Data Set ID:
SPL3SMP

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  • The Dual Channel Algorithm (DCA) has been replaced by the Modified Dual Channel Algorithm (MDCA).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

Parameter(s):
  • MICROWAVE > BRIGHTNESS TEMPERATURE
  • SOILS > SOIL MOISTURE/WATER CONTENT > SOIL MOISTURE
Data Format(s):
  • HDF5
Spatial Coverage:
N: 85.044, 
S: -85.044, 
E: 180, 
W: -180
Platform(s):SMAP
Spatial Resolution:
  • 36 km x 36 km
Sensor(s):SMAP L-BAND RADIOMETER
Temporal Coverage:
  • 31 March 2015
Version(s):V6
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

Close

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: https://doi.org/10.5067/EVYDQ32FNWTH. [Date Accessed].
Created: 
7 January 2019
Last modified: 
10 October 2019

Data Description

Parameters

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 Appendix of this document for details on all parameters.

File Information

Format

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 Appendix.

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:
SMAP_L3_SM_P_yyyymmdd_RLVvvv_NNN.[ext]

For example:
SMAP_L3_SM_P_20170117_R14010_001.h5

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

Coverage

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.

Resolution

36 km

Geolocation

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
0
Standard Parallel
30
Scale factor at longitude of true origin
N/A
Datum
WGS 84
Ellipsoid/spheroid
WGS 84
Units
meter
False easting
0
False northing
0
EPSG code
6933
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
Reference

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

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.

Latencies

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

Resolution

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

Background

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.

Acquisition

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.

Processing

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.

Instrumentation

Description

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
Version
Date
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.

V5

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.

V4

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

V3

April 2016

Changes to this version include:

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

V2

October 2015

Changes to this version include:

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

V1

September 2015

First public release 

Related Data Sets

SMAP Data at NSIDC | Overview

SMAP Radar Data at the ASF DAAC

Related Websites

SMAP at NASA JPL

Contacts and Acknowledgments

Investigators

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

References

References

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. https://smap.jpl.nasa.gov/observatory/instrument/ [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

Appendix - Data Fields

This appendix provides a description of all data fields within the SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture (SPL3SMP) product. The data are grouped into three main HDF5 groups:

  • Metadata
  • Soil_Moisture_Retrieval_Data_AM
  • Soil_Moisture_Retrieval_Data_PM

For a description of metadata fields for this product, refer to the Product Specification Document. Table A1 describes the data fields of a typical SPL3SMP file/granule.

Note: Data field names in the PM group are appended with _pm, such as EASE_column_index_pm.

Table A1. SPL3SMP Data Fields
Data Field Name Precision Byte Unit Valid Min Valid Max Fill/Gap Value Derivation Method(s)**
EASE_column_index Uint16 2 N/A 0 963  65534 2
EASE_row_index Uint16 2 N/A 0 405  65534 2
albedo Float32 4 N/A 0.0 1.0 -9999.0 6
boresight_incidence Float32 4 Degree 0.0 90.0 -9999.0 1
bulk_density Float32 4 N/A 0.0 1.0 -9999.0 4
clay_fraction Float32 4 N/A 0.0 3.0 -9999.0 4
freeze_thaw_fraction Float32 4 N/A 0.0 1.0 -9999.0 6 or 7
grid_surface_status Uint16 2 N/A 0 (indicated land) 1 (indicates water) 65534 8
landcover_class Uint8 1 N/A 0 16 254 6
landcover_class_fraction Unit8 1 N/A 0.0 1.0 -9999.0 6
latitude Float32 4 Degree -90.0 +90.0 -9999.0 2
latitude_centroid Float32 4 Degree -90.0 +90.0 -9999.0 1
longitude Float32 4 Degree -180.0 +180.0 -9999.0 2
longitude_centroid Float32 4 Degree -180.0 +180.0 -9999.0 1
radar_water_body_fraction Float32 4 N/A 0.0 1.0 -9999.0 6 or 7
retrieval_qual_flag Uint16 2 N/A 0 65,536 65534 4
roughness_coefficient Float32 4 N/A 0.0 3.0 -9999.0 6
soil_moisture Float32 4 m3/m3 0.02 Soil Porosity -9999.0 4
soil_moisture_error Float32 4 m3/m3 0.00 Soil Porosity -9999.0 4 or 6
static_water_body_fraction Float32 4 N/A 0.0 1.0 -9999.0 6
surface_flag Uint16 2 N/A 0 65,536 65534 4
surface_temperature Float32 4 Kelvin 253.15 313.15 -9999.0 6
surface_water_fraction_mb_h Float32 4 N/A 0.0 1.0 -9999.0 1
surface_water_fraction_mb_v Float32 4 N/A 0.0 1.0 -9999.0 1
tb_3_corrected Float32 4 Kelvin -50.0 +50.0 -9999.0 1
tb_4_corrected Float32 4 Kelvin -50.0 +50.0 -9999.0 1
tb_h_corrected Float32 4 Kelvin 0.0 330.0 -9999.0 1
tb_h_uncorrected Float32 4 Kelvin 0.0 340.0 -9999.0 1
tb_qual_flag_3 Uint16 2 N/A 0 65,536 65534 4
tb_qual_flag_4 Uint16 2 N/A 0 65,536 65534 4
tb_qual_flag_h Uint16 2 N/A 0 65,536 65534 4
tb_qual_flag_v Uint16 2 N/A 0 65,536 65534 4
tb_time_seconds Float64 8 Second 0 N/A -9999.0 1
tb_time_utc Char24 24 N/A 2014-10-31T
00:00:00.000Z
N/A 16777214 1
tb_v_corrected Float32 4 Kelvin 0.0 330.0 -9999.0 3
tb_v_uncorrected Float32 4 Kelvin 0.0 340.0 -9999.0 1
vegetation_opacity Float32 4 N/A 0.00 5.00 -9999.0 5
vegetation_water_content Float32 4 kg/m2 0.0 30.0 -9999.0 6

** Derivation methods are:

  1. From SPL1CTB
  2. From 36 km EASE-Grid 2.0 array definition
  3. Value corrected for the presence of water wherever water/land areal fraction is below a threshold; when the fraction is zero, no correction is performed
  4. Determined by SPL2SMP processing software
  5. Available only with option algorithms that use two polarization channels
  6. From external ancillary data whose location and time stamp coincide with those of the input data
  7. From SPL2SMA
  8. Nearest-neighbor interpolation

Data Field Definitions

EASE_column_index

The column index of the 36 km grid cell that contains the associated data.

EASE_row_index

The row index of the 36 km grid cell that contains the associated data.

albedo

Daily global composite of single-scattering albedo at 36-km grid posting. Note that this parameter is the same ‘omega’ parameter in the ‘tau-omega’ model for a given polarization channel.

boresight_incidence

Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of incidence angles of L1B_TB observations whose boresights fall within a 36-km EASE-Grid 2.0 cell. The incidence angle is defined as the included angle between the antenna boresight vector and the normal to the Earth’s surface.

bulk_density
Daily global composite of bulk density at 36-km grid posting.

clay_fraction
Daily global composite of clay fraction at 36-km grid posting.

freeze_thaw_fraction

Daily global composite of freeze/thaw areal fraction at 36-km grid posting . The fraction is computed based on the number of frozen land pixels and thawed land pixels reported on the 3-km global cylindrical EASE-Grid 2.0 projection in the SMAP Level 2 Active Soil Moisture Product (L2_SM_A). If there are NF frozen ground pixels and NT thawed land pixels within a 36-km grid cell, this parameter refers to the fraction of NF / (NF + NT). At present the L2_SM_P processing software can be configured to provide this parameter from a dynamic ancillary data database or from the SMAP L2_SM_A product. Since the failure of the SMAP radar this field has been derived from external soil temperature ancillary data.

grid_surface_status

Surface type (land or water) as determined by the antenna boresight location.

landcover_class

Daily global composite of the first three most dominant land cover classes according to the IGBP land cover map. The relative dominance is determined based on ranking among land cover classes using statistical mode.

Table A2 provides a description of MODIS IGBP classes and the precentage of each land type.

Class Description Percentage
Table A2. MODIS IGBP Land Classification and Percentage
0 Water -
1 Evergreen Needleleaf Forest 3.96
2 Evergreen Broadleaf Forest 10.04
3 Deciduous Needleleaf Forest 0.63
4 Deciduous Broadleaf Forest 1.59
5 Mixed Forests 4.69
6 Closed Shrublands 0.55
7 Open Shrublands 18.26
8 Woody Savannas 7.52
9 Savannas 6.97
10 Grasslands 9.27
11 Permanent Wetlands 0.22
12 Croplands 8.95
13 Urban and Built-Up 0.50
14 Cropland/Natural Vegetation Mosaic 2.10
15 Snow and Ice 11.04
16 Barren or Sparsely Vegetated

13.70

landcover_class_fraction

Daily global composite of the areal fractions of the first three most dominant land cover classes according to a 500-meter MODIS IGBP land cover map. The relative dominance is determined based on ranking among all land cover classes using statistical mode. For example, if there are N1 pixels that correspond to first class and there are NT pixels comprising all land cover classes within a 36-km grid cells, the corresponding percentage refers to (N1 / NT).

Table A2 provides a description of MODIS IGBP classes and the precentage of each land type.

latitude

Latitude of the center of the 36-km EASE-Grid 2.0 cell.

latitude_centroid

Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of latitudes of L1B_TB observations whose boresights fall within a 36-km EASE-Grid 2.0 cell.

longitude

Longitude of the center of a 36-km EASE-Grid 2.0 cell.

longitude_centroid

Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of longitudes of L1B_TB observations whose boresights fall within a 36-km EASE-Grid 2.0 cell.

radar_water_body_fraction

Daily global composite of the radar-derived water body areal fraction at 36-km grid posting. The fraction is computed based on the number of water pixels and land pixels reported on the 3-km global cylindrical EASE-Grid 2.0 projection in the SMAP Level 2 Active Soil Moisture Product (L2_SM_A). If there are NW water pixels and NL land pixels within a 36-km grid cell, this parameter refers to the fraction of NW / (NW + NL). Note that NW is the number of water pixels regardless of their temporal span – NW captures both static water pixels and transient water pixels. Since the failure of the SMAP radar this field has been set to the static_water_body_fraction field.

retrieval_qual_flag

Daily global composite of a 16-bit binary string of 1’s and 0’s that indicate whether retrieval was performed or not at a given grid cell. When retrieval was performed, it contains additional bits to further indicate the exit status and quality of the retrieval. A summary of bit definition of the retrieval_qual_flag field is listed in Table A3. The retrieval_qual_flag field is internally linked to the output produced by the baseline algorithm (option 2 as of now).

Table A3. Retrieval Quality Flag Definition
Bit Retrieval Information Bit Value and Interpretation
0 Recommended Quality 0: Soil moisture retrieval has recommended quality
1: Soil moisture retrieval has uncertain quality
1 Retrieval Attempted 0: Soil moisture retrieval was attempted
1: Soil moisture retrieval was skipped
2 Retrieval Successful 0: Soil moisture retrieval was successful
1: Soil moisture retrieval was not successful
3* Retrieval Successful 0: Freeze/thaw state retrieval was successful
1: Freeze/thaw state retrieval was not successful
4-15 Undefined 0 (not used in this product)

roughness_coefficient

Daily global composite of roughness coefficient at 36-km grid posting. Note that this parameter is the same ‘h’ coefficient in the ‘tau-omega’ model for a given polarization channel.

soil_moisture

Daily global composite of the estimated soil moisture at 36-km grid posting, as returned by the L2_SM_P processing software. The soil_moisture field is internally linked to the output produced by the baseline algorithm (option 2 as of now).

soil_moisture_error

Daily global composite of the estimated ‘1-sigma’ error of the soil_moisture output parameter. The valid minimum and maximum below are subject to further analysis on real data. This data field is currently filled with FillValue.

static_water_body_fraction

Daily global composite of the static water body areal fraction at 36-km grid posting . The fraction is computed based on the number of water pixels and land pixels reported on a 250-meter grid. If there are NW water pixels and NL land pixels within a 36-km grid cell, this parameter refers to the fraction of NW / (NW + NL). Note that NW is the number of water pixels regardless of their temporal span – NW captures both static water pixels and transient water pixels when the original data was acquired.

surface_flag

Daily global composite of a 16-bit binary string of 1’s and 0’s that indicate the presence or absence of certain surface conditions at a grid cell. In Table A4, a ‘0’ indicates the presence of a surface condition favorable to soil moisture retrieval. Each surface condition is numerically compared against two non-negative thresholds: T1 and T2, where T1 < T2. In most cases, when a surface condition is found to be below T1, retrieval is attempted and flagged for recommended quality. Between T1 and T2, retrieval is still attempted but flagged for uncertain quality. Above T2, retrieval is skipped. A summary of surface conditions and their thresholds are listed in Table A4.

Note: Bit position '0' refers to the least significant bit. Final bit positions and definitions are subject to future revision and expansion as needed.

Table A4. Surface Condition Bit Flag Definition
Bit
Surface Condition
T1
T2
Bit Value and Interpretation
0
Static Water
0.05
0.50
0: Water areal fraction ≤ T1 and IGBP wetland fraction < 0.50:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
1
Radar-derived Water Fraction
0.05
0.50
0: Water areal fraction ≤ T1 and IGBP wetland fraction < 0.50:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
2
Coastal Proximity
N/A
1.0
0: Distance to nearby significant water bodies > T2 (number of 36-km grid cells)
1: Otherwise
3
Urban Area
0.25
1.00
0: Urban areal fraction ≤ T1:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
4
Precipitation
2.78e-04 (equivalent to
1.0 mm/hr)
7.06e-03 (equivalent to
25.4 mm/hr)
0: Precipitation fraction ≤ T1:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
5
Snow
0.05
0.50
0: Snow areal fraction ≤ T1:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
6
Permanent Ice
0.05
0.50
0: Ice areal fraction ≤ T1:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
7
Frozen Ground* (from radiometer-derived FT state)
0.05
0.50
0: Freeze ground areal fraction ≤ T1:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
8
Frozen Ground (from modeled effective soil temperature)

 
0.05
0.50
0: Freeze ground areal fraction ≤ T1:
  • Retrieval attempted for fraction ≤ T2
1: Otherwise:
  • Retrieval skipped for fraction > T2
9
Mountainous Terrain
0: Slope standard deviation ≤ T1
1: Otherwise
10
Dense Vegetation
5.0
30.0
0: Vegetation Water Content (VWC) ≤ T1:
  • Retrieval attempted for VWC ≤ T2
1: Otherwise:
  • Retrieval skipped for VWC > T2
11
Nadir Region / Undefined
0 (not used in this product)
12-15
Undefined
0

surface_temperature

Daily global composite of effective soil temperature (averaged over the top 5-cm soil layer) at 36-km spatial scale. This parameter is used as input ancillary data parameter to the L2_SM_P processing software for both baseline and option algorithms. The valid minimum and maximum below are subject to further analysis on real data.

It has come to our attention that this parameter is often mistaken for the physical temperature of the top soil layer. The designation “effective” signifies an attempt to capture the soil integrated temperature and canopy temperature in a single parameter, as is widely reported in the literature.  Depending on the actual emission sensing depth (which varies with soil moisture), this parameter usually does not coincide with a thermal physical temperature at a fixed depth (e.g. 5 cm or 10 cm).

surface_water_fraction_mb_h

Daily global composite of the water fraction with the SMAP radiometer main-beam (mb) IFOV weighted by antenna gain pattern at the horizontal polarization.

surface_water_fraction_mb_v
Daily global composite of the water fraction with the SMAP radiometer main-beam (mb) IFOV weighted by antenna gain pattern at the vertical polarization.

tb_3_corrected

Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of L1B_TB 3rd Stokes polarized brightness temperatures whose boresights fall within a 36-km EASE-Grid 2.0 cell.

tb_4_corrected

Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of L1B_TB 4th Stokes polarized brightness temperatures whose boresights fall within a 36-km EASE-Grid 2.0 cell.

tb_h_corrected

Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of L1B_TB horizontally polarized brightness temperatures whose boresights fall within a 36-km EASE-Grid 2.0 cell. Wherever water fraction is below a threshold, water brightness temperature correction is applied to this parameter prior to L2_SM_P inversion.

tb_h_uncorrected
Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of L1B_TB horizontally polarized brightness temperatures prior to water correction whose boresights fall within a 36-km EASE-Grid 2.0 cell.

tb_qual_flag_3

Daily global composite of a 16-bit or two-byte binary number formed by applying a Boolean ‘AND’ operation between the same parameters from both fore- and aft-looking groups in the input L1C_TB granule. A ‘0’ indicates that both the fore-looking and aft- looking L1C_TB observations satisfy a given quality criterion described in L1B_TB’s tb_qual_flag_3 output parameter; a ‘1’ indicates that the same criterion is violated by either fore-looking or aft-looking (or both) L1C_TB observations. Bit position '0' refers to the least significant digit. Bit positions are defined in Table A5.

Table A5. Quality Flag Bit Definitions
Bit Position Bit Value and Interpretation
0 0 = Observation has acceptable quality
1 = Observation does not have acceptable quality
1 0 = Observation within physical range
1 = Observation beyond physical range
2 0 = RFI was not detected in the observation
1 = RFI was detected in the observation
3 0 = RFI was detected and corrected in the observation
1 = RFI was detected by not correctable in the observation
4 0 = Observation has acceptable NEDT
1 = Observation did not have acceptable NEDT
5 0 = Direct sun correction was successful
1 = Direct sun correction was not successful
6 0 = Reflected sun correction was successful
1 = Reflected sun correction was not successful
7 0 = Reflected moon correction was successful
1 = Reflected moon correction was not successful
8 0 = Direct galaxy correction was successful
1 = Direct galaxy correction was not successful
9 0 = Reflected galaxy correction was successful
1 = Reflected galaxy correction was not successful
10 0 = Atmosphere correction was successful
1 = Atmosphere correction was not successful
11 Intentionally left undefined
12 0 = Observation was a valid value
1 = Observation was a null value
13 0 = Observation was within half orbit
1 = Observation was outside half orbit
14 0 = TA minus TA_FILTERED was less than a threshold
1 = TA minus TA_FILTERED was greater than a threshold
15 0 = Observation was free of RFI
1 = Observation was RFI contaminated

tb_qual_flag_4

Daily global composite of a 16-bit or two-byte binary number formed by applying a Boolean ‘AND’ operation between the same parameters from both fore- and aft-looking groups in the input L1C_TB granule. A ‘0’ indicates that both the fore-looking and aft- looking L1C_TB observations satisfy a given quality criterion described in L1B_TB’s tb_qual_flag_4 output parameter; a ‘1’ indicates that the same criterion is violated by either fore-looking or aft-looking (or both) L1C_TB observations. Bit position '0' refers to the least significant digit. Bit positions are defined in Table A5.

tb_qual_flag_h

Daily global composite of a 16-bit or two-byte binary number formed by applying a Boolean ‘AND’ operation between the same parameters from both fore- and aft-looking groups in the input L1C_TB granule. A ‘0’ indicates that both the fore-looking and aft- looking L1C_TB observations satisfy a given quality criterion described in L1B_TB’s tb_qual_flag_h output parameter; a ‘1’ indicates that the same criterion is violated by either fore-looking or aft-looking (or both) L1C_TB observations. Bit position '0' refers to the least significant digit. Bit definitions are defined in Table A6.

Table A6. Quality Flag Bit Definitions
Bit Position Bit Value and Interpretation
0 0 = Observation has acceptable quality
1 = Observation does not have acceptable quality
1 0 = Observation within physical range
1 = Observation beyond physical range
2 0 = RFI was not detected in the observation
1 = RFI was detected by not correctable in the observation
3 0 = RFI was detected and corrected in the observation
1 = RFI was detected but not correctable in the observation
4 0 = Observation had acceptable NEDT
1 = Observation did not have acceptable NEDT
5 0 = Direct sun correction was successful
1 = Direction sun correction was not successful
6 0 = Reflected sun correction was successful
1 = Reflected sun correction was not successful
7 0 = Reflected moon correction was successful
1 = Reflected moon correction was not successful
8 0 = Direct galaxy correction was successful
1 = Direct galaxy correction was not successful
9 0 = Reflected galaxy correction was successful
1 = Reflected galaxy correction was not successful
10 0 = Atmosphere correction was successful
1 = Atmosphere correction was not successful
11 0 = Faraday rotation correction was successful
1 = Faraday rotation correction was not successful
12 0 = Observation was a valid value
1 = Observation was a null value
13 0 = Water correction was not performed
1 = Water correction was performed
14 0 = TA minus TA_FILTERED was less than a threshold
1 = TA minus TA_FILTERED was greater than a threshold
15 0 = Observationw as free of RFI
1 = Observation was RFI contaminated

tb_qual_flag_v

Daily global composite of a 16-bit or two-byte binary number formed by applying a Boolean ‘AND’ operation between the same parameters from both fore- and aft-looking groups in the input L1C_TB granule. A ‘0’ indicates that both the fore-looking and aft- looking L1C_TB observations satisfy a given quality criterion described in L1B_TB’s tb_qual_flag_v output parameter; a ‘1’ indicates that the same criterion is violated by either fore-looking or aft-looking (or both) L1C_TB observations. Bit position '0' refers to the least significant digit. Bit definitions are defined in Table A6.

tb_time_seconds

Daily composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the average of UTC acquisition times of L1B_TB observations whose boresights fall within a 36-km EASE-Grid 2.0 cell. The result is then expressed in J2000 seconds (the number of seconds since 12:00:00.000 on January 1, 2000 Barycentric Dynamical Time (TDB)).

tb_time_utc

Daily composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the average of UTC acquisition times, in ASCII representation, of L1B_TB observations whose boresights fall within a 36-km EASE-Grid 2.0 cell.

tb_v_corrected

Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of L1B_TB vertically polarized brightness temperatures whose boresights fall within a 36-km EASE-Grid 2.0 cell. Wherever water fraction is below a threshold, water brightness temperature correction is applied to this parameter prior to L2_SM_P inversion.

tb_v_uncorrected
Daily global composite of the arithmetic average of the same parameters found in the fore- and aft-looking groups in the input L1C_TB granule. The resulting parameter thus describes the weighted average of L1B_TB vertically polarized brightness temperatures prior to water correction whose boresights fall within a 36-km EASE-Grid 2.0 cell.

vegetation_opacity

Daily global composite of the estimated vegetation opacity at 36-km grid posting, as returned by the L2_SM_P processing software. Note that this parameter is the same ‘tau’ parameter normalized by the cosine of the incidence angle in the ‘tau-omega’ model:

tau-omega equation
where b is a landcover-based parameter described in the SMAP Level 2/3 Passive Soil Moisture Product ATBD, VWC is vegetation water content in kg/m2 derived from NDVI climatology, and + is the incidence angle (= 40 deg) for SMAP. The valid minimum and maximum below are subject to further analysis on real data. The vegetation_opacity field is internally linked to the output produced by the baseline algorithm (option 2 as of now).

vegetation_water_content

Daily global composite of the vegetation water content at 36-km grid posting. This parameter is used as input ancillary data parameter to the L2_SM_P processing software when the baseline algorithm is used. The valid minimum and maximum below are subject to further analysis on real data.

Fill/Gap Values

SMAP data products employ fill values to indicate when no valid data appear in a particular data element. Fill values ensure that data elements retain the correct shape. Gap values locate portions of a data stream that do not appear in the output data file.

Fill values appear in the SPL3SMP product when the SPL3SMP SPS can process some, but not all, of the input data for a particular swath grid cell. Fill data may appear in the product in any of the following circumstances:

  • One of Science Production Software (SPS) executables that generate the SMAP SPL3SMP product is unable to calculate a particular science or engineering data value. The algorithm encounters an error. The error disables generation of valid output. The SPS reports a fill value instead.
  • Some of the required science or engineering algorithmic input are missing. Data over the region that contributes to particular grid cell may appear in only some of the input data streams. Since data are valuable, the SPL3SMP product records any outcome that can be calculated with the available input. Missing data appear as fill values.
  • Non-essential information is missing from the input data stream. The lack of non-essential information does not impair the algorithm from generating needed output. The missing data appear as fill values.
  • Fill values appear in the input radiometer SPL1CTB product.

SMAP data products employ a specific set of data values to connote that an element is fill. The selected values that represent fill are dependent on the data type. 

No valid value in the SPL3SMP product is equal to the values that represent fill. If any exceptions should exist in the future, the SPL3SMP content will provide a means for users to discern between elements that contain fill and elements that contain genuine data values. This document will also contain a description of the method used to ascertain which elements are fill and which elements are genuine.

The SPL3SMP product records gaps when entire frames within the time span of a particular data granule do not appear. Gaps can occur under one of two conditions:

  • One or more complete frames of data are missing from all data streams.
  • The subset of input data that is available for a particular frame is not sufficient to process any frame output.

The SPL1CTB product records gaps in the product level metadata. The following conditions will indicate that no gaps appear in the data product:

  • Only one instance of the attributes Extent/rangeBeginningDateTime and Extent/rangeEndingDateTime will appear in the product metadata.
  • The character string stored in metadata element Extent/rangeBeginningDateTime will match the character string stored in metadata element OrbitMeasuredLocation/halfOrbitStartDateTime.
  • The character string stored in metadata element Extent/rangeEndingDateTime will match the character string stored in metadata element OrbitMeasuredLocation/halfOrbitStopDateTime.

One of two conditions will indicate that gaps appear in the data product:

  • The time period covered between Extent/rangeBeginningDateTime and Extent/RangeEndingDateTime does not cover the entire half orbit as specified in OrbitMeasuredLocation/halfOrbitStartDateTime and OrbitMeasuredLocation/halfOrbitStartDateTime.
  • More than one pair of Extent/rangeBeginningDateTime and Extent/rangeEndingDateTime appears in the data product. Time periods within the time span of the half orbit that do not fall within the sets of Extent/rangeBeginningDateTime and Extent/rangeEndingDateTime constitute data gaps.

Acronyms and Abbreviations

Table A7 lists the acronyms and abbreviations used in this document.

Table A7. Acronyms and Abbreviations
Abbreviation Definition
Char 8-bit character
IGBP International Geosphere-Biosphere Programme
Int8 8-bit (1-byte) signed integer
Int16 16-bit (2-byte) signed integer
Int32 32-bit (4-byte) signed integer
Float32 32-bit (4-byte) floating-point integer
Float64 64-bit (8-byte) floating-point integer
H-pol Horizontally polarized
N/A Not Applicable
NF Number of frozen ground pixels
NL Number of land pixels
NT Number of thawed land pixels
NW Number of water pixels
SI International System of Units
SPL3SMP SMAP L3 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture
SPS Science Production Software
T1, T2 Threshold 1, Threshold 2
TB Brightness Temperature
Uint8 8-bit (1-byte) unsigned integer
Uint16 16-bit (2-byte) unsigned integer
UTC Universal Coordinated Time
V-pol Vertically polarized
VWC Vegetation Water Content

How To

Programmatically access to data with services such as subsetting, reformatting, and reprojection
This article provides a step-by-step getting started guide to utilizing an Application Programming Interface, or API, for programmatic access to data from the NSIDC Distributed Active Archive Center (DAAC) based on spatial and temporal filters, as well as subsetting, reformatting, and... read more
How to import and geolocate SMAP Level-3 and Level-4 data in ENVI
The following are instructions on how to import and geolocate SMAP Level-3 Radiometer Soil Moisture HDF5 data in ENVI. Testing notes Software: ENVI Software version: 5.3 Platform: Windows 7 Data set: SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil... read more
How do I visualize SMAP data in Worldview?
This video tutorial provides step-by-step instructions on how to visualize SMAP data in Worldview (http://worldview.earthdata.nasa.gov/). NASA Worldview is a map-based application... read more
How do I search, order, and customize SMAP data using Earthdata Search?
In this step-by-step tutorial, we will demonstrate how to search, order, and customize NASA Soil Moisture Active Passive, or SMAP data using the NASA Earthdata Search application. NASA Earthdata search provides an interactive map-based search environment where you can filter your results based on... read more
How do I interpret the surface and quality flag information in the Level-2 and -3 passive soil moisture products?
SMAP data files contain rich quality information that can be useful for many data users. The retrieval quality flag and surface flag bit values and interpretations are documented in the respective product Data Fields pages: Level-2 soil moisture product (SPL2SMP)... read more
How to Import SMAP HDF Data Into ArcGIS
Selected SMAP L4, Version 4 HDF data (SPL4SMAU, SPL4SMGP, & SPL4SMLM) can be added to ArcGIS with a simple drag/drop or using the 'Add Data' function. These data can be imported and visualized but not geolocated. In order to import, project, and scale these data and other SMAP L3 and L4 HDF... read more
How do I access data using OPeNDAP?
Data can be programmatically accessed using NSIDC’s OPeNDAP Hyrax server, allowing you to reformat and subset data based on parameter and array index. For more information on OPeNDAP, including supported data sets and known issues, please see our OPeNDAP documentation: ... read more
How to extract point and area samples of SMAP data using AppEEARS
This step-by-step tutorial demonstrates how to access NASA SMAP data using the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS). AppEEARS allows users to obtain and display point and area data using spatial, temporal, and layer subsets. SMAP data from NSIDC that are... read more
How to learn more about SMAP ancillary data
SMAP Ancillary data sets are used to produce SMAP Level-1, -2, -3, and -4 standard data products. Several of these ancillary data sets are produced by external organizations, such as NOAA, the NASA Global Modeling and Assimilation... read more
How to visualize SMAP WMS layers with ArcGIS and Google Earth
NASA's Global Imagery Browse Services (GIBS) provides up to date, full resolution imagery for selected SMAP data sets. Adding GIBS layers via OGC methods, such as Web Map Service (WMS), Web Map Tile Service (WMTS) and Tiled Web Map Service (TWMS) provides an easy way to visualize the entire time... read more

FAQ

What are the latencies for SMAP radiometer data sets?
The following table describes both the required and actual latencies for the different SMAP radiometer data sets. Latency is defined as the time (# days, hh:mm:ss) from data acquisition to product generation. Short name Title Latency Required Actual (mean1) SPL1AP SMAP L1A... read more
What data subsetting, reformatting, and reprojection services are available for SMAP data?
The following table describes the data subsetting, reformatting, and reprojection services that are currently available for SMAP data via the NASA Earthdata Search tool and a Data Subscription... read more