Author
CHAN, S. - Jet Propulsion Laboratory | |
BINDLISH, R. - Science Systems, Inc | |
O'NEILL, PEGGY, E. - National Aeronautics And Space Administration (NASA) | |
NJOKU, ENI - Jet Propulsion Laboratory | |
Jackson, Thomas | |
COLLIANDER, ANDREAS - Jet Propulsion Laboratory | |
CHEN, FAN - Science Systems, Inc | |
BURGIN, M. - Jet Propulsion Laboratory | |
DUNBAR, R.S. - Jet Propulsion Laboratory | |
PEIPMEIER, J. - National Aeronautics And Space Administration (NASA) | |
YUEH, S. - Jet Propulsion Laboratory | |
ENTEKHABI, DARA - Collaborator | |
Cosh, Michael | |
CALDWELL, TODD - University Of Texas | |
WALKER, JEFF - Monash University | |
WU, X - Monash University | |
BERG, A. - University Of Guelph | |
ROWLANDSON, T. - University Of Guelph | |
PACHECO, A. - Agriculture And Agri-Food Canada | |
MCNAIRN, H. - Agriculture And Agri-Food Canada | |
THIBEAULT, M. - Collaborator | |
MARTINEZ-FERNANDEZ, J. - University Of Salamanca | |
GONZALEZ-ZAMORA, A. - University Of Salamanca | |
Seyfried, Mark | |
Bosch, David | |
Starks, Patrick | |
Goodrich, David - Dave | |
Prueger, John | |
PALECKI, M. - National Oceanic & Atmospheric Administration (NOAA) | |
SMALL, E.E. - University Of Colorado | |
ZREDA, M. - University Of Arizona | |
CALVET, J.C. - Ecole Nationale | |
Crow, Wade | |
KERR, Y. - Center For The Study Of The Biosphère From Space(CESBIO) |
Submitted to: IEEE Transactions on Geoscience and Remote Sensing
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 4/1/2016 Publication Date: 5/25/2016 Citation: Chan, S., Bindlish, R., O'Neill, P., Njoku, E., Jackson, T.J., Colliander, A., Chen, F., Burgin, M., Dunbar, R., Peipmeier, J., Yueh, S., Entekhabi, D., Cosh, M.H., Caldwell, T., Walker, J., Wu, X., Berg, A., Rowlandson, T., Pacheco, A., McNairn, H., Thibeault, M., Martinez-Fernandez, J., Gonzalez-Zamora, A., Seyfried, M.S., Bosch, D.D., Starks, P.J., Goodrich, D.C., Prueger, J.H., Palecki, M., Small, E., Zreda, M., Calvet, J., Crow, W.T., Kerr, Y. 2016. Assessment of the SMAP level 2 passive soil moisture product. IEEE Transactions on Geoscience and Remote Sensing. 54(8):1-14. doi:10.1109/TGRS.2016.2561938. Interpretive Summary: The first assessment of the Soil Moisture Active Passive (SMAP) satellite products based on the radiometer instrument showed that the retrievals are exceeding the mission goal of 0.04 m3/m3. Assessment methodologies utilized include comparisons of SMAP soil moisture retrievals with in situ soil moisture observations from core validation sites and sparse networks and inter-comparison with products from Soil Moisture Ocean Salinity (SMOS) satellite. Three alternative algorithms were considered and the results supported the recommendation to use the Single Channel Algorithm-Vertical Polarization as the baseline. SMAP has been providing products routinely since April, 2015. These results support the reliability of these products for use in agricultural hydrology, weather, and climate applications. Technical Abstract: The NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on Jan 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every 2–3 days using an L-band (active) radar and an L-band (passive) radiometer. SMAP provides three geophysical (level 2) soil moisture products: a radiometer-only product (L2_SM_P), a radar-only product (L2_SM_A), and a combined radar/radiometer product (L2_SM_AP). The SMAP radiometer-only soil moisture product (L2_SM_P) provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. The L2_SM_P product was assessed to have attained preliminary (beta) science quality and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC). This paper provides a summary of the L2_SM_P product and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted through October 2015, at a limited number of core validation sites and several hundred sparse networks points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance amongst algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the core validation sites was 0.038 m3/m3 unbiased root-mean-square difference (ubRMSD), which meets the SMAP mission requirement of 0.040 m3/m3. |