SearcharxivSearch

arXiv · 2001.04213

Outer scale of the wide-range Prandtl/Schmidt number spectrum on beam wander for oceanic optical turbulence

Abstract

Light propagation in ocean is influenced by the refractive-index which is related to temperature, salinity, outer-scale, etc. Based on Hill's model 1 (H1), two kinds of oceanic refractive-index spectrum (ORIS) have been proposed to describe the second order characteristic of refractive-index. Most recently, several ORIS models were proposed based on Hill's model 4 (H4), which gave a better precision in high wave-numbers (viscous-diffusive range). However, the outer scale, as a key parameter related to practical environment, has not been introduced into any oceanic H4-based spectra. In this paper, we take the outer-scale parameter into an H4-based spectrum which is adapted to the wide-range Prandtl/Schmidt number [Opt. Express. 20, 11111(2019)]. The proposed outer-scaled spectrum could be used in analyzing wave propagation in limited outer-scaled environment with different values of average temperature and salinity. We further derived the beam wander formula of collimated laser beam. Numerical calculations show that the beam wander influenced by outer-scale length $L_{0}$ is more obvious than that influenced by average temperature $\langle T\rangle$, when $L_{0}$ varies from $10 \rm m$ to $100 \rm m$, and $\langle T\rangle$ ranges from $0^{\circ} \rm C$ to $30^{\circ} \rm C$. When salinity fluctuations prevails ($\omega \rightarrow 0$), the influence of outer scale becomes weaker. In contribution proportion of beam wander, the temperature-salt coupling term is the much larger than that of temperature or salinity term.

Explore related subjects

Keep this discovery

BibTeXRIS

Jian-Dong Cai, Jin-Ren Yao, Han-Tao Wang, Hua-Jun Zhang, Ming-Yuan Ren, Yu Zhang. 2020-01-13. Outer scale of the wide-range Prandtl/Schmidt number spectrum on beam wander for oceanic optical turbulence. https://arxiv.org/abs/2001.04213

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