Prospects for Imaging Terrestrial Water Storage in South America Using Daily GPS Observations
Autor: | Bin Yong, Henry Montecino, Vagner G. Ferreira, Peng Yuan, Abubakar S. Mohammed, Ahmed Abdalla, Christopher E. Ndehedehe |
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Rok vydání: | 2019 |
Předmět: |
010504 meteorology & atmospheric sciences
Correlation coefficient Mean squared error GPS drought 010502 geochemistry & geophysics 01 natural sciences hydrologic loading Data assimilation GRACE ddc:550 lcsh:Science Terrestrial water storage 0105 earth and related environmental sciences business.industry crustal deformation Inversion (meteorology) Geodesy Earth sciences Gps data Global Positioning System General Earth and Planetary Sciences Environmental science lcsh:Q business Amazon basin |
Zdroj: | Remote Sensing, Vol 11, Iss 6, p 679 (2019) Remote Sensing Volume 11 Issue 6 Pages: 679 Remote sensing, 11 (6), 679 |
ISSN: | 2072-4292 |
DOI: | 10.3390/rs11060679 |
Popis: | Few studies have used crustal displacements sensed by the Global Positioning System (GPS) to assess the terrestrial water storage (TWS), which causes loadings. Furthermore, no study has investigated the feasibility of using GPS to image TWS over South America (SA), which contains the world’s driest (Atacama Desert) and wettest (Amazon Basin) regions. This work presents a resolution analysis of an inversion of GPS data over SA. Firstly, synthetic experiments were used to verify the spatial resolutions of GPS-imaged TWS and examine the resolving accuracies of the inversion based on checkerboard tests and closed-loop simulations using “TWS„ from the Noah-driven Global Land Data Assimilation System (GLDAS-Noah). Secondly, observed radial displacements were used to image daily TWS. The inverted results of TWS at a resolution of 300 km present negligible errors, as shown by synthetic experiments involving 397 GPS stations across SA. However, as a result of missing daily observations, the actual daily number of available stations varied from 60–353, and only 6% of the daily GPS-imaged TWS agree with GLDAS-Noah TWS, which indicates a root-mean-squared error (RMSE) of less than 100 kg/m 2 . Nevertheless, the inversion shows agreement that is better than 0.50 and 61.58 kg/m 2 in terms of the correlation coefficient (Pearson) and RMSE, respectively, albeit at each GPS site. |
Databáze: | OpenAIRE |
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