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At least 163 records · Page 9

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↗

AVE-SESAME 1: 25-MB sounding data

Seven atmospheric variability experiments (AVE), two atmospheric variability and severe storms experiments (AVSSE), and six atmospheric variability experiment-severe environmental storm and mesoscale experiments (AVE-SESAME) conducted by NASA are discussed. The dates, observation times, and data reports for each of the experiments for which data was processed are listed. The AVE experiments were conducted primarily to study atmospheric variability with emphasis on spatial and temporal in atmospheric structure that can be detected from soundings taken at 3 hr intervals but not seen in soundings taken at 12 hr intervals. The AVSSE experiments were conducted to study atmospheric structure and variability associated with severe storms combining both rawinsonde and aircraft data to provide information on near storm environments. The method of processing is discussed, estimates of the rms errors in the data are presented, an example of contact data is given, and soundings are listed which exhibited abnormal characteristics.

Gerhard, M. L.↗

Survey: National Meteorological Center

The National Meteorological Center (NMC) is comprised of three operational divisions (Development, Automation, and Forecast) and an Administrative Division. The Development Division develops and implements mathematical models for forecasting the weather. The Automation Division provides the software and processing services to accommodate the models used in daily forecasts. The Forecasting Division applies a combination of numerical and manual techniques to produce analyses and prognoses up to 120 hr into the future. This guidance material is combined with severe storm information from the National Hurricane Center and the National Severe Storms Forecasting Center to develop locally tailored forecasts by the Weather Service Forecast Offices and, in turn, by the local Weather Service Offices. A very general flow of this information is shown. A more detailed illustration of data flow into, within, and from the NMC is given. The interrelations are depicted between the various meteorological organizations and activities.

Source record↗

Lightning location relative to storm structure in a supercell storm and a multicell storm

Relationships between lightning location and storm structure are examined for one radar volume scan in each of two mature, severe storms. One of these storms had characteristics of a supercell storm, and the other was a multicell storm. Data were analyzed from dual-Doppler radar and dual-VHF lightning-mapping systems. The distributions of VHF impulse sources were compared with radar reflectivity, vertical air velocity, and their respective gradients. In the supercell storm, lightning tended to occur along streamlines above and down-shear of the updraft and reflectivity cores; VHF impulse sources were most concentrated in reflectivities between 30 and 40 dBZ and were distributed uniformly with respect to updraft speed. In the multicell storm, on the other hand, lightning tended to coincide with the vertical reflectivity and updraft core and with the diverging streamlines near the top of the storm. The results suggest that the location of lightning in these severe storms were most directly associated with the wind field structure relative to updraft and reflectivity cores. Since the magnitude and vertical shear of the environmental wind are fundamental in determining the reflectivity and wind field structure of a storm, it is suggested that these environmental parameters are also fundamental in determining lightning location.

Ray, Peter S.↗

The CORDEX-CORE EXP-I Initiative: Description and Highlight Results from the Initial Analysis

Here we describe the first effort within the Coordinated Regional Climate Downscaling Experiment–Coordinated Output for Regional Evaluation, or CORDEX-CORE EXP-I. It consists of a set of twenty-first-century projections with two regional climate models (RCMs) downscaling three global climate model (GCM) simulations from the CMIP5 program, for two greenhouse gas concentration pathways (RCP8.5 and RCP2.6), over nine CORDEX domains at ~25-km grid spacing. Illustrative examples from the initial analysis of this ensemble are presented, covering a wide range of topics, such as added value of RCM nesting, extreme indices, tropical and extratropical storms, monsoons, ENSO, severe storm environments, emergence of change signals, and energy production. They show that the CORDEX-CORE EXP-I ensemble can provide downscaled information of unprecedented comprehensiveness to increase understanding of processes relevant for regional climate change and impacts, and to assess the added value of RCMs. The CORDEX-CORE EXP-I dataset, which will be incrementally augmented with new simulations, is intended to be a public resource available to the scientific and end-user communities for application to process studies, impacts on different socioeconomic sectors, and climate service activities. The future of the CORDEX-CORE initiative is also discussed.

54 ENVIRONMENTAL SCIENCES↗

Statistically conditioned least squares retrievals planned for the VAS demonstration experiment

Problems in the retrieval of atmospheric profiles from passively observed satellite radiances are reviewed. Plans are described for statistically conditioned least squares retrievals of temperature and moisture profiles around mesoscale events, based upon the expected sensitivity of the VAS channels to the atmospheric variations. Simulated soundings for a global data set and for the 1976 National Storm Laboratory (NSSL) severe storm data set are also examined. This combination of radiance modeling and statistical conditioning should yield reliable mesoscale soundings and provide a test bed for sounding research and development with the VAS instrument.

Chester, D.↗

The NASA Short-term Prediction and Research Transition (SPoRT) Center: A Research to Operations Test Bed

Over the last three years, NASA/MSFC scientists have embarked on an effort to transition unique NASA EOS data/products and research technology to selected NWSEOs in the southeast U.S. This activity, called the Short-term Prediction and - Research Transition (SPoRT) program, supports the NASA Science Mission Directorate and its Earth-Sun System Mission to develop a scientific understanding of the Earth System and its response to natural or human-induced changes that will enable improved prediction capability for climate, weather, and natural hazards. The overarching question related to weather prediction is "How well can weather forecasting duration and reliability be improved by new space-based observations, data assimilation, and modeling?" The transition activity has included the real-time delivery of MODIS data and products to several NWS Forecast Offices. Local NWS FOs have used the MODIS data to complement the coarse resolution GOES data for a number of applications. Specialized products have also been developed and made available to local and remote offices for their weather applications. Data from &e Lightning Mapping Array (LMA) network has been used in severe storm forecasts at several offices in the region. At the regional scale and forecast horizons from 0-1 day, the next generation of high-resolution mesoscale forecast and data assimilation models have been used to provide local offices with unique weather forecasts not otherwise available. The continued use of near red-time infusion of NASA science products into high-resolution mesoscale forecast and decision-making models can be expected to improve the model initialization as well as short-term forecasts. A current focus of SPoRT is to expand collaborations to include contributions from the assimilation of AMSR-E data in the ADASIARPS forecast system (OU), inclusion of MODIS SSTs and AIRS thermodynamic profiles in the WRF, and to extend the distribution of real-time MODIS and AMSR-E data and products to the Florida coastal WFOs. A SPoRT Test bed, together with input from other interagency and university partners, will provide a means and a process to effectively transition ESE observations and technology to NWS operations and decision makers at both the globdnational and regional scales. The transition of emerging experimental products into operations through the SPoRT infrastructure will allow NASA to foster and accelerate the progress of this Science Mission Directorate research strategy over the coming years.

Jedlovec, Gary J.↗

The Future of Supercells in the United States

A supercell is a distinct type of intense, long-lived thunderstorm that is defined by its quasi-steady, rotating updraft. Supercells are responsible for most damaging hail and deadly tornadoes, causing billions of dollars in losses and hundreds of casualties annually. This research uses high-resolution, convection-permitting climate simulations across 15-yr epochs that span the twenty-first century to assess how supercells may change across the United States. Specifically, the study explores how late-twentieth-century supercell populations compare with their late-twenty-first-century counterparts for two—intermediate and pessimistic—anthropogenic climate change trajectories. An algorithm identifies, segments, and tracks supercells in the simulation output using updraft helicity, which measures the magnitude of corkscrew flow through a storm’s updraft and is a common proxy for supercells. Results reveal that supercells will be more frequent and intense in future climates, with robust spatiotemporal shifts in their populations. Supercells are projected to become more numerous in regions of the eastern United States, while decreasing in frequency in portions of the Great Plains. Supercell risk is expected to escalate outside of the traditional severe storm season, with supercells and their perils likely to increase in late winter and early spring months under both emissions scenarios. Conversely, the latter part of the severe storm season may be curtailed, with supercells expected to decrease midsummer through early fall. These results suggest the potential for more significant tornadoes, hail, and extreme rainfall that, when combined with an increasingly vulnerable society, may produce disastrous consequences.

54 ENVIRONMENTAL SCIENCES↗

Wind field measurement in the nonprecipitous regions surrounding storms by an airborne pulsed Doppler lidar system, appendix A

Coherent Doppler lidar appears to hold great promise in contributing to the basic store of knowledge concerning flow field characteristics in the nonprecipitous regions surrounding severe storms. The Doppler lidar, through its ability to measure clear air returns, augments the conventional Doppler radar system, which is most useful in the precipitous regions of the storm. A brief description of the Doppler lidar severe storm measurement system is provided along with the technique to be used in performing the flow field measurements. The application of the lidar is addressed, and the planned measurement program is outlined.

Bilbro, J. W.↗

Operational evaluation of thunderstorm penetration test flights during project Storm Hazards '80

The National Aeronautics and Space Administration is conducting a research project called Storm Hazards '80 in order to study the prediction, detectability and avoidance of the hazards of severe storms for aircraft operations. The project, using a highly instrumented NASA F-106B airplane to penetrate thunderstorms, gathered and correlated data from both airborne and ground based instrumentation. The objectives of this project are to determine the effects of lightning on the design and operation of aircraft composite structures and digital electronic systems. The data will be used to determine the correlation of lightning hazards with other severe storm hazards, such as heavy precipitation, hail, turbulence and wind-shear, in order to develop an initial data base for use in design and avoidance. The NASA F-106B was equipped with a weather radar, stormscope, lightning measurement instrumentation and air sampling equipment. This paper will focus on the operational aspects of thunderstorm penetrations and the pilot techniques used to avoid the extremely hazardous portions of the storm such as the tornadoes and hail. It will deal with the effects of the storm elements on the aircraft hardware, avionics and the crew.

Keyser, G. L., Jr.↗

AMU NEXRAD Exploitation Task

This report documents the results of the Applied Meteorology Unit's NEXRAD Exploitation Task. The objectives of this task are to determine what radar signatures are present prior to and at the time of convection initiation, and to determine radar signatures which will help distinguish whether the ensuing convection will become severe. Radar data from the WSR-88D radar located at NWS Melbourne (WSR-88D/KMLB) were collected between June and September 1995, and 16 convective case studies were analyzed for which the radar was operating during the entire period of interest. All WSR-88D/KMLB products were scrutinized for their utility in detecting convection initiation and severe storm signatures. Through process of elimination, it was found that the 0.5 deg reflectivity product with the lowest reflectivity values displayed is the best product to monitor for convection initiation signatures. Seven meteorological features associated with the initiation of deep convection were identified: the Merritt Island and Indian River convergence zones, interlake convergence, horizontal convective rolls, the sea breeze, storm outflow boundaries, and fires. Their reflectivity values ranged from -5 to 20 dBZ. Of the three severe weather phenomena (winds greater than or equal to 50 kts, tornado, 3/4 inch hail), high wind events due to microbursts were most common in the data set. It was found that the values and trends of composite reflectivity, vertically integrated liquid, and core aspect ratio were key indicators of the potential of a cell to produce a microburst. The data were not analyzed for the other two severe weather phenomena because they rarely occurred during the data collection period. This report also includes suggestions for new WSR-88D products, summaries of ongoing research aimed at creating new products, and explicit recommended procedures for detecting convection initiation and severe storm signatures in the radar data using the currently available technology.

Lambert, Winifred C.↗

Centralized Storm Information System (CSIS)

A final progress report is presented on the Centralized Storm Information System (CSIS). The primary purpose of the CSIS is to demonstrate and evaluate real time interactive computerized data collection, interpretation and display techniques as applied to severe weather forecasting. CSIS objectives pertaining to improved severe storm forecasting and warning systems are outlined. The positive impact that CSIS has had on the National Severe Storms Forecast Center (NSSFC) is discussed. The benefits of interactive processing systems on the forecasting ability of the NSSFC are described.

Norton, C. C.↗

A stability analysis of AVE-4 severe weather soundings

The stability and vertical structure of an average severe storm sounding, consisting of both thermodynamic and wind vertical profiles, were investigated to determine if they could be distinguished from an average lag sounding taken 3 to 6 hours prior to severe weather occurrence. The term average is defined here to indicate the arithmetic mean of a parameter, as a function of altitude, determined from a large number of available observations taken either close to severe weather occurrence, or else more than 3 hours before it occurs. The investigative computations were also done to help determine if a severe storm forecast or index could possibly be used or developed. These mean vertical profiles of thermodynamic and wind parameters as a function of severity of the weather, determined from manually digitized radar (MDR) categories are presented. Profile differences and stability index differences are presented along with the development of the Johnson Lag Index (JLI) which is determined entirely upon environmental vertical parameter differences between conditions 3 hours prior to severe weather, and severe weather itself.

Johnson, D. L.↗

Ionospheric remote sensing of medium-scale gravity waves and tornadic storms

Gravity waves associated with severe storms are investigated on the basis of ionospheric sounding using a ground-based Doppler system. Reverse-group ray tracing computations are used to determine the origin of over 20 gravity waves detected within 800 km of Huntsville, Alabama in association with a group of tornadoes, isolated tornadoes in the presence of a squall line, and isolated tornadoes in the absence of a squall line. Gravity waves associated with tornadoes are found either to be generated by thunderstorms with enhanced convection embedded in a squall line, or in an isolated cloud with enhanced convection. The computed wave sources are observed in all cases to be located near the points where the tornadoes touched down more than an hour after wave excitation. Results show that gravity waves play an important role in troposphere-ionosphere coupling during times of intense convection associated with tornadic storm activity.

Hung, R. J.↗

Delineating mid- and low-level water vapor patterns in pre-convective environments using VAS moisture channels

Infrared and visible imagery from VAS are used to delineate mid- and lower-tropospheric moisture fields for a variety of severe storm cases in the southern and central United States. The ability of sequences of images to isolate areas of large negative vertical moisture gradients and apparent convective instability prior to the onset of convective storms is assessed. A variety of image combination procedures are used to deduce the stability fields which are then compared with the available radiosonde data. The results for several severe storm cases indicate that VAS can detect mid- and low-level mesoscale water vapor fields as distinct radiometric signals. The VAS imagery shows a strong tendency for thunderstorms to develop along the edges of bands of midlevel dryness as they overtake either preexisting or developing low-level moisture maxima. Image sequences depict the speed with which deep moist and dry layers can develop and move.

Petersen, R. A.↗

A multiscale numerical study into the cascade of kinetic energy leading to severe local storms

The cascade of kinetic energy from macro- through mesoscales is studied on the basis of a nested grid system used to solve a set of nonlinear differential equations. The kinetic energy cascade and the concentration of vorticity through the hydrodynamic spectrum provide a means for predicting the location and intensity of severe weather from large-scale data sets. A mechanism described by the surface pressure tendency equation proves to be important in explaining how initial middle-tropospheric mass-momentum imbalances alter the low-level pressure field.

Paine, D. A.↗

Some potential research applications of GOES/VAS data in meteorology

The understanding and utilization of radiance data from the VAS instrument for meteorological purposes which requires an extensive and organized research plan whose ultimate goal is to provide quantitative measurements of the structure/dynamics of the atmosphere is outlined. The unique multispectral VAS data are potentially useful in almost all aspects of meteorology but have immediate applications in the mesoscale and severe storm research area since measurements are available over regional areas at time intervals of less than 1 hour. The higher priority research applications of VAS data pertaining to the interpretation and utilization of the passive VAS radiance measurements for mesoscale and severe-storm research are reviewed.

Wilson, G. S.↗