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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fungal diversity and function in metagenomes sequenced from extreme environments

Fungi are increasingly recognized as key players in various extreme environments. Here we present an analysis of publicly-sourced metagenomes from global extreme environments, focusing on fungal taxonomy and function. The majority of 855 selected metagenomes contained scaffolds assigned to fungi. Relative abundance of fungi was as high as 10% of protein-coding genes with taxonomic annotation, with up to 289 fungal genera per sample. Despite taxonomic clustering by environment, fungal communities were more dissimilar than archaeal and bacterial communities, both for within- and between-environment comparisons. Relatively abundant fungal classes in extreme environments included Dothideomycetes, Eurotiomycetes, Leotiomycetes, Pezizomycetes, Saccharomycetes, and Sordariomycetes. Broad generalists and prolific aerial spore formers were the most relatively abundant fungal genera detected in most of the extreme environments, bringing up the question of whether they are actively growing in those environments or just surviving as spores. More specialized fungi were common in some environments, such as zoosporic taxa in cryosphere water and hot springs. Relative abundances of genes involved in adaptation to general, thermal, oxidative, and osmotic stress were greatest in soda lake, acid mine drainage, and cryosphere water samples.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Validation and functional characterization of transcription factors in wheat using cell-free protein expression and high-throughput sequencing technologies

Transcription factors (TFs) are critical biomolecules that control and regulate gene expression in every organism. In wheat, there are 3,606 genes annotated as putative TFs which are primarily uncharacterized. In this work, using a DAP-seq approach, we have validated and characterized a select number of TFs (5bl and 5dl) belonging to GeBP family of proteins, responsible for plant cellular growth, development, and differentiation. We found that top DNA binding motifs for 5bl and 5dl are (G/T)N(T/G)GTGGT and (C/G)AA(C/G)AA respectively. These motifs/peaks are enriched in the promoter regions of the genes, which are associated with rRNA biogenesis and protein maturation pathways. This study is also a first demonstration that DAP-seq can be applied for such a complex and large genome such as wheat.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Characterization of Multiple Trichloroethene, cis-Dichloroethene and 1,1-Dichloroethene Degrading Propanotrophic Communities

Aerobic cometabolism offers a viable strategy for the remediation of chlorinated solvent plumes at oxic sites where anaerobic approaches are limited. In this study, propane-enriched mixed cultures (derived from agricultural soils and an impacted site sediment) which previously degraded 1,4-dioxane, were evaluated for their capacity to also degrade trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), and 1,1-dichloroethene (1,1-DCE) over successive transfers. Sustained biodegradation of TCE and cDCE was observed across multiple enrichments, and cultures enriched on one compound generally degraded the other. In contrast, 1,1-DCE biodegradation was restricted to a subset of cultures and removal times increased over transfers. Further, 1,1-DCE removal was absent at elevated concentrations, both trends consistent with inhibitory or toxic effects. Whole genome sequencing analyses revealed pronounced substrate-dependent selection of microbial communities, with cDCE-degrading cultures being dominated by Mycobacterium and Mycolicibacterium, whereas TCE-degrading cultures were dominated by Rhodococcus. Rhodococcus metagenome-assembled genomes (MAGs) in the TCE degrading cultures classified as R. opacus or R. wratislaviensis. 1,1-DCE degrading cultures were dominated by Pseudonocardia, although the associated MAGs contained a truncated propane monooxygenase alpha subunit. Functional gene analysis identified both group 5 (prmABCD) and putative group 6 propane monooxygenases. The following KBase narratives contain the quality controlled reads, MAGs (fasta assemblies) and the prokka annotations for each assembly TCE Site 1A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254918) TCE Soil 2A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254919) TCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254920) TCE Soil T4 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254921) cDCE Site 1A 1B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254915) cDCE Soils T2 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254927) cDCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254928) cDCE Soil 4A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254942) 1,1-DCE T2 T3 Propanotrophic MAGs (https://narrative.kbase.us/narrative/254903)

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The mutation atlas of giant kelp (Macrocystis pyrifera): a mutation database resource for natural knockouts

Giant kelp (Macrocystis pyrifera) is a paramount species of immense ecological and economic importance. It forms dense underwater forests, providing crucial habitat and serving as a foundation species for diverse marine ecosystems. Understanding the genetics of giant kelp is essential for conservation and sustainable farming, safeguarding these valuable ecosystems and their benefits. By analyzing mutations based on their impact, we can gain insights into the potential functional consequences and implications for the organism, helping to identify critical genes or regions that may play a significant role in adaptation, development, and environmental response. To achieve this, we annotated the effects and impact of spontaneous mutations in 559 giant kelp individuals from four different populations. We found over 15.9 million mutations in genes of giant kelp, and classified them into modifier, low, moderate, and high impact depending on their predicted effects. The creation of this mutation effect database, attached to the seedbank of these individuals, offers several applications, including enhancing breeding programs, aiding genetic engineering with naturally occurring mutations, and developing strategies to mitigate the impact of environmental changes.

Plant Sciences↗
DOE OSTI2025

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Separation of life stages within anaerobic fungi (Neocallimastigomycota) highlights differences in global transcription and metabolism

Anaerobic gut fungi of the phylum Neocallimastigomycota are microbes proficient in valorizing low-cost but difficult-to-breakdown lignocellulosic plant biomass. Characterization of different fungal life stages and how they contribute to biomass breakdown are critical for biotechnological applications, yet we lack foundational knowledge about the transcriptional, metabolic, and enzyme secretion behavior of different life stages of anaerobic gut fungi: zoospores, germlings, immature thalli, and mature zoosporangia. A Miracloth-based technique was developed to enrich cell pellets with zoospores - the free-swimming, flagellated, young life stage of anaerobic gut fungi. By contrast, fungal mats contained relatively more vegetative, encysted, mature sporangia that form films. Global gene expression profiles were compared from two sample types (zoospore-enriched cell pellets vs. mature mats) harvested from the anaerobic gut fungal strain Neocallimastix californiae G1. Despite cultures being grown on glucose, the fungal zoospore-enriched samples were transcriptionally primed to encounter plant matter substrate, as evidenced by upregulation of catabolic carbohydrate-active enzymes and putative carbohydrate transporters. Furthermore, we report significant differential gene expression for gene annotation groups, including putative secondary metabolites and transcription factors. Understanding global gene expression differences between the fungal zoospore-enriched cells and mature fungi aid in characterizing fungal development, unmasking gene function, and guiding cultivation conditions and engineering targets to promote enzyme secretion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Application of unsupervised deep learning to image segmentation and in-situ contact angle measurements in a CO 2 -water-rock system

Rock surface wettability is a critical property that regulates multiphase flows in porous media, which can be quantified using the surface contact angle (CA). X-ray micro-computed tomography (μCT) provides an effective approach to in-situ measurements of surface CAs. However, the CA measurement accuracy depends significantly on the quality of CT image segmentation, which is the clustering of CT pixels into separate phases. Inspired by this, we developed a deep learning (DL)-based CA measurement workflow. Motivated by the recent tremendous progress in unsupervised learning techniques and aiming to avoid expensive manual data annotations, an unsupervised DL pipeline for CT image segmentation was proposed and implemented, which includes unsupervised model training and post-processing. The unsupervised model training was driven by a novel loss function constrained with feature similarity and spatial continuity and implemented by iterative forward and backward paths; the former clustered the pixel-wise feature vectors extracted by convolution neural networks, whereas the latter updated the parameters using gradient descent. An over-segmentation strategy was adopted for model training. The post-processing steps based on agglomerative hierarchical clustering (AHC) were implemented to further merge the over-segmented model output to the desired cluster number, which is intended to improve the efficiency of image segmentation. The developed unsupervised DL pipeline was compared with other commonly-used image segmentation methods using pixel-wise and physics-based evaluation metrics on a synthetic raw-image dataset, which had a known ground truth. The unsupervised DL pipeline showed the best performance. Next, the segmented images were input to an automatic CA measurement tool, and the results were validated by comparisons with manual measurements. The CA values from the manual and automatic measurements showed similar distributions and statistical properties. The automatic measurement demonstrated a wider spectrum because of the much larger number of measurement data points. The primary novelty of the unsupervised DL pipeline developed in this study lies in the novel loss function and the over-segmentation strategy associated with AHC post-processing. Finally, the workflow has been proven an efficient tool for pore-scale wettability characterization, which has a wide range of applications in fundamental studies of multiphase flows in natural porous media, which have critical implications to geological carbon sequestration, hydrocarbon energy recovery, and contaminant transport in groundwater.

42 ENGINEERING↗
DOE OSTI2020

Perspectives on ENCODE

The Encyclopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression. The project has been extended to model organisms, particularly the mouse. Finally, in the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Rover requirements for the planet surface segment of the space exploration initiative

Annotated requirements for rovers to be used for the First Lunar Outpost (FLO) of the Space Exploration Initiative (SEI) and for Mars missions are presented. The requirements are presented in the form of functions as opposed to performance. SEI surface systems will be required to execute many roving vehicle functions ranging from transporting humans to recovery and transporting raw materials to a processing plant. Some of the roving vehicles will be highly automated. These automation functions may include the following: teleoperated site survey and certification; teleoperation for repair; autonomous operations for resource location and mining; autonomous navigation and terrain traverse; and telerobotic scientific investigations. These requirements are complex, contradictory, and will be costly if they are not carefully analyzed and properly allocated to conceptual elements. Of greatest importance will be the iterative analysis of requirements and synergistic utilization of vehicle elements.

Roberts, Barney B.↗
DOE OSTI2024

Biological Parts Search Portal (BioParts) v1.0.0

BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.

Plahar, Hector↗
DOE OSTI2021

A Preprocessing Tool for Enhanced Ion Mobility–Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility–mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Further, other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bactericidal effectors of the Stenotrophomonas maltophilia type IV secretion system: functional definition of the nuclease TfdA and structural determination of TfcB

ABSTRACT Stenotrophomonas maltophilia expresses a type IV protein secretion system (T4SS) that promotes contact-dependent killing of other bacteria and does so partly by secreting the effector TfcB. Here, we report the structure of TfcB, comprising an N-terminal domain similar to the catalytic domain of glycosyl hydrolase (GH-19) chitinases and a C-terminal domain for recognition and translocation by the T4SS. Utilizing a two-hybrid assay to measure effector interactions with the T4SS coupling protein VirD4, we documented the existence of five more T4SS substrates. One of these was protein 20845, an annotated nuclease. A S. maltophilia mutant lacking the gene for 20845 was impaired for killing Escherichia coli , Klebsiella pneumoniae , and Pseudomonas aeruginosa . Moreover, the cloned 20845 gene conferred robust toxicity, with the recombinant E. coli being rescued when 20845 was co-expressed with its cognate immunity protein. The 20845 effector was an 899 amino-acid protein, comprised of a GHH-nuclease domain in its N-terminus, a large central region of indeterminant function, and a C-terminus for secretion. Engineered variants of the 20845 gene that had mutations in the predicted catalytic site did not impede E. coli , indicating that the antibacterial effect of 20845 involves its nuclease activity. Using flow cytometry with DNA staining, we determined that 20845, but not its mutant variants, confers a loss in DNA content of target bacteria. Database searches revealed that uncharacterized homologs of 20845 occur within a range of bacteria. These data indicate that the S. maltophilia T4SS promotes interbacterial competition through the action of multiple toxic effectors, including a potent, novel DNase. IMPORTANCE Stenotrophomonas maltophilia is a multi-drug-resistant, Gram-negative bacterium that is an emerging pathogen of humans. Patients with cystic fibrosis are particularly susceptible to S. maltophilia infection. In hospital water systems and various types of infections, S. maltophilia co-exists with other bacteria, including other pathogens such as Pseudomonas aeruginosa . We previously demonstrated that S. maltophilia has a functional VirB/D4 type VI protein secretion system (T4SS) that promotes contact-dependent killing of other bacteria. Since most work on antibacterial systems involves the type VI secretion system, this observation remains noteworthy. Moreover, S. maltophilia currently stands alone as a model for a human pathogen expressing an antibacterial T4SS. Using biochemical, genetic, and cell biological approaches, we now report both the discovery of a novel antibacterial nuclease (TfdA) and the first structural determination of a bactericidal T4SS effector (TfcB).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Morphogene-assisted transformation of Sorghum bicolor allows more efficient genome editing

Sorghum bicolor (L.) Moench, the fifth most important cereal worldwide, is a multi-use crop for feed, food, forage and fuel. To enhance the sorghum and other important crop plants, establishing gene function is essential for their improvement. For sorghum, identifying genes associated with its notable abiotic stress tolerances requires a detailed molecular understanding of the genes associated with those traits. The limits of this knowledge became evident from our earlier in-depth sorghum transcriptome study showing that over 40% of its transcriptome had not been annotated. Here, we describe a full spectrum of tools to engineer, edit, annotate and characterize sorghum’s genes. Efforts to develop those tools began with a morphogene-assisted transformation (MAT) method that led to accelerated transformation times, nearly half the time required with classical callus-based, non-MAT approaches. These efforts also led to expanded numbers of amenable genotypes, including several not previously transformed or historically recalcitrant. Another transformation advance, termed altruistic, involved introducing a gene of interest in a separate Agrobacterium strain from the one with morphogenes, leading to plants with the gene of interest but without morphogenes. The MAT approach was also successfully used to edit a target exemplary gene, phytoene desaturase. To identify single-copy transformed plants, we adapted a high-throughput technique and also developed a novel method to determine transgene independent integration. These efforts led to an efficient method to determine gene function, expediting research in numerous genotypes of this widely grown, multi-use crop.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Crystallization↗
DOE OSTI2023

Metatranscriptomics sheds light on the links between the functional traits of fungal guilds and ecological processes in forest soil ecosystems

Soil fungi belonging to different functional guilds, such as saprotrophs, pathogens, and mycorrhizal symbionts, play key roles in forest ecosystems. To date, no study has compared the actual gene expression of these guilds in different forest soils. We used metatranscriptomics to study the competition for organic resources by these fungal groups in boreal, temperate, and Mediterranean forest soils. Using a dedicated mRNA annotation pipeline combined with the JGI MycoCosm database, we compared the transcripts of these three fungal guilds, targeting enzymes involved in C- and N mobilization from plant and microbial cell walls. Genes encoding enzymes involved in the degradation of plant cell walls were expressed at a higher level in saprotrophic fungi than in ectomycorrhizal and pathogenic fungi. However, ectomycorrhizal and saprotrophic fungi showed similarly high expression levels of genes encoding enzymes involved in fungal cell wall degradation. Transcripts for N-related transporters were more highly expressed in ectomycorrhizal fungi than in other groups. Here, we showed that ectomycorrhizal and saprotrophic fungi compete for N in soil organic matter, suggesting that their interactions could decelerate C cycling. Metatranscriptomics provides a unique tool to test controversial ecological hypotheses and to better understand the underlying ecological processes involved in soil functioning and carbon stabilization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

RCSB protein data Bank: Next‐generation advanced search for exploration of experimental structures and computed structure models

Abstract The Protein Data Bank (PDB), established in 1971, is the primary global, open‐access archive for experimentally determined 3D macromolecular structures (proteins, RNA, DNA). The research‐focused RCSB.org web‐portal provides access to these data alongside more than one million machine‐learning‐predicted structure models, greatly expanding the available structural landscape. Rapid growth of both experimental and computational structures has increased the need for powerful yet accessible search tools that serve a broad and diverse scientific community. Herein, we describe a redesigned RCSB Protein Data Bank RCSB.org Advanced Search capability that supports intuitive discovery of 3D structures through a unified interface. This interface integrates annotation‐, sequence‐, and 3D structure‐based searches, embeds an interactive 3D viewer, and incorporates curated biological knowledge, such as catalytic site definitions from Mechanism and Catalytic Site Atlas and ligand‐guided structural motifs, for constructing geometry‐driven queries. A new Chemical Search tool allows definition of chemical queries via an integrated drawing tool or standard identifiers, seamlessly combining them with annotation filters. By allowing query definition directly within spatial and chemical contexts, these search interfaces reduce the need for detailed knowledge of residue numbering, chain identifiers, or external cheminformatics software. This capability enables efficient exploration of structures, chemical diversity, and structure–function relationships across all life domains. The redesigned interfaces can be accessed directly at rcsb.org/search/advanced for Advanced Search and rcsb.org/search/chemical for Chemical Search.

Rose, Yana [Research Collaboratory for Structural ↗
NASA NTRS1999

Statistical Perspectives on Stratospheric Transport

Long-lived tropospheric source gases, such as nitrous oxide, enter the stratosphere through the tropical tropopause, are transported throughout the stratosphere by the Brewer-Dobson circulation, and are photochemically destroyed in the upper stratosphere. These chemical constituents, or "tracers" can be used to track mixing and transport by the stratospheric winds. Much of our understanding about the stratospheric circulation is based on large scale gradients and other spatial features in tracer fields constructed from satellite measurements. The point of view presented in this paper is different, but complementary, in that transport is described in terms of tracer probability distribution functions (PDFs). The PDF is computed from the measurements, and is proportional to the area occupied by tracer values in a given range. The flavor of this paper is tutorial, and the ideas are illustrated with several examples of transport-related phenomena, annotated with remarks that summarize the main point or suggest new directions. One example shows how the multimodal shape of the PDF gives information about the different branches of the circulation. Another example shows how the statistics of fluctuations from the most probable tracer value give insight into mixing between different regions of the atmosphere. Also included is an analysis of the time-dependence of the PDF during the onset and decline of the winter circulation, and a study of how "bursts" in the circulation are reflected in transient periods of rapid evolution of the PDF. The dependence of the statistics on location and time are also shown to be important for practical problems related to statistical robustness and satellite sampling. The examples illustrate how physically-based statistical analysis can shed some light on aspects of stratospheric transport that may not be obvious or quantifiable with other types of analyses. An important motivation for the work presented here is the need for synthesis of the large and growing database of observations of the atmosphere and the vast quantities of output generated by atmospheric models.

Sparling, L. C.↗