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Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau
- Source :
- Remote Sensing, Vol 8, Iss 3, p 268 (2016), Remote Sensing; Volume 8; Issue 3; Pages: 268, Remote sensing, 8(3):268. MDPI
- Publication Year :
- 2016
- Publisher :
- MDPI AG, 2016.
-
Abstract
- The inter-comparison of different soil moisture (SM) products over the Tibetan Plateau (TP) reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with the in situ measured data climatology. In this study, the in situ soil moisture networks, combined with the classification of climate zones over the TP, were used to produce the in situ measured SM climatology at the plateau scale. The generated TP scale in situ SM climatology was then used to scale the model-simulated SM data, which was subsequently used to scale the SM satellite observations. The climatology-scaled satellite and model-simulated SM were then blended objectively, by applying the triple collocation and least squares method. The final blended SM can replicate the SM dynamics across different climatic zones, from sub-humid regions to semi-arid and arid regions over the TP. This demonstrates the need to constrain the model-simulated SM estimates with the in situ measurements before their further applications in scaling climatology of SM satellite products.
- Subjects :
- In situ
010504 meteorology & atmospheric sciences
Science
0208 environmental biotechnology
triple collocation
02 engineering and technology
Atmospheric sciences
01 natural sciences
climatic zones
AMSRE
Tibetan Plateau
ERA-Interim
Water content
Scaling
0105 earth and related environmental sciences
Remote sensing
soil moisture
Tibet-Obs
ASCAT
geography
Plateau
geography.geographical_feature_category
Simulation modeling
Arid
020801 environmental engineering
ITC-ISI-JOURNAL-ARTICLE
Soil water
General Earth and Planetary Sciences
Environmental science
Satellite
ITC-GOLD
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 8
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....212f795a63db2e6ebef5b659031f714c