Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/176294
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite |
Autor: | Piles, María CSIC ORCID; Ballabrera-Poy, Joaquim CSIC ORCID ; Muñoz-Sabater, J. | Palabras clave: | Climatology SMOS Soil moisture Trends Signal decomposition |
Fecha de publicación: | ene-2019 | Editor: | Multidisciplinary Digital Publishing Institute | Citación: | Remote Sensing 11(1): 95 (2019) | Resumen: | Soil moisture observations are expected to play an important role in monitoring global climate trends. However, measuring soil moisture is challenging because of its high spatial and temporal variability. Point-scale in-situ measurements are scarce and, excluding model-based estimates, remote sensing remains the only practical way to observe soil moisture at a global scale. The ESA-led Soil Moisture and Ocean Salinity (SMOS) mission, launched in 2009, measures the Earth's surface natural emissivity at L-band and provides highly accurate soil moisture information with a 3-day revisiting time. Using the first six full annual cycles of SMOS measurements (June 2010-June 2016), this study investigates the temporal variability of global surface soil moisture. The soil moisture time series are decomposed into a linear trend, interannual, seasonal, and high-frequency residual (i.e., subseasonal) components. The relative distribution of soil moisture variance among its temporal components is first illustrated at selected target sites representative of terrestrial biomes with distinct vegetation type and seasonality. A comparison with GLDAS-Noah and ERA5 modeled soil moisture at these sites shows general agreement in terms of temporal phase except in areas with limited temporal coverage in winter season due to snow. A comparison with ground-based estimates at one of the sites shows good agreement of both temporal phase and absolute magnitude. A global assessment of the dominant features and spatial distribution of soil moisture variability is then provided. Results show that, despite still being a relatively short data set, SMOS data provides coherent and reliable variability patterns at both seasonal and interannual scales. Subseasonal components are characterized as white noise. The observed linear trends, based upon one strong El Niño event in 2016, are consistent with the known El Niño Southern Oscillation (ENSO) teleconnections. This work provides new insight into recent changes in surface soil moisture and can help further our understanding of the terrestrial branch of the water cycle and of global patterns of climate anomalies. Also, it is an important support to multi-decadal soil moisture observational data records, hydrological studies and land data assimilation projects using remotely sensed observations | Descripción: | Special issue Ten Years of Remote Sensing at Barcelona Expert Center.-- 21 pages, 12 figures, 2 tables | Versión del editor: | https://dx.doi.org/10.3390/rs11010095 | URI: | http://hdl.handle.net/10261/176294 | DOI: | 10.3390/rs11010095 | Identificadores: | doi: 10.3390/rs11010095 issn: 2072-4292 e-issn: 2072-4292 |
Aparece en las colecciones: | (ICM) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
Piles_et_al_2019.pdf | 1,35 MB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
29
checked on 08-abr-2024
WEB OF SCIENCETM
Citations
27
checked on 22-feb-2024
Page view(s)
282
checked on 18-abr-2024
Download(s)
256
checked on 18-abr-2024
Google ScholarTM
Check
Altmetric
Altmetric
Este item está licenciado bajo una Licencia Creative Commons