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Petersen, Walter A.

Publications and source records attributed to Petersen, Walter A..

At least 73 records · Page 4
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NASA NTRS2011

The NASA CloudSat/GPM Light Precipitation Validation Experiment (LPVEx)

Ground-based measurements of cool-season precipitation at mid and high latitudes (e.g., above 45 deg N/S) suggest that a significant fraction of the total precipitation volume falls in the form of light rain, i.e., at rates less than or equal to a few mm/h. These cool-season light rainfall events often originate in situations of a low-altitude (e.g., lower than 2 km) melting level and pose a significant challenge to the fidelity of all satellite-based precipitation measurements, especially those relying on the use of multifrequency passive microwave (PMW) radiometers. As a result, significant disagreements exist between satellite estimates of rainfall accumulation poleward of 45 deg. Ongoing efforts to develop, improve, and ultimately evaluate physically-based algorithms designed to detect and accurately quantify high latitude rainfall, however, suffer from a general lack of detailed, observationally-based ground validation datasets. These datasets serve as a physically consistent framework from which to test and refine algorithm assumptions, and as a means to build the library of algorithm retrieval databases in higher latitude cold-season light precipitation regimes. These databases are especially relevant to NASA's CloudSat and Global Precipitation Measurement (GPM) ground validation programs that are collecting high-latitude precipitation measurements in meteorological systems associated with frequent coolseason light precipitation events. In an effort to improve the inventory of cool-season high-latitude light precipitation databases and advance the physical process assumptions made in satellite-based precipitation retrieval algorithm development, the CloudSat and GPM mission ground validation programs collaborated with the Finnish Meteorological Institute (FMI), the University of Helsinki (UH), and Environment Canada (EC) to conduct the Light Precipitation Validation Experiment (LPVEx). The LPVEx field campaign was designed to make detailed measurements of cool-season light precipitation by leveraging existing infrastructure in the Helsinki Precipitation Testbed. LPVEx was conducted during the months of September--October, 2010 and featured coordinated ground and airborne remote sensing components designed to observe and quantify the precipitation physics associated with light rain in low-altitude melting layer environments over the Gulf of Finland and neighboring land mass surrounding Helsinki, Finland.

Petersen, Walter A.↗
NASA NTRS2010

Distributed Disdrometer and Rain Gauge Measurement Infrastructure Developed for GPM Ground Validation

Global Precipitation Mission (GPM)retrieval algorithm validation requires datasets characterizing the 4-D structure, variability, and correlation properties of hydrometeor particle size distributions (PSD) and accumulations over satellite fields of view (FOV;<10 km). Collection of this data provides a means to assess retrieval errors related to beam filling and algorithm PSD assumptions. Hence, GPM Ground Validation is developing a deployable network of precipitation gauges and disdrometers to provide fine-scale measurements of PSD and precipitation accumulation variability. These observations will be combined with dual-frequency, polarimetric, and profiling radar data in a bootstrapping fashion to extend validated PSD measurements to a large coverage domain. Accordingly, a total of 24 Parsivel disdrometers(PD), 5 3rd-generation 2D Video Disdrometers (2DVD), 70 tipping bucket rain gauges (TBRG),9 weighing gauges, 7 Hot-Plate precipitation sensors (HP), and 3 Micro Rain Radars (MRR) have been procured. In liquid precipitation the suite of TBRG, PD and 2DVD instruments will quantify a broad spectrum of rain rate and PSD variability at sub-kilometer scales. In the envisioned network configuration 5 2DVDs will act as reference points for 16 collocated PD and TBRG measurements. We find that PD measurements provide similar measures of the rain PSD as observed with collocated 2DVDs (e.g., D0, Nw) for rain rates less than 15 mm/hr. For heavier rain rates we will rely on 2DVDs for PSD information. For snowfall we will combine point-redundant observations of SWER distributed over three or more locations within a FOV. Each location will contain at least one fenced weighing gauge, one HP, two PDs, and a 2DVD. MRRs will also be located at each site to extend the measurement to the column. By collecting SWER measurements using different instrument types that employ different measurement techniques our objective is to separate measurement uncertainty from natural variability in SWER and PSD. As demonstrated using C3VP polarimetric radar, gauge, and 2DVD/PD datasets these measurements can be combined to bootstrap an area wide SWER estimate via constrained modification of density-diameter and radar reflectivity-snowfall relationships. These data will be combined with snowpack, airborne microphysics, radar, radiometer, and tropospheric sounding data to refine GPM snowfall retrievals. The gauge and disdrometer instruments are being developed to operate autonomously when necessary using solar power and wireless communications. These systems will be deployed in numerous field campaigns through 2016. Planned deployment of these systems include field campaigns in Finland (2010), Oklahoma (2011), Canada (2012) and North Carolina (2013). GPM will also deploy 20 pairs of TBRGs within a 25 km2 region along the Virginia coast under NASA NPOL radar coverage in order to quantify errors in point-area rainfall measurements.

Petersen, Walter A.↗
NASA NTRS2010

Analysis of TRMM-LIS Lightning and Related Microphysics Using a Cell-Scale Database

Previous studies of tropical lightning activity using Tropical Rainfall Measurement Mission (TRMM) Lightning Imaging Sensor (LIS) data performed analyses of lightning behavior over mesoscale "feature" scales or over uniform grids. In order to study lightning and the governing ice microphysics intrinsic to thunderstorms at a more process-specific scale (i.e., the scale over which electrification processes and lightning occur in a "unit" thunderstorm), a new convective cell-scale database was developed by analyzing and refining the University of Utah's Precipitation Features database and retaining precipitation data parameters computed from the TRMM precipitation radar (PR), microwave imager (TMI) and LIS instruments. The resulting data base was to conduct a limited four-year study of tropical continental convection occurring over the Amazon Basin, Congo, Maritime Continent and the western Pacific Ocean. The analysis reveals expected strong correlations between lightning flash counts per cell and ice proxies, such as ice water path, minimum and average 85GHz brightness temperatures, and 18dBz echo top heights above the freezing level in all regimes, as well as regime-specific relationships between lighting flash counts and PR-derived surface rainfall rates. Additionally, radar CFADs were used to partition the 3D structure of cells in each regime at different flash counts. The resulting cell-scale analyses are compared to previous mesoscale feature and gridded studies wherever possible.

Leroy, Anita↗
NASA NTRS2010

Electrically-Active Convection and Tropical Cyclogenesis in the Atlantic and East Pacific

It has been hypothesized that deep, intense convective-scale "hot" towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., "electrically-hot towers") present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5degN-20degN and 130degW-20degE in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves and to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and over various smaller longitude bands by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged IR brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation. Results suggest a clear distinction between developing and non-developing waves as developing waves near their region of development in terms of the intensity of convection (indicated by lightning flash rate), coverage of cold cloudiness (indicated by the percentage of a 2.5deg by 2.5deg box covered by IR brightness temperatures less than 210 K), and large-scale variables, such as midlevel moisture and upper-level upward motion. For example, waves that developed in the East Pacific longitude band (i.e., 130degW-95degW) were observed in that band to have a flash rate of 56.4 flashes/day, a coverage by brightness temperatures less than 210 K equal to 2.2%, a 700-hPa specific humidity anomaly of 0.4 g/kg, and a 300-hPa omega value of -0.04 Pascals/s in the trough phase compared to the non-developing wave trough values of 22.1 flashes/day, a coverage by brightness temperatures less than 210 K equal to 0.9%, a 700-hPa specific humidity anomaly of -0.3 g/kg, and a 300-hPa omega value of -0.01 Pascals/s.

Leppert, Kenneth D., II↗
NASA NTRS2010

The Use of Radar to Improve Rainfall Estimation over the Tennessee and San Joaquin River Valleys

This slide presentation provides an overview of the collaborative radar rainfall project between the Tennessee Valley Authority (TVA), the Von Braun Center for Science & Innovation (VCSI), NASA MSFC and UAHuntsville. Two systems were used in this project, Advanced Radar for Meteorological & Operational Research (ARMOR) Rainfall Estimation Processing System (AREPS), a demonstration project of real-time radar rainfall using a research radar and NEXRAD Rainfall Estimation Processing System (NREPS). The objectives, methodology, some results and validation, operational experience and lessons learned are reviewed. The presentation. Another project that is using radar to improve rainfall estimations is in California, specifically the San Joaquin River Valley. This is part of a overall project to develop a integrated tool to assist water management within the San Joaquin River Valley. This involves integrating several components: (1) Radar precipitation estimates, (2) Distributed hydro model, (3) Snowfall measurements and Surface temperature / moisture measurements. NREPS was selected to provide precipitation component.

Petersen, Walter A.↗
NASA NTRS2010

Exploring a Physically Based Tool for Lightning Cessation: Preliminary Results

The University of Alabama in Huntsville (UAHuntsville) and NASA s Marshall Space Flight Center are collaborating with the 45th Weather Squadron (45WS) at Cape Canaveral Air Force Station (CCAFS) to enable improved nowcasting of lightning cessation. The project centers on use of dual-polarimetric radar capabilities, and in particular, the new C-band dual-polarimetric weather radar acquired by the 45WS. Special emphasis is placed on the development of a physically based operational algorithm to predict lightning cessation. While previous studies have developed statistically based lightning cessation algorithms, we believe that dual-polarimetric radar variables offer the possibility to improve existing algorithms through the inclusion of physically meaningful trends reflecting interactions between in-cloud electric fields and microphysics. Specifically, decades of polarimetric radar research using propagation differential phase has demonstrated the presence of distinct phase and ice crystal alignment signatures in the presence of strong electric fields associated with lightning. One question yet to be addressed is: To what extent can these ice-crystal alignment signatures be used to nowcast the cessation of lightning activity in a given storm? Accordingly, data from the UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR) along with the North Alabama Lightning Mapping Array are used in this study to investigate the radar signatures present before and after lightning cessation. A summary of preliminary results will be presented.

Schultz, Elsie V.↗
NASA NTRS2010

Recent Advancements in Lightning Jump Algorithm Work

In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).

Schultz, Christopher J.↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Molthan, Andrew L.↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Molthan, Andrew L.↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties within a Single-Moment Microphysics Scheme

The assumptions of a single-moment microphysics scheme (NASA Goddard) were evaluated using a variety of surface, aircraft and radar data sets. Fixed distribution intercepts and snow bulk densities fail to represent the vertical variability and diversity of crystal populations for this event. Temperature-based equations have merit, but they can be adversely affected by complex temperature profiles that are inverted or isothermal. Column-based approaches can mitigate complex profiles of temperature but are restricted by the ability of the model to represent cloud depth. Spheres are insufficient for use in CloudSat reflectivity comparisons due to Mie resonance, but reasonable for Rayleigh scattering applications. Microphysics schemes will benefit from a greater range of snow crystal characteristics to accommodate naturally occurring diversity.

Molthan, Andrew L.↗
NASA NTRS2009

Exploring Alternative Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. The combination of reliable cloud microphysics and radar reflectivity may constrain radiative transfer models used in satellite simulators during future missions, including EarthCARE and the NASA Global Precipitation Measurement. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a mid latitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗
NASA NTRS2009

Regime-based TRMM and GV Microphysical Studies at MSFC and UAH

Differences in rain rate between TMI and PR vary systematically with PR Z-profile statistics, whose frequency of occurrence is modified to create seasonal biases in the sub-tropical Southeastern U.S. (and almost certainly elsewhere). Tropical (non-tropical) DSDs in N. Alabama exhibit larger (smaller) D(sub 0), and larger (smaller) N(sub 0) and mu. The formulation process for empirical retrievals of DSD using dual-pol radar is sensitive to D(sub max) assumptions used in the scattering model stage. 4. DSD retrievals from Parsivel disdrometers compare favorably to those of the 2DVD unless rain rates exceed 25 mm/hr and D(sub m) exceeds 2 mm (at which point the Parsivels overestimate D(sub m) and rain rate).

Petersen, Walter A.↗
NASA NTRS2009

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗
NASA NTRS2009

The UAH/NSSTC Advanced Radar for Meteorological and Operational Research (ARMOR)

The past four years have seen a marked enhancement in meteorological-radar infrastructure and radar-research capability at the University of Alabama-Huntsville (UAH) and National Space Science and Technology Center (NSSTC; a collaborative center supported by UAH, NASA-MSFC and USRA). This enhancement is due in part to the development of the ARMOR C-band dual-polarimetric radar facility (amongst other mobile radar facilities also discussed in this conference). The ARMOR radar, located at Huntsville International Airport, originated as a unique collaboration between university, government and broadcast meteorologists (the very first of its kind relative to concurrent operational, research and broadcast applications of dual-polarimetry). Contributions from each of these entities resulted in the upgrade of a surplus National Weather Service WSR-74C radar to a research-grade C-band polarimetric radar. The initial upgrade of the radar took place in late 2004 with WHNT-TV purchase and installation of a SIGMET (now Vaisala) Antenna Mounted Receiver (AMR), RVP8/RCP8 radar processor/antenna controller, new radome, and a new dual-polarimetric antenna feed. The AMR enabled simultaneous transmit and receive (STSR) capability and hence collection of dual-polarimetric moments. During the initial part of the AMR upgrade the original WSR74C antenna reflector and 250 kW magnetron-transmitter were used. In early 2005, a new 350 kW magnetron transmitter was purchased from Baron Services and installed. In October of 2006 a new high performance parabolic antenna and dual-pol feed (Seavey) were installed together with a new Orbit pedestal. ARMOR Radar control and data delivery are facilitated through the use of T-1 lines that run from the airport to both NSSTC and WHNT-TV in Huntsville. Under current operating protocols radar scanning and product development are completed at NSSTC, though meteorologists at WHNT-TV can also control the radar if desired. In its default scanning configuration the radar is operated 24/7 in an STSR polarimetric rain scan mode alternating with a surveillance scan on a 5-minute cycle; scans separated by 2.5 minutes. Every 2.5 minutes the raw data arrive at NSSTC where they are corrected in real time for attenuation and differential attenuation (using a constrained ZDR/Z-PHI approach) and new products are generated (e.g., rain maps, hydrometeor identification etc.). The raw and derived products are archived at NSSTC and also redistributed locally in real time over the network within NSSTC to the National Weather Service Forecast Office in Huntsville (collocated with NSSTC) for operational use. During periods of interesting weather the radar is often operated in full, sector, or RHI volume modes from NSSTC and coincident with UAH mobile radar or NWS NEXRAD radar platforms as needed.

Petersen, Walter A.↗
NASA NTRS2009

NASA Global Precipitation Mission Ground Validation Implementation

The Global Precipitation Mission (GPM; core-satellite launch 2013) will provide Ka/Ku-band dual-frequency precipitation radar (DPR) and accompanying passive microwave radiometer-diagnosed precipitation estimates over a latitude range of 65 N to 65 S. The extended latitudinal domain of GPM coverage combined with requirements to detect (and in the case of liquid, estimate) liquid and frozen precipitation rates for values ranging from several hundred to just a few tenths of a millimeter per hour present new challenges to the development of physically-based satellite precipitation retrieval algorithms. On regional scales select national and international resources such as existing calibrated radar and rain gauge networks can provide basic datasets that enable direct statistical validation of GPM core-satellite reflectivitys and core/constellation rain rate measurements. Near-term planned field campaign involvements include Finland/Baltic Sea (fall 2010; joint CloudSat,GPM, and European study of precipitation in low-altitude melting layers and snowfall in the vicinity of the Helsinki testbed), central Oklahoma (spring 2011; joint with DOE ARM- precipitation retrievals over a mid-latitude continental land surface), and the Great Lakes region (winter 2011-12, snowfall retrieval).

Petersen, Walter A.↗
NASA NTRS2009

Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather

Previous studies have demonstrated that rapid increases in total lightning activity (intracloud + cloud-to-ground) are often observed tens of minutes in advance of the occurrence of severe weather at the ground. These rapid increases in lightning activity have been termed "lightning jumps." Herein, we document a positive correlation between lightning jumps and the manifestation of severe weather in thunderstorms occurring across the Tennessee Valley and Washington D.C. A total of 107 thunderstorms were examined in this study, with 69 of the 107 thunderstorms falling into the category of non-severe, and 38 into the category of severe. From the dataset of 69 isolated non-severe thunderstorms, an average peak 1 minute flash rate of 10 flashes/min was determined. A variety of severe thunderstorm types were examined for this study including an MCS, MCV, tornadic outer rainbands of tropical remnants, supercells, and pulse severe thunderstorms. Of the 107 thunderstorms, 85 thunderstorms (47 non-severe, 38 severe) from the Tennessee Valley and Washington D.C tested 6 lightning jump algorithm configurations (Gatlin, Gatlin 45, 2(sigma), 3(sigma), Threshold 10, and Threshold 8). Performance metrics for each algorithm were then calculated, yielding encouraging results from the limited sample of 85 thunderstorms. The 2(sigma) lightning jump algorithm had a high probability of detection (POD; 87%), a modest false alarm rate (FAR; 33%), and a solid Heidke Skill Score (HSS; 0.75). A second and more simplistic lightning jump algorithm named the Threshold 8 lightning jump algorithm also shows promise, with a POD of 81% and a FAR of 41%. Average lead times to severe weather occurrence for these two algorithms were 23 minutes and 20 minutes, respectively. The overall goal of this study is to advance the development of an operationally-applicable jump algorithm that can be used with either total lightning observations made from the ground, or in the near future from space using the GOES-R Geostationary Lightning Mapper.

Schultz, Christopher J.↗