SearcharxivSearch

arXiv · 1802.09782

Potential energy surface, dipole moment surface and the intensity calculations for the 10 micron, 5 micron, and 3 micron bands of ozone

Abstract

Monitoring ozone concentrations in the Earth's atmosphere using spectroscopic methods is a major activity which undertaken both from the ground and from space. However there are long-running issues of consistency between measurements made at infrared (IR) and ultraviolet (UV) wavelengths. In addition, key O$_3$ IR bands at 10 \muu, 5 \muu\ and 3 \muu\ also yield results which differ by a few percent when used for retrievals. These problems stem from the underlying laboratory measurements of the line intensities. Here we use quantum chemical techniques, first principles electronic structure and variational nuclear-motion calculations, to address this problem. A new high-accuracy \ai\ dipole moment surface (DMS) is computed. Several spectroscopically-determined potential energy surfaces (PESs) are constructed by fitting to empirical energy levels in the region below 7000 \cm\ starting from an \ai\ PES. Nuclear motion calculations using these new surfaces allow the unambiguous determination of the intensities of 10 \muu\ band transitions, and the computation of the intensities of 10 \muu\ and 5 \muu\ bands within their experimental error. A decrease in intensities within the 3 \muu\ is predicted which appears consistent with atmospheric retrievals. The PES and DMS form a suitable starting point both for the computation of comprehensive ozone line lists and for future calculations of electronic transition intensities

Explore related subjects

Keep this discovery

BibTeXRIS

Oleg L. Polyansky, Nikolai F. Zobov, Irina I. Mizus, Aleksandra A. Kyuberis, Lorenzo Lodi, Jonathan Tennyson. 2018-02-27. Potential energy surface, dipole moment surface and the intensity calculations for the 10 micron, 5 micron, and 3 micron bands of ozone. https://doi.org/10.1016/j.jqsrt.2018.02.018

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