SearcharxivSearch

arXiv · 0910.4750

Investigation of particle and molecular extinction effects in remote sensing by ultraviolet DIAL in the lower atmosphere

Abstract

This study presents theoretical investigation of the effects of particle and molecular extinction in horizontal remote sensing near the ground for several visibilities at UV wavelengths by neglecting the spatial inhomogeneity of aerosol in the atmosphere and taking into account the dependence of refracting on air temperature and pressure. Due to weak attenuation of oxygen and other gaseous atmospheric constituents in this region, we have only considered the effect of ozone in calculation. The results are important to estimate systematic errors in measuring gas concentration introduced by large wavelength separation in UV-DIAL. The total attenuation (km-1) at wavelengths is listed in the form of a table from 200 to 400 nm for several values of visibilities. It is found the aerosol attenuation in UV region varies quite smoothly with wavelength and therefore systematic error caused by aerosol scattering is negligible in remote sensing by UV-DIAL even with large wavelength separation. Moreover, it has been found that only aerosol extinction is dominant in lidar remote sensing in the lower atmosphere in UV region. In large altitude that aerosol concentration is lower; the molecular scattering is important especially for wavelengths larger than 310 nm.

Explore related subjects

Keep this discovery

BibTeXRIS

Gholamreza Shayeganrad, Leila Mashhadi, Davood Momeni. 2009-10-25. Investigation of particle and molecular extinction effects in remote sensing by ultraviolet DIAL in the lower atmosphere. https://arxiv.org/abs/0910.4750

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