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At least 379 records · Page 21

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision at the Shuttle Landing Facility. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAFs), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. Both the SMG and the MLB are currently implementing the Weather Research and Forecasting Environmental Modeling System (WRF EMS) software into their operations. The WRF EMS software allows users to employ both dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model- the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, provides SMG and NWS MLB with a lot of flexibility. It also creates challenges, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and to determine which configuration will best predict warm season convective initiation in East-Central Florida. Four different combinations of WRF initializations will be run (ADAS-ARW, ADAS-NMM, LAPS-ARW, and LAPS-NMM) at a 4-km resolution over the Florida peninsula and adjacent coastal waters. Five candidate convective initiation days using three different flow regimes over East-Central Florida will be examined, as well as two null cases (non-convection days). Each model run will be integrated 12 hours with three runs per day, at 0900, 1200, and 1500 UTe. ADAS analyses will be generated every 30 minutes using Level II Weather Surveillance Radar-1988 Doppler (WSR-88D) data from all Florida radars to verify the convection forecast. These analyses will be run on the same domain as the four model configurations. To quantify model performance, model output will be subjectively compared to the ADAS analyses of convection to determine forecast accuracy. In addition, a subjective comparison of the performance of the ARW using a high-resolution local grid with 2-way nesting, I-way nesting, and no nesting will be made for select convective initiation cases. The inner grid will cover the East-Central Florida region at a resolution of 1.33 km. The authors will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for predicting warm season convective initiation over East-Central Florida.

Watson, Leela R.↗

Hydrometeor Size Distribution Measurements by Imaging the Attenuation of a Laser Spot

The optical extinction of a laser due to scattering of particles is a well-known phenomenon. In a laboratory environment, this physical principle is known as the Beer-Lambert law, and is often used to measure the concentration of scattering particles in a fluid or gas. This method has been experimentally shown to be a usable means to measure the dust density from a rocket plume interaction with the lunar surface. Using the same principles and experimental arrangement, this technique can be applied to hydrometeor size distributions, and for launch-pad operations, specifically as a passive hail detection and measurement system. Calibration of a hail monitoring system is a difficult process. In the past, it has required comparison to another means of measuring hydrometeor size and density. Using a technique recently developed for estimating the density of surface dust dispersed during a rocket landing, measuring the extinction of a laser passing through hail (or dust in the rocket case) yields an estimate of the second moment of the particle cloud, and hydrometeor size distribution in the terrestrial meteorological case. With the exception of disdrometers, instruments that measure rain and hail fall make indirect measurements of the drop-size distribution. Instruments that scatter microwaves off of hydrometeors, such as the WSR-88D (Weather Surveillance Radar 88 Doppler), vertical wind profilers, and microwave disdrometers, measure the sixth moment of the drop size distribution (DSD). By projecting a laser onto a target, changes in brightness of the laser spot against the target background during rain and hail yield a measurement of the DSD's second moment by way of the Beer-Lambert law. In order to detect the laser attenuation within the 8-bit resolution of most camera image arrays, a minimum path length is required. Depending on the intensity of the hail fall rate for moderate to heavy rainfall, a laser path length of 100 m is sufficient to measure variations in optical extinction using a digital camera. For hail fall only, the laser path may be shorter because of greater scattering due to the properties of hailstones versus raindrops. A photodetector may replace the camera in automated installations. Laser-based rain and hail measurement systems are available, but they are based on measuring the interruption of a thin laser beam, thus counting individual hydrometeors. These systems are true disdrometers since they also measure size and velocity. The method reported here is a simple method, requiring far less processing, but it is not a disdrometer.

Lane, John↗

Automated Discovery of Flight Track Anomalies

As new technologies are developed to handle the complexities of the Next Generation Air Transportation System (NextGen), it is increasingly important to address both current and future safety concerns along with the operational, environmental, and efficiency issues within the National Airspace System (NAS). In recent years, the Federal Aviation Administration’s (FAA) safety offices have been researching ways to utilize the many safety databases maintained by the FAA, such as those involving flight recorders, radar tracks, weather, and many other high- volume sensors, in order to monitor this unique and complex system. Although a number of current technologies do monitor the frequency of known safety risks in the NAS, very few methods currently exist that are capable of analyzing large data repositories with the purpose of discovering new and previously unmonitored safety risks. While monitoring the frequency of known events in the NAS enables mitigation of already identified problems, a more proactive approach of finding unidentified issues still needs to be addressed. This is especially important in the proactive identification of new, emergent safety issues that may result from the planned introduction of advanced NextGen air traffic management technologies and procedures. Development of an automated tool that continuously evaluates the NAS to discover both events exhibiting flight characteristics indicative of safety-related concerns as well as operational anomalies will heighten the awareness of such situations in the aviation community and serve to increase the overall safety of the NAS. This paper discusses the extension of previous anomaly detection work to identify operationally significant flights within the highly complex airspace encompassing the New York area of operations, focusing on the major airports of Newark International (EWR), LaGuardia International (LGA), and John F. Kennedy International (JFK). In addition, flight traffic in the vicinity of Denver International (DEN) airport/airspace is also investigated to evaluate the impact on operations due to variances in seasonal weather and airport elevation. From our previous research, subject matter experts determined that some of the identified anomalies were significant, but could not reach conclusive findings without additional supportive data. To advance this research further, causal examination using domain experts is continued along with the integration of air traffic control (ATC) voice data to shed much needed insight into resolving which flight characteristic(s) may be impacting an aircraft's unusual profile. Once a flight characteristic is identified, it could be included in a list of potential safety precursors. This paper also describes a process that has been developed and implemented to automatically identify and produce daily reports on flights of interest from the previous day.

Matthews, Bryan↗

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗

Engineering a visual system for seeing through fog

We examine the requirements for on-board aircraft sensor systems that would allow pilots to 'see through' poor weather, especially fog, and land and rollout aircraft under conditions that currently cause flight cancellations and airport closures. Three visual aspects of landing and rollout are distinguished: guidance, hazard detection and hazard recognition. The visual features which support the tasks are discussed. Three broad categories of sensor technology are examined: passive millimeter wave (PMMW), imaging radar, and passive infrared (IR). PMMW and imaging radar exhibit good weather penetration, but poor spatial and temporal resolution. Imaging radar exhibits good weather penetration, but typically relies on a flat-earth assumption which can lead to interpretive errors. PMMW systems have a narrow field of view. IR has poorer weather penetration but good spatial resolution. We recommend using both millimeter-wave and infrared sensor systems, blending the images using multiresolution digital-image pyramid-processing technology, and fusing the resulting real-time images with stored database imagery of the same scene.

Larimer, J.↗

Efficient transfer of weather information to the pilot in flight

Efficient methods for providing weather information to the pilot in flight are summarized. Use of discrete communications channels in the aeronautical, VHF band or subcarriers in the VOR navigation band are considered the best possibilities. Data rates can be provided such that inputs to the ground based transmitters from 2400 band telephone lines are easily accommodated together with additional data. The crucial weather data considered for uplinking are identified as radar reflectivity patterns relating to precipitation, spherics data, hourly sequences, nowcasts, forecasts, cloud top heights with freezing and icing conditions, the critical weather map and satellite maps. NEXRAD, the ground based, Doppler weather radar which will produce an improved weather product also encourages use of an uplink to fully utilize its capability to improve air safety.

Mcfarland, R. H.↗

Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) Cost-Benefit Analysis

Lightning Launch Commit Criteria (LLCC) are designed to prevent space launch vehicles from flight through environments conducive to natural or triggered lightning and are used for all U.S. government and commercial launches at government and civilian ranges. They are maintained by a committee known as the NASA/USAF Lightning Advisory Panel (LAP). The previous LLCC for anvil cloud, meant to avoid triggered lightning, have been shown to be overly restrictive. Some of these rules have had such high safety margins that they prohibited flight under conditions that are now thought to be safe 90% of the time, leading to costly launch delays and scrubs. The LLCC for anvil clouds was upgraded in the summer of 2005 to incorporate results from the Airborne Field Mill (ABFM) experiment at the Eastern Range (ER). Numerous combinations of parameters were considered to develop the best correlation of operational weather observations to in-cloud electric fields capable of rocket triggered lightning in anvil clouds. The Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) was the best metric found. Dr. Harry Koons of Aerospace Corporation conducted a risk analysis of the VAHIRR product. The results indicated that the LLCC based on the VAHIRR product would pose a negligible risk of flying through hazardous electric fields. Based on these findings, the Kennedy Space Center Weather Office is considering seeking funding for development of an automated VAHIRR algorithm for the new ER 45th Weather Squadron (45 WS) RadTec 431250 weather radar and Weather Surveillance Radar-1988 Doppler (WSR-88D) radars. Before developing an automated algorithm, the Applied Meteorology Unit (AMU) was tasked to determine the frequency with which VAHIRR would have allowed a launch to safely proceed during weather conditions otherwise deemed "red" by the Launch Weather Officer. To do this, the AMU manually calculated VAHIRR values based on candidate cases from past launches with known anvil cloud LLCC violations. An automated algorithm may be developed if the analyses from past launches show VAHIRR would have provided a significant cost benefit by allowing a launch to proceed. The 45 WS at the ER and 30th Weather Squadron (30 WS) at the Western Range provided the AMU with launch weather summaries from past launches that were impacted by LLCC. The 45 WS provided summaries from 14 launch attempts and the 30 WS fkom 5. The launch attempts occurred between December 2001 and June 2007. These summaries helped the AMU determine when the LLCC were "red" due to anvil cloud. The AMU collected WSR-88D radar reflectivity, cloud-to-ground lightning strikes, soundings and satellite imagery. The AMU used step-by-step instructions for calculating VAHIRR manually as provided by the 45 WS. These instructions were used for all of the candidate cases when anvil cloud caused an LLCC violation identified in the launch weather summaries. The AMU evaluated several software programs capable of visualizing radar data so that VAHIRR could be calculated and chose GR2Analyst from Gibson Ridge Software, LLC. Data availability and lack of detail from some launch weather summaries permitted analysis of six launch attempts from the ER and none from the WR. The AMU did not take into account whether or not other weather LCC violations were occurring at the same time as the anvil cloud LLCC since the goal of this task was to determine how often VAHIRR provided relief to the anvil cloud LLCC at any time during several previous launch attempts. Therefore, in the statistics presented in this report, it is possible that even though VAHIRR provided relief to the anvil cloud LLCC, other weather LCC could have been violated not permitting the launch to proceed. The results of this cost-benefit analysis indicated VAHIRR provided relief from the anvil cloud LLCC between about 15% and 18% of the time for varying 5-minute time periods based on summaries fkom six launch attempts and would have allowed launch to proceed that were otherwise "NO GO" due to the anvil cloud LLCC if the T-0 time occurred during the anvil cloud LLCC violations.

Bauman, William H., III↗

Comprehensive Severe Weather Impact Assessment and Monitoring using Synthetic Aperture Radar and Auxiliary Data

Remote sensing datasets, particularly acquired by Synthetic Aperture Radar (SAR) sensors, have become increasingly important in severe weather disaster impact studies given their ability to observe the Earth largely irrespective of weather and sunlight conditions. The reliability of existing SAR change detection products applied on a pair of SAR images is constrained by the limitation of current methods to differentiate and classify disaster specific changes from anthropogenic surface alterations. Moreover, the inherent properties of the sensors, variations in SAR backscatter due to changes in surface conditions, and other factors exacerbate these limitations. We proposed a novel procedure expanding on earlier SAR-based change detection methods to exclude anthropogenic alterations and other sources of ambiguity that might lead to inaccurate mapping of the impacts of severe weather disasters. We applied the proposed procedure that is based on long term interferometric and amplitude-based change detection analyses of Sentinel- 1 SAR imagery to two study sites recently impacted by severe weather disasters (Flooding post severe weather events in urban centers; Hailstorm damage on crops). For the first case study, Sentinel-1 SLC scenes from two flood events in the Houston area (April 2016 flooding event and Hurricane Harvey of August-September 2017) were used to construct a flood map depicting areas repeatedly affected by the flood. Pixels with consistent coherence values in the pre-disaster coherence stack were retained for comparison with the pre- and post-disaster coherence stack and pixels with significant decline (greater than 60%) in coherence values were retained in the final flood map. The findings of the applied technique were calibrated and validated through datasets from NOAA/NWS Service storm reports, aerial imaging (NOAA and Civil Air Patrol), Federal Emergency Management Agency (FEMA) reporting, and targeted collections of NASA’s L-band UAVSAR data. Findings and products derived from the adopted methodology can be useful in disaster response and mitigation activities.

Gebremichael, Esayas↗

Spaceborne Radar Would Measure Rain And Clouds

Report describes conceptual design of spaceborne radar system mapping precipitation and clouds at mid-latitudes to provide data for research on global weather and climate. Radar operates at two frequencies. Lower (35 GHz) provides vertical profiles of rainfall at rates up to 20 mm/h and enables probing of cirrus clouds. Higher (94 GHz) enables detection and quantitative measurements of clouds of all types and provides rain profiles at rates up to 10 mm/h.

Im, Eastwood↗

Ice sheet studies using synthetic aperture radar

The objective was to demonstrate the utility of synthetic aperture radar in ice sheet studies. The major advantage of SAR imagery over visible imagery is the all-weather capability of radar and the ability to specify look angle. Available digital SAR imagery over ice sheets was collected and examined both qualitatively and quantitatively using corroborative data, such as LANDSAT imagery, to confirm feature identification and interpretations. A simple scattering model will be developed to assess the relative importance of surface topography, composition, and subsurface layering to the intensity of radar backscatter. Recommendations of system parameters will be made for optimal SAR operation over ice sheets.

Bindschadler, R.↗

A traffic accident dataset for Chattanooga, Tennessee

This publication presents an annotated accident dataset which fuses traffic data from radar detection sensors, weather condition data, and light condition data with traffic accident data (as illustrated in Fig. 1) in a format that is easy to process using machine learning tools, databases, or data workflows. The purpose of this data is to analyze, predict, and detect traffic patterns when accidents occur. Each file contains a timeseries of traffic speeds, flows, and occupancies at the sensor nearest to the accident, as well as 5 neighboring sensors upstream and downstream. It also contains information about the accident type, date, and time. In addition to the accident data, we provide baseline data for typical traffic patterns during a given time of day. Overall, the dataset contains 6 months of annotated traffic data from November 2020 to April 2021. During this timeframe, and 361 accidents occurred in the monitored area around Chattanooga, Tennessee. This dataset served as the basis for a study on topology-aware automated accident detection for a companion publication [1].

97 MATHEMATICS AND COMPUTING↗

Report on the comparison of the scan strategies employed by the Patrick Air Force Base WSR-74C/McGill radar and the NWS Melbourne WSR-88D radar

The objective of this investigation is to determine whether the current standard WSR-88D radar (NEXRAD) scan strategies permit the use of the Melbourne WSR-88D to perform the essential functions now performed by the Patrick Air Force Base (PAFB) WSR-74C/McGill radar for evaluating shuttle weather flight rules (FR) and launch commit criteria (LCC). To meet this objective, the investigation compared the beam coverage patterns of the WSR-74C/McGill radar located at PAFB and the WSR-88D radar located at the Melbourne National Weather Service (NWS) Office over the area of concern for weather FR and LCC evaluations. The analysis focused on beam coverage within four vertical 74 km radius cylinders (1 to 4 km above ground level (AGL), 4 to 8 km AGL, 8 to 12 km AGL, and 1 to 12 km AGL) centered on Kennedy Space Center (KSC) Launch Complex 39A. The PAFB WSR-74C/McGill radar is approximately 17 km north-northeast of the Melbourne WSR-88D radar. The beam coverage of the WSR-88D using VCP 11 located at the Melbourne NWS Office is comparable (difference in percent of the atmosphere sampled between the two radars is 10 percent or less) within the area of concern to the beam coverage of the WSR-74C/McGill radar located at PAFB. Both radars provide good beam coverage over much of the atmospheric region of concern. In addition, both radars provide poor beam coverage (coverage less than 50 percent) over limited regions near the radars due to the radars' cone of silence and gaps in coverage within the higher elevation scans. Based on scan strategy alone, the WSR-88D radar could be used to perform the essential functions now performed by the PAFB WSR-74C/McGill radar for evaluating shuttle weather FR and LCC. Other radar characteristics may, however, affect the decision as to which radar to use in a given case.

Taylor, Gregory↗

Certification methodology applied to the NASA experimental radar system

The objective of the research is to apply selected FAA certification techniques to the NASA experimental wind shear radar system. Although there is no intent to certify the NASA system, the procedures developed may prove useful to manufacturers that plan to undergo the certification process. The certification methodology for forward-looking wind shear detection radars will require estimation of system performance in several FAA-specified microburst/clutter scenarios as well as the estimation of probabilities of missed and false hazard alerts under general operational conditions. Because of the near-impossibility of obtaining these results experimentally, analytical and simulation approaches must be used. Hazard detection algorithms were developed that derived predictive estimates of aircraft hazard from basic radar measurements of weather reflectivity and radial wind velocity. These algorithms were designed to prevent false alarms due to ground clutter while providing accurate predictions of hazard to the aircraft due to weather. A method of calculation of the probability of missed and false hazard alerts has been developed that takes into account the effect of the various algorithms used in the system and provides estimates of the probability of missed and false alerts per microburst encounter under weather conditions found at Denver, Kansas City, and Orlando. Simulation techniques have been developed that permit the proper merging of radar ground clutter data (obtained from flight tests) with simulated microburst data (obtained from microburst models) to estimate system performance using the microburst/clutter scenarios defined by the FAA.

Britt, Charles L.↗

Observing System Simulation Experiments to Determine the Impact of Spaceborne Differential Absorption Radar Measurements of Marine Surface Pressure on Numerical Weather Prediction

Surface air pressures over marine regions can potentially be measured by estimating the total atmospheric column oxygen content with differential absorption radar (DAR). A demonstration instrument, the Microwave Barometric Radar and Sounder (MBARS) has been funded by NASA for airborne missions in 2024 to show proof of concept. In this presentation, the potential use of such marine surface pressure observations from a spaceborne DAR platform to improve numerical weather prediction is examined using the NASA/GMAO global Observing System Simulation Experiment. Several aspects of the instrument are explored, including contamination by heavy precipitation and the expected error characteristics of the observations. Different orbit and scan configurations are compared, including various constellations of nadir smallsats and A-Train-type scanning configurations. The impacts of marine surface pressure observations are put into context with the current global observing network with a Forecast Sensitivity Observation Impact tool.

Nikki Privé↗

A Comprehensive Forward Model for Spaceborne Radar Instruments

We present the development and validation of a comprehensive forward model designed to enhance remote sensing capabilities of spaceborne radar instruments. To overcome limitations in existing models, we integrated a Discrete Dipole Approximation (DDA) cloud scattering database into our Radiative Transfer Model (RTM), focusing on microwave frequencies. By simulating the optical properties of non-spherical frozen hydrometeors, the DDA technique effectively reduced discrepancies between simulated and observed values, surpassing traditional Mie tables. The evaluation of DDA lookup tables involved comparisons with a collocated dataset comprising short-term forecasts and satellite microwave data, providing evidence of their superiority. Additionally, we address the challenges of assimilating active radar measurements, which offer vertically resolved insights into clouds and precipitation. We explored the assimilation of spaceborne radar measurements in Numerical Weather Prediction (NWP) models by integrating a forward radar model, along with its adjoint and tangent linear, into the data assimilation system. Evaluation using CloudSat measurements demonstrated promising agreement between simulations and observations, particularly when the input hydrometeor profiles aligned with the measured reflectivity profiles, showcasing the potential of the developed forward radar model. Moreover, we discuss other challenges in radar measurement assimilation within NWP models, including potential observation errors and biases.

Isaac Moradi↗

Configuration and Evaluation of a Dual-Doppler 3-D Wind Field System

Current LSP, GSDO, and SLS space vehicle operations are halted when wind speeds from specific directions exceed defined thresholds and when lightning is a threat. Strong winds and lightning are difficult parameters for the 45th Weather Squadron (45 WS) to forecast, yet are important in the protection of customer vehicle operations and the personnel that conduct them. A display of the low-level horizontal wind field to reveal areas of high winds or convergence would be a valuable tool for forecasters in assessing the timing of high winds, or convection initiation and subsequent lightning occurrence. This is especially important for areas where no weather observation platforms exist. Developing a dual-Doppler radar capability would provide such a display to assist forecasters in predicting high winds and convection initiation. The wind fields can also be used to initialize a local mesoscale numerical weather prediction model to help improve the model forecast winds, convection initiation, and other phenomena. The 45 WS and NWS MLB tasked the Applied Meteorology Unit (AMU) to develop a dual- Doppler wind field display using data from the 45th Space Wing radar, known as the Weather Surveillance Radar (WSR), NWS MLB Weather Surveillance Radar 1988 Doppler (KMLB), and the Orlando International Airport Terminal Doppler Weather Radar (KMCO). They also stipulated that the software used should be freely available. The AMU evaluated two software packages and, with concurrence from NWS MLB and the 45 WS, chose the Warning Decision Support System-Integrated Information (WDSS-II). The AMU collected data from two significant weather cases: a tornadic event on 14 April 2013 and a severe wind and hail event on 12 February 2014. For the 14 April case, the data were from WSR and KMLB. For the 12 February case, the data were from KMCO and KMLB. The AMU installed WDSS-II on a Linux PC, then processed and quality controlled the radar data for display and analysis using WDSS-II tools. Because of issues with de-aliasing the WSR velocity field, the AMU did not use data from this radar in this study and only analyzed the 12 February case. Merging the data to create the dual-Doppler analysis involved several steps. The AMU used instructions from the WDSS-II website and discussion forum to determine the correct tools to use for the analysis, and was successful in creating a merged reflectivity field, which was critical to the success of creating a merged velocity field. However, the AMU was unable to create a merged velocity field. The AMU researched the WDSS-II forum for discussions on similar issues, asked questions on the forum, and tested different options and values in the merger tool with no success. Developing a dual-Doppler wind field was the main goal of this task, but that was not accomplished. It could be an issue of not using the correct options or the correct value for the options used, or there could be issues with the radar data. There is a follow-on AMU task to install the operational version of WDSS-II in the NWS MLB office. This will provide more opportunities to try different options and input values in order to create a merged wind field from KMCO and KMLB.

Doppler radar↗

Radar images of the earth from space

The operational principles and imagery available from microwave SAR radars for earth observations from aircraft, the Shuttle, and Seasat are explored. Using microwave frequencies is noted to offer imagery access in day or night, all-weather conditions. SAR radar functions by obtaining a series of reflected signals over a single path, with data processing combining the echoes into an image corresponding to what may be obtained with a large antenna. A stable, reference signal is added to the incoming signals in order to establish the phase and amplitude of echoes. Because the wavelengths of the images can be precisely controlled, Doppler shifts can be detected, thus allowing point by point scattering analysis in two-dimensions. The Shuttle SIR-A and the Seasat radar feature a ground resolution of 25 m. Applications of the satellite systems to terrain, ice mapping, and for a Venus radar mapper mission are described.

Elachi, C.↗

Description and availability of airborne Doppler radar data

An airborne, forward-looking, pulse, Doppler radar has been developed in conjunction with the joint FAA/NASA Wind Shear Program. This radar represents a first in an emerging technology. The radar was developed to assess the applicability of an airborne radar to detect low altitude hazardous wind shears for civil aviation applications. Such a radar must be capable of looking down into the ground clutter environment and extracting wind estimates from relatively low reflectivity weather targets. These weather targets often have reflectivities several orders of magnitude lower than the surrounding ground clutter. The NASA radar design incorporates numerous technological and engineering achievements in order to accomplish this task. The basic R/T unit evolved from a standard Collins 708 weather radar, which supports specific pulse widths of 1-7 microns and Pulse Repetition Frequencies (PRF) of less than 1-10 kHz. It was modified to allow for the output of the first IF signal, which fed a NASA developed receiver/detector subsystem. The NASA receiver incorporated a distributed, high-speed digital attenuator, producing a range bin to range bin automatic gain control system with 65 dB of dynamic range. Using group speed information supplied by the aircraft's navigation system, the radar signal is frequency demodulated back to base band (zero Doppler relative to stationary ground). The In-phase & Quadrature-phase (I/Q) components of the measured voltage signal are then digitized by a 12-bit A-D converter (producing an additional 36 dB of dynamic range). The raw I/Q signal for each range bin is then recorded (along with the current radar & aircraft state parameters) by a high-speed Kodak tape recorder.

Harrah, S. D.↗