Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ASSIMILATION”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Use of four-dimensional data assimilation by Newtonian relaxation and latent-heat forcing to improve a mesoscale-model precipitation forecast - A case study

The Penn State/NCAR mesoscale model was used to study special static-initialization (SI) and dynamic-initialization (DI) techniques designed to improve short-range quantitative precipitation forecasts (QPFs), as applied to the heavy convective rainfall that occurred in Texas, Oklahoma, and Kansas during the May 9-10, 1979 SESAMY IV study period. In the DI procedure, two types of four-dimensional data assimilation (FDDA) procedures were used to incorporate data during a 12-h preforecast period, one using the Newtonian relaxation, the other using latent-heat forcing. It was found that combined use of either the preforecast or in-forecast latent-heat forcing with the Newtonian relaxation produced an improved forecast (relative to a conventional forecast procedure) of rainfall intensity compared to the use of the Newtonian relaxation alone. The use of the experimental SI with prescribed latent heating during the first forecast hour produced greatly improved rainfall rates.

Wang, Wei↗
NASA NTRS1990

Continuous assimilation of Geosat altimetric sea level observations into a numerical synoptic ocean model of the California Current

The Geosat altimetric sea level observations for the period from January to December 1987 were continuously assimilated into a realistic wind-driven numerical synoptic ocean model of the California Current in order to evaluate the effectiveness of using a realistic synoptic ocean model for interpolating (dynamically) real altimetric sea level observations onto a regular grid. The accuracy of dynamical interpolation was tested by comparing the gridded sea level residuals to ones estimated from in situ observations (by expendable bathythermographs) collected in the California Current region during the same period. The comparison yielded nearly exact agreement at low frequency (i.e., semiannual cycle), but less agreement on month-to-month time scales of variability, possibly due to the unfiltered nature of the in situ estimates.

White, Warren B.↗
NASA NTRS1990

Coupling of Coastal Zone Color Scanner data to a physical-biological model of the southeastern U.S. continental shelf ecosystem. I - CZCS data description and Lagrangian particle tracing experiments. II - An Eulerian model. III - Nutrient and phytoplankton fluxes and CZCS data assimilation

Surface phytoplankton biomass of the southeastern U.S. continental shelf area is discussed based on coastal zone color scanner (CZCS) images obtained in April 1980. Data of chlorophyll distributions are analyzed in conjunction with concurrent flow and temperature fields. Lagrangian particle tracing experiments show that the particles move consistently with the evolution of the chlorophyll patterns. A four-component physical-biological model for a horizontal plane at a nominal depth of 17 m is presented. Model simulations using various physical-biological dynamics and boundary conditions show that the variability of chlorophyll distributions is controlled by horizontal advection. Phytoplankton and nutrient fluxes, calculated using the model, show considerable variability with time. The chlorophyll distributions obtained from the CZCS images are assimilated into the model to improve the phytoplankton flux estimates.

Ishizaka, Joji↗
NASA NTRS1991

Global heating distributions for January 1979 calculated from GLA assimilated and simulated model-based datasets

This study surveys the large-scale distribution of heating for January 1979 obtained from five sources of information. Through intercomparison of these distributions, with emphasis on satellite-derived information, an investigation is conducted into the global distribution of atmospheric heating and the impact of observations on the diagnostic estimates of heating derived from assimilated datasets. The results indicate a substantial impact of satellite information on diagnostic estimates of heating in regions where there is a scarcity of conventional observations. The addition of satellite data provides information on the atmosphere's temperature and wind structure that is important for estimation of the global distribution of heating and energy exchange.

Schaack, Todd K.↗
NASA NTRS1991

Simplification of the Kalman filter for meteorological data assimilation

The paper proposes a new statistical method of data assimilation that is based on a simplification of the Kalman filter equations. The forecast error covariance evolution is approximated simply by advecting the mass-error covariance field, deriving the remaining covariances geostrophically, and accounting for external model-error forcing only at the end of each forecast cycle. This greatly reduces the cost of computation of the forecast error covariance. In simulations with a linear, one-dimensional shallow-water model and data generated artificially, the performance of the simplified filter is compared with that of the Kalman filter and the optimal interpolation (OI) method. The simplified filter produces analyses that are nearly optimal, and represents a significant improvement over OI.

Dee, Dick P.↗
NASA NTRS1991

Exploration of relationships between low-Ti and high-Ti pristine lunar glasses using an armalcolite assimilation model

The pristine glasses of Delano are the most primitive lunar basaltic magma compositions discovered to date. They are grouped into two (and possibly three) arrays: a low-alumina array and a high alumina array. These glasses are very olivine normative and are multiply saturated at pressures of approximately 20 kbar, implying a depth of origin of 400 to 500 km in the Moon. Thus, these glasses appear to be the best candidates for primitive partial melts of the upper lunar mantle. One of the most perplexing characteristics of the pristine glasses is a positive correlation between Ni and SiO2 within each array. This is contrary to the terrestrial experience, where Ni is observed to positively correlate with MgO and negatively correlate with SiO2. These systematics are believed to be due to the depletion of Ni by olivine fractionation. The difference between the lunar and terrestrial Ni vs. SiO2 trends may be partially ascribed to the Ti-rich component. In the case of the pristine glasses, SiO2 increases not because of olivine fractionation, but because they contain less of the high-Ti component. An attempt was made to model this variation in Ni and SiO2 with a simple assimilation-fractional crystallization (AFC) model. Silica and Ni both decreased dramatically as the AFC process proceeded. Only 15 to 20 percent AFC was necessary to produce the observed variation, and the SiO2 vs. Ni variation was modeled quite well. The D(Ni) for olivine/liquid in this model was taken to be 10 and the olivine was assumed to be Fe sub 80. However, the results of this model for Ti and Mg were less than satisfactory. It seemed difficult to achieve the high TiO2 contents of some glasses (16 to 17 wt. percent) by this method. Continual addition of ilmenite by AFC could indeed raise the titania concentrations to the necessary levels, but only by enriching the magma in FeO and greatly depleting the magma in MgO. An attempt was made to circumvent this problem by using armalcolite, (Fe, Mg)Ti2O5, in the AFC model, and the results are presented.

Jones, John H.↗
NASA NTRS1991

A Variational Assimilation Method for Satellite and Conventional Data: Model 2 (version 1)

The Model II variational data assimilation model is the second of the four variational models designed to blend diverse meteorological data into a dynamically constrained data set. Model II differs from Model I in that it includes the thermodynamic equation as the fifth dynamical constraint. Thus, Model II includes all five of the primative equations that govern atmospheric flow for a dry atmosphere.

Achtemeier, Gary L.↗
NASA NTRS1990

Global analyses of water vapor, cloud and precipitation derived from a diagnostic assimilation of SSM/I geophysical retrievals

An analytical approach is described for diagnostically assimilating moisture data from Special Sensor Microwave Imager (SSM/I) into a global analysis of water vapor, cloud content, and precipitation. In this method, 3D fields of wind and temperature values taken from ECMWF gridded analysis are used to drive moisture conservation equations with parameterized microphysical treatment of vapor, liquid, and ice; the evolving field of water vapor is periodically updated or constrained by SSM/I retrievals of precipitable water. Initial results indicate that this diagnostic model can produce realistic large-scale fields of cloud and precipitation. The resulting water vapor analyses agree well with SSM/I and have an additional advantage of being synoptic.

Robertson, Franklin R.↗
NASA NTRS1992

The minor stratospheric warming of January 1989 - Results from STRATAN, a stratospheric-tropospheric data assimilation system

Using a stratospheric-tropospheric data assimilation system, referred to as STRATAN, a minor sudden stratospheric warming that occurred in January 1989 is investigated. The event had a maximum influence on the stratospheric circulation near 2 hPa. The zonal mean circulation reversed briefly in the polar region as the temperature increased 34 K in 3 days. The cause of the warming is shown to be the rapid development and subsequent movement of a warm anomaly, which initially developed in the midlatitudes. The development of the warm anomaly is caused by adiabatic descent, and the dissipation by radiative cooling. A brief comparison with the NMC analysis and temperature sounding data is also presented.

Steenrod, Stephen D.↗
NASA NTRS1992

Validation and assimilation of Seasat altimeter wave heights using the WAM wave model

The third-generation wave model, WAM, is presently used to investigate the mutual consistency of the Seasat global data sets of scatterometer winds and altimeter wave heights for the complete Seasat period. While modeled and observed wave heights are in reasonable agreement on the global average, regional differences can be great and on occasion exceed 40 percent. These errors are primarily attributable to forcing wind field deficiencies; the friction velocities of the Goddard Laboratory for Atmospheres are found to be significantly underestimated in the high-wind belt of the Southern Hemisphere. A wave data assimilation scheme is presented in which the wave field is updated without change to the forcing wind field.

Bauer, Eva↗
NASA NTRS1992

Assimilation of ERBE data with a nonlinear programming technique to improve cloud-cover diagnosis

A method is developed to assimilate satellite data for the purpose of improving the diagnosis of fractional cloud cover within a numerical weather prediction model. The method makes use of a nonlinear programming technique to find a set of parameters for the cloud diagnosis that minimizes the difference between the observed and model-produced outgoing longwave radiation (OLR). The algorithm and theoretical basis of the method are presented. The method has been applied in two forecast experiments using a numerical weather prediction model. The results from a winter case demonstrate that the root-mean-square (rms) difference between the observed and forecasted OLR can be reduced by 50 percent when the optimized cloud diagnosis is used, with the remaining rms difference within the background noise.

Wu, Xiangqian↗
NASA NTRS1991

Assimilation of altimeter topography into oceanic models

The primary goals of the authors are to build an intuition for assimilation techniques and to investigate the impact of variable altimeter topography on simple or complex oceanic models. In particular, applying various techniques and sensitivity studies to model and data constraints plays a key role. We are starting to use quasi-geostrophic, semigeostrophic, and primitive-equation (PE) models and to test the schemes in regions of interest to the World Ocean Circulation Experiment (WOCE), as well as in the northeast Atlantic and the Mediterranean. The impact of scatterometer wind forcing on the results is also investigated. The use of Geosat, European Remote Sensing satellite (ERS-1), and TOPEX/POSEIDON altimetry data is crucial in fine tuning the models and schemes to the selected areas of interest.

Demey, Pierre↗
NASA NTRS1993

Production of long-term global water vapor and liquid water data set using ultra-fast methods to assimilate multi-satellite and radiosonde observations

During the next decade, many programs and experiments under the Global Energy and Water Cycle Experiment (GEWEX) will utilize present day and future data sets to improve our understanding of the role of moisture in climate, and its interaction with other variables such as clouds and radiation. An important element of GEWEX will be the GEWEX Water Vapor Project (GVaP), which will eventually initiate a routine, real-time assimilation of the highest quality, global water vapor data sets including information gained from future data collection systems, both ground and space based. The comprehensive global water vapor data set being produced by METSAT Inc. uses a combination of ground-based radiosonde data, and infrared and microwave satellite retrievals. This data is needed to provide the desired foundation from which future GEWEX-related research, such as GVaP, can build. The first year of this project was designed to use a combination of the best available atmospheric moisture data including: radiosonde (balloon/acft/rocket), HIRS/MSU (TOVS) retrievals, and SSM/I retrievals, to produce a one-year, global, high resolution data set of integrated column water vapor (precipitable water) with a horizontal resolution of 1 degree, and a temporal resolution of one day. The time period of this pilot product was to be det3ermined by the availability of all the input data sets. January 1988 through December 1988 were selected. In addition, a sample of vertically integrated liquid water content (LWC) was to be produced with the same temporal and spatial parameters. This sample was to be produced over ocean areas only. Three main steps are followed to produce a merged water vapor and liquid water product. Input data from Radiosondes, TOVS, and SSMI/I is quality checked in steps one and two. Processing is done in step two to generate individual total column water vapor and liquid water data sets. The third step, and final processing task, involves merging the individual output products to produce the integrated water vapor product. A final quality control is applied to the merged data sets.

Vonderhaar, T. H.↗
NASA NTRS1994

Technical report series on global modeling and data assimilation. Volume 1: Documentation of the Goddard Earth Observing System (GEOS) General Circulation Model, version 1

This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.

Suarez, Max J.↗
NASA NTRS1995

Technical report series on global modeling and data assimilation. Volume 5: Documentation of the AIRES/GEOS dynamical core, version 2

A detailed description of the numerical formulation of Version 2 of the ARIES/GEOS 'dynamical core' is presented. This code is a nearly 'plug-compatible' dynamics for use in atmospheric general circulation models (GCMs). It is a finite difference model on a staggered latitude-longitude C-grid. It uses second-order differences for all terms except the advection of vorticity by the rotation part of the flow, which is done at fourth-order accuracy. This dynamical core is currently being used in the climate (ARIES) and data assimilation (GEOS) GCMs at Goddard.

Suarez, Max J.↗
NASA NTRS1994

Advanced data assimilation in strongly nonlinear dynamical systems

Advanced data assimilation methods are applied to simple but highly nonlinear problems. The dynamical systems studied here are the stochastically forced double well and the Lorenz model. In both systems, linear approximation of the dynamics about the critical points near which regime transitions occur is not always sufficient to track their occurrence or nonoccurrence. Straightforward application of the extended Kalman filter yields mixed results. The ability of the extended Kalman filter to track transitions of the double-well system from one stable critical point to the other depends on the frequency and accuracy of the observations relative to the mean-square amplitude of the stochastic forcing. The ability of the filter to track the chaotic trajectories of the Lorenz model is limited to short times, as is the ability of strong-constraint variational methods. Examples are given to illustrate the difficulties involved, and qualitative explanations for these difficulties are provided. Three generalizations of the extended Kalman filter are described. The first is based on inspection of the innovation sequence, that is, the successive differences between observations and forecasts; it works very well for the double-well problem. The second, an extension to fourth-order moments, yields excellent results for the Lorenz model but will be unwieldy when applied to models with high-dimensional state spaces. A third, more practical method--based on an empirical statistical model derived from a Monte Carlo simulation--is formulated, and shown to work very well. Weak-constraint methods can be made to perform satisfactorily in the context of these simple models, but such methods do not seem to generalize easily to practical models of the atmosphere and ocean. In particular, it is shown that the equations derived in the weak variational formulation are difficult to solve conveniently for large systems.

Miller, Robert N.↗
NASA NTRS1994

A fixed-lag Kalman smoother for retrospective data assimilation

Analyses incorporating future data, as well as current and past data, are termed retrospective analyses. In this paper, the fixed-lag Kalman smoother (FLKS) is proposed as a means of providing retrospective analysis capability in data assimilation. The FLKS is a direct generalization of the Kalman filter. It incorporates all data observed up to and including some fixed amount of time past each analysis time. A computationally efficient form of the FLKS is derived. A simple scalar examination of the FLKS demonstrates that incorporating future data improves analyses the most in the presence of dynamical instabilities, for accurate models and for accurate observations. An implementation of the FLKS for two-dimensional linear shallow-water model corroborates the scalar analysis. The numerical experiments also demonstrate the ability of the FLKS to propagate information upstream as well as downstream, thus improving analysis quality substantially in data voids.

Cohn, Stephen E.↗
NASA NTRS1994

Suboptimal schemes for atmospheric data assimilation based on the Kalman filter

This work is directed toward approximating the evolution of forecast error covariances for data assimilation. The performance of different algorithms based on simplification of the standard Kalman filter (KF) is studied. These are suboptimal schemes (SOSs) when compared to the KF, which is optimal for linear problems with known statistics. The SOSs considered here are several versions of optimal interpolation (OI), a scheme for height error variance advection, and a simplified KF in which the full height error covariance is advected. To employ a methodology for exact comparison among these schemes, a linear environment is maintained, in which a beta-plane shallow-water model linearized about a constant zonal flow is chosen for the test-bed dynamics. The results show that constructing dynamically balanced forecast error covariances rather than using conventional geostrophically balanced ones is essential for successful performance of any SOS. A posteriori initialization of SOSs to compensate for model - data imbalance sometimes results in poor performance. Instead, properly constructed dynamically balanced forecast error covariances eliminate the need for initialization. When the SOSs studied here make use of dynamically balanced forecast error covariances, the difference among their performances progresses naturally from conventional OI to the KF. In fact, the results suggest that even modest enhancements of OI, such as including an approximate dynamical equation for height error variances while leaving height error correlation structure homogeneous, go a long way toward achieving the performance of the KF, provided that dynamically balanced cross-covariances are constructed and that model errors are accounted for properly. The results indicate that such enhancements are necessary if unconventional data are to have a positive impact.

Todling, Ricardo↗