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At least 109 records · Page 6

Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Latent Heating Profiles

In this study, satellite passive microwave sensor observations from the TRMM Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1-QR) in regions of precipitation. The TMI heating algorithm (TRAIN) is calibrated, or "trained" using relatively accurate estimates of heating based upon spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based upon a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically-integrated condensation and surface precipitation. Estimates of Q1-QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1-QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structure with sharper and more intense heating peaks than the rawinsonde estimates. 2

Grecu, Mircea↗

TPSAS-NF1676L-10863-DND

One important aspect of successful climate monitoring is satellite calibration. There is at least a 25-year of operational geostationary (GEO) record available for climate studies, if properly calibrated. The Global Space-based Inter-Calibration System (GSICS) project is another effort to provide the climate community consistent calibration across multiple platforms. Also, the Clouds and the Earth's Radiant Energy System (CERES) project, provides consistent GEO retrieved cloud properties and derived broadband fluxes across multiple platforms. This year GSICS is focusing on geostationary visible channel calibration. The GSICS strategy is to use multiple approaches, such as cross-calibrating the GEO radiances against MODIS as a reference, deep convective clouds as bright stable targets, deserts, sun-glint, stars, moon and other model based calibration methods. Each of these methods is independent of each other and can assess the stability of the GEO visible instrument with differing uncertainties. This study focuses on the inter-calibration of the GEO radiances against MODIS as a reference by using collocated, and coincident ray-matched radiances. The advantage of the ray-matching technique is that it provides a full dynamic range of radiances to check the linearity of the GEO visible instrument. This presentation will focus on the technique, some error analysis, comparisons with other methods, and an approach to inter-calibrate historical GEOs before MODIS.

D R Doelling↗

Remote Sensing of Multiple Cloud Layer Heights Using Multi-Angular Measurements

Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASAs airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross-correlations between this set and co-located sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allow retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSPs CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC(exp. 4)RS) campaign. RSP retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 nm and 1880 nm and their combination. The 1880-nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption.

Sinclair, Kenneth↗

A Classification of Ice Crystal Habits Using Combined Lidar and Scanning Polarimeter Observations during the SEAC4RS Campaign

Using collocated NASA Cloud Physics Lidar (CPL) and Research Scanning Polarimeter (RSP) data from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign, a new observational-based method was developed which uses a K-means clustering technique to classify ice crystal habit types into seven categories: column, plates, rosettes, spheroids, and three different type of irregulars. Intercompared with the collocated SPEC, Inc., Cloud Particle Imager (CPI) data, the frequency of the detected ice crystal habits from the proposed method presented in the study agrees within 5% with the CPI-reported values for columns, irregulars, rosettes, and spheroids, with more disagreement for plates. This study suggests that a detailed ice crystal habit retrieval could be applied to combined space-based lidar and polarimeter observations such as CALIPSO and POLDER in addition to future missions such as the Aerosols, Clouds, Convection, and Precipitation (A-CCP).

Natalie Midzak↗

Improving the geological interpretation of magnetic and gravity satellite anomalies

Quantitative analysis of the geologic component of observed satellite magnetic and gravity fields requires accurate isolation of the geologic component of the observations, theoretically sound and viable inversion techniques, and integration of collateral, constraining geologic and geophysical data. A number of significant contributions were made which make quantitative analysis more accurate. These include procedures for: screening and processing orbital data for lithospheric signals based on signal repeatability and wavelength analysis; producing accurate gridded anomaly values at constant elevations from the orbital data by three-dimensional least squares collocation; increasing the stability of equivalent point source inversion and criteria for the selection of the optimum damping parameter; enhancing inversion techniques through an iterative procedure based on the superposition theorem of potential fields; and modeling efficiently regional-scale lithospheric sources of satellite magnetic anomalies. In addition, these techniques were utilized to investigate regional anomaly sources of North and South America and India and to provide constraints to continental reconstruction. Since the inception of this research study, eleven papers were presented with associated published abstracts, three theses were completed, four papers were published or accepted for publication, and an additional manuscript was submitted for publication.

Hinze, William J.↗

A spectral element method for fluid dynamics - Laminar flow in a channel expansion

A spectral element method that combines the generality of the finite element method with the accuracy of spectral techniques is proposed for the numerical solution of the incompressible Navier-Stokes equations. In the spectral element discretization, the computational domain is broken into a series of elements, and the velocity in each element is represented as a high-order Lagrangian interpolant through Chebyshev collocation points. The hyperbolic piece of the governing equations is then treated with an explicit collocation scheme, while the pressure and viscous contributions are treated implicitly with a projection operator derived from a variational principle. The implementation of the technique is demonstrated on a one-dimensional inflow-outflow advection-diffusion equation, and the method is then applied to laminar two-dimensional (separated) flow in a channel expansion. Comparisons are made with experiment and previous numerical work.

Patera, A. T.↗

Analysis of opposed jet hydrogen-air counter flow diffusion flame

A computational simulation of the opposed-jet diffusion flame is performed to study its structure and extinction limits. The present analysis concentrates on the nitrogen-diluted hydrogen-air diffusion flame, which provides the basic information for many vehicle designs such as the aerospace plane for which hydrogen is a candidate as the fuel. The computer program uses the time-marching technique to solve the energy and species equations coupled with the momentum equation solved by the collocation method. The procedure is implemented in two stages. In the first stage, a one-step forward overal chemical reaction is chosen with the gas phase chemical reaction rate determined by comparison with experimental data. In the second stage, a complete chemical reaction mechanism is introduced with detailed thermodynamic and transport property calculations. Comparison between experimental extinction data and theoretical predictions is discussed. The effects of thermal diffusion as well as Lewis number and Prandtl number variations on the diffusion flame are also presented.

Ho, Y. H.↗

Towards a Marine Stratus Climatology on Drizzle Occurrence from CALIPSO

Marine stratus are a predominant feature of our planet with the annual mean coverage exceeding 20%. They strongly reflect sunlight, yet exert only a modest effect on outgoing infrared radiation, providing a significant net cooling to the Earth’s radiative balance. Their formation is coupled to boundary layer circulations that are driven, in part, by cloud top radiative cooling and evaporative cooling from precipitation in downdrafts. Understanding how these cloud systems evolve as the climate changes is a key question that requires additional information on their lifecycle and microphysical properties to accurately represent their behavior in global circulation models. From a large-scale perspective, insight into the microphysical properties of marine stratus at cloud top can be realized through estimates of the effective radius (Re) of the droplet size distributions derived from MODIS observations. Estimates on the occurrence of rain/drizzle are available from CloudSat. Together these observations indicate that precipitation frequently occurs in clouds with higher cloud top Re. This relationship is consistent with the well documented shift in cloud top droplet size distributions towards fewer, yet larger droplets prior the onset of precipitation. Here we report on a new and complementary set observations from the CALIPSO mission. The approach derives an extinction-to-backscatter ratio (Sc, also known as the cloud lidar ratio) using an established relationship that depends on observations of the lidar attenuated backscatter and volume depolarization ratio within the cloud. Because Sc is strongly and inversely related to Re, a change in the derived Sc from higher to lower values corresponds to a change in the droplet size distribution as seen by MODIS. This change in the lidar signals at cloud top clearly identifies clouds that are capable of precipitation. The presentation provides a brief overview of the approach for deriving Sc and compares CALIOP-derived Sc with observations from other techniques. CALIOP classifications of drizzling clouds, based on the retrieved values Sc, are compared to independent, collocated assessments of drizzle occurrence reported in the standard CloudSat data products. Regional and seasonal comparisons highlight the strengths and weaknesses of the two sensors. A machine learning approach that combines information from both CALIOP and CloudSat showcases possible improvements in the global identification of scenes likely to contain rain-bearing clouds.

CALIPSO↗

Small deflection of a class of clamped thin plates using collocation

Equations are given for the optimization of a class of two-and three-dimensional structures. The application of existing analytical techniques to the response of thin clamped plates is described. The ratios of deflections to plate thickness are given for uniform transverse loads as well as for uniform plus linearly varying transverse loads. Deflections are presented at angular increments of 5 degrees and at radial increments of 0.1 of the radius.

Worley, W. J.↗

Flexible system model reduction and control system design based upon actuator and sensor influence functions

A model reduction technique based on aggregation with respect to sensor and actuator influence functions rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the reduced-order plant model and the neglected plant model are derived. For the special case of collocated actuators and sensors, these expressions lead to the derivation of constraints on the controller gains that are, given the validity of the perturbation technique, sufficient to guarantee the stability of the closed-loop system. A case study demonstrates the derivation of stabilizing controllers based on the present technique. The use of control and observation synthesis in modifying the dimension of the reduced-order plant model is also discussed. A numerical example is provided for illustration.

Yam, Yeung↗

Plates and shells containing a surface crack under general loading conditions

The severity of the underlying assumptions of the line-spring model (LSM) are such that verification with three-dimensional solutions is necessary. Such comparisons show that the model is quite accurate, and therefore, its use in extensive parameter studies is justified. Investigations into the endpoint behavior of the line-spring model have led to important conclusions about the ability of the model to predict stresses in front of the crack tip. An important application of the LSM was to solve the contact plate bending problem. Here the flexibility of the model to allow for any crack shape is exploited. The use of displacement quantities as unknowns in the formulation of the problem leads to strongly singular integral equations, rather than singular integral equations which result from using displacement derivatives. The collocation method of solving the integral equations was found to be better and more convenient than the quadrature technique. Orthogonal polynomials should be used as fitting functions when using the LSM as opposed to simpler functions such as power series.

Joseph, Paul F.↗

Experimental studies of adaptive structures for precision performance

An experimental study was made of the adaptive structure concept. Experimental data were obtained for a three-longeron, thirteen-bay truss-type test structure. This test structure can be softly suspended as well as rigidly clamped at the central bay. The load-carrying active member consists of a stack of concentric piezoelectric wafers, an eddy current displacement sensor, and a strain gage force sensor. A bridge (or compound) feedback technique developed in communication engineering is applied to the problem of active damping augmentation in adaptive structures. Using collocated force and velocity feedback around the active member, a desired output mechanical impedance can be implemented to maximize energy absorption by the active members. In addition, large gains can be implemented to linearize the active member's nonlinear behavior. Good agreements with linear finite element analysis was found for both static and dynamic structural responses. An 11 percent damping in the first bending mode was demonstrated in the closed-loop damping experiment.

Chen, G.-S.↗

A dual reciprocal boundary element formulation for viscous flows

The advantages inherent in the boundary element method (BEM) for potential flows are exploited to solve viscous flow problems. The trick is the introduction of a so-called dual reciprocal technique in which the convective terms are represented by a global function whose unknown coefficients are determined by collocation. The approach, which is necessarily iterative, converts the governing partial differential equations into integral equations via the distribution of fictitious sources or dipoles of unknown strength on the boundary. These integral equations consist of two parts. The first is a boundary integral term, whose kernel is the unknown strength of the fictitious sources and the fundamental solution of a convection-free flow problem. The second part is a domain integral term whose kernel is the convective portion of the governing PDEs. The domain integration can be transformed to the boundary by using the dual reciprocal (DR) concept. The resulting formulation is a pure boundary integral computational process.

Lafe, Olu↗

Analysis of Combustion Instability in Liquid Fuel Rocket Motors

The development of a technique to be used in the solution of nonlinear velocity-sensitive combustion instability problems is described. The orthogonal collocation method was investigated. It found that the results are heavily dependent on the location of the collocation points and characteristics of the equations, so the method was rejected as unreliabile. The Galerkin method, which has proved to be very successful in analysis of the pressure sensitive combustion instability was found to work very well. It was found that the pressure wave forms exhibit a strong second harmonic distortion and a variety of behaviors are possible depending on the nature of the combustion process and the parametric values involved. A one-dimensional model provides further insight into the problem by allowing a comparison of Galerkin solutions with more exact finite-difference computations.

Wong, K. W.↗

The eigenvalue spectrum of the Rayleigh equation for a plane shear layer

The eigenvalue spectrum of the Rayleigh equation is examined using three different solution techniques. In particular, a simple second-order finite difference scheme and two spectral methods, the Chebyshev tau and Chebyshev collocation methods, are used to discretize the equation. All of the approximation methods are shown to be capable of predicting the discrete spectrum as well as the continuous spectrum associated with the critical point singularity for the Rayleigh equation. The global eigenvalue methods considered here provide an efficient way of obtaining either an approximation to the complete eigenvalue spectrum or initial guesses for a local shooting procedure for the discrete part of the spectrum.

Liou, William W.-W.↗

Use of TEMPO as a Proxy for Hyperspectral Geostationary Ocean Color Measurements from the GeoXO OCX Instrument: Harnessing Machine Learning and Principal Component Techniques for Atmospheric and Glint Correction

Retrievals of ocean color from space are important for better understanding the ocean ecosystem. The launch of atmospheric geostationary hyperspectral sensors such as TEMPO, provides a unique opportunity to examine the diurnal variability in ocean ecology. While TEMPO does not have as high spatial resolution or full spectral coverage as planned coastal ocean sensors such as the Geosynchronous Littoral Imaging and Monitoring Radiometer (GLIMR) or GeoXO Ocean Color instrument (OCX), its hourly measurements provide coverage of regions such as Lake Erie and the Gulf of Mexico at spatial scales of approximately 5 km. These data can be useful for testing new algorithms. We will apply our newly developed machine learning based atmospheric correction approach for ocean color retrievals to TEMPO data. Our approach begins by decomposing measured radiances from hyperspectral sensors into spectral features that describe the scattering and absorption of the atmosphere as well as the underlying surface reflectance. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from collocated MODIS/VIIRS physically-based retrievals. This machine learning approach does not rely on radiative transfer modeling, and the use of MODIS/VIIRS data for training accounts for possible calibration b in hyperspectral data. Previously, we applied our approach using blue and UV wavelengths with the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can estimate ocean color properties in less-than-ideal conditions such as lightly to moderately clouded conditions as well as sun glint and thus improve the spatial coverage of ocean color measurements. TEMPO provides an opportunity to improve on this approach since it will provide collocated measurements at green and red wavelengths that were not available from OMI and TROPOMI and are important particularly for coastal waters. Additionally, our technique can be applied early in the mission and has potential to demonstrate the value of near real time ocean color products that are important for monitoring of harmful algae blooms and other oceanic phenomena.

Zachary Fasnacht↗

Numerical derivative techniques for trajectory optimization

The adoption of robust numerical optimization techniques in trajectory simulation programs has resulted in powerful design and analysis tools. These trajectory simulation/optimization programs are widely used, and a representative list includes the GTS system, the POST program, and newer collocation methods such as OTIS and FONPAC. All of these programs rely on optimization algorithms which require objective function and constraint gradient data during the iteration process. However, most trajectory optimization problems lack simple analytical expressions for these derivatives. In the general case a function evaluation involves integrating aerodynamic, propulsive, and gravity forces over multiple trajectory phases with complex control models. With the newer collocation methods, the integration is replaced by defect constraints and cubic approximations for the state. While analytic gradient expressions can sometimes be derived for trajectory optimization problems, the derivation is cumbersome, time consuming, and prone to mistakes. Fortunately, an alternate method exists for the gradient evaluation, namely finite difference approximations. In this paper some finite difference gradient techniques developed for use with the GTS system are presented. These techniques include methods for computing first and second partial derivatives of single and multiple sets of functions. A key feature of these methods is an error control mechanism which automatically adjusts the perturbation size to obtain accurate derivative values.

Hallman, Wayne P.↗

An adaptive identification and control scheme for large space structures

A unified identification and control scheme capable of achieving space at form performance objectives under nominal or failure conditions is described. Preliminary results are also presented, showing that the methodology offers much promise for effective robust control of large space structures. The control method is a multivariable, adaptive, output predictive controller called Model Predictive Control (MPC). MPC uses a state space model and input reference trajectories of set or tracking points to adaptively generate optimum commands. For a fixed model, MPC processes commands with great efficiency, and is also highly robust. A key feature of MPC is its ability to control either nonminimum phase or open loop unstable systems. As an output controller, MPC does not explicitly require full state feedback, as do most multivariable (e.g., Linear Quadratic) methods. Its features are very useful in LSS operations, as they allow non-collocated actuators and sensors. The identification scheme is based on canonical variate analysis (CVA) of input and output data. The CVA technique is particularly suited for the measurement and identification of structural dynamic processes - that is, unsteady transient or dynamically interacting processes such as between aerodynamics and structural deformation - from short, noisy data. CVA is structured so that the identification can be done in real or near real time, using computationally stable algorithms. Modeling LSS dynamics in 1-g laboratories has always been a major impediment not only to understanding their behavior in orbit, but also to controlling it. In cases where the theoretical model is not confirmed, current methods provide few clues concerning additional dynamical relationships that are not included in the theoretical models. CVA needs no a priori model data, or structure; all statistically significant dynamical states are determined using natural, entropy-based methods. Heretofore, a major limitation in applying adaptive controllers to LSS problems has been the requirement for accurate models. We feel that MPC coupled with the CVA identification scheme will resolve this limitation. The results are based on research performed under an SBIR grant, administered by the Air Force Office of Scientific Research.

Carroll, J. V.↗