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At least 73 records · Page 4

Seasonal, Spectral, and Regional Characterization of Deep Convective Clouds Top-of-Atmosphere Bidirectional Reflectance for Improved Satellite Intercalibration

The NASA CERES project provides the scientific community with regional broadband fluxes designed for long-term climate monitoring. The CERES climate quality dataset requires that the CERES instrument, as well as the MODIS and VIIRS imager records to be radiometrically stable over time. Deep Convective Clouds (DCCs) are spectrally uniform, near-Lambertian natural diffusers offering high signal-to-noise ratio and stable radiometric response in the VIS-NIR spectrum. For shortwave infrared (SWIR) wavelengths greater than 1.2µm, the DCC response is significantly influenced by cloud particle size and atmospheric absorption. Previous studies improved the characterization of the SWIR band DCC radiance, by using channel specific monthly empirical BRDFs as well as using the probability density function mean statistic to track the SWIR band stability. Also, that the DCC radiance is greater over land than over ocean and that the TWP DCC radiance has the lowest tropical DCC radiance. This study confirms and improves upon the previous studies. The study stratified the tropics regionally into land and ocean domains and applied their respective ocean-only and land-only empirical monthly BRDFs and normalized the land DCC BRDF corrected radiances with their ocean counterpart. This approach provided the most stable DCC response. The DCC BRDF corrected radiance monthly standard error was 0.24%, 0.62%, 0.59%, and 0.43% for the 1.24µm, 1.37µm, 1.61µm, and 2.25µm SWIR bands, which reduced the standard error 20%, 13%, 24%, and 26%, respectively when compared with the all-surface approach. The same approach was attempted over the Tropical Western Pacific and found not to be an improvement over the tropical domain. Further stratification of the tropical domain will need to balance sufficient sampling while accounting for regional DCC radiance differences.

Prathana Khakurel↗

The Spectral Information Based Angular Correction Methodology for Satellite Intercalibration Applications

Satellite inter-calibration often requires collocated observations with minimized discrepancies in sun-view angles, observation times, and sensor characteristics. The collocation criteria directly impact achievable inter-calibration accuracy. Addressing potential angular mismatches in inter-calibration samples is critical but not as fully recognized and addressed as spatial-temporal mismatches in many studies. To achieve high-accuracy corrections for errors due to mismatched sun-view geometry angles, an angular correction algorithm has been developed for the Climate Absolute Radiance and Refractivity Observatory Pathfinder (CPF) mission. This algorithm uses spectral correlation relationships to estimate differences in spectral radiances measured at different angles. This methodology can be extended for inter-calibrations between sensors measuring band radiances across a broad spectral region. We demonstrate its application in reducing angular mismatch errors between collocated measurements of multi-spectral imaging sensors, using the inter-calibration between the Moderate Resolution Imaging Spectrometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) as an example. The angular correction allows for more relaxed collocation criteria so that more satellite-based inter-calibration samples can be utilized. Furthermore, implementing the angular correction algorithm improves inter-calibration accuracy in applications where angular mismatch errors have not been explicitly addressed previously.

Wan Wu↗

Harnessing CPF Hyperspectral Radiances to Homogenize Earth Observing Systems

Homogenization across Earth observing systems is essential for ensuring consistency in geophysical retrievals over time and enabling the construction of long-term climate records. As the first SI Traceable Satellite (SITSat) for the reflected solar, the CLARREO Pathfinder (CPF) will provide high-accuracy spectrally resolved benchmark measurements of Earth-reflected solar radiation, serving as a standardized in-orbit reference for other reflected solar (RS) instruments. The CPF intercalibration team has developed a state-of-the-art method to intercalibrate the RS channels of the VIIRS instrument onboard the NOAA-20 satellite using CPF benchmark measurements, aiming for a methodology uncertainty of 0.3-0.6% (1-sigma). To achieve this stringent accuracy, the CPF team has devised strategies to mitigate the effects of spatial, spectral, polarization, and angular disparities between the intercalibration footprints of CPF and VIIRS. Despite nearly identical instrument designs, the three VIIRS instruments currently in operation onboard SNPP, NOAA-20, and NOAA-21 platforms exhibit systematic radiometric biases up to 8%. Although each VIIRS sensor’s calibration is independent and traceable to standards maintained by NIST, there is significant concern within the community about which VIIRS sensor most accurately represents the absolute radiometric scale. The precise intercalibration between CPF and NOAA-20 VIIRS will reveal the absolute radiometric accuracy of VIIRS. This accuracy can then be extended to other RS sensors, including MODIS and other VIIRS sensors, via vicarious methods. The 3-nm spectral sampling of CPF measurements will enable users to quantify scene-dependent spectral biases between sensors, thereby aiding in establishing both spectral and radiometric homogenization across these platforms. The CPF mission overview, along with details of its intercalibration capabilities and homogenization approaches, will be discussed at the meeting.

Raj Bhatt↗

NASA's CLARREO Pathfinder Mission: The Reflected Solar’s First SITSat

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder mission will take reflected solar (RS) highly accurate measurements needed to monitor Earth’s climate and will be the first RS SI-traceable Satellite Sensor (SITSat). The mission includes a RS spectrometer that will be installed on the International Space Station (ISS) and take measurements for at least one year. CLARREO Pathfinder (CPF) will use on-orbit calibration to achieve an unprecedented high accuracy with SI-traceability and the inter-calibration of other on-orbit instruments. The spectrometer is based on the HyperSpectral Imager for Climate Science (HySICS) instrument developed by the University of Colorado/Laboratory for Atmospheric and Space Physics of Boulder, CO, USA. HySICS is being designed to have a radiometric uncertainty of 0.3% (1-sigma), a five to ten times improvement over existing spaceflight RS instruments. High accuracy SI-traceable measurements such as these are critical to develop long-term climate-quality data sets. Additionally, by measuring spectral reflectance with high accuracy the CPF instrument will serve as an on-orbit intercalibration radiometric reference for operational Earth-viewing sensors, such as the Clouds and Earth’s Radiant Energy System (CERES) broadband shortwave instrument and the Visible/Infrared Imaging Radiometer Suite (VIIRS). Two-axis pointing, a spectral range from 350 nm to 2300 nm, and a spectral resolution ≤6 nm enable CPF to provide nearly coincident temporal, spatial, angular, and spectral matching of intercalibration targets, with sampling sufficient to reduce random errors. The intercalibration method will refine knowledge of target sensors’ effective offsets, gain, non-linearity, spectral response, and polarization sensitivity (as is relevant). Calibrated reflectance and reflected radiance spectra will be distributed to the scientific community through a NASA Distributed Active Archive Center (DAAC). We will present an overview of the CLARREO Pathfinder mission, its anticipated impact on monitoring climate variability, and the novel CPF direct intercalibration approach.

climate↗

Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap was undertaken preparatory to extending the 1979-2007 NASA Goddard Space Flight Center (GSFC) NASA Team algorithm time series of global sea ice extents and areas. The 1979- 2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in Northern Hemisphere sea ice extents is -0.0156%, with a standard deviation of the differences of 0.6204%, and the yearly mean difference in Northern Hemisphere sea ice areas is 0.5433%, with a standard deviation of 0.3519%. For the Southern Hemisphere, the yearly mean difference in sea ice extents is 0.0304% +/- 0.4880%, and the mean difference in sea ice areas is 0.1550% +/- 0.3753%. This F13/F17 intercalibration enables the extension of the 28-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available.

Cavalieri, Donald J.↗

Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap was undertaken preparatory to extending the 1979-2007 NASA Goddard Space Flight Center (GSFC) NASA Team algorithm time series of global sea ice extents and areas. The 1979- 2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in Northern Hemisphere sea ice extents is -0.0156%, with a standard deviation of the differences of 0.6204%, and the yearly mean difference in Northern Hemisphere sea ice areas is 0.5433%, with a standard deviation of 0.3519%. For the Southern Hemisphere, the yearly mean difference in sea ice extents is 0.0304% 0.4880%, and the mean difference in sea ice areas is 0.1550% 0.3753%. This F13/F17 intercalibration enables the extension of the 28-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available.

Cavalieri, Donald J.↗

Incorporating the TRMM Dataset into the GPM Mission Data Suite

In June 2015 the TRMM satellite came to its end. The 17 plus year of mission data that it provided has proven a valuable asset to a variety of science communities. This 17plus year data set does not, however, stagnate with the end of the mission itself. NASA/JAXA intend to integrate the TRMM data set into the data suite of the GPM mission. This will ensure the creation of a consistent, intercalibrated, accurate dataset within GPM that extends back to November of 1998. This paper describes the plans for incorporating the TRMM 17plus year data into the GPM data suite. These plans call for using GPM algorithms for both radiometer and radar to reprocess TRMM data as well as intercalibrating partner radiometers using GPM intercalibration techniques. This reprocessing will mean changes in content, logical format and physical format as well as improved geolocation, sensor corrections and retrieval techniques.

TRMM↗

ATLAS-1 and middle atmosphere global change

To understand the extent and trends of middle atmosphere change, it is necessary to establish the baseline of atmospheric behavior and its response to changes in solar irradiance over at least a solar cycle. An element in NASA's global change program is the ATLAS shuttle series. The international payload includes several instruments intended to make precise, absolute measurements of solar irradiance, each being calibrated before and after each shuttle flight. These instruments, in addition to obtaining an 11-year database, will also intercalibrate solar instruments on the Earth Radiation Budget (ERB) and Upper Atmosphere Research (UARS) satellites. Other instruments will measure the atmospheric composition and temperature, also intercalibrating instruments on Television and Infrared Observation Satellite (TIROS)-N and UARS. Some have flown on shuttle missions dating back to 1983 and it is hoped that the ATLAS series will provide a capability until the turn of the century. This paper reviews the early results of the ATLAS-1 mission, which flew between March 24 and April 2, 1992.

Torr, Marsha R.↗

HF radar signatures of the cusp and low-latitude boundary layer

Continuous ground-based observations of ionospheric and magnetospheric regions are critical to the Geospace Environmental Modeling (GEM) program. It is therefore important to establish clear intercalibrations between different ground-based instruments and satellites in order to clearly place the ground-based observations in context with the corresponding in situ satellite measurements. HF-radars operating at high latitudes are capable of observing very large spatial regions of the ionosphere on a nearly continuous basis. In this paper we report on an intercalibration study made using the Polar Anglo-American Conjugate Radar Experiment radars located at Goose Bay, Labrador, and Halley Station, Antarctica, and the Defense Meteorological Satellite Program (DMSP) satellites. The DMSP satellite data are used to provide clear identifications of the ionospheric cusp and the low-latitude boundary layer (LLBL). The radar data for eight cusp events and eight LLBL events have been examined in order to determine a radar signature of these ionospheric regions. This intercalibraion indicates that the cusp is always characterized by wide, complex Doppler power spectra, whereas the LLBL is usually found to have spectra dominated by a single component. The distribution of spectral widths in the cusp is of a generally Gaussian form with a peak at about 220 m/s. The distribution of spectral widths in the LLBL is more like an exponential distribution, with the peak of the distribution occurring at about 50 m/s. There are a few cases in the LLBL where the Doppler power spectra are strikingly similar to those observed in the cusp.

Baker, K. B.↗

Polar Hydra Data Analysis

The science activities are: 1) Hydra is still operating successfully on orbit. 2) A large amount of analysis and discovery has occurred with the Hydra ground data processing this past year. 3) Full interdetector calibration has been implemented and documented. This intercalibration was necessitated by the incorrect installation of bias resistors in the pre-acceleration stage to the electron channeltrons. This had the effect of making the counting efficiency for electrons energy dependent as well as channeltron specific. The nature of the error had no impact on the ion detection efficiency since they have a different bias arrangement. This intercalibration is so effective, that the electron and ion moment densities are routinely produced with a level of agreement better than 20%. 4) The data processing routinely removes glint in the sensors and produces public energy time spectrograms on the web overnight. 6) Routine, but more intensive computer processing codes are operational that determine for electrons and ions, the density, the flow vector, the pressure tensor and the heat flux by numerical integration. These codes use the magnetic field to sustain the quality of their output. To gain access to this high quality magnetic field within our data stream we have monitored Russell's web page for zero levels and timing files (since his data acquisition is not telemetry synchronous) and have a local reconstruction of B for our use. We have also detected a routine anomaly in the magnetometer data stream that we have documented to Chris Russell and developed an editing algorithm to intercept these "hits" and remove them from the geophysical analysis.

Scudder, J. D.↗