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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2022

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2023, with start- and end-of-season phenological transition dates derived through the end of autumn 2022. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step Contains 35 files in *.csv format inside a compressed (*.zip) file. Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) Contains one file in *.csv format Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. Contains three files in HTML format, one for each vegetation type One additional file in HTML format with the transition dates plotted for each vegetation type, by year R files for processing Phenocam files and flags. Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/y7z5mau7. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released phenocam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

SPRUCE Experiment, Marcell Experimental Forest, Sp↗
DOE OSTI2024

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2023

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2024, with start- and end-of-season phenological transition dates derived through the end of autumn 2023. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) • Contains one file in *.csv format (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure • Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type • One additional file in HTML format with the transition dates plotted for each vegetation type, by year (2) R files for processing Phenocam files and flags. • Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released data inclusive of the 2015-2022 data (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

Spruce and Peatland Responses Under Changing Envir↗
DOE OSTI2019

Information-rich localization microscopy through machine learning

Recent years have witnessed the development of single-molecule localization microscopy as a generic tool for sampling diverse biologically relevant information at the super-resolution level. While current approaches often rely on the target-specific alteration of the point spread function to encode the multidimensional contents of single fluorophores, the details of the point spread function in an unmodified microscope already contain rich information. Here we introduce a data-driven approach in which artificial neural networks are trained to make a direct link between an experimental point spread function image and its underlying, multidimensional parameters, and compare results with alternative approaches based on maximum likelihood estimation. To demonstrate this concept in real systems, we decipher in fixed cells both the colors and the axial positions of single molecules in regular localization microscopy data.

42 ENGINEERING↗
DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗
DOE OSTI2021

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing the fluid flow rates across the wells - and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. Data and supporting literature from a study describing a new approach combining reservoir modeling and machine learning to produce models that enable strategies for the mitigation of decreased heat and power production rates over time for geothermal power plants. The computational approach used enables translation of sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy and discovery of optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an "open-source" reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 hours, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 seconds. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs. Includes a synthetic, yet realistic, model of a geothermal reservoir, referred to as open-source reservoir (OSR). OSR is a 10-well (4 injection wells and 6 production wells) system that resembles Brady Hot Springs (a commercially operational geothermal field in Nevada, USA) at a high level but has a number of sufficiently modified characteristics (which renders any possible similarity between specific characteristics like temperatures and pressures as purely random). We study OSR through CMG simulations with a wide range of flow allocation scenarios. Includes a dataset with 101 simulated scenarios that cover the period of time between 2020 and 2040 and a link to the published paper about this project, where we focus on the Machine Learning work for predicting OSR's energy production based on the simulation data, as well as a link to the GitHub repository where we have published the code we have developed (please refer to the repository's readme file to see instructions on how to run the code). Additional links are included to associated work led by the USGS to identify geologic factors associated with well productivity in geothermal fields. Below are the high-level steps for applying the same modeling + ML process to other geothermal reservoirs: 1. Develop a geologic model of the geothermal field. The location of faults, upflow zones, aquifers, etc. need to be accounted for as accurately as possible 2. The geologic model needs to be converted to a reservoir model that can be used in a reservoir simulator, such as, for instance, CMG STARS, TETRAD, or FALCON 3. Using native state modeling, the initial temperature and pressure distributions are evaluated, and they become the initial conditions for dynamic reservoir simulations 4....

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Mach-Zehnder recording systems for pulsed power diagnostics

Fiber-optic transmission and recording systems, based on Mach-Zehnder modulators, have been developed and installed at the National Ignition Facility (NIF), and are being developed for other pulsed-power facilities such as the Z accelerator at Sandia, with different requirements. We present the design and performance characteristics for the mature analog links, based on the system developed for the Gamma Reaction History diagnostic at the OMEGA laser and at NIF. For a single detector channel, two Mach-Zehnders are used to provide high dynamic range at the full recording bandwidth with no gaps in the coverage. We present laboratory and shot data to estimate upper limits on the radiation effects as they impact recorded data quality. Finally, we will assess the technology readiness level for mature and developing implementations of Mach-Zehnder links for these environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Distance Restraints from Crosslinking Mass Spectrometry: Mining a Molecular Dynamics Simulation Database to Evaluate Lysine-Lysine Distances

Integrative structural biology models the structures of protein complexes that are intractable by classical structural methods (because of extreme size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such method is chemical cross-linking mass spectrometry (XL-MS), in which cross-linked peptides, derived from a covalently cross-linked protein complex and identified by liquid chromatography-mass spectrometry, pinpoint protein residues close in three-dimensional space. The commonly used lysine-reactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS3) have a linker arm that is 11.4 Å long when fully extended. However, XL-MS studies on proteins of known structure frequently report cross-links that exceed this distance. Typically, a tolerance of ~3 Å is added to the theoretical maximum to account for this observation, with little justification for the value chosen. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of all protein folds, to investigate the change in lysine-lysine distances resulting from native-state dynamics on the time-scale of tens of nanoseconds. We conclude that observed cross-links are consistent with a protein structure if the distance between cross-linked lysine Nζ atoms is less than the cross-linker length plus 11.3 Å. For DSS or BS3, this corresponds to a Cα to Cα distance of 30.4 Å. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures, and indicates the appropriate values of an XLMS derived distance constraint to use in structural modeling.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Photodissociative Cross-Linking of Non-covalent Peptide-Peptide Ion Complexes in the Gas Phase

We report a gas-phase UV photodissociation study investigating non-covalent interactions between neutral hydrophobic pentapeptides and peptide ions incorporating a diazirine-tagged photoleucine residue. Phenylalanine (Phe) and proline (Pro) were chosen as the conformation-affecting residues that were incorporated into a small library of neutral pentapeptides. Gas-phase ion-molecule complexes of these peptides with photo-labeled pentapeptides were subjected to photodissociation. Selective photocleavage of the diazirine ring at 355 nm formed short-lived carbene intermediates that underwent cross-linking by insertion into H–X bonds of the target peptide. The cross-link positions were established from collision-induced dissociation tandem mass spectra (CID-MS{sup 3}) providing sequence information on the covalent adducts. Effects of the amino acid residue (Pro or Phe) and its position in the target peptide sequence were evaluated. For proline-containing peptides, interactions resulting in covalent cross-links in these complexes became more prominent as proline was moved towards the C-terminus of the target peptide sequence. The photocross-linking yields of phenylalanine-containing peptides depended on the position of both phenylalanine and photoleucine. Density functional theory calculations were used to assign structures of low-energy conformers of the (GLPMG + GLL*LK + H){sup +} complex. Born-Oppenheimer molecular dynamics trajectory calculations were used to capture the thermal motion in the complexes within 100 ps and determine close contacts between the incipient carbene and the H–X bonds in the target peptide. This provided atomic-level resolution of potential cross-links that aided spectra interpretation and was in agreement with experimental data. .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

The small molecule 2-phenylethynesulfonamide induces covalent modification of p53

p53 is a tumor suppressor protein which is either lost or inactivated in a large majority of tumors. The small molecule 2-phenylethynesulfonamide (PES) was originally identified as the inhibitor of p53 effects on the mitochondrial death pathway. In this report we demonstrate that p53 protein from PES-treated cells was detected in reduced mobility bands between molecular weights 95–220 kDa. Resolution of p53 aggregates on urea gel was unable to reduce the high molecular weight p53 aggregates, which were shown to be primarily located in the nucleus. Therefore, our data suggest that PES exerts its effects through covalent cross-linking and nuclear retention of p53. - Highlights: • p53 protein is in high molecular weight complexes in the nucleus of PES-treated cells. • PES is a drug that inhibits pro-apoptotic p53 action at the mitochondria. • We propose that PES action involves cross-linking and nuclear retention of p53.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

A pandemic influenza modeling and visualization tool

The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a modeling and visualization toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects of the pandemic on the population through a spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Magnetic Structure and Exchange Interactions in Quasi-One-Dimensional MnCl 2 (urea) 2

MnCl 2 (urea) 2 is a new linear chain coordination polymer that exhibits slightly counter-rotated Mn 2 Cl 2 rhomboids along the chain-axis. The material crystallizes in the noncentrosymmetric orthorhombic space group Iba2, with each Mn(II) ion equatorially surrounded by four Cl – that lead to bibridged ribbons. Additionally, urea ligands coordinate via O atoms in the axial positions. Hydrogen bonds of the Cl···H–N and O···H–N type link the chains into a quasi-3D network. Magnetic susceptibility data reveal a broad maximum at 9 K that is consistent with short-range magnetic order. Pulsed-field magnetization measurements conducted at 0.6 K show that a fully polarized magnetic state is achieved at B sat = 19.6 T with another field-induced phase transition occurring at 2.8 T. Zero-field neutron diffraction studies made on a powdered sample of MnCl 2 (urea) 2 reveal that long-range magnetic order occurs below T N = 3.2(1) K. Additional Bragg peaks due to antiferromagnetic (AFM) ordering can be indexed according to the Ib'a2' magnetic space group and propagation vector τ = [0, 0, 0]. Rietveld profile analysis of these data revealed a Néel-type collinear ordering of Mn(II) ions with an ordered magnetic moment of 4.06(6) μ B (5 μ B is expected for isotropic S = 5/2) oriented along the b-axis, i.e., perpendicular to the chain-axis that runs along the c-direction. Owing to the potential for spatial exchange anisotropy and the pitfalls in modeling bulk magnetic data, we analyzed inelastic neutron scattering data to retrieve the exchange constants: J c = 2.22 K (intrachain), J a = -0.10 K (interchain), and D = -0.14 K with J > 0 assigned to AFM coupling. Lastly, this J configuration is most unusual and contrasts the more commonly observed AFM interchain coupling of 1D chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. Here, we end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.

58 GEOSCIENCES↗
DOE OSTI2019

Gene Ontology Causal Activity Modeling (GO-CAM) moves beyond GO annotations to structured descriptions of biological functions and systems

To increase the utility of Gene Ontology (GO) annotations for interpretation of genome-wide experimental data, we have developed GO-CAM, a structured framework for linking multiple GO annotations into an integrated model of a biological system. Here, we expect that GO-CAM will enable new applications in pathway and network analysis, as well as improve standard GO annotations for traditional GO-based applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Oral microbiome and mycobiome dynamics in cancer therapy-induced oral mucositis

Cancer therapy-induced oral mucositis is a frequent major oncological problem, secondary to cytotoxicity of chemo-radiation treatment. Oral mucositis commonly occurs 7–10 days after initiation of therapy; it is a dose-limiting side effect causing significant pain, eating difficulty, need for parenteral nutrition and a rise of infections. The pathobiology derives from complex interactions between the epithelial component, inflammation, and the oral microbiome. Our longitudinal study analysed the dynamics of the oral microbiome (bacteria and fungi) in nineteen patients undergoing chemo-radiation therapy for oral and oropharyngeal squamous cell carcinoma as compared to healthy volunteers. The microbiome was characterized in multiple oral sample types using rRNA and ITS sequence amplicons and followed the treatment regimens. Microbial taxonomic diversity and relative abundance may be correlated with disease state, type of treatment and responses. Identification of microbial-host interactions could lead to further therapeutic interventions of mucositis to re-establish normal flora and promote patients’ health. Data presented here could enhance, complement and diversify other studies that link microbiomes to oral disease, prophylactics, treatments, and outcome.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-D-BRB-04: Pinnacle Scripting: Improving Efficiency While Maintaining Safety

Scripting capabilities and application programming interfaces (APIs) are becoming commonly available in modern treatment planning systems. These links to the treatment planning system (TPS) allow users to read data from the TPS, and in some cases use TPS functionality and write data back to the TPS. Such tools are powerful extensions, allowing automation of routine clinical tasks and supporting research, particularly research involving repetitive tasks on large patient populations. The data and functionality exposed by scripting/API capabilities is vendor dependent, as are the languages used by script/API engines, such as the Microsoft .NET framework or Python. Scripts deployed in a clinical environment must be commissioned and validated like any other software tool. This session will provide an overview of scripting applications and a discussion of best practices, followed by a practical introduction to the scripting capabilities of three commercial treatment planning systems. Learning Objectives: Understand the scripting capabilities available in several treatment planning systems Learn how to get started using scripting capabilities Understand the best practices for safe script deployment in a clinical environment R. Popple, Varian Medical Systems has provided research support unrelated to the topic of this session.R. Cardan, Varian Medical Systems for grant research, product evaluation, and teaching honorarium.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Structures of Pathogenic Fungal FKBP12s Reveal Possible Self-Catalysis Function

Invasive fungal infections remain difficult to treat and require novel targeting strategies. The 12-kDa FK506-binding protein (FKBP12) is a ubiquitously expressed peptidyl-prolyl isomerase with considerable homology between fungal pathogens and is thus a prime candidate for future targeting efforts to generate a panfungal strategy. Despite decades of research on FKBPs, their substrates and mechanisms of action remain unclear. Here we describe structural, biochemical, and in vivo analyses of FKBP12s from the pathogenic fungi Candida albicans, Candida glabrata, and Aspergillus fumigatus. Strikingly, multiple apo A. fumigatus and C. albicans FKBP12 crystal structures revealed a symmetric, intermolecular interaction involving the deep insertion of an active-site loop proline into the active-site pocket of an adjacent subunit. Such interactions have not been observed in previous FKBP structures. This finding indicates the possibility that this is a self-substrate interaction unique to the A. fumigatus and C. albicans fungal proteins that contain this central proline. Structures obtained with the proline in the cis and trans states provide more data in support of self-catalysis. Moreover, cysteine cross-linking experiments captured the interacting dimer, supporting the idea that it forms in solution. Finally, genetic studies exploring the impact of mutations altering the central proline and an adjacent residue provide evidence that any dimeric state formed in vivo, where FKBP12 concentrations are low, is transient. Taken together, these findings suggest a unique mechanism of self-substrate regulation by fungal FKBP12s, lending further novel understanding of this protein for future drug-targeting efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Orbital controls on Namib Desert hydroclimate over the past 50,000 years

Abstract Despite being one of the world’s oldest deserts, and the subject of decades of research, evidence of past climate change in the Namib Desert is extremely limited. As such, there is significant debate regarding the nature and drivers of climate change in the low-latitude drylands of southwestern Africa. Here we present data from stratified accumulations of rock hyrax urine that provide the first continuous high-resolution terrestrial climate record for the Namib Desert spanning the past 50,000 yr. These data, spanning multiple sites, show remarkably coherent variability that is clearly linked to orbital cycles and the evolution and perturbation of global boundary conditions. Contrary to some previous predictions of southwestern African climate change, we show that orbital-scale cycles of hydroclimatic variability in the Namib Desert region are in phase with those of the northern tropics, with increased local summer insolation coinciding with periods of increased aridity. Supported by climate model simulations, our analyses link this to variations in position and intensity of atmospheric pressure cells modulated by hemispheric and land-sea temperature gradients. We conclude that hydroclimatic variability at orbital time scales is driven by the combined influence of direct low-latitude insolation forcing and the influence of remote controls on the South Atlantic anticyclone, with attendant impacts on upwelling and sea-surface temperature variations.

Geology↗