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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Suppression of NLRP3 inflammasome attenuates stress-induced depression-like behavior in NLGN3-deficient mice

Highlights: • NLGN3 deletion attenuates stress-induced depression-like phenotype. • NLGN3 deficiency ameliorates neuron injury and glial cell activation. • NLGN3 knockout reduces NLRP3 inflammasome and NF-κB activity in cortex, hippocampus and amygdala. • NLGN3 knockdown alleviates inflammation in LPS-stimulated AST through NLRP3 inflammasome. Depression, regulated by central nervous system (CNS), is a significant inflammatory disorder. Neuroligin3 (NLGN3) has been implicated in brain functions. In the study, a chronic unpredictable mild stress (CUMS) model in wild type (WT) or NLGN3-knockout (KO) mice was established to explore the role of NLGN3 in regulating depression and to reveal the underlying molecular mechanism. The results indicated that NLGN3-knockout markedly reversed the loss of body weight, the reduction of sucrose consumption, the decrease of immobile time in the forced swimming tests (FST) and tail suspension tests (TST) induced by CUMS paradigm. CUMS up-regulated corticosterone (CORT) in serum, and down-regulated serotonin (5-HT), norepinephrine (NE) and brain-derived neurotrophic factor (BDNF) in hippocampus of mice, which were significantly reversed by NLGN3 deficiency. The results further demonstrated that NLGN3-knockout improved the degenerative neurons in cortex and hippocampus of CUMS-treated mice, accompanied with a significant decrease of ionized calciumbinding adapter molecule 1 (Iba-1) and glial fibrillary acidic protein (GFAP) expressions. Additionally, NLGN3-KO mice challenged with CUMS showed a significant reduction of pro-inflammatory cytokines and chemokine, including tumor necrosis factor-alpha (TNF-α), interleukin-18 (IL-18), interleukin-1 beta (IL-1β), interleukin-4 (IL-4), CC-chemokine ligand-1 (CCL-1) and CXC-chemokine ligand-1 (CXCL-1), in cortex, hippocampus and amygdala tissue samples. Western blot analysis suggested that NLGN3-knockout inhibited the activation of nod-like receptor protein 3 (NLRP3) inflammasome and its adaptor of apoptosis-associated speck like protein (ASC), and reduced the expression of Caspase-1, along with the inactivation of nuclear factor-κB (NF-κB) in CUMS-challenged mice. The role of NLGN3 in regulating depression in mice was confirmed in vitro using astrocytes stimulated by LPS that NLGN3 knockdown reduced LPS-induced inflammation. Importantly, the suppressive effects of NLGN3-knockdown on inflammatory response were reversed by NLRP3 or ASC over-expression in AST exposed to LPS. In sum, our findings indicated that suppressing NLGN3 played a potential antidepressant role in CUMS animal model by inactivating NLRP3 inflammasome, providing a new therapeutic avenue for depression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Niche differentiation among annually recurrent coastal Marine Group II Euryarchaeota

Since the discovery of archaeoplankton in 1992, the euryarchaeotal Marine Group II (MGII) remains uncultured and less understood than other planktonic archaea. We characterized the seasonal dynamics of MGII populations in the southern North Sea on a genomic and microscopic level over the course of four years. We recovered 34 metagenome-assembled genomes (MAGs) of MGIIa and MGIIb that corroborated proteorhodopsin-based photoheterotrophic lifestyles. However, MGIIa and MGIIb MAG genome sizes differed considerably (~1.9 vs. ~1.4 Mbp), as did their transporter, peptidase, flagella and sulfate assimilation gene repertoires. MGIIb populations were characteristic of winter samples, whereas MGIIa accounted for up to 23% of the community at the beginning of summer. Both clades consisted of annually recurring, sequence-discrete populations with low intra-population sequence diversity. Oligotyping of filtered cell-size fractions and microscopy consistently suggested that MGII cells were predominantly free-living. Cells were coccoid and ~0.7 µm in diameter, likely resulting in grazing avoidance. Based on multiple lines of evidence, we propose distinct niche adaptations of MGIIa and MGIIb Euryarchaeota populations that are characteristic of summer and winter conditions in the coastal North Sea.

Environmental Sciences & Ecology↗
DOE OSTI2022

Practical galaxy morphology tools from deep supervised representation learning

Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Adaptive Power Flow Approximations With Second-Order Sensitivity Insights

The power flow equations are fundamental to power system planning, analysis, and control. However, the inherent non-linearity and non-convexity of these equations present formidable obstacles in problem-solving processes. To mitigate these challenges, recent research has proposed adaptive power flow linearizations that aim to achieve accuracy over wide operating ranges. The accuracy of these approximations inherently depends on the curvature of the power flow equations within these ranges, which necessitates considering second-order sensitivities. In this paper, we leverage second-order sensitivities to both analyze and improve power flow approximations. We evaluate the curvature across broad operational ranges and subsequently utilize this information to inform the computation of various sample-based power flow approximation techniques. Additionally, we leverage second-order sensitivities to guide the development of rational approximations that yield linear constraints in optimization problems. In conclusion, this approach is extended to enhance accuracy beyond the limitations of linear functions across varied operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Dual transposon sequencing profiles the genetic interaction landscape in bacteria

Gene redundancy complicates systematic characterization of gene function as single-gene deletions may not produce discernible phenotypes. We report dual transposon sequencing (dual Tn-seq), a platform for assaying the fitness of a comprehensive double mutant pool in parallel. Dual Tn-seq couples random barcode transposon site sequencing with the Cre-lox system, enabling deep sampling of 73% of the 1.3 million possible double gene deletions in Streptococcus pneumoniae. The genetic interactions identified span a wide range of biochemical processes, revealing new factors in presumably well-studied pathways, exemplified by a cytidine triphosphate synthase PyrJ. Moreover, this approach should permit further investigation of growth condition–specific genetic interactions. Because dual Tn-seq does not require the construction of a large array of single mutants, it should be readily adaptable to various microorganisms.

CTP synthesis↗
DOE OSTI2019

Target Formulation and Construction in Mesh Quality Improvement

In the Target-matrix Optimization Paradigm (TMOP), it’s long been understood that one must create a set of target matrices before the mesh can be optimized. But there is still no general method to create correct, effective targets in response to a specific mesh quality improvement goal. The TMOP literature describes how certain sets of target matrices can be used to control the shape or size of mesh elements, but those examples address only a fraction of the problems that can occur in mesh quality improvement and were not derived from a general framework for target matrix construction. In this work, a general method of target construction is introduced based on an independent set of geometric parameters which are intrinsic to the Jacobian matrices upon which TMOP is based. The parameters enable a systematic approach to target definition and construction. The approach entails two parts. The first part defines correspondences between available raw data (stuff about the mesh and/or the physical solution) and intermediate data (e.g., a field of error estimates). Once the correspondences are established, the raw data is processed into intermediate field data existing on mesh sample points. The second part is to create a model that represents the values of the geometric target parameters as functions of the intermediate data. The model is then tested numerically to establish model constants and effectiveness. This systematic approach to target construction is illustrated in a set of examples to show how it can be applied to common problems in mesh optimization such as equidistribution of geometric properties, preservation of existing good quality, and adaptation of the mesh to the solution. The result is a systematic method of target construction for TMOP which can be applied to a wide variety of planar and volume mesh quality improvement tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Schwarz Alternating Method for the Seamless Coupling of Nonlinear Reduced Order Models and Full Order Models

Projection-based model order reduction allows for the parsimonious representation of full order models (FOMs), typically obtained through the discretization of a set of partial differential equations (PDEs) using conventional techniques (e.g., finite element, finite volume, finite difference methods) where the discretization may contain a very large number of degrees of freedom. As a result of this more compact representation, the resulting projection-based reduced order models (ROMs) can achieve considerable computational speedups, which are especially useful in real-time or multi-query analyses. One known deficiency of projection-based ROMs is that they can suffer from a lack of robustness, stability and accuracy, especially in the predictive regime, which ultimately limits their useful application. Another research gap that has prevented the widespread adoption of ROMs within the modeling and simulation community is the lack of theoretical and algorithmic foundations necessary for the “plug-and-play” integration of these models into existing multi-scale and multi-physics frameworks. This paper describes a new methodology that has the potential to address both of the aforementioned deficiencies by coupling projection-based ROMs with each other as well as with conventional FOMs by means of the Schwarz alternating method [41]. Leveraging recent work that adapted the Schwarz alternating method to enable consistent and concurrent multiscale coupling of finite element FOMs in solid mechanics [35, 36], we present a new extension of the Schwarz framework that enables FOM-ROM and ROM-ROM coupling, following a domain decomposition of the physical geometry on which a PDE is posed. In order to maintain efficiency and achieve computation speed-ups, we employ hyper-reduction via the Energy-Conserving Sampling and Weighting (ECSW) approach [13]. We evaluate the proposed coupling approach in the reproductive as well as in the predictive regime on a canonical test case that involves the dynamic propagation of a traveling wave in a nonlinear hyper-elastic material.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Potential Challenges of HyBlend Storage in a Methane Reservoir Located in Southwestern United States

Hydrogen has been identified as a flexible energy carrier with zero or negative emissions across multiple energy systems. It is possible to utilize hydrogen by storing Hyblend, or hydrogen gas blended with methane, in existing natural gas infrastructure. However, the compatibility of adapting the current CH4 storage strategies to include H2 injection has not been fully demonstrated. It is essential that we understand the impact of H2 gas on the naturally occurring microbial community of subsurface storage reservoirs before deploying large-scale H2-CH4 storage. We designed a series of experiments that allowed us to identify potential geochemical and microbial challenges of HyBlend Storage in existing methane reservoirs. First, we collected and characterized field fluid samples from a methane reservoir located in southwestern United States. Next, we used these field fluid samples to complete a series of short-term reactor experiments at reservoir conditions (80 °C and ~1,000 psi) for a natural gas (100% CH4) and HyBlend(80% CH4/20% H2) storage environment to measure the transformation of gas content. We conducted both biotic and abiotic (sterilized) measurements to accurately understand and decouple abiotic and microbially driven processes. Overall, we found that our field sample was characterized by a diverse microbial community with the metabolic capacity for sulfur reduction, iron reduction, and acetogenesis. Across our reactors, there was minimal change in geochemistry.

hydrogen storage↗
DOE OSTI2023

Influence of Mild Chronic Stress and Social Isolation on Acute Ozone-Induced Alterations in Stress Biomarkers and Brain-Region-Specific Gene Expression in Male Wistar–Kyoto Rats

Individuals with psychosocial stress often experience an exaggerated response to air pollutants. Ozone (O 3 ) exposure has been associated with the activation of the neuroendocrine stress-response system. We hypothesized that preexistent mild chronic stress plus social isolation (CS), or social isolation (SI) alone, would exacerbate the acute effects of O 3 exposure on the circulating adrenal-derived stress hormones, and the expression of the genes regulating glucocorticoid stress signaling via an altered stress adaptation in a brain-region-specific manner. Male Wistar–Kyoto rats (5 weeks old) were socially isolated, plus were subjected to either CS (noise, confinement, fear, uncomfortable living, hectic activity, and single housing), SI (single housing only, restricted handling and no enrichment) or no stress (NS; double housing, frequent handling and enrichment provided) for 8 weeks. The rats were then exposed to either air or O 3 (0.8 ppm for 4 h), and the samples were collected immediately after. The indicators of sympathetic and hypothalamic–pituitary axis (HPA) activation (i.e., epinephrine, corticosterone, and lymphopenia) increased with O 3 exposure, but there were no effects from CS or SI, except for the depletion of serum BDNF. CS and SI revealed small changes in brain-region-specific glucocorticoid-signaling-associated markers of gene expression in the air-exposed rats (hypothalamic Nr3c1, Nr3c2 Hsp90aa1, Hspa4 and Cnr1 inhibition in SI; hippocampal HSP90aa1 increase in SI; and inhibition of the bed nucleus of the stria terminalis (BNST) Cnr1 in CS). Gene expression across all brain regions was altered by O 3 , reflective of glucocorticoid signaling effects, such as Fkbp5 in NS, CS and SI. The SI effects on Fkbp5 were greatest for SI in BNST. O 3 increased Cnr2 expression in the hypothalamus and olfactory bulbs of the NS and SI groups. O 3 , in all stress conditions, generally inhibited the expression of Nr3c1 in all brain regions, Nr3c2 in the hippocampus and hypothalamus and Bdnf in the hippocampus. SI, in general, showed slightly greater O 3 -induced changes when compared to NS and CS. Serum metabolomics revealed increased sphingomyelins in the air-exposed SI and O 3 -exposed NS, with underlying SI dampening some of the O 3 -induced changes. These results suggest a potential link between preexistent SI and acute O 3 -induced increases in the circulating adrenal-derived stress hormones and brain-region-specific gene expression changes in glucocorticoid signaling, which may partly underlie the stress dynamic in those with long-term SI.

gene expression↗
NASA NTRS1982

Concepted design of a surface measurement system for large deployable space antennas

The sensor system is in essence a point design, specifically interfacing with the Harris, Inc., 1000 meter deployable mesh communication antenna. The design can, without large modification, be adapted to other large deployable antennas such as the Lockheed Wrap-rib, the General Dynamics Precision Erectable Truss and the TRW Advanced Sunflower antennas. Measurements are optical displacements. The elements of the system are a central cluster of receivers near the apex of the antenna and active bright targets at the antenna. The cluster defines a single coordinate frame from which all surface positions are referenced. The receivers continuously observe an extended array of sample points located throughout the reflecting surface and its supporting structure. For the Harris antenna, the surface samples are at the mesh gore lines and at the supporting hoop. Output data is in real-time, compatible with on-board processing and active control of antenna figure. Lifetime of the system is at least 10 years continuous operation in space.

Neiswander, R. S.↗
NASA NTRS1995

Dynamic Acoustic Detection of Boundary Layer transition

The wind tunnel investigation into the acoustic nature of boundary layer transition using miniature microphones. This research is the groundwork for entry into the National Transonic Facility (NTF) at the NASA Langley Research Center (LaRC). Due to the extreme environmental conditions of NTF testing, low temperatures and high pressures, traditional boundary layer detection methods are not available. The emphasis of this project and further studies is acoustical sampling of a typical boundary layer and environmental durability of the miniature microphones. The research was conducted with the 14 by 22 Foot Subsonic Tunnel, concurrent with another wind tunnel test. Using the resources of LaRC, a full inquiry into the feasibility of using Knowles Electronics, Inc. EM-3086 microphones to detect the surface boundary layer, under differing conditions, was completed. This report shall discuss the difficulties encountered, product performance and observations, and future research adaptability of this method.

Grohs, Jonathan R.↗
NASA NTRS1996

Propulsion Selection for 85kft Remotely Piloted Atmospheric Science Aircraft

This paper describes how a 3 stage turbocharged gasoline engine was selected to power NASA's atmospheric science unmanned aircraft now under development. The airplane, whose purpose is to fly sampling instruments through targeted regions of the upper atmosphere at the exact location and time (season, time of day) where the most interesting chemistry is taking place, must have a round trip range exceeding 1000 km, carry a payload of about 500 lb to altitudes exceeding 80 kft over the site, and be able to remain above that altitude for at least 30 minutes before returning to base. This is a subsonic aircraft (the aerodynamic heating and shock associated with supersonic flight could easily destroy the chemical species that are being sampled) and it must be constructed so it will operate out of small airfields at primitive remote sites worldwide, under varying climate and weather conditions. Finally it must be low cost, since less than $50 M is available for its development. These requirements put severe constraints on the aircraft design (for example, wing loading in the vicinity of 10 psf) and have in turn limited the propulsion choices to already-existing hardware, or limited adaptations of existing hardware. The only candidate that could emerge under these circumstances was a propeller driven aircraft powered by spark ignited (SI) gasoline engines, whose intake pressurization is accomplished by multiple stages of turbo-charging and intercooling. Fortunately the turbocharged SI powerplant, owing to its rich automotive heritage and earlier intensive aero powerplant development during WWII, enjoys in addition to its potentially low development costs some subtle physical advantages (arising from its near-stochiometric combustion) that may make it smaller and lighter than either a turbine engine or a diesel for these altitudes. Just as fortunately, the NASA/industry team developing this aircraft includes the same people who built multi-stage turbocharged SI powerplants for unmanned military spyplanes in the early 1980's. Now adapting hardware developed for reconaissance at 65-70 kft to the interests of atmospheric science at 80-90 kft, their efforts should yield an aero powerplant that pushes the altitude limits of subsonic air breathing propulsion.

Bents, David J.↗
DOE OSTI2021

Enhanced oxidation resistance of (Mo 95 W 5 ) 85 Ta 10 (TiZr) 5 refractory multi-principal element alloy up to 1300°C

Refractory-metal-based alloys are a potential replacement of current nickel-based superalloys due to their excellent mechanical strength at extremely high temperatures. However, severe oxidation in a high-temperature working environment limits their application. To address this challenge, a two-step coating process (including a Mo precoat and a Si-B pack cementation) was applied to an innovative refractory multi-principal element alloy (RMPEA) (Mo 95 W 5 ) 85 Ta 10 (TiZr) 5 . The coating is composed of an aluminoborosilica glass layer on top of a RMPEA-Si-B multilayered structure. Here, the coating effectively protects the RMPEA from oxidation in high-temperature environments, as demonstrated by phase-stable operation at 10–20% higher temperatures over state-of-the-art systems without any forced-cooling system. Following an isothermal exposure at 1300 °C, the weight change of the coated sample follows a paralinear kinetics with a minor weight loss of 4.2 mg/cm 2 after 50 h. Thermal cycling tests between 1300 °C and room temperature in air resulted in the total weight gain of only 2.6 mg/cm 2 after 450 cycles. The coating shows an excellent adherence to the substrate with a boride layer acting as a barrier that maintains the coating integrity. This two-step Mo-Si-B coating method can be adapted to provide environmental resistance to a wide range of RMPEA.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Active oversight and quality control in standard Bayesian optimization for autonomous experiments

The fusion of experimental automation and machine learning has catalyzed a new era in materials research, prominently featuring Gaussian Process (GP) Bayesian Optimization (BO) driven autonomous experiments. Here we introduce a Dual-GP approach that enhances traditional GPBO by adding a secondary surrogate model to dynamically constrain the experimental space based on real-time assessments of the raw experimental data. This Dual-GP approach enhances the optimization efficiency of traditional GPBO by isolating more promising space for BO sampling and more valuable experimental data for primary GP training. We also incorporate a flexible, human-in-the-loop intervention method in the Dual-GP workflow to adjust for unanticipated results. We demonstrate the effectiveness of the Dual-GP model with synthetic model data and implement this approach in autonomous pulsed laser deposition experimental data. This Dual-GP approach has broad applicability in diverse GPBO-driven experimental settings, providing a more adaptable and precise framework for refining autonomous experimentation for more efficient optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Delayed Gamma-Ray Spectroscopy for Non-Destructive Assay of Nuclear Materials

High-­energy, beta-delayed gamma-­ray spectroscopy is a potential, non-­destructive assay techniques for the independent verification of declared quantities of special nuclear materials at key stages of the fuel cycle and for directly assaying nuclear material inventories for spent fuel handling, interim storage, reprocessing facilities, repository sites, and final disposal. Other potential applications include determination of MOX fuel composition, characterization of nuclear waste packages, and challenges in homeland security and arms control verification. Experimental measurements were performed to evaluate fission fragment yields, to test methods for determining isotopic fractions, and to benchmark the modeling code package. Experimental measurement campaigns were carried out at the IAC using a photo-­neutron source and at OSU using a thermal neutron beam from the TRIGA reactor to characterize the emission of high-­energy delayed gamma rays from 235 U, 239 Pu, and 241 Pu targets following neutron induced fission. Data were collected for pure and combined targets for several irradiation/spectroscopy cycle times ranging from 10/10 seconds to 15/30 minutes.The delayed gamma-ray signature of 241 Pu, a significant fissile constituent in spent fuel, was measured and compared to 239 Pu. The 241 Pu/ 239 Pu ratios varied between 0.5 and 1.2 for ten prominent lines in the 2700-­3600 keV energy range. Such significant differences in relative peak intensities make it possible to determine relative fractions of these isotopes in a mixed sample. A method for determining fission product yields by fitting the energy and time dependence of the delayed gamma-­ray emission was developed and demonstrated on a limited 235 U data set. De-­convolution methods for determining fissile fractions were developed and tested on the experimental data. The use of high count-­rate LaBr 3 detectors was investigated as a potential alternative to HPGe detectors. Modeling capabilities were added to an existing framework and codes were adapted as needed for analyzing experiments and assessing application-­specific assay concepts. A de-­convolution analysis of the delayed gamma-­ray response spectra modeled for spent fuel assemblies was performed using the same method that was applied to the experimental spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1981

Adaptively pointing spaceborne radar for precipitation measurements

An auxiliary concept of adaptive pointing applicable to meteorological radar is discussed. This control technique would resolve the conflicts among speed of scan or scan width, resolution, and dwell time per resolution element. At T1(orbital position) a passive infrared radiometer imager scans a swath ahead of the spacecraft; an appropriate algorithm indicates which clouds are probably producing precipitation. These locations are then used by the on-board antenna controller to program the antenna scan so that the radar samples clouds A and B at times T2 and T3 respectively.

Atlas, D.↗
NASA NTRS1995

On-line estimation of error covariance parameters for atmospheric data assimilation

A simple scheme is presented for on-line estimation of covariance parameters in statistical data assimilation systems. The scheme is based on a maximum-likelihood approach in which estimates are produced on the basis of a single batch of simultaneous observations. Simple-sample covariance estimation is reasonable as long as the number of available observations exceeds the number of tunable parameters by two or three orders of magnitude. Not much is known at present about model error associated with actual forecast systems. Our scheme can be used to estimate some important statistical model error parameters such as regionally averaged variances or characteristic correlation length scales. The advantage of the single-sample approach is that it does not rely on any assumptions about the temporal behavior of the covariance parameters: time-dependent parameter estimates can be continuously adjusted on the basis of current observations. This is of practical importance since it is likely to be the case that both model error and observation error strongly depend on the actual state of the atmosphere. The single-sample estimation scheme can be incorporated into any four-dimensional statistical data assimilation system that involves explicit calculation of forecast error covariances, including optimal interpolation (OI) and the simplified Kalman filter (SKF). The computational cost of the scheme is high but not prohibitive; on-line estimation of one or two covariance parameters in each analysis box of an operational bozed-OI system is currently feasible. A number of numerical experiments performed with an adaptive SKF and an adaptive version of OI, using a linear two-dimensional shallow-water model and artificially generated model error are described. The performance of the nonadaptive versions of these methods turns out to depend rather strongly on correct specification of model error parameters. These parameters are estimated under a variety of conditions, including uniformly distributed model error and time-dependent model error statistics.

Dee, Dick P.↗