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LPRM/AMSR-E/Aqua Daily L3 Descending and 2-Layer Palmer Water Balance Model Root Zone Soil Moisture

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Abstract: This Level 3 (gridded) root-zone soil moisture product is derived via the assimilation of Land Parameter Retrieval Model (LPRM)/Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E)/NASA EOS Aqua surface soil moisture retrievals into the 2-Layer Palmer Water Balance Model, using a 1-dimensional, 30-member Ensemble Kalman filter (EnKF). The 2-Layer Palmer Water Balance Model was ... View entire text
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Caption:  Root zone soil moisture from EnKF-based assimilation of LPRM/AMSR-E nighttime C-band retrievals into 2-Layer Palmer Water Balance Model
Geographic Coverage
Spatial coordinates   
  N: 60.0   S: -60.0   E: 180.0   W: -180.0

Data Set Citation
Dataset Originator/Creator: USDA Agricultural Research Service
Dataset Title: LPRM/AMSR-E/Aqua Daily L3 Descending and 2-Layer Palmer Water Balance Model Root Zone Soil Moisture
Dataset Release Date: 05.21.2012
Dataset Release Place: Greenbelt, MD U.S.A.
Dataset Publisher: Goddard Earth Sciences Data and Information Services Center (GES DISC)
Version: 1
Online Resource:
Temporal Coverage
Start Date: 2002-06-01
Stop Date: 2010-12-31
Data Resolution
Latitude Resolution: 25 km
Longitude Resolution: 25 km
Horizontal Resolution Range: 10 km - < 50 km or approximately .09 degree - < .5 degree
Temporal Resolution: Daily
Temporal Resolution Range: Daily - < Weekly
ISO Topic Category
Quality The accuracy of the EnKF root zone soil moisture (RZSM) predictions depends on (1) the magnitude of errors in the model forecasts and satellite surface soil moisture retrievals from which the RZSM is derived, (2) the quality of error information provided to the EnKF (and used to optimally weigh conflicting information obtained from various sources), and (3) the vertical accuracy of the model (used as the basis for extrapolating surface soil moisture measurements to constrain soil moisture at greater vertical depths). Validation results suggest that the EnKF generally provides a more accurate RZSM prediction, compared with the baseline 2-Layer Palmer Model predictions (particularly in sparsely-vegetated and/or data-poor regions of the world).
Access Constraints None
Use Constraints None
Data Set Progress
Data Center
Hydrology DISC, Goddard Earth Sciences Data and Information Services Center, Global Change Data Center, Earth Sciences Division, Science and Exploration Directorate, Goddard Space Flight Center, NASA Supplemental Info
Data Center URL:

Data Center Personnel
Phone: 301-614-5224
Fax: 301-614-5268
Email: gsfc-help-disc at
Contact Address:
Goddard Earth Sciences Data and Information Services Center
Code 610.2
NASA Goddard Space Flight Center
City: Greenbelt
Province or State: MD
Postal Code: 20771
Country: USA
Distribution Media: Online (FTP)
Distribution Size: (per file) 4 MB
Distribution Format: NETCDF
Fees: None
Phone: 301 504 6847
Fax: 301 504 8931
Email: Wade.Crow at
Contact Address:
USDA-ARS Hydrology and Remote Sensing Laboratory
Bldg. 007, Rm. 104, BARC-West
City: Beltsville
Province or State: MD
Postal Code: 20705-2350
Country: USA
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Owe, M., R. de Jeu, and T. Holmes (2008), Multisensor historical climatology of satellite-derived global land surface moisture, Journal of Geophysical Research, 113, F01002, 17 pp., doi:10.1029/2007JF000769
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Extended Metadata Properties
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Creation and Review Dates
DIF Creation Date: 2012-05-05
Last DIF Revision Date: 2016-01-20

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