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NASA NTRS2010

Utilization of Hydrologic Remote Sensing Data in Land Surface Modeling and Data Assimilation: Current Status and Challenges

Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Earth's land surface at an unprecedented scale and frequency. The myriad of these land surface observations must be integrated with the state-of-the-art land surface model forecasts using data assimilation to generate spatially and temporally coherent estimates of environmental conditions. These analyses are of critical importance to real-world applications such as agricultural production, water resources management and flood, drought, weather and climate prediction. This need motivated the development of NASA Land Information System (LIS), which is an expert system encapsulating a suite of modeling, computational and data assimilation tools required to address challenging hydrological problems. LIS integrates the use of several community land surface models, use of ground and satellite based observations, data assimilation and uncertainty estimation techniques and high performance computing and data management tools to enable the assessment and prediction of hydrologic conditions at various spatial and temporal scales of interest. This presentation will focus on describing the results, challenges and lessons learned from the use of remote sensing data for improving land surface modeling, within LIS. More specifically, studies related to the improved estimation of soil moisture, snow and land surface temperature conditions through data assimilation will be discussed. The presentation will also address the characterization of uncertainty in the modeling process through Bayesian remote sensing and computational methods.

Kumar, Sujay V.↗

NASA NTRS1984

Shuttle payload dynamic environments - Update

This paper represents a brief summary of a report titled, 'Shuttle Payload Bay Dynamic Environments Summary and Conclusion Report' prepared by the Jet Propulsion Laboratory for the NASA Office of Aeronautics and Space Technology (OAST). The report provides a summary of the dynamic environmental data taken during the first five Space Shuttle flights. The present paper is concerned with a brief synopsis of the report's acoustic and high frequency data evaluation, taking into account also an example acoustic prediction method. Attention is given to an acoustic data summary, a vibration data summary, environmental uncertainties, data reduction errors, spatial bias errors, payload effects, spatial variation, flight to flight variation, payload prediction, and an example prediction.

Oconnell, M.↗

NASA NTRS1992

The role and future of space technology in disaster reduction

This paper describes the potential uses of satellite remote sensing in the mitigation of disasters and their effects by means of prevention, preparedness, and relief. A review is given of the capabilities of communications, geophysical, meteorological, and earth-resources satellites to point out potential applications in the three categories. A complete list of available spacecraft is presented in a table giving data on disaster-related applications. Key functions for disaster mitigation include their use as data resources and as experimental sources of information that can be of use in disaster prediction. Satellites with high temporal or spatial resolutions are useful for providing consistent prompt information required for disaster-management specialists. The use of SAR and TRMM scanning radar techniques to directly measure rainfall and other quantities of relevance to the prediction of disasters.

Walter, Louis S.↗

NASA NTRS1996

The barberplaid illusion: plaid motion is biased by elongated apertures

The perceived direction of motion of plaids windowed by elongated spatial Gaussians is biased toward the window's long axis. The bias increases as the relative angle between the plaid motion and the long axis of the window increases, peaks at a relative angle of approximately 45 deg, and then decreases. The bias increases as the window is made narrower (at fixed height) and decreases as the component spatial frequency increases (at fixed aperture size). We examine several models of human motion processing (cross-correlation, motion-energy, intersection-of-constraints, and vector-sum), and show that none of these standard models can predict our data. We conclude that spatial integration of motion signals plays a crucial role in plaid motion perception and that current models must be explicitly expanded to include such spatial interactions.

NASA Center ARC↗

NASA NTRS2005

Variability of the ocean-induced magnetic field predicted at sea surface and at satellite altitudes

Spatial and temporal variability of the magnetic field component induced by ocean circulation is investigated on the basis of a standard thin-shell approximation of electro- and magneto-static equations. Well-known difficulties of numerical solution of the governing equations are resolved by reducing the problem to an equation for the electric field potential,(ef) as opposed to a more conventional approach focused on the vertical jump, (psi), of the magnetic field potential across a combined ocean/ marine-sediment-layer spherical shell. The present formulation permits using more realistic input data on ocean currents and ultimately yields much greater (by at least an order of magnitude) values of the magnetic field at sea surface than predicted in earlier studies. Such large values are comparable to, and in some cases exceed, magnetic field variations caused by lithospheric and ionospheric sources on monthly to interannual timescales. At the 400-km altitude (of CHAMP satellite), the field attains 6 nT. The model predictions show favorable comparisons with some in situ measurements as well as with Challenging Minisatellite Payload (CHAMP) satellite magnetometer data.

ocean induced magnetic field↗

NASA NTRS1983

The window of visibility: A psychological theory of fidelity in time-sampled visual motion displays

Many visual displays, such as movies and television, rely upon sampling in the time domain. The spatiotemporal frequency spectra for some simple moving images are derived and illustrations of how these spectra are altered by sampling in the time domain are provided. A simple model of the human perceiver which predicts the critical sample rate required to render sampled and continuous moving images indistinguishable is constructed. The rate is shown to depend upon the spatial and temporal acuity of the observer, and upon the velocity and spatial frequency content of the image. Several predictions of this model are tested and confirmed. The model is offered as an explanation of many of the phenomena known as apparent motion. Finally, the implications of the model for computer-generated imagery are discussed.

Watson, A. B.↗

NASA NTRS2011

An Extended View of Ozone and Chemistry in the Atmosphere of Mars

We present an ongoing effort to characterize chemistry in Mars' atmosphere in multiple seasons on timescales longer than spaceflight missions through coordinated efforts by GSFC's HIPWAC spectrometer and Mars Express SPICAM, archival measurements, and tests/application of photochemical models. The trace species ozone (03) is an effective probe of Mars' atmospheric chemistry because it is destroyed by odd-hydrogen species (HOx, from water vapor photolysis). Observed ozone is a critical test for specific predictions by 3-D photochemical models (spatial, diurnal, seasonal). Coordinated measurements by HIPWAC and SPICAM quantitatively linked mission data to the 23-year GSFC ozone data record and also revealed unanticipated inter-decadal variability of same-season ozone abundances, a possible indicator of changing cloud activity (heterogeneous sink for HOx). A detailed study of long-term conditions is critical to characterizing the predictability of Mars' seasonal chemical behavior, particularly in light of the implications of and the lack of explanation for reported methane behavior.

Smith, Ramsey L.↗

NASA NTRS2004

CO2 Condensation Models for Mars

During the polar night in both hemispheres of Mars, regions of low thermal emission, frequently referred to as "cold spots", have been observed by Mariner 9, Viking and Mars Global Surveyor (MGS) spacecraft. These cold spots vary in time and appear to be associated with topographic features suggesting that they are the result of a spectral-emission effect due to surface accumulation of fine-grained frost or snow. Presented here are simulations of the Martian polar night using the NASA Ames General Circulation Cloud Model. This cloud model incorporates all the microphysical processes of carbon dioxide cloud formation, including nucleation, condensation and sedimentation and is coupled to a surface frost scheme that includes both direct surface condensation and precipitation. Using this cloud model we simulate the Mars polar nights and compare model results to observations from the Thermal Emission Spectrometer (TES) and the Mars Orbiter Laser Altimeter (MOLA). Model predictions of "cold spots" compare well with TES observations of low emissivity regions, both spatially and as a function of season. The model predicted frequency of CO2 cloud formation also agrees well with MOLA observations of polar night cloud echoes. Together the simulations and observations in the North indicate a distinct shift in atmospheric state centered about Ls 270 which we believe may be associated with the strength of the polar vortex.

Colaprete, A.↗

NASA NTRSDate not supplied

Predicting contamination accumulation in facilities with limited data

In preparation for the James Webb Space Telescope (JWST) launch at Centre Spatial Guyanias (CSG) in French Guiana, particulate contamination accumulation predictions were necessary for each facility in which the hardware would be exposed because the Telescope would be uncovered in each of the facilities and had strict particulate requirements. These included facilities for final integration and testing, fueling, transportation and encapsulation. Minimal heritage data existed from CSG and previous launch campaigns to use as a basis for contamination predictions. Data from the Automatic Transfer Vehicle and Herschel & Planck launch campaigns were used in conjunction with facility monitoring data provided by ESA and data collected during JWST working group visits to CSG. These campaigns were conducted at varying cleanliness levels that were typically less stringent than JWST requirements. Each facility was evaluated using the data provided and likely performance improvement with the addition of High Efficiency Particulate Air filter (HEPA) banks operating when possible. Once the launch campaign was completed, the predicted fallout was compared with actual data collected throughout the campaign. Based on the actual measurements, JWST’s primary and secondary mirrors turned out to be much cleaner than what was predicted.

James Webb Space Telescope, contamination, cleanro↗

NASA NTRSDate not supplied

Predicting contamination accumulation in facilities with limited data

"In preparation for the James Webb Space Telescope (JWST) launch at Centre Spatial Guyanias (CSG) in French Guiana, particulate contamination accumulation predictions were necessary for each facility in which the hardware would be exposed because the Telescope would be uncovered in each of the facilities and had strict particulate requirements. These included facilities for final integration and testing, fueling, transportation and encapsulation. Minimal heritage data existed from CSG and previous launch campaigns to use as a basis for contamination predictions. Data from the Automatic Transfer Vehicle and Herschel & Planck launch campaigns were used in conjunction with facility monitoring data provided by ESA and data collected during JWST working group visits to CSG. These campaigns were conducted at varying cleanliness levels that were typically less stringent than JWST requirements. Each facility was evaluated using the data provided and likely performance improvement with the addition of High Efficiency Particulate Air filter (HEPA) banks operating when possible. Once the launch campaign was completed, the predicted fallout was compared with actual data collected throughout the campaign. Based on the actual measurements, JWST’s primary and secondary mirrors are likely much cleaner than was expected with the predicted fallout in each facility. "

James Webb Space Telescope, contamination, cleanro↗

NASA NTRS2010

Application of Raytracing Through the High Resolution Numerical Weather Model HIRLAM for the Analysis of European VLBI

An important limitation for the precision in the results obtained by space geodetic techniques like VLBI and GPS are tropospheric delays caused by the neutral atmosphere, see e.g. [1]. In recent years numerical weather models (NWM) have been applied to improve mapping functions which are used for tropospheric delay modeling in VLBI and GPS data analyses. In this manuscript we use raytracing to calculate slant delays and apply these to the analysis of Europe VLBI data. The raytracing is performed through the limited area numerical weather prediction (NWP) model HIRLAM. The advantages of this model are high spatial (0.2 deg. x 0.2 deg.) and high temporal resolution (in prediction mode three hours).

Garcia-Espada, Susana↗

NASA NTRS2002

Holographic Gratings for Optical Processing

Investigation of astronomical objects and tracking of man-made space objects lead to generation of huge amount of information for optical processing. Traditional big-size optical elements (such as optical telescopes) have a tendency for increasing aperture size in order to improve sensitivity. This tendency leads to increasing of weight and costs of optical systems and stimulate search for the new, more adequate technologies. One approach to meet these demands is based on developing of holographic optical elements using new polymeric materials. We have investigated possibility to use new material PQ-PMMA (phenantrenequinone-doped PMMA (Polymethyl Methacrylate)) for fabrication of highly selective optical filters and fast spatial-temporal light modulators. This material was originally developed in Russia and later was tested in CalTech as a candidate material for optical storage. Our theoretical investigation predicts the possibility of realization of fast spatial and temporal light modulation, using volume reflection-type spectral filter. We have developed also model of holographic-grating recording in PQ-PMMA material, based on diffusional amplification. This mechanism of recording allow to receive high diffraction efficiency during recording of reflection-type volume holographic grating (holographic mirror). We also investigated recording of dynamic gratings in the photorefractive crystals LiNbO3 (LN) for space-based spectroscopy and for adaptive correction of aberrations in the telescope's mirrors. We have shown, that specific 'photogalvanic' mechanism of holographic grating recording in LN allow to realize recording of blazed gratings for volume and surface gratings. Possible applications of dynamic gratings in LN for amplification of images, transmitted through an imaging fiber guide was also demonstrated.

Nickolai Kukhtarev↗

NASA NTRS2022

Modeling the Errors of a Time Series Algorithm for Retrieving Soil Moisture in the NISAR Mission

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) mission plan to launch a SAR operating at L- and S-band with a 12-day repeat frequency. A global soil moisture product at 200 m spatial resolution derived from 200 m NISAR radar measurements is currently under development. Although several retrieval algorithms are being investigated, this paper focuses on a “time series ratio” retrieval approach. In order to understand and assess the performance of this algorithm, an error model has been developed and is reported in this paper. The model is applied to examine errors as a function of the instrument characteristics and for a given location. Initial progress in including vegetation effects and in predicting errors as a function of spatial location is also described.

NISAR↗

NASA NTRS2017

UAV Trajectory Modeling Using Neural Networks

Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.

Neural Networks↗

NASA NTRS1982

A numerical model simulation of the regional air pollution meteorology of the greater Chesapeake Bay area - Summer day case study

The mesoscale numerical model of the University of Virginia (UVMM), has been applied to the greater Chesapeake Bay area in order to provide a detailed description of the air pollution meteorology during a typical summer day. This model provides state of the art simulations for land-sea thermally induced circulations. The model-predicted results agree favorably with available observed data. The effects of synoptic flow and sea breeze coupling on air pollution meteorological characteristics in this region, are demonstrated by a spatial and temporal presentation of various model predicted fields. A transport analysis based on predicted wind velocities indicated possible recirculation of pollutants back onto the Atlantic coast due to the sea breeze circulation.

Segal, M.↗

NASA NTRS2013

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗

NASA NTRS1987

Numerical simulation of a plane turbulent mixing layer, with applications to isothermal, rapid reactions

A hybrid method has been developed for the numerical prediction of turbulent mixing in a spatially-developing, free shear layer. Most significantly, the computation incorporates the effects of large-scale structures, Schmidt number and Reynolds number on mixing, which have been overlooked in the past. In flow field prediction, large-eddy simulation was conducted by a modified 2-D vortex method with subgrid-scale modeling. The predicted mean velocities, shear layer growth rates, Reynolds stresses, and the RMS of longitudinal velocity fluctuations were found to be in good agreement with experiments, although the lateral velocity fluctuations were overpredicted. In scalar transport, the Monte Carlo method was extended to the simulation of the time-dependent pdf transport equation. For the first time, the mixing frequency in Curl's coalescence/dispersion model was estimated by using Broadwell and Breidenthal's theory of micromixing, which involves Schmidt number, Reynolds number and the local vorticity. Numerical tests were performed for a gaseous case and an aqueous case. Evidence that pure freestream fluids are entrained into the layer by large-scale motions was found in the predicted pdf. Mean concentration profiles were found to be insensitive to Schmidt number, while the unmixedness was higher for higher Schmidt number. Applications were made to mixing layers with isothermal, fast reactions. The predicted difference in product thickness of the two cases was in reasonable quantitative agreement with experimental measurements.

Lin, P.↗

NASA NTRS2004

GEWEX America Prediction Project (GAPP) Science and Implementation Plan

The purpose of this Science and Implementation Plan is to describe GAPP science objectives and the activities required to meet these objectives, both specifically for the near-term and more generally for the longer-term. The GEWEX Americas Prediction Project (GAPP) is part of the Global Energy and Water Cycle Experiment (GEWEX) initiative that is aimed at observing, understanding and modeling the hydrological cycle and energy fluxes at various time and spatial scales. The mission of GAPP is to demonstrate skill in predicting changes in water resources over intraseasonal-to-interannual time scales, as an integral part of the climate system.

TIME SCALES↗