An improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution “all weather” product
<p>This study uses the synergy of multi-resolution soil moisture (SM) satellite estimates from the Soil Moisture Ocean Salinity (SMOS) mission, a dense network of ground-based SM measurements, and a soil–vegetation–atmosphere transfer (SVAT) model, SURFEX (externalized surface), module ISBA (i...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2019-01-01
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Series: | Hydrology and Earth System Sciences |
Online Access: | https://www.hydrol-earth-syst-sci.net/23/255/2019/hess-23-255-2019.pdf |
Summary: | <p>This study uses the synergy of multi-resolution soil moisture (SM) satellite
estimates from the Soil Moisture Ocean Salinity (SMOS) mission, a dense
network of ground-based SM measurements, and a soil–vegetation–atmosphere
transfer (SVAT) model, SURFEX (externalized surface), module ISBA
(interactions between soil, biosphere and atmosphere), to examine the benefits of
the SMOS level 4 (SMOS-L4) version 3.0, or “all weather” high-resolution soil moisture
disaggregated product (SMOS-L4<span class="inline-formula"><sup>3.0</sup></span>; <span class="inline-formula">∼1</span> km).
The added value compared to SMOS level 3 (SMOS-L3; <span class="inline-formula">∼25</span> km) and SMOS level 2 (SMOS-L2; <span class="inline-formula">∼15</span> km) is investigated. In situ SM observations over the
Valencia anchor station (VAS; SMOS calibration and validation – Cal/Val – site in
Europe) are used for comparison. The SURFEX (ISBA) model is used to simulate
point-scale surface SM (SSM) and, in combination with high-quality
atmospheric information data, namely from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Système d'analyse
fournissant des renseignements atmosphériques à la neige (SAFRAN) meteorological
analysis system, to obtain a representative SSM mapping over the VAS. The
sensitivity to realistic initialization with SMOS-L4<span class="inline-formula"><sup>3.0</sup></span> is assessed to simulate the spatial and temporal distribution of SSM.
Results demonstrate the following: (a) All SMOS products correctly capture the temporal
patterns, but the spatial patterns are not accurately reproduced by the
coarser resolutions, probably in relation to the contrast with point-scale in
situ measurements. (b) The potential of the SMOS-L4<span class="inline-formula"><sup>3.0</sup></span> product is pointed
out to adequately characterize SM spatio-temporal variability, reflecting
patterns consistent with intensive point-scale SSM samples on a daily timescale. The restricted temporal availability of this product dictated by the
revisit period of the SMOS satellite compromises the averaged SSM
representation for longer periods than a day. (c) A seasonal analysis points
out improved consistency during December–January–February and
September–October–November, in contrast to significantly worse correlations in
March–April–May (in relation to the growing vegetation) and June–July–August
(in relation to low SSM values < 0.1 m<span class="inline-formula"><sup>3</sup></span> m<span class="inline-formula"><sup>−3</sup></span>
and low spatial
variability). (d) The combined use of the SURFEX (ISBA) SVAT model with the
SAFRAN system, initialized with SMOS-L4<span class="inline-formula"><sup>3.0</sup></span> 1 km disaggregated data, is
proven to be a suitable tool for producing regional SM maps with high
accuracy, which could be used as initial conditions for model simulations, flood
forecasting, crop monitoring and crop development strategies, among others.</p> |
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ISSN: | 1027-5606 1607-7938 |