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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Observing Exoplanets with High Dispersion Coronagraphy. I. The Scientific Potential of Current and Next-generation Large Ground and Space Telescopes

Direct imaging of exoplanets presents a formidable technical challenge owing to the small angular separation and high contrast between exoplanets and their host stars. High Dispersion Coronagraphy (HDC) is a pathway to achieve unprecedented sensitivity to Earth-like planets in the habitable zone. Here, we present a framework to simulate HDC observations and data analyses. The goal of these simulations is to perform a detailed analysis of the trade-off between raw star light suppression and spectral resolution for various instrument configurations, target types, and science cases. We predict the performance of an HDC instrument at Keck observatory for characterizing directly imaged gas-giant planets in near-infrared bands. We also simulate HDC observations of an Earth-like planet using next-generation ground-based (TMT) and spaced-base telescopes (HabEx and LUVOIR). We conclude that ground-based ELTs are more suitable for HDC observations of an Earth-like planet than future space-based missions owing to the considerable difference in collecting area. For ground-based telescopes, HDC observations can detect an Earth-like planet in the habitable zone around an M-dwarf star at 10{sup −4} star light suppression level. Compared to the 10{sup −7} planet/star contrast, HDC relaxes the star light suppression requirement by a factor of 10{sup 3}. For space-based telescopes, detector noise will be a major limitation at spectral resolutions higher than 10{sup 4}. Considering detector noise and speckle chromatic noise, R = 400 (1600) is the optimal spectral resolutions for HabEx (LUVOIR). The corresponding star light suppression requirement to detect a planet with planet/star contrast = 6.1×10{sup −11} is relaxed by a factor of 10 (100) for HabEx (LUVOIR).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bioverse: A Comprehensive Assessment of the Capabilities of Extremely Large Telescopes to Probe Earth-like O 2 Levels in Nearby Transiting Habitable-zone Exoplanets

Molecular oxygen is a strong indicator of life on Earth and may indicate biological processes on exoplanets too. Recent studies proposed that Earth-like O 2 levels might be detectable on nearby exoplanets using high-resolution spectrographs on future extremely large telescopes (ELTs). However, these studies did not consider constraints like relative velocities, planet occurrence rates, and target observability. We expanded on past studies by creating a homogeneous catalog of 286,391 main-sequence stars within 120 pc using Gaia DR3 and used the Bioverse framework to simulate the likelihood of finding nearby transiting Earth analogs. We also simulated a survey of M dwarfs within 20 pc accounting for η ⊕ estimates, transit probabilities, relative velocities, and target observability to determine how long ELTs and theoretical 50–100 m ground-based telescopes need to observe to probe for Earth-like O 2 levels with an R = 100,000 spectrograph. This would only be possible within 50 yr for up to ~21% of nearby M-dwarf systems if a suitable transiting habitable-zone Earth analog was discovered, assuming signals from every observable partial transit from each ELT can be combined. If so, Earth-like O 2 levels could be detectable on TRAPPIST-1 d–g within 16–55 yr, respectively, and about half that time with an R = 500,000 spectrograph. These results have important implications for whether ELTs can survey nearby habitable-zone Earth analogs for O 2 via transmission spectroscopy. Our work provides the most comprehensive assessment to date of the ground-based capabilities to search for life beyond the solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Planetary Accretion Shock. I. Framework for Radiation-hydrodynamical Simulations and First Results

The key aspect determining the postformation luminosity of gas giants has long been considered to be the energetics of the accretion shock at the surface of the planet. We use one-dimensional radiation-hydrodynamical simulations to study the radiative loss efficiency and to obtain postshock temperatures and pressures and thus entropies. The efficiency is defined as the fraction of the total incoming energy flux that escapes the system (roughly the Hill sphere), taking into account the energy recycling that occurs ahead of the shock in a radiative precursor. We focus in this paper on a constant equation of state (EOS) to isolate the shock physics but use constant and tabulated opacities. While robust quantitative results will have to await a self-consistent treatment including hydrogen dissociation and ionization, the results presented here show the correct qualitative behavior and can be understood from semianalytical calculations. The shock is found to be isothermal and supercritical for a range of conditions relevant to the core accretion formation scenario (CA), with Mach numbers M≳3. Across the shock, the entropy decreases significantly by a few times k{sub B}/baryon. While nearly 100% of the incoming kinetic energy is converted to radiation locally, the efficiencies are found to be as low as roughly 40%, implying that a significant fraction of the total accretion energy is brought into the planet. However, for realistic parameter combinations in the CA scenario, we find that a nonzero fraction of the luminosity always escapes the Hill sphere. This luminosity could explain, at least in part, recent observations in the young LkCa 15 and HD 100546 systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dust Polarization Maps from TIGRESS: E/B Power Asymmetry and TE Correlation

We present the first large set of all-sky synthetic dust polarization maps derived directly from a self-consistent magnetohydrodynamics simulation using the TIGRESS framework. Turbulence in this simulation is predominantly driven by supernova explosions, with rates that are self-consistently regulated by feedback loops. The simulation covers both the outer scale and inertial range of turbulence with uniformly high resolution. The shearing-box utilized in the simulation, in concert with resolved supernova-driven turbulence, enables the capturing of generation, growth, and saturation of both turbulent and mean magnetic fields. We construct polarization maps at 353 GHz, as seen by observers inside a model of the multiphase, turbulent, magnetized interstellar medium (ISM). To fully sample the simulated ISM state, we use 350 snapshots spanning over $\sim 350\,\mathrm{Myr}$ (more than six feedback loops) and nine representative observers. The synthetic skies show a prevalent E/B power asymmetry (${EE}\gt {BB}$) and positive TE correlation in broad agreement with observations by the Planck satellite. However, the ranges of ${EE}/{BB}\sim 1.4\mbox{-}1.7$ and ${TE}/{({TT}\cdot {EE})}^{1/2}\sim 0.2\mbox{-}0.3$ are generally lower than those measured by Planck. We find large fluctuations of E/B asymmetry and TE correlation depending on the observer's position and temporal fluctuations of ISM properties due to bursts of star formation. The synthetic maps are made publicly available to provide novel models of the microwave sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Dwarf Galaxies at Cosmic Noon: New JWST Constraints on Satellite Models and Subhalo Tidal Evolution

The advent of JWST has revolutionized the study of faint satellite galaxies at z ≳ 1, enabling statistical constraints on galaxy evolution and the galaxy–halo connection in a previously unexplored mass and redshift regime. We compare satellite abundances at 1 < z < 3.5 from recent JWST observations with predictions from cosmological dark-matter-only zoom-in simulations. We identify and quantify several sources of biases that can impact theoretical satellite counts, finding that assumptions about subhalo tidal evolution introduce the largest uncertainty in predictions for the satellite mass function. Using a flexible galaxy disruption model, we explore a range of disruption scenarios, spanning hydrodynamically motivated and idealized prescriptions, to bracket plausible physical outcomes. We show that varying galaxy durability can change the predicted satellite mass functions by a factor of ∼3.5. The JWST data and our fiducial model are consistent within 1σ–2σ across the full redshift (1 < z < 3.5) and stellar mass (M⋆ > 10 7 M ⊙ ) range probed. We find evidence that subhalos are at least as long-lived as predicted by hydrodynamic simulations. Our framework will enable robust constraints on the tidal evolution of subhalos with future observations. This work presents the first direct comparison between cosmological models and observations of the high-redshift satellite population in this low-mass regime. These results showcase JWST’s emerging power to test structure formation in the first half of the Universe in a new domain and to constrain the physical processes driving the evolution of low-mass galaxies across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Multigroup Thermal Radiation Transport with Tensor Trains

We investigate the application of tensor-train (TT) algorithms to multigroup thermal radiation transport (i.e., photon radiation transport). The TT framework enables simulations at discretizations that might otherwise be computationally infeasible on conventional hardware. We show that solutions to certain multigroup problems possess an intrinsic low-rank structure, which the TT representation leverages effectively. This enables us to solve problems where the discretized solution size exceeds a trillion parameters on a single node. The solver is evaluated on a range of test problems with varying levels of complexity, consistently achieving compression factors greater than 100× and speedups exceeding 2×. We also investigate alternative TT topologies by analyzing the low-rank structure of the merged spatio-spectral core to assess the potential for greater compression. This analysis suggests that compression gains could increase by factors as large as 7. Our results indicate that the low-rank structure of the merged spatio-spectral core captures the spatio-spectral complexity of the solution, largely driven by the opacity structure of the medium. Beyond identifying opportunities for improved compression, this analysis highlights the types of errors that may arise in angle-integrated quantities when exploiting this low-rank structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Propagating Uncertainties in the SALT3 Model-training Process to Cosmological Constraints

Type Ia supernovae (SNe Ia) are standardizable candles that must be modeled empirically to yield cosmological constraints. To understand the robustness of this modeling to variations in the model-training procedure, we build an end-to-end pipeline to test the recently developed SALT3 model. We explore the consequences of removing pre-2000s low-z or poorly calibrated U-band data, adjusting the amount and fidelity of SN Ia spectra, and using a model-independent framework to simulate the training data. We find that the SALT3 model surfaces are improved by having additional spectra and U-band data, and can be shifted by ~5% if host-galaxy contamination is not sufficiently removed from SN spectra. We find that resulting measurements of w are consistent to within 2.5% for all of the training variants explored in this work, with the largest shifts coming from variants that add color-dependent calibration offsets or host-galaxy contamination to the training spectra and those that remove pre-2000s low-z data. These results demonstrate that the SALT3 model-training procedure is largely robust to reasonable variations in the training data, but that additional attention must be paid to the treatment of spectroscopic data in the training process. We also find that the training procedure is sensitive to the color distributions of the input data—the resulting w measurement can be biased by ~2% if the color distribution is not sufficiently wide. Future low-z data, particularly u-band observations and high signal-to-noise ratio SN Ia spectra, will help to significantly improve SN Ia modeling in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A robust approach to Gaussian process implementation

Abstract. Gaussian process (GP) regression is a flexible modeling technique used to predict outputs and to capture uncertainty in the predictions. However, the GP regression process becomes computationally intensive when the training spatial dataset has a large number of observations. To address this challenge, we introduce a scalable GP algorithm, termed MuyGPs, which incorporates nearest-neighbor and leave-one-out cross-validation during training. This approach enables the evaluation of large spatial datasets with state-of-the-art accuracy and speed in certain spatial problems. Despite these advantages, conventional quadratic loss functions used in the MuyGPs optimization, such as root mean squared error (RMSE), are highly influenced by outliers. We explore the behavior of MuyGPs in cases involving outlying observations and, subsequently, develop a robust approach to handle and mitigate their impact. Specifically, we introduce a novel leave-one-out loss function based on the pseudo-Huber function (LOOPH) that effectively accounts for outliers in large spatial datasets within the MuyGPs framework. Our simulation study shows that the LOOPH loss method maintains accuracy despite outlying observations, establishing MuyGPs as a powerful tool for mitigating unusual observation impacts in the large data regime. In the analysis of US ozone data, MuyGPs provides accurate predictions and uncertainty quantification, demonstrating its utility in managing data anomalies. Through these efforts, we advance the understanding of GP regression in spatial contexts.

Mukangango, Juliette↗
DOE OSTI2025

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗
DOE OSTI2026

Runoff evaluation in an Earth System Land Model for permafrost regions in Alaska

Modeling of hydrological runoff is essential for accurately capturing spatiotemporal feedbacks within the land–atmosphere system, particularly in sensitive regions such as permafrost landscapes. However, substantial uncertainties persist in the terrestrial runoff parameterization schemes used in Earth system and land surface models. This is particularly true in permafrost regions, where landscape heterogeneity is high and reliable observational data are scarce. In this study, we evaluate the performance of runoff parameterization schemes in the Energy Exascale Earth System Model (E3SM) land model (ELM). Our proposed framework leverages simulation results from the Advanced Terrestrial Simulator (ATS), which is a physics-based integrated surface/subsurface hydrologic model that has been successfully evaluated previously in Arctic tundra regions. We used ATS to simulate runoff from 22 representative hillslopes in the Sagavanirktok River basin, located on the North Slope of Alaska, then compared the output with ELM's parameterized representation of total runoff. Results show that (1) ELM's total runoff was the same order of magnitude as the ATS simulations, and both models were similarly variable over time; (2) minor adjustments to coefficients in ELM's runoff parameterization improved the match between the ATS simulation and ELM's parameterized representation of annual and seasonal total runoff; (3) overall, runoff responses in ATS and ELM are more similar in flat hillslope environments compared to steep hillslopes; and (4) shallower active layer thicknesses and higher precipitation simulations resulted in lower correlations between the two models due to greater total runoff. By incorporating the optimized runoff coefficients from the Sagavanirktok River basin into ELM, the simulated total runoff better matched the streamflow observations at a small watershed located on the Seward Peninsula of Alaska. Our findings revealed important insights into the effectiveness of runoff parameterizations in land surface models and pathways for improving runoff coefficients in typical Arctic regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
NASA NTRS1982

Radiative transfer model for heterogeneous 3-D scenes

A general mathematical framework for simulating processes in heterogeneous 3-D scenes is presented. Specifically, a model was designed and coded for application to radiative transfers in vegetative scenes. The model is unique in that it predicts (1) the directional spectral reflectance factors as a function of the sensor's azimuth and zenith angles and the sensor's position above the canopy, (2) the spectral absorption as a function of location within the scene, and (3) the directional spectral radiance as a function of the sensor's location within the scene. The model was shown to follow known physical principles of radiative transfer. Initial verification of the model as applied to a soybean row crop showed that the simulated directional reflectance data corresponded relatively well in gross trends to the measured data. However, the model can be greatly improved by incorporating more sophisticated and realistic anisotropic scattering algorithms

Kimes, D. S.↗
NASA NTRS2012

Radiative Transfer Through Clouds and Its Applications in Support of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) Mission

The Greenland and Antarctic ice sheets, which contain enough ice to raise sea level by about 7 and 60 m, respectively, are losing mass at an increasing rate. To acquire continuous information of the cryosphere, after the Ice, Cloud, and land Elevation Satellite (ICESat) (2003-2010), NASA is actively planning for the ICESat-2 mission. Both ICESat and ICESat-2 are space-borne lidar altimetry systems. The systems measure the time of flight of the arriving photons that are reflected by the surface to deduce the elevation of the underlying terrain. As one of NASA's top priority missions, ICESat-2 is scheduled to launch in 2016. One of the major science goals of ICESat-2 is to quantify the ice sheet mass balance to determine its contributions to the sea level change and its impacts on ocean circulation (Abdalati et al. 2010). Compared to ICESat, which operates at 40 Hz and records the reflected laser energy as a waveform, the significantly improved ICESat-2 lidar employs a 532 nm micro-pulse photon counting system that operates at a high frequency of 10kHz with single photon detectability (Yang et al. 2012). To achieve its science goals, ICESat-2 requires the ability of detecting the elevation change with an accuracy of 0.2 cm/year over the entire ice sheet. Since every photon emitted by the lidar system will travel through the atmosphere, clouds can certainly affect the flight time of the arriving photons. Forward scattering by cloud particles increases the photon path length, thus resulting in biases in ice sheet elevation measurements known as atmospheric path delay (Duta et al. 2001, Yang et al. 2010, 2011). To ensure the accuracy of ICESat-2 surface elevation measurements, it is critical to understand how clouds would affect the travel time of arriving photons. In this talk, we will first present a framework that simulates the behavior of a space-borne 532 mn micro-pulse photon counting lidar in cloudy and clear atmospheres. To investigate the process of laser propagation through clouds, a 3-D Monte Carlo radiative transfer model is used to simulate the photon path distribution and the Poisson distribution is adopted for the number of photon returns. Since the photon counting system only registers the time of the first arriving photon within the detector "dead time", the retrieved average surface elevation tends to bias towards higher values. This is known as the first photon bias. With the scenarios simulated here, the first photon bias for clear sky is about 6.5 cm. Clouds affect surface altimetry in two ways: (1) cloud attenuation lowers the average number of arriving photons and hence reduces the first photon bias; (2) cloud forward scattering increases the photon path length and makes the surface appear further away from the satellite. Compared to clear sky, the average surface elevation detected by the photon counting system for cloudy sky with optical depth 1.0 is 4.0 to 6.0 cm lower for the simulations conducted. The effect of surface roughness on the accuracy of elevation retrievals will also discussed.

Yang, Yuekui↗
NASA NTRS2013

Nuclear Thermal Rocket Simulation in NPSS

Four nuclear thermal rocket (NTR) models have been created in the Numerical Propulsion System Simulation (NPSS) framework. The models are divided into two categories. One set is based upon the ZrC-graphite composite fuel element and tie tube-style reactor developed during the Nuclear Engine for Rocket Vehicle Application (NERVA) project in the late 1960s and early 1970s. The other reactor set is based upon a W-UO2 ceramic- metallic (CERMET) fuel element. Within each category, a small and a large thrust engine are modeled. The small engine models utilize RL-10 turbomachinery performance maps and have a thrust of approximately 33.4 kN (7,500 lbf ). The large engine models utilize scaled RL-60 turbomachinery performance maps and have a thrust of approximately 111.2 kN (25,000 lbf ). Power deposition profiles for each reactor were obtained from a detailed Monte Carlo N-Particle (MCNP5) model of the reactor cores. Performance factors such as thermodynamic state points, thrust, specific impulse, reactor power level, and maximum fuel temperature are analyzed for each engine design.

Belair, Michael L.↗
NASA NTRS2013

Nuclear Thermal Rocket Simulation in NPSS

Four nuclear thermal rocket (NTR) models have been created in the Numerical Propulsion System Simulation (NPSS) framework. The models are divided into two categories. One set is based upon the ZrC-graphite composite fuel element and tie tube-style reactor developed during the Nuclear Engine for Rocket Vehicle Application (NERVA) project in the late 1960s and early 1970s. The other reactor set is based upon a W-UO2 ceramic-metallic (CERMET) fuel element. Within each category, a small and a large thrust engine are modeled. The small engine models utilize RL-10 turbomachinery performance maps and have a thrust of approximately 33.4 kN (7,500 lbf ). The large engine models utilize scaled RL-60 turbomachinery performance maps and have a thrust of approximately 111.2 kN (25,000 lbf ). Power deposition profiles for each reactor were obtained from a detailed Monte Carlo N-Particle (MCNP5) model of the reactor cores. Performance factors such as thermodynamic state points, thrust, specific impulse, reactor power level, and maximum fuel temperature are analyzed for each engine design.

Belair, Michael L.↗
NASA NTRS2016

Tool for the Integrated Dynamic Numerical Propulsion System Simulation (NPSS)/Turbine Engine Closed-Loop Transient Analysis (TTECTrA) User's Guide

The Tool for Turbine Engine Closed-Loop Transient Analysis (TTECTrA ver2) is a control design tool thatenables preliminary estimation of transient performance for models without requiring a full nonlinear controller to bedesigned. The program is compatible with subsonic engine models implemented in the MATLAB/Simulink (TheMathworks, Inc.) environment and Numerical Propulsion System Simulation (NPSS) framework. At a specified flightcondition, TTECTrA will design a closed-loop controller meeting user-defined requirements in a semi or fully automatedfashion. Multiple specifications may be provided, in which case TTECTrA will design one controller for each, producing acollection of controllers in a single run. Each resulting controller contains a setpoint map, a schedule of setpointcontroller gains, and limiters; all contributing to transient characteristics. The goal of the program is to providesteady-state engine designers with more immediate feedback on the transient engine performance earlier in the design cycle.

Transient↗
NASA NTRS2015

A Complementary Note to 'A Lag-1 Smoother Approach to System-Error Estimation': The Intrinsic Limitations of Residual Diagnostics

Recently, this author studied an approach to the estimation of system error based on combining observation residuals derived from a sequential filter and fixed lag-1 smoother. While extending the methodology to a variational formulation, experimenting with simple models and making sure consistency was found between the sequential and variational formulations, the limitations of the residual-based approach came clearly to the surface. This note uses the sequential assimilation application to simple nonlinear dynamics to highlight the issue. Only when some of the underlying error statistics are assumed known is it possible to estimate the unknown component. In general, when considerable uncertainties exist in the underlying statistics as a whole, attempts to obtain separate estimates of the various error covariances are bound to lead to misrepresentation of errors. The conclusions are particularly relevant to present-day attempts to estimate observation-error correlations from observation residual statistics. A brief illustration of the issue is also provided by comparing estimates of error correlations derived from a quasi-operational assimilation system and a corresponding Observing System Simulation Experiments framework.

Fixed-lag smoothing↗