Search NASA⌕ Search

SEARCH · Search NASA

Results for “radar activities”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Passive Microwave Radiometry and Active Radar Sounding as Complementary Tools for Geophysical Investigations of Icy Ocean Worlds

Juno Microwave Radiometer (MWR) observations of Europa and Ganymede offer critical insights into the icy shells of these moons ahead of NASA's Europa Clipper and ESA's JUpiter ICy moons Explorer (JUICE) missions. Both missions are equipped with active radar sounders designed to address key unknowns such as ice shell thickness, thermal state, and composition. In this study, we explore how passive microwave radiometry and active radar sounding can constrain ice shell properties, focusing on Europa. Using modeled microwave brightness temperature observations at 0.6 and 1.2 GHz alongside simulated radar attenuation rate observations, we show that each instrument can independently produce robust ice shell thickness constraints under idealized conditions. We then relax these assumptions, quantifying how uncertainties from non-ideal properties—including convective layers, freezing-point depression, and chloride-doped ice—affect thickness estimates. Finally, we demonstrate how combining observations from these complementary techniques breaks degeneracies between ice shell properties, enabling more robust constraints than either method alone. This approach will maximize the science return of Europa Clipper and JUICE, advancing our understanding of the thermophysical structure and habitability of icy ocean worlds.

58 GEOSCIENCES↗

Ka-Band ARM Zenith Radar (KAZR) Active Remote Sensing of Clouds (ARSCL) CloudSat Calibration (KAZRARSCL-CLOUDSAT) (Value-Added Product Report)

The Ka-band ARM Zenith Radar Active Remote Sensing of CLouds CloudSat-aligned (KAZRARSCL-CLOUDSAT) Value-Added Product (VAP) applies satellite-based reflectivity calibrations to KAZRARSCL data sets. The Atmospheric Radiation Measurement (ARM) user facility has primarily used radar subsystem calibration monitoring to track cloud radar reflectivity drift over time, since reliable external calibration sources or other absolute references (such as corner reflectors) have historically been unavailable or impracticable. A study by Kollias et al. (2019) examined cloud reflectivity profiles observed with a well-characterized spaceborne downward-pointing millimeter cloud radar, operating as part of NASA’s CloudSat satellite mission (Tanelli et al. 2008). The Kollias team derived monthly statistical reflectivity offsets between CloudSat and the various generations of ARM cloud radars (millimeter wavelength cloud radar [MMCR], W-Band ARM Cloud Radar [WACR[, and Ka-band ARM Zenith Radar [KAZR]) for many, but not all, months at most fixed and mobile ARM sites over the period 2007-2017. These offsets, when available, are applied to the existing KAZRARSCL VAP products using the KAZRARSCL-CLOUDSAT VAP.

54 ENVIRONMENTAL SCIENCES↗

MOSAIC-CONUS: A Multimodal, Multi-Temporally Paired Dataset for Earth Sciences

Earth embeddings—vector representations of geographic locations indexed in space and time—are emerging as a unifying interface for geospatial AI. However, their quality depends not only on model design, but on how multimodal Earth observation (EO) data are spatially indexed, temporally aligned, and cross-modally associated during pretraining. We introduce MOSAIC-CONUS (Multimodal Observations with Spatially Aligned Imagery, Urban Points of Interest, In-Situ Measurements and Text Captions), a large-scale EO dataset over the contiguous United States, organized around 250,000 stratified point indices that serve as stable spatial keys across seven modalities: active radar, passive optical imagery, lidar-derived elevation, land cover, functional context, hydrometeorological measurements, and textual summaries. Unlike existing EO datasets, MOSAIC-CONUS introduces four contributions not jointly addressed in prior work: 1. an open-source, large-scale multimodal EO corpus structured around point-indexed data designed to support Earth embedding learning; 2. explicit radar-optical pairing tables spanning twelve temporal alignment regimes, formalizing cross-sensor alignment as a controllable variable for analyzing how temporal mismatch across modalities influences learned embeddings quality; 3. a benchmark suite spanning cross-modal retrieval, annual nightlights regression, and basin-held-out streamflow prediction, positioning MOSAIC-CONUS as a benchmark-ready resource for multimodal AI systems; and 4. a language-based embedding layer through co-registered textual summaries, enabling Earth embeddings to function as a queryable interface for agentic AI systems. The dataset and pairing protocols are publicly released.

54 ENVIRONMENTAL SCIENCES↗

KAZRARSCL-c0-Cloud Boundaries subset

The KAZR-ARSCL VAP provides cloud boundaries and best-estimate time-height fields of radar moments. The VAP merges corrected, but uncalibrated, KAZR moments from all active radar modes with cloud base and cloud mask observations from the micropulse lidar (MPL), cloud base from the ceilometer, as well information from soundings, rain gauge, and microwave radiometer instruments to produce two data streams, one with best-estimate cloud base and cloud layer boundaries, and another which also includes best-estimate time-height fields of radar moments. This DOI is for the data stream that contain cloud layer boundaries only. Please note that the reflectivity used in this level c0 product is uncalibrated.

54 ENVIRONMENTAL SCIENCES↗

Geolocation tracking for human identification and activity recognition using radar deep transfer learning

Abstract Human identification and activity recognition (HIAR) is crucial for many applications, such as surveillance, smart homes, and assisted living. As a sensing modality, radar has many unique characteristics including privacy protection, and contactless sensing. Single classification systems have shown to be accurate, but for long‐term solutions both human identification (ID) and human activity recognition (HAR) will need to be integrated in one system where it can be utilised simultaneously. In this article, a novel radar‐based human tracking system is presented where three classifiers are utilised to identify the subject and his/her behaviour. For any kind of motion, the system tracks the subject and detect the type of his/her motion. Based on the detected type of motion, the three classifiers are utilised for identification and activity recognition. The classifiers are built utilising deep transfer learning where three radar datasets are established to train and validate each of the deep networks. To recognise six activities and 10 human subjects, the three classifiers, namely, HAR, Gait ID, and Heart sound ID, achieve superior performance compared to the best reported results in literature with classification accuracies of 97.6%, 100%, and 41.8% respectively. Three successful examples are presented to demonstrate the introduced concept.

Alkasimi, Ahmad↗

Frost Table Elevation across a Low-Centered and a High-Centered Polygon, Mapped using Ground Penetrating Radar, Utqiagvik (Barrow), Alaska, 2015

Ground Penetrating Radar, active layer thickness point measurements, and ground elevation surveys were conducted on a low-centered and a high-centered polygon in Utqiagvik (Barrow), AK (on October 2nd, 2015) to map frost table topography and evaluate its influence on hydrological flow. Data were collected to improve our understanding of the topography of the permafrost table across polygons which may have a major influence on hydrology. This dataset includes 2 zip files containing the raw data, 2 csv files of processed data, and a pdf user guide.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Rapid SACR Observations of Convection at Bankhead National Forest (RAPID) Field Campaign Report

Improving our representation of convective cell processes requires better quantification of convective clouds throughout their entire life cycle. This includes gaining a clearer understanding of the controls on key convective cloud properties, such as updraft intensity, particle size distributions, rainfall rates, and hydrometeor species. Our inability to improve convective cloud process modeling stems, in part, from a limited understanding of convective cell properties, particularly given how rapidly these storms evolve. This lack of detailed observations in the most intense and organized convective storms is especially significant, as large errors remain in representing these clouds, which are critical for severe weather prediction and Earth system model performance. Cloud and precipitation radars are essential tools for studying cloud microphysics and dynamics, particularly in deeper convective clouds. The recent U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s third Mobile Facility (AMF3) Bankhead National Forest (BNF) deployment provides a unique opportunity to investigate important land–atmosphere interactions, as well as the environmental controls on deep convective cloud processes, in a location favorable for frequent convection. We operate the X/Ka-band Scanning ARM Cloud Radar (X/Ka SACR) using a scan strategy optimized to capture these rapidly evolving clouds and their properties, thereby improving studies of deep convective cloud processes. This effort is strengthened by a complementary and coordinated partnership with ongoing university and multi-agency radar activities collocated in north Alabama—a unique opportunity to examine clouds and precipitation from a lifetime-centric perspective.

54 ENVIRONMENTAL SCIENCES↗

Deliberate Motion Analytics Applied to CUAS Sensor Fusion

The Advanced Reactor Safeguards and Security (ARSS) program in the Department of Energy’s Office of Nuclear Energy (DOE-NE) seeks to identify new technology solutions for safeguards and security challenges associated with domestic deployment of advanced nuclear reactors. Research in the ARSS program is investigating alternative physical protection system (PPS) approaches that leverage new detection technologies. This report shows test results from a new form of artificial intelligence (AI) that is called deliberate motion analytics (DMA) when used to spatially and temporally fuse active radar and passive radio frequency (RF) detection that significantly improves detection of uncrewed aircraft systems (UASs). DMA is designed to filter out false positive alarms yet provide highly reliable intrusion detection at nuclear power plants (NPPs) and advanced small modular reactor (ASMR) perimeters. This form of AI is considered to be an enabling technology for security of the future and supports the ARSS investigation of alternative PPSs.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

ARM FY2025 Radar Plan

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is dedicated to delivering high-quality radar data that significantly advance our understanding of cloud and precipitation processes, improving climate models. With radars operating across diverse frequencies, scanning modes, and global climate conditions, extensive staffing is essential for effective management. Due to current staffing constraints, achieving the expected level of operational excellence requires a more strategic approach. To address this challenge, ARM has developed an operational radar plan for the upcoming Fiscal Year 2025 (FY25) based on budget and staffing considerations. This report summarizes the Fiscal Year 2024 (FY24) ARM radar-related activities and outlines the strategic plan for FY25. It presents a comprehensive radar plan that includes detailed activities, priorities, and a projected timeline aligned with the ARM radar roadmap. Key tasks, detailed in Table 1, cover various radar operational stages and coordinated efforts among ARM teams.

54 ENVIRONMENTAL SCIENCES↗

Laser Disdrometer Quantities (LDQUANTS) and Video Disdrometer Quantities (VDISQUANTS) Value-Added Products Report

Disdrometers are useful instruments that measure the distribution of raindrop sizes (drop size distribution: DSD) and the associated rainfall rates/accumulation as those raindrops fall to the ground. These DSDs are a quantity of interest to members of the modeler and observational communities. However, use of disdrometer data for model evaluation, radar monitoring, or other activities requires careful quality control and processing for key DSD properties of interest (e.g., the number concentration of drops) to ensure appropriate physical (scattering, fall speed) assumptions. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Laser Disdrometer Quantities and Video Disdrometer Quantities Value-Added Product (LDQUANTS/VDISQUANTS VAP) uses standard methods from Tokay et al. (e.g., 2013, 2014) to filter drops with unrealistic fall speeds. Further, it estimates several microphysical/geophysical quantities of parameterized DSDs (gamma or exponential assumption type fitting methods) as in previous disdrometer studies and ARM long-term efforts (e.g., Testud et al. 2001, Giangrande et al. 2014, Thompson et al. 2015). Disdrometers are also beneficial for cross-checks with other instrumentation, including rain gauges and radars. To support research interests and related radar monitoring activities, this product calculates radar equivalent quantities, including dual polarization radar quantities (e.g., Z, Differential Reflectivity ZDR, etc.), using T-Matrix scattering and additional wavelength, temperature, and drop shape assumptions (e.g., Thurai et al. 2007). All of these efforts allow disdrometer data sets to become more useful and easily handled by modeling and observational studies, or routine instrumentation checks.

47 OTHER INSTRUMENTATION↗

Ultra-wideband mutual coupling compensation of active electronically scanned arrays in multi-channel radar systems

Technologies pertaining to the calibration of ultra-wide-band active-electronically-scanned arrays to compensate for transmit and receive mutual coupling between array elements and/or non-ideal isolated channels are described herein. A plurality of near-field measurements are taken by way of probe or probes that may be moved among a plurality of positions aligned with respective elements in the array. For each position of the probe, each of the elements of the array is stimulated to transmit or receive a calibration signal to or from the probe, respectively. Frequency-domain transfer functions are computed from the received signals by the probe or the element for each of the array elements in each of the positions of the probe. The inverse of the matrix of transfer functions comprise frequency-domain transmit and receive correction factors that are used to modify desired array inputs/outputs such that the modified signals correct for mutual coupling between elements in the array.

42 ENGINEERING↗

Simulations of Winter Arctic Clouds and Associated Radiation Fluxes Using Different Cloud Microphysics Schemes in the Polar WRF: Comparisons With CloudSat, CALIPSO, and CERES

Clouds are important for the Arctic climate, but simulating such clouds with numerical models is still challenging. The accuracy of model clouds has not been sufficiently examined due to the harsh Arctic environment obstructing cloud observations, especially during Arctic winters experiencing polar nights. This study compares the Arctic winter clouds simulated by a weather forecast model to cloud observations from active (lidar and radar) satellite instruments. The model successfully produced cloud patterns similar to the satellite observations. However, the choice of the cloud physics module in the model can modify the amount of cloud water significantly enough to affect the simulated surface climate.

54 ENVIRONMENTAL SCIENCES↗

Improving Process Level Understanding of Boundary Layer Winds over the Northeast U.S. Shelf: The Third Wind Forecast Improvement Project (WFIP3)

The third Wind Forecast Improvement Project (WFIP3), a U.S. Department of Energy and National Oceanic and Atmospheric Administration sponsored investigation, sought to improve understanding of the physical phenomena in the atmosphere and ocean that dictate the structure and variability of wind and thermodynamic fields within the marine atmospheric boundary layer. WFIP3 focused on mesoscale and submesoscale flows -- including sea breezes, low-level jets, low-level clouds, and coastal storms -- and the ability of advanced numerical model parameterizations to represent them within fully coupled oceanic and atmospheric modeling systems and foundational weather forecast models. WFIP3 conducted a comprehensive 18-month observational study over the Northeast U.S. outer continental shelf, a high-use coastal zone, using a 3D multiscale sensor array to highly resolve the temporal, vertical, and horizontal structure of the coupled atmospheric and oceanic boundary layers. Multiple land-based study sites adjacent to the coastal ocean observed surface meteorology and vertical profiles of atmospheric properties via passive infrared and microwave radiometers, active lidars and radars, and radiosondes. At sea, an array of surface flux buoys and two vertical profiling lidar buoys observed both atmospheric and oceanic properties, augmented by land-based oceanographic radar systems and routine ship-based surveys. Intensive observations of the marine atmospheric boundary layer over the ocean was done from an air-sea interaction flux tower and extended deployments of a large autonomous barge platform. Numerous critical forecasting phenomena were observed that are being evaluated within regional coupled and uncoupled modeling systems, including the National Oceanic and Atmospheric Administration's foundational High-Resolution Rapid Refresh forecast model.

Kirincich, Anthony↗

Droplet Number Concentration Value-Added Product

The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloud layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.

97 MATHEMATICS AND COMPUTING↗

Improving High Resolution Offshore Wind Resource Assessments and Forecasts using Observations in the MA/RI Lease Areas

The third Wind Forecast Improvement Project (WFIP3) sought to improve understanding of the physical phenomena in the atmosphere and ocean that dictate the structure and variability of wind and thermodynamic fields within the Marine Atmospheric Boundary Layer (MABL). WFIP3 conducted a comprehensive 18-month observational study over the Northeast U.S. outer continental shelf, a high use coastal zone, using a 3-D multiscale sensor array to highly resolve the temporal, vertical, and horizontal structure of the coupled atmospheric and oceanic boundary layers. Multiple land-based study sites adjacent to the coastal ocean observed surface meteorology and vertical profiles of atmospheric properties via passive infrared and microwave radiometers, active lidars and radars, and radiosondes. At sea, an array of surface flux buoys and two vertical profiling lidar buoys observed both atmospheric and oceanic properties, augmented by land-based oceanographic radar systems and routine ship-based surveys. Intensive observations of the MABL over the ocean was done from an air-sea interaction flux tower and extended deployments of a large barge platform. WFIP3 focused on mesoscale and sub-mesoscale flows -- including sea breezes, low-level jets, low-level clouds, and coastal storms -- and the ability of advanced numerical model parameterizations to represent them within fully coupled oceanic and atmospheric modeling systems and foundational weather forecast models. Numerous critical forecasting phenomena were observed, however the project was terminated prior to the completion of the field observational period and the analysis period.

54 ENVIRONMENTAL SCIENCES↗

PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere

Forward models are a key tool to generate synthetic observations given knowledge of the atmospheric state. In this way, they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud-resolving models (CRMs). Herein, CRM profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for upward- and downward-looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing upwelling and downwelling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications and interfaces to many different formats of input and output, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh–Gans approximation (SSRGA) for both active and passive applications, which becomes especially important for the investigation of frozen hydrometeors.

54 ENVIRONMENTAL SCIENCES↗

Apparatus, system and method for highlighting activity-induced change in multi-pass synthetic aperture radar imagery

Described herein are various technologies relating to constructing a differenced change product (DCP) image. A plurality of synthetic aperture radar (SAR) images of a scene are generated based upon radar signals directed towards and reflected off of the scene, and a plurality of coherence change detection (CCD) images of the scene are generated based upon the SAR images. The CCD images are registered with one another, and their pixel values re-scaled according to a monotonic mapping function. The DCP image is generated based upon a computed pixel-wise difference between a pair of the re-scaled CCD images. The DCP image identifies locations in the scene where human activity-induced change is likely to have occurred between a pair of SAR passes of the scene.

42 ENGINEERING↗

Weather radar utility in hazard detection and response

Publicly accessible weather radar data have significant capabilities for meteorological measurements and predictions and, further, have the potential to measure nonmeteorological events that include smoke, ash, and debris plumes as well as explosions. The ability to identify and track nonmeteorological events can be of assistance in emergency response, hazard mitigation, and related activities in locations where radar coverage both exists and is recorded and accessible to the user. Here, in this study, events from multiple locations in the United States that are reported in news outlets are assessed using a manual inspection process of Level 2 weather radar data to identify anthropogenic and nonbiological returns. Explosive events are also identified, and a large high-altitude debris cloud from the intentional destruction of the SpaceX Starship is tracked across a wide area. Finally, future efforts using a machine learning model are discussed as a means of automating the process and potentially enabling near-real-time nonmeteorological event identification in the same areas where the data are accessible. Using weather radar data can be a valuable new tool for Department of Defense systems to aid in military awareness, and for interagency emergency response and forensic mission experts to consider national weather service data in their mission profiles. Radar data can be effective in detecting several common types of emergencies and inform and aid response personnel.

54 ENVIRONMENTAL SCIENCES↗