Characteristics of Lightning Within Electrified Snowfall Events Using Total Lightning Measurements

No abstract availabl

Characteristics of Lightning Within Electrified Snowfall Events Using Lightning Mapping Arrays

This study examined 34 lightning flashes within four separate thundersnow events derived from lightning mapping arrays (LMAs) in northern Alabama, central Oklahoma, and Washington, DC. The goals were to characterize the in-cloud component of each lightning flash, as well as the correspondence between the LMA observations and lightning data taken from national lightning networks like the National Lightning Detection Network (NLDN). Individual flashes were examined in detail to highlight several observations within the dataset. The study results demonstrated that the structures of these flashes were primarily normal polarity. The mean area encompassed by this set of flashes is 375 square kilometers, with a maximum flash extent of 2300 square kilometers, a minimum of 3 square kilometers, and a median of 128 square kilometers. An average of 2.29 NLDN flashes were recorded per LMA-derived lightning flash. A maximum of 11 NLDN flashes were recorded in association with a single LMA-derived flash on 10 January 2011. Additionally, seven of the 34 flashes in the study contain zero NLDN identified flashes. Eleven of the 34 flashes initiated from tall human-made objects (e.g., communication towers). In at least six lightning flashes, the NLDN detected a return stroke from the cloud back to the tower and not the initial upward leader. This study also discusses lightning's interaction with the human built environment and provides an example of lightning within heavy snowfall observed by GOES-16's Geostationary Lightning Mapper

Exploring Lightning Jump Characteristics

This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase in the total lightning flash rate (i.e., lightning jump, LJ). An automated storm tracking method is used to identify storm "clusters" and total lightning activity from three different lightning detection systems over Oklahoma, northern Alabama and Washington, D.C. On average and for different employed thresholds, the clusters that encompass at least one LJ (LJ1) last longer, relate to higher Maximum Expected Size of Hail, Vertical Integrated Liquid and lightning flash rates (area-normalized) than the clusters that did not exhibit any LJ (LJ0). The respective mean values for LJ1 (LJ0) clusters are 80 min (35 min), 14 mm (8 mm), 25 kg per square meter (18 kg per square meter) and 0.05 flash per min per square kilometer (0.01 flash per min per square kilometer). Furthermore, the LJ1 clusters are also characterized by slower decaying autocorrelation functions, a result that implies a less "random" behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm's dissipation. Depending of the LJ strength (i.e., varying thresholds), these values typically range between 20-60 min, with stronger jumps indicating more time until storm decay. This study's results support the hypothesis that the LJ is a proxy for the storm's kinematic and microphysical state rather than a coincidental value

A Total Lightning Perspective of the 20 May 2013 Moore, Oklahoma Supercell

In the early afternoon of 20 May 2013, a storm initiated to the westsouthwest of Newcastle, Oklahoma. This storm would rapidly intensify into the parent supercell of the tornado that struck the city of Moore, Oklahoma. This article describes what contributions total lightning observations from the Oklahoma Lightning Mapping Array could provide to operational forecasters had these observations been available in realtime. This effort includes a focus on the GOESR pseudogeostationary lightning mapper demonstration product as well as the NASA SPoRT / Meteorological Development Laboratory's total lightning tracking tool. These observations and tools identified several contributions. Two distinct lightning jumps at 1908 and 1928 UTC provided a lead time of 19 minutes ahead of severe hail and 26 minutes ahead of the Moore, Oklahoma tornado's touchdown. These observations provide strong situational awareness to forecasters, as the lightning jumps are related to the rapid strengthening of the storm's updraft and mesocyclone and serve as a precursor to the stretching of the storm vortex ahead severe weather

Characterization of Optical Energy Output in Thunderstorms to Enhance Severe Thunderstorm Identification

No abstract availabl

DICER1 mutations in childhood cystic nephroma and its relationship to DICER1-renal sarcoma

The pathogenesis of cystic nephroma of the kidney has interested pathologists for over 50 years. Emerging from its initial designation as a type of unilateral multilocular cyst, cystic nephroma has been considered as either a developmental abnormality or a neoplasm or both. Many have viewed cystic nephroma as the benign end of the pathologic spectrum with cystic partially differentiated nephroblastoma and Wilms tumor, whereas others have considered it a mixed epithelial and stromal tumor. We hypothesize that cystic nephroma, like the pleuropulmonary blastoma in the lung, represents a spectrum of abnormal renal organogenesis with risk for malignant transformation. Here we studied DICER1 mutations in a cohort of 20 cystic nephromas and 6 cystic partially differentiated nephroblastomas, selected independently of a familial association with pleuropulmonary blastoma and describe four cases of sarcoma arising in cystic nephroma, which have a similarity to the solid areas of type II or III pleuropulmonary blastoma. The genetic analyses presented here confirm that DICER1 mutations are the major genetic event in the development of cystic nephroma. Further, cystic nephroma and pleuropulmonary blastoma have similar DICER1 loss of function and ‘hotspot' missense mutation rates, which involve specific amino acids in the RNase IIIb domain. We propose an alternative pathway with the genetic pathogenesis of cystic nephroma and DICER1-renal sarcoma paralleling that of type I to type II/III malignant progression of pleuropulmonary blastoma

Communications Biophysics

Contains research objectives and reports on six research projects split into three sections.National Institutes of Health (Grant 5 P01 NS13126-07)National Institutes of Health (Training Grant 5 T32 NS07047-05)National Institutes of Health (Training Grant 2 T32 NS07047-06)National Science Foundation (Grant BNS 77-16861)National Institutes of Health (Grant 5 R01 NS1284606)National Institutes of Health (Grant 5 T32 NS07099)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 5 R01 NS14092-04)Gallaudet College SubcontractKarmazin Foundation through the Council for the Arts at M.I.T.National Institutes of Health (Grant 1 R01 NS1691701A1)National Institutes of Health (Grant 5 R01 NS11080-06)National Institutes of Health (Grant GM-21189

How do farmers learn from extension services? Evidence from Malawi

Though extension services have long since proved their value to agricultural production and farmer prosperity, their record in sub‐Saharan Africa has been mixed. To study the impact of such programs on farmers' learning about agricultural technologies, we implemented a quasi‐randomized controlled trial and collected detailed panel data among Malawian farmers. Based on those findings, we develop a two‐stage learning framework, in which farmers formulate yield expectations before deciding on how much effort to invest in learning about these processes. Using data centered on farmer beliefs, knowledge, and constraints, we find evidence that beliefs about potential yields hinge on first‐hand and local experience, and that these beliefs significantly impact learning efforts. Consistent with this, we find that farmers who participated in season‐long, farmer‐led demonstration plot cultivation plan to adopt more components of new multi‐component technology, compared to farmers who were invited to attend only field‐day events

Communications Biophysics

Contains reports on seven research projects split into three sections.National Institutes of Health (Grant 5 PO1 NS13126)National Institutes of Health (Grant 1 RO1 NS18682)National Institutes of Health (Training Grant 5 T32 NS07047)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 1 F33 NS07202-01)National Institutes of Health (Grant 5 RO1 NS10916)National Institutes of Health (Grant 5 RO1 NS12846)National Institutes of Health (Grant 1 RO1 NS16917)National Institutes of Health (Grant 1 RO1 NS14092-05)National Science Foundation (Grant BNS 77 21751)National Institutes of Health (Grant 5 R01 NS11080)National Institutes of Health (Grant GM-21189