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conference on atmospheric and environmental remote sensing data processing and utilization IV - Readiness for GEOSS II

作者： Amerault, Clark Doyle, James USN Res Lab Marine Meteorol Div Monterey CA 93943 USA

ISBN: (纸本)9780819473059

An adjoint limited area numerical weather prediction model with multiple nests has been developed. The adjoint modeling system has the capability to pass gradient information from the finer spaced nest to the coarser spaced domain. Therefore, gradients of scalar functions calculated from small scale features can be computed with respect to the large scale model state. Sensitivity experiments were performed to show that the nested adjoint model produces physically meaningful gradients. Results from data assimilation experiments will be presented at the conference. An ad joint model such as the one presented here, could be in important tool for variational assimilation schemes that intend to make use of high resolution remotely sensed data.

关键词： adjoint data assimilation mesoscale

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Application of a testbed for validating remote sensor data and retrieval algorithms

Application of a testbed for validating remote sensor data a...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Lipton, A Moncet, JL Galantowicz, J Hu, HJ Lynch, R Boukabara, SA Hogan, DB d'Entremont, R He, YG Atmospher & Environm Res Inc 131 Hartwell Ave Lexington MA 02421 USA

ISBN: (纸本)0819454869

The AER algorithm testbed has been applied to instruments measuring in spectra from the ultraviolet to the microwave. The sensor simulation component starts with environmental data from numerical weather prediction models, surface property and terrain databases, and imagers, and simulates the detailed sensor spatial and spectral sampling processes, radiative transfer, polarization, and detector characteristics. This simulation is integrated with algorithm execution, to provide end-to-end capability. The tools allow for simulation of specific sensor errors, and tracing of their impact through the algorithm process to the quality of the retrieved environmental products. A critical component of the testbed is its radiative transfer models, which employ state-of-the-science programs for line-by-line optical properties, for radiative transfer in scattering atmospheres, and for a variety of surfaces. Fast and accurate computational methods are incorporated, such as Optimal Spectral Sampling (OSS). Application examples are shown, including characterization of AMSU sensor data errors and retrieval performance evaluation, in which retrievals from the microwave sounder data and infrared image data contribute to the interpretation of remote sensing phenomena in cloudy environments.

关键词： sensor simulation remote sensing radiative transfer satellite

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Compression of AIRS data using empirical mode decomposition

Compression of AIRS data using empirical mode decomposition

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Gladkova, I Roytman, L Goldberg, M Weber, J CUNY City Coll NOAA CREST New York NY 10031 USA

ISBN: (纸本)0819454869

In this paper, we consider an application of the Empirical Mode Decomposition (EMD) introduced by Norden E. Huang in 1996 to the compression of 3D hyperspectral sounding data. The EMD is a new data analysis method which is based on expansion of the data in terms of Intrinsic Mode Functions (IMF). These IMFs are based on and derived from the data set. Since EMD adaptively represent the signal as a sum of "well behaved" amplitude/frequency modulated components, we found it very well suited for the whitening part of the compression scheme.

关键词： compression empirical mode decomposition intrinsic mode functions Karhunen-Loeve

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Satellite ocean remote sensing at NOAA/NESDIS

Satellite ocean remote sensing at NOAA/NESDIS

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Bayler, EJ NOAA NESDIS Ctr Satellite Applicat & Res Camp Springs MD 20746 USA

ISBN: (纸本)0819454869

Satellite oceanography within the Center for Satellite Applications and Research (STAR) in National Oceanic and atmospheric Administrationis (NOAA) National environmental Satellite, data, and Information Service (NESDIS) focuses on observation retrievals and applications to address the NOAA missions of environmental assessment, prediction, and stewardship. Satellite oceanography within NOAA/NESDIS is an end-to-end process, addressing user requirements, sensor design support, observation retrieval research and development, calibration, applications and product research and development, the transition of research to operations, continuing product validation, and operational user support. The breadth of scientific investigation encompasses three functional areas: satellite ocean sensors, ocean dynamics/data assimilation, and marine ecosystems/climate. A cross-cutting science team from these functional areas has been established for each core subject: sea-surface temperature, sea-surface height, sea-surface roughness, ocean color, ocean surface winds, and sea ice. These science teams pursue the science and issues end to end within the core subject, with the primary objective being the transition of research to operations. data fusion opportunities between science teams are also pursued. Each science team area addresses the common themes of calibration/validation, data assimilation, climate, and operational oceanography. Experimental and operational products, as well as user support, are provided to the user community via the NOAA OceanWatch/CoastWatch program.

关键词： Satellites Oceanography remote sensing Climatology data modeling Algorithm development environmental sensing Sensors Calibration Ocean optics

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Operational applications of remote sensing in hydrology: success, prospects and problems

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HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES 1998年第6期43卷 947-968页

作者： Rango, A Shalaby, AI USDA ARS Hydrol Lab Beltsville MD 20705 USA

The use of remote sensing information in operational hydrology is relatively limited, but specific examples can be cited for determining precipitation, soil moisture, groundwater, snow, surface water and basin characteristics. The application of remote sensing in hydrology can be termed operational if at least one of two conditions are met: (a) the application produces an output on a regular basis, or (b) the remote sensing data are used regularly on a continuing basis as part of a procedure to solve a problem or make decisions. When surveying the various operational applications, simple approaches and simple remote sensing data sets are the most successful. In the data-sparse developing countries, many operational remote sensing approaches exist (out of necessity) that may not be needed in developed countries because of existing data networks. To increase the use of remote sensing in operational hydrology in developed countries, pilot projects need to be increased and information services must be improved. Increased utilization of GIS to combine remote sensing with other information will promote new products and applications. End user training must be improved by focusing on satellite data processing and manipulation. In developing countries the same improvements are needed plus some more basic ones. There is a need for international monetary assistance to establish long-term remote sensing data, improved database systems and image processing capabilities. There is also the need to set up innovative regional training centres throughout the developing world.

关键词： .satellite data Basin Characteristics PILOT PROJECTS developed countries remote sensing data Operational Hydrology Operational Applications use of remote Application of remote hydrology success prospects sensing information operational remote sensing sensing in operational

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Testbed architecture for rapid prototyping and assessment of environmental remote sensing algorithms

Testbed architecture for rapid prototyping and assessment of...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Zaccheo, TS Galantowicz, J Hogan, DB Kennelly, EJ Snell, HE Atmospher & Environm Res Inst Lexington MA 02421 USA

ISBN: (纸本)0819454869

The Interactive Algorithm Tool Box (IATB) is a multi-layered architecture designed to aid in the rapid implementation and end-to-end assessment of algorithms for estimating environmental parameters from remote sensing data. This architectural scheme employs a layered approach. The primary layer provides common methods for accessing sensor, ancillary and auxiliary data as well as user configurable parameters. The second layer provides a standard set of tools that can be used in the development of the target remote sensing algorithm and its supporting simulation tools. One of the primary tools provides a self-consistent mechanism for performing radiative transfer calculations over a broad spectral range from the Microwave to the Infrared/Visible. This toolbox also provides standard mechanisms for building first-order sensor models. The final layer provides a platform independent "wrapper" for integrating the target algorithm and its simulation tools with a set of standard and custom analysis tools. This layer provides an end-to-end product that can be used for extended analysis and calibration/validation with either simulated or "real" data. The testbed architecture has been applied to instruments measuring in spectra from the visible to the microwave. It has been employed during the development of algorithms for existing remote sensing systems (e.g. AMSU and AIRS) as well as sensor suites that will be flown on next generation satellites (e.g. NPOESS and GOES). This paper describes the IATB architecture and presents the implementation for several applications.

关键词： remote sensing retrieval algorithm sensor simulation satellite

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Ground truth-based variability analysis of atmospheric inversion in the presence of clouds

Ground truth-based variability analysis of atmospheric inver...

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conference on atmospheric and environmental remote sensing data processing and utilization II

作者： Klempner, Scott L. Bartlett, Brent Schott, John R. Rochester Inst Technol Rochester NY 14623 USA

ISBN: (纸本)0819463809

A data collection experiment was held on 10 May 2006 in which various types of ground truth were collected. During analysis of the data, it became apparent that a good deal of temporal and spatial variability existed both between the two collection sites and between each of the flight lines. The variability was primarily manifested in the total sky radiance spectra collected during each flight line. These effects were believed to be due to a rapidly changing sky environment populated by sparse clouds that grew thicker as the collection continued. After discussing the theoretical considerations of remotely sensing in the presence of clouds and other objects, the results of our analysis are presented. It was observed that temporal variability resulted in approximately 2-15% error in sky radiance across the visible wavelengths, and that spatial variability in sky radiance could be shown to be responsible for up to 5% error in retrieved reflectance. Additional theoretical work in modeling the expected radiance contributions of a cloudy sky and the impacts of cloud-induced variability is on-going and will be supported by these results.

关键词： atmospheric calibration atmospheric inversion empirical line method ground truth error modeling MODTRAN

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Reference software implementation for GIFTS ground data processing

Reference software implementation for GIFTS ground data proc...

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conference on atmospheric and environmental remote sensing data processing and utilization II

作者： Garcia, R. K. Howell, H. B. Knuteson, R. O. Martin, G. D. Olson, E. R. Smuga-Otto, M. J. Univ Wisconsin Space Sci & Engn Ctr 1225 W Dayton St Madison WI 53706 USA

ISBN: (纸本)0819463809

Future satellite weather instruments such as high spectral resolution imaging interferometers pose a challenge to the atmospheric science and software development communities due to the immense data volumes they will generate. An open-source, scalable reference software implementation demonstrating the calibration of radiance products from an imaging interferometer, the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS), is presented. This paper covers essential design principles laid out in summary system diagrams, lessons learned during implementation and preliminary test results from the GIFTS Information processing System (GIPS) prototype.

关键词： data processing scalable software Fourier Transform Spectrometer GIFTS cluster computing

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Development of the IASI operational processing and distribution system

Development of the IASI operational processing and distribut...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： King, T Wolf, W Goldberg, M Barnet, C Sun, H Zhou, L QSS Grp Inc Lanham MD 20706 USA

ISBN: (纸本)0819454869

Development and testing of the IASI processing and distribution system is currently ongoing at NOAA/NESDIS/ORA. Level I C data for 8461 channels will be available to NESDIS/NOAA from EUMETSAT shortly after MetOp 1 launch (currently scheduled for October 2005). Prior to launch, a simulation system will provide pseudo near-real time data for system testing and refinement. This will allow for a smooth and immediate system transition to the actual data processing when it becomes available. The ingested EUMETSAT level1C data will be subset both spectrally and spatially and then placed into BUFR format for a number of products including: (1) Level 1C (calibrated, apodized, and navigated) brightness temperatures, (2) cloud-cleared radiances, and (3) PCA reconstructed radiances. The subset level1C data will be delivered within three hours of observation. System validation will consist of comparing the products to collocated radiosonde observations and model forecasts.

关键词： Binary data Clouds data acquisition data processing Infrared radiation data centers Algorithm development data modeling atmospheric modeling Satellites

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Simulation of atmospheric profile retrieval from hyperspectral infrared data under cloudy condition

Simulation of atmospheric profile retrieval from hyperspectr...

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conference on atmospheric and Enviromental remote sensing data processing and utilization III: Readiness for GEOSS

作者： Guan, Li Huang, Hung Lung Nanjing Univ Informat Sci & Technol Sch Remote Sensing Nanjing 210044 Peoples R China Univ Wisconsin Cooperat Inst Meteorol Satellite Studies Madison WI 53706 USA

ISBN: (纸本)9780819468321

In this paper the simulated space-based high spectral resolution infrared radiances with different cloud top heights and effective cloud fractions are used to demonstrate the measurement sensitivity and atmospheric profile retrieval performance. The simulated cloudy retrieval of atmospheric temperature and moisture derived from the statistical eigenvector regression algorithm are analyzed with and without the cloud top height classification. Collocated cloudy AIRS (the atmospheric InfraRed Sounder) and the associated clear MODIS (the Moderate Resolution Imaging Spectroradiomete) infrared observations within the AIRS field of view (FOV) are also used to demonstrate the profile retrieval improvement below the cloud layer. The results show that the knowledge of cloud height is critical to sounding retrieval performance. In addition this paper has demonstrated that the use of collocated clear MODIS multi-spectral imager data along with the AIRS high spectral resolution infrared radiances can greatly improve the single FOV cloudy retrieval even under opaque cloudy condition.

关键词： infrared high spectral resolution atmospheric infrared sounder temperature and humidity retrieval

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