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At least 181 records · Page 10

Preliminary observations of velocity fields at the solar poles

Using the 13 m Littrow spectrograph at Sacramento Peak Observatory, the Doppler shift of Fe I 5863 A in the polar regions of the sun over a 20 day interval is studied. The daily observations were assembled into a polar projection of the line-of-sight velocity field. The projection shows a very clear pattern of supergranulation. When a low-pass spatial filter is run over the data, a pattern of large-scale (80-100 Mm) velocity features can be seen. Cross-correlation studies show that the supergranular pattern rotates with a synodic period of 35 days, while there is evidence that the larger features rotate with a shorter period of about 30 days. At present, it is not possible to say whether the large-scale patterns represent a new scale of convection (possibly related to the dominant convective eddy in the lower solar convection zone) or to the low-wavenumber tail of a distribution of supergranular cells.

Cram, L. E.↗

Monthly mean large-scale analyses of upper-tropospheric humidity and wind field divergence derived from three geostationary satellites

This paper describes the results from a collaborative study between the European Space Operations Center, the European Organization for the Exploitation of Meteorological Satellites, the National Oceanic and Atmospheric Administration, and the Cooperative Institute for Meteorological Satellite Studies investigating the relationship between satellite-derived monthly mean fields of wind and humidity in the upper troposphere for March 1994. Three geostationary meteorological satellites GOES-7, Meteosat-3, and Meteosat-5 are used to cover an area from roughly 160 deg W to 50 deg E. The wind fields are derived from tracking features in successive images of upper-tropospheric water vapor (WV) as depicted in the 6.5-micron absorption band. The upper-tropospheric relative humidity (UTH) is inferred from measured water vapor radiances with a physical retrieval scheme based on radiative forward calculations. Quantitative information on large-scale circulation patterns in the upper-troposphere is possible with the dense spatial coverage of the WV wind vectors. The monthly mean wind field is used to estimate the large-scale divergence; values range between about-5 x 10(exp -6) and 5 x 10(exp 6)/s when averaged over a scale length of about 1000-2000 km. The spatial patterns of the UTH field and the divergence of the wind field closely resemble one another, suggesting that UTH patterns are principally determined by the large-scale circulation. Since the upper-tropospheric humidity absorbs upwelling radiation from lower-tropospheric levels and therefore contributes significantly to the atmospheric greenhouse effect, this work implies that studies on the climate relevance of water vapor should include three-dimensional modeling of the atmospheric dynamics. The fields of UTH and WV winds are useful parameters for a climate-monitoring system based on satellite data. The results from this 1-month analysis suggest the desirability of further GOES and Meteosat studies to characterize the changes in the upper-tropospheric moisture sources and sinks over the past decade.

Schmetz, Johannes↗

Seasonal and Geographical Variations in Fundamental Weather Patterns during Extreme Precipitation as Identified from Omega Equation Forcing

Abstract We investigate the large-scale weather patterns during extreme precipitation (PEx) events over the conterminous United States (CONUS) by applying a version of the quasigeostrophic (QG) omega equation. This work aims to develop a climatology of the weather patterns most related to PEx events during current climate. Extreme events are examined for each of seven regions defined by consistent annual cycles of precipitation and spanning the CONUS. For the CONUS we train several self-organizing maps (SOM) on a pressure–time series of vertical velocity from each of the advective forcing terms in the QG omega equation for each extreme event. The unsupervised learning of the SOM allows us to identify the most descriptive set of nine patterns in vertical velocity associated with precipitation extremes. This method finds multiple frontal- and cyclone-driven patterns while grouping primarily convective events into one pattern. Frontal events include a synoptic pattern consistent with West Coast atmospheric river events as well as pattern groups linked to developing and to mature (“occluded”) frontal cyclones. The primary patterns found during PEx events vary seasonally and geographically. Frontal cyclone patterns are most common during PEx events during summer in the part of the Great Plains and during winter for the Northeast, Southeast, Pacific Northwest, and Southwest. Convection is the most common pattern during summer in all regions. Except in the Southeast, the annual cycles of monthly number of PEx events and average precipitation match well, partially validating our choice of regions to aggregate PEx events.

Meteorology & Atmospheric Sciences↗

Symmetry-breaking-induced rare fluctuations in a time-delay dynamic system

Inspired by the experimental and numerical findings, we study the dynamic instabilities of two coupled nonlinear delay differential equations that are used to describe the coherent oscillations between the top and bottom boundary layers in turbulent Rayleigh–Bénard convection. By introducing two sensitivity parameters for the instabilities of the top and bottom boundary layers, we find three different types of solutions, namely in-phase single-period oscillations, multi-period oscillations and chaos. The chaos solution contains rare but large amplitude fluctuations. The statistical properties of these fluctuations are consistent with those observed in the experiment for the massive eruption of thermal plumes, which causes random reversals of the large-scale circulation in turbulent Rayleigh–Bénard convection. Finally, our study thus provides new insights into the origin of rare massive eruptions and sudden changes of large-scale flow pattern that are often observed in convection systems of geophysical and astrophysical scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hoop/column antenna RF verification model. Volume 2: Analysis and correlation

As part of the Large Space System Technology Program, the theoretical and experimental results of the RF characteristic of a hoop/column, quad aperture antenna using an RF verification model are presented. To satisfy the primary purposes of the model, experimental pattern data is provided for the quad aperture configuration at different reflector edge illumination levels, from which the geometry and edge effects can be assessed, and experimental data which can be compared with calculations using various theoretical reflector scattering formulae are provided. It also experimentally determines the effects upon secondary patterns of scale model quartz cables, as used in the hoop/column design, upon secondary patterns in order to assess the importance of developing a scattering theory to predict such effects. In addition, a comprehensive theoretical study and the experimental pattern results of quad aperture antenna feeds, a discussion of the fundamental affect of parasitic side lobes, their amplitude, and location in space.

Croswell, W. F.↗

Hoop/Column Antenna: RF Verification Model. Volume 1: Test Results

As part of the Large Space System Technology Program, this report, in two volumes, presents the theoretical and experimental results of the RF characteristic of a hoop/column, quad aperture antenna using an RF verification model. To satisfy the primary purposes of the model it provides experimental pattern data for the quad aperture configuration at different reflector edge illumination levels, from which the geometry and edge effects can be assessed, and provides experimental data which can be compared with calculations using various theoretical reflector scattering formulae. It also experimentally determines the effects upon secondary patterns of scale model quartz cables, as used in the hoop/column design, upon secondary patterns in order to assess the importance of developing a scattering theory to predict such effects. In addition, this report contains a comprehensive theoretical study and the experimental pattern results of quad aperture antenna feeds, a discussion of the fundamental affect of parasitic side lobes, their amplitude, and location in space.

Croswell, W. F.↗

The rotation of photospheric magnetic fields: A random walk transport model

In an earlier study of solar differential rotation, we showed that the transport of magnetic flux across latitudes acts to establish quasi-stationary patterns, therby accounting for the observed rigid rotation of the large-scale photospheric field. In that paper, the effect of supergranular convection was represented by a continuum diffusion, limiting the applicability of the calculations to large spatial scales. Here we extend the model to scales comparable to that of the supergranulation itself by replacing the diffusive transport with a discrete random walk process. Rotation curves are derived by cross-correlating the simulated photospheric field maps for a variety of time lags and spatial resolutions. When the lag between maps is relatively short less than or approximately = 15 days), the midlatitude correlation functions show two distinct components: a broad feature associated with the large-scale unipolar patterns and a narrow feature originating from small magnetic structures encompossing from one to several supergranular cells. By fitting the broad component we obtain the rigid rotation profile of the patterns, whereas by fitting the narrow component, we recover the differential rate of the photospheric plasma itself. For time lags of 1 month or greater, only the broad feature associated with the long-lived patterns remains clearly identifiable in the simulations.

Wang, Y. -M.↗

Three-Dimensional Simulations of Mantle Convection in Io

Io has very high surface heat flow and an abundance of volcanic activity, which are thought to be driven by nonuniform tidal heating in its interior. This nonuniform heat is transported to the base of the lithosphere by very vigorous convection in Io's silicate mantle, the form of which is presumably responsible for the distribution of surface features such as volcanoes and mountains. We here present three-dimensional spherical calculations of mantle convection in Io, in order to ascertain the likely form of this convection and the resulting distribution of heat flow at the surface and core-mantle boundary. Different models of tidal dissipation are considered: the endmember scenarios (identified by M. N. Ross and G. Schubert) of dissipation in the entire mantle, or dissipation in a thin (approximately 100-km-thick) asthenosphere, as well as the 'preferred' distribution of M. N. Ross et al. comprising 1/3 mantle and 2/3 asthenosphere heating. The thermal structure of Io's mantle and asthenosphere is found to be strongly dependent on tidal heating mode, as well as whether the mantle-asthenosphere boundary is permeable or impermeable. Results indicate a large-scale flow pattern dominated by the distribution of tidal heating, with superimposed small-scale asthenospheric instabilities that become more pronounced with increasing Rayleigh number. These small-scale instabilities spread out the surface heat flux, resulting in smaller heat flux variations with increasing Rayleigh number. Scaled to Io's Rayleigh number of O(10(exp 12)) variations of order a few percent are expected. This small but significant variation in surface heat flux may be compatible with the observed distributions of volcanic centers and mountains, which appear fairly uniform at first sight but display a discernible distribution when suitably processed. The observed distribution of volcanic centers is similar to the asthenosphere heating distribution, implying that most of the tidal heating in Io occurs in an asthenosphere.

Tackley, Paul J.↗

Method and apparatus for two-dimensional absolute optical encoding

This invention presents a two-dimensional absolute optical encoder and a method for determining position of an object in accordance with information from the encoder. The encoder of the present invention comprises a scale having a pattern being predetermined to indicate an absolute location on the scale, means for illuminating the scale, means for forming an image of the pattern; and detector means for outputting signals derived from the portion of the image of the pattern which lies within a field of view of the detector means, the field of view defining an image reference coordinate system, and analyzing means, receiving the signals from the detector means, for determining the absolute location of the object. There are two types of scale patterns presented in this invention: grid type and starfield type.

Leviton, Douglas B.↗

The South Pacific convergence zone (SPCZ): A review

The circulation features associated with the South Pacific convergence zone (SPCZ) and its accompanying cloud band are reviewed and discussed. The paper focuses on the following topics: location, structure, and characteristics of the SPCZ; theories and observations concerning its existence; the significance and scope of the SPCZ in global-scale circulation patterns; quasi-periodic changes in its location and strength; and synoptic-scale features within its regional influence (e.g., cyclones, subtropical jets). It concludes with some challenging problems for the future.

Vincent, Dayton G.↗

Experimental Examination of Additively Manufactured Patterns on Structural Nuclear Materials for Digital Image Correlation Strain Measurements

Abstract Background There are a limited number of commercially available sensors for monitoring the deformation of materials in-situ during harsh environment applications, such as those found in the nuclear and aerospace industries. Such sensing devices, including weldable strain gauges, extensometers, and linear variable differential transformers, can be destructive to material surfaces being investigated and typically require relatively large surface areas to attach (> 10 mm in length). Digital image correlation (DIC) is a viable, non-contact alternative to in-situ strain deformation. However, it often requires implementing artificial patterns using splattering techniques, which are difficult to reproduce. Objective Additive manufacturing capabilities offer consistent patterns using programmable fabrication methods. Methods In this work, a variety of small-scale periodic patterns with different geometries were printed directly on structural nuclear materials (i.e., stainless steel and aluminum tensile specimens) using an aerosol jet printer (AJP). Unlike other additive manufacturing techniques, AJP offers the advantage of materials selection. DIC was used to track and correlate strain to alternative measurement methods during cyclic loading, and tensile tests (up to 1100 µɛ) at room temperature. Results The results confirmed AJP has better control of pattern parameters for small fields of view and facilitate the ability of DIC algorithms to adequately process patterns with periodicity. More specifically, the printed 100 μm spaced dot and 150 μm spaced line patterns provided accurate measurements with a maximum error of less than 2% and 4% on aluminum samples when compared to an extensometer and commercially available strain gauges. Conclusion Our results highlight a new pattern fabrication technique that is form factor friendly for digital image correlation in nuclear applications.

Novich, K. A. (ORCID:0000000204466022)↗

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗

Remote sensing from unoccupied aerial systems: Opportunities to enhance Arctic plant ecology in a changing climate

The Arctic is warming at a faster rate than any other biome on Earth, resulting in widespread changes in vegetation composition, structure, and function that have important feedbacks to the global climate system. The heterogeneous nature of arctic landscapes creates challenges for monitoring and improving understanding of these ecosystems, as current efforts typically rely on ground, airborne, or satellite-based observations that are limited in space, time, or pixel resolution. The use of remote sensing instruments on small Unoccupied Aerial Systems (UASs) has emerged as an important tool to bridge the gap between detailed, but spatially limited ground-level measurements, and lower resolution, but spatially extensive high-altitude airborne and satellite observations. UASs allow researchers to view, describe and quantify vegetation dynamics at fine spatial scales (1-10 cm) over areas much larger than typical field plots. UASs can be deployed with a high degree of temporal flexibility, enabling observation across diurnal, seasonal, and annual timescales. In this work, we review how established and emerging UAS remote sensing technologies can enhance arctic plant ecological research by quantifying fine-scale vegetation patterns and processes, and by enhancing the ability to link ground-based measurements with broader-scale information obtained from airborne and satellite platforms. Synthesis: Improved ecological understanding and model representation of arctic vegetation is needed to forecast the fate of the Arctic in a rapidly changing climate. Observations from UASs provide an approach to address this need, however, the use of this technology in the Arctic currently remains limited. Here we share recommendations to better enable and encourage the use of UASs to improve the description, scaling, and model representation of arctic vegetation.

54 ENVIRONMENTAL SCIENCES↗

Modeling spatial patterns of longleaf pine needle dispersal using long-term data

Abstract Background Predicting patterns of fire behavior and effects in frequent fire forests relies on an understanding of fine-scale spatial patterns of available fuels. Leaf litter is a significant canopy-derived fine fuel in fire-maintained forests. Litter dispersal is dependent on foliage production, stand structure, and wind direction, but the relative importance of these factors is unknown. Results Using a 10-year litterfall dataset collected within eighteen 4-ha longleaf pine ( Pinus palustris Mill.) plots varying in canopy spatial pattern, we compared four spatially explicit models of annual needle litter dispersal: a model based only on basal area, an overstory abundance index (OAI) model, both isotropic and anisotropic litter kernel models, and a null model that assumed no spatial relationship. The best model was the anisotropic model (R 2 = 0.656) that incorporated tree size, location, and prevailing wind direction, followed by the isotropic model (R 2 = 0.612), basal area model (R 2 = 0.488), OAI model (R 2 = 0.416), and the null model (R 2 = 0.08). Conclusions As with previous studies, the predictive capability of the litter models was robust when internally validated with a subset of the original dataset (R 2 = 0.196–0.549); however, the models were less robust when challenged with an independent dataset (R 2 = 0.122–0.319) from novel forest stands. Our model validation underscores the need for rigorous tests with independent, external datasets to confirm the validity of litter dispersal models. These models can be used in the application of prescribed fire to estimate fuel distribution and loading, as well as aid in the fine tuning of fire behavior models to better understand fire outcomes across a range of forest canopy structures.

54 ENVIRONMENTAL SCIENCES↗

Production regimes in four eastern boundary current systems

High productivity (maxima ~3 g C m(sup -2)day(sup -1)) of the Eastern Boundary Currents (EBCs), i.e. the California, Peru-Humboldt, Canary and Benguela Currents, is driven by a combination of local forcing and large-scale circulation. The characteristics of the deep water brought to the surface by upwelling favorable winds depend on the large-scale circulation patterns. Here we use a new hydrographic and nutrient climatology together with satellite measurements ofthe wind vector, sea-surface temperature (SST), chlorophyll concentration, and primary production modeled from ocean color to quantify the meridional and seasonal patterns of upwelling dynamics and biological response. The unprecedented combination of data sets allows us to describe objectively the variability for small regions within each current and to characterize the governing factors for biological production. The temporal and spatial environmental variability was due in most regions to large-scale circulation, alone or in combination with offshore transport (local forcing). The observed meridional and seasonal patterns of biomass and primary production were most highlycorrelated to components representing large-scale circulation. The biomass sustained by a given nutrient concentration in the Atlantic EBCs was twice as large as that of the Pacific EBCs. This apparent greater efficiency may be due toavailability of iron, physical retention, or differences in planktonic community structure.

circulation patternsoceans↗

Future projections of wind patterns in California with the variable-resolution CESM: a clustering analysis approach

Wind energy production is expected to be affected by shifts in wind patterns that will accompany climate change. However, many questions remain on the magnitude and character of this impact, especially on regional scales. In this study, clustering is used to group and analyze large-scale wind patterns in California using model simulations from the variable-resolution Community Earth System Model (VR-CESM). Specifically, simulations have been produced that cover historical (1980–2000), mid-century (2030–2050), and end-of-century (2080–2100) time periods. Once clustered, observed changes to wind patterns can be analyzed in terms of both the change in frequency of those clusters and changes to winds within-clusters. Statistically significant capacity factors changes have been found at all five wind plant sites. Further, decomposition of the capacity factor changes into frequency changes and within-cluster changes enables a better understanding of their drivers. A further examination of the synoptic-scale fields associated with each cluster then provides a better understanding of how changes to large-scale meteorological fields are important for driving changes in localized wind speeds.

17 WIND ENERGY↗

Assessing the large-scale drivers of precipitation in the northeastern United States via linear orthogonal decomposition

This study examines the linear orthogonal modes associated with monthly precipitation in the northeastern United States, from CESM1 LENS (35 ensemble members, 1979–2005) and two reanalysis datasets (ERA5, 1950–2018 and NOAA-CIRES-DOE 20CRv3, 1950–2015). Calendar months are aggregated together, and any linear trends in data are removed. Using region-averaged precipitation anomaly time series and monthly anomalies for several global 2D atmospheric fields, a linear orthogonal decomposition method is implemented to iteratively extract time series (based on field and geographic location) of absolute maximum correlation. Linear modes associated with this method are then projected onto the full set of 2D fields to provide physical insight into the mechanisms involved in generating precipitation. In this region, the first mode is associated with vapor transport from the Atlantic seaboard, the second mode is characterized by westward vapor transport associated with extratropical cyclones, and the third mode captures vapor transport from the Gulf of Mexico during the fall and winter. However, the third mode is less robust in the spring and summer. Results are generally consistent across the datasets, and applying multiple linear regression with the linear modes to predict the precipitation anomalies produces R-squared values of around 0.54–0.65 for CESM1 LENS, and around 0.58–0.88 for reanalysis, with the lowest values generally in the spring and late summer. The influence of low-frequency climate variability on the modes is considered for CESM1 LENS, and the modes in late winter can be predicted with some success via a combination of several, prominent large-scale teleconnection patterns.

54 ENVIRONMENTAL SCIENCES↗