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Description

SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products:

  • SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D)
  • SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3)
  • SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG).
    For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection.

Version Description

Changes to this version include: - The Catchment model now includes the PEATCLSM hydrology module for peatlands and uses an updated global map of peatland distribution. - Revised parameters are used in the L-band radiative transfer model that converts the simulated soil moisture and temperature estimates into Tb predictions for the radiance-based L4_SM analysis. Specifically, the L-band parameters for scattering albedo climatology, soil roughness climatology, and (seasonally-varying) vegetation opacity climatology are obtained from the SPL2SMP_E, Version 5, dual-channel retrieval product (April 2015 - March 2022). - The brightness temperature scaling parameters in the updated Level-4 soil moisture algorithm are based on seven years of SMAP observations and model simulations (April 2015 - March 2022). - For peatlands, the EnKF state vector now additionally includes the "catchment deficit" model prognostic variable. For the full major and minor version history, go to https://nsidc.org/data/smap/version-history

Product Summary

Platforms
GEOS-5 ,
SMAP
Instruments
NOT APPLICABLE ,
SMAP L-BAND RADIOMETER
Spatial Extent

N: 85.044 S: -85.044 E: 180 W: -180

Spatial Resolution
9 Kilometers x 9 Kilometers
Spatial Reference System(s)
WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Location
GLOBAL LAND
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
2015-03-31 to 2021-01-01
Concept ID
C2938666109-NSIDC_CPRD
Data State
DEPRECATED
Number of Files/Granules
0
Processing Level
4
Published
Updated
Science Keywords
Soil Classification ,
Soil Depth ,
Soil Porosity ,
Soil Texture ,
Terrain Elevation

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Reichle, R., De Lannoy, G., Koster, R., Crow, W., Kimball, J., Liu, Q., & Bechtold, M. (2022). SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants, Version 7 [Dataset]. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/KN96XNPZM4EG Date Accessed: 2026-08-09

Documents

Publications Citing This Dataset

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Title Year Author Topic
Soil moisture buffers the impact of precipitation variability on ecosystem productivity Wang, Huiqi, Bassiouni, Maoya, Kang, Yanghui, Rifai, Sami W., Gherardi, Laureano A., Ukkola, Anna, Keenan, Trevor F. Soil Classification, Soil Depth, Soil Porosity, Soil Texture, Terrain Elevation, Brightness Temperature, Surface Soil Moisture, Photosynthesis, Primary Production, Vegetation Productivity, Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Root Zone Soil Moisture
Streamflow calibration in ungauged basins using SWOT discharge and SMAP surface soil moisture products Crow, Wade T., Durand, Michael, Coss, Steve, Reichle, Rolf H. Soil Classification, Soil Depth, Soil Porosity, Soil Texture, Terrain Elevation
Satellite soil moisture as an additional observational constraint for machine learning-based irrigation water use modeling Huang, Xin, He, Qing, Hanasaki, Naota, Oki, Taikan Root Zone Soil Moisture, Surface Soil Moisture, Brightness Temperature, Soil Classification, Soil Depth, Soil Porosity, Soil Texture, Terrain Elevation
Spatiotemporal Seamless Estimation of Global Surface Soil Moisture Using Triple Collocation, Machine Learning, and Data Assimilation Xu, Lei, Ye, Zhenni, Dai, Jin, Li, Qi, Hong, Youting, Tao, Yun, Yu, Hongchu, Zhang, Chong, Chen, Zeqiang, Chen, Nengcheng Carbon, Nitrogen, Soil Water Holding Capacity, Soil Bulk Density, Soil Chemistry, Soil Classification, Soil Moisture/Water Content, Soil Horizons/Profile, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Surface Temperature, Humidity, Evapotranspiration, Surface Winds, Rain, Precipitation Rate, Snow, Soil Temperature, Land Surface Temperature, Snow Water Equivalent, Runoff, Land Use/Land Cover Classification, Surface Soil Moisture, Soil Depth, Soil Porosity, Soil Texture, Terrain Elevation
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