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At least 541 records · Page 30

The Earth Observing System

The Earth Observing System (EOS), the centerpiece of NASA's Mission to Planet Earth, is to study the interactions of the atmosphere, land, oceans, and living organisms, using the perspective of space to observe the earth as a global environmental system. To better understand the role of clouds in global change, EOS will measure incoming and emitted radiation at the top of the atmosphere. Then, to study characteristics of the atmosphere that influence radiation transfer between the top of the atmosphere and the surface, EOS wil observe clouds, water vapor and cloud water, aerosols, temperature and humidity, and directional effects. To elucidate the role of anthropogenic greenhouse gas and terrestrial and marine plants as a source or sink for carbon, EOS will observe the biological productivity of lands and oceans. EOS will also study surface properties that affect biological productivity at high resolution spatially and spectrally.

Wilson, Stan↗

Clouds and Radiation from the Earth Observing System

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, four EOS science missions are scheduled for launch, representing observations of (i) total solar irradiance, (ii) Earth radiation budget, (iii) land cover & land use change, (iv) ocean processes (vector wind, sea surface temperature, and ocean color), (v) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (vi) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation we will describe how scientists are using MODIS (Moderate Resolution Imaging Spectroradiometer), an earth-viewing cross-track scanning spectroradiometer on the Terra (AM-1) satellite, for the remote sensing of cloud and aerosol properties. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmosphere processes.

King, Michael D.↗

Development of a Nonlinear Probability of Collision Tool for the Earth Observing System

The Earth Observing System (EOS) spacecraft Terra, Aqua, and Aura fly in constellation with several other spacecraft in 705-kilometer mean altitude sun-synchronous orbits. All three spacecraft are operated by the Earth Science Mission Operations (ESMO) Project at Goddard Space Flight Center (GSFC). In 2004, the ESMO project began assessing the probability of collision of the EOS spacecraft with other space objects. In addition to conjunctions with high relative velocities, the collision assessment method for the EOS spacecraft must address conjunctions with low relative velocities during potential collisions between constellation members. Probability of Collision algorithms that are based on assumptions of high relative velocities and linear relative trajectories are not suitable for these situations; therefore an algorithm for handling the nonlinear relative trajectories was developed. This paper describes this algorithm and presents results from its validation for operational use. The probability of collision is typically calculated by integrating a Gaussian probability distribution over the volume swept out by a sphere representing the size of the space objects involved in the conjunction. This sphere is defined as the Hard Body Radius. With the assumption of linear relative trajectories, this volume is a cylinder, which translates into simple limits of integration for the probability calculation. For the case of nonlinear relative trajectories, the volume becomes a complex geometry. However, with an appropriate choice of coordinate systems, the new algorithm breaks down the complex geometry into a series of simple cylinders that have simple limits of integration. This nonlinear algorithm will be discussed in detail in the paper. The nonlinear Probability of Collision algorithm was first verified by showing that, when used in high relative velocity cases, it yields similar answers to existing high relative velocity linear relative trajectory algorithms. The comparison with the existing high velocity/linear theory will also be used to determine at what relative velocity the analysis should use the new nonlinear theory in place of the existing linear theory. The nonlinear algorithm was also compared to a known exact solution for the probability of collision between two objects when the relative motion is strictly circular and the error covariance is spherically symmetric. Figure I shows preliminary results from this comparison by plotting the probabilities calculated from the new algorithm and those from the exact solution versus the Hard Body Radius to Covariance ratio. These results show about 5% error when the Hard Body Radius is equal to one half the spherical covariance magnitude. The algorithm was then combined with a high fidelity orbit state and error covariance propagator into a useful tool for analyzing low relative velocity nonlinear relative trajectories. The high fidelity propagator is capable of using atmospheric drag, central body gravitational, solar radiation, and third body forces to provide accurate prediction of the relative trajectories and covariance evolution. The covariance propagator also includes a process noise model to ensure realistic evolutions of the error covariance. This paper will describe the integration of the nonlinear probability algorithm and the propagators into a useful collision assessment tool. Finally, a hypothetical case study involving a low relative velocity conjunction between members of the Earth Observation System constellation will be presented.

McKinley, David P.↗

HIRIS - NASAS's High-Resolution Imaging Spectrometer for the Earth Observing System

Modern Earth science is beginning to examine interactions among the different terrestrial components at all temporal and spatial scales. Such a global perspective requires an integrated remote-sensing program, the Earth Observing System (EOS), which uses instruments throughout the electromagnetic spectrum to collect data about the Earth's surface, oceans and atmosphere over a range of selected scales. At the finest scales, we will require instruments capable of detailed sampling both spatially and spectrally. We have designed the High-Resoulution Imaging Spectrometer (HIRIS) to acquire simultaneous images in 192 spectral bands in the dominant wavelengths of the solar spectrum, 0.4 to 2.5 micrometers, at a spectral sampling interval of 10 nm. The ground instantaneous field of view (GIFOV) will be 30 m over a 24 km swath. A pointing capability will allow image acquisition up to +52 deg/-30 deg down track and +/-45 deg or more cross-track. Thus we will be able to study surface spectral bidirectional reflectance properties and variations in atmospheric attenuation with viewing angle. The cross-track pointing will also allow multiple viewing opportunities during one 16-day orbital revisit cycle, so that any part of the Earth may be imaged in a two-day period.

Dozier, J.↗

Analysis of active volcanoes from the Earth Observing System

The Earth Observing System (EOS) scheduled for launch in 1997 and 1999 is briefly described, and the EOS volcanology investigation objectives are discussed. The volcanology investigation will include long- and short-term monitoring of selected volcanoes, the detection of precursor activity associated with unanticipated eruptions, and a detailed study of on-going eruptions. A variety of instruments on the EOS platforms will enable the study of local- and regional-scale thermal and deformational features of volcanoes, and the chemical and structural features of volcanic eruption plumes and aerosols.

Mouginis-Mark, Peter↗

Acquisition/expulsion system for earth orbital propulsion system study. Volume 3: Cryogenic test

A ground test program was conducted to verify several of the design methods and techniques that were used in designing cryogenic acquisition/expulsion systems. The testing of a 63.5-cm diameter DSL subscale model was particularly significant. Under these tests, the operational characteristics of the DSL concept were verified using LH2 and LN2. Demonstration of the gas free liquid expulsion characteristics was accomplished by expelling LH2 under -1 g using both GH2 and GHe pressurization. Loading of the acquisition/expulsion device was successfully accomplished using LH2 and LN2. The liquid free vapor venting performance of the model was limited because of the thermal stratification under the -1 g test conditions.

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Acquisition/expulsion system for earth orbital propulsion system study. Volume 4: Flight test article

Two orbital test plans were prepared to verify one of the passive cryogenic storage tank/feedline candidate designs. One plan considered the orbital test article to be launched as a dedicated payload using an Atlas F burner launching configuration. The second plan proposed to launch the orbital test article as a secondary payload on the Titan E/Centaur proof flight. The secondary payload concept was pursued until January 1973, when work to build the hardware for this phase of the contract was terminated for lack of a sponsor for the flight. The dedicated payload launched on an Atlas F is described.

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TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 3: Mission and System Requirements for the Total Earth Resources System

Resource management missions to be performed by TERSSE are described. Mission and user requirements are defined along with information flows developed for each major resource management mission. Other topics discussed include: remote sensing platforms, remote sensor requirements, ground system architecture, and such related issues as cloud cover, resolution, orbit mechanics, and aircraft versus satellite.

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Study and prototype of data system interactions for the Earth Observing System Data and Information System

A crucial part of the Earth Observing System (EOS) is its Data and Information System (EOSDIS). The success of EOS depends not only on its instruments and science studies, but also on its ability to help scientists integrate data sets of geophysical and biological measurements taken by various instruments and investigators. NASA contractors have completed Phase B studies of EOSDIS, in particular its architecture, functionality, and user interfacing. At this point in time, it may seem impossible to exercise the EOSDIS or any of its components since they do not exist; i.e., if the EOSDIS is accepted as a totally new system, distinct from any existing DIS. However, if EOSDIS is seen as evolving from existing data systems, then some limited prototyping studies can be conducted by using currently functioning systems. In support of both the EOSDIS Science Advisory Panel and the EOSDIS Project, a prototyping activity was carried out by a cross section of interdisciplinary scientists. That prototyping activity is summarized and some conclusions are drawn that can be used by NASA-Goddard to evaluate and modify the specifications soon to be released in an RFP to build EOSDIS.

Emmitt, G. D.↗

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗

The Earth Observing System (EOS)

The Earth Observing System is a US National Aeronautics and Space Administration (NASA) program consisting of a science segment, a data system, and a space segment made up of a series of polar-orbiting and mid-inclination satellites for long-term monitoring of the Earth as an integrated system, including observations of the land surface, biosphere, atmosphere, cryosphere, and oceans. Initially conceived in the mid-late 1980s, it was implemented as a series of large "flagship" missions and smaller focused satellites, often in partnership with instruments and sometimes spacecraft from other nations. In 1984 NASA formed several instrument panels to develop concepts for “facility instruments” that would provide comprehensive support to the scientific and applications’ communities, each with a supporting science team competitively selected via peer-review. An Announcement of Opportunity was released in 1988 and proposals were solicited for three types of proposals: (i) instrument investigations that would include the provision of instrumentation for flight on a polar platform, including non-Earth science payloads requiring polar orbits (PI instruments), (ii) research facility instrument team member and team leader investigations for facility instruments, and (iii) interdisciplinary science investigations to provide data analysis and modeling, preparing to use data acquired from the space platforms. The initial selections made in 1989 included support for 24 instrument investigations, 6 research facility instrument investigations, and 28 interdisciplinary investigations. Although considerable changes were made over the years in the structure and orbital configuration of the various instruments and platforms, a total of 10 different missions were eventually flown, as shown in Fig. 1. These included three multiinstrument flagship platforms known as Terra (launched in 1999), Aqua (launched in 2002), and Aura (launched in 2004), where the Terra mission emphasis was primarily on land processes, Aqua on the hydrological cycle, and Aura on atmospheric chemistry. In addition to these flagship missions the EOS missions included Landsat 7 (land cover classification and change), QuikScat (wind speed and direction over the oceans), Jason-1 (ocean surface topography and sea level), ACRIMSAT (total solar irradiance (TSI)), SAGE III (stratospheric aerosol and ozone levels), ICESat (ice, cloud, and land elevation), and SORCE (Solar Radiation and Climate Experiment; total and spectral solar irradiance). In addition EOS supported CERES (an Earth radiation budget sensor) and LIS (a lightning sensor), that flew as part of the NASA/JAXA Tropical Rainfall Measuring Mission (1997), and SeaWinds (wind speed and direction), that flew as part of the short-lived ADEOS II (Midori II, 2002) mission of JAXA (Japan Aerospace Exploration Agency). The EOS contributions are too numerous to present in detail in this article, but can be viewed for convenience as a means of obtaining global measurements (with appropriate characteristics) of the 24 variables and variable groups listed in Table 1. This table was created by the EOS community in the late 1990s as a way to succinctly indicate which instruments on the various EOS platforms were expected to contribute to each of the specified variables in primary (bold), secondary (bold italics), or contributing (roman) roles. All of the science data products produced by these space missions are available without charge throughout the world, and are thus highly valued for their many contributions to applications such as air quality, fires, land cover change, and the state of the oceans, as well as for science and monitoring of the state of the Earth system and its changes over time. These and other international satellites have played a crucial role in understanding and documenting global change, including (i) global surface temperature and atmospheric temperature and water vapor profiles, (ii) glacial retreat, (iii) sea ice extent and change, (iv) solar radiation into and out of the Earth-atmosphere system, (v) atmospheric aerosol and cloud properties, (vi) sources and sinks of

ICESat↗

Understanding our Changing Planet: NASA's Earth Science Enterprise

NASA has been studying the Earth and its changing environment by observing the atmosphere, oceans, land, ice, and snow and their influence on climate and weather since the agency's creation. This study has lead to a new approach to understanding the interaction of the Earth's systems, Earth System Science. The Earth Science Enterprise, NASA's comprehensive program for Earth System Science, uses satellites and other tools to intensively study the Earth. The Earth Science Enterprise has three main components: (1) a series of Earth-observing satellites, (2) an advanced data system and (3) teams of scientist who study the data. Key areas of study include: (1) clouds, (2) water and energy cycles, (3) oceans, (4) chemistry of the atmosphere, (5) land surface, water and ecosystems processes; (6) glaciers and polar ice sheets, and (7) the solid earth.

Forehand, Lon↗

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗