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The Level 1b Algorithm Theoretical Basis Document (ATBD) describes the theoretical basis of the algorithms used to convert engineering units or data numbers from the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the Humidity Sounder Brazil (HSB) to physical radiances.
The level 1b Algorithm Theoretical Basis Document (ATBD) describes the theoretical bases of the algorithms used to convert the raw detector output (data numbers) from the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU) and Humidity Sounder Brazil (HSB) to physical radiance units and, in the case of AIRS, perform in-orbit spectral calibrations.
The purpose of this document is to describe the characteristics of moderate resolution imaging spectroradiometer (MODIS) airborne simulator level 1B data, the calibration and geolocation methods used in processing, the structure and format of the level 1B data files, and methods for accessing the data. The MODIS airborne simulator is a scanning spectrometer which flies on a NASA ER-2 and provides spectral information similar to that which will be provided by the MODIS.
TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.
A computer program performs level- 1B processing (the term 1B is explained below) of data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS), which is an instrument aboard the Aura spacecraft. This software accepts, as input, the raw EOS MLS scientific and engineering data and the Aura spacecraft ephemeris and attitude data. Its output consists of calibrated instrument radiances and associated engineering and diagnostic data. [This software is one of several computer programs, denoted product generation executives (PGEs), for processing EOS MLS data. Starting from level 0 (representing the aforementioned raw data, the PGEs and their data products are denoted by alphanumeric labels (e.g., 1B and 2) that signify the successive stages of processing.] At the time of this reporting, this software is at version 2.2 and incorporates improvements over a prior version that make the code more robust, improve calibration, provide more diagnostic outputs, improve the interface with the Level 2 PGE, and effect a 15-percent reduction in file sizes by use of data compression.
The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) SensorModule (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets and off-axis effects are also implemented. In the third block, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.
The Physical-space/Finite-volume Data Assimilation System (fvDAS) is the next generation global atmospheric data assimilation system in development at the Data Assimilation Office (DAO) at NASA's Goddard Space Flight Center. It is based on a new finite-volume general circulation model jointly developed by NASA and NCAR, and on the Physical-Space Statistical Analysis System (PSAS) developed at the DAO. In this talk we will focus on the assimilation of data from the (Advanced) TIROS Operational Vertical Sounder (ATOVS), with emphasis on the impact of cloud- and land-affected level 1B radiances. Recently, it has been shown that the use of observations from satellite-borne microwave and infrared radiometers in data assimilation systems consistently increases forecast skill. Considerable effort has been expended over the past two decades, particularly with the (Advanced) TIROS Operational Vertical Sounder (ATOVS), to achieve this result. The positive impact on forecast skill has resulted from improvements in quality control algorithms, systematic error correction schemes, and more sophisticated data assimilation algorithms. Despite these advances, there are still many issues regarding the use of satellite data in data assimilation systems that remain unresolved. In particular, most operational centers still do not assimilate cloud- and land-affected TOVS data. In this study, we evaluate the impact of assimilating cloud-and land-affected TOVS/ATOVS level 1B data in DAO's next generation fvDAS, using a 1D variational scheme. We will discuss the impact of these data on both tropospheric and stratospheric forecasts, as well as on the general aspects of the earth climate system.
This is Part 3 of the AIRS level 1b Algorithm Theoretical Basis Document (ATBD).
This software is an improvement on Version 2, which was described in EOS MLS Level 1B Data Processing, Version 2.2, NASA Tech Briefs, Vol. 33, No. 5 (May 2009), p. 34. It accepts the EOS MLS Level 0 science/engineering data, and the EOS Aura spacecraft ephemeris/attitude data, and produces calibrated instrument radiances and associated engineering and diagnostic data. This version makes the code more robust, improves calibration, provides more diagnostics outputs, defines the Galactic core more finely, and fixes the equator crossing. The Level 1 processing software manages several different tasks. It qualifies each data quantity using instrument configuration and checksum data, as well as data transmission quality flags. Statistical tests are applied for data quality and reasonableness. The instrument engineering data (e.g., voltages, currents, temperatures, and encoder angles) is calibrated by the software, and the filter channel space reference measurements are interpolated onto the times of each limb measurement with the interpolates being differenced from the measurements. Filter channel calibration target measurements are interpolated onto the times of each limb measurement, and are used to compute radiometric gain. The total signal power is determined and analyzed by each digital autocorrelator spectrometer (DACS) during each data integration. The software converts each DACS data integration from an autocorrelation measurement in the time domain into a spectral measurement in the frequency domain, and estimates separately the spectrally, smoothly varying and spectrally averaged components of the limb port signal arising from antenna emission and scattering effects. Limb radiances are also calibrated.
MODIS continues to be an important instrument for NASA’s Earth Observing System (EOS). Terra and Aqua MODIS have produced more than 22 and 20 years of global datasets that have significantly helped scientists better understand the Earth’s systems respectively. The MODIS Level-1B (L1B) algorithms use the uncalibrated, geolocated Earth scene observations as input and convert the instrument response into calibrated reflectance and radiance, which are used to generate the downstream science products. The sustained calibration and characterization activities undertaken by the MODIS Characterization Support Team have resulted in several upgrades to the L1B algorithms in order to maintain accurate calibration in the data products. In this paper, we present an overview of the L1B algorithm designated as Collection 7. Various algorithm enhancements both in the reflective bands and thermal bands characterization, are currently under science testing and evaluation. Once applied in data processing (projected in early 2023), they are expected to manifest in improved science products, both in terms of radiometric accuracy and long-term stability.
Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30° N. These biases – of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3) – were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30–60° N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR–MODIS BTDs in the 30–60° N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1–MODIS29. For IIR2–MODIS31 and IIR3–MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3–MODIS32 in June, where the night-minus-day difference is around −0.1 K.
The Moderate Resolution Imaging Spectroradiometer (MODIS) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and Aqua satellites, launched in December 1999 and May 2002, respectively. The MODIS Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) reflectance factors for the sensor's reflective solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the MODIS L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the MODIS collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle.
A complement of Readiness, Implementation and Management Plans (RIMPs) to facilitate management of post-launch product test activities for the official Geostationary Operational Environmental Satellite (GOES-R) Level 1b (L1b) products have been developed and documented. Separate plans have been created for each of the GOES-R sensors including: the Advanced Baseline Imager (ABI), the Extreme ultraviolet and X-ray Irradiance Sensors (EXIS), Geostationary Lightning Mapper (GLM), GOES-R Magnetometer (MAG), the Space Environment In-Situ Suite (SEISS), and the Solar Ultraviolet Imager (SUVI). The GOES-R program has implemented these RIMPs in order to address the full scope of CalVal activities required for a successful demonstration of GOES-R L1b data product quality throughout the three validation stages: Beta, Provisional and Full Validation. For each product maturity level, the RIMPs include specific performance criteria and required artifacts that provide evidence a given validation stage has been reached, the timing when each stage will be complete, a description of every applicable Post-Launch Product Test (PLPT), roles and responsibilities of personnel, upstream dependencies, and analysis methods and tools to be employed during validation. Instrument level Post-Launch Tests (PLTs) are also referenced and apply primarily to functional check-out of the instruments.
The Moderate-resolution Imaging Spectroradiometer (MODIS) instruments are on-board the Aqua and Terra spacecraft, launched in 2002 and 1999, respectively. Since beginning operation, they have continued to collect valuable remote sensing data of the Earth in 36 spectral bands ranging in wavelengths from 0.41 to 14.5 μm. The Level 1B (L1B) algorithm produces calibrated top of the atmosphere (TOA) radiances for each Earth-view (EV) pixel and calibrated TOA reflectances for the reflective solar bands using geo-located, uncalibrated instrument data and calibration look up tables (LUTs) produced regularly by the MODIS Characterization Support Team (MCST). The L1B algorithm also calculates an uncertainty value for each EV pixel. The calibrated radiance and reflectance products are used to generate higher-level science products. A separate L1B code version is maintained for both MODIS instruments so that sensor specific issues can be handled individually. The current L1B algorithm version produces the Collection 6.1 (C6.1) products and was released in 2017. An overview of the C6.1 algorithm is provided together with improvements made since its release. Also discussed briefly are the planned improvements in the Collection 7 L1B algorithm.
The radiometric response of the EOS-AM1 Multi-angle Imaging SpectroRadiometer (MISR) is to be measured throughout the six-year mission. This paper discusses the investigations and algorithm changes that have occurred in the production of the ARP since launch, and discusses changes to the Level 1B data that might be expected should data be reprocessed.
The BOREAS RSS-2 team used the ASAS instrument, mounted on the NASA C-130 aircraft, to create at-sensor radiance images of various sites as a function of spectral wavelength, view geometry (combinations of view zenith angle, view azimuth angle, solar zenith angle, and solar azimuth angle), and altitude. The level-1b ASAS images of the BOREAS study areas were collected from April to September 1994 and March to July 1996.
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 Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. For BOREAS, the Thermal Infrared Multispectral Scanner (TIMS) imagery, along with other aircraft images, was collected to provide spatially extensive information over the primary study areas. The Level-1b TIMS images cover the time periods of 16 to 20 Apr 1994 and 06 to 17 Sep 1994. The system calibrated images are stored in binary image format files. The TIMS images are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).