SearcharxivSearch

arXiv · 2107.05338

Could macroscopic dark matter (macros) give rise to mini-lightning flashes out of a blue sky without clouds?

Abstract

A recent study pointed out that macroscopic dark matter (macros) traversing through the earth's atmosphere can give rise to hot and ionized channels similar to those associated with lightning leaders. The authors of the study investigated the possibility that when such channels created by macros pass through a thundercloud, lightning leaders may locked into these ionized channels creating lightning discharges with perfectly straight channels. They suggested the possibility of detecting such channels as a means of detecting the passage of macros through the atmosphere. In this paper, we show that macros crossing the atmosphere under fair weather conditions could also give rise to mini lightning flashes with current amplitudes in the order of few hundreds of Amperes. These mini lightning flashes would generate a thunder signature similar to or stronger than those of long laboratory sparks and they could also be detected by optical means. As in the case of thunderstorm assisted macro lightning, these mini-lightning flashes are also associated with straight channels. Moreover, since the frequency of mini lightning flashes are about three hundred times more frequent than the macro generated lightning flashes which were assisted by thunderstorms, they could be used as a means to look for the paths of macroscopic dark matter crossing the atmosphere.

Explore related subjects

Keep this discovery

BibTeXRIS

Vernon Cooray, Gerald Cooray, Marcos Rubinstein, Farhad Rachidi. 2021-07-12. Could macroscopic dark matter (macros) give rise to mini-lightning flashes out of a blue sky without clouds?. https://doi.org/10.3390/atmos12091230

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Windowed Envelope Statistics for Time-Domain Significant Wave Height Estimation From HF Radar

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

physics.ao-ph

KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations

Accurate kilometer-scale near-surface winds are important for understanding atmospheric processes over complex terrain, yet remain difficult to reconstruct from sparse and unevenly distributed observations. Here we introduce KiloDA, a diffusion framework for hourly kilometer-scale wind reconstruction from surface stations. KiloDA learns the statistical distribution and spatial structure of wind fields from historical 3-km Weather Research and Forecasting (WRF) model forecasts. At each reconstruction time, no contemporaneous WRF field is used. Instead, station observations provide the only constraints on the current atmospheric state and guide posterior sampling from the learned prior. In idealized WRF experiments, KiloDA recovers localized wind structures when only 0.24% of grid cells are observed and shows an overall advantage over conventional interpolation across terrain conditions and wind speed regimes. This capability largely transfers to real observations. In a fully withheld region, KiloDA reduces the median wind speed root mean square error (RMSE) by 19% relative to ERA5 reanalysis, using only observations outside the region, with the largest improvements over high-elevation and high-relief terrain. A random station holdout further confirms that this advantage extends across different complex-terrain locations and holdout configurations. These results show that historical model archives can provide useful structural knowledge for reconstructing kilometer-scale wind fields from sparse observations without requiring an accurate model estimate of the current atmospheric state.

physics.ao-ph