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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Techniques of Validation of Aerosol and Water Vapor Retrievals From MODIS

Aerosols are extremely important for global climate studies and modeling in the quest to characterize the global radiation budget and forcing. The physical characteristics, composition, abundance, and spatial distribution and dynamics of aerosols are still very poorly known. Aerosol column optical thickness and other parameters as well as column precipitable water vapor amount are some of the main atmospheric parameters retrieved from the MODIS instrument on board the Terra satellite. To ensure the reliability of these parameters, we have embarked on a very massive validation effort. This involves cross correlation between the retrievals from the satellite data and those obtained from sunphotometer measurements at a large number of ground stations spread throughout the globe. Notable among these ground stations is a large network of over 100 stations coordinated under the Aerosol Robotic Network (AERONET) project. Whereas MODIS retrieves the aerosol parameters throughout the globe once or twice a day during the daytime, the ground measurements cover only discrete locations of the earth, though the retrievals are done several times a day. We have devised a method to. match the MODIS and ground retrievals through spatial statistics for the MODIS data and temporal statistics for the ground data. This has produced good comparisons and has enabled the validation of MODIS aerosol and water vapor retrievals at over 100 discrete locations in various parts of the earth both over the land and over the ocean. Currently, the validation statistical data is produced routinely by the MODIS aerosol group and is even available not only for validation but also for use by the science community for short and long term studies at various parts of the earth. One important advantage is that the system can be expanded to incorporate more locations where ground measurements and other studies may be conducted at any time during the lifetime of MODIS.

Ichoku, Charles↗
NASA NTRS2004

AQUARIUS: A Passive/Active Microwave Sensor to Monitor Sea Surface Salinity Globally from Space

Salinity is important for understanding ocean dynamics, energy exchange with the atmosphere and the global water cycle. Existing data is limited and much of the ocean has never even been sampled. Sea surface salinity can be measured remotely by satellite and a three year mission for this purpose called AquariudSAC-D has recently been selected by NASA's Earth System Science Pathfinder (ESSP) program. The objective is to map the salinity field globally with a spatial resolution of 100 km and a monthly average accuracy of 0.2 psu. The mission, scheduled for launch in 2008, is a partnership of the United States National Aeronautics and Space Agency (NASA) and the Argentine Comision National de Actividades Epaciales (CONAE).

LeVine, David↗
NASA NTRS2021

Extending the Licklider Transmission Protocol to Multi-Band Links

Most deep space missions return data to Earth using links operating at a single frequency band. Indeed, their data requirements are low enough that bandwidth regulations do not constrain the system. In contrast, spacecraft such as Kepler or Europa Clipper are transitioning to a new operational paradigm where engineering and science data are transmitted through simultaneous links operating at different frequency bands (henceforth termed multi-band links). This ensures, for instance, that critical data is correctly received using a well characterized X-band link, while science data at a much larger data rate can be returned efficiently (both in terms of bandwidth and energy) through a Ka-band link.Having a spacecraft establish two simultaneous links with a ground station opens a large span of potential improvements for space communications and mission operations. In this paper, we consider the problem of running a Licklider Transmission Protocol (LTP) session over a multi-band link. LTP is an implementation of a selective Automatic Repeat reQuest (ARQ) protocol, i.e. it ensures correct delivery of data over an error prone link with potentially long propagation delays. To maximize its efficiency in deep space environments, LTP operates in deferred-ACK mode and is typically included as one of the core protocols in the Delay Tolerant Networking (DTN) suite.The contributions of this paper are as follows: First, we propose an extension to LTP for multi-band links (denoted MBLTP) and sketch how it can be implemented without modifying the current definition of LTP data units. Next, we develop bounds on the performance of MBLTP when transmitting a single data file over a multi-band link. Three metrics are considered, file expected delivery time, total energy spent and bundle jitter. The results of the analytic model are first benchmarked against simulations to ensure validity, and then compared against the performance of both traditional LTP and Parallel LTP (PLTP).We demonstrate that MBLTP can significantly reduce the latency and jitter with which data products are delivered to destination over a deep space link compared to LTP at moderate energy cost. Similarly, we also demonstrate that MBLTP outperforms PLTP in all considered metrics.

Sanchez Net, Marc↗
NASA NTRSDate not supplied

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Aqua-FM4_Edition1)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CLEAR-SKY LONGWAVE FLUX↗
DOE OSTI2018

Disturbance and Vegetation Dynamics in Earth System Models: Workshop Report

This report summarizes discussion and outcomes from the March 2018 workshop, Disturbance and Vegetation Dynamics in Earth System Models, sponsored by the Office of Biological and Environmental Research (BER) within the U.S. Department of Energy Office of Science. The goals of this workshop, held in Gaithersburg, Maryland, were to (1) identify key uncertainties in current dynamic vegetation models limiting the ability to adequately represent vegetation in Earth System Models (ESMs) and (2) identify and prioritize research directions that can improve models, including forest structural change and feedbacks and responses to disturbance. Failure to capture disturbance dynamics and feedbacks limits the utility of ESMs for predictive understanding and application to societally important problems. This workshop considered (a) dynamic processes that significantly affect terrestrial ecosystems and the coupled Earth system and (b) the data constraints and modeling challenges important for future progress. There were three dominant workshop conclusions: vegetation changes, including disturbance- driven changes, are affecting climate and natural resources; these impacts are expected to increase in the future; and, yet, current models have insufficient data and process representations to adequately predict these changes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Ka-Band Multibeam Aperture Phased Array Being Developed

Phased-array antenna systems offer many advantages to low-Earth-orbiting satellite systems. Their large scan angles and multibeam capabilities allow for vibration-free, rapid beam scanning and graceful degradation operation for high rate downlink of data to users on the ground. Technology advancements continue to reduce the power, weight, and cost of these systems to make phased arrays a competitive alternative in comparison to the gimbled reflector system commonly used in science missions. One effort to reduce the cost of phased arrays is the development of a Ka-band multibeam aperture (MBA) phased array by Boeing Corporation under a contract jointly by the NASA Glenn Research Center and the Office of Naval Research. The objective is to develop and demonstrate a space-qualifiable dual-beam Ka-band (26.5-GHz) phased-array antenna. The goals are to advance the state of the art in Ka-band active phased-array antennas and to develop and demonstrate multibeam transmission technology compatible with spacecraft in low Earth orbit to reduce the cost of future missions by retiring certain development risks. The frequency chosen is suitable for space-to-space and space-to-ground communication links. The phased-array antenna has a radiation pattern designed by combining a set of individual radiating elements, optimized with the type of radiating elements used, their positions in space, and the amplitude and phase of the currents feeding the elements. This arrangement produces a directional radiation pattern that is proportional to the number of individual radiating elements. The arrays of interest here can scan the main beam electronically with a computerized algorithm. The antenna is constructed using electronic components with no mechanical parts, and the steering is performed electronically, without any resulting vibration. The speed of the scanning is limited primarily by the control electronics. The radiation performance degrades gracefully if a portion of the elements fail. The arrays can be constructed to conform to a mounting surface, and multibeam capability is integral to the design. However, there are challenges for mission designers using monolithic-microwave-integrated-circuit- (MMIC-) based arrays because of reduced power efficiency, higher costs, and certain system effects that result in link degradations. The multibeam aperture phased-array antenna development is attempting to address some of these issues, particularly manufacturing, costs, and system performance.

Reinhart, Richard C.↗
DOE OSTI2023

CORPSE model with litter decomposition parameters derived from the LIDET dataset

This is a version of the CORPSE model (Carbon, Organisms, Rhizosphere and Protection in the Soil Environment, Sulman et al. 2014) that uses litter decomposition parameters derived from a modified Monte Carlo simulation using the LIDET litter decomposition dataset (Long-term Intersite Decomposition Experiment Team, Harmon 2013). The code also includes the Baseline parameters, and the eight other best parameter sets identified in a modified Monte Carlo simulation. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of files:The folder "Input Files" contains one folder for each LIDET site with data necessary to run the model. Note that "(site)" in the filenames below indicates where the LIDET site code appears (see Table 1 for site codes). Data streams include: CORPSE_full_spinup_litter.csv, CORPSE_full_spinup_rhizo.csv, CORPSE_full_spinup_bulk.csv, litterbag_init_100g_6spp.csv: initial C and N (kg C or N/m2) pool values for each soil layer, the litterbag_init_100_6spp.csv file is for the litterbag layer and is the same file for all sites. All initial C and N files have the same columns (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 soilT (site) DOY274start.csv: Average daily soil temperature (oC) interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). soilT (site) DOY274start.csv: Average daily soil volumetric water content (VWC) scalar interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). litter production.csv: Average daily litter production values for each site, data sources listed in Table S3 of related publication. litter (site) CN.csv: C:N ratio for each species from LIDET dataset (Table 2, Harmon 2013). (site).csv: Table indicating number of observations for each species decomposed at each site. Instructions: Save the model code ("CORPSE_LIDET.R") and "Input Files" folder in the same folder. Also make a folder for the model output (e.g., "results_Baseline") in the same folder. Set the working directory (setwd) in the model code to the folder with the files saved in step #1. Select the parameter set to use for the litter and litterbag compartments, comment out all other parameter sets. Run code. Output will be saved in the folder made in step 1. Output destination can be changed as necessary in code section called "Running the model." Table 1 LIDET sites and site codes used in model files. Site Code - Site AND - H.J. Andrews Experimental Forest BNZ - Bonanza Creek Experimental Forest BSF - Blodgett Research Forest CDR - Cedar Creek Natural History Area CPR - Central Plains Experimental Range HBR - Hubbard Brook Experimental Forest HFR - Harvard Forest JUN - Juneau KBS - Kellogg Biological Station KNZ - Konza Prairie Research Natural Area NWT - Niwot Ridge/Green Lakes Valley OLY - Olympic National Park OLY Conifer forest SEV - Sevilleta National Wildlife Refuge SMR - Santa Margarita Ecological Reserve UFL - University of Florida VCR - Virginia Coast Reserve Table 2 LIDET species and species codes used in model files (6 common species). Species - Species Code Sugar maple (Acer saccharum) - ACSA Drypetes (Drypetes glauca) - DRGL Red pine (Pinus resinosa) - PIRE Chestnut oak (Quercus prinus) - QUPR Western redcedar (Thuja plicata) - THPL Wheat (Triticum aestivum) - TRAE References:Bonan, G. B., Hartman, M. D., Parton, W. J., & Wieder, W. R. (2013). Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Global Change Biology, 19(3), 957-974. https://doi.org/https://doi.org/10.1111/gcb.12031 Harmon, M. (2013). LTER Intersite Fine Litter Decomposition Experiment (LIDET), 1990 to 2002. Long-Term Ecological Research. Forest Science Data Bank, Corvallis, OR. [Data set]. Accessed http://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023. https://doi.org/10.6073/pasta/f35f56bea52d78b6a1ecf1952b4889c5. Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., & Pacala, S. W. (2014). Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2. Nature Climate Change, 4, 1099 - 1102. https://doi.org/10.1038/nclimate2436

Juice, Stephanie↗
DOE OSTI2025

Characterization of Root Zone Soil Moisture and Herpetofaunal Biodiversity in the Southern Great Plains

(1) Goal: The scientific objective to the proposed research is to develop a proto-type downscaled (<1 km) version of the root-zone soil moisture product called SoilMERGE or SMERGE. This objective is linked as root zone soil moisture is a critical climate variable that has a more direct influence on plant growth than precipitation. Therefore, the developed downscaled version of SMERGE can be used as input into biodiversity informatic techniques (i.e., maximum entropy modeling) Development of downscaled SMERGE will be facilitated by Department of Energy (DOE) resources specifically data from the DOE Atmospheric Radiation Measurement (ARM) facility and modeling platforms such as the Energy Exascale Earth System Model (E3SM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Science Hybrid Orbiter and Lunar Relay (SCHOLR) Architecture and Design

Considered both a stepping-stone to deep space and a key to unlocking the mysteries of planetary formation, the Moon offers a unique opportunity for scientific study. Robotic precursor missions are being developed to improve technology and enable new approaches to exploration. Robots, lunar landers, and satellites play significant roles in advancing science and technologies, offering close range and in-situ observations. Science and exploration data gathered from these nodes and a lunar science satellite is intended to support future human expeditions and facilitate future utilization of lunar resources. To attain a global view of lunar science, the nodes will be distributed over the lunar surface, including locations on the far side of the Moon. Given that nodes on the lunar far side do not have direct line-of-sight for Earth communications, the planned presence of such nodes creates the need for a lunar communications relay satellite. Since the communications relay capability would only be required for a small portion of the satellite s orbit, it may be possible to include communication relay components on a science spacecraft. Furthermore, an integrated satellite has the potential to reduce lunar surface mission costs. A SCience Hybrid Orbiter and Lunar Relay (SCHOLR) is proposed to accomplish scientific goals while also supporting the communications needs of landers on the far side of the Moon. User needs and design drivers for the system were derived from the anticipated needs of future robotic and lander missions. Based on these drivers and user requirements, accommodations for communications payload aboard a science spacecraft were developed. A team of interns identified and compared possible SCHOLR architectures. The final SCHOLR architecture was analyzed in terms of orbiter lifetime, lunar surface coverage, size, mass, power, and communications data rates. This paper presents the driving requirements, operational concept, and architecture views for SCHOLR within a lunar surface nodal network. Orbital and bidirectional link analysis, between lunar nodes, orbiter, and Earth, as well as a conceptual design for the spacecraft are also presented

Trase, Kathryn K.↗
NASA NTRS1988

NASA earth science and applications division: The program and plans for FY 1988-1989-1990

Described here are the Division's research goals, priorities and emphases for the next several years and an outline of longer term plans. Included are highlights of recent accomplishments, current activities in FY 1988, research emphases in FY 1989, and longer term future plans. Data and information systems, the Geodynamics Program, the Land Processes Program, the Oceanic Processes Program, the Atmospheric Dynamics and Radiation Program, the Atmospheric Chemistry Program, and space flight programs are among the topic covered.

Source record↗
NASA NTRS2009

Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

Neil, Doreen O.↗
NASA NTRS2011

Earth-Affecting Solar Causes Observatory (EASCO): Results of the Mission Concept Study

Coronal mass ejections (CMEs) corotating interaction regions (CIRs) are two large-scale structures that originate from the Sun and affect the heliosphere in general and Earth in particular. While CIRs are generally detected by in-situ plasma signatures, CMEs are remote-sensed when they are still close to the Sun. The current understanding of CMEs primarily come from the SOHO and STEREO missions. In spite of the enormous progress made, there are some serious deficiencies in these missions. For example, these missions did not carry all the necessary instruments (STEREO did not have a magnetograph; SOHO did not have in-situ magnetometer). From the Sun-Earth line, SOHO was not well-suited for observing Earth-directed CMEs because of the occulting disk. STEREO's angle with the Sun-Earth line is changing constantly, so only a limited number of Earth-directed CMEs were observed in profile. In order to overcome these difficulties, we proposed a news L5 mission concept known as the Earth-Affecting Solar Causes Observatory (EASCO). The mission concept was recently studied at the Mission Design Laboratory (MDL), NASA Goddard Space Flight Center. The aim of the MDL study was to see how the scientific payload consisting of ten instruments can be accommodated in the spacecraft bus, what propulsion system can transfer the payload to the Sun-Earth L5, and what launch vehicles are appropriate. The study found that all the ten instruments can be readily accommodated and can be launched using an intermediate size vehicle such as Taurus II with enhanced faring. The study also found that a hybrid propulsion system consisting of an ion thruster (using approximately 55 kg of Xenon) and hydrazine (approximately 10 kg) is adequate to place the payload at L5. The transfer will take about 2 years and the science mission will last for 4 years around the next solar maximum in 2025. The mission can be readily extended for another solar cycle to get a solar-cycle worth of data on Earth-affecting CMEs and CIRs. This paper provides a highlight of the MDL study results.

Gopalswamy, Natchimuthuk↗
NASA NTRSDate not supplied

The Crustal Dynamics Data Information System (CDDIS) – Updates and Future Developments

As earth observing services and techniques have flourished, data and products have exponentially grown, like the proliferation of GNSS stations capable of providing real-time data, SLR stations shifting to kHz lasers, and VLBI’s implementation of VGOS telescopes. The CDDIS is continually evolving to fulfill the new storage, quality check, and latency requirements that these changes bring, as well as meet new standards such as the shift toward FAIR and open science. These have shaped how the CDDIS develops new software and resources. Beginning next year, the CDDIS will begin to transition their data and products to the AWS cloud, beginning with DORIS data. This poster will highlight the CDDIS’s recently updated processing system, new data and products available, and future work.

Justine Woo↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Aqua-FM3_Edition1-CV)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2006-11-02] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

WINDOW DETECTOR OUTPUT↗
DOE OSTI2022

Semi-automated Design of Artificial Intelligence Earth Science Models

Prediction and observation of water cycles involve not only patterns isolated in space and time, but rather modeling complex spatio-temporal relationships across multiple sources of data and domains. For instance, Evapotranspiration (ET) and Leaf Area Indexes (LAI) are two critical components in DOE’s Energy Exascale Earth System Model (E3SM). Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, current ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFT), which fail to capture the fine-scale variations due to change in vegetation type across the globe. Within this context and in light of the data-model integration challenges highlighted in the EESSD Strategic Plan, the new era of AI model development for geosciences calls for data-driven methods that provide domain scientists with estimations of parameters such as PFT and LAI in an efficient, interpretable, and easy-to-operate manner.

Ambrozio Dias, Philipe↗
NASA NTRS2015

Exploring Our Solar System with CubeSats and NanoSats

The Jet Propulsion Laboratory (JPL) is NASA's lead center for robotic exploration of our solar system. We are known for our large, flagship missions, such as Voyager, which gave humanity its first close look at Jupiter and Saturn; and the Mars Rovers, which have excited millions worldwide with their daring landing exploits. Less familiar to those outside NASA may be our role in developing the Kepler mission, which has discovered more than 2000 planets around other stars; or the recently launched Soil Moisture Active Passive (SMAP) mission, one of many JPL Earth Science missions. A recent JPL initiative has emphasized low cost missions that use rapidly evolving technology developed for CubeSats and NanoSat s to explore our solar system. Costs are significantly lower (by one or two orders of magnitude) than for conventional JPL missions, and development time is also significantly shorter. At present 21 such CubeSat flight projects are under way at the laboratory with various partners : some in flight, some in development, some in advanced formulation. Four are planned as deep space missions. To succeed in exploring deep space CubeSat/NanoSat missions have to address several challenges: the more severe radiation environment, communications and navigation at a distance, propulsion, and packaging of instruments that can return valuable science into a compact volume/mass envelope. Instrument technologies, including cameras, magnetometers, spectrometers, radiometers, and even radars are undergoing miniaturization to fit on these smaller platforms. Other key technologies are being matured for smallsats and NanoSats in deep space, including micro -electric propulsion, compact radio (and optical) communications, and onboard data reduction. This paper will describe missions that utilize these developments including the first two deep space CubeSats (INSPIRE), planned for launch in 2017; the first pair of CubeSats to be sent to another planet (MARCO), manifested with the InSight Mars lander launch in March of 2016; a helicopter "drone" on Mars to extend the reach of future rovers; plans for a Lunar Flashlight mission to shine a light on the permanently shadowed craters of the Moon's poles; a Near Earth Asteroid CubeSat missio n; and a CubeSat constellation to demonstrate time series measurements of storm systems on Earth. From these beginnings, the potential for CubeSats and NanoSats to add to our knowledge of the solar system could easily grow exponentially. Imagine if every deep space mission carried one or more CubeSats that could operate independently (even for a brief period) on arrival at their target body. At only incremental additional cost, such spacecraft could go closer, probe deeper, and provide science measurements that we would not risk with the host spacecraft. This paper will describe examples including a NanoSat to probe the composition of Venus' atmosphere, impactors and close flybys of Europa, lunar probes, and soft landers for the moons of Mars. Low cost access to deep space also offers the potential for independent CubeSat/NanoSat missions - allowing us to characterize the population of near Earth asteroids for example, deploy a constellation around Venus, or take closer looks at the asteroid belt.

Deep Space↗
NASA NTRS1988

Earth Observing System (EOS) advanced altimetry

In the post-TOPEX era, satellite radar altimeters will be developed with the capability of measuring the earth's surface topography over a wide swath of coverage, rather than just at the satellite's nadir. The identification of potential spacecraft flight missions in the future was studied. The best opportunity was found to be the Earth Observing System (EOS). It is felt that an instrument system that has a broad appeal to the earth sciences community stands a much better chance of being selected as an EOS instrument. Consequently, the Topography and Rain Radar Imager (TARRI) will be proposed as a system that has the capability to profile the Earth's topography regardless of the surface type. The horizontal and height resolutions of interest are obviously significantly different over land, ice, and water; but, the use of radar to provide an all-weather observation capability is applicable to the whole earth. The scientific guidance for the design and development of this instrument and the eventual scientific utilization of the data produced by the TARRI will be provided by seven science teams. The teams are formed around scientific disciplines and are titled: Geology/Geophysics, Hydrology/Rain, Oceanography, Ice/Snow, Geodesy/Orbit/Attitude, Cartography, and Surface Properties/Techniques.

Parsons, C. L.↗
NASA NTRS2004

GRACE KBR and Accelerometer Data Reduction and Calibration

The Gravity Recovery and Climate Experiment (GRACE), launched on March 17, 2002, represents the state-of-the-art in geodetic observations of the static and time varying components of the Earth's geopotential field. The fundamental measurement used to observe gravity is the inter-satellite range and range rate between two coplanar, low altitude satellites obtained from a K-band ranging (KBR) system. In addition to the K-band ranging system, each satellite possess a Super-STAR Accelerometer, a GPS receiver/antenna package, Star Cameras and a Laser Retro Reflector (LRR) to complete the compliment of science instruments. The GRACE project has now released two years of Level 1B data derived from the science instruments and sensors. An integral component of our time variable gravity research is the reduction, calibration and analyses of these Level 1B data. In particular we have analyzed several months of K-band ranging (KBR1B), accelerometry (ACC1B) and GPS navigation (GNAV1B) data. Accelerometer calibration and KBR data reduction methodology and results will be presented. We discuss the impact of these analyses on the recovery of time variable gravity.

Rowlands, David D.↗