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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

TRMM↗
NASA NTRS2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗
NASA NTRS1992

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

Maslanik, J. A.↗
NASA NTRS2002

Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

Bell, Thomas L.↗
NASA NTRS1983

Implications of complete watershed soil moisture measurements to hydrologic modeling

A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.

Engman, E. T.↗
NASA NTRS1979

The nature of asteroidal differentiation processes - Implications for primordial heat sources

A review of the geochemical data on basaltic achondrite group meteorites, here defined as diogenites, eucrites, howardites, mesosiderites, main-group pallasites and IIIAB irons, suggests that the following processes and properties were important in determining the compositions of igneous materials on asteroidal sized bodies: (1) inhomogeneities in source rock compositions, (2) variable degrees of partial melting from 5-100%, (3) multiple melt genesis from a single source region, (4) fractional crystallization, and (5) remelting of earlier formed igneous rocks. All of this activity started during or shortly after the major asteroidal accretion phase as suggested by the numerous 4.6 Gyr ages for eucrites and may have lasted for at least 200 m.y. The above properties imply an early, intense heat source that was both spatially and temporally variable. A review of asteroid thermal modeling for various heat sources shows that heating by short-lived Al-26 alone appears to be incapable of supplying the observed geochemical variations.

Mittlefehldt, D. W.↗
NASA NTRS1987

Numerical simulations of magnetospheric plasmas - Review and quadrennial report to the IUGG

This article provides a broad survey of U.S. progress during the quadrennium 1983-1986 in the category 'numerical simulations of magnetospheric plasmas'. There has been a substantial increase of activity in this area during this period. Simulations have been instrumental in providing valuable insights into large scale dynamic phenomena, nonlinear effects, and complex kinetic phenomena in a wide variety of subject areas, including shocks and double layers, ionosphere-magnetosphere coupling phenomena, and important microphysical processes such as broadband electrostatic noise. The methodology of computer simulation has also been advanced during this quadrennium. Vlasov algorithms have been improved; hybrid codes in 2 and 3D have been developed and applied to magnetospheric problems; and complex problems have been subjected with increasing frequency to a multipronged attack in which several types of simulation models, each designed to accurately model phenomena within a particular range of temporal or spatial scales, are employed synergistically.

Palmadesso, Peter J.↗
NASA NTRS1988

Comparison of field-aligned currents at ionospheric and magnetospheric altitudes

Using the empirical terrestrial magnetospheric magnetic field models of Tsyganenko and Usmanov (1982) and Tsyganenko (1987) the average field-aligned currents (FACs) in the magnetosphere were determined as a function of the Kp index. Three major model FAC systems were identified, namely, the dayside region 1, the nightside region 1, and the nightside polar cap. The models provide information about the sources of the current systems. Mapped ionospheric model FACs are compared with low-altitude measurements obtained by the spacecraft. It is found that low-altitude data can reveal either classic region 1/2 or more highly structured FAC patterns. Therefore, statistical results either obtained from observations or inferred from models are expected to be averages over temporally and spatially shifting patterns.

Spence, H. E.↗
NASA NTRS1989

Strain accumulation and surface deformation along the San Andreas, California

The goal of this project remains to be the achievement of a better understanding of the regional and local deformation and crustal straining processes in western North America, particularly the effect of the San Andreas and nearby faults on the spatial and temporal crustal deformation behavior. Construction of theoretical models based on the mechanics of coupled elastic plate/viscoelastic foundation and large scale crack mechanics provide a rational basis for the interpretation of seismic and aseismic anomalies and expedite efforts in forecasting the stability of plate boundary deformations. In the present period, special focus is placed on the 3-D effect of irregular fault locked patches on the ground measured deformation fields. Specifically, use is made of a newly developed 3-D boundary element program to analyze the fault slip and vertical ground motion in the Parkfield area on the San Andreas.

Li, Victor C.↗
NASA NTRS1991

A space-time neural network

Introduced here is a novel technique which adds the dimension of time to the well known back propagation neural network algorithm. Cited here are several reasons why the inclusion of automated spatial and temporal associations are crucial to effective systems modeling. An overview of other works which also model spatiotemporal dynamics is furnished. A detailed description is given of the processes necessary to implement the space-time network algorithm. Several demonstrations that illustrate the capabilities and performance of this new architecture are given.

Villarreal, James A.↗
NASA NTRS1992

Crustal deformation along the San Andreas, California

The goal is to achieve a better understanding of the regional and local deformation and crustal straining processes in western North America, particularly the effects of the San Andreas and nearby faults on the spatial and temporal crustal deformation behavior. Construction of theoretical models based on the mechanics of coupled elastic plate, viscoelastic foundation and large scale crack mechanics provide a rational basis for the interpretation of seismic and aseismic anomalies and expedite efforts in forecasting the stability of plate boundary deformation. Special focus is placed on the three dimensional time dependent surface deformation due to localized slippage in a elastic layer coupled to a visco-elastic substrate. The numerical analysis is based on a 3-D boundary element technique. Extension to visco-elastic coupling demands the derivation of 3-D time dependent Green's function. This method was applied to analyze the viscoelastic surface displacements due to a dislocated embedded patch. Surface uplift as a function of time and position are obtained. Comparisons between surface uplift for long and short dislocated patches are made.

Li, Victor C.↗
NASA NTRS1993

Estimates of lithospheric thickness on Venus

Magellan altimetry data have revealed many examples of topographic flexure on Venus. Modeling of flexural features is of interest as it provides information on spatial (and for the earth, temporal) variations in lithospheric thickness. Lithospheric thickness may be determined solely from modeling topographic flexure or by combining gravity and topography data. On Venus even the highest resolution gravity is insufficient for modeling all but the very longest wavelength flexural features, so we rely heavily on altimetry data for information about lithospheric thickness. Sandwell and Schubert modeled flexure around four coronae and found lithospheric thicknesses h, in the range 35 - 70 km. Studies of several more flexural features suggests that these are typical of Aphrodite Terra and other chasmata regions on Venus. However lithospheric thicknesses associated with other regions are in the range 15-30 km. McKenzie et al. noted that part of Aphrodite Terra appeared similar in planform and morphology to the subduction zones of the East Indies on Earth. Other flexure studies using Magellan data have looked at smaller coronae (h = 5-30 km) and rifts (h = 8-20 km). It can be seen that the range of thicknesses suggested by studies to date is extremely large, and it is difficult to establish whether their mean is in agreement with that predicted by heat flow scaling arguments (h approximately 18 km). Here we present results from a global study of flexure on Venus, with particular emphasis on the variation in our results with different tectonic settings.

Johnson, C. L.↗
NASA NTRS1995

Aerosol Radiative Effects: Expected Variations in Optical Depth Spectra and Climate Forcing, with Implications for Closure Experiment Strategies

We examine measurement strategies for reducing uncertainties in aerosol direct radiative forcing by focused experiments that combine surface, air, and space measurements. Particularly emphasized are closure experiments, which test the degree of agreement among different measurements and calculations of aerosol properties and radiative effects. By combining results from previous measurements of large-scale smokes, volcanic aerosols, and anthropogenic aerosols with models of aerosol evolution, we estimate the spatial and temporal variability in optical depth spectra to be expected in the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX, planned for summer 1996 off the Eastern U.S. seaboard). In particular, we examine the expected changes in the wavelength dependence of optical depth as particles evolve through nucleation, growth by condensation and coagulation, and removal via sedimentation. We then calculate the expected radiative climate forcing (i.e. change in net radiative flux) for typical expected aerosols and measurement conditions (e.g. solar elevations, surface albedos, radiometer altitudes). These calculations use new expressions for flux and albedo changes, which account not only for aerosol absorption, but also for instantaneous solar elevation angles and the dependence of surface albedo on solar elevation. These factors, which are usually ignored or averaged in calculations of global aerosol effects, can have a strong influence on fluxes measured in closure experiments, and hence must be accounted for in calculations if closure is to be convincingly tested. We compare the expected measurement signal to measurement uncertainties expected for various techniques in various conditions. Thereby we derive recommendations for measurement strategies that combine surface, airborne, and spaceborne measurements.

Russell, Philip B.↗
NASA NTRS2019

Assimilated Hydrological Data at NASA GES DISC with Examples of Extreme Events

Extreme weather and climate events, such as heavy rainfall, heatwave, floods and droughts, and strong wind, can have devastating impacts on society. NASA and NOAA, based on independent analyses, recently announced that global surface temperatures in 2018 are the fourth warmest since 1880, behind only those of 2016, 2017, and 2015 (nasa.gov). Also in 2018, the United States experienced 14 billion-dollar disasters, ranking as the fourth highest total number of such events, behind only the years 2017, 2011, and 2016 (climate.gov). Many research studies have focused on acquiring observational and modeling data, to reveal linkages between increasing extreme events, global water and energy cycle, and global climate change. However, draw conclusions is still a challenge. NASA Goddard Earth Sciences Data and Information Services Center is one of twelve NASA Earth Observing System (EOS) data centers that process, archive, document, and distribute data from Earth science missions and related projects. The GES DISC hosts a wide range of remotely-sensed and model data and provides reliable and robust data access and services to users worldwide. This presentation provides a few examples of extreme event study that use Land Surface Model (LSM) assimilated, quality-controlled, and spatially and temporally consistent, hydrological data from the GES DISC. Also provided is a summary table for the hydrological data holdings, along with discussions of recent updates to data and data services.

Rui, Hualan↗
NASA NTRS2011

Evaluating the Application of Multi-Satellite Observations in Hydrologic Modeling

When monitoring local or regional hydrosphere dynamics for applications such as agricultural productivity or drought and flooding events, it is necessary to have accurate, high-resolution estimates of terrestrial water and energy storages. Though in-situ observations provide reliable estimates of hydrologic states and fluxes, they are only capable of accurately capturing the dynamics at relatively discrete points in space and time, which makes them inadequate for characterizing the variability of the water budget across scales. In contrast, satellite-based remote sensing is ideal for providing observations of hydrological states and fluxes because it provides spatially-distributed observations at spatial and temporal scales required for regional land surface process modeling. Due to the continued progress in algorithm development and emerging satellite technology, we now have near-real time monitoring of several components of the water cycle including precipitation, soil moisture, lake and river height, terrestrial water storage, snow cover, and evapotranspiration. As these data become more readily available, their application to hydrologic modeling is becoming more common, however there remains little consensus on the most appropriate method for optimal integration and evaluation in regard to hydrological applications. Here we present two case studies operationally applying several remotely sensed products from AMSR-E, GRACE, and MODIS and discuss assimilation strategies, ease of integration and interpretation, and methods for quantifying the success of the application methodology.

Bolten, John↗
NASA NTRS2015

The Ocean Colour Climate Change Initiative: II. Spatial and Temporal Homogeneity of Satellite Data Retrieval Due to Systematic Effects in Atmospheric Correction Processors

The established procedure to access the quality of atmospheric correction processors and their underlying algorithms is the comparison of satellite data products with related in-situ measurements. Although this approach addresses the accuracy of derived geophysical properties in a straight forward fashion, it is also limited in its ability to catch systematic sensor and processor dependent behaviour of satellite products along the scan-line, which might impair the usefulness of the data in spatial analyses. The Ocean Colour Climate Change Initiative (OC-CCI) aims to create an ocean colour dataset on a global scale to meet the demands of the ecosystem modelling community. The need for products with increasing spatial and temporal resolution that also show as little systematic and random errors as possible, increases. Due to cloud cover, even temporal means can be influenced by along-scanline artefacts if the observations are not balanced and effects cannot be cancelled out mutually. These effects can arise from a multitude of results which are not easily separated, if at all. Among the sources of artefacts, there are some sensor-specific calibration issues which should lead to similar responses in all processors, as well as processor-specific features which correspond with the individual choices in the algorithms. A set of methods is proposed and applied to MERIS data over two regions of interest in the North Atlantic and the South Pacific Gyre. The normalised water leaving reflectance products of four atmospheric correction processors, which have also been evaluated in match-up analysis, is analysed in order to find and interpret systematic effects across track. These results are summed up with a semi-objective ranking and are used as a complement to the match-up analysis in the decision for the best Atmospheric Correction (AC) processor. Although the need for discussion remains concerning the absolutes by which to judge an AC processor, this example demonstrates clearly, that relying on the match-up analysis alone can lead to misjudgement.

Ocean Colour↗
NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗
NASA NTRS2011

Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

Kumar, Sujay V.↗