Radar detection of the tropopause and clear air turbulence.
Radar detection of tropopause and clear air turbulence
TROPOPAUSE↗
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Developing a Hail and Wind Damage Swath Event Database from Daily MODIS True Color Imagery and Storm Reports for Impact Analysis and Applications
Hail and damaging winds are two threats associated with intense and severe thunderstorms that traverse the Midwest and Great Plains during the primary growing season. In certain severe thunderstorm events, large swaths of agricultural crops are impacted, allowing the damage to be viewed from multiple satellite remote sensing platforms. Previous studies have focused on analyzing individual hail and wind damage swaths (HWDSs) using satellite remote sensing, but these swaths have never been officially archived or documented. This lack of documentation has made it difficult to analyze the spatial extent and temporal frequency of HWDSs from year to year. This study utilizes daily true color imagery from MODIS aboard NASA’s Terra and Aqua satellites and daily local storm reports from the Storm Prediction Center to build a database of HWDSs occurring in the months of May through August, for years 2000 through 2020. This database identified 1,646 HWDSs in 12 states throughout the Midwest and Great Plains, confirmed through a combination of archived severe weather warnings, radar information, and official storm reports. For each entry in the HWDS database, a geospatial outline is provided along with the most likely date of first visible damage from MODIS imagery as well as the physical characteristics and time of occurrence estimated from available warnings. This study also provides a summary of the radar characteristics for a portion of the database. This database will further the understanding of severe weather damage by hail and wind to agriculture to help understand the frequency of these events and assist in mapping the impacted areas.
Climatology↗
Radar scatterometry - An active remote sensing tool.
Radar scatterometer remote sensing measurement of variation of radar scattering coefficient with angle, wavelength and polarization
WEATHER RADAR↗
Changes in the TRMM Version-5 and Version-6 Precipitation Radar Products Due to Orbit Boost
The performance of the version-5 and version-6 Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) products before and after the satellite orbit boost is assessed through a series of comparisons with Weather Surveillance Radar (WSR)-88D ground-based radar in Melbourne, Florida. Analysis of the comparisons of radar reflectivity near the storm top from the ground radar and both versions of the PR indicates that the PR bias relative to the WSR radar at Melbourne is on the order of 1dB for both pre- and post-boost periods, indicating that the PR products maintain accurate calibration after the orbit boost. Comparisons with the WSR-88D near-surface reflectivity factors indicate that both versions of the PR products accurately correct for attenuation in stratiform rain. However, in convective rain, both versions exhibit negative biases in the near-surface radar reflectivity with version-6 products having larger negative biases than version-5. Rain rate comparisons between the ground and space radars show similar characteristics
Liao, Liang↗
Flight test evaluation of a video tracker for enhanced offshore airborne radar approach capability
As a part of NASA's Rotorcraft All-Weather Operations Research Program, advanced airborne radar approach (ARA) concepts are being investigated. Since data from previous NASA/FAA flight tests showed significant ARA limitations, a research program was initiated at NASA Ames Research Center to determine the benefit that could be derived by automating certain radar functions and superimposing course display data on the radar display. To evaluate these concepts, a newly developed video tracking system which interfaces with weather radar was acquired. After the pilot designates a destination target, the system tracks the target video as it moves on the radar indicator. Using a small, efficient microprocessor, the autotracker presents valuable approach data on the radar screen and automatically adjusts the radar gain and tilt. Results of a limited flight test evaluation of the autotracker show that the course display concept, combined with automated gain and tilt functions, is effective for improving ARA's and reducing radar operator workload.
Clary, G. R.↗
Hybrid Estimates of Path Attenuation for the DPR
The purpose of this study is to investigate ways to combine estimates from the Surface Reference and Hitschfeld-Bordan methods into a hybrid path attenuation estimate and to study its performance using dual-frequency radar data provided by the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Mission (GPM) satellite.
DPR↗
Observed Response of the Raindrop Size Distribution to Changes in the Melting Layer
Vertical variability in the raindrop size distribution (RSD) can disrupt the basic assumption of a constant rain profile that is customarily parameterized in radar-based quantitative precipitation estimation (QPE) techniques. This study investigates the utility of melting layer (ML) characteristics to help prescribe the RSD, in particular the mass-weighted mean diameter (Dm), of stratiform rainfall. We utilize ground-based polarimetric radar to map the ML and compare it with Dm observations from the ground upwards to the bottom of the ML. The results show definitive proof that a thickening, and to a lesser extent a lowering, of the ML causes an increase in raindrop diameter below the ML that extends to the surface. The connection between rainfall at the ground and the overlying microphysics in the column provide a means for improving radar QPE at far distances from a ground-based radar or close to the ground where satellite-based radar rainfall retrievals can be ill-defined.
Weather↗
Comparison of simulated and actual wind shear radar data products
Prior to the development of the NASA experimental wind shear radar system, extensive computer simulations were conducted to determine the performance of the radar in combined weather and ground clutter environments. The simulation of the radar used analytical microburst models to determine weather returns and synthetic aperture radar (SAR) maps to determine ground clutter returns. These simulations were used to guide the development of hazard detection algorithms and to predict their performance. The structure of the radar simulation is reviewed. Actual flight data results from the Orlando and Denver tests are compared with simulated results. Areas of agreement and disagreement of actual and simulated results are shown.
Britt, Charles L.↗
Potential Use of Spaceborne Differential Absorption Radar Measurements of Marine Surface Pressure to Improve Weather and Tropical Cyclone Forecasting
Differential absorption radar (DAR) has been identified as a method to remotely sense surface air pressure, particularly over the marine surface. Such an instrument would provide an estimate of the total atmospheric column oxygen content from which the surface air pressure can be calculated. NASA recently funded the development of a demonstrator instrument, the airborne Microwave Barometric Radar and Sounder (MBARS) to test and evaluate this retrieval. The potential impact of surface pressure observations from a spaceborne sensor is evaluated using the updated NASA/GMAO global Observing System Simulation Experiment framework. Initial experiments showing the impact of different orbital configurations of DAR surface pressure measurements on overall NWP will be shown, including Forecast Sensitivity Observation Impact metrics. Case studies of satellite-based surface air pressure retrievals on tropical cyclones will also be discussed.
DAR↗
Ground Validation Activities for the INCUS Satellite Mission
Over the next decade, there will be several satellite-based radar missions designed to estimate vertical motions and mass flux within deep convection. One of these is the upcoming Investigation of Cumulus Updrafts (INCUS) mission. INCUS will do this using a low-Earth orbit train of three small satellites carrying Ka-band radars to observe the 3-D evolution of radar reflectivity within deep convective cells at time intervals of 30-, 90-, and 120-sec. One approach to validating this novel time-difference (delta-t) approach would include a pair of Doppler radars flown on two different high-altitude aircraft (i.e., satellite simulator), but that solution is not practical within the scope of a cost-capped Earth Venture mission like INCUS. Instead, the ground-based validation (GV) approach for INCUS will consist of using vertical profiling radars, including analysis of existing convective cases, and multiple polarimetric, Doppler radars performing coordinated rapid sampling of the same convective cell. These new observations will be collected in the coming years through local deployments of existing research radar facilities at 1 - 3 sites over multiple seasons to capture a statistically significant sample of storm types (both pre- and post-launch) or as a single post-launch field campaign in a region where convection is very predictable. This presentation will include an overview of INCUS GV, both pre- and post-launch activities, as well as some of our collaborations with the radar community to address some of the challenges in sampling the vertical evolution of convective cells on 120-sec or less time scales.
remote sensing↗
Post-Severe Thunderstorm Damage Assessment from March 2-3, 2020, Nashville, TN, Using Synthetic Aperture Radar Observations
Severe weather events (e.g., hurricanes, tornadoes) are responsible for most weather-related infrastructure and building damages. The destruction caused by these events can cross several states, making damage estimates difficult, especially in heavily vegetated or rural areas. Drone or optical imagery is often relied upon in these cases but is limited by solar and atmospheric conditions. Synthetic Aperture Radar (SAR) is an active sensor allowing for day and night collections in all weather conditions. This research highlights the benefits and limitations of using SAR to detect tornado tracks and associated damages while also assessing the strengths and weaknesses of two SAR sensors with varying wavelengths and spatial resolutions from the March 2020 Tornado Outbreak. The outbreak occurred overnight on March 2-3, when several supercell thunderstorms tracked across multiple states producing numerous tornadoes (EF-0 through EF-4) and large hail. Most of the damage occurred in central Tennessee, resulting in 25 fatalities, hundreds of injuries, and over a billion dollars worth of damage. Publicly available C-band (~6 cm) imagery from the European Space Agency’s Sentinel-1 satellite and commercial X-band (~3 cm) imagery from Airbus’s TerraSAR-X satellite were used to generate amplitude and coherence products. The closest post-event collections were used for the amplitude products, and the closest pre- and post-collections were used to create the coherence pairs. If damage tracks were identified in any of the SAR products, the length (miles) and max width (yards) were recorded and compared to the National Weather Service Storm Data official records. SAR successfully detected five rated EF-1 or higher out of ten recorded tornadoes. However, none of the four EF-0 tornadoes were identified. X- and C-band SAR sensors are heavily impacted by dense vegetation, underestimating the extent of damage. Despite these limitations, SAR products can be beneficial when looking at severe weather impacts, especially during the winter and early spring when the coherence products are less influenced by vegetation. The upcoming L-band (~24 cm) NISAR mission will provide more accurate estimates of damage, with the longer wavelength, expanding the applications of SAR to assist in damage assessment caused by severe thunderstorms.
Hannah G Pankratz↗
The MST radar technique: Requirements for operational weather forecasting
There is a feeling that the accuracy of mesoscale forecasts for spatial scales of less than 1000 km and time scales of less than 12 hours can be improved significantly if resources are applied to the problem in an intensive effort over the next decade. Since the most dangerous and damaging types of weather occur at these scales, there are major advantages to be gained if such a program is successful. The interest in improving short term forecasting is evident. The technology at the present time is sufficiently developed, both in terms of new observing systems and the computing power to handle the observations, to warrant an intensive effort to improve stormscale forecasting. An assessment of the extent to which the so-called MST radar technique fulfills the requirements for an operational mesoscale observing network is reviewed and the extent to which improvements in various types of forecasting could be expected if such a network is put into operation are delineated.
Larsen, M. F.↗
Graupel and Hail Identification Algorithm for the Dual-frequency Precipitation Radar (DPR) on the GPM Core Satellite
Precipitation consists of many types of hydrometeors, such as raindrops, ice crystals, graupel, and hail. Due to their impacts, graupel and hail (GH) have received particular attention in the literature. Global Precipitation Measurement (GPM) dual-frequency radar (DPR) has proved to be a very reliable system for global precipitation retrievals. This paper aims to develop a GH identification algorithm for GPM DPR. This algorithm is constructed using a precipitation type index (PTI) defined for DPR. The PTI is effective in separating hydrometeor types and is calculated using measurements of reflectivity, dual-frequency ratio, and storm top height data. The output of the algorithm is a Boolean product representing the existence of graupel or hail along with the vertical profile for each Ku- and Ka-band matched footprint. Cross validation is performed with the Weather Service Radar (WSR-88D) network over continental United States as well as during the Remote sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) experiment. Evaluation of the GH identification algorithm is performed on a global basis, which illustrates promising comparisons with the global lightning and hail precipitation maps generated using radar and radiometer.
54 ENVIRONMENTAL SCIENCES↗
Laser Disdrometer Quantities (LDQUANTS) and Video Disdrometer Quantities (VDISQUANTS) Value-Added Products Report
Disdrometers are useful instruments that measure the distribution of raindrop sizes (drop size distribution: DSD) and the associated rainfall rates/accumulation as those raindrops fall to the ground. These DSDs are a quantity of interest to members of the modeler and observational communities. However, use of disdrometer data for model evaluation, radar monitoring, or other activities requires careful quality control and processing for key DSD properties of interest (e.g., the number concentration of drops) to ensure appropriate physical (scattering, fall speed) assumptions. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Laser Disdrometer Quantities and Video Disdrometer Quantities Value-Added Product (LDQUANTS/VDISQUANTS VAP) uses standard methods from Tokay et al. (e.g., 2013, 2014) to filter drops with unrealistic fall speeds. Further, it estimates several microphysical/geophysical quantities of parameterized DSDs (gamma or exponential assumption type fitting methods) as in previous disdrometer studies and ARM long-term efforts (e.g., Testud et al. 2001, Giangrande et al. 2014, Thompson et al. 2015). Disdrometers are also beneficial for cross-checks with other instrumentation, including rain gauges and radars. To support research interests and related radar monitoring activities, this product calculates radar equivalent quantities, including dual polarization radar quantities (e.g., Z, Differential Reflectivity ZDR, etc.), using T-Matrix scattering and additional wavelength, temperature, and drop shape assumptions (e.g., Thurai et al. 2007). All of these efforts allow disdrometer data sets to become more useful and easily handled by modeling and observational studies, or routine instrumentation checks.
47 OTHER INSTRUMENTATION↗
Leveraging the Multiplatform Precipitation Feature Database of Combined Ground Radar and Satellite Lightning Observations for Convective Studies
The Multiplatform Precipitation Feature (MPF) database combines coincident observations of lightning from space with satellite- and ground-based radar data in a storm-based, feature-defined framework. The concept for the MPF database stems from the motivation to extend the scale and scope of investigations into the complex connections between ice precipitation, updrafts, and lightning in thunderstorms. The earliest iteration of the MPF database incorporates NASA International Space Station Lightning Imaging Sensor (ISS LIS) observations alongside the NASA Global Precipitation Measurement (GPM) Mission Dual-frequency Precipitation Radar (DPR) and Validation Network (VN). Because of the specific role of the GPM VN in forming the first MPFs, this subset is referred to as the VNMPF database. The synthesis of these multi-scale and multi-resolution observations leveraged each platform’s unique insights into convective properties and processes, offering a more complete view of deep convection over the large viewing area afforded by satellite coverage. The VNMPF database established the feasibility and infrastructure to combine microphysical, kinematic, and lightning observations from multiple satellite- and ground-based platforms. Following this successful proof-of-concept, recent progress has expanded the MPF database to make use of coincident ISS LIS lightning observations and data from the operational Weather Surveillance Radar - 1988 Doppler (WSR-88D) network, where individual WSR-88D proximity facilitates vertical wind retrievals via dual-Doppler analysis. These database changes have expanded the scope of the dataset by removing the requirement for coincident GPM and ISS LIS overpasses. This increases the sample size dramatically and facilitates analysis of higher-resolution radar-derived properties. These advancements allow both storm-scale and unprecedented broad statistical analyses of deep convection from electrical, kinematic, and microphysical perspectives over the contiguous United States. This presentation outlines the construction of the new MPF database and introduces some preliminary analyses of the convection captured within it. Early results summarize relationships based on updraft characteristics ascertained from WSR-88D dual-Doppler three-dimensional wind retrievals, properties of ice microphysics gleaned from dual-polarization analyses, and electrical characteristics observed by the ISS LIS. The expanded scale and scope offered by more than five years of ISS LIS observations enable new insights into regional and seasonal variations in the microphysical, kinematic, and electrical relationships of convection. Analysis of the database highlights the potential for advancements in lightning meteorology made possible by combining large-scale spaceborne lightning detection and proven storm interrogation tools such as operational polarimetric Doppler radar.
Lightning↗
The evolution of convective storms from their footprints on the sea as viewed by synthetic aperture radar from space
SEASAT synthetic aperture radar (SAR) echoes from the sea have previously been shown to be the result of rain and winds produced by convective stroms; rain damps the surface waves and causes ech-free holes, while the diverging winds associated with downdraft generate waves and associated echoes surrounding the holes. Gust fronts are also evident. Such a snapshot from 8 July 1978 has been examined in conjunction with ground-based radar. This leads to the conclusion that the SAR storm footprints resulted from storm processes that occurred up to an hour or more prior to the snapshot. A sequence of events is discerned from the SAR imagery in which new cell growth is triggered in between the converging outflows of two preexisting cells. In turn, the new cell generates a mini-squall line along its expanding gust front. While such phenomena are well known over land, the spaceborne SAR now allows important inferences to be made about the nature and frequency of convective storms over the oceans. The storm effects on the sea have significant implications for spaceborne wind scatterometry and rainfall measurements. Some of the findings herein remain speculative because of the great distance to the Miami weather radar-the only source of corroborative data.
Atlas, David↗
Maintaining a Local Data Integration System in Support of Weather Forecast Operations
Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) have used a local data integration system (LDIS) as part of their forecast and warning operations. Each has benefited from 3-dimensional analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive and complete understanding of evolving fine-scale weather features. Recent efforts have been undertaken to update the LDIS through the formal tasking process of NASA's Applied Meteorology Unit. The goals include upgrading LDIS with the latest version of ADAS, incorporating new sources of observational data, and making adjustments to shell scripts written to govern the system. A series of scripts run a complete modeling system consisting of the preprocessing step, the main model integration, and the post-processing step. The preprocessing step prepares the terrain, surface characteristics data sets, and the objective analysis for model initialization. Data ingested through ADAS include (but are not limited to) Level II Weather Surveillance Radar- 1988 Doppler (WSR-88D) data from six Florida radars, Geostationary Operational Environmental Satellites (GOES) visible and infrared satellite imagery, surface and upper air observations throughout Florida from NOAA's Earth System Research Laboratory/Global Systems Division/Meteorological Assimilation Data Ingest System (MADIS), as well as the Kennedy Space Center ICape Canaveral Air Force Station wind tower network. The scripts provide NWS MLB and SMG with several options for setting a desirable runtime configuration of the LDIS to account for adjustments in grid spacing, domain location, choice of observational data sources, and selection of background model fields, among others. The utility of an improved LDIS will be demonstrated through postanalysis warm and cool season case studies that compare high-resolution model output with and without the ADAS analyses. Operationally, these upgrades will result in more accurate depictions of the current local environment to help with short-range weather forecasting applications, while also offering an improved initialization for local versions of the Weather Research and Forecasting model.
Watson, Leela R.↗
The effects of clutter-rejection filtering on estimating weather spectrum parameters
The effects of clutter-rejection filtering on estimating the weather parameters from pulse Doppler radar measurement data are investigated. The pulse pair method of estimating the spectrum mean and spectrum width of the weather is emphasized. The loss of sensitivity, a measure of the signal power lost due to filtering, is also considered. A flexible software tool developed to investigate these effects is described. It allows for simulated weather radar data, in which the user specifies an underlying truncated Gaussian spectrum, as well as for externally generated data which may be real or simulated. The filter may be implemented in either the time or the frequency domain. The software tool is validated by comparing unfiltered spectrum mean and width estimates to their true values, and by reproducing previously published results. The effects on the weather parameter estimates using simulated weather-only data are evaluated for five filters: an ideal filter, two infinite impulse response filters, and two finite impulse response filters. Results considering external data, consisting of weather and clutter data, are evaluated on a range cell by range cell basis. Finally, it is shown theoretically and by computer simulation that a linear phase response is not required for a clutter rejection filter preceeding pulse-pair parameter estimation.
Davis, W. T.↗