Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite

Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite

Special issue Ten Years of Remote Sensing at Barcelona Expert Center.-- 21 pages, 12 figures, 2 tables

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Main Authors: Piles, María, Ballabrera-Poy, Joaquim, Muñoz-Sabater, J.
Format: artículo biblioteca
Published: Multidisciplinary Digital Publishing Institute 2019-01
Subjects:Climatology, SMOS, Soil moisture, Trends, Signal decomposition,
Online Access:http://hdl.handle.net/10261/176294
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spelling dig-icm-es-10261-1762942020-12-13T09:26:14Z Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite Piles, María Ballabrera-Poy, Joaquim Muñoz-Sabater, J. Climatology SMOS Soil moisture Trends Signal decomposition Special issue Ten Years of Remote Sensing at Barcelona Expert Center.-- 21 pages, 12 figures, 2 tables 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 Peer Reviewed 2019-02-18T12:09:20Z 2019-02-18T12:09:20Z 2019-01 2019-02-18T12:09:21Z artículo http://purl.org/coar/resource_type/c_6501 doi: 10.3390/rs11010095 issn: 2072-4292 e-issn: 2072-4292 Remote Sensing 11(1): 95 (2019) http://hdl.handle.net/10261/176294 10.3390/rs11010095 Publisher's version https://dx.doi.org/10.3390/rs11010095 Sí open Multidisciplinary Digital Publishing Institute
institution ICM ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-icm-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del ICM España
topic Climatology
SMOS
Soil moisture
Trends
Signal decomposition
Climatology
SMOS
Soil moisture
Trends
Signal decomposition
spellingShingle Climatology
SMOS
Soil moisture
Trends
Signal decomposition
Climatology
SMOS
Soil moisture
Trends
Signal decomposition
Piles, María
Ballabrera-Poy, Joaquim
Muñoz-Sabater, J.
Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite
description Special issue Ten Years of Remote Sensing at Barcelona Expert Center.-- 21 pages, 12 figures, 2 tables
format artículo
topic_facet Climatology
SMOS
Soil moisture
Trends
Signal decomposition
author Piles, María
Ballabrera-Poy, Joaquim
Muñoz-Sabater, J.
author_facet Piles, María
Ballabrera-Poy, Joaquim
Muñoz-Sabater, J.
author_sort Piles, María
title Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite
title_short Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite
title_full Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite
title_fullStr Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite
title_full_unstemmed Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite
title_sort dominant features of global surface soil moisture variability observed by the smos satellite
publisher Multidisciplinary Digital Publishing Institute
publishDate 2019-01
url http://hdl.handle.net/10261/176294
work_keys_str_mv AT pilesmaria dominantfeaturesofglobalsurfacesoilmoisturevariabilityobservedbythesmossatellite
AT ballabrerapoyjoaquim dominantfeaturesofglobalsurfacesoilmoisturevariabilityobservedbythesmossatellite
AT munozsabaterj dominantfeaturesofglobalsurfacesoilmoisturevariabilityobservedbythesmossatellite
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