Evaluation of Precipitable Water Vapor from Four Satellite Products and Four Reanalysis Datasets against GPS Measurements on the Southern Tibetan Plateau | |
Wang, Y (Wang, Yan)1,2; Yang, K (Yang, Kun)1,3,4; Pan, ZY (Pan, Zhengyang)1,2; Qin, J (Qin, Jun)1; Chen, DL (Chen, Deliang)5; Lin, CG (Lin, Changgui)5; Chen, YY (Chen, Yingying)1,4; Lazhu (Lazhu)1,2; Tang, WJ (Tang, Wenjun)1,4; Han, ML (Han, Menglei)3; Lu, N (Lu, Ning)6; Wu, H (Wu, Hui)7; Yang, K | |
Source Publication | JOURNAL OF CLIMATE |
2017 | |
Volume | 30Issue:15Pages:5699-5713 |
DOI | 10.1175/JCLI-D-16-0630.1 |
Abstract | The southern Tibetan Plateau (STP) is the region in which water vapor passes from South Asia into the Tibetan Plateau (TP). The accuracy of precipitable water vapor (PWV) modeling for this region depends strongly on the quality of the available estimates of water vapor advection and the parameterization of land evaporation models. While climate simulation is frequently improved by assimilating relevant satellite and reanalysis products, this requires an understanding of the accuracy of these products. In this study, PWV data from MODIS infrared and near-infrared measurements, AIRS Level-2 and Level-3, MERRA, ERA-Interim, JRA-55, and NCEP final reanalysis (NCEP-Final) are evaluated against ground-based GPS measurements at nine stations over the STP, which covers the summer monsoon season from 2007 to 2013. The MODIS infrared product is shown to underestimate water vapor levels by more than 20% (1.84 mm), while the MODIS near-infrared product overestimates them by over 40% (3.52 mm). The AIRS PWV product appears to be most useful for constructing high-resolution and high-quality PWV datasets over the TP; particularly the AIRS Level-2 product has a relatively low bias (0.48 mm) and RMSE (1.83 mm) and correlates strongly with the GPS measurements (R = 0.90). The four reanalysis datasets exhibit similar performance in terms of their correlation coefficients (R = 0.87-0.90), bias (0.72-1.49 mm), and RMSE (2.19-2.35 mm). The key finding is that all the reanalyses have positive biases along the PWV seasonal cycle, which is linked to the well-known wet bias over the TP of current climate models. |
Subject Area | 自然地理学 |
WOS ID | WOS:000405470400006 |
Language | 英语 |
Indexed By | SCI |
Keyword | Asian Summer Monsoon Diurnal-variation Climate Models Era-interim System Cycle Retrievals Transport Rainfall Moisture |
WOS Research Area | Meteorology & Atmospheric Sciences |
WOS Subject | Meteorology & Atmospheric Sciences ; Meteorology & Atmospheric Sciences |
Cooperation Status | 国际 |
Subtype | Article |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.itpcas.ac.cn/handle/131C11/8018 |
Collection | 图书馆 |
Corresponding Author | Yang, K |
Affiliation | 1.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing, Peoples R China. 2.Univ Chinese Acad Sci, Beijing, Peoples R China. 3.Tsinghua Univ, Dept Earth Syst Sci, Beijing, Peoples R China. 4.Chinese Acad Sci, Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China. 5.Univ Gothenburg, Dept Earth Sci, Reg Climate Grp, Gothenburg, Sweden. 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China. 7.Chinese Acad Meteorol Sci, Beijing, Peoples R China. |
Recommended Citation GB/T 7714 | Wang, Y ,Yang, K ,Pan, ZY ,et al. Evaluation of Precipitable Water Vapor from Four Satellite Products and Four Reanalysis Datasets against GPS Measurements on the Southern Tibetan Plateau[J]. JOURNAL OF CLIMATE,2017,30(15):5699-5713. |
APA | Wang, Y .,Yang, K .,Pan, ZY .,Qin, J .,Chen, DL .,...&Yang, K.(2017).Evaluation of Precipitable Water Vapor from Four Satellite Products and Four Reanalysis Datasets against GPS Measurements on the Southern Tibetan Plateau.JOURNAL OF CLIMATE,30(15),5699-5713. |
MLA | Wang, Y ,et al."Evaluation of Precipitable Water Vapor from Four Satellite Products and Four Reanalysis Datasets against GPS Measurements on the Southern Tibetan Plateau".JOURNAL OF CLIMATE 30.15(2017):5699-5713. |
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