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NASA NTRS2010

Global Precipitation at Your Fingertips, Part I: Data

The most accurate satellite estimates come from the first precipitation radar (PR) to fly in space, aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. Although important for research, the PR's coverage is too limited to give routine monitoring of global precipitation. Rather, we depend on observations of the Earth system's natural emission of microwave energy. Even these data are not available at all times since the satellites on which the microwave sensors fly are in "low Earth orbit", or LEO, some 400-800 km above the surface. Such LEO satellites pass over any given spot on Earth twice a day. In contrast, "geosynchronous Earth orbit", or GEO, satellites at an altitude of about 35,000 km orbit at the same speed that the Earth revolves and therefore always view the same part of the surface. The trade-off is that GEO sensors provide less-precise estimates computed from the Earth system's natural emissions of infrared (IR) energy. Other satellite datasets are used to provide estimates in regions where both microwave and IR have difficulty, such as polar regions or times before mid-1987 when microwave data became available. Finally, rain gauge data where available, have proved to be valuable for helping to reduce biases in the satellite data, which are persistent differences between the satellite estimate and the precipitation that actually occurred. The datasets discussed below take slightly different approaches to mixing and matching the various kinds of input data to create global estimates of precipitation that answer different needs and/or take advantage of different input data. Each is produced at the NASA Goddard Space Flight Center, in Greenbelt, Maryland, USA. [Other combination datasets are produced at other data centers.]

Huffman, George J.↗
NASA NTRS1980

Identification of flexible aircraft from flight data

This paper describes a frequency-domain method for the estimation of the aeroelastic equations of motion of an aircraft using discrete sinusoidal inputs to the control surface actuators. The theory of estimation of the signal inputs and outputs is described as well as the method of obtaining accurate transfer functions from the resulting Bode plots. Methods of quantifying the accuracy of the results from more than one control input are discussed along with ways to obtain state-space and reduced-order models from the transfer function estimates. Presented is a summary of the results obtained in using the technique to develop a model of the USAF Total In-Flight Simulator (TIFS) aircraft which includes five symmetrical elastic modes of motion of the aircraft.

Eulrich, B. J.↗
NASA NTRS2010

A Summary of NASA Related Contributions for the Remote Sensing of Evapotranspiration in Support of Water Management and Agriculture

The amount of evapotranspiration (ET) to the atmosphere can account for 60% or more of the water loss in many semi-arid locations, and can critically affect local economies tied to agriculture, recreation, hydroelectric power, ecosystems, and numerous other water-related areas. NASA supports many activities using satellite and Earth science data to more accurately and cost effectively estimate ET. NASA ET related work includes the research, development and application of techniques. The free and open access of NASA satellite data and products now permits a much wider application of ET mapping. Typically the NASA supported approaches ranges from large regional and continental ET mapping using MODIS (also with AIRS and CERES), GRACE (gravimetric water balance), geostationary (e.g., GOES and Meteosat for near continental sca|e), land surface modeling (i.e, Land Data Assimilation Systems) to fine scale mapping such as provided bvLandsatdata(<100 m). Usually satellite or airborne thermal imagery are used as input to an ET estimated surface energy balance based approach. There are currently several of these ET approaches under development and implementation including 'METRIC', 'SEBS', 'ALEXI/DisALEXI', etc.. One exception is an approach using GRACE satellite data that estimates the terrestrial water storage using gravimetric data over large areas and estimates ET indirectly. Also land surface modeling within the context of data assimilation and integration schemes provides the capability to integrate in situ, ancillary and satellite together to provide a spatially and synoptic estimates of ET also for use to provide for short-term ET predictions. We will summarize NASA related activities contributing to the improved estimation of ET for water management and agriculture with an emphasis on the Western U3.. This summary includes a description of ET projects in the Middle Rio Grande, Yakima, North Platte and other selected basins in the western US. We will also discuss plans to further address ET applications through working with the USDA and the Group on Earth Observations (GEO) to extend and evaluate western U.S. ET mapping to other parts of the U.S. and internationally.

Toll, David↗
NASA NTRS1993

A comparative robustness evaluation of feedforward neurofilters

A comparative performance and robustness analysis is provided for feedforward neurofilters trained with back propagation to filter additive white noise. The signals used in this analysis are simulated pitch rate responses to typical pilot command inputs for a modern fighter aircraft model. Various configurations of nonlinear and linear neurofilters are trained to estimate exact signal values from input sequences of noisy sampled signal values. In this application, nonlinear neurofiltering is found to be more efficient than linear neurofiltering in removing the noise from responses of the nominal vehicle model, whereas linear neurofiltering is found to be more robust in the presence of changes in the vehicle dynamics. The possibility of enhancing neurofiltering through hybrid architectures based on linear and nonlinear neuroprocessing is therefore suggested as a way of taking advantage of the robustness of linear neurofiltering, while maintaining the nominal performance advantage of nonlinear neurofiltering.

Troudet, Terry↗
NASA NTRS2009

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Reichle, Rolf↗
NASA NTRS1997

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or "time to drying" (t(sub d)), is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage 1 drying (as water is removed from storage), and then become more or less constant during soil limited, or "stage 2" drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Salvucci, Guido D.↗
NASA NTRS2000

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or 'time to drying' (t(sub d)) is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage I drying (as water is removed from storage), and then become more or less constant during soil limited, or 'stage II' drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Salvucci, Guido D.↗
NASA NTRS1979

Is the galactic corona produced by galactic flares?

The effect of the differential rotation of the disk of the Galaxy on magnetic field which penetrates the disk is considered. The magnetic field will be progressively distorted from a potential (current-free) form and will at some stage become unstable. It is expected that an MHD instability, a resistive instability, or a combination of the two, will result in the release of the excess magnetic energy and that part of the released energy will be converted into heat. By estimating the energy release and the rate at which this process will occur and by assuming that this energy input is balanced by radiation, estimates were obtained of the parameters of the resulting plasma. It appears that this process alone can heat a galactic corona to temperatures of order 10 to the 6th power K.

Sturrock, P. A.↗
NASA NTRSDate not supplied

Continuing Long-term Global SO 2 Data Record with JPSS OMPS Instruments

NASA’s long-term Earth Observing System (EOS) SO 2 climate data record (CDR) started with Aura/Ozone Monitoring Instrument (OMI, launched in 2004) and is now being continued with the SNPP/Ozone Mapping and Profiler Suite (OMPS, launched in 2011). Both OMI and SNPP/OMPS SO 2 CDRs are produced with the Goddard principal component analysis (PCA) spectral fitting algorithm. By inherently accounting for various instrumental factors, the PCA technique enables highly consistent retrievals between different instruments. In this presentation, we will provide an overview on our effort to further extend the EOS SO 2 CDR, by implementing the PCA SO 2 algorithm with multiple OMPS instruments flying on the Joint Polar Satellite System (JPSS) constellation, including NOAA-20 (launched in 2017) and NOAA-21 (launched in 2022). We will present results analyzing our new NOAA-20/OMPS PCA SO 2 EOS continuity product, to be publicly released in fall of 2023. We will show statistical analyses on the quality of NOAA-20 PCA SO 2 product, such as retrieval noise, biases over background areas, and long-term stability. We will employ a previously established top-down method to estimate SO2 emissions from selected large point sources, using NOAA-20 SO 2 retrievals and assimilated wind fields as input. The SO 2 emission estimates derived from NOAA-20 retrievals will be compared with those from OMI, SNPP/OMPS, and S5P/TROPOMI (TROPOspheric Monitoring Instrument). We will also demonstrate the application of a new machine learning technique that further reduces the noise of NOAA-20 SO 2 retrievals. Finally, we will present preliminary PCA SO 2 retrievals from recently launched satellite sensors, including NOAA-21/OMPS and NASA’s geostationary TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument.

SO2↗
NASA NTRS1971

More solar models and neutrino fluxes.

Derivation of neutrino fluxes from a sequence of solar models that differ from one another in regard to opacity, equation of state, and nuclear cross-section factors. Using current estimates of the relevant input parameters, capture rates are obtained that range between three and ten times the most recent result of the Davis Cl 37 neutrino-capture experiment. The contribution to a theoretical capture rate due to neutrinos from all reactions other than B 8 decay ranges from 0.5 to 1.5 times the latest observational result. Comparison with results of other solar model calculations indicates reasonable agreement when results are normalized to the same input parameters.

Abraham, Z.↗
NASA NTRS1971

Satellite tracking by combined optimal estimation and control techniques.

Combined optimal estimation and control techniques are applied for the first time to satellite tracking systems. Both radio antenna and optical tracking systems of NASA are considered. The optimal estimation is accomplished using an extended Kalman filter resulting in an estimated state of the satellite and of the tracking system. This estimated state constitutes an input to the optimal controller. The optimal controller treats a linearized system with a quadratic performance index. The maximum principle is applied and a steady-state approximation to the resulting Riccati equation is obtained. A computer program, RATS, implementing this algorithm is described. A feasibility study of real-time implementation, tracking simulations, and parameter sensitivity studies are also reported.

Dressler, R. M.↗
NASA NTRS1974

The response of a propeller anemometer to turbulent flow with the mean wind vector perpendicular to the axis of rotation

Determination of the properties of the system transfer function of the vertical-velocity propeller anemometer. A treatment of this problem is presented which is based on an analysis of estimates of the system transfer function derived from estimates of spectra calculated from time histories of indicated vertical velocity and on estimates of the associated input Eulerian vertical-velocity frequency spectra based on the hypothesis that instrument degradation of the Fourier components occurs in the inertial subrange.

Fichtl, G. H.↗
NASA NTRS1976

LACIE performance predictor final operational capability program description, volume 3

The requirements and processing logic for the LACIE Error Model program (LEM) are described. This program is an integral part of the Large Area Crop Inventory Experiment (LACIE) system. LEM is that portion of the LPP (LACIE Performance Predictor) which simulates the sample segment classification, strata yield estimation, and production aggregation. LEM controls repetitive Monte Carlo trials based on input error distributions to obtain statistical estimates of the wheat area, yield, and production at different levels of aggregation. LEM interfaces with the rest of the LPP through a set of data files.

Source record↗
NASA NTRS1977

AEROX: Computer program for transonic aircraft aerodynamics to high angles of attack. Volume 1: Aerodynamic methods and program users' guide

The AEROX program estimates lift, induced-drag and pitching moments to high angles (typ. 60 deg) for wings and for wingbody combinations with or without an aft horizontal tail. Minimum drag coefficients are not estimated, but may be input for inclusion in the total aerodynamic parameters which are output in listed and plotted formats. The theory, users' guide, test cases, and program listing are presented.

Axelson, J. A.↗
NASA NTRS1983

Stability and control over the supersonic and hypersonic speed range

The performance and aerodynamic characteristics of the Space Shuttle Columbia are analyzed over the speed range from Mach 2 to 26 using flight data taken from the first five Space Transportation System flights. These data are used to reconstruct the entry trajectory, calculate vehicle performance, and estimate lateral stability and control derivatives including those assocated with the onboard Reaction Control System. The trajectory reconstruction process is discussed in its relationship to the determination of the vehicle flight characteristics. Vehicle performance results are presented which show that lift and drag were generally overpredicted by 3 percent and that the life-to-drag ratio was underpredicted by 1 percent. Anomalies in pitching-moment trim characteristics are shown and noted to be due to real-gas and Mach-number effects. Lateral stability and control derivatives estimated using programmed test input maneuvers are corrected with preflight predictions and are usually within the uncertainties associated with the predictions. The lateral reaction-control system effectiveness is evaluated.

Compton, H. R.↗
NASA NTRS1985

On the application of a hairpin vortex model of wall turbulence to trailing edge noise prediction

The goal is to develop a technique via a hairpin vortex model of the turbulent boundary layer, which would lead to the estimation of the aerodynamic input for use in trailing edge noise prediction theories. The work described represents an initial step in reaching this goal. The hairpin vortex is considered as the underlying structure of the wall turbulence and the turbulent boundary layer is viewed as an ensemble of typical hairpin vortices of different sizes. A synthesis technique is examined which links the mean flow and various turbulence quantities via these typical vortices. The distribution of turbulence quantities among vortices of different scales follows directly from the probability distribution needed to give the measured mean flow vorticity. The main features of individual representative hairpin vortices are discussed in detail and a preliminary assessment of the synthesis approach is made.

Liu, N. S.↗
NASA NTRS1985

Multiple-input experimental modal analysis

The development of experimental modal analysis techniques is reviewed. System and excitation assumptions are discussed. The methods examined include the forced normal mode excitation method, the frequency response function method, the damped complex exponential response method, the Ibrahim time domain approach, the polyreference approach, and mathematical input-output model methods. The current trend toward multiple input utilization in the estimation of system parameters is noted.

Allemang, R. J.↗