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Classifying Software For Reuse

Scheme for classifying software facilitates and accelerates retrieval of software components. Method aids reuse of software and increases software developers' productivity. Used to discover software components meeting specified need in large collection of useful, reliable components. Classification and retrieval methodology applies equally to things unrelated to software, such as hardware, patents, legal cases, and books. Searcher enables user to find desired software without being required to answer excessive number of questions and without presenting user with too many possible answers to any one question. Although it guides inexperienced user through system, it lets expert user forge ahead without artificial restriction.

Snyder, William V.↗

The effects of small ice crystals on the infrared radiative properties of cirrus clouds

To be successful in the development of satellite retrieval methodologies for the determination of cirrus cloud properties, we must have fundamental scattering and absorption data on nonspherical ice crystals that are found in cirrus clouds. Recent aircraft observations (Platt et al. 1989) reveal that there is a large amount of small ice particles, on the order of 10 micron, in cirrus clouds. Thus it is important to explore the potential differences in the scattering and absorption properties of ice crystals with respect to their sizes and shapes. In this study the effects of nonspherical small ice crystals on the infrared radiative properties of cirrus clouds are investigated using light scattering properties of spheroidal particles. In Section 2, using the anomalous diffraction theory for spheres and results from the exact spheroid scattering program, efficient parameterization equations are developed for calculations of the scattering and absorption properties for small ice crystals. Parameterization formulas are also developed for large ice crystals using results computed from the geometric ray-tracing technique and the Fraunhofer diffraction theory for spheroids and hexagonal crystals. This is presented in Section 3. Finally, applications to the satellite remote sensing are described in Section 4.

Takano, Y.↗

Atmospheric profiles from active space-based radio measurements

The paper describes determinations of atmospheric profiles from space-based radio measurements and the retrieval methodology used, with special attention given to the measurement procedure and the characteristics of the soundings. It is speculated that reliable profiles of the terrestrial atmosphere can be obtained by the occultation technique from the surface to a height of about 60 km. With the full complement of 21 the Global Positioning System (GPS) satellites and one GPS receiver in sun synchronous polar orbit, a maximum of 42 soundings could be obtained for each complete orbit or about 670 per day, providing almost uniform global coverage.

Hardy, Kenneth R.↗

A Modified Linear-Mixing Method for Calculating Atmospheric Path Radiances of Aerosol Mixtures

The top-of-atmosphere (TOA) path radiance generated by an aerosol mixture can be synthesized by linearly adding the contributions of the individual aerosol components, weighted by their fractional optical depths. The method, known as linear mixing, is exact in the single-scattering limit. When multiple scattering is significant, the method reproduces the atmospheric path radiance of the mixture with less than 3% errors for weakly absorbing aerosols up to optical thickness of 0.5. However, when strongly absorbing aerosols are included in the mixture, the errors are much larger. This is due to neglecting the effect of multiple interactions between the aerosol components, especially when the values of the single-scattering albedos of these components are so different that the parameter epsilon = (Sigma)f(sub i) absolute value of bar omega(sub i) - bar omega(sub mix)/bar omega(sub i), is larger than approx. 0.1, where bar omega(sub i) and f(sub i) are the single-scattering albedo and the fractional abundance of the i th component, and bar omega(sub i) is the effective single-scattering albedo of the mixture. We describe an empirical, modified linear-mixing method which effectively accounts for the multiple interactions between aerosol components. The modified and standard methods are identical when epsilon = 0.0 and give similar results when epsilon less than or equal to 0.05. For optical depths larger than approx. 0.5, or when epsilon greater than 0.05, only the modified method can reproduce the radiances within 5% error for common aerosol types up to optical thickness of 2.0. Because this method facilitates efficient and accurate atmospheric path radiance calculations for mixtures of a wide variety of aerosol types, it will be used as part of the aerosol retrieval methodology for the Earth Observing System (EOS) multiangle imaging spectroradiometer (MISR), scheduled for launch into polar orbit in 1998.

Abdou, W. A.↗

A Modified Linear-Mixing Method for Calculating Atmospheric Path Radiances of Aerosol Mixtures

The top-of-atmosphere (TOA) path radiance generated by an aerosol mixture can be synthesized by linearly adding the contributions of the individual aerosol components, weighted by their fractional optical depths. The method, known as linear mixing, is exact in the single-scattering limit. When multiple scattering is significant, the method reproduces the atmospheric path radiance of the mixture with less than 3% errors for weakly absorbing aerosols up to optical thickness of 0.5. However, when strongly absorbing aerosols are included in the mixture, the errors are much larger. This is due to neglecting the effect of multiple interactions between the aerosol components, especially when the values of the single-scattering albedos of these components are so different that the parameter e = the sum of f(sub i)[(bar)omega(sub i) - (bar)omega(sub mix)]/(bar)omega(sub i) is larger than approximately 0.1, where (bar)omega(sub i)and f(sub i) are the single-scattering albedo and the fractional abundance of the ith component, and (bar)omega(sub mix) is the effective single-scattering albedo of the Mixture. We describe an empirical, modified linear-mixing method which effectively accounts for the multiple interactions between aerosol components. The modified and standard methods are identical when epsilon = 0.0 and give similar results when epsilon is less than or equal to 0.05. For optical depths larger than approximately 0.5, or when epsilon is greater than 0.05, only the modified method can reproduce the radiances within 5% error for common aerosol types up to optical thickness of 2.0. Because this method facilitates efficient and accurate atmospheric path radiance calculations for mixtures of a wide variety of aerosol types, it will be used as part of the aerosol retrieval methodology for the Earth Observing System (EOS) multiangle imaging spectroradiometer (MISR), scheduled for launch into polar orbit in 1998.

Abdou, W. A.↗

The Atmospheric Trace Molecule Spectroscopy (ATMOS) Experiment: Deployment on the ATLAS Space Shuttle Missions

The ATMOS Fourier transform spectrometer was flown for a fourth time on the Space Shuttle as part of the ATLAS-3 instrument payload in November 1994. More than 190 sunrise and sunset occultation events provided measurements of more than 30 atmospheric trace gases at latitudes 3 - 49 deg N and 65 - 72 deg S, including observations both inside and outside the Antarctic polar vortex. The instrument configuration, data retrieval methodology, and mission background are described to place in context analyses of ATMOS data presented in this issue.

Gunson, M. R.↗

Validation of GOES-9 Satellite-Derived Cloud Properties over the Tropical Western Pacific Region

Real-time processing of hourly GOES-9 images in the ARM TWP region began operationally in October 2003 and is continuing. The ARM sites provide an excellent source for validating this new satellitederived cloud and radiation property dataset. Derived cloud amounts, heights, and broadband shortwave fluxes are compared with similar quantities derived from ground-based instrumentation. The results will provide guidance for estimating uncertainties in the GOES-9 products and to develop improvements in the retrieval methodologies and input.

Khaiyer, Mandana M.↗

Near Real-time Derived Products from MODIS

As part of the Short-term Prediction Research Transition (SPoRT) program at NASA/MSFC, near real-time total precipitable water and land/sea surface temperature products from MODIS, on NASA's Terra and Aqua satellites, are being derived from a subset of MODIS channels with spectral characteristics similar to those planned for the GOES-R ABI. Under the SPoRT program these products are made available to several NWS Forecast Offices to assist in the preparation of short-term forecasts. This transition activity, from research to operations, serves to prepare forecasters for the next generation of satellite observing capabilities through real-time, hands-on applications to their forecast problems. The derived products are produced from a physical retrieval algorithm which can be applied to polar or geostationary measurements. The algorithm is a perturbation solution of the radiation transfer equation for a nonscattering atmosphere requiring first-guess temperature and moisture profiles. For this application first-guess information is obtained from the latest model forecasts. The utility of this retrieval approach is that it provides a near real-time high resolution update of a model's forecasted parameter allowing forecasters to validate and monitor the performance of the model's forecast. The poster will provide a description of the retrieval methodology and examples of the derived products. Case studies will also be presented comparing these products with those obtained from the Earth Observing System (EOS) MODIS science team algorithms.

Suggs, Ron↗

The Geostationary Operational Environmental Satellite (GOES) Product Generation System

The Geostationary Operational Environmental Satellite (GOES) Product Generation System (GPGS) is introduced and described. GPGS is a set of computer programs developed and maintained at the Global Hydrology and Climate Center and is designed to generate meteorological data products using visible and infrared measurements from the GOES-East Imager and Sounder instruments. The products that are produced by GPGS are skin temperature, total precipitable water, cloud top pressure, cloud albedo, surface albedo, and surface insolation. A robust cloud mask is also generated. The retrieval methodology for each product is described to include algorithm descriptions and required inputs and outputs for the programs. Validation is supplied where applicable.

Haines, S. L.↗

Using Multi-Angle Imaging SpectroRadiometer (MISR) bidirectional reflectances for land surface studies

MISR imagery enables new methods for cloud screening and retrieval of aerosol properties over a wide range of surface types, and these data are used to compensate for atmospheric effects in the surface retrievals. The derived surface angular signatures are governed, at least in part, by macroscopic texture at the subpixel scale. Such information complements spectral data in distinguishing different types of surface cover, retrieving land surface hemispherical reflectance,and determining biogeophysical properties such as leaf area index and fractional absorbed photosynthetically active radiation. Regional and global MISR data products will be presented to illustrate the capabilities of the instrument andassociated retrieval methodologies.

MISR bidirectional surface studies spectr↗

Biases in Total Precipitable Water Vapor Climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer

We examine differences in total precipitable water vapor (PWV) from the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Scanning Radiometer (AMSR-E) experiments sharing the Aqua spacecraft platform. Both systems provide estimates of PWV over water surfaces. We compare AIRS and AMSR-E PWV to constrain AIRS retrieval uncertainties as functions of AIRS retrieved infrared cloud fraction. PWV differences between the two instruments vary only weakly with infrared cloud fraction up to about 70%. Maps of AIRS-AMSR-E PWV differences vary with location and season. Observational biases, when both instruments observe identical scenes, are generally less than 5%. Exceptions are in cold air outbreaks where AIRS is biased moist by 10-20% or 10-60% (depending on retrieval processing) and at high latitudes in winter where AIRS is dry by 5-10%. Sampling biases, from different sampling characteristics of AIRS and AMSR-E, vary in sign and magnitude. AIRS sampling is dry by up to 30% in most high-latitude regions but moist by 5-15% in subtropical stratus cloud belts. Over the northwest Pacific, AIRS samples conditions more moist than AMSR-E by a much as 60%. We hypothesize that both wet and dry sampling biases are due to the effects of clouds on the AIRS retrieval methodology. The sign and magnitude of these biases depend upon the types of cloud present and on the relationship between clouds and PWV. These results for PWV imply that climatologies of height-resolved water vapor from AIRS must take into consideration local meteorological processes affecting AIRS sampling.

Atmospheric Infrared Sounder (AIRS)↗

NASA's Advancements in Space-Based Spectrometry Lead to Improvements in Weather Prediction and Understanding of Climate Processes

AIRS is a precision state of the art High Spectral Resolution Multi-detector IR grating array spectrometer that was launched into a polar orbit on EOS Aqua in 2002. AIRS measures most of the infra-red spectrum with very low noise from 650/cm to 2660/cm with a resolving power of 2400 at a spatial resolution of 13 km. The objectives of AIRS were to perform accurate determination of atmospheric temperature and moisture profiles in up to 90% partial cloud cover conditions for the purpose of improving numerical weather prediction and understanding climate processes. AIRS data has also been used to determine accurate trace gas profiles. A brief overview of the retrieval methodology used to analyze AIRS observations under partial cloud cover will be presented and sample results will be shown from the weather and climate perspectives.

Susskind, Joel↗

Lessons Learned from AIRS: Improved Determination of Surface and Atmospheric Temperatures Using Only Shortwave AIRS Channels

This slide presentation reviews the use of shortwave channels available to the Atmospheric Infrared Sounder (AIRS) to improve the determination of surface and atmospheric temperatures. The AIRS instrument is compared with the Infrared Atmospheric Sounding Interferometer (IASI) on-board the MetOp-A satellite. The objectives of the AIRS/AMSU were to (1) provide real time observations to improve numerical weather prediction via data assimilation, (2) Provide observations to measure and explain interannual variability and trends and (3) Use of AIRS product error estimates allows for QC optimized for each application. Successive versions in the AIRS retrieval methodology have shown significant improvement.

Susskind, Joel↗

SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation

Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.

Bindlish, Rajat↗

Hyperspectral Microwave Atmospheric Sounder (HyMAS) Architecture and Design Accommodations

The Hyperspectral Microwave Atmospheric Sounder (HyMAS) is being developed at Lincoln Laboratories and accommodated by the Goddard Space Flight Center for a flight opportunity on a NASA research aircraft. The term "hyperspectral microwave" is used to indicate an all-weather sounding that performs equivalent to hyperspectral infrared sounders in clear air with vertical resolution of approximately 1 km. Deploying the HyMAS equipped scanhead with the existing Conical Scanning Microwave Imaging Radiometer (CoSMIR) shortens the path to a flight demonstration. Hyperspectral microwave is achieved through the use of independent RF antennas that sample the volume of the Earth s atmosphere through various levels of frequencies, thereby producing a set of dense, spaced vertical weighting functions. The simulations proposed for HyMAS 118/183-GHz system should yield surface precipitation rate and water path retrievals for small hail, soft hail, or snow pellets, snow, rainwater, etc. with accuracies comparable to those of the Advanced Technology Microwave Sounder. Further improvements in retrieval methodology (for example, polarization exploitation) are expected. The CoSMIR instrument is a packaging concept re-used on HyMAS to ease the integration features of the scanhead. The HyMAS scanhead will include an ultra-compact Intermediate Frequency Processor (IFP) module that is mounted inside the door to improve thermal management. The IFP is fabricated with materials made of Low-Temperature Co-fired Ceramic (LTCC) technology integrated with detectors, amplifiers, A/D conversion and data aggregation. The IFP will put out 52 channels of 16 bit data comprised of 4-9 channel data streams for temperature profiles and 2-8 channel streams for water vapor. With the limited volume of the existing CoSMIR scanhead and new HyMAS front end components, the HyMAS team at Goddard began preliminary layout work inside the new drum. Importing and re-using models of the shell, the scan head computer, and the slip rings developed for CoSMIR was the starting point. The next step was to modify the antenna faceplate to accommodate the dimensions of the three dual polarization Gaussian Optics Antenna (GOA) assemblies. Two mechanical concepts for the core technology, the hyperspectral IFP, were captured in a design tradeoff. Connector models considered minimum bend radii for the IFP analog connectors. Hyperspectral imaging is accomplished by strategically using a short wavelength intermediate frequency of 18-29 GHz, and thus reducing the size of components in the connection of the front end to the IFP. The SMK (2.92mm) Series connector will lay near the hinge line to minimize its flexing. The digital output of the IFP will use a Serial Peripheral Interface (SPI) that must be accommodated by the scan head computer. To make that computer more reliable, maintainable, and forward compatible with the 52 HyMAS channels, a testbed of the scan head, calibration, and archive computers and the PIC24 microprocessor that resides on the IFP is in development. The computers will be programmed using a new framework application called Interoperable Remote Component (IRC). This software allows flexibility to program computers that communicate with each other and can adapt easily to the emerging HyMAS requirements for data format, algorithms, and graphical user interface (GUI). It is expected that the CoSMIR instrument will cut over to the IRC after it is adapted on an updated CoSMIR testbed.

Hilliard, Lawrence↗

Deriving a Suite of Climate Data Records from 21-years of Sounder Observations

Two retrieval algorithms, a Single Field-of-view Sounder Atmospheric Product (SiFSAP) Level 2 algorithm and a Climate Fingerprinting Sounder Product (ClimFiSP) Level 3 algorithm, have been developed at NASA Langley Research Center. In this presentation, we will demonstrate the radiance closure build into these two algorithms. This is possible due to the use of a principal-component-based radiative transfer model (PCRTM). The PCRTM enables the inclusion of all available spectral information from hyperspectral IR sounders. It also has fast and accurate capability of modeling observed cloudy radiance spectra directly. The SiFSAP, which fits sounder radiance spectra using PCRTM as forward model and an optimal estimation as inverse model, has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. With great support from NASA sounder SIPS, the SiFSAP algorithm has been delivered to NASA GES DISC for L2 and L3 data generation and releasing. The ClimFiSP uses a spectral fingerprinting method to directly generate L3 data products from spatiotemporally averaged L1 data. The goal of ClimFiSP is to generate high-quality climate data records (CDRs) from multiple IR sounders (e.g. Aqua AIRS, SNPP CrIS, NOAA-20 and NOAA-21 CrIS) using a consistent retrieval methodology. Using CHIRP L1 data, we have generated 20-years of CDRs for atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties. The algorithm will be transitioned to Sounder SIPS soon and eventually to NASA GES DISC.

Xu Liu↗

Evolutionary Computing Methods for Spectral Retrieval

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

Terrile, Richard↗

Analysis of CrIs/ATMS Using AIRS Version-7 Retrieval and QC Methodology

The objective of this research is to develop and implement an algorithm to analyze a long term data record of CrIS/ATMS observations so as to produce monthly mean gridded Level-3 products which are consistent with, and will serve as a seamless follow on to, those of AIRS Version-7. We feel the best way to achieve this result is to analyze CrIS/ATMS data using retrieval and Quality Control (QC) methodologies which are scientifically equivalent to those used in AIRS Version-7. We developed and implemented a single retrieval program that uses as input either AIRS/AMSU or CrIS/ATMS radiance observations, and has appropriate switches that take into account the spectral and radiometric differences between CrIS and AIRS. Our methodology is call CHART (Climate Heritage AIRS Retrieval Technique).

Susskind, Joel↗