Search NASA⌕ Search

Engineering topics

Scarino, Benjamin

Publications and source records attributed to Scarino, Benjamin.

12 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Extreme Case of Spectral Band Difference Correction Between the OSIRIS-REX-NAVCAM2 and DSCOVR-EPIC Imagers

Earth-viewed images acquired during a recent asteroid intercept mission present a unique opportunity for radiometric calibration of visible imagers onboard a space exploration probe. Measurements from the CERES consistent DSCOVR-EPIC imager act as a reference in providing spatially, temporally, and angularly matched radiance values for deriving OSIRIS-REx-NavCam sensor calibration gains. The calibration is accomplished using an optimized all-sky tropical ocean ray-matching technique, which employs complex pixel remapping, navigation correction, and angular geometry consideration. Of critical consideration in this specific inter-calibration event is the extreme difference in spectral response function (SRF) width between the NavCam and EPIC imagers, which could cause a rather large bias. The NASA-LaRC SCIAMACHY based online spectral band adjustment factor (SBAF) calculation tool provides an empirical solution to such potential spectral-difference-induced biases through a high spectral- resolution hyper spectral convolution approach. The adjustments produced from this tool can effectively reduce the calibration gain bias of NavCam2 by nearly 6%, thereby adjusting the NavCam2 sensor to within 3.2% of its prelaunch calibration. These results highlight the capability of the SBAF tool to account for exceptionally disparate SRFs.

Scarino, Benjamin↗
NASA NTRS2018

Enhancements to the Open Access Spectral Band Adjustment Factor Online Calculation Tool for Visible Channels

With close to 40 years of satellite observations, from which, cloud, land-use, and aerosol parameters can be measured, inter-consistent calibrations are needed to normalize retrievals across satellite records. Various visible-sensor inter-calibration techniques have been developed that utilize radiometrically stable Earth targets, e.g., deep convective clouds and desert/polar ice pseudo-invariant calibration sites. Other equally effective, direct techniques for intercalibration between satellite imagers are simultaneous nadir overpass comparisons and ray-matched radiance pairs. Combining independent calibration results from such varied techniques yields robust calibration coefficients, and is a form of self-validation. One potential source of significant error when cross-calibrating satellite sensors, however, are the often small but substantial spectral discrepancies between comparable bands, which must be accounted for. As such, visible calibration methods rely on a Spectral Band Adjustment Factor (SBAF) to account for the spectral-response function- induced radiance differences between analogous imagers. The SBAF is unique to each calibration method as it is a function of the Earth-reflected spectra. In recent years, NASA Langley pioneered the use of SCIAMACHY-, GOME-2-, and Hyperion-retrieved Earth spectra to compute SBAFs. By carefully selecting hyperspectral footprints that best represent the conditions inherent to an inter-calibration technique, the uncertainty in the SBAF is greatly reduced. NASA Langley initially provided the Global Space-based Inter-calibration System processing and research centers with online SBAF tools, with which users select conditions to best match their calibration criteria. This article highlights expanded SBAF tool capabilities for visible wavelengths, with emphasis on the use of the spectral range filtering for the purpose of separating scene conditions for the channel that the SBAF is needed based on the reflectance values of other bands. In other words, spectral filtering will enable better scene-type selection for bands where scene determination is difficult without information from other channels, which should prove valuable to users in the calibration community.

Scarino, Benjamin↗
NASA NTRS2018

Cross-Calibration of AQUA-MODIS and NPP-VIIRS Reflective Solar Bands for a Seamless Record of CERES Cloud and Flux Properties

The CERES measured shortwave and longwave fluxes rely on the cloud properties derived using the coincident observations from the accompanying high-resolution MODIS and VIIRS imagers. The calibration consistency is required between MODIS and VIIRS radiances to ensure that the CERES provided cloud property retrievals are temporally consistent. This paper presents multiple approaches of cross-calibrating the spectrally comparable reflective solar bands (RSB) of Aqua-MODIS and NPP- VIIRS, and estimates the radiometric biases for individual band pair. The inter-comparison is performed between the Aqua-MODIS collection 6.1 level 1B and NPP-VIIRS Land PEATE V1 datasets. Radiometric biases up to 3% were estimated bet een the MODIS and VIIRS radiances for visible bands.

Bhatt, Rajendra↗
NASA NTRS2018

Geostationary Visible Imager Calibration for the CERES SYN1deg Edition 4 Product

The Clouds and the Earth’s Radiant Energy System (CERES) project relies on geostationary (GEO) imager derived TOA broadband fluxes and cloud properties to account for the regional diurnal fluctuations between the Terra and Aqua CERES and MODIS measurements. Anchoring the GEO visible calibration to the MODIS reference calibration and stability is critical for consistent fluxes and cloud retrievals across the 16 GEO imagers utilized in the CERES record. The CERES Edition 4A used GEO and MODIS ray-matched radiance pairs over all-sky tropical ocean (ATO-RM) to transfer the MODIS calibration to the GEO imagers. The primary GEO ATO-RM calibration was compared with the deep convective cloud (DCC) ray-matching and invariant desert/DCC target calibration methodologies, which are all tied to the same Aqua-MODIS calibration reference. Results indicate that most GEO record mean calibration method biases are within 1% with respect to ATO-RM. Most calibration method temporal trends were within 0.5% relative to ATO-RM. The monthly gain trend standard errors were mostly within 1% for all methods and GEOs. The close agreement amongst the independent calibration techniques validates all methodologies, and verifies that the coefficients are not artifacts of the methodology but rather adequately represent the true GEO visible imager degradation.

Doelling, David↗
NASA NTRS2017

Utilizing the Precessing Orbit of TRMM to Produce Hourly Corrections of Geostationary Infrared Imager Data with the VIRS Sensor

Accurate characterization of the Earth's radiant energy is critical for many climate monitoring and weather forecasting applications. For example, groups at the NASA Langley Research Center rely on stable visible- and infrared-channel calibrations in order to understand the temporal/spatial distribution of hazardous storms, as determined from an automated overshooting convective top detection algorithm. Therefore, in order to facilitate reliable, climate-quality retrievals, it is important that consistent calibration coefficients across satellite platforms are made available to the remote sensing community, and that calibration anomalies are recognized and mitigated. One such anomaly is the infrared imager brightness temperature (BT) drift that occurs for some Geostationary Earth Orbit satellite (GEOsat) instruments near local midnight. Currently the Global Space-Based Inter-Calibration System (GSICS) community uses the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) sensor as a common reference to uniformly calibrate GEOsat IR imagers. However, the combination of IASI, which has a 21:30 local equator crossing time (LECT), and hyperspectral Atmospheric Infrared Sounder (AIRS; 01:30 LECT) observations are unable to completely resolve the GEOsat midnight BT bias. The precessing orbit of the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS), however, allows sampling of all local hours every 46 days. Thus, VIRS has the capability to quantify the BT midnight effect observed in concurrent GEOsat imagers. First, the VIRS IR measurements are evaluated for long-term temporal stability between 2002 and 2012 by inter-calibrating with Aqua-MODIS. Second, the VIRS IR measurements are assessed for diurnal stability by inter-calibrating with Meteosat-9 (Met-9), a spin-stabilized GEOsat imager that does not manifest any diurnal dependency. In this case, the Met-9 IR imager is first adjusted with the official GSICS calibration coefficients. Then VIRS is used as a diurnal calibration reference transfer to produce hourly corrections of GEOsat IR imager BT. For the 9 three-axis stabilized GEO imagers concurrent with VIRS, the midnight effect increased the BT on average by 0.5 K (11 microns) and 0.4 K (12 microns), with a peak at approx.01:00 local time. As expected, the spin-stabilized GEOsats revealed a smaller diurnal temperature cycle (mostly < 0.2 K) with inconsistent peak hours.

Scarino, Benjamin↗
NASA NTRS2017

Characterizing Response Versus Scan-Angle for MODIS Reflective Solar Bands Using Deep Convective Clouds

MODIS consists of a cross-track, two-sided scan mirror, whose reflectance is not uniform but is a function of angle of incidence (AOI). This feature, known as response versusscan-angle (RVS), was characterized for all reflective solar bands of both MODIS instruments prior to launch. The RVS characteristic has changed on orbit, which must be tracked precisely over time to ensure the quality of MODIS products. The MODIS characterization support team utilizes the onboard calibrators and the earth view responses from multiple pseudo invariant desert sites to track the RVS changes at different AOIs. The drawback of using deserts is the assumption that these sites are radiometrically stable during the monitoring period. In addition, the 16-day orbit repeat cycle of MODIS allows for only a limited set of AOIs over a given desert. We propose a novel and robust approach of characterizing the MODIS RVS using tropical deep convective clouds (DCC). The method tracks the monthly DCC response at specified sets of AOIs to compute the temporal RVS changes. Initial results have shown that the Aqua-MODIS collection 6 band 1 level 1B radiances show considerable residual RVS dependencies, with long-term drifts up to 2.3 at certain AOIs.

Clouds↗
NASA NTRS2016

The Calibration of the DSCOVR EPIC Multiple Visible Channel Instrument Using MODIS and VIIRS as a Reference

The Deep Space Climate Observatory (DSCOVR), launched on 11 February 2015, is a satellite positioned near the Lagrange-1 (L1) point, carrying several instruments that monitor space weather, and Earth-view sensors designed for climate studies. The Earth Polychromatic Imaging Camera (EPIC) onboard DSCOVR continuously views the sun-illuminated portion of the Earth with spectral coverage in the UV, VIS, and NIR bands. Although the EPIC instrument does not have any onboard calibration abilities, its constant view of the sunlit Earth disk provides a unique opportunity for simultaneous viewing with several other satellite instruments. This arrangement allows the EPIC sensor to be inter-calibrated using other well-characterized satellite instrument reference standards. Two such instruments with onboard calibration are MODIS, flown on Aqua and Terra, and VIIRS, onboard Suomi-NPP. The MODIS and VIIRS reference calibrations will be transferred to the EPIC instrument using both all-sky ocean and deep convective clouds (DCC) ray-matched EPIC and MODIS/VIIRS radiance pairs. An automated navigation correction routine was developed to more accurately align the EPIC and MODIS/VIIRS granules. The automated navigation correction routine dramatically reduced the uncertainty of the resulting calibration gain based on the EPIC and MODIS/VIIRS radiance pairs. The SCIAMACHY-based spectral band adjustment factors (SBAF) applied to the MODIS/ VIIRS radiances were found to successfully adjust the reference radiances to the spectral response of the specific EPIC channel for over-lapping spectral channels. The SBAF was also found to be effective for the non-overlapping EPIC channel 10. Lastly, both ray-matching techniques found no discernable trends for EPIC channel 7 over the year of publically released EPIC data.

Haney, Conor↗
NASA NTRS2016

An Assessment of New Satellite Data Products for the Development of a Long-Term Global Solar Resource at 10-100 km

A project representing an effort to reprocess the NASA based solar resource data sets is reviewed. The effort represented a collaboration between NASA, NOAA, NREL and the SUNY-Albany and aimed to deliver a 10 km resolution, 3-hourly data set spanning from 1983 through near-present. Part of the project was to transition project capability to NREL for annual processing to extend data set. Due to delays in the key input project called ISCCP, we evaluate only Beta versions of this data set and also introduce the potential use of another NASA Langley based cloud data set for the CERES project. The CERES project uses these cloud properties to compute global top-of-atmosphere and surface fluxes at the 1x1 degree resolution. Here, we also briefly discuss these data sets in potential usage for solar resource benchmarking.

Stackhouse, Paul W., Jr.↗
NASA NTRS2014

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-­‐real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-­‐real time globally from both geostationary (GEO) and low-­‐earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

Minnis, Patrick↗
NASA NTRS2014

Calibrating Historical IR Sensors Using GEO, and AVHRR Infrared Tropical Mean Calibration Models

Long-term, remote-sensing-based climate data records (CDRs) are highly dependent on having consistent, wellcalibrated satellite instrument measurements of the Earth's radiant energy. Therefore, by making historical satellite calibrations consistent with those of today's imagers, the Earth-observing community can benefit from a CDR that spans a minimum of 30 years. Most operational meteorological satellites rely on an onboard blackbody and space looks to provide on-orbit IR calibration, but neither target is traceable to absolute standards. The IR channels can also be affected by ice on the detector window, angle dependency of the scan mirror emissivity, stray-light, and detector-to-detector striping. Being able to quantify and correct such degradations would mean IR data from any satellite imager could contribute to a CDR. Recent efforts have focused on utilizing well-calibrated modern hyper-spectral sensors to intercalibrate concurrent operational IR imagers to a single reference. In order to consistently calibrate both historical and current IR imagers to the same reference, however, another strategy is needed. Large, well-characterized tropical-domain Earth targets have the potential of providing an Earth-view reference accuracy of within 0.5 K. To that effort, NASA Langley is developing an IR tropical mean calibration model in order to calibrate historical Advanced Very High Resolution Radiometer (AVHRR) instruments. Using Meteosat-9 (Met-9) as a reference, empirical models are built based on spatially/temporally binned Met-9 and AVHRR tropical IR brightness temperatures. By demonstrating the stability of the Met-9 tropical models, NOAA-18 AVHRR can be calibrated to Met-9 by matching the AVHRR monthly histogram averages with the Met-9 model. This method is validated with ray-matched AVHRR and Met-9 biasdifference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and thereby establish a climate-quality IR data record.

Scarino, Benjamin↗