealized OC pool.

58 GEOSCIENCES↗