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This is the final submittal of the Earth Observing System/Advanced Microwave Sounding Unit-A Firmware Version Description Document. Its purpose is to provide a precise description of the particular version of the firmware being released. This description also defines the version of the requirements and design applicable to this version.
This paper presents the results of conceptual level thermal analyses of a High Speed Civil Transport (HSCT) wing using p-version finite elements. The work was motivated by a thermal analysis of a HSCT wing structure which showed the importance of radiation heat transfer throughout the structure. The analysis also showed that refining a traditional finite element mesh to accurately capture the temperature distribution on the internal structure led to very large meshes with unacceptably long execution times. Further study indicated using p-version finite elements might improve computation performance for this class of problem. Methods for determining internal radiation heat transfer were then developed and demonstrated on test problems representative of the geometry found in an aircraft wing structure. This paper presents the results of the application of these new methods to the analysis of a high speed aircraft wing. Results for both a wing box model as well as a full wing model are presented. 'Me reduced wing box model allows for a comparison of the traditional finite element method with mesh refinement (h-refinement) to the new p-version finite elements while the full wing model demonstrates the applicability and efficiency of p-version finite elements for large models.
A research project is underway at NASA Glenn to produce a computer code which can accurately predict ice growth under a wide range of meteorological conditions for any aircraft surface. This report will present a description of the code inputs and outputs from version 2.2.2 of this code, which is called LEWICE. This version differs from release 2.0 due to the addition of advanced thermal analysis capabilities for de-icing and anti-icing applications using electrothermal heaters or bleed air applications. An extensive effort was also undertaken to compare the results against the database of electrothermal results which have been generated in the NASA Glenn Icing Research Tunnel (IRT) as was performed for the validation effort for version 2.0. This report will primarily describe the features of the software related to the use of the program. Appendix A of this report has been included to list some of the inner workings of the software or the physical models used. This information is also available in the form of several unpublished documents internal to NASA. This report is intended as a replacement for all previous user manuals of LEWICE. In addition to describing the changes and improvements made for this version, information from previous manuals may be duplicated so that the user will not need to consult previous manuals to use this code.
This document contains the course notes on the computational fluid dynamics code CFL3D version 6.4. It is intended to provide from basic to advanced users the information necessary to successfully use the code for a broad range of cases. Much of the course covers capability that has been a part of previous versions of the code, with material compiled from a CFL3D v5.0 manual and from the CFL3D v6 web site prior to the current release. This part of the material is presented to users of the code not familiar with computational fluid dynamics. There is new capability in CFL3D version 6.4 presented here that has not previously been published. There are also outdated features no longer used or recommended in recent releases of the code. The information offered here supersedes earlier manuals and updates outdated usage. Where current usage supersedes older versions, notation of that is made. These course notes also provides hints for usage, code installation and examples not found elsewhere.
The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 pm C02 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 pm C02 observations are now used primarily in the generation of cloud cleared radiances Ri. This approach allows for the generation of accurate values of Ri and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by- channel error estimates for Ri. These error estimates are used for quality control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of quality control using the NASA GEOS-5 data assimilation system. Assimilation of quality controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done Operationally by ECMWF and NCEP. Forecasts resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.
The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing and reprocessing of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains a number of significant improvements over Version 4. Two very significant improvements are described briefly below. 1) The AIRS Science Team Radiative Transfer Algorithm (RTA) has now been upgraded to accurately account for effects of non-local thermodynamic equilibrium on the AIRS observations. This allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval algorithm during both day and night. Following theoretical considerations, the,AIRS Version 5 temperature profile retrieval step uses only 15 micron CO2 radiances for those channels sensitive to atmospheric emission in the stratosphere. Tropospheric temperature profile information is obtained almost exclusively from clear column radiances in the 4.3 micron CO2 band. These clear column radiances are a derived product that are indicative of radiances AIRS channels would have seen if the field of view were completely clear. Tropospheric sounding 15 micron CO2 observations are used heavily in the determination of the parameters necessary to generate for all sounding channels. This approach allows for the generation of accurate values of and T(p) under most cloud conditions.
A research project is underway at NASA Glenn to produce a computer code which can accurately predict ice growth under a wide range of meteorological conditions for any aircraft surface. This report will present a description of the code inputs and outputs from version 3.2 of this software, which is called LEWICE. This version differs from release 2.0 due to the addition of advanced thermal analysis capabilities for de-icing and anti-icing applications using electrothermal heaters or bleed air applications, the addition of automated Navier-Stokes analysis, an empirical model for supercooled large droplets (SLD) and a pneumatic boot option. An extensive effort was also undertaken to compare the results against the database of electrothermal results which have been generated in the NASA Glenn Icing Research Tunnel (IRT) as was performed for the validation effort for version 2.0. This report will primarily describe the features of the software related to the use of the program. Appendix A has been included to list some of the inner workings of the software or the physical models used. This information is also available in the form of several unpublished documents internal to NASA. This report is intended as a replacement for all previous user manuals of LEWICE. In addition to describing the changes and improvements made for this version, information from previous manuals may be duplicated so that the user will not need to consult previous manuals to use this software.
Version 3.31 of Modeling and Analysis for Controlled Optical Systems (MACOS) has been released. MACOS is an easy-to-use computer program for modeling and analyzing the behaviors of a variety of optical systems, including systems that have large, segmented apertures and are aligned with the technology of wavefront sensing and control. Two previous versions were described in "Improved Software for Modeling Controlled Optical Systems" (NPO-19841) NASA Tech Briefs, Vol. 21, No. 12 (December 1997), page 42 and "Optics Program Modified for Multithreaded Parallel Computing" (NPO-40572) NASA Tech Briefs, Vol. 30, No. 1 (January 2006) page 13a. The present version incorporates the following enhancements over prior versions: a) A powerful system-optimization facility includes algorithms for linear, nonlinear, unconstrained, and constrained optimization of optical systems under a variety of settings. b) There is now enhanced capability to perturb optical components individually and on subsystem levels, and to optimize system performance by adjusting selected individual components as well as subsystems. c) Capabilities for modeling a variety of new optical aperture types have been added. d) Effects of multilayer thin-film coats on optical surfaces can now be taken into account when tracing polarized rays. e) Major software-engineering work was performed to make MACOS more reliable, flexible, and manageable for purposes of maintenance and further development.
The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of cloud cleared radiances R(sub i). This approach allows for the generation of accurate values of R(sub i) and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel error estimates for R(sub i). These error estimates are used for Quality Control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of Quality Control using the NASA GEOS-5 data assimilation system. Assimilation of Quality Controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done operationally by ECMWF and NCEP. Forecast resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.
We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.
The GPCP has developed Version 2.1 of its long-term (1979-present) global Satellite-Gauge (SG) data sets to take advantage of the improved GPCC gauge analysis, which is one key input. As well, the OPI estimates used in the pre-SSM/I era have been rescaled to 20 years of the SSM/I-era SG. The monthly, pentad, and daily GPCP products have been entirely reprocessed, continuing to enforce consistency of the submonthly estimates to the monthly. Version 2.1 is close to Version 2, with the global ocean, land, and total values about 0%, 6%, and 2% higher, respectively. The revised long-term global precipitation rate is 2.68 mm/d. The corresponding tropical (25 N-S) increases are 0%, 7%, and 3%. Long-term linear changes in the data tend to be smaller in Version 2.1, but the statistics are sensitive to the threshold for land/ocean separation and use of the pre-SSM/I part of the record.
The final version (3.0) of the Montage software has been released. To recapitulate from previous NASA Tech Briefs articles about Montage: This software generates custom, science-grade mosaics of astronomical images on demand from input files that comply with the Flexible Image Transport System (FITS) standard and contain image data registered on projections that comply with the World Coordinate System (WCS) standards. This software can be executed on single-processor computers, multi-processor computers, and such networks of geographically dispersed computers as the National Science Foundation s TeraGrid or NASA s Information Power Grid. The primary advantage of running Montage in a grid environment is that computations can be done on a remote supercomputer for efficiency. Multiple computers at different sites can be used for different parts of a computation a significant advantage in cases of computations for large mosaics that demand more processor time than is available at any one site. Version 3.0 incorporates several improvements over prior versions. The most significant improvement is that this version is accessible to scientists located anywhere, through operational Web services that provide access to data from several large astronomical surveys and construct mosaics on either local workstations or remote computational grids as needed.
Version 4.0 of the Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC) has been developed as an improved means of computational simulation of advanced composite materials. The previous version of MAC/GMC was described in "Comprehensive Micromechanics-Analysis Code" (LEW-16870), NASA Tech Briefs, Vol. 24, No. 6 (June 2000), page 38. To recapitulate: MAC/GMC is a computer program that predicts the elastic and inelastic thermomechanical responses of continuous and discontinuous composite materials with arbitrary internal microstructures and reinforcement shapes. The predictive capability of MAC/GMC rests on a model known as the generalized method of cells (GMC) - a continuum-based model of micromechanics that provides closed-form expressions for the macroscopic response of a composite material in terms of the properties, sizes, shapes, and responses of the individual constituents or phases that make up the material. Enhancements in version 4.0 include a capability for modeling thermomechanically and electromagnetically coupled ("smart") materials; a more-accurate (high-fidelity) version of the GMC; a capability to simulate discontinuous plies within a laminate; additional constitutive models of materials; expanded yield-surface-analysis capabilities; and expanded failure-analysis and life-prediction capabilities on both the microscopic and macroscopic scales.
Advanced Life Support Sizing Analysis Tool (ALSSAT) at the time of this reporting has been updated to version 6.0. A previous version was described in Tool for Sizing Analysis of the Advanced Life Support System (MSC- 23506), NASA Tech Briefs, Vol. 29, No. 12 (December 2005), page 43. To recapitulate: ALSSAT is a computer program for sizing and analyzing designs of environmental-control and life-support systems for spacecraft and surface habitats to be involved in exploration of Mars and the Moon. Of particular interest for analysis by ALSSAT are conceptual designs of advanced life-support (ALS) subsystems that utilize physicochemical and biological processes to recycle air and water and process human wastes to reduce the need of resource resupply. ALSSAT is a means of investigating combinations of such subsystems technologies featuring various alternative conceptual designs and thereby assisting in determining which combination is most cost-effective. ALSSAT version 6.0 has been improved over previous versions in several respects, including the following additions: an interface for reading sizing data from an ALS database, computational models of a redundant regenerative CO2 and Moisture Removal Amine Swing Beds (CAMRAS) for CO2 removal, upgrade of the Temperature & Humidity Control's Common Cabin Air Assembly to a detailed sizing model, and upgrade of the Food-management subsystem.
The TRMM data system has been providing near-realtime data products to the community since late 1999. While the TRMM project never had near-realtime production requirements, the science and applications communities had a great interest in receiving TRMM data as quickly as possible. As a result these NRT data are provided under a best-effort scenario but with the objective of having the swath data products available within three hours of data collection 90% of the time. In July of 2011 the Joint Precipitation Measurement Missions Science Team (JPST) authorized the reprocessing of TRMM mission data using the new version 7 algorithms. The reprocessing of the 14+ years of the mission was concluded within 30 days. Version 7 algorithms had substantial changes in the data product file formats both for data and metadata. In addition, the algorithms themselves had major modifications and improvements. The general approach to versioning up the NRT is to wait for the regular production algorithms to have run for a while and shake out any issues that might arise from the new version before updating the NRT products. Because of the substantial changes in data/metadata formats as well as the algorithm improvements themselves, the update of NRT to V7 followed an even more conservative path than usual. This was done to ensure that applications agencies and other users of the TRMM NRT would not be faces with short-timeframes for conversion to the new format. This paper will describe the process by which the TRMM NRT was updated to V7 and the V7 data products themselves.
The Spaceport Command and Control System (SCCS) at Kennedy Space Center (KSC) is a control system for monitoring and launching manned launch vehicles. Simulations of ground support equipment (GSE) and the launch vehicle systems are required throughout the life cycle of SCCS to test software, hardware, and procedures to train the launch team. The simulations of the GSE at the launch site in conjunction with off-line processing locations are developed using Simulink, a piece of Commercial Off-The-Shelf (COTS) software. The simulations that are built are then converted into code and ran in a simulation engine called Trick, a Government off-the-shelf (GOTS) piece of software developed by NASA. In the world of hardware and software, it is not uncommon to see the products that are utilized be upgraded and patched or eventually fade away into an obsolete status. In the case of SCCS simulation software, Matlab, a MathWorks product, has released a number of stable versions of Simulink since the deployment of the software on the Development Work Stations in the Linux environment (DWLs). The upgraded versions of Simulink has introduced a number of new tools and resources that, if utilized fully and correctly, will save time and resources during the overall development of the GSE simulation and its correlating documentation. Unfortunately, simply importing the already built simulations into the new Matlab environment will not suffice as it will produce results that may not be expected as they were in the version that is currently being utilized. Thus, an upgrade execution plan was developed and executed to fully upgrade the simulation environment to one of the latest versions of Matlab.
The purpose of this handbook is to describe recommended methods for a trans-disciplinary, systems-based approach for regional-scale (local to national scale) integrated assessment of agricultural systems under future climate, bio-physical and socio-economic conditions. An earlier version of this Handbook was developed and used by several AgMIP Regional Research Teams (RRTs) in Sub-Saharan Africa (SSA) and South Asia (SA)(AgMIP handbook version 4.2, www.agmip.org/regional-integrated-assessments-handbook/). In contrast to the earlier version, which was written specifically to guide a consistent set of integrated assessments across SSA and SA, this version is intended to be more generic such that the methods can be applied to any region globally. These assessments are the regional manifestation of research activities described by AgMIP in its online protocols document (available at www.agmip.org). AgMIP Protocols were created to guide climate, crop modeling, economics, and information technology components of its projects.
We use surface fine particulate matter (PM2.5) measurements collected by the United States Environmental Protection Agency (US EPA) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks as independent validation for Version 1 of the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero) developed by the Global Modeling Assimilation Office (GMAO). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua satellites. By combining the spatial and temporal coverage of GEOS-5 with observational constraints on AOD, MERRAero has the potential to provide improved estimates of PM2.5 compared to the model alone and with greater coverage than available observations.Importantly, assimilation of AOD data constrains the total column aerosol mass in MERRAero subject to assumptions about optical properties for each of the species represented in GOGART. However, single visible wavelength AOD data does not contain sufficient information content to correct errors in either aerosol vertical placement or composition, critical elements for a proper characterization of surface PM2.5. Despite this, we find that the data-assimilation equipped version of GEOS-5 better represents observed PM2.5 between 2003 and 2012 compared to the same version of the model without AOD assimilation. Compared to measurements from the EPA-AQS network, MERRAero shows better PM2.5 agreement with the IMPROVE network measurements, which are composed essentially of rural stations. Regardless the data network, MERRAero PM2.5 are closer to observation values during the summer while larger discrepancies are observed during the winter. Comparing MERRAero to PM2.5 data collected by the Chemical Speciation Network (CSN) offers greater insight on the species MERRAero predicts well and those for which there are biases relative to the EPA observations. Analysis of this speciated data indicates that the lack of nitrate emissions in MERRAero and an underestimation of carbonaceous emissions in the Western US explains much of the reanalysis bias during the winter. To further understand discrepancies between the reanalysis and observations, we use complimentary data to assess two important aspects of MERRAero that are of relevance to the diagnosis of PM2.5, in particular AOD and vertical structure