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NASA NTRS2000

Section on Observed Impacts on El Nino

Agricultural applications of El Nino forecasts are already underway in some countries and need to be evaluated or re-evaluated. For example, in Peru, El Nino forecasts have been incorporated into national planning for the agricultural sector, and areas planted with rice and cotton (cotton being the more drought-tolerant crop) are adjusted accordingly. How well are this and other such programs working? Such evaluations will contribute to the governmental and intergovernmental institutions, including the Inter-American Institute for Global Change Research and the US National Ocean and Atmospheric Agency that are fostering programs to aid the effective use of forecasts. As El Nino climate forecasting grows out of the research mode into operational mode, the research focus shifts to include the design of appropriate modes of utilization. Awareness of and sensitivity to the costs of prediction errors also grow. For example, one major forecasting model failed to predict the very large El Nino event of 1997, when Pacific sea-surface temperatures were the highest on record. Although simple correlations between El Nino events and crop yields may be suggestive, more sophisticated work is needed to understand the subtleties of the interplay among the global climate system, regional climate patterns, and local agricultural systems. Honesty about the limitations of an forecast is essential, especially when human livelihoods are at stake. An end-to-end analysis links tools and expertise from the full sequence of ENSO cause-and-effect processes. Representatives from many disciplines are needed to achieve insights, e.g, oceanographers and atmospheric scientists who predict El Nino events, climatologists who drive global climate models with sea-surface temperature predictions, agronomists who translate regional climate connections in to crop yield forecasts, and economists who analyze market adjustments to the vagaries of climate and determine the value of climate forecasts. Methods include historical studies to understand past patterns and to test hindcasts of the prediction tools, crop modeling, spatial analysis and remote sensing. This research involves expanding, deepening, and applying the understanding of physical climate to the fields of agronomy and social science; and the reciprocal understanding of crop growth and farm economics to climatology. Delivery of a regional climate forecast with no information about how the climate forecast was derived limits its effectiveness. Explanation of a region's major climate driving forces helps to place a seasonal forecast in context. Then, a useful approach is to show historical responses to previous El Nino events, and projections, with uncertainty intervals, of crop response from dynamic process crop growth models. Regional ID forecasts should be updated with real-time weather conditions. Since every El Nino event is different, it is important to track, report and advise on each new event as it unfolds. The stability of human enterprises depends on understanding both the potentialities and the limits of predictability. Farmers rely on past experience to anticipate and respond to fluctuations in the biophysical systems on which their livelihoods depend. Now scientists are improving their ability to predict some major elements of climate variability. The improvements in the reliability of El Nino forecasts are encouraging, but seasonal forecasts for agriculture are not, and will probably never be completely infallible, due to the chaotic nature of the climate system. Uncertainties proliferate as we extend beyond Pacific sea-surface temperatures to climate teleconnections and agricultural outcomes. The goal of this research is to shed as a clear light as possible on these inherent uncertainties and thus to contribute to the development of appropriate responses to El Nino and other seasonal forecasts for a range of stakeholders, which, ultimately, includes food consumers everywhere.

Rosenzweig, Cynthia↗

NASA NTRS1998

Evaluation of Landscape Structure Using AVIRIS Quicklooks and Ancillary Data

Currently the best tool for examining landscape structure is remote sensing, because remotely sensed data provide complete and repeatable coverage over landscapes in many climatic regimes. Many sensors, with a variety of spatial scales and temporal repeat cycles, are available. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has imaged over 4000 scenes from over 100 different sites throughout North America. For each of these scenes, one-band "quicklook" images have been produced for review by AVIRIS investigators. These quicklooks are free, publicly available over the Internet, and provide the most complete set of landscape structure data yet produced. This paper describes the methodologies used to evaluate the landscape structure of quicklooks and generate corresponding datasets for climate, topography and land use. A brief discussion of preliminary results is included at the end. Since quicklooks correspond exactly to their parent AVIRIS scenes, the methods used to derive climate, topography and land use data should be applicable to any AVIRIS analysis.

Sanderson, Eric W.↗

NASA NTRS2000

Thermal Remote Sensing and the Thermodynamics of Ecosystem Development

Luvall, Jeffrey C.↗

NASA NTRS2000

The Use of Thermal Remote Sensing to Study Thermodynamics of Ecosystem Development

Luvall, Jeffrey C.↗

NASA NTRS2001

Thermal Remote Sensing and the Thermodynamics of Ecosystems Development

Luvall, Jeffrey C.↗

NASA NTRS2001

Real-Time Optical Monitoring of Flow Kinetics and Gas Phase Reactions Under High-Pressure OMCVD Conditions

This contribution addresses the real-time optical characterization of gas flow and gas phase reactions as they play a crucial role for chemical vapor phase depositions utilizing elevated and high pressure chemical vapor deposition (HPCVD) conditions. The objectives of these experiments are to validate on the basis of results on real-time optical diagnostics process models simulation codes, and provide input parameter sets needed for analysis and control of chemical vapor deposition at elevated pressures. Access to microgravity is required to retain high pressure conditions of laminar flow, which is essential for successful acquisition and interpretation of the optical data. In this contribution, we describe the design and construction of the HPCVD system, which include access ports for various optical methods of real-time process monitoring and to analyze the initial stages of heteroepitaxy and steady-state growth in the different pressure ranges. To analyze the onset of turbulence, provisions are made for implementation of experimental methods for in-situ characterization of the nature of flow. This knowledge will be the basis for the design definition of experiments under microgravity, where gas flow conditions, gas phase and surface chemistry, might be analyzed by remote controlled real-time diagnostics tools, developed in this research project.

Dietz, N.↗

NASA NTRS2001

A Genuine TEAM Player

Qualtech Systems, Inc. developed a complete software system with capabilities of multisignal modeling, diagnostic analysis, run-time diagnostic operations, and intelligent interactive reasoners. Commercially available as the TEAMS (Testability Engineering and Maintenance System) tool set, the software can be used to reveal unanticipated system failures. The TEAMS software package is broken down into four companion tools: TEAMS-RT, TEAMATE, TEAMS-KB, and TEAMS-RDS. TEAMS-RT identifies good, bad, and suspect components in the system in real-time. It reports system health results from onboard tests, and detects and isolates failures within the system, allowing for rapid fault isolation. TEAMATE takes over from where TEAMS-RT left off by intelligently guiding the maintenance technician through the troubleshooting procedure, repair actions, and operational checkout. TEAMS-KB serves as a model management and collection tool. TEAMS-RDS (TEAMS-Remote Diagnostic Server) has the ability to continuously assess a system and isolate any failure in that system or its components, in real time. RDS incorporates TEAMS-RT, TEAMATE, and TEAMS-KB in a large-scale server architecture capable of providing advanced diagnostic and maintenance functions over a network, such as the Internet, with a web browser user interface.

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NASA NTRS2003

A Fast Implementation of the ISOCLUS Algorithm

Unsupervised clustering is a fundamental tool in numerous image processing and remote sensing applications. For example, unsupervised clustering is often used to obtain vegetation maps of an area of interest. This approach is useful when reliable training data are either scarce or expensive, and when relatively little a priori information about the data is available. Unsupervised clustering methods play a significant role in the pursuit of unsupervised classification. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points (or samples) in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute a set of cluster centers in d-space. Although there is no specific optimization criterion, the algorithm is similar in spirit to the well known k-means clustering method in which the objective is to minimize the average squared distance of each point to its nearest center, called the average distortion. One significant feature of ISOCLUS over k-means is that clusters may be merged or split, and so the final number of clusters may be different from the number k supplied as part of the input. This algorithm will be described in later in this paper. The ISOCLUS algorithm can run very slowly, particularly on large data sets. Given its wide use in remote sensing, its efficient computation is an important goal. We have developed a fast implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm, the filtering algorithm, by Kanungo et al.. They showed that, by storing the data in a kd-tree, it was possible to significantly reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm. For technical reasons, which are explained later, it is necessary to make a minor modification to the ISOCLUS specification. We provide empirical evidence, on both synthetic and Landsat image data sets, that our algorithm's performance is essentially the same as that of ISOCLUS, but with significantly lower running times. We show that our algorithm runs from 3 to 30 times faster than a straightforward implementation of ISOCLUS. Our adaptation of the filtering algorithm involves the efficient computation of a number of cluster statistics that are needed for ISOCLUS, but not for k-means.

Memarsadeghi, Nargess↗

NASA NTRS2003

The Cloud Radar System

Improvement in our understanding of the radiative impact of clouds on the climate system requires a comprehensive view of clouds including their physical dimensions, dynamical generation processes, and detailed microphysical properties. To this end, millimeter vave radar is a powerful tool by which clouds can be remotely sensed. The NASA Goddard Space Flight Center has developed the Cloud Radar System (CRS). CRS is a highly sensitive 94 GHz (W-band) pulsed-Doppler polarimetric radar that is designed to fly on board the NASA high-altitude ER-2 aircraft. The instrument is currently the only millimeter wave radar capable of cloud and precipitation measurements from above most all clouds. Because it operates from high-altitude, the CRS provides a unique measurement perspective for cirrus cloud studies. The CRS emulates a satellite view of clouds and precipitation systems thus providing valuable measurements for the implementation and algorithm validation for the upcoming NASA CloudSat mission that is designed to measure ice cloud distributions on the global scale using a spaceborne 94 GHz radar. This paper describes the CRS instrument and preliminary data from the recent Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE). The radar design is discussed. Characteristics of the radar are given. A block diagram illustrating functional components of the radar is shown. The performance of the CRS during the CRYSTAL-FACE campaign is discussed.

Racette, Paul↗

NASA NTRS2004

Simulation of Avifauna Distributions Using Remote Sensing

Remote sensing has proved a fruitful tool for understanding the distribution and functioning of plant communities at multiple scales and to understand their coupling to bioclimatic and anthropogenic factors. But a similar approach to understanding the distribution and abundance of bird species as well as many other animal organisms is lacking. The increasing need for such understanding is evident with the recent examples of threats to human health via avian vector transmission and the increasing emphasis on global conservation biology. From experimental observations we know that species richness tends to track biological or environmental gradients. In this paper, we explore the fundamental idea that thermal and water-relation environments of birds, as estimated from satellite data and biophysical models, can define the constraints on their Occurrences and richness. We develop individual bird energy budget models and use these models to define the climate space niche of birds. Using satellite data assimilation products to drive our models, we disperse a distribution of virtual or actual bird species across the landscape in accordance to the limits expressed by their climate space niche. Here, we focus on the North American summer breeding season and give two examples to illustrate our approach. The first is a tundra loving bird, e.g. corresponding to the Culidris genus, and a second genus example, Myiurchus, that corresponds to arid or semi-arid regions. We define these birds in terms of their basic physiology and morphological characteristics, construct avian energetic simulations to predict their allowable metabolic ranges and climate space limits.

Smith, James A.↗

NASA NTRS2007

Evaluation of Integrating the Invasive Species Forecasting System to Support National Park Service Decisions on Fire Management Activities and Invasive Plant Species Control

The USGS and NASA, in conjunction with Colorado State University, George Mason University and other partners, have developed the Invasive Species Forecasting System (ISFS), a flexible tool that capitalizes on NASA's remote sensing resource to produce dynamic habitat maps of invasive terrestrial plant species across the United States. In 2006 ISFS was adopted to generate predictive invasive habitat maps to benefit noxious plant and fire management teams in three major National Park systems: The Greater Yellowstone Area (Yellowstone / Grand Tetons National Parks), Sequoia and Kings Canyon National Park, and interior Alaskan (between Denali, Gates of The Arctic and Yukon-Charley). One of the objectives of this study is to explore how the ISFS enhances decision support apparatus in use by National Park management teams. The first step with each park system was to work closely with park managers to select top-priority invasive species. Specific species were chosen for each study area based on management priorities, availability of observational data, and their potential for invasion after fire disturbances. Once focal species were selected, sources of presence/absence data were collected from previous surveys for each species in and around the Parks. Using logistic regression to couple presence/absence points with environmental data layers, the first round of ISFS habitat suitability maps were generated for each National Park system and presented during park visits over the summer of 2006. This first engagement provided a demonstration of what the park service can expect from ISFS and initiated the ongoing dialog on how the parks can best utilized the system to enhance their decisions related to invasive species control. During the park visits it was discovered that separate "expert opinion" maps would provide a valuable baseline to compare against the ISFS model output. Opinion maps are a means of spatially representing qualitative knowledge into a quantitative two-dimensional map. Furthermore, our approach combines the qualitative expert opinion habitat maps -- with the quantitative ISFS habitat maps in a difference map that shows where the two maps agree and disagree. The objective of the difference map is to help focus future field sampling and improve model results. This paper presents a demonstration of the habitat, expert opinion, and difference map for Yellowstone National Park.

Ma, Peter↗

NASA NTRS2006

NASA Tech Briefs, December 2006

Topic include: Inferring Gear Damage from Oil-Debris and Vibration Data; Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs; User Interactive Software for Analysis of Human Physiological Data; Representation of Serendipitous Scientific Data; Automatic Locking of Laser Frequency to an Absorption Peak; Self-Passivating Lithium/Solid Electrolyte/Iodine Cells; Four-Quadrant Analog Multipliers Using G4-FETs; Noise Source for Calibrating a Microwave Polarimeter; Hybrid Deployable Foam Antennas and Reflectors; Coating MCPs with AlN and GaN; Domed, 40-cm-Diameter Ion Optics for an Ion Thruster; Gesture-Controlled Interfaces for Self-Service Machines; Dynamically Alterable Arrays of Polymorphic Data Types; Identifying Trends in Deep Space Network Monitor Data; Predicting Lifetime of a Thermomechanically Loaded Component; Partial Automation of Requirements Tracing; Automated Synthesis of Architecture of Avionic Systems; SSRL Emergency Response Shore Tool; Wholly Aromatic Ether-Imides as n-Type Semiconductors; Carbon-Nanotube-Carpet Heat-Transfer Pads; Pulse-Flow Microencapsulation System; Automated Low-Gravitation Facility Would Make Optical Fibers; Alignment Cube with One Diffractive Face; Graphite Composite Booms with Integral Hinges; Tool for Sampling Permafrost on a Remote Planet; and Special Semaphore Scheme for UHF Spacecraft Communications.

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NASA NTRS2011

Monitoring Global Freshwater Resources with GRACE

Freshwater resources include surface waters, groundwater, and seasonal snowpack. Given adequate ground based measurements, all of these can be monitored effectively, however, outside of the developed world such measurements often are not systematic and the data not centralized, and as a result reports of freshwater availability may be largely anecdotal. Even in the developed world it can be difficult to quantify changes in groundwater storage over large scales. Owing to its global coverage, satellite remote sensing has become a valuable tool for freshwater resources assessment. In particular, the Gravity Recovery and Climate Experiment (GRACE) has demonstrated an unequaled ability to monitor total terrestrial water storage including groundwater at regional to continental scales. In this presentation we will identify apparent trends in terrestrial water storage observed by GRACE over the past nine years and attempt to explain their origins and predict whether they are likely to continue. Trends in certain regions where groundwater extraction has significantly depleted aquifers, including northern India and California, will be discussed in detail.

Rodell, Matt↗

NASA NTRS2012

Laboratory Studies of Solid Carbon Dioxide in Planetary and Interstellar Ices

Laboratory spectra have shown that CO2. is a powerful diagnostic tool for analyzing infrared data from remote observations, as it has been detected on icy moons in the outer solar system as well as dust grain surfaces in the interstellar medium. IR absorption profiles of CO2 wi thin ice mixtures containing H2O and CH30H change with respect to tem perature and mixture ratios. In this particular study, the CO2 stretch mode around 235O cm (exp -1) (4.3 rricrons) is systematically observ ed in different mixtures with H2O and CH30H in temperature ranges from 15K to 150 K, as well as vibrational modes in the near-IR such as th e combination bands near 3700 cm (exp -1) (2.7 microns) and 5080 (exp -1) (2.0 microns). Additionally, some high?temperature deposits (T > 50 K) of H2O, CH30H, and CO2 ice mixtures were performed to determine the maximum temperatures at which CO2 will deposit on the sample win dow. These data may then be used to interpret spectra obtained from remote IR observations. This research was sponsored by Oak Ridge Associ ated Universities (ORAU) through the NASA Postdoctoral Program (NPP) as well as Ames Research Center and the SETI institute who provided fa cilities and equipment.

White, Douglas↗

NASA NTRS2012

Laboratory Spectra of CO2 Vibrational Modes in Planetary Ice Analogs

Laboratory spectra have shown that CO2 is a powerful diagnostic tool for analyzing infrared data from remote observations, as it has been detected on icy moons in the outer Solar System as well as dust grain surfaces in the interstellar medium (ISM). IR absorption band profiles of CO2 within ice mixtures containing H2O and CH3OH change with respect to temperature and mixture ratios. In this particular study, the CO2 asymmetric stretching mode near 4.3 m (2350 cm (exp-1)), overtone mode near 1.97 m (5080 cm (exp-1)), and the combination bands near 2.7 m (3700 cm (exp-1)), 2.8 m (3600 cm (exp-1)), and 2.02 m (4960 cm (exp -1)), are systematically observed in different mixtures with H2O and CH3OH in temperature ranges from 15K to 150 K. Additionally, some high-temperature deposits (T greater than 50 K) of H2O, CH3OH, and CO2 ice mixtures were performed. These data may then be used to interpret infrared observational data obtained from icy surfaces in the outer Solar System and beyond.

White, Douglas↗

NASA NTRS2013

Thermal Remote Sensing and the Thermodynamics of Ecosystem Development

Thermal remote sensing can provide environmental measuring tools with capabilities for measuring ecosystem development and integrity. Recent advances in applying principles of nonequilibrium thermodynamics to ecology provide fundamental insights into energy partitioning in ecosystems. Ecosystems are nonequilibrium systems, open to material and energy flows, which grow and develop structures and processes to increase energy degradation. More developed terrestrial ecosystems will be more effective at dissipating the solar gradient (degrading its exergy content) and can be measured by the effective surface temperature of the ecosystem on a landscape scale. Ecosystems are viewed as open thermodynamic systems with a large gradient impressed on them by the exergy flux from the sun. Ecosystems, according to the restated second law, develop in ways that systematically increases their ability to degrade the incoming solar exergy, hence negating it's ability to set up even larger gradients. Thus it should be expected that more mature ecosystems degrade the exergy they capture more completely than a less developed ecosystem. The degree to which incoming solar exergy is degraded is a function of the surface temperature of the ecosystem. If a group of ecosystems receives the same amount of incoming radiation, we would expect that the most mature ecosystem would reradiate its energy at the lowest quality level and thus would have the lowest surface temperature (coldest black body temperature). Initial development work was done using NASA's airborne Thermal Infrared Multispectral Scanner (TIMS) followed by the use of a multispectral visible and thermal scanner-Airborne Thermal and Land Applications Sensor (ATLAS). Luvall and his coworkers have documented ecosystem energy budgets, including tropical forests, midlatitude varied ecosystems, and semiarid ecosystems. These data show that under similar environmental conditions (air temperature, relative humidity, winds, and solar irradiance) and within a given biome type, the more developed the ecosystem, the cooler it's surface temperature and the more degraded the quality of it's reradiated energy. HyspIRI is a hyperspectral visible/Near IR and multispectral thermal future global satellite mission that will collect data to study the world's ecosystems and will provide a benchmark on the state of the worlds ecosystems against which future changes can be assessed. HyspIRI will provide global data sets that will provide a means for measuring ecosystem development and integrity.

Luvall, Jeffrey C.↗

NASA NTRS2013

Thermal Remote Sensing and the Thermodynamics of Ecosystem Development

Thermal remote sensing can provide environmental measuring tools with capabilities for measuring ecosystem development and integrity. Recent advances in applying principles of nonequilibrium thermodynamics to ecology provide fundamental insights into energy partitioning in ecosystems. Ecosystems are nonequilibrium systems, open to material and energy flows, which grow and develop structures and processes to increase energy degradation. More developed terrestrial ecosystems will be more effective at dissipating the solar gradient (degrading its exergy content) and can be measured by the effective surface temperature of the ecosystem on a landscape scale. Ecosystems are viewed as open thermodynamic systems with a large gradient impressed on them by the exergy flux from the sun. Ecosystems, according to the restated second law, develop in ways that systematically increases their ability to degrade the incoming solar exergy, hence negating it's ability to set up even larger gradients. Thus it should be expected that more mature ecosystems degrade the exergy they capture more completely than a less developed ecosystem. The degree to which incoming solar exergy is degraded is a function of the surface temperature of the ecosystem. If a group of ecosystems receives the same amount of incoming radiation, we would expect that the most mature ecosystem would reradiate its energy at the lowest quality level and thus would have the lowest surface temperature (coldest black body temperature). Initial development work was done using NASA's airborne Thermal Infrared Multispectral Scanner (TIMS) followed by the use of a multispectral visible and thermal scanner- Airborne Thermal and Land Applications Sensor (ATLAS). Luvall and his coworkers have documented ecosystem energy budgets, including tropical forests, midlatitude varied ecosystems, and semiarid ecosystems. These data show that under similar environmental conditions (air temperature, relative humidity, winds, and solar irradiance) and within a given biome type, the more developed the ecosystem, the cooler it's surface temperature and the more degraded the quality of it's reradiated energy. HyspIRI is a hyperspectral visible/Near IR and multispectral thermal future global satellite mission that will collect data to study the world's ecosystems and will provide a benchmark on the state of the worlds ecosystems against which future changes can be assessed. HyspIRI will provide global data sets that will provide a means for measuring ecosystem development and integrity.

Luvall, Jeffrey C.↗

NASA NTRS2018

Remote Sensing Applications for Water Resources Management, Including Droughts, Floods, and Associated Water Cycle Extremes II

Water resources management can benefit from applications of remote sensing and hydrologic models. These tools can be especially valuable during extreme events and in data-sparse regions. Observational platforms include the GPM, SMAP, Terra, Aqua, Landsat, GRACE, and Sentinel satellites, and other satellite and airborne platforms. They can support the operational water resources management community in responding to climate change, increases in climate variability and the frequency of extreme events. This session will highlight advances in the use of satellite, airborne and ground-based sensor networks to: measure the quantity/quality of hydrologic resources in the U.S. and internationally; provide information to water managers to improve water resources management; and support risk-based decision making. Topics of interest include (1) extreme events such as floods and droughts; (2) water supply and snow water resource monitoring and forecasting; (3) evapotranspiration, soil moisture, groundwater, and agricultural water management; (4) water quality and (5) global water sustainability.

Bolten, John D.↗