Results for “weather radar” — Page 6

NASA NTRS2019

Use of Polarimetric Radar Measurements to Constrain Simulated Convective Cell Evolution: A Pilot Study with Lagrangian Tracking

To probe the potential value of a radar-driven field campaign to constrain simulation of isolated convection subject to a strong aerosol perturbation, convective cells observed by the operational KHGX weather radar in the vicinity of Houston, Texas, are examined individually and statistically. Cells observed in a single case study of onshore flow conditions during July 2013 are first examined and compared with cells in a regional model simulation. Observed and simulated cells are objectively identified and tracked from observed or calculated positive specific differential phase (K(sub DP)) above the melting level, which is related to the presence of supercooled liquid water. Several observed and simulated cells are subjectively selected for further examination. Below the melting level, we compare sequential cross sections of retrieved and simulated raindrop size distribution parameters. Above the melting level, we examine time series of KDP and radar differential reflectivity (Z(sub DR)) statistics from observations and calculated from simulated supercooled rain properties, alongside simulated vertical wind and supercooled rain mixing ratio statistics. Results indicate that the operational weather radar measurements offer multiple constraints on the properties of simulated convective cells, with substantial value added from derived K(sub DP) and retrieved rain properties. The value of collocated three-dimensional lightning mapping array measurements, which are relatively rare in the continental US, supports the choice of Houston as a suitable location for future field studies to improve the simulation and understanding of convective updraft physics. However, rapid evolution of cells between routine volume scans motivates consideration of adaptive scan strategies or radar imaging technologies to amend operational weather radar capabilities. A 3-year climatology of isolated cell tracks, prepared using a more efficient algorithm, yields additional relevant information. Isolated cells are found within the KHGX domain on roughly 40 % of days year-round, with greatest concentration in the northwest quadrant, but roughly 5-fold more cells occur during June through September. During this enhanced occurrence period, the cells initiate following a strong diurnal cycle that peaks in the early afternoon, typically follow a south-to-north flow, and dissipate within 1 h, consistent with the case study examples. Statistics indicate that ∼ 150 isolated cells initiate and dissipate within 70 km of the KHGX radar during the enhanced occurrence period annually, and roughly 10 times as many within 200 km, suitable for multi-instrument Lagrangian observation strategies. In addition to ancillary meteorological and aerosol measurements, robust vertical wind speed retrievals would add substantial value to a radar-driven field campaign.

Fridlind, Ann M.↗

NASA NTRS1980

Navigation errors encountered using weather-mapping radar for helicopter IFR guidance to oil rigs

In 1978 a joint NASA-FAA helicopter flight test was conducted to examine the use of weather-mapping radar for IFR guidance during landing approaches to oil rig helipads. The following navigation errors were measured: total system error, radar-range error, radar-bearing error, and flight technical error. Three problem areas were identified: (1) operational problems leading to pilot blunders, (2) poor navigation to the downwind final approach point, and (3) pure homing on final approach. Analysis of these problem areas suggests improvement in the radar equipment, approach procedure, and pilot training, and gives valuable insight into the development of future navigation aids to serve the off-shore oil industry.

Phillips, J. D.↗

NASA NTRS2020

Meteoritic Material Recovered from the 07 March 2018 Meteorite Fall into the Olympic Coast National Marine Sanctuary

On 07 March 2018 at 20:05 local time (08 March 03:05 UTC), a dramatic meteor occurred over Olympic Coast National Marine Sanctuary (OCNMS) off of the Washington state coast (“OCNMS fall”, henceforth). Data to include seismometry (from both on-shore and submarine seismometers), weather radar imagery (Figure 1), and a moored weather buoy, were used to accurately identify the fall site. The site was visited by the exploration vessel E/V Nautilus (Ocean Exploration Trust) on 01 July 2018 [1] and by the research vessel R/V Falkor (Schmidt Ocean Institute) from 03-06 June 2019. Remotely operated vehicles (ROVs) from both vessels were used to search for meteorites and sample seafloor sediments. These expeditions performed the first attempts to recover meteorites from a specific observed fall in the open ocean. Analysis of weather radar data indicates that this fall was unusually massive and featured meteorites of unusually high mechanical toughness, such that large meteorites were disproportionately produced compared to other meteorite falls (Figure 2)[2-4]. We report the recovery of many (>100) micrometeorite-sized melt spherules and other fragments, and one small (~1mm3 ) unmelted meteorite fragment identified to date. Approximately 80% of the fragments were recovered from a single sample, collected from a round pit in the seafloor sediment. Melt spherules are almost exclusively type I iron-rich spherules with little discernible oxidation. Analyses are currently underway to attempt to answer the primary science question by identifying the parent meteorite type. Also, differences in the number and nature of samples collected by Nautilus and Falkor reveal a distinct loss rate to oxidation over the 15 months following the fall that is useful to inform future recovery efforts.

Fries, M.↗

NASA NTRS1990

Analysis and improved design considerations for airborne pulse Doppler radar signal processing in the detection of hazardous windshear

High resolution windspeed profile measurements are needed to provide reliable detection of hazardous low altitude windshear with an airborne pulse Doppler radar. The system phase noise in a Doppler weather radar may degrade the spectrum moment estimation quality and the clutter cancellation capability which are important in windshear detection. Also the bias due to weather return Doppler spectrum skewness may cause large errors in pulse pair spectral parameter estimates. These effects are analyzed for the improvement of an airborne Doppler weather radar signal processing design. A method is presented for the direct measurement of windspeed gradient using low pulse repetition frequency (PRF) radar. This spatial gradient is essential in obtaining the windshear hazard index. As an alternative, the modified Prony method is suggested as a spectrum mode estimator for both the clutter and weather signal. Estimation of Doppler spectrum modes may provide the desired windshear hazard information without the need of any preliminary processing requirement such as clutter filtering. The results obtained by processing a NASA simulation model output support consideration of mode identification as one component of a windshear detection algorithm.

Lee, Jonggil↗

NASA NTRS2011

Sensitivity of Spaceborne and Ground Radar Comparison Results to Data Analysis Methods and Constraints

With the availability of active weather radar observations from space from the Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TR.MM) satellite, numerous studies have been performed comparing PR reflectivity and derived rain rates to similar observations from ground-based weather radars (GR). These studies have used a variety of algorithms to compute matching PR and GR volumes for comparison. Most studies have used a fixed 3-dimensional Cartesian grid centered on the ground radar, onto which the PR and GR data are interpolated using a proprietary approach and/or commonly available GR analysis software (e.g., SPRINT, REORDER). Other studies have focused on the intersection of the PR and GR viewing geometries either explicitly or using a hybrid of the fixed grid and PR/GR common fields of view. For the Dual-Frequency Precipitation Radar (DPR) of the upcoming Global Precipitation Measurement (GPM) mission, a prototype DPR/GR comparison algorithm based on similar TRMM PR data has been developed that defines the common volumes in terms of the geometric intersection of PR and GR rays, where smoothing of the PR and GR data are minimized and no interpolation is performed. The PR and GR volume-averaged reflectivity values of each sample volume are accompanied by descriptive metadata, for attributes including the variability and maximum of the reflectivity within the sample volume, and the fraction of range gates in the sample average having reflectivity values above an adjustable detection threshold (typically taken to be 18 dBZ for the PR). Sample volumes are further characterized by rain type (Stratiform or Convective), proximity to the melting layer, underlying surface (land/water/mixed), and the time difference between the PR and GR observations. The mean reflectivity differences between the PR and GR can differ between data sets produced by the different analysis methods; and for the GPM prototype, by the type of constraints and categorization applied to the data. In this paper, we will show results comparing the 3-D gridded analysis "black box" approach to the GPM prototype volume-matching approach, using matching TRMM PR and WSR-88D ground radar data. The affects of applying data constraints and data categorizations on the volume-matched data to the results will be shown, and explanations of the differences in terms of data and analysis algorithm characteristics will be presented. Implications of the differences to the determination of PR/DPR calibration differences and use of ground radar data to evaluate the PR and DPR attenuation correction algorithms will be discussed.

Morris, Kenneth R.↗

DOE OSTI2025

Calibration and Validation of the SAIL Radar

Calibration of a weather radar is not a simple process, as is well described and documented in several articles (Chandrasekar, V, L Baldini, N Bharadwaj, and PL Smith. 2015. "Calibration procedures for global precipitation-measurement ground-validation radars." URSI Radio Science Bulletin 2015(355): 45–73, https://10.23919/URSIRSB.2015.7909473.). Direct hardware-based characterization is called calibration whereas indirect check with other sources such as disdrometer, or comparison with other radars or indirect means, is called validation. The validation process has its own measurement error and the comparison should fall within its limit. In the following we describe calibration and validation processes for the SAIL radar. Based on the comparison of calibration and validation, an addition of 2 dB is suggested for the SAIL radar observations, with a nuanced Z dr calibration correction, as presented. If a fixed Z dr calibration is preferred, a bias addition of 0.5 dB is suggested.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2007

X-Band Radar for Studies of Tropical Storms from High Altitude UAV Platform

The increased role of unmanned aerial vehicles (UAV) in NASA's suborbital program has created a strong interest in the development of instruments with new capabilities, more compact sizes and reduced weights than the instruments currently operated on manned aircrafts. There is a strong demand and tremendous potential for using high altitude UAV (HUAV) to carry weather radars for measurements of reflectivity and wind fields from tropical storms. Tropical storm genesis frequently occurs in ocean regions that are inaccessible to piloted aircraft due to the long off shore range and the required periods of time to gather significant data. Important factors of interest for the study of hurricane genesis include surface winds, profiled winds, sea surface temperatures, precipitation, and boundary layer conditions. Current satellite precipitation and surface wind sensors have resolutions that are too large and revisit times that are too infrequent to study this problem. Furthermore, none of the spaceborne sensors measure winds within the storm itself. A dual beam X-band Doppler radar, UAV Radar (URAD), is under development at the NASA Goddard Space Flight Center for the study of tropical storms from HUAV platforms, such as a Global Hawk. X-band is the most desirable frequency for airborne weather radars since these can be built in a relatively compact size using off-the-shelf components which cost significantly less than other higher frequency radars. Furthermore, X-band radars provide good sensitivity with tolerable attenuation in storms. The low-cost and light-weight URAD will provide new capabilities for studying hurricane genesis by analyzing the vertical structure of tropical cyclones as well as 3D reflectivity and wind fields in clouds. It will enable us to measure both the 3D precipitation structure and surface winds by using two antenna beams: fixed nadir and conical scanning each produced by its associated subsystem. The nadir subsystem is a magnetron based radar modified from a marine radar transceiver. It is capable of measuring vertical reflectivity and velocity profile while being a lower-cost, smaller size, and lighter weight version of the NASA ER-2 Doppler Radar (EDOP), which has flown during many NASA field campaigns and has provided valuable scientific information on hurricanes and weather phenomena. Unfortunately, EDOP is too large and heavy for most UAV platforms, but the experience gained with this instrument provided us with the heritage to build a new low-cost, light-weight, smaller system that will be capable of flying on UAVs. The scanning subsystem uses a TWT transmitter and provides measurements of 3D reflectivity/wind fields in-clouds. Conical scanning of the radar beam at a 35 deg. incidence angle will also provide information of surface wind speed and direction derived from the surface return over a single 360 deg. sweep. URAD data system will be Linux based with the capability of autonomous operation. It will utilize cutting edge digital receiver and FPGA technologies to carry out the data acquisition and processing tasks. High speed navigation data from the aircraft will also be captured and saved along with radar data for 3D measurement field reconstruction and aircraft motion correction. There is a tremendous potential for UAVs to carry down-looking weather radars for measurements of reflectivity, horizontal and vertical winds from tropical storms. With operation from HUAV platforms, the dual beam X-band radar under development promises to provide greatly needed information for tropical storm research.

Rodriquez, Shannon↗

NASA NTRS2013

Effects of Tunable Data Compression on Geophysical Products Retrieved from Surface Radar Observations with Applications to Spaceborne Meteorological Radars

This paper presents results and analyses of applying an international space data compression standard to weather radar measurements that can easily span 8 orders of magnitude and typically require a large storage capacity as well as significant bandwidth for transmission. By varying the degree of the data compression, we analyzed the non-linear response of models that relate measured radar reflectivity and/or Doppler spectra to the moments and properties of the particle size distribution characterizing clouds and precipitation. Preliminary results for the meteorologically important phenomena of clouds and light rain indicate that for a 0.5 dB calibration uncertainty, typical for the ground-based pulsed-Doppler 94 GHz (or 3.2 mm, W-band) weather radar used as a proxy for spaceborne radar in this study, a lossless compression ratio of only 1.2 is achievable. However, further analyses of the non-linear response of various models of rainfall rate, liquid water content and median volume diameter show that a lossy data compression ratio exceeding 15 is realizable. The exploratory analyses presented are relevant to future satellite missions, where the transmission bandwidth is premium and storage requirements of vast volumes of data, potentially problematic.

cloud properties↗

NASA NTRS1977

Communications Link Characterization Experiment (CLCE), volume 3

The results of data which were acquired, reduced and analyzed as of June 1977, from the Communications Link Characterization Experiment while utilizing the Communications Link Characterization Experiment while utilizing the Communications Technology Satellite is presented. The long term yearly and worst month propagation data from both stations are presented for the defined yearly period and the test results of the Goddard Television Experiment are described. The data for the continuing path length analysis are updated. Progress on the continuing analysis of utilizing the weather radars for attenuation prediction is given and the concept of the weather radar ratio is presented.

Source record↗

NASA NTRS2003

The Application of Lidar to Synthetic Vision System Integrity

One goal in the development of a Synthetic Vision System (SVS) is to create a system that can be certified by the Federal Aviation Administration (FAA) for use at various flight criticality levels. As part of NASA s Aviation Safety Program, Ohio University and NASA Langley have been involved in the research and development of real-time terrain database integrity monitors for SVS. Integrity monitors based on a consistency check with onboard sensors may be required if the inherent terrain database integrity is not sufficient for a particular operation. Sensors such as the radar altimeter and weather radar, which are available on most commercial aircraft, are currently being investigated for use in a real-time terrain database integrity monitor. This paper introduces the concept of using a Light Detection And Ranging (LiDAR) sensor as part of a real-time terrain database integrity monitor. A LiDAR system consists of a scanning laser ranger, an inertial measurement unit (IMU), and a Global Positioning System (GPS) receiver. Information from these three sensors can be combined to generate synthesized terrain models (profiles), which can then be compared to the stored SVS terrain model. This paper discusses an initial performance evaluation of the LiDAR-based terrain database integrity monitor using LiDAR data collected over Reno, Nevada. The paper will address the consistency checking mechanism and test statistic, sensitivity to position errors, and a comparison of the LiDAR-based integrity monitor to a radar altimeter-based integrity monitor.

Campbell, Jacob L.↗

NASA NTRS2008

Hail Size Distribution Mapping

A 3-D weather radar visualization software program was developed and implemented as part of an experimental Launch Pad 39 Hail Monitor System. 3DRadPlot, a radar plotting program, is one of several software modules that form building blocks of the hail data processing and analysis system (the complete software processing system under development). The spatial and temporal mapping algorithms were originally developed through research at the University of Central Florida, funded by NASA s Tropical Rainfall Measurement Mission (TRMM), where the goal was to merge National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD) volume reflectivity data with drop size distribution data acquired from a cluster of raindrop disdrometers. In this current work, we adapted these algorithms to process data from a cluster of hail disdrometers positioned around Launch Pads 39A or 39B, along with the corresponding NWS radar data. Radar data from all NWS NEXRAD sites is archived at the National Climatic Data Center (NCDC). That data can be readily accessed at . 3DRadPlot plots Level III reflectivity data at four scan elevations (this software is available at Open Channel Software, ). By using spatial and temporal interpolation/extrapolation based on hydrometeor fall dynamics, we can merge the hail disdrometer array data coupled with local Weather Surveillance Radar-1988, Doppler (WSR-88D) radial velocity and reflectivity data into a 4-D (3-D space and time) picture of hail size distributions. Hail flux maps can then be generated and used for damage prediction and assessment over specific surfaces corresponding to structures within the disdrometer array volume. Immediately following a hail storm, specific damage areas and degree of damage can be identified for inspection crews.

Source record↗

DOE OSTI2021

Inpainting radar missing data regions with deep learning

Abstract. Missing and low-quality data regions are a frequent problem for weather radars. They stem from a variety of sources: beam blockage, instrument failure, near-ground blind zones, and many others. Filling in missing data regions is often useful for estimating local atmospheric properties and the application of high-level data processing schemes without the need for preprocessing and error-handling steps – feature detection and tracking, for instance. Interpolation schemes are typically used for this task, though they tend to produce unrealistically spatially smoothed results that are not representative of the atmospheric turbulence and variability that are usually resolved by weather radars. Recently, generative adversarial networks (GANs) have achieved impressive results in the area of photo inpainting. Here, they are demonstrated as a tool for infilling radar missing data regions. These neural networks are capable of extending large-scale cloud and precipitation features that border missing data regions into the regions while hallucinating plausible small-scale variability. In other words, they can inpaint missing data with accurate large-scale features and plausible local small-scale features. This method is demonstrated on a scanning C-band and vertically pointing Ka-band radar that were deployed as part of the Cloud Aerosol and Complex Terrain Interactions (CACTI) field campaign. Three missing data scenarios are explored: infilling low-level blind zones and short outage periods for the Ka-band radar and infilling beam blockage areas for the C-band radar. Two deep-learning-based approaches are tested, a convolutional neural network (CNN) and a GAN that optimize pixel-level error or combined pixel-level error and adversarial loss respectively. Both deep-learning approaches significantly outperform traditional inpainting schemes under several pixel-level and perceptual quality metrics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Study of Microphysical Signatures Based on Spectral Polarimetry during the RELAMPAGO Field Experiment in Argentina

Weather radars with dual-polarization capabilities enable the study of various characteristics of hydrometeors, including their size, shape, and orientation. Radar polarimetric measurements, coupled with Doppler information, allow for analysis in the spectral domain. This analysis can be leveraged to reveal valuable insight into the microphysics and kinematics of hydrometeors in precipitation systems. This paper uses spectral polarimetry to investigate precipitation microphysics and kinematics in storm environments observed during the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field experiment in Argentina. This study uses range–height indicator scan measurements from a C-band polarimetric Doppler weather radar deployed during the field campaign. Here, in this work, the impact of storm dynamics on hydrometeors is studied, including the size sorting of hydrometeors due to vertical wind shear. In addition, particle microphysical processes because of aggregation and growth of ice crystals in anvil clouds, as well as graupel formation resulting from the riming of ice crystals and dendrites, are also analyzed here. The presence of different particle size distributions because of the mixing of hydrometeors in a sheared environment and resulting size sorting has been reported using spectral differential reflectivity (sZ dr ) slope. Spectral reflectivity sZ h and sZ dr have also been used to understand the signature of ice crystal aggregation in an anvil cloud. The regions of pristine ice crystals are identified from vertical profiles of spectral polarimetric variables in anvil cloud because of sZ h < 0 dB and sZ dr values around 2 dB. It is also found that the growth process of these ice crystals causes a skewed bimodal sZ h spectrum due to the presence of both pristine ice crystals and dry snow. Next, graupel formation due to riming has been studied, and it is found that the riming process produces sZ h values of about 10 dB and corresponding sZ dr values of 1 dB. This positive sZ dr indicates the presence of needle/columnar secondary ice particles formed by ice multiplication processes in the riming zones. Last, the temporal evolution of a storm is investigated by analyzing changes in hydrometeor types with time and their influence on the spectral polarimetric variables.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

xsacrcfrspccopol (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). At ARM's tropical sites, X-band radars are paired with the Ka-band because they are better suited for the atmospheric attenuation in this region. Beamwidth for the X-band is approximately 1 degree, and the Ka-band beamwidth is roughly 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the XSACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. For the second ARM Mobile Facility (AMF2), the XSACR can be dismounted from the pedestal it shares with the KASACR and mounted on a separate pedestal. This allows the XSACR to operate more like a weather (precipitation) radar in deployments where such local coverage is lacking. Measurements collected with the XSACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, differential Reflectivity (Zdr), correlation coefficient (rho-hv), and specific differential phase (phi-dp). XSACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

xsacrcfrspcxpol (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). At ARM's tropical sites, X-band radars are paired with the Ka-band because they are better suited for the atmospheric attenuation in this region. Beamwidth for the X-band is approximately 1 degree, and the Ka-band beamwidth is roughly 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the XSACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. For the second ARM Mobile Facility (AMF2), the XSACR can be dismounted from the pedestal it shares with the KASACR and mounted on a separate pedestal. This allows the XSACR to operate more like a weather (precipitation) radar in deployments where such local coverage is lacking. Measurements collected with the XSACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, differential Reflectivity (Zdr), correlation coefficient (rho-hv), and specific differential phase (phi-dp). XSACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

xsacrcfrspccross (a1)

ARM's scanning cloud radars are fully coherent dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (WSACR; 1.7 kW peak power) or X-band (XSACR; 20 kW peak power). At ARM's tropical sites, X-band radars are paired with the Ka-band because they are better suited for the atmospheric attenuation in this region. Beamwidth for the X-band is approximately 1 degree, and the Ka-band beamwidth is roughly 0.3 degrees. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the XSACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. For the second ARM Mobile Facility (AMF2), the XSACR can be dismounted from the pedestal it shares with the KASACR and mounted on a separate pedestal. This allows the XSACR to operate more like a weather (precipitation) radar in deployments where such local coverage is lacking. Measurements collected with the XSACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, differential Reflectivity (Zdr), correlation coefficient (rho-hv), and specific differential phase (phi-dp). XSACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Bistatic scatter from rain

An experimental investigation of bistatic scatter from rain was conducted, using a 143-km scatter path at frequencies of 4.5 and 7.7 GHz. The ratio of transmitted to received power (transmission loss) was measured for scattering angles ranging from 6 to 130 deg. Simultaneous weather radar observations were made at a frequency of 1.3 GHz. Transmission loss estimates for the bistatic scatter path were computed, using the weather radar data, the bistatic radar equation, and a model for the scattering cross section per unit volume of rain based upon Rayleigh scattering by an ensemble of water spheres. The measured and estimated transmission loss values were compared to test the use of the scattering model for the estimation of interference. The averaged ratio of measured-to-calculated transmission loss for the 4.5 GHz data is 1.2 plus or minus 0.4 dB. The averaged ratio for the 7.7 GHz data is -1.6 plus or minus 0.5 dB.

Crane, R. K.↗

NASA NTRS1987

Airborne Doppler radar for wind shear detection

There has been extensive discussion concerning the use of ground based Doppler radars for the detection and measurement of microburst features and the mapping of associated wind shears. Recent and planned research at Langley into technology and techniques useful for the future development of airborne Doppler weather radar systems for both turbulence and wind shear detection are addressed. Such systems, if successfully developed, would represent a marked increase in performance over airborne weather radars currently available. A principal difficulty in extending to airborne radars the capabilities of current ground based Doppler radars is emphasized.

Staton, Leo↗