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At least 145 records · Page 8
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NASA NTRS1994

Principal modes of atmospheric circulation anomalies associated with global angular momentum fluctuations

This paper provides a description of the variability of global atmospheric angular momentum (GAM) and its relationship with principal modes of three-dimensional atmospheric circulation anomalies. The data used are 5-day mean global wind fields from the European Centre for Medium-Range Weather Forecasts initialized dataset for 1980-1989. Significant seasonal variation of GAM is observed with maxima in April and November and a minimum during late July. The amplitude of the annual cycle is largest in the upper troposphere and decreases toward the surface. Although the lower tropospheric contribution to the total angular momentum is relatively small, its annual cycle is out of phase with those of the upper atmosphere and GAM. Also identified is a distinct semiannual component, with double peaks appearing in April and November. This signal is most noticeable in the upper troposphere above the 300-mb level. The principal modes of zonal-mean angular momentum and meridional circulation anomalies and their coupled modes are obtained by using empirical orthogonal function analysis and singular value decomposition. It is shown that the leading modes of the angular momentum and meridional circulation are coupled with each other and are responsible for much of the variability in GAM. The coupled modes represent fluctuations of upper-level subtropical zonal flow, which are linked to the modulation of Hadley circulation intensity in both hemispheres. It is found that GAM is highly correlated with the first eigenvector of upper-level streamfunction anomalies, which consists of a superrotational flow in the tropics and subtropics, except over the central Pacific where a 'blocked' flow with two subtropical anticyclonic circulation cells straddling the equator is found. Much of the blocked flow is due to the establishment of dipole anomalies in the velocity potential with centers over the central Pacific and the Maritime Continent on the interannual time scale. On the intraseasonal time scale, GAM fluctuation is dominated by superrotational flow in the tropics, with the blocked flow present to a much lesser extent. The associated velocity potential anomaly has a weak dipole structure with centers over the Indian Ocean and the eastern Pacific. The implications of the above results on the total angular momentum balance of the earth-atmosphere system are also discussed.

Kang, In-Sik↗
NASA NTRS1994

The Uranian aurora and its relationship to the magnetosphere

About 32 h of Voyager Ultraviolet Spectrometer (UVS) observations of Uranus H2 band airglow emission (875 less than or equal to lambda less than or equal to 1115 A) have been analyzed using the singular value decomposition (SVD) approach to inversion, producing an intensity map showing aurora at both magnetic poles. An H Lyman alpha aurora may also be present but is difficult to separate from scattered solar and local interstellar medium components. SVD analysis of variance shows that the intensity estimate is significantly larger than the error estimate over both Uranographic poles and part of the equatorial region, fortuitously including both magnetic polar regions. The Goddard Space Flight Center Q(sub 3) magnetic field model correctly predicts that the aurora should be larger in area and emit more power at the weaker N magnetic pole than at the stronger S magnetic pole. However, the auroral emissions are quite localized in magnetic longitude and so do not form complete auroral ovals. The brightest auroral emission at each magnetic pole is confined to a range of approximately 90 deg of magnetic longitude centered on the magnetotail direction, at moderate magnetic L parameter (5 less than or equal to L less than or equal to 10), but some emission at each pole is distributed over a range of more than 180 deg of longitude. The magnetic longitudes of the aurora are completely inconsistent with the 'windshield wiper' effect for either ions or electrons, indicating that some other effect, such as rapid depletion of the population of precipitating particles of highly localized strong pitch-angle diffusion, may be acting to localize emission. The low apparent L of the precipitating particles indicates that their energies may be less than or equal to 10 keV. Hence magnetospheric convection is likely to be important, and thus particles exciting the aurora may not remain on constant L shells. The precipitating particles may be a relatively low-energy population at high L that is heated to aurora-exciting energy by adiabatic compression during convection to low L. We estimate that the total auroral power output at H Lyman alpha and shorter wavelengths is about 3 x 10(exp 9) to 7 x 10(exp 9) W, requiring about 10 times that much power for excitation.

Herbert, Floyd↗
NASA NTRS1994

Observed correlations between winter-mean tropospheric and stratospheric circulation anomalies

It is shown that interannual variability of the northern winter stratospheric flow in 1964-1993 was closely linked to large-scale circulation anomalies in the middle troposphere. Of the known tropospheric teleconnection patterns, the one having the strongest relation to the DJF (December-February) zonal-mean stratospheric flow was the North Atlantic Oscillation (NAO). Singular value decomposition between the 500 and 50-hPa geopotential heights produced a 500-hPa structure containing elements of the NAO pattern, but including an anomaly in eastern Siberia. During this time period, the correlation of NAO-related modes to the polar lower stratosphere exceeded that of the equatorial quasi-biennial oscillation.

Baldwin, Mark P.↗
NASA NTRS1994

Shortwave feedbacks and El Nino-Southern Oscillation: Forced ocean coupled ocean-atmosphere experiments

Changes in tropical sea surface temperature (SST) can produce changes in cloudiness that modify incoming solar shortwave (SW) radiation, which in turn affects SST. The effects of this negative feedback on Pacific interannual variability are examined in forced ocean model and hybrid coupled ocean-atmosphere model simulations. Two empirical schemes are used to model the large-scale, low-frequency response of surface SW to SST anomalies. The first scheme attempts to account for the nonlocal nature of the atmospheric response to SST based patterns of covariability analyzed through singular value decomposition. In the observations the primary coupled mode of variability is composed of a SW anomaly in the central Pacific that covaries with anomalous SST in the eastern Pacific. This is applied in the model as a nonlocal feedback. The second scheme examines the effects of a purely local feedback with a spatially varying coefficient of magnitude chosen similar to the first scheme. In almost all cases the second scheme behaved similarly to the first, presumably because the correlation scale of SST is large enough for El Nino-Southern Oscillation (ENSO) dynamics that there is little sensitivity to the local approximation in the SW feedback. In simulations forced by time series of observed wind stress the SW feedback induced very minor SST damping. Results for a simpified heat budget analysis showed that while the SW feedback increased the local heat flux damping on SST, it also induced a mean shallowing of the mixed layer. The resulting changes in both the local mean vertical temperature gradient and the zonal velocity response to the wind stress acted to oppose the local heat flux damping effects. When the observed SW anomalies were applied to forced simulations, the simulated SST anomalies were modified as expected, and agreement with observed SST improved. In coupled simulations the SW feedbacks had greater impact than in the case of specified stress. The main effects were to decrease the magnitude of the warm and cold SST anomalies in the central Pacific, while leaving the pattern and evolution of ENSO anomalies essentially unchanged elsewhere. The SW feedbacks thus produce a modest improvement of the model ENSO SST pattern compared with observations, although they tended to shorten the period of the model ENSO cycle. Overall the results suggest that large-scale SW feedbacks are of quantitative importance to simulating some aspects of the ENSO cycle but are not critical to the overall occurrence of the phenomenon.

Waliser, Duane E.↗
NASA NTRS1996

A Feasibility Study on a Parallel Mechanism for Examining the Space Shuttle Orbiter Payload Bay Radiators

The goal of the project was to develop the necessary analysis tools for a feasibility study of a cable suspended robot system for examining the space shuttle orbiter payload bay radiators These tools were developed to address design issues such as workspace size, tension requirements on the cable, the necessary accuracy and resolution requirements and the stiffness and movement requirements of the system. This report describes the mathematical models for studying the inverse kinematics, statics, and stiffness of the robot. Each model is described by a matrix. The manipulator Jacobian was also related to the stiffness matrix, which characterized the stiffness of the system. Analysis tools were then developed based on the singular value decomposition (SVD) of the corresponding matrices. It was demonstrated how the SVD can be used to quantify the robot's performance and to provide insight into different design issues.

Roberts, Rodney G.↗
NASA NTRS1998

Toward a More Robust Pruning Procedure for MLP Networks

Choosing a proper neural network architecture is a problem of great practical importance. Smaller models mean not only simpler designs but also lower variance for parameter estimation and network prediction. The widespread utilization of neural networks in modeling highlights an issue in human factors. The procedure of building neural models should find an appropriate level of model complexity in a more or less automatic fashion to make it less prone to human subjectivity. In this paper we present a Singular Value Decomposition based node elimination technique and enhanced implementation of the Optimal Brain Surgeon algorithm. Combining both methods creates a powerful pruning engine that can be used for tuning feedforward connectionist models. The performance of the proposed method is demonstrated by adjusting the structure of a multi-input multi-output model used to calibrate a six-component wind tunnel strain gage.

Stepniewski, Slawomir W.↗
NASA NTRS1999

An Assessment of the Impact of the 1997-98 El Nino on the Asian-Australian Monsoon

Using state-of-the-art satellite-gauge monthly rainfall estimate and optimally interpolated sea surface temperature (SST) data, we have assessed the 1997-98 AA-monsoon anomalies in terms of three basic causal factors: basin-scale SST, regional coupling, and internal variability. Singular Value Decomposition analyses of rainfall and SST are carried out globally over the entire tropics and regionally over the AA-monsoon domain. Contributions to monsoon rainfall predictability by various factors are evaluated from cumulative anomaly correlation with dominant regional SVD modes. Results reveal a dominant, large-scale monsoon-El Nino coupled mode with well-defined centers of action in the near-equatorial monsoon regions during the boreal summer and winter respectively. The observed 1997-98 AA-monsoon anomalies are found to be very complex with approximately 34% of the anomalies of the Asian (boreal) summer monsoon and 74% of the Australia (austral) monsoon attributable to basin-scale SST influence associated with El Nino. Regional coupled processes contribute an additional 19% and 10%, leaving about 47% and 16% due to internal dynamics for the boreal and austral monsoon respectively. For the boreal summer monsoon, it is noted that the highest monsoon predictability is not necessary associated with major El Nino events (e.g. 1997, 1982) but rather in non-El Nino years (e.g. 1980, 1988) when contributions from the regional coupled modes far exceed those from the basin-scale SST. The results suggest that in order to improve monsoon seasonal-to-interannual predictability, there is a need to exploit not only monsoon-El Nino relationship, but also intrinsic monsoon regional coupled processes.

Lau, K.-M.↗
NASA NTRS1999

Assessment of the 1997-1998 Asian Monsoon Anomalies

Using State-of-the-art satellite-gauge monthly rainfall estimate and optimally interpolated sea surface temperature (SST) data, we have assessed the 1997-98 Asian monsoon anomalies in terms of three basic causal factors: basin-scale SST, regional coupling, and internal variability. Singular Value Decomposition analysis of rainfall and SST are carried out globally over the entire tropics and regionally over the Asian monsoon domain. Contributions to monsoon rainfall predictability by various factors are evaluated from cumulative anomaly correlation with dominant regional SVD modes. Results reveal a dominant, large-scale monsoon-El Nino coupled mode with well-defined centers of action in the near-equatorial monsoon regions. it is noted that some subcontinental regions such as all-India, or arbitrarily chosen land regions over East Asia, while important socio-economically, are not near the centers of influence from El Nino, hence are not necessarily representative of the response of the entire monsoon region to El Nino. The observed 1997-98 Asian monsoon anomalies are found to be very complex with approximately 34% of the anomalies attributable to basin- scale SST influence associated with El Nino. Regional coupled processes contribute an additional 19%, leaving about 47% due to internal dynamics. Also noted is that the highest monsoon predictability is not necessary associated with major El Nino events (e.g. 1997, 1982) but rather in non-El Nino years (e.g. 1980, 1988) when contributions from the regional coupled modes far exceed those from the basin-scale SST. The results suggest that in order to improve monsoon seasonal-to-interannual predictability, there is a need to exploit not only monsoon-El Nino relationship, but also monsoon regional coupled processes and their modulation by long-term climate change.

Lau, William K.-M.↗
NASA NTRS1999

East Asian Summer Monsoon Rainfall: A Historical Perspective of the 1998 Flood over Yangtze River

One of the main factors that might have caused the disastrous flood in China during 1998 summer is long-term variations that include a trend indicating increasing monsoon rainfall over the Yangtze River Valley. China's 160-station monthly rainfall anomaly for the summers of 1955-98 is analyzed for exploring such long-term variations. Singular value decomposition (SVD) between the summer rainfall and the global sea surface temperature (SST) anomalies reveals that the rainfall over Yangtze River Valley is closely related to global and regional SST variabilities at both interannual and interdecadal timescales. SVD1 mode links the above normal rainfall condition in central China to an El Nino-like SSTA distribution, varying on interannual timescale modified by a trend during the period. SVD3 mode links positive rainfall anomaly in Yangtze River Valley to the warm SST anomaly in the subtropical western Pacific, varying on interannual timescales modified by interdecadal timescales. This link tends to be stronger when the Nino3 area becomes colder and the western subtropical Pacific becomes warmer. The 1998 summer is a transition season when the 1997/98 El Nino event was in its decaying phase, and the SST in the Nino3 area emerged below normal anomaly while the subtropical western Pacific SST above normal. Thus, the first and third SVD modes become dominant in 1998 summer, favoring more Asian summer monsoon rainfall over the Yangtze River Valley.

Weng, H.-Y.↗
NASA NTRS1999

How to Estimate Attitude from Vector Observations

The most robust estimators minimizing Wahba's loss function are Davenport's q method and the Singular Value Decomposition (SVD) method. The q method is faster than the SVD method with three or more measurements. The other algorithms are less robust since they solve the characteristic polynomial equation to find the maximum eigenvalue of Davenport's K matrix. They are only preferable when speed or processor power is an important consideration. Of these, Fast Optimal Attitude Matrix (FOAM) is the most robust and faster than the q method. Robustness is only an issue for measurements with widely differing accuracies, so the fastest algorithms, Quaternion ESTimator (QUEST), EStimator of the Optimal Quaternion (ESOQ), and ESOQ2, are well suited to star sensor applications.

Markley, F. Landis↗
NASA NTRS2000

New Developments in Quaternion Estimation from Vector Observations

This paper contains a critical comparison of estimators minimizing Wahba's loss function. Some new results are presented for the QUaternion ESTimator (QUEST) and EStimators of the Optimal Quaternion (ESOQ and ESOQ2) to avoid the computational burden of sequential rotations in these algorithms. None of these methods is as robust in principle as Davenport's q method or the Singular Value Decomposition (SVD) method, which are significantly slower. Robustness is only an issue for measurements with widely differing accuracies, so the fastest estimators, the modified ESOQ and ESOQ2, are well suited to sensors that track multiple stars with comparable accuracies. More robust forms of ESOQ and ESOQ2 are developed that are intermediate in speed.

Markley, F. Landis↗
NASA NTRS1999

A Method to Solve Interior and Exterior Camera Calibration Parameters for Image Resection

An iterative method is presented to solve the internal and external camera calibration parameters, given model target points and their images from one or more camera locations. The direct linear transform formulation was used to obtain a guess for the iterative method, and herein lies one of the strengths of the present method. In all test cases, the method converged to the correct solution. In general, an overdetermined system of nonlinear equations is solved in the least-squares sense. The iterative method presented is based on Newton-Raphson for solving systems of nonlinear algebraic equations. The Jacobian is analytically derived and the pseudo-inverse of the Jacobian is obtained by singular value decomposition.

Samtaney, Ravi↗
NASA NTRS2001

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

Brenner, Marty↗
NASA NTRS1995

Model-Based Obstacle Detention From Image Sequences

This paper proposes a method for detecting obstacles on a runway from monocular image sequences. The surface of the runway is modeled as a plane and the model flow field corresponding to the runway is described by 8 coefficients. The set of 8 coefficients describing the initial model flow field is given by the data from Inertial Navigation System (INS). The uncertainties of this initial model flow field are estimated and used to obtain the accurate model flow field. The residual flow field after warping images by the accurate model flow field is computed by solving over determined gradient-based optical flow equations using a singular value decomposition (SVD). This SVD gives us a new insight of the uncertainties inherent in the optical flow computation. Those pixels with large residual flow vectors are considered as obstacles. Experimental results for two real image sequences are presented.

Sull, Sanghoon↗
NASA NTRS2004

Trend and Variability of China Precipitation in Spring and Summer: Linkage to Sea Surface Temperatures

Observational records in the past 50 years show an upward trend of boreal-summer precipitation over central eastern China and a downward trend over northern China. During boreal spring, the trend is upward over southeastern China and downward over central eastern China. This study explores the forcing mechanism of these trends in association with the global sea-surface temperature (SST) variations on the interannual and inter-decadal timescales. Results based on Singular Value Decomposition analyses (SVD) show that the interannual variability of China precipitation in boreal spring and summer can be well defined by two centers of actions for each season, which are co-varying with two interannual modes of SSTs. The first SVD modes of precipitation in spring and summer, which are centered in southeastern China and northern China, respectively, are linked to an ENSO-like mode of SSTs. The second SVD modes of precipitation in both seasons are confined to central eastern China, and are primarily linked to SST variations over the warm pool and Indian Ocean. Features of the anomalous 850-hPa winds and 700-Wa geopotential height corresponding to these modes support a physical mechanism that explains the causal links between the modal variations of precipitation and SSTs. On the decadal and longer timescale, similar causal links are found between the same modes of precipitation and SSTs, except for the case of springtime precipitation over central eastern China. For this case, while the interannual mode of precipitation is positively correlated with the interannual variations of SSTs over the warm pool and Indian Ocean; the inter-decadal mode is negatively correlated with a different SST mode, the North Pacific mode. The later is responsible for the observed downward trend of springtime precipitation over central eastern China. For all other cases, both the interannual and inter-decadal variations of precipitation can be explained by the same mode of SSTs. The upward trend of springtime precipitation over southeastern China and downward trend of summertime precipitation over northern China are attributable to the warming trend of the ENSO-like mode. The recent frequent summertime floods over central eastern China are linked to the warming trend of SSTs over the warm pool and Indian Ocean.

Yang, Fanglin↗
NASA NTRS2001

Dynamic modeling of gene expression data

We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.

NASA Discipline Plant Biology↗
NASA NTRS2005

Constraining Oceanic Sources and Sinks of CO2 by Inverse Modeling: A First Step Toward Assimilation of In Situ and Remote Data

The primary goal of this collaborative project, lead by Nicholas Gruber at UCLA, is to better quantify the air-sea fluxes of pre-industrial and anthropogenic carbon dioxide CO2 for the global ocean with a newly developed inverse method. The method involves using ocean general circulation models (OGCMs) to characterize the subsurface distribution of tracers injected for different regions of the ocean surface. By linearly combining a series of these basis (or Greens) functions, one should be able to recreate any arbitrary ocean tracer field. In our case, we are using the global database of ocean dissolved inorganic carbon (DIC) from the WOCE/JGOFS global CO2 survey from the 1990s. The observed DIC field has been partitioned into pre-industrial and anthropogenic components using the empirical C* technique. We then solve for an optimal combination of the regional basis functions that best match the two sets observations in a least-squares sense with singular value decomposition. This in turn provides solutions for the regional air-sea CO2 fluxes (pre-industrial and anthropogenic) that are independent of more traditional estimates derived from surface water disequilibria in the partial pressure of CO2 and wind speed gas exchange parameterizations. We are apply the method to a suite of nine different OGCMs to test the robustness of the derived surface fluxes fields to differences in ocean circulation. Together with a collegue Keith Lindsay at NCAR, S. Doney's role in this project was to create the appropriate steady-state and temporally evolving basis functions from the NCAR CSM-1 ocean circulation model. Because of a slow start across the project in defining a common set of experimental protocols, we requested and were given a one year, no cost extension. Both the steady-state and temporally evolving basis functions were delivered to the UCLA group for further analysis. Additional information is included in the original extended abstract.

Doney, Scott↗
NASA NTRS2005

SVD analysis of Aura TES spectral residuals

Singular Value Decomposition (SVD) analysis is both a powerful diagnostic tool and an effective method of noise filtering. We present the results of an SVD analysis of an ensemble of spectral residuals acquired in September 2004 from a 16-orbit Aura Tropospheric Emission Spectrometer (TES) Global Survey and compare them to alternative methods such as zonal averages. In particular, the technique highlights issues such as the orbital variation of instrument response and incompletely modeled effects of surface emissivity and atmospheric composition.

spectra↗