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NASA NTRS2021

A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion

Dense time-series remote sensing data with detailed spatial information are highly desired for the monitoring of dynamic earth systems. Due to the sensor tradeoff, most remote sensing systems cannot provide images with both high spatial and temporal resolutions. Spatiotemporal image fusion models provide a feasible solution to generate such a type of satellite imagery, yet existing fusion methods are limited in predicting rapid and/or transient phenological changes. Additionally, a systematic approach to assessing and understanding how varying levels of temporal phenological changes affect fusion results is lacking in spatiotemporal fusion research. The objective of this study is to develop an innovative hybrid deep learning model that can effectively and robustly fuse the satellite imagery of various spatial and temporal resolutions. The proposed model integrates two types of network models: super-resolution convolutional neural network (SRCNN) and long short-term memory (LSTM). SRCNN can enhance the coarse images by restoring degraded spatial details, while LSTM can learn and extract the temporal changing patterns from the time-series images. To systematically assess the effects of varying levels of phenological changes, we identify image phenological transition dates and design three temporal phenological change scenarios representing rapid, moderate, and minimal phenological changes. The hybrid deep learning model, alongside three benchmark fusion models, is assessed in different scenarios of phenological changes. Results indicate the hybrid deep learning model yields significantly better results when rapid or moderate phenological changes are present. It holds great potential in generating high-quality time-series datasets of both high spatial and temporal resolutions, which can further benefit terrestrial system dynamic studies. The innovative approach to understanding phenological changes’ effect will help us better comprehend the strengths and weaknesses of current and future fusion models.

spatiotemporal fusion↗

NASA NTRS1977

Finite element analysis of aeroacoustic jet-flap flows

A computational analysis was performed on the steady, turbulent aerodynamic flowfields associated with a jet-blown flap. For regions devoid of flow separation, a parabolic approximation to the governing time-averaged Navier-Stokes equations was applied. Numerical results are presented for the symmetry plane flow of a slot-nozzle planar jet flap geometry, including prediction of flowfield evolution within the secondary mixing region immediately downstream of the trailing edge. Using a two equation turbulence kinetic energy closure model, rapid generation and decay of large spatial gradients in mean and correlated fluctuating velocity components within the immediate wake region were predicted. Modifications to the turbulent flow structure, as induced by porous surface treatment of the flap, were evaluated. The recirculating flow within a representative discrete slot in the surface was evaluated, using the two dimensional, time-averaged Navier-Stokes equations.

Baker, A. J.↗

NASA NTRS2018

Regional Replay: A Unique Reanalysis-Based Tool for Addressing Model Error

Understanding and correcting errors in general circulation and climate models has long been part intuition and part trial and error. Efforts to diagnose the errors and provide some guidance to developers have been of some value, though such efforts, with few exceptions, have been more successful in identifying and documenting the errors in the model simulations rather than the model deficiencies that produced them. Modern atmospheric reanalyses such as MERRA-2 provide much-improved estimates of our climate system at hourly to interannual and longer time scales and have become an important tool for assessing model performance. Here we use MERRA-2 to address biases in the NASA/GMAO GEOS model by employing a "regional replay" approach developed in the GMAO. The regional replay approach constrains the model to remain close to the reanalysis over arbitrary regions and selected model variables, thus allowing us to examine how model error generated over one area is spatially translated across the globe. Several examples are given including an assessment of the global impact of errors produced over the Tibet region.

Tibet Region↗

NASA NTRS2005

Disk-averaged synthetic spectra of Mars

The principal goal of the NASA Terrestrial Planet Finder (TPF) and European Space Agency's Darwin mission concepts is to directly detect and characterize extrasolar terrestrial (Earthsized) planets. This first generation of instruments is expected to provide disk-averaged spectra with modest spectral resolution and signal-to-noise. Here we use a spatially and spectrally resolved model of a Mars-like planet to study the detectability of a planet's surface and atmospheric properties from disk-averaged spectra. We explore the detectability as a function of spectral resolution and wavelength range, for both the proposed visible coronograph (TPFC) and mid-infrared interferometer (TPF-I/Darwin) architectures. At the core of our model is a spectrum-resolving (line-by-line) atmospheric/surface radiative transfer model. This model uses observational data as input to generate a database of spatially resolved synthetic spectra for a range of illumination conditions and viewing geometries. The model was validated against spectra recorded by the Mars Global Surveyor-Thermal Emission Spectrometer and the Mariner 9-Infrared Interferometer Spectrometer. Results presented here include disk-averaged synthetic spectra, light curves, and the spectral variability at visible and mid-infrared wavelengths for Mars as a function of viewing angle, illumination, and season. We also considered the differences in the spectral appearance of an increasingly ice-covered Mars, as a function of spectral resolution, signal-to-noise and integration time for both TPF-C and TPFI/ Darwin.

Mars↗

NASA NTRS2008

Matching Observations to Model Resolution for Future Weather and Climate Applications

High spatial resolution sounding observations will improve initialization and assimilation into the next generation forecast models and validation of the next generation of climate models. One such advanced sounder concept for low earth orbit is the Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) which proposes to provide highvspatial hyperspectral resolution observations in the mid to longwave infrared. This paper explores the effects of spatial resolution on the errors expected from the combined use of models and observations for representing scene information. We calculate the frequency response of the instrument and model and determine the error at any given spatial frequency. The results show that it is vital to have observations match the spatial resolution of models to minimize the uncertainty in the representation of the scene contents.

spatial resolution↗

NASA NTRS1985

Generation of Surface Coordinates by Elliptic Partial Differential Equations

The problem of generating spatial coordinates by numerical methods through carefully selected mathematical models is of current interest both in mechanics and physics. The problem of generation of a desired system of coordinates in a given surface was considered, which essentially is an effort directed to the problem of grid generation in a two-dimensional non-Euclidean space. The mathematical model selected for this purpose is based on the formulae of Gauss for a surface. The proposed equations can be used to generate a new coordinate system from the data of an already given coordinate system in a surface. If the coefficients of the first and second fundamental forms have been given, then the proposed equations can be used to generate a surface satisfying the given data (surface fitting). The proposed equations can also be used to generate surfaces in the space between two arbitrary given surfaces, thus providing 3D grids in an Euclidean space.

Warsi, Z. U. A.↗

NASA NTRS1984

A spatial model of wind shear and turbulence

The purpose of the spatial model considered in the present investigation is to generate the wind environment for use by others for flight simulation. Winds and gusts are provided over any finite area (e.g., aircraft body) from which aircraft loads and moments may be calculated. Three-dimensional autospectral information and correlation are contained in the data. It is pointed out that the three-dimensionality as contained in the spatial model affords much greater realism than widely used one-dimensional models. The resulting simulated wind is a nonlinear, non-Gaussian combination of real atmospheric winds and Gaussian, three-dimensional turbulence modulated by gust intensities which may vary freely as desired over space. The turbulence as represented by a product of a varying gust intensity and simulated turbulence is nonlinear and non-Gaussian.

Campbell, C. W.↗

NASA NTRS1982

Other satellite atmospheres: Their nature and planetary interactions

The Io sodium cloud model was successfully generated to include the time and spatial dependent lifetime sink produced by electron impact ionization as the plasma torus oscillates about the satellite plane, while simultaneously including the additional time dependence introduced by the action of solar radiation pressure on the cloud. Very preliminary model results are discussed and continuing progress in analysis of the peculiar directional features of the sodium cloud is also reported. Significant progress was made in developing a model for the Io potassium cloud and differences anticipated between the potassium and sodium cloud are described. An effort to understand the hydrogen atmosphere associated with Saturn's rings was initiated and preliminary results of a very and study are summarized.

Smyth, W. H.↗

NASA NTRS1984

Numerical simulations of loops heated to solar flare temperatures. III - Asymmetrical heating

A numerical model is defined for asymmetric full solar flare loop heating and comparisons are made with observational data. The Dynamic Flux Tube Model is used to describe the heating process in terms of one-dimensional, two fluid conservation equations of mass, energy and momentum. An adaptive grid allows for the downward movement of the transition region caused by an advancing conduction front. A loop 20,000 km long is considered, along with a flare heating system and the hydrodynamic evolution of the loop. The model was applied to generating line profiles and spatial X-ray and UV line distributions, which were compared with SMM, P78-1 and Hintori data for Fe, Ca and Mg spectra. Little agreement was obtained, and it is suggested that flares be treated as multi-loop phenomena. Finally, it is concluded that chromospheric evaporation is not an effective mechanism for generating the soft X-ray bursts associated with flares.

Cheng, C.-C.↗

NASA NTRS1994

Strong gravitational lensing statistics as a test of cosmogonic scenarios

Gravitational lensing statistics can provide a direct and powerful test of cosmic structure formation theories. Since lensing tests, directly, the magnitude of the nonlinear mass density fluctuations on lines of sight to distant objects, no issues of 'bias' (of mass fluctuations with respect to galaxy density fluctuations) exist here, although lensing observations provide their own ambiguities of interpretation. We develop numerical techniques for generating model density distributions with the very large spatial dynamic range required by lensing considerations and for identifying regions of the simulations capable of multiple image lensing in a conservative and computationally efficient way that should be accurate for splittings significantly larger than 3 seconds. Applying these techniques to existing standard Cold dark matter (CDM) (Omega = 1) and Primeval Baryon Isocurvature (PBI) (Omega = 0.2) simulations (normalized to the Cosmic Background Explorer Satellite (COBE) amplitude), we find that the CDM model predicts large splitting (greater than 8 seconds) lensing events roughly an order-of-magnitude more frequently than the PBI model. Under the reasonable but idealized assumption that lensing structrues can be modeled as singular isothermal spheres (SIS), the predictions can be directly compared to observations of lensing events in quasar samples. Several large splitting (Delta Theta is greater than 8 seconds) cases are predicted in the standard CDM model (the exact number being dependent on the treatment of amplification bias), whereas none is observed. In a formal sense, the comparison excludes the CDM model at high confidence (essentially for the same reason that CDM predicts excessive small-scale cosmic velocity dispersions.) A very rough assessment of low-density but flat CDM model (Omega = 0.3, Lambda/3H(sup 2 sub 0) = 0.7) indicates a far lower and probably acceptable level of lensing. The PBI model is consistent with, but not strongly tested by, the available lensing data, and other open models would presumably do as well as PBI. These preliminary conclusions and the assumptions on which they are based can be tested and the analysis can be applied to other cosmogonic models by straightforward extension of the work presented here.

Cen, Renyue↗

NASA NTRS2012

Understanding Changes in Water Availability in the Rio Grande/Rio Bravo del Norte Basin Under the Influence of Large-Scale Circulation Indices Using the Noah Land Surface Model

Water availability plays an important role in the socio-economic development of a region. It is however, subject to the influence of large-scale circulation indices, resulting in periodic excesses and deficits. An assessment of the degree of correlation between climate indices and water availability, and the quantification of changes with respect to major climate events is important for long-term water resources planning and management, especially in transboundary basins as it can help in conflict avoidance. In this study we first establish the correlation of the Pacific Decadal Oscillation (PDO) and El Nino-Southern Oscillation (ENSO) with gauged precipitation in the Rio Grande basin, and quantify the changes in water availability using runoff generated from the Noah land surface model. Both spatial and temporal variations are noted, with winter and spring being most influenced by conditions in the Pacific Ocean. Negative correlation is observed at the headwaters and positive correlation across the rest of the basin. The influence of individual ENSO events, classified using four different criteria, is also examined. El Ninos (La Ninas) generally cause an increase (decrease) in runoff, but the pattern is not consistent; percentage change in water availability varies across events. Further, positive PDO enhances the effect of El Nino and dampens that of La Nina, but during neutral/transitioning PDO, La Nina dominates meteorological conditions. Long El Ninos have more influence on water availability than short duration high intensity events. We also note that the percentage increase during El Ninos significantly offsets the drought-causing effect of La Ninas.

Khedun, C. Prakash↗

NASA NTRS1982

Spatially Characterizing Effective Timber Supply

The structure of a computer-oriented cartographic model for assessing roundwood supply for generation of base load electricity is discussed. The model provides an analytical procedure for coupling spatial information of harvesting economics and owner willingness to sell stumpages. Supply is characterized in terms of standing timber; of accessibility considering various harvesting and hauling factors; and of availability as affected by ownership and residential patterns. Factors governing accessibility to timber include effective harvesting distance to haulic roads as modified by barriers and slopes. Haul distance is expressed in units that take into account the relative ease of travel along various road types to a central processing facility. Areas of accessible timber are grouped into spatial units, termed 'timbersheds', of common access to particular haul road segments that belong to unique 'transport zones'. Timber availability considerations include size of ownership parcels, housing density and excluded areas. The analysis techniques are demonstrated for a cartographic data base in western Massachusetts.

Berry, J. K.↗

NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗

NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗

NASA NTRS2023

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R 2 ) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr -1 (original) to −57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.

Greenland Ice Sheet↗

NASA NTRS2022

The Earth Model Column Collaboratory (EMC2) v1.1: An Open-Source Ground-Based Lidar and Radar Instrument Simulator and Subcolumn Generator for Large-Scale Models

Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Earth Model Column Collaboratory↗

NASA NTRS1992

Navier-Stokes analyses of flows over slender airframes

An account is given of the current development status of Navier-Stokes algorithms for the analysis of 3D viscous flows over slender airframes, emphasizing the design and analysis of practical configurations. The pacing items of the numerical algorithms used encompass grid generation, spatial and temporal differencing, and transition and turbulence modeling. Attention is given to the high angle-of-attack prediction capability of the various methods whose results are compared with experimental data; it is in that regime that Navier-Stokes methods surpass the prediction capabilities of flow solvers based on simpler mathematical models.

Thomas, James L.↗

NASA NTRS2019

The LUVOIR Extreme Coronagraph for Living Planetary Systems (ECLIPS) II. Performance Evaluation, Aberration Sensitivity Analysis and Exoplanet Detection Simulations

Future space missions such as the Large UV-Optical-Infrared Surveyor (LUVOIR) and the Habitable Exoplanet Observatory (HabEx) require coronagraphs with active wavefront control to suppress starlight to discover and characterize habitable exoplanets. The Extreme Coronagraph for Living Planetary Systems (ECLIPS) is the coronagraph instrument on the LUVOIR Surveyor mission concept, an 8–15m segmented telescope. ECLIPS is split into three channels: UV (200 to 400 nm), optical (400 nm to 850 nm), and NIR (850 nm to 2.0 microns), with each channel equipped with two deformable mirrors for wavefront control, a suite of coronagraph masks, a low-order/out-of-band wavefront sensor, and separate science imagers and spectrographs. The Apodized Pupil Lyot Coronagraph (APLC) and the Vector Vortex Coronagraph (VVC) are the baselined mask technologies for ECLIPS to enable the required 10 -10 contrast for observations in the habitable zones of nearby stars. Their performance depends on active wavefront sensing and control, as well as metrology subsystems to compensate for aberrations induced by segment errors (piston and tip/tilt, among others), secondary mirror misalignment, and global low-order wavefront errors. Here we present the latest results of the simulation of these effects for the two technologies and discuss the achieved contrast for exoplanet detection and characterization after closed-loop wavefront estimation and control algorithms have been applied. Finally, we show simulated observations using high-fidelity spatial and spectral input models of complete planetary systems generated with the Haystacks code framework.

Roser Juanola-Parramon↗