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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗
NASA NTRS1990

Observations of the galactic plane by the zodiacal infrared project

The two rocket flights of the Zodiacal Infrared Project (ZIP), flown 18 August 1980 and 31 July 1981, were intended to provide data on the near-infrared thermal emission of the interplanetary dust cloud over a broad range of ecliptic coordinates (latitudes -60 to +85 degrees, solar elongation angles 22 to 90 degrees and 140 to 180 degrees). In addition, their multiple crossings of the Galactic plane provided low resolution spectral data (delta lambda/lambda ranging from 1. to 0.1, for effective wavelengths from 3 to 30 microns) for most of the first quadrant (longitudes 30 to 100 degrees). Examples are displayed. Having made a thorough reanalysis of the calibration of the ZIP database, researchers present the salient features of the Galactic plane as observed by ZIP. The binned, in-plane data, corrected for zodiacal emission, generally show an exponential decrease with increasing longitude. The fitted exponential scale-length is 0.038/degree, and can be inverted to derive a radial density profile. Channel ratios are converted to temperatures by using model spectra in which thermal emitters with emissivity approx. 1/lambda are convolved with the filter responses. The results for channels 5 (11 microns) and 12 (21 microns) are shown, along with similarly derived temperatures from Infrared Astronomy Satellite (IRAS) 12 microns and 25 microns data. The ZIP data show little variation with longitude, consistent with IRAS results. A narrow spectral feature at 13 microns appears consistently in data for the plane (uncorrected for zodiacal emission). However, this is strongly contaminated by calibration problems for channel 8. Researchers suggest that residual emission at 13 microns arises from the (NeII) line at 12.8 microns.

Rickard, L. J.↗
NASA NTRS2014

NASA's Astromaterials Database: Enabling Research Through Increased Access to Sample Data, Metadata and Imagery

The Astromaterials Acquisition & Curation Office at NASA's Johnson Space Center (JSC) is the designated facility for curating all of NASA's extraterrestrial samples. Today, the suite of collections includes the lunar samples from the Apollo missions, cosmic dust particles falling into the Earth's atmosphere, meteorites collected in Antarctica, comet and interstellar dust particles from the Stardust mission, asteroid particles from Japan's Hayabusa mission, solar wind atoms collected during the Genesis mission, and space‐exposed hardware from several missions. To support planetary science research on these samples, JSC's Astromaterials Curation Office hosts NASA's Astromaterials Curation digital repository and data access portal [http://curator.jsc.nasa.gov/], providing descriptions of the missions and collections, and critical information about each individual sample. Our office is designing and implementing several informatics initiatives to better serve the planetary research community. First, we are re‐hosting the basic database framework by consolidating legacy databases for individual collections and providing a uniform access point for information (descriptions, imagery, classification) on all of our samples. Second, we continue to upgrade and host digital compendia that summarize and highlight published findings on the samples (e.g., lunar samples, meteorites from Mars). We host high resolution imagery of samples as it becomes available, including newly scanned images of historical prints from the Apollo missions. Finally we are creating plans to collect and provide new data, including 3D imagery, point cloud data, micro CT data, and external links to other data sets on selected samples. Together, these individual efforts will provide unprecedented digital access to NASA's Astromaterials, enabling preservation of the samples through more specific and targeted requests, and supporting new planetary science research and collaborations on the samples.

Evans, Cindy↗
DOE OSTI2016

Advances in Grid Computing for the FabrIc for Frontier Experiments Project at Fermialb

The FabrIc for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientic Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of diering size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certicate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have signicantly matured, and present an increasingly complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the eorts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production work ows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular work ows, and support troubleshooting and triage in case of problems. Recently a new certicate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specic third-party Certicate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.

Herner, K.↗
NASA NTRS2012

Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry

Satellite retrievals of snow depth and water equivalent (SWE) are critical for monitoring watershed scale processes around the world. However, the problem is especially challenging in mountainous regions where complex heterogeneities limit the utility of low resolution satellite sensors. The Geoscience Laser Altimeter Sensor (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat) collected surface elevation data along near-repeat reference transects over land areas from 2003-2009. Although intended for monitoring ice caps and sea ice, the seven year global GLAS data base has provided unprecedented opportunity to test the capability of satellite lidar technology for estimating snow depth over land. GLAS single track and low repeat frequency does not provide data sufficient for operational estimates. However, its comparatively small footprint size of -65 m and its database of seasonal repeat observations during both snow and no-snow conditions have been sufficient to evaluate the potential of spacebased lidar altimetry for estimating snow depth. Recent analysis of ICESat elevations in the Uinta Mountains in NE Utah provide encouraging results for watershed scale estimates of snow depth. Research reported here focuses on the sensitivity of several versions of an ICESat snow depth algorithm to a range of landscape types defined by vegetation cover, slope and roughness. Results are compared to available SNOTEL data.

Jasinski, Michael F.↗
DOE OSTI2024

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗
NASA NTRS1998

Monitoring Direct Effects of Delta, Atlas, and Titan Launches from Cape Canaveral Air Station

Launches of Delta, Atlas, and Titan rockets from Cape Canaveral Air Station (CCAS) have potential environmental effects that could arise from direct impacts of the launch exhaust (e.g., blast, heat), deposition of exhaust products of the solid rocket motors (hydrogen chloride, aluminum oxide), or other effects such as noise. Here we: 1) review previous reports, environmental assessments, and environmental impact statements for Delta, Atlas, and Titan vehicles and pad areas to clarity the magnitude of potential impacts; 2) summarize observed effects of 15 Delta, 22 Atlas, and 8 Titan launches; and 3) develop a spatial database of the distribution of effects from individual launches and cumulative effects of launches. The review of previous studies indicated that impacts from these launches can occur from the launch exhaust heat, deposition of exhaust products from the solid rocket motors, and noise. The principal effluents from solid rocket motors are hydrogen chloride (HCl), aluminum oxide (Al2O3), water (H2O), hydrogen (H2), carbon monoxide (CO), and carbon dioxide (CO2). The exhaust plume interacts with the launch complex structure and water deluge system to generate a launch cloud. Fall out or rain out of material from this cloud can produce localized effects from acid or particulate deposition. Delta, Atlas, and Titan launch vehicles differ in the number and size of solid rocket boosters and in the amount of deluge water used. All are smaller and use less water than the Space Shuttle. Acid deposition can cause damage to plants and animals exposed to it, acidify surface water and soil, and cause long-term changes to community composition and structure from repeated exposure. The magnitude of these effects depends on the intensity and frequency of acid deposition.

Schmalzer, Paul A.↗
DOE OSTI2021

Physics-Infused AI/ML Based Digital-Twin Framework for Flow-Induced-Vibration Damage Prediction in a Nuclear Reactor Heat Exchanger

This report summarizes some of the ongoing work related to the development of an expert-elicitation-digital-twin framework for real time damage state prediction in heat exchanger components of a nuclear reactor. The framework is targeted towards predicting damage associated with coupled low cycle fatigue (associated with regular heat-up, cool-down and power operation transients) and high cycle fatigue (associated with flow induced vibration transients). The overall framework will be based on a NoSQL based database, physics-infused-geometry-dependent virtual-sensor data, different AI/ML techniques-based data-driven-predictive-model applications (Apps) and real-time plant sensor measurements available through few existing sensors. Towards this overall goal, this report updates some of the ongoing work, such as on implementation of a NoSQL Database (such as MongoDB), FE based heat transfer analysis of a heat exchanger (e.g. of a PWR steam generator) for generating geometry-dependent virtual sensor data and evaluation of various AI/ML models such as based on multivariate linear regression, ensembled decision-tree based Random-Forest and Gradient-Boosting regression and high-dimensional-kernel-function-transformation based Support-Vector-Machine regression models. The AI/ML models were evaluated for predicting multi-time-series thermal states at thousands of 3D point-clouds

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2014

Characteristics of Precipitation Features and Annual Rainfall during the TRMM Era in the Central Andes

The central Andes extends from 7 deg to 21 deg S, with its eastern boundary defined by elevation (1000m and greater) and its western boundary by the coastline. The authors used a combination of surface observations, reanalysis, and the University of Utah Tropical Rainfall Measuring Mission (TRMM) precipitation features (PF) database to understand the characteristics of convective systems and associated rainfall in the central Andes during the TRMM era, 1998-2012. Compared to other dry (West Africa), mountainous (Himalayas), and dynamically linked (Amazon) regions in the tropics, the central Andes PF population was distinct from these other regions, with small and weak PFs dominating its cumulative distribution functions and annual rainfall totals. No more than 10% of PFs in the central Andes met any of the thresholds used to identify and define deep convection (minimum IR cloud-top temperatures, minimum 85-GHz brightness temperature, maximum height of the 40-dBZ echo). For most of the PFs, available moisture was limited (less than 35mm) and instability low (less than 500 J kg(exp -1)). The central Andes represents a largely stable, dry to arid environment, limiting system development and organization. Hence, primarily short-duration events (less than 60 min) characterized by shallow convection and light to light-moderate rainfall rates (0.5-4.0 mm h(exp -1)) were found.

Andes Mountains↗
DOE OSTI2019

Development of a Real-Time Mobility Control and Visualization System with Predictive Vehicle Speed Control for Connected and Automated Vehicles (CAVs)

The Oak Ridge National Laboratory is developing a cloud-based platform for the deployment and evaluation of mobility- and efficiency-oriented connected and automated vehicles (CAVs) applications that will include fundamental data management, communications and visualization elements. This system will serve as a data portal, providing indirect communications that are relevant to efficiency applications, and can be used for both real world CAVs deployments and virtual systems that allow evaluation of new CAVs applications and algorithms. Predictive vehicle speed control algorithms have been developed and will be integrated with the real-time queryable transportation database and geospatial platform to achieve optimized energy efficiency and improved traffic flow in off-freeway driving. This paper describes the technology and summarizes evaluations being conducted for a corridor in Chattanooga, Tennessee, where the technology is expected to be initially deployed. To evaluate the fuel savings resulting from the vehicle speed control and the RTMCS data framework, vehicle powertrain simulations will be completed using results from a calibrated microscopic traffic model.

Laclair, Tim↗
DOE OSTI2019

A Scalable Online Monitoring System Based on Elasticsearch for Distributed Data Acquisition in Cms

The part of the CMS Data Acquisition (DAQ) system responsible for data readout and event building is a complex network of interdependent distributed applications. To ensure successful data taking, these programs have to be constantly monitored in order to facilitate the timeliness of necessary corrections in case of any deviation from specified behaviour. A large number of diverse monitoring data samples are periodically collected from multiple sources across the network. Monitoring data are kept in memory for online operations and optionally stored on disk for post-mortem analysis. We present a generic, reusable solution based on an open source NoSQL database, Elasticsearch, which is fully compatible and non-intrusive with respect to the existing system. The motivation is to benefit from an off the-shelf software to facilitate the development, maintenance and support efforts. Elasticsearch provides failover and data redundancy capabilities as well as a programming language independent JSON-over-HTTP interface. The possibility of horizontal scaling matches the requirements of a DAQ monitoring system. The data load from all sources is balanced by redistribution over an Elasticsearch cluster that can be hosted on a computer cloud. In order to achieve the necessary robustness and to validate the scalability of the approach the above monitoring solution currently runs in parallel with an existing in-house developed DAQ monitoring system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

C-SAPR2 Convective Cell Tracking Database during CACTI

The convective cell tracking database V1 using the ARM CSAPR2 radar data set at the Sierras de Córdoba (COR) AMF site in Argentina consists of individually tracked convective cells during the entire CACTI field campaign from 15 October 2018 to 3 March 2019. The cell tracking database is produced by applying an updated version of the FLEXible object TRaKeR (FLEXTRKR) (Feng et al. 2022) to the Cartesian gridded CSAPR2 PPI data set produced by the Taranis radar processing package (Hardin et al. 2020).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

A Multi-Wavelength Study of the Hot Component of the Interstellar Medium

The goals of this research are as follows: (1) Using the large number of lines of sight available in the ME database, identify the lines of sight with high-velocity components in interstellar lines, from neutral species through Si VI, C IV, and N V; (2) Compare the column density of the main components (i.e. low velocity components) of the interstellar lines with distance, galactic longitude and latitude, and galactic radial position. Derive statistics on the distribution of components in space (e.g. mean free path, mean column density of a component). Compare with model predictions for the column densities in the walls of old SNR bubbles and superbubbles, in evaporating cloud boundaries and in turbulent mixing layers; (3) For the lines of sight associated with multiple high velocity, high ionization components, model the shock parameters for the associated superbubble and SNR to provide more accurate energy input information for hot phase models and galactic halo models. Thus far 49 lines of sight with at least one high velocity component to the C IV lines have been identified; and (4) Obtain higher resolution data for the lines of sight with high velocity components (and a few without) to further refine these models.

Nichols, Joy↗
NASA NTRS2013

Impact of Radiatively Interactive Dust Aerosols in the NASA GEOS-5 Climate Model: Sensitivity to Dust Particle Shape and Refractive Index

We investigate the radiative effects of dust aerosols in the NASA GEOS-5 atmospheric general circulation model. GEOS-5 is improved with the inclusion of a sectional aerosol and cloud microphysics module, the Community Aerosol and Radiation Model for Atmospheres (CARMA). Into CARMA we introduce treatment of the dust and sea salt aerosol lifecycle, including sources, transport evolution, and sinks. The aerosols are radiatively coupled to GEOS-5, and we perform a series of multi-decade AMIP-style simulations in which dust optical properties (spectral refractive index and particle shape distribution) are varied. Optical properties assuming spherical dust particles are from Mie theory, while those for non-spherical shape distributions are drawn from a recently available database for tri-axial ellipsoids. The climatologies of the various simulations generally compare well to data from the MODIS, MISR, and CALIOP space-based sensors, the ground-based AERONET, and surface measurements of dust deposition and concentration. Focusing on the summertime Saharan dust cycle we show significant variability in our simulations resulting from different choices of dust optical properties. Atmospheric heating due to dust enhances surface winds over important Saharan dust sources, and we find a positive feedback where increased dust absorption leads to increased dust emissions. We further find that increased dust absorption leads to a strengthening of the summertime Hadley cell circulation, increasing dust lofting to higher altitudes and strengthening the African Easterly Jet. This leads to a longer atmospheric residence time, higher altitude, and generally more northward transport of dust in simulations with the most absorbing dust optical properties. We find that particle shape, although important for radiance simulations, is a minor effect compared to choices of refractive index, although total atmospheric forcing is enhanced by greater than 10 percent for simulations incorporating a spheroidal shape distribution versus ellipsoidal or spherical shapes.

radiative forcing↗
NASA NTRS2004

Accuracy Assessments and Validation of an Expanded UV Irradiance Database from Satellite Total Ozone Mapping Spectrometer (TOMS)

The TOMS UV irradiance database (1978 to 2000) has been expanded to include 5 new products (noon irradiance at 305, 310, 324, and 380 nm, and noon erythemal-weighted irradiance), in addition to the existing erythemal daily exposure, which permit direct Comparisons with ground-based measurements from UV spectrometers. Sensitivity studies are conducted to estimate uncertainties of the new TOMS UV irradiance data due to algorithm apriori assumptions. Comparisons with Brewer spectrometers as well as filter radiometers are used to review of the sources of known errors. Inability to distinguish between snow and cloud cover using only TOMS data results in large errors in estimating surface UV using snow climatology. A correction is suggested for the case when the regional snow albedo is known from an independent source. The summer-time positive bias between TOMS UV estimations and Brewer measurements can be seen at all wavelengths. This suggests the difference is not related to ozone absorption effects. We emphasize that uncertainty of boundary layer UV aerosol absorption properties remains a major source of error in modeling UV irradiance in clear sky conditions. Neglecting aerosol absorption by the present TOMS algorithm results in a positive summertime bias in clear-sky UV estimations over many locations. Due to high aerosol variability the bias is strongly site dependent. Data from UV-shadow-band radiometer and well-calibrated CIMEL sun-sky radiometer are used to quantify the bias at NASA/GSFC site in Greenbelt, MD. Recommendations are given to enable potential users to better account for local conditions by combining standard TOMS UV data with ancillary ground measurements.

Krotkov, N. A.↗
NASA NTRS2014

A Super-Resolution Laser Altimetry Concept

A super-resolution laser altimetry technique has been proposed to provide improved lidar altimetry from Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar data, and it is applicable to other similar atmospheric profiling lidar with low-pass filters. To achieve high altimetry resolution, the new technique relies on an empirical relationship between the peak signal ratio and the distance between land surface and the peak signal range bin center, which is directly derived from the CALIPSO lidar measurements and does not require the CALIPSO's transient response. The CALIPSO surface elevation results in Northern America retrieved by the new technique agree with the National Elevation Database high resolution elevation maps, and the comparisons suggest that the precision of the technique is much better than 1.4 m. The preliminary data product of land surface elevation retrieved by the new technique from CALIPSO lidar measurements is available to the altimetry community for evaluation.

Lu, Xiaomei↗
NASA NTRSDate not supplied

Toward The Development of Hailstorm Climatologies Derived From Reanalyses and Infared/Passive Microwave Satellite Imagers

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) and Meteosat series, provide both historical and near-real-time observations of cloud top patterns that are commonly associated with severe convection. Environmental conditions favorable for severe weather are thought to be represented well by reanalyses. Predicting exactly where convection and costly storm hazards like hail will occur using models or satellite imagery alone, however, is extremely challenging. The multivariate combination of satellite-observed cloud patterns with reanalysis environmental parameters, linked to United States Next Generation Weather Radar- (NEXRAD-) estimated Maximum Expected Size of Hail (MESH) using a deep neural network (DNN), enables estimation of potentially severe hail likelihood for any observed storm cell. These estimates are specifically designed to make hail likelihood distinctions based on satellite-indicated points of deep convection within environments favorable for storm development. We seek an approach that can be used to estimate climatological hailstorm frequency and risk throughout the historical satellite data record. This presentation demonstrates that statistical distributions of convective parameters from satellite and reanalysis show separation between non-severe/severe hailstorm classes for predictors including overshooting cloud top temperature and area characteristics, convective available potential energy, vertical wind shear, 500 hPa temperature, mid-level lapse rate, precipitable water, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN to produce a hail likelihood metric with a critical success index of 0.504 and Heidke skill score of 0.403, which is exceptional among recent analogous hail studies. Furthermore, applications of the DNN to select case studies demonstrate good qualitative agreement between hail likelihood and MESH. These hail classifications are aggregated across an 11-year GOES-12/13 image database to derive a hail frequency and severity climatology, which denotes the Central Plains, the Midwest, and northwestern Mexico as being the most hail-prone regions within the domain studied. Opportunities for training and applying DNN-based hailstorm predictions to recently developed GOES-8/10/12/13/16 and Meteosat Second Generation convective storm detection and characterization climatologies over South America and South Africa, respectively, will also be presented.

Kristopher Bedka↗
NASA NTRSDate not supplied

Retrieve Methane from IR sounder measurements Using Machine Learning-Enhanced Physical Inversion

The sensitivity of IR sounder measurements to atmospheric CH 4 is often limited due to interferences from signals of other trace gases, insufficient thermal contrast, and cloud blockage. In order to resolve the geographical and vertical distribution of atmospheric CH 4 profiles, accurate scene-dependent a priori information is critically needed to support an optimal estimation method-based physical inversion scheme. Following the principles of indexing, representation, and retrieval, a spectral fingerprinting methodology is developed to address the needs for both accuracy and computational efficiency in sounder-based CH 4 retrieval. Within this framework, a clustering method based on machine learning is first employed to stratify and identify the a priori state within the pre-constructed database, using optimized spectral radiances as predictors. The corresponding radiative kernel is then used to establish the physical inversion scheme for finding the solution. High-quality data from CH 4 data assimilation systems like the Carbon-Tracker and the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, as well as the state-of-art sounder products are used to build the training database, including radiative kernels. We will demonstrate the results retrieved from CrIS observations and the associated validation work.

Wan Wu↗