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Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy~ precipitation processes will be discussed.

Tao, Wei-Kuo↗

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Shen, Suhung↗

FUN3D Mesh Adaptation Simulations of 4th AIAA High-Lift Prediction Workshop Case 1a

This paper describes in detail the FUN3D Mesh adaptation simulation results for Case 1a of the 4th AIAA High-Lift Prediction Workshop (HLPW-4). The Stabilized Finite Element library with FUN3D is used along with the Negative Spalart-Allmaras One-Equation Model to simulate fully turbulent free-air flow around the High Lift version of the Common Research Model at three flap settings. Meshes are adapted using multi-scale and goal-oriented metrics. The results are presented and the discussion focuses on the predicted differences between the three flap settings. Coefficients of lift, drag, and pitching moment are predicted within 7% of values measured in the QinetiQ 5m Wind Tunnel at each flap setting. Predicted surface pressures and skin friction distributions show inconsistent discrepancies with measurements across the flap settings. Consequently, flap increments for these figures of merit are not well predicted. These predictions are consistent with submissions to the HLPW-4 from other RANS-SA methods. Visualizations of Liutex vortex cores colored by angular velocity are presented as possible new quantitative and qualitative perspective for solution evaluation.

High-Lift Prediction Workshop↗

NASA Tech Briefs, April 2012

Topics include: Computational Ghost Imaging for Remote Sensing; Digital Architecture for a Trace Gas Sensor Platform; Dispersed Fringe Sensing Analysis - DFSA; Indium Tin Oxide Resistor-Based Nitric Oxide Microsensors; Gas Composition Sensing Using Carbon Nanotube Arrays; Sensor for Boundary Shear Stress in Fluid Flow; Model-Based Method for Sensor Validation; Qualification of Engineering Camera for Long-Duration Deep Space Missions; Remotely Powered Reconfigurable Receiver for Extreme Environment Sensing Platforms; Bump Bonding Using Metal-Coated Carbon Nanotubes; In Situ Mosaic Brightness Correction; Simplex GPS and InSAR Inversion Software; Virtual Machine Language 2.1; Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction; Pandora Operation and Analysis Software; Fabrication of a Cryogenic Bias Filter for Ultrasensitive Focal Plane; Processing of Nanosensors Using a Sacrificial Template Approach; High-Temperature Shape Memory Polymers; Modular Flooring System; Non-Toxic, Low-Freezing, Drop-In Replacement Heat Transfer Fluids; Materials That Enhance Efficiency and Radiation Resistance of Solar Cells; Low-Cost, Rugged High-Vacuum System; Static Gas-Charging Plug; Floating Oil-Spill Containment Device; Stemless Ball Valve; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Oxygen-Methane Thruster; Lunar Navigation Determination System - LaNDS; Launch Method for Kites in Low-Wind or No-Wind Conditions; Supercritical CO2 Cleaning System for Planetary Protection and Contamination Control Applications; Design and Performance of a Wideband Radio Telescope; Finite Element Models for Electron Beam Freeform Fabrication Process Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System; Vehicle Detection for RCTA/ANS (Autonomous Navigation System); Image Mapping and Visual Attention on the Sensory Ego-Sphere; HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis; and IMAGESEER - IMAGEs for Education and Research.

Source record↗

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.

Tao, Wei-Kuo↗

New Therapeutic Window of Regenerative Opportunity in Diabetic Retinopathy by VESGEN Analysis

Vascular pattern may serve as a useful new biomarker principle of complex, multi-scale signaling in pathological, physiological angiogenesis and microvascular remodeling. Each angiogenesis stimulator or inhibitor we have analyzed, including VEGF, bFGF, TGF-beta1, angiostatin and triamcinolone acetonide, has induced a novel "fingerprint" or "signature" biomarker vascular pattern that is spatio-temporally unique. Remodeling vasculature thereby provides an informative read-out of dominant molecular signaling, when analyzed by innovative, fractal-based VESsel GENeration (VESGEN) Analysis software. Using VESGEN to analyze ophthalmic clinical vascular images, we recently introduced a potential paradigm shift to the understanding of early-stage progression that suggests new regenerative opportunities for human diabetic retinopathy (DR), the major blinding disease for working-aged adults. In a pilot study, we discovered that angiogenesis oscillates as a surprising, homeostatic-like regeneration of retinal vessels during early progression of DR (IOVS 51(1):498). Results suggest that the term non-proliferative DR may be a misnomer. In new studies, normalization of the vasculature will be determined from the response of vascular pattern to therapeutic monitoring and treatment. We have mapped and quantified in vivo experimental models of angiogenesis, lymphangiogenesis and intravital blood flow from cellular/molecular to higher systems levels that include a murine model of infant retinopathy of prematurity (ROP); developing and pathological coronary and placental-like vessel models; progressive intestinal inflammation, growing murine tumors, and other pathological, physiological and therapeutically treated tissues of transgenic mice and avian embryos. Vascular Alterations, Visual Impairments (VIIP) & Increased Intracranial Pressure (ICP), Immunosuppression & Bone Loss: NASA-defined risk categories for human space exploration and ISS Utilization

Parsons-Wingert, Patricia A.↗

Seals Research at Texas A/M University

The Turbomachinery Laboratory at Texas A&M has been providing experimental data and computational codes for the design seals for many years. The program began with the development of a Halon based seal test rig. This facility provided information about the effective stiffness and damping in whirling seals. The Halon effectively simulated cryogenic fluids. Another test facility was developed (using air as the working fluid) where the stiffness and damping matrices can be determined. This data was used to develop bulk flow models of the seal's effect upon rotating machinery; in conjunction with this research, a bulk flow model for calculation of performance and rotordynamic coefficients of annular pressure seals of arbitrary non-uniform clearance for barotropic fluids such as LH2, LOX, LN2, and CH4 was developed. This program is very efficient (fast) and converges for very large eccentricities. Currently, work is being performed on a bulk flow analysis of the effects of the impeller-shroud interaction upon the stability of pumps. The data was used along with data from other researchers to develop an empirical leakage prediction code for MSFC. Presently, the flow field inside labyrinth and annular seals are being studied in detail. An advanced 3-D Doppler anemometer system is being used to measure the mean velocity and entire Reynolds stress tensor distribution throughout the seals. Concentric and statically eccentric seals were studied; presently, whirling seals are being studied. The data obtained are providing valuable information about the flow phenomena occurring inside the seals, as well as a data base for comparison with numerical predictions and for turbulence model development. A finite difference computer code was developed for solving the Reynolds averaged Navier Stokes equation inside labyrinth seals. A multi-scale k-epsilon turbulence model is currently being evaluated. A new seal geometry was designed and patented using a computer code. A large scale, 2-D seal flow visualization facility is also being developed.

Morrison, Gerald L.↗

Multi-Scale Fractal Analysis of Image Texture and Pattern

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Emerson, Charles W.↗

NASA Goddard Giovanni Support for YOTC

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.

Ostrenga, Dana↗

NASA Giovanni Tool for Visualization and Analysis Support for the YOTC Program

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been two folds: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. Because the goal of Overview of Year Of Tropical Convection (YOTC) involves examining a scientifically complex, multi-scale "process", rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 - April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO, and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO).

Ostrenga, Dana↗

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Putman, William M.↗

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

crop modeling↗