TY - JOUR
T1 - Assessment of Soil Moisture SMAP Retrievals and ELBARA-III Measurements in a Tibetan Meadow Ecosystem
AU - Zheng, Donghai
AU - Wang, Xin
AU - van der Velde, Rogier
AU - Schwank, Mike
AU - Ferrazzoli, Paolo
AU - Wen, Jun
AU - Wang, Zuoliang
AU - Colliander, Andreas
AU - Bindlish, Rajat
AU - Su, Zhongbo
PY - 2019/9
Y1 - 2019/9
N2 - This letter presents the results evaluating retrievals of liquid water content (θ liq ) performed with a zero-order radiative transfer (τ-ω) model under frozen and thawed soil conditions from Soil Moisture Active Passive (SMAP) and ELBARA-III brightness temperature (T B p ) measurements collected over a Tibetan meadow ecosystem. A good agreement is found between time series of the SMAP and ELBARA-III measured T B p resulting in a Pearson product-moment coefficient (R) larger than 0.87. Differences noted between the two data sets can be associated with discrepancies in θ liq measured in the specific footprints, whereby the SMAP measurements are best explained by the in situ θ liq . Furthermore, the in situ θ liq has a better agreement with the horizontally polarized SMAP and ELBARA-III measurements (THB ) in the cold season, whereas the vertically polarized measurements (TVB ) are1111better correlated with θ liq in the warm season. With the implementation of new vegetation and surface roughness parameterizations for the τ-ω model, the dynamics of in situ θ liq is better reproduced by corresponding retrievals for both frozen and thawed soil conditions, leading to the reduction in the unbiased root-mean-square error (ubRMSE) by more than 31% in comparison with these retrievals using SMAP default parameterizations. Notably, the single-channel algorithm configured with the new parameterizations using SMAP TVB measured during the ascending overpass provides the best θ liq retrievals with a ubRMSE of 0.035 m 3 ·m -3 that is well within the SMAP mission requirements.
AB - This letter presents the results evaluating retrievals of liquid water content (θ liq ) performed with a zero-order radiative transfer (τ-ω) model under frozen and thawed soil conditions from Soil Moisture Active Passive (SMAP) and ELBARA-III brightness temperature (T B p ) measurements collected over a Tibetan meadow ecosystem. A good agreement is found between time series of the SMAP and ELBARA-III measured T B p resulting in a Pearson product-moment coefficient (R) larger than 0.87. Differences noted between the two data sets can be associated with discrepancies in θ liq measured in the specific footprints, whereby the SMAP measurements are best explained by the in situ θ liq . Furthermore, the in situ θ liq has a better agreement with the horizontally polarized SMAP and ELBARA-III measurements (THB ) in the cold season, whereas the vertically polarized measurements (TVB ) are1111better correlated with θ liq in the warm season. With the implementation of new vegetation and surface roughness parameterizations for the τ-ω model, the dynamics of in situ θ liq is better reproduced by corresponding retrievals for both frozen and thawed soil conditions, leading to the reduction in the unbiased root-mean-square error (ubRMSE) by more than 31% in comparison with these retrievals using SMAP default parameterizations. Notably, the single-channel algorithm configured with the new parameterizations using SMAP TVB measured during the ascending overpass provides the best θ liq retrievals with a ubRMSE of 0.035 m 3 ·m -3 that is well within the SMAP mission requirements.
KW - Frozen and thawed soil
KW - Grassland
KW - L-band microwave radiometry
KW - Liquid water content
KW - Soil Moisture Active Passive (SMAP)
KW - Tibetan Plateau
KW - ITC-ISI-JOURNAL-ARTICLE
KW - 22/4 OA procedure
UR - https://ezproxy2.utwente.nl/login?url=https://doi.org/10.1109/LGRS.2019.2897786
UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2019/isi/vandervelde_ass.pdf
U2 - 10.1109/LGRS.2019.2897786
DO - 10.1109/LGRS.2019.2897786
M3 - Article
SN - 1545-598X
VL - 16
SP - 1407
EP - 1411
JO - IEEE geoscience and remote sensing letters
JF - IEEE geoscience and remote sensing letters
IS - 9
ER -