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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

NOAA-L

The National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) have jointly developed a valuable series of polar-orbiting Earth environmental observation satellites since 1978. These satellites provide global data to NOAA's short- and long-range weather forecasting systems. The system consists of two polar-orbiting satellites known as the Advanced Television Infrared Observation Satellites (TIROS-N) (ATN). Operating as a pair, these satellites ensure that environmental data, for any region of the Earth, is no more than six hours old. These polar-orbiting satellites have not only provided cost-effective data for very immediate and real needs but also for extensive climate and research programs. The weather data (including images seen on television news programs) has afforded both convenience and safety to viewers throughout the world. The satellites also support the SARSAT (Search and Rescue Satellite Aided Tracking) part of the COSPAS-SARSAT constellation. Russia provides the COSPAS (Russian for Space Systems for the Search of Vessels in Distress) satellites. The international COSPAS-SARSAT system provides for the detection and location of emergency beacons for ships, aircraft, and people in distress and has contributed to the saving of more than 10,000 lives since its inception in 1982.

McCain, Harry G.↗
NASA NTRS1995

An Analysis of the NOAA Satellite-Derived Snow-Cover Record, 1972 - Present

The large-scale distribution of snow cover over northern hemisphere lands has been a topic of increasing attention in recent years. This interest has been spurred, at least in part, by concerns associated with potential changes in the global climate system associated with anthropogenic and natural causes. Satellite observations using visible satellite imagery permit a hemispheric analysis of snow extent. For almost three decades the National Oceanic and Atmospheric Administration (NOAA) has been using visible imagery to produce weekly charts depicting the extent of snow cover over northern hemisphere lands. These charts constitute the longest satellite-derived environmental dataset available on a continuous basis and produced in a consistent manner. We will briefly describe the NOAA charts and then provide an update on the variability of snow extent over the hemisphere from January 1972 through August 1995. Concentration will be on snow kinematics.

Robinson, David A.↗
NASA NTRS1999

The NOAA-9 Earth Radiation Budget Experiment Wide Field-of-View Data Set

The Earth Radiation Budget Experiment (ERBE) consisted of wide field-of-view (WFOV) radiometers and scanning radiometers for measuring outgoing longwave radiation and solar radiation reflected from the Earth. These instruments were carried by the dedicated Earth Radiation Budget Satellite (ERBS) and by the NOAA-9 and -10 operational spacecraft. The WFOV radiometers provided data from which instantaneous fluxes at the top of the atmosphere (TOA) are computed by use of a numerical filter algorithm. Monthly mean fluxes over a 5-degree equal angle grid are computed from the instantaneous TOA fluxes. The WFOV radiometers aboard the NOAA-9 spacecraft operated from February 1985 through December 1992, at which time a failure of the shortwave radiometer ended the usable data after nearly 8 years. This paper examines the monthly mean products from that data set.

Bush, Kathryn A.↗
NASA NTRS2004

Decision Support Tool Evaluation Report for General NOAA Oil Modeling Environment(GNOME) Version 2.0

NASA's Earth Science Applications Directorate evaluated the potential of NASA remote sensing data and modeling products to enhance the General NOAA Oil Modeling Environment (GNOME) decision support tool. NOAA's Office of Response and Restoration (OR&R) Hazardous Materials (HAZMAT) Response Division is interested in enhancing GNOME with near-realtime (NRT) NASA remote sensing products on oceanic winds and ocean circulation. The NASA SeaWinds sea surface wind and Jason-1 sea surface height NRT products have potential, as do sea surface temperature and reflectance products from the Moderate Resolution Imaging Spectroradiometer and sea surface reflectance products from Landsat and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer. HAZMAT is also interested in the Advanced Circulation model and the Ocean General Circulation Model. Certain issues must be considered, including lack of data continuity, marginal data redundancy, and data formatting problems. Spatial resolution is an issue for near-shore GNOME applications. Additional work will be needed to incorporate NASA inputs into GNOME, including verification and validation of data products, algorithms, models, and NRT data.

Spruce, Joseph P.↗
NASA NTRS2007

The Calibration of AVHRR Visible Dual Gain using Meteosat-8 for NOAA-16 to 18

The NOAA AVHRR program has given the remote sensing community over 25 years of imager radiances to retrieve global cloud, vegetation, and aerosol properties. This dataset can be used for long-term climate research, if the AVHRR instrument is well calibrated. Unfortunately, the AVHRR instrument does not have onboard visible calibration and does degrade over time. Vicarious post-launch calibration is necessary to obtain cloud properties that are not biased over time. The recent AVHRR-3 instrument has a dual gain in the visible channels in order to achieve greater radiance resolution in the clear-sky. This has made vicarious calibration of the AVHRR-3 more difficult to unravel. Reference satellite radiances from well-calibrated instruments, usually equipped with solar diffusers, such as MODIS, have been used to successfully vicariously calibrate other visible instruments. Transfer of calibration from one satellite to another using co-angled, collocated, coincident radiances has been well validated. Terra or Aqua MODIS and AVHRR comparisons can only be performed over the poles during summer. However, geostationary satellites offer a transfer medium that captures both parts of the dual gain. This AVHRR-3 calibration strategy uses, calibrated with MODIS, Meteosat-8 radiances simultaneously to determine the dual gains using 50km regions. The dual gain coefficients will be compared with the nominal coefficients. Results will be shown for all visible channels for NOAA-17.

Doelling, David R.↗
NASA NTRS2016

A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits: Validation - Part 2

Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target-modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2 percent and 3 percent for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions. The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1 percent for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1 percent and 2 percent for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

Doelling, David R.↗
NASA NTRS2018

Lidar Validation Measurements at the NOAA Mauna Loa Observatory NDACC Station

NASA's Goddard Space Flight Center (GSFC) transported two lidar instruments to the NOAA facility at the Mauna Loa Observatory (MLO) on the Big Island of Hawaii, to participate in an official, extended validation campaign. This site is situated 11,141 ft. above sea level on the side of the mountain. The observatory has been making atmospheric measurements regularly since the 1950's, and has hosted the GSFC Stratospheric Ozone (STROZ) Lidar and the GSFC Aerosol and Temperature (AT) Lidar on several occasions, most recently between November, 2012 and November, 2015. The purpose of this extended deployment was to participate in Network for the Detection of Atmospheric Composition Change (NDACC) Validation campaigns with the JPL Stratospheric Ozone Lidar and the NOAA Temperature, Aerosol and Water Vapor instruments as part of the routine NDACC Validation Protocol.

Lidar↗
NASA NTRS2018

Geonex: A NASA-NOAA Collaboration for Producing Land Surface Products from Geostationary Sensors Using Cloud Computing

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement.Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. We estimate the cost of deploying GEONEX to be $400 - 750 a month for processing data (every 30 minutes) and producing products over the conterminous US. For products such as Fire, latency can be as little as 10 minutes from the time of data acquisition.

Geostationary↗
NASA NTRS2018

GEONEX: Webpage to Display NASA-NOAA Collaboration of Producing Land Surface Products from Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement.In order to better introduce the GEONEX products to the science community, we set up a simple webpage (www.geonex.org) to describe the background and the motivation of the project, the algorithms used in deriving the products, and user manuals to the data files. We will also update the status of the data processing, in particular the near-real-time products, on the website and provide links (in text or json files) to the latest datasets.

geostationary↗
NASA NTRS2018

NOAA-20 VIIRS Thermal Emissive Bands On-Orbit Performance

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument onboard the NOAA-20 satellite (launched on November 18, 2017) started to collect Earth-view data after its nadir door opened on December 13, 2017. Seven of the VIIRS bands, I4-5 and M12-16 are thermal emissive bands (TEBs), covering a spectral range from 3.6 to 12.5 meters. They began collecting valid data after the cold focal plane assembly (CFPA) cooled down to its nominal operating temperature on January 6, 2018. This paper will present the performance of each TEB, including calibration coefficients, noise equivalent differential temperature (NEdT), on-orbit calibration coefficient estimates from scheduled onboard blackbody warm-up and cool-down (WUCD) data, as well as related telemetry temperatures. Several methods are tested and compared in the WUCD data analysis for estimating the calibration coefficients. Based on the preliminary results, the NEdT of each band is well below the design specification and very close to that of the VIIRS onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The detector gains appear stable for bands on the short- and mid-wave infrared CFPA, whereas the detector gains have larger than expected degradation for bands on the long-wave infrared CFPA during the early mission. All TEB-related telemetry temperatures are stable. The on-orbit performance of NOAA-20 VIIRS TEB is compared with VIIRS onboard the SNPP.

Thermal Emissive Bands (TEB)↗
NASA NTRS2018

Initial Investigation of the Angular Dependence of the NOAA-20 VIIRS Solar Diffuser BRDF Change Factor

The NOAA-20 (formerly the Joint Polar Satellite System-1) satellite was launched on November 18, 2017. One of the five scientific instruments aboard the NOAA-20 satellite (N20) is the Visible Infrared Imaging Radiometer Suite (VIIRS). The VIIRS scans the earth surface in 22 spectral bands, of which 14 are denoted as the reflective solar bands (RSBs) with design band central wavelengths from 412 to 2250 nm. The VIIRS regularly performs on-orbit radiometric calibration of its RSBs, primarily through observations of an onboard sunlit solar diffuser (SD). The on-orbit change of the SD bidirectional reflectance distribution function (BRDF) value, denoted as the H-factor, is determined by an onboard solar diffuser stability monitor (SDSM). We have shown that the H-factor for the SD on the VIIRS instrument on the Suomi National Polar-orbiting Partnership (SNPP) satellite is both incident and outgoing sunlight direction dependent. This angular dependence profoundly affects the on-orbit radiometric calibration process and results. Here, we give preliminary results for the angular dependence for the N20 VIIRS SD H-factor, and compare the dependence with that for the SNPP VIIRS.

radiometric calibration↗
NASA NTRS2019

Early Calibration and Performance Assessments of NOAA-20 VIIRS Thermal Emissive Bands

The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the NOAA-20 (previously JPSS-1) spacecraft has successfully operated since its launch in November, 2017. Similar to the first VIIRS instrument on the Suomi-NPP spacecraft, data is collected in 22 spectral bands that are calibrated by a set of onboard calibrators. This paper provides an overview of the NOAA-20 VIIRS on-orbit operation and calibration, with a particular focus on the thermal emissive bands (TEBs). Results presented in this paper include the on-orbit changes in the TEB spectral band responses, detector noise characterization, and key calibration parameters, such as the non-linear coefficients derived from the blackbody warm-up cool-down cycle. Other issues, such as the early mission long-wave infrared (LWIR) response degradation due to icing on the dewar window, and their impact on sensor calibration are also discussed. Since launch, the VIIRS instrument temperature has been stable to within ± 0.8K and the cold focal plane temperatures are well controlled with variations less than 40 mK. With the exception of the early degradation observed in the LWIR bands, the TEB gains have been stable to within 0.04% (except I5 at 0.07%). Based on the current performance, VIIRS is expected to meet its calibration requirements throughout its design lifetime.

NEdT↗
NASA NTRS2019

Early Calibration and Performance Assessments of NOAA-20 VIIRS Thermal Emissive Bands

The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the NOAA-20 (previously JPSS-1) spacecraft has successfully operated since its launch in November, 2017. Similar to the rst VIIRS instrument on the Suomi-National Polar-orbiting Partnership (SNPP) spacecraft, the data are collected in 22 spectral bands that are calibrated by a set of onboard calibrators. This paper provides an overview of the NOAA-20 VIIRS on-orbit operation and calibration, with a particular focus on the thermal emissive bands (TEBs). The results presented in this paper include the on-orbit changes in the TEB spectral band responses, detector noise characterization, and key calibration parameters, such as the nonlinear coefcients derived from the blackbody warm-up cool-down cycles. Other issues, such as the early mission long-wave infrared (LWIR) response degradation due to icing on the dewar window, and their impact on sensor calibration are also discussed. Since launch, the VIIRS instrument temperature has been stable to within ±0.8 K and the cold focal plane temperatures are well controlled with variations less than 40 mK. With the exception of the early degradation observed in the LWIR bands, the TEB gains have been stable to within 0.04% (except I5 at 0.07%). Based on the current performance, VIIRS is expected to meet its calibration requirements throughout its design lifetime.

noise equivalent 25 differential temperature (NEdT↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with a high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of the atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRS2021

NOAA-20 VIIRS Reflective Solar bands on-Orbit Calibration Using a Hybrid Approach

The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) has been in orbit for more than two and a half years. VIIRS has 22 bands, among which 14 are reflective solar bands (RSBs) covering a spectral range from 0.41 to 2.25 μm. The RSBs are calibrated on-orbit using an onboard solar diffuser (SD), on-orbit degradation of which is tracked by an onboard SD stability monitor (SDSM). NOAA-20 VIIRS is also scheduled to view the Moon approximately monthly and the lunar observations are used to track the RSB on-orbit changes as well. Both SD and lunar calibration results for the RSBs are shown and it is demonstrated that the two sets of the calibration coefficients diverge with time, especially at short wavelengths. The divergence is due to the non-uniformity of the SD degradation, which results in a long-term bias in the calibration coefficients derived from the SD calibration. A hybrid method, which properly combines the SD and lunar calibration results, is applied to generate the RSB calibration coefficients as has been done for SNPP VIIRS RSBs. The hybrid results have both the accuracy and frequency and ensure the high quality of the VIIRS sensor data records (SDR).

Calibration↗
NASA NTRS2021

Crosstalk Effect in NOAA 20 VIIRS Thermal Emissive Bands

Crosstalk contamination in the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal emissive bands (TEBs) has been a known issue since prelaunch, that has amplified on-orbit for some of bands. A linear algorithm has been developed and successfully applied to mitigate the crosstalk effect and restore the quality and accuracy of the MODIS L1B products. Significant crosstalk effect has also been found and characterized in TEBs of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP). NOAA-20 VIIRS, a follow-on instrument to SNPP VIIRS, was launched on November 18, 2017. In this report, it is shown that there are nonnegligible crosstalk contaminations among the TEBs of NOAA-20 VIIRS as well. They are characterized using the scheduled lunar observations and compared with those in SNPP VIIRS.

Calibration↗
NASA NTRS2021

Quantifying Uncertainties in Nighttime Light Retrievals From Suomi-NPP and NOAA-20 VIIRS Day/Night Band Data

Satellite observations of nighttime lights (NTL) from Suomi-NPP and NOAA-20 VIIRS Day/Night Band data have been widely used to estimate human activities. Long-term changes such as urban development and abrupt short-term changes such as power outages have been monitored from temporal NTL acquired by satellites. While high temporal NTL variation has been found across NTL data of varying temporal scale (e.g., daily, monthly, and annual composites), the sources of measurement error and uncertainty are poorly understood. This paper quantifies the sources of VIIRS-derived NTL uncertainty due to view-illumination geometry, surface Bidirectional Reflectance Distribution Function (BRDF)/albedo, and the effects of snow cover, lunar irradiance, aerosol loading, cloud mask, vegetation, geometry, and ephemeral artifacts (e.g., the Aurora Borealis). Based on this current assessment of NASA Black Marble retrievals (VNP46, Collection V001), we found that angular and atmospheric effects dominate retrieval uncertainty. Errors introduced by upstream data inputs (e.g., a coarser nighttime snow cover flag and misclassification errors in the existing VIIRS nighttime cloud mask) were also found to impact retrieval quality. Despite these challenges, a consistent daily NTL time series record can be routinely generated from top-of-atmosphere VNP46 radiances. Key recommendations include: (1) the use of lunar-BRDF adjusted and atmospherically corrected NTL (i.e., as identified as high-quality retrievals in the VNP46 QA fields), (2) development and improvement to the VIIRS snow cover and cloud masks algorithms to accurately reflect NTL retrieval conditions, (3) characterizing seasonal variations in NTL due to vegetation and snow, (4) reducing geometric effects due to the spatial mismatch of gridded pixel and observation footprint, (5) employing angularly-consistent NTL observations from multiple VIIRS instruments (i.e., Suomi-NPP and NOAA-20) to reduce pixel-based uncertainties and address persistent data gaps, and (6) being mindful of surface-reflected radiance from aurora events at mid-to-high latitudes.

Zhuosen Wang↗