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NASA NTRSDate not supplied

Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the Howard County government in Maryland to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a prediction model capable of hindcasting the two severe flash flood events that devastated Ellicott City, and transitioned to an Long Short-Term Memory (LSTM) based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using the Nash-Sutcliffe Efficiency (NSE). The final product, called the Sequentially Trained Real-time EstimAted Model (STREAM), predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh (HRRR) model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate the OEM’s emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

Ryan Hammock↗

NASA NTRSDate not supplied

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

NASA NTRSDate not supplied

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

NASA NTRS2017

Reconnection-Driven Coronal-Hole Jets with Gravity and Solar Wind

Coronal-hole jets occur ubiquitously in the Sun's coronal holes, at EUV and X-ray bright points associated with intrusions of minority magnetic polarity. The embedded-bipole model for these jets posits that they are driven by explosive, fast reconnection between the stressed closed field of the embedded bipole and the open field of the surrounding coronal hole. Previous numerical studies in Cartesian geometry, assuming uniform ambient magnetic field and plasma while neglecting gravity and solar wind, demonstrated that the model is robust and can produce jet-like events in simple configurations. We have extended these investigations by including spherical geometry,gravity, and solar wind in a nonuniform, coronal hole-like ambient atmosphere. Our simulations confirm that the jet is initiated by the onset of a kink-like instability of the internal closed field, which induces a burst of reconnection between the closed and external open field, launching a helical jet. Our new results demonstrate that the jet propagation is sustained through the outer corona, in the form of a traveling nonlinear Alfven wave front trailed by slower-moving plasma density enhancements that are compressed and accelerated by the wave. This finding agrees well with observations of white-light coronal-hole jets, and can explain microstreams and torsional Alfven waves detected in situ in the solar wind. We also use our numerical results to deduce scaling relationships between properties of the coronal source region and the characteristics of the resulting jet, which can be tested against observations.

Karpen, J. T.↗

NASA NTRS1997

A Deep Imaging Survey of NGC 6475 and a Deep Survey of the Young Open Cluster Alpha Persei

We have published three papers directly related to the x-ray data (see below), and one other paper directly related to the optical photometry obtained in connection to the ROSAT data analysis (also listed below). In addition, we have used the x-ray data in combination with the optical photometry and with high resolution optical spectra that we have obtained (to derive spectroscopic rotational velocities) to address questions related to the dependence of coronal activity on the rotation rate, mass, and other characteristics of the target stars. The overall goal of our ROSAT projects has been to determine the time evolution of coronal activity in low mass stars, and from that behavior place constraints on the physical processes involved in generating coronal activity. NGC 6475 and Alpha Persei are important parts of that process. We are now beginning to address how these data constrain theoretical models of angular momentum evolution and dynamo magnetic field generation (see paper by Stauffer et al. and Krishnamurthi et al. listed below in the "related papers" section). We are still working on two papers pertaining to this grant (rotational velocities and chromospheric activity of Alpha Persei x-ray sources and rotational velocities and lithium abundances of NGC 6475 sources), but we will publish those papers using funds from other grants.

Stauffer, John R.↗

NASA NTRS2024

Sentinel-1 Snow Depth Assimilation to Improve River Discharge Estimates in the Western European Alps

Seasonal snow is an important water source and contributor to river discharge in mountainous regions. Therefore the amount of snow and its distribution are necessary inputs for hydrological modeling. Recent research has shown the potential of the Sentinel-1 radar satellite to map snow depth (SD) at sub-kilometer resolution in mountainous regions. In this study we assimilate these new SD retrievals into the Noah-Multiparameterization land surface model using an ensemble Kalman filter for the western European Alps. The land surface model was coupled to the Hydrological Modeling and Analysis Platform (HyMAP), a global flow routing scheme that provides simulations of routed river discharge. The performance with different precipitation forcing inputs, namely MERRA-2 (with and without gauge based correction) and ERA5, was compared based on in situ precipitation and SD stations, with ERA5 leading to the best SD performance. The Sentinel-1 based data assimilation (DA) results show small but systematic improvements for SD estimates, with the mean absolute error reducing from 36.4 cm for the open loop (OL) to 35.6 cm for the DA across all stations and timesteps, improving 318 out of 516 in situ sites. The DA updates in SD also result in enhanced snow water equivalent and discharge simulations. The median temporal correlation between discharge simulations and measurements increases from 0.73 to 0.78 for the DA. This study demonstrates the utility of the Sentinel-1 SD retrievals to improve not only the representation of snow in mountain ranges, but also the snow melt contribution to river discharge, and hydrological modeling in general.

Isis Brangers↗

NASA NTRS2023

Aurora Detection From Nighttime Lights for Earth and Space Science Applications

This research leverages data from the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer (VIIRS) instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. We demonstrate the value of mining the VIIRS DNB for aurora and describe our use of unsupervised machine learning to create a binary mask for aurora occurrence. This mask can be used to flag aurora-contaminated observations for NASA's nighttime lights products for Earth science applications. The identification of auroral regions can also be used for Space Weather applications, for example, for comparison with aurora forecast model and with other satellite- or ground-based aurora observations. The DNB is a broadband channel that is sensitive to wavelengths from 500 to 900 nm, which covers most of the visible light spectrum, and as the name implies, captures light even at night with a sensitivity at the nanowatt level. This band is suitable for aurora observations since the light emitted by the aurora tends to be dominated by emissions from atomic oxygen, resulting in a greenish glow at a wavelength of 557.7 nm, especially at an altitude of 110 km. This study compares the global nighttime derived aurora regions for 17 and 18 March with the NOAA Space Weather Prediction Center's (SWPC) probability product for the St. Patrick's Day geomagnetic storm in 2015. VIIRS sensors are slated to be added to the next generation of polar-orbiting operational satellites. Our novel automated approach to aurora identification opens up an efficient way to leverage this unique data source.

Aurora↗

NASA NTRS1983

The response of thermospheric atomic nitrogen to magnetic storms

Neutral composition data obtained by the open-source neutral-mass spectrometer on the polar orbiting Atmosphere Explorer D satellite during the periods October 31 to November 15, 1975, and January 5 to 15, 1976, are used to characterize the response of thermospheric atomic nitrogen densities to geomagnetic activity. These periods provided nearly simultaneous polar and low-latitude data coverage. At low and middle latitudes near dawn and at all latitudes on the dayside, N densities at 400 km appear to vary like those of a species of atomic mass 14: N is observed to increase with increasing geomagnetic activity in a manner similar to that of O. At auroral latitudes near dawn, however, there is a more complex dependence on the amplitude of the disturbance. For substorm-scale activity, N tends to increase during periods of auroral heating but exhibits a sharp temporary decrease afterward. During large storms there is a significant but short-lived increase of N at auroral latitudes. The present results support current models showing that N is produced and transported out of the auroral zone during geomagnetic disturbances.

Engebretson, M. J.↗

NASA NTRS1978

The importance of quadrupole sources in prediction of transonic tip speed propeller noise

A theoretical analysis is presented for the harmonic noise of high speed, open rotors. Far field acoustic radiation equations based on the Ffowcs-Williams/Hawkings theory are derived for a static rotor with thin blades and zero lift. Near the plane of rotation, the dominant sources are the volume displacement and the rho U(2) quadrupole, where u is the disturbance velocity component in the direction blade motion. These sources are compared in both the time domain and the frequency domain using two dimensional airfoil theories valid in the subsonic, transonic, and supersonic speed ranges. For nonlifting parabolic arc blades, the two sources are equally important at speeds between the section critical Mach number and a Mach number of one. However, for moderately subsonic or fully supersonic flow over thin blade sections, the quadrupole term is negligible. It is concluded for thin blades that significant quadrupole noise radiation is strictly a transonic phenomenon and that it can be suppressed with blade sweep. Noise calculations are presented for two rotors, one simulating a helicopter main rotor and the other a model propeller. For the latter, agreement with test data was substantially improved by including the quadrupole source term.

Hanson, D. B.↗

NASA NTRS1997

Oceanic Observations

For many years, merchant ships and the naval fleets of various countries have been the major source of data over and in the open ocean. Oceanographic research experiments and process studies in the field have also contributed to the climatological data bases for the global ocean, but, for the most part, these have been limited in duration and extent. However, over the last 10 years under the auspices of the World Climate Research Program and the International Geosphere Biosphere Program the role of the oceans in global and climate change has taken on increased significance. This has created a need for a considerably improved understanding of the seasonal, interannual, decadal and longer time-scale variability of the physical and biogeochemical attributes of the global ocean. As a result, over the past 10 years several major international field programs have been implemented and have had a tremendous impact on the number of in situ observations obtained for the global ocean. The Tropical Ocean Global Atmosphere (TOGA) program, the World Ocean Circulation Experiment (WOCE), and the Joint Global Ocean Flux Study (JGOFS) were designed with observational, modelling, and process study components aimed at analyzing different aspects of the ocean's role in the coupled climate system. In parallel with the field programs, continuous space-based observations of sea surface temperature, sea surface topography, and sea surface winds spanning nearly a decade or longer have become a reality. During this same time period, numerical ocean models and computational power have advanced to the point where the oceanographic observations, both in situ and remotely sensed, can be assimilated into numerical ocean models in order to provide a four-dimensional (x-y-z-t) depiction of the evolving state of the global ocean.

Busalacchi, Antonio J.↗

NASA NTRS2019

Utilization of Airborne Observations to Assess Model Parametrizations of Critical RH Profiles in the Arctic Ocean

Observational paucity is a reality in the Arctic Ocean. This is especially true for near-surface variables such as temperature, moisture, heat fluxes and BL clouds. As a result, modeling has become one of the major avenues for understanding current and future Arctic trends. Reanalyses are frequently used to force global ocean circulation and sea-ice models. But in northern high latitudes, model integrations and reanalyses are known to have large uncertainties in temperature and humidity profiles, and in boundary layer cloudiness. These are common sources of error in the surface radiative budget terms.An important way to diagnose these biases spatially and temporally is by using satellite remote sensing data. However, remotely-sensed observations also have large uncertainties, especially in near-surface temperature and relative humidity profiles.In situ observational studies are important in bridging our knowledge gap in regions such as the Arctic Ocean. Here, we utilize airborne and ship observations from the ARISE, ACME-IV, and ASCOS campaigns to construct critical relative humidity (RH) profiles over the Beaufort Sea. Such profiles are used as parameterization inputs in the NASA GOES global model to derive the total water condensate in a model grid-box, which determines the cloud fraction. Currently, the critical RH profiles are derived by global AIRS data, relaying mostly on mid-latitude regions, which are not necessarily relevant to the Arctic.We derive campaign-wide mean, standard deviation, and critical RH values, for grid size of 50x50 km and altitude bins between 50 to 400 m, covering both open-ocean and sea-ice covered regions. We compare profiles over open ocean and sea-ice, and look at correlations between the observed critical RH values and water condensate (by cloud number concentration) from observations versus the modeled ones. We then input our calculated values of minimal critical RH values into a set of GEOS single column model (SCM) simulations over the ARISE and ASCOS regions and compare the differences between the predicted values of cloud liquid water path (LWP), ice water path (IWP) and surface fluxes with the observed ones under the range of input parameterizations. Finally, we discuss the implications on surface radiative budget predictions in this region.

Segal-Rozenhaimer, Michal↗

NASA NTRS2003

Low-Energy Study of Gamma-Ray Bursts Having Spectral Line Features

Gamma-ray bursts (GRBs) are energetic, short-duration emissions of gamma-rays. The Burst and Transient Source Experiment (BATSE) that was onboard NASA s Compton Gamma-Ray Observatory has done much to advance our understanding of GRBs. Perhaps foremost is to establish that GRBs originate from astronomical sources that exist well beyond our galaxy. Another area in which BATSE has been instrumental is to provide high-resolution data that can be used in spectral studies. Before BATSE, there were many reports of GRB spectra containing what appeared to be spectral absorption lines, whereas Briggs, after an extensive computer search of 117 bright BATSE GRBs, reported finding only one case that might be an absorption line and ten cases that might be emission lines. None of the eleven BATSE cases were definitively identified as spectral lines, and Briggs indicated reasons as to why the pre-BATSE reports should not be taken as conclusive. It remains an open question as to what these spectral-like features are, or if they are even real. The purpose of this work is, for the subset of the eleven BATSE GRBs for which low-energy data are available from two BATSE's Spectroscopy Detectors (SDs), to include these data in the spectral analysis. Such a study will provide additional constraints on the model spectral functions to better ascertain the reality of the line features. The spectral analysis program used was RMFIT. Of the six GRBs that met the selection criteria, the analysis was performed on only three of them due to a lack of time.

Pangia, Michael J.↗

NASA NTRS2013

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four‐dimensional numerical model simulations is propelling the wider adoption of ultra‐resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well‐integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display‐to‐dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data‐intensive information. This information can be digital‐cinema animations, high‐resolution images, high‐definition video‐teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross‐platform, community‐driven, open‐source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Jedlovec, Gary↗

NASA NTRS2021

TLSLEAF: Automatic Leaf Angle Estimates From Single-Scan Terrestrial Laser Scanning

Leaf angle distribution (LAD) in forest canopies affects estimates of leaf area, light interception, and global-scale photosynthesis, but is often simplified to a single theoretical value. Here, we present TLSLeAF (Terrestrial Laser Scanning Leaf Angle Function), an automated open-source method of deriving LADs from terrestrial laser scanning. TLSLeAF produces canopy-scale leaf angle and LADs by relying on gridded laser scanning data. The approach increases processing speed, improves angle estimates, and requires minimal user input. Key features are automation, leaf–wood classification, beta parameter output, and implementation in R to increase accessibility for the ecology community. TLSLeAF precisely estimates leaf angle with minimal distance effects on angular estimates while rapidly producing LADs on a consumer-grade machine. We challenge the popular spherical LAD assumption, showing sensitivity to ecosystem type in plant area index and foliage profile estimates that translate to c. 25% and c. 11% increases in canopy net photosynthesis (c. 25%) and solar-induced chlorophyll fluorescence (c. 11%). TLSLeAF can now be applied to the vast catalog of laser scanning data already available from ecosystems around the globe. The ease of use will enable widespread adoption of the method outside of remote-sensing experts, allowing greater accessibility for addressing ecological hypotheses and large-scale ecosystem modeling efforts.

3D↗

NASA NTRS1994

Emission-line studies of young stars. 4: The optical forbidden lines

Optical forbidden line strengths and profiles are discussed for a sample of 30 T Tauri stars and 12 Herbig Ae-Be stars. Transitions of (C I), (N II), (O I), (O II), (S II), (Ca II), (Cr II), (Fe II), and (Ni II) are detected. Profile variability occurred in DG Tau and probably other sources. The ensemble profiles can be divided into four generic components that may represent distinct emitting regions; (1) narrow rest-velocity lines, (2) 'low'-velocity lines (peaking at less than or approximately +/- 50 km s(exp -1)), (3) 'high'-velocity (usually greater than or approximately +/- 100 km s(exp -1)) blueshifted peaks or wings, and (4) high-velocity redshifted peaks. Among T Tauri stars, the rest-velocity lines appear most often in sources with weak and narrow permitted lines, such as the Ca II triplet. The low- and high-velocity blueshifted components usually appear together in sources with strong and broad Ca II triplet lines. If the velocity-shifted lines form in jets, the smallest (full) opening angles required by the profiles are less than or approximately 20 deg for the narrow, blueshifted (Ca II) lines of DG Tau and HL Tau. Other lines in DG Tau are much broader, implying larger opening angles or greater velocity dispersions. The variability in DG Tau also implies significant changes in the collimation or velocity coherence on timescales of a few years. RW Aur and AS 353A have blue- and redshifted line peaks that could form in oppositely directed jets. The strong (S II) lambda 6716 and lambda 6731 lines in RW Aur are exclusively redshifted and require opening angles less than or approximately 60 deg. Measurements of different profiles in the same spectrum show that the physical conditions change with the line-of-sight velocities. The most persistent trends are for more (N II) and (O II) and less (O I) lambda 5577 flux at high velocities. Constraints on the physical conditions are derived by modeling the emission lines via multilevel ions in 'coronal ionization equilibrium.' A single temperature and density cannot fully describe the line spectra in any velocity interval. Temperatures in the (O I) region are 9000 less than or approximately T(sub e) less than 14,000 K, and the ionization fraction (of H) is less than 35%. The densities derived from (O I) include n(sub e) less than or approximately 5 x 10(exp 5) to approximately 10(exp 7) cm(exp -3), but n(sub e) greater than or approximately 10(exp 6) cm(exp -3) obtains only at low velocities. In the (S II) regions the densities are lower, 10(exp 3) less than or approximately n(sub e) less than or approximately 7 x 10(exp 4) cm(exp -3), and the temperatures are probably higher, T(sub e) greater than or approximately 13,000 K. At high velocities (only) there is additional hot gas that produces (N II) and (O II), possibly most of the (S II), and little (O I). This region is characterized by T(sub e) greater than or approximately 15,000 K, n(sub e) less than or approximately 10(exp 5) cm(exp -3), and an ionization fraction greater than or approximately 50%. When combined with the spatially segregated emitting regions observed by others by spectral imaging, these results suggest decreasing n(sub e) and increasing T(sub e) away from the star in at least the high velocity gas.

Hamann, Fred↗

NASA NTRS2006

Ultra-fine-scale filamentary structures in the Outer Corona and the Solar Magnetic Field

Filamentary structures following magnetic field lines pervade the Sun's atmosphere and offer us insight into the solar magnetic field. Radio propagation measurements have shown that the smallest filamentary structures in the solar corona are more than 2 orders of magnitude finer than those seen in solar imaging. Here we use radio Doppler measurements to characterize their transverse density gradient and determine their finest scale in the outer corona at 20-30 R(circled dot operator), where open magnetic fields prevail. Filamentary structures overly active regions have the steepest gradient and finest scale, while those overlying coronal holes have the shallowest gradient and least finest scale. Their organization by the underlying corona implies that these subresolution structures extend radially from the entire Sun, confirming that they trace the coronal magnetic field responsible for the radial expansion of the solar wind. That they are rooted all over the Sun elucidates the association between the magnetic field of the photosphere and that of the corona, as revealed by the similarity between the power spectra of the photospheric field and the coronal density fluctuations. This association along with the persistence of filamentary structures far from the Sun demonstrate that subresolution magnetic fields must play an important role not only in magnetic coupling of the photosphere and corona, but also in coronal heating and solar wind acceleration through the process of small-scale magnetic reconnection. They also explain why current widely used theoretical models that extrapolate photospheric magnetic fields into the corona do not predict the correct source of the solar wind.

Sun : Corona↗

NASA NTRSDate not supplied

Creating Satellite Data Products in the Cloud: SatCORPS Global Cloud Composites

Real time satellite observations and real time derived cloud products are becoming an important tool for both science as well as business ventures. The SatCORPS group leverages public and private cloud-based sources of satellite observations to create its Global Cloud Composite product in near real-time. This dataset allows others access to cloud information that can be accessed directly from the cloud. In this work, we describe the software algorithms and software infrastructure that we have created to create and distribute this product through our hybrid cloud and on-premises system that leverages the strengths and weaknesses of each platform. We will also describe the GCC product itself in terms of the scientific parameters available, resolution and temporal availability. Finally, we will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global cloud products with very low latency which we see that as filling a rapidly growing need in the research, modelling and business community. We present a detailed description of the SatCORPS GCC product in terms of the capabilities and research benefits as well as the delivery architecture in AWS. We take the discussion further and describe the web tools that the SatCORPS group has developed that allow users to access and use the GIS data that it creates.

Global Cloud Composite SatCORPS SMCE AWS↗

NASA NTRS1988

Wave/current interaction model

The wave-current interaction for the application to remote sensing data via numerical simulations and data comparison is modelled. Using the field data of surface current shear, wind condition and ambient wave spectrum, the numerical simulations of directional wave spectrum evolution were used to interpret and to compare with the aircraft data from Radar Ocean Wave Spectrometer (ROWS) and Surface Contour Radar (SCR) across the front during Frontal Air Sea Interaction Experiment (FASINEX). The wave-ice interaction was inspired by the observation of large amplitude waves hundreds of kms inside the ice pack in the Weddell Sea, resulting in breakup of the ice pack. The developed analysis of processes includes the refraction of waves at the pack edge, the effects of pack compression on wave propagation, wave train stability and buckling stability in the ice pack. Sources of pack compression and interaction between wave momentum and pack compression are investigated. Viscous camping of propagating waves in the marginal ice zone are also studied. The analysis suggests an explanation for the change in wave dispersion observed from the ship and the sequence of processes that cause ice pack breakup, pressure ridge formation and the formation of open bands of water.

Liu, A. K.↗