Ice-nucleating particle emissions from photochemically aged diesel and biodiesel exhaust

NASA Astrophysics Data System (ADS)

Schill, G. P.; Jathar, S. H.; Kodros, J. K.; Levin, E. J. T.; Galang, A. M.; Friedman, B.; Link, M. F.; Farmer, D. K.; Pierce, J. R.; Kreidenweis, S. M.; DeMott, P. J.

2016-05-01

Immersion-mode ice-nucleating particle (INP) concentrations from an off-road diesel engine were measured using a continuous-flow diffusion chamber at -30°C. Both petrodiesel and biodiesel were utilized, and the exhaust was aged up to 1.5 photochemically equivalent days using an oxidative flow reactor. We found that aged and unaged diesel exhaust of both fuels is not likely to contribute to atmospheric INP concentrations at mixed-phase cloud conditions. To explore this further, a new limit-of-detection parameterization for ice nucleation on diesel exhaust was developed. Using a global-chemical transport model, potential black carbon INP (INPBC) concentrations were determined using a current literature INPBC parameterization and the limit-of-detection parameterization. Model outputs indicate that the current literature parameterization likely overemphasizes INPBC concentrations, especially in the Northern Hemisphere. These results highlight the need to integrate new INPBC parameterizations into global climate models as generalized INPBC parameterizations are not valid for diesel exhaust.

Radiative flux and forcing parameterization error in aerosol-free clear skies

DOE PAGES

Pincus, Robert; Mlawer, Eli J.; Oreopoulos, Lazaros; ...

2015-07-03

This article reports on the accuracy in aerosol- and cloud-free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present-day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m 2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present-day conditions is essentiallymore » unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. As a result, a dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.« less

Neutrons in proton pencil beam scanning: parameterization of energy, quality factors and RBE

NASA Astrophysics Data System (ADS)

Schneider, Uwe; Hälg, Roger A.; Baiocco, Giorgio; Lomax, Tony

2016-08-01

The biological effectiveness of neutrons produced during proton therapy in inducing cancer is unknown, but potentially large. In particular, since neutron biological effectiveness is energy dependent, it is necessary to estimate, besides the dose, also the energy spectra, in order to obtain quantities which could be a measure of the biological effectiveness and test current models and new approaches against epidemiological studies on cancer induction after proton therapy. For patients treated with proton pencil beam scanning, this work aims to predict the spatially localized neutron energies, the effective quality factor, the weighting factor according to ICRP, and two RBE values, the first obtained from the saturation corrected dose mean lineal energy and the second from DSB cluster induction. A proton pencil beam was Monte Carlo simulated using GEANT. Based on the simulated neutron spectra for three different proton beam energies a parameterization of energy, quality factors and RBE was calculated. The pencil beam algorithm used for treatment planning at PSI has been extended using the developed parameterizations in order to calculate the spatially localized neutron energy, quality factors and RBE for each treated patient. The parameterization represents the simple quantification of neutron energy in two energy bins and the quality factors and RBE with a satisfying precision up to 85 cm away from the proton pencil beam when compared to the results based on 3D Monte Carlo simulations. The root mean square error of the energy estimate between Monte Carlo simulation based results and the parameterization is 3.9%. For the quality factors and RBE estimates it is smaller than 0.9%. The model was successfully integrated into the PSI treatment planning system. It was found that the parameterizations for neutron energy, quality factors and RBE were independent of proton energy in the investigated energy range of interest for proton therapy. The pencil beam algorithm has been extended using the developed parameterizations in order to calculate the neutron energy, quality factor and RBE.

Neutrons in proton pencil beam scanning: parameterization of energy, quality factors and RBE.

PubMed

Schneider, Uwe; Hälg, Roger A; Baiocco, Giorgio; Lomax, Tony

2016-08-21

The biological effectiveness of neutrons produced during proton therapy in inducing cancer is unknown, but potentially large. In particular, since neutron biological effectiveness is energy dependent, it is necessary to estimate, besides the dose, also the energy spectra, in order to obtain quantities which could be a measure of the biological effectiveness and test current models and new approaches against epidemiological studies on cancer induction after proton therapy. For patients treated with proton pencil beam scanning, this work aims to predict the spatially localized neutron energies, the effective quality factor, the weighting factor according to ICRP, and two RBE values, the first obtained from the saturation corrected dose mean lineal energy and the second from DSB cluster induction. A proton pencil beam was Monte Carlo simulated using GEANT. Based on the simulated neutron spectra for three different proton beam energies a parameterization of energy, quality factors and RBE was calculated. The pencil beam algorithm used for treatment planning at PSI has been extended using the developed parameterizations in order to calculate the spatially localized neutron energy, quality factors and RBE for each treated patient. The parameterization represents the simple quantification of neutron energy in two energy bins and the quality factors and RBE with a satisfying precision up to 85 cm away from the proton pencil beam when compared to the results based on 3D Monte Carlo simulations. The root mean square error of the energy estimate between Monte Carlo simulation based results and the parameterization is 3.9%. For the quality factors and RBE estimates it is smaller than 0.9%. The model was successfully integrated into the PSI treatment planning system. It was found that the parameterizations for neutron energy, quality factors and RBE were independent of proton energy in the investigated energy range of interest for proton therapy. The pencil beam algorithm has been extended using the developed parameterizations in order to calculate the neutron energy, quality factor and RBE.

Quantifying the biological impact of surface ocean light attenuation by colored detrital matter in an ESM using a new optical parameterization

NASA Astrophysics Data System (ADS)

Kim, G. E.; Pradal, M.-A.; Gnanadesikan, A.

2015-08-01

Light attenuation by colored detrital material (CDM) was included in a fully coupled Earth system model (ESM). This study presents a modified parameterization for shortwave attenuation, which is an empirical relationship between 244 concurrent measurements of the diffuse attenuation coefficient for downwelling irradiance, chlorophyll concentration and light absorption by CDM. Two ESM model runs using this parameterization were conducted, with and without light absorption by CDM. The light absorption coefficient for CDM was prescribed as the average of annual composite MODIS Aqua satellite data from 2002 to 2013. Comparing results from the two model runs shows that changes in light limitation associated with the inclusion of CDM decoupled trends between surface biomass and nutrients. Increases in surface biomass were expected to accompany greater nutrient uptake and therefore diminish surface nutrients. Instead, surface chlorophyll, biomass and nutrients increased together. These changes can be attributed to the different impact of light limitation on surface productivity versus total productivity. Chlorophyll and biomass increased near the surface but decreased at greater depths when CDM was included. The net effect over the euphotic zone was less total biomass leading to higher nutrient concentrations. Similar results were found in a regional analysis of the oceans by biome, investigating the spatial variability of response to changes in light limitation using a single parameterization for the surface ocean. In coastal regions, surface chlorophyll increased by 35 % while total integrated phytoplankton biomass diminished by 18 %. The largest relative increases in modeled surface chlorophyll and biomass in the open ocean were found in the equatorial biomes, while the largest decreases in depth-integrated biomass and chlorophyll were found in the subpolar and polar biomes. This mismatch of surface and subsurface trends and their regional dependence was analyzed by comparing the competing factors of diminished light availability and increased nutrient availability on phytoplankton growth in the upper 200 m. Understanding changes in biological productivity requires both surface and depth-resolved information. Surface trends may be minimal or of the opposite sign than depth-integrated amounts, depending on the vertical structure of phytoplankton abundance.

Multiscale Cloud System Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell W.

2009-01-01

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

PubMed

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

2017-01-01

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

Influence of the vertical mixing parameterization on the modeling results of the Arctic Ocean hydrology

NASA Astrophysics Data System (ADS)

Iakshina, D. F.; Golubeva, E. N.

2017-11-01

The vertical distribution of the hydrological characteristics in the upper ocean layer is mostly formed under the influence of turbulent and convective mixing, which are not resolved in the system of equations for large-scale ocean. Therefore it is necessary to include additional parameterizations of these processes into the numerical models. In this paper we carry out a comparative analysis of the different vertical mixing parameterizations in simulations of climatic variability of the Arctic water and sea ice circulation. The 3D regional numerical model for the Arctic and North Atlantic developed in the ICMMG SB RAS (Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the Russian Academy of Science) and package GOTM (General Ocean Turbulence Model1,2, http://www.gotm.net/) were used as the numerical instruments . NCEP/NCAR reanalysis data were used for determination of the surface fluxes related to ice and ocean. The next turbulence closure schemes were used for the vertical mixing parameterizations: 1) Integration scheme based on the Richardson criteria (RI); 2) Second-order scheme TKE with coefficients Canuto-A3 (CANUTO); 3) First-order scheme TKE with coefficients Schumann and Gerz4 (TKE-1); 4) Scheme KPP5 (KPP). In addition we investigated some important characteristics of the Arctic Ocean state including the intensity of Atlantic water inflow, ice cover state and fresh water content in Beaufort Sea.

How certain are the process parameterizations in our models?

NASA Astrophysics Data System (ADS)

Gharari, Shervan; Hrachowitz, Markus; Fenicia, Fabrizio; Matgen, Patrick; Razavi, Saman; Savenije, Hubert; Gupta, Hoshin; Wheater, Howard

2016-04-01

Environmental models are abstract simplifications of real systems. As a result, the elements of these models, including system architecture (structure), process parameterization and parameters inherit a high level of approximation and simplification. In a conventional model building exercise the parameter values are the only elements of a model which can vary while the rest of the modeling elements are often fixed a priori and therefore not subjected to change. Once chosen the process parametrization and model structure usually remains the same throughout the modeling process. The only flexibility comes from the changing parameter values, thereby enabling these models to reproduce the desired observation. This part of modeling practice, parameter identification and uncertainty, has attracted a significant attention in the literature during the last years. However what remains unexplored in our point of view is to what extent the process parameterization and system architecture (model structure) can support each other. In other words "Does a specific form of process parameterization emerge for a specific model given its system architecture and data while no or little assumption has been made about the process parameterization itself? In this study we relax the assumption regarding a specific pre-determined form for the process parameterizations of a rainfall/runoff model and examine how varying the complexity of the system architecture can lead to different or possibly contradictory parameterization forms than what would have been decided otherwise. This comparison implicitly and explicitly provides us with an assessment of how uncertain is our perception of model process parameterization in respect to the extent the data can support.

Development and Testing of Coupled Land-surface, PBL and Shallow/Deep Convective Parameterizations within the MM5

NASA Technical Reports Server (NTRS)

Stauffer, David R.; Seaman, Nelson L.; Munoz, Ricardo C.

2000-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins using a 3-D mesoscale model, the PSUINCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. It was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having a detailed land-surface parameterization, an advanced boundary-layer parameterization, and a more complete shallow convection parameterization than are available in most current models. The methodology was based on the application in the MM5 of new or recently improved parameterizations covering these three physical processes. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the Southern Great Plains (SGP): (1) the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) described by Wetzel and Boone; (2) the 1.5-order turbulent kinetic energy (TKE)-predicting scheme of Shafran et al.; and (3) the hybrid-closure sub-grid shallow convection parameterization of Deng. Each of these schemes has been tested extensively through this study and the latter two have been improved significantly to extend their capabilities.

Cloud microphysics modification with an online coupled COSMO-MUSCAT regional model

NASA Astrophysics Data System (ADS)

Sudhakar, D.; Quaas, J.; Wolke, R.; Stoll, J.; Muehlbauer, A. D.; Tegen, I.

2015-12-01

Abstract: The quantification of clouds, aerosols, and aerosol-cloud interactions in models, continues to be a challenge (IPCC, 2013). In this scenario two-moment bulk microphysical scheme is used to understand the aerosol-cloud interactions in the regional model COSMO (Consortium for Small Scale Modeling). The two-moment scheme in COSMO has been especially designed to represent aerosol effects on the microphysics of mixed-phase clouds (Seifert et al., 2006). To improve the model predictability, the radiation scheme has been coupled with two-moment microphysical scheme. Further, the cloud microphysics parameterization has been modified via coupling COSMO with MUSCAT (MultiScale Chemistry Aerosol Transport model, Wolke et al., 2004). In this study, we will be discussing the initial result from the online-coupled COSMO-MUSCAT model system with modified two-moment parameterization scheme along with COSP (CFMIP Observational Simulator Package) satellite simulator. This online coupled model system aims to improve the sub-grid scale process in the regional weather prediction scenario. The constant aerosol concentration used in the Seifert and Beheng, (2006) parameterizations in COSMO model has been replaced by aerosol concentration derived from MUSCAT model. The cloud microphysical process from the modified two-moment scheme is compared with stand-alone COSMO model. To validate the robustness of the model simulation, the coupled model system is integrated with COSP satellite simulator (Muhlbauer et al., 2012). Further, the simulations are compared with MODIS (Moderate Resolution Imaging Spectroradiometer) and ISCCP (International Satellite Cloud Climatology Project) satellite products.

Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate

NASA Technical Reports Server (NTRS)

Seaman, Nelson L.; Stauffer, David R.; Munoz, Ricardo C.

2001-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.

On testing two major cumulus parameterization schemes using the CSU Regional Atmospheric Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kao, C.Y.J.; Bossert, J.E.; Winterkamp, J.

1993-10-01

One of the objectives of the DOE ARM Program is to improve the parameterization of clouds in general circulation models (GCMs). The approach taken in this research is two fold. We first examine the behavior of cumulus parameterization schemes by comparing their performance against the results from explicit cloud simulations with state-of-the-art microphysics. This is conducted in a two-dimensional (2-D) configuration of an idealized convective system. We then apply the cumulus parameterization schemes to realistic three-dimensional (3-D) simulations over the western US for a case with an enormous amount of convection in an extended period of five days. In themore » 2-D idealized tests, cloud effects are parameterized in the ``parameterization cases`` with a coarse resolution, whereas each cloud is explicitly resolved by the ``microphysics cases`` with a much finer resolution. Thus, the capability of the parameterization schemes in reproducing the growth and life cycle of a convective system can then be evaluated. These 2-D tests will form the basis for further 3-D realistic simulations which have the model resolution equivalent to that of the next generation of GCMs. Two cumulus parameterizations are used in this research: the Arakawa-Schubert (A-S) scheme (Arakawa and Schubert, 1974) used in Kao and Ogura (1987) and the Kuo scheme (Kuo, 1974) used in Tremback (1990). The numerical model used in this research is the Regional Atmospheric Modeling System (RAMS) developed at Colorado State University (CSU).« less

Confronting Models with Data: The GEWEX Cloud Systems Study

NASA Technical Reports Server (NTRS)

Randall, David; Curry, Judith; Duynkerke, Peter; Krueger, Steven; Moncrieff, Mitchell; Ryan, Brian; Starr, David OC.; Miller, Martin; Rossow, William; Tselioudis, George

2002-01-01

The GEWEX Cloud System Study (GCSS; GEWEX is the Global Energy and Water Cycle Experiment) was organized to promote development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. The strategy of GCSS is to use two distinct kinds of models to analyze and understand observations of the behavior of several different types of clouds systems. Cloud-system-resolving models (CSRMs) have high enough spatial and temporal resolutions to represent individual cloud elements, but cover a wide enough range of space and time scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the surgically extracted column physics of atmospheric general circulation models. SCMs are used to test cloud parameterizations in an un-coupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data is collected in various field programs and provided to the CSRM Community, which uses the data to "certify" the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM Community. We report here the results of a re-thinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, and an explicit recognition of the importance of data integration.

Cooperative Solutions in Multi-Person Quadratic Decision Problems: Finite-Horizon and State-Feedback Cost-Cumulant Control Paradigm

DTIC Science & Technology

2007-01-01

CONTRACT NUMBER Problems: Finite -Horizon and State-Feedback Cost-Cumulant Control Paradigm (PREPRINT) 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...cooperative cost-cumulant control regime for the class of multi-person single-objective decision problems characterized by quadratic random costs and... finite -horizon integral quadratic cost associated with a linear stochastic system . Since this problem formation is parameterized by the number of cost

Evaluation of different parameterizations of the spatial heterogeneity of subsurface storage capacity for hourly runoff simulation in boreal mountainous watershed

NASA Astrophysics Data System (ADS)

Hailegeorgis, Teklu T.; Alfredsen, Knut; Abdella, Yisak S.; Kolberg, Sjur

2015-03-01

Identification of proper parameterizations of spatial heterogeneity is required for precipitation-runoff models. However, relevant studies with a specific aim at hourly runoff simulation in boreal mountainous catchments are not common. We conducted calibration and evaluation of hourly runoff simulation in a boreal mountainous watershed based on six different parameterizations of the spatial heterogeneity of subsurface storage capacity for a semi-distributed (subcatchments hereafter called elements) and distributed (1 × 1 km2 grid) setup. We evaluated representation of element-to-element, grid-to-grid, and probabilistic subcatchment/subbasin, subelement and subgrid heterogeneities. The parameterization cases satisfactorily reproduced the streamflow hydrographs with Nash-Sutcliffe efficiency values for the calibration and validation periods up to 0.84 and 0.86 respectively, and similarly for the log-transformed streamflow up to 0.85 and 0.90. The parameterizations reproduced the flow duration curves, but predictive reliability in terms of quantile-quantile (Q-Q) plots indicated marked over and under predictions. The simple and parsimonious parameterizations with no subelement or no subgrid heterogeneities provided equivalent simulation performance compared to the more complex cases. The results indicated that (i) identification of parameterizations require measurements from denser precipitation stations than what is required for acceptable calibration of the precipitation-streamflow relationships, (ii) there is challenges in the identification of parameterizations based on only calibration to catchment integrated streamflow observations and (iii) a potential preference for the simple and parsimonious parameterizations for operational forecast contingent on their equivalent simulation performance for the available input data. In addition, the effects of non-identifiability of parameters (interactions and equifinality) can contribute to the non-identifiability of the parameterizations.

Comprehensive assessment of parameterization methods for estimating clear-sky surface downward longwave radiation

NASA Astrophysics Data System (ADS)

Guo, Yamin; Cheng, Jie; Liang, Shunlin

2018-02-01

Surface downward longwave radiation (SDLR) is a key variable for calculating the earth's surface radiation budget. In this study, we evaluated seven widely used clear-sky parameterization methods using ground measurements collected from 71 globally distributed fluxnet sites. The Bayesian model averaging (BMA) method was also introduced to obtain a multi-model ensemble estimate. As a whole, the parameterization method of Carmona et al. (2014) performs the best, with an average BIAS, RMSE, and R 2 of - 0.11 W/m2, 20.35 W/m2, and 0.92, respectively, followed by the parameterization methods of Idso (1981), Prata (Q J R Meteorol Soc 122:1127-1151, 1996), Brunt and Sc (Q J R Meteorol Soc 58:389-420, 1932), and Brutsaert (Water Resour Res 11:742-744, 1975). The accuracy of the BMA is close to that of the parameterization method of Carmona et al. (2014) and comparable to that of the parameterization method of Idso (1981). The advantage of the BMA is that it achieves balanced results compared to the integrated single parameterization methods. To fully assess the performance of the parameterization methods, the effects of climate type, land cover, and surface elevation were also investigated. The five parameterization methods and BMA all failed over land with the tropical climate type, with high water vapor, and had poor results over forest, wetland, and ice. These methods achieved better results over desert, bare land, cropland, and grass and had acceptable accuracies for sites at different elevations, except for the parameterization method of Carmona et al. (2014) over high elevation sites. Thus, a method that can be successfully applied everywhere does not exist.

Thermodynamic integration based on classical atomistic simulations to determine the Gibbs energy of condensed phases: Calculation of the aluminum-zirconium system

NASA Astrophysics Data System (ADS)

Harvey, J.-P.; Gheribi, A. E.; Chartrand, P.

2012-12-01

In this work, an in silico procedure to generate a fully coherent set of thermodynamic properties obtained from classical molecular dynamics (MD) and Monte Carlo (MC) simulations is proposed. The procedure is applied to the Al-Zr system because of its importance in the development of high strength Al-Li alloys and of bulk metallic glasses. Cohesive energies of the studied condensed phases of the Al-Zr system (the liquid phase, the fcc solid solution, and various orthorhombic stoichiometric compounds) are calculated using the modified embedded atom model (MEAM) in the second-nearest-neighbor formalism (2NN). The Al-Zr MEAM-2NN potential is parameterized in this work using ab initio and experimental data found in the literature for the AlZr3-L12 structure, while its predictive ability is confirmed for several other solid structures and for the liquid phase. The thermodynamic integration (TI) method is implemented in a general MC algorithm in order to evaluate the absolute Gibbs energy of the liquid and the fcc solutions. The entropy of mixing calculated from the TI method, combined to the enthalpy of mixing and the heat capacity data generated from MD/MC simulations performed in the isobaric-isothermal/canonical (NPT/NVT) ensembles are used to parameterize the Gibbs energy function of all the condensed phases in the Al-rich side of the Al-Zr system in a CALculation of PHAse Diagrams (CALPHAD) approach. The modified quasichemical model in the pair approximation (MQMPA) and the cluster variation method (CVM) in the tetrahedron approximation are used to define the Gibbs energy of the liquid and the fcc solid solution respectively for their entire range of composition. Thermodynamic and structural data generated from our MD/MC simulations are used as input data to parameterize these thermodynamic models. A detailed analysis of the validity and transferability of the Al-Zr MEAM-2NN potential is presented throughout our work by comparing the predicted properties obtained from this formalism with available ab initio and experimental data for both liquid and solid phases.

Integrable nonlinear Schrödinger system on a lattice with three structural elements in the unit cell

NASA Astrophysics Data System (ADS)

Vakhnenko, Oleksiy O.

2018-05-01

Developing the idea of increasing the number of structural elements in the unit cell of a quasi-one-dimensional lattice as applied to the semi-discrete integrable systems of nonlinear Schrödinger type, we construct the zero-curvature representation for the general integrable nonlinear system on a lattice with three structural elements in the unit cell. The integrability of the obtained general system permits to find explicitly a number of local conservation laws responsible for the main features of system dynamics and in particular for the so-called natural constraints separating the field variables into the basic and the concomitant ones. Thus, considering the reduction to the semi-discrete integrable system of nonlinear Schrödinger type, we revealed the essentially nontrivial impact of concomitant fields on the Poisson structure and on the whole Hamiltonian formulation of system dynamics caused by the nonzero background values of these fields. On the other hand, the zero-curvature representation of a general nonlinear system serves as an indispensable key to the dressing procedure of system integration based upon the Darboux transformation of the auxiliary linear problem and the implicit Bäcklund transformation of field variables. Due to the symmetries inherent to the six-component semi-discrete integrable nonlinear Schrödinger system with attractive-type nonlinearities, the Darboux-Bäcklund dressing scheme is shown to be simplified considerably, giving rise to the appropriately parameterized multi-component soliton solution consisting of six basic and four concomitant components.

Parameterizing microphysical effects on variances and covariances of moisture and heat content using a multivariate probability density function: a study with CLUBB (tag MVCS)

DOE PAGES

Griffin, Brian M.; Larson, Vincent E.

2016-11-25

Microphysical processes, such as the formation, growth, and evaporation of precipitation, interact with variability and covariances (e.g., fluxes) in moisture and heat content. For instance, evaporation of rain may produce cold pools, which in turn may trigger fresh convection and precipitation. These effects are usually omitted or else crudely parameterized at subgrid scales in weather and climate models.A more formal approach is pursued here, based on predictive, horizontally averaged equations for the variances, covariances, and fluxes of moisture and heat content. These higher-order moment equations contain microphysical source terms. The microphysics terms can be integrated analytically, given a suitably simplemore » warm-rain microphysics scheme and an approximate assumption about the multivariate distribution of cloud-related and precipitation-related variables. Performing the integrations provides exact expressions within an idealized context.A large-eddy simulation (LES) of a shallow precipitating cumulus case is performed here, and it indicates that the microphysical effects on (co)variances and fluxes can be large. In some budgets and altitude ranges, they are dominant terms. The analytic expressions for the integrals are implemented in a single-column, higher-order closure model. Interactive single-column simulations agree qualitatively with the LES. The analytic integrations form a parameterization of microphysical effects in their own right, and they also serve as benchmark solutions that can be compared to non-analytic integration methods.« less

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example

PubMed Central

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F.; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C.

2017-01-01

Background Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Objective Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Methods Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson’s disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Results Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Conclusion Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation. PMID:28441410

The terminal area simulation system. Volume 1: Theoretical formulation

NASA Technical Reports Server (NTRS)

Proctor, F. H.

1987-01-01

A three-dimensional numerical cloud model was developed for the general purpose of studying convective phenomena. The model utilizes a time splitting integration procedure in the numerical solution of the compressible nonhydrostatic primitive equations. Turbulence closure is achieved by a conventional first-order diagnostic approximation. Open lateral boundaries are incorporated which minimize wave reflection and which do not induce domain-wide mass trends. Microphysical processes are governed by prognostic equations for potential temperature water vapor, cloud droplets, ice crystals, rain, snow, and hail. Microphysical interactions are computed by numerous Orville-type parameterizations. A diagnostic surface boundary layer is parameterized assuming Monin-Obukhov similarity theory. The governing equation set is approximated on a staggered three-dimensional grid with quadratic-conservative central space differencing. Time differencing is approximated by the second-order Adams-Bashforth method. The vertical grid spacing may be either linear or stretched. The model domain may translate along with a convective cell, even at variable speeds.

Multiresponse modeling of variably saturated flow and isotope tracer transport for a hillslope experiment at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Scudeler, Carlotta; Pangle, Luke; Pasetto, Damiano; Niu, Guo-Yue; Volkmann, Till; Paniconi, Claudio; Putti, Mario; Troch, Peter

2016-10-01

This paper explores the challenges of model parameterization and process representation when simulating multiple hydrologic responses from a highly controlled unsaturated flow and transport experiment with a physically based model. The experiment, conducted at the Landscape Evolution Observatory (LEO), involved alternate injections of water and deuterium-enriched water into an initially very dry hillslope. The multivariate observations included point measures of water content and tracer concentration in the soil, total storage within the hillslope, and integrated fluxes of water and tracer through the seepage face. The simulations were performed with a three-dimensional finite element model that solves the Richards and advection-dispersion equations. Integrated flow, integrated transport, distributed flow, and distributed transport responses were successively analyzed, with parameterization choices at each step supported by standard model performance metrics. In the first steps of our analysis, where seepage face flow, water storage, and average concentration at the seepage face were the target responses, an adequate match between measured and simulated variables was obtained using a simple parameterization consistent with that from a prior flow-only experiment at LEO. When passing to the distributed responses, it was necessary to introduce complexity to additional soil hydraulic parameters to obtain an adequate match for the point-scale flow response. This also improved the match against point measures of tracer concentration, although model performance here was considerably poorer. This suggests that still greater complexity is needed in the model parameterization, or that there may be gaps in process representation for simulating solute transport phenomena in very dry soils.

Subgrid-scale parameterization and low-frequency variability: a response theory approach

NASA Astrophysics Data System (ADS)

Demaeyer, Jonathan; Vannitsem, Stéphane

2016-04-01

Weather and climate models are limited in the possible range of resolved spatial and temporal scales. However, due to the huge space- and time-scale ranges involved in the Earth System dynamics, the effects of many sub-grid processes should be parameterized. These parameterizations have an impact on the forecasts or projections. It could also affect the low-frequency variability present in the system (such as the one associated to ENSO or NAO). An important question is therefore to know what is the impact of stochastic parameterizations on the Low-Frequency Variability generated by the system and its model representation. In this context, we consider a stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012). We test this approach in the context of a low-order coupled ocean-atmosphere model, detailed in Vannitsem et al. (2015), for which a part of the atmospheric modes is considered as unresolved. A natural separation of the phase-space into a slow invariant set and its fast complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts. References: Vannitsem S, Demaeyer J, De Cruz L, Ghil M. 2015. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica D: Nonlinear Phenomena 309: 71-85. Wouters J, Lucarini V. 2012. Disentangling multi-level systems: averaging, correlations and memory. Journal of Statistical Mechanics: Theory and Experiment 2012(03): P03 003.

Controllers, observers, and applications thereof

NASA Technical Reports Server (NTRS)

Gao, Zhiqiang (Inventor); Zhou, Wankun (Inventor); Miklosovic, Robert (Inventor); Radke, Aaron (Inventor); Zheng, Qing (Inventor)

2011-01-01

Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also apply to state feedback and state observer based controllers, as well as linear active disturbance rejection (ADRC) controllers. Parameterization simplifies the use of ADRC. A discrete extended state observer (DESO) and a generalized extended state observer (GESO) are described. They improve the performance of the ESO and therefore ADRC. A tracking control algorithm is also described that improves the performance of the ADRC controller. A general algorithm is described for applying ADRC to multi-input multi-output systems. Several specific applications of the control systems and processes are disclosed.

Parameterizing Coefficients of a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

A method of parameterizing the coefficients of a dynamical system based of a proper orthogonal decomposition (POD) representing the flow dynamics of a viscous fluid has been introduced. (A brief description of POD is presented in the immediately preceding article.) The present parameterization method is intended to enable construction of the dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers. The need for this or a similar method arises as follows: A procedure that includes direct numerical simulation followed by POD, followed by Galerkin projection to a dynamical system has been proven to enable representation of flow dynamics by a low-dimensional model at the Reynolds number of the simulation. However, a more difficult task is to obtain models that are valid over a range of Reynolds numbers. Extrapolation of low-dimensional models by use of straightforward Reynolds-number-based parameter continuation has proven to be inadequate for successful prediction of flows. A key part of the problem of constructing a dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers is the problem of understanding and providing for the variation of the coefficients of the dynamical system with the Reynolds number. Prior methods do not enable capture of temporal dynamics over ranges of Reynolds numbers in low-dimensional models, and are not even satisfactory when large numbers of modes are used. The basic idea of the present method is to solve the problem through a suitable parameterization of the coefficients of the dynamical system. The parameterization computations involve utilization of the transfer of kinetic energy between modes as a function of Reynolds number. The thus-parameterized dynamical system accurately predicts the flow dynamics and is applicable to a range of flow problems in the dynamical regime around the Hopf bifurcation. Parameter-continuation software can be used on the parameterized dynamical system to derive a bifurcation diagram that accurately predicts the temporal flow behavior.

Evaluation of the WRF-Urban Modeling System Coupled to Noah and Noah-MP Land Surface Models Over a Semiarid Urban Environment

NASA Astrophysics Data System (ADS)

Salamanca, Francisco; Zhang, Yizhou; Barlage, Michael; Chen, Fei; Mahalov, Alex; Miao, Shiguang

2018-03-01

We have augmented the existing capabilities of the integrated Weather Research and Forecasting (WRF)-urban modeling system by coupling three urban canopy models (UCMs) available in the WRF model with the new community Noah with multiparameterization options (Noah-MP) land surface model (LSM). The WRF-urban modeling system's performance has been evaluated by conducting six numerical experiments at high spatial resolution (1 km horizontal grid spacing) during a 15 day clear-sky summertime period for a semiarid urban environment. To assess the relative importance of representing urban surfaces, three different urban parameterizations are used with the Noah and Noah-MP LSMs, respectively, over the two major cities of Arizona: Phoenix and Tucson metropolitan areas. Our results demonstrate that Noah-MP reproduces somewhat better than Noah the daily evolution of surface skin temperature and near-surface air temperature (especially nighttime temperature) and wind speed. Concerning the urban areas, bulk urban parameterization overestimates nighttime 2 m air temperature compared to the single-layer and multilayer UCMs that reproduce more accurately the daily evolution of near-surface air temperature. Regarding near-surface wind speed, only the multilayer UCM was able to reproduce realistically the daily evolution of wind speed, although maximum winds were slightly overestimated, while both the single-layer and bulk urban parameterizations overestimated wind speed considerably. Based on these results, this paper demonstrates that the new community Noah-MP LSM coupled to an UCM is a promising physics-based predictive modeling tool for urban applications.

“Using Statistical Comparisons between SPartICus Cirrus Microphysical Measurements, Detailed Cloud Models, and GCM Cloud Parameterizations to Understand Physical Processes Controlling Cirrus Properties and to Improve the Cloud Parameterizations”

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woods, Sarah

2015-12-01

The dual objectives of this project were improving our basic understanding of processes that control cirrus microphysical properties and improvement of the representation of these processes in the parameterizations. A major effort in the proposed research was to integrate, calibrate, and better understand the uncertainties in all of these measurements.

Introducing Convective Cloud Microphysics to a Deep Convection Parameterization Facilitating Aerosol Indirect Effects

NASA Astrophysics Data System (ADS)

Alapaty, K.; Zhang, G. J.; Song, X.; Kain, J. S.; Herwehe, J. A.

2012-12-01

Short lived pollutants such as aerosols play an important role in modulating not only the radiative balance but also cloud microphysical properties and precipitation rates. In the past, to understand the interactions of aerosols with clouds, several cloud-resolving modeling studies were conducted. These studies indicated that in the presence of anthropogenic aerosols, single-phase deep convection precipitation is reduced or suppressed. On the other hand, anthropogenic aerosol pollution led to enhanced precipitation for mixed-phase deep convective clouds. To date, there have not been many efforts to incorporate such aerosol indirect effects (AIE) in mesoscale models or global models that use parameterization schemes for deep convection. Thus, the objective of this work is to implement a diagnostic cloud microphysical scheme directly into a deep convection parameterization facilitating aerosol indirect effects in the WRF-CMAQ integrated modeling systems. Major research issues addressed in this study are: What is the sensitivity of a deep convection scheme to cloud microphysical processes represented by a bulk double-moment scheme? How close are the simulated cloud water paths as compared to observations? Does increased aerosol pollution lead to increased precipitation for mixed-phase clouds? These research questions are addressed by performing several WRF simulations using the Kain-Fritsch convection parameterization and a diagnostic cloud microphysical scheme. In the first set of simulations (control simulations) the WRF model is used to simulate two scenarios of deep convection over the continental U.S. during two summer periods at 36 km grid resolution. In the second set, these simulations are repeated after incorporating a diagnostic cloud microphysical scheme to study the impacts of inclusion of cloud microphysical processes. Finally, in the third set, aerosol concentrations simulated by the CMAQ modeling system are supplied to the embedded cloud microphysical scheme to study impacts of aerosol concentrations on precipitation and radiation fields. Observations available from the ARM microbase data, the SURFRAD network, GOES imagery, and other reanalysis and measurements will be used to analyze the impacts of a cloud microphysical scheme and aerosol concentrations on parameterized convection.

A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations

NASA Astrophysics Data System (ADS)

Cariolle, D.; Teyssèdre, H.

2007-01-01

This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory works. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the resolution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small. The model also reproduces fairly well the polar ozone variability, with notably the formation of "ozone holes" in the southern hemisphere with amplitudes and seasonal evolutions that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone contents inside the polar vortex of the southern hemisphere over longer periods in spring time. It is concluded that for the study of climatic scenarios or the assimilation of ozone data, the present parameterization gives an interesting alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

Development of a Cloud Resolving Model for Heterogeneous Supercomputers

NASA Astrophysics Data System (ADS)

Sreepathi, S.; Norman, M. R.; Pal, A.; Hannah, W.; Ponder, C.

2017-12-01

A cloud resolving climate model is needed to reduce major systematic errors in climate simulations due to structural uncertainty in numerical treatments of convection - such as convective storm systems. This research describes the porting effort to enable SAM (System for Atmosphere Modeling) cloud resolving model on heterogeneous supercomputers using GPUs (Graphical Processing Units). We have isolated a standalone configuration of SAM that is targeted to be integrated into the DOE ACME (Accelerated Climate Modeling for Energy) Earth System model. We have identified key computational kernels from the model and offloaded them to a GPU using the OpenACC programming model. Furthermore, we are investigating various optimization strategies intended to enhance GPU utilization including loop fusion/fission, coalesced data access and loop refactoring to a higher abstraction level. We will present early performance results, lessons learned as well as optimization strategies. The computational platform used in this study is the Summitdev system, an early testbed that is one generation removed from Summit, the next leadership class supercomputer at Oak Ridge National Laboratory. The system contains 54 nodes wherein each node has 2 IBM POWER8 CPUs and 4 NVIDIA Tesla P100 GPUs. This work is part of a larger project, ACME-MMF component of the U.S. Department of Energy(DOE) Exascale Computing Project. The ACME-MMF approach addresses structural uncertainty in cloud processes by replacing traditional parameterizations with cloud resolving "superparameterization" within each grid cell of global climate model. Super-parameterization dramatically increases arithmetic intensity, making the MMF approach an ideal strategy to achieve good performance on emerging exascale computing architectures. The goal of the project is to integrate superparameterization into ACME, and explore its full potential to scientifically and computationally advance climate simulation and prediction.

Linear units improve articulation between social and physical constructs: An example from caregiver parameterization for children supported by complex medical technologies

NASA Astrophysics Data System (ADS)

Bezruczko, N.; Stanley, T.; Battle, M.; Latty, C.

2016-11-01

Despite broad sweeping pronouncements by international research organizations that social sciences are being integrated into global research programs, little attention has been directed toward obstacles blocking productive collaborations. In particular, social sciences routinely implement nonlinear, ordinal measures, which fundamentally inhibit integration with overarching scientific paradigms. The widely promoted general linear model in contemporary social science methods is largely based on untransformed scores and ratings, which are neither objective nor linear. This issue has historically separated physical and social sciences, which this report now asserts is unnecessary. In this research, nonlinear, subjective caregiver ratings of confidence to care for children supported by complex, medical technologies were transformed to an objective scale defined by logits (N=70). Transparent linear units from this transformation provided foundational insights into measurement properties of a social- humanistic caregiving construct, which clarified physical and social caregiver implications. Parameterized items and ratings were also subjected to multivariate hierarchical analysis, then decomposed to demonstrate theoretical coherence (R2 >.50), which provided further support for convergence of mathematical parameterization, physical expectations, and a social-humanistic construct. These results present substantial support for improving integration of social sciences with contemporary scientific research programs by emphasizing construction of common variables with objective, linear units.

Parameterized reduced-order models using hyper-dual numbers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fike, Jeffrey A.; Brake, Matthew Robert

2013-10-01

The goal of most computational simulations is to accurately predict the behavior of a real, physical system. Accurate predictions often require very computationally expensive analyses and so reduced order models (ROMs) are commonly used. ROMs aim to reduce the computational cost of the simulations while still providing accurate results by including all of the salient physics of the real system in the ROM. However, real, physical systems often deviate from the idealized models used in simulations due to variations in manufacturing or other factors. One approach to this issue is to create a parameterized model in order to characterize themore » effect of perturbations from the nominal model on the behavior of the system. This report presents a methodology for developing parameterized ROMs, which is based on Craig-Bampton component mode synthesis and the use of hyper-dual numbers to calculate the derivatives necessary for the parameterization.« less

Sensitivity of Coupled Tropical Pacific Model Biases to Convective Parameterization in CESM1

NASA Astrophysics Data System (ADS)

Woelfle, M. D.; Yu, S.; Bretherton, C. S.; Pritchard, M. S.

2018-01-01

Six month coupled hindcasts show the central equatorial Pacific cold tongue bias development in a GCM to be sensitive to the atmospheric convective parameterization employed. Simulations using the standard configuration of the Community Earth System Model version 1 (CESM1) develop a cold bias in equatorial Pacific sea surface temperatures (SSTs) within the first two months of integration due to anomalous ocean advection driven by overly strong easterly surface wind stress along the equator. Disabling the deep convection parameterization enhances the zonal pressure gradient leading to stronger zonal wind stress and a stronger equatorial SST bias, highlighting the role of pressure gradients in determining the strength of the cold bias. Superparameterized hindcasts show reduced SST bias in the cold tongue region due to a reduction in surface easterlies despite simulating an excessively strong low-level jet at 1-1.5 km elevation. This reflects inadequate vertical mixing of zonal momentum from the absence of convective momentum transport in the superparameterized model. Standard CESM1simulations modified to omit shallow convective momentum transport reproduce the superparameterized low-level wind bias and associated equatorial SST pattern. Further superparameterized simulations using a three-dimensional cloud resolving model capable of producing realistic momentum transport simulate a cold tongue similar to the default CESM1. These findings imply convective momentum fluxes may be an underappreciated mechanism for controlling the strength of the equatorial cold tongue. Despite the sensitivity of equatorial SST to these changes in convective parameterization, the east Pacific double-Intertropical Convergence Zone rainfall bias persists in all simulations presented in this study.

3D models mapping optimization through an integrated parameterization approach: cases studies from Ravenna

NASA Astrophysics Data System (ADS)

Cipriani, L.; Fantini, F.; Bertacchi, S.

2014-06-01

Image-based modelling tools based on SfM algorithms gained great popularity since several software houses provided applications able to achieve 3D textured models easily and automatically. The aim of this paper is to point out the importance of controlling models parameterization process, considering that automatic solutions included in these modelling tools can produce poor results in terms of texture utilization. In order to achieve a better quality of textured models from image-based modelling applications, this research presents a series of practical strategies aimed at providing a better balance between geometric resolution of models from passive sensors and their corresponding (u,v) map reference systems. This aspect is essential for the achievement of a high-quality 3D representation, since "apparent colour" is a fundamental aspect in the field of Cultural Heritage documentation. Complex meshes without native parameterization have to be "flatten" or "unwrapped" in the (u,v) parameter space, with the main objective to be mapped with a single image. This result can be obtained by using two different strategies: the former automatic and faster, while the latter manual and time-consuming. Reverse modelling applications provide automatic solutions based on splitting the models by means of different algorithms, that produce a sort of "atlas" of the original model in the parameter space, in many instances not adequate and negatively affecting the overall quality of representation. Using in synergy different solutions, ranging from semantic aware modelling techniques to quad-dominant meshes achieved using retopology tools, it is possible to obtain a complete control of the parameterization process.

A revised radiation package of G-packed McICA and two-stream approximation: Performance evaluation in a global weather forecasting model

NASA Astrophysics Data System (ADS)

Baek, Sunghye

2017-07-01

For more efficient and accurate computation of radiative flux, improvements have been achieved in two aspects, integration of the radiative transfer equation over space and angle. First, the treatment of the Monte Carlo-independent column approximation (MCICA) is modified focusing on efficiency using a reduced number of random samples ("G-packed") within a reconstructed and unified radiation package. The original McICA takes 20% of CPU time of radiation in the Global/Regional Integrated Model systems (GRIMs). The CPU time consumption of McICA is reduced by 70% without compromising accuracy. Second, parameterizations of shortwave two-stream approximations are revised to reduce errors with respect to the 16-stream discrete ordinate method. Delta-scaled two-stream approximation (TSA) is almost unanimously used in Global Circulation Model (GCM) but contains systematic errors which overestimate forward peak scattering as solar elevation decreases. These errors are alleviated by adjusting the parameterizations of each scattering element—aerosol, liquid, ice and snow cloud particles. Parameterizations are determined with 20,129 atmospheric columns of the GRIMs data and tested with 13,422 independent data columns. The result shows that the root-mean-square error (RMSE) over the all atmospheric layers is decreased by 39% on average without significant increase in computational time. Revised TSA developed and validated with a separate one-dimensional model is mounted on GRIMs for mid-term numerical weather forecasting. Monthly averaged global forecast skill scores are unchanged with revised TSA but the temperature at lower levels of the atmosphere (pressure ≥ 700 hPa) is slightly increased (< 0.5 K) with corrected atmospheric absorption.

Predictive Compensator Optimization for Head Tracking Lag in Virtual Environments

NASA Technical Reports Server (NTRS)

Adelstein, Barnard D.; Jung, Jae Y.; Ellis, Stephen R.

2001-01-01

We examined the perceptual impact of plant noise parameterization for Kalman Filter predictive compensation of time delays intrinsic to head tracked virtual environments (VEs). Subjects were tested in their ability to discriminate between the VE system's minimum latency and conditions in which artificially added latency was then predictively compensated back to the system minimum. Two head tracking predictors were parameterized off-line according to cost functions that minimized prediction errors in (1) rotation, and (2) rotation projected into translational displacement with emphasis on higher frequency human operator noise. These predictors were compared with a parameterization obtained from the VE literature for cost function (1). Results from 12 subjects showed that both parameterization type and amount of compensated latency affected discrimination. Analysis of the head motion used in the parameterizations and the subsequent discriminability results suggest that higher frequency predictor artifacts are contributory cues for discriminating the presence of predictive compensation.

Regularized wave equation migration for imaging and data reconstruction

NASA Astrophysics Data System (ADS)

Kaplan, Sam T.

The reflection seismic experiment results in a measurement (reflection seismic data) of the seismic wavefield. The linear Born approximation to the seismic wavefield leads to a forward modelling operator that we use to approximate reflection seismic data in terms of a scattering potential. We consider approximations to the scattering potential using two methods: the adjoint of the forward modelling operator (migration), and regularized numerical inversion using the forward and adjoint operators. We implement two parameterizations of the forward modelling and migration operators: source-receiver and shot-profile. For both parameterizations, we find requisite Green's function using the split-step approximation. We first develop the forward modelling operator, and then find the adjoint (migration) operator by recognizing a Fredholm integral equation of the first kind. The resulting numerical system is generally under-determined, requiring prior information to find a solution. In source-receiver migration, the parameterization of the scattering potential is understood using the migration imaging condition, and this encourages us to apply sparse prior models to the scattering potential. To that end, we use both a Cauchy prior and a mixed Cauchy-Gaussian prior, finding better resolved estimates of the scattering potential than are given by the adjoint. In shot-profile migration, the parameterization of the scattering potential has its redundancy in multiple active energy sources (i.e. shots). We find that a smallest model regularized inverse representation of the scattering potential gives a more resolved picture of the earth, as compared to the simpler adjoint representation. The shot-profile parameterization allows us to introduce a joint inversion to further improve the estimate of the scattering potential. Moreover, it allows us to introduce a novel data reconstruction algorithm so that limited data can be interpolated/extrapolated. The linearized operators are expensive, encouraging their parallel implementation. For the source-receiver parameterization of the scattering potential this parallelization is non-trivial. Seismic data is typically corrupted by various types of noise. Sparse coding can be used to suppress noise prior to migration. It is a method that stems from information theory and that we apply to noise suppression in seismic data.

A new parameterization for surface ocean light attenuation in Earth System Models: assessing the impact of light absorption by colored detrital material

NASA Astrophysics Data System (ADS)

Kim, G. E.; Pradal, M.-A.; Gnanadesikan, A.

2015-03-01

Light limitation can affect the distribution of biota and nutrients in the ocean. Light absorption by colored detrital material (CDM) was included in a fully coupled Earth System Model using a new parameterization for shortwave attenuation. Two model runs were conducted, with and without light attenuation by CDM. In a global average sense, greater light limitation associated with CDM increased surface chlorophyll, biomass and nutrients together. These changes can be attributed to the movement of biological productivity higher up the water column, which increased surface chlorophyll and biomass while simultaneously decreasing total biomass. Meanwhile, the reduction in biomass resulted in greater nutrient availability throughout the water column. Similar results were found on a regional scale in an analysis of the oceans by biome. In coastal regions, surface chlorophyll increased by 35% while total integrated phytoplankton biomass diminished by 18%. The largest relative increases in modeled surface chlorophyll and biomass in the open ocean were found in the equatorial biomes, while largest decreases in depth-integrated biomass and chlorophyll were found in the subpolar and polar biomes. This mismatch of surface and subsurface trends and their regional dependence was analyzed by comparing the competing factors of diminished light availability and increased nutrient availability on phytoplankton growth in the upper 200 m. Overall, increases in surface biomass were expected to accompany greater nutrient uptake and therefore diminish surface nutrients, but changes in light limitation decoupled trends between these two variables. Understanding changes in biological productivity requires both surface and depth-resolved information. Surface trends may be minimal or of the opposite sign to depth-integrated amounts, depending on the vertical structure of phytoplankton abundance.

Error in Radar-Derived Soil Moisture due to Roughness Parameterization: An Analysis Based on Synthetical Surface Profiles

PubMed Central

Lievens, Hans; Vernieuwe, Hilde; Álvarez-Mozos, Jesús; De Baets, Bernard; Verhoest, Niko E.C.

2009-01-01

In the past decades, many studies on soil moisture retrieval from SAR demonstrated a poor correlation between the top layer soil moisture content and observed backscatter coefficients, which mainly has been attributed to difficulties involved in the parameterization of surface roughness. The present paper describes a theoretical study, performed on synthetical surface profiles, which investigates how errors on roughness parameters are introduced by standard measurement techniques, and how they will propagate through the commonly used Integral Equation Model (IEM) into a corresponding soil moisture retrieval error for some of the currently most used SAR configurations. Key aspects influencing the error on the roughness parameterization and consequently on soil moisture retrieval are: the length of the surface profile, the number of profile measurements, the horizontal and vertical accuracy of profile measurements and the removal of trends along profiles. Moreover, it is found that soil moisture retrieval with C-band configuration generally is less sensitive to inaccuracies in roughness parameterization than retrieval with L-band configuration. PMID:22399956

R-parametrization and its role in classification of linear multivariable feedback systems

NASA Technical Reports Server (NTRS)

Chen, Robert T. N.

1988-01-01

A classification of all the compensators that stabilize a given general plant in a linear, time-invariant multi-input, multi-output feedback system is developed. This classification, along with the associated necessary and sufficient conditions for stability of the feedback system, is achieved through the introduction of a new parameterization, referred to as R-Parameterization, which is a dual of the familiar Q-Parameterization. The classification is made to the stability conditions of the compensators and the plant by themselves; and necessary and sufficient conditions are based on the stability of Q and R themselves.

The Grell-Freitas Convection Parameterization: Recent Developments and Applications Within the NASA GEOS Global Model

NASA Technical Reports Server (NTRS)

Freitas, Saulo R.; Grell, Georg; Molod, Andrea; Thompson, Matthew A.

2017-01-01

We implemented and began to evaluate an alternative convection parameterization for the NASA Goddard Earth Observing System (GEOS) global model. The parameterization is based on the mass flux approach with several closures, for equilibrium and non-equilibrium convection, and includes scale and aerosol awareness functionalities. Recently, the scheme has been extended to a tri-modal spectral size approach to simulate the transition from shallow, mid, and deep convection regimes. In addition, the inclusion of a new closure for non-equilibrium convection resulted in a substantial gain of realism in model simulation of the diurnal cycle of convection over the land. Here, we briefly introduce the recent developments, implementation, and preliminary results of this parameterization in the NASA GEOS modeling system.

Parameterized LMI Based Diagonal Dominance Compensator Study for Polynomial Linear Parameter Varying System

NASA Astrophysics Data System (ADS)

Han, Xiaobao; Li, Huacong; Jia, Qiusheng

2017-12-01

For dynamic decoupling of polynomial linear parameter varying(PLPV) system, a robust dominance pre-compensator design method is given. The parameterized precompensator design problem is converted into an optimal problem constrained with parameterized linear matrix inequalities(PLMI) by using the conception of parameterized Lyapunov function(PLF). To solve the PLMI constrained optimal problem, the precompensator design problem is reduced into a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a new constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator is achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation on a turbofan engine PLPV model.

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE PAGES

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; ...

2017-09-14

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Parameterized reduced order models from a single mesh using hyper-dual numbers

NASA Astrophysics Data System (ADS)

Brake, M. R. W.; Fike, J. A.; Topping, S. D.

2016-06-01

In order to assess the predicted performance of a manufactured system, analysts must consider random variations (both geometric and material) in the development of a model, instead of a single deterministic model of an idealized geometry with idealized material properties. The incorporation of random geometric variations, however, potentially could necessitate the development of thousands of nearly identical solid geometries that must be meshed and separately analyzed, which would require an impractical number of man-hours to complete. This research advances a recent approach to uncertainty quantification by developing parameterized reduced order models. These parameterizations are based upon Taylor series expansions of the system's matrices about the ideal geometry, and a component mode synthesis representation for each linear substructure is used to form an efficient basis with which to study the system. The numerical derivatives required for the Taylor series expansions are obtained via hyper-dual numbers, and are compared to parameterized models constructed with finite difference formulations. The advantage of using hyper-dual numbers is two-fold: accuracy of the derivatives to machine precision, and the need to only generate a single mesh of the system of interest. The theory is applied to a stepped beam system in order to demonstrate proof of concept. The results demonstrate that the hyper-dual number multivariate parameterization of geometric variations, which largely are neglected in the literature, are accurate for both sensitivity and optimization studies. As model and mesh generation can constitute the greatest expense of time in analyzing a system, the foundation to create a parameterized reduced order model based off of a single mesh is expected to reduce dramatically the necessary time to analyze multiple realizations of a component's possible geometry.

A Global Data Assimilation System for Atmospheric Aerosol

NASA Technical Reports Server (NTRS)

daSilva, Arlindo

1999-01-01

We will give an overview of an aerosol data assimilation system which combines advances in remote sensing of atmospheric aerosols, aerosol modeling and data assimilation methodology to produce high spatial and temporal resolution 3D aerosol fields. Initially, the Goddard Aerosol Assimilation System (GAAS) will assimilate TOMS, AVHRR and AERONET observations; later we will include MODIS and MISR. This data assimilation capability will allows us to integrate complementing aerosol observations from these platforms, enabling the development of an assimilated aerosol climatology as well as a global aerosol forecasting system in support of field campaigns. Furthermore, this system provides an interactive retrieval framework for each aerosol observing satellites, in particular TOMS and AVHRR. The Goddard Aerosol Assimilation System (GAAS) takes advantage of recent advances in constituent data assimilation at DAO, including flow dependent parameterizations of error covariances and the proper consideration of model bias. For its prognostic transport model, GAAS will utilize the Goddard Ozone, Chemistry, Aerosol, Radiation and Transport (GOCART) model developed at NASA/GSFC Codes 916 and 910.3. GOCART includes the Lin-Rood flux-form, semi-Langrangian transport model with parameterized aerosol chemistry and physical processes for absorbing (dust and black carbon) and non-absorbing aerosols (sulfate and organic carbon). Observations and model fields are combined using a constituent version of DAO's Physical-space Statistical Analysis System (PSAS), including its adaptive quality control system. In this talk we describe the main components of this assimilation system and present preliminary results obtained by assimilating TOMS data.

A Heuristic Parameterization for the Integrated Vertical Overlap of Cumulus and Stratus

NASA Astrophysics Data System (ADS)

Park, Sungsu

2017-10-01

The author developed a heuristic parameterization to handle the contrasting vertical overlap structures of cumulus and stratus in an integrated way. The parameterization assumes that cumulus is maximum-randomly overlapped with adjacent cumulus; stratus is maximum-randomly overlapped with adjacent stratus; and radiation and precipitation areas at each model interface are grouped into four categories, that is, convective, stratiform, mixed, and clear areas. For simplicity, thermodynamic scalars within individual portions of cloud, radiation, and precipitation areas are assumed to be internally homogeneous. The parameterization was implemented into the Seoul National University Atmosphere Model version 0 (SAM0) in an offline mode and tested over the globe. The offline control simulation reasonably reproduces the online surface precipitation flux and longwave cloud radiative forcing (LWCF). Although the cumulus fraction is much smaller than the stratus fraction, cumulus dominantly contributes to precipitation production in the tropics. For radiation, however, stratus is dominant. Compared with the maximum overlap, the random overlap of stratus produces stronger LWCF and, surprisingly, more precipitation flux due to less evaporation of convective precipitation. Compared with the maximum overlap, the random overlap of cumulus simulates stronger LWCF and weaker precipitation flux. Compared with the control simulation with separate cumulus and stratus, the simulation with a single-merged cloud substantially enhances the LWCF in the tropical deep convection and midlatitude storm track regions. The process-splitting treatment of convective and stratiform precipitation with an independent precipitation approximation (IPA) simulates weaker surface precipitation flux than the control simulation in the tropical region.

Radar and microphysical characteristics of convective storms simulated from a numerical model using a new microphysical parameterization

NASA Technical Reports Server (NTRS)

Ferrier, Brad S.; Tao, Wei-Kuo; Simpson, Joanne

1991-01-01

The basic features of a new and improved bulk-microphysical parameterization capable of simulating the hydrometeor structure of convective systems in all types of large-scale environments (with minimal adjustment of coefficients) are studied. Reflectivities simulated from the model are compared with radar observations of an intense midlatitude convective system. Simulated reflectivities using the novel four-class ice scheme with a microphysical parameterization rain distribution at 105 min are illustrated. Preliminary results indicate that this new ice scheme works efficiently in simulating midlatitude continental storms.

Parameterizing by the Number of Numbers

NASA Astrophysics Data System (ADS)

Fellows, Michael R.; Gaspers, Serge; Rosamond, Frances A.

The usefulness of parameterized algorithmics has often depended on what Niedermeier has called "the art of problem parameterization". In this paper we introduce and explore a novel but general form of parameterization: the number of numbers. Several classic numerical problems, such as Subset Sum, Partition, 3-Partition, Numerical 3-Dimensional Matching, and Numerical Matching with Target Sums, have multisets of integers as input. We initiate the study of parameterizing these problems by the number of distinct integers in the input. We rely on an FPT result for Integer Linear Programming Feasibility to show that all the above-mentioned problems are fixed-parameter tractable when parameterized in this way. In various applied settings, problem inputs often consist in part of multisets of integers or multisets of weighted objects (such as edges in a graph, or jobs to be scheduled). Such number-of-numbers parameterized problems often reduce to subproblems about transition systems of various kinds, parameterized by the size of the system description. We consider several core problems of this kind relevant to number-of-numbers parameterization. Our main hardness result considers the problem: given a non-deterministic Mealy machine M (a finite state automaton outputting a letter on each transition), an input word x, and a census requirement c for the output word specifying how many times each letter of the output alphabet should be written, decide whether there exists a computation of M reading x that outputs a word y that meets the requirement c. We show that this problem is hard for W[1]. If the question is whether there exists an input word x such that a computation of M on x outputs a word that meets c, the problem becomes fixed-parameter tractable.

Extensions of different type parameterized inequalities for generalized [Formula: see text]-preinvex mappings via k-fractional integrals.

PubMed

Zhang, Yao; Du, Ting-Song; Wang, Hao; Shen, Yan-Jun; Kashuri, Artion

2018-01-01

The authors discover a general k -fractional integral identity with multi-parameters for twice differentiable functions. By using this integral equation, the authors derive some new bounds on Hermite-Hadamard's and Simpson's inequalities for generalized [Formula: see text]-preinvex functions through k -fractional integrals. By taking the special parameter values for various suitable choices of function h , some interesting results are also obtained.

A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations

NASA Astrophysics Data System (ADS)

Cariolle, D.; Teyssèdre, H.

2007-05-01

This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2-D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory work. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the solution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results from the two versions show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small, of the order of 10%. The model also reproduces fairly well the polar ozone variability, notably the formation of "ozone holes" in the Southern Hemisphere with amplitudes and a seasonal evolution that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone content inside the polar vortex of the Southern Hemisphere over longer periods in spring time. It is concluded that for the study of climate scenarios or the assimilation of ozone data, the present parameterization gives a valuable alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models.

Integrating Cloud Processes in the Community Atmosphere Model, Version 5.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, S.; Bretherton, Christopher S.; Rasch, Philip J.

2014-09-15

This paper provides a description on the parameterizations of global cloud system in CAM5. Compared to the previous versions, CAM5 cloud parameterization has the following unique characteristics: (1) a transparent cloud macrophysical structure that has horizontally non-overlapped deep cumulus, shallow cumulus and stratus in each grid layer, each of which has own cloud fraction, mass and number concentrations of cloud liquid droplets and ice crystals, (2) stratus-radiation-turbulence interaction that allows CAM5 to simulate marine stratocumulus solely from grid-mean RH without relying on the stability-based empirical empty stratus, (3) prognostic treatment of the number concentrations of stratus liquid droplets and icemore » crystals with activated aerosols and detrained in-cumulus condensates as the main sources and evaporation-sedimentation-precipitation of stratus condensate as the main sinks, and (4) radiatively active cumulus. By imposing consistency between diagnosed stratus fraction and prognosed stratus condensate, CAM5 is free from empty or highly-dense stratus at the end of stratus macrophysics. CAM5 also prognoses mass and number concentrations of various aerosol species. Thanks to the aerosol activation and the parameterizations of the radiation and stratiform precipitation production as a function of the droplet size, CAM5 simulates various aerosol indirect effects associated with stratus as well as direct effects, i.e., aerosol controls both the radiative and hydrological budgets. Detailed analysis of various simulations revealed that CAM5 is much better than CAM3/4 in the global performance as well as the physical formulation. However, several problems were also identifed, which can be attributed to inappropriate regional tuning, inconsistency between various physics parameterizations, and incomplete model physics. Continuous efforts are going on to further improve CAM5.« less

Integrated spatiotemporal characterization of dust sources and outbreaks in Central and East Asia

NASA Astrophysics Data System (ADS)

Darmenova, Kremena T.

The potential of atmospheric dust aerosols to modify the Earth's environment and climate has been recognized for some time. However, predicting the diverse impact of dust has several significant challenges. One is to quantify the complex spatial and temporal variability of dust burden in the atmosphere. Another is to quantify the fraction of dust originating from human-made sources. This thesis focuses on the spatiotemporal characterization of sources and dust outbreaks in Central and East Asia by integrating ground-based data, satellite multisensor observations, and modeling. A new regional dust modeling system capable of operating over a span of scales was developed. The modeling system consists of a dust module DuMo, which incorporates several dust emission schemes of different complexity, and the PSU/NCAR mesoscale model MM5, which offers a variety of physical parameterizations and flexible nesting capability. The modeling system was used to perform for the first time a comprehensive study of the timing, duration, and intensity of individual dust events in Central and East Asia. Determining the uncertainties caused by the choice of model physics, especially the boundary layer parameterization, and the dust production scheme was the focus of our study. Implications to assessments of the anthropogenic dust fraction in these regions were also addressed. Focusing on Spring 2001, an analysis of routine surface meteorological observations and satellite multi-sensor data was carried out in conjunction with modeling to determine the extent to which integrated data set can be used to characterize the spatiotemporal distribution of dust plumes at a range of temporal scales, addressing the active dust sources in China and Mongolia, mid-range transport and trans-Pacific, long-range transport of dust outbreaks on a case-by-case basis. This work demonstrates that adequate and consistent characterization of individual dust events is central to establishing a reliable climatology, ultimately leading to improved assessments of dust impacts on the environment and climate. This will also help to identify the appropriate temporal and spatial scales for adequate intercomparison between model results and observational data as well as for developing an integrated analysis methodology for dust studies.

Toward computational models of magma genesis and geochemical transport in subduction zones

NASA Astrophysics Data System (ADS)

Katz, R.; Spiegelman, M.

2003-04-01

The chemistry of material erupted from subduction-related volcanoes records important information about the processes that lead to its formation at depth in the Earth. Self-consistent numerical simulations provide a useful tool for interpreting this data as they can explore the non-linear feedbacks between processes that control the generation and transport of magma. A model capable of addressing such issues should include three critical components: (1) a variable viscosity solid flow solver with smooth and accurate pressure and velocity fields, (2) a parameterization of mass transfer reactions between the solid and fluid phases and (3) a consistent fluid flow and reactive transport code. We report on progress on each of these parts. To handle variable-viscosity solid-flow in the mantle wedge, we are adapting a Patankar-based FAS multigrid scheme developed by Albers (2000, J. Comp. Phys.). The pressure field in this scheme is the solution to an elliptic equation on a staggered grid. Thus we expect computed pressure fields to have smooth gradient fields suitable for porous flow calculations, unlike those of commonly used penalty-method schemes. Use of a temperature and strain-rate dependent mantle rheology has been shown to have important consequences for the pattern of flow and the temperature structure in the wedge. For computing thermal structure we present a novel scheme that is a hybrid of Crank-Nicholson (CN) and Semi-Lagrangian (SL) methods. We have tested the SLCN scheme on advection across a broad range of Peclet numbers and show the results. This scheme is also useful for low-diffusivity chemical transport. We also describe our parameterization of hydrous mantle melting [Katz et. al., G3, 2002 in review]. This parameterization is designed to capture the melting behavior of peridotite--water systems over parameter ranges relevant to subduction. The parameterization incorporates data and intuition gained from laboratory experiments and thermodynamic calculations yet it remains flexible and computationally efficient. Given accurate solid-flow fields, a parameterization of hydrous melting and a method for calculating thermal structure (enforcing energy conservation), the final step is to integrate these components into a consistent framework for reactive-flow and chemical transport in deformable porous media. We present preliminary results for reactive flow in 2-D static and upwelling columns and discuss possible mechanical and chemical consequences of open system reactive melting with application to arcs.

Quantifying the economic risks of climate change

NASA Astrophysics Data System (ADS)

Diaz, Delavane; Moore, Frances

2017-11-01

Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost-benefit integrated assessment models, with guidance for future work.

Sensitivity of Pacific Cold Tongue and Double-ITCZ Bias to Convective Parameterization

NASA Astrophysics Data System (ADS)

Woelfle, M.; Bretherton, C. S.; Pritchard, M. S.; Yu, S.

2016-12-01

Many global climate models struggle to accurately simulate annual mean precipitation and sea surface temperature (SST) fields in the tropical Pacific basin. Precipitation biases are dominated by the double intertropical convergence zone (ITCZ) bias where models exhibit precipitation maxima straddling the equator while only a single Northern Hemispheric maximum exists in observations. The major SST bias is the enhancement of the equatorial cold tongue. A series of coupled model simulations are used to investigate the sensitivity of the bias development to convective parameterization. Model components are initialized independently prior to coupling to allow analysis of the transient response of the system directly following coupling. These experiments show precipitation and SST patterns to be highly sensitive to convective parameterization. Simulations in which the deep convective parameterization is disabled forcing all convection to be resolved by the shallow convection parameterization showed a degradation in both the cold tongue and double-ITCZ biases as precipitation becomes focused into off-equatorial regions of local SST maxima. Simulations using superparameterization in place of traditional cloud parameterizations showed a reduced cold tongue bias at the expense of additional precipitation biases. The equatorial SST responses to changes in convective parameterization are driven by changes in near equatorial zonal wind stress. The sensitivity of convection to SST is important in determining the precipitation and wind stress fields. However, differences in convective momentum transport also play a role. While no significant improvement is seen in these simulations of the double-ITCZ, the system's sensitivity to these changes reaffirm that improved convective parameterizations may provide an avenue for improving simulations of tropical Pacific precipitation and SST.

Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system

NASA Astrophysics Data System (ADS)

Dong, J.; Ek, M. B.; Wei, H.; Meng, J.

2017-12-01

Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).

Protoplanetary disk formation and evolution models: DM Tau and GM Aur

NASA Astrophysics Data System (ADS)

Hueso, R.; Guillot, T.

2002-09-01

We study the formation and evolution of protoplanetary disks using an axisymmetric turbulent disk model. We compare model results with observational parameters derived for the DM Tau and GM Aur systems. These are relatively old T Tauri stars with large and massive protoplanetary disks. Early disk formation is studied in the standard scenario of slowly rotating isothermal collapsing spheres and is strongly dependent on the initial angular momentum and the collapse accretion rate. The viscous evolution of the disk is integrated in time using the classical Alpha prescription of turbulence. We follow the temporal evolution of the disks until their characteristics fit the observed characteristics of DM Tau and GM Aur. We therefore obtain the set of model parameters that are able to explain the present state of these disks. We also study the disk evolution under the Beta parameterization of turbulence, recently proposed for sheared flows on protoplanetary disks. Both parameterizations allow explaining the present state of both DM Tau and GM Aur. We infer a value of Alpha between 5x10-3 to 0.02 for DM Tau and one order of magnitude smaller for GM Aur. Values of the Beta parameter are in accordance with theoretical predictions of Beta around 2x10-5 but with a larger dispersion on other model parameters, which make us favor the Alpha parameterization of turbulence. Implications for planetary system development in these systems are presented. In particular, GM Aur is a massive and slowly evolving disk where conditions are very favorable for planetesimal growth. The large value of present disk mass and the relatively small observed accretion rate of this system may also be indicative of the presence of an inner gas giant planet. Acknowledgements: This work has been supported by Programme Nationale de Planetologie. R. Hueso acknowledges a post-doctoral fellowship from Gobierno Vasco.

Approaches for Subgrid Parameterization: Does Scaling Help?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2016-04-01

Arguably the scaling behavior is a well-established fact in many geophysical systems. There are already many theoretical studies elucidating this issue. However, the scaling law is slow to be introduced in "operational" geophysical modelling, notably for weather forecast as well as climate projection models. The main purpose of this presentation is to ask why, and try to answer this question. As a reference point, the presentation reviews the three major approaches for traditional subgrid parameterization: moment, PDF (probability density function), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in the atmosphere and the oceans. The PDF approach is intuitively appealing as it directly deals with a distribution of variables in subgrid scale in a more direct manner. The third category, originally proposed by Aubry et al (1988) in context of the wall boundary-layer turbulence, is specifically designed to represent coherencies in compact manner by a low--dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (POD, or empirical orthogonal functions, EOF) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. The mass-flux formulation that is currently adopted in majority of atmospheric models for parameterizing convection can also be considered a special case of the mode decomposition, adopting the segmentally-constant modes for the expansion basis. The mode decomposition can, furthermore, be re-interpreted as a type of Galarkin approach for numerically modelling the subgrid-scale processes. Simple extrapolation of this re-interpretation further suggests us that the subgrid parameterization problem may be re-interpreted as a type of mesh-refinement problem in numerical modelling. We furthermore see a link between the subgrid parameterization and downscaling problems along this line. The mode decomposition approach would also be the best framework for linking between the traditional parameterizations and the scaling perspectives. However, by seeing the link more clearly, we also see strength and weakness of introducing the scaling perspectives into parameterizations. Any diagnosis under a mode decomposition would immediately reveal a power-law nature of the spectrum. However, exploiting this knowledge in operational parameterization would be a different story. It is symbolic to realize that POD studies have been focusing on representing the largest-scale coherency within a grid box under a high truncation. This problem is already hard enough. Looking at differently, the scaling law is a very concise manner for characterizing many subgrid-scale variabilities in systems. We may even argue that the scaling law can provide almost complete subgrid-scale information in order to construct a parameterization, but with a major missing link: its amplitude must be specified by an additional condition. The condition called "closure" in the parameterization problem, and known to be a tough problem. We should also realize that the studies of the scaling behavior tend to be statistical in the sense that it hardly provides complete information for constructing a parameterization: can we specify the coefficients of all the decomposition modes by a scaling law perfectly when the first few leading modes are specified? Arguably, the renormalization group (RNG) is a very powerful tool for reducing a system with a scaling behavior into a low dimension, say, under an appropriate mode decomposition procedure. However, RNG is analytical tool: it is extremely hard to apply it to real complex geophysical systems. It appears that it is still a long way to go for us before we can begin to exploit the scaling law in order to construct operational subgrid parameterizations in effective manner.

Analysis of sensitivity to different parameterization schemes for a subtropical cyclone

NASA Astrophysics Data System (ADS)

Quitián-Hernández, L.; Fernández-González, S.; González-Alemán, J. J.; Valero, F.; Martín, M. L.

2018-05-01

A sensitivity analysis to diverse WRF model physical parameterization schemes is carried out during the lifecycle of a Subtropical cyclone (STC). STCs are low-pressure systems that share tropical and extratropical characteristics, with hybrid thermal structures. In October 2014, a STC made landfall in the Canary Islands, causing widespread damage from strong winds and precipitation there. The system began to develop on October 18 and its effects lasted until October 21. Accurate simulation of this type of cyclone continues to be a major challenge because of its rapid intensification and unique characteristics. In the present study, several numerical simulations were performed using the WRF model to do a sensitivity analysis of its various parameterization schemes for the development and intensification of the STC. The combination of parameterization schemes that best simulated this type of phenomenon was thereby determined. In particular, the parameterization combinations that included the Tiedtke cumulus schemes had the most positive effects on model results. Moreover, concerning STC track validation, optimal results were attained when the STC was fully formed and all convective processes stabilized. Furthermore, to obtain the parameterization schemes that optimally categorize STC structure, a verification using Cyclone Phase Space is assessed. Consequently, the combination of parameterizations including the Tiedtke cumulus schemes were again the best in categorizing the cyclone's subtropical structure. For strength validation, related atmospheric variables such as wind speed and precipitable water were analyzed. Finally, the effects of using a deterministic or probabilistic approach in simulating intense convective phenomena were evaluated.

The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas

NASA Astrophysics Data System (ADS)

Freitas, Saulo R.; Panetta, Jairo; Longo, Karla M.; Rodrigues, Luiz F.; Moreira, Demerval S.; Rosário, Nilton E.; Silva Dias, Pedro L.; Silva Dias, Maria A. F.; Souza, Enio P.; Freitas, Edmilson D.; Longo, Marcos; Frassoni, Ariane; Fazenda, Alvaro L.; Silva, Cláudio M. Santos e.; Pavani, Cláudio A. B.; Eiras, Denis; França, Daniela A.; Massaru, Daniel; Silva, Fernanda B.; Santos, Fernando C.; Pereira, Gabriel; Camponogara, Gláuber; Ferrada, Gonzalo A.; Campos Velho, Haroldo F.; Menezes, Isilda; Freire, Julliana L.; Alonso, Marcelo F.; Gácita, Madeleine S.; Zarzur, Maurício; Fonseca, Rafael M.; Lima, Rafael S.; Siqueira, Ricardo A.; Braz, Rodrigo; Tomita, Simone; Oliveira, Valter; Martins, Leila D.

2017-01-01

We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS), in which different previous versions for weather, chemistry, and carbon cycle were unified in a single integrated modeling system software. This new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. The description of the main model features includes several examples illustrating the quality of the transport scheme for scalars, radiative fluxes on surface, and model simulation of rainfall systems over South America at different spatial resolutions using a scale aware convective parameterization. Additionally, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America, are shown. Atmospheric chemistry examples show the model performance in simulating near-surface carbon monoxide and ozone in the Amazon Basin and the megacity of Rio de Janeiro. For tracer transport and dispersion, the model capabilities to simulate the volcanic ash 3-D redistribution associated with the eruption of a Chilean volcano are demonstrated. The gain of computational efficiency is described in some detail. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5 km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near-surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding both its functionalities and skills are discussed. Finally, we highlight the relevant contribution of this work to building a South American community of model developers.

The Brazilian Developments on the Regional Atmospheric Modeling System (BRAMS 5.2): An Integrated Environmental Model Tuned for Tropical Areas

NASA Technical Reports Server (NTRS)

Freitas, Saulo R.; Panetta, Jairo; Longo, Karla M.; Rodrigues, Luiz F.; Moreira, Demerval S.; Rosario, Nilton E.; Silva Dias, Pedro L.; Silva Dias, Maria A. F.; Souza, Enio P.; Freitas, Edmilson D.;

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Anisotropic Shear Dispersion Parameterization for Mesoscale Eddy Transport

NASA Astrophysics Data System (ADS)

Reckinger, S. J.; Fox-Kemper, B.

2016-02-01

The effects of mesoscale eddies are universally treated isotropically in general circulation models. However, the processes that the parameterization approximates, such as shear dispersion, typically have strongly anisotropic characteristics. The Gent-McWilliams/Redi mesoscale eddy parameterization is extended for anisotropy and tested using 1-degree Community Earth System Model (CESM) simulations. The sensitivity of the model to anisotropy includes a reduction of temperature and salinity biases, a deepening of the southern ocean mixed-layer depth, and improved ventilation of biogeochemical tracers, particularly in oxygen minimum zones. The parameterization is further extended to include the effects of unresolved shear dispersion, which sets the strength and direction of anisotropy. The shear dispersion parameterization is similar to drifter observations in spatial distribution of diffusivity and high-resolution model diagnosis in the distribution of eddy flux orientation.

Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems

DOE PAGES

Perkins, Casey; Muller, George

2015-10-08

The number of connections between physical and cyber security systems is rapidly increasing due to centralized control from automated and remotely connected means. As the number of interfaces between systems continues to grow, the interactions and interdependencies between them cannot be ignored. Historically, physical and cyber vulnerability assessments have been performed independently. This independent evaluation omits important aspects of the integrated system, where the impacts resulting from malicious or opportunistic attacks are not easily known or understood. Here, we describe a discrete event simulation model that uses information about integrated physical and cyber security systems, attacker characteristics and simple responsemore » rules to identify key safeguards that limit an attacker's likelihood of success. Key features of the proposed model include comprehensive data generation to support a variety of sophisticated analyses, and full parameterization of safeguard performance characteristics and attacker behaviours to evaluate a range of scenarios. Lastly, we also describe the core data requirements and the network of networks that serves as the underlying simulation structure.« less

Using Discrete Event Simulation to Model Attacker Interactions with Cyber and Physical Security Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perkins, Casey; Muller, George

The number of connections between physical and cyber security systems is rapidly increasing due to centralized control from automated and remotely connected means. As the number of interfaces between systems continues to grow, the interactions and interdependencies between them cannot be ignored. Historically, physical and cyber vulnerability assessments have been performed independently. This independent evaluation omits important aspects of the integrated system, where the impacts resulting from malicious or opportunistic attacks are not easily known or understood. Here, we describe a discrete event simulation model that uses information about integrated physical and cyber security systems, attacker characteristics and simple responsemore » rules to identify key safeguards that limit an attacker's likelihood of success. Key features of the proposed model include comprehensive data generation to support a variety of sophisticated analyses, and full parameterization of safeguard performance characteristics and attacker behaviours to evaluate a range of scenarios. Lastly, we also describe the core data requirements and the network of networks that serves as the underlying simulation structure.« less

An Interactive Preliminary Design System of High Speed Forebody and Inlet Flows

NASA Technical Reports Server (NTRS)

Liou, May-Fun; Benson, Thomas J.; Trefny, Charles J.

2010-01-01

This paper demonstrates a simulation-based aerodynamic design process of high speed inlet. A genetic algorithm is integrated into the design process to facilitate the single objective optimization. The objective function is the total pressure recovery and is obtained by using a PNS solver for its computing efficiency. The system developed uses existing software of geometry definition, mesh generation and CFD analysis. The process which produces increasingly desirable design in each genetic evolution over many generations is automatically carried out. A generic two-dimensional inlet is created as a showcase to demonstrate the capabilities of this tool. A parameterized study of geometric shape and size of the showcase is also presented.

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

Improvement of the GEOS-5 AGCM upon Updating the Air-Sea Roughness Parameterization

NASA Technical Reports Server (NTRS)

Garfinkel, C. I.; Molod, A.; Oman, L. D.; Song, I.-S.

2011-01-01

The impact of an air-sea roughness parameterization over the ocean that more closely matches recent observations of air-sea exchange is examined in the NASA Goddard Earth Observing System, version 5 (GEOS-5) atmospheric general circulation model. Surface wind biases in the GEOS-5 AGCM are decreased by up to 1.2m/s. The new parameterization also has implications aloft as improvements extend into the stratosphere. Many other GCMs (both for operational weather forecasting and climate) use a similar class of parameterization for their air-sea roughness scheme. We therefore expect that results from GEOS-5 are relevant to other models as well.

An analysis of MM5 sensitivity to different parameterizations for high-resolution climate simulations

NASA Astrophysics Data System (ADS)

Argüeso, D.; Hidalgo-Muñoz, J. M.; Gámiz-Fortis, S. R.; Esteban-Parra, M. J.; Castro-Díez, Y.

2009-04-01

An evaluation of MM5 mesoscale model sensitivity to different parameterizations schemes is presented in terms of temperature and precipitation for high-resolution integrations over Andalusia (South of Spain). As initial and boundary conditions ERA-40 Reanalysis data are used. Two domains were used, a coarse one with dimensions of 55 by 60 grid points with spacing of 30 km and a nested domain of 48 by 72 grid points grid spaced 10 km. Coarse domain fully covers Iberian Peninsula and Andalusia fits loosely in the finer one. In addition to parameterization tests, two dynamical downscaling techniques have been applied in order to examine the influence of initial conditions on RCM long-term studies. Regional climate studies usually employ continuous integration for the period under survey, initializing atmospheric fields only at the starting point and feeding boundary conditions regularly. An alternative approach is based on frequent re-initialization of atmospheric fields; hence the simulation is divided in several independent integrations. Altogether, 20 simulations have been performed using varying physics options, of which 4 were fulfilled applying the re-initialization technique. Surface temperature and accumulated precipitation (daily and monthly scale) were analyzed for a 5-year period covering from 1990 to 1994. Results have been compared with daily observational data series from 110 stations for temperature and 95 for precipitation Both daily and monthly average temperatures are generally well represented by the model. Conversely, daily precipitation results present larger deviations from observational data. However, noticeable accuracy is gained when comparing with monthly precipitation observations. There are some especially conflictive subregions where precipitation is scarcely captured, such as the Southeast of the Iberian Peninsula, mainly due to its extremely convective nature. Regarding parameterization schemes performance, every set provides very similar results either for temperature or precipitation and no configuration seems to outperform the others both for the whole region and for every season. Nevertheless, some marked differences between areas within the domain appear when analyzing certain physics options, particularly for precipitation. Some of the physics options, such as radiation, have little impact on model performance with respect to precipitation and results do not vary when the scheme is modified. On the other hand, cumulus and boundary layer parameterizations are responsible for most of the differences obtained between configurations. Acknowledgements: The Spanish Ministry of Science and Innovation, with additional support from the European Community Funds (FEDER), project CGL2007-61151/CLI, and the Regional Government of Andalusia project P06-RNM-01622, have financed this study. The "Centro de Servicios de Informática y Redes de Comunicaciones" (CSIRC), Universidad de Granada, has provided the computing time. Key words: MM5 mesoscale model, parameterizations schemes, temperature and precipitation, South of Spain.

Parameterization guidelines and considerations for hydrologic models

Treesearch

 R. W. Malone; G. Yagow; C. Baffaut; M.W  Gitau; Z. Qi; Devendra Amatya; P.B.   Parajuli; J.V. Bonta; T.R.  Green

2015-01-01

 Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) are important and difficult tasks. An exponential...

An epidemiological modeling and data integration framework.

PubMed

Pfeifer, B; Wurz, M; Hanser, F; Seger, M; Netzer, M; Osl, M; Modre-Osprian, R; Schreier, G; Baumgartner, C

2010-01-01

In this work, a cellular automaton software package for simulating different infectious diseases, storing the simulation results in a data warehouse system and analyzing the obtained results to generate prediction models as well as contingency plans, is proposed. The Brisbane H3N2 flu virus, which has been spreading during the winter season 2009, was used for simulation in the federal state of Tyrol, Austria. The simulation-modeling framework consists of an underlying cellular automaton. The cellular automaton model is parameterized by known disease parameters and geographical as well as demographical conditions are included for simulating the spreading. The data generated by simulation are stored in the back room of the data warehouse using the Talend Open Studio software package, and subsequent statistical and data mining tasks are performed using the tool, termed Knowledge Discovery in Database Designer (KD3). The obtained simulation results were used for generating prediction models for all nine federal states of Austria. The proposed framework provides a powerful and easy to handle interface for parameterizing and simulating different infectious diseases in order to generate prediction models and improve contingency plans for future events.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Griffin, Brian M.; Larson, Vincent E.

Microphysical processes, such as the formation, growth, and evaporation of precipitation, interact with variability and covariances (e.g., fluxes) in moisture and heat content. For instance, evaporation of rain may produce cold pools, which in turn may trigger fresh convection and precipitation. These effects are usually omitted or else crudely parameterized at subgrid scales in weather and climate models.A more formal approach is pursued here, based on predictive, horizontally averaged equations for the variances, covariances, and fluxes of moisture and heat content. These higher-order moment equations contain microphysical source terms. The microphysics terms can be integrated analytically, given a suitably simplemore » warm-rain microphysics scheme and an approximate assumption about the multivariate distribution of cloud-related and precipitation-related variables. Performing the integrations provides exact expressions within an idealized context.A large-eddy simulation (LES) of a shallow precipitating cumulus case is performed here, and it indicates that the microphysical effects on (co)variances and fluxes can be large. In some budgets and altitude ranges, they are dominant terms. The analytic expressions for the integrals are implemented in a single-column, higher-order closure model. Interactive single-column simulations agree qualitatively with the LES. The analytic integrations form a parameterization of microphysical effects in their own right, and they also serve as benchmark solutions that can be compared to non-analytic integration methods.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Sun Ung, E-mail: sunung@umich.edu; Monroe, Charles W., E-mail: cwmonroe@umich.edu

The inverse problem of parameterizing intermolecular potentials given macroscopic transport and thermodynamic data is addressed. Procedures are developed to create arbitrary-precision algorithms for transport collision integrals, using the Lennard-Jones (12–6) potential as an example. Interpolation formulas are produced that compute these collision integrals to four-digit accuracy over the reduced-temperature range 0.3≤T{sup ⁎}≤400, allowing very fast computation. Lennard-Jones parameters for neon, argon, and krypton are determined by simultaneously fitting the observed temperature dependences of their viscosities and second virial coefficients—one of the first times that a thermodynamic and a dynamic property have been used simultaneously for Lennard-Jones parameterization. In addition tomore » matching viscosities and second virial coefficients within the bounds of experimental error, the determined Lennard-Jones parameters are also found to predict the thermal conductivity and self-diffusion coefficient accurately, supporting the value of the Lennard-Jones (12–6) potential for noble-gas transport-property correlation.« less

Inhomogeneous Heisenberg spin chain and quantum vortex filament as non-holonomically deformed NLS systems

NASA Astrophysics Data System (ADS)

Abhinav, Kumar; Guha, Partha

2018-03-01

Through the Hasimoto map, various dynamical systems can be mapped to different integrodifferential generalizations of Nonlinear Schrödinger (NLS) family of equations some of which are known to be integrable. Two such continuum limits, corresponding to the inhomogeneous XXX Heisenberg spin chain [J. Phys. C 15, L1305 (1982)] and that of a thin vortex filament moving in a superfluid with drag [Eur. Phys. J. B 86, 275 (2013) 86; Phys. Rev. E 91, 053201 (2015)], are shown to be particular non-holonomic deformations (NHDs) of the standard NLS system involving generalized parameterizations. Crucially, such NHDs of the NLS system are restricted to specific spectral orders that exactly complements NHDs of the original physical systems. The specific non-holonomic constraints associated with these integrodifferential generalizations additionally posses distinct semi-classical signature.

Dimensionless parameterization of lidar for laser remote sensing of the atmosphere and its application to systems with SiPM and PMT detectors.

PubMed

Agishev, Ravil; Comerón, Adolfo; Rodriguez, Alejandro; Sicard, Michaël

2014-05-20

In this paper, we show a renewed approach to the generalized methodology for atmospheric lidar assessment, which uses the dimensionless parameterization as a core component. It is based on a series of our previous works where the problem of universal parameterization over many lidar technologies were described and analyzed from different points of view. The modernized dimensionless parameterization concept applied to relatively new silicon photomultiplier detectors (SiPMs) and traditional photomultiplier (PMT) detectors for remote-sensing instruments allowed predicting the lidar receiver performance with sky background available. The renewed approach can be widely used to evaluate a broad range of lidar system capabilities for a variety of lidar remote-sensing applications as well as to serve as a basis for selection of appropriate lidar system parameters for a specific application. Such a modernized methodology provides a generalized, uniform, and objective approach for evaluation of a broad range of lidar types and systems (aerosol, Raman, DIAL) operating on different targets (backscatter or topographic) and under intense sky background conditions. It can be used within the lidar community to compare different lidar instruments.

Weather Research and Forecasting model simulation of an onshore wind farm: assessment against LiDAR and SCADA data

NASA Astrophysics Data System (ADS)

Santoni, Christian; Garcia-Cartagena, Edgardo J.; Zhan, Lu; Iungo, Giacomo Valerio; Leonardi, Stefano

2017-11-01

The integration of wind farm parameterizations into numerical weather prediction models is essential to study power production under realistic conditions. Nevertheless, recent models are unable to capture turbine wake interactions and, consequently, the mean kinetic energy entrainment, which are essential for the development of power optimization models. To address the study of wind turbine wake interaction, one-way nested mesoscale to large-eddy simulation (LES) were performed using the Weather Research and Forecasting model (WRF). The simulation contains five nested domains modeling the mesoscale wind on the entire North Texas Panhandle region to the microscale wind fluctuations and turbine wakes of a wind farm located at Panhandle, Texas. The wind speed, direction and boundary layer profile obtained from WRF were compared against measurements obtained with a sonic anemometer and light detection and ranging system located within the wind farm. Additionally, the power production were assessed against measurements obtained from the supervisory control and data acquisition system located in each turbine. Furthermore, to incorporate the turbines into very coarse LES, a modification to the implementation of the wind farm parameterization by Fitch et al. (2012) is proposed. This work was supported by the NSF, Grants No. 1243482 (WINDINSPIRE) and IIP 1362033 (WindSTAR), and TACC.

Parameterization of Transport and Period Matrices with X-Y Coupling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Courant, E. D.

A parameterization of 4x4 matrices describing linear beam transport systems has been obtained by Edwards and Teng. Here we extend their formalism to include dispersive effects, and give perscriptions for incorporating it in the program SYNCH.

Uniting statistical and individual-based approaches for animal movement modelling.

PubMed

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

PubMed Central

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

An offline approach for output-only Bayesian identification of stochastic nonlinear systems using unscented Kalman filtering

NASA Astrophysics Data System (ADS)

Erazo, Kalil; Nagarajaiah, Satish

2017-06-01

In this paper an offline approach for output-only Bayesian identification of stochastic nonlinear systems is presented. The approach is based on a re-parameterization of the joint posterior distribution of the parameters that define a postulated state-space stochastic model class. In the re-parameterization the state predictive distribution is included, marginalized, and estimated recursively in a state estimation step using an unscented Kalman filter, bypassing state augmentation as required by existing online methods. In applications expectations of functions of the parameters are of interest, which requires the evaluation of potentially high-dimensional integrals; Markov chain Monte Carlo is adopted to sample the posterior distribution and estimate the expectations. The proposed approach is suitable for nonlinear systems subjected to non-stationary inputs whose realization is unknown, and that are modeled as stochastic processes. Numerical verification and experimental validation examples illustrate the effectiveness and advantages of the approach, including: (i) an increased numerical stability with respect to augmented-state unscented Kalman filtering, avoiding divergence of the estimates when the forcing input is unmeasured; (ii) the ability to handle arbitrary prior and posterior distributions. The experimental validation of the approach is conducted using data from a large-scale structure tested on a shake table. It is shown that the approach is robust to inherent modeling errors in the description of the system and forcing input, providing accurate prediction of the dynamic response when the excitation history is unknown.

Data error and highly parameterized groundwater models

USGS Publications Warehouse

Hill, M.C.

2008-01-01

Strengths and weaknesses of highly parameterized models, in which the number of parameters exceeds the number of observations, are demonstrated using a synthetic test case. Results suggest that the approach can yield close matches to observations but also serious errors in system representation. It is proposed that avoiding the difficulties of highly parameterized models requires close evaluation of: (1) model fit, (2) performance of the regression, and (3) estimated parameter distributions. Comparisons to hydrogeologic information are expected to be critical to obtaining credible models. Copyright ?? 2008 IAHS Press.

A General Framework for Thermodynamically Consistent Parameterization and Efficient Sampling of Enzymatic Reactions

PubMed Central

Saa, Pedro; Nielsen, Lars K.

2015-01-01

Kinetic models provide the means to understand and predict the dynamic behaviour of enzymes upon different perturbations. Despite their obvious advantages, classical parameterizations require large amounts of data to fit their parameters. Particularly, enzymes displaying complex reaction and regulatory (allosteric) mechanisms require a great number of parameters and are therefore often represented by approximate formulae, thereby facilitating the fitting but ignoring many real kinetic behaviours. Here, we show that full exploration of the plausible kinetic space for any enzyme can be achieved using sampling strategies provided a thermodynamically feasible parameterization is used. To this end, we developed a General Reaction Assembly and Sampling Platform (GRASP) capable of consistently parameterizing and sampling accurate kinetic models using minimal reference data. The former integrates the generalized MWC model and the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, our framework enables parameterization of any oligomeric enzyme kinetics without sacrificing complexity or using simplifying assumptions. This thermodynamically safe parameterization relies on the definition of a reference state upon which feasible parameter sets can be efficiently sampled. Uniform sampling of the kinetics space enabled dissecting enzyme catalysis and revealing the impact of thermodynamics on reaction kinetics. Our analysis distinguished three reaction elasticity regions for common biochemical reactions: a steep linear region (0> ΔGr >-2 kJ/mol), a transition region (-2> ΔGr >-20 kJ/mol) and a constant elasticity region (ΔGr <-20 kJ/mol). We also applied this framework to model more complex kinetic behaviours such as the monomeric cooperativity of the mammalian glucokinase and the ultrasensitive response of the phosphoenolpyruvate carboxylase of Escherichia coli. In both cases, our approach described appropriately not only the kinetic behaviour of these enzymes, but it also provided insights about the particular features underpinning the observed kinetics. Overall, this framework will enable systematic parameterization and sampling of enzymatic reactions. PMID:25874556

Quantifying the measurement errors in a LI-6400 gas exchange system and their effects on the parameterization of Farquhar et al. model for C3 leaves

USDA-ARS?s Scientific Manuscript database

The LI-6400 gas exchange system (Li-Cor, Inc, Lincoln, NE, USA) has been widely used for the measurement of net gas exchanges and calibration/parameterization of leaf models. Measurement errors due to diffusive leakages of water vapor and carbon dioxide between inside and outside of the leaf chamber...

PICASSO: an end-to-end image simulation tool for space and airborne imaging systems II. Extension to the thermal infrared: equations and methods

NASA Astrophysics Data System (ADS)

Cota, Stephen A.; Lomheim, Terrence S.; Florio, Christopher J.; Harbold, Jeffrey M.; Muto, B. Michael; Schoolar, Richard B.; Wintz, Daniel T.; Keller, Robert A.

2011-10-01

In a previous paper in this series, we described how The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) tool may be used to model space and airborne imaging systems operating in the visible to near-infrared (VISNIR). PICASSO is a systems-level tool, representative of a class of such tools used throughout the remote sensing community. It is capable of modeling systems over a wide range of fidelity, anywhere from conceptual design level (where it can serve as an integral part of the systems engineering process) to as-built hardware (where it can serve as part of the verification process). In the present paper, we extend the discussion of PICASSO to the modeling of Thermal Infrared (TIR) remote sensing systems, presenting the equations and methods necessary to modeling in that regime.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Chemical Transformation System: Cloud Based ...

EPA Pesticide Factsheets

Integrated Environmental Modeling (IEM) systems that account for the fate/transport of organics frequently require physicochemical properties as well as transformation products. A myriad of chemical property databases exist but these can be difficult to access and often do not contain the proprietary chemicals that environmental regulators must consider. We are building the Chemical Transformation System (CTS) to facilitate model parameterization and analysis. CTS integrates a number of physicochemical property calculators into the system including EPI Suite, SPARC, TEST and ChemAxon. The calculators are heterogeneous in their scientific methodologies, technology implementations and deployment stacks. CTS also includes a chemical transformation processing engine that has been loaded with reaction libraries for human biotransformation, abiotic reduction and abiotic hydrolysis. CTS implements a common interface for the disparate calculators accepting molecular identifiers (SMILES, IUPAC, CAS#, user-drawn molecule) before submission for processing. To make the system as accessible as possible and provide a consistent programmatic interface, we wrapped the calculators in a standardized RESTful Application Programming Interface (API) which makes it capable of servicing a much broader spectrum of clients without constraints to interoperability such as operating system or programming language. CTS is hosted in a shared cloud environment, the Quantitative Environmental

Path Integrals for Electronic Densities, Reactivity Indices, and Localization Functions in Quantum Systems

PubMed Central

Putz, Mihai V.

2009-01-01

The density matrix theory, the ancestor of density functional theory, provides the immediate framework for Path Integral (PI) development, allowing the canonical density be extended for the many-electronic systems through the density functional closure relationship. Yet, the use of path integral formalism for electronic density prescription presents several advantages: assures the inner quantum mechanical description of the system by parameterized paths; averages the quantum fluctuations; behaves as the propagator for time-space evolution of quantum information; resembles Schrödinger equation; allows quantum statistical description of the system through partition function computing. In this framework, four levels of path integral formalism were presented: the Feynman quantum mechanical, the semiclassical, the Feynman-Kleinert effective classical, and the Fokker-Planck non-equilibrium ones. In each case the density matrix or/and the canonical density were rigorously defined and presented. The practical specializations for quantum free and harmonic motions, for statistical high and low temperature limits, the smearing justification for the Bohr’s quantum stability postulate with the paradigmatic Hydrogen atomic excursion, along the quantum chemical calculation of semiclassical electronegativity and hardness, of chemical action and Mulliken electronegativity, as well as by the Markovian generalizations of Becke-Edgecombe electronic focalization functions – all advocate for the reliability of assuming PI formalism of quantum mechanics as a versatile one, suited for analytically and/or computationally modeling of a variety of fundamental physical and chemical reactivity concepts characterizing the (density driving) many-electronic systems. PMID:20087467

Path integrals for electronic densities, reactivity indices, and localization functions in quantum systems.

PubMed

Putz, Mihai V

2009-11-10

The density matrix theory, the ancestor of density functional theory, provides the immediate framework for Path Integral (PI) development, allowing the canonical density be extended for the many-electronic systems through the density functional closure relationship. Yet, the use of path integral formalism for electronic density prescription presents several advantages: assures the inner quantum mechanical description of the system by parameterized paths; averages the quantum fluctuations; behaves as the propagator for time-space evolution of quantum information; resembles Schrödinger equation; allows quantum statistical description of the system through partition function computing. In this framework, four levels of path integral formalism were presented: the Feynman quantum mechanical, the semiclassical, the Feynman-Kleinert effective classical, and the Fokker-Planck non-equilibrium ones. In each case the density matrix or/and the canonical density were rigorously defined and presented. The practical specializations for quantum free and harmonic motions, for statistical high and low temperature limits, the smearing justification for the Bohr's quantum stability postulate with the paradigmatic Hydrogen atomic excursion, along the quantum chemical calculation of semiclassical electronegativity and hardness, of chemical action and Mulliken electronegativity, as well as by the Markovian generalizations of Becke-Edgecombe electronic focalization functions - all advocate for the reliability of assuming PI formalism of quantum mechanics as a versatile one, suited for analytically and/or computationally modeling of a variety of fundamental physical and chemical reactivity concepts characterizing the (density driving) many-electronic systems.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE PAGES

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-02

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

NASA Astrophysics Data System (ADS)

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-01

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donahue, Aaron S.; Caldwell, Peter M.

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

Usage of Parameterized Fatigue Spectra and Physics-Based Systems Engineering Models for Wind Turbine Component Sizing: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parsons, Taylor; Guo, Yi; Veers, Paul

Software models that use design-level input variables and physics-based engineering analysis for estimating the mass and geometrical properties of components in large-scale machinery can be very useful for analyzing design trade-offs in complex systems. This study uses DriveSE, an OpenMDAO-based drivetrain model that uses stress and deflection criteria to size drivetrain components within a geared, upwind wind turbine. Because a full lifetime fatigue load spectrum can only be defined using computationally-expensive simulations in programs such as FAST, a parameterized fatigue loads spectrum that depends on wind conditions, rotor diameter, and turbine design life has been implemented. The parameterized fatigue spectrummore » is only used in this paper to demonstrate the proposed fatigue analysis approach. This paper details a three-part investigation of the parameterized approach and a comparison of the DriveSE model with and without fatigue analysis on the main shaft system. It compares loads from three turbines of varying size and determines if and when fatigue governs drivetrain sizing compared to extreme load-driven design. It also investigates the model's sensitivity to shaft material parameters. The intent of this paper is to demonstrate how fatigue considerations in addition to extreme loads can be brought into a system engineering optimization.« less

Development and Exploration of a Regional Stormwater BMP Performance Database to Parameterize an Integrated Decision Support Tool (i-DST)

NASA Astrophysics Data System (ADS)

Bell, C.; Li, Y.; Lopez, E.; Hogue, T. S.

2017-12-01

Decision support tools that quantitatively estimate the cost and performance of infrastructure alternatives are valuable for urban planners. Such a tool is needed to aid in planning stormwater projects to meet diverse goals such as the regulation of stormwater runoff and its pollutants, minimization of economic costs, and maximization of environmental and social benefits in the communities served by the infrastructure. This work gives a brief overview of an integrated decision support tool, called i-DST, that is currently being developed to serve this need. This presentation focuses on the development of a default database for the i-DST that parameterizes water quality treatment efficiency of stormwater best management practices (BMPs) by region. Parameterizing the i-DST by region will allow the tool to perform accurate simulations in all parts of the United States. A national dataset of BMP performance is analyzed to determine which of a series of candidate regionalizations explains the most variance in the national dataset. The data used in the regionalization analysis comes from the International Stormwater BMP Database and data gleaned from an ongoing systematic review of peer-reviewed and gray literature. In addition to identifying a regionalization scheme for water quality performance parameters in the i-DST, our review process will also provide example methods and protocols for systematic reviews in the field of Earth Science.

Biogeochemical modelling vs. tree-ring data - comparison of forest ecosystem productivity estimates

NASA Astrophysics Data System (ADS)

Zorana Ostrogović Sever, Maša; Barcza, Zoltán; Hidy, Dóra; Paladinić, Elvis; Kern, Anikó; Marjanović, Hrvoje

2017-04-01

Forest ecosystems are sensitive to environmental changes as well as human-induce disturbances, therefore process-based models with integrated management modules represent valuable tool for estimating and forecasting forest ecosystem productivity under changing conditions. Biogeochemical model Biome-BGC simulates carbon, nitrogen and water fluxes, and it is widely used for different terrestrial ecosystems. It was modified and parameterised by many researchers in the past to meet the specific local conditions. In this research, we used recently published improved version of the model Biome-BGCMuSo (BBGCMuSo), with multilayer soil module and integrated management module. The aim of our research is to validate modelling results of forest ecosystem productivity (NPP) from BBGCMuSo model with observed productivity estimated from an extensive dataset of tree-rings. The research was conducted in two distinct forest complexes of managed Pedunculate oak in SE Europe (Croatia), namely Pokupsko basin and Spačva basin. First, we parameterized BBGCMuSo model at a local level using eddy-covariance (EC) data from Jastrebarsko EC site. Parameterized model was used for the assessment of productivity on a larger scale. Results of NPP assessment with BBGCMuSo are compared with NPP estimated from tree ring data taken from trees on over 100 plots in both forest complexes. Keywords: Biome-BGCMuSo, forest productivity, model parameterization, NPP, Pedunculate oak

Longwave Radiative Flux Calculations in the TOVS Pathfinder Path A Data Set

NASA Technical Reports Server (NTRS)

Mehta, Amita; Susskind, Joel

1999-01-01

A radiative transfer model developed to calculate outgoing longwave radiation (OLR) and downwelling longwave, surface flux (DSF) from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder Path A retrieval products is described. The model covers the spectral range of 2 to 2800 cm in 14 medium medium spectral bands. For each band, transmittances are parameterized as a function of temperature, water vapor, and ozone profiles. The form of the band transmittance parameterization is a modified version of the approach we use to model channel transmittances for the High Resolution Infrared Sounder 2 (HIRS2) instrument. We separately derive effective zenith angle for each spectral band such that band-averaged radiance calculated at that angle best approximates directionally integrated radiance for that band. We develop the transmittance parameterization at these band-dependent effective zenith angles to incorporate directional integration of radiances required in the calculations of OLR and DSF. The model calculations of OLR and DSF are accurate and differ by less than 1% from our line-by-line calculations. Also, the model results are within 1% range of other line-by-line calculations provided by the Intercomparison of Radiation Codes in Climate Models (ICRCCM) project for clear-sky and cloudy conditions. The model is currently used to calculate global, multiyear (1985-1998) OLR and DSF from the TOVS Pathfinder Path A Retrievals.

Parameterized data-driven fuzzy model based optimal control of a semi-batch reactor.

PubMed

Kamesh, Reddi; Rani, K Yamuna

2016-09-01

A parameterized data-driven fuzzy (PDDF) model structure is proposed for semi-batch processes, and its application for optimal control is illustrated. The orthonormally parameterized input trajectories, initial states and process parameters are the inputs to the model, which predicts the output trajectories in terms of Fourier coefficients. Fuzzy rules are formulated based on the signs of a linear data-driven model, while the defuzzification step incorporates a linear regression model to shift the domain from input to output domain. The fuzzy model is employed to formulate an optimal control problem for single rate as well as multi-rate systems. Simulation study on a multivariable semi-batch reactor system reveals that the proposed PDDF modeling approach is capable of capturing the nonlinear and time-varying behavior inherent in the semi-batch system fairly accurately, and the results of operating trajectory optimization using the proposed model are found to be comparable to the results obtained using the exact first principles model, and are also found to be comparable to or better than parameterized data-driven artificial neural network model based optimization results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Parameterized examination in econometrics

NASA Astrophysics Data System (ADS)

Malinova, Anna; Kyurkchiev, Vesselin; Spasov, Georgi

2018-01-01

The paper presents a parameterization of basic types of exam questions in Econometrics. This algorithm is used to automate and facilitate the process of examination, assessment and self-preparation of a large number of students. The proposed parameterization of testing questions reduces the time required to author tests and course assignments. It enables tutors to generate a large number of different but equivalent dynamic questions (with dynamic answers) on a certain topic, which are automatically assessed. The presented methods are implemented in DisPeL (Distributed Platform for e-Learning) and provide questions in the areas of filtering and smoothing of time-series data, forecasting, building and analysis of single-equation econometric models. Questions also cover elasticity, average and marginal characteristics, product and cost functions, measurement of monopoly power, supply, demand and equilibrium price, consumer and product surplus, etc. Several approaches are used to enable the required numerical computations in DisPeL - integration of third-party mathematical libraries, developing our own procedures from scratch, and wrapping our legacy math codes in order to modernize and reuse them.

Stochastic Convection Parameterizations: The Eddy-Diffusivity/Mass-Flux (EDMF) Approach (Invited)

NASA Astrophysics Data System (ADS)

Teixeira, J.

2013-12-01

In this presentation it is argued that moist convection parameterizations need to be stochastic in order to be realistic - even in deterministic atmospheric prediction systems. A new unified convection and boundary layer parameterization (EDMF) that optimally combines the Eddy-Diffusivity (ED) approach for smaller-scale boundary layer mixing with the Mass-Flux (MF) approach for larger-scale plumes is discussed. It is argued that for realistic simulations stochastic methods have to be employed in this new unified EDMF. Positive results from the implementation of the EDMF approach in atmospheric models are presented.

A MULTILAYER BIOCHEMICAL DRY DEPOSITION MODEL 1. MODEL FORMULATION

EPA Science Inventory

A multilayer biochemical dry deposition model has been developed based on the NOAA Multilayer Model (MLM) to study gaseous exchanges between the soil, plants, and the atmosphere. Most of the parameterizations and submodels have been updated or replaced. The numerical integration ...

Parameterization guidelines and considerations for hydrologic models

USDA-ARS?s Scientific Manuscript database

Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) is an important and difficult task. An exponential increase in literature has been devoted to the use and develo...

Gsflow-py: An integrated hydrologic model development tool

NASA Astrophysics Data System (ADS)

Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.

2017-12-01

Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

Modelling surface-water depression storage in a Prairie Pothole Region

USGS Publications Warehouse

Hay, Lauren E.; Norton, Parker A.; Viger, Roland; Markstrom, Steven; Regan, R. Steven; Vanderhoof, Melanie

2018-01-01

In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.

Anisotropic shear dispersion parameterization for ocean eddy transport

NASA Astrophysics Data System (ADS)

Reckinger, Scott; Fox-Kemper, Baylor

2015-11-01

The effects of mesoscale eddies are universally treated isotropically in global ocean general circulation models. However, observations and simulations demonstrate that the mesoscale processes that the parameterization is intended to represent, such as shear dispersion, are typified by strong anisotropy. We extend the Gent-McWilliams/Redi mesoscale eddy parameterization to include anisotropy and test the effects of varying levels of anisotropy in 1-degree Community Earth System Model (CESM) simulations. Anisotropy has many effects on the simulated climate, including a reduction of temperature and salinity biases, a deepening of the southern ocean mixed-layer depth, impacts on the meridional overturning circulation and ocean energy and tracer uptake, and improved ventilation of biogeochemical tracers, particularly in oxygen minimum zones. A process-based parameterization to approximate the effects of unresolved shear dispersion is also used to set the strength and direction of anisotropy. The shear dispersion parameterization is similar to drifter observations in spatial distribution of diffusivity and high-resolution model diagnosis in the distribution of eddy flux orientation.

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

NASA Technical Reports Server (NTRS)

Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

2016-01-01

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

A reduced-form approach for representing the impacts of wind and solar PV deployment on the structure and operation of the electricity system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Nils; Strubegger, Manfred; McPherson, Madeleine

In many climate change mitigation scenarios, integrated assessment models of the energy and climate systems rely heavily on renewable energy technologies with variable and uncertain generation, such as wind and solar PV, to achieve substantial decarbonization of the electricity sector. However, these models often include very little temporal resolution and thus have difficulty in representing the integration costs that arise from mismatches between electricity supply and demand. The global integrated assessment model, MESSAGE, has been updated to explicitly model the trade-offs between variable renewable energy (VRE) deployment and its impacts on the electricity system, including the implications for electricity curtailment,more » backup capacity, and system flexibility. These impacts have been parameterized using a reduced-form approach, which allows VRE integration impacts to be quantified on a regional basis. In addition, thermoelectric technologies were updated to include two modes of operation, baseload and flexible, to better account for the cost, efficiency, and availability penalties associated with flexible operation. In this paper, the modeling approach used in MESSAGE is explained and the implications for VRE deployment in mitigation scenarios are assessed. Three important stylized facts associated with integrating high VRE shares are successfully reproduced by our modeling approach: (1) the significant reduction in the utilization of non-VRE power plants; (2) the diminishing role for traditional baseload generators, such as nuclear and coal, and the transition to more flexible technologies; and (3) the importance of electricity storage and hydrogen electrolysis in facilitating the deployment of VRE.« less

Data mining through simulation.

PubMed

Lytton, William W; Stewart, Mark

2007-01-01

Data integration is particularly difficult in neuroscience; we must organize vast amounts of data around only a few fragmentary functional hypotheses. It has often been noted that computer simulation, by providing explicit hypotheses for a particular system and bridging across different levels of organization, can provide an organizational focus, which can be leveraged to form substantive hypotheses. Simulations lend meaning to data and can be updated and adapted as further data come in. The use of simulation in this context suggests the need for simulator adjuncts to manage and evaluate data. We have developed a neural query system (NQS) within the NEURON simulator, providing a relational database system, a query function, and basic data-mining tools. NQS is used within the simulation context to manage, verify, and evaluate model parameterizations. More importantly, it is used for data mining of simulation data and comparison with neurophysiology.

Evaluating and Improving Wind Forecasts over South China: The Role of Orographic Parameterization in the GRAPES Model

NASA Astrophysics Data System (ADS)

Zhong, Shuixin; Chen, Zitong; Xu, Daosheng; Zhang, Yanxia

2018-06-01

Unresolved small-scale orographic (SSO) drags are parameterized in a regional model based on the Global/Regional Assimilation and Prediction System for the Tropical Mesoscale Model (GRAPES TMM). The SSO drags are represented by adding a sink term in the momentum equations. The maximum height of the mountain within the grid box is adopted in the SSO parameterization (SSOP) scheme as compensation for the drag. The effects of the unresolved topography are parameterized as the feedbacks to the momentum tendencies on the first model level in planetary boundary layer (PBL) parameterization. The SSOP scheme has been implemented and coupled with the PBL parameterization scheme within the model physics package. A monthly simulation is designed to examine the performance of the SSOP scheme over the complex terrain areas located in the southwest of Guangdong. The verification results show that the surface wind speed bias has been much alleviated by adopting the SSOP scheme, in addition to reduction of the wind bias in the lower troposphere. The target verification over Xinyi shows that the simulations with the SSOP scheme provide improved wind estimation over the complex regions in the southwest of Guangdong.

Geometry Control System for Exploratory Shape Optimization Applied to High-Fidelity Aerodynamic Design of Unconventional Aircraft

NASA Astrophysics Data System (ADS)

Gagnon, Hugo

This thesis represents a step forward to bring geometry parameterization and control on par with the disciplinary analyses involved in shape optimization, particularly high-fidelity aerodynamic shape optimization. Central to the proposed methodology is the non-uniform rational B-spline, used here to develop a new geometry generator and geometry control system applicable to the aerodynamic design of both conventional and unconventional aircraft. The geometry generator adopts a component-based approach, where any number of predefined but modifiable (parametric) wing, fuselage, junction, etc., components can be arbitrarily assembled to generate the outer mold line of aircraft geometry. A unique Python-based user interface incorporating an interactive OpenGL windowing system is proposed. Together, these tools allow for the generation of high-quality, C2 continuous (or higher), and customized aircraft geometry with fast turnaround. The geometry control system tightly integrates shape parameterization with volume mesh movement using a two-level free-form deformation approach. The framework is augmented with axial curves, which are shown to be flexible and efficient at parameterizing wing systems of arbitrary topology. A key aspect of this methodology is that very large shape deformations can be achieved with only a few, intuitive control parameters. Shape deformation consumes a few tenths of a second on a single processor and surface sensitivities are machine accurate. The geometry control system is implemented within an existing aerodynamic optimizer comprising a flow solver for the Euler equations and a sequential quadratic programming optimizer. Gradients are evaluated exactly with discrete-adjoint variables. The algorithm is first validated by recovering an elliptical lift distribution on a rectangular wing, and then demonstrated through the exploratory shape optimization of a three-pronged feathered winglet leading to a span efficiency of 1.22 under a height-to-span ratio constraint of 0.1. Finally, unconventional aircraft configurations sized for a regional mission are compared against a conventional baseline. Each aircraft is optimized by varying wing section and wing planform (excluding span) under lift and trim constraints at a single operating point. Based on inviscid pressure drag, the box-wing, C-tip blended-wing-body, and braced-wing configurations considered here are respectively 22%, 25%, and 45% more efficient than the tube-and-wing configuration.

High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2): Large Eddy Simulation Study Over Germany

NASA Astrophysics Data System (ADS)

Dipankar, A.; Stevens, B. B.; Zängl, G.; Pondkule, M.; Brdar, S.

2014-12-01

The effect of clouds on large scale dynamics is represented in climate models through parameterization of various processes, of which the parameterization of shallow and deep convection are particularly uncertain. The atmospheric boundary layer, which controls the coupling to the surface, and which defines the scale of shallow convection, is typically 1 km in depth. Thus, simulations on a O(100 m) grid largely obviate the need for such parameterizations. By crossing this threshold of O(100m) grid resolution one can begin thinking of large-eddy simulation (LES), wherein the sub-grid scale parameterization have a sounder theoretical foundation. Substantial initiatives have been taken internationally to approach this threshold. For example, Miura et al., 2007 and Mirakawa et al., 2014 approach this threshold by doing global simulations, with (gradually) decreasing grid resolution, to understand the effect of cloud-resolving scales on the general circulation. Our strategy, on the other hand, is to take a big leap forward by fixing the resolution at O(100 m), and gradually increasing the domain size. We believe that breaking this threshold would greatly help in improving the parameterization schemes and reducing the uncertainty in climate predictions. To take this forward, the German Federal Ministry of Education and Research has initiated a project on HD(CP)2 that aims for a limited area LES at resolution O(100 m) using the new unified modeling system ICON (Zängl et al., 2014). In the talk, results from the HD(CP)2 evaluation simulation will be shown that targets high resolution simulation over a small domain around Jülich, Germany. This site is chosen because high resolution HD(CP)2 Observational Prototype Experiment took place in this region from 1.04.2013 to 31.05.2013, in order to critically evaluate the model. Nesting capabilities of ICON is used to gradually increase the resolution from the outermost domain, which is forced from the COSMO-DE data, to the innermost and finest resolution domain centered around Jülich (see Fig. 1 top panel). Furthermore, detailed analyses of the simulation results against the observation data will be presented. A reprsentative figure showing time series of column integrated water vapor (IWV) for both model and observation on 24.04.2013 is shown in bottom panel of Fig. 1.

Aircraft applications of fault detection and isolation techniques

NASA Astrophysics Data System (ADS)

Marcos Esteban, Andres

In this thesis the problems of fault detection & isolation and fault tolerant systems are studied from the perspective of LTI frequency-domain, model-based techniques. Emphasis is placed on the applicability of these LTI techniques to nonlinear models, especially to aerospace systems. Two applications of Hinfinity LTI fault diagnosis are given using an open-loop (no controller) design approach: one for the longitudinal motion of a Boeing 747-100/200 aircraft, the other for a turbofan jet engine. An algorithm formalizing a robust identification approach based on model validation ideas is also given and applied to the previous jet engine. A general linear fractional transformation formulation is given in terms of the Youla and Dual Youla parameterizations for the integrated (control and diagnosis filter) approach. This formulation provides better insight into the trade-off between the control and the diagnosis objectives. It also provides the basic groundwork towards the development of nested schemes for the integrated approach. These nested structures allow iterative improvements on the control/filter Youla parameters based on successive identification of the system uncertainty (as given by the Dual Youla parameter). The thesis concludes with an application of Hinfinity LTI techniques to the integrated design for the longitudinal motion of the previous Boeing 747-100/200 model.

Evaluating and Understanding Parameterized Convective Processes and Their Role in the Development of Mesoscale Precipitation Systems

NASA Technical Reports Server (NTRS)

Fritsch, J. Michael; Kain, John S.

1996-01-01

Research efforts focused on numerical simulations of two convective systems with the Penn State/NCAR mesoscale model. The first of these systems was tropical cyclone Irma, which occurred in 1987 in Australia's Gulf of Carpentaria during the AMEX field program. Comparison simulations of this system were done with two different convective parameterization schemes (CPS's), the Kain-Fritsch (KF) and the Betts-Miller (BM) schemes. The second system was the June 10-11, 1985 squall line simulation, which occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. Simulations of this system using the KF scheme were examined in detail.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

PubMed Central

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

Application of Seasonal CRM Integrations to Develop Statistics and Improved GCM Parameterization of Subgrid Cloud-Radiation Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiaoqing Wu; Xin-Zhong Liang; Sunwook Park

2007-01-23

The works supported by this ARM project lay the solid foundation for improving the parameterization of subgrid cloud-radiation interactions in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and concurrent ARM observations to produce long-term, consistent cloud and radiative property datasets at the cloud scale (Wu et al. 2006, 2007). With these datasets, we have investigated the mesoscale enhancement of cloud systems on surface heat fluxes (Wu and Guimond 2006), quantified the effects of cloud horizontal inhomogeneity and vertical overlap on the domain-averaged radiative fluxes (Wu and Liang 2005), and subsequently validatedmore » and improved the physically-based mosaic treatment of subgrid cloud-radiation interactions (Liang and Wu 2005). We have implemented the mosaic treatment into the CCM3. The 5-year (1979-1983) AMIP-type simulation showed significant impacts of subgrid cloud-radiation interaction on the climate simulations (Wu and Liang 2005). We have actively participated in CRM intercomparisons that foster the identification and physical understanding of common errors in cloud-scale modeling (Xie et al. 2005; Xu et al. 2005, Grabowski et al. 2005).« less

Sensitivity of a Cumulus Parameterization Scheme to Precipitation Production Representation and Its Impact on a Heavy Rain Event over Korea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Ji-Young; Hong, Song-You; Sunny Lim, Kyo-Sun

The sensitivity of a cumulus parameterization scheme (CPS) to a representation of precipitation production is examined. To do this, the parameter that determines the fraction of cloud condensate converted to precipitation in the simplified Arakawa–Schubert (SAS) convection scheme is modified following the results from a cloud-resolving simulation. While the original conversion parameter is assumed to be constant, the revised parameter includes a temperature dependency above the freezing level, whichleadstolessproductionoffrozenprecipitating condensate with height. The revised CPS has been evaluated for a heavy rainfall event over Korea as well as medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). The inefficient conversionmore » of cloud condensate to convective precipitation at colder temperatures generally leads to a decrease in pre-cipitation, especially in the category of heavy rainfall. The resultant increase of detrained moisture induces moistening and cooling at the top of clouds. A statistical evaluation of the medium-range forecasts with the revised precipitation conversion parameter shows an overall improvement of the forecast skill in precipitation and large-scale fields, indicating importance of more realistic representation of microphysical processes in CPSs.« less

A New Canopy Integration Factor

NASA Astrophysics Data System (ADS)

Badgley, G.; Anderegg, L. D. L.; Baker, I. T.; Berry, J. A.

2017-12-01

Ecosystem modelers have long debated how to best represent within-canopy heterogeneity. Can one big leaf represent the full range of canopy physiological responses? Or you need two leaves - sun and shade - to get things right? Is it sufficient to treat the canopy as a diffuse medium? Or would it be better to explicitly represent separate canopy layers? These are open questions that have been subject of an enormous amount of research and scrutiny. Yet regardless of how the canopy is represented, each model must grapple with correctly parameterizing its canopy in a way that properly translates leaf-level processes to the canopy and ecosystem scale. We present a new approach for integrating whole-canopy biochemistry by combining remote sensing with ecological theory. Using the Simple Biosphere model (SiB), we redefined how SiB scales photosynthetic processes from leaf-to-canopy as a function of satellite-derived measurements of solar-induced chlorophyll fluorescence (SIF). Across multiple long-term study sites, our approach improves the accuracy of daily modeled photosynthesis by as much as 25 percent. We share additional insights on how SIF might be more directly integrated into photosynthesis models, as well as present ideas for harnessing SIF to more accurately parameterize canopy biochemical variables.

Limitations of one-dimensional mesoscale PBL parameterizations in reproducing mountain-wave flows

DOE PAGES

Munoz-Esparza, Domingo; Sauer, Jeremy A.; Linn, Rodman R.; ...

2015-12-08

In this study, mesoscale models are considered to be the state of the art in modeling mountain-wave flows. Herein, we investigate the role and accuracy of planetary boundary layer (PBL) parameterizations in handling the interaction between large-scale mountain waves and the atmospheric boundary layer. To that end, we use recent large-eddy simulation (LES) results of mountain waves over a symmetric two-dimensional bell-shaped hill [Sauer et al., J. Atmos. Sci. (2015)], and compare them to four commonly used PBL schemes. We find that one-dimensional PBL parameterizations produce reasonable agreement with the LES results in terms of vertical wavelength, amplitude of velocitymore » and turbulent kinetic energy distribution in the downhill shooting flow region. However, the assumption of horizontal homogeneity in PBL parameterizations does not hold in the context of these complex flow configurations. This inappropriate modeling assumption results in a vertical wavelength shift producing errors of ≈ 10 m s–1 at downstream locations due to the presence of a coherent trapped lee wave that does not mix with the atmospheric boundary layer. In contrast, horizontally-integrated momentum flux derived from these PBL schemes displays a realistic pattern. Therefore results from mesoscale models using ensembles of one-dimensional PBL schemes can still potentially be used to parameterize drag effects in general circulation models. Nonetheless, three-dimensional PBL schemes must be developed in order for mesoscale models to accurately represent complex-terrain and other types of flows where one-dimensional PBL assumptions are violated.« less

Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system

USGS Publications Warehouse

Olabarrieta, Maitane; Warner, John C.; Armstrong, Brandy N.; Zambon, Joseph B.; He, Ruoying

2012-01-01

The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor'Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor'easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor'Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.

Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system

USGS Publications Warehouse

Olabarrieta, Maitane; Warner, John C.; Armstrong, Brandy N.; Zambon, Joseph B.; He, Ruoying

2012-01-01

The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor’Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor’easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor’Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.

How well does your model capture the terrestrial ecosystem dynamics of the Arctic-Boreal Region?

NASA Astrophysics Data System (ADS)

Stofferahn, E.; Fisher, J. B.; Hayes, D. J.; Huntzinger, D. N.; Schwalm, C.

2016-12-01

The Arctic-Boreal Region (ABR) is a major source of uncertainties for terrestrial biosphere model (TBM) simulations. These uncertainties are precipitated by a lack of observational data from the region, affecting the parameterizations of cold environment processes in the models. Addressing these uncertainties requires a coordinated effort of data collection and integration of the following key indicators of the ABR ecosystem: disturbance, flora / fauna and related ecosystem function, carbon pools and biogeochemistry, permafrost, and hydrology. We are developing a model-data integration framework for NASA's Arctic Boreal Vulnerability Experiment (ABoVE), wherein data collection for the key ABoVE indicators is driven by matching observations and model outputs to the ABoVE indicators. The data are used as reference datasets for a benchmarking system which evaluates TBM performance with respect to ABR processes. The benchmarking system utilizes performance metrics to identify intra-model and inter-model strengths and weaknesses, which in turn provides guidance to model development teams for reducing uncertainties in TBM simulations of the ABR. The system is directly connected to the International Land Model Benchmarking (ILaMB) system, as an ABR-focused application.

Parameterized post-Newtonian cosmology

NASA Astrophysics Data System (ADS)

Sanghai, Viraj A. A.; Clifton, Timothy

2017-03-01

Einstein’s theory of gravity has been extensively tested on solar system scales, and for isolated astrophysical systems, using the perturbative framework known as the parameterized post-Newtonian (PPN) formalism. This framework is designed for use in the weak-field and slow-motion limit of gravity, and can be used to constrain a large class of metric theories of gravity with data collected from the aforementioned systems. Given the potential of future surveys to probe cosmological scales to high precision, it is a topic of much contemporary interest to construct a similar framework to link Einstein’s theory of gravity and its alternatives to observations on cosmological scales. Our approach to this problem is to adapt and extend the existing PPN formalism for use in cosmology. We derive a set of equations that use the same parameters to consistently model both weak fields and cosmology. This allows us to parameterize a large class of modified theories of gravity and dark energy models on cosmological scales, using just four functions of time. These four functions can be directly linked to the background expansion of the universe, first-order cosmological perturbations, and the weak-field limit of the theory. They also reduce to the standard PPN parameters on solar system scales. We illustrate how dark energy models and scalar-tensor and vector-tensor theories of gravity fit into this framework, which we refer to as ‘parameterized post-Newtonian cosmology’ (PPNC).

Impact of different parameterization schemes on simulation of mesoscale convective system over south-east India

NASA Astrophysics Data System (ADS)

Madhulatha, A.; Rajeevan, M.

2018-02-01

Main objective of the present paper is to examine the role of various parameterization schemes in simulating the evolution of mesoscale convective system (MCS) occurred over south-east India. Using the Weather Research and Forecasting (WRF) model, numerical experiments are conducted by considering various planetary boundary layer, microphysics, and cumulus parameterization schemes. Performances of different schemes are evaluated by examining boundary layer, reflectivity, and precipitation features of MCS using ground-based and satellite observations. Among various physical parameterization schemes, Mellor-Yamada-Janjic (MYJ) boundary layer scheme is able to produce deep boundary layer height by simulating warm temperatures necessary for storm initiation; Thompson (THM) microphysics scheme is capable to simulate the reflectivity by reasonable distribution of different hydrometeors during various stages of system; Betts-Miller-Janjic (BMJ) cumulus scheme is able to capture the precipitation by proper representation of convective instability associated with MCS. Present analysis suggests that MYJ, a local turbulent kinetic energy boundary layer scheme, which accounts strong vertical mixing; THM, a six-class hybrid moment microphysics scheme, which considers number concentration along with mixing ratio of rain hydrometeors; and BMJ, a closure cumulus scheme, which adjusts thermodynamic profiles based on climatological profiles might have contributed for better performance of respective model simulations. Numerical simulation carried out using the above combination of schemes is able to capture storm initiation, propagation, surface variations, thermodynamic structure, and precipitation features reasonably well. This study clearly demonstrates that the simulation of MCS characteristics is highly sensitive to the choice of parameterization schemes.

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

Zhang, Yanjun; Tao, Gang; Chen, Mou

2016-09-01

This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

The Soil Model Development and Intercomparison Panel (SoilMIP) of the International Soil Modeling Consortium (ISMC)

NASA Astrophysics Data System (ADS)

Vanderborght, Jan; Priesack, Eckart

2017-04-01

The Soil Model Development and Intercomparison Panel (SoilMIP) is an initiative of the International Soil Modeling Consortium. Its mission is to foster the further development of soil models that can predict soil functions and their changes (i) due to soil use and land management and (ii) due to external impacts of climate change and pollution. Since soil functions and soil threats are diverse but linked with each other, the overall aim is to develop holistic models that represent the key functions of the soil system and the links between them. These models should be scaled up and integrated in terrestrial system models that describe the feedbacks between processes in the soil and the other terrestrial compartments. We propose and illustrate a few steps that could be taken to achieve these goals. A first step is the development of scenarios that compare simulations by models that predict the same or different soil services. Scenarios can be considered at three different levels of comparisons: scenarios that compare the numerics (accuracy but also speed) of models, scenarios that compare the effect of differences in process descriptions, and scenarios that compare simulations with experimental data. A second step involves the derivation of metrics or summary statistics that effectively compare model simulations and disentangle parameterization from model concept differences. These metrics can be used to evaluate how more complex model simulations can be represented by simpler models using an appropriate parameterization. A third step relates to the parameterization of models. Application of simulation models implies that appropriate model parameters have to be defined for a range of environmental conditions and locations. Spatial modelling approaches are used to derive parameter distributions. Considering that soils and their properties emerge from the interaction between physical, chemical and biological processes, the combination of spatial models with process models would lead to consistent parameter distributions correlations and could potentially represent self-organizing processes in soils and landscapes.

Human Mars Entry, Descent, and Landing Architecture Study Overview

NASA Technical Reports Server (NTRS)

Cianciolo, Alicia D.; Polsgrove, Tara T.

2016-01-01

The Entry, Descent, and Landing (EDL) Architecture Study is a multi-NASA center activity to analyze candidate EDL systems as they apply to human Mars landing in the context of the Evolvable Mars Campaign. The study, led by the Space Technology Mission Directorate (STMD), is performed in conjunction with the NASA's Science Mission Directorate and the Human Architecture Team, sponsored by NASA's Human Exploration and Operations Mission Directorate. The primary objective is to prioritize future STMD EDL technology investments by (1) generating Phase A-level designs for selected concepts to deliver 20 t human class payloads, (2) developing a parameterized mass model for each concept capable of examining payloads between 5 and 40 t, and (3) evaluating integrated system performance using trajectory simulations. This paper summarizes the initial study results.

SUBGRID PARAMETERIZATION OF SNOW DISTRIBUTION FOR AN ENERGY AND MASS BALANCE SNOW COVER MODEL. (R824784)

EPA Science Inventory

Representation of sub-element scale variability in snow accumulation and ablation is increasingly recognized as important in distributed hydrologic modelling. Representing sub-grid scale variability may be accomplished through numerical integration of a nested grid or through a l...

System integration of wind and solar power in integrated assessment models: A cross-model evaluation of new approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pietzcker, Robert C.; Ueckerdt, Falko; Carrara, Samuel

Mitigation-Process Integrated Assessment Models (MP-IAMs) are used to analyze long-term transformation pathways of the energy system required to achieve stringent climate change mitigation targets. Due to their substantial temporal and spatial aggregation, IAMs cannot explicitly represent all detailed challenges of integrating the variable renewable energies (VRE) wind and solar in power systems, but rather rely on parameterized modeling approaches. In the ADVANCE project, six international modeling teams have developed new approaches to improve the representation of power sector dynamics and VRE integration in IAMs. In this study, we qualitatively and quantitatively evaluate the last years' modeling progress and study themore » impact of VRE integration modeling on VRE deployment in IAM scenarios. For a comprehensive and transparent qualitative evaluation, we first develop a framework of 18 features of power sector dynamics and VRE integration. We then apply this framework to the newly-developed modeling approaches to derive a detailed map of strengths and limitations of the different approaches. For the quantitative evaluation, we compare the IAMs to the detailed hourly-resolution power sector model REMIX. We find that the new modeling approaches manage to represent a large number of features of the power sector, and the numerical results are in reasonable agreement with those derived from the detailed power sector model. Updating the power sector representation and the cost and resources of wind and solar substantially increased wind and solar shares across models: Under a carbon price of 30$/tCO2 in 2020 (increasing by 5% per year), the model-average cost-minimizing VRE share over the period 2050-2100 is 62% of electricity generation, 24%-points higher than with the old model version.« less

Developing Remote Sensing Products for Monitoring and Modeling Great Lakes Coastal Wetland Vulnerability to Climate Change and Land Use

NASA Astrophysics Data System (ADS)

Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W.

2014-12-01

Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to improve the hydrological model through higher resolution products and parameterization of variables that have previously been largely unknown.

Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.

PubMed

Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong

2017-10-01

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.

Prototype of an Integrated Hurricane Information System for Research: Description and Illustration of its Use in Evaluating WRF Model Simulations

NASA Astrophysics Data System (ADS)

Hristova-Veleva, S.; Chao, Y.; Vane, D.; Lambrigtsen, B.; Li, P. P.; Knosp, B.; Vu, Q. A.; Su, H.; Dang, V.; Fovell, R.; Tanelli, S.; Garay, M.; Willis, J.; Poulsen, W.; Fishbein, E.; Ao, C. O.; Vazquez, J.; Park, K. J.; Callahan, P.; Marcus, S.; Haddad, Z.; Fetzer, E.; Kahn, R.

2007-12-01

In spite of recent improvements in hurricane track forecast accuracy, currently there are still many unanswered questions about the physical processes that determine hurricane genesis, intensity, track and impact on large- scale environment. Furthermore, a significant amount of work remains to be done in validating hurricane forecast models, understanding their sensitivities and improving their parameterizations. None of this can be accomplished without a comprehensive set of multiparameter observations that are relevant to both the large- scale and the storm-scale processes in the atmosphere and in the ocean. To address this need, we have developed a prototype of a comprehensive hurricane information system of high- resolution satellite, airborne and in-situ observations and model outputs pertaining to: i) the thermodynamic and microphysical structure of the storms; ii) the air-sea interaction processes; iii) the larger-scale environment as depicted by the SST, ocean heat content and the aerosol loading of the environment. Our goal was to create a one-stop place to provide the researchers with an extensive set of observed hurricane data, and their graphical representation, together with large-scale and convection-resolving model output, all organized in an easy way to determine when coincident observations from multiple instruments are available. Analysis tools will be developed in the next step. The analysis tools will be used to determine spatial, temporal and multiparameter covariances that are needed to evaluate model performance, provide information for data assimilation and characterize and compare observations from different platforms. We envision that the developed hurricane information system will help in the validation of the hurricane models, in the systematic understanding of their sensitivities and in the improvement of the physical parameterizations employed by the models. Furthermore, it will help in studying the physical processes that affect hurricane development and impact on large-scale environment. This talk will describe the developed prototype of the hurricane information systems. Furthermore, we will use a set of WRF hurricane simulations and compare simulated to observed structures to illustrate how the information system can be used to discriminate between simulations that employ different physical parameterizations. The work described here was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics ans Space Administration.

QUANTIFYING THE CLIMATE, AIR QUALITY AND HEALTH BENEFITS OF IMPROVED COOKSTOVES: AN INTEGRATED LABORATORY, FIELD AND MODELING STUDY

EPA Science Inventory

Expected results and outputs include: extensive dataset of in-field and laboratory emissions data for traditional and improved cookstoves; parameterization to predict cookstove emissions from drive cycle data; indoor and personal exposure data for traditional and improved cook...

Can avian reproductive outcomes estimated with MCnest be made more robust using stochastic parameterizations?

EPA Science Inventory

The Markov chain nest productivity model, or MCnest, is a set of algorithms for integrating the results of avian toxicity tests with reproductive life-history data to project the relative magnitude of chemical effects on avian reproduction. The mathematical foundation of MCnest i...

Evaluating and Understanding Parameterized Convective Processes and Their Role in the Development of Mesoscale Precipitation Systems

NASA Technical Reports Server (NTRS)

Fritsch, J. Michael (Principal Investigator); Kain, John S.

1995-01-01

Research efforts during the first year focused on numerical simulations of two convective systems with the Penn State/NCAR mesoscale model. The first of these systems was tropical cyclone Irma, which occurred in 1987 in Australia's Gulf of Carpentaria during the AMEX field program. Comparison simulations of this system were done with two different convective parameterization schemes (CPS's), the Kain-Fritsch (1993 - KF) and the Betts-Miller (Betts 1986- BM) schemes. The second system was the June 10-11 1985 squall line simulation, which occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. Simulations of this system using the KF scheme were examined in detail.

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

NASA Technical Reports Server (NTRS)

Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N.

2016-01-01

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

Attitude/attitude-rate estimation from GPS differential phase measurements using integrated-rate parameters

NASA Technical Reports Server (NTRS)

Oshman, Yaakov; Markley, Landis

1998-01-01

A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.

The uniform quantized electron gas revisited

NASA Astrophysics Data System (ADS)

Lomba, Enrique; Høye, Johan S.

2017-11-01

In this article we continue and extend our recent work on the correlation energy of the quantized electron gas of uniform density at temperature T=0 . As before, we utilize the methods, properties, and results obtained by means of classical statistical mechanics. These were extended to quantized systems via the Feynman path integral formalism. The latter translates the quantum problem into a classical polymer problem in four dimensions. Again, the well known RPA (random phase approximation) is recovered as a basic result which we then modify and improve upon. Here we analyze the condition of thermodynamic self-consistency. Our numerical calculations exhibit a remarkable agreement with well known results of a standard parameterization of Monte Carlo correlation energies.

A theory-based parameterization for heterogeneous ice nucleation and implications for the simulation of ice processes in atmospheric models

NASA Astrophysics Data System (ADS)

Savre, J.; Ekman, A. M. L.

2015-05-01

A new parameterization for heterogeneous ice nucleation constrained by laboratory data and based on classical nucleation theory is introduced. Key features of the parameterization include the following: a consistent and modular modeling framework for treating condensation/immersion and deposition freezing, the possibility to consider various potential ice nucleating particle types (e.g., dust, black carbon, and bacteria), and the possibility to account for an aerosol size distribution. The ice nucleating ability of each aerosol type is described using a contact angle (θ) probability density function (PDF). A new modeling strategy is described to allow the θ PDF to evolve in time so that the most efficient ice nuclei (associated with the lowest θ values) are progressively removed as they nucleate ice. A computationally efficient quasi Monte Carlo method is used to integrate the computed ice nucleation rates over both size and contact angle distributions. The parameterization is employed in a parcel model, forced by an ensemble of Lagrangian trajectories extracted from a three-dimensional simulation of a springtime low-level Arctic mixed-phase cloud, in order to evaluate the accuracy and convergence of the method using different settings. The same model setup is then employed to examine the importance of various parameters for the simulated ice production. Modeling the time evolution of the θ PDF is found to be particularly crucial; assuming a time-independent θ PDF significantly overestimates the ice nucleation rates. It is stressed that the capacity of black carbon (BC) to form ice in the condensation/immersion freezing mode is highly uncertain, in particular at temperatures warmer than -20°C. In its current version, the parameterization most likely overestimates ice initiation by BC.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE PAGES

Cai, X.; Yang, Z. -L.; Fisher, J. B.; ...

2016-01-15

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, X.; Yang, Z. -L.; Fisher, J. B.

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

The GIS weasel - An interface for the development of spatial information in modeling

USGS Publications Warehouse

Viger, R.J.; Markstrom, S.M.; Leavesley, G.H.; ,

2005-01-01

The GIS Weasel is a map and Graphical User Interface (GUI) driven tool that has been developed as an aid to modelers in the delineation, characterization of geographic features, and their parameterization for use in distributed or lumped parameter physical process models. The interface does not require user expertise in geographic information systems (GIS). The user does need knowledge of how the model will use the output from the GIS Weasel. The GIS Weasel uses Workstation ArcInfo and its the Grid extension. The GIS Weasel will run on all platforms that Workstation ArcInfo runs (i.e. numerous flavors of Unix and Microsoft Windows).The GIS Weasel requires an input ArcInfo grid of some topographical description of the Area of Interest (AOI). This is normally a digital elevation model, but can be the surface of a ground water table or any other data that flow direction can be resolved from. The user may define the AOI as a custom drainage area based on an interactively specified watershed outlet point, or use a previously created map. The user is then able to use any combination of the GIS Weasel's tool set to create one or more maps for depicting different kinds of geographic features. Once the spatial feature maps have been prepared, then the GIS Weasel s many parameterization routines can be used to create descriptions of each element in each of the user s created maps. Over 200 parameterization routines currently exist, generating information about shape, area, and topological association with other features of the same or different maps, as well many types of information based on ancillary data layers such as soil and vegetation properties. These tools easily integrate other similarly formatted data sets.

Parameterization of Cirrus Cloud Vertical Profiles and Geometrical Thickness Using CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Khatri, P.; Iwabuchi, H.; Saito, M.

2017-12-01

High-level cirrus clouds, which normally occur over more than 20% of the globe, are known to have profound impacts on energy budget and climate change. The scientific knowledge regarding the vertical structure of such high-level cirrus clouds and their geometrical thickness are relatively poorer compared to low-level water clouds. Knowledge regarding cloud vertical structure is especially important in passive remote sensing of cloud properties using infrared channels or channels strongly influenced by gaseous absorption when clouds are geometrically thick and optically thin. Such information is also very useful for validating cloud resolving numerical models. This study analyzes global scale data of ice clouds identified by Cloud profiling Radar (CPR) onboard CloudSat and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO to parameterize (i) vertical profiles of ice water content (IWC), cloud-particle effective radius (CER), and ice-particle number concentration for varying ice water path (IWP) values and (ii) the relation of cloud geometrical thickness (CGT) with IWP and CER for varying cloud top temperature (CTT) values. It is found that the maxima in IWC and CER profile shifts towards cloud base with the increase of IWP. Similarly, if the cloud properties remain same, CGT shows an increasing trend with the decrease of CTT. The implementation of such cloud vertical inhomogeneity parameterization in the forward model used in the Integrated Cloud Analysis System ICAS (Iwabuchi et al., 2016) generally shows increase of brightness temperatures in infrared channels compared to vertically homogeneous cloud assumption. The cloud vertical inhomogeneity is found to bring noticeable changes in retrieved cloud properties. Retrieved CER and cloud top height become larger for optically thick cloud. We will show results of comparison of cloud properties retrieved from infrared measurements and active remote sensing.

A review of recent research on improvement of physical parameterizations in the GLA GCM

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.

1990-01-01

A systematic assessment of the effect of a series of improvements in physical parameterizations of the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) are summarized. The implementation of the Simple Biosphere Model (SiB) in the GCM is followed by a comparison of SiB GCM simulations with that of the earlier slab soil hydrology GCM (SSH-GCM) simulations. In the Sahelian context, the biogeophysical component of desertification was analyzed for SiB-GCM simulations. Cumulus parameterization is found to be the primary determinant of the organization of the simulated tropical rainfall of the GLA GCM using Arakawa-Schubert cumulus parameterization. A comparison of model simulations with station data revealed excessive shortwave radiation accompanied by excessive drying and heating to the land. The perpetual July simulations with and without interactive soil moisture shows that 30 to 40 day oscillations may be a natural mode of the simulated earth atmosphere system.

Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent

2016-11-25

The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. Themore » chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.« less

Coordinated Parameterization Development and Large-Eddy Simulation for Marine and Arctic Cloud-Topped Boundary Layers

NASA Technical Reports Server (NTRS)

Bretherton, Christopher S.

2002-01-01

The goal of this project was to compare observations of marine and arctic boundary layers with: (1) parameterization systems used in climate and weather forecast models; and (2) two and three dimensional eddy resolving (LES) models for turbulent fluid flow. Based on this comparison, we hoped to better understand, predict, and parameterize the boundary layer structure and cloud amount, type, and thickness as functions of large scale conditions that are predicted by global climate models. The principal achievements of the project were as follows: (1) Development of a novel boundary layer parameterization for large-scale models that better represents the physical processes in marine boundary layer clouds; and (2) Comparison of column output from the ECMWF global forecast model with observations from the SHEBA experiment. Overall the forecast model did predict most of the major precipitation events and synoptic variability observed over the year of observation of the SHEBA ice camp.

A note on: "A Gaussian-product stochastic Gent-McWilliams parameterization"

NASA Astrophysics Data System (ADS)

Jansen, Malte F.

2017-02-01

This note builds on a recent article by Grooms (2016), which introduces a new stochastic parameterization for eddy buoyancy fluxes. The closure proposed by Grooms accounts for the fact that eddy fluxes arise as the product of two approximately Gaussian variables, which in turn leads to a distinctly non-Gaussian distribution. The directionality of the stochastic eddy fluxes, however, remains somewhat ad-hoc and depends on the reference frame of the chosen coordinate system. This note presents a modification of the approach proposed by Grooms, which eliminates this shortcoming. Eddy fluxes are computed based on a stochastic mixing length model, which leads to a frame invariant formulation. As in the original closure proposed by Grooms, eddy fluxes are proportional to the product of two Gaussian variables, and the parameterization reduces to the Gent and McWilliams parameterization for the mean buyoancy fluxes.

A New Trans-Disciplinary Approach to Regional Integrated Assessment of Climate Impact and Adaptation in Agricultural Systems (Invited)

NASA Astrophysics Data System (ADS)

Antle, J. M.; Valdivia, R. O.; Jones, J.; Rosenzweig, C.; Ruane, A. C.

2013-12-01

This presentation provides an overview of the new methods developed by researchers in the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for regional climate impact assessment and analysis of adaptation in agricultural systems. This approach represents a departure from approaches in the literature in several dimensions. First, the approach is based on the analysis of agricultural systems (not individual crops) and is inherently trans-disciplinary: it is based on a deep collaboration among a team of climate scientists, agricultural scientists and economists to design and implement regional integrated assessments of agricultural systems. Second, in contrast to previous approaches that have imposed future climate on models based on current socio-economic conditions, this approach combines bio-physical and economic models with a new type of pathway analysis (Representative Agricultural Pathways) to parameterize models consistent with a plausible future world in which climate change would be occurring. Third, adaptation packages for the agricultural systems in a region are designed by the research team with a level of detail that is useful to decision makers, such as research administrators and donors, who are making agricultural R&D investment decisions. The approach is illustrated with examples from AgMIP's projects currently being carried out in Africa and South Asia.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

NASA Astrophysics Data System (ADS)

White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John

2017-08-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

USGS Publications Warehouse

White, Jeremy; Stengel, Victoria G.; Rendon, Samuel H.; Banta, John

2017-01-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

Active Fault Tolerant Control for Ultrasonic Piezoelectric Motor

NASA Astrophysics Data System (ADS)

Boukhnifer, Moussa

2012-07-01

Ultrasonic piezoelectric motor technology is an important system component in integrated mechatronics devices working on extreme operating conditions. Due to these constraints, robustness and performance of the control interfaces should be taken into account in the motor design. In this paper, we apply a new architecture for a fault tolerant control using Youla parameterization for an ultrasonic piezoelectric motor. The distinguished feature of proposed controller architecture is that it shows structurally how the controller design for performance and robustness may be done separately which has the potential to overcome the conflict between performance and robustness in the traditional feedback framework. A fault tolerant control architecture includes two parts: one part for performance and the other part for robustness. The controller design works in such a way that the feedback control system will be solely controlled by the proportional plus double-integral PI2 performance controller for a nominal model without disturbances and H∞ robustification controller will only be activated in the presence of the uncertainties or an external disturbances. The simulation results demonstrate the effectiveness of the proposed fault tolerant control architecture.

The integrated effects of future climate and hydrologic uncertainty on sustainable flood risk management

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Wi, S.; Brown, C. M.

2013-12-01

Flood risk management performance is investigated within the context of integrated climate and hydrologic modeling uncertainty to explore system robustness. The research question investigated is whether structural and hydrologic parameterization uncertainties are significant relative to other uncertainties such as climate change when considering water resources system performance. Two hydrologic models are considered, a conceptual, lumped parameter model that preserves the water balance and a physically-based model that preserves both water and energy balances. In the conceptual model, parameter and structural uncertainties are quantified and propagated through the analysis using a Bayesian modeling framework with an innovative error model. Mean climate changes and internal climate variability are explored using an ensemble of simulations from a stochastic weather generator. The approach presented can be used to quantify the sensitivity of flood protection adequacy to different sources of uncertainty in the climate and hydrologic system, enabling the identification of robust projects that maintain adequate performance despite the uncertainties. The method is demonstrated in a case study for the Coralville Reservoir on the Iowa River, where increased flooding over the past several decades has raised questions about potential impacts of climate change on flood protection adequacy.

Landau singularities and symbology: One- and two-loop MHV amplitudes in SYM theory

DOE PAGES

Dennen, Tristan; Spradlin, Marcus; Volovich, Anastasia

2016-03-14

We apply the Landau equations, whose solutions parameterize the locus of possible branch points, to the one- and two-loop Feynman integrals relevant to MHV amplitudes in planar N = 4 super-Yang-Mills theory. We then identify which of the Landau singularities appear in the symbols of the amplitudes, and which do not. Finally, we observe that all of the symbol entries in the two-loop MHV amplitudes are already present as Landau singularities of one-loop pentagon integrals.

Development of a Three-Dimensional Spectral Element Model for NWP: Idealized Simulations on the Sphere

NASA Astrophysics Data System (ADS)

Viner, K.; Reinecke, P. A.; Gabersek, S.; Flagg, D. D.; Doyle, J. D.; Martini, M.; Ryglicki, D.; Michalakes, J.; Giraldo, F.

2016-12-01

NEPTUNE: the Navy Environmental Prediction sysTem Using the NUMA*corE, is a 3D spectral element atmospheric model composed of a full suite of physics parameterizations and pre- and post-processing infrastructure with plans for data assimilation and coupling components to a variety of Earth-system models. This talk will focus on the initial struggles and solutions in adapting NUMA for stable and accurate integration on the sphere using both the deep atmosphere equations and a newly developed shallow-atmosphere approximation, as demonstrated through idealized test cases. In addition, details of the physics-dynamics coupling methodology will be discussed. NEPTUNE results for test cases from the 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) will be shown and discussed. *NUMA: Nonhydrostatic Unified Model of the Atmosphere; Kelly and Giraldo 2012, JCP

iTOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

NASA Astrophysics Data System (ADS)

Finsterle, S.; Commer, M.; Edmiston, J. K.; Jung, Y.; Kowalsky, M. B.; Pau, G. S. H.; Wainwright, H. M.; Zhang, Y.

2017-11-01

iTOUGH2 is a simulation-optimization framework for the TOUGH suite of nonisothermal multiphase flow models and related simulators of geophysical, geochemical, and geomechanical processes. After appropriate parameterization of subsurface structures and their properties, iTOUGH2 runs simulations for multiple parameter sets and analyzes the resulting output for parameter estimation through automatic model calibration, local and global sensitivity analyses, data-worth analyses, and uncertainty propagation analyses. Development of iTOUGH2 is driven by scientific challenges and user needs, with new capabilities continually added to both the forward simulator and the optimization framework. This review article provides a summary description of methods and features implemented in iTOUGH2, and discusses the usefulness and limitations of an integrated simulation-optimization workflow in support of the characterization and analysis of complex multiphysics subsurface systems.

Multi-Level Adaptation in End-User Development of 3D Virtual Chemistry Experiments

ERIC Educational Resources Information Center

Liu, Chang; Zhong, Ying

2014-01-01

Multi-level adaptation in end-user development (EUD) is an effective way to enable non-technical end users such as educators to gradually introduce more functionality with increasing complexity to 3D virtual learning environments developed by themselves using EUD approaches. Parameterization, integration, and extension are three levels of…

MODEL EVALUATION SCIENCE TO MEET TODAY'S QUALITY ASSURANCE REQUIREMENTS FOR REGULATORY USE: ADDRESSING UNCERTAINTY, SENSITIVITY, AND PARAMETERIZATION

EPA Science Inventory

The EPA/ORD National Exposure Research Lab's (NERL) UA/SA/PE research program addresses both tactical and strategic needs in direct support of ORD's client base. The design represents an integrated approach in achieving the highest levels of quality assurance in environmental de...

MEETING IN TUCSON: MODEL EVALUATION SCIENCE TO MEET TODAY'S QUALITY ASSURANCE REQUIREMENTS FOR REGULATORY USE: ADDRESSING UNCERTAINTY, SENSITIVITY, AND PARAMETERIZATION

EPA Science Inventory

The EPA/ORD National Exposure Research Lab's (NERL) UA/SA/PE research program addresses both tactical and strategic needs in direct support of ORD's client base. The design represents an integrated approach in achieving the highest levels of quality assurance in environmental dec...

An Integrated Modeling and Observational Study of Three-Dimensional Upper Ocean Boundary Layer Dynamics and Parameterizations

DTIC Science & Technology

2012-04-26

for public release ; distribution is unlimited. 4 Figure 3. First Kuroshio survey. Colors show MODIS SST image. Inset shows the survey...Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, USA. *To whom correspondence should be addressed. E-mail: stevens@scripps.edu 15

Integrated calibration of multiview phase-measuring profilometry

NASA Astrophysics Data System (ADS)

Lee, Yeong Beum; Kim, Min H.

2017-11-01

Phase-measuring profilometry (PMP) measures per-pixel height information of a surface with high accuracy. Height information captured by a camera in PMP relies on its screen coordinates. Therefore, a PMP measurement from a view cannot be integrated directly to other measurements from different views due to the intrinsic difference of the screen coordinates. In order to integrate multiple PMP scans, an auxiliary calibration of each camera's intrinsic and extrinsic properties is required, in addition to principal PMP calibration. This is cumbersome and often requires physical constraints in the system setup, and multiview PMP is consequently rarely practiced. In this work, we present a novel multiview PMP method that yields three-dimensional global coordinates directly so that three-dimensional measurements can be integrated easily. Our PMP calibration parameterizes intrinsic and extrinsic properties of the configuration of both a camera and a projector simultaneously. It also does not require any geometric constraints on the setup. In addition, we propose a novel calibration target that can remain static without requiring any mechanical operation while conducting multiview calibrations, whereas existing calibration methods require manually changing the target's position and orientation. Our results validate the accuracy of measurements and demonstrate the advantages on our multiview PMP.

A new parameterization for integrated population models to document amphibian reintroductions

USGS Publications Warehouse

Duarte, Adam; Pearl, Christopher; Adams, Michael J.; Peterson, James T.

2017-01-01

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog (Rana pretiosa) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010–2011 to 0.86 in 2012–2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data.

A new parameterization for integrated population models to document amphibian reintroductions.

PubMed

Duarte, Adam; Pearl, Christopher A; Adams, Michael J; Peterson, James T

2017-09-01

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog (Rana pretiosa) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010-2011 to 0.86 in 2012-2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data. © 2017 by the Ecological Society of America.

Holistic versus monomeric strategies for hydrological modelling of human-modified hydrosystems

NASA Astrophysics Data System (ADS)

Nalbantis, I.; Efstratiadis, A.; Rozos, E.; Kopsiafti, M.; Koutsoyiannis, D.

2011-03-01

The modelling of human-modified basins that are inadequately measured constitutes a challenge for hydrological science. Often, models for such systems are detailed and hydraulics-based for only one part of the system while for other parts oversimplified models or rough assumptions are used. This is typically a bottom-up approach, which seeks to exploit knowledge of hydrological processes at the micro-scale at some components of the system. Also, it is a monomeric approach in two ways: first, essential interactions among system components may be poorly represented or even omitted; second, differences in the level of detail of process representation can lead to uncontrolled errors. Additionally, the calibration procedure merely accounts for the reproduction of the observed responses using typical fitting criteria. The paper aims to raise some critical issues, regarding the entire modelling approach for such hydrosystems. For this, two alternative modelling strategies are examined that reflect two modelling approaches or philosophies: a dominant bottom-up approach, which is also monomeric and, very often, based on output information, and a top-down and holistic approach based on generalized information. Critical options are examined, which codify the differences between the two strategies: the representation of surface, groundwater and water management processes, the schematization and parameterization concepts and the parameter estimation methodology. The first strategy is based on stand-alone models for surface and groundwater processes and for water management, which are employed sequentially. For each model, a different (detailed or coarse) parameterization is used, which is dictated by the hydrosystem schematization. The second strategy involves model integration for all processes, parsimonious parameterization and hybrid manual-automatic parameter optimization based on multiple objectives. A test case is examined in a hydrosystem in Greece with high complexities, such as extended surface-groundwater interactions, ill-defined boundaries, sinks to the sea and anthropogenic intervention with unmeasured abstractions both from surface water and aquifers. Criteria for comparison are the physical consistency of parameters, the reproduction of runoff hydrographs at multiple sites within the studied basin, the likelihood of uncontrolled model outputs, the required amount of computational effort and the performance within a stochastic simulation setting. Our work allows for investigating the deterioration of model performance in cases where no balanced attention is paid to all components of human-modified hydrosystems and the related information. Also, sources of errors are identified and their combined effect are evaluated.

A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models

NASA Astrophysics Data System (ADS)

Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.

2016-12-01

Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.

Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nenes, Athanasios

The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated newmore » parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.« less

Quadratic Frequency Modulation Signals Parameter Estimation Based on Two-Dimensional Product Modified Parameterized Chirp Rate-Quadratic Chirp Rate Distribution.

PubMed

Qu, Zhiyu; Qu, Fuxin; Hou, Changbo; Jing, Fulong

2018-05-19

In an inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, the azimuth echo signals of the target are always modeled as multicomponent quadratic frequency modulation (QFM) signals. The chirp rate (CR) and quadratic chirp rate (QCR) estimation of QFM signals is very important to solve the ISAR image defocus problem. For multicomponent QFM (multi-QFM) signals, the conventional QR and QCR estimation algorithms suffer from the cross-term and poor anti-noise ability. This paper proposes a novel estimation algorithm called a two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD) for QFM signals parameter estimation. The 2D-PMPCRD employs a multi-scale parametric symmetric self-correlation function and modified nonuniform fast Fourier transform-Fast Fourier transform to transform the signals into the chirp rate-quadratic chirp rate (CR-QCR) domains. It can greatly suppress the cross-terms while strengthening the auto-terms by multiplying different CR-QCR domains with different scale factors. Compared with high order ambiguity function-integrated cubic phase function and modified Lv's distribution, the simulation results verify that the 2D-PMPCRD acquires higher anti-noise performance and obtains better cross-terms suppression performance for multi-QFM signals with reasonable computation cost.

Querying databases of trajectories of differential equations: Data structures for trajectories

NASA Technical Reports Server (NTRS)

Grossman, Robert

1989-01-01

One approach to qualitative reasoning about dynamical systems is to extract qualitative information by searching or making queries on databases containing very large numbers of trajectories. The efficiency of such queries depends crucially upon finding an appropriate data structure for trajectories of dynamical systems. Suppose that a large number of parameterized trajectories gamma of a dynamical system evolving in R sup N are stored in a database. Let Eta is contained in set R sup N denote a parameterized path in Euclidean Space, and let the Euclidean Norm denote a norm on the space of paths. A data structure is defined to represent trajectories of dynamical systems, and an algorithm is sketched which answers queries.

Effective Atomic Number, Mass Attenuation Coefficient Parameterization, and Implications for High-Energy X-Ray Cargo Inspection Systems

NASA Astrophysics Data System (ADS)

Langeveld, Willem G. J.

The most widely used technology for the non-intrusive active inspection of cargo containers and trucks is x-ray radiography at high energies (4-9 MeV). Technologies such as dual-energy imaging, spectroscopy, and statistical waveform analysis can be used to estimate the effective atomic number (Zeff) of the cargo from the x-ray transmission data, because the mass attenuation coefficient depends on energy as well as atomic number Z. The estimated effective atomic number, Zeff, of the cargo then leads to improved detection capability of contraband and threats, including special nuclear materials (SNM) and shielding. In this context, the exact meaning of effective atomic number (for mixtures and compounds) is generally not well-defined. Physics-based parameterizations of the mass attenuation coefficient have been given in the past, but usually for a limited low-energy range. Definitions of Zeff have been based, in part, on such parameterizations. Here, we give an improved parameterization at low energies (20-1000 keV) which leads to a well-defined Zeff. We then extend this parameterization up to energies relevant for cargo inspection (10 MeV), and examine what happens to the Zeff definition at these higher energies.

On the joint inversion of geophysical data for models of the coupled core-mantle system

NASA Technical Reports Server (NTRS)

Voorhies, Coerte V.

1991-01-01

Joint inversion of magnetic, earth rotation, geoid, and seismic data for a unified model of the coupled core-mantle system is proposed and shown to be possible. A sample objective function is offered and simplified by targeting results from independent inversions and summary travel time residuals instead of original observations. These data are parameterized in terms of a very simple, closed model of the topographically coupled core-mantle system. Minimization of the simplified objective function leads to a nonlinear inverse problem; an iterative method for solution is presented. Parameterization and method are emphasized; numerical results are not presented.

Reduction by invariants and projection of linear representations of Lie algebras applied to the construction of nonlinear realizations

NASA Astrophysics Data System (ADS)

Campoamor-Stursberg, R.

2018-03-01

A procedure for the construction of nonlinear realizations of Lie algebras in the context of Vessiot-Guldberg-Lie algebras of first-order systems of ordinary differential equations (ODEs) is proposed. The method is based on the reduction of invariants and projection of lowest-dimensional (irreducible) representations of Lie algebras. Applications to the description of parameterized first-order systems of ODEs related by contraction of Lie algebras are given. In particular, the kinematical Lie algebras in (2 + 1)- and (3 + 1)-dimensions are realized simultaneously as Vessiot-Guldberg-Lie algebras of parameterized nonlinear systems in R3 and R4, respectively.

WetNet: Using SSM/I data interactively for global distribution of tropical rainfall and precipitable water

NASA Technical Reports Server (NTRS)

Zipser, Edward J.; Mcguirk, James P.

1993-01-01

The research objectives were the following: (1) to use SSM/I to categorize, measure, and parameterize effects of rainfall systems around the globe, especially mesoscale convective systems; (2) to use SSM/I to monitor key components of the global hydrologic cycle, including tropical rainfall and precipitable water, and links to increasing sea surface temperatures; and (3) to assist in the development of efficient methods of exchange of massive satellite data bases and of analysis techniques, especially their use at a university. Numerous tasks have been initiated. First and foremost has been the integration and startup of the WetNet computer system into the TAMU computer network. Scientific activity was infeasible before completion of this activity. Final hardware delivery was not completed until October 1991, after which followed a period of identification and solution of several hardware and software and software problems. Accomplishments representing approximately four months work with the WetNEt system are presented.

GEWEX Cloud Systems Study (GCSS)

NASA Technical Reports Server (NTRS)

Moncrieff, Mitch

1993-01-01

The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.

Thermal Evolution of the Earth from a Plate Tectonics Point of View

NASA Astrophysics Data System (ADS)

Grigne, C.; Combes, M.; Le Yaouanq, S.; Husson, L.; Conrad, C. P.; Tisseau, C.

2011-12-01

Earth's thermal history is classically studied using scaling laws that link the surface heat loss to the temperature and viscosity of the convecting mantle. When such a parameterization is used in the global heat budget of the Earth to integrate the mantle temperature backwards in time, a runaway increase of temperature is obtained, leading to the so-called "thermal catastrophe". We propose a new approach that does not rely on convective scaling laws but instead considers the dynamics of plate tectonics, including temperature-dependent surface processes. We use a multi-agent system to simulate time-dependent plate tectonics in a 2D cylindrical geometry with evolutive plate boundaries. Plate velocities are computed using local force balance and explicit parameterizations for plate boundary processes such as trench migration, subduction initiation, continental breakup and plate suturing. The number of plates is not imposed but emerges naturally. At a given time step, heat flux is integrated from the seafloor age distribution and a global heat budget is used to compute the evolution of mantle temperature. This approach has a very low computational cost and allows us to study the effect of a wide range of input parameters on the long-term thermal evolution of the system. For Earth-like parameters, an average cooling rate of 60-70K per billion years is obtained, which is consistent with petrological and rheological constraints. Two time scales arise in the evolution of the heat flux: a linear long-term decrease and high-amplitude short-term fluctuations due to tectonic rearrangements. We show that the viscosity of the mantle is not a key parameter in the thermal evolution of the system and that no thermal catastrophe occurs when considering tectonic processes. The cooling rate of the Earth depends mainly on its ability to replace old insulating seafloor by young thin oceanic lithosphere. Therefore, the main controlling factors are parameters such as the resistance of continental lithosphere to breakup or the critical age for subduction initiation. We infer that simple convective considerations alone cannot account for the complex nature of mantle heat loss and that tectonic processes dictate the thermal evolution of the Earth.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

NASA Astrophysics Data System (ADS)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach), and iii) process-level evaluation at climate time-scales. The advantages and disadvantages of each approach will be identified and discussed, and some thoughts about possible future developments will be given.

A statistical comparison of cirrus particle size distributions measured using the 2-D stereo probe during the TC4, SPARTICUS, and MACPEX flight campaigns with historical cirrus datasets

NASA Astrophysics Data System (ADS)

Schwartz, M. Christian

2017-08-01

This paper addresses two straightforward questions. First, how similar are the statistics of cirrus particle size distribution (PSD) datasets collected using the Two-Dimensional Stereo (2D-S) probe to cirrus PSD datasets collected using older Particle Measuring Systems (PMS) 2-D Cloud (2DC) and 2-D Precipitation (2DP) probes? Second, how similar are the datasets when shatter-correcting post-processing is applied to the 2DC datasets? To answer these questions, a database of measured and parameterized cirrus PSDs - constructed from measurements taken during the Small Particles in Cirrus (SPARTICUS); Mid-latitude Airborne Cirrus Properties Experiment (MACPEX); and Tropical Composition, Cloud, and Climate Coupling (TC4) flight campaigns - is used.Bulk cloud quantities are computed from the 2D-S database in three ways: first, directly from the 2D-S data; second, by applying the 2D-S data to ice PSD parameterizations developed using sets of cirrus measurements collected using the older PMS probes; and third, by applying the 2D-S data to a similar parameterization developed using the 2D-S data themselves. This is done so that measurements of the same cloud volumes by parameterized versions of the 2DC and 2D-S can be compared with one another. It is thereby seen - given the same cloud field and given the same assumptions concerning ice crystal cross-sectional area, density, and radar cross section - that the parameterized 2D-S and the parameterized 2DC predict similar distributions of inferred shortwave extinction coefficient, ice water content, and 94 GHz radar reflectivity. However, the parameterization of the 2DC based on uncorrected data predicts a statistically significantly higher number of total ice crystals and a larger ratio of small ice crystals to large ice crystals than does the parameterized 2D-S. The 2DC parameterization based on shatter-corrected data also predicts statistically different numbers of ice crystals than does the parameterized 2D-S, but the comparison between the two is nevertheless more favorable. It is concluded that the older datasets continue to be useful for scientific purposes, with certain caveats, and that continuing field investigations of cirrus with more modern probes is desirable.

Achievements and challenges in structural bioinformatics and computational biophysics.

PubMed

Samish, Ilan; Bourne, Philip E; Najmanovich, Rafael J

2015-01-01

The field of structural bioinformatics and computational biophysics has undergone a revolution in the last 10 years. Developments that are captured annually through the 3DSIG meeting, upon which this article reflects. An increase in the accessible data, computational resources and methodology has resulted in an increase in the size and resolution of studied systems and the complexity of the questions amenable to research. Concomitantly, the parameterization and efficiency of the methods have markedly improved along with their cross-validation with other computational and experimental results. The field exhibits an ever-increasing integration with biochemistry, biophysics and other disciplines. In this article, we discuss recent achievements along with current challenges within the field. © The Author 2014. Published by Oxford University Press.

Achievements and challenges in structural bioinformatics and computational biophysics

PubMed Central

Samish, Ilan; Bourne, Philip E.; Najmanovich, Rafael J.

2015-01-01

Motivation: The field of structural bioinformatics and computational biophysics has undergone a revolution in the last 10 years. Developments that are captured annually through the 3DSIG meeting, upon which this article reflects. Results: An increase in the accessible data, computational resources and methodology has resulted in an increase in the size and resolution of studied systems and the complexity of the questions amenable to research. Concomitantly, the parameterization and efficiency of the methods have markedly improved along with their cross-validation with other computational and experimental results. Conclusion: The field exhibits an ever-increasing integration with biochemistry, biophysics and other disciplines. In this article, we discuss recent achievements along with current challenges within the field. Contact: Rafael.Najmanovich@USherbrooke.ca PMID:25488929

Foliage Density Distribution and Prediction of Intensively Managed Loblolly Pine

Treesearch

Yujia Zhang; Bruce E. Borders; Rodney E. Will; Hector De Los Santos Posadas

2004-01-01

The pipe model theory says that foliage biomass is proportional to the sapwood area at the base of the live crown. This knowledge was incorporated in an effort to develop a foliage biomass prediction model from integrating a stipulated foliage biomass distribution function within the crown. This model was parameterized using data collected from intensively managed...

The Roles of Internal Representation and Processing in Problem Solving Involving Insight: A Computational Complexity Perspective

ERIC Educational Resources Information Center

Wareham, Todd

2017-01-01

In human problem solving, there is a wide variation between individuals in problem solution time and success rate, regardless of whether or not this problem solving involves insight. In this paper, we apply computational and parameterized analysis to a plausible formalization of extended representation change theory (eRCT), an integration of…

Application of New Chorus Wave Model from Van Allen Probe Observations in Earth's Radiation Belt Modeling

NASA Astrophysics Data System (ADS)

Wang, D.; Shprits, Y.; Spasojevic, M.; Zhu, H.; Aseev, N.; Drozdov, A.; Kellerman, A. C.

2017-12-01

In situ satellite observations, theoretical studies and model simulations suggested that chorus waves play a significant role in the dynamic evolution of relativistic electrons in the Earth's radiation belts. In this study, we developed new wave frequency and amplitude models that depend on Magnetic Local Time (MLT)-, L-shell, latitude- and geomagnetic conditions indexed by Kp for upper-band and lower-band chorus waves using measurements from the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrument onboard the Van Allen Probes. Utilizing the quasi-linear full diffusion code, we calculated corresponding diffusion coefficients in each MLT sector (1 hour resolution) for upper-band and lower-band chorus waves according to the new developed wave models. Compared with former parameterizations of chorus waves, the new parameterizations result in differences in diffusion coefficients that depend on energy and pitch angle. Utilizing obtained diffusion coefficients, lifetime of energetic electrons is parameterized accordingly. In addition, to investigate effects of obtained diffusion coefficients in different MLT sectors and under different geomagnetic conditions, we performed simulations using four-dimensional Versatile Electron Radiation Belt simulations and validated results against observations.

Model-driven harmonic parameterization of the cortical surface: HIP-HOP.

PubMed

Auzias, G; Lefèvre, J; Le Troter, A; Fischer, C; Perrot, M; Régis, J; Coulon, O

2013-05-01

In the context of inter subject brain surface matching, we present a parameterization of the cortical surface constrained by a model of cortical organization. The parameterization is defined via an harmonic mapping of each hemisphere surface to a rectangular planar domain that integrates a representation of the model. As opposed to previous landmark-based registration methods we do not match folds between individuals but instead optimize the fit between cortical sulci and specific iso-coordinate axis in the model. This strategy overcomes some limitation to sulcus-based registration techniques such as topological variability in sulcal landmarks across subjects. Experiments on 62 subjects with manually traced sulci are presented and compared with the result of the Freesurfer software. The evaluation involves a measure of dispersion of sulci with both angular and area distortions. We show that the model-based strategy can lead to a natural, efficient and very fast (less than 5 min per hemisphere) method for defining inter subjects correspondences. We discuss how this approach also reduces the problems inherent to anatomically defined landmarks and open the way to the investigation of cortical organization through the notion of orientation and alignment of structures across the cortex.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, Hannah C.; Houze, Robert A.

To equitably compare the spatial pattern of ice microphysical processes produced by three microphysical parameterizations with each other, observations, and theory, simulations of tropical oceanic mesoscale convective systems (MCSs) in the Weather Research and Forecasting (WRF) model were forced to develop the same mesoscale circulations as observations by assimilating radial velocity data from a Doppler radar. The same general layering of microphysical processes was found in observations and simulations with deposition anywhere above the 0°C level, aggregation at and above the 0°C level, melting at and below the 0°C level, and riming near the 0°C level. Thus, this study ismore » consistent with the layered ice microphysical pattern portrayed in previous conceptual models and indicated by dual-polarization radar data. Spatial variability of riming in the simulations suggests that riming in the midlevel inflow is related to convective-scale vertical velocity perturbations. Finally, this study sheds light on limitations of current generally available bulk microphysical parameterizations. In each parameterization, the layers in which aggregation and riming took place were generally too thick and the frequency of riming was generally too high compared to the observations and theory. Additionally, none of the parameterizations produced similar details in every microphysical spatial pattern. Discrepancies in the patterns of microphysical processes between parameterizations likely factor into creating substantial differences in model reflectivity patterns. It is concluded that improved parameterizations of ice-phase microphysics will be essential to obtain reliable, consistent model simulations of tropical oceanic MCSs.« less

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

The cloud-phase feedback in the Super-parameterized Community Earth System Model

NASA Astrophysics Data System (ADS)

Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

A Family of Poisson Processes for Use in Stochastic Models of Precipitation

NASA Astrophysics Data System (ADS)

Penland, C.

2013-12-01

Both modified Poisson processes and compound Poisson processes can be relevant to stochastic parameterization of precipitation. This presentation compares the dynamical properties of these systems and discusses the physical situations in which each might be appropriate. If the parameters describing either class of systems originate in hydrodynamics, then proper consideration of stochastic calculus is required during numerical implementation of the parameterization. It is shown here that an improper numerical treatment can have severe implications for estimating rainfall distributions, particularly in the tails of the distributions and, thus, on the frequency of extreme events.

New Parameterization of Neutron Absorption Cross Sections

NASA Technical Reports Server (NTRS)

Tripathi, Ram K.; Wilson, John W.; Cucinotta, Francis A.

1997-01-01

Recent parameterization of absorption cross sections for any system of charged ion collisions, including proton-nucleus collisions, is extended for neutron-nucleus collisions valid from approx. 1 MeV to a few GeV, thus providing a comprehensive picture of absorption cross sections for any system of collision pairs (charged or uncharged). The parameters are associated with the physics of the problem. At lower energies, optical potential at the surface is important, and the Pauli operator plays an increasingly important role at intermediate energies. The agreement between the calculated and experimental data is better than earlier published results.

ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

The parameterization of microchannel-plate-based detection systems

NASA Astrophysics Data System (ADS)

Gershman, Daniel J.; Gliese, Ulrik; Dorelli, John C.; Avanov, Levon A.; Barrie, Alexander C.; Chornay, Dennis J.; MacDonald, Elizabeth A.; Holland, Matthew P.; Giles, Barbara L.; Pollock, Craig J.

2016-10-01

The most common instrument for low-energy plasmas consists of a top-hat electrostatic analyzer (ESA) geometry coupled with a microchannel-plate-based (MCP-based) detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Here we develop a comprehensive mathematical description of particle detection systems. As a function of instrument azimuthal angle, we parameterize (1) particle scattering within the ESA and at the surface of the MCP, (2) the probability distribution of MCP gain for an incident particle, (3) electron charge cloud spreading between the MCP and anode board, and (4) capacitive coupling between adjacent discrete anodes. Using the Dual Electron Spectrometers on the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission as an example, we demonstrate a method for extracting these fundamental detection system parameters from laboratory calibration. We further show that parameters that will evolve in flight, namely, MCP gain, can be determined through application of this model to specifically tailored in-flight calibration activities. This methodology provides a robust characterization of sensor suite performance throughout mission lifetime. The model developed in this work is not only applicable to existing sensors but also can be used as an analytical design tool for future particle instrumentation.

Real-Time Minimization of Tracking Error for Aircraft Systems

NASA Technical Reports Server (NTRS)

Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John

2013-01-01

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

A volumetric conformal mapping approach for clustering white matter fibers in the brain

PubMed Central

Gupta, Vikash; Prasad, Gautam; Thompson, Paul

2017-01-01

The human brain may be considered as a genus-0 shape, topologically equivalent to a sphere. Various methods have been used in the past to transform the brain surface to that of a sphere using harmonic energy minimization methods used for cortical surface matching. However, very few methods have studied volumetric parameterization of the brain using a spherical embedding. Volumetric parameterization is typically used for complicated geometric problems like shape matching, morphing and isogeometric analysis. Using conformal mapping techniques, we can establish a bijective mapping between the brain and the topologically equivalent sphere. Our hypothesis is that shape analysis problems are simplified when the shape is defined in an intrinsic coordinate system. Our goal is to establish such a coordinate system for the brain. The efficacy of the method is demonstrated with a white matter clustering problem. Initial results show promise for future investigation in these parameterization technique and its application to other problems related to computational anatomy like registration and segmentation. PMID:29177252

Fully parameterized model of a voltage-driven capacitive coupled micromachined ohmic contact switch for RF applications

NASA Astrophysics Data System (ADS)

Heeb, Peter; Tschanun, Wolfgang; Buser, Rudolf

2012-03-01

A comprehensive and completely parameterized model is proposed to determine the related electrical and mechanical dynamic system response of a voltage-driven capacitive coupled micromechanical switch. As an advantage over existing parameterized models, the model presented in this paper returns within few seconds all relevant system quantities necessary to design the desired switching cycle. Moreover, a sophisticated and detailed guideline is given on how to engineer a MEMS switch. An analytical approach is used throughout the modelling, providing representative coefficients in a set of two coupled time-dependent differential equations. This paper uses an equivalent mass moving along the axis of acceleration and a momentum absorption coefficient. The model describes all the energies transferred: the energy dissipated in the series resistor that models the signal attenuation of the bias line, the energy dissipated in the squeezed film, the stored energy in the series capacitor that represents a fixed separation in the bias line and stops the dc power in the event of a short circuit between the RF and dc path, the energy stored in the spring mechanism, and the energy absorbed by mechanical interaction at the switch contacts. Further, the model determines the electrical power fed back to the bias line. The calculated switching dynamics are confirmed by the electrical characterization of the developed RF switch. The fabricated RF switch performs well, in good agreement with the modelled data, showing a transition time of 7 µs followed by a sequence of bounces. Moreover, the scattering parameters exhibit an isolation in the off-state of >8 dB and an insertion loss in the on-state of <0.6 dB up to frequencies of 50 GHz. The presented model is intended to be integrated into standard circuit simulation software, allowing circuit engineers to design the switch bias line, to minimize induced currents and cross actuation, as well as to find the mechanical structure dimensions necessary for the desired switching time and actuation voltage waveform. Moreover, process related design rules can be automatically verified.

Chemical transport models: the combined non-local diffusion and mixing schemes, and calculation of in-canopy resistance for dry deposition fluxes.

PubMed

Mihailovic, Dragutin T; Alapaty, Kiran; Podrascanin, Zorica

2009-03-01

Improving the parameterization of processes in the atmospheric boundary layer (ABL) and surface layer, in air quality and chemical transport models. To do so, an asymmetrical, convective, non-local scheme, with varying upward mixing rates is combined with the non-local, turbulent, kinetic energy scheme for vertical diffusion (COM). For designing it, a function depending on the dimensionless height to the power four in the ABL is suggested, which is empirically derived. Also, we suggested a new method for calculating the in-canopy resistance for dry deposition over a vegetated surface. The upward mixing rate forming the surface layer is parameterized using the sensible heat flux and the friction and convective velocities. Upward mixing rates varying with height are scaled with an amount of turbulent kinetic energy in layer, while the downward mixing rates are derived from mass conservation. The vertical eddy diffusivity is parameterized using the mean turbulent velocity scale that is obtained by the vertical integration within the ABL. In-canopy resistance is calculated by integration of inverse turbulent transfer coefficient inside the canopy from the effective ground roughness length to the canopy source height and, further, from its the canopy height. This combination of schemes provides a less rapid mass transport out of surface layer into other layers, during convective and non-convective periods, than other local and non-local schemes parameterizing mixing processes in the ABL. The suggested method for calculating the in-canopy resistance for calculating the dry deposition over a vegetated surface differs remarkably from the commonly used one, particularly over forest vegetation. In this paper, we studied the performance of a non-local, turbulent, kinetic energy scheme for vertical diffusion combined with a non-local, convective mixing scheme with varying upward mixing in the atmospheric boundary layer (COM) and its impact on the concentration of pollutants calculated with chemical and air-quality models. In addition, this scheme was also compared with a commonly used, local, eddy-diffusivity scheme. Simulated concentrations of NO2 by the COM scheme and new parameterization of the in-canopy resistance are closer to the observations when compared to those obtained from using the local eddy-diffusivity scheme. Concentrations calculated with the COM scheme and new parameterization of in-canopy resistance, are in general higher and closer to the observations than those obtained by the local, eddy-diffusivity scheme (on the order of 15-22%). To examine the performance of the scheme, simulated and measured concentrations of a pollutant (NO2) were compared for the years 1999 and 2002. The comparison was made for the entire domain used in simulations performed by the chemical European Monitoring and Evaluation Program Unified model (version UNI-ACID, rv2.0) where schemes were incorporated.

Sea breeze: Induced mesoscale systems and severe weather

NASA Technical Reports Server (NTRS)

Nicholls, M. E.; Pielke, R. A.; Cotton, W. R.

1990-01-01

Sea-breeze-deep convective interactions over the Florida peninsula were investigated using a cloud/mesoscale numerical model. The objective was to gain a better understanding of sea-breeze and deep convective interactions over the Florida peninsula using a high resolution convectively explicit model and to use these results to evaluate convective parameterization schemes. A 3-D numerical investigation of Florida convection was completed. The Kuo and Fritsch-Chappell parameterization schemes are summarized and evaluated.

NASA Tech Briefs, June 2010

NASA Technical Reports Server (NTRS)

2010-01-01

Topics covered include: Situational Awareness from a Low-Cost Camera System; Data Acquisition System for Multi-Frequency Radar Flight Operations Preparation; Mercury Toolset for Spatiotemporal Metadata; Social Tagging of Mission Data; Integrating Radar Image Data with Google Maps; Demonstration of a Submillimeter-Wave HEMT Oscillator Module at 330 GHz; Flexible Peripheral Component Interconnect Input/Output Card; Interface Supports Lightweight Subsystem Routing for Flight Applications; MMIC Amplifiers and Wafer Probes for 350 to 500 GHz; Public Risk Assessment Program; Particle Swarm Optimization Toolbox; Telescience Support Center Data System Software; Update on PISCES; Ground and Space Radar Volume Matching and Comparison Software; Web-Based Interface for Command and Control of Network Sensors; Orbit Determination Toolbox; Distributed Observer Network; Computer-Automated Evolution of Spacecraft X-Band Antennas; Practical Loop-Shaping Design of Feedback Control Systems; Fully Printed High-Frequency Phased-Array Antenna on Flexible Substrate; Formula for the Removal and Remediation of Polychlorinated Biphenyls in Painted Structures; Integrated Solar Concentrator and Shielded Radiator; Water Membrane Evaporator; Modeling of Failure for Analysis of Triaxial Braided Carbon Fiber Composites; Catalyst for Carbon Monoxide Oxidation; Titanium Hydroxide - a Volatile Species at High Temperature; Selective Functionalization of Carbon Nanotubes: Part II; Steerable Hopping Six-Legged Robot; Launchable and Retrievable Tetherobot; Hybrid Heat Exchangers; Orbital Winch for High-Strength, Space-Survivable Tethers; Parameterized Linear Longitudinal Airship Model; and Physics of Life: A Model for Non-Newtonian Properties of Living Systems.

A Survey of Phase Variable Candidates of Human Locomotion

PubMed Central

Villarreal, Dario J.; Gregg, Robert D.

2014-01-01

Studies show that the human nervous system is able to parameterize gait cycle phase using sensory feedback. In the field of bipedal robots, the concept of a phase variable has been successfully used to mimic this behavior by parameterizing the gait cycle in a time-independent manner. This approach has been applied to control a powered transfemoral prosthetic leg, but the proposed phase variable was limited to the stance period of the prosthesis only. In order to achieve a more robust controller, we attempt to find a new phase variable that fully parameterizes the gait cycle of a prosthetic leg. The angle with respect to a global reference frame at the hip is able to monotonically parameterize both the stance and swing periods of the gait cycle. This survey looks at multiple phase variable candidates involving the hip angle with respect to a global reference frame across multiple tasks including level-ground walking, running, and stair negotiation. In particular, we propose a novel phase variable candidate that monotonically parameterizes the whole gait cycle across all tasks, and does so particularly well across level-ground walking. In addition to furthering the design of robust robotic prosthetic leg controllers, this survey could help neuroscientists and physicians study human locomotion across tasks from a time-independent perspective. PMID:25570873

Prototype Mcs Parameterization for Global Climate Models

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.

2017-12-01

Excellent progress has been made with observational, numerical and theoretical studies of MCS processes but the parameterization of those processes remain in a dire state and are missing from GCMs. The perceived complexity of the distribution, type, and intensity of organized precipitation systems has arguably daunted attention and stifled the development of adequate parameterizations. TRMM observations imply links between convective organization and large-scale meteorological features in the tropics and subtropics that are inadequately treated by GCMs. This calls for improved physical-dynamical treatment of organized convection to enable the next-generation of GCMs to reliably address a slew of challenges. The multiscale coherent structure parameterization (MCSP) paradigm is based on the fluid-dynamical concept of coherent structures in turbulent environments. The effects of vertical shear on MCS dynamics implemented as 2nd baroclinic convective heating and convective momentum transport is based on Lagrangian conservation principles, nonlinear dynamical models, and self-similarity. The prototype MCS parameterization, a minimalist proof-of-concept, is applied in the NCAR Community Climate Model, Version 5.5 (CAM 5.5). The MCSP generates convectively coupled tropical waves and large-scale precipitation features notably in the Indo-Pacific warm-pool and Maritime Continent region, a center-of-action for weather and climate variability around the globe.

Integrated control-structure design

NASA Technical Reports Server (NTRS)

Hunziker, K. Scott; Kraft, Raymond H.; Bossi, Joseph A.

1991-01-01

A new approach for the design and control of flexible space structures is described. The approach integrates the structure and controller design processes thereby providing extra opportunities for avoiding some of the disastrous effects of control-structures interaction and for discovering new, unexpected avenues of future structural design. A control formulation based on Boyd's implementation of Youla parameterization is employed. Control design parameters are coupled with structural design variables to produce a set of integrated-design variables which are selected through optimization-based methodology. A performance index reflecting spacecraft mission goals and constraints is formulated and optimized with respect to the integrated design variables. Initial studies have been concerned with achieving mission requirements with a lighter, more flexible space structure. Details of the formulation of the integrated-design approach are presented and results are given from a study involving the integrated redesign of a flexible geostationary platform.

Evaluating the improvements of the BOLAM meteorological model operational at ISPRA: A case study approach - preliminary results

NASA Astrophysics Data System (ADS)

Mariani, S.; Casaioli, M.; Lastoria, B.; Accadia, C.; Flavoni, S.

2009-04-01

The Institute for Environmental Protection and Research - ISPRA (former Agency for Environmental Protection and Technical Services - APAT) runs operationally since 2000 an integrated meteo-marine forecasting chain, named the Hydro-Meteo-Marine Forecasting System (Sistema Idro-Meteo-Mare - SIMM), formed by a cascade of four numerical models, telescoping from the Mediterranean basin to the Venice Lagoon, and initialized by means of analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). The operational integrated system consists of a meteorological model, the parallel verision of BOlogna Limited Area Model (BOLAM), coupled over the Mediterranean sea with a WAve Model (WAM), a high-resolution shallow-water model of the Adriatic and Ionian Sea, namely the Princeton Ocean Model (POM), and a finite-element version of the same model (VL-FEM) on the Venice Lagoon, aimed to forecast the acqua alta events. Recently, the physically based, fully distributed, rainfall-runoff TOPographic Kinematic APproximation and Integration (TOPKAPI) model has been integrated into the system, coupled to BOLAM, over two river basins, located in the central and northeastern part of Italy, respectively. However, at the present time, this latter part of the forecasting chain is not operational and it is used in a research configuration. BOLAM was originally implemented in 2000 onto the Quadrics parallel supercomputer (and for this reason referred to as QBOLAM, as well) and only at the end of 2006 it was ported (together with the other operational marine models of the forecasting chain) onto the Silicon Graphics Inc. (SGI) Altix 8-processor machine. In particular, due to the Quadrics implementation, the Kuo scheme was formerly implemented into QBOLAM for the cumulus convection parameterization. On the contrary, when porting SIMM onto the Altix Linux cluster, it was achievable to implement into QBOLAM the more advanced convection parameterization by Kain and Fritsch. A fully updated serial version of the BOLAM code has been recently acquired. Code improvements include a more precise advection scheme (Weighted Average Flux); explicit advection of five hydrometeors, and state-of-the-art parameterization schemes for radiation, convection, boundary layer turbulence and soil processes (also with possible choice among different available schemes). The operational implementation of the new code into the SIMM model chain, which requires the development of a parallel version, will be achieved during 2009. In view of this goal, the comparative verification of the different model versions' skill represents a fundamental task. On this purpose, it has been decided to evaluate the performance improvement of the new BOLAM code (in the available serial version, hereinafter BOLAM 2007) with respect to the version with the Kain-Fritsch scheme (hereinafter KF version) and to the older one employing the Kuo scheme (hereinafter Kuo version). In the present work, verification of precipitation forecasts from the three BOLAM versions is carried on in a case study approach. The intense rainfall episode occurred on 10th - 17th December 2008 over Italy has been considered. This event produced indeed severe damages in Rome and its surrounding areas. Objective and subjective verification methods have been employed in order to evaluate model performance against an observational dataset including rain gauge observations and satellite imagery. Subjective comparison of observed and forecast precipitation fields is suitable to give an overall description of the forecast quality. Spatial errors (e.g., shifting and pattern errors) and rainfall volume error can be assessed quantitatively by means of object-oriented methods. By comparing satellite images with model forecast fields, it is possible to investigate the differences between the evolution of the observed weather system and the predicted ones, and its sensitivity to the improvements in the model code. Finally, the error in forecasting the cyclone evolution can be tentatively related with the precipitation forecast error.

Flow Charts: Visualization of Vector Fields on Arbitrary Surfaces

PubMed Central

Li, Guo-Shi; Tricoche, Xavier; Weiskopf, Daniel; Hansen, Charles

2009-01-01

We introduce a novel flow visualization method called Flow Charts, which uses a texture atlas approach for the visualization of flows defined over curved surfaces. In this scheme, the surface and its associated flow are segmented into overlapping patches, which are then parameterized and packed in the texture domain. This scheme allows accurate particle advection across multiple charts in the texture domain, providing a flexible framework that supports various flow visualization techniques. The use of surface parameterization enables flow visualization techniques requiring the global view of the surface over long time spans, such as Unsteady Flow LIC (UFLIC), particle-based Unsteady Flow Advection Convolution (UFAC), or dye advection. It also prevents visual artifacts normally associated with view-dependent methods. Represented as textures, Flow Charts can be naturally integrated into hardware accelerated flow visualization techniques for interactive performance. PMID:18599918

Importance of Air Absorption During Mechanical Integrity Testing

NASA Astrophysics Data System (ADS)

Arnold, Fredric C.

1990-11-01

Wells used for injection of liquid industrial waste into deep saline aquifers are required to be periodically tested for mechanical integrity. A generally accepted method to demonstrate mechanical integrity is to pressurize the casing-tubing annulus and monitor any decline in pressure. If air is used to pressurize the annulus, uncertainty may exist in differentiating between absorption of air into water in the annulus and loss of pressure due to the absence of mechanical integrity. An analytical model of air absorbance has been derived and used to quantify the pressure decline due to dissolving and diffusion of the air in annular water. A parameteric study was made to determine when annular pressure decline due to absorption of air is significant.

A New WRF-Chem Treatment for Studying Regional Scale Impacts of Cloud-Aerosol Interactions in Parameterized Cumuli

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berg, Larry K.; Shrivastava, ManishKumar B.; Easter, Richard C.

A new treatment of cloud-aerosol interactions within parameterized shallow and deep convection has been implemented in WRF-Chem that can be used to better understand the aerosol lifecycle over regional to synoptic scales. The modifications to the model to represent cloud-aerosol interactions include treatment of the cloud dropletnumber mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. Thesechanges have beenmore » implemented in both the WRF-Chem chemistry packages as well as the Kain-Fritsch cumulus parameterization that has been modified to better represent shallow convective clouds. Preliminary testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS) as well as a high-resolution simulation that does not include parameterized convection. The simulation results are used to investigate the impact of cloud-aerosol interactions on the regional scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column integrated BC can be as large as -50% when cloud-aerosol interactions are considered (due largely to wet removal), or as large as +35% for sulfate in non-precipitating conditions due to the sulfate production in the parameterized clouds. The modifications to WRF-Chem version 3.2.1 are found to account for changes in the cloud drop number concentration (CDNC) and changes in the chemical composition of cloud-drop residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to WRF-Chem version 3.5, and it is anticipated that they will be included in a future public release of WRF-Chem.« less

Structure and covariance of cloud and rain water in marine stratocumulus

NASA Astrophysics Data System (ADS)

Witte, Mikael; Morrison, Hugh; Gettelman, Andrew

2017-04-01

Many state of the art cloud microphysics parameterizations in large-scale models use assumed probability density functions (pdfs) to represent subgrid scale variability of relevant resolved scale variables such as vertical velocity and cloud liquid water content (LWC). Integration over the assumed pdfs of small scale variability results in physically consistent prediction of nonlinear microphysical process rates and obviates the need to apply arbitrary tuning parameters to the calculated rates. In such parameterizations, the covariance of cloud and rain LWC is an important quantity for parameterizing the accretion process by which rain drops grow via collection of cloud droplets. This covariance has been diagnosed by other workers from a variety of observational and model datasets (Boutle et al., 2013; Larson and Griffin, 2013; Lebsock et al., 2013), but there is poor agreement in findings across the studies. Two key assumptions that may explain some of the discrepancies among past studies are 1) LWC (both cloud and rain) distributions are statistically stationary and 2) spatial structure may be neglected. Given the highly intermittent nature of precipitation and the fact that cloud LWC has been found to be poorly represented by stationary pdfs (e.g. Marshak et al., 1997), neither of the aforementioned assumptions are valid. Therefore covariance must be evaluated as a function of spatial scale without the assumption of stationary statistics (i.e. variability cannot be expressed as a fractional standard deviation, which necessitates well-defined first and second moments of the LWC distribution). The present study presents multifractal analyses of both rain and cloud LWC using aircraft data from the VOCALS-REx field campaign to illustrate the importance of spatial structure in microphysical parameterizations and extends the results of Boutle et al. (2013) to provide a parameterization of rain-cloud water covariance as a function of spatial scale without the assumption of statistical stationarity.

Potential Improvements to Remote Primary Productivity Estimation in the Southern California Current System

NASA Astrophysics Data System (ADS)

Jacox, M.; Edwards, C. A.; Kahru, M.; Rudnick, D. L.; Kudela, R. M.

2012-12-01

A 26-year record of depth integrated primary productivity (PP) in the Southern California Current System (SCCS) is analyzed with the goal of improving satellite net primary productivity (PP) estimates. The ratio of integrated primary productivity to surface chlorophyll correlates strongly to surface chlorophyll concentration (chl0). However, chl0 does not correlate to chlorophyll-specific productivity, and appears to be a proxy for vertical phytoplankton distribution rather than phytoplankton physiology. Modest improvements in PP model performance are achieved by tuning existing algorithms for the SCCS, particularly by empirical parameterization of photosynthetic efficiency in the Vertically Generalized Production Model. Much larger improvements are enabled by improving accuracy of subsurface chlorophyll and light profiles. In a simple vertically resolved production model, substitution of in situ surface data for remote sensing estimates offers only marginal improvements in model r2 and total log10 root mean squared difference, while inclusion of in situ chlorophyll and light profiles improves these metrics significantly. Autonomous underwater gliders, capable of measuring subsurface fluorescence on long-term, long-range deployments, significantly improve PP model fidelity in the SCCS. We suggest their use (and that of other autonomous profilers such as Argo floats) in conjunction with satellites as a way forward for improved PP estimation in coastal upwelling systems.

Optimizing the Betts-Miller-Janjic cumulus parameterization with Intel Many Integrated Core (MIC) architecture

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.-L.

2015-10-01

The schemes of cumulus parameterization are responsible for the sub-grid-scale effects of convective and/or shallow clouds, and intended to represent vertical fluxes due to unresolved updrafts and downdrafts and compensating motion outside the clouds. Some schemes additionally provide cloud and precipitation field tendencies in the convective column, and momentum tendencies due to convective transport of momentum. The schemes all provide the convective component of surface rainfall. Betts-Miller-Janjic (BMJ) is one scheme to fulfill such purposes in the weather research and forecast (WRF) model. National Centers for Environmental Prediction (NCEP) has tried to optimize the BMJ scheme for operational application. As there are no interactions among horizontal grid points, this scheme is very suitable for parallel computation. With the advantage of Intel Xeon Phi Many Integrated Core (MIC) architecture, efficient parallelization and vectorization essentials, it allows us to optimize the BMJ scheme. If compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670, the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.4x and 17.0x, respectively.

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC.

PubMed

Mukhtar, Hussnain; Lin, Yu-Pin; Shipin, Oleg V; Petway, Joy R

2017-07-12

This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH₃-N and NO₃-N. Results indicate that the integrated FME-GLUE-based model, with good Nash-Sutcliffe coefficients (0.53-0.69) and correlation coefficients (0.76-0.83), successfully simulates the concentrations of ON-N, NH₃-N and NO₃-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH₃-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO₃-N simulation, which was measured using global sensitivity.

Distributed parameterization of complex terrain

NASA Astrophysics Data System (ADS)

Band, Lawrence E.

1991-03-01

This paper addresses the incorporation of high resolution topography, soils and vegetation information into the simulation of land surface processes in atmospheric circulation models (ACM). Recent work has concentrated on detailed representation of one-dimensional exchange processes, implicitly assuming surface homogeneity over the atmospheric grid cell. Two approaches that could be taken to incorporate heterogeneity are the integration of a surface model over distributed, discrete portions of the landscape, or over a distribution function of the model parameters. However, the computational burden and parameter intensive nature of current land surface models in ACM limits the number of independent model runs and parameterizations that are feasible to accomplish for operational purposes. Therefore, simplications in the representation of the vertical exchange processes may be necessary to incorporate the effects of landscape variability and horizontal divergence of energy and water. The strategy is then to trade off the detail and rigor of point exchange calculations for the ability to repeat those calculations over extensive, complex terrain. It is clear the parameterization process for this approach must be automated such that large spatial databases collected from remotely sensed images, digital terrain models and digital maps can be efficiently summarized and transformed into the appropriate parameter sets. Ideally, the landscape should be partitioned into surface units that maximize between unit variance while minimizing within unit variance, although it is recognized that some level of surface heterogeneity will be retained at all scales. Therefore, the geographic data processing necessary to automate the distributed parameterization should be able to estimate or predict parameter distributional information within each surface unit.

Impacts of parameterized orographic drag on the Northern Hemisphere winter circulation

PubMed Central

Bechtold, Peter; Beljaars, Anton; Bozzo, Alessio; Pithan, Felix; Shepherd, Theodore G.; Zadra, Ayrton

2016-01-01

Abstract A recent intercomparison exercise proposed by the Working Group for Numerical Experimentation (WGNE) revealed that the parameterized, or unresolved, surface stress in weather forecast models is highly model‐dependent, especially over orography. Models of comparable resolution differ over land by as much as 20% in zonal mean total subgrid surface stress (τtot). The way τtot is partitioned between the different parameterizations is also model‐dependent. In this study, we simulated in a particular model an increase in τtot comparable with the spread found in the WGNE intercomparison. This increase was simulated in two ways, namely by increasing independently the contributions to τtot of the turbulent orographic form drag scheme (TOFD) and of the orographic low‐level blocking scheme (BLOCK). Increasing the parameterized orographic drag leads to significant changes in surface pressure, zonal wind and temperature in the Northern Hemisphere during winter both in 10 day weather forecasts and in seasonal integrations. However, the magnitude of these changes in circulation strongly depends on which scheme is modified. In 10 day forecasts, stronger changes are found when the TOFD stress is increased, while on seasonal time scales the effects are of comparable magnitude, although different in detail. At these time scales, the BLOCK scheme affects the lower stratosphere winds through changes in the resolved planetary waves which are associated with surface impacts, while the TOFD effects are mostly limited to the lower troposphere. The partitioning of τtot between the two schemes appears to play an important role at all time scales. PMID:27668040

Impacts of parameterized orographic drag on the Northern Hemisphere winter circulation

NASA Astrophysics Data System (ADS)

Sandu, Irina; Bechtold, Peter; Beljaars, Anton; Bozzo, Alessio; Pithan, Felix; Shepherd, Theodore G.; Zadra, Ayrton

2016-03-01

A recent intercomparison exercise proposed by the Working Group for Numerical Experimentation (WGNE) revealed that the parameterized, or unresolved, surface stress in weather forecast models is highly model-dependent, especially over orography. Models of comparable resolution differ over land by as much as 20% in zonal mean total subgrid surface stress (τtot). The way τtot is partitioned between the different parameterizations is also model-dependent. In this study, we simulated in a particular model an increase in τtot comparable with the spread found in the WGNE intercomparison. This increase was simulated in two ways, namely by increasing independently the contributions to τtot of the turbulent orographic form drag scheme (TOFD) and of the orographic low-level blocking scheme (BLOCK). Increasing the parameterized orographic drag leads to significant changes in surface pressure, zonal wind and temperature in the Northern Hemisphere during winter both in 10 day weather forecasts and in seasonal integrations. However, the magnitude of these changes in circulation strongly depends on which scheme is modified. In 10 day forecasts, stronger changes are found when the TOFD stress is increased, while on seasonal time scales the effects are of comparable magnitude, although different in detail. At these time scales, the BLOCK scheme affects the lower stratosphere winds through changes in the resolved planetary waves which are associated with surface impacts, while the TOFD effects are mostly limited to the lower troposphere. The partitioning of τtot between the two schemes appears to play an important role at all time scales.

An Investigation on the role of Planetary Boundary Layer Parameterization scheme on the performance of a hydrostatic atmospheric model over a Coastal Region

NASA Astrophysics Data System (ADS)

Anurose, J. T.; Subrahamanyam, Bala D.

2012-07-01

As part of the ocean/land-atmosphere interaction, more than half of the total kinetic energy is lost within the lowest part of atmosphere, often referred to as the planetary boundary layer (PBL). A comprehensive understanding of the energetics of this layer and turbulent processes responsible for dissipation of kinetic energy within the PBL require accurate estimation of sensible and latent heat flux and momentum flux. In numerical weather prediction (NWP) models, these quantities are estimated through different surface-layer and PBL parameterization schemes. This research article investigates different factors influencing the accuracy of a surface-layer parameterization scheme used in a hydrostatic high-resolution regional model (HRM) in the estimation of surface-layer turbulent fluxes of heat, moisture and momentum over the coastal regions of the Indian sub-continent. Results obtained from this sensitivity study of a parameterization scheme in HRM revealed the role of surface roughness length (z_{0}) in conjunction with the temperature difference between the underlying ground surface and atmosphere above (ΔT = T_{G} - T_{A}) in the estimated values of fluxes. For grid points over the land surface where z_{0} is treated as a constant throughout the model integration time, ΔT showed relative dominance in the estimation of sensible heat flux. In contrast to this, estimation of sensible and latent heat flux over ocean were found to be equally sensitive on the method adopted for assigning the values of z_{0} and also on the magnitudes of ΔT.

Computation of the phase response curve: a direct numerical approach.

PubMed

Govaerts, W; Sautois, B

2006-04-01

Neurons are often modeled by dynamical systems--parameterized systems of differential equations. A typical behavioral pattern of neurons is periodic spiking; this corresponds to the presence of stable limit cycles in the dynamical systems model. The phase resetting and phase response curves (PRCs) describe the reaction of the spiking neuron to an input pulse at each point of the cycle. We develop a new method for computing these curves as a by-product of the solution of the boundary value problem for the stable limit cycle. The method is mathematically equivalent to the adjoint method, but our implementation is computationally much faster and more robust than any existing method. In fact, it can compute PRCs even where the limit cycle can hardly be found by time integration, for example, because it is close to another stable limit cycle. In addition, we obtain the discretized phase response curve in a form that is ideally suited for most applications. We present several examples and provide the implementation in a freely available Matlab code.

Hydrodynamic Modeling to Assess the Impact of Man-Made Fishing Canals on Floodplain Dynamics: A Case Study in the Logone Floodplain

NASA Astrophysics Data System (ADS)

Shastry, A. R.; Durand, M. T.; Fernandez, A.; Phang, S. C.; Hamilton, I.; Laborde, S.; Mark, B. G.; Moritz, M.; Neal, J. C.

2017-12-01

The Logone floodplain in northern Cameroon, also known as Yaayre, is an excellent example of coupled human-natural systems because of strong couplings between social, ecological and hydrologic systems. Overbank flow from the Logone River inundates the floodplain ( 8000 km2) annually and the flood is essential for fish populations and the fishers that depend on them for their livelihood. However, a recent trend of construction of fishing canals threatens to change flood dynamics like duration and timing of onset and may reduce fish productivity. Fishers dig canals during dry season, which are used to catch fish by collecting and channeling water during the flood recession. By connecting the floodplain to the river, these fishing canals act an extension of the river drainage network. The goal of this study is to characterize the relationship between the observed exponential increase in numbers of fishing canals and flood dynamics. We modelled the Logone floodplain as a two-dimensional hydrodynamic model with sub-grid parameterizations of channels using LISFLOOD-FP. We use a simplified version of the hydraulic system at a grid-cell size of 1-km, upscaled using a new high accuracy map of global terrain elevations from Shuttle Radar Topography Mission (SRTM). Using data from a field-collected survey performed in 2014, 1120 fishing canal were collated and parameterized as 111 sub-grid channels and the fishnet structure was represented as a combination of weir and mesh screens. 49 mapped floodplain depressions were also represented as sub-grid channels. In situ discharge observations available at Katoa between 2001 and 2007 were used as input for the model. Preliminary results show that presence of canals resulted in a 24% quicker recession of water in the natural depressions showing increasing canal numbers lead to quicker flood recession. We also investigate the rate of effect increasing number of fishing canals has on flood recession by simulating varying numbers of canals. This model will be integrated within a larger modelling effort to quantify the floodplain's hydraulic, biological and human couplings. This larger integrated model will link inputs and outputs across three different models (flood, fish and fisher) for a holistic insight into the drivers and dynamics of this coupled human and natural system.

Surge of Bering Glacier and Bagley Ice Field: Parameterization of surge characteristics based on automated analysis of crevasse image data and laser altimeter data

NASA Astrophysics Data System (ADS)

Stachura, M.; Herzfeld, U. C.; McDonald, B.; Weltman, A.; Hale, G.; Trantow, T.

2012-12-01

The dynamical processes that occur during the surge of a large, complex glacier system are far from being understood. The aim of this paper is to derive a parameterization of surge characteristics that captures the principle processes and can serve as the basis for a dynamic surge model. Innovative mathematical methods are introduced that facilitate derivation of such a parameterization from remote-sensing observations. Methods include automated geostatistical characterization and connectionist-geostatistical classification of dynamic provinces and deformation states, using the vehicle of crevasse patterns. These methods are applied to analyze satellite and airborne image and laser altimeter data collected during the current surge of Bering Glacier and Bagley Ice Field, Alaska.

FIRE Science Results 1989

NASA Technical Reports Server (NTRS)

Mcdougal, David S. (Editor)

1990-01-01

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation research program formed in 1984 to increase the basic understanding of cirrus and marine stratocumulus cloud systems, to develop realistic parameterizations for these systems, and to validate and improve ISCCP cloud product retrievals. Presentations of results culminating the first 5 years of FIRE research activities were highlighted. The 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, the Extended Time Observations (ETO), and modeling activities are described. Collaborative efforts involving the comparison of multiple data sets, incorporation of data measurements into modeling activities, validation of ISCCP cloud parameters, and development of parameterization schemes for General Circulation Models (GCMs) are described.

Universal Parameterization of Absorption Cross Sections

NASA Technical Reports Server (NTRS)

Tripathi, R. K.; Cucinotta, Francis A.; Wilson, John W.

1997-01-01

This paper presents a simple universal parameterization of total reaction cross sections for any system of colliding nuclei that is valid for the entire energy range from a few AMeV to a few AGeV. The universal picture presented here treats proton-nucleus collision as a special case of nucleus-nucleus collision, where the projectile has charge and mass number of one. The parameters are associated with the physics of the collision system. In general terms, Coulomb interaction modifies cross sections at lower energies, and the effects of Pauli blocking are important at higher energies. The agreement between the calculated and experimental data is better than all earlier published results.

Stochastic Least-Squares Petrov--Galerkin Method for Parameterized Linear Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Kookjin; Carlberg, Kevin; Elman, Howard C.

Here, we consider the numerical solution of parameterized linear systems where the system matrix, the solution, and the right-hand side are parameterized by a set of uncertain input parameters. We explore spectral methods in which the solutions are approximated in a chosen finite-dimensional subspace. It has been shown that the stochastic Galerkin projection technique fails to minimize any measure of the solution error. As a remedy for this, we propose a novel stochatic least-squares Petrov--Galerkin (LSPG) method. The proposed method is optimal in the sense that it produces the solution that minimizes a weightedmore » $$\\ell^2$$-norm of the residual over all solutions in a given finite-dimensional subspace. Moreover, the method can be adapted to minimize the solution error in different weighted $$\\ell^2$$-norms by simply applying a weighting function within the least-squares formulation. In addition, a goal-oriented seminorm induced by an output quantity of interest can be minimized by defining a weighting function as a linear functional of the solution. We establish optimality and error bounds for the proposed method, and extensive numerical experiments show that the weighted LSPG method outperforms other spectral methods in minimizing corresponding target weighted norms.« less

Challenges in horizontal model integration.

PubMed

Kolczyk, Katrin; Conradi, Carsten

2016-03-11

Systems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control. To answer important biomedical questions, however, one has to go beyond the study of isolated pathways towards the joint study of interacting signaling pathways or the joint study of signal transduction and cell cycle control. Thereby the reuse of established models is preferable, as it will generally reduce the modeling effort and increase the acceptance of the combined model in the field. Obtaining a combined model can be challenging, especially if the submodels are large and/or come from different working groups (as is generally the case, when models stored in established repositories are used). To support this task, we describe a semi-automatic workflow based on established software tools. In particular, two frequent challenges are described: identification of the overlap and subsequent (re)parameterization of the integrated model. The reparameterization step is crucial, if the goal is to obtain a model that can reproduce the data explained by the individual models. For demonstration purposes we apply our workflow to integrate two signaling pathways (EGF and NGF) from the BioModels Database.

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

SURA-IOOS Coastal Inundation Testbed Inter-Model Evaluation of Tides, Waves, and Hurricane Surge in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Kerr, P. C.; Donahue, A.; Westerink, J. J.; Luettich, R.; Zheng, L.; Weisberg, R. H.; Wang, H. V.; Slinn, D. N.; Davis, J. R.; Huang, Y.; Teng, Y.; Forrest, D.; Haase, A.; Kramer, A.; Rhome, J.; Feyen, J. C.; Signell, R. P.; Hanson, J. L.; Taylor, A.; Hope, M.; Kennedy, A. B.; Smith, J. M.; Powell, M. D.; Cardone, V. J.; Cox, A. T.

2012-12-01

The Southeastern Universities Research Association (SURA), in collaboration with the NOAA Integrated Ocean Observing System program and other federal partners, developed a testbed to help accelerate progress in both research and the transition to operational use of models for both coastal and estuarine prediction. This testbed facilitates cyber-based sharing of data and tools, archival of observation data, and the development of cross-platform tools to efficiently access, visualize, skill assess, and evaluate model results. In addition, this testbed enables the modeling community to quantitatively assess the behavior (e.g., skill, robustness, execution speed) and implementation requirements (e.g. resolution, parameterization, computer capacity) that characterize the suitability and performance of selected models from both operational and fundamental science perspectives. This presentation focuses on the tropical coastal inundation component of the testbed and compares a variety of model platforms as well as grids in simulating tides, and the wave and surge environments for two extremely well documented historical hurricanes, Hurricanes Rita (2005) and Ike (2008). Model platforms included are ADCIRC, FVCOM, SELFE, SLOSH, SWAN, and WWMII. Model validation assessments were performed on simulation results using numerous station observation data in the form of decomposed harmonic constituents, water level high water marks and hydrographs of water level and wave data. In addition, execution speed, inundation extents defined by differences in wetting/drying schemes, resolution and parameterization sensitivities are also explored.

Quantifying the predictive consequences of model error with linear subspace analysis

USGS Publications Warehouse

White, Jeremy T.; Doherty, John E.; Hughes, Joseph D.

2014-01-01

All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory, and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed, and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.

Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.

Parameterization of plume chemistry into large-scale atmospheric models: Application to aircraft NOx emissions

NASA Astrophysics Data System (ADS)

Cariolle, D.; Caro, D.; Paoli, R.; Hauglustaine, D. A.; CuéNot, B.; Cozic, A.; Paugam, R.

2009-10-01

A method is presented to parameterize the impact of the nonlinear chemical reactions occurring in the plume generated by concentrated NOx sources into large-scale models. The resulting plume parameterization is implemented into global models and used to evaluate the impact of aircraft emissions on the atmospheric chemistry. Compared to previous approaches that rely on corrected emissions or corrective factors to account for the nonlinear chemical effects, the present parameterization is based on the representation of the plume effects via a fuel tracer and a characteristic lifetime during which the nonlinear interactions between species are important and operate via rates of conversion for the NOx species and an effective reaction rates for O3. The implementation of this parameterization insures mass conservation and allows the transport of emissions at high concentrations in plume form by the model dynamics. Results from the model simulations of the impact on atmospheric ozone of aircraft NOx emissions are in rather good agreement with previous work. It is found that ozone production is decreased by 10 to 25% in the Northern Hemisphere with the largest effects in the north Atlantic flight corridor when the plume effects on the global-scale chemistry are taken into account. These figures are consistent with evaluations made with corrected emissions, but regional differences are noticeable owing to the possibility offered by this parameterization to transport emitted species in plume form prior to their dilution at large scale. This method could be further improved to make the parameters used by the parameterization function of the local temperature, humidity and turbulence properties diagnosed by the large-scale model. Further extensions of the method can also be considered to account for multistep dilution regimes during the plume dissipation. Furthermore, the present parameterization can be adapted to other types of point-source NOx emissions that have to be introduced in large-scale models, such as ship exhausts, provided that the plume life cycle, the type of emissions, and the major reactions involved in the nonlinear chemical systems can be determined with sufficient accuracy.

A new fractional snow-covered area parameterization for the Community Land Model and its effect on the surface energy balance

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2011-11-01

One function of the Community Land Model (CLM4) is the determination of surface albedo in the Community Earth System Model (CESM1). Because the typical spatial scales of CESM1 simulations are large compared to the scales of variability of surface properties such as snow cover and vegetation, unresolved surface heterogeneity is parameterized. Fractional snow-covered area, or snow-covered fraction (SCF), within a CLM4 grid cell is parameterized as a function of grid cell mean snow depth and snow density. This parameterization is based on an analysis of monthly averaged SCF and snow depth that showed a seasonal shift in the snow depth-SCF relationship. In this paper, we show that this shift is an artifact of the monthly sampling and that the current parameterization does not reflect the relationship observed between snow depth and SCF at the daily time scale. We demonstrate that the snow depth analysis used in the original study exhibits a bias toward early melt when compared to satellite-observed SCF. This bias results in a tendency to overestimate SCF as a function of snow depth. Using a more consistent, higher spatial and temporal resolution snow depth analysis reveals a clear hysteresis between snow accumulation and melt seasons. Here, a new SCF parameterization based on snow water equivalent is developed to capture the observed seasonal snow depth-SCF evolution. The effects of the new SCF parameterization on the surface energy budget are described. In CLM4, surface energy fluxes are calculated assuming a uniform snow cover. To more realistically simulate environments having patchy snow cover, we modify the model by computing the surface fluxes separately for snow-free and snow-covered fractions of a grid cell. In this configuration, the form of the parameterized snow depth-SCF relationship is shown to greatly affect the surface energy budget. The direct exposure of the snow-free surfaces to the atmosphere leads to greater heat loss from the ground during autumn and greater heat gain during spring. The net effect is to reduce annual mean soil temperatures by up to 3°C in snow-affected regions.

A new fractional snow-covered area parameterization for the Community Land Model and its effect on the surface energy balance

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2012-11-01

One function of the Community Land Model (CLM4) is the determination of surface albedo in the Community Earth System Model (CESM1). Because the typical spatial scales of CESM1 simulations are large compared to the scales of variability of surface properties such as snow cover and vegetation, unresolved surface heterogeneity is parameterized. Fractional snow-covered area, or snow-covered fraction (SCF), within a CLM4 grid cell is parameterized as a function of grid cell mean snow depth and snow density. This parameterization is based on an analysis of monthly averaged SCF and snow depth that showed a seasonal shift in the snow depth-SCF relationship. In this paper, we show that this shift is an artifact of the monthly sampling and that the current parameterization does not reflect the relationship observed between snow depth and SCF at the daily time scale. We demonstrate that the snow depth analysis used in the original study exhibits a bias toward early melt when compared to satellite-observed SCF. This bias results in a tendency to overestimate SCF as a function of snow depth. Using a more consistent, higher spatial and temporal resolution snow depth analysis reveals a clear hysteresis between snow accumulation and melt seasons. Here, a new SCF parameterization based on snow water equivalent is developed to capture the observed seasonal snow depth-SCF evolution. The effects of the new SCF parameterization on the surface energy budget are described. In CLM4, surface energy fluxes are calculated assuming a uniform snow cover. To more realistically simulate environments having patchy snow cover, we modify the model by computing the surface fluxes separately for snow-free and snow-covered fractions of a grid cell. In this configuration, the form of the parameterized snow depth-SCF relationship is shown to greatly affect the surface energy budget. The direct exposure of the snow-free surfaces to the atmosphere leads to greater heat loss from the ground during autumn and greater heat gain during spring. The net effect is to reduce annual mean soil temperatures by up to 3°C in snow-affected regions.

Molecular dynamics simulations and free energy calculations on the enzyme 4-hydroxyphenylpyruvate dioxygenase.

PubMed

De Beer, Stephanie B A; Glättli, Alice; Hutzler, Johannes; Vermeulen, Nico P E; Oostenbrink, Chris

2011-07-30

4-Hydroxyphenylpyruvate dioxygenase is a relevant target in both pharmaceutical and agricultural research. We report on molecular dynamics simulations and free energy calculations on this enzyme, in complex with 12 inhibitors for which experimental affinities were determined. We applied the thermodynamic integration approach and the more efficient one-step perturbation. Even though simulations seem well converged and both methods show excellent agreement between them, the correlation with the experimental values remains poor. We investigate the effect of slight modifications on the charge distribution of these highly conjugated systems and find that accurate models can be obtained when using improved force field parameters. This study gives insight into the applicability of free energy methods and current limitations in force field parameterization. Copyright © 2011 Wiley Periodicals, Inc.

Impact of Parameterized Lee Wave Drag on the Energy Budget of an Eddying Global Ocean Model

DTIC Science & Technology

2013-08-26

Teixeira, J., Peng, M., Hogan, T.F., Pauley, R., 2002. Navy Operational Global Atmospheric Prediction System (NOGAPS): Forcing for ocean models...Impact of parameterized lee wave drag on the energy budget of an eddying global ocean model David S. Trossman a,⇑, Brian K. Arbic a, Stephen T...input and output terms in the total mechanical energy budget of a hybrid coordinate high-resolution global ocean general circulation model forced by winds

Practical quality control tools for curves and surfaces

NASA Technical Reports Server (NTRS)

Small, Scott G.

1992-01-01

Curves (geometry) and surfaces created by Computer Aided Geometric Design systems in the engineering environment must satisfy two basic quality criteria: the geometric shape must have the desired engineering properties; and the objects must be parameterized in a way which does not cause computational difficulty for geometric processing and engineering analysis. Interactive techniques are described which are in use at Boeing to evaluate the quality of aircraft geometry prior to Computational Fluid Dynamic analysis, including newly developed methods for examining surface parameterization and its effects.

Analytical probabilistic proton dose calculation and range uncertainties

NASA Astrophysics Data System (ADS)

Bangert, M.; Hennig, P.; Oelfke, U.

2014-03-01

We introduce the concept of analytical probabilistic modeling (APM) to calculate the mean and the standard deviation of intensity-modulated proton dose distributions under the influence of range uncertainties in closed form. For APM, range uncertainties are modeled with a multivariate Normal distribution p(z) over the radiological depths z. A pencil beam algorithm that parameterizes the proton depth dose d(z) with a weighted superposition of ten Gaussians is used. Hence, the integrals ∫ dz p(z) d(z) and ∫ dz p(z) d(z)2 required for the calculation of the expected value and standard deviation of the dose remain analytically tractable and can be efficiently evaluated. The means μk, widths δk, and weights ωk of the Gaussian components parameterizing the depth dose curves are found with least squares fits for all available proton ranges. We observe less than 0.3% average deviation of the Gaussian parameterizations from the original proton depth dose curves. Consequently, APM yields high accuracy estimates for the expected value and standard deviation of intensity-modulated proton dose distributions for two dimensional test cases. APM can accommodate arbitrary correlation models and account for the different nature of random and systematic errors in fractionated radiation therapy. Beneficial applications of APM in robust planning are feasible.

Enhanced representation of soil NO emissions in the ...

EPA Pesticide Factsheets

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and

Computation of European carbon balance components through synergistic use of CARBOEUROPE eddy covariance, MODIS remote sensing data and advanced ecosystem and statistical modeling

NASA Astrophysics Data System (ADS)

Reichstein, M.; Dinh, N.; Running, S.; Seufert, G.; Tenhunen, J.; Valentini, R.

2003-04-01

Here we present spatially distributed bottom-up estimates of European carbon balance components for the year 2001, that stem from a newly built modeling system that integrates CARBOEUROPE eddy covariance CO_2 exchange data, remotely sensed vegetation properties via the MODIS-Terra sensor, European-wide soils data, and a suite of carbon balance models of different complexity. These estimates are able to better constrain top-down atmospheric-inversion carbon balance estimates within the dual-constraint approach for estimating continental carbon balances. The models that are used to calculate gross primary production (GPP) include a detailed layered canopy model with Farquhar-type photosynthesis (PROXELNEE), sun-shade big-leaf formulations operating at a daily time-step and a simple radiation-use efficiency model. These models are parameterized from eddy covariance data through inverse estimation techniques. Also for the estimation of soil and ecosystem respiration (Rsoil, Reco) we profit from a large data set of eddy covariance and soil chamber measurements, that enables us to the parameterize and validate a recently developed semi-empirical model, that includes a variable temperature sensitivity of respiration. As the outcome of the modeling system we present the most likely daily to annual numbers of carbon balance components (GPP, Reco, Rsoil), but we also issue a thorough analysis of biases and uncertainties in carbon balance estimates that are introduced through errors in the meteorological and remote sensing input data and through uncertainties in the model parameterization. In particular, we analyze 1) the effect of cloud contamination of the MODIS data, 2) the sensitivity to the land-use classification (Corine versus MODIS), 3) the effect of different soil parameterizations as derived from new continental-scale soil maps, and 4) the necessity to include soil drought effects into models of GPP and respiration. While the models describe the eddy covariance data quite well with r^2 values always greater than 0.7, there are still uncertainties in the European carbon balance estimate that exceed 0.3 PgC/yr. In northern (boreal) regions the carbon balance estimate is very much contingent on a high-quality filling of cloud contaminated remote sensing data, while in the southern (Mediterranean) regions a correct description of the soil water holding capacity is crucial. A major source of uncertainty also still is the estimation of heterotrophic respiration at continental scales. Consequently more spatial surveys on soil carbon stocks, turnover and history are needed. The study demonstrates that both, the inclusion of considerable geo-biological variability into a carbon balance modeling system, a high-quality cloud screening and gap-filling of the MODIS remote sensing data, and a correct description of soil drought effects are mandatory for realistic bottom-up estimates of European carbon balance components.

Integration of Advanced Statistical Analysis Tools and Geophysical Modeling

DTIC Science & Technology

2010-12-01

Carin Duke University Douglas Oldenburg University of British Columbia Stephen Billings, Leonard Pasion Laurens Beran Sky Research...means and covariances estimated for each class [5]. For this study, dipole polarizabilities were fit with a Pasion -Oldenburg parameterization of 8 −1...model for unexploded ordnance classification with EMI data,” IEEE Geosci. Remote Sensing Letters, vol. 4, pp. 629–633, 2007. [4] L. R. Pasion

Measurements and parameterization of neutron energy spectra from targets bombarded with 120 GeV protons

NASA Astrophysics Data System (ADS)

Kajimoto, T.; Shigyo, N.; Sanami, T.; Iwamoto, Y.; Hagiwara, M.; Lee, H. S.; Soha, A.; Ramberg, E.; Coleman, R.; Jensen, D.; Leveling, A.; Mokhov, N. V.; Boehnlein, D.; Vaziri, K.; Sakamoto, Y.; Ishibashi, K.; Nakashima, H.

2014-10-01

The energy spectra of neutrons were measured by a time-of-flight method for 120 GeV protons on thick graphite, aluminum, copper, and tungsten targets with an NE213 scintillator at the Fermilab Test Beam Facility. Neutron energy spectra were obtained between 25 and 3000 MeV at emission angles of 30°, 45°, 120°, and 150°. The spectra were parameterized as neutron emissions from three moving sources and then compared with theoretical spectra calculated by PHITS and FLUKA codes. The yields of the theoretical spectra were substantially underestimated compared with the yields of measured spectra. The integrated neutron yields from 25 to 3000 MeV calculated with PHITS code were 16-36% of the experimental yields and those calculated with FLUKA code were 26-57% of the experimental yields for all targets and emission angles.

Integration for Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Nickovic, S.; Huete, A.; Budge, A.; Flowers, L.

2008-01-01

The objective of the program is to assess the feasibility of combining a dust transport model with MODIS derived phenology to study pollen transport for integration with a public health decision support system. The use of pollen information has specifically be identified as a critical need by the New Mexico State Health department for inclusion in the Environmental Public Health Tracking (EPHT) program. Material and methods: Pollen can be transported great distances. Local observations of plan phenology may be consistent with the timing and source of pollen collected by pollen sampling instruments. The Dust REgional Atmospheric Model (DREAM) is an integrated modeling system designed to accurately describe the dust cycle in the atmosphere. The dust modules of the entire system incorporate the state of the art parameterization of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particles size distribution on aerosol dispersion. The model was modified to use pollen sources instead of dust. Pollen release was estimated based on satellite-derived phenology of key plan species and vegetation communities. The MODIS surface reflectance product (MOD09) provided information on the start of the plant growing season, growth stage, and pollen release. The resulting deterministic model is useful for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. The proposed linkage in this project provided critical information on the location timing and modeled transport of pollen directly to the EPHT> This information is useful to support the centers for disease control and prevention (CDC)'s National EPHT and the state of New Mexico environmental public health decision support for asthma and allergies alerts.

Description of the NCAR Community Climate Model (CCM3). Technical note

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kiehl, J.T.; Hack, J.J.; Bonan, G.B.

This repor presents the details of the governing equations, physical parameterizations, and numerical algorithms defining the version of the NCAR Community Climate Model designated CCM3. The material provides an overview of the major model components, and the way in which they interact as the numerical integration proceeds. This version of the CCM incorporates significant improvements to the physic package, new capabilities such as the incorporation of a slab ocean component, and a number of enhancements to the implementation (e.g., the ability to integrate the model on parallel distributed-memory computational platforms).

Evaluation of Simulated Marine Aerosol Production Using the WaveWatchIII Prognostic Wave Model Coupled to the Community Atmosphere Model within the Community Earth System Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, M. S.; Keene, William C.; Zhang, J.

2016-11-08

Primary marine aerosol (PMA) is emitted into the atmosphere via breaking wind waves on the ocean surface. Most parameterizations of PMA emissions use 10-meter wind speed as a proxy for wave action. This investigation coupled the 3 rd generation prognostic WAVEWATCH-III wind-wave model within a coupled Earth system model (ESM) to drive PMA production using wave energy dissipation rate – analogous to whitecapping – in place of 10-meter wind speed. The wind speed parameterization did not capture basin-scale variability in relations between wind and wave fields. Overall, the wave parameterization did not improve comparison between simulated versus measured AOD ormore » Na +, thus highlighting large remaining uncertainties in model physics. Results confirm the efficacy of prognostic wind-wave models for air-sea exchange studies coupled with laboratory- and field-based characterizations of the primary physical drivers of PMA production. No discernible correlations were evident between simulated PMA fields and observed chlorophyll or sea surface temperature.« less

Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

NASA Astrophysics Data System (ADS)

Bonan, Gordon B.; Patton, Edward G.; Harman, Ian N.; Oleson, Keith W.; Finnigan, John J.; Lu, Yaqiong; Burakowski, Elizabeth A.

2018-04-01

Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin-Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.

Computational issues in complex water-energy optimization problems: Time scales, parameterizations, objectives and algorithms

NASA Astrophysics Data System (ADS)

Efstratiadis, Andreas; Tsoukalas, Ioannis; Kossieris, Panayiotis; Karavokiros, George; Christofides, Antonis; Siskos, Alexandros; Mamassis, Nikos; Koutsoyiannis, Demetris

2015-04-01

Modelling of large-scale hybrid renewable energy systems (HRES) is a challenging task, for which several open computational issues exist. HRES comprise typical components of hydrosystems (reservoirs, boreholes, conveyance networks, hydropower stations, pumps, water demand nodes, etc.), which are dynamically linked with renewables (e.g., wind turbines, solar parks) and energy demand nodes. In such systems, apart from the well-known shortcomings of water resources modelling (nonlinear dynamics, unknown future inflows, large number of variables and constraints, conflicting criteria, etc.), additional complexities and uncertainties arise due to the introduction of energy components and associated fluxes. A major difficulty is the need for coupling two different temporal scales, given that in hydrosystem modeling, monthly simulation steps are typically adopted, yet for a faithful representation of the energy balance (i.e. energy production vs. demand) a much finer resolution (e.g. hourly) is required. Another drawback is the increase of control variables, constraints and objectives, due to the simultaneous modelling of the two parallel fluxes (i.e. water and energy) and their interactions. Finally, since the driving hydrometeorological processes of the integrated system are inherently uncertain, it is often essential to use synthetically generated input time series of large length, in order to assess the system performance in terms of reliability and risk, with satisfactory accuracy. To address these issues, we propose an effective and efficient modeling framework, key objectives of which are: (a) the substantial reduction of control variables, through parsimonious yet consistent parameterizations; (b) the substantial decrease of computational burden of simulation, by linearizing the combined water and energy allocation problem of each individual time step, and solve each local sub-problem through very fast linear network programming algorithms, and (c) the substantial decrease of the required number of function evaluations for detecting the optimal management policy, using an innovative, surrogate-assisted global optimization approach.

Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

Computation at a coordinate singularity

NASA Astrophysics Data System (ADS)

Prusa, Joseph M.

2018-05-01

Coordinate singularities are sometimes encountered in computational problems. An important example involves global atmospheric models used for climate and weather prediction. Classical spherical coordinates can be used to parameterize the manifold - that is, generate a grid for the computational spherical shell domain. This particular parameterization offers significant benefits such as orthogonality and exact representation of curvature and connection (Christoffel) coefficients. But it also exhibits two polar singularities and at or near these points typical continuity/integral constraints on dependent fields and their derivatives are generally inadequate and lead to poor model performance and erroneous results. Other parameterizations have been developed that eliminate polar singularities, but problems of weaker singularities and enhanced grid noise compared to spherical coordinates (away from the poles) persist. In this study reparameterization invariance of geometric objects (scalars, vectors and the forms generated by their covariant derivatives) is utilized to generate asymptotic forms for dependent fields of interest valid in the neighborhood of a pole. The central concept is that such objects cannot be altered by the metric structure of a parameterization. The new boundary conditions enforce symmetries that are required for transformations of geometric objects. They are implemented in an implicit polar filter of a structured grid, nonhydrostatic global atmospheric model that is simulating idealized Held-Suarez flows. A series of test simulations using different configurations of the asymptotic boundary conditions are made, along with control simulations that use the default model numerics with no absorber, at three different grid sizes. Typically the test simulations are ∼ 20% faster in wall clock time than the control-resulting from a decrease in noise at the poles in all cases. In the control simulations adverse numerical effects from the polar singularity are observed to increase with grid resolution. In contrast, test simulations demonstrate robust polar behavior independent of grid resolution.

Effects of downscaled high-resolution meteorological data on the PSCF identification of emission sources

DOE PAGES

Cheng, Meng -Dawn; Kabela, Erik D.

2016-04-30

The Potential Source Contribution Function (PSCF) model has been successfully used for identifying regions of emission source at a long distance in this study, the PSCF model relies on backward trajectories calculated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. In this study, we investigated the impacts of grid resolution and Planetary Boundary Layer (PBL) parameterization (e.g., turbulent transport of pollutants) on the PSCF analysis. The Mellor-Yamada-Janjic (MYJ) and Yonsei University (YUS) parameterization schemes were selected to model the turbulent transport in the PBL within the Weather Research and Forecasting (WRF version 3.6) model. Two separate domain grid sizesmore » (83 and 27 km) were chosen in the WRF downscaling in generating the wind data for driving the HYSPLIT calculation. The effects of grid size and PBL parameterization are important in incorporating the influ- ence of regional and local meteorological processes such as jet streaks, blocking patterns, Rossby waves, and terrain-induced convection on the transport of pollutants by a wind trajectory. We found high resolution PSCF did discover and locate source areas more precisely than that with lower resolution meteorological inputs. The lack of anticipated improvement could also be because a PBL scheme chosen to produce the WRF data was only a local parameterization and unable to faithfully duplicate the real atmosphere on a global scale. The MYJ scheme was able to replicate PSCF source identification by those using the Reanalysis and discover additional source areas that was not identified by the Reanalysis data. In conclusion, a potential benefit for using high-resolution wind data in the PSCF modeling is that it could discover new source location in addition to those identified by using the Reanalysis data input.« less

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.

2009-01-01

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Parameterizing the Spatial Markov Model From Breakthrough Curve Data Alone

NASA Astrophysics Data System (ADS)

Sherman, Thomas; Fakhari, Abbas; Miller, Savannah; Singha, Kamini; Bolster, Diogo

2017-12-01

The spatial Markov model (SMM) is an upscaled Lagrangian model that effectively captures anomalous transport across a diverse range of hydrologic systems. The distinct feature of the SMM relative to other random walk models is that successive steps are correlated. To date, with some notable exceptions, the model has primarily been applied to data from high-resolution numerical simulations and correlation effects have been measured from simulated particle trajectories. In real systems such knowledge is practically unattainable and the best one might hope for is breakthrough curves (BTCs) at successive downstream locations. We introduce a novel methodology to quantify velocity correlation from BTC data alone. By discretizing two measured BTCs into a set of arrival times and developing an inverse model, we estimate velocity correlation, thereby enabling parameterization of the SMM in studies where detailed Lagrangian velocity statistics are unavailable. The proposed methodology is applied to two synthetic numerical problems, where we measure all details and thus test the veracity of the approach by comparison of estimated parameters with known simulated values. Our results suggest that our estimated transition probabilities agree with simulated values and using the SMM with this estimated parameterization accurately predicts BTCs downstream. Our methodology naturally allows for estimates of uncertainty by calculating lower and upper bounds of velocity correlation, enabling prediction of a range of BTCs. The measured BTCs fall within the range of predicted BTCs. This novel method to parameterize the SMM from BTC data alone is quite parsimonious, thereby widening the SMM's practical applicability.

Bioaccumulation and Aquatic System Simulator (BASS) User's Manual Beta Test Version 2.1. EPA/600/R-01/035

EPA Pesticide Factsheets

this report describes the theoretical development, parameterization, and application software of a generalized, community-based, bioaccumulation model called BASS (Bioaccumulation and Aquatic System Simulator).

The applicability of the viscous α-parameterization of gravitational instability in circumstellar disks

NASA Astrophysics Data System (ADS)

Vorobyov, E. I.

2010-01-01

We study numerically the applicability of the effective-viscosity approach for simulating the effect of gravitational instability (GI) in disks of young stellar objects with different disk-to-star mass ratios ξ . We adopt two α-parameterizations for the effective viscosity based on Lin and Pringle [Lin, D.N.C., Pringle, J.E., 1990. ApJ 358, 515] and Kratter et al. [Kratter, K.M., Matzner, Ch.D., Krumholz, M.R., 2008. ApJ 681, 375] and compare the resultant disk structure, disk and stellar masses, and mass accretion rates with those obtained directly from numerical simulations of self-gravitating disks around low-mass (M∗ ∼ 1.0M⊙) protostars. We find that the effective viscosity can, in principle, simulate the effect of GI in stellar systems with ξ≲ 0.2- 0.3 , thus corroborating a similar conclusion by Lodato and Rice [Lodato, G., Rice, W.K.M., 2004. MNRAS 351, 630] that was based on a different α-parameterization. In particular, the Kratter et al.'s α-parameterization has proven superior to that of Lin and Pringle's, because the success of the latter depends crucially on the proper choice of the α-parameter. However, the α-parameterization generally fails in stellar systems with ξ≳ 0.3 , particularly in the Classes 0 and I phases of stellar evolution, yielding too small stellar masses and too large disk-to-star mass ratios. In addition, the time-averaged mass accretion rates onto the star are underestimated in the early disk evolution and greatly overestimated in the late evolution. The failure of the α-parameterization in the case of large ξ is caused by a growing strength of low-order spiral modes in massive disks. Only in the late Class II phase, when the magnitude of spiral modes diminishes and the mode-to-mode interaction ensues, may the effective viscosity be used to simulate the effect of GI in stellar systems with ξ≳ 0.3 . A simple modification of the effective viscosity that takes into account disk fragmentation can somewhat improve the performance of α-models in the case of large ξ and even approximately reproduce the mass accretion burst phenomenon, the latter being a signature of the early gravitationally unstable stage of stellar evolution [Vorobyov, E.I., Basu, S., 2006. ApJ 650, 956]. However, further numerical experiments are needed to explore this issue.

Pion, Kaon, Proton and Antiproton Production in Proton-Proton Collisions

NASA Technical Reports Server (NTRS)

Norbury, John W.; Blattnig, Steve R.

2008-01-01

Inclusive pion, kaon, proton, and antiproton production from proton-proton collisions is studied at a variety of proton energies. Various available parameterizations of Lorentz-invariant differential cross sections as a function of transverse momentum and rapidity are compared with experimental data. The Badhwar and Alper parameterizations are moderately satisfactory for charged pion production. The Badhwar parameterization provides the best fit for charged kaon production. For proton production, the Alper parameterization is best, and for antiproton production the Carey parameterization works best. However, no parameterization is able to fully account for all the data.

Data Automata in Scala

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2014-01-01

The field of runtime verification has during the last decade seen a multitude of systems for monitoring event sequences (traces) emitted by a running system. The objective is to ensure correctness of a system by checking its execution traces against formal specifications representing requirements. A special challenge is data parameterized events, where monitors have to keep track of the combination of control states as well as data constraints, relating events and the data they carry across time points. This poses a challenge wrt. efficiency of monitors, as well as expressiveness of logics. Data automata is a form of automata where states are parameterized with data, supporting monitoring of data parameterized events. We describe the full details of a very simple API in the Scala programming language, an internal DSL (Domain-Specific Language), implementing data automata. The small implementation suggests a design pattern. Data automata allow transition conditions to refer to other states than the source state, and allow target states of transitions to be inlined, offering a temporal logic flavored notation. An embedding of a logic in a high-level language like Scala in addition allows monitors to be programmed using all of Scala's language constructs, offering the full flexibility of a programming language. The framework is demonstrated on an XML processing scenario previously addressed in related work.

Explicit simulation of a midlatitude Mesoscale Convective System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexander, G.D.; Cotton, W.R.

1996-04-01

We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation andmore » testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.« less

Circuit Design Optimization Using Genetic Algorithm with Parameterized Uniform Crossover

NASA Astrophysics Data System (ADS)

Bao, Zhiguo; Watanabe, Takahiro

Evolvable hardware (EHW) is a new research field about the use of Evolutionary Algorithms (EAs) to construct electronic systems. EHW refers in a narrow sense to use evolutionary mechanisms as the algorithmic drivers for system design, while in a general sense to the capability of the hardware system to develop and to improve itself. Genetic Algorithm (GA) is one of typical EAs. We propose optimal circuit design by using GA with parameterized uniform crossover (GApuc) and with fitness function composed of circuit complexity, power, and signal delay. Parameterized uniform crossover is much more likely to distribute its disruptive trials in an unbiased manner over larger portions of the space, then it has more exploratory power than one and two-point crossover, so we have more chances of finding better solutions. Its effectiveness is shown by experiments. From the results, we can see that the best elite fitness, the average value of fitness of the correct circuits and the number of the correct circuits of GApuc are better than that of GA with one-point crossover or two-point crossover. The best case of optimal circuits generated by GApuc is 10.18% and 6.08% better in evaluating value than that by GA with one-point crossover and two-point crossover, respectively.

Representation, Modeling and Recognition of Outdoor Scenes

DTIC Science & Technology

1994-04-01

B. C. Vemuri and R . Malladi . Deformable models: Canonical parameters for surface representation and multiple view integration. In Conference on...or a high disparity gradient. If both L- R and R -L disparity images are made available, then mirror images of this pattern may be sought in the two...et at., 1991, Terzopoulos and Vasilescu, 1991, Vemuri and Malladi , 1991], parameterized surfaces [Stokely and Wu, 1992, Lowe, 1991], local surfaces

Trajectory Optimization for Helicopter Unmanned Aerial Vehicles (UAVs)

DTIC Science & Technology

2010-06-01

the Nth-order derivative of the Legendre Polynomial ( )NL t . Using this method, the range of integration is transformed universally to [-1,+1...which is the interval for Legendre Polynomials . Although the LGL interpolation points are not evenly spaced, they are symmetric about the midpoint 0...the vehicle’s kinematic constraints are parameterized in terms of polynomials of sufficient order, (2) A collision-free criterion is developed and

Integrating the Nqueens Algorithm into a Parameterized Benchmark Suite

DTIC Science & Technology

2016-02-01

FOB is a 64-node heterogeneous cluster consisting of 16-IBM dx360M4 nodes, each with one NVIDIA Kepler K20M GPUs and 48-IBM dx360M4 nodes, and each...nodes have 256-GB of memory and an NVIDIA Tesla K40 GPU. More details on Excalibur can be found on the US Army DSRC website.19 Figures 3 and 4 show the

Impact of a Stochastic Parameterization Scheme on El Nino-Southern Oscillation in the Community Climate System Model

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Berner, J.; Sardeshmukh, P. D.

2017-12-01

Stochastic parameterizations have been used for more than a decade in atmospheric models. They provide a way to represent model uncertainty through representing the variability of unresolved sub-grid processes, and have been shown to have a beneficial effect on the spread and mean state for medium- and extended-range forecasts. There is increasing evidence that stochastic parameterization of unresolved processes can improve the bias in mean and variability, e.g. by introducing a noise-induced drift (nonlinear rectification), and by changing the residence time and structure of flow regimes. We present results showing the impact of including the Stochastically Perturbed Parameterization Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. SPPT results in a significant improvement in the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. We use a Linear Inverse Modelling framework to gain insight into the mechanisms by which SPPT has improved ENSO-variability.

Improving Calculation Accuracies of Accumulation-Mode Fractions Based on Spectral of Aerosol Optical Depths

NASA Astrophysics Data System (ADS)

Ying, Zhang; Zhengqiang, Li; Yan, Wang

2014-03-01

Anthropogenic aerosols are released into the atmosphere, which cause scattering and absorption of incoming solar radiation, thus exerting a direct radiative forcing on the climate system. Anthropogenic Aerosol Optical Depth (AOD) calculations are important in the research of climate changes. Accumulation-Mode Fractions (AMFs) as an anthropogenic aerosol parameter, which are the fractions of AODs between the particulates with diameters smaller than 1μm and total particulates, could be calculated by AOD spectral deconvolution algorithm, and then the anthropogenic AODs are obtained using AMFs. In this study, we present a parameterization method coupled with an AOD spectral deconvolution algorithm to calculate AMFs in Beijing over 2011. All of data are derived from AErosol RObotic NETwork (AERONET) website. The parameterization method is used to improve the accuracies of AMFs compared with constant truncation radius method. We find a good correlation using parameterization method with the square relation coefficient of 0.96, and mean deviation of AMFs is 0.028. The parameterization method could also effectively solve AMF underestimate in winter. It is suggested that the variations of Angstrom indexes in coarse mode have significant impacts on AMF inversions.

Ideas for the rapid development of the structural models in mechanical engineering

NASA Astrophysics Data System (ADS)

Oanta, E.; Raicu, A.; Panait, C.

2017-08-01

Conceiving computer based instruments is a long run concern of the authors. Some of the original solutions are: optimal processing of the large matrices, interfaces between the programming languages, approximation theory using spline functions, numerical programming increased accuracy based on the extended arbitrary precision libraries. For the rapid development of the models we identified the following directions: atomization, ‘librarization’, parameterization, automatization and integration. Each of these directions has some particular aspects if we approach mechanical design problems or software development. Atomization means a thorough top-down decomposition analysis which offers an insight regarding the basic features of the phenomenon. Creation of libraries of reusable mechanical parts and libraries of programs (data types, functions) save time, cost and effort when a new model must be conceived. Parameterization leads to flexible definition of the mechanical parts, the values of the parameters being changed either using a dimensioning program or in accord to other parts belonging to the same assembly. The resulting templates may be also included in libraries. Original software applications are useful for the model’s input data generation, to input the data into CAD/FEA commercial applications and for the data integration of the various types of studies included in the same project.

Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models

USGS Publications Warehouse

Welter, David E.; Doherty, John E.; Hunt, Randall J.; Muffels, Christopher T.; Tonkin, Matthew J.; Schreuder, Willem A.

2012-01-01

An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.

A new stomatal paradigm for earth system models? (Invited)

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Williams, M. D.; Fisher, R. A.; Oleson, K. W.; Lombardozzi, D.

2013-12-01

The land component of climate, and now earth system, models has simulated stomatal conductance since the introduction in the mid-1980s of the so-called second generation models that explicitly represented plant canopies. These second generation models used the Jarvis-style stomatal conductance model, which empirically relates stomatal conductance to photosynthetically active radiation, temperature, vapor pressure deficit, CO2 concentration, and other factors. Subsequent models of stomatal conductance were developed from a more mechanistic understanding of stomatal physiology, particularly that stomata are regulated so as to maximize net CO2 assimilation (An) and minimize water loss during transpiration (E). This concept is embodied in the Ball-Berry stomatal conductance model, which relates stomatal conductance (gs) to net assimilation (An), scaled by the ratio of leaf surface relative humidity to leaf surface CO2 concentration, or the Leuning variant which replaces relative humidity with a vapor pressure deficit term. This coupled gs-An model has been widely used in climate and earth system models since the mid-1990s. An alternative approach models stomatal conductance by directly optimizing water use efficiency, defined as the ratio An/gs or An/E. Conceptual developments over the past several years have shown that the Ball-Berry style model can be derived from optimization theory. However, an explicit optimization model has not been tested in an earth system model. We compare the Ball-Berry model with an explicit optimization model, both implemented in a new plant canopy parameterization developed for the Community Land Model, the land component of the Community Earth System Model. The optimization model is from the Soil-Plant-Atmosphere (SPA) model, which integrates plant and soil hydraulics, carbon assimilation, and gas diffusion. The canopy parameterization is multi-layer and resolves profiles of radiation, temperature, vapor pressure, leaf water stress, stomatal conductance, and photosynthetic capacity within the canopy. Stomatal conductance for each layer is calculated so as to maximize carbon gain, within the limitations of plant water storage and soil-to-canopy water transport. An iterative procedure determines for every model timestep the maximum stomatal conductance for a canopy layer and the associated assimilation rate. We compare the Ball-Berry stomatal model and the SPA stomatal model within the multi-layer canopy parameterization. We use eddy covariance flux tower data for six sites (three deciduous broadleaf forest and three evergreen needleleaf forest) spanning a total of 51 site-years. The multi-layer canopy has improved simulation of gross primary production (GPP), evapotranspiration, and sensible heat flux compared with the most recent version of the Community Land Model (CLM4.5). The Ball-Berry and SPA stomatal models have prominent differences in simulated fluxes and compared with observations. This is most evident during drought.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

Mineral solubilities in the Na-K-Mg-Ca-Cl-SO 4-H 2O system: a re-evaluation of the sulfate chemistry in the Spencer-Møller-Weare model

NASA Astrophysics Data System (ADS)

Marion, Giles M.; Farren, Ronald E.

1999-05-01

The Spencer-Møller-Weare (SMW) (1990) model is parameterized for the Na-K-Mg-Ca-Cl-SO 4-H 2O system over the temperature range from -60° to 25°C. This model is one of the few complex chemical equilibrium models for aqueous solutions parameterized for subzero temperatures. The primary focus of the SMW model parameterization and validation deals with chloride systems. There are problems with the sulfate parameterization of the SMW model, most notably with sodium sulfate and magnesium sulfate. The primary objective of this article is to re-estimate the Pitzer-equation parameters governing interactions among sodium, potassium, magnesium, and calcium with sulfate in the SMW model. A mathematical algorithm is developed to estimate 22 temperature-dependent Pitzer-equation parameters. The sodium sulfate reparameterization reduces the overall standard error (SE) from 0.393 with the SMW Pitzer-equation parameters to 0.155. Similarly, the magnesium sulfate reparameterization reduces the SE from 0.335 to 0.124. In addition to the sulfate reparameterization, five additional sulfate minerals are included in the model, which allows a more complete treatment of sulfate chemistry in the Na-K-Mg-Ca-Cl-SO 4-H 2O system. Application of the model to seawater evaporation predicts gypsum precipitation at a seawater concentration factor (SCF) of 3.37 and halite precipitation at an SCF of 10.56, which are in good agreement with previous experimental and theoretical estimates. Application of the model to seawater freezing helps explain the two pathways for seawater freezing. Along the thermodynamically stable "Gitterman pathway," calcium precipitates as gypsum and the seawater eutectic is -36.2°C. Along the metastable "Ringer-Nelson-Thompson pathway," calcium precipitates as antarcticite and the seawater eutectic is -53.8°C.

CloudSat 2C-ICE product update with a new Ze parameterization in lidar-only region.

PubMed

Deng, Min; Mace, Gerald G; Wang, Zhien; Berry, Elizabeth

2015-12-16

The CloudSat 2C-ICE data product is derived from a synergetic ice cloud retrieval algorithm that takes as input a combination of CloudSat radar reflectivity ( Z e ) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation lidar attenuated backscatter profiles. The algorithm uses a variational method for retrieving profiles of visible extinction coefficient, ice water content, and ice particle effective radius in ice or mixed-phase clouds. Because of the nature of the measurements and to maintain consistency in the algorithm numerics, we choose to parameterize (with appropriately large specification of uncertainty) Z e and lidar attenuated backscatter in the regions of a cirrus layer where only the lidar provides data and where only the radar provides data, respectively. To improve the Z e parameterization in the lidar-only region, the relations among Z e , extinction, and temperature have been more thoroughly investigated using Atmospheric Radiation Measurement long-term millimeter cloud radar and Raman lidar measurements. This Z e parameterization provides a first-order estimation of Z e as a function extinction and temperature in the lidar-only regions of cirrus layers. The effects of this new parameterization have been evaluated for consistency using radiation closure methods where the radiative fluxes derived from retrieved cirrus profiles compare favorably with Clouds and the Earth's Radiant Energy System measurements. Results will be made publicly available for the entire CloudSat record (since 2006) in the most recent product release known as R05.

Modeling the energy balance in Marseille: Sensitivity to roughness length parameterizations and thermal admittance

NASA Astrophysics Data System (ADS)

Demuzere, M.; De Ridder, K.; van Lipzig, N. P. M.

2008-08-01

During the ESCOMPTE campaign (Experience sur Site pour COntraindre les Modeles de Pollution atmospherique et de Transport d'Emissions), a 4-day intensive observation period was selected to evaluate the Advanced Regional Prediction System (ARPS), a nonhydrostatic meteorological mesoscale model that was optimized with a parameterization for thermal roughness length to better represent urban surfaces. The evaluation shows that the ARPS model is able to correctly reproduce temperature, wind speed, and direction for one urban and two rural measurements stations. Furthermore, simulated heat fluxes show good agreement compared to the observations, although simulated sensible heat fluxes were initially too low for the urban stations. In order to improve the latter, different roughness length parameterization schemes were tested, combined with various thermal admittance values. This sensitivity study showed that the Zilitinkevich scheme combined with and intermediate value of thermal admittance performs best.

Evaluating and Understanding Parameterized Convective Processes and their Role in the Development of Mesoscale Precipitation Systems

NASA Technical Reports Server (NTRS)

Fritsch, J. Michael; Kain, John S.

1997-01-01

Research efforts during the second year have centered on improving the manner in which convective stabilization is achieved in the Penn State/NCAR mesoscale model MM5. Ways of improving this stabilization have been investigated by (1) refining the partitioning between the Kain-Fritsch convective parameterization scheme and the grid scale by introducing a form of moist convective adjustment; (2) using radar data to define locations of subgrid-scale convection during a dynamic initialization period; and (3) parameterizing deep-convective feedbacks as subgrid-scale sources and sinks of mass. These investigations were conducted by simulating a long-lived convectively-generated mesoscale vortex that occurred during 14-18 Jul. 1982 and the 10-11 Jun. 1985 squall line that occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. The long-lived vortex tracked across the central Plains states and was responsible for multiple convective outbreaks during its lifetime.

From Global to Cloud Resolving Scale: Experiments with a Scale- and Aerosol-Aware Physics Package and Impact on Tracer Transport

NASA Astrophysics Data System (ADS)

Grell, G. A.; Freitas, S. R.; Olson, J.; Bela, M.

2017-12-01

We will start by providing a summary of the latest cumulus parameterization modeling efforts at NOAA's Earth System Research Laboratory (ESRL) will be presented on both regional and global scales. The physics package includes a scale-aware parameterization of subgrid cloudiness feedback to radiation (coupled PBL, microphysics, radiation, shallow and congestus type convection), the stochastic Grell-Freitas (GF) scale- and aerosol-aware convective parameterization, and an aerosol aware microphysics package. GF is based on a stochastic approach originally implemented by Grell and Devenyi (2002) and described in more detail in Grell and Freitas (2014, ACP). It was expanded to include PDF's for vertical mass flux, as well as modifications to improve the diurnal cycle. This physics package will be used on different scales, spanning global to cloud resolving, to look at the impact on scalar transport and numerical weather prediction.

Aerodynamic Shape Optimization Design of Wing-Body Configuration Using a Hybrid FFD-RBF Parameterization Approach

NASA Astrophysics Data System (ADS)

Liu, Yuefeng; Duan, Zhuoyi; Chen, Song

2017-10-01

Aerodynamic shape optimization design aiming at improving the efficiency of an aircraft has always been a challenging task, especially when the configuration is complex. In this paper, a hybrid FFD-RBF surface parameterization approach has been proposed for designing a civil transport wing-body configuration. This approach is simple and efficient, with the FFD technique used for parameterizing the wing shape and the RBF interpolation approach used for handling the wing body junction part updating. Furthermore, combined with Cuckoo Search algorithm and Kriging surrogate model with expected improvement adaptive sampling criterion, an aerodynamic shape optimization design system has been established. Finally, the aerodynamic shape optimization design on DLR F4 wing-body configuration has been carried out as a study case, and the result has shown that the approach proposed in this paper is of good effectiveness.

Monitoring with Data Automata

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2014-01-01

We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.

Self-similar Relativisitic Disks revisted

NASA Astrophysics Data System (ADS)

Cai, M. J.; Shu, F. H.

2001-05-01

We revisit the rotating self-similar disk first studied by Lynden-Bell and Pineault and extend it to include pressure. A two-parameter family of solutions is constructed numerically. These disks are parameterized by the constant linear rotation velocity v, and the isothermal sound speed γ 1/2. For sufficiently high velocities, an ergo region develops in the form of the exterior of a cone. For each value of γ , there is a maximum velocity vc above which there is no equilibrium solutions. For this solution the frame dragging is infinite and the ergo cone closes on the rotation axis. The null geodesic equations are also integrated numerically. Due to the infinite extend and mass of the system, all photon trajectories are focused towards the disk. The behavior of equatorial photons orbits is qualitatively the same as that of cold disks.

Large-Scale Transport Responses to Tropospheric Circulation Changes Using GEOS-5

NASA Technical Reports Server (NTRS)

Orbe, Clara; Molod, Andrea; Arnold, Nathan; Waugh, Darryn W.; Yang, Huang

2017-01-01

The mean age since air was last at the Northern Hemisphere midlatitude surface is a fundamental property of tropospheric transport. Recent comparisons among chemistry climate models, however, reveal that there are large differences in the mean age among models and that these differences are most likely related to differences in tropical (parameterized) convection. Here we use aquaplanet simulations of the Goddard Earth Observing System Model Version 5 (GEOS-5) to explore the sensitivity of the mean age to changes in the tropical circulation. Tropical circulation changes are forced by prescribed localized off-equatorial warm sea surface temperature anomalies that (qualitatively) reproduce the convection and circulation differences among the comprehensive models. Idealized chemical species subject to prescribed OH loss are also integrated in parallel in order to illustrate the impact of tropical transport changes on interhemispheric constituent transport.

Novel Networked Remote Laboratory Architecture for Open Connectivity Based on PLC-OPC-LabVIEW-EJS Integration. Application in Remote Fuzzy Control and Sensors Data Acquisition.

PubMed

González, Isaías; Calderón, Antonio José; Mejías, Andrés; Andújar, José Manuel

2016-10-31

In this paper the design and implementation of a network for integrating Programmable Logic Controllers (PLC), the Object-Linking and Embedding for Process Control protocol (OPC) and the open-source Easy Java Simulations (EJS) package is presented. A LabVIEW interface and the Java-Internet-LabVIEW (JIL) server complete the scheme for data exchange. This configuration allows the user to remotely interact with the PLC. Such integration can be considered a novelty in scientific literature for remote control and sensor data acquisition of industrial plants. An experimental application devoted to remote laboratories is developed to demonstrate the feasibility and benefits of the proposed approach. The experiment to be conducted is the parameterization and supervision of a fuzzy controller of a DC servomotor. The graphical user interface has been developed with EJS and the fuzzy control is carried out by our own PLC. In fact, the distinctive features of the proposed novel network application are the integration of the OPC protocol to share information with the PLC and the application under control. The user can perform the tuning of the controller parameters online and observe in real time the effect on the servomotor behavior. The target group is engineering remote users, specifically in control- and automation-related tasks. The proposed architecture system is described and experimental results are presented.

Novel Networked Remote Laboratory Architecture for Open Connectivity Based on PLC-OPC-LabVIEW-EJS Integration. Application in Remote Fuzzy Control and Sensors Data Acquisition

PubMed Central

González, Isaías; Calderón, Antonio José; Mejías, Andrés; Andújar, José Manuel

2016-01-01

In this paper the design and implementation of a network for integrating Programmable Logic Controllers (PLC), the Object-Linking and Embedding for Process Control protocol (OPC) and the open-source Easy Java Simulations (EJS) package is presented. A LabVIEW interface and the Java-Internet-LabVIEW (JIL) server complete the scheme for data exchange. This configuration allows the user to remotely interact with the PLC. Such integration can be considered a novelty in scientific literature for remote control and sensor data acquisition of industrial plants. An experimental application devoted to remote laboratories is developed to demonstrate the feasibility and benefits of the proposed approach. The experiment to be conducted is the parameterization and supervision of a fuzzy controller of a DC servomotor. The graphical user interface has been developed with EJS and the fuzzy control is carried out by our own PLC. In fact, the distinctive features of the proposed novel network application are the integration of the OPC protocol to share information with the PLC and the application under control. The user can perform the tuning of the controller parameters online and observe in real time the effect on the servomotor behavior. The target group is engineering remote users, specifically in control- and automation-related tasks. The proposed architecture system is described and experimental results are presented. PMID:27809229

Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed graph condition.

PubMed

Wang, Wei; Wen, Changyun; Huang, Jiangshuai; Fan, Huijin

2017-11-01

In this paper, a backstepping based distributed adaptive control scheme is proposed for multiple uncertain Euler-Lagrange systems under directed graph condition. The common desired trajectory is allowed totally unknown by part of the subsystems and the linearly parameterized trajectory model assumed in currently available results is no longer needed. To compensate the effects due to unknown trajectory information, a smooth function of consensus errors and certain positive integrable functions are introduced in designing virtual control inputs. Besides, to overcome the difficulty of completely counteracting the coupling terms of distributed consensus errors and parameter estimation errors in the presence of asymmetric Laplacian matrix, extra information transmission of local parameter estimates are introduced among linked subsystem and adaptive gain technique is adopted to generate distributed torque inputs. It is shown that with the proposed distributed adaptive control scheme, global uniform boundedness of all the closed-loop signals and asymptotically output consensus tracking can be achieved. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A Vertically Lagrangian Finite-Volume Dynamical Core for Global Models

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann

2003-01-01

A finite-volume dynamical core with a terrain-following Lagrangian control-volume discretization is described. The vertically Lagrangian discretization reduces the dimensionality of the physical problem from three to two with the resulting dynamical system closely resembling that of the shallow water dynamical system. The 2D horizontal-to-Lagrangian-surface transport and dynamical processes are then discretized using the genuinely conservative flux-form semi-Lagrangian algorithm. Time marching is split- explicit, with large-time-step for scalar transport, and small fractional time step for the Lagrangian dynamics, which permits the accurate propagation of fast waves. A mass, momentum, and total energy conserving algorithm is developed for mapping the state variables periodically from the floating Lagrangian control-volume to an Eulerian terrain-following coordinate for dealing with physical parameterizations and to prevent severe distortion of the Lagrangian surfaces. Deterministic baroclinic wave growth tests and long-term integrations using the Held-Suarez forcing are presented. Impact of the monotonicity constraint is discussed.

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC

PubMed Central

Mukhtar, Hussnain; Lin, Yu-Pin; Shipin, Oleg V.; Petway, Joy R.

2017-01-01

This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH3-N and NO3-N. Results indicate that the integrated FME-GLUE-based model, with good Nash–Sutcliffe coefficients (0.53–0.69) and correlation coefficients (0.76–0.83), successfully simulates the concentrations of ON-N, NH3-N and NO3-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH3-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO3-N simulation, which was measured using global sensitivity. PMID:28704958

Dynamic analysis of nonlinear rotor-housing systems

NASA Technical Reports Server (NTRS)

Noah, Sherif T.

1988-01-01

Nonlinear analysis methods are developed which will enable the reliable prediction of the dynamic behavior of the space shuttle main engine (SSME) turbopumps in the presence of bearing clearances and other local nonlinearities. A computationally efficient convolution method, based on discretized Duhamel and transition matrix integral formulations, is developed for the transient analysis. In the formulation, the coupling forces due to the nonlinearities are treated as external forces acting on the coupled subsystems. Iteration is utilized to determine their magnitudes at each time increment. The method is applied to a nonlinear generic model of the high pressure oxygen turbopump (HPOTP). As compared to the fourth order Runge-Kutta numerical integration methods, the convolution approach proved to be more accurate and more highly efficient. For determining the nonlinear, steady-state periodic responses, an incremental harmonic balance method was also developed. The method was successfully used to determine dominantly harmonic and subharmonic responses fo the HPOTP generic model with bearing clearances. A reduction method similar to the impedance formulation utilized with linear systems is used to reduce the housing-rotor models to their coordinates at the bearing clearances. Recommendations are included for further development of the method, for extending the analysis to aperiodic and chaotic regimes and for conducting critical parameteric studies of the nonlinear response of the current SSME turbopumps.

Hierarchical Robot Control System and Method for Controlling Select Degrees of Freedom of an Object Using Multiple Manipulators

NASA Technical Reports Server (NTRS)

Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor); Abdallah, Muhammad E. (Inventor)

2013-01-01

A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type.

Assessing the performance of wave breaking parameterizations in shallow waters in spectral wave models

NASA Astrophysics Data System (ADS)

Lin, Shangfei; Sheng, Jinyu

2017-12-01

Depth-induced wave breaking is the primary dissipation mechanism for ocean surface waves in shallow waters. Different parametrizations were developed for parameterizing depth-induced wave breaking process in ocean surface wave models. The performance of six commonly-used parameterizations in simulating significant wave heights (SWHs) is assessed in this study. The main differences between these six parameterizations are representations of the breaker index and the fraction of breaking waves. Laboratory and field observations consisting of 882 cases from 14 sources of published observational data are used in the assessment. We demonstrate that the six parameterizations have reasonable performance in parameterizing depth-induced wave breaking in shallow waters, but with their own limitations and drawbacks. The widely-used parameterization suggested by Battjes and Janssen (1978, BJ78) has a drawback of underpredicting the SWHs in the locally-generated wave conditions and overpredicting in the remotely-generated wave conditions over flat bottoms. The drawback of BJ78 was addressed by a parameterization suggested by Salmon et al. (2015, SA15). But SA15 had relatively larger errors in SWHs over sloping bottoms than BJ78. We follow SA15 and propose a new parameterization with a dependence of the breaker index on the normalized water depth in deep waters similar to SA15. In shallow waters, the breaker index of the new parameterization has a nonlinear dependence on the local bottom slope rather than the linear dependence used in SA15. Overall, this new parameterization has the best performance with an average scatter index of ∼8.2% in comparison with the three best performing existing parameterizations with the average scatter index between 9.2% and 13.6%.

Integrated model-experimental framework to assess carbon cycle components in disturbed mountainous terrain

NASA Astrophysics Data System (ADS)

Stenzel, J.; Hudiburg, T. W.; Berardi, D.; McNellis, B.; Walsh, E.

2017-12-01

In forests vulnerable to drought and fire, there is critical need for in situ carbon and water balance measurements that can be integrated with earth system modeling to predict climate feedbacks. Model development can be improved by measurements that inform a mechanistic understanding of the component fluxes of net carbon uptake (i.e., NPP, autotrophic and heterotrophic respiration) and water use, with specific focus on responses to climate and disturbance. By integrating novel field-based instrumental technology, existing datasets, and state-of-the-art earth system modeling, we are attempting to 1) quantify the spatial and temporal impacts of forest thinning on regional biogeochemical cycling and climate 2) evaluate the impact of forest thinning on forest resilience to drought and disturbance in the Northern Rockies ecoregion. The combined model-experimental framework enables hypothesis testing that would otherwise be impossible because the use of new in situ high temporal resolution field technology allows for research in remote and mountainous terrains that have been excluded from eddy-covariance techniques. Our preliminary work has revealed some underlying difficulties with the new instrumentation that has led to new ideas and modified methods to correctly measure the component fluxes. Our observations of C balance following the thinning operations indicate that the recovery period (source to sink) is longer than hypothesized. Finally, we have incorporated a new plant functional type parameterization for Northern Rocky mixed-conifer into our simulation modeling using regional and site observations.

The response of the SSM/I to the marine environment. Part 2: A parameterization of the effect of the sea surface slope distribution on emission and reflection

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Katsaros, Kristina B.

1994-01-01

Based on a geometric optics model and the assumption of an isotropic Gaussian surface slope distribution, the component of ocean surface microwave emissivity variation due to large-scale surface roughness is parameterized for the frequencies and approximate viewing angle of the Special Sensor Microwave/Imager. Independent geophysical variables in the parameterization are the effective (microwave frequency dependent) slope variance and the sea surface temperature. Using the same physical model, the change in the effective zenith angle of reflected sky radiation arising from large-scale roughness is also parameterized. Independent geophysical variables in this parameterization are the effective slope variance and the atmospheric optical depth at the frequency in question. Both of the above model-based parameterizations are intended for use in conjunction with empirical parameterizations relating effective slope variance and foam coverage to near-surface wind speed. These empirical parameterizations are the subject of a separate paper.

Evaluating Lightning-generated NOx (LNOx) Parameterization based on Cloud Top Height at Resolutions with Partially-resolved Convection for Upper Tropospheric Chemistry Studies

NASA Astrophysics Data System (ADS)

Wong, J.; Barth, M. C.; Noone, D. C.

2012-12-01

Lightning-generated nitrogen oxides (LNOx) is an important precursor to tropospheric ozone production. With a meteorological time-scale variability similar to that of the ozone chemical lifetime, it can nonlinearly perturb tropospheric ozone concentration. Coupled with upper-air circulation patterns, LNOx can accumulate in significant amount in the upper troposphere with other precursors, thus enhancing ozone production (see attached figure). While LNOx emission has been included and tuned extensively in global climate models, its inclusions in regional chemistry models are seldom tested. Here we present a study that evaluates the frequently used Price and Rind parameterization based on cloud-top height at resolutions that partially resolve deep convection using the Weather Research and Forecasting model with Chemistry (WRF-Chem) over the contiguous United States. With minor modifications, the parameterization is shown to generate integrated flash counts close to those observed. However, the modeled frequency distribution of cloud-to-ground flashes do not represent well for storms with high flash rates, bringing into question the applicability of the intra-cloud/ground partitioning (IC:CG) formulation of Price and Rind in some studies. Resolution dependency also requires attention when sub-grid cloud-tops are used instead of the originally intended grid-averaged cloud-top. LNOx passive tracers being gathered by monsoonal upper tropospheric anticyclone.

Parameterization of the ACRU model for estimating biophysical and climatological change impacts, Beaver Creek, Alberta

NASA Astrophysics Data System (ADS)

Forbes, K. A.; Kienzle, S. W.; Coburn, C. A.; Byrne, J. M.

2006-12-01

Multiple threats, including intensification of agricultural production, non-renewable resource extraction and climate change, are threatening Southern Alberta's water supply. The objective of this research is to calibrate/evaluate the Agricultural Catchments Research Unit (ACRU) agrohydrological model; with the end goal of forecasting the impacts of a changing environment on water quantity. The strength of this model is the intensive multi-layered soil water budgeting routine that integrates water movement between the surface and atmosphere. The ACRU model was parameterized using data from Environment Canada's climate database for a twenty year period (1984-2004) and was used to simulate streamflow for Beaver Creek. The simulated streamflow was compared to Environment Canada's historical streamflow database to validate the model output. The Beaver Creek Watershed, located in the Porcupine Hills southwestern Alberta, Canada contains a heterogeneous cover of deciduous, coniferous, native prairie grasslands and forage crops. In a catchment with highly diversified land cover, canopy architecture cannot be overlooked in rainfall interception parameterization. Preliminary testing of ACRU suggests that streamflows were sensitive to varied levels of leaf area index (LAI), a representative fraction of canopy foliage. Further testing using remotely sensed LAI's will provide a more accurate representation of canopy foliage and ultimately best represent this important element of the hydrological cycle and the associated processes which govern the natural hydrology of the Beaver Creek watershed.

An Economical Analytical Equation for the Integrated Vertical Overlap of Cumulus and Stratus

NASA Astrophysics Data System (ADS)

Park, Sungsu

2018-03-01

By extending the previously proposed heuristic parameterization, the author derived an analytical equation computing the overlap areas between the precipitation (or radiation) areas and the cloud areas in a cloud system consisting of cumulus and stratus. The new analytical equation is accurate and much more efficient than the previous heuristic equation, which suffers from the truncation error in association with the digitalization of the overlap areas. Global test simulations with the new analytical formula in an offline mode showed that the maximum cumulus overlap simulates more surface precipitation flux than the random cumulus overlap. On the other hand, the maximum stratus overlap simulates less surface precipitation flux than random stratus overlap, which is due to the increase in the evaporation rate of convective precipitation from the random to maximum stratus overlap. The independent precipitation approximation (IPA) marginally decreases the surface precipitation flux, implying that IPA works well with other parameterizations. In contrast to the net production rate of precipitation and surface precipitation flux that increase when the cumulus and stratus are maximally and randomly overlapped, respectively, the global mean net radiative cooling and longwave cloud radiative forcing (LWCF) increase when the cumulus and stratus are randomly overlapped. On the global average, the vertical cloud overlap exerts larger impacts on the precipitation flux than on the radiation flux. The radiation scheme taking the subgrid variability of water vapor between the cloud and clear portions into account substantially increases the global mean LWCF in tropical deep convection and midlatitude storm track regions.

A stochastic multicloud convective parameterization in the NCEP Climate Forecast System (CFSv2) : implementation and calibration.

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Krishna, R. P. M.; Mukhopadhyay, P.; Majda, A.

2017-12-01

A stochastic multicloud (SMCM) cumulus parameterization is implemented in the National Centres for Environmental Predictions (NCEP) Climate Forecast System version 2 (CFSv2) model, named as the CFSsmcm model. We present here results from a systematic attempt to understand the CFSsmcm model's sensitivity to the SMCM parameters. To asses the model-sentivity to the different SMCM parameters, we have analized a set of 14 5-year long climate simulations produced by the CFSsmcm model. The model is found to be resilient to minor changes in the parameter values. The middle tropospheric dryness (MTD) and the stratiform cloud decay timescale are found to be most crucial parameters in the SMCM formulation in the CFSsmcm model.

Tropical Diabatic Heating and the Role of Convective Processes as Represented in Several Contemporary Climate Models

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Roads, John; Oglesby, Robert; Marshall, Susan

2004-01-01

One of the most fundamental properties of the global heat balance is the net heat input into the tropical atmosphere that helps drive the planetary atmospheric circulation. Although broadly understood in terms of its gross structure and balance of source / sink terms, incorporation of the relevant processes in predictive models is still rather poor. The work reported here examines the tropical radiative and water cycle behavior as produced by four contemporary climate models. Among these are the NSIPP-2 (NASA Seasonal to Interannual Prediction Project) which uses the RAS convective parameterization; the FVCCM, a code using finite volume numerics and the CCM3.6 physics; FVCCM-MCRAS again having the finite volume numerics, but MCRAS convective parameterization and a different radiation treatment; and, finally, the NCEP GSM which uses the RAS. Using multi-decadal integrations with specified SSTs we examine the statistics of radiative / convective processes and associated energy transports, and then estimate model energy flux sensitivities to SST changes. In particular the behavior of the convective parameterizations is investigated. Additional model integrations are performed specifically to assess the importance representing convective inhibition in regulating convective cloud-top structure and moisture detrainment as well as controlling surface energy fluxes. To evaluate the results of these experiments, a number of satellite retrievals are used: TRMM retrievals of vertical reflectivity structure, rainfall rate, and inferred diabatic heating are analyzed to show both seasonal and interannual variations in vertical structure of latent heat release. Top-of-atmosphere radiative fluxes from ERBS and CERES are used to examine shortwave and longwave cloud forcing and to deduce required seasonal energy transports. Retrievals of cloud properties from ISCCP and water vapor variations from SSM/T-2 are also used to understand behavior of the humidity fields. These observations are supplemented with output form the DOE Reanalysis-2.

The rational parameterization theorem for multisite post-translational modification systems.

PubMed

Thomson, Matthew; Gunawardena, Jeremy

2009-12-21

Post-translational modification of proteins plays a central role in cellular regulation but its study has been hampered by the exponential increase in substrate modification forms ("modforms") with increasing numbers of sites. We consider here biochemical networks arising from post-translational modification under mass-action kinetics, allowing for multiple substrates, having different types of modification (phosphorylation, methylation, acetylation, etc.) on multiple sites, acted upon by multiple forward and reverse enzymes (in total number L), using general enzymatic mechanisms. These assumptions are substantially more general than in previous studies. We show that the steady-state modform concentrations constitute an algebraic variety that can be parameterized by rational functions of the L free enzyme concentrations, with coefficients which are rational functions of the rate constants. The parameterization allows steady states to be calculated by solving L algebraic equations, a dramatic reduction compared to simulating an exponentially large number of differential equations. This complexity collapse enables analysis in contexts that were previously intractable and leads to biological predictions that we review. Our results lay a foundation for the systems biology of post-translational modification and suggest deeper connections between biochemical networks and algebraic geometry.

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE PAGES

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

2015-03-11

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Users Manual for the Geospatial Stream Flow Model (GeoSFM)

USGS Publications Warehouse

Artan, Guleid A.; Asante, Kwabena; Smith, Jodie; Pervez, Md Shahriar; Entenmann, Debbie; Verdin, James P.; Rowland, James

2008-01-01

The monitoring of wide-area hydrologic events requires the manipulation of large amounts of geospatial and time series data into concise information products that characterize the location and magnitude of the event. To perform these manipulations, scientists at the U.S. Geological Survey Center for Earth Resources Observation and Science (EROS), with the cooperation of the U.S. Agency for International Development, Office of Foreign Disaster Assistance (USAID/OFDA), have implemented a hydrologic modeling system. The system includes a data assimilation component to generate data for a Geospatial Stream Flow Model (GeoSFM) that can be run operationally to identify and map wide-area streamflow anomalies. GeoSFM integrates a geographical information system (GIS) for geospatial preprocessing and postprocessing tasks and hydrologic modeling routines implemented as dynamically linked libraries (DLLs) for time series manipulations. Model results include maps that depicting the status of streamflow and soil water conditions. This Users Manual provides step-by-step instructions for running the model and for downloading and processing the input data required for initial model parameterization and daily operation.

Towards a more efficient and robust representation of subsurface hydrological processes in Earth System Models

NASA Astrophysics Data System (ADS)

Rosolem, R.; Rahman, M.; Kollet, S. J.; Wagener, T.

2017-12-01

Understanding the impacts of land cover and climate changes on terrestrial hydrometeorology is important across a range of spatial and temporal scales. Earth System Models (ESMs) provide a robust platform for evaluating these impacts. However, current ESMs lack the representation of key hydrological processes (e.g., preferential water flow, and direct interactions with aquifers) in general. The typical "free drainage" conceptualization of land models can misrepresent the magnitude of those interactions, consequently affecting the exchange of energy and water at the surface as well as estimates of groundwater recharge. Recent studies show the benefits of explicitly simulating the interactions between subsurface and surface processes in similar models. However, such parameterizations are often computationally demanding resulting in limited application for large/global-scale studies. Here, we take a different approach in developing a novel parameterization for groundwater dynamics. Instead of directly adding another complex process to an established land model, we examine a set of comprehensive experimental scenarios using a very robust and establish three-dimensional hydrological model to develop a simpler parameterization that represents the aquifer to land surface interactions. The main goal of our developed parameterization is to simultaneously maximize the computational gain (i.e., "efficiency") while minimizing simulation errors in comparison to the full 3D model (i.e., "robustness") to allow for easy implementation in ESMs globally. Our study focuses primarily on understanding both the dynamics for groundwater recharge and discharge, respectively. Preliminary results show that our proposed approach significantly reduced the computational demand while model deviations from the full 3D model are considered to be small for these processes.

An Integrative Wave Model for the Marginal Ice Zone based on a Rheological Parameterization

DTIC Science & Technology

2013-09-30

climate in the present and future Arctic seas. OBJECTIVES 1. To build a comprehensive wave-ice interaction mathematical framework for a wide...group (e.g. Fox and Squire, 1994, Meylan and Squire, 1996, Bennetts and Squire, 2009) is also applicable to the case of ice floes imbedded in a frazil...environmental protection purposes: such as navigation route planning, offshore structure design in the Arctic , and coastal erosion prevention. They

Sensitivity of WRF precipitation on microphysical and boundary layer parameterizations during extreme events in Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Pytharoulis, I.; Karagiannidis, A. F.; Brikas, D.; Katsafados, P.; Papadopoulos, A.; Mavromatidis, E.; Kotsopoulos, S.; Karacostas, T. S.

2010-09-01

Contemporary atmospheric numerical models contain a large number of physical parameterization schemes in order to represent the various atmospheric processes that take place in sub-grid scales. The choice of the proper combination of such schemes is a challenging task for research and particularly for operational purposes. This choice becomes a very important decision in cases of high impact weather in which the forecast errors and the concomitant societal impacts are expected to be large. Moreover, it is well known that one of the hardest tasks for numerical models is to predict precipitation with a high degree of accuracy. The use of complex and sophisticated schemes usually requires more computational time and resources, but it does not necessarily lead to better forecasts. The aim of this study is to investigate the sensitivity of the model predicted precipitation on the microphysical and boundary layer parameterizations during extreme events. The nonhydrostatic Weather Research and Forecasting model with the Advanced Research dynamic solver (WRF-ARW Version 3.1.1) is utilized. It is a flexible, state-of-the-art numerical weather prediction system designed to operate in both research and operational mode in global and regional scales. Nine microphysical and two boundary layer schemes are combined in the sensitivity experiments. The 9 microphysical schemes are: i) Lin, ii) WRF Single Moment 5-classes, iii) Ferrier new Eta, iv) WRF Single Moment 6-classes, v) Goddard, vi) New Thompson V3.1, vii) WRF Double Moment 5-classes, viii) WRF Double Moment 6-classes, ix) Morrison. The boundary layer is parameterized using the schemes of: i) Mellor-Yamada-Janjic (MYJ) and ii) Mellor-Yamada-Nakanishi-Niino (MYNN) level 2.5. The model is integrated at very high horizontal resolution (2 km x 2 km in the area of interest) utilizing 38 vertical levels. Three cases of high impact weather in Eastern Mediterranean, associated with strong synoptic scale forcing, are employed in the numerical experiments. These events are characterized by strong precipitation with daily amounts exceeding 100 mm. For example, the case of 24 to 26 October 2009 was associated with floods in the eastern mainland of Greece. In Pieria (northern Greece), that was the most afflicted area, one individual perished in the overflowed Esonas river and significant damages were caused in both the infrastructure and cultivations. Precipitation amounts of 347 mm in 3 days were measured in the station of Vrontou, Pieria (which is at an elevation of only 120 m). The model results are statistically analysed and compared to the available surface observations and satellite derived precipitation data in order to identify the parameterizations (and their combinations) that provide the best representation of the spatiotemporal variability of precipitation in extreme conditions. Preliminary results indicate that the MYNN boundary layer parameterization outperforms the one of MYJ. However, the best results are produced by the combination of the Ferrier new Eta microphysics with the MYJ scheme, which are the default schemes of the well-known and reliable ETA and WRF-NMM models. Similarly, good results are produced by the combination of the New Thompson V3.1 microphysics with MYNN boundary layer scheme. On the other hand, the worst results (with mean absolute error up to about 150 mm/day) appear when the WRF Single Moment 5-classes scheme is used with MYJ. Finally, an effort is made to identify and analyze the main factors that are responsible for the aforementioned differences.

a Cumulus Parameterization Study with Special Attention to the Arakawa-Schubert Scheme

NASA Astrophysics Data System (ADS)

Kao, Chih-Yue Jim

Arakawa and Schubert (1974) developed a cumulus parameterization scheme in a framework that conceptually divides the mutual interaction of the cumulus convection and large-scale disturbance into the categories of large -scale budget requirements and the quasi-equilibrium assumption of cloud work function. We have applied the A-S scheme through a semi-prognostic approach to two different data sets: one is for an intense tropical cloud band event; the other is for tropical composite easterly wave disturbances. Both were observed in GATE. The cloud heating and drying effects predicted by the Arakawa-Schubert scheme are found to agree rather well with the observations. However, it is also found that the Arakawa-Schubert scheme underestimates both condensation and evaporation rates substantially when compared with the cumulus ensemble model results (Soong and Tao, 1980; Tao, 1983). An inclusion of the downdraft effects, as formulated by Johnson (1976), appears to alleviate this deficiency. In order to examine how the Arakawa-Schubert scheme works in a fully prognostic problem, a simulation of the evolution and structure of the tropical cloud band, mentioned above, under the influence of an imposed large-scale low -level forcing has been made, using a two-dimensional hydrostatic model with the inclusion of the Arakawa-Schubert scheme. Basically, the model result indicates that the meso-scale convective system is driven by the excess of the convective heating derived from the Arakawa-Schubert scheme over the adiabatic cooling due to the imposed large-scale lifting and induced meso-scale upward motion. However, as the convective system develops, the adiabatic warming due to the subsidence outside the cloud cluster gradually accumulates into a secondary temperature anomaly which subsequently reduces the original temperature contrast and inhibits the further development of the convective system. A 24 hour integration shows that the model is capable of simulating many important features such as the life cycle, intensity of circulation, and rainfall rates.

An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

NASA Technical Reports Server (NTRS)

Perrott, M. H.; Cohen, R. J.

1996-01-01

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Van Looy, Kris; Bouma, Johan; Herbst, Michael; Koestel, John; Minasny, Budiman; Mishra, Umakant; Montzka, Carsten; Nemes, Attila; Pachepsky, Yakov A.; Padarian, José; Schaap, Marcel G.; Tóth, Brigitta; Verhoef, Anne; Vanderborght, Jan; van der Ploeg, Martine J.; Weihermüller, Lutz; Zacharias, Steffen; Zhang, Yonggen; Vereecken, Harry

2017-12-01

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

2D image of local density and magnetic fluctuations from line-integrated interferometry-polarimetry measurements.

PubMed

Lin, L; Ding, W X; Brower, D L

2014-11-01

Combined polarimetry-interferometry capability permits simultaneous measurement of line-integrated density and Faraday effect with fast time response (∼1 μs) and high sensitivity. Faraday effect fluctuations with phase shift of order 0.05° associated with global tearing modes are resolved with an uncertainty ∼0.01°. For physics investigations, local density fluctuations are obtained by inverting the line-integrated interferometry data. The local magnetic and current density fluctuations are then reconstructed using a parameterized fit of the polarimetry data. Reconstructed 2D images of density and magnetic field fluctuations in a poloidal cross section exhibit significantly different spatial structure. Combined with their relative phase, the magnetic-fluctuation-induced particle transport flux and its spatial distribution are resolved.

2D image of local density and magnetic fluctuations from line-integrated interferometry-polarimetry measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, L., E-mail: lianglin@ucla.edu; Ding, W. X.; Brower, D. L.

2014-11-15

Combined polarimetry-interferometry capability permits simultaneous measurement of line-integrated density and Faraday effect with fast time response (∼1 μs) and high sensitivity. Faraday effect fluctuations with phase shift of order 0.05° associated with global tearing modes are resolved with an uncertainty ∼0.01°. For physics investigations, local density fluctuations are obtained by inverting the line-integrated interferometry data. The local magnetic and current density fluctuations are then reconstructed using a parameterized fit of the polarimetry data. Reconstructed 2D images of density and magnetic field fluctuations in a poloidal cross section exhibit significantly different spatial structure. Combined with their relative phase, the magnetic-fluctuation-induced particlemore » transport flux and its spatial distribution are resolved.« less

Subgrid-scale physical parameterization in atmospheric modeling: How can we make it consistent?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2016-07-01

Approaches to subgrid-scale physical parameterization in atmospheric modeling are reviewed by taking turbulent combustion flow research as a point of reference. Three major general approaches are considered for its consistent development: moment, distribution density function (DDF), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in geophysics and engineering. The DDF (commonly called PDF) approach is intuitively appealing as it deals with a distribution of variables in subgrid scale in a more direct manner. Mode decomposition was originally applied by Aubry et al (1988 J. Fluid Mech. 192 115-73) in the context of wall boundary-layer turbulence. It is specifically designed to represent coherencies in compact manner by a low-dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (empirical orthogonal functions) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. Among those, wavelet is a particularly attractive alternative. The mass-flux formulation that is currently adopted in the majority of atmospheric models for parameterizing convection can also be considered a special case of mode decomposition, adopting segmentally constant modes for the expansion basis. This perspective further identifies a very basic but also general geometrical constraint imposed on the massflux formulation: the segmentally-constant approximation. Mode decomposition can, furthermore, be understood by analogy with a Galerkin method in numerically modeling. This analogy suggests that the subgrid parameterization may be re-interpreted as a type of mesh-refinement in numerical modeling. A link between the subgrid parameterization and downscaling problems is also pointed out.

Parameterizing deep convection using the assumed probability density function method

DOE PAGES

Storer, R. L.; Griffin, B. M.; Höft, J.; ...

2014-06-11

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Storer, R. L.; Griffin, B. M.; Höft, J.

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Storer, R. L.; Griffin, B. M.; Hoft, Jan

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. Themore » same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Importance of Physico-Chemical Properties of Aerosols in the Formation of Arctic Ice Clouds

NASA Astrophysics Data System (ADS)

Keita, S. A.; Girard, E.

2014-12-01

Ice clouds play an important role in the Arctic weather and climate system but interactions between aerosols, clouds and radiation are poorly understood. Consequently, it is essential to fully understand their properties and especially their formation process. Extensive measurements from ground-based sites and satellite remote sensing reveal the existence of two Types of Ice Clouds (TICs) in the Arctic during the polar night and early spring. TIC-1 are composed by non-precipitating very small (radar-unseen) ice crystals whereas TIC-2 are detected by both sensors and are characterized by a low concentration of large precipitating ice crystals. It is hypothesized that TIC-2 formation is linked to the acidification of aerosols, which inhibit the ice nucleating properties of ice nuclei (IN). As a result, the IN concentration is reduced in these regions, resulting to a smaller concentration of larger ice crystals. Over the past 10 years, several parameterizations of homogeneous and heterogeneous ice nucleation have been developed to reflect the various physical and chemical properties of aerosols. These parameterizations are derived from laboratory studies on aerosols of different chemical compositions. The parameterizations are also developed according to two main approaches: stochastic (that nucleation is a probabilistic process, which is time dependent) and singular (that nucleation occurs at fixed conditions of temperature and humidity and time-independent). This research aims to better understand the formation process of TICs using a newly-developed ice nucleation parameterizations. For this purpose, we implement some parameterizations (2 approaches) into the Limited Area version of the Global Multiscale Environmental Model (GEM-LAM) and use them to simulate ice clouds observed during the Indirect and Semi-Direct Arctic Cloud (ISDAC) in Alaska. We use both approaches but special attention is focused on the new parameterizations of the singular approach. Simulation results of the TICs-2 observed on April 15th and 25th (polluted or acidic cases) and TICs-1 observed on April 5th (non-polluted cases) will be presented.

A protocol for parameterization and calibration of RZWQM2 in field research

USDA-ARS?s Scientific Manuscript database

Use of agricultural system models in field research requires a full understanding of both the model and the system it simulates. Since the 1960s, agricultural system models have increased tremendously in their complexity due to greater understanding of the processes simulated, their application to r...

Parameterization and scaling of arctic ice conditions in the context of ice-atmospheric processes

NASA Technical Reports Server (NTRS)

Barry, R. G.; Steffen, K.; Heinrichs, J. F.; Key, J. R.; Maslanik, J. A.; Serreze, M. C.; Weaver, R. L.

1995-01-01

The goals of this project are to observe how the open water/thin ice fraction in a high-concentration ice pack responds to different short-period atmospheric forcings, and how this response is represented in different scales of observation. The objectives can be summarized as follows: determine the feasibility and accuracy of ice concentration and ice typing by ERS-1 SAR backscatter data, and whether SAR data might be used to calibrate concentration estimates from optical and massive-microwave sensors; investigate methods to integrate SAR data with other satellite data for turbulent heat flux parameterization at the ocean/atmosphere interface; determine how the development and evolution of open water/thin ice areas within the interior ice pack vary under different atmospheric synoptic regimes; compare how open-water/thin ice fractions estimated from large-area divergence measurements differ from fractions determined by summing localized openings in the pack; relate these questions of scale and process to methods of observation, modeling, and averaging over time and space.

Role of a cumulus parameterization scheme in simulating atmospheric circulation and rainfall in the nine-layer Goddard Laboratory for Atmospheres General Circulation Model

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Chao, Winston C.; Walker, G. K.

1992-01-01

The influence of a cumulus convection scheme on the simulated atmospheric circulation and hydrologic cycle is investigated by means of a coarse version of the GCM. Two sets of integrations, each containing an ensemble of three summer simulations, were produced. The ensemble sets of control and experiment simulations are compared and differentially analyzed to determine the influence of a cumulus convection scheme on the simulated circulation and hydrologic cycle. The results show that cumulus parameterization has a very significant influence on the simulation circulation and precipitation. The upper-level condensation heating over the ITCZ is much smaller for the experiment simulations as compared to the control simulations; correspondingly, the Hadley and Walker cells for the control simulations are also weaker and are accompanied by a weaker Ferrel cell in the Southern Hemisphere. Overall, the difference fields show that experiment simulations (without cumulus convection) produce a cooler and less energetic atmosphere.

Polychromatic sparse image reconstruction and mass attenuation spectrum estimation via B-spline basis function expansion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Renliang, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu; Dogandžić, Aleksandar, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu

2015-03-31

We develop a sparse image reconstruction method for polychromatic computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. To obtain a parsimonious measurement model parameterization, we first rewrite the measurement equation using our mass-attenuation parameterization, which has the Laplace integral form. The unknown mass-attenuation spectrum is expanded into basis functions using a B-spline basis of order one. We develop a block coordinate-descent algorithm for constrained minimization of a penalized negative log-likelihood function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and sparsity of themore » density map image in the wavelet domain. This algorithm alternates between a Nesterov’s proximal-gradient step for estimating the density map image and an active-set step for estimating the incident spectrum parameters. Numerical simulations demonstrate the performance of the proposed scheme.« less

Shape design sensitivity analysis and optimization of three dimensional elastic solids using geometric modeling and automatic regridding. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Yao, Tse-Min; Choi, Kyung K.

1987-01-01

An automatic regridding method and a three dimensional shape design parameterization technique were constructed and integrated into a unified theory of shape design sensitivity analysis. An algorithm was developed for general shape design sensitivity analysis of three dimensional eleastic solids. Numerical implementation of this shape design sensitivity analysis method was carried out using the finite element code ANSYS. The unified theory of shape design sensitivity analysis uses the material derivative of continuum mechanics with a design velocity field that represents shape change effects over the structural design. Automatic regridding methods were developed by generating a domain velocity field with boundary displacement method. Shape design parameterization for three dimensional surface design problems was illustrated using a Bezier surface with boundary perturbations that depend linearly on the perturbation of design parameters. A linearization method of optimization, LINRM, was used to obtain optimum shapes. Three examples from different engineering disciplines were investigated to demonstrate the accuracy and versatility of this shape design sensitivity analysis method.

Image registration using stationary velocity fields parameterized by norm-minimizing Wendland kernel

NASA Astrophysics Data System (ADS)

Pai, Akshay; Sommer, Stefan; Sørensen, Lauge; Darkner, Sune; Sporring, Jon; Nielsen, Mads

2015-03-01

Interpolating kernels are crucial to solving a stationary velocity field (SVF) based image registration problem. This is because, velocity fields need to be computed in non-integer locations during integration. The regularity in the solution to the SVF registration problem is controlled by the regularization term. In a variational formulation, this term is traditionally expressed as a squared norm which is a scalar inner product of the interpolating kernels parameterizing the velocity fields. The minimization of this term using the standard spline interpolation kernels (linear or cubic) is only approximative because of the lack of a compatible norm. In this paper, we propose to replace such interpolants with a norm-minimizing interpolant - the Wendland kernel which has the same computational simplicity like B-Splines. An application on the Alzheimer's disease neuroimaging initiative showed that Wendland SVF based measures separate (Alzheimer's disease v/s normal controls) better than both B-Spline SVFs (p<0.05 in amygdala) and B-Spline freeform deformation (p<0.05 in amygdala and cortical gray matter).

Viscous Aerodynamic Shape Optimization with Installed Propulsion Effects

NASA Technical Reports Server (NTRS)

Heath, Christopher M.; Seidel, Jonathan A.; Rallabhandi, Sriram K.

2017-01-01

Aerodynamic shape optimization is demonstrated to tailor the under-track pressure signature of a conceptual low-boom supersonic aircraft. Primarily, the optimization reduces nearfield pressure waveforms induced by propulsion integration effects. For computational efficiency, gradient-based optimization is used and coupled to the discrete adjoint formulation of the Reynolds-averaged Navier Stokes equations. The engine outer nacelle, nozzle, and vertical tail fairing are axi-symmetrically parameterized, while the horizontal tail is shaped using a wing-based parameterization. Overall, 48 design variables are coupled to the geometry and used to deform the outer mold line. During the design process, an inequality drag constraint is enforced to avoid major compromise in aerodynamic performance. Linear elastic mesh morphing is used to deform volume grids between design iterations. The optimization is performed at Mach 1.6 cruise, assuming standard day altitude conditions at 51,707-ft. To reduce uncertainty, a coupled thermodynamic engine cycle model is employed that captures installed inlet performance effects on engine operation.

Investigate wave-mean flow interaction and transport in the extratropical winter stratosphere

NASA Technical Reports Server (NTRS)

Smith, Anne K.

1993-01-01

The grant supported studies using several models along with observations in order to investigate some questions of wave-mean flow interaction and transport in the extratropical winter stratosphere. A quasi-geostrophic wave model was used to investigate the possibility that resonant growth of planetary wave 2 may have played a role in the sudden stratospheric warming of February 1979. The results of the time-dependent integration support the interpretation of resonance during February, 1979. Because of the possibility that the model treatment of critical line interactions exerted a controlling influence on the atmospheric dynamics, a more accurate model was needed for wave-mean flow interaction studies. A new model was adapted from the 3-dimensional primitive equation model developed by K. Rose and G. Brasseur. In its present form the model is global, rather than hemispheric; it contains an infrared cooling algorithm and a parameterized solar heating; it has parameterized gravity wave drag; and the chemistry has been entirely revised.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Looy, Kris; Bouma, Johan; Herbst, Michael

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

DOE PAGES

Van Looy, Kris; Bouma, Johan; Herbst, Michael; ...

2017-12-28

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less

Evaluating Cloud Initialization in a Convection-permit NWP Model

NASA Astrophysics Data System (ADS)

Li, Jia; Chen, Baode

2015-04-01

In general, to avoid "double counting precipitation" problem, in convection permit NWP models, it was a common practice to turn off convective parameterization. However, if there were not any cloud information in the initial conditions, the occurrence of precipitation could be delayed due to spin-up of cloud field or microphysical variables. In this study, we utilized the complex cloud analysis package from the Advanced Regional Prediction System (ARPS) to adjust the initial states of the model on water substance, such as cloud water, cloud ice, rain water, et al., that is, to initialize the microphysical variables (i.e., hydrometers), mainly based on radar reflectivity observations. Using the Advanced Research WRF (ARW) model, numerical experiments with/without cloud initialization and convective parameterization were carried out at grey-zone resolutions (i.e. 1, 3, and 9 km). The results from the experiments without convective parameterization indicate that model ignition with radar reflectivity can significantly reduce spin-up time and accurately simulate precipitation at the initial time. In addition, it helps to improve location and intensity of predicted precipitation. With grey-zone resolutions (i.e. 1, 3, and 9 km), using the cumulus convective parameterization scheme (without radar data) cannot produce realistic precipitation at the early time. The issues related to microphysical parametrization associated with cloud initialization were also discussed.

Parameterized hardware description as object oriented hardware model implementation

NASA Astrophysics Data System (ADS)

Drabik, Pawel K.

2010-09-01

The paper introduces novel model for design, visualization and management of complex, highly adaptive hardware systems. The model settles component oriented environment for both hardware modules and software application. It is developed on parameterized hardware description research. Establishment of stable link between hardware and software, as a purpose of designed and realized work, is presented. Novel programming framework model for the environment, named Graphic-Functional-Components is presented. The purpose of the paper is to present object oriented hardware modeling with mentioned features. Possible model implementation in FPGA chips and its management by object oriented software in Java is described.

Alternatives for jet engine control

NASA Technical Reports Server (NTRS)

Sain, M. K.

1981-01-01

Research centered on basic topics in the modeling and feedback control of nonlinear dynamical systems is reported. Of special interest were the following topics: (1) the role of series descriptions, especially insofar as they relate to questions of scheduling, in the control of gas turbine engines; (2) the use of algebraic tensor theory as a technique for parameterizing such descriptions; (3) the relationship between tensor methodology and other parts of the nonlinear literature; (4) the improvement of interactive methods for parameter selection within a tensor viewpoint; and (5) study of feedback gain representation as a counterpart to these modeling and parameterization ideas.

CONNJUR Workflow Builder: A software integration environment for spectral reconstruction

PubMed Central

Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert; Martyn, Timothy O.; Ellis, Heidi J.C.; Gryk, Michael R.

2015-01-01

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses. PMID:26066803

CONNJUR Workflow Builder: a software integration environment for spectral reconstruction.

PubMed

Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert; Martyn, Timothy O; Ellis, Heidi J C; Gryk, Michael R

2015-07-01

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses.

Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism

PubMed Central

Mannan, Ahmad A.; Toya, Yoshihiro; Shimizu, Kazuyuki; McFadden, Johnjoe; Kierzek, Andrzej M.; Rocco, Andrea

2015-01-01

An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-‘omics’ steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population. PMID:26469081

Automatic human body modeling for vision-based motion capture system using B-spline parameterization of the silhouette

NASA Astrophysics Data System (ADS)

Jaume-i-Capó, Antoni; Varona, Javier; González-Hidalgo, Manuel; Mas, Ramon; Perales, Francisco J.

2012-02-01

Human motion capture has a wide variety of applications, and in vision-based motion capture systems a major issue is the human body model and its initialization. We present a computer vision algorithm for building a human body model skeleton in an automatic way. The algorithm is based on the analysis of the human shape. We decompose the body into its main parts by computing the curvature of a B-spline parameterization of the human contour. This algorithm has been applied in a context where the user is standing in front of a camera stereo pair. The process is completed after the user assumes a predefined initial posture so as to identify the main joints and construct the human model. Using this model, the initialization problem of a vision-based markerless motion capture system of the human body is solved.

A parsimonious land data assimilation system for the SMAP/GPM satellite era

USDA-ARS?s Scientific Manuscript database

Land data assimilation systems typically require complex parameterizations in order to: define required observation operators, quantify observing/forecasting errors and calibrate a land surface assimilation model. These parameters are commonly defined in an arbitrary manner and, if poorly specified,...

Validation of whitecap fraction and breaking wave parameters from WAVEWATCH-III using in situ and remote-sensing data

NASA Astrophysics Data System (ADS)

Leckler, F.; Hanafin, J. A.; Ardhuin, F.; Filipot, J.; Anguelova, M. D.; Moat, B. I.; Yelland, M.; Prytherch, J.

2012-12-01

Whitecaps are the main sink of wave energy. Although the exact processes are still unknown, it is clear that they play a significant role in momentum exchange between atmosphere and ocean, and also influence gas and aerosol exchange. Recently, modeling of whitecap properties was implemented in the spectral wave model WAVEWATCH-III ®. This modeling takes place in the context of the Oceanflux-Greenhouse Gas project, to provide a climatology of breaking waves for gas transfer studies. We present here a validation study for two different wave breaking parameterizations implemented in the spectral wave model WAVEWATCH-III ®. The model parameterizations use different approaches related to the steepness of the carrying waves to estimate breaking wave probabilities. That of Ardhuin et al. (2010) is based on the hypothesis that breaking probabilities become significant when the saturation spectrum exceeds a threshold, and includes a modification to allow for greater breaking in the mean wave direction, to agree with observations. It also includes suppression of shorter waves by longer breaking waves. In the second, (Filipot and Ardhuin, 2012) breaking probabilities are defined at different scales using wave steepness, then the breaking wave height distribution is integrated over all scales. We also propose an adaptation of the latter to make it self-consistent. The breaking probabilities parameterized by Filipot and Ardhuin (2012) are much larger for dominant waves than those from the other parameterization, and show better agreement with modeled statistics of breaking crest lengths measured during the FAIRS experiment. This stronger breaking also has an impact on the shorter waves due to the parameterization of short wave damping associated with large breakers, and results in a different distribution of the breaking crest lengths. Converted to whitecap coverage using Reul and Chapron (2003), both parameterizations agree reasonably well with commonly-used empirical fits of whitecap coverage against wind speed (Monahan and Woolf, 1989) and with the global whitecap coverage of Anguelova and Webster (2006), derived from space-borne radiometry. This is mainly due to the fact that the breaking of larger waves in the parametrization by Filipot and Ardhuin (2012) is compensated for by the intense breaking of smaller waves in that of Ardhuin et al. (2010). Comparison with in situ data collected during research ship cruises in the North and South Atlantic (SEASAW, DOGEE and WAGES), and the Norwegian Sea (HiWASE) between 2006 and 2011 also shows good agreement. However, as large scale breakers produce a thicker foam layer, modeled mean foam thickness clearly depends on the scale of the breakers. Foam thickness is thus a more interesting parameter for calibrating and validating breaking wave parameterizations, as the differences in scale can be determined. With this in mind, we present the initial results of validation using an estimation of mean foam thickness using multiple radiometric bands from satellites SMOS and AMSR-E.

Prediction of convective activity using a system of parasitic-nested numerical models

NASA Technical Reports Server (NTRS)

Perkey, D. J.

1976-01-01

A limited area, three dimensional, moist, primitive equation (PE) model is developed to test the sensitivity of quantitative precipitation forecasts to the initial relative humidity distribution. Special emphasis is placed on the squall-line region. To accomplish the desired goal, time dependent lateral boundaries and a general convective parameterization scheme suitable for mid-latitude systems were developed. The sequential plume convective parameterization scheme presented is designed to have the versatility necessary in mid-latitudes and to be applicable for short-range forecasts. The results indicate that the scheme is able to function in the frontally forced squallline region, in the gently rising altostratus region ahead of the approaching low center, and in the over-riding region ahead of the warm front. Three experiments are discussed.

Entanglement and Berry Phase in a Parameterized Three-Qubit System

NASA Astrophysics Data System (ADS)

Shao, Wenyi; Du, Yangyang; Yang, Qi; Wang, Gangcheng; Sun, Chunfang; Xue, Kang

2017-03-01

In this paper, we construct a parameterized form of unitary breve {R}_{123}(θ 1,θ 2,φ) matrix through the Yang-Baxterization method. Acting such matrix on three-qubit natural basis as a quantum gate, we can obtain a set of entangled states, which possess the same entanglement value depending on the parameters 𝜃 1 and 𝜃 2. Particularly, such entangled states can produce a set of maximally entangled bases Greenberger-Horne-Zeilinger (GHZ) states with respect to 𝜃 1 = 𝜃 2 = π/2. Choosing a useful Hamiltonian, one can study the evolution of the eigenstates and investigate the result of Berry phase. It is not difficult to find that the Berry phase for this new three-qubit system consistent with the solid angle on the Bloch sphere.

Atmospheric numerical modeling resource enhancement and model convective parameterization/scale interaction studies

NASA Technical Reports Server (NTRS)

Cushman, Paula P.

1993-01-01

Research will be undertaken in this contract in the area of Modeling Resource and Facilities Enhancement to include computer, technical and educational support to NASA investigators to facilitate model implementation, execution and analysis of output; to provide facilities linking USRA and the NASA/EADS Computer System as well as resident work stations in ESAD; and to provide a centralized location for documentation, archival and dissemination of modeling information pertaining to NASA's program. Additional research will be undertaken in the area of Numerical Model Scale Interaction/Convective Parameterization Studies to include implementation of the comparison of cloud and rain systems and convective-scale processes between the model simulations and what was observed; and to incorporate the findings of these and related research findings in at least two refereed journal articles.

Developpement de techniques numeriques pour l'estimation, la modelisation et la prediction de proprietes thermodynamiques et structurales de systems metalliques a fort ordonnancement chimique

NASA Astrophysics Data System (ADS)

Harvey, Jean-Philippe

In this work, the possibility to calculate and evaluate with a high degree of precision the Gibbs energy of complex multiphase equilibria for which chemical ordering is explicitly and simultaneously considered in the thermodynamic description of solid (short range order and long range order) and liquid (short range order) metallic phases is studied. The cluster site approximation (CSA) and the cluster variation method (CVM) are implemented in a new minimization technique of the Gibbs energy of multicomponent and multiphase systems to describe the thermodynamic behaviour of metallic solid solutions showing strong chemical ordering. The modified quasichemical model in the pair approximation (MQMPA) is also implemented in the new minimization algorithm presented in this work to describe the thermodynamic behaviour of metallic liquid solutions. The constrained minimization technique implemented in this work consists of a sequential quadratic programming technique based on an exact Newton’s method (i.e. the use of exact second derivatives in the determination of the Hessian of the objective function) combined to a line search method to identify a direction of sufficient decrease of the merit function. The implementation of a new algorithm to perform the constrained minimization of the Gibbs energy is justified by the difficulty to identify, in specific cases, the correct multiphase assemblage of a system where the thermodynamic behaviour of the equilibrium phases is described by one of the previously quoted models using the FactSage software (ex.: solid_CSA+liquid_MQMPA; solid1_CSA+solid2_CSA). After a rigorous validation of the constrained Gibbs energy minimization algorithm using several assessed binary and ternary systems found in the literature, the CVM and the CSA models used to describe the energetic behaviour of metallic solid solutions present in systems with key industrial applications such as the Cu-Zr and the Al-Zr systems are parameterized using fully consistent thermodynamic an structural data generated from a Monte Carlo (MC) simulator also implemented in the framework of this project. In this MC simulator, the modified embedded atom model in the second nearest neighbour formalism (MEAM-2NN) is used to describe the cohesive energy of each studied structure. A new Al-Zr MEAM-2NN interatomic potential needed to evaluate the cohesive energy of the condensed phases of this system is presented in this work. The thermodynamic integration (TI) method implemented in the MC simulator allows the evaluation of the absolute Gibbs energy of the considered solid or liquid structures. The original implementation of the TI method allowed us to evaluate theoretically for the first time all the thermodynamic mixing contributions (i.e., mixing enthalpy and mixing entropy contributions) of a metallic liquid (Cu-Zr and Al-Zr) and of a solid solution (face-centered cubic (FCC) Al-Zr solid solution) described by the MEAM-2NN. Thermodynamic and structural data obtained from MC and molecular dynamic simulations are then used to parameterize the CVM for the Al-Zr FCC solid solution and the MQMPA for the Al-Zr and the Cu-Zr liquid phase respectively. The extended thermodynamic study of these systems allow the introduction of a new type of configuration-dependent excess parameters in the definition of the thermodynamic function of solid solutions described by the CVM or the CSA. These parameters greatly improve the precision of these thermodynamic models based on experimental evidences found in the literature. A new parameterization approach of the MQMPA model of metallic liquid solutions is presented throughout this work. In this new approach, calculated pair fractions obtained from MC/MD simulations are taken into account as well as configuration-independent volumetric relaxation effects (regular like excess parameters) in order to parameterize precisely the Gibbs energy function of metallic melts. The generation of a complete set of fully consistent thermodynamic, physical and structural data for solid, liquid, and stoichiometric compounds and the subsequent parameterization of their respective thermodynamic model lead to the first description of the complete Al-Zr phase diagram in the range of composition [0 ≤ XZr ≤ 5 / 9] based on theoretical and fully consistent thermodynamic properties. MC and MD simulations are performed for the Al-Zr system to define for the first time the precise thermodynamic behaviour of the amorphous phase for its entire range of composition. Finally, all the thermodynamic models for the liquid phase, the FCC solid solution and the amorphous phase are used to define conditions based on thermodynamic and volumetric considerations that favor the amorphization of Al-Zr alloys.

Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.