Point cloud registration, as the first step for the use of point cloud data, has attracted increasing attention. In order to obtain the entire point cloud of a scene, the registration of point clouds from multiple views is necessary. In this paper, we propose an automatic method for the coarse registration of point clouds. The 2D lines are first extracted from the two point clouds being matched. Then, the line correspondences are established and the 2D transformation is calculated. Finally, a method is developed to calculate the displacement along the z-axis. With the 2D transformation and displacement, the 3D transformation can be easily achieved. Thus, the two point clouds are aligned together. The experimental results well demonstrate that our method can obtain high-precision registration results and is computationally very efficient. In the experimental results obtained by our method, the biggest rotation error is 0.5219^o, and the biggest horizontal and vertical errors are 0.2319 m and 0.0119 m, respectively. The largest total computation time is only 713.4647 s.

The upper tropospheric water vapor is a key component of Earth's climate. Understanding variations in upper tropospheric water vapor and identifying its influencing factors is crucial for enhancing our comprehension of global climate change. While many studies have shown the impact of El Niño-Southern Oscillation (ENSO) and global warming on water vapor, how they affect the upper tropospheric water vapor remains unclear. Long-term, high-precision ERA5 specific humidity data from the European Centre for Medium-Range Weather Forecasts (ECMWF) provided the data foundation for this study. On this basis, we successfully obtained the patterns of global warming (Independent Component 1, IC1) and ENSO (Independent Component 2, IC2) by employing the strategy of independent component analysis (ICA) combined with non-parametric optimal dimension selection to investigate the upper tropospheric water vapor variations and responses to ENSO and global warming. The results indicate that global warming and ENSO are the primary factors contributing to water vapor variations in the upper troposphere, achieving the significant correlations of 0.87 and 0.61 with water vapor anomalies respectively. Together, they account for 86% of the global interannual variations in water vapor. Consistent with previous studies, our findings also find positive anomalies in upper tropospheric water vapor during El Niño years and negative anomalies during La Niña years. Moreover, the influence extent of ENSO on upper tropospheric water vapor varies with the changing seasons.

Objectives: To explore the pathology, diagnosis, therapeutic strategies and prognosis of primary temporal inverted papilloma.Methods: We present one of the first reported cases of primary temporal inverted papilloma with premalignant change. The available data are reviewed.Results: To the best of our knowledge, only 10 evaluable cases of this tumour have been reported. The recurrence rate is higher for this tumour than for sinonasal inverted papilloma.Conclusion: Primary temporal inverted papilloma is extremely rare, and its diagnosis should be made only following clinical exclusion of sinonasal papilloma. Therapy mainly comprises radical resection of the lesion, and long-term post-operative follow up is mandatory.

Zenith hydrostatic delay (ZHD) is a crucial parameter in Global Navigation Satellite System (GNSS) navigation and positioning and GNSS meteorology. Since the Saastamoinen ZHD model has a larger error in China, it is significant to improve the Saastamoinen ZHD model. This work first estimated the Saastamoinen model using the integrated ZHD as reference values obtained from radiosonde data collected at 73 stations in China from 2012 to 2016. Then, the residuals between the reference values and the Saastamoinen modeled ZHDs were calculated, and the correlations between the residuals and meteorological parameters were explored. The continuous wavelet transform method was used to recognize the annual and semiannual characteristics of the residuals. Because of the nonlinear variation characteristics of residuals, the nonlinear least squares estimation method was introduced to establish an improved ZHD model—China Revised Zenith Hydrostatic Delay (CRZHD)—adapted for China. The accuracy of the CRZHD model was assessed using radiosonde data and International GNSS Service (IGS) data in 2017; the radiosonde data results show that the CRZHD model is superior to the Saastamoinen model with a 69.6% improvement. The three IGS stations with continuous meteorological data present that the BIAS and RMSE are decreased by 2.7 and 1.5 (URUM), 5.9 and 5.3 (BJFS), and 9.6 and 8.8 mm (TCMS), respectively. The performance of the CRZHD model retrieving PWV was discussed using radiosonde data in 2017. It is shown that the CRZHD model retrieving PWV (CRZHD-PWV) outperforms the Saastamoinen model (SAAS-PWV), in which the precision is improved by 44.4%. The BIAS ranged from −1 to 1 mm and RMSE ranged from 0 to 2 mm in CRZHD-PWV account for 89.0% and 95.9%, while SAAS-PWV account for 46.6% and 58.9%. Significance Statement: Zenith hydrostatic delay (ZHD) is one of the most important parameters in Global Navigation Satellite System (GNSS) navigation and positioning and GNSS meteorology, which can be derived from a precise ZHD model due to its stability. This research established an improved ZHD model for China to obtain accurate ZHD, which is a prerequisite for pinpoint precipitable water vapor (PWV) retrieval. And the PWV value is beneficial to analyze the change in precipitation in some regions, forecast the short-term rainfall, and monitor the climate.

El Niño-Southern Oscillation related signals (ENSORS) in the troposphere and lower stratosphere (TLS) are the prominent source of inter-annual variability in the weather and climate system of the Earth, and are especially important for monitoring El Niño-Southern Oscillation (ENSO). In order to reduce the influence of quasi-biennial oscillations and other unknown signals compared with the traditional empirical orthogonal functions (EOF) method, a new processing strategy involving fusion of a low-pass filter with an optimal filtering frequency (hereafter called the optimal low-pass filter) and EOF is proposed in this paper for the extraction of ENSORS in the TLS. Using this strategy, ENSORS in the TLS over different areas were extracted effectively from the specific humidity profiles provided by the Global Navigation Satellite System (GNSS) radio occultation (RO) of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission from June 2006 to June 2014. The spatial and temporal responses of the extracted ENSORS to ENSO at different altitudes in the TLS were analyzed. The results show that the most suitable areas for extracting ENSORS are over the areas of G25 (−25°S–25°N, 180°W–180°E) −G65(−65°S–65°N, 180°W–180°E) in the upper troposphere (250–200 hpa) which show a lag time of 3 months relative to the Oceanic Niño index (ONI). In the troposphere, ENSO manifests as a major inter-annual variation. The ENSORS extracted from the N3.4 (−5°S to 5°N, 120°W to 170°W) area are responsible for 83.59% of the variability of the total specific humidity anomaly (TSHA) at an altitude of 250 hpa. Over all other defined areas which contain the N3.4 areas, ENSORS also explain the major variability in TSHA. In the lower stratosphere, the extracted ENSORS present an unstable pattern at different altitudes because of the weak ENSO effect. Moreover, the spatial and temporal responses of ENSORS and ONI to ENSO across the globe are in good agreement. Over the areas with strong correlation between ENSORS and ONI, the larger the correlation coefficient is, the shorter the lag time between them. Furthermore, the ENSORS from zonal-mean specific humidity monthly anomalies at different altitudes can clearly present the vertical structure of ENSO in the troposphere. This study provides a new approach for monitoring ENSO events.