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At least 109 records · Page 6

Projected Changes to Hydroclimate Seasonality in the Continental United States

Future changes to the hydrological cycle are projected in a warming world, and any shifts in drought risk may prove extremely consequential for natural and human systems. In addition to long-term moistening, drying, or warming trends, perturbations to the annual cycle of regional hydroclimate variables may also have substantial impacts. We analyze projected changes in several hydroclimate variables across the continental United States, along with shifts in the amplitude and phase of their annual cycles. We find that even in regions where no robust change in the annual mean is expected, coherent changes to the annual cycle are projected. In particular, we identify robust regional phase shifts toward earlier arrival of peak evaporation in the northern regions, and peak runoff and total soil moisture in the western regions. Changes in the amplitude of the annual cycle of total and surface soil moisture are also projected, and reflect changes to the annual cycle in surface water supply and demand. Whether changes become detectable above the background noise of internal variability depends strongly on the future scenario considered, and significant changes to the annual cycle are largely avoided in the lowest-forcing scenario.

drought↗

LWS/SET Technology Experiment Carrier

This paper examines the approach taken to building a low-cost, modular spacecraft bus that can be used to support a variety of technology experiments in different space environments. It describes the techniques used and design drivers considered to ensure experiment independence from as yet selected host spacecraft. It describes the technology experiment carriers that will support NASA's Living With a Star Space Environment Testbed space missions. NASA has initiated the Living With a Star (LWS) Program to develop a better scientific understanding to address the aspects of the connected Sun-Earth system that affect life and society. A principal goal of the program is to bridge the gap between science, engineering, and user application communities. The Space Environment Testbed (SET) Project is one element of LWS. The Project will enable future science, operational, and commercial objectives in space and atmospheric environments by improving engineering approaches to the accommodation and/or mitigation of the effects of solar variability on technological systems. The SET Project is highly budget constrained and must seek to take advantage of as yet undetermined partnering opportunities for access to space. SET will conduct technology validation experiments hosted on available flight opportunities. The SET Testbeds will be developed in a manner that minimizes the requirements for accommodation, and will be flown as flight opportunities become available. To access the widest range of flight opportunities, two key development requirements are to maintain flexibility with respect to accommodation constraints and to have the capability to respond quickly to flight opportunities. Experiments, already developed to the technology readiness level of needing flight validation in the variable Sun-Earth environment, will be selected on the basis of the need for the subject technology, readiness for flight, need for flight resources and particular orbit. Experiments will be accumulated by the Project and manifested for specific flight opportunities as they become available. The SET Carrier is designed to present a standard set of interfaces to SET technology experiments and to be modular and flexible enough to interface to a variety of possible host spacecraft. The Carrier will have core components and mission unique components. Once the core carrier elements have been developed, only the mission unique components need to be defined and developed for any particular mission. This approach will minimize the mission specific cost and development schedule for a given flight opportunity. The standard set of interfaces provided by SET to experiments allows them to be developed independent of the particulars of a host spacecraft. The Carrier will provide the power, communication, and the necessary monitoring features to operate experiments. The Carrier will also provide all of the mechanical assemblies and harnesses required to adapt experiments to a particular host. Experiments may be hosted locally with the Carrier or remotely on the host spacecraft. The Carrier design will allow a single Carrier to support a variable number of experiments and will include features that support the ability to incrementally add experiments without disturbing the core architecture.

Sherman, Barry↗

Modeling Climate-Biosphere Interactions in the Boreal Forest

The overall goal of this BOREAS Program was to develop, test, and apply a model of the carbon balance of boreal forest sites with a significant groundcover component (moss or lichen). The basic question addressed with this model was: What is the sensitivity of the boreal forest carbon balance to weather variability? More specifically: What are the differences in the sensitivities of carbon gains (photosynthesis) and carbon losses (respiration) of the various components of the ecosystem? Are there different seasonalities to their sensitivities (e.g., warmer springs will have one effect, warmer summers a different effect)? What are the effects of different patterns of successive weather years (wet/dry, warm/cool)? What, for example, would be the difference in effects of two "warmer than normal" months-one with each day warmer than normal, and the other with three normal weeks and one very hot week? Due to weather variability, how "noisy" will any carbon flux or carbon pool signal be that we might use to try to detect change? The project resulted in the development of a new boreal forest ecosystem model. This model was the first model in the BOREAS project to look closely at the role of mosses in the ecosystem carbon balance, and also was the first model in the BOREAS project to look closely at interannual variability in carbon fluxes. Along with the work of many other groups, TE-19 modeling analysis pointed to the need for a second, longer field season in 1996, with particular focus on the spring and fall transitions and on ground vegetation. BOREAS groups TE-19 (Frolking), TGB-1 (Crill) & TGB-3 (Moore & Roulet) analyzed BOREAS data and other published and unpublished data to develop a relationship between peatland ecosystem productivity and incoming radiation, which is quite distinct from the upland ecosystem relationships observed in other studies.

Frolking, Steve↗

Differentiating the role of land surface variability and cloudiness variability on global energy transport within the atmosphere and oceans

The following provides the final report on NASA IDP Project NAGW-1840 'Differentiating the Role of Land Surface Variability on Global Energy Transport within the Atmosphere and Oceans'. The project was designed to investigate the role of regional perturbations in the earth radiation budget on atmospheric and oceanic energy transports on an interannual basis. We proposed a modeling strategy based on an entropy extremum principle that could be used to separate the transports into oceanic and atmospheric components so as to better understand the effects of regional perturbations at the distinct atmospheric and oceanic time scales. The original focus was to consider the maintenance and year-to-year modulation of a large-scale, low-latitude North African-West Pacific Ocean net radiation dipole, which we had detected in the Nimbus 6 and 7 record of earth radiation budget measurements, and which necessitated significant cross-meridional energy transports to maintain global equilibrium. In addition, perturbations in the radiation balance term were to be partitioned into cloud-induced and surface-induced components to better understand the feedbacks between clouds and surface boundary conditions on interannual variability of the radiation balance.

Smith, Eric A.↗

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗

Variable plant spacing

The goal of this project was to develop a system for varying the spacings between soybean plants as they grow to maximize the number of plants grown in a given volume. The project was studied to aid in the development of NASA's Controlled Ecological Life Support System (CELSS). The resulting design consists of plant trays which are three dimensional trapezoids arranged into circles in a compact geometrical configuration. These circles are stacked together in back to back pairs to form a long cylinder. In each growth tray, plants will be housed in individual containers containing a nutrient delivery system and a plant support mechanism. Between the containers, a half trellis has been designed to space the plants for maximum space efficiency. The design allows for localized seeding and harvesting mechanisms due to the chambers' geometrical configuration. In addition, the components have been designed for ease of cleaning and minimal maintenance. Next semester, the individual components will be constructed and tested to determine the success of the design.

Bledsoe, Jim↗

A method for linearizing a nonlinear system with six state variables and three control variables

A nonlinear system governed by x = f(x,u) with six state variables and three control variables is considered in this project. A set of transformations from (x,u) - space to (z,v) - space is defined such that the linear tangent model is independent of the operating point in the z-space. Therefore, it is possible to design a control law satisfying all operating points in the transformed space. An algorithm to construct the above transformations and to obtain the associated linearized system is described in this report. This method is applied to a rigid body using pole placement for the control law. Results are verified by numerical simulation. Closed loop poles in x-space using traditional local linearization are compared with those pole placements in the z-space.

Hsia, W. S.↗

Passive navigation using image irradiance tracking

Rotorcraft operating at low altitudes require navigational schemes for locating the terrain and obstacles. Due to the covert nature of missions to be accomplished, a passive navigation scheme is desirable. This paper describes the development of a passive navigation scheme combining image sequences from a vehicle mounted camera with vehicle motion variables. Geometric properties of perspective projection together with an image irradiance tracking scheme at each pixel are used to determine the range to various objects within the field-of-view. Derivation of the numerical algorithm and simulation results are given. Other applications of the proposed approach include navigation for autonomous planetary rovers and telerobots.

Menon, P. K. A.↗

A Lagrange multiplier based divide and conquer finite element algorithm

A novel domain decomposition method based on a hybrid variational principle is presented. Prior to any computation, a given finite element mesh is torn into a set of totally disconnected submeshes. First, an incomplete solution is computed in each subdomain. Next, the compatibility of the displacement field at the interface nodes is enforced via discrete, polynomial and/or piecewise polynomial Lagrange multipliers. In the static case, each floating subdomain induces a local singularity that is resolved very efficiently. The interface problem associated with this domain decomposition method is, in general, indefinite and of variable size. A dedicated conjugate projected gradient algorithm is developed for solving the latter problem when it is not feasible to explicitly assemble the interface operator. When implemented on local memory multiprocessors, the proposed methodology requires less interprocessor communication than the classical method of substructuring. It is also suitable for parallel/vector computers with shared memory and compares favorably with factorization based parallel direct methods.

Farhat, C.↗

Intensive Exercise Training During Bed Rest Attenuates Deconditioning

Intensive exercise training during bed rest attenuates deconditioning. Med. Sci. Sports Exerc., Vol. 29, No. 2, pp. 207-215, 1997. A 30-d 6 deg head-down bed rest project was conducted to evaluate variable high-intensity, short-duration, isotonic cycle ergometer exercise (ITE) training and high-intensity intermittent resistive isokinetic exercise (IKE) training regimens designed to maintain peak VO2 and muscle mass, strength, and endurance at ambulatory control levels throughout prolonged bed rest. Other elements of the deconditioning (adaptive) syndrome, such as proprioception, psychological performance, hypovolemia, water balance, body composition, and orthostatic tolerance, were also measured. Major findings are summarized in this paper. Compared with response during bed rest of the no exercise (NOE) control group: the ITE training regimen (a) maintained work capacity (peak VO2), (b) maintained plasma and red cell volumes, (c) induced positive body water balance, (d) decreased quality of sleep and mental concentration, and (e) had no effect on the decrease in orthostatic tolerance; the IKE training regimen (f) attenuated the decrease in peak VO2 by 50%, (g) attenuated loss of red cell volume by 40% but had no effect on loss of plasma volume, (b) induced positive body water balance, (i) had no adverse effect on quality of sleep or concentration, and 0) had no effect on the decrease in orthostatic tolerance. These findings suggest that various elements of the deconditioning syndrome can be manipulated by duration and intensity of ITE or IKE training regimens and that several different training protocols will be required to maintain or restore physiological and psychological performance of individuals confined to prolonged bed rest.

Greenleaf, John E.↗

Accurate Realization of GPS Vertical Global Reference Frame

The few millimeter per year level accuracy of radial global velocity estimates with the Global Positioning System (GPS) is at least an order of magnitude poorer than the accuracy of horizontal global motions. An improvement in the accuracy of radial global velocities would have a very positive impact on a number of geophysical studies of current general interest such as global sea-level and climate change, coastal hazards, glacial isostatic adjustment, atmospheric and oceanic loading, glaciology and ice mass variability, tectonic deformation and volcanic inflation, and geoid variability. The goal of this project is to improve our current understanding of GPS error sources associated with estimates of radial velocities at global scales. GPS error sources relevant to this project can be classified in two broad categories: (1) those related to the analysis of the GPS phase observable, and (2) those related to the combination of the positions and velocities of a set of globally distributed stations as determined from the analysis of GPS data important aspect in the first category include the effect on vertical rate estimates due to standard analysis choices, such as orbit modeling, network geometry, ambiguity resolution, as well as errors in models (or simply the lack of models) for clocks, multipath, phase-center variations, atmosphere, and solid-Earth tides. The second category includes the possible methods of combining and defining terrestrial reference flames for determining vertical velocities in a global scale. The latter has been the subject of our research activities during this reporting period.

Elosegui, Pedro↗

Monitoring Invasive Aquatic Vegetation in Lake Okeechobee, Florida, Using NDVI Derived from Modis Data

Lake Okeechobee, located in southern Florida, encompasses approximately 1,700 sq km and is a vital part of the Lake Okeechobee and Everglades ecosystem. Major cyanobacterial blooms have been documented in Lake Okeechobee since the 1970s and have continued to plague the ecosystem. Similarly, hydrilla, water hyacinth, and water lettuce have been documented in the lake and continue to threaten the ecosystem by their rapid growth. This study examines invasive aquatic vegetation occurrence through the use of the Normalized Difference Vegetation Index (NDVI) calculated on MOD09 surface reflectance imagery. Occurrence during 2008 was analyzed using the Time Series Product Tool (TSPT), a MATLAB-based program developed at John C. Stennis Space Center. This project tracked spatial and temporal variability of cyanobacterial blooms, and overgrowth of water lettuce, water hyacinth, and hydrilla. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer (MODIS) data to assist in water quality management.

Woods, Kate↗

Neural Network Machine Learning and Dimension Reduction for Data Visualization

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Liles, Charles A.↗

Inlet Turbulence and Length Scale Measurements in a Large Scale Transonic Turbine Cascade

Constant temperature hotwire anemometry data were acquired to determine the inlet turbulence conditions of a transonic turbine blade linear cascade. Flow conditions and angles were investigated that corresponded to the take-off and cruise conditions of the Variable Speed Power Turbine (VSPT) project and to an Energy Efficient Engine (EEE) scaled rotor blade tip section. Mean and turbulent flowfield measurements including intensity, length scale, turbulence decay, and power spectra were determined for high and low turbulence intensity flows at various Reynolds numbers and spanwise locations. The experimental data will be useful for establishing the inlet boundary conditions needed to validate turbulence models in CFD codes.

hotwire↗

Understanding the Uncertainty and Variability of Earth’s Radiation Budget Components Over the Past 3 Decades from the NASA’s GEWEX Surface Radiation Budget Release 4 Integrated Product

The NASA/GEWEX Surface Radiation Budget (SRB) project produced a 30+ year time series of 3-hourly Top-of-Atmosphere (TOA) and surface radiative flux components at a 1x1 degree resolution. This SRB Release 4 Integrated Productare derived using imager data products from the cross-calibrated from ISCCP (International Satellite Cloud Climatology Project) “HSeries” radiance, cloud and surface property data products. The ISCCP HXS product replaces ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use and discuss radiative flux sensitivities to in this presentation. Total solar irradiance is now variable consistent with SORCE measurements. Sea surface (SeaFlux v2.0) and land surface products (LandFlux) are utilized to achieve an radiative flux estimatesintegrated with global data sets from these GEWEX projects. The variable aerosol composition are specified using a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC) also used for background aerosol in the ISCCP HX. Numerous other improvements were made to the SW and LW algorithms including improved cloud optical property treatments and specification of surface spectral albedo and emissivity for various surface conditions. Here we analyze the new SWand LWSRB datasets, comparing them to the previous Release 3, BSRN, GEBA and PMEL surface measurements, and ERBE and CERES satellite datasets. For surface flux validation besides ensemble comparisons, we show the variability of SRB vs surface measurements from BSRN beginning in 1992 and GEBA SW from 1983. We assess the variability of the surface flux anomalies, particularly the net fluxes and the cloud radiative effects, over the entire time period including the period containing CERES overlap. For the TOA fluxes, the anomalies of the fluxes in the early period are compared to the MEaSURES ERBE and the latter period to CERES EBAF/SYN1Deg datasets for a benchmark. Long-term changes in the surface radiation budget components and cloud radiative effects are shown and discussed relative to CERES and surface measurements. This includes a change point analysis that helps associate various changes in the ISCCP GEO/LEO configurations and other inputs to variations in the radiative budget components.

Earth Radiation Budget↗

On-Line Analysis of Physiologic and Neurobehavioral Variables During Long-Duration Space Missions

The goal of this project is to develop reliable statistical algorithms for on-line analysis of physiologic and neurobehavioral variables monitored during long-duration space missions. Maintenance of physiologic and neurobehavioral homeostasis during long-duration space missions is crucial for ensuring optimal crew performance. If countermeasures are not applied, alterations in homeostasis will occur in nearly all-physiologic systems. During such missions data from most of these systems will be either continually and/or continuously monitored. Therefore, if these data can be analyzed as they are acquired and the status of these systems can be continually assessed, then once alterations are detected, appropriate countermeasures can be applied to correct them. One of the most important physiologic systems in which to maintain homeostasis during long-duration missions is the circadian system. To detect and treat alterations in circadian physiology during long duration space missions requires development of: 1) a ground-based protocol to assess the status of the circadian system under the light-dark environment in which crews in space will typically work; and 2) appropriate statistical methods to make this assessment. The protocol in Project 1, Circadian Entrainment, Sleep-Wake Regulation and Neurobehavioral will study human volunteers under the simulated light-dark environment of long-duration space missions. Therefore, we propose to develop statistical models to characterize in near real time circadian and neurobehavioral physiology under these conditions. The specific aims of this project are to test the hypotheses that: 1) Dynamic statistical methods based on the Kronauer model of the human circadian system can be developed to estimate circadian phase, period, amplitude from core-temperature data collected under simulated light- dark conditions of long-duration space missions. 2) Analytic formulae and numerical algorithms can be developed to compute the error in the estimates of circadian phase, period and amplitude determined from the data in Specific Aim 1. 3) Statistical models can detect reliably in near real- time (daily) significant alternations in the circadian physiology of individual subjects by analyzing the circadian and neurobehavioral data collected in Project 1. 4) Criteria can be developed using the Kronauer model and the recently developed Jewett model of cognitive -performance and subjective alertness to define altered circadian and neurobehavioral physiology and to set conditions for immediate administration of countermeasures.

Brown, Emery N.↗

Future Climate Change Significantly Alters Interannual Wheat Yield Variability Over Half of Harvested Areas

Climate change affects the spatial and temporal distribution of crop yields, which can critically impair food security across scales. A number of previous studies have assessed the impact of climate change on mean crop yield and future food availability, but much less is known about potential future changes in interannual yield variability. Here, we evaluate future changes in relative interannual global wheat yield variability (the coefficient of variation (CV)) at 0.25° spatial resolution for two representative concentration pathways (RCP4.5 and RCP8.5). A multi-model ensemble of crop model emulators based on global process-based models is used to evaluate responses to changes in temperature, precipitation, and CO2. The results indicate that over 60% of harvested areas could experience significant changes in interannual yield variability under a high-emission scenario by the end of the 21st century (2066–2095). About 31% and 44% of harvested areas are projected to undergo significant reductions of relative yield variability under RCP4.5 and RCP8.5, respectively. In turn, wheat yield is projected to become more unstable across 23% (RCP4.5) and 18% (RCP8.5) of global harvested areas—mostly in hot or low fertilizer input regions, including some of the major breadbasket countries. The major driver of increasing yield CV change is the increase in yield standard deviation, whereas declining yield CV is mostly caused by stronger increases in mean yield than in the standard deviation. Changes in temperature are the dominant cause of change in wheat yield CVs, having a greater influence than changes in precipitation in 53% and 72% of global harvested areas by the end of the century under RCP4.5 and RCP8.5, respectively. This research highlights the potential challenges posed by increased yield variability and the need for tailored regional adaptation strategies.

Climate change↗