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NASA NTRS2015

A Prototype Hail Detection Algorithm and Hail Climatology Developed with the Advanced Microwave Sounding Unit (AMSU)

In previous studies published in the open literature, a strong relationship between the occurrence of hail and the microwave brightness temperatures (primarily at 37 and 85 GHz) was documented. These studies were performed with the Nimbus‐7 SMMR, the TRMM Microwave Imager (TMI) and most recently, the Aqua AMSR‐E sensor. This lead to climatologies of hail frequency from TMI and AMSR‐E, however, limitations include geographical domain of the TMI sensor (35 S to 35 N) and the overpass time of the Aqua satellite (130 am/pm local time), both of which reduce an accurate mapping of hail events over the global domain and the full diurnal cycle. Nonetheless, these studies presented exciting, new applications for passive microwave sensors. Since 1998, NOAA and EUMETSAT have been operating the AMSU‐A/B and the MHS on several operational satellites: NOAA‐15 through NOAA‐19; MetOp‐A and ‐B. With multiple satellites in operation since 2000, the AMSU/MHS sensors provide near global coverage every 4 hours, thus, offering a much larger time and temporal sampling than TRMM or AMSR‐E. With similar observation frequencies near 30 and 85 GHz and additionally three at the 183 GHz water vapor band, the potential to detect strong convection associated with severe storms on a more comprehensive time and space scale exists. In this study, we develop a prototype AMSU‐based hail detection algorithm through the use of collocated satellite and surface hail reports over the continental U.S. for a 12‐year period (2000‐2011). Compared with the surface observations, the algorithm detects approximately 40 percent of hail occurrences. The simple threshold algorithm is then used to generate a hail climatology that is based on all available AMSU observations during 2000‐11 that is stratified in several ways, including total hail occurrence by month (March through September), total annual, and over the diurnal cycle. Independent comparisons are made compared to similar data sets derived from other satellite, ground radar and surface reports. The algorithm was also applied to global land measurements for a single year and showed close agreement with other satellite based hail climatologies. Such a product could serve as a prototype for use with a future geostationary based microwave sensor such as NASA's proposed PATH mission.

Ferraro, Ralph↗

NASA NTRS2015

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the MODIS sensor aboard the NASA Aqua satellite. Aqua was chosen due to an afternoon orbit over the United States when land surface temperatures are relatively warm and improve the contrast between damaged and undamaged areas. This orbit is also similar to the orbit of the Suomi-National Polar-orbiting Partnership (NPP) satellite. The Suomi NPP satellite hosts the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which is the next generation of a MODIS-like sensor in polar orbit.

MODIS VIIRS↗

NASA NTRS2015

Assessment of MODIS and VIIRS Solar Diffuser On-Orbit Degradation

Both MODIS and VIIRS instruments use a solar diffuser (SD) for their reflective solar bands (RSB) on-orbit calibration. On-orbit changes in SD bi-directional reflectance factor (BRF) are tracked by a solar diffuser stability monitor (SDSM) using its alternate measurements of the sunlight reflected off the SD panel and direct sunlight through a fixed attenuation screen. The SDSM calibration data are collected by a number of filtered detectors, covering wavelengths from 0.41 to 0.94 micrometers. In this paper we describe briefly the Terra and Aqua MODIS and S-NPP VIIRS SDSM on-orbit operation and calibration activities and strategies, provide an overall assessment of their SDSM on-orbit performance, including wavelength-dependent changes in the SDSM detector responses and changes in their SD BRF, and discuss remaining challenging issues and their potential impact on RSB calibration quality. Due to different launch dates, operating configurations, and calibration frequencies, the Terra and Aqua MODIS and S-NPP VIIRS SD have experienced different amount of SD degradation. However, in general the shorter the wavelength, the larger is the SD on-orbit degradation. On the other hand, the larger changes in SDSM detector responses are observed at longer wavelengths in the near infrared (NIR).

MODIS↗

NASA NTRS2015

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (MODIS) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from Aqua using the CERES-MODIS Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for Aqua). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-MODIS Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-MODIS Edition-2 results.

Sun-Mack, Sunny↗

NASA NTRS2016

The NASA Applied Sciences Program: Volcanic Ash Observations and Applications

Since 2000, the NASA Applied Sciences Program has been actively transitioning observations and research to operations. Particular success has been achieved in developing applications for NASA Earth Observing Satellite (EOS) sensors, integrated observing systems, and operational models for volcanic ash detection, characterization, and transport. These include imager applications for sensors such as the MODerate resolution Imaging SpectroRadiometer (MODIS) on NASA Terra and Aqua satellites, and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NASA/NOAA Suomi NPP satellite; sounder applications for sensors such as the Atmospheric Infrared Sounder (AIRS) on Aqua, and the Cross-track Infrared Sounder (CrIS) on Suomi NPP; UV applications for the Ozone Mapping Instrument (OMI) on the NASA Aura Satellite and the Ozone Mapping Profiler Suite (OMPS) on Suomi NPP including Direct readout capabilities from OMI and OMPS in Alaska (GINA) and Finland (FMI):; and lidar applications from the Caliop instrument coupled with the imaging IR sensor on the NASA/CNES CALIPSO satellite. Many of these applications are in the process of being transferred to the Washington and Alaska Volcanic Ash Advisory Centers (VAAC) where they support operational monitoring and advisory services. Some have also been accepted, transitioned and adapted for direct, onboard, automated product production in future U.S. operational satellite systems including GOES-R, and in automated volcanic cloud detection, characterization and alerting tools at the VAACs. While other observations and applications remain to be developed for the current constellation of NASA EOS sensors and integrated with observing and forecast systems, future requirements and capabilities for volcanic ash observations and applications are also being developed. Many of these are based on technologies currently being tested on NASA aircraft, Unmanned Aerial Systems (UAS) and balloons. All of these efforts and the potential advances that will be realized by integrating them are shared in this presentation.

Murray, John J.↗

NASA NTRS2016

Alternative Method of On-Orbit Response-Versus-Scan-Angle Characterization for MODIS Reflective Solar Bands

The moderate resolution imaging spectroradiometer (MODIS) has 20 reflective solar bands (RSB), covering a spectral range from 0.41 to 2.2 microns, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the reflectance of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's reflectance over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and Aqua MODIS. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the MODIS characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard responses are fit first as a function of AOI before fitting temporally in order to eliminate the dependence on the stability of the desert site. Comprehensive comparisons are performed with current C6 RVS results for both Terra and Aqua MODIS. Results demonstrate that this alternative method provides a supplemental means to monitor the on-orbit RVS for MODIS RSB.

solar bands↗

NASA NTRS2015

Next-Generation Angular Distribution Models for Top-of-Atmosphere Radiative Flux Calculation from CERES Instruments: Validation

Radiative fluxes at the top of the atmosphere (TOA) from the Clouds and the Earth's Radiant Energy System (CERES) instrument are fundamental variables for understanding the Earth's energy balance and how it changes with time. TOA radiative fluxes are derived from the CERES radiance measurements using empirical angular distribution models (ADMs). This paper evaluates the accuracy of CERES TOA fluxes using direct integration and flux consistency tests. Direct integration tests show that the overall bias in regional monthly mean TOA shortwave (SW) flux is less than 0.2Wm(exp -2) and the RMSE is less than 1.1Wm(exp -2). The bias and RMSE are very similar between Terra and Aqua. The bias in regional monthly mean TOA LW fluxes is less than 0.5Wm(exp -2) and the RMSE is less than 0.8Wm(exp -)2 for both Terra and Aqua. The accuracy of the TOA instantaneous flux is assessed by performing tests using fluxes inverted from nadir- and oblique-viewing angles using CERES along-track observations and temporally and spatially matched MODIS observations, and using fluxes inverted from multi-angle MISR observations. The averaged TOA instantaneous SW flux uncertainties from these two tests are about 2.3% (1.9Wm(exp -2) over clear ocean, 1.6% (4.5Wm(exp -2) over clear land, and 2.0% (6.0Wm(exp -) over clear snow/ice; and are about 3.3% (9.0Wm(exp -2), 2.7% (8.4Wm(exp -2), and 3.7% (9.9Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA SW flux uncertainties are generally larger for thin broken clouds than for moderate and thick overcast clouds. The TOA instantaneous daytime LW flux uncertainties derived from the CERESMODIS test are 0.5% (1.5Wm(exp -2), 0.8% (2.4Wm(exp -2), and 0.7% (1.3Wm(exp -2) over clear ocean, land, and snow/ice; and are about 1.5% (3.5Wm(exp -2), 1.0% (2.9Wm(exp -2), and 1.1% (2.1Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA instantaneous nighttime LW flux uncertainties are about 0.5-1% (<2.0Wm(exp -2) for all surface types. Flux uncertainties caused by errors in scene identification are also assessed by using the collocated CALIPSO, CloudSat, CERES and MODIS data product. Errors in scene identification tend to underestimate TOA SW flux by about 0.6Wm(exp -2) and overestimate TOA daytime (nighttime) LW flux by 0.4 (0.2)Wm(exp -2) when all CERES viewing angles are considered.

Su, W.↗

NASA NTRS2013

Geostationary Enhanced Temporal Interpolation for CERES Flux Products

The Clouds and the Earth's Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth's top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1 deg latitude x 1 deg longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m(sub -2) over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

Doelling, David R.↗

NASA NTRS2016

Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for product intercomparisons, spatial aggregations may be used. It was found that if per-grid-cell differences on the order of 10(in LSR or NDVI) are tolerated, the product intercomparisons are expected to be immune from differences in spatial sampling.

VIIRS↗

NASA NTRS2016

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

The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the performance of the SD over time, provides the absolute reference for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the zero input radiance, respectively. The MODIS instrument views the Earth's surface through a two-sided scan mirror, whose reflectance is a function of angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different assigned RVS positions. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent in the left side Earth-view scans.

Bhatt, Rajendra↗

NASA NTRS2016

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

The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the performance of the SD over time, provides the absolute reference for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the zero input radiance, respectively. The MODIS instrument views the Earths surface through a two-sided scan mirror, whose reflectance is a function of angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different assigned RVS positions. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent in the left side Earth-view scans.

Bhatt, Rajendra↗

NASA NTRS2017

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, a polar orbiting Earth remote sensing instrument built using a strong MODIS background, employs a similarly designed on-board calibrating source - a V-grooved blackbody for the thermal emissive bands (TEB). The central wavelengths of most VIIRS TEBs are very close to those of MODIS with the exception of the 10.7 micron channel. To ensure the long term continuity of climate data records derived using VIIRS and MODIS TEB, it is necessary to assess any systematic differences between the two instruments, including scenes with temperatures significantly lower than blackbody operating temperatures at approximately 290 K. Previous work performed by the MODIS Characterization Support Team (MCST) at NASAGSFC used the frequent observations of the Dome Concordia site located in Antarctica to evaluate the calibration stability and consistency of Terra and Aqua MODIS over the mission lifetime. The near-surface temperature measurements from an automatic weather station (AWS) provide a direct reference useful for tracking the stability and determining the relative bias between the two MODIS instruments. In this study, the same technique is applied to the VIIRS TEB and the results are compared with those from the matched MODIS TEB. The results of this study show a small negative bias when comparing the matching VIIRS and Aqua MODIS TEB, implying a higher scene temperature retrieval for S-VIIRS at the cold end. Statistically no significant drift is observed for VIIRS TEB performance over the first 3.5 years of the mission.

Madhavan, Sriharsha↗

NASA NTRS2016

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations: 2. Retrieval Evaluation

An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (tau) and effective radius (r(sub eff)) retrievals perform best for ice clouds having 0.5 < tau< 7 and r(sub eff) < 50microns. For global ice clouds, the averaged retrieval uncertainties of tau and r(sub eff) are 19% and 33%, respectively. For optically thick ice clouds with tau larger than 10, however, the tau and r(sub eff) retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48km. Relatively large h uncertainty (e.g., > 1km) occurs for tau < 0.5. Analysis of 1month of the OE-IR retrievals shows large tau and r(sub eff) uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent tau and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 r(sub eff) are found.

cloud optics↗

NASA NTRS2016

MODIS Solar Diffuser On-Orbit Degradation Characterization Using Improved SDSM Screen Modeling

The Solar Diffuser (SD) is used for the MODIS reflective solar bands (RSB) calibration. An on-board Solar Diffuser Stability Monitor (SDSM) tracks the degradation of its on-orbit bi-directional reflectance factor (BRF). To best match the SDSM detector signals from its Sun view and SD view, a fixed attenuation screen is placed in its Sun view path, where the responses show ripples up to 10%, much larger than design expectation. Algorithms have been developed since the mission beginning to mitigate the impacts of these ripples. In recent years, a look-up-table (LUT) based approach has been implemented to account for these ripples. The LUT modeling of the elevation and azimuth angles is constructed from the detector 9 (D9) of SDSM observations in the MODIS early mission. The response of other detectors is normalized to D9 to reduce the ripples observed in the sun-view data. The accuracy of all detectors degradation estimation depends on how well the D9 approximated. After multiple years of operation (Terra: 16 years; Aqua: 14 years), degradation behavior of all detectors can be monitored by their own. This paper revisits the LUT modeling and proposes a dynamic scheme to build a LUT independently for each detector. Further refinement in the Sun view screen characterization will be highlighted to ensure the degradation estimation accuracy. Results of both Terra and Aqua SD on-orbit degradation are derived from the improved modeling and curve fitting strategy.

Chen, H.↗

NASA NTRS2016

Scheduling Observations of Celestial Objects for Earth Observing Sensor Calibration

Radiometric calibration of Earth-observing satellite sensors is critical for tracking on-orbit gain changes through- out the satellite's mission. The Moon, being a stable, well-characterized radiometric target, has been used effectively for tracking the relative gain changes of the reflective solar bands for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board EOS AM-1 (Terra) and PM-1 (Aqua). The Moon is viewed through the MODIS space-view port, and the relative phase of the Moon is restricted to within 0.5 degrees of a chosen target phase to increase the accuracy of the calibration. These geometric restrictions require spacecraft maneuvers in order to bring space-view port into proper alignment with the position of the Moon when the phase requirement is met. In this paper, we describe a versatile tool for scheduling such maneuvers based on the required geometry and lunar phase restrictions for a general spacecraft bound instrument. The results of the scheduling tool have been verified using lunar images from Aqua and Terra MODIS after a scheduled roll maneuver was performed. This tool has also been tested for the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Advanced Technology Microwave Sounder on-board the Suomi-NPP spacecraft. As an extension of this work, we have also developed a tool for scheduling views of bright stars. These stars provide another well-characterized radiometric source that can be used for sensor calibration. This tool has been implemented to determine the times in which a chosen star can be viewed by the high gain stages of the day/night band for the VIIRS instrument.

Wilson, Truman↗

NASA NTRS2017

Filter Tuning Using the Chi-Squared Statistic

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) performs orbit determination (OD) for the Aqua and Aura satellites. Both satellites are located in low Earth orbit (LEO), and are part of what is considered the A-Train satellite constellation. Both spacecraft are currently in the science phase of their respective missions. The FDF has recently been tasked with delivering definitive covariance for each satellite.The main source of orbit determination used for these missions is the Orbit Determination Toolkit developed by Analytical Graphics Inc. (AGI). This software uses an Extended Kalman Filter (EKF) to estimate the states of both spacecraft. The filter incorporates force modelling, ground station and space network measurements to determine spacecraft states. It also generates a covariance at each measurement. This covariance can be useful for evaluating the overall performance of the tracking data measurements and the filter itself. An accurate covariance is also useful for covariance propagation which is utilized in collision avoidance operations. It is also valuable when attempting to determine if the current orbital solution will meet mission requirements in the future.This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The Chi-square statistic is calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance.For the EKF to correctly calculate the covariance, error models associated with tracking data measurements must be accurately tuned. Over estimating or under estimating these error values can have detrimental effects on the overall filter performance. The filter incorporates ground station measurements, which can be tuned based on the accuracy of the individual ground stations. It also includes measurements from the NASA space network (SN), which can be affected by the assumed accuracy of the TDRS satellite state at the time of the measurement.The force modelling in the EKF is also an important factor that affects the propagation accuracy and covariance sizing. The dominant force in the LEO orbit regime is the drag force caused by atmospheric drag. Accurate accounting of the drag force is especially important for the accuracy of the propagated state. The implementation of a box and wing model to improve drag estimation accuracy, and its overall effect on the covariance state is explored.The process of tuning the EKF for Aqua and Aura support is described, including examination of the measurement errors of available observation types (Doppler and range), and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-square statistic, calculated based of the ODTK EKF solutions, are assessed versus accepted norms for the orbit regime.

Covariance Analysis↗

NASA NTRS2017

Band-to-Band Misregistration of the Images of MODIS Onboard Calibrators and Its Impact on Calibration

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard Terra and Aqua satellites are radiometrically calibrated on-orbit with a set of onboard calibrators (OBCs), including a solar diffuser, a blackbody, and a space view port through which the detectors can view the dark space. As a whisk-broom scanning spectroradiometer, thirty-six MODIS spectral bands are assembled in the along-scan direction on four focal plane assemblies (FPAs). These bands capture images of the same target sequentially with the motion of a scan mirror. Then the images are coregistered onboard by delaying the appropriate band-dependent amount of time, depending on the band locations on the FPA. While this coregistration mechanismis functioning well for the far-field remote targets such as earth view scenes or the moon, noticeable band-to-band misregistration in the along-scan direction has been observed for near field targets, particularly in OBCs. In this paper, the misregistration phenomenon is presented and analyzed. It is concluded that the root cause of the misregistration is that the rotating element of the instrument, the scan mirror, is displaced from the focus of the telescope primary mirror. The amount of the misregistrationis proportional to the band location on the FPA and is inversely proportional to the distance between the target and the scan mirror. The impact of this misregistration on the calibration of MODIS bands is discussed. In particular, the calculation of the detector gain coefficient m1of bands 8-16 (412 nm 870 nm) is improved by up to 1.5% for Aqua MODIS.

Wang, Zhipeng↗

NASA NTRS2014

Obtaining Remote-Sensing Reflectance from Multiple Instrument Systems

Obtaining accurate in situ measurements of Apparent Optical Properties (AOPs) is critical to maintaining satellite data quality. One approach to ensure accuracy is to deploy several independent instruments to measure the same phenomenon. During a cruise in June 2012, off the lee coast of the island of Hawaii, repeated profiles were made with two separate radiometric systems, one from Satlantic, Inc. (Hyperpro) and the other from Biospherical Instruments, Inc. (C-Ops). The C-Ops is multispectral, while the Hyperpro is hyperspectral. Both measure above-water solar irradiance (E(sub s)), downwelling in-water irradiance (E(sub d)), and upwelling in-water radiance (L(sub u)). From these measurements remotely-sensed reflectance (R(sub rs))can be calculated and compared with satellite data. All instruments were calibrated shortly before use, and while differences are to be expected due to temporal changes and spectral weighting differences, these should be consistent and minimal. We explore these differences, and compare to data retrieved from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODIS Aqua) when available. We also examine data collection and processing protocols for these systems.

Carbon↗