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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Peters-Lidard, Christa D.↗
NASA NTRS2018

TPSAS-NF1676L-30074-DND

NASA is at forefront in developing unique active/passive remote sensing capabilities towards space-based observations for understanding the complexities and interactions among Earth system components. The world is facing significant environmental challenges and a robust, integrated, and flexible system of observations and models are needed for understanding the short-and long-term impact on the Earth system. A fundamental challenge for the coming decade is to ensure that space-based observations, analyses, better interpretive understanding, enhanced predictive models, broadened international community participation, and improved means for information assimilation and disseminations are well coordinated to realize the full economic, societal, and security benefit of Earth science. This presentation will provide an overview of active/passive remote sensing technologies and techniques from ground and space towards NASA’s future vision for Earth science missions for global observations, and the challenges associated in applying them for societal benefit.

Upendra N Singh↗
NASA NTRS2009

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Peters-Lidard, Christa D.↗
NASA NTRS1990

Overview of the potential instrument payload for the EOS system

The Earth Observing System (EOS) is a key element of the U.S. Program in Global Change. It is NASA's initiative to provide the scientific means to observe the earth as a system. The EOS satellite system and accompanying Data and Information System (DIS) provide spacebased platforms and groundbased elements for scientific research and information extraction. The program recognizes the need for global coverage, long term observations, and multidisciplinary analyses in order to detect subtle changes in the environment's state. A multidisciplinary payload of active and passive sensors is proposed to accomplish the objectives of the program. International partners are an important element of the program. This paper focuses on the instrument complement for the EOS-A spacecraft since those decisions will occur this year. Significant programmatic constraints and program science decisions will impact the selection of the EOS-A payload.

Thompson, Leslie L.↗
NASA NTRS2016

Overview of the SMAP Applications and the SMAP Early Adopters Program - NASA's First Mission-Directed Outreach Effort

Satellite data provide global observations of many of the earths system processes and features. These data are valuable for developing scientific products that increase our understanding of how the earths systems are integrated. The water, energy and carbon cycle exchanges between the land and atmosphere are linked by soil moisture. NASAs Soil Moisture Active Passive (SMAP) mission provides soil moisture and freeze thaw measurements from space and allows scientists to link the water energy and carbon cycles. In order for SMAP data to be best integrated into decision support systems, the mission has engaged with the stakeholder community since 2009 and has attempted to scale the utility of the data to the thematic societal impacts of the satellite product applications. The SMAP Mission, which launched on January 31, 2015, has actively grown an Early Adopter (EA) community as part of its applications effort and worked with these EAs to demonstrate a scaled thematic impact of SMAP data product in societally relevant decision support applications. The SMAP mission provides global observations of the Earths surface soil moisture, providing high accuracy, resolution and continuous global coverage. Through the Early Adopters Program, the SMAP Applications Team will spend the next 2 years after launch documenting and evaluating the use of SMAP science products in applications related to weather forecasting, drought, agriculture productivity, floods, human health and national security.

SMAP↗
NASA NTRS2013

Smarter Earth Science Data System

The explosive growth in Earth observational data in the recent decade demands a better method of interoperability across heterogeneous systems. The Earth science data system community has mastered the art in storing large volume of observational data, but it is still unclear how this traditional method scale over time as we are entering the age of Big Data. Indexed search solutions such as Apache Solr (Smiley and Pugh, 2011) provides fast, scalable search via keyword or phases without any reasoning or inference. The modern search solutions such as Googles Knowledge Graph (Singhal, 2012) and Microsoft Bing, all utilize semantic reasoning to improve its accuracy in searches. The Earth science user community is demanding for an intelligent solution to help them finding the right data for their researches. The Ontological System for Context Artifacts and Resources (OSCAR) (Huang et al., 2012), was created in response to the DARPA Adaptive Vehicle Make (AVM) programs need for an intelligent context models management system to empower its terrain simulation subsystem. The core component of OSCAR is the Environmental Context Ontology (ECO) is built using the Semantic Web for Earth and Environmental Terminology (SWEET) (Raskin and Pan, 2005). This paper presents the current data archival methodology within a NASA Earth science data centers and discuss using semantic web to improve the way we capture and serve data to our users.

data center↗
NASA NTRS2010

Dynamic Optimization of Multi-Spacecraft Relative Navigation Configurations in the Earth-Moon System

In this paper, the notion of relative navigation introduced by Hill, Lo and Born is analyzed for a large class of periodic orbits in the Earth-Moon three-body problem, due to its potential in supporting Moon exploration efforts. In particular, a navigation metric is introduced and used as a cost function to optimize over a class of periodic orbits. While the problem could be solve locally as an optimal control problem, a dynamical based approach that allows for a global/systematic view of the problem is proposed. First, the simpler problem of multiple spacecraft placement on a given periodic orbit is solved before the notion of continuation and bifurcation analysis is used to expand the range of solutions thus obtained.

Three Body Problem↗
NASA NTRS2019

The Global Fire Atlas of Individual Fire Size, Duration, Speed and Direction

Natural and human-ignited fires affect all major biomes, altering ecosystem structure, biogeochemical cycles and atmospheric composition. Satellite observations provide global data on spatiotemporal patterns of biomass burning and evidence for the rapid changes in global fire activity in response to land management and climate. Satellite imagery also provides detailed information on the daily or sub-daily position of fires that can be used to understand the dynamics of individual fires. The Global Fire Atlas is a new global dataset that tracks the dynamics of individual fires to determine the timing and location of ignitions, fire size and duration, and daily expansion, fire line length, speed, and direction of spread. Here, we present the underlying methodology and Global Fire Atlas results for 2003–2016 derived from daily moderate-resolution (500 m) Collection 6 MCD64A1 burned-area data. The algorithm identified 13.3 million individual fires over the study period, and estimated fire perimeters were in good agreement with independent data for the continental United States. A small number of large fires dominated sparsely populated arid and boreal ecosystems, while burned area in agricultural and other human-dominated landscapes was driven by high ignition densities that resulted in numerous smaller fires. Long-duration fires in boreal regions and natural landscapes in the humid tropics suggest that fire season length exerts a strong control on fire size and total burned area in these areas. In arid ecosystems with low fuel densities, high fire spread rates resulted in large, short-duration fires that quickly consumed available fuels. Importantly, multiday fires contributed the majority of burned area in all biomass burning regions. A first analysis of the largest, longest and fastest fires that occurred around the world revealed coherent regional patterns of extreme fires driven by large-scale climate forcing. Global Fire Atlas data are publicly available through http://www.globalfiredata.org (last access: 9 August 2018) and https://doi.org/10.3334/ORNLDAAC/1642, and individual fire information and summary data products provide new information for benchmarking fire models within ecosystem and Earth system models, understanding vegetation–fire feedbacks, improving global emissions estimates, and characterizing the changing role of fire in the Earth system.

global fire atlas↗
NASA NTRS1983

Infrared limb-darkening effects for the earth-atmosphere system

An infrared radiative transfer model has been developed for evaluating anisotropic functions in the longwave region (5-50 microns) due to limb-darkening effects in the earth's atmosphere. An accurate narrow-band model of absorption has been used for computing transmission functions of the atmosphere. Absorption due to all major and minor atmospheric constituents has been taken into account including the continuum absorption due to water vapor. Anisotropic functions have been calculated for several latitudinal and seasonal climatological-average model atmospheres. The effects of the variability of various meteorological parameters, e.g. surface temperature, surface relative humidity, and cloud-top height have been examined. It has been found that the variability of cloud parameters has the largest effect on the infrared anisotropic functions.

Gupta, S. K.↗
NASA NTRS1988

Near term space transportation systems for earth orbit and planetary applications

With the resumption of Space Shuttle flights in mid-1988, many of the initial flights will include a mix of upper stage propulsion systems for geosynchronous orbit and planetary mission applications. This paper presents a system definition and the modifications required to the Inertial Upper Stage and the Transfer Orbit Stage for the near term Space Shuttle missions, namely the Tracking and Data Relay Satellite, Magellan, Galileo, Ulysses, Mars Observer, and the Advanced Communications Technology Satellite. The definition and capabilities of the Orbital Maneuvering Vehicle, currently being developed by NASA to perform a wide range of on-orbit missions and services in support of orbiting spacecraft, are also included.

Saucier, Sidney↗
NASA NTRS1980

Geophysical parameters of the earth-moon system

Doppler tracking data from Lunar Orbiter 4 have been combined with laser ranging data from lunar retroreflectors to yield a number of geophysical and geodetic parameters for the earth and moon. This joint solution gives values of (1) the lunar principal polar moment C/M R squared = 0.3905 plus or minus 0.0023, (2) GM(E) = 398600.461 plus or minus 0.026 cu km/sq s, and (3) an earth/moon mass ratio at 81.300587 plus or minus 0.000049. Also determined are the harmonics of a complete lunar gravity field through degree and order 5, the obliquity of the lunar pole, selenocentric coordinates of the lunar retroreflectors, geocentric coordinates of the McDonald Observatory, and the lunar secular acceleration. The lunar potential Love number is weakly determined at 0.022 plus or minus 0.013, and a suprisingly large dissipation of rotational energy is inferred, though either solid body tidal dissipation or liquid core mantle interactions could be causes.

Ferrari, A. J.↗
NASA NTRS1994

Earth Observing System (EOS)/Advanced Microwave Sounding Unit-A (AMSU-A) worst-case analysis: Antenna beam pointing

This report presents a worst-case analysis of the EOS/AMSU-A (Earth Observing System/Advanced Microwave Sounding Unit-A) Antenna beam-pointing accuracy. There are three sources of beam pointing error. These are mechanical tolerances in the manufacture and assembly of the parts, allowable axial displacement of the reflector relative to the motor shaft, and on-orbit thermal distortions. For the worst-case analysis, each will be assumed to act independently and thus each contribution is additive.

Ely, Wayne↗
NASA NTRS1976

Advanced Earth Observation System Instrumentation Study (AEOSIS)

The feasibility, practicality, and cost are investigated for establishing a national system or grid of artificial landmarks suitable for automated (near real time) recognition in the multispectral scanner imagery data from an earth observation satellite (EOS). The intended use of such landmarks, for orbit determination and improved mapping accuracy is reviewed. The desirability of using xenon searchlight landmarks for this purpose is explored theoretically and by means of experimental results obtained with LANDSAT 1 and LANDSAT 2. These results are used, in conjunction with the demonstrated efficiency of an automated detection scheme, to determine the size and cost of a xenon searchlight that would be suitable for an EOS Searchlight Landmark Station (SLS), and to facilitate the development of a conceptual design for an automated and environmentally protected EOS SLS.

Var, R. E.↗
NASA NTRS1984

Earth observing system (Eos) requirements for a polar platform

This paper describes the requirements that the polar platform will have to meet if it is to satisfy the needs of the scientific earth observation communities in the early 1990s. The Eos is a prime mission for the polar platform. The polar platform will be a large satellite in a sun synchronous orbit that could be built up from the same components that are to be used to build the Space Station and its co-orbiting freeflying satellite. It will be serviced from the Shuttle so that it will be kept in operation and up-to-date for at least a decade. An initial set of scientific requirements has been documented by a Science and Missions Requirements Working Group (S&MRWG). These scientific requirements have been translated into derived technical requirements for the polar platform. These derived requirements are presented.

Muller, R. M.↗
NASA NTRSDate not supplied

Millimeter Wave Airborne Radar System for Earth Science Applications

The innovative element of this IRAD will be the merging inexpensive components into a design that yields a SWaP-C (i.e., size, weight, power, and/or cost) system suitable to be mounted on unmanned aerial vehicles (UAVs) or be integrated with larger ground-based radars to provide intermediate atmospheric sensing.

Clouds and precipitation↗
NASA NTRS1992

Science Goals and Mission Objectives of Nasa's Laser Atmospheric Wind Sounder Program

Knowledge of the global wind field is widely recognized as fundamental to advancing our understanding and prediction of the total Earth system. Yet, because wind profiles are primarily measured by land-based rawinsondes, the oceanic areas (covering three quarters of the Earth's surface) and many regions of the less developed southern hemisphere land areas are poorly observed. The gap between our requirements for wind data and their availability continues to widen. For example, as faster computers become available to model the atmosphere with ever increasing resolution and sophistication, our ability to model the atmosphere will be hampered by a lack of data, particularly wind profiles. In order to address this important deficiency in wind observations, NASA plans to construct the Laser Atmospheric Wind Sounder (LAWS) instrument, with deployment tentatively scheduled between 2002 and 2005 as part of NASA's Earth Observing System (EOS) mission. Addressed here is the importance of wind measurements for advancing our understanding and prediction of the total Earth System. The current characteristics of the LAWS instrument under study are also summarized.

Baker, Wayman E.↗
NASA NTRS2004

Making NASA Earth Observing System Satellite Data Accessible to the K-12 and Citizen Scientist Communities

The Atmospheric Sciences Data Center (ASDC) at NASA s Langley Research Center houses over 700 data sets related to Earth s radiation budget, clouds, aerosols and tropospheric chemistry. These data sets are produced to increase academic understanding of the natural and anthropogenic perturbations that influence global climate change. The Mentoring and inquirY using NASA Data on Atmospheric and earth science for Teachers and Amateurs (MY NASA DATA) project has been established to systematically support educational activities at all levels of formal and informal education by reducing these large data holdings to microsets that will be easily explored and understood by the K-12 and the amateur scientist communities

Moore, Susan W.↗