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NASA NTRS2023

Multiyear Dry Periods in Southern Africa

Characteristics and physical features related to low precipitation across many years in Southern Africa that lead to societal disruptions are diagnosed using observed analyses and an ensemble of historical coupled climate model simulations during 1921 to 2014. Four regions are evaluated, as identified through a hierarchical clustering algorithm applied to the Standardized Precipitation Index (SPI) during the October–April precipitation season. Although dryness spanning many October–April occurs periodically in each region, they seldom occur simultaneously, consistent with largely insignificant SPI cross-correlations between them. However, characteristics relevant to low precipitation across many years are generalizable between the four regions, including the serial persistence of October–April precipitation, the likelihood of consecutive dry October–April, and the likelihood of dry October–April in temporal extents of up to 10 consecutive such 7-month seasons. Systematic precipitation persistence is not a feature in any of the four Southern Africa regions, as serial correlations of October–April SPI are not statistically significant at any time lags. It follows that there is an exponential-folding decay in the likelihood of consecutive October–April for various SPI thresholds and that there is a large spread in the likelihood of low October–April SPI across many years. In terms of physical features, low October–April SPI in each Southern Africa region is closely related to local atmospheric circulations; however, they are not as closely related to sea surface temperatures (SSTs). These results suggest that dryness spanning many years is determined primarily by persistent local circulations related to atmospheric variability and to a lesser extent variability related to SST anomalies, including the El Niño–Southern Oscillation.

subtropical Indian Ocean dipole↗

DOE OSTI2023

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Employment access assessed using the mobility energy productivity (MEP) metric

Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Emergence of quasiparticles in a doped Mott insulator

How a Mott insulator develops into a weakly coupled metal upon doping is a central question to understanding various emergent correlated phenomena. To analyze this evolution and its connection to the high- T c cuprates, we study the single-particle spectrum for the doped Hubbard model using cluster perturbation theory on superclusters. Starting from extremely low doping, we identify a heavily renormalized quasiparticle dispersion that immediately develops across the Fermi level, and a weakening polaronic side band at higher binding energy. The quasiparticle spectral weight roughly grows at twice the rate of doping in the low doping regime, but this rate is halved at optimal doping. In the heavily doped regime, we find both strong electron-hole asymmetry and a persistent presence of Mott spectral features. Finally, we discuss the applicability of the single-band Hubbard model to describe the evolution of nodal spectra measured by angle-resolved photoemission spectroscopy (ARPES) on the single-layer cuprate La 2– x Sr x CuO 4 (0 ≤ x ≤ 0.15). This work benchmarks the predictive power of the Hubbard model for electronic properties of high- T c cuprates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Radiation hydrodynamics modeling of the highest compression inertial confinement fusion ignition experiment from the National Ignition Campaign

The recently completed National Ignition Campaign (NIC) on the National Ignition Facility (NIF) showed significant discrepancies between post-shot simulations of implosion performance and experimentally measured performance, particularly in thermonuclear yield. This discrepancy between simulation and observation persisted despite concerted efforts to include all of the known sources of performance degradation within a reasonable two-dimensional (2-D), and even three-dimensional (3-D), simulation model, e.g., using measured surface imperfections and radiation drives adjusted to reproduce observed implosion trajectories [Clark et al., Phys. Plasmas 20, 056318 (2013)]. Since the completion of the NIC, several effects have been identified that could explain these discrepancies and that were omitted in previous simulations. In particular, there is now clear evidence for larger than anticipated long-wavelength radiation drive asymmetries and a larger than expected perturbation seeded by the capsule support tent. This paper describes an updated suite of one-dimensional (1-D), 2-D, and 3-D simulations that include the current best understanding of these effects identified since the NIC, as applied to a specific NIC shot. The relative importance of each effect on the experimental observables is compared. In combination, these effects reduce the simulated-to-measured yield ratio from 125:1 in 1-D to 1.5:1 in 3-D, as compared to 15:1 in the best 2-D simulations published previously. While the agreement with the experimental data remains imperfect, the comparison to the data is significantly improved and suggests that the largest sources for the previous discrepancies between simulation and experiment are now being included.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Policy-relevant differences between secondhand and thirdhand smoke: strengthening protections from involuntary exposure to tobacco smoke pollutants

Starting in the 1970s, individuals, businesses and the public have increasingly benefited from policies prohibiting smoking indoors, saving thousands of lives and billions of dollars in healthcare expenditures. Smokefree policies to protect against secondhand smoke exposure, however, do not fully protect the public from the persistent and toxic chemical residues from tobacco smoke (also known as thirdhand smoke) that linger in indoor environments for years after smoking stops. Nor do these policies address the economic costs that individuals, businesses and the public bear in their attempts to remediate this toxic residue. We discuss policy-relevant differences between secondhand smoke and thirdhand smoke exposure: persistent pollutant reservoirs, pollutant transport, routes of exposure, the time gap between initial cause and effect, and remediation and disposal. We examine four policy considerations to better protect the public from involuntary exposure to tobacco smoke pollutants from all sources. We call for (a) redefining smokefree as free of tobacco smoke pollutants from secondhandandthirdhand smoke; (b) eliminating exemptions to comprehensive smoking bans; (c) identifying indoor environments with significant thirdhand smoke reservoirs; and (d) remediating thirdhand smoke. We use the case of California as an example of how secondhand smoke-protective laws may be strengthened to encompass thirdhand smoke protections. The health risks and economic costs of thirdhand smoke require that smokefree policies, environmental protections, real estate and rental disclosure policies, tenant protections, and consumer protection laws be strengthened to ensure that the public is fully protected from and informed about the risks of thirdhand smoke exposure.

Public, Environmental & Occupational Health↗

NASA NTRS1979

Aircraft vortex marking program

A simple, reliable device for identifying atmospheric vortices, principally as generated by in-flight aircraft and with emphasis on the use of nonpolluting aerosols for marking by injection into such vortex (-ices) is presented. The refractive index and droplet size were determined from an analysis of aerosol optical and transport properties as the most significant parameters in effecting vortex optimum light scattering (for visual sighting) and visual persistency of at least 300 sec. The analysis also showed that a steam-ejected tetraethylene glycol aerosol with droplet size near 1 micron and refractive index of approximately 1.45 could be a promising candidate for vortex marking. A marking aerosol was successfully generated with the steam-tetraethylene glycol mixture from breadboard system hardware. A compact 25 lb/f thrust (nominal) H2O2 rocket chamber was the key component of the system which produced the required steam by catalytic decomposition of the supplied H2O2.

Pompa, M. F.↗

NASA NTRS1994

Time scales of pattern evolution from cross-spectrum analysis of advanced very high resolution radiometer and coastal zone color scanner imagery

We have selected square subareas (110 km on a side) from coastal zone color scanner (CZCS) and advanced very high resolution radiometer (AVHRR) images for 1981 in the California Current region off northern California for which we could identify sequences of cloud-free data over periods of days to weeks. We applied a two-dimensional fast Fourier transformation to images after median filtering, (x, y) plane removal, and cosine tapering. We formed autospectra and coherence spectra as functions of a scalar wavenumber. Coherence estimates between pairs of images were plotted against time separation between images for several wide wavenumber bands to provide a temporal lagged coherence function. The temporal rate of loss of correlation (decorrelation time scale) in surface patterns provides a measure of the rate of pattern change or evolution as a function of spatial dimension. We found that patterns evolved (or lost correlation) approximately twice as rapidly in upwelling jets as in the 'quieter' regions between jets. The rapid evolution of pigment patterns (lifetime of about 1 week or less for scales of 50-100 km) ought to hinder biomass transfer to zooplankton predators compared with phytoplankton patches that persist for longer times. We found no significant differences between the statistics of CZCS and AVHRR images (spectral shape or rate of decorrelation). In addition, in two of the three areas studied, the peak correlation between AVHRR and CZCS images from the same area occurred at zero lag, indicating that the patterns evolved simutaneously. In the third area, maximum coherence between thermal and pigment patterns occurred when pigment images lagged thermal images by 1-2 days, mirroring the expected lag of high pigment behind low temperatures (and high nutrients) in recently upwelled water. We conclude that in dynamic areas such as coastal upwelling systems, the phytoplankton cells (identified by pigment color patterns) behave largely as passive scalars at the mesoscale and that growth, death, and sinking of phytoplankton collectively play at most a mariginal role in determining the spectral statistics of the pigment patterns.

Denman, Kenneth L.↗

DOE OSTI2019

Resolving Detonation NanoDiamond Size Evolution and Morphology at Sub-Microsecond Time-Scales During High-Explosive Detonations

Characterization of the initial morphology of detonation nanodiamond (DND) has been the focus of many research studies that aim to develop fundamental understanding of carbon condensation under extreme conditions. Identifying the pathways of DND formation has the potential for significant impact in many of the controlled synthesis of nanoscale carbon with tailored functionality; currently, a wide range of possible (and conflicting) mechanisms of nucleation and growth have been proposed and further research is essential. Building a comprehensive understanding of DND formation is challenging because it requires in situ characterization on the sub-µs time-scale during a high explosive detonation. In this study, time resolved small angle X-ray scattering (TR-SAXS) is used to reveal the early-stage DND morphology from < 0.1 μs to 6 μs after the detonation front passes through the X-ray beam path. We address the ambiguity of models previously reported for analysis of small angle scattering from DND by comparing (i) in situ, TR-SAXS recorded during early-stage particulate formation and (ii) ex situ SAXS and transmission electron microscopy measurements (TEM) of products recovered from detonation of the same high-explosive within a carefully designed ice chamber. The SAXS from both late-time ( > 1 μs) in situ and recovered DND exhibit consistent features in the I(q) curve. Such close similarity allows a high fidelity SAXS model derived from the ex situ SAXS and TEM measurements to be applied to the in situ data, which yields new insight into the early stage (< 1µs) morphology of DND. Our analysis indicates a size-distribution of DND particles is observed within 0.1 μs post-detonation and have a mean core diameter slightly below 4 nm and surface texture that consists of hemispherical protrusions that extend ~ 1 nm from the surface. Beyond ~ 0.3 μs, the size distribution increases slightly, while the surface texture persists for several microseconds after the detonation. Combined with thermochemical simulations, these results indicate that during detonation of Composition B, carbon is condensed into nanoscale diamond much faster than previously reported in other studies. Furthermore, the surface texture of the DND is shown to arise during condensation rather than via subsequent graphitization.

carbon condensation↗

DOE OSTI2021

Structural and chemical evolution in layered oxide cathodes of lithium-ion batteries revealed by synchrotron techniques

Abstract Rechargeable battery technologies have revolutionized electronics, transportation and grid energy storage. Many materials are being researched for battery applications, with layered transition metal oxides (LTMO) the dominating cathode candidate with remarkable electrochemical performance. Yet, daunting challenges persist in the quest for further battery developments targeting lower cost, longer lifespan, improved energy density and enhanced safety. This is, in part, because of the intrinsic complexity of real-world batteries, featuring sophisticated interplay among microstructural, compositional and chemical heterogeneities, which has motivated tremendous research efforts using state-of-the-art analytical techniques. In this research field, synchrotron techniques have been identified as a suite of effective methods for advanced battery characterization in a non-destructive manner with sensitivities to the lattice, electronic and morphological structures. This article provides a holistic overview of cutting-edge developments in synchrotron-based research on LTMO battery cathode materials. We discuss the complexity and evolution of LTMO’s material properties upon battery operation and review recent synchrotron-based research works that address the frontier challenges and provide novel insights in this field. Finally, we formulate a perspective on future directions of synchrotron-based battery research, involving next-generation X-ray facilities and advanced computational developments.

25 ENERGY STORAGE↗

DOE OSTI2014

Interrogation of the Burkholderia pseudomallei genome to address differential virulence among isolates

Infection by the Gram-negative pathogen Burkholderia pseudomallei results in the disease melioidosis, acquired from the environment in parts of southeast Asia and northern Australia. Clinical symptoms of melioidosis range from acute (fever, pneumonia, septicemia, and localized infection) to chronic (abscesses in various organs and tissues, most commonly occurring in the lungs, liver, spleen, kidney, prostate and skeletal muscle), and persistent infections in humans are difficult to cure. Understanding the basic biology and genomics of B. pseudomallei is imperative for the development of new vaccines and therapeutic interventions. This formidable task is becoming more tractable due to the increasing number of B. pseudomallei genomes that are being sequenced and compared. Here, we compared three B. pseudomallei genomes, from strains MSHR668, K96243 and 1106a, to identify features that might explain why MSHR668 is more virulent than K96243 and 1106a in a mouse model of B. pseudomallei infection. Our analyses focused on metabolic, virulence and regulatory genes that were present in MSHR668 but absent from both K96243 and 1106a. We also noted features present in K96243 and 1106a but absent from MSHR668, and identified genomic differences that may contribute to variations in virulence noted among the three B. pseudomallei isolates. While this work contributes to our understanding of B. pseudomallei genomics, more detailed experiments are necessary to characterize the relevance of specific genomic features to B. pseudomallei metabolism and virulence. Functional analyses of metabolic networks, virulence and regulation shows promise for examining the effects of B. pseudomallei on host cell metabolism and will lay a foundation for future prediction of the virulence of emerging strains. Continued emphasis in this area will be critical for protection against melioidosis, as a better understanding of what constitutes a fully virulent Burkholderia isolate may provide for better diagnostic and medical countermeasure strategies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream

Although river ecosystems constitute a small fraction of Earth’s total area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. To address this gap, we assessed how viral and microbial communities change over a 48-hour period by sampling surface water and pore water compartments of the wastewater-impacted River Erpe in Germany. We sampled every 3 hours resulting in 32 samples for which we obtained metagenomes along with geochemical and metabolite measurements. From our metagenomes, we identified 6,500 viral and 1,033 microbial metagenome assembled genomes (MAGs) and found distinct community membership and abundance associated with each river compartment (e.g., Competibacteraceae in surfacewater and Sulfurimonadaceae in pore water). We show that 17% of our viral MAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to river carbon and nitrogen cycling via denitrification and nitrogen fixation. Together, these findings demonstrate that members of the surface water microbiome from this urban river are stable over multiple diurnal cycles. These temporal insights raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Use of Arrott plots to identify Néel temperature (T{sub N}) in metamagnetic Ni{sub 48}Co{sub 6}Mn{sub 26}Al{sub 20} polycrystalline ribbons

(Ni{sub 48}Co{sub 6})Mn{sub 26}Al{sub 20} polycrystalline ribbons with B2 structure at room temperature are investigated. Considering the presence of competing magnetic interactions, Arrott-plot analysis gives T{sub N} ∼ 170 K. A broad ferromagnetic-paramagnetic transition (T{sub C}) is observed at ∼200 K. H-T phase-diagram is used to validate the presence of competing exchange interactions that persist till very close to T{sub C}. Based on Néel theory, a cluster model is used to explain the presence of ferromagnetic and antiferromagnetic clusters in the sample. Formation of ferromagnetic clusters can be understood in terms of positive exchange interactions among the Mn atoms that are neighboring Co atoms located at Ni sites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

DOE OSTI2013

FAST STAR, SLOW STAR; OLD STAR, YOUNG STAR: SUBGIANT ROTATION AS A POPULATION AND STELLAR PHYSICS DIAGNOSTIC

Stellar rotation is a strong function of both mass and evolutionary state. Missions such as Kepler and CoRoT provide tens of thousands of rotation periods, drawn from stellar populations that contain objects at a range of masses, ages, and evolutionary states. Given a set of reasonable starting conditions and a prescription for angular momentum loss, we address the expected range of rotation periods for cool field stellar populations (∼0.4-2.0 M{sub ☉}). We find that cool stars fall into three distinct regimes in rotation. Rapid rotators with surface periods less than 10 days are either young low-mass main sequence (MS) stars, or higher mass subgiants which leave the MS with high rotation rates. Intermediate rotators (10-40 days) can be either cool MS dwarfs, suitable for gyrochronology, or crossing subgiants at a range of masses. Gyrochronology relations must therefore be applied cautiously, since there is an abundant population of subgiant contaminants. The slowest rotators, at periods greater than 40 days, are lower mass subgiants undergoing envelope expansion. We identify additional diagnostic uses of rotation periods. There exists a period-age relation for subgiants distinct from the MS period-age relations. There is also a period-radius relation that can be used as a constraint on the stellar radius, particularly in the interesting case of planet host stars. The high-mass/low-mass break in the rotation distribution on the MS persists onto the subgiant branch, and has potential as a diagnostic of stellar mass. Finally, this set of theoretical predictions can be compared to extensive datasets to motivate improved modeling.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Long-lived neutron-star remnants from asymmetric binary neutron star mergers: element formation, kilonova signals and gravitational waves

We present 3D general-relativistic neutrino-radiation hydrodynamics simulations of two asymmetric binary neutron star mergers producing long-lived neutron stars remnants and spanning a fraction of their cooling time scale. The mergers are characterized by significant tidal disruption with neutron rich material forming a massive disc around the remnant. The latter develops one-armed dynamics that is imprinted in the emitted kilo-Hertz gravitational waves. Angular momentum transport to the disc is initially driven by spiral-density waves and enhanced by turbulent viscosity and neutrino heating on longer timescales. The mass outflows are composed by neutron-rich dynamical ejecta of mass ∼10 −3 –10 −2 M ⊙ followed by a persistent spiral-wave/neutrino-driven wind of ≳ 10 −2 M ⊙ with material spanning a wide range of electron fractions, ∼0.1–0.55. Dynamical ejecta (winds) have fast velocity tails up to ∼0.8 (∼0.4) c. The outflows are further evolved to days timescale using 2D ray-by-ray radiation-hydrodynamics simulations that include an online nuclear network. We find complete r-process yields and identify the production of 56 Ni and the subsequent decay chain to 56 Co and 56 Fe. Synthetic kilonova light curves predict an extended (near-) infrared peak a few days postmerger originating from r-process in the neutron-rich/high-opacity ejecta and UV/optical peaks at a few hours (ten minutes) postmerger originating from weak r-process (free-neutron decay) in the faster ejecta components. Additionally, the fast tail of tidal origin generates kilonova afterglows potentially detectable in radio and X band on a few to ten years time scale. Quantitative effects originating from the tidal disruption merger dynamics are reflected in the multimessenger emissions.

abundances↗

DOE OSTI2023

Microbial necromass in cropland soils: A global meta-analysis of management effects

Microbial necromass is a large and persistent component of soil organic carbon (SOC), especially under croplands. The effects of cropland management on microbial necromass accumulation and its contribution to SOC have been measured in individual studies but have not yet been summarized on the global scale. For this study, we conducted a meta-analysis of 481-paired measurements from cropland soils to examine the management effects on microbial necromass and identify the optimal conditions for its accumulation. Nitrogen fertilization increased total microbial necromass C by 12%, cover crops by 14%, no or reduced tillage (NT/RT) by 20%, manure by 21%, and straw amendment by 21%. Microbial necromass accumulation was independent of biochar addition. NT/RT and straw amendment increased fungal necromass and its contribution to SOC more than bacterial necromass. Manure increased bacterial necromass higher than fungal, leading to decreased ratio of fungal-to-bacterial necromass. Greater microbial necromass increases after straw amendments were common under semi-arid and in cool climates in soils with pH <8, and were proportional to the amount of straw input. In contrast, NT/RT increased microbial necromass mainly under warm and humid climates. Manure application increased microbial necromass irrespective of soil properties and climate. Management effects were especially strong when applied during medium (3–10 years) to long (10+ years) periods to soils with larger initial SOC contents, but were absent in sandy soils. Close positive links between microbial biomass, necromass and SOC indicate the important role of stabilized microbial products for C accrual. Microbial necromass contribution to SOC increment (accumulation efficiency) under NT/RT, cover crops, manure and straw amendment ranged from 45% to 52%, which was 9%–16% larger than under N fertilization. In summary, long-term cropland management increases SOC by enhancing microbial necromass accumulation, and optimizing microbial necromass accumulation and its contribution to SOC sequestration requires site-specific management.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1987

Cluster analysis of multiple planetary flow regimes

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Mo, Kingtse↗