Volume 5, Issue 4, August 2016, Page: 48-55
A Comprehensive Analysis of a Heavy Precipitation Event in Chengdu Plain (China) Based on Ground-Based GPS
Wang Hao, College of Meteorological Observation, Chengdu University of Information Technology, Chengdu, China
Wang Yue, Meteorological Service Center, Chengdu Meteorological Bureau, Chengdu, China
Wang Yongqian, College of Resources and Environment, Chengdu University of Information Technology, Chengdu, China
Received: Aug. 3, 2016;       Accepted: Aug. 11, 2016;       Published: Aug. 31, 2016
DOI: 10.11648/j.earth.20160504.11      View  3018      Downloads  102
Abstract
This study utilized the ground-based GPS water vapor monitoring network in the Chengdu Plain (102.9°–104.9°E, 30.1°–31.4°N), alongside radiosonde data and National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data, to conduct a comprehensive analysis of a heavy precipitation event in this region in 2008. Correlations were found between the GPS precipitable water vapor (GPS-PWV) variations, the actual precipitation in the region, and the physical mechanism for the GPS-PWV variations. The research results indicate that the variation trends in precipitable water vapor had a significant correlation with actual precipitation. The precipitable water vapor increased and decreased significantly before and after the precipitation event, respectively. The residence time of precipitable water vapor at high levels was correlated with the duration of actual precipitation to some extent. The maximum value of the precipitation intensity lagged behind the precipitable water vapor peak, which brought forward precipitation to a certain degree. A strong ascending motion of the air was linked to increases in PWV, and the intensity of the ascending motion was strongly correlated with GPS-PWV. Different atmospheric thermodynamic conditions also had a notable effect on GPS-PWV variations.
Keywords
Ground-Based GPS, Precipitable Water Vapor, Heavy Precipitation, Dynamic Conditions, Thermodynamic Conditions
To cite this article
Wang Hao, Wang Yue, Wang Yongqian, A Comprehensive Analysis of a Heavy Precipitation Event in Chengdu Plain (China) Based on Ground-Based GPS, Earth Sciences. Vol. 5, No. 4, 2016, pp. 48-55. doi: 10.11648/j.earth.20160504.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
J. T. Kiehl and K. E. Trenberth, “Earth’s annual global mean energy budget,” Bull. Am. Meteor. Soc., vol. 78, pp. 197–208, 1997.
[2]
H. Wang, M. We, G. Li, S. Zhou, and Q. Zeng, “Analysis of precipitable water vapor from GPS measurements in Chengdu region: Distribution and evolution characteristics in autumn,” Advances in Space Research, vol. 52, pp. 656–667, 2013.
[3]
G. Li and J. Deng, “Atmospheric water monitoring by using ground-based GPS during heavy rains produced by TPV and SWV,” Adv. Meteorol. 2013, doi:10.1155/2013/793957.
[4]
G. Li, D. Huang, J. Guo, G. Li, L. Hao, and H. Wang, Ground-based GPS meteorology, Science Press, Beijing, 2010, pp. 1-346. (in Chinese)
[5]
V. Sibylle, D. Reinhard, R. Axel, and F. Mathias, “Validation of precipitable water vapor within the NCEP/DOE reanalysis using global GPS observations from one decade,” J. Climate, vol. 23, pp. 1675–1695, 2010.
[6]
M. Bevis, S. Businger, and T. Herring, “GPS Meteorology: Remote sensing of atmospheric water vapor using the Global Positioning System,” J. Geophys. Res., vol. 97, pp. 15787–15801, 1992.
[7]
H. Wang, J. He, M. Wei, Z. Zhang, and S. Tang, “Synthesis analysis of one severe convection precipitation event in Jiangsu using ground-based GPS technology,” Atmos., vol. 6 (7), pp. 908–927, 2015.
[8]
Y. Li, B. Xu, X. Hu, and P. He, “Test and study of the earth-based GPS technique for remote sensing of atmospheric precipitable water,” J. Appl. Meteor. Sci., vol. 12 (1), pp. 61–69, 2001. (in Chinese)
[9]
Q. Ye, L. Yang, J. Ding, Y. Lu, X. Xu, H. Yi, J. Zhu, and X. Liu, “Application of GPS/PWV data to forecast strong convection weather in Shanghai,” Torrential Rain and Disasters, vol. 27 (2), pp. 141–148, 2008.
[10]
B. Radhakrishna, F. Fabry, J. Braun, and T. Hove, “Precipitable water from GPS over the continental United States: diurnal cycle, intercomparisons with NARR, and link with convective initiation,” J. Clim., vol. 28, pp. 2584–2599, 2015.
[11]
A. Moore, I. Small, S. Gutman, Y. Bock, J. Dumas, P. Fang, J. Haase, M. Jackson, and J. Laber, “National weather service forecasters use GPS precipitable water vapor for enhanced situational awareness during the southern California summer monsoon,” Bull. Amer. Meteor. Soc., vol. 96, pp. 1879–1894, 2015.
[12]
R. Kevin and F. Anthony, “Three-dimensional UAV-based atmospheric tomography,” J. Atmos. Ocean. Tech., vol. 30, pp. 336–344, 2013.
[13]
L. P. Gradinarsky and P. Jarlemark, “Ground-based GPS tomography of water vapor: analysis of simulated and real data,” J. Meteor. Soc. JPN., vol. 82 (1B), pp. 551–560, 2004.
[14]
H. Wang and G. Li, “Construction and Application about the Monitoring System of Water Vapor Derived from Ground-based GPS in Chengdu,” J. Geo-Info. Sci., vol. 13 (2), pp. 213–218, 2011. (in Chinese)
[15]
C. R. Rocken, H. T. Van, and M. Johnson, “GPS/STORM-GPS sensing of atmospheric water vapor for meteorology,” J. Atmos. Ocean. Tech., vol. 12, pp. 468–478, 1995.
[16]
G. Elgered, J. L. Davis, and T. A. Herring, “Geodesy by radio interferometry: water vapor radiometry for estimation of the wet delay,” J. Geophys. Res., vol. 96, pp. 6541–6555, 1991.
[17]
M. Bevis, S. Businger, and T. A. Herring, “GPS Meteorology: Remote sensing of atmospheric water vapor using the Global Positioning System,” J. Geophys. Res., vol. 97, pp. 1578-15801, 1992.
[18]
J. Guo, G. Li, and D. Huang, “Establish local model for weighted mean temperature of the troposphere based on 40a radiosonde data in Chengdu and Chongqing region,” J. Wuhan Univ. (Inf. Sci.), vol. 33, pp. 43–46, 2008.
[19]
H. Wang, M. Wei, G. Li, S. Zhou, and Q. Zeng, “Analysis of precipitable water vapor from GPS measurements in Chengdu region: Distribution and evolution characteristics in autumn,” Adv. Space Res., vol. 52, pp. 656–667, 2013.
[20]
E. Kalnay, M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L Gandin, M. Iredell, S. Saha, G White, and J. Woollen, “The NCEP/NCAR 40-year reanalysis project,” Bull. Am. Meteorol. Soc. Vol. 77, pp. 437–471, 1996.
[21]
H. Wang, M. Wei, and S. Zhou, “A feasibility study for the construction of an atmospheric precipitable water vapor model based on the neural network technology,” Desalin. Water. Treat., 52 (37–39), pp. 7412–7421, 2014.
[22]
H. Wang, D. Wang, and G. Li, “A method of inserting and mending for the GPS precipitable water vapor,” 2011 International Conference on Multimedia Technology, pp. 3350–3353, 2011.
[23]
H. Wang, G. Chen, H. Lei, Y. Wang, and S. Tang, “Improving the Predictability of Severe Convective Weather Processes by Using Wind Vectors and Potential Temperature Changes: A Case Study of a Severe Thunderstorm,” Adv. Meteorol., DOI 10.1155/2016/8320189, 2016.
Browse journals by subject