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This paper will describe the production of the Ancillary Geographic Product (AGP) in support of the Earth Observing System (EOS) Multi-angle Imaging SpectroRadiometer (MISR) instrument data processing. The AGP is essentially a global database of geographic properties, tailored to the needs of the MISR mission.
The Multi-Angle Imaging SpectroRadiometer (MISR) instrument is being developed at JPL for the EOS AM1 spacecraft, scheduled for launch in June 1998. The development status and strategy for observing atmospheric aerosols are described.
The Atmospheric Infrared Sounder (AIRS) is a facility instrument on the Earth Observing System (EOS) P.M. platform. It will be launched into a 705 km high polar orbit in the year 2000. On the platform with AIRS are the Advanced Microwave Sounding Unit (AMSU) and the Microwave Humidity Sounder (MHS). The three instruments are designed to meet NASA's global change research objectives and NOAA's operational sounding requirements for global weather predictions. AIRS, AMSU, and MHS will provide global tempeature profiles with 1 k rms accuracy in 1 km thick layers in the troposphere and water burden with 10 % accuracy. This is more than a factor of two better than the current operational sounding system, TOVS, and is expected to result in a significant improvement in the medium range forecast accuracy.
Multiangle, multispectral remote sensing observations, such as those anticipated from the Multiangle, multispectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multiangle Imaging SpectroRadiometer (MISR), promise to significantly improve our ability to constrain aerosol properties from space.
The Atmospheric Infrared Sounder (AIRS) was launched May 4, 2002 on the EOS Aqua Spacecraft. A discussion is given of the objectives of the AIRS experiment, including requirements on the data products. We summarize the instrument characteristics, including sensitivity, noise, and spectral response, and preflight calibration results leading to the estimate of the calibration accuracy. The Level 1B calibration algorithm is presented as well as the results of in-flight stability and sensitivity measurements.
The collocation of a National Weather Service (NWS) Forecast Office with atmospheric scientists from NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama has afforded a unique opportunity for science sharing and technology transfer. Specifically, the NWS office in Huntsville has interacted closely with research scientists within the SPORT (Short-term Prediction and Research and Transition) Center at MSFC. One significant technology transfer that has reaped dividends is the transition of unique NASA EOS polar orbiting datasets into NWS field operations. NWS forecasters primarily rely on the AWIPS (Advanced Weather Information and Processing System) decision support system for their day to day forecast and warning decision making. Unfortunately, the transition of data from operational polar orbiters or low inclination orbiting satellites into AWIPS has been relatively slow due to a variety of reasons. The ability to integrate these high resolution NASA datasets into operations has yielded several benefits. The MODIS (MODerate-resolution Imaging Spectrometer ) instrument flying on the Aqua and Terra satellites provides a broad spectrum of multispectral observations at resolutions as fine as 250m. Forecasters routinely utilize these datasets to locate fine lines, boundaries, smoke plumes, locations of fog or haze fields, and other mesoscale features. In addition, these important datasets have been transitioned to other WFOs for a variety of local uses. For instance, WFO Great Falls Montana utilizes the MODIS snow cover product for hydrologic planning purposes while several coastal offices utilize the output from the MODIS and AMSR-E instruments to supplement observations in the data sparse regions of the Gulf of Mexico and western Atlantic. In the short term, these datasets have benefited local WFOs in a variety of ways. In the longer term, the process by which these unique datasets were successfully transitioned to operations will benefit the planning and implementation of products and datasets derived from both NPP and NPOESS. This presentation will provide a brief overview of current WFO usage of satellite data, the transition of datasets between SPORT and the N W S , and lessons learned for future transition efforts.
This viewgraph presentation reviews four years of absolute calibration of hyperspectral data from the AIRS instrument located on the EOS AQUA spacecraft. The following topics are discussed: 1) A quick overview of AIRS; 2) What absolute calibration accuracy and stability are required for climate applications?; 3) Validating of radiance accuracy and stability: Results from four years of AIRS data; and 4) Conclusions.
The authors describe in this paper the progress achieved to-date with the reengineering of the Earth Observing System (EOS) Data and Operations System (EDOS), the experience gained in the process and the ensuing reduction of ground systems operations costs. The reengineering effort included a major methodology change, applying to an existing schedule driven system, a data-driven system approach.
The EOS Aura mission, launched in 2004, provides a comprehensive assessment of the stratospheric dynamics and chemistry. This talk will focus on results from Aura including the chemistry of polar ozone depletion. The data from Aura can be directly linked to UARS data to produce long term trends in stratospheric trace gases.
An Extensible Markup Language (XML) document type definition (DTD) standard for the structure and contents of HDF-EOS files and their contents, and an equivalent standard in the form of schemas, have been developed.
Real-time satellite information provides one of many data sources used by NWS weather forecast offices (WFOs) to diagnose current weather conditions and to assist in short-term forecast preparation. While GOES satellite data provides relatively coarse spatial resolution coverage of the continental U.S. on a 10-15 minute repeat cycle, polar orbiting imagery has the potential to provide snapshots of weather conditions at high-resolution in many spectral channels. Additionally, polar orbiting sounding data can provide additional information on the thermodynamic structure of the atmosphere in data sparse regions of at asynoptic observation times. The NASA Short-term Prediction Research and Transition (SPoRT) project has demonstrated the utility of polar orbiting MODIS and AIRS data on the Terra and Aqua satellites to improve weather diagnostics and short-term forecasting on the regional and local scales. SPoRT scientists work directly forecasters at selected WFOS in the Southern Region (SR) to help them ingest these unique data streams into their AWIPS system, understand how to use the data (through on-site and distance learn techniques), and demonstrate the utility of these products to address significant forecast problems. This process also prepares forecasters for the use of similar observational capabilities from NPOESS operational sensors. NPOESS environmental data records (EDRs) from the Visible 1 Infrared Imager I Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrlS) and Advanced Technology Microwave Sounder (ATMS) instruments and additional value-added products produced by NESDIS will be available in near real-time and made available to WFOs to extend their use of NASA EOS data into the NPOESS era. These new data streams will be integrated into the NWs's new AWIPS II decision support tools. The AWIPS I1 system to be unveiled in WFOs in 2009 will be a JAVA-based decision support system which preserves the functionality of the existing systems and offers unique development opportunities for new data sources and applications in the Service Orientated Architecture ISOA) environment. This paper will highlight some of the SPoRT activities leading to the integration of VllRS and CrIS/ATMS data into the display capabilities of these new systems to support short-term forecasting problems at WFOs.
Aqua measures the Earth's water cycle, energy fluxes, vegetation and temperatures. The Atmospheric Infrared Sounder (AIRS), Advanced Microwave Sounding Unit (AMSU) and Humidity Sounder for Brazil (HSB) were launched on the EOS Aqua spacecraft in May 2002. AIRS has had good radiometric and spectral sensitivity, stability, and accuracy and is suitable for climate studies. Temperature products compare well with radiosondes and models over the limited test range (|LAT| less than 40 degrees). Early trace gas products demonstrate the potential of AIRS. NASA is developing the next generation of hyperspectral IR imagers. JPL is ready to participate with US government agencies and US industry to transfer AIRS technology and science experience.
Data assimilation is a potentially powerful method of extracting the maximum amount of information from observed data by combining their information with models. in this application, we will use stratospheric ozone profiles retrieved from EOS MLS and total column amounts retrieved from OMI' along with the GEOS-5 GCM, that includes a representation of ozone chemistry and transport. The presentation will discuss how well we can derive tropospheric ozone column information in this system, including its sensitivity to model errors and some assumptions made in the assimilation system. We discuss also ozone structures in the tropopause region and their sensitivity to model resolution and other fact=ors. An important issue we examine is how much more information we obtain from ozone assimilation than from model studies using state of the art chemistry models - answering such questions helps determine how useful ozone assimilation really is, given our present capabilities in chemical modeling.
The Ozone Monitoring Instrument (OMI), which is on the EOS AURA satellite, retrieves vertical column densities (VCDs) of NO2, along with those of several other trace gases. The relatively high spatial resolution and daily global coverage of the instrument make it particularly well-suited to monitoring tropospheric pollution at scales on the order of 20 km. The OMI NO2 algorithm distinguishes polluted regions from background stratospheric NO2 using a separation algorithm that relies on the smoothly varying stratospheric NO2 and estimations of both stratospheric and tropospheric air mass factors (AMFs). Version 1 of OMI NO2 data has been released for public use. An overview of OMI NO2 data, some recent results and a description of the improvements for version 2 of the algorithm will be presented.
A computer program performs level-2 processing of thermal-microwave-radiance data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS). The purpose of the processing is to estimate the composition and temperature of the atmosphere versus altitude from .8 to .90 km. "Level-2" as used here is a specialists f term signifying both vertical profiles of geophysical parameters along the measurement track of the instrument and processing performed by this or other software to generate such profiles. Designed to be flexible, the program is controlled via a configuration file that defines all aspects of processing, including contents of state and measurement vectors, configurations of forward models, measurement and calibration data to be read, and the manner of inverting the models to obtain the desired estimates. The program can operate in a parallel form in which one instance of the program acts a master, coordinating the work of multiple slave instances on a cluster of computers, each slave operating on a portion of the data. Optionally, the configuration file can be made to instruct the software to produce files of simulated radiances based on state vectors formed from sets of geophysical data-product files taken as input.
Standard products from the five sensors on NASA's Earth Observing System's (EOS) Terra satellite are being used world-wide for earth science research and applications. This paper describes the evolution of the Terra data systems over the last decade in which the distributed systems that produce, archive and distribute high quality Terra data products were scaled by two orders of magnitude.
The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua missions has shown considerable capability for mapping snowcover. The typical approach that has used, along with other criteria, the Normalized Snow Difference Index (NDSI) that takes the difference between 500 meter observations at 1.64 micrometers (MODIS band 6) and 0.555 micrometers (MODIS band 4) over the sum of these observations to determine whether MODIS pixels are snowcovered or not in mapping the extent of snowcover. For many hydrological and climate studies using remote sensing of snowcover, it is desirable to assess if the MODIS snowcover observations could not be enhanced by providing the fraction of snowcover in each MODIS observation (pixel). Pursuant to this objective studies have been conducted to assess whether there is sufficient "signal%o in the NDSI parameter to provide useful estimates of fractional snowcover in each MODIS 500 meter pixel. To accomplish this objective high spatial resolution (30 meter) Landsat snowcover observations were used and co-registered with MODIS 500 meter pixels. The NDSI approach was used to assess whether a Landsat pixel was or was not snowcovered. Then the number of snowcovered Landsat pixels within a MODIS pixel was used to determine the fraction of snowcover within each MODIS pixel. The e results were then used to develop statistical relationships between the NDSI value for each 500 meter MODIS pixel and the fraction of snowcover in the MODIS pixel. Such studies were conducted for three widely different areas covered by Landsat scenes in Alaska, Russia, and the Quebec Province in Canada. The statistical relationships indicate that a 10 percent accuracy can be attained. The variability in the statistical relationship for the three areas was found to be remarkably similar (-0.02 for mean error and less than 0.01 for mean absolute error and standard deviation). Independent tests of the relationships were accomplished by taking the relationship of fractional snow-cover to NDSI from one area (e.g., Alaska) and testing it on the other two areas (e.g. Russia and Quebec). Again the results showed that fractional snow-cover can be estimated to 10 percent. The results have been shown to have advantages over other published fractional snowcover algorithms applied to MODIS data. Most recently the fractional snow-cover algorithm has been applied using 500-meter observations over the state of Colorado for a period spanning 25 days. The results exhibit good behavior in mapping the spatial and temporal variability in snowcover over that 25-day period. Overall these studies indicate that robust estimates of fractional snow-cover can be attained using the NDSI parameter over areas extending in size from watersheds relatively large compared to MODIS pixels to global land cover. Other refinements to this approach as well as different approaches are being examined for mapping fractional snow-cover using MODIS observations.
This study presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetic active radiation (PAR) absorbed by chlorophyll of a canopy (fAPAR(sub chl)) and leaf water content (LWC), for future HyspIRI implementation at 60 m spatial resolution. For this, we used existing 30 m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRI-like images were atmospherically corrected to obtain surface reflectance, and spectrally resampled to produce 60 m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest[1]. With this study, we provide additional evidence that the fAPARchl product is more realistic for describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPAR(sub canopy)), and thus should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle studies and ecosystem studies.