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NASA NTRS2013

Dawn Orbit Determination Team : Trajectory Modeling and Reconstruction Processes at Vesta

The NASA Dawn spacecraft was launched on September 27, 2007 on a mission to study the asteroid belt's two largest objects, Vesta and Ceres. It is the first deep space orbiting mission to demonstrate solar-electric ion propulsion, providing the necessary delta-V to enable capture and escape from two extraterrestrial bodies. At this time, Dawn has completed its science campaign at Vesta and is currently on its journey to Ceres, where it will arrive in mid-2015. The spacecraft spent over a year in orbit around Vesta from July 2011 through August 2012, capturing science data during four dedicated orbit phases. In order to maintain the reference orbits necessary for science and enable the transfers between those orbits, precise and timely orbit determination was required. The constraints associated with low-thrust ion propulsion coupled with the relatively unknown a priori gravity and rotation models for Vesta presented unique challenges for the Dawn orbit determination team. While [1] discusses the prediction performance of the orbit determination products, this paper discusses the dynamics models, filter configuration, and data processing implemented to deliver a rapid orbit determination capability to the Dawn project.

Vesta↗

NASA NTRSDate not supplied

Using AI/ML to Address Satellite Cloud Remote Sensing Challenges

Various AI/ML tools, employed within the Clouds and the Earth's Radiant Energy System (CERES) Satellite Cloud and Radiation Property retrieval System (SatCORPS) project, are being used to mitigate satellite radiance artifacts and thereby yield more accurate cloud and radiation data products. Neural network and K-nearest neighbor approaches have been developed that enable us to better address common passive satellite remote sensing challenges, such as corrupted imagery, day/night cloud property discontinuities, solar terminator artifacts, inadequate knowledge of the land surface emission temperature (i.e., skin temperature), and poor assumptions about vertical cloud structure, that have otherwise proven difficult to solve using more conventional methods. Fixing these problems promotes a more consistent Earth radiation budget record. These efforts demonstrate effective use of AI/ML architecture to exploit complex, multivariate predictor relationships and produce usable output at satellite spatial and temporal resolutions that would otherwise be ignored or have large biases.

Benjamin Scarino↗

NASA NTRS2004

Validation of Infrared Azimuthal Model as Applied to GOES Data Over the ARM SGP

The goal of this research is to identify and reduce the GOES-8 IR temperature biases, induced by a fixed geostationary position, during the course of a day. In this study, the same CERES LW window channel model is applied to GOES-8 IR temperatures during clear days over the Atmospheric Radiation Measurement-Southern Great Plains Central Facility (SCF). The model-adjusted and observed IR temperatures are compared with topof- the-atmosphere (TOA) estimated temperatures derived from a radiative transfer algorithm based on the atmospheric profile and surface radiometer measurements. This algorithm can then be incorporated to derive more accurate Ts from real-time satellite operational products.

Gambheer, Arvind V.↗

NASA NTRS2014

TPSAS-NF1676L-19256-DND

The NASA/GEWEX (Global Energy and Water Exchanges project) Surface Radiation Budget (SRB) project produces longwave and shortwave radiative fluxes for the surface and top-of-atmosphere (TOA) (see, Stackhouse et al., 2011, GEWEX News). The primary inputs of cloud and meteorology data have been undergoing improvements in quality and spatial and temporal resolution. In anticipation of the release of these data, the SRB longwave flux algorithm has been updated both to accommodate these data and to improve the algorithm used in deriving radiative fluxes. Changes in the inputs and algorithm are as follows: - Synchronized algorithm with version used by NASA CERES (Rose et al. 2006). - Atmospheric aerosols were added. - Beta version of ISCCP H cloud properties used. - Beta version of ISCCP nnHIRS temperature and humidity used. - Option of using a newly derived beta Princeton land surface temperature and diurnal Seaflux sea surface temperature as surface skin temperature added - Updated ozone profile with GISS ozone and MEaSUREs GOZCARDS. - Updated maps of surface topography, vegetation type, and snow/ice by ISCCP. The beta GLW v4 IP has enhanced the output fluxes by adding pristine-sky (no clouds or aerosols) fluxes. The new version also computes fluxes at selected atmospheric levels (including the tropopause) rather than just at the surface and TOA. The purpose of this study is to explore the effect of the above changes on the surface and top-of-atmosphere fluxes. These fluxes are compared to the previous version (release 3.1). We show preliminary results for the mid-seasonal months of 2007.

J Colleen Mikovitz↗

NASA NTRS2022

Unique Observational Constraints on the Seasonal and Longitudinal Variability of the Earth’s Planetary Albedo and Cloud Distribution Inferred From EPIC Measurements

Thorough comparison to observations is key to developing a credible climate model forecasting capability. Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation provide a unique observational perspective that permits a more reliable model/data comparison than is possible with the otherwise available satellite data. The uniqueness is in the DSCOVR satellite’s viewing geometry, which enables continuous viewing of the Earth’s sunlit hemisphere from its Lissajous orbit around the Lagrangian L1 point. The key instrument is the Earth Polychromatic Imaging Camera (EPIC), which views the Earth’s sunlit hemisphere with 1024-by-1024-pixel imagery in 10 narrow spectral bands from 317 to 780 nm, acquiring up to 22 high spatial resolution images per day. The additional feature is that the frequency of EPIC image acquisition is nearly identical to that of the climate GCM data generation scheme where climate data for the entire globe are ‘instantaneously’ calculated at 1-h radiation time-step intervals. Implementation of the SHS (Sunlit Hemisphere Sampling) EPIC-view geometry for the in-line GCM output data sampling establishes a precise self-consistency in the space-time data sampling between EPIC observational and GCM output data generation and sampling. The remaining problem is that the GCM generated data are radiative fluxes, while the EPIC measurements are backscatter-dependent radiances. Radiance to flux conversion is a complex problem with no simple way to convert GCM radiative fluxes into spectral radiances. The more expedient approach is to convert the EPIC spectral radiances into broadband radiances by MODIS/CERES-based regression relationships and then into solar radiative fluxes using the CERES angular distribution models. Averaging over the sunlit hemisphere suppresses the meteorological weather noise, but preserves the intra-seasonal larger scale variability. Longitudinal slicing by the Earth’s rotation permits a self-consistent model/data comparison of the longitudinal model/data differences in the variability of the reflected solar radiation. Ancillary EPIC Composite data provide additional cloud property information for climate model diagnostics. Comparison of EPIC-derived seasonal and longitudinal variability of the Earth’s planetary albedo with the GISS ModelE2 results shows systematic overestimate of cloud reflectivity over the Pacific Ocean with corresponding underestimates over continental land areas.

DSCOVR↗

NASA NTRS1990

Surface radiation budget in the Clouds and the Earth's Radiant Energy System (CERES) effort and in the Global Energy and Water Cycle Experiment (GEWEX)

The surface radiation budget (SRB) and the atmospheric radiative flux divergence (ARD) are vital components of the weather and climate system. The importance of radiation in a complex international scientific endeavor, the GEWEX of the World Climate Research Programme is explained. The radiative transfer techniques and satellite instrumentation that will be used to retrieve the SRB and ARD later in this decade with the CERES are discussed; CERES is a component of the Earth Observing System satellite program. Examples of consistent SRB and ARD retrievals made with Nimbus-7 and International Satellite Cloud Climatology Project data from July 1983 are presented.

Charlock, Thomas P.↗

NASA NTRS2004

Two MODIS Aerosol Products Over Ocean on the Terra and Aqua CERES SSF Datasets

Over ocean, two aerosol products are reported on the Terra and Aqua CERES SSFs. Both are derived from MODIS, but using different sampling and aerosol algorithms. This study briefly summarizes these products, and compares using 2 weeks of global Terra data from 15-21 December 2000, and 1-7 June 2001.

Ignatov, Alexander↗

NASA NTRS2008

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Molnar, Gyula↗

NASA NTRS2011

Optical Navigation for Dawn at Vesta

The Dawn S/C, launched in September 2007, towards Vesta and Ceres, will enter into orbit about asteroid Vesta in July 2011 and will conduct science remote sensing operations for approximately one year at various orbital altitudes. Vesta navigation operations begin with early approach in May 2011 until departure to Ceres in July 2012. A key navigation aspect is optical navigation, which will be conducted at all mission phases. Here we review the optical navigation plan, imaging, methodology, data types, as well as expected performance in the context of the overall mission navigation. A key aspect of optical navigation at Dawn that will receive particular attention is the extensive use of landmark navigation during most of mission phases. In addition to supporting real-time navigation operations, optical navigation will be used to determine some key physical characteristics of Vesta, such as the asteroid's pole & shape, to assist mission design & science operations.

Vesta↗

NASA NTRS2021

LiDAR-Inertial Based Navigation and Mapping for Precision Landing

Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.

Katake, Anup↗

NASA NTRS1999

Validation of Surface Skin Temperature and Moisture Profiles Using Satellite Data

New validation techniques and metrics using satellite data have been developed to evaluate the quality of model-based estimates of surface skin temperature (Tg) and moisture profiles (q). The satellite data consist of clear sky outgoing long-wave radiation (CLR), broadband radiances from 8 to 12 mu (RadWn), brightness temperature centered around 10.8 mu (Tbb), and total precipitable water (TPW) from microwave radiometry. We show that CLR can be used to diagnose Tg. Furthermore, by using a combination of CLR and RadWn from CERES-TRMM measurements and TPW from SSM/I, we are able to identify errors in the moisture profile. Finally, three-hourly Tbb from the International Satellite Cloud Climatology Project can be used to evaluate the amplitude and diurnal variation of Tg. For purpose of illustration, Tg and q are evaluated from runs with an early version of the Goddard Earth Observing System Data Assimilation System (GEOS-2). It is found that, in general, Tg is too cold in the winter hemisphere and q is too wet in the upper atmosphere. In order to address these deficiencies, several improvements have been implemented into GEOS-2, including a Land-Surface-Model, a Moist Turbulence Scheme, and the assimilation of new TOVS retrievals. Preliminary results indicate positive impacts from each of these implementations.

Wu, Man Li C.↗

NASA NTRSDate not supplied

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Intercalibration Data Analysis Strategy

One of the prime science objectives of NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is to acquire unprecedentedly accurate Système Internationale (SI)-traceable Earth-view measurements that can be used as reference for intercalibrating the Clouds and the Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard NOAA-20 satellite. The hyperspectral nature of CPF measurements will significantly reduce spectrally induced biases when intercalibrating multiband or broadband satellite instruments with CPF. This advancement eliminates the requirement for spectral band adjustment factors, representing a substantial improvement in sensor intercalibration studies. The CPF intercalibration team is aiming to achieve a maximum intercalibration methodology uncertainty of 0.3 % (k=1). Our studies have revealed that the most significant contribution to the targeted uncertainty budget originates from the combined effects of spatial and temporal matching errors. Spatial matching error arises from discrepancies in CPF and target instrument pixel resolution and geolocation uncertainty, while temporal matching error is caused by changes in scene radiances over time, occurring between when the target and reference instruments observe the same scenes. To estimate the maximum expected uncertainty contribution from these sources, spatial and temporal matching noise analyses were conducted using algorithmically filtered Landsat 9 Operational Land Imager (OLI) and Geostationary Operational Environmental Satellite (GOES)-16 ABI CONUS scan data as proxies for CPF and target instruments. In the upcoming conference presentation, we will elaborate on the methodology employed in these experiments, provide details of the data filtering algorithms, and present results of the spatial and temporal matching uncertainty analyses.

Intercalibration↗

NASA NTRS2014

CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling

The implementation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to provide an on-orbit intercalibration standard with accuracy of 0.3% (k = 2) for relevant Earth observing sensors. The goal of reference intercalibration, as established in the Decadal Survey, is to enable rigorous high-accuracy observations of critical climate change parameters, including reflected broadband radiation [Clouds and Earth's Radiant Energy System (CERES)], cloud properties [Visible Infrared Imaging Radiometer Suite (VIIRS)], and changes in surface albedo, including snow and ice albedo feedback. In this paper, we describe the CLARREO approach for performing intercalibration on orbit in the reflected solar (RS) wavelength domain. It is based on providing highly accurate spectral reflectance and reflected radiance measurements from the CLARREO Reflected Solar Spectrometer (RSS) to establish an on-orbit reference for existing sensors, namely, CERES and VIIRS on Joint Polar Satellite System satellites, Advanced Very High Resolution Radiometer and follow-on imagers on MetOp, Landsat imagers, and imagers on geostationary platforms. One of two fundamental CLARREO mission goals is to provide sufficient sampling of high-accuracy observations that are matched in time, space, and viewing angles with measurements made by existing instruments, to a degree that overcomes the random error sources from imperfect data matching and instrument noise. The data matching is achieved through CLARREO RSS pointing operations on orbit that align its line of sight with the intercalibrated sensor. These operations must be planned in advance; therefore, intercalibration events must be predicted by orbital modeling. If two competing opportunities are identified, one target sensor must be given priority over the other. The intercalibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, optics spectral response, and sensitivity to polarization. In this paper, we use existing satellite data and orbital simulationmethods to determinemission requirements for CLARREO, its instrument pointing ability, methodology, and needed intercalibration sampling and data matching for accurate intercalibration of RS radiation sensors on orbit.

radiometry↗

NASA NTRS2001

Evaluation and Improvement of Earth Radiation Budget Data Sets

The tasks performed during this grant are as follows: (1) Advanced scan patterns for enhanced spatial and angular sampling of ground targets; (2) Inter-calibration of polar orbiter in low Earth orbits (LEO) and geostationary (GEO) broadband radiance measurements; (3) Synergism between CERES on TRMM and Terra; (4) Improved surface solar irradiance measurements; (5) SW flux observations from Ultra Long Duration Balloons at 35 km altitude; (6) Nighttime cloud property retrieval algorithm; (7) Retrievals of overlapped and mixed-phase clouds.

Haeffelin, Martial P. A.↗

NASA NTRS1985

Estimating solar radiation for plant simulation models

Five algorithms producing daily solar radiation surrogates using daily temperatures and rainfall were evaluated using measured solar radiation data for seven U.S. locations. The algorithms were compared both in terms of accuracy of daily solar radiation estimates and terms of response when used in a plant growth simulation model (CERES-wheat). Requirements for accuracy of solar radiation for plant growth simulation models are discussed. One algorithm is recommended as being best suited for use in these models when neither measured nor satellite estimated solar radiation values are available.

Hodges, T.↗

NASA NTRS1989

On the wavelength dependence of apparent emissivity of asteroid microwave emissions - Ceres and Vesta

Observations of Ceres and Vesta demonstrate the need for modifying the physical parameters of the standard model procedure in treating single-wavelength observations. It is suggested that simultaneous IR and cm-wavelength data should be used in order to determine such properties as the surface dielectric characteristics, layer depth, and radio emissivity. If using the standard model, an emissivity of 0.8 should be adopted for wavelengths of longer than 1 cm.

Webster, William J., Jr.↗

NASA NTRS2018

Dawn's Second and Final Extended Mission: A New Operational Campaign at Ceres

Dawn has been in orbit around Ceres since March 2015. In 2016, Dawn completed its prime mission of exploring Vesta and Ceres, and it completed an extended mission at the dwarf planet in 2017. The spacecraft has lost all reaction wheel control, making attitude control dependent on a dwindling supply of hydrazine. Nevertheless, in 2017 the project was approved for a second and final extended mission at Ceres. Starting in April 2018, Dawn used its ion propulsion system to maneuver to two new orbits. These highly elliptical orbits provided hydrazine-efficient opportunities for the acquisition of valuable new data. Now in the second of these orbits, Dawn's lowest altitude is only 9% of the lowest altitude previously in the mission, enabling significant improvements in the spatial resolution of the data. We describe Dawn operations in its second extended mission, the nature of the orbits, and the observation campaigns. We also summarize expectations for the end of the mission.

Rayman, Marc D.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-11678-DND

Cloud vertical profiles retrieved from CALIPSO and CloudSat data provide additional information that greatly improves the estimate of atmospheric radiative heating rates and potentially improves the estimate of the global surface radiation budget. To utilize CALIPSO and CloudSat cloud vertical profiles, we combined their profiles and generated merged profiles. Weused the merged cloud profiles and MODIS derived cloud profiles by the CERES cloud algorithm in irradiance computations. In this study, the improvement of the irradiance by CALIPSO and CloudSat derived merged cloud vertical profiles is evaluated by comparing modeled irradiances with and without merged cloud profiles. Because of lower cloud base heights provided by the merged profiles compared with cloud base heights derived from an empirical formula using the MODIS derived cloud top height and optical thickness, the global annual mean surface longwave downward irradiance increases approximately by 7 Wm-2. While CALIPSO version 3 data have not been incorporated in the irradiance computation and the effect of the new CALIPSO data needs to be assessed, a comparison with surface observations suggests an improvement of surface downward longwave irradiance computations. The surface downward longwave irradiance computed with CALIPSO and CloudSat merged clouds agrees better with surface observations than the irradiance computed with MODIS only does. The bias difference over ARM SGP sites with 2 years of data decreases from -5 W m-2to -2 Wm-2, and it decreases from -9 Wm-2to no bias over polar validation sites. The result suggests that CALIPSO CloudSat derived merged clouds significantly improve surface longwave irradiance estimates once they are combined with MODIS derived cloud properties and with temperature and humidity profiles from reanalysis.

Seiji Kato↗