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At least 37 records · Page 2

Sensitivity Analysis and Uncertainty Quantification of a Mars Ascent Vehicle Concept

The design of a conceptual Mars ascent vehicle is a challenging problem. In order to aid the vehicle and mission concept design it is important to understand the driving design parameters and the expected performance in the presence of model errors and uncertainties. An existing six degree of freedom simulation model is analyzed on a statistical basis using the methods available in the Design Analysis Kit for Optimization and Terascale Applications toolkit. The methods utilized include conventional Monte Carlo techniques, metamodeling via polynomial chaos expansions, and global variance-based sensitivity analyses. Two additional analysis methods referred to as “Monte Carlo filtering” and ”Classification trees” are used to determine which uncertain parameters are driving the performance of the vehicle. Monte Carlo filtering provides a methodology to determine which parameters cause qualitatively different behavior while the classification trees use heuristics to partition the input space and assign probabilities to each partition. These methods serve as qualitative descriptors of model sensitivity while variance-based global sensitivity analysis seeks a quantitative mapping from total output variance to the variance of individual inputs. Application of these techniques to several outputs of a Mars ascent vehicle concept simulation indicates that only a select few input factors dominate their variance.

Noyes, Connor↗

The analysis sensitivity to tropical winds from the Global Weather Experiment

The global scale divergent and rotational flow components of the Global Weather Experiment (GWE) are diagnosed from three different analyses of the data. The rotational flow shows closer agreement between the analyses than does the divergent flow. Although the major outflow and inflow centers are similarly placed in all analyses, the global kinetic energy of the divergent wind varies by about a factor of 2 between different analyses while the global kinetic energy of the rotational wind varies by only about 10 percent between the analyses. A series of real data assimilation experiments has been performed with the GLA general circulation model using different amounts of tropical wind data during the First Special Observing Period of the Global Weather Experiment. In exeriment 1, all available tropical wind data were used; in the second experiment, tropical wind data were suppressed; while, in the third and fourth experiments, only tropical wind data with westerly and easterly components, respectively, were assimilated. The rotational wind appears to be more sensitive to the presence or absence of tropical wind data than the divergent wind. It appears that the model, given only extratropical observations, generates excessively strong upper tropospheric westerlies. These biases are sufficiently pronounced to amplify the globally integrated rotational flow kinetic energy by about 10 percent and the global divergent flow kinetic energy by about a factor of 2. Including only easterly wind data in the tropics is more effective in controlling the model error than including only westerly wind data. This conclusion is especially noteworthy because approximately twice as many upper tropospheric westerly winds were available in these cases as easterly winds.

Paegle, J.↗

Uncertainty and Sensitivity Analysis of Afterbody Radiative Heating Predictions for Earth Entry

The objective of this work was to perform sensitivity analysis and uncertainty quantification for afterbody radiative heating predictions of Stardust capsule during Earth entry at peak afterbody radiation conditions. The radiation environment in the afterbody region poses significant challenges for accurate uncertainty quantification and sensitivity analysis due to the complexity of the flow physics, computational cost, and large number of un-certain variables. In this study, first a sparse collocation non-intrusive polynomial chaos approach along with global non-linear sensitivity analysis was used to identify the most significant uncertain variables and reduce the dimensions of the stochastic problem. Then, a total order stochastic expansion was constructed over only the important parameters for an efficient and accurate estimate of the uncertainty in radiation. Based on previous work, 388 uncertain parameters were considered in the radiation model, which came from the thermodynamics, flow field chemistry, and radiation modeling. The sensitivity analysis showed that only four of these variables contributed significantly to afterbody radiation uncertainty, accounting for almost 95% of the uncertainty. These included the electronic- impact excitation rate for N between level 2 and level 5 and rates of three chemical reactions in uencing N, N(+), O, and O(+) number densities in the flow field.

West, Thomas K., IV↗

Partitioning of ocean and land uptake of CO2 as inferred by delta C-13 measurements from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network

Using delta C-13 measurements in atmospheric CO2 from a cooperative global air sampling network, we determined the partitioning of the net uptake of CO2 between ocean and land as a function of latitude and time. The majority of delta C-13 measurements were made at the Institute of Arctic and Alpine Research (INSTAAR) of the University of Colorado. We perform an inverse deconvolution of both CO2 and delta C-13 observations, using a two-dimensional model of atmospheric transport. Also, the discrimination against C-13 by plant photosynthesis, as a function of latitude and time, is calculated from global runs of the simple biosphere (SiB) model. Uncertainty due to the longitudinal structure of the data, which is not represented by the model, is studied through a bootstrap analysis by adding and omitting measurement sites. The resulting error estimates for our inferred sources and sinks are of the order of 1 GTC (1 GTC = 10(exp 15) gC). Such error bars do not reflect potential systematic errors arising from our estimates of the isotopic disequilibria between the atmosphere and the oceans and biosphere, which are estimated in a separate sensitivity analysis. With respect to global totals for 1992 we found that 3.2 GTC of carbon dissolved into the ocean and that 1.5 GTC were sequestered by land ecosystems. Northern hemisphere ocean gyres north of 15 deg N absorbed 2.7 GTC. The equatorial oceans between 10 deg S and 10 deg N were a net source to the atmosphere of 0.9 GTC. We obtained a sink of 1.6 GTC in southern ocean gyres south of 20 deg S, although the deconvolution is poorly constrained by sparse data coverage at high southern latitudes. The seasonal uptake of CO2 in the northern gyres appears to be correlated with a bloom of phytoplankton in surface waters. On land, northern temperate and boreal ecosystems between 35 deg N and 65 deg N were found to be a major sink of CO2 in 1992, as large as 3.5 GTC. Northern tropical ecosystems (equator-30 deg N) appear to be a net source to the source to the atmosphere of 2 GTC which could reflect biomass burning. A small sink, 0.3 GTC, was inferred for southern tropical ecosystems (30 deg S-equator).

Ciais, Philippe↗

Space-Time Variations in Water Vapor as Observed by the UARS Microwave Limb Sounder

Water vapor in the upper troposphere has a significant impact on the climate system. Difficulties in making accurate global measurements have led to uncertainty in understanding water vapor's coupling to the hydrologic cycle in the lower troposphere and its role in radiative energy balance. The Microwave Limb Sounder (MLS) on the Upper Atmosphere Research Satellite is able to retrieve water vapor concentration in the upper troposphere with good sensitivity and nearly global coverage. An analysis of these preliminary retrievals based on 3 years of observations shows the water vapor distribution to be similar to that measured by other techniques and to model results. The primary MLS water vapor measurements were made in the stratosphere, where this species acts as a conserved tracer under certain conditions. As is the case for the upper troposphere, most of the stratospheric discussion focuses on the time evolution of the zonal mean and zonally varying water vapor. Stratospheric results span a 19-month period and tropospheric results a 36-month period, both beginning in October of 1991. Comparisons with stratospheric model calculations show general agreement, with some differences in the amplitude and phase of long-term variations. At certain times and places, the evolution of water vapor distributions in the lower stratosphere suggests the presence of meridional transport.

Elson, Lee S.↗

Global Energy and Water Budgets in MERRA

Reanalyses, retrospectively analyzing observations over climatological time scales, represent a merger between satellite observations and models to provide globally continuous data and have improved over several generations. Balancing the Earth s global water and energy budgets has been a focus of research for more than two decades. Models tend to their own climate while remotely sensed observations have had varying degrees of uncertainty. This study evaluates the latest NASA reanalysis, called the Modern Era Retrospective-analysis for Research and Applications (MERRA), from a global water and energy cycles perspective. MERRA was configured to provide complete budgets in its output diagnostics, including the Incremental Analysis Update (IAU), the term that represents the observations influence on the analyzed states, alongside the physical flux terms. Precipitation in reanalyses is typically sensitive to the observational analysis. For MERRA, the global mean precipitation bias and spatial variability are more comparable to merged satellite observations (GPCP and CMAP) than previous generations of reanalyses. Ocean evaporation also has a much lower value which is comparable to observed data sets. The global energy budget shows that MERRA cloud effects may be generally weak, leading to excess shortwave radiation reaching the ocean surface. Evaluating the MERRA time series of budget terms, a significant change occurs, which does not appear to be represented in observations. In 1999, the global analysis increments of water vapor changes sign from negative to positive, and primarily lead to more oceanic precipitation. This change is coincident with the beginning of AMSU radiance assimilation. Previous and current reanalyses all exhibit some sensitivity to perturbations in the observation record, and this remains a significant research topic for reanalysis development. The effect of the changing observing system is evaluated for MERRA water and energy budget terms.

Bosilovich, Michael G.↗

Multidisciplinary optimization of controlled space structures with global sensitivity equations

A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.

Padula, Sharon L.↗

Sensitivity Analysis for Coupled Aero-structural Systems

A novel method has been developed for calculating gradients of aerodynamic force and moment coefficients for an aeroelastic aircraft model. This method uses the Global Sensitivity Equations (GSE) to account for the aero-structural coupling, and a reduced-order modal analysis approach to condense the coupling bandwidth between the aerodynamic and structural models. Parallel computing is applied to reduce the computational expense of the numerous high fidelity aerodynamic analyses needed for the coupled aero-structural system. Good agreement is obtained between aerodynamic force and moment gradients computed with the GSE/modal analysis approach and the same quantities computed using brute-force, computationally expensive, finite difference approximations. A comparison between the computational expense of the GSE/modal analysis method and a pure finite difference approach is presented. These results show that the GSE/modal analysis approach is the more computationally efficient technique if sensitivity analysis is to be performed for two or more aircraft design parameters.

Giunta, Anthony A.↗

Sensitivity of Photolysis Frequencies and Key Tropospheric Oxidants in a Global Model to Cloud Vertical Distributions and Optical Properties

As a follow-up study to our recent assessment of the radiative effects of clouds on tropospheric chemistry, this paper presents an analysis of the sensitivity of such effects to cloud vertical distributions and optical properties in a global 3-D chemical transport model (GEOS4-Chem CTM). GEOS-Chem was driven with a series of meteorological archives (GEOS1-STRAT, GEOS-3 and GEOS-4) generated by the NASA Goddard Earth Observing System data assimilation system, which have significantly different cloud optical depths (CODs) and vertical distributions. Clouds in GEOS1-STRAT and GEOS-3 have more similar vertical distributions while those in GEOS-4 are optically much thinner in the tropical upper troposphere. We find that the radiative impact of clouds on global photolysis frequencies and hydroxyl radical (OH) is more sensitive to the vertical distribution of clouds than to the magnitude of column CODs. Model simulations with each of the three cloud distributions all show that the change in the global burden of O3 due to clouds is less than 5%. Model perturbation experiments with GEOS-3, where the magnitude of 3-D CODs are progressively varied by -100% to 100%, predict only modest changes (<5%) in global mean OH concentrations. J(O1D), J(NO2) and OH concentrations show the strongest sensitivity for small CODs and become insensitive at large CODs due to saturation effects. Caution should be exercised not to use in photochemical models a value for cloud single scattering albedo lower than about 0.999 in order to be consistent with the current knowledge of cloud absorption at the UV wavelength. Our results have important implications for model intercomparisons and climate feedback on tropospheric photochemistry.

Liu, Hongyu↗

Benchmark Data Set for Wheat Growth Models: Field Experiments and AgMIP Multi-Model Simulations.

The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario.

climate change impact↗

Site Distribution and Aliasing Effects in the Inversion for Load Coefficients and Geocenter Motion from GPS Data

Precise GPS measurements of elastic relative site displacements due to surface mass loading offer important constraints on global surface mass transport. We investigate effects of site distribution and aliasing by higher-degree (n greater than or equal 2) loading terms on inversion of GPS data for n = 1 load coefficients and geocenter motion. Covariance and simulation analyses are conducted to assess the sensitivity of the inversion to aliasing and mismodeling errors and possible uncertainties in the n = 1 load coefficient determination. We found that the use of center-of-figure approximation in the inverse formulation could cause 10- 15% errors in the inverted load coefficients. n = 1 load estimates may be contaminated significantly by unknown higher-degree terms, depending on the load scenario and the GPS site distribution. The uncertainty in n = 1 zonal load estimate is at the level of 80 - 95% for two load scenarios.

global positioning system↗

(abstract) Sensitivity to Forest Biomass Based on Analysis of Scattering Mechanism

The estimation of forest biomass on a global scale is an important input to global climate and carbon cycle models. Remote sensing using synthetic aperture radar offers a means to obtain such a data set. Although it has been clear for some time that radar signals penetrate forest canopies, only recently has it been demonstrated that these signals are indeed sensitive to biomass. Inasmuch as the majority of a forest's biomass is in the trunks, it is important that the radar is sensing the trunk biomass as opposed to the branch or leaf biomass. In this study we use polarimetric AIRSAR P- and L-band data from a variety of forests to determine if the radar penetrates to the trunk by examining the scattering mechanism as determined using van Zyl's scattering interaction model, and the levels at which saturation occurs with respect to sensitivity of radar backscatter to total biomass. In particular, the added sensitivity of P-band relative to L-band is addressed. Results using data from the Duke Forest in North Carolina, the Bonanza Creek Experimental Forest in Alaska, Shasta Forest in California, the Black Forest in Germany, the temporate/boreal transition forests in northern Michigan, and coastal forests along the Oregon Transect will be presented.

forest canopy biomass radar scattering mechanism↗

An assessment of the FGGE satellite observing system during SOP-1

The sensitivity of a Goddard Laboratory for Atmospheric Sciences global objective analysis cycle to the addition of FGGE level II-b data is assessed. The GOAS system comprises a predictive continuity provided by a model first-guess forecast integrated from a previous forecast and updated by data gathered in the interim. FGGE data originated in the Jan.-Mar. 1979 period and were acquired by rawinsondes, pilot balloons, surface stations, satellites, ships, and drifting buoys deployed during SOP-1. Focussing on 2-5 and 8-day forecasts, comparisons were made of the 6 hr forecast error at the 300 mb height in three experiments using all, no-satellite (NOSAT), and without rawinsondes or pilot balloons modes. Larger errors occurred in the case of NOSAT, while significant corrections to the GOAS predictions were noted using all the FGGE data. It was concluded that all forecasts were improved by inclusion of full FGGE data sets, including forecasting beyond one week.

Halem, M.↗

Overview of global scale research Doppler lidar activities

Efforts in support of a global backscatter mission are reviewed briefly. Lidar system sensitivity was calibrated by means of ground-based tests. The analysis of ground-based data and planning of a global backscatter mission were conducted. Proposals for FY-85 include using a more powerful laser to conduct backscatter measurements.

Fitzjarrald, D. E.↗

Improvements of the Load Schedule for the Machine Calibration of a Strain-Gage Balance

The load schedule for the calibration of a six-component force balance in a calibration machine was improved. Now, single-component loads are repeated in regular intervals during the calibration. This approach has several advantages. First, the number of single-component loads increases to about twenty-two percent of all loads and load combinations. Consequently, more accurate numerical estimates of the primary bridge sensitivities can be obtained if global regression is used for the analysis of the calibration data. In addition, single-component repeats make it possible to track the stability of the applied loads during the calibration process. Finally, interactions of single-component repeats can be compared with interactions that are observed during the application of manual loads to the balance. Machine calibration and manual data sets of two force balances are used to illustrate benefits of the new load schedule. It is shown in the examples how differences between the observed interactions of machine calibration and manual data can be quantified. The suggested improvements can also be implemented in the load schedule for the machine calibration of a moment or direct-read balance as long as single-component loads are included that are described in the design load format of the balance.

wind tunnel test↗