Zobrazeno 1 - 10
of 133
pro vyhledávání: '"Chenbo Xie"'
Publikováno v:
Photonics, Vol 11, Iss 6, p 510 (2024)
Due to the complex and variable nature of the atmospheric conditions, traditional multi-wavelength differential absorption lidar (DIAL) methods often suffer from significant errors when inverting ozone concentrations. As the detection range increases
Externí odkaz:
https://doaj.org/article/1fb10cd30ab94f8882b85a15c919aed7
Publikováno v:
Photonics, Vol 11, Iss 5, p 398 (2024)
In the study of atmospheric wind fields from the upper troposphere to the stratosphere (10 km to 50 km), direct detection wind LiDAR is considered a promising method that offers high-precision atmospheric wind field data. In 2020, Xie et al. of the A
Externí odkaz:
https://doaj.org/article/0617be4c265d4899bfbb5c2001cde285
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1571 (2024)
Over the past three decades, China has seen aerosol levels substantially surpass the global average, significantly impacting regional climate. This study investigates the long-term and seasonal variations of aerosols in the Huai River Basin (HRB) usi
Externí odkaz:
https://doaj.org/article/abda9c839aa7407496d06db3e4df6e29
Publikováno v:
Remote Sensing, Vol 16, Iss 6, p 1076 (2024)
The Fabry–Perot interferometer (FPI) plays a crucial role as the frequency discriminator in the incoherent Doppler wind lidar. However, in the practical receiver system, reflections occurring between optical elements introduce non-normal incident c
Externí odkaz:
https://doaj.org/article/c63f78ce3a7c447599adffd77c2f13fe
Publikováno v:
Results in Physics, Vol 43, Iss , Pp 106050- (2022)
This paper explores the effects of different factors on the results and accuracy of aerosol optical property measurements made in overlap factor regions using scanning lidar, simulation calculations and aerosol detection experiments. First, the measu
Externí odkaz:
https://doaj.org/article/77e7fea411034c14af1db5087385e1c2
Publikováno v:
Archives of Environmental Protection, Vol 47, Iss 3, Pp 98-107 (2021)
The prediction of PM2.5 is important for environmental forecasting and air pollution control. In this study, four machine learning methods, ground-based LiDAR data and meteorological data were used to predict the ground-level PM2.5 concentrations in
Externí odkaz:
https://doaj.org/article/9e3208ae1d0b417397370e5853c1f8af
Publikováno v:
Remote Sensing, Vol 15, Iss 12, p 3046 (2023)
To provide references for the design of the lab’s upcoming prototype of the compact spaceborne lidar with a high-repetition-rate laser (CSLHRL), in this paper, the detection signal of spaceborne lidar was simulated by the measured signal of ground-
Externí odkaz:
https://doaj.org/article/8d488bc2d3ea49ef9cc755d714f0fb41
Publikováno v:
Remote Sensing, Vol 15, Iss 4, p 952 (2023)
This paper investigates the transmitter and receiver performance of an active rotating tropospheric stratospheric Doppler wind Lidar. A 532 nm laser was determined as the detection wavelength based on transmission and scattering aspects. A ten-fold G
Externí odkaz:
https://doaj.org/article/281c6f69f55948f4af7b906bfec65008
Autor:
Ming Zhao, Chenbo Xie, Bangxin Wang, Kunming Xing, Jianfeng Chen, Zhiyuan Fang, Lu Li, Liangliang Cheng
Publikováno v:
Remote Sensing, Vol 14, Iss 21, p 5556 (2022)
A Doppler lidar mounted on a rotary platform has been developed for measuring wind fields in the upper troposphere and stratosphere. The rotating platform was used to support a large system for the detection of wind velocities of sight (VOS) in four
Externí odkaz:
https://doaj.org/article/8a05de5e4a744a3382bd80cc4c28453b
Autor:
Hao Yang, Zhiyuan Fang, Ye Cao, Chenbo Xie, Tian Zhou, Bangxin Wang, Kunming Xing, Simone Lolli
Publikováno v:
Earth and Space Science, Vol 8, Iss 3, Pp n/a-n/a (2021)
Abstract Dust storms pose a serious threat to air quality and public health through large‐scale, long‐distance transport. In early April 2018, two severe dust storm events occurred in the Taklimakan and Gobi Deserts in northwestern China. The adv
Externí odkaz:
https://doaj.org/article/2fee6e8bd20745938dd397c2a88b521c