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NASA NTRSDate not supplied

Recent Developments in the Assimilation of Microwave and Radar Observations Into NWP Models

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRS1983

Development and flight test of an X-band precision approach concept for remote-area rotorcraft operations

A novel airborne radar-based precision approach concept was developed and flight tested as a part of NASA's Rotorcraft All-Weather Operations Research Program. A demonstration, transponder-based beacon landing system (BLS), incorporating state-of-the-art X-band radar technology and digital processing techniques, was built and flight tested to demonstrate the concept feasibility. The BLS airborne hardware consists of an add-on microprocessor, installed in conjunction with the aircraft weather/mapping radar, which analyzes the radar beacon receiver returns and determines range, localizer deviation, and glide slope deviation. The ground station is an inexpensive, portable unit which can be quickly deployed at a landing site. Results from the flight test program show that the BLS concept has a significant potential for providing rotorcraft with low-cost, precision, instrument approach capability in remote areas.

Clary, G. R.↗

NASA NTRS1983

Development and flight test of an X-band precision approach concept for remote-area rotorcraft operations

Clary, G. R.↗

NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗

NASA NTRS1993

On the estimation of the correlation dimension and its application to radar reflector discrimination

Recently, system theorists have recognized that low order systems of nonlinear differential equations can give rise to solutions which are neither periodic, constant, nor predictable in steady state, but which are nonetheless bounded and deterministic. This behavior, which was first described in the study of weather systems, has been termed 'chaotic.' Much study of chaotic systems has concentrated on analysis of the systems' phase space attractors. It has been recognized that invariant measures of the attractor possess inherent information about the system. One such measure is the dimension of the attractors. The dimension of a chaotic attractor has been shown to be noninteger, leading to the term 'strange attractor;' the attractor is said to have a fractal structure. The correlation dimension has become one of the most popular measures of dimension. However, many problems have been identified in correlation dimension estimation from time sequences. The most common methods for obtaining the correlation dimension have been least squares curves fitting to find the slope of the correlation integral and the Takens Estimator. However, these estimates show unacceptable sensitivity to the upper limit on the distance chosen. Here, a new method is proposed which is shown to be rather insensitive to the upper limit and to perform in a very stable manner, at least in the absence of noise. The correlation dimension is also shown to be an effective discriminant in distinguishing between radar returns resulting from weather and those from the ground. The weather returns are shown to have a correlation dimension generally between 2.0 and 3.0, while ground returns have a correlation dimension exceeding 3.0.

Barnett, Kevin D.↗

NASA NTRS1984

Development and flight test of a helicopter compact, portable, precision landing system concept

An airborne, radar-based, precision approach concept is being developed and flight tested as a part of NASA's Rotorcraft All-Weather Operations Research Program. A transponder-based beacon landing system (BLS) applying state-of-the-art X-band radar technology and digital processing techniques, was built and is being flight tested to demonstrate the concept feasibility. The BLS airborne hardware consists of an add-on microprocessor, installed in conjunction with the aircraft weather/mapping radar, which analyzes the radar beacon receiver returns and determines range, localizer deviation, and glide-slope deviation. The ground station is an inexpensive, portable unit which can be quickly deployed at a landing site. Results from the flight test program show that the BLS concept has a significant potential for providing rotorcraft with low-cost, precision instrument approach capability in remote areas.

Clary, G. R.↗

NASA NTRS2021

Retrieval of Snow Water Equivalent by the Precipitation Imaging Package (PIP) over Northern Great Lakes

Performance of the Precipitation Imaging Package (PIP) for estimating the snow water equivalent (SWE) is evaluated through a comparative study with the collocated National Oceanic and Atmospheric Administration National Weather Service snow stake field measurements. The PIP together with a vertically pointing radar, a weighing bucket gauge, and a laser-optical disdrometer was deployed at the NWS Marquette, Michigan office building for a long-term field study supported by the National Aeronautics and Space Administration’s Global Precipitation Measurement mission Ground Validation program. The site was also equipped with a weather station. During the 2017-18 winter, PIP functioned nearly uninterrupted at frigid temperatures accumulating 2345.8 mm of geometric snow depth over a total of 499 hours. This long record consists of 30 events, and the PIP-retrieved and snow stake field measured SWE differed less than 15% in every event. For the windy events, the wind corrected stake field record agreed better with the PIP-retrieved SWE. Two of the major events with the longest duration and the highest accumulation are examined in detail. The particle mass with a given diameter was much lower during a shallow, colder, uniform lake-effect event than in the deep, less cold, and variable synoptic event. This study demonstrated that PIP is a robust instrument for operational use, and is reliable for deriving the bulk properties of falling snow.

Ali Tokay↗

NASA NTRS1993

Current and future use of TOPSAR digital topographic data for volcanological research

In several investigations of volcanoes, high quality digital elevation models (DEM's) are required to study either the geometry of the volcano or to investigate temporal changes in relief due to eruptions. Examples include the analysis of volume changes of a volcanic dome, the prediction of flow paths for pyroclastic flows, and the quantitative investigation of the geometry of valleys carved by volcanic mudflows. Additionally, to provide input data for models of lava flow emplacement, accurate measurements are needed of the thickness of lava flows as a function of distance from the vent and local slope. Visualization of volcano morphology is also aided by the ability to view a DEM from oblique perspectives. Until recently, the generation of these DEM's has required either high resolution stereo air photographs or extensive field surveying using the Global Positioning System (GPS) and other field techniques. Through the use of data collected by the NASA/JPL TOPSAR system, it is now possible to remotely measure the topography of volcanoes using airborne radar interferometry. TOPSAR data can be collected day or night under any weather conditions, thereby avoiding the problems associated with the derivation of DEM's from air photographs that may often contain clouds. Here we describe some of our initial work on volcanoes using TOPSAR data for Mt. Hekla (Iceland) and Vesuvius (Italy). We also outline various TOPSAR topographic studies of volcanoes in the Galapagos and Hawaii that will be conducted in the near future, describe how TOPSAR complements the volcanology investigations to be conducted with orbital radars (SIR-C/X-SAR, JERS-1 and ERS-1), and place these studies into the broader context of NASA's Global Change Program.

Mouginis-Mark, Peter J.↗

DOE OSTI2025

The Sensor Dilemma in Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) are at the forefront in advancing the way we interact and perceive with the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as Radar, LiDAR and Video Imaging which are the most popular modalities for ITS. Real-time perception data from these sensors allows intelligent infrastructure side decision making to improve the energy, efficiency and safety at traffic intersections. As traffic departments across the United States are transitioning from traditional loop detectors / emulators and embracing newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception which is reliable, inexpensive, easy to setup and has robust performance in varying weather conditions. However, choosing a sensor which checks all boxes is not straightforward as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long range vehicles and weather resistance but lacks high resolution. LiDAR is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines Radar, LiDAR and camera sensors capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. Through this evaluation, we hope to draw attention to the necessity of National Renewable Energy Laboratory's (NREL) Infrastructure Perception and Control (IPC) framework which presents a multi-sensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like Radar, LiDAR and cameras, offers the most robust solution for enhancing the safety and efficiency in intelligent transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1996

Performance of the NASA Airborne Radar with the Windshear Database for Forward-Looking Systems

This document describes the simulation approach used to test the performance of the NASA airborne windshear radar. An explanation of the actual radar hardware and processing algorithms provides an understanding of the parameters used in the simulation program. This report also contains a brief overview of the NASA airborne windshear radar experimental flight test results. A description of the radar simulation program shows the capabilities of the program and the techniques used for certification evaluation. Simulation of the NASA radar is comprised of three steps. First, the choice of the ground clutter data must be made. The ground clutter is the return from objects in or nearby an airport facility. The choice of the ground clutter also dictates the aircraft flight path since ground clutter is gathered while in flight. The second step is the choice of the radar parameters and the running of the simulation program which properly combines the ground clutter data with simulated windshear weather data. The simulated windshear weather data is comprised of a number of Terminal Area Simulation System (TASS) model results. The final step is the comparison of the radar simulation results to the known windshear data base. The final evaluation of the radar simulation is based on the ability to detect hazardous windshear with the aircraft at a safe distance while at the same time not displaying false alerts.

Switzer, George F.↗

NASA NTRS2005

Modern Radar Techniques for Geophysical Applications: Two Examples

The last decade of the evolution of radar was heavily influenced by the rapid increase in the information processing capabilities. Advances in solid state radio HF devices, digital technology, computing architectures and software offered the designers to develop very efficient radars. In designing modern radars the emphasis goes towards the simplification of the system hardware, reduction of overall power, which is compensated by coding and real time signal processing techniques. Radars are commonly employed in geophysical radio soundings like probing the ionosphere; stratosphere-mesosphere measurement, weather forecast, GPR and radio-glaciology etc. In the laboratorio di Geofisica Ambientale of the Istituto Nazionale di Geofisica e Vulcanologia (INGV), Rome, Italy, we developed two pulse compression radars. The first is a HF radar called AIS-INGV; Advanced Ionospheric Sounder designed both for the purpose of research and for routine service of the HF radio wave propagation forecast. The second is a VHF radar called GLACIORADAR, which will be substituting the high power envelope radar used by the Italian Glaciological group. This will be employed in studying the sub glacial structures of Antarctica, giving information about layering, the bed rock and sub glacial lakes if present. These are low power radars, which heavily rely on advanced hardware and powerful real time signal processing. Additional information is included in the original extended abstract.

Arokiasamy, B. J.↗

DOE OSTI2023

Multi–year analysis of rain–snow levels at Marquette, Michigan

This study uses observations from a ground-based instrument suite to investigate the rain-snow level in stratiform rainfall from January 2014 to April 2020 in the Upper Great Lakes Region. The height above the surface where ice melts to rain, the rain-snow level (RSL), influences microphysical assumptions in remote sensing precipitation retrievals and the ability of space-based radar to discriminate surface precipitation phase because of ground clutter. The instrument suite is installed at the Marquette, MI (MQT) National Weather Service station adjacent to Lake Superior. Rain events and the RSL are studied through a ground-based vertically profiling radar (Micro Rain Radar), a custom NASA-developed video disdrometer (Precipitation Imaging Package), and reanalyses products from ECMWF ERA5 and NASA MERRA-2. Further, distinct macro and micro physical characteristics are observed in precipitation events with shallow RSL ( < 1.8 km above ground level [AGL]) and intermediate RSL ( > 1.8 km AGL). Intermediate RSL correspond to rain events with relatively higher rain rates and a higher concentration of small drops in the drop size distributions (DSDs). Shallow RSL DSDs contain relatively higher concentrations of large drops with lower fall speeds suggesting that partially melted snowflakes may be reaching the surface. Reflectivity-rain-rate relationships are also impacted by microphysical differences associated with RSL regimes. Radar-detected RSL agree with reanalysis-derived melt levels- especially at wet-bulb isotherms of 0.5°C and 1°C. Seasonal differences such as shallow rain-snow levels in winter, fall, and spring have subsequent implications for satellite detectability.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2008

Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

Molthan, Andrew L.↗

DOE OSTI2020

Synergetic Use of the WSR-88D Radars, GOES-R Satellites, and Lightning Networks to Study Microphysical Characteristics of Hurricanes

Abstract This study analyzes the microphysics and precipitation pattern of Hurricanes Harvey (2017) and Florence (2018) in both the eyewall and outer rainband regions. From the retrievals by a satellite red–green–blue scheme, the outer rainbands show a strong convective structure while the inner eyewall has less convective vigor (i.e., weaker upper-level reflectivities and electrification), which may be related to stronger vertical wind shear that hinders fast vertical motions. The WSR-88D column-vertical profiles further confirm that the outer rainband clouds have strong vertical motion and large ice-phase hydrometeor formation aloft, which correlates well with 3D Lightning Mapping Array source counts in height and time. From the results from this study, it is determined that the inner eyewall region is dominated by warm rain, whereas the external rainband region contains intense mixed-phase precipitation. External rainbands are defined here as those that reside outside of the main hurricane circulation, associated with surface tropical storm wind speeds. The synergy of satellite and radar dual-polarization parameters is instrumental in distinguishing between the key microphysical features of intense convective rainbands and the warm-rain-dominated eyewall regions within the hurricanes. Substantial amounts of ice aloft and intense updrafts in the external rainbands are indicative of heavy surface precipitation, which can have important implications for severe weather warnings and quantitative precipitation forecasts. The novel part of this study is to combine ground-based radar measurement with satellite observations to study hurricane microphysical structure from surface to cloud top so as to fill in the gaps between the two observational techniques.

Meteorology & Atmospheric Sciences↗

NASA NTRS1995

Lightning forecasting studies using LDAR, LLP, field mill, surface mesonet, and Doppler radar data

The ultimate goal of this research is to develop rules, algorithms, display software, and training materials that can be used by the operational forecasters who issue weather advisories for daily ground operations and launches by NASA and the United States Air Force to improve real-time forecasts of lightning. Doppler radar, Lightning Detection and Ranging (LDAR), Lightning Location and Protection (LLP), field mill (Launch Pad Lightning Warning System -- LPLWS), wind tower (surface mesonet) and additional data sets have been utilized in 10 case studies of thunderstorms in the vicinity of KSC during the summers of 1994 and 1995. These case studies reveal many intriguing aspects of cloud-to-ground, cloud-to-cloud, in-cloud, and cloud-to-air lightning discharges in relation to radar thunderstorm structure and evolution. They also enable the formulation of some preliminary working rules of potential use in the forecasting of initial and final ground strike threat. In addition, LDAR and LLP data sets from 1993 have been used to quantify the lightning threat relative to the center and edges of LDAR discharge patterns. Software has been written to overlay and display the various data sets as color imagery. However, human intervention is required to configure the data sets for proper intercomparison. Future efforts will involve additional software development to automate the data set intercomparisons, to display multiple overlay combinations in a windows format, and to allow for animation of the imagery. The software package will then be used as a tool to examine more fully the current cases and to explore additional cases in a timely manner. This will enable the formulation of more general and reliable forecasting guidelines and rules.

Forbes, Gregory S.↗

DOE OSTI2025

The Sensor Dilemma in Intelligent Transportation Systems: Evaluating Radar, Lidar and Camera: Preprint

Intelligent transportation systems (ITS) are at the forefront in advancing the way we interact with and perceive the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as radar, lidar, and video imaging, which are the most popular modalities for ITS. Real-time perception data from these sensors allow intelligent infrastructure-side decision-making to improve the energy, efficiency, and safety at traffic intersections. As traffic departments across the United States transition from traditional loop detectors and emulators and embrace newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception that is reliable, inexpensive, and easy to set up and that has robust performance in varying weather conditions. However, choosing a sensor that checks all these boxes is not straightforward, as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long-range vehicles and weather resistance but lacks high resolution. Lidar is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines radar, lidar, and camera sensor capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like radar, lidar, and cameras offers the most robust solution for enhancing the safety and efficiency of ITS. Through this evaluation, we hope to draw attention to the necessity of the National Renewable Energy Laboratory's infrastructure perception and control framework, which presents a multisensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1977

On the hysteresis of the sea surface and its applicability to wave height predictions

Because of the low dissipation rate of wave energy on the ocean's surface, the wave height at some location and time must be dependent upon wind fields in existence there at previous times and upon swell propagated there from other regions. To study these relationships, significant wave height (SWH) measurements from the Geos-3 radar altimeter are used in conjunction with anemometer windspeed measurements from weather ships, L, C, and R. During the passage of large cyclonic disturbances near the fixed locations of these vessels in the North Atlantic in February 1976, distinct hysteresis profiles that characterize the sea's memory during generation and dissipation conditions are observed. Examples are given that demonstrate the influences of cyclone intensity, movement, velocity, and shape on the configuration of these profiles.

Parsons, C. L.↗

NASA NTRS2000

Coherent Doppler Laser Radar: Technology Development and Applications

NASA's Marshall Space Flight Center has been investigating, developing, and applying coherent Doppler laser radar technology for over 30 years. These efforts have included the first wind measurement in 1967, the first airborne flights in 1972, the first airborne wind field mapping in 1981, and the first measurement of hurricane eyewall winds in 1998. A parallel effort at MSFC since 1982 has been the study, modeling and technology development for a space-based global wind measurement system. These endeavors to date have resulted in compact, robust, eyesafe lidars at 2 micron wavelength based on solid-state laser technology; in a factor of 6 volume reduction in near diffraction limited, space-qualifiable telescopes; in sophisticated airborne scanners with full platform motion subtraction; in local oscillator lasers capable of rapid tuning of 25 GHz for removal of relative laser radar to target velocities over a 25 km/s range; in performance prediction theory and simulations that have been validated experimentally; and in extensive field campaign experience. We have also begun efforts to dramatically improve the fundamental photon efficiency of the laser radar, to demonstrate advanced lower mass laser radar telescopes and scanners; to develop laser and laser radar system alignment maintenance technologies; and to greatly improve the electrical efficiency, cooling technique, and robustness of the pulsed laser. This coherent Doppler laser radar technology is suitable for high resolution, high accuracy wind mapping; for aerosol and cloud measurement; for Differential Absorption Lidar (DIAL) measurements of atmospheric and trace gases; for hard target range and velocity measurement; and for hard target vibration spectra measurement. It is also suitable for a number of aircraft operations applications such as clear air turbulence (CAT) detection; dangerous wind shear (microburst) detection; airspeed, angle of attack, and sideslip measurement; and fuel savings through headwind minimization. In addition to the airborne and space platforms, a coherent Doppler laser radar system in an unmanned aerial vehicle (UAV) could provide battlefield weather and target identification.

Kavaya, Michael J.↗