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Record W2055455840 · doi:10.1175/2010mwr3452.1

The North American Lightning Detection Network (NALDN)—Analysis of Flash Data: 2001–09

2010· article· en· W2055455840 on OpenAlexaffabout
Richard E. Orville, Gary R. Huffines, William R. Burrows, Kenneth L. Cummins

Bibliographic record

VenueMonthly Weather Review · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsLightning detectionLightning (connector)Flash (photography)MeteorologyEnvironmental sciencePeak currentClimatologyUpper-atmospheric lightningGeographyGeologyLightning strikeThunderstormPhysics

Abstract

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Cloud-to-ground (CG) lightning data have been analyzed for the years 2001–09 for North America, which includes Alaska, Canada, and the lower 48 U.S. states. Flashes recorded within the North American Lightning Detection Network (NALDN) are examined. No corrections for detection efficiency variability are made over the 9 yr of the dataset or over the large geographical area comprising North America. There were network changes in the NALDN during the 9 yr, but these changes have not been corrected for nor have the recorded data been altered in any way with the exception that all positive lightning reports with peak currents less than 15 kA have been deleted. Thus, the reader should be aware that secular changes are not just climatological in nature. All data were analyzed with a spatial resolution of 20 km. The analyses presented in this work provide a synoptic view of the interannual variability of lightning observations in North America, including the impacts of physical changes in the network during the 9 yr of study. These data complement and extend previous analyses that evaluate the U.S. NLDN during periods of upgrade. The total (negative and positive) flashes for ground flash density, the percentage of positive lightning, and the positive flash density have been analyzed. Furthermore, the negative and positive first stroke peak currents and the flash multiplicity have been examined. The highest flash densities in Canada are along the U.S.–Canadian border (1–2 flashes per square kilometer) and in the United States along the Gulf of Mexico coast from Texas through Florida (exceeding 14 flashes per square kilometer in Florida). The Gulf Stream is “outlined” by higher flash densities off the east coast of the United States. Maximum annual positive flash densities in Canada range primarily from 0.01 to 0.3 flashes per square kilometer, and in the United States to over 0.5 flashes per square kilometer in the Midwest and in the states of Louisiana and Mississippi. The annual percentage of positive lightning to ground varies from less than 2% over Florida to values exceeding 25% off the West Coast, Alaska, and the Yukon. A localized maximum in the percentage of positive lightning in the NALDN occurs in Manitoba and western Ontario, just north of North Dakota and Minnesota. When averaged over North America, first stroke negative median peak currents range from 19.8 kA in 2001 to 16.0 kA in 2009 and for all years, average 16.1 kA. First stroke positive median peak currents range from a high of 29.0 kA in 2008 and 2009 to a low of 23.3 kA in 2003 with a median of 25.7 kA for all years. There is a relatively sharp transition from low to high median negative peak currents along the Gulf and Atlantic coasts of the United States. No sharp transitions are observed for the median positive peak currents. Relatively lower positive peak currents occur throughout the southeastern United States. The highest values of mean negative multiplicity exceed 3.0 strokes per flash in the NALDN with some variation over the 9 yr. Lower values of mean negative multiplicity occur in the western United States. Positive flash mean multiplicity is slightly higher than 1.1, with the highest values of 1.7 observed in the southwestern states. As has been noted in prior research, CG lightning has significant variations from storm to storm as well as between geographical regions and/or seasons and, consequently, a single distribution for any lightning parameter, such as multiplicity or peak current, may not be sufficient to represent or describe the parameter.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.598

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.249
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations132
Published2010
Admission routes2
Has abstractyes

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