Spatial Interpolation of Atmospheric Weighted Mean Temperature Grid Products in China with Consideration of Vertical Lapse Rate

HUANG Liangke; LI Chen; XIE Shaofeng; LIU Lilong; CHEN Jun; LI Junyu

doi:10.13203/j.whugis20200304

Volume 48 Issue 2

Feb. 2023

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2023 > 48(2): 295-300. > DOI: 10.13203/j.whugis20200304

HUANG Liangke, LI Chen, XIE Shaofeng, LIU Lilong, CHEN Jun, LI Junyu. Spatial Interpolation of Atmospheric Weighted Mean Temperature Grid Products in China with Consideration of Vertical Lapse Rate[J]. Geomatics and Information Science of Wuhan University, 2023, 48(2): 295-300. DOI: 10.13203/j.whugis20200304

Citation:

PDF (9185 KB)

Spatial Interpolation of Atmospheric Weighted Mean Temperature Grid Products in China with Consideration of Vertical Lapse Rate

HUANG Liangke^{1, 2,},
LI Chen¹,
XIE Shaofeng^{1, 2, ,},
LIU Lilong^{1, 2},
CHEN Jun³,
LI Junyu^{1, 2, 3}

1.
College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541006, China
2.
Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541006, China
3.
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China

More Information

Received Date: July 30, 2021
Available Online: February 16, 2023
Published Date: February 04, 2023

Graphical Abstract

Abstract

Abstract

Objectives Atmospheric weighted mean temperature (T_m) is a key parameter of global navigation satellite system (GNSS) to retrieve precipitable water vapor (PWV). Currently, the T_m information provided by the existing T_m model is hard to capture its diurnal cycle variation, thus its application in high time resolution GNSS PWV estimation is limited. Atmospheric reanalysis data can provide T_m grid products with high spatial and temporal resolution, but they need to be spatially adjusted when used, and the variation of T_m in elevation is much greater than that in horizontal direction.
Methods Moreover, for the highly undulating terrain in China, a spatial interpolation method which considering the vertical lapse rate is proposed for T_m grid products in China. The proposed method is verified with the global geodetic observing system (GGOS) atmosphere T_m grid product and the MERRA‑2 T_m grid product provided by national aeronautics and space administration using the data of 89 radiosonde stations distributed in China as reference values.
Results The results show that: (1) In spatial interpolation of T_m grid products considering vertical lapse rate, the performance of inverse distance weighted method is better than that of bilinear interpolation method, and the biases of the T_m grid products of GGOS atmospheric center and MERRA‑2 in China are 0.72 K and 0.23 K, respectively, and the root mean square errors are 1.94 K and 1.87 K, respectively. (2) The performance of spatial interpolation which considering the vertical lapse rate is significantly better than that without vertical lapse rate, especially in western China where the terrain is undulating.
Conclusions Therefore, the spatial interpolation method which considering the vertical lapse rate has important applications in high-precision and high-resolution GNSS water vapor remote sensing for China.

FullText(HTML)

References (11)

References

[1]	Jin S G, Luo O F. Variability and Climatology of PWV from Global 13-Year GPS Observations[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(7): 1918-1924. doi: 10.1109/TGRS.2008.2010401
[2]	Zhao Q Z, Yao Y B, Yao W Q. GPS-Based PWV for Precipitation Forecasting and Its Application to a Typhoon Event[J]. Journal of Atmospheric and Solar‑Terrestrial Physics, 2018, 167: 124-133. doi: 10.1016/j.jastp.2017.11.013
[3]	Suparta W, Rahman R. Spatial Interpolation of GPS PWV and Meteorological Variables over the West Coast of Peninsular Malaysia During 2013 Klang Valley Flash Flood[J]. Atmospheric Research, 2016, 168: 205-219. doi: 10.1016/j.atmosres.2015.09.023
[4]	Bevis M, Businger S, Chiswell S, et al. GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water[J]. Journal of Applied Meteorology, 1994, 33(3): 379-386. doi: 10.1175/1520-0450(1994)033<0379:GMMZWD>2.0.CO;2
[5]	Bevis M, Businger S, Herring T, et al. GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System[J]. Journal of Geophysical Research, 1992, 97(D14): 15787. doi: 10.1029/92JD01517
[6]	Huang L K, Jiang W P, Liu L L, et al. A New Global Grid Model for the Determination of Atmospheric Weighted Mean Temperature in GPS Precipitable Water Vapor[J]. Journal of Geodesy, 2019, 93(2): 159-176. doi: 10.1007/s00190-018-1148-9
[7]	赵静旸, 宋淑丽, 朱文耀. ERA-Interim应用于中国地区地基GPS/PWV计算的精度评估[J]. 武汉大学学报(信息科学版), 2014, 39(8): 935-939. doi: 10.13203/j.whugis20120006 Zhao Jingyang, Song Shuli, Zhu Wenyao. Accuracy Assessment of Applying ERA-Interim Reanalysis Data to Calculate Ground-Based GPS/PWV over China[J]. Geomatics and Information Science of Wuhan University, 2014, 39(8): 935-939. doi: 10.13203/j.whugis20120006
[8]	许超钤, 姚宜斌, 张豹, 等. GGOS Atmosphere大气加权平均温度数据的精度检验与分析[J]. 测绘地理信息, 2014, 39(4): 13-16. https://www.cnki.com.cn/Article/CJFDTOTAL-CHXG201404005.htm Xu Chaoqian, Yao Yibin, Zhang Bao, et al. Accuracy Analysis and Test on the Weighted Mean Temperature of the Atmosphere Grid Data Offered by GGOS Atmosphere[J]. Journal of Geomatics, 2014, 39(4): 13-16. https://www.cnki.com.cn/Article/CJFDTOTAL-CHXG201404005.htm
[9]	Huang L, Liu L, Chen H, et al. An Improved Atmospheric Weighted Mean Temperature Model and Its Impact on GNSS Precipitable Water Vapor Estimates for China[J]. GPS Solutions, 2019, 23(2): 51. doi: 10.1007/s10291-019-0843-1
[10]	姚宜斌, 张豹, 许超钤, 等. T_m-T_s的相关性分析及全球纬度相关的线性关系模型构建[J]. 科学通报, 2014, 59(9): 816-824. https://www.cnki.com.cn/Article/CJFDTOTAL-KXTB201409011.htm Yao Yibin, Zhang Bao, Xu Chaoqian, et al. Correlation Analysis of T_m-T_s and Construction of Linear Relationship Model Related to Global Latitude[J]. Chinese Science Bulletin, 2014, 59(9): 816-824. https://www.cnki.com.cn/Article/CJFDTOTAL-KXTB201409011.htm
[11]	黄良珂, 彭华, 刘立龙, 等. 顾及垂直递减率函数的中国区域大气加权平均温度模型[J]. 测绘学报, 2020, 49(4): 432-442. https://www.cnki.com.cn/Article/CJFDTOTAL-CHXB202004004.htm Huang Liangke, Peng Hua, Liu Lilong, et al. An Empirical Atmospheric Weighted Mean Temperature Model Considering the Lapse Rate Function for China[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(4): 432-442. https://www.cnki.com.cn/Article/CJFDTOTAL-CHXB202004004.htm

[1]	NIU Quanfu, LIU Mingzhi, ZHANG Man, CHENG Weiming. Vegetation Dynamic Change and Its Response to Climate and Topography in Altay Region of Xinjiang in Recent 20 Years[J]. Geomatics and Information Science of Wuhan University, 2023, 48(9): 1522-1530. DOI: 10.13203/j.whugis20210189
[2]	ZHANG Chen, HE Biao, GUO Renzhong, MA Ding, CHEN Yebin. A Data Conversion Method from Oblique Photogrammetric 3D Models to Renderable Assets in Unreal Engine 4[J]. Geomatics and Information Science of Wuhan University, 2023, 48(4): 514-524. DOI: 10.13203/j.whugis20210574
[3]	WANG Pengxin, CHEN Chi, ZHANG Yue, ZHANG Shuyu, LIU Junming. Estimation of Winter Wheat Yield Using Assimilated Bi-variables and PCA-Copula Method[J]. Geomatics and Information Science of Wuhan University, 2022, 47(8): 1201-1212. DOI: 10.13203/j.whugis20220038
[4]	LEI Lei, LI Zhenhong, YANG Hao, YANG Guijun. Extraction of the Leaf Area Density of Maize Using UAV-LiDAR Data[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1737-1745. DOI: 10.13203/j.whugis20200674
[5]	YU Ying, SONG Zhangliang, FAN Wenyi, YANG Xiguang. Scale Conversion from Canopy Spectra to Leaf Spectra[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1560-1565, 1573. DOI: 10.13203/j.whugis20160552
[6]	QIN Zhanfei, SHEN Jian, XIE Baoni, YAN Lin, CHANG Qingrui. Hyperspectral Estimation Model for Predicting LAI of Rice in Ningxia Irrigation Zone[J]. Geomatics and Information Science of Wuhan University, 2017, 42(8): 1159-1166. DOI: 10.13203/j.whugis20150132
[7]	ZHANG Xun, ZHONG Ershun, ZHANG Xiaohu, WANG Shaohua, LI Shaojun. A Modified Algorithm to Construct Gridded Area Cartogramsby Scale Effect Index[J]. Geomatics and Information Science of Wuhan University, 2015, 40(8): 1100-1104. DOI: 10.13203/j.whugis20130370
[8]	LIU　Hui. Extraction　of 　the　Floor　Area　Ratio　in 　the　Central　District 　of 　Fuzhou　Cit y Based　on　an　Improved　Shadow　Index　Model[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10): 1241-1247.
[9]	XIONG Jinguo, WANG Shixin, ZHOU Yi, Yan Fuli. Influence of Landscape Pattern Index on the Area Extracted from ETM~+ and MODIS[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 98-103.
[10]	WANG Xiaohong, LIU Yaolin, DU Xiao. Drought Monitoring Using Vegetation Leaf Water in China[J]. Geomatics and Information Science of Wuhan University, 2007, 32(6): 498-501.

Cited By

Get Citation

PDF

XML

Article views (474) PDF downloads (72)

Spatial Interpolation of Atmospheric Weighted Mean Temperature Grid Products in China with Consideration of Vertical Lapse Rate

Abstract

References

Related Articles

Catalog

Related

Spatial Interpolation of Atmospheric Weighted Mean Temperature Grid Products in China with Consideration of Vertical Lapse Rate

Abstract

References

Related Articles

Catalog

Related

Export File

Citation

Format

Content