Data Set ID: 

SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 6

This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band soil moisture data are resampled to a global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0).

This is the most recent version of these data.

Version Summary: 

Changes to this version include:

  • The Dual Channel Algorithm (DCA) has been replaced by the Modified Dual Channel Algorithm (MDCA). MDCA achieves better retrieval performance through the modeling of polarization mixing between the vertically and horizontally polarized brightness temperature channels, as well as new estimates of single-scattering albedo and roughness coefficients. MDCA supersedes optional algorithms MPRA (option 4) and E-DCA (option 5).
  • As part of the option algorithm changes, the following data fields were added: albedo_option3, roughness_coefficient_option3, bulk_density, clay_fraction.
  • The baseline algorithm (SCA-V) remains unchanged.
  • Improved aggregation of values in input ancillary data, e.g. roughness, soil texture, NDVI. The fix has negligible impacts on retrievals estimated to be of recommended quality.

COMPREHENSIVE Level of Service

Data: Data integrity and usability verified; data customization services available for select data

Documentation: Key metadata and comprehensive user guide available

User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services

See All Level of Service Details

Data Format(s):
  • HDF5
Spatial Coverage:
N: 85.044, 
S: -85.044, 
E: 180, 
W: -180
Spatial Resolution:
  • 36 km x 36 km
Temporal Coverage:
  • 31 March 2015
Temporal Resolution1 dayMetadata XML:View Metadata Record
Data Contributor(s):O'Neill, P. E., S. Chan, E. G. Njoku, T. Jackson, and R. Bindlish.

Geographic Coverage

Other Access Options

Other Access Options


As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

O'Neill, P. E., S. Chan, E. G. Njoku, T. Jackson, and R. Bindlish. 2019. SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 6. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: [Date Accessed].
7 January 2019
Last modified: 
15 August 2019

Data Description


The main output of this data set is 0-5 cm surface soil moisture (cm3/cm3) presented on the global 36 km EASE-Grid 2.0. Also included are Brightness Temperature (Tb) measurements (K), representing the weighted average of SMAP Level-1B brightness temperatures whose boresights fall within each 36 km EASE-Grid 2.0 grid cell.

Refer to the Data Fields document for details on all parameters.

File Information


Data are provided in HDF5 format (.h5). For compatible software and more information of HDF5 files, including an HDF5 tutorial, visit the HDF Group's HDF5 website.

File Contents

As shown in Figure 1, each HDF5 file is organized into three main groups, Metadata and Soil Moisture Retrieval Data (both AM and PM), all of which contain sub-groups and/or data sets.

Figure 1. Subset of File Contents
For a complete list of file contents, refer to the Data Fields page.

The Metadata Fields group includes all the metadata that describe the full content of each file. For a description of all metadata fields for this product, refer to the Product Specification Document.

The Soil Moisture Retrieval Data AM group contains soil moisture data, ancillary data, and quality assessment flags for each descending half-orbit pass of the satellite (where the satellite moves from North to South and 6:00 a.m. is the Local Solar Time (LST) at the equator). The Soil Moisture Retrieval Data PM group contains soil moisture data, ancillary data, and quality assessment flags for each ascending half-orbit pass of the satellite (where the satellite moves from South to North and 6:00 p.m. is the LST at the equator). Corrected brightness temperatures are also provided for each AM and PM group.

File Naming Convention

Files are named according to the following convention and as described in Table 1:

For example:

Table 1. File Naming Conventions
Variable Description
SMAP Indicates SMAP mission data
L3_SM_P Indicates specific product (L3: Level-3; SM: Soil Moisture; P: Passive)
yyyymmdd 4-digit year, 2-digit month, 2-digit day of the first data element that appears in the product.
RLVvvv Composite Release ID (CRID), where:
R Release
L Launch Indicator (1: post-launch standard data)
V 1-Digit Major CRID Version Number
vvv 3-Digit Minor CRID Version Number
Refer to the SMAP Data Versions page for version information.
NNN Product Counter: Number of times the file was generated under the same version for a particular date/time interval (002: second time)
.[ext] File extensions include:
.h5 HDF5 data file
.qa Quality Assurance file
.xml XML Metadata file

File Size

Each file is approximately 25 - 30 MB.

Spatial Information


Data set coverage spans from 180°W to 180°E and from approximately 85.044°N and 85.044°S. The gap in coverage at both the North and South Pole, called a pole hole, has a radius of approximately 400 km.


36 km


Data are gridded using the 36 km EASE-Grid 2.0 projection.The following tables provide information for geolocating this data set. For more on EASE-Grid 2.0, refer to the EASE Grids website.

Table 2. Geolocation Details for the Global EASE-Grid
Geographic coordinate system
WGS 84
Projected coordinate system
EASE-Grid 2.0 Global
Longitude of true origin
Standard Parallel
Scale factor at longitude of true origin
WGS 84
WGS 84
False easting
False northing
EPSG code
PROJ4 string
+proj=cea +lon_0=0 +lat_ts=30 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs

Table 3. Grid Details for the Global EASE-Grid
Grid cell size (x, y pixel dimensions) 36,032.22 projected meters (x)
36,032.22 projected meters (y)
Number of columns 964
Number of rows 406
Geolocated lower left point in grid 85.044° S, 180.000 ° W
Nominal gridded resolution 36 km by 36 km
Grid rotation N/A
ulxmap – x-axis map coordinate of the outer edge of the upper-left pixel -17367530.45 m
ulymap – y-axis map coordinate of the outer edge of the upper-left pixel 7314540.83 m

Temporal Information


Coverage spans from 31 March 2015 to present.

Satellite and Processing Events

Due to instrument maneuvers, data downlink anomalies, data quality screening, and other factors, small gaps in the SMAP time series will occur. Details of these events are maintained on two master lists:

SMAP On-Orbit Events List for Instrument Data Users
Master List of Bad and Missing Data

A significant gap in coverage occurred between 19 June and 23 July 2019 after the SMAP satellite went into Safe Mode. A brief description of the event and its impact on data quality is available in the SMAP Post-Recovery Notice.


FAQ: What are the latencies for SMAP radiometer data sets?


Each Level-3 file is a daily composite of half-orbit files/swaths. Note that data from descending passes (a.m.) and ascending passes (p.m.) are stored separately in the same daily composite granule.

Data Acquisition and Processing


The microwave portion of the electromagnetic spectrum, which includes wavelengths from a few centimeters to a meter, has long held the most promise for estimating surface soil moisture remotely. Passive microwave sensors measure the natural thermal emission emanating from the soil surface. The variation in the intensity of this radiation depends on the dielectric properties and temperature of the target medium, which for the near-surface soil layer is a function of the amount of moisture present. Low microwave frequencies, at L-band or approximately 1 GHz, offer the following additional advantages:

  • The atmosphere is almost completely transparent, providing all-weather sensing
  • Transmission of signals from the underlying soil is possible through sparse and moderate vegetation layers (up to at least 5 kg/m2 of vegetation water content)
  • Measurement is independent of solar illumination which allows for day and night observations

For more details, refer to "Section 2: Passive Remote Sensing of Soil Moisture" of the Algorithm Theoretical Basis Document (ATBD) for this product (O'Neill et al. 2018), which is available as a technical reference.


The SMAP Level-3 radiometer soil moisture product (SPL3SMP) is a daily gridded composite of the SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture, Version 6 (SPL2SMP) data. The derivation of soil moisture from SMAP brightness temperatures occurs in the Level-2 processing. Refer to the SPL2SMP user guide for details on soil moisture algorithms and ancillary data.


The SPL3SMP product is a daily global product. To generate the product, individual SPL2SMP half-orbit files, acquired over the course of one day, are composited to produce a daily multi-orbit global map of retrieved soil moisture. Where the SPL2SMP swaths overlap, poleward of approximately +/- 65° latitude, three options were considered for compositing multiple data points at a given grid cell:

  1. Use the most recent (or last-in) data point
  2. Take the average of all data points within the grid cell
  3. Choose the data points observed closest to 6:00 a.m. Local Solar Time (LST) for observations derived from SMAP descending passes and closest to 6:00 p.m. LST for observations derived from SMAP descending passes

The current approach for the SPL3SMP product is to use the third option - choosing the nearest 6:00 a.m. LST and nearest 6:00 p.m. LST pass to perform Level-3 compositing separately for descending and ascending passes, respectively. For a given L2 half-orbit granule whose time stamp (yyyymmddThhmmss) is expressed in UTC, only the hhmmss part is converted into local solar time (O'Neill et al. 2016).

Quality, Errors, and Limitations

Error Sources

Anthropogenic RFI, principally from ground-based surveillance radars, can contaminate both radar and radiometer measurements at L-band frequencies. The SMAP radar and radiometer electronics and algorithms include design features to mitigate the effects of RFI. The SMAP radiometer implements a combination of time and frequency diversity, kurtosis detection, and use of thresholds to detect and, where possible, mitigate RFI.

Level-2 radiometer data can also contain bit errors caused by noise in communication links and memory storage devices. Consultative Committee on Space Data Systems (CCSDS) packets include error-detecting Cyclic Redundancy Checks (CRCs), which are used to flag errors.

More information about error sources is provided in "Section 4.6: Algorithm Error Performance" of the ATBD (O'Neill et al. 2018).

Quality Overview

SMAP products provide multiple means to assess quality. Each product contains bit flags, uncertainty measures, and file-level metadata that provide quality information. For information regarding the specific bit flags, uncertainty measures, and file-level metadata contained in this product, refer to the Product Specification Document. For in-depth details regarding the quality of these data, refer to the Validated Assessment Report.

Each HDF5 file contains metadata with Quality Assessment (QA) metadata flags that are set by the Science Data Processing System (SDS) at the JPL prior to delivery to the National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC). A separate QA file with a .qa file extension is also associated with the HDF5 file; it contains useful statistics to help users better assess the quality of the associated data file. If a product does not fail QA, it is ready to be used for higher-level processing, browse generation, active science QA, archive, and distribution. If a product fails QA, it is never delivered to NSIDC DAAC.

Data Flags

Bit flags generated from input SMAP data and ancillary data are also employed to help determine the quality of the retrievals. Ancillary data help determine either specific aspects of the processing (such as corrections for transient water) or the quality of the retrievals (e.g. precipitation flag). These flags will provide information on whether the ground is frozen, snow-covered, or flooded, or whether it is actively precipitating at the time of the satellite overpass. Other flags will indicate areas of steeply sloped topography or urban, heavily forested, or permanent snow/ice coverage.

For a description of the data flag types and methods of flagging, refer to the "Data Flags" section in the SPL2SMP user guide. All flags in SPL2SMP are carried over into the SPL3SMP product.



For a detailed description of the SMAP instrument, visit the SMAP Instrument page at the Jet Propulsion Laboratory (JPL) SMAP website.

Software and Tools

For tools that work with SMAP data, see the Tools web page.

Version History

Table 4. Summary of Version Changes
Description of Changes
V6 August 2019

Changes to this version include:

  • The following data fields were added: bulk_density, clay_fraction, bulk_density_pm, clay_fraction_pm.
  • The baseline algorithm (SCA-V) remains unchanged.
  • Improved aggregation of values in input ancillary data, e.g. roughness, soil texture, NDVI. The fix has negligible impacts on retrievals estimated to be of recommended quality.


June 2018

Changes to this version include:

  • Level-1B water-corrected brightness temperatures are used in passive soil moisture retrieval. This procedure corrects for anomalous soil moisture values seen near coastlines in the previous version and should result in less rejected data due to waterbody contamination. Five new data fields accommodate this correction: grid_surface_status, surface_water_fraction_mb_h, surface_water_fraction_mb_v, tb_h_uncorrected, and tb_v_uncorrected.
  • Improved depth correction for effective soil temperature used in passive soil moisture retrieval; new results are captured in the surface_temperature data field. This correction reduces the dry bias seen when comparing SMAP data to in situ data from the core validation sites.
  • Frozen ground flag updated to reflect improved freeze/thaw detection algorithm, providing better accuracy; new results are captured in bit 7 of the surface_flag.


December 2016

Changes to this version include:

  • Added 6:00 p.m. ascending half orbits, which provide:
    • More frequent regional/global coverage (critical in flood monitoring)
    • Soil moisture diurnal variability information (useful in data assimilation systems)
    • Consistency with other similar satellite-based soil moisture products
  • Contains frozen ground flag (bit 7 of surface_flag) derived using Normalized Polarization Ration (NPR)-based SMAP passive freeze-thaw retrieval; replaces former SMAP radar-based freeze/thaw flag


April 2016

Changes to this version include:

  • Transitioned to Validated-Stage 2
  • Uses updated SPL2SMP V3 Validated data as input


October 2015

Changes to this version include:

  • Uses  SPL1CTB SPL2SMP V2 Beta data as input
  • Corrects the retrieval quality flag error


September 2015

First public release 

Related Data Sets

SMAP Data at NSIDC | Overview

SMAP Radar Data at the ASF DAAC

Related Websites


Contacts and Acknowledgments


Peggy O'Neill
NASA Goddard Space Flight Center
Global Modeling and Assimilation Office
Mail Code 610.1
8800 Greenbelt Rd.
Greenbelt, MD 20771 USA

Steven Chan
Jet Propulsion Laboratory
4800 Oak Grove Drive 
Pasadena, CA 91109 USA

Tom Jackson
United States Department of Agriculture/Agricultural Research Service (USDA/ARS) 
Hydrology and Remote Sensing Laboratory
104 Bldg. 007, BARC-West 
Beltsville, MD 20705 USA

Rajat Bindlish
NASA Goddard Space Flight Center
Hydrological Sciences Laboratory
8800 Greenbelt Rd.
Greenbelt, MD 20771 USA



Jackson, T. , P. O’Neill, S. Chan, R. Bindlish, A. Colliander, F. Chen , S. Dunbar , J. Piepmeier , S. Misra , M. Cosh , T. Caldwell, J. Walker, X. Wu, A. Berg, T. Rowlandson, A. Pacheco, H. McNairn, M. Thibeault, J. Martínez-Fernández, Á. González-Zamora, E. Lopez-Baeza, F. Udall, M. Seyfried, D. Bosch, P. Starks, C. Holifield, J. Prueger, Z. Su, R. van der Velde, J. Asanuma, M. Palecki, E. Small, M. Zreda, J. Calvet, W. Crow, Y. Kerr, S. Yueh, and D. Entekhabi. 2018. Calibration and Validation for the L2/3_SM_P Version 5 and L2/3_SM_P_E Version 2 Data Products. SMAP Project, JPL D-56297, Jet Propulsion Laboratory. Pasadena, CA. (PDF, 1.1 MB; see Technical References)

Jet Propulsion Laboratory (JPL). "SMAP Instrument." JPL SMAP Soil Moisture Active Passive. [20 August 2015].

Carroll, M.L., C. M. DiMiceli, M. R. Wooten, A. B. Hubbard, R.A. Sohlberg, and J. R. G. Townshend. 2017. MOD44W MODIS/Terra Land Water Mask Derived from MODIS and SRTM L3 Global 250m SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD. doi: 10.5067/MODIS/MOD44W.006

O'Neill, P. E., E. G. Njoku, T. J. Jackson, S. Chan, and R. Bindlish. 2018. SMAP Algorithm Theoretical Basis Document: Level 2 & 3 Soil Moisture (Passive) Data Products, Revision D. SMAP Project, JPL D-66480, Jet Propulsion Laboratory, Pasadena, CA. (PDF, 1.7 MB; see Technical References)

O'Neill, P. E., E. G. Njoku, T. J. Jackson, S. Chan, and R. Bindlish. 2016. SMAP Algorithm Theoretical Basis Document: Level 2 & 3 Soil Moisture (Passive) Data Products. SMAP Project, JPL D-66480, Jet Propulsion Laboratory, Pasadena, CA. (PDF, 3.3 MB; see Technical References

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