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At least 523 records · Page 29

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially-distributed ensemble Kalman filter. Version 4 of the L4_SM modeling system includes a reduction in the upward recharge of surface soil moisture from below under non-equilibrium conditions, resulting in reduced bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted RMSE in Version 4 is 0.039 m(exp 3) m(exp -3) for surface and 0.026 m(exp 3) m(exp -3) for root-zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near-global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01-0.02 m(exp 3) m(exp -3)) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm year (exp -1)) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

RMSE↗

Status of the NASA GMAO Observing System Simulation Experiment

An Observing System Simulation Experiment (OSSE) is a pure modeling study used when actual observations are too expensive or difficult to obtain. OSSEs are valuable tools for determining the potential impact of new observing systems on numerical weather forecasts and for evaluation of data assimilation systems (DAS). An OSSE has been developed at the NASA Global Modeling and Assimilation Office (GMAO, Errico et al 2013). The GMAO OSSE uses a 13-month integration of the European Centre for Medium- Range Weather Forecasts 2005 operational model at T511/L91 resolution for the Nature Run (NR). Synthetic observations have been updated so that they are based on real observations during the summer of 2013. The emulated observation types include AMSU-A, MHS, IASI, AIRS, and HIRS4 radiance data, GPS-RO, and conventional types including aircraft, rawinsonde, profiler, surface, and satellite winds. The synthetic satellite wind observations are colocated with the NR cloud fields, and the rawinsondes are advected during ascent using the NR wind fields. Data counts for the synthetic observations are matched as closely as possible to real data counts, as shown in Figure 2. Errors are added to the synthetic observations to emulate representativeness and instrument errors. The synthetic errors are calibrated so that the statistics of observation innovation and analysis increments in the OSSE are similar to the same statistics for assimilation of real observations, in an iterative method described by Errico et al (2013). The standard deviations of observation minus forecast (xo-H(xb)) are compared for the OSSE and real data in Figure 3. The synthetic errors include both random, uncorrelated errors, and an additional correlated error component for some observational types. Vertically correlated errors are included for conventional sounding data and GPS-RO, and channel correlated errors are introduced to AIRS and IASI (Figure 4). HIRS, AMSU-A, and MHS have a component of horizontally correlated error. The forecast model used by the GMAO OSSE is the Goddard Earth Observing System Model, Version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) DAS. The model version has been updated to v. 5.13.3, corresponding to the current operational model. Forecasts are run on a cube-sphere grid with 180 points along each edge of the cube (approximately 0.5 degree horizontal resolution) with 72 vertical levels. The DAS is cycled at 6-hour intervals, with 240 hour forecasts launched daily at 0000 UTC. Evaluation of the forecasting skill for July and August is currently underway. Prior versions of the GMAO OSSE have been found to have greater forecasting skill than real world forecasts. It is anticipated that similar forecast skill will be found in the updated OSSE.

OSSE↗

Stochastic model of temporal changes of wind spectra in the free atmosphere

Data for wind profile spectra changes with respect to time from Cape Kennedy, Florida for the time period from 28 November 1964 to 11 May 1967 have been analyzed. A universal statistical distribution of the spectral change which encompasses all vertical wave numbers, wind speed categories, and elapsed time has been developed for the standard deviation of the time changes of detailed wind profile spectra as a function of wave number.

Huang, Y. H.↗

Band analysis by spectral curve fitting

A method of estimating the values of the parameters in the models describing the positions, widths, and intensities of the lines in rotation-vibration bands of gases, without the need for line by line analysis, is described. To illustrate the technique, portions of the 1-0 bands of HCl and CO have been analyzed. The values of up to 27 parameters, their standard deviations, and the correlations between the parameters required to describe the spectra have been obtained.

Lin, C. L.↗

Spacebased Estimation of Moisture Transport in Marine Atmosphere Using Support Vector Regression

An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere ((Theta)) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data ((Theta) calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of (Theta) derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation comparedwith rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.

Support vector regression↗

Evaluation of GOME Satellite Measurements of Tropospheric NO2 and HCHO using Regional Data from Aircraft Campaigns in the Southeastern United States

We compare tropospheric measurements of nitrogen dioxide (NO2) and formaldehyde (HCHO) from the Global Ozone Monitoring Experiment (GOME) satellite instrument with in situ measurements over eastern Texas and the southeast United States. On aveiage, the GOME and in situ measurements of tropospheric NO2 and HCHO columns are consistent despite pronounced sampling differences. The geometric mean in situ to GOME ratios over the campaign are 1.08 for NO2 and 0.84 for HCHO, with corresponding geometric standard deviations of 1.27 and 1.38. The correlation of the observed column spatial variability between the two NO2 measurement sets is encouraging before (r2 = 0.54, n = 18) and after (r2 = 0.67, n = 18) correcting for a sampling bias. Mean relative vertical profiles of HCHO and NO2 calculated with a global three-dimensional model (GEOS-CHEM) and used in the GOME retrieval are highly consistent with in situ measurements; differences would affect the retrieved NO2 and HCHO columns by a few percent. GOME HCHO columns over eastern Texas include contributions from anthropogenic volatile organic compound (VOC) emissions but are dominated by biogenic VOC emissions at the regional scale in August-September when HCHO columns are within 20% of those over the southeastern United States. In situ measurements show that during summer the lowest 1500 m (the lower mixed layer) contains 75% of the tropospheric NO2 column over Houston and Nashville, and 60% of the HCHO column over Houston. Future validation of space-based measurements of tropospheric NO2 and HCHO columns over polluted regions should include coincident in situ measurements that span the entire satellite footprint, especially in the heterogeneous mixed layer.

Martin, R. V.↗

Actively Controlled Shaft Seals for Aerospace Applications

This study experimentally investigates an actively controlled mechanical seal for aerospace applications. The seal of interest is a gas seal, which is considerably more compact than previous actively controlled mechanical seals that were developed for industrial use. In a mechanical seal, the radial convergence of the seal interface has a primary effect on the film thickness. Active control of the film thickness is established by controlling the radial convergence of the seal interface with a piezoelectric actuator. An actively controlled mechanical seal was initially designed and evaluated using a mathematical model. Based on these results, a seal was fabricated and tested under laboratory conditions. The seal was tested with both helium and air, at rotational speeds up to 3770 rad/sec, and at sealed pressures as high as 1.48 x 10(exp 6) Pa. The seal was operated with both manual control and with a closed-loop control system that used either the leakage rate or face temperature as the feedback. The output of the controller was the voltage applied to the piezoelectric actuator. The seal operated successfully for both short term tests (less than one hour) and for longer term tests (four hours) with a closed-loop control system. The leakage rates were typically 5-15 slm (standard liters per minute), and the face temperatures were generally maintained below 100C. When leakage rate was used as the feedback signal, the setpoint leakage rate was typically maintained within 1 slm. However, larger deviations occurred during sudden changes in sealed pressure. When face temperature was used as the feedback signal, the setpoint face temperature was generally maintained within 3 C, with larger deviations occurring when the sealed pressure changes suddenly. the experimental results were compared to the predictions from the mathematical model. The model was successful in predicting the trends in leakage rate that occurred as the balance ratio and sealed pressure changed, although the leakage rates were not quantitatively predicted with a high degree of accuracy. This model could be useful in providing valuable design information for future actively controlled mechanical seals.

Salant, Richard F.↗

Dynamics of solar filaments. VI - Center-to-limb study of H-alpha and C IV velocities in a quiescent filament

The rotation of a stable quiescent filament from near disk center to the limb has been observed. Observations of intensity and velocity were made in H-alpha and C IV, and compared with magnetic field measurements. From the H-alpha observations, it is concluded that the filament is made up of many small scale magnetic features that are not coherently aligned along the neutral line. They are especially convoluted at the apparent 'footpoints'. The measured velocities are of the order of a few kilometers per second in both lines. However, the comparison of the standard deviations of the C IV velocities in and out of the filament as it rotates toward the limb shows that the vertical velocities in the filament are greater than the horizontal velocities. Measurements of velocity do not make it possible to distinguish between the Raadu-Kuperus (1973) or Kippenhahn-Schluter (1957) models for prominences because neither theory is adequately developed for this comparison. However, the observation of the many fine loops brings into question the correctness of either model.

Simon, G.↗

Development of a Cryogenic Thermal Distortion Measurement Facility for Testing the James Webb Space Telescope Instrument Support Integration Module 2-D Test Assemblies

The James Webb Space Telescope Instrument Support Integration Module (ISIM) is being designed and developed at the Goddard Space Flight Center. The ISM Thermal Distortion Testing (ITDT) program was started with the primary objective to validate the ISM mechanical design process. The ITDT effort seeks to establish confidence and demonstrate the ability to predict thermal distortion in composite structures at cryogenic temperatures using solid element models. This-program's goal is to better ensure that ISIM meets all the mechanical and structural requirements by using test results to verify or improve structural modeling techniques. The first step to accomplish the ITDT objectives was to design, and then construct solid element models of a series 2-D test assemblies that represent critical building blocks of the ISIM structure. Second, the actual test assemblies consisting of composite tubes and invar end fittings were fabricated and tested for thermal distortion. This paper presents the development of the GSFC Cryo Distortion Measurement Facility (CDMF) to meet the requirements of the ISIM 2-D test. assemblies, and other future ISIM testing needs. The CDMF provides efficient cooling with both a single, and two-stage cryo-cooler. Temperature uniformity of the test assemblies during thermal transients and at steady state is accomplished by using sapphire windows for all of the optical ports on the radiation shields and by using .thermal straps to cool the test assemblies. Numerical thermal models of the test assemblies were used to predict the temperature uniformity of the parts during cooldown and at steady state. Results of these models are compared to actual temperature data from the tests. Temperature sensors with a 0.25K precision were used to insure that test assembly gradients did not exceed 2K lateral, and 4K axially. The thermal distortions of two assemblies were measured during six thermal cycles from 320K to 35K using laser interferometers. The standard deviation for all of the distortion measurements is less than 0.5 microns, which falls within the ISIM requirement of 3 microns.

Miller, Franklin↗

Broken Ergodicity in Ideal, Homogeneous, Incompressible Turbulence

We discuss the statistical mechanics of numerical models of ideal homogeneous, incompressible turbulence and their relevance for dissipative fluids and magnetofluids. These numerical models are based on Fourier series and the relevant statistical theory predicts that Fourier coefficients of fluid velocity and magnetic fields (if present) are zero-mean random variables. However, numerical simulations clearly show that certain coefficients have a non-zero mean value that can be very large compared to the associated standard deviation. We explain this phenomena in terms of broken ergodicity', which is defined to occur when dynamical behavior does not match ensemble predictions on very long time-scales. We review the theoretical basis of broken ergodicity, apply it to 2-D and 3-D fluid and magnetohydrodynamic simulations of homogeneous turbulence, and show new results from simulations using GPU (graphical processing unit) computers.

Morin, Lee↗

Bounds on Lorentz Violation Parameters in the DUNE Experiment

The Standard Model (SM) has been highly successful in describing fundamental interactions, yet phenomena like neutrino oscillations point to physics beyond its framework. Among the proposed extensions, Lorentz invariance violation (LIV) stands out as a compelling possibility. Long-baseline neutrino experiments such as DUNE, with its 1300 km baseline, offer a promising setting to test LIV effects with high precision. In this work, we evaluate DUNE s sensitivity to LIV by analyzing event rates and oscillation probabilities using the GLoBES framework. A custom implementation of LIV parameters was employed to derive bounds on the aa and cc matrices, identifying the parameter values that lead to a 10% deviation from the standard oscillation probability. Our results show partial agreement with previous studies for the aa parameters, while deviations in the cc parameters highlight the impact of differing methodologies and sensitivities. These findings reinforce the relevance of LIV searches and motivate further theoretical and experimental efforts in this direction.

Cruz, Thiago. [Tech. Fed. Parana U.]↗

System statistical reliability model and analysis

A digital computer code was developed to simulate the time-dependent behavior of the 5-kwe reactor thermoelectric system. The code was used to determine lifetime sensitivity coefficients for a number of system design parameters, such as thermoelectric module efficiency and degradation rate, radiator absorptivity and emissivity, fuel element barrier defect constant, beginning-of-life reactivity, etc. A probability distribution (mean and standard deviation) was estimated for each of these design parameters. Then, error analysis was used to obtain a probability distribution for the system lifetime (mean = 7.7 years, standard deviation = 1.1 years). From this, the probability that the system will achieve the design goal of 5 years lifetime is 0.993. This value represents an estimate of the degradation reliability of the system.

Lekach, V. S.↗

Weather and climate extremes in a changing Arctic

Weather and climate extremes are increasingly occurring in the Arctic. Here, in this Review, we evaluate historical and projected changes in rare Arctic extremes across the atmosphere, cryosphere and ocean and elucidate their driving mechanisms. Clear shifts occur in mean and extreme distributions after ~2000. For instance, pre-2000 to post-2000 observational probabilities of 1.5 standard deviation events increase by 20% for atmospheric heat waves, 76.7% for Atlantic layer warm events, 83.5% for Arctic sea ice loss and 62.9% for Greenland Ice Sheet melt extent — in many cases, low probability, rare extreme events in the early period become the norm in the latter period. These observed changes can be explained using a ‘pushing and triggering’ concept, representing interplay between external forcing and internal variability: long-term warming destabilizes the climate system and ‘pushes’ it to a new state, allowing subsequent variability associated with large-scale atmosphere–ocean–ice interactions and synoptic systems to ‘trigger’ extreme events over different timescales. Ongoing anthropogenic warming is expected to further increase the frequency and magnitude of extremes, such that simulated probabilities of 1.5 standard deviation events increase by 72.6% for atmospheric heat waves, 68.7% for Atlantic layer warm events and 93.3% for Greenland Ice Sheet melt rate between historic (1984–2014) and future (2069–2099) periods under a very high emission scenario. Future research should prioritize the development of physically based metrics, enhance high-resolution observation and modelling capabilities and improve understanding of multiscale Arctic climate drivers.

atmospheric dynamics↗

JT150 1/2-scale nozzle jet noise experiment and comparison with prediction

As part of a program to study flight effects on the exhaust noise of a full scale JT15D engine, static half scale model jet noise experiments were conducted. Acoustic data were recorded for microphone angles of 45 deg to 155 deg with jet conditions for the model scale nozzle corresponding closely to those at 55, 73 and 97 percent of corrected rated speed for the full scale engine. These data are useful for determining the relative importance of jet and core noise in the static full scale engine test data and will in turn allow for a proper evaluation of flight effects on the exhaust noise results. The model scale data are also compared with the coaxial jet noise prediction. Above 1000 Hz, the prediction is nominally 0 to 3 dB higher than the data. The arithmetic mean of the differences between the experimental OASPL and the predicted OASPL for all angles for each run ranged from 0 to -3.2 dB. The standard deviation of all the OASPL differences is 2.2 dB. The discrepancies are greatest at low primary jet velocities and appear to be due to inadequacy in the variable jet density exponent incorporated in the prediction procedure.

Groesbeck, D. E.↗

Study of wind change for the development of loads reduction techniques for the space shuttle

Wind change statistics are analyzed for Vandenberg AFB, California (VAFB) and Kennedy Space Center, Florida (KSC). Means and standard deviations of wind component change and vector wind change modulus within 3-9 and 9-16 km altitude bands are tabulated. The contribution to 3.5 hr wind component change by wind perturbations in various wavelength bands is evaluated. Probability distributions of maximum 3.5 hr wind change in an altitude band are presented and a model for wind change at a specified altitude is tested with data derived from six data bases from VAFB and Santa Monica, California.

Adelfang, S. I.↗

Data Assimilation in the Presence of Forecast Bias: The GEOS Moisture Analysis

We describe the application of the unbiased sequential analysis algorithm developed by Dee and da Silva (1998) to the GEOS DAS moisture analysis. The algorithm estimates the persistent component of model error using rawinsonde observations and adjusts the first-guess moisture field accordingly. Results of two seasonal data assimilation cycles show that moisture analysis bias is almost completely eliminated in all observed regions. The improved analyses cause a sizable reduction in the 6h-forecast bias and a marginal improvement in the error standard deviations.

Dee, Dick P.↗

Predicting performance of parallel computations

An accurate and computationally efficient method for predicting the performance of a class of parallel computations running on concurrent systems is described. A parallel computation is modeled as a task system with precedence relationships expressed as a series-parallel directed acyclic graph. Resources in a concurrent system are modeled as service centers in a queuing network model. Using these two models as inputs, the method outputs predictions of expected execution time of the parallel computation and the concurrent system utilization. The method is validated against both detailed simulation and actual execution on a commercial multiprocessor. Using 100 test cases, the average error of the prediction when compared to simulation statistics is 1.7 percent, with a standard deviation of 1.5 percent; the maximum error is about 10 percent.

Mak, Victor W.↗

Global Reference Atmospheric Model - 1990

GRAM-90, improvement on original model, provides values of atmospheric parameters, either automatically at positions along linear path or along any set of connected positions specified by user. Parameters produced include monthly total and mean values of pressure, density, temperature, and wind, as well as perturbation values and magnitudes. Also provides thermal wind shear for monthly mean winds, percent deviation from standard atmosphere, mean vertical wind, and perturbation data for each position. Perturbation data consist of values of quasi-biennial and random perturbations. Written in FORTRAN 77.

Justus, C. G.↗