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At least 847 records · Page 47

Precise tracking of the Magellan and Pioneer Venusorbiters by same-beam interferometry. Part 1: Dataaccuracy analysis

Simultaneous tracking of two spacecraft in orbit about a distant planet by two widely separated Earth-based radio antennas provides more-accurate positioning information than can be obtained by tracking each spacecraft separately. A demonstration of this tracking technique, referred to as same-beam interferometry (SBI), is currently being done using the Magellan and Pioneer 12 orbiters at Venus. Signals from both spacecraft fall within the same beamwidth of the Deep Space Station antennas. The plane-of-sky position difference between spacecraft is precisely determined by doubly differenced phase measurements. This radio metric measurement naturally complements line-of-sight Doppler. Data was first collected from Magellan and Pioneer 12 on August 11-12, 1990, shortly after Magellan was inserted into Venus orbit. Data were subsequently acquired in February and April 1991, providing a total of 34 hours of same-beam radio metric observables. Same-beam radio metric residuals have been analyzed and compared with model measurement error predictions. The predicted error is dominated by solar plasma fluctuations. The rms of the residuals is less than predicted by about 25 percent for 5-min averages. The shape of the spectrum computed from residuals is consistent with that derived from a model of solar plasma fluctuations. This data type can greatly aid navigation of a second spacecraft when the first is well-known in its orbit.

Border, J. S.↗

Impact of Flow-Dependent Error Correlations and Tropospheric Chemistry on Assimilated Ozone

The presentation compares different versions of a global three-dimensional ozone data assimilation system developed at NASA's Data Assimilation Office. The Solar Backscatter Ultraviolet/2 (SBUV/2) total and partial ozone column retrievals are the sole data assimilated in all of the experiments presented. We study the impact of changing the forecast error covariance model from a version assuming static correlations with a one that captures a short-term Lagrangian evolution of those correlations. This is further combined with a study of the impact of neglecting the tropospheric ozone production, loss and dry deposition rates, which are obtained from the Harvard GEOS-CHEM model. We compare statistical characteristics of the assimilated data and the results of validation against independent observations, obtained from WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres. On the other hand, the main sensitivity to tropospheric chemistry is in the Tropics and sub-Tropics. The best agreement between the assimilated ozone and the in-situ sonde data is in the experiment using both flow-dependent error covariances and tropospheric chemistry.

Wargan, K.↗

Application of artificial neural networks in hydrological modeling: A case study of runoff simulation of a Himalayan glacier basin

The simulation of runoff from a Himalayan Glacier basin using an Artificial Neural Network (ANN) is presented. The performance of the ANN model is found to be superior to the Energy Balance Model and the Multiple Regression model. The RMS Error is used as the figure of merit for judging the performance of the three models, and the RMS Error for the ANN model is the latest of the three models. The ANN is faster in learning and exhibits excellent system generalization characteristics.

Buch, A. M.↗

DAO's Next Generation Physical-Space/Finite-Volume Data Assimilation System: Formulation and Initial Evaluation

The Physical-space/Finite-volume Data Assimilation System (fvDAS) is the next generation global atmospheric data assimilation system in development at the Data Assimilation Office at NASA's Goddard Space Flight Center. It is based on a new finite-volume general circulation model jointly developed by NASA and NCAR, and on the Physical-Space Statistical Analysis System (PSAS) developed at the DAO. In this talk we will describe the general system formulation, the adaptive quality control and general aspects of the error covariance modeling. The NASA-NCAR GCM is a completely new model which replaces the CEOs GCM used in the previous GEOS-1/2/3 Data Assimilation systems. A particular configuration of adaptive Statistical Quality Control and the Physical-space Statistical Analysis System (PSAS) are currently implemented in DAO's operational Data Assimilation System. However, the unique finite-volume formulation of the NASA-NCAR GCM, combined with the generality of the observation-space formulation of PSAS, provides for a very simple and accurate model-analysis interface. The system assimilates a variety of conventional and satellite observations. In particular, TOVS Level 1B radiances are assimilated using a 1-D variational scheme, both in clear sky and cloudy conditions. Computationally, the fvDAS runs approximately 10 times faster than the operational GEOS-Terra system. We will show that the next-generation fvDAS has much improved observation-minus-6hr forecast (O-F) statistics, as well as 5-day forecast skills. Top of the atmosphere radiation fields are in closer agreement with CERES measurements, with realistic precipitation and moisture fields. We will also show that the finite-volume formulation of the fvDAS produce assimilated fields which are more suitable for driving constituent transport models.

daSilva, A.↗

Non-exercise Estimation of V02max Using a Dichotomy of Meeting or Not Meeting DHHS Physical Activity Recommendations

The physical activity guidelines (PAG) established by the US Dept. of Health and Human Services in 2008 is consistent with a rating of >/= 6 on the 11-point NASA Physical Activity Status Scale (PASS). Wier, et. al. developed non-exercise models for estimating VO2(sub max) from a combination of PASS, age, gender and either waist girth (WG) (R = 0.810, SEE= 4.799 ml/kg/min), %Fat (R = 0. 817, SEE = 4.716 ml/kg/min) or BMI (R = 0.802, SEE = 4.900 ml . kg-1. min -1 ). PURPOSE: to develop non-exercise models to estimate VO2max from age, gender, body composition (WG, %Fat, BMI) and PASS dichotomized at meets or does not meet the PAG (PAG-PASS), and to compare the accuracy of the PAG-PASS models with the models using the 11-point PASS. METHODS: 2417 men and 384 women were measured for VO2max by indirect calorimetry (RER >1.1); age (yr), gender by M = 1, W = 0; WG at the umbilicus; %fat by skin-folds, BMI by weight (kg) divided by height squared (m 2 ) , and PAGPASS by PASS < 6 = 0 and =/> 6 = 1. RESULTS: Three models were developed by multiple regression to estimate VO2(sub max) from age, gender, PAG-PASS and either WG (R = 0.790, SEE=5.019 ml/kg/min), %FAT (R= 0.080, SEE = 4.915 ml/kg/min) or BMI (R = 0.777, SEE = 5.162ml/kg/min). Cross-validation by the PRESS technique confirmed these statistics. Simple correlations between measured VO2(sub max) and estimates from the PAG-PASS models with WG, %Fat and BMI were 0.790, 0.800 and 0.777, minimally different from the correlations obtained with the PASS models (0.810, 0.810, and 0.802). PAG-PASS and PASS model constant errors were also similar: < 1 ml/kg/min for subsamples of age, gender, PASS and for VO2(sub max) between 30 and 50 ml/kg/min (70% of the sample) but > 1 ml/kg/min for VO2(sub max) <30 and >50 ml/kg/min. CONCLUSIONS: Non-exercise models using the combined effects of age, gender, body composition and the dichotomized PAG-PASS provide estimates of VO2(sub max) that are accurate for most adults, and the accuracy of these models are similar to previously published models using the 11-point PASS.

Wier, Larry T.↗

A Fast Visible-Infrared Imaging Radiometer Suite Simulator for Cloudy Atmopheres

A fast instrument simulator is developed to simulate the observations made in cloudy atmospheres by the Visible Infrared Imaging Radiometer Suite (VIIRS). The correlated k-distribution (CKD) technique is used to compute the transmissivity of absorbing atmospheric gases. The bulk scattering properties of ice clouds used in this study are based on the ice model used for the MODIS Collection 6 ice cloud products. Two fast radiative transfer models based on pre-computed ice cloud look-up-tables are used for the VIIRS solar and infrared channels. The accuracy and efficiency of the fast simulator are quantify in comparison with a combination of the rigorous line-by-line (LBLRTM) and discrete ordinate radiative transfer (DISORT) models. Relative errors are less than 2 for simulated TOA reflectances for the solar channels and the brightness temperature differences for the infrared channels are less than 0.2 K. The simulator is over three orders of magnitude faster than the benchmark LBLRTM+DISORT model. Furthermore, the cloudy atmosphere reflectances and brightness temperatures from the fast VIIRS simulator compare favorably with those from VIIRS observations.

VIIRS Instrument Simulator↗

Optial Experiments and Model Validation of Perturbed Starshade Designs

Starshades are a leading technology to enable the direct detection and spectroscopic characterization of Earth- like exoplanets. Critical starshade technologies are currently being advanced through the S5 Project and at the Princeton starshade testbed. We report on the status of Milestone 2 of the S5 Project, optical model validation. We present results from optical experiments of starshades with intentional perturbations built into their design. These perturbations are representative of the type of perturbations possible in a flight design and serve as points of validation for dffraction models and error budgets. We show experimental results for two perturbed shapes, a mask with all petals shifted radially outward by 5 um and a mask with shallow sine waves built into two petals. We compare these data to outputs of the optical model and demonstrate better than 25% agreement. We also present images taken in crossed polarized light and use those data to constrain physical parameters of the optical edge. Bringing in previously obtained results for other perturbed shapes, we show an agreement between experiment and model of better than 25% and argue that this satisfies the Milestone 2 criteria.

Galvin, Michael↗

Solar Probe Plus: Unique Navigation Modeling Challenges

The Solar Probe Plus (SPP) mission is preparing to launch in 2018, and will directly investigate the outer atmosphere of our star. At 9.86 solar radii, SPP must operate in an unexplored regime. The environment and aspects of the mission design present some unique challenges for navigation, particularly in terms of modeling the dynamics. Non-gravitational force models, unique to this mission, are given with analytical expressions. For each of these models (and error sources), a maximum bound on the force perturbation magnitude is quantified numerically. Additionally, the effect of charged particles on radiometric observables is discussed, along with methods being employed to pre-process the measurements. This survey is an overview of unique modeling employed by SPP navigation, but also a reference for future missions traveling near the Sun.

Jones, Drew Ryan↗

Analysis of Subpixel Registration Accuracy

Geometric and probabilistic models for subpixel accuracy are developed. The geometric models bound the error in offset estimation using the pixels in an observed digital straight line. One probabilistic model bounds the estimate of error offset for continuous images. The other model bounds the error for discrete images given that one is in the correct pixel.

Lavine, D.↗

High-precision radiometric tracking for planetary approach and encounter in the inner solar system

The benefits of improved radiometric tracking data have been studied for planetary approach within the inner Solar System using the Mars Rover Sample Return trajectory as a model. It was found that the benefit of improved data to approach and encounter navigation was highly dependent on the a priori uncertainties assumed for several non-estimated parameters, including those for frame-tie, Earth orientation, troposphere delay, and station locations. With these errors at their current levels, navigational performance was found to be insensitive to enhancements in data accuracy. However, when expected improvements in these errors are modeled, performance with current-accuracy data significantly improves, with substantial further improvements possible with enhancements in data accuracy.

Christensen, C. S.↗

The GEOS Ozone Data Assimilation System: Design and Validation

An ozone data assimilation system has been developed at the Data Assimilation Office of the NASA/Goddard Space Flight Center to provide global three-dimensional analyzed ozone mixing ratio and total column ozone. The Total Ozone Mapping Spectrometer (TOMS) total column ozone and the Solar Backscatter Ultraviolet (SBUV) or SBUV/2 partial ozone profile data are assimilated. The analyzed winds from the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) drive the ozone transport. Following every transport model timestep, the model prediction is combined with the observations using a global, physical-space based, statistical analysis scheme. Due to the smaller size of the ozone system than that of a global meteorological data assimilation system, new statistical analysis methodology, including anisotropic and flow-dependent forecast error correlation models, can be implemented and tested in the ozone system more easily. Sample results from the winter 1992 validation period are presented. There is a close agreement between the analyzed fields and the independent observations from ozone sondes and the Halogen Occultation Experiment (HALOE).

Stajner, I.↗

Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions

Wetland methane (CH4) emissions comprise about one-third of the global CH4 source. The latitudinal distribution and climate sensitivity of wetland CH4 fluxes are the key determinants of the global CH4-climate feedback. However, large differences exist between bottom-up estimates, informed by ground-based flux measurements, and top-down estimates derived from spaceborne total column CH4. Despite the extensive coverage of satellite CH4 concentration observations, challenges remain with using top-down estimates to test bottom-up models, mainly because of the uncertainties in the satellite retrievals, the model representation errors, the variable prior emissions, and the confounding role of the posterior error covariance structures. Here, we use satellite-based top-down CH4 flux estimates (2010–2012) to test and refine 42 bottom-up estimates of wetland emissions that use a range of hypothesized wetland extents and process controls. Our comparison between bottom-up models and satellite-based fluxes innovatively accounts for cross-correlations and spatial uncertainties typically found in top-down inverse estimates, such that only the information from satellite observations and the atmospheric transport model is kept as a constraint. We present a satellite-constrained wetland CH4 ensemble product derived from assembling the highest-performance bottom-up models, which estimates global wetland CH4 emissions of 148 (117–189, 5th–95th percentile) Tg CH4 yr−1. We find that tropical wetland emissions contribute 72% (63%–85%) to the global wetland total. We also find that a lower-than-expected temperature sensitivity agrees better with atmospheric CH4 measurements. Overall, our approach demonstrates the potential for using satellites to quantitatively refine bottom-up wetland CH4 emission estimates, their latitudinal distributions, and their sensitivity to climate.

wetland ch4↗

Modeling Pluto-Charon mutual eclipse events. I - First-order models

The present 'first order' analytical and numerical models of light curves due to mutual events between close planetary binaries, the effects of shadowing are included. Attention is given to the case of the Pluto-Charon system. The results of the analytical and numerical approaches agree to well within the expected light curve measurement error. The model predicts that the current mutual eclipse event series will end by November 1990.

Dunbar, R. Scott↗

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Hartman, Brian Davis↗

An improved error assessment for the GEM-T1 gravitational model

Several tests were designed to determine the correct error variances for the GEM-T1 gravitational solution which was derived exclusively from satellite tracking data. The basic method employs both wholly independent and dependent subset data solutions and produces a full field coefficient by coefficient estimate of the model uncertainties. The GEM-T1 errors were further analyzed using a method based upon eigenvalue-eigenvector analysis which calibrates the entire covariance matrix. Dependent satellite and independent altimetric and surface gravity data sets, as well as independent satellite deep resonance information, confirm essentially the same error assessment.

Lerch, F. J.↗

A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

Wen, John T.↗

Multimodel Ensembles of Wheat Growth: Many Models are Better than One

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop model scan give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 2438 for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.

model intercomparison↗

Planting data and wheat yield models

The author has identified the following significant results. A variable date starter model for spring wheat depending on temperature was more precise than a fixed date model. The same conclusions for fall-planted wheat were not reached. If the largest and smallest of eight temperatures were used to estimate daily maximum and minimum temperatures; respectively, a 1-4 F bias would be introduced into these extremes. For Kansas, a reduction of 0.5 bushels/acre in the root-mean-square-error between model and SRS yields was achieved by a six fold increase (7 to 42) in the density of weather stations. An additional reduction of 0.3 b/A was achieved by incorporating losses due to rusts in the model.

Feyerherm, A. M.↗