Photon-counting dual-comb spectroscopy (DCS) opens new possibilities for deploying DCS in scenarios previously constrained by limited detection sensitivity. However, inevitable optical path fluctuations hinder its practical implementation. Here, we propose a method to ensure the long-term stability of photon-counting DCS, overcoming turbulent optical paths, achieving attowatt-level detection sensitivity and quick acquisition times. Using a compact all-fiber dual-comb system, we achieve 20 nm broadband DCS of H¹³C¹⁴N across the C-band with an average detected power of only 4 attowatts per-comb line. Despite significant vibrations throughout measurements, the spectra maintain comb-line resolution and shot-noise-limited signal-to-noise ratios. Additionally, the system demonstrates successful deployment in open-path measurements, overcoming 93 dB attenuation. Our approach enables remote sensing of CO₂, H₂O, and HDO over a continuous 20-h observation period. This method highlights the potential for applications in fields such as metrology, quantum physics, and atmospheric sensing, especially in turbulent environments like open air or water, within a field-deployable system.

Accurate detection of wind profiles within the troposphere is essential for atmospheric dynamics research and extreme weather forecasting. Coherent Doppler wind lidar (CDWL) is widely regarded as the most suitable technique for high spatial and temporal resolution wind profile detection. However, since coherent detection relies heavily on the concentration of aerosol particles, which cause Mie scattering, the received backscattering lidar signal exhibits significantly low intensity at high altitudes. As a result, conventional methods, such as spectral centroid estimator, often fail to produce credible and accurate wind retrieval results in these regions. To address this issue, we introduce a deep learning model for lidar wind profile retrieval, which integrates Transformer architecture with the Kolmogorov-Arnold network. Our model is trained solely on targets derived from the traditional wind retrieval algorithm and utilizes radiosonde measurements as the ground truth for test results evaluation. Experimental results demonstrate that our model not only extends the maximum vertical wind profile detection range but also produces more accurate results, exhibiting a level of precision that surpasses the labeled targets. This phenomenon, which we refer to as super-accuracy, is explored by investigating the potential underlying factors that contribute to this intriguing occurrence. In addition, we compare the performance of our method with other state-of-the-art (SOTA) models, highlighting its superior effectiveness and capability in high-resolution wind retrieval. In the future, our proposed model could potentially be extended to other remote sensing spectrum signal processing applications (e.g., microwave Doppler lidar), thereby establishing a benchmark for future research and driving the advancement of deep learning models in this domain.

Detectors based on single-photon avalanche diodes (SPADs) operating in free-running mode surfer from distorted detection signals due to the impact of afterpulse, dead time, and the non-linear detection efficiency response. This study presents a correction method based on conditional probability. In the experiments with high temporal resolution and huge dynamic range conditions, this method’s residual sum of squares is near 68 times smaller than the uncorrected received data of SPAD and near 50 times smaller than deconvolution method. This method is applied to polarization lidar and CO2 lidar, and the performance shows significant improvement. This method effectively mitigates the impact of SPAD afterpulse, dead time, and detection efficiency non-linear response, making it suitable for all SPADs. Especially, our method is primarily employed for atmospheric detection.

Differential absorption Lidar (DIAL) in the ultraviolet (UV) region is an effective approach for monitoring tropospheric ozone. 4H-SiC single-photon detectors (SPDs) are emergent devices for UV single-photon detection. Here, we demonstrate a 4H-SiC SPD-based ozone DIAL. We design and fabricate the 4H-SiC single-photon avalanche diode with a beveled mesa structure and optimized layer thickness. An active quenching circuit with a quenching time of 1.03 ns is developed to significantly mitigate the afterpulsing effect while enhancing the maximum count rate. After characterization, the SPD exhibits excellent performance with a photon detection efficiency of 16.6% at 266 nm, a dark count rate of 138 kcps, a maximum count rate of 13 Mcps, and an afterpulse probability of 2.7% at room temperature. Then, we apply two 4H-SiC SPDs in an ozone DIAL. The measured ozone concentrations at altitudes of 1–3.5 km agree well with the results of a commercial ozone DIAL. Our work provides an alternative solution for general UV Lidar applications.

This study reports an extreme ionospheric plasma depletion event over the Eastern Pacific from postmidnight to early morning during the superstorm's recovery phase on 21 November 2003 observed by the DMSP F13, ROCSAT‐1, GRACE, and CHAMP satellites, and two ground‐based GPS receivers. The depletion and its interhemispheric geomagnetic conjugate effect occurred between ∼40°S and 40°N geomagnetic latitudes. This suggests a possible extremely long‐range flux tube connection with an apex altitude exceeding 6,000 km over the geomagnetic equator. Notably, the observed altitude for midlatitude depletions of equatorial origin in the morning is the highest ever reported. Previous studies have primarily observed the extension of equatorial plasma bubbles to middle latitudes in the post‐sunset hours. The continuous upward vertical plasma drift, supported by ROCSAT‐1 and TIE‐GCM simulations, may drive the unprecedentedly strong latitudinal extension of these midlatitude plasma depletions in the midnight‐to‐morning sector.