Assimilating data into ionospheric models: the real-time revolution
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Results of the Flight Test of a Dummy of the MX-656 Rocket-Propelled Models
The data obtained from the flight of a simplified (dummy) rocket-propelled model of the MX-656 have been analyzed to determine the booster-model characteristics and the model-alone characteristics up to a Mach number of 1.3. The data indicate that the model-booster combination is satisfactory. The model alone is longitudinally stable i n the Mach number range covered by the test (0.9 to 1.3) with the center of gravity at -15 percent of the mean aerodynamic chord. With the stabilizer setting at 0 deg. the variation of normal-force coefficient with Mach number is not large. The total-drag-coefficient variation with Mach number is not unusual. About 12 percent of the total drag at a Mach number of 1.3 can be attributed to body base drag.
Mitchell, Jesse L.↗
Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model
An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.
Data Assimilation↗
A History of Collapse Factor Modeling and Empirical Data for Cryogenic Propellant Tanks
One of the major technical problems associated with cryogenic liquid propellant systems used to supply rocket engines and their subassemblies and components is the phenomenon of propellant tank pressurant and ullage gas collapse. This collapse is mainly caused by heat transfer from ullage gas to tank walls and interfacing propellant, which are both at temperatures well below those of this gas. Mass transfer between ullage gas and cryogenic propellant can also occur and have minor to significant secondary effects that can increase or decrease ullage gas collapse. Pressurant gas is supplied into cryogenic propellant tanks in order to initially pressurize these tanks and then maintain required pressures as propellant is expelled from these tanks. The net effect of pressurant and ullage gas collapse is increased total mass and mass flow rate requirements of pressurant gases. For flight vehicles this leads to significant and undesirable weight penalties. For rocket engine component and subassembly ground test facilities this results in significantly increased facility hardware, construction, and operational costs. "Collapse Factor" is a parameter used to quantify the pressurant and ullage gas collapse. Accurate prediction of collapse factors, through analytical methods and modeling tools, and collection and evaluation of collapse factor data has evolved over the years since the start of space exploration programs in the 1950 s. Through the years, numerous documents have been published to preserve results of studies associated with the collapse factor phenomenon. This paper presents a summary and selected details of prior literature that document the aforementioned studies. Additionally other literature that present studies and results of heat and mass transfer processes, related to or providing important insights or analytical methods for the studies of collapse factor, are presented.
deQuay, Laurence↗
Constraining Clouds and Convective Parameterizations in A Climate Model Using Paleoclimate Data
Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.
cloud and convective parameterization↗
Data Assimilation and Transport Modeling in Terrestrial and Planetary Atmospheres
Data assimilation is a blanket term used to describe a number of techniques for retrieving important physical parameters from observational data, subject to constraints imposed by prior knowledge (such as, in the case of meteorology, the primitive equations that govern atmospheric motion). Since these newly developed methods make efficient use of computational resources, they are of great importance in the interpretation of the voluminous datasets that are now produced by satellite missions. As proposed, these techniques have been applied to the study of the Martian and terrestrial atmospheres based on available satellite observations. In addition, a sophisticated hydrodynamic model (non-hydrostatic, and therefore applicable to the study of the interiors of the giant planets) has also been developed and successfully applied to the study of tidally induced motions in Jupiter.
Houben, Howard C.↗
Determination of airplane model structure from flight data using splines and stepwise regression
A procedure for the determination of airplane model structure from flight data is presented. The model is based on a polynomial spline representation of the aerodynamic coefficients, and the procedure is implemented by use of a stepwise regression. First, a form of the aerodynamic force and moment coefficients amenable to the utilization of splines is developed. Next, expressions for the splines in one and two variables are introduced. Then the steps in the determination of an aerodynamic model structure and the estimation of parameters are discussed briefly. The focus is on the application to flight data of the techniques developed.
Klein, V.↗
The Cold Land Processes Experiment (CLPX-1): Analysis and Modelling of LSOS Data (IOP3 Period)
Microwave brightness temperatures at 18.7,36.5, and 89 GHz collected at the Local-Scale Observation Site (LSOS) of the NASA Cold-Land Processes Field Experiment in February, 2003 (third Intensive Observation Period) were simulated using a Dense Media Radiative Transfer model (DMRT), based on the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). Inputs to the model were averaged from LSOS snow pit measurements, although different averages were used for the lower frequencies vs. the highest one, due to the different penetration depths and to the stratigraphy of the snowpack. Mean snow particle radius was computed as a best-fit parameter. Results show that the model was able to reproduce satisfactorily brightness temperatures measured by the University of Tokyo s Ground Based Microwave Radiometer system (CBMR-7). The values of the best-fit snow particle radii were found to fall within the range of values obtained by averaging the field-measured mean particle sizes for the three classes of Small, Medium and Large grain sizes measured at the LSOS site.
Tedesco, Marco↗
Evaluation of Sulfur Flow Emplacement on Io from Galileo Data and Numerical Modeling
Galileo images of bright lava flows surrounding Emakong Patera have been analyzed and numerical modeling has been performed to assess whether these flows could have resulted from the emplacement of sulfur lavas on Io. Images from the solid-state imaging.(SSI) camera show that these bright, white to yellow Emakong flows are up to 370 km long and contain dark, sinuous features that are interpreted to be lava conduits, approx. 300-500 m wide and > 100 km long. Near-Infrared Mapping Spectrometer (NIMS) thermal emission data yield a color temperature estimate of 344 K +/- 60 K (less than or equal to 131 C) within the Emakong caldera. We suggest that these bright flows likely resulted from either sulfur lavas or silicate lavas that have undergone extensive cooling, pyroclastic mantling, and/or alteration with bright sulfurous materials. The Emakong bright flows have estimated volumes of approx. 250-350 cu km, similar to some of the smaller Columbia River Basalt flows. If the Emakong flows did result from effusive sulfur eruptions, then they are orders of magnitude greater in volume than any terrestrial sulfur flows. Our numerical modeling results show that sulfur lavas on Io could have been emplaced as turbulent flows, which were capable of traveling tens to hundreds of kilometers, consistent with the predictions of Sagan [ 19793 and Fink et al. [ 19831. Our modeled flow distances are also consistent with the measured lengths of the Emakong channels and bright flows. Modeled thermal erosion rates are approx. 1-4 m/d for flows erupted at approx. 140-180 C, which are consistent with the melting rates of Kieffer et al. [2000]. The Emakong channels could be thermal erosional in nature; however, the morphologic signatures of thermal erosion channels cannot be discerned from available images. There are planned Galileo flybys of Io in 2001 which provide excellent opportunities to obtain high-resolution morphologic and color data of Emakong Patera. Such observations could, along with further modeling, provide additional information to better constrain whether sulfur lavas produced the Emakong flows.
Williams, David A.↗
Extraction of model performance from wall data in a 2-dimensional transonic flexible walled test section
Data obtained from the boundary of a test section provides information on the model contained within it. A method for extracting some of this data in two dimensional testing is described. Examples of model data are included on lift, pitching moment and wake displacement thickness. A FORTRAN listing is also described, having a form suitable for incorporation into the software package used in the running of such a test section.
Goodyer, M. J.↗
Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data
Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.
MCKissick, Burnell T.↗
Mentat: An object-oriented macro data flow system
Mentat, an object-oriented macro data flow system designed to facilitate parallelism in distributed systems, is presented. The macro data flow model is a model of computation similar to the data flow model with two principal differences: the computational complexity of the actors is much greater than in traditional data flow systems, and there are persistent actors that maintain state information between executions. Mentat is a system that combines the object-oriented programming paradigm and the macro data flow model of computation. Mentat programs use a dynamic structure called a future list to represent the future of computations.
Grimshaw, Andrew S.↗
Model Error Estimation for the CPTEC Eta Model
Statistical data assimilation systems require the specification of forecast and observation error statistics. Forecast error is due to model imperfections and differences between the initial condition and the actual state of the atmosphere. Practical four-dimensional variational (4D-Var) methods try to fit the forecast state to the observations and assume that the model error is negligible. Here with a number of simplifying assumption, a framework is developed for isolating the model error given the forecast error at two lead-times. Two definitions are proposed for the Talagrand ratio tau, the fraction of the forecast error due to model error rather than initial condition error. Data from the CPTEC Eta Model running operationally over South America are used to calculate forecast error statistics and lower bounds for tau.
Tippett, Michael K.↗
CD volume design and verification
In this paper, we describe a prototype for CD-ROM volume design and verification. This prototype allows users to create their own model of CD volumes by modifying a prototypical model. Rule-based verification of the test volumes can then be performed later on against the volume definition. This working prototype has proven the concept of model-driven rule-based design and verification for large quantity of data. The model defined for the CD-ROM volumes becomes a data model as well as an executable specification.
Li, Y. P.↗
Using 3-D Numerical Weather Data in Piloted Simulations
This report describes the process of acquiring and using 3-D numerical model weather data sets in NASA Langley's Research Flight Deck (RFD). A set of software tools implement the process and can be used for other purposes as well. Given time and location information of a weather phenomenon of interest, the user can download associated numerical weather model data. These data are created by the National Oceanic and Atmospheric Administration (NOAA) High Resolution Rapid Refresh (HRRR) model, and are then processed using a set of Mathworks' Matlab(TradeMark) scripts to create the usable 3-D weather data sets. Each data set includes radar re ectivity, water vapor, component winds, temperature, supercooled liquid water, turbulence, pressure, altitude, land elevation, relative humidity, and water phases. An open-source data processing program, wgrib2, is available from NOAA online, and is used along with Matlab scripts. These scripts are described with sucient detail to make future modi cations. These software tools have been used to generate 3-D weather data for various RFD experiments.
Daniels, Taumi S.↗
Time required for an adequate thermal-vacuum test of flight model spacecraft
Data from thermal vacuum tests of flight model spacecraft
Timmins, A. R.↗
Formulation and implementation of nonstationary adaptive estimation algorithm with applications to air-data reconstruction
The dynamics model and data sources used to perform air-data reconstruction are discussed, as well as the Kalman filter. The need for adaptive determination of the noise statistics of the process is indicated. The filter innovations are presented as a means of developing the adaptive criterion, which is based on the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of the filter innovations is presented. The algorithm as developed is applied to air-data reconstruction for the space shuttle, and data obtained from the third landing are presented. To verify the performance of the adaptive algorithm, the reconstruction is also performed using a constant covariance Kalman filter. The results of the reconstructions are compared, and the adaptive algorithm exhibits better performance.
Whitmore, S. A.↗
Formulation and implementation of nonstationary adaptive estimation algorithm with applications to air-data reconstruction
The dynamics model and data sources used to perform air-data reconstruction are discussed, as well as the Kalman filter. The need for adaptive determination of the noise statistics of the process is indicated. The filter innovations are presented as a means of developing the adaptive criterion, which is based on the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of the filter innovations is presented. The algorithm as developed is applied to air-data reconstruction for the Space Shuttle, and data obtained from the third landing are presented. To verify the performance of the adaptive algorithm, the reconstruction is also performed using a constant covariance Kalman filter. The results of the reconstructions are compared, and the adaptive algorithm exhibits better performance.
Whitmore, S. A.↗