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At least 559 records · Page 31

A model of stationary gravity wave breakdown with convective adjustment

A steady WKB model of gravity wave propagation including convective adjustment is used to investigate approximations used in various gravity-wave parameterization schemes. First, it is shown that estimates of the wave breaking height assuming a single horizontal wavenumber gravity wave can lead to errors if the topography is not sinusoidal. Second, the model results show that the assumption that wave growth ceases with the onset of convection or shear instability is an oversimplification. Since convection appears first over a very limited spatial region of the wave field, the wave is initially unaffected by turbulent mixing. However, when the convection zone spreads over a large portion of the wave field the amplitude is constrained. Estimates of the heat flux by breaking gravity waves are used to develop a simple parameterization of the vertical diffusion in terms of the Reynolds stress.

Schoeberl, Mark R.↗

Tracking magnetogram proper motions by multiscale regularization

Long uninterrupted sequences of solar magnetograms from the global oscillations network group (GONG) network and from the solar and heliospheric observatory (SOHO) satellite will provide the opportunity to study the proper motions of magnetic features. The possible use of multiscale regularization, a scale-recursive estimation technique which begins with a prior model of how state variables and their statistical properties propagate over scale. Short magnetogram sequences are analyzed with the multiscale regularization algorithm as applied to optical flow. This algorithm is found to be efficient, provides results for all the spatial scales spanned by the data and provides error estimates for the solutions. It is found that the algorithm is less sensitive to evolutionary changes than correlation tracking.

Jones, Harrison P.↗

The use of magnetic field data to estimate attitude and trajectory for the Rossi X-Ray Timing Explorer (RXTE)

A single augmented extended Kalman filter (EKF) is proposed for the simultaneous and autonomous estimation of spacecraft trajectory and attitude with data from the Rossi X-ray timing explorer (RXTE) magnetometer and gyro-measured body rates. The derivation of the EKF is outlined, including the measurement update and the propagation. The results from a 12 hour span of data are processed and compared with operational estimations computed at the NASA Goddard Space Flight Center (MD). The filter was found to be able to overcome very large initial errors and converge to steady state averages of less than 30 km in position, 0.05 km/s in velocity and 3 deg in attitude.

Deutschmann, Julie↗

A Study into the Method of Precise Orbit Determination of a HEO Orbiter by GPS and Accelerometer

In the present day, orbit determination by Global Positioning System (GPS) is not unusual. Especially for low-cost small satellites, position determination by an on-board GPS receiver provides a cheap, reliable and precise method. However, the original purpose of GPS is for ground users, so the transmissions from all of the GPS satellites are directed toward the Earth s surface. Hence there are some restrictions for users above the GPS constellation to detect those signals. On the other hand, a desire for precise orbit determination for users in orbits higher than GPS constellation exists. For example, the next Japanese Very Long Baseline Interferometry (VLBI) mission "ASTRO-G" is trying to determine its orbit in an accuracy of a few centimeters at apogee. The use of GPS is essential for such ultra accurate orbit determination. This study aims to construct a method for precise orbit determination for such high orbit users, especially in High Elliptical Orbits (HEOs). There are several approaches for this objective. In this study, a hybrid method with GPS and an accelerometer is chosen. Basically, while the position cannot be determined by an on-board GPS receiver or other Range and Range Rate (RARR) method, all we can do to estimate the user satellite s position is to propagate the orbit along with the force model, which is not perfectly correct. However if it has an accelerometer (ACC), the coefficients of the air drag and the solar radiation pressure applied to the user satellite can be updated and then the propagation along with the "updated" force model can improve the fitting accuracy of the user satellite s orbit. In this study, it is assumed to use an accelerometer available in the present market. The effects by a bias error of an accelerometer will also be discussed in this paper.

Ikenaga, Toshinori↗

ACTS and OLYMPUS propagation experiments

The OLYMPUS and ACTS satellites both provide opportunities for 10 to 30 GHz propagation measurements. The spacecraft are sufficiently alike that OLYMPUS can be used to test some prototype ACTS equipment and experiments. Data are particularly needed on short term signal behavior and in support of uplink power control and adaptive forward error correction (FEC) techniques. The Virginia Tech Satellite Communications Group has proposed a set of OLYMPUS experiments including attenuation and fade rate measurements, data communications, uplink power control, rain scatter interference, and small-scale site diversity operation. A digital signal processing receiver for the OLYMPUS and ACTS beacon signals is being developed.

Bostian, Charles W.↗

A probabilistic fracture mechanics approach for structural reliability assessment of space flight systems

A probabilistic fracture mechanics approach for predicting the failure life distribution due to subcritical crack growth is presented. A state-of-the-art crack propagation method is used in a Monte Carlo simulation to generate a distribution of failure lives. The crack growth failure model expresses failure life as a function of stochastic parameters including environment, loads, material properties, geometry, and model specification errors. A stochastic crack growth rate model that considers the uncertainties due to scatter in the data and mode misspecification is proposed. The rationale for choosing a particular type of probability distribution for each stochastic input parameter and for specifying the distribution parameters is presented. The approach is demonstrated through a probabilistic crack growth failure analysis of a welded tube in the Space Shuttle Main Engine. A discussion of the results from this application of the methodology is given.

Sutharshana, S.↗

Propagation of quasiplane waves along an impedance boundary

The parabolic approximation for the acoustic equations of motion is applied to the study of the sound field generated by a time harmonic plane wave at grazing incidence to a finite impedance boundary. The resulting equations possess a solution which may be expressed in terms of the complementary error function. Asymptotic expansion of this solution for field points near the boundary provides results compatible with those for a point source on the boundary for both the soft boundary (finite impedance) and hard boundary (the limit in which the impedance becomes infinite) cases. The presence of a surface wave in the solution is also established.

Mcaninch, G. L.↗

Ionospheric propagation correction modeling for satellite altimeters

The theoretical basis and avaliable accuracy verifications were reviewed and compared for ionospheric correction procedures based on a global ionsopheric model driven by solar flux, and a technique in which measured electron content (using Faraday rotation measurements) for one path is mapped into corrections for a hemisphere. For these two techniques, RMS errors for correcting satellite altimeters data (at 14 GHz) are estimated to be 12 cm and 3 cm, respectively. On the basis of global accuracy and reliability after implementation, the solar flux model is recommended.

Nesterczuk, G.↗

Integrated Multi-Satellite Evaluation for the Global Precipitation Measurement: Impact of Precipitation Types on Spaceborne Precipitation Estimation

Integrated multi-sensor assessment is proposed as a novel approach to advance satellite precipitation validation in order to provide users and algorithm developers with an assessment adequately coping with the varying performances of merged satellite precipitation estimates. Gridded precipitation rates retrieved from space sensors with quasi-global coverage feed numerous applications ranging from water budget studies to forecasting natural hazards caused by extreme events. Characterizing the error structure of satellite precipitation products is recognized as a major issue for the usefulness of these estimates. The Global Precipitation Measurement (GPM) mission aims at unifying precipitation measurements from a constellation of low-earth orbiting (LEO) sensors with various capabilities to detect, classify and quantify precipitation. They are used in combination with geostationary observations to provide gridded precipitation accumulations. The GPM Core Observatory satellite serves as a calibration reference for consistent precipitation retrieval algorithms across the constellation. The propagation of QPE uncertainty from LEO active/passive microwave (PMW) precipitation estimates to gridded QPE is addressed in this study, by focusing on the impact of precipitation typology on QPE from the Level-2 GPM Core Observatory Dual-frequency Precipitation Radar (DPR) to the Microwave Imager (GMI) to Level-3 IMERG precipitation over the Conterminous U.S. A high-resolution surface precipitation used as a consistent reference across scales is derived from the ground radar-based Multi-Radar/Multi-Sensor. While the error structure of the DPR, GMI and subsequent IMERG is complex because of the interaction of various error factors, systematic biases related to precipitation typology are consistently quantified across products. These biases display similar features across Level-2 and Level-3, highlighting the need to better resolve precipitation typology from space and the room for improvement in global-scale precipitation estimates. The integrated analysis and framework proposed herein applies more generally to precipitation estimates from sensors and error sources affecting low-earth orbiting satellites and derived gridded products.

Rainfall↗

Integrated Multi-satellite Evaluation for the Global Precipitation Measurement: Impact of Precipitation Types on Spaceborne Precipitation Estimation

An integrated multi-sensor assessment is proposed as a novel approach to advance satellite precipitation validation in order to provide users and algorithm developers with an assessment adequately coping with the varying performances of merged satellite precipitation estimates. Gridded precipitation rates retrieved from space sensors with quasi-global coverage feed numerous applications ranging from water budget studies to forecasting natural hazards caused by extreme events. Characterizing the error structure of satellite precipitation products is recognized as a major issue for the usefulness of these estimates. The Global Precipitation Measurement (GPM) mission aims at unifying precipitation measurements from a constellation of low-earth orbiting (LEO) sensors with various capabilities to detect, classify and quantify precipitation. They are used in combination with geostationary observations to provide gridded precipitation accumulations. The GPM Core Obser­vatory satellite serves as a calibration reference for consistent precipitation retrieval algorithms across the constellation. The propagation of QPE uncertainty from LEO active/passive microwave (PMW) precipitation estimates to gridded QPE is addressed in this study, by focusing on the impact of precipitation typology on QPE from the Level-2 GPM Core Observatory Dual-frequency Precipitation Radar (DPR) to the Microwave Imager (GMI) to Level-3 IMERG precipitation over the Conterminous U.S. A high-resolution surface precipitation used as a consistent reference across scales is derived from the ground radar-based Multi-Radar/Multi­Sensor. While the error structure of the DPR, GMI and subsequent IMERG is complex because of the interaction of various error factors, systematic biases related to precipitation typology are consistently quantified across products. These biases display similar features across Level-2 and Level-3, highlighting the need to better resolve precipitation typology from space and the room for improvement in global­scale precipitation estimates. The integrated analysis and framework proposed herein applies more generally to precipitation estimates from sensors and error sources affecting low-earth orbiting satellites and derived gridded products.

Pierre-Emmanuel Kirstette↗

Rossby waves in a fluctuating zonal mean flow

The effects of the zonal mean wind variability on the energy propagation of a stationary Rossby wave in a barotropic nondivergent atmosphere are studied. It is shown that the random nature of the zonal wind fluctuations do not allow Rossby wave energy to propagate from its energy source. The mechanism for this effect is strongly dependent on the spatial resolution at which the zonal mean flow is assumed to be known. Some speculations are offered on the relation between this mechanism and the systematic error of some low-resolution climate models.

Pandolfo, Lionel↗

Verification Assessment of Flow Boundary Conditions for CFD Analysis of Supersonic Inlet Flows

Boundary conditions for subsonic inflow, bleed, and subsonic outflow as implemented into the WIND CFD code are assessed with respect to verification for steady and unsteady flows associated with supersonic inlets. Verification procedures include grid convergence studies and comparisons to analytical data. The objective is to examine errors, limitations, capabilities, and behavior of the boundary conditions. Computational studies were performed on configurations derived from a "parameterized" supersonic inlet. These include steady supersonic flows with normal and oblique shocks, steady subsonic flow in a diffuser, and unsteady flow with the propagation and reflection of an acoustic disturbance.

Slater, John W.↗

Divergence Free High Order Filter Methods for the Compressible MHD Equations

The generalization of a class of low-dissipative high order filter finite difference methods for long time wave propagation of shock/turbulence/combustion compressible viscous gas dynamic flows to compressible MHD equations for structured curvilinear grids has been achieved. The new scheme is shown to provide a natural and efficient way for the minimization of the divergence of the magnetic field numerical error. Standard diver- gence cleaning is not required by the present filter approach. For certain MHD test cases, divergence free preservation of the magnetic fields has been achieved.

Yea, H. C.↗

High Order Filter Methods for the Non-ideal Compressible MHD Equations

The generalization of a class of low-dissipative high order filter finite difference methods for long time wave propagation of shock/turbulence/combustion compressible viscous gas dynamic flows to compressible MHD equations for structured curvilinear grids has been achieved. The new scheme is shown to provide a natural and efficient way for the minimization of the divergence of the magnetic field numerical error. Standard divergence cleaning is not required by the present filter approach. For certain non-ideal MHD test cases, divergence free preservation of the magnetic fields has been achieved.

Yee, H. C.↗

Results of the Compensated Earth-Moon-Earth Retroreflector Laser Link (CEMERLL) Experiment

Adaptive optics techniques can be used to realize a robust low bit-error-rate link by mitigating the atmosphere-induced signal fades in optical communications links between ground-based transmitters and deep-space probes. Phase I of the Compensated Earth-Moon-Earth Retroreflector Laser Link (CEMERLL) experiment demonstrated the first propagation of an atmosphere-compensated laser beam to the lunar retroreflectors. A 1.06-micron Nd:YAG laser beam was propagated through the full aperture of the 1.5-m telescope at the Starfire Optical Range (SOR), Kirtland Air Force Base, New Mexico, to the Apollo 15 retroreflector array at Hadley Rille. Laser guide-star adaptive optics were used to compensate turbulence-induced aberrations across the transmitter's 1.5-m aperture. A 3.5-m telescope, also located at the SOR, was used as a receiver for detecting the return signals. JPL-supplied Chebyshev polynomials of the retroreflector locations were used to develop tracking algorithms for the telescopes. At times we observed in excess of 100 photons returned from a single pulse when the outgoing beam from the 1.5-m telescope was corrected by the adaptive optics system. No returns were detected when the outgoing beam was uncompensated. The experiment was conducted from March through September 1994, during the first or last quarter of the Moon.

Wilson, K. E.↗

Soil Moisture Data Assimilation

Accurate knowledge of soil moisture at the continental scale is important for improving predictions of weather, agricultural productivity and natural hazards, but observations of soil moisture at such scales are limited to indirect measurements, either obtained through satellite remote sensing or from meteorological networks. Land surface models simulate soil moisture processes, using observation-based meteorological forcing data, and auxiliary information about soil, terrain and vegetation characteristics. Enhanced estimates of soil moisture and other land surface variables, along with their uncertainty, can be obtained by assimilating observations of soil moisture into land surface models. These assimilation results are of direct relevance for the initialization of hydro-meteorological ensemble forecasting systems. The success of the assimilation depends on the choice of the assimilation technique, the nature of the model and the assimilated observations, and, most importantly, the characterization of model and observation error. Systematic differences between satellite-based microwave observations or satellite-retrieved soil moisture and their simulated counterparts require special attention. Other challenges include inferring root-zone soil moisture information from observations that pertain to a shallow surface soil layer, propagating information to unobserved areas and downscaling of coarse information to finer-scale soil moisture estimates. This chapter summarizes state-of-the-art solutions to these issues with conceptual data assimilation examples, using techniques ranging from simplified optimal interpolation to spatial ensemble Kalman filtering. In addition, operational soil moisture assimilation systems are discussed that support numerical weather prediction at ECMWF and provide value-added soil moisture products for the NASA Soil Moisture Active Passive mission.

radar backscatter↗

ACIX-Aqua: A Global Assessment of Atmospheric Correction Methods for Landsat-8 and Sentinel-2 Over Lakes, Rivers, and Coastal Waters

Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (ρ̂w). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ρ̂w560 and ρ̂w664 were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ρ̂w490≤λ≤743nm yielded 25–70% uncertainties in derived Chla and TSS products for top-performing AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems.

Nima Pahlevan↗

First Attempt of Global-scale Assimilation of Subdaily Scale Soil Moisture Estimates from CYGNSS and SMAP into a Land Surface Model

Soil moisture performs a key function in the hydrologic process and understanding the global-scale water cycle. However, estimations of soil moisture taken from current sun-synchronous orbit (SSO) satellites are limited in that they are neither spatially nor temporally continuous. This limitation creates discontinuous soil moisture observation from space and hampers our understanding of the fundamental processes that control the surface hydrologic cycle across both time and space domains. Here, we propose to use frequent soil moisture observations from NASA’s constellation of eight micro-satellites called the Cyclone Global Navigation Satellite System(CYGNSS) together with the Soil Moisture Active Passive (SMAP) to assimilate subdaily-scale soil moisture intoa land surface model(LSM). Our results, which are based on triple collocation analysis(TCA), show how current scientific advances in satellite systems can fill previous gaps in soil moisture observations in subdaily scale bypast observations, and eventually adds value to improvements in global scale soil moisture estimates in LSMs. Overall, TCA-based fractional mean square errors (fMSE) of LSM soil moisture are improved by 61% with the synergetic assimilation of CYGNSS data with SMAP soil moisture observations. However, assimilating satellite-based soil moisture over dense vegetation areas can degrade the performance of LSMs as these areas propagate erroneous soil moisture information to LSMs. To our knowledge, this study isthe first global assimilation of GNSS-based soil moisture observations in land surface models.

Hyunglok Kim↗