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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Linkages between terrestrial ecosystems and the atmosphere

The primary research issue in understanding the role of terrestrial ecosystems in global change is analyzing the coupling between processes with vastly differing rates of change, from photosynthesis to community change. Representing this coupling in models is the central challenge to modeling the terrestrial biosphere as part of the earth system. Terrestrial ecosystems participate in climate and in the biogeochemical cycles on several temporal scales. Some of the carbon fixed by photosynthesis is incorporated into plant tissue and is delayed from returning to the atmosphere until it is oxidized by decomposition or fire. This slower (i.e., days to months) carbon loop through the terrestrial component of the carbon cycle, which is matched by cycles of nutrients required by plants and decomposers, affects the increasing trend in atmospheric CO2 concentration and imposes a seasonal cycle on that trend. Moreover, this cycle includes key controls over biogenic trace gas production. The structure of terrestrial ecosystems, which responds on even longer time scales (annual to century), is the integrated response to the biogeochemical and environmental constraints that develop over the intermediate time scale. The loop is closed back to the climate system since it is the structure of ecosystems, including species composition, that sets the terrestrial boundary condition in the climate system through modification of surface roughness, albedo, and, to a great extent, latent heat exchange. These separate temporal scales contain explicit feedback loops which may modify ecosystem dynamics and linkages between ecosystems and the atmosphere. The long-term change in climate, resulting from increased atmospheric concentrations of greenhouse gases (e.g., CO2, CH4, and nitrous oxide (N2O)) will further modify the global environment and potentially induce further ecosystem change. Modeling these interactions requires coupling successional models to biogeochemical models to physiological models that describe the exchange of water, energy, and biogenic trace gases between the vegetation and the atmosphere at fine time scales. There does not appear to be any obvious way to allow direct reciprocal coupling of atmospheric general circulation models (GCM's), which inherently run with fine time steps, to ecosystem or successional models, which have coarse temporal resolution, without the interposition of physiological canopy models. This is equally true for biogeochemical models of the exchange of carbon dioxide and trace gases. This coupling across time scales is nontrivial and sets the focus for the modeling strategy.

Bretherton, Francis↗
NASA NTRS2007

Coincident Occurrences of Tropical Individual Cirrus Clouds and Deep Convective Systems Derived from TRMM Observations

Measurements of cloud properties and atmospheric radiation taken between January and August 1998 by the Tropical Rainfall Measuring Mission (TRMM) satellite were used to investigate the effect of spatial and temporal scales on the coincident occurrences of tropical individual cirrus clouds (ICCs) and deep convective systems (DCSs). It is found that there is little or even negative correlation between instantaneous occurrences of ICC and DCS in small areas, in which both types of clouds cannot grow and expand simultaneously. When spatial and temporal domains are increased, ICCs become more dependent on DCSs due to the origination of many ICCs from DCSs and moisture supply from the DCS in the upper troposphere for the ICCs to grow, resulting in significant positive correlation between the two types of tropical high clouds in large spatial and long temporal scales. This result may suggest that the decrease of tropical high clouds with SST from model simulations is likely caused by restricted spatial domains and limited temporal periods. Finally, the radiative feedback due to the change in tropical high cloud area coverage with sea surface temperature appears small and about -0.14 W/sq m per degree Kelvin.

Lin, Bing↗
NASA NTRS2018

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗
NASA NTRS2018

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗
NASA NTRS2010

Magnetic Reconnection: A Fundamental Process in Space Plasmas

For many years, collisionless magnetic reconnect ion has been recognized as a fundamental process, which facilitates plasma transport and energy release in systems ranging from the astrophysical plasmas to magnetospheres and even laboratory plasma. Beginning with work addressing solar dynamics, it has been understood that reconnection is essential to explain solar eruptions, the interaction of the solar wind with the magnetosphere, and the dynamics of the magnetosphere. Accordingly, the process of magnetic reconnection has been and remains a prime target for space-based and laboratory studies, as well as for theoretical research. Much progress has been made throughout the years, beginning with indirect verifications by studies of processes enabled by reconnection, such as Coronal Mass Ejections, Flux Transfer Events, and Plasmoids. Theoretical advances have accompanied these observations, moving knowledge beyond the Sweet-Parker theory to the recognition that other, collisionless, effects are available and likely to support much faster reconnect ion rates. At the present time we are therefore near a break-through in our understanding of how collisionless reconnect ion works. Theory and modeling have advanced to the point that two competing theories are considered leading candidates for explaining the microphysics of this process. Both theories predict very small spatial and temporal scales. which are. to date, inaccessible to space-based or laboratory measurements. The need to understand magnetic reconnect ion has led NASA to begin the implementation of a tailored mission, Magnetospheric MultiScale (MMS), a four spacecraft cluster equipped to resolve all relevant spatial and temporal scales. In this presentation, we present an overview of current knowledge as well as an outlook towards measurements provided by MMS.

Hesse, Michael↗
NASA NTRSDate not supplied

A Model for Ice Accretion Roughness Evolution and Spatial Variations

Over the past decade, multiple investigations of ice accretion roughness and spatial variations have been performed in the Icing Research Tunnel (IRT) at the NASA Glenn Research Center. The early investigations used models of NACA 0012 airfoils with different chord sizes and focused on temporal scaling and primary cloud scaling parameters such as stagnation point collection efficiency. Subsequent investigations included the effects of model sweep, airfoil shape, airfoil lifting condition, and freestream static temperature. To develop a predictive model for roughness evolution in generalized icing situations, the maximum roughness values for the airfoils and conditions used in the angle of attack and freestream temperature investigations were scaled to eliminate the temporal variations. LEWICE simulations were employed to identify the local collection efficiency at the locations of maximum roughness, and a two-dimensional panel-method code was used to identify the local static pressure at the location of the maximum roughness. Because of the stochastic nature of ice accretion roughness, a physics-directed approach was employed to develop a multi-dimensional correlation based on the local pressure coefficient, the local total temperature, the cloud properties, and the cloud exposure time. The resulting correlation predictions are compared to ice shapes measured in the IRT for both a 21-in. NACA 0012 airfoil model and a 60-in. HAARP-II model. The resulting predictions indicate that the local freezing fraction must be included in the roughness predictive model. Implications regarding icing heat transfer predictions using the resulting roughness model are also discussed.

Icing↗
NASA NTRS2021

Systematic Review on Effects of Bioenergy From Edible Versus Inedible Feedstocks on Food Security

Achieving food security is a critical challenge of the Anthropocene that may conflict with environmental and societal goals such as increased energy access. The“fuel versus food”debate coupled with climate mitigation efforts has given rise to next-generation biofuels. Findings of this systematic review indicate just over half of the studies (56% of 224 publications) reported a negative impact of bioenergy production on food security. However, no relationship was found between bioenergy feedstocks that are edible versus inedible and food security (Pvalue=0.15). A strong relationship was found between bioenergy and type of food security parameter (Pvalue < 0.001), sociodemographic index of study location (Pvalue=0.001),spatial scale (Pvalue < 0.001), and temporal scale (Pvalue=0.017). Programs and policies focused on bioenergy and climat emitigation should monitor multiple food security parameters at various scales over the long term toward achieving diverse sustainability goals.

food security↗
NASA NTRS2001

A non-earthcentric approach to life detection

The ultimate goal of a comprehensive life detection strategy is never to miss life when we encounter it. To accomplish this goal, we must define life in universal, that is, non-Earthcentric, measurable terms. Next, we must understand the nature of biosignatures observed from the measured parameters of life. And finally, we must have a clear idea of the end-member states for the search--what does life, past life, or no life look like (in terms of the measured parameters) at multiple spatial and temporal scales? If we can approach these problems both in the laboratory and in the field on Earth, then we have a chance of being able to detect life elsewhere in our solar system. What are the required limits of detection at each of those scales? What spatial, spectral, and temporal resolutions are necessary to detect life? These questions are actively being investigated in our group, and in this report, we present our strategy and approach to non-Earthcentric life detection.

Extraterrestrial Environment↗
NASA NTRS1995

Finding the forest in the trees. The challenge of combining diverse environmental data

Development of analytical and functional guidelines to help researchers and technicians engaged in interdisciplinary research to better plan and implement their supporting data management activities is addressed. An emphasis is on the projects that involve both geophysical and ecological issues. Six case studies were used to identify and to understand problems associated with collecting, integrating, and analyzing environmental data from local to global spatial scales and over a range of temporal scales. These case studies were also used to elaborate the common barriers to interfacing data of disparate sources and types. A number of lessons derived from the case studies are summarized and analyzed.

Source record↗
NASA NTRS2004

Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data

Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

Minnis, Patrick↗
NASA NTRS2005

Plasma sheet turbulence observed by Cluster II

Cluster fluxgate magnetometer (FGM) and ion spectrometer (CIS) data are employed to analyze magnetic field fluctuations within the plasma sheet during passages through the magnetotail region in the summers of 2001 and 2002 and, in particular, to look for characteristics of magnetohydrodynamic (MHD) turbulence. Power spectral indices determined from power spectral density functions are on average larger than Kolmogorov's theoretical value for fluid turbulence as well as Kraichnan's theoretical value for MHD plasma turbulence. Probability distribution functions of the magnetic fluctuations show a scaling law over a large range of temporal scales with non-Gaussian distributions at small dissipative scales and inertial scales and more Gaussian distribution at large driving scales. Furthermore, a multifractal analysis of the magnetic field components shows scaling behavior in the inertial range of the fluctuations from about 20 s to 13 min for moments through the fifth order. Both the scaling behavior of the probability distribution functions and the multifractal structure function suggest that intermittent turbulence is present within the plasma sheet. The unique multispacecraft aspect and fortuitous spacecraft spacing allow us to examine the turbulent eddy scale sizes. Dynamic autocorrelation and cross correlation analysis of the magnetic field components allow us to determine that eddy scale sizes fit within the plasma sheet. These results suggest that magnetic field turbulence is occurring within the plasma sheet resulting in turbulent energy dissipation.

Weygand, James M.↗
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 NTRS1995

Finding the forest in the trees: The challenge of combining diverse environmental data

It has become increasingly important to conduct interdisciplinary environmental research assessments, both nationally and internationally. For this reason, the Committee for a Pilot Study on Database Interfaces was charged to review and advise on data interfacing activities. The committee used six case studies (1) to identify and understand the most important problems associated with collecting, integrating, and analyzing environmental data from local to global spatial scales and over a very wide range of temporal scales; and (2) to elaborate the common barriers to interfacing data of disparate sources and types. Consistent with the committee's charge, the primary focus was the interfacing of geophysical and ecological data. The case studies used by the committee were: The Impact Assessment Project for Drought Early Warning in the Sahel, The National Acid Precipitation Assessment Program, The H.J. Andrew Experimental Forest Long-Term Ecological Research Site, The Carbon Dioxide Information Analysis Center, The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment, and The California Cooperative Oceanic Fisheries Investigation. The committee derived a number of lessons from the case studies, and these lessons are summarized at the end of each case study and analyzed in the last chapter. Some are generic in nature; others are more specific to a discipline or project. The conclusions and recommendations are based on the committee's analysis of the case studies and additional research. They are organized according to four major areas of barriers or challenges to the effective interfacing of diverse environmental data. In the final section the committee offers a set of broadly applicable principles (Ten Keys to Success) that can be used by scientists and data managers in planning and conducting interfacing activities.

Source record↗
NASA NTRS2017

Cross-Disciplinarity in the Advance of Antarctic Ecosystem Research

The biodiversity, ecosystem services and climate variability of the Antarctic continent, and the Southern Ocean are major components of the whole Earth system. Antarctic ecosystems are driven more strongly by the physical environment than many other marine and terrestrial ecosystems. As a consequence, to understand ecological functioning, cross-disciplinary studies are especially important in Antarctic research. The conceptual study presented here is based on a workshop initiated by the Research Programme Antarctic Thresholds - Ecosystem Resilience and Adaption of the Scientific Committee on Antarctic Research, which focused on challenges in identifying and applying cross-disciplinary approaches in the Antarctic. Novel ideas, and first steps in their implementation, were clustered into eight themes, ranging from scale problems, risk maps, organism and ecosystem responses to multiple environmental changes, to evolutionary processes. Scaling models and data across different spatial and temporal scales were identified as an overarching challenge. Approaches to bridge gaps in the research programmes included multi-disciplinary monitoring, linking biomolecular findings and simulated physical environments, as well as integrative ecological modelling. New strategies in academic education are proposed. The results of advanced cross-disciplinary approaches can contribute significantly to our knowledge of ecosystem functioning, the consequences of climate change, and to global assessments that ultimately benefit humankind.

Scaling↗
NASA NTRS2016

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.

upscaling↗
NASA NTRS1993

Observational aspects of the low-frequency intraseasonal variability of the atmosphere in middle latitudes

An integrated description of the planetary-scale structures that emerge as organized entities on intraseasonal temporal scales in the middle latitudes is developed. Spatial scales of atmospheric motions involved in the generation of variability in the LF range are specified. An overview of the 3D structure of the seasonally averaged eddies in which the intraseasonal fluctuations are superposed is presented. The generation and maintenance mechanisms possibly responsible for the existence of the seasonal, quasi-stationary disturbances are discussed. It is shown that in the LF, low-zonal wavenumber part of the spectrum, the power displayed by standing variance exceeds that of propagating variance and vice versa for HFs and wavenumbers.

Pandolfo, Lionel↗
NASA NTRS2000

In-Situ Environmental Measurements Needed for Future Mars Missions

Existing measurements and modeling studies indicate that the climate and general circulation of the thin, predominately CO2 Martian atmosphere are characterized by large-amplitude variations with a wide range of spatial and temporal scales. Remote sensing observations from Earth-based telescopes and the Mariner 9, Viking, Phobos, and Mars Global Surveyor (MGS) orbiters show that the prevailing climate includes large-scale seasonal variations in surface and atmospheric temperatures (140 to 300 K), dust optical depth (0.15 to 1), and water vapor (10 to 100 precipitable microns). These observations also provided the first evidence for episodic regional and global dust storms that produce even larger perturbations in the atmospheric thermal structure and general circulation. In-situ measurements by the Viking and Mars Pathfinder Landers reinforced these conclusions, documenting changes in the atmospheric pressure on diurnal (5%) and seasonal (>20%) time scales, as well as large diurnal variations in the near-surface temperature (40 to 70 K), wind velocity (0 to 35 m/s), and dust optical depth (0.3 to 6). These in-situ measurements also reveal phenomena with temporal and spatial scales that cannot be resolved from orbit, including rapid changes in near-surface temperatures (+/- 10 K in 10 seconds), large near-surface vertical temperature gradients (+/- 15 K/meter), diurnally-varying slope winds, and dust devils . Modeling studies indicate that these changes are forced primarily by diurnal and seasonal variations in solar insolation, but they also include contributions from atmospheric thermal tides, baroclinic waves (fronts), Kelvin waves, slope winds, and monsoonal flows from the polar caps.

Crisp, D.↗
NASA NTRS1993

Transmantle flux tectonics

Venus, Earth, and Mars have surfaces that display topographic domes and depressions with quasi-circular planimetric shapes, relief of 0 to several km, and large spatial scales (10(exp 2) to 10(exp 4) km). Our morphostructural mapping reveals hierarchical arrangements of these features. They are explained by a model of long-acting mantle convection, as a particular case of convection in a stratified and random inhomogeneous medium, which develops the form of a hierarchy of different convective pattern scales, each arising from different levels in the mantle. The hypothesis of transmantle flux tectonics parsimoniously explains a diversity of seemingly unrelated terrestrial planetary phenomena, including Earth megaplumes, global resurfacing epochs on Venus, and cyclic ocean formation and global climate change for Mars. All these phenomenon are hypothesized to be parsimoniously explained by a process of transmantle flux tectonics in which long-acting mantle convection generates stresses in blocks of planetary lithosphere to produce distinctive quasi-circular global-hierarchical morphostructure (QGM) patterns. Transmantle flux tectonics differs from plume tectonics in that individual plumes are not considered in isolation. Rather, a wholly interactive process is envisioned in which various spatial and temporal scales of convection operate contemporaneously and hierarchically within other scales. This process of continual change by hierarchical convective cells affects the surface at varying temporal and spatial scales, and its effects are discernable through their relic geological manifestations, the QGM patterns.

Finn, V. J.↗