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NASA NTRS2012

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗

NASA NTRS2012

The Kinematic and Microphysical Control of Storm Integrated Lightning Flash Extent

The objective of this preliminary study is to investigate the kinematic and microphysical control of lightning properties, particularly those that may govern the production of nitrogen oxides (NOx) in thunderstorms, such as flash rate, type and extent. The mixed-phase region is where the noninductive charging (NIC) process is thought to generate most storm electrification during rebounding collisions between ice particles in the presence of supercooled water. As a result, prior radar-based studies have demonstrated that lightning flash rate is well correlated to kinematic and microphysical properties in the mixed-phase region of thunderstorms such as updraft volume, graupel mass, or ice mass flux. There is also some evidence that lightning type is associated with the convective state. Intracloud (IC) lightning tends to dominate during the updraft accumulation of precipitation ice mass while cloud-to-ground (CG) lightning is more numerous during the downdraft-driven descent of radar echo associated with graupel and hail. More study is required to generalize these relationships, especially regarding lightning type, in a wide variety of storm modes and meteorological conditions. Less is known about the co-evolving relationship between storm kinematics, microphysics, morphology and three-dimensional flash extent, despite its importance for lightning NOx production. To address this conceptual gap, the NASA MSFC Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection NetworkTM (NLDN) observations following ordinary convective cells through their lifecycle. LNOM provides estimates of flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles. For this study, LNOM is applied in a Lagrangian sense to well isolated convective cells on 3 April 2007 (single cell and multi-cell hailstorm, non-severe multicell) and 6 July 2007 (non-severe multi-cell) over Northern Alabama. The LNOM lightning characteristics are compared to the evolution of updraft and precipitation properties inferred from dual-Doppler and polarimetric radar analyses applied to observations from a nearby Doppler radar network, including the UA Huntsville Advanced Radar for Meteorological and Operational Research (ARMOR, C-band, polarimetric). The LNOM estimated SAD and lightning NOx production profiles are placed in the context of radar derived profiles of vertical motion, precipitation types and amounts. Finally, these analyses are used to determine if storm integrated flash channel extent is as well correlated to volumetric updraft and precipitation ice characteristics in the mixed phase region as flash rate for these individual convective cells.

Carey, Lawrence↗

DOE OSTI2026

SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images

The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state-of-the-art fake image detection methods overfit to their training data and catastrophically fail when evaluated on curated hard test sets with strong distribution shifts. In this work, we argue that it is more principled to learn a tight decision boundary around the real image distribution and treat the fake category as a sink class. To this end, we propose SimLBR, a simple and efficient framework for fake image detection with Latent Blending Regularization (LBR). Our method significantly improves cross-generator generalization, achieving up to +24.85% accuracy and +69.62% recall on the challenging Chameleon benchmark. SimLBR is also highly efficient, training orders of magnitude faster than existing approaches. Furthermore, we emphasize the need for reliability-oriented evaluation in fake image detection, introducing risk-adjusted metrics and worst-case estimates to better assess model robustness. All the code and models are availabe at: https://github.com/mvrl/SimLBR

Dhakal, Aayush [Washington University, St. Louis]↗

DOE OSTI2024

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies: Methods and Results from the Haynesville, Anadarko, and Permian Basins

Significantly reducing methane emissions from the oil and gas sector can decrease the rate of climate change over the next two decades, buying critical time for a global energy transition. However, emissions inventories that can be used by oil and gas operators and environmental regulators to identify optimal methane emission mitigation strategies are either based on conservative emission factor methods, or are inconsistent between studies due to differences in sampling strategies or survey technologies. We developed a new approach for methane emissions survey design that yields representative basinwide methane emissions inventories by surveying a subset of total assets in a given oil and gas basin. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions that can be reconciled with future studies. We further present results from deploying this strategy in two oil and gas producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma. Aerial surveys were performed in 2023 using the Insight M LeakSurveyor™ technology. Preliminary results from methane emissions detected by Insight M indicate that aerially detected emissions above roughly 30 kg(CH4)/hr by themselves contribute a fractional loss rate of 1.13% of gross gas production across oil and gas operations in the Haynesville Basin, with aerially detected emissions equivalent to 2.67% of gross gas production in the Woodford Shale. We supplement these aerial estimates with modeled emissions that are below the LeakSurveyor’s survey sensitivity using a recently published inventory-based model of methane emissions, which we update for our survey areas. We then combine our aerial detections with modeled emissions to yield methane emission distributions and inventories that incorporate the full range of potential methane emissions from the smallest to the largest. These results can be used to identify the most effective methane mitigation strategies for our study areas, and can be reconciled with future methane emissions surveys that use different technologies.

Sherwin, Evan (ORCID:0000000321804297)↗

DOE OSTI2021

The development of rainfall retrievals from radar at Darwin

Abstract. The U.S. Department of Energy Atmospheric Radiation Measurement program Tropical Western Pacific site hosted a C-band polarization (CPOL) radar in Darwin, Australia. It provides 2 decades of tropical rainfall characteristics useful for validating global circulation models. Rainfall retrievals from radar assume characteristics about the droplet size distribution (DSD) that vary significantly. To minimize the uncertainty associated with DSD variability, new radar rainfall techniques use dual polarization and specific attenuation estimates. This study challenges the applicability of several specific attenuation and dual-polarization-based rainfall estimators in tropical settings using a 4-year archive of Darwin disdrometer datasets in conjunction with CPOL observations. This assessment is based on three metrics: statistical uncertainty estimates, principal component analysis (PCA), and comparisons of various retrievals from CPOL data. The PCA shows that the variability in R can be consistently attributed to reflectivity, but dependence on dual-polarization quantities was wavelength dependent for 1 10mmh-1. Rainfall estimates during these conditions primarily originate from deep convective clouds with median drop diameters greater than 1.5 mm. An uncertainty analysis and intercomparison with CPOL show that a Colorado State University blended technique for tropical oceans, with modified estimators developed from video disdrometer observations, is most appropriate for use in all cases, such as when 1 10mmh-1 (deeper convective rain).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2005

Workshop on Oxygen in Asteroids and Meteorites

Contents include the following: Constraints on the detection of solar nebula's oxidation state through asteroid observation. Oxidation/Reduction Processes in Primitive Achondrites. Low-Temperature Chemical Processing on Asteroids. On the Formation Location of Asteroids and Meteorites. The Spectral Properties of Angritic Basalts. Correlation Between Chemical and Oxygen Isotopic Compositions in Chondrites. Effect of In-Situ Aqueous Alteration on Thermal Model Heat Budgets. Oxidation-Reduction in Meteorites: The Case of High-Ni Irons. Ureilite Atmospherics: Coming up for Air on a Parent Body. High Temperature Effects Including Oxygen Fugacity, in Pre-Planetary and Planetary Meteorites and Asteroids. Oxygen Isotopic Variation of Asteroidal Materials. High-Temperature Chemical Processing on Asteroids: An Oxygen Isotope Perspective. Oxygen Isotopes and Origin of Opaque Assemblages from the Ningqiang Carbonaceous Chondrite. Water Distribution in the Asteroid Belt. Comparative Planetary Mineralogy: V Systematics in Planetary Pyroxenes and fo 2 Estimates for Basalts from Vesta.

Source record↗

DOE OSTI2025

Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle

The terrestrial biosphere exchanges a large amount of CO 2 with the atmosphere through photosynthesis and respiration, determining the magnitude of land carbon sink and consequently influencing the rate of global warming. The magnitudes of global photosynthesis and respiration, however, vary widely across models (100-200 PgC/year), constituting a key and persistent source of uncertainty in carbon cycle and climate modelling. Here, we argue that the uncertainty in the land carbon cycle modelling is largely attributable to the uncertainty in biogeography – the distribution of plant functional types (PFTs). Using an ensemble of dynamic global vegetation models (DGVMs), we find a strong dependence of total photosynthesis on total area for each PFT. The dependence allows us to reduce the spread of land carbon cycle estimates by ~75% using remote sensing-based PFT maps. We further find that 56 ± 21% of climate-driven changes in global photosynthesis modelled by DGVMs are caused by changes in PFT distribution in the last two decades. Our study identifies vegetation biogeography as a main controlling factor of uncertainty in land carbon cycle modelling and highlights the importance of biogeography-climate interactions in carbon cycle and climate studies.

Zhao, Ruiying [National Univ. of Singapore (Singap↗

DOE OSTI2025

Benchmarking greenhouse gas emissions from US wastewater treatment for targeted reduction

Here, in this study, to assess the national climate impact of wastewater treatment and inform decarbonization, we assembled a comprehensive greenhouse gas inventory of 15,863 facilities in the contiguous USA. Considering location and treatment configurations, we modelled on-site CH 4 , N 2 O and CO 2 production and emissions associated with energy, chemical inputs and solids disposal. Using Monte Carlo simulations, we estimated median national emissions at 47 million tonnes of CO 2 equivalent per year, with on-site process CH 4 and N 2 O emissions exceeding current government estimates by 41%. Treatment configurations with anaerobic digesters are responsible for 16 million tonnes of CO 2 equivalent per year of fugitive methane, outweighing benefits achieved through on-site electricity generation. Systems designed for nutrient removal have the highest greenhouse gas emissions intensity, attributable to energy requirements and N 2 O production, demonstrating current trade-offs between meeting water quality and climate objectives. We analysed key sensitivities and included a geospatial analysis to highlight the scale and distribution of opportunities for reducing life cycle greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

EVI-EnSitePy (Electric Vehicle Infrastructure – Energy Estimation and Site Optimization Tool in Python) [EVI-X Modeling Suite] [SWR-25-07]

EVI-EnSitePy is a comprehensive agent-based tool designed for the analysis and design of high-power charging sites, encompassing a wide array of site agents including Electric Vehicles (EVs), chargers, energy storage units (ESS), renewable energy resources (DER), and loads. This versatile tool offers diverse functionalities and a modular modeling approach, allowing detailed configuration of agents based on power ratings, port numbers, energy capacities, demand requirements, charger interfaces, and flexibility to customize the tool for project specific goals. By simulating agent interactions and employing various metrics, EVI-EnSitePy enables the assessment of site performance, exploration of energy management systems (EMS), and implementation of innovative EV charging policies. Utilizing EV charge schedules and arrival states, the tool performs thorough charging site simulations, with outputs consisting of agent and site-level power profiles and statistical metrics. Employing a tree graph structure, EVI-EnSitePy supports nested site structures and power distribution modeling. The tool's ability to generate charging schedules deterministically or via stochastic analysis further enhances its versatility. Through its features and capabilities, EVI-EnSitePy offers a powerful platform for informed decision-making in the realm of high-power charging site design and operation.

Jackson, Derek [National Renewable Energy Laborato↗

DOE OSTI2020

The Nature and State of Groundwater Contamination at the Nevada National Security Site: What Have We Learned from Decades of Groundwater Analysis? - 20337

The regulatory framework for remediating radionuclide contamination from underground nuclear testing at the Nevada National Security Site (NNSS) is based on a combination of characterization and modeling studies, monitoring, and institutional controls [1]. Currently, tritium is the largest contributor (∼90%) to the estimated 44.6 million-curie radionuclide inventory resulting from underground testing [2]. Because of its short half-life (12.32 years), its relative contribution reduces below 10% of the total radiologic inventory over the next 120 years as a result of radioactive decay. Although tritium levels are observed well above the Safe Drinking Water Act (SDWA) maximum contaminant levels (MCLs) in groundwater, other radionuclides are well below their MCLs except within the nuclear test near-field (nuclear test cavity and chimney) environment. In fact, most device-derived radionuclides are below their MCL in groundwater even in samples collected from this near-field environment. The distribution of radionuclides following the nuclear detonation greatly influences the availability of potential contaminants for groundwater transport. Tritium is initially distributed in the gas phase, later as tritiated water in steam, and finally as liquid water, and is available to groundwater transport away from the near-field environment. Other radionuclides that are mobile in groundwater are {sup 14}C, {sup 36}Cl, {sup 99}Tc, and {sup 129}I though their radiologic inventory is small when compared to tritium. Many radionuclides (e.g. U, Pu, Am) are incorporated to a significant extent into the melt glass at the bottom of the cavity and are accessible to groundwater primarily through the slow process of glass dissolution. These radionuclides are also adsorbed to the surfaces of the crushed rock within the cavity and chimney which limits their migration in groundwater. Although colloid facilitated transport of radionuclides at the NNSS has been observed [3], radionuclide concentrations decrease with time and migration distances due to desorption and colloid filtration processes. Current studies indicate that radionuclides associated with colloids are unlikely to migrate downgradient from NNSS underground nuclear tests at concentrations above the SDWA MCL [4][5]. The results of over 50 years of sampling, along with an understanding of these post detonation processes, indicate that tritium is the only contaminant of concern downgradient of testing and that even tritium will not exceed its MCL in groundwater after ∼120 years. Although other longer-lived radionuclides may continue to be released slowly from the near-field environment they will likely never reach levels exceeding their MCLs in groundwater downgradient of the NNSS. Groundwater monitoring will continue to verify these observations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Uncertainty Quantification for Capacity Expansion Planning

This report quantifies the uncertainty in output decisions from a Capacity Expansion Planning (CEP) model. The need to understand how uncertainties within CEP models and modeling assumptions affect Quantities of Interest (QoIs) such as expansion and operating costs, as well as expansion decisions remains an ongoing challenge in scientific research and industrial operations. This area of research is particularly important for models which seek to capture how large networks will evolve and operate under increased sources of variable generation, i.e., higher penetration of renewable technologies such as solar and wind generators. Uncertainty quantification (UQ) of CEP models which estimate expansion costs and decisions, and production cost models which estimate operating costs and dispatch decisions, is a key focus of research at NREL. The Regional Energy Deployment System (ReEDS) represents a state-of-the-art CEP model and considers a range of possible grid evolutions in an attempt to identify key drivers, ramifications, and decisions which contribute to better informed investment and policy decisions. However, research to quantify how uncertainties and model assumptions, such as unit commitment (UC), within ReEDS may be affecting its outputs remains challenging due to to size and complexity of the model

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Voltammetric Measurement of Rates and Energetics for Surface Methoxylation of Si(100) in Methanol with Dissolved Electron Acceptors Using Si Ultramicroelectrodes

The steady-state voltammetric responses of n-type Si(100) semiconductor ultramicroelectrodes (SUMEs) immersed in air- and water-free methanolic electrolytes have been measured. The response characteristics of these SUMEs in the absence of illumination were modeled and understood through a framework that describes the distribution of the applied potential across the semiconductor/electrolyte contact using four discrete regions: the semiconductor space charge, surface, Helmholtz, and diffuse layers. The latter region was described by the full Gouy–Chapman model. This framework afforded insight on how relevant parameters such as the semiconductor band edge potentials, the reorganization energies for charge transfer, the standard potential of redox species in solution, the density and energy of surface state populations, and the presence of an insulating (tunneling) layer individually and collectively dictate the observable current–potential responses. With this information, the methoxylation of Si surfaces was evaluated by analysis of the change in voltammetric responses during the course of prolonged immersion in methanol. Here, the electrochemical data were consistent with a surface methoxylation mechanism that depended on the standard potential of redox species dissolved in solution. Estimates of the enthalpies of adsorption as well as the potential-dependent rate constant for surface methoxylation were obtained. Collectively, these measurements supported the contention that the rates of Si surface reactions can be systematically tuned by exposure to dissolved outer-sphere electron acceptors. Moreover, the data represent the quantitative utility of voltammetry with SUMEs for the measurement of semiconductor/liquid contacts.

14 SOLAR ENERGY↗

DOE OSTI2026

Battery Energy Storage System (BESS) End-of-Performance and Decommissioning Considerations [Slides]

This presentation provides a comprehensive overview of end-of-performance and decommissioning considerations for large-scale Battery Energy Storage Systems (BESS). It outlines expected system lifespans, midterm assessment needs, and pathways for extending operational life through augmentation or repowering. The presentation details regulatory requirements that govern decommissioning plans, cost estimates, financial assurance mechanisms, and performance obligations across multiple jurisdictions. It further examines end-of-life equipment management, including recycling, waste handling, transportation, and environmental compliance. Designed to support Malawi's electricity-sector institutions, the presentation highlights how planning for decommissioning and environmental stewardship can be integrated early in project development to ensure safe, financially accountable, and environmentally responsible BESS system retirement.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1996

Durability and Damage Tolerance of High Temperature Polymeric Composites

Modern durability and damage tolerance predictions for composite material systems rely on accurate estimates of the local stress and material states for each of the constituents, as well as the manner in which the constituents interact. In this work, an number of approaches to estimating the stress states and interactions are developed. First, an elasticity solution is presented for the problem of a penny-shaped crack in an N-phase composite material system opened by a prescribed normal pressure. The stress state around such a crack is then used to estimate the stress concentrations due to adjacent fiber fractures in composite materials. The resulting stress concentrations are then used to estimate the tensile strength of the composite. The predicted results are compared with experimental values. In addition, a cumulative damage model for fatigue is presented. Modifications to the model are made to include the effects of variable amplitude loading. These modifications are based upon the use of remaining strength as a damage metric and the definition of an equivalent generalized time. The model is initially validated using results from the literature. Also, experimental data from APC-2 laminates and IM7/K3B laminates are used in the model. The use of such data for notched laminates requires the use of an effective hole size, which is calculated based upon strain distribution measurements. Measured remaining strengths after fatigue loading are compared with the predicted values for specimens fatigued at room temperature and 350 F (177 C).

Case, Scott W.↗

DOE OSTI2025

Simplified Model and Approach to Transform Infrared Surface Temperature to Film Effectiveness in a Conjugate Heat Transfer Experiment

In the pursuit of more efficient gas turbines, film cooling is a critical technology. This article describes a simplified engineering model based on a one-dimensional thermal resistance network. The model is used to relate film-cooling effectiveness and heat transfer augmentation to local overall cooling effectiveness in a conjugate flat plate experiment. Here, this article presents experimental proof-of-concept data to demonstrate the potential for this model. In contrast to previous approaches, neither the wall heat flux nor the adiabatic wall temperature is required to estimate the local film-cooling performance parameters. The model predicts surface temperatures that are within the experimental uncertainties over the range for which the model is trained and to within five percent when the model is extrapolated to higher coolant channel Reynolds numbers. This article is relevant to conjugate test rigs that can measure the hot-surface temperature distribution with and without film cooling. This information may also be relevant to designers as a method to approximate surface temperatures or used as an approximate heat transfer model for optimization studies.

advanced turbines↗

NASA NTRS1992

The thermal engine of Venus: Implications from the impact crater distribution

Questions concerning the state of Venus' volcanological activity are currently under investigation. These questions were raised by the imaging radar and altimetric data obtained by the Magellan spacecraft, which began mapping Venus in Sept. 1990. Clues about the answers to these questions are provided by the nature and distribution of impact craters on the surface of Venus. Statistical tests show that the distribution of craters on Venus cannot be distinguished from a completely spatially random population. Further, the majority of craters look relatively pristine; only about 5 percent of the observed craters appear to be embayed or flooded by lavas. The simplest interpretation of these observations is a model in which the impact craters lie on a surface that has been undisturbed by volcanological and tectonic processes since the time the surface was formed. Counting up the number of craters and estimating the rate at which meteoroids strike the surface then gives an age for the venusian surface of 500 million years; in this model the volcanic activity since that time has been essentially nil. This scenario is described as a 'production' model, or perhaps more appropriately, a 'catastrophic' model.

Phillips, Roger J.↗

DOE OSTI2021

Rigorous constraints on three-nucleon forces in chiral effective field theory from fast and accurate calculations of few-body observables

We explore the constraints on the three-nucleon force (3NF) of chiral effective field theory (χ EFT) that are provided by bound-state observables in the A = 3 and A = 4 sectors. Our statistically rigorous analysis incorporates experimental error, computational method uncertainty, and the uncertainty due to truncation of the χ EFT expansion at next-to-next-to-leading order. A consistent solution for the 3 H binding energy, the 4 He binding energy and radius, and the 3 H β-decay rate can only be obtained if χ EFT truncation errors are included in the analysis. Here, the β-decay rate is the only one of these that yields a nondegenerate constraint on the 3NF low-energy constants, which makes it crucial for the parameter estimation. We use eigenvector continuation for fast and accurate emulation of no-core shell model calculations of the few-nucleon observables. This facilitates sampling of the posterior probability distribution, allowing us to also determine the distributions of the parameters that quantify the truncation error. We find a χ EFT expansion parameter of Q = 0.33 ± 0.06 for these observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

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.↗