2010
DOI: 10.5194/hess-14-1509-2010
|View full text |Cite
|
Sign up to set email alerts
|

Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

Abstract: Abstract. In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS 1 database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km 2 ). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe.A faithful repre… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
16
0

Year Published

2011
2011
2024
2024

Publication Types

Select...
8
1
1

Relationship

0
10

Authors

Journals

citations
Cited by 21 publications
(16 citation statements)
references
References 31 publications
0
16
0
Order By: Relevance
“…In general, it is expected that correlations between satellite and gauge precipitation measurements, and even correlations between gauges, worsen at these fine temporal resolutions [39,40], making this a more challenging task.…”
Section: Discussionmentioning
confidence: 99%
“…In general, it is expected that correlations between satellite and gauge precipitation measurements, and even correlations between gauges, worsen at these fine temporal resolutions [39,40], making this a more challenging task.…”
Section: Discussionmentioning
confidence: 99%
“…Additionally, many key hydrologic processes are extremely difficult to parameterize (e.g., irrigation, dam operation, snow melting, and interception), especially in challenging regions (deserts, pluvial forests, and high altitudes). Therefore, modelled soil moisture data surely represents an important dataset that, however, needs to be used with caution [70,71].…”
Section: Hydrological and Land Surface Modellingmentioning
confidence: 99%
“…This leads to the deviations between satellite and ground-based measurements. To diminish the deviations, the in situ efforts should focus on separation of the respective contribution of these factors under a broad range of environmental conditions (Bircher et al, 2012;Juglea et al, 2010) before the planned refinement of the retrieval algorithm and data reprocessing (Dente et al, 2012). This should allow one to obtain more consistent data and yield quantitative maps of global soil moisture dynamics that is one of the main objectives of the SMOS mission .…”
Section: Introductionmentioning
confidence: 99%