TY - JOUR
T1 - SMOS soil moisture retrievals using the land parameter retrieval model
T2 - Evaluation over the mUrrumbidgee Catchment, southeast Australia
AU - van der Schalie, R.
AU - Parinussa, R. M.
AU - Renzullo, L. J.
AU - van Dijk, A. I.J.M.
AU - Su, C. H.
AU - de Jeu, R. A.M.
N1 - Publisher Copyright:
© 2015 Elsevier Inc.
PY - 2015/6/5
Y1 - 2015/6/5
N2 - 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 0.069-0.085m3m-3 (0.084-0.106m3m-3 for SMOS L3) and small bias of -0.02-0.01m3m-3 (0.03-0.06m3m-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.
AB - 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 0.069-0.085m3m-3 (0.084-0.106m3m-3 for SMOS L3) and small bias of -0.02-0.01m3m-3 (0.03-0.06m3m-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.
KW - Land parameter retrieval model (LPRM)
KW - Passive microwave radiometry
KW - Remote sensing
KW - Soil moisture
KW - Soil moisture and ocean salinity (SMOS)
UR - http://www.scopus.com/inward/record.url?scp=84937758688&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2015.03.006
DO - 10.1016/j.rse.2015.03.006
M3 - Article
SN - 0034-4257
VL - 163
SP - 70
EP - 79
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
ER -