Next Article in Journal
Challenges and Opportunities in Remote Sensing-Based Fuel Load Estimation for Wildfire Behavior and Management: A Comprehensive Review
Previous Article in Journal
A Submerged and Buried Mesolithic Site off Svanemøllen Harbor, Copenhagen, Denmark: Acoustic Detection (Human-Altered Lithic Detection) and Verification by Means of Coring
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control

1
Meteorological Observation Center of China Meteorological Administration, Beijing 100081, China
2
Tianjin Meteorological Radar Research and Test Center, Tianjin 300061, China
3
The School of Remote Sensing Information Engineering, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(3), 414; https://doi.org/10.3390/rs17030414
Submission received: 21 November 2024 / Revised: 20 January 2025 / Accepted: 22 January 2025 / Published: 25 January 2025

Abstract

Water vapor is an active trace component in the troposphere and has a significant impact on meteorology and the atmospheric environment. In order to meet demands for high-precision water vapor and aerosol observations for numerical weather prediction (NWP), the China Meteorological Administration (CMA) deployed 49 Raman aerosol lidar systems and established the first Raman–Mie scattering lidar network in China (CARLNET) for routine measurements. In this paper, we focus on the water vapor measurement capabilities of the CARLNET. The uncertainty of the water vapor Raman channel calibration coefficient (Cw) is determined using an error propagation formula. The theoretical relationship between the uncertainty of the calibration coefficient and the water vapor mixing ratio (WVMR) is constructed based on least squares fitting. Based on the distribution of lidar in regions with different humidity conditions, the method of real-time calibration and quality control based on radiosonde data is established for the first time. Based on the uncertainty requirements of the World Meteorological Organization for water vapor in data assimilation, the calibration and quality control thresholds of the WVMR in regions with different humidity conditions are determined by fitting real-time lidar and radiosonde data. Lastly, based on the radiosonde results, the calibration algorithm established in this study is used to calibrate CARLNET data from October to December 2023. Compared with traditional calibration results, the results show that the stability and detection accuracy of the CARLNET significantly improved after calibration in regions with different humidity conditions. The deviation of the Cw decreased from 12.84~18.47% to 5.41~11.54%. The inversion error of the WVMR compared to radiosonde decreased from 1.05~0.46 g/kg to 0.82~0.34 g/kg. The reliability of the improved calibration algorithm and the CARLNET’s performance have been verified, enabling them to provide high-precision water vapor products for NWP.
Keywords: Raman–Mie scattering lidar observation network; water vapor mixing ratio; lidar calibration; quality control Raman–Mie scattering lidar observation network; water vapor mixing ratio; lidar calibration; quality control

Share and Cite

MDPI and ACS Style

Shao, N.; Wang, Q.; Bu, Z.; Yin, Z.; Dai, Y.; Chen, Y.; Wang, X. China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control. Remote Sens. 2025, 17, 414. https://doi.org/10.3390/rs17030414

AMA Style

Shao N, Wang Q, Bu Z, Yin Z, Dai Y, Chen Y, Wang X. China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control. Remote Sensing. 2025; 17(3):414. https://doi.org/10.3390/rs17030414

Chicago/Turabian Style

Shao, Nan, Qin Wang, Zhichao Bu, Zhenping Yin, Yaru Dai, Yubao Chen, and Xuan Wang. 2025. "China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control" Remote Sensing 17, no. 3: 414. https://doi.org/10.3390/rs17030414

APA Style

Shao, N., Wang, Q., Bu, Z., Yin, Z., Dai, Y., Chen, Y., & Wang, X. (2025). China Aerosol Raman Lidar Network (CARLNET)—Part I: Water Vapor Raman Channel Calibration and Quality Control. Remote Sensing, 17(3), 414. https://doi.org/10.3390/rs17030414

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop