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At least 685 records · Page 38

The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model

This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. An Ensemble Kalman Filter is used to test such hypothesis across the Contiguous United States during April 2015 – December 2018. The performance of the proposed methodology is assessed for several modeled vegetation and water variables (evapotranspiration, net ecosystem exchange, and soil moisture) in terms of random errors and anomaly correlation coefficients against a set of independent validation datasets (i.e., Global Land Evaporation Amsterdam Model, FLUXCOM, and International Soil Moisture Network). Results show that the assimilation of leaf area index mostly improves the estimation of evapotranspiration and net ecosystem exchange, whereas the assimilation of surface soil moisture alone improves surface soil moisture content, especially in the western US, in terms of both root mean squared error and anomaly correlation coefficient. The joint assimilation of vegetation and soil moisture information combines the results of individual vegetation and soil moisture assimilations and reduces errors (and increases correlations with the reference datasets) in evapotranspiration, net ecosystem exchange, and surface soil moisture simulated by the land surface model. However, because soil moisture satellite observations only provide information on the water content in the top 5 cm of the soil column, the impact of the proposed data assimilation technique on root zone soil moisture is limited. This work moves one step forward in the direction of improving our estimation and understanding of land surface interactions using a multi-variate data assimilation approach, which can be particularly useful in regions of the world where ground observations are sparse or missing altogether.

Data assimilation↗

The short-term prediction of universal time and length of day using atmospheric angular momentum

The ability to predict short-term variations in the Earth's rotation has gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Earth's orientation corresponding to the rotation angle, can be measured by number of high-precision space geodetic techniques. A Kalman filter developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed times series and a set of predictions for UT1, as well as for additional Earth orientation components. These UT1 predictions utilize an empirically derived random walk stochastic model for the length of the day (LOD) and require frequent and up-to-date measurements of either UT1 or LOD to keep errors from quickly accumulating. Recent studies have shown that LOD variations are correlated with changes in the Earth's axial atmospheric angular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely available from meteorological analysis centers; these data can supplement geodetic measurements to improve the short-term prediction of LOD and have therefore been incorporated as independent data types in the JPL Kalman filter. We find that AAM and, to a lesser extent, AAM forecast data are extremely helpful in generating accurate near-real-time estimates of UT1 and LOD and in improving short-term predictions of these quantities out to about 10 days.

Freedman, A. P.↗

Space Shuttle Orbiter descent navigation

The entry operational sequence (OPS 3) begins approximately 2 hours prior to the deorbit maneuver and continues through atmospheric entry, terminal area energy management (TAEM), approach and landing, and rollout. During this flight phase, the navigation state vector is estimated by the Space Shuttle Orbiter onboard navigation system. This estimate is computed using a six-element sequential Kalman filter, which blends inertial measurement unit (IMU) delta-velocity data with external navaid data. The external navaids available to the filter are tactical air navigation (TACAN), barometric altimeter, and microwave scan beam landing system (MSBLS). Attention is given to the functional design of the Orbiter navigation system, the descent navigation sensors and measurement processing, predicted Kalman gains, correlation coefficients, and current flights navigation performance.

Montez, M. N.↗

Baseline ozone results from 1923 to 1955

Baseline total atmospheric ozone values from the year 1923 to 1955 are reported which have been derived from observations of the solar constant made by Smithsonian Institution sites in both the Northern and Southern Hemispheres. Ozone was determined from absorption by the broad, weak Chappuis band near 0.6 microns as measured on 1194 days at Mt. Montezuma, Chile and 970 days at Table Mountain, California. Results show systematic changes on the order of 25 percent in the ozone level at Montezuma with a time scale of 10-20 years, although the previously reported 30 percent decrease between 1920-1930 and 1940-1950 is found to have been erroneous. Comparisons of ozone data with geomagnetic indices and sunspot number show a suggestive correlation of ozone with sunspot number, although the relation is not borne out by comparison of ozone and sunspot cycles, or by Fourier analysis. Comparison of ozone data in the Chappuis band obtained by a modern filter-wheel radiometer with that obtained from a Dobson spectrometer at Mauna Loa Observatory shows Chappuis band measurements to be 14 percent lower.

Angione, R. J.↗

A globally efficient means of distributing UTC time and frequency through GPS

Time and frequency outputs comparable in quality to the best laboratories have been demonstrated on an integrated system suitable for field application on a global basis. The system measures the time difference between 1 pulse-per-second (pps) signals derived from local primary frequency standards and from a multi-channel GPS C/A receiver. The measured data is processed through optimal SA Filter algorithms that enhance both the stability and accuracy of GPS timing signals. Experiments were run simultaneously at four different sites. Even with large distances between sites, the overall results show a high degree of cross-correlation of the SA noise. With sufficiently long simultaneous measurement sequences, the data shows that determination of the difference in local frequency from an accepted remote standard to better than 1 x 10(exp -14) is possible. This method yields frequency accuracy, stability, and timing stability comparable to that obtained with more conventional common-view experiments. In addition, this approach provides UTC(USNO MC) in real time to an accuracy better than 20 ns without the problems normally associated with conventional common-view techniques. An experimental tracking loop was also set up to demonstrate the use of enhanced GPS for dissemination of UTC(USNO MC) over a wide geographic area. Properly disciplining a cesium standard with a multi-channel GPS receiver, with additional input from USNO, has been found to permit maintaining a timing precision of better than 10 ns between Palo Alto, CA and Washington, DC.

Kusters, John A.↗

Finite Element Aircraft Simulation of Turbulence

A turbulence model has been developed for realtime aircraft simulation that accommodates stochastic turbulence and distributed discrete gusts as a function of the terrain. This model is applicable to conventional aircraft, V/STOL aircraft, and disc rotor model helicopter simulations. Vehicle angular activity in response to turbulence is computed from geometrical and temporal relationships rather than by using the conventional continuum approximations that assume uniform gust immersion and low frequency responses. By using techniques similar to those recently developed for blade-element rotor models, the angular-rate filters of conventional turbulence models are not required. The model produces rotational rates as well as air mass translational velocities in response to both stochastic and deterministic disturbances, where the discrete gusts and turbulence magnitudes may be correlated with significant terrain features or ship models. Assuming isotropy, a two-dimensional vertical turbulence field is created. A novel Gaussian interpolation technique is used to distribute vertical turbulence on the wing span or lateral rotor disc, and this distribution is used to compute roll responses. Air mass velocities are applied at significant centers of pressure in the computation of the aircraft's pitch and roll responses.

McFarland, R. E.↗

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Active radar backscatter (s◦) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s◦ and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s◦ or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s◦ and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

GLEAM↗

Soil Moisture Data Assimilation to Estimate Irrigation Water Use

Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.

R Abolafia-Rosenzweig↗

Monitoring Noble Gases (Xe and Kr) and Aerosols (Cs and Rb) in a Molten Salt Reactor Surrogate Off-Gas Stream Using Laser-Induced Breakdown Spectroscopy (LIBS)

In this study with surrogate materials we show that laser-induced breakdown spectroscopy (LIBS) is a robust tool with promising capability toward monitoring gaseous (Xe and Kr) and aerosol (Cs and Rb) species in an off-gas stream from a molten salt reactor (MSR). MSRs will continually evolve fission products into the cover gas flowing across the reactor headspace. The cover gas entrains Xe and Kr gases, along with aerosol particles, before passing into an off-gas treatment system. Univariate models of Xe and Kr peaks showed a strong correlation to concentration indicated by their coefficients of determination of 0.983 and 0.997, respectively. Multivariate models were built for all four analytes using partial least squares regression coupled with preprocessing steps including normalization, trimming, and/or genetic algorithm derived filters. The models were evaluated by predicting the concentrations of the analytes in four validation samples, in which all calibration models were successfully validated at a confidence interval of 99.9%. Finally, pressure controllers were used to regulate the mass flow rate of Kr flowing into the measurement cell in sinusoidal and stepwise waveforms to test the real-time monitoring capabilities of the regression models. Both univariate and partial least squares Kr models were able to successfully quantify the gas concentration in the real-time evaluation. The root mean squared error of prediction (RMSEP) values for these real-time tests were calculated to be 0.051, 0.060, and 0.121 mol% demonstrating the measurement systems’ capability to perform online monitoring with acceptable accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Guseman, L. F., Jr.↗

Autonomous reconfigurable GPS/INS navigation and pointing system for rendezvous and docking

This paper describes the results of an integrated navigation and pointing system software development effort sponsored by the NASA MSFC through a SBIR Phase 2 Program. The integrated Global Positioning System (GPS)/Inertial Navigation System (INS) implements an autonomous navigation filter that is reconfigurable in real-time to accommodate mission contingencies. An onboard expert system monitors the spacecraft status and reconfigures the navigation filter accordingly, to optimize the system performance. The navigation filter is a multi-mode Kalman filter to estimate the spacecraft position, velocity, and attitude. Three different GPS-based attitude determination techniques, namely, velocity vector matching, attitude vector matching, and interferometric processing, are implemented to encompass different mission contingencies. The integrated GPS/INS navigation filter will use any of these techniques depending on the mission phase and the state of the sensors. The first technique, velocity vector matching, uses the GPS velocity measurement to estimate the INS velocity errors and exploits the correlation between INS velocity and attitude errors to estimate the attitude. The second technique, attitude vector matching, uses INS gyro measurements and GPS carrier phase (integrated Doppler) measurements during a spacecraft rotation maneuver to determine the attitude. Both of these techniques require only one GPS antenna onboard to determine the spacecraft attitude. The third technique, interferometric processing, requires use of multiple GPS antennae. In order to determine 3-axis body attitude, three GPS antennae (2 no-coplanor baselines) are required.

Upadhyay, Triveni N.↗

Pollution Detection Devices

Barringer Research, Inc.'s COSPEC IVB (correlation spectrometer) can sense from a considerable distance emissions from a volcanic eruption. Remote sensor is capable of measuring sulfur dioxide and nitrogen dioxide in the atmosphere. An associated product, GASPEC, a compression of Non-dispersive Gas Filter Spectrometer, is an infrared/ultraviolet gas analyzer which can be used as either a ground based detector or in aircraft/spacecraft applications. Extremely sensitive, it is useful in air pollution investigations for detecting a variety of trace elements, vapors, which exist in the atmosphere in small amounts.

Source record↗

Nonlinear interactions of electromagnetic waves with a thermally generated cesium plasma.

The interaction of a large‐amplitude disturbing wave with a thermally generated, highly ionized cesium plasma has been investigated using a small‐amplitude sensing wave as a probe. The subsequent interaction between the disturbing and sensing waves is related to the plasma electron temperature. The plasma was contained in a magnetic field of 500–1000 G and had an electron plasma frequency near 10 GHz and an electron gyromagnetic frequency around 2 GHz. The sensing wave was a 10 GHz plane wave of approximately 1.5 mW input power and the disturbing wave was 7.5 GHz plane wave of about 1.2 W peak power. Measurements of the sensing‐wave transmitted power were made using standard microwave techniques. A notch filter in the sensing‐wave receiving circuit reduced the scattered disturbing‐wave interference to an immeasurably low level. Langmuir probes were used to detect disturbing‐wave modulation and to measure plasma temperatures and densities. Measurements of the interaction were correlated with a solution of the Boltzmann transport equation for a perturbed Maxwellian distribution function with binary Coulomb collisions.

Jack G Hewitt, Jr↗

Distortion range of filter synthetic discriminant function binary phase-only filters

This paper considers the performance of filter synthetic-discriminant-function binary-phase-only filters (fSDF-BPOFs) with images in the distortion range that were not members of the training set. This evaluation was performed to understand better the distortion range that can be effectively covered by fSDF-BPOFs. The peak correlation and peak clutter responses were measured over various distortion ranges for in-plane and out-of-plane rotations. The peak correlation initially decreased rapidly as the distortion range increased but decreased gradually as the distortion range became larger for the images used in this study. The distortion ranges that can be effectively covered by fSDF-BPOFs appear to be modest: 0-30 deg for in-plane rotation and 0-10 deg for out-of-plane rotation. The results indicate that a temporal multiplexing scheme will be required to cover a large distortion range when BPOFs are used.

Jared, David A.↗

Precipitation-Based ENSO Indices

In this study gridded observed precipitation data sets are used to construct rainfall-based ENSO indices. The monthly El Nino and La Nina Indices (EI and LI) measure the steepest zonal gradient of precipitation anomalies between the equatorial Pacific and the Maritime Continent. This is accomplished by spatially averaging precipitation anomalies using a spatial boxcar filter, finding the maximum and minimum averages within a Pacific and Maritime Continent domain for each month, and taking differences. EI and LI can be examined separately or combined to produce one ENSO Precipitation Index (ESPI). ESPI is well correlated with traditional sea surface temperature and pressure indices, leading Nino 3.4. One advantage precipitation indices have over more conventional indices, is describing the strength and position of the Walker circulation. Examples are given of tracking the impact of ENSO events on the tropical precipitation fields.

Adler, Robert↗

Constraints of Melting, Sea-Level and the Paleoclimate from GRACE

To gauge the accuracy of the GRACE data, we have undertaken a study to compare deformations predicted by GRACE inferences of seasonal water loading to crustal position variations determined from GRACE data. Two manuscripts that resulted from this study are attached. We found a very high correlation between the GRACE and GPS determinations for South America [Duvis et al., 2004]. We also developed a statistical approach for choosing which Stokes coefficients to include. This approach proves to be somewhat more accurate than the traditional Gaussian filter [Duvis et al., 2005].

Davis, James L.↗

Change in ozone trends at southern high latitudes

Long-term ozone variations at 60-70degS in spring are investigated using ground-based and satellite measurements. Strong positive correlation is shown between year-to-year variations of ozone and temperature in the Antarctic collar region in Septembers and Octobers. Based on this relationship, the effect of year-to-year variations in vortex dynamics has been filtered out. This process results in an ozone time series that shows increasing springtime ozone losses over the Antarctic until the mid-1990s. Since approximately 1997 the ozone losses have leveled off. The analysis confirms that this change is consistent across all instruments and is statistically significant at the 95% confidence level. This analysis quantifies the beginning of the recovery of the ozone hole, which is expected from the leveling off of stratospheric halogen loading due to the ban on CFCs and other halocarbons initiated by the Montreal Protocol.

Yang, E.-S.↗

Rapid Initial-State Preparation for the Quantum Simulation of Strongly Correlated Molecules

Studies on quantum algorithms for ground-state energy estimation often assume perfect ground-state preparation; however, in reality the initial state will have imperfect overlap with the true ground state. Here, we address that problem in two ways: by faster preparation of matrix-product-state (MPS) approximations and by more efficient filtering of the prepared state to find the ground-state energy. We show how to achieve unitary synthesis with a Toffoli complexity about 7 × lower than that in prior work and use that to derive a more efficient MPS-preparation method. For filtering, we present two different approaches: sampling and binary search. For both, we use the theory of window functions to avoid large phase errors and minimize the complexity. We find that the binary-search approach provides better scaling with the overlap at the cost of a larger constant factor, such that it will be preferred for overlaps less than about 0.003 . Finally, we estimate the total resources to perform ground-state energy estimation of Fe - S cluster systems, including the Fe Mo cofactor by estimating the overlap of different MPS initial states with potential ground states of the Fe Mo cofactor using an extrapolation procedure. With a modest MPS bond dimension of 4000 , our procedure produces an estimate of approximately 0.9 overlap squared with a candidate ground state of the Fe Mo cofactor, producing a total resource estimate of 7.3 × 10 10 Toffoli gates; neglecting the search over candidates and assuming the accuracy of the extrapolation, this validates prior estimates that have used perfect ground-state overlap. This presents an example of a practical path to prepare states of high overlap in a challenging-to-compute chemical system. Published by the American Physical Society 2025

Berry, Dominic W. (ORCID:0000000334461449)↗