SMOS soil moisture retrievals using the land parameter retrieval model: Evaluation over the Murrumbidgee Catchment, southeast Australia
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van der Schalie, R; Parinussa, R M; Renzullo, Luigi J; Van Dijk, Albert; Su, C-H; de Jeu, Richard A.M.
Description
The land parameter retrieval model (LPRM) is a methodology that retrieves soil moisture from low frequency dual polarized microwave measurements and has been extensively tested on C-, X- and Ku-band frequencies. Its performance on L-band is tested here by using observations from the Soil Moisture and Ocean Salinity (SMOS) satellite. These observations have potential advantages compared to higher frequencies: a low sensitivity to cloud and vegetation contamination, an increased thermal sampling...[Show more]
dc.contributor.author | van der Schalie, R | |
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dc.contributor.author | Parinussa, R M | |
dc.contributor.author | Renzullo, Luigi J | |
dc.contributor.author | Van Dijk, Albert | |
dc.contributor.author | Su, C-H | |
dc.contributor.author | de Jeu, Richard A.M. | |
dc.date.accessioned | 2015-12-10T23:30:42Z | |
dc.identifier.issn | 0034-4257 | |
dc.identifier.uri | http://hdl.handle.net/1885/68302 | |
dc.description.abstract | The land parameter retrieval model (LPRM) is a methodology that retrieves soil moisture from low frequency dual polarized microwave measurements and has been extensively tested on C-, X- and Ku-band frequencies. Its performance on L-band is tested here by using observations from the Soil Moisture and Ocean Salinity (SMOS) satellite. These observations have potential advantages compared to higher frequencies: a low sensitivity to cloud and vegetation contamination, an increased thermal sampling depth and a greater sensitivity to soil moisture fluctuations. These features make it desirable to add SMOS-derived soil moisture retrievals to the existing European Space Agency (ESA) long-term climatological soil moisture data record, to be harmonized with other passive microwave soil moisture estimates from the LPRM. For multi-channel observations, LPRM infers the effective soil temperature (Teff ) from higher frequency channels. This is not possible for a single channel mission like SMOS and therefore two alternative sources for Teff were tested: (1) MERRA-Land and (2) ECMWF numerical weather prediction systems, respectively. SMOS measures brightness temperature at a range of incidence angles, different incidence angle bins (45°, 52.5° and 60°) were tested for both ascending and descending swaths. Three LPRM algorithm parameters were optimized to match remotely sensed soil moisture with ground based observations: the single scattering albedo, roughness and polarization mixing factor. The soil moisture retrievals were optimized and evaluated against ground-based data from the Murrumbidgee Soil Moisture Monitoring Network (OzNet) in southeast Australia. The agreement with single-angle SMOS LPRM retrievals was close to the official SMOS L3 product, provided the three parameters were optimized for the OzNet dataset, with linear correlation of 0.70-0.75 (0.75-0.77 for SMOS L3), root-mean-square error of 0.069-0.085m3 m-3 (0.084-0.106m3 m-3 for SMOS L3) and small bias of -0.02-0.01m3 m-3 (0.03-0.06m3 m-3 for SMOS L3). These results suggest that the LPRM can be applied successfully to single-angle SMOS L-band observations, but further testing is required to determine if the same set of parameters can be used in other geographic areas. | |
dc.publisher | Elsevier | |
dc.source | Remote Sensing of Environment | |
dc.title | SMOS soil moisture retrievals using the land parameter retrieval model: Evaluation over the Murrumbidgee Catchment, southeast Australia | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 163 | |
dc.date.issued | 2015 | |
local.identifier.absfor | 050299 - Environmental Science and Management not elsewhere classified | |
local.identifier.ariespublication | a383154xPUB1676 | |
local.type.status | Published Version | |
local.contributor.affiliation | van der Schalie, R, VU University Amsterdam | |
local.contributor.affiliation | Parinussa, R M, VU University Amsterdam | |
local.contributor.affiliation | Renzullo, Luigi J , CSIRO Land and Water | |
local.contributor.affiliation | Van Dijk, Albert, College of Medicine, Biology and Environment, ANU | |
local.contributor.affiliation | Su, C-H, University of Melbourne | |
local.contributor.affiliation | de Jeu, Richard A.M., VU University Amsterdam | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 70 | |
local.bibliographicCitation.lastpage | 79 | |
local.identifier.doi | 10.1016/j.rse.2015.03.006 | |
local.identifier.absseo | 961003 - Natural Hazards in Farmland, Arable Cropland and Permanent Cropland Environments | |
dc.date.updated | 2016-06-14T08:28:44Z | |
local.identifier.scopusID | 2-s2.0-84925955050 | |
Collections | ANU Research Publications |
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