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This paper describes the validation of ozone data from the Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS). The MLS ozone retrievals are obtained from the calibrated microwave radiances (emission spectra) in two separate bands, at frequencies near 205 and 183 GHz.
The past decade has seen a rapid increase in availability and usage of near-real-time data from satellite sensors. The EOSDIS (Earth Observing System Data and Information System) was not originally designed to provide data with sufficiently low latency to satisfy the requirements for near-real-time users. The EOS (Earth Observing System) instruments aboard the Terra, Aqua and Aura satellites make global measurements daily, which are processed into higher-level 'standard' products within 8-40 hours of observation and then made available to users, primarily earth science researchers. However, applications users, operational agencies, and even researchers desire EOS products in near-real-time to support research and applications, including numerical weather and climate prediction and forecasting, monitoring of natural hazards, ecological/invasive species, agriculture, air quality, disaster relief and homeland security. These users often need data much sooner than routine science processing allows, usually within 3 hours, and are willing to trade science product quality for timely access. While Direct Broadcast provides more timely access to data, it does not provide global coverage. In 2002, a joint initiative between NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration), and the DOD (Department of Defense) was undertaken to provide data from EOS instruments in near-real-time. The NRTPE (Near Real Time Processing Effort) provided products within 3 hours of observation on a best-effort basis. As the popularity of these near-real-time products and applications grew, multiple near-real-time systems began to spring up such as the Rapid Response System. In recognizing the dependence of customers on this data and the need for highly reliable and timely data access, NASA's Earth Science Division sponsored the Earth Science Data and Information System Project (ESDIS)-led development of a new near-real-time system called LANCE (Land, Atmosphere Near-Real-Time Capability for EOS) in 2009. LANCE consists of special processing elements, co-located with selected EOSDIS data centers and processing facilities. A primary goal of LANCE is to bring multiple near-real-time systems under one umbrella, offering commonality in data access, quality control, and latency. LANCE now processes and distributes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments within 3 hours of satellite observation. The Rapid Response System and the Fire Information for Resource Management System (FIRMS) capabilities will be incorporated into LANCE in 2011. LANCE maintains a central website to facilitate easy access to data and user services. LANCE products are extensively tested and compared with science products before being made available to users. Each element also plans to implement redundant network, power and server infrastructure to ensure high availability of data and services. Through the user registration system, users are informed of any data outages and when new products or services will be available for access. Building on a significant investment by NASA in developing science algorithms and products, LANCE creates products that have a demonstrated utility for applications requiring near-real-time data. From lower level data products such as calibrated geolocated radiances to higher-level products such as sea ice extent, snow cover, and cloud cover, users have integrated LANCE data into forecast models and decision support systems. The table above shows the current near-real-time product categories by instrument. The ESDIS Project continues to improve the LANCE system and use the experience gained through practice to seek adjustments to improve the quality and performance of the system. For example, anGC-compliant Web Map Service (WMS) will be added shortly that will allow users to download geo-referenced MODIS images for arbitrary bounding boxes. Further, an OGC-compliant Web Coverage Service (WCS) will be added later this year that will expedite user access to arbitrary data subsets or re-formatted products. AIRS images are now served through WMS and available in multiple formats (PNG, GeoTIFF, KMZ). NASA has established a LANCE User Working Group to steer the development of the system and create a forum for sharing ideas and experiences that are expected to further improve the LANCE capabilities. The LANCE system has proved a success by satisfying the growing needs of the applications and operational communities for land and atmosphere data in near-real-time. NASA's Earth Sciences Division was able to leverage existing science research capabilities to provide the near-real-time community with products and imagery that support monitoring of disasters in a timely manner.
The Atmospheric Infrared Spectrometer (AIRS) Science Processing System is a collection of computer programs, denoted product generation executives (PGEs), for processing the readings of the AIRS suite of infrared and microwave instruments orbiting the Earth aboard NASA's Aqua spacecraft. Following from level 0 (representing raw AIRS data), the PGEs and their data products are denoted by alphanumeric labels (1A, 1B, and 2) that signify the successive stages of processing. Once level-0 data have been received, the level-1A PGEs begin processing, performing such basic housekeeping tasks as ensuring that all the Level-0 data are present and ordering the data according to observation times. The level-1A PGEs then perform geolocation-refinement calculations and conversions of raw data numbers to engineering units. Finally, the level-1A data are grouped into packages, denoted granules, each of which contain the data from a six-minute observation period. The granules are forwarded, along with calibration data, to the Level-1B PGEs for processing into calibrated, geolocated radiance products. The Level-2 PGEs, which are not yet operational, are intended to process the level-1B data into temperature and humidity profiles, and other geophysical properties.
The Orbiting Carbon Observatory is scheduled for launch from Vandenberg Air Force Base in California in January 2009. This Earth System Science Pathfinder (ESSP) mission carries and points a single instrument that incorporates 3 high-resolution grating spectrometers designed to measure the absorption of reflected sunlight by near-infrared carbon dioxide (CO2) and molecular oxygen bands. These spectra will be analyzed to retrieve estimates of the column-averaged CO2 dry air mole fraction, X(sub CO2). Pre-flight qualification and calibration tests completed in early 2008 indicate that the instrument will provide high quality X(sub CO2) data. The instrument was integrated into the spacecraft, and the completed Observatory was qualified and tested during the spring and summer of 2008, in preparation for delivery to the launch site in the fall of this year. The Observatory will initially be launched into a 635 km altitude, near-polar orbit. The on-board propulsion system will then raise the orbit to 705 km and insert OCO into the Earth Observing System Afternoon Constellation (A-Train). The first routine science observations are expected about 45 days after launch. Calibrated spectral radiances will be archived starting about 6 months later. An exploratory X(sub CO2) product will be validated and then archived starting about 3 months after that.
Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (SNPP) satellite Environmental Data Record (EDR) is retrieved from calibrated ultraspectral radiance so called Sensor Data Record (SDR). It is critical to understand the accuracy of retrieved EDRs, which mainly depends on SDR accuracy (e.g., instrument random noise and absolute accuracy), an ill-posed retrieval system, and radiative transfer model errors. There are few approaches to validate EDR products, e.g., some common methods are to rely on radiosonde measurements, ground-based measurements, and dedicated aircraft campaign providing in-situ measurements of atmosphere and/or employing similar ultraspectral interferometer sounders. Ultraspectral interferometer sounder aboard aircraft measures SDR to retrieve EDR, which is often used to validate satellite measurements of SDR and EDR. The SNPP Calibration/Validation Campaign was conducted during May 2013. The NASA high-altitude aircraft ER-2 that carried ultraspectral interferometer sounders such as the NASA Atmospheric Sounder Testbed-Interferometer (NAST-I) flew under the SNPP satellite that carries the Cross-track Infrared Sounder (CrIS). Here we inter-compare the EDRs produced with different retrieval algorithms from SDRs measured by the sensors from satellite and aircraft. The available dropsonde and radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis were also used to draw the conclusion from this experiment.
Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary results of this experiment under a winter, Arctic environment are presented.
Polarization sensitivity is a critical property that must be characterized for spaceborne remote sensing instruments designed to measure reflected solar radiation. Broadband testing of the first Joint Polar-orbiting Satellite System (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS) showed unexpectedly large polarization sensitivities for the bluest bands on VIIRS (centered between 400 and 600 nm). Subsequent ray trace modeling indicated that large diattenuation on the edges of the bandpass for these spectral bands was the driver behind these large sensitivities. Additional testing using the National Institute of Standards and Technologies Traveling Spectral Irradiance and Radiance Responsivity Calibrations Using Uniform Sources was added to the test program to verify and enhance the model. The testing was limited in scope to two spectral bands at two scan angles; nonetheless, this additional testing provided valuable insight into the polarization sensitivity. Analysis has shown that the derived diattenuation agreed with the broadband measurements to within an absolute difference of about0.4 and that the ray trace model reproduced the general features of the measured data. Additionally, by deriving the spectral responsivity, the linear diattenuation is shown to be explicitly dependent on the changes in bandwidth with polarization state.
The calibrated upwelling radiance spectra measured by AVIRIS are increasingly being analyzed with radiative transfer codes. Analysis of AVIRIS data with the LOWTRAN and MODTRAN radiative transfer codes has led to indications of an error in the solar irradiance spectra used by these codes. This paper presents evidence for the error and a proposed update to the solar irradiance spectra used by LOWTRAN and MODTRAN.
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NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will make global ocean color and atmospheric measurements to provide extended data records of ocean ecology and global biogeochemistry, along with polarimetric measurements for advanced observations of aerosols, clouds and the ocean. PACE will contain three instruments: the primary Ocean Color Instrument (OCI), and two multi-angle polarimeters (MAPs). The latter instruments are contributed under a ‘Do-No-Harm’ (to the rest of the PACE mission) principle, and the PACE Science Data Processing System (SDPS) is only required to produce Level-1b (geolocated radiances with calibration applied) data without performance requirements. However, there is a strong desire to produce data in a format that merges the disparate spatial resolutions, viewing geometry and sampling nature of the three instruments. Our terminology for this format is Level 1c (L1C). This format will be an input to Level 2 algorithms produced from standalone MAP instrument observations, or from algorithms employing multi-sensor fusion. Creating the L1C format has several components. This includes choice of projection method, the means by which multi-angle views are properly incorporated into that projection (‘aggregation’) the means to represent wavelength and light polarization state, the selection of data to be included within the L1C file, and the handling of ancillary data either required for L1C file generation or needed in that format for L2 processing.
The author has identified the following significant results. A theory has been developed of a method for determining the reflectivities of natural areas from ERTS-1 data. This method requires the following measurements: (1) ground truth reflectivity data from two different calibration areas; (2) radiance data from ERTS-1 MSS imagery for the same two calibration areas; and (3) radiance data from ERTS-1 MSS imagery for the area(s) in which reflectivity is to be determined. The method takes into account sun angle effects and atmospheric effects on the radiance seen by the space sensor. If certain assumptions are made, the ground truth data collection need not be simultaneous with the ERTS-1 overflight. The method allows the calculation of a conversion factor for converting ERTS-1 MSS radiance measurements of a given overflight to reflectivity values. This conversion factor can be used to determine the reflectivity of any area in the general vicinity of the calibration areas which has a relatively similar overlying atmosphere. This method, or some modification of it, may be useful in ERTS investigations which require the determination of spectral signatures of areas from spacecraft data.
TOA (top-of-atmosphere) radiance from high-spatial-resolution satellite imagery systems is important for a wide variety of research and applications. Many research initiatives require data with absolute radiometric accuracy better than a few percent. The conversion of satellite digital numbers to radiance depends on accurate radiometric calibration. A common method for determining and validating radiometric calibrations is to rely upon vicarious calibration approaches. Historically, vicarious calibration methods use radiative transfer codes with ground-based atmosphere and surface reflectance or radiance inputs for estimating TOA radiance values. These TOA radiance values are compared against the satellite digital numbers to determine the radiometric calibration. However, the radiative transfer codes used depend on many assumptions about the aerosol properties and the atmospheric point spread function. A measurement-based atmospheric radiance estimation approach for high-spatial-resolution, multispectral, visible/near-infrared sensors is presented that eliminates the use of radiative transfer codes and many of the underlying assumptions. A comparison between the radiative transfer and non-radiative transfer approaches is made.
On 7 Mar. 1991, an in-flight calibration experiment was held at the Ivanpah Playa in southeastern California for the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Five AVIRIS overflights were acquired of a calibration target designated on the Ivanpah Playa surface. At the time of the overflights, the reflectance of the calibration target was measured with a field spectrometer. In addition, the atmospheric optical depths and water vapor abundance were measured from a radiometer station adjacent to the calibration target. These in-situ measurements were used to constrain the MODTRAN radiative transfer code to model the upwelling spectral radiance incident to the sensor aperture during the overflights. Analyses of this modeled radiance in conjunction with the laboratory-calibrated radiance were used to determine the spectral and radiometric calibration of AVIRIS while in flight.
This paper reports the results of a comparison between the AVIRIS portable radiance standard and the Landsat transfer radiometer.
Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify recovery. We have shown that validation of radiances is the most effective means for correcting absolute accuracy and long term drifts of backscatter type satellite measurements. This method by-passes the algorithms used for both satellite and ground based measurements which are normally used to validate and correct the satellite data. Validation of radiances will also improve all higher level data products derived from the satellite observations. Backscatter algorithms suffer from several errors such as unrepresentative a-priori data and air mass factor corrections. Radiance comparisons employ forward models but are inherently more accurate and than inverse (retrieval) algorithms. A new method for satellite validation is planned which will compliment measurements from the existing ground-based networks. This method will employ very accurate comparisons between ground based zenith sky radiances and satellite nadir radiances. These comparisons will rely heavily on the experience derived from the Shuttle SBUV (SSBUV) program which provided a reference standard of radiance measurements for SBUV/2, TOMS, and GOME. This new measurement program, called "Skyrad", employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. The Skyrad instruments (SSBUV, Brewer spectrophotometers, and possibly others) will be calibrated and maintained to a precision of a few tenths of a percent. Skyrad data will then enable long term calibration of upcoming satellite instruments such as QuickTOMS. SBUV/2s and SCIAMACHY with a high degree of precision. This technique can be further employed to monitor the performance of future instruments such as GOME-2, OMI, and OMPS. Initial ground observations taken from Goddard Space Flight Center compared with radiative transfer calculations has indicated the feasibility of this method.
We have shown that validation of radiances is a very effective means for correcting absolute accuracy and long term drifts of backscatter type satellite measurements. This method by-passes the algorithms used for both satellite and ground based measurements which are normally used to validate and correct the satellite data. A new method for satellite validation is planned which will compliment measurements from the existing ground-based networks. This method will employ very accurate comparisons between ground based zenith sky radiances and satellite nadir radiances. These comparisons will rely heavily on the experience derived from the Shuttle SBUV (SSBUV) program which provided a reference standard of radiance measurements for SBUV/2, TOMS, and GOME. This new measurement program, called 'Skyrad', employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. The Skyrad instruments (SSBUV, Brewer spectrophotometers, and possibly others) will be calibrated and maintained to a precision of a few tenths of a percent. Skyrad data will then enable long term calibration of upcoming satellite instruments such as QuickTOMS, SBUV/2s and SCIAMACHY with a high degree of precision. This technique can be further employed to monitor the performance of future instruments such as GOMEZ, OMI, and OMPS. Additional information is included in the original extended abstract.
The post-launch degradation of the visible (channel 1: 0.58- 068 microns) and near-infrared (channel 2: approx. 0.72 - l.l microns) channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-7, -9, and -11 Polar-orbiting Operational Environmental Satellites (POES) was estimated using the south-eastern part of the Libyan Desert as a radiometrically stable calibration target. The relative annual degradation rates, in per cent, for the two channels are, respectively: 3.6 and 4.3 (NOAA-7); 5.9 and 3.5 (NOAA-9); and 1.2 and 2.0 (NOAA-11). Using the relative degradation rates thus determined, in conjunction with absolute calibrations based on congruent path aircraft/satellite radiance measurements over White Sands, New Mexico (USA), the variation in time of the absolute gain or slope of the AVHRR on NOAA-9 was evaluated. Inter-satellite calibration linkages were established, using the AVHRR on NOAA-9 as a normalization standard. Formulae for the calculation of calibrated radiances and albedos (AVHRR usage), based on these interlinkages, are given for the three AVHRRs.
One important aspect of successful climate monitoring is satellite calibration. There is at least a 25-year of operational geostationary (GEO) record available for climate studies, if properly calibrated. The Global Space-based Inter-Calibration System (GSICS) project is another effort to provide the climate community consistent calibration across multiple platforms. Also, the Clouds and the Earth's Radiant Energy System (CERES) project, provides consistent GEO retrieved cloud properties and derived broadband fluxes across multiple platforms. This year GSICS is focusing on geostationary visible channel calibration. The GSICS strategy is to use multiple approaches, such as cross-calibrating the GEO radiances against MODIS as a reference, deep convective clouds as bright stable targets, deserts, sun-glint, stars, moon and other model based calibration methods. Each of these methods is independent of each other and can assess the stability of the GEO visible instrument with differing uncertainties. This study focuses on the inter-calibration of the GEO radiances against MODIS as a reference by using collocated, and coincident ray-matched radiances. The advantage of the ray-matching technique is that it provides a full dynamic range of radiances to check the linearity of the GEO visible instrument. This presentation will focus on the technique, some error analysis, comparisons with other methods, and an approach to inter-calibrate historical GEOs before MODIS.