Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 1606.07471

Comment on "Atmospheric ionization by high-fluence, hard spectrum solar proton events and their probable appearance in the ice core archive" by A.L. Melott et al

K. A. Duderstadt·J. E. Dibb·C. H. Jackman·C. E. Randall·N. A. Schwadron·S. C. Solomon·H. E. Spence
View original source ↗Read source document ↗Export metadata ↓

Abstract

Melott et al. [2016] suggest that individual solar proton events (SPEs) are detectable as nitrate ion spikes in ice cores. They use the high fluence, high energy (hard spectrum) SPE of 23 February 1956 to calculate an enhancement of HNO3 from the surface to 46 km that is equivalent to a ~120 ng cm-2 nitrate ion spike observed in the GISP2H ice core. The Melott et al. [2016] approach is fundamentally flawed, since it considers only the absolute column burden of SPE-produced nitrate and not the pre-existing nitrate in the stratosphere. Modeling studies supported by extensive observations [Duderstadt et al., 2014, 2016, and this comment] show background HNO3 in the lower and middle stratosphere equivalent to 2000 to 3000 ng cm-2 nitrate. These high levels of background nitrate must also be included when estimating SPE enhancements to the deposition of nitrate ions that might eventually be preserved in an ice core. The 1956 SPE results in less than a 5% increase in the column burden of atmospheric HNO3, not large enough to explain the nitrate spike seen in the GISP2H ice core. Even extreme SPE enhancements cannot explain nitrate peaks (typically hundreds of percent increases) observed in the ice record [Duderstadt et al., 2016]. Realistic mechanisms linking nitrate ions in ice cores to SPEs have not been established. It is time to move the search for indicators of SPEs away from nitrate ions: Nitrate ions cannot be used as proxies for individual SPEs in the ice core record.

Explore related subjects

physics.ao-phastro-ph.EPastro-ph.IMastro-ph.SRphysics.geo-ph

Keep this discovery

BibTeXRIS

K. A. Duderstadt, J. E. Dibb, C. H. Jackman, C. E. Randall, N. A. Schwadron, S. C. Solomon, H. E. Spence. 2016-07-08. Comment on "Atmospheric ionization by high-fluence, hard spectrum solar proton events and their probable appearance in the ice core archive" by A.L. Melott et al. https://doi.org/10.1002/2016jd025220

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

KEEP EXPLORING

Related papers

arXiv2026

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↗
arXiv2026

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↗