Data Set ID:

SMAP Enhanced L3 Radiometer Global and Northern Hemisphere Daily 9 km EASE-Grid Freeze/Thaw State, Version 2

This enhanced Level-3 (L3) product provides a daily composite of global and Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1C (L1C) interpolated brightness temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures. The data are then posted to two 9 km Earth-fixed, Equal-Area Scalable Earth Grids, Version 2.0 (EASE-Grid 2.0): a global cylindrical and a Northern Hemisphere azimuthal.

This is the most recent version of these data.

Version Summary:

Changes to this version include:

  • Implementation of a supplementary single-channel V-pol (SCV) algorithm
    for areas of lower latitudes where the seasonal difference of the NPR algorithm is
    too small to be effectively used to discriminate freeze/thaw state. This change
    provides stronger flag agreement between Tair and Tsoil, and for ascending/p.m.
    versus descending/a.m. overpasses due to physics (e.g. the NPR algorithm response to wet snow over frozen soil in spring). It also addresses an artifact of the validation approach (e.g. soils remain thawed for weeks after freeze onset in fall
    due to insulation from snow).
  • With the addition of the new SCV algorithm to augment the NPR baseline
    algorithm, spatial coverage of freeze/thaw data was extended to global. Data are
    output on a fixed global 36 km EASE-Grid 2.0 and are provided in the Freeze_Thaw_Retrieval_Data_Global group.
  • Updated retrieval_quality_flag for water contamination/permanent
  • Implementation of false flag mitigation using TB screening and AMSR-E
    weekly climatology maps, resulting in significantly fewer false flags.

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

  • Microwave > Brightness Temperature
  • Snow/Ice > Freeze/Thaw > Freeze/Thaw State
  • Snow/Ice > Freeze/Thaw > Transition Direction
Data Format(s):
  • HDF5
Spatial Coverage:
N: 85.044, 
N: 85.044, 
S: 45, 
S: -85.044, 
E: 180, 
E: 180, 
W: -180
W: -180
Platform(s):SMAP Observatory
Spatial Resolution:
  • 9 km x 9 km
Temporal Coverage:
  • 31 March 2015
Temporal Resolution1 dayMetadata XML:View Metadata Record
Data Contributor(s):Xu, X., R. S. Dunbar, C. Derksen, A. Colliander, Y. Kim, and J. S. Kimball.

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.

Xu, X., R. S. Dunbar, C. Derksen, A. Colliander, Y. Kim, and J. S. Kimball. 2018. SMAP Enhanced L3 Radiometer Global and Northern Hemisphere Daily 9 km EASE-Grid Freeze/Thaw State, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: [Date Accessed].
4 January 2019
Last modified: 
7 August 2019

Data Description


Freeze/thaw (F/T) state and the direction of diurnal freeze/thaw transitions (frozen in the morning to thawed in the afternoon and vice versa) derived from brightness temperatures are output on two 9 km Earth-fixed, Equal-Area Scalable Earth Grids, Version 2.0 (EASE-Grid 2.0): a global cylindrical and a Northern Hemisphere azimuthal. Freeze/thaw state, the occurrence of freeze/thaw transitions, and the direction of transitions are expressed in boolean values (0 or 1). For freeze/thaw state, 0 indicates thawed conditions and 1 indicates frozen. For freeze/thaw transition state, 1 indicates the a.m. and p.m. FT states are not in transition and 2 indicates they are in transition. The transition direction flag is only meaningful if there is a transition (transition state = 2), and is set to 2 for a.m. frozen/p.m. thawed and 1 for a.m. thawed/p.m. frozen. 

Also included are brightness temperatures (TBs) in kelvin for a 36 km EASE-Grid 2.0 cell.

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

File Information


Data are in HDF5 format. For software and more information, including an HDF5 tutorial, visit the HDF Group's HDF5 website.

File Contents

As shown in Figure 1, each HDF5 file is organized into the following main groups, which contain additional groups and/or data sets:

Figure 1. Subset of File Contents
For a complete list of file contents for the SMAP enhanced Level-3 freeze/thaw product, refer to the Data Fields page. 

Data Fields

Each file contains the main data groups summarized in this section. For a complete list and description of all data fields within these groups, refer to the Data Fieldsdocument.

Data element arrays are three dimensional, with the exception of transition_direction and transition_state_flag arrays, which are two dimensional. Arrays in the Polar group have dimensions of 2000 rows and 2000 columns in each a.m. and p.m. layer; the Global group array dimensions are 1624 rows x 3856 columns. For the a.m./p.m. index of the array, the a.m. layer is assigned to the index value 0 and the p.m. layer is assigned to index value 1.

Freeze/Thaw Retrieval Data Global

Includes freeze/thaw data, latitude and longitude arrays, and associated quality assessment flags. Also includes all ancillary data, such as landcover classification and open water body fraction, and all radiometer data and associated quality assessment flags. Data are provided in the 9 km Global EASE-Grid 2.0 projection.

Freeze/Thaw Retrieval Data Polar

Contains the same data fields as the global projection group, but data are provided in the 9 km Northern Hemisphere azimuthal EASE-Grid 2.0 projection. 

Metadata Fields

Includes all metadata that describe the full content of each file. For a description of all metadata fields for this product, refer to the Metadata Fields document.

File Naming Convention

Files are named according to the following convention, which is described in Table 1:


For example:



Table 1. File Naming Conventions
Variable Description
SMAP Indicates SMAP mission data
L3_FT_P_E Indicates specific product (L3: Level-3; FT: Freeze/Thaw; P: Passive; E: Enhanced)
yyyymmdd 4-digit year, 2-digit month, 2-digit day; date in Universal Coordinated Time (UTC) 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 Number of times the file was generated under the same version for a particular date/time interval (002: 2nd time)
.[ext] File extensions include:
.h5 HDF5 data file
.qa Quality Assurance file
.xml XML Metadata file

File Size

Each file is approximately 65 MB.

File Volume

The daily data volume is approximately 65 MB.

Spatial Information


Coverage for the the Northern Hemisphere EASE-Grid 2.0 projection extends to all land regions north of 45°N latitude, and from 180°W to 180°E. For the global EASE-Grid 2.0 projection, coverage spans from 180°W to 180°E, and from approximately 85.044°N and 85.044°S. The gap in coverage at the North Pole, called a pole hole, has a radius of approximately 400 km. The swath width is 1000 km, enabling nearly complete global coverage every two to three days.


The native spatial resolution of the radiometer footprint is 36 km. Data are then interpolated using the Backus-Gilbert optimal interpolation algorithm into the Northern Hemisphere azimuthal EASE-Grid 2.0 projection with 9 km spacing.

EASE-Grid 2.0

These data are provided on the global cylindrical and Northern Hemisphere azimuthal EASE-Grid 2.0 (Brodzik et al. 2012). Each grid cell has a nominal area of approximately 9 x 9 km2 regardless of longitude and latitude. Using this projection, north polar data arrays have dimensions of 2000 rows and 2000 columns, and global data arrays have dimensions of 1624 rows and 3856 columns.

EASE-Grid 2.0 has a flexible formulation. By adjusting a single scaling parameter, a family of multi-resolution grids that nest within one another can be generated. The nesting can be adjusted so that smaller grid cells can be tessellated to form larger grid cells. Figure 2 shows a schematic of the nesting.

This feature of perfect nesting provides SMAP data products with a convenient common projection for both high-resolution radar observations and low-resolution radiometer observations, as well as for their derived geophysical products. For more on EASE-Grid 2.0, refer to the EASE Grids website.

Figure 2. Perfect Nesting in EASE-Grid 2.0

Temporal Information


Coverage spans from 31 March 2015 to the 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.

To ensure complete coverage of the freeze/thaw domain in each daily file, a.m. and p.m. data for the current day are combined with a.m. and p.m. data from previous days. A maximum of three days of past data is used, and is necessary only near the southern margin of the freeze/thaw domain.

Data Acquisition and Processing


The SPL3FTP_E product is derived using a temporal change detection approach that has been previously developed and successfully applied using time-series satellite remote sensing radar backscatter and radiometric brightness temperature data from a variety of sensors and spectral wavelengths. The approach is to identify the landscape freeze/thaw (F/T) state via the temporal response of the normalized polarization ratio (NPR) of the brightness temperature, which is sensitive to changes in the dielectric constant of the landscape that occur as the water within the components transitions between frozen and non-frozen conditions.

This approach assumes that the large changes in dielectric constant occurring between frozen and non-frozen conditions dominates the corresponding NPR temporal dynamics across the seasons, rather than other potential sources of temporal variability such as changes in canopy structure and biomass, large precipitation events, or changes in soil moisture.

However, in lower-latitude areas where the seasonal difference of the NPR is too small to be effectively used to discriminate F/T state, the V-polarization (V-pol) brightness temperature is compared to a threshold value to retrieve the F/T state. At very low latitudes where no F/T transitions occur, no algorithm is applied.


SMAP enhanced Level-3 radiometer freeze/thaw data (SPL3FTP_E) are derived from SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures, Version 1 (SPL1CTB_E).

Derivation Techniques and Algorithms

This section has been adapted from Dunbar et al. (2016), the Algorithm Theoretical Basis Document (ATBD) for this data set.

This product (SPL3FTP_E) is an enhanced version of the SMAP L3 Radiometer Northern Hemisphere Daily 36 km EASE-Grid Freeze/Thaw State (SPL3FTP) product. Both products are derived using the same techniques and algorithms described in this section.

For information regarding the Backus-Gilbert optimal interpolation algorithm used to enhance the input data for this product, refer to the SPL1CTB_E user guide.

The SMAP enhanced Level-3 radiometer freeze/thaw product is derived from SMAP L1C Enhanced Radiometer Half-Orbit 36 km EASE-Grid Brightness Temperatures, Version 3 (SPL1CTB_E). The derivation of freeze/thaw from SMAP brightness temperature measurements occurs during an intermediate Level-2 processing step of the input Level-1 brightness temperature data. During the Level-2 processing step, the freeze/thaw algorithm utilizes a seasonal threshold approach to convert SMAP brightness temperature measurements to freeze/thaw state. For an overview of the steps involved in processing this data product, refer to Figure 4 in the Processing Steps section.

Baseline NPR Algorithm

The SPL3FTP_E freeze/thaw baseline algorithm examines the time series progression of the brightness temperature signature relative to signatures acquired during seasonal reference frozen and thawed states. The algorithm uses the normalized polarization ratio (NPR) of SMAP radiometer measurements defined by:

NPR=(TBV-TBH)/(TBV+TBH)      (Equation 1)

A seasonal scale factor D(t) is defined for an observation acquired at time t as:

Dt=(NPR(t)-NPR(fr))/(NPR(th)-NPR(fr))      (Equation 2)

where NPR(t) is the normalized polarization ratio calculated at time t, for which a freeze/thaw classification is sought, and NPR(fr) and NPR(th) are normalized polarization ratios corresponding to the frozen and thawed reference states, respectively. The twenty lowest/highest NPR values from SMAP radiometer measurements during July and August 2015 (thaw) and January and February 2018 (freeze) for the northern (≥45°N) domain were retained and averaged to create the freeze/thaw reference. Data were separated by ascending and descending orbit. The methodological approach to NPR freeze and thaw references will continue to be refined in future product releases. In addition, the SMAP reference values are updated following each transition season. Reprocessing of the SMAP data record to incorporate annual variations in the SMAP freeze/thaw reference states should improve product accuracy over the use of static reference conditions. The SMAP freeze and thaw NPR references are shown in Figures 3a through 3c below (and in Section 4.2.2 of the ATBD).

Initial SMAP freeze and thaw NPR references
Figure 3. SMAP Freeze and Thaw NPR References
SMAP radiometer (a) freeze and (b) thaw references; (c) reference difference between panels (a) and (b). Units are NPR-scaled by 100. References for this version cover July and August 2015 (thaw) and January and February 2018 (freeze). 

A threshold level is then defined such that:

D(t) > T       (thaw)
D(t) <=T
      (freeze)      (Equation 3)

defines the thawed and frozen landscape states, respectively. This series of equations (1-3) are run on a grid cell-by-cell basis for unmasked portions of the F/T domain. The output from Equation 3 is a dimensionless binary state variable designating either frozen or thawed conditions for each unmasked grid cell. The threshold values can be optimized on a grid-cell-by-grid-cell basis. Optimization approaches will be evaluated in advance of future product releases.

SCV Algorithm

The single-channel V-pol (SCV) freeze/thaw algorithm has been introduced in this version to address the areas at lower latitudes where the NPR seasonal F/T reference difference is too small to adequately discriminate the F/T state. This algorithm, originally developed for use with AMSR-E data and applied here using SMAP data, assigns a V-pol brightness temperature threshold, and provides a value of the correlation between the brightness temperature and physical surface temperature to each pixel. Depending on the sign of the SCV correlation Rscv (retrieved SCV), the F/T state is assigned as follows:

Equation 4 & 5 SPL3FTP    (Equation 4)

The SCV retrievals are flagged in the retrieval_quality_flag when the absolute value Rscv ≤ 0.5. The retrieval_algorithm_flag element indicates whether the NPR algorithm (value=1) or the SCV algorithm (value=2) were applied in the pixel. A value of 0 for the retrieval_algorithm_flag indicates that no retrieval was performed in the pixel.

False Flag Mitigation

Following the pixel-wise determination of freeze/thaw state, two additional processing steps are applied to mitigate summer season false freeze and winter season false thaw retrievals. First, if the brightness temperature magnitude at either V- or H-pol is greater than 273 K, the pixel is set to thaw regardless of the retrieval. Second, a temporally fixed 'never frozen' mask calculated from weekly AMSR-E freeze/thaw maps (using the approach described in Kim et al. 2012) is applied to remove obviously false summer freeze flags. False freeze retrievals occur in some regions of the F/T domain because of small differences between the reference freeze and thaw values (see Figure 3c). Implementation of weekly AMSR-E-derived ‘never frozen’ and ‘never thawed’ climatology masks in this release has significantly reduced the occurrence of false flags in the F/T retrievals.

Ancillary Data

Ancillary data sets are used to:

  1. Support initialization of the thresholds employed in the algorithm
  2. Set flags that indicate potential problem regions
  3. Define masks where no retrievals should be performed

Ancillary data used in SPL3FTP_E processing includes data sets of inland open water, permanent ice and snow, and urban areas in order to derive masks so that no retrievals occur over these regions. Ancillary data sets of mountainous areas, fractional open water cover, and precipitation are used to derive flags so that a confidence interval can be associated with the retrieval. All ancillary data sets are resampled to a spatial scale and geographic projection that matches the SPL3FTP_E product in accordance with the guidelines of the SMAP mission.

Ancillary data sets used for SPL3FTP_E data processing were in place prior to launch, with no need for periodic updates during post-launch operations. A continuous surface map of fractional area of open water was used to represent fractional water coverage within a grid consistent with the resolution and projection of the SPL3FTP_E product. For the SPL3FTP_E development, the lake fraction threshold within a grid cell was set to 50%. Determination of a physically-based lake fraction will be finalized for a forthcoming SPL3FTP_E release. Table 2 lists the ancillary data employed in support of SPL3FTP_E production. Similar ancillary data were used for production of the SMAP radar freeze/thaw (SPL3FTA) product.

Table 2. Input Ancillary Data for SPL3FTP_E
Data Type Data Source(s) Frequency Resolution Extent Use
Vegetation Type Moderate Resolution Imaging Spectroradiometer International Geosphere Biosphere Programme (MODIS-IGBP) Once 250 m Global Sensitivity Analysis
Global Modeling and Assimilation Office (GMAO) Analyses Time of Acquisition 0.25 degrees Global Sensitivity Analysis

Static Water Bodies

MODIS Land-Water Mask (MODIS44W) Once 250 m Global Mask/Flag
Mountainous Areas NASA Global Digital Elevation Model (DEM) Once 30 m Global Mask/Flag
Permanent Ice and Snow MODIS-IGBP Permanent Ice and Snow Class Once 500 m Global Mask/Flag
Seasonal Snow National Oceanic and Atmospheric Administration/National Ice Center Interactive Multisensor Snow and Ice Mapping System (NOAA IMS) Daily 1 km Northern Hemisphere Flag
Never-Thawed/Never-Frozen Masks Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Annual 25 km Northern Hemisphere False Flag Mitigation

For more information, refer to the ATBD for this product (Dunbar et al. 2016).


This product is generated by the SMAP Science Data Processing System (SDS) at the Jet Propulsion Laboratory (JPL) in Pasadena, California USA. Figure 4 shows the processing sequence for generation of the SMAP enhanced L3 freeze/thaw (F/T) radiometer product (SPL3FTP_E).

The derivation of freeze/thaw from SMAP brightness temperature measurements occurs during an intermediate Level-2 processing step of the input enhanced Level-1C brightness temperature data. During the Level-2 processing step, the freeze/thaw algorithm utilizes a seasonal threshold approach to convert SMAP brightness temperature measurements to freeze/thaw state.

To generate this product, the processing software:

  1. Ingests one day's worth of Level-1C files and creates individual global and Northern Hemisphere composites as two-dimensional or three-dimensional arrays for each output parameter defined in the Level-1C data
  2. Intermediate Level-2 processing step:
    Converts SMAP brightness temperature measurements to freeze/thaw state. Classifies frozen and thawed landscape states on a grid cell-by-cell basis for unmasked portions of the FT domain by:
    1. Utilizing the NPR of SMAP radiometer measurements—or for areas of low latitudes, utilizing the SCV of SMAP radiometer measurements—during seasonal reference frozen and thawed states
    2. Where utilizing SCV, applies a fixed threshold of 0.5 to determine either frozen or thawed conditions relative to the reference states
    3. Employing ancillary data sets to set flags for potential problem regions, and define masks where no retrievals should be performed
    4. Mitigating summer season false freeze and winter season false thaw retrievals by:
      1. Designating pixels as 'thaw' when TB magnitude at V or H pol is greater than 273 K
      2. Applying a fixed AMSR-E derived 'never frozen' mask
  3. The processing software then combines a.m. and p.m. data for the current day with a.m. and p.m. data from previous days to ensure complete coverage of the freeze/thaw domain in each daily file. Note that a maximum of three days of past data is used, and is necessary only near the southern margin of the freeze/thaw domain. Wherever data overlap occurs, as is typical at high latitudes, data which were acquired closest to 6:00 a.m. and 6:00 p.m. local solar times are chosen.

For details regarding each of these processing steps, refer to the Derivation Techniques and Algorithms section of this document.

    SPL3FTP Processing Flow
    Figure 4. Processing Sequence for the Enhanced L3 Freeze/Thaw Radiometer Product (SPL3FTP_E)

    As a result, the output enhanced Level-3 radiometer freeze/thaw product distinguishes four levels of freeze/thaw conditions determined from the ascending 6:00 a.m. and descending 6:00 p.m. SPL1CTB_E data, including:

    • Frozen (from both a.m. and p.m. overpass times)
    • Non-frozen (a.m. and p.m.)
    • Transitional (a.m. frozen; p.m. non-frozen)
    • Inverse-transitional (a.m. non-frozen; p.m. frozen)

    For more information on the algorithm processing flow, refer to the ATBD for this product, Section 2.2: L3_FT_P Production (Dunbar et al. 2016).

    Quality, Errors, and Limitations

    Error Sources

    Anthropogenic Radio Frequency Interference (RFI), principally from ground-based surveillance radars, can contaminate both radar and radiometer measurements at L-band. The SMAP radar and radiometer electronics and algorithms include design features to mitigate the effects of RFI. The SMAP radiometer utilizes selective filters and an adjustable carrier frequency to tune to predetermined RFI-free portions of the spectrum while on orbit.

    The landscape freeze/thaw state retrieval represented by the SPL3FTP algorithm and products characterizes the predominant frozen or non-frozen state of the land surface within the sensor Field of View (FOV) and does not distinguish freeze/thaw characteristics among different landscape elements, including surface snow, soil, open water, or vegetation. The lower frequency L-band retrievals from SMAP are expected to have greater sensitivity to surface soil freeze/thaw conditions under low to moderate vegetation cover. Microwave freeze/thaw sensitivity is strongly constrained by intervening vegetation biomass, soil moisture levels, and snow wetness. Ambiguity in relating changes in the radiometer signal to these specific landscape components is a challenge to validation of the freeze/thaw product (Colliander et al. 2012). In northern boreal and tundra landscapes, L-band penetration depth is greater under frozen conditions when land surface liquid water levels are low, and markedly reduced under thawed conditions due to characteristically moist surface organic layer and soil active layer conditions, even under relatively low tundra vegetation biomass levels (Du et al. 2014).

    Note that spatial classification error is expected to be larger in regions with small differences between frozen and thawed NPR references, particularly at lower latitudes. This includes areas where freeze/thaw is ephemeral and densely vegetated areas due to vegetation scattering effects on microwave emissivity. Small TB V- and H-polarization differences and lower NPR dynamic range increase the uncertainty in the retrievals using the NPR algorithm. In regions of complex terrain, freeze/thaw heterogeneity is greater which also adversely impacts retrieval performance. In arid regions, the small amount of water present in the thawed state makes the soil permittivity close to the frozen state, which can cause false freeze retrieval errors. These are largely mitigated through additional screening.

    To address spatial classification errors at lower latitudes, the SCV Algorithm assigns a V-pol brightness temperature (TBv) threshold and provides applies it on a pixel-by-pixel basis to determine freeze/thaw state using a computed value of the correlation between the TBv and physical surface temperature at each pixel. Additional mitigation steps for this version include brightness temperature screening and the use of a 'never frozen' mask based on AMSR-E weekly climatology maps. 

    Finally, a major assumption of the NPR seasonal threshold-based temporal change freeze/thaw classification is that the major temporal shifts in brightness temperature are caused by land surface dielectric changes from temporal freeze/thaw transitions. This assumption generally holds for higher latitudes and elevations where seasonal frozen temperatures are a significant part of the annual cycle and a large constraint to land surface water mobility and ecosystem processes (e.g., Kim et al. 2012). However, freeze/thaw classification accuracy is expected to be reduced where other environmental factors may cause large temporal shifts in brightness temperature, including large rainfall events and surface inundation, and changes in vegetation biomass (e.g. phenology, disturbance and land cover change). Winter season false thaw in areas of complex terrain are due to uncertainty in the references due to sub-grid heterogeneity. While there is a strong NPR response to freeze/thaw transitions, NPR is not stable during summer due to the influence of vegetation, soil moisture, etc. Depolarization of summer season measurements leads to false freeze retrievals that must be mitigated. To address this, a temporally fixed 'never frozen' mask calculated from weekly AMSR-E freeze/thaw maps has been implemented in this version to remove obviously false summer freeze flags; refer to the False Flag Mitigation section of this document for details. 

    For an assessment of algorithm performance and sources of uncertainty using in situ observations, and other satellite data sets, refer to the Validated Assessment Report for this product.

    Quality Assessment

    For in-depth details regarding the quality of these Version 1 Validated data, refer to the Validated Assessment Report.

    Quality Overview

    The SPL3FTP_E product has sufficient fidelity and accuracy to identify the primary seasonal freeze and thaw transitions, and distinguish diurnal freeze/thaw state changes common during seasonal transitions.

    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 Data Fields and Metadata Fields documents.

    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 metadata file with an .xml file extension is also delivered to NSIDC DAAC with the HDF5 file; it contains the same information as the HDF5 file-level metadata.

    A separate QA file with a .qa file extension is also associated with each data file. QA files are ASCII text files that contain statistical information in order 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.



    For a detailed description of the SMAP instrument, visit the SMAP Instrument page at the JPL SMAP website.

    Software and Tools

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

    Version History

    Document Creation Date

    December 2016

    Document Revision Date

    June 2018

    Related Data Sets

    SMAP Data at NSIDC | Overview

    SMAP Radar Data at the ASF DAAC

    Related Websites


    Contacts and Acknowledgments


    Xiaolan Xu, Scott Dunbar, Andreas Colliander
    Jet Propulsion Laboratory
    California Institute of Technology
    Pasadena, CA 91109 USA

    Chris Derksen
    Climate Research Division 
    Environment Canada
    Toronto, ON M3H 5T4 Canada

    John Kimball, Youngwook Kim
    Numerical Terradynamic Simulation Group (NTSG)
    College of Forestry & Conservation
    The University of Montana
    Missoula, MT 59812-1049 USA



    Brodzik, M. J., B. Billingsley, T. Haran, B. Raup, and M. H. Savoie. 2012. EASE-Grid 2.0: Incremental but significant improvements for Earth-gridded data sets. ISPRS Int. J. Geo-Inf. 1(1):32-45.

    Brodzik, M. J., B. Billingsley, T. Haran, B. Raup, and M. H. Savoie. 2014. Correction: Brodzik, M. J. et al. EASE-Grid 2.0: Incremental but significant improvements for Earth-gridded data sets. ISPRS Int. J. Geo-Inf 2012. 1(1):32-45 ISPRS Int. J. Geo-Inf. 3(3):1154-1156.

    Entekhabi, D. et al. 2014. SMAP Handbook–Soil Moisture Active Passive: Mapping Soil Moisture and Freeze/Thaw from Space. Pasadena, CA USA: SMAP Project, JPL CL#14-2285, Jet Propulsion Laboratory.

    Derksen, C., X. Xu,, R. S. Dunbar, A. Colliander, Y. Kim, J. Kimball. 2016. Soil Moisture Active Passive (SMAP) Project Calibration and Validation for the L3_FT_P and L3_FT_P_E Data Products (Version 1). SMAP Project, JPL D-56296. Jet Propulsion Laboratory, Pasadena, CA. (PDF, 2.6 MB)

    Dunbar, S., X. Xu, A. Colliander, C. Derksen, K. McDonald, E. Podest. E. Njoku, J. Kimball, and Y. Kim. 2016. Algorithm Theoretical Basis Document (ATBD): SMAP Level 3 Radiometer Freeze/Thaw Data Products (L3_FT_P and L3_FT_P_E). SMAP Project, Jet Propulsion Laboratory, Pasadena, CA. (PDF, 8 MB)

    Dunbar, S. 2018. SMAP Level 3 Freeze-Thaw (L3_FT_P) Product Specification Document. SMAP Project, JPL D-56293. Jet Propulsion Laboratory, Pasadena, CA. (PDF, 692 KB; see Technical References)

    Frolking S., K. McDonald, J. Kimball, R. Zimmermann, J. B. Way and S. W. Running. 1999. Using the space-borne NASA Scatterometer (NSCAT) to determine the frozen and thawed seasons of a boreal landscape. Journal of Geophysical Research, 104(D22), 27,895-27,907.

    Kim, Y., J. S. Kimball, K. Zhang, and K. C. McDonald. 2012. Satellite detection of increasing northern hemisphere non-frozen seasons from 1979 to 2008: implications for regional vegetation growth. Remote Sensing of Environment, 121, 472-487.

    Kim, Y., J. S. Kimball, J. Glassy, and K. C. McDonald. 2014. MEaSUREs Global Record of Daily Landscape Freeze/Thaw Status. Version 3. [indicate subset used]. Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center.

    Kim, Y., J.S. Kimball, K.C. McDonald and J. Glassy, 2011. Developing a global data record of daily landscape freeze/thaw status using satellite passive microwave remote sensing. IEEE Transactions on Geoscience and Remote Sensing 49, 949-960.

    Kimball, J., K. McDonald, A. Keyser, S. Frolking, and S. Running. 2001. Application of the NASA Scatterometer (NSCAT) for Classifying the Daily Frozen and Non-Frozen Landscape of Alaska, Remote Sensing of Environment, 75, 113-126.

    Kimball, J.S., K.C. McDonald, S.W. Running, and S. Frolking. 2004a. Satellite radar remote sensing of seasonal growing seasons for boreal and subalpine evergreen forests. Remote Sensing of Environment, 90, 243-258.

    Kimball, J.S., M. Zhao, K.C. McDonald, F.A. Heinsch, and S. Running. 2004b. Satellite observations of annual variability in terrestrial carbon cycles and seasonal growing seasons at high northern latitudes. In Microwave Remote Sensing of the Atmosphere and Environment IV, G. Skofronick Jackson and S. Uratsuka (Eds.), Proceedings of SPIE - The International Society for Optical Engineering, 5654, 244-254.

    McDonald, K.C., J.S. Kimball, E. Njoku, R. Zimmermann, and M. Zhao. 2004. Variability in springtime thaw in the terrestrial high latitudes: Monitoring a major control on the biospheric assimilation of atmospheric CO2 with spaceborne microwave remote sensing. Earth Interactions, 8(20), 1-23.

    Podest, E., K.C. McDonald, and J.S. Kimball. 2014. Multi-sensor microwave sensitivity to freeze-thaw dynamics across a complex boreal landscape. Transactions in Geoscience and Remote Sensing, 52, 6818-6828.

    Rawlins, M. A, K. C. McDonald, S. Frolking, R. B. Lammers, M. Fahnestock, J. S. Kimball, C. J. Vorosmarty. 2005. Remote Sensing of Pan-Arctic Snowpack Thaw Using the SeaWinds Scatterometer, Journal of Hydrology, 312/1-4, 294-311.

    Rignot E., and Way, J.B. 1994. Monitoring freeze-thaw cycles along north-south Alaskan transects using ERS-1 SAR, Remote Sensing of Environment, 49, 131-137. 

    Rignot, E., Way, J.B., McDonald, K., Viereck, L., Williams, C., Adams, P., Payne, C., Wood, W., and Shi, J. 1994. Monitoring of environmental conditions in taiga forests using ERS-1 SAR, Remote Sensing of Environment, 49, 145-154.

    Way, J. B., R. Zimmermann, E. Rignot, K. McDonald, and R. Oren. 1997. Winter and Spring Thaw as Observed with Imaging Radar at BOREAS, Journal of Geophysical Research, 102(D24), 29673-29684.

    Wismann, V. 2000. Monitoring of seasonal thawing in Siberia with ERS scatterometer data. IEEE Transactions on Geoscience and Remote Sensing, 38, 1804–1809.

    Technical References

    For additional references, such as ATBDs, refer to the Technical References tab at the top of this user guide. 

    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 the Common Metadata Repository (CMR) API. CMR is a metadata system that provides search capabilities for data at NSIDC. A synchronous REST interface utilizes the ... 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 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 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


    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. Short name Title Subsetting... read more
    How are the enhanced SMAP radiometer products generated and what are the benefits of using these products?
    There is considerable overlap of the SMAP radiometer footprints, or Instantaneous Fields of View (IFOVs), which are defined by the contours where the sensitivity of the antenna has fallen by 3db from its maximum. The IFOVs are spaced about 11 km apart in the along scan direction with scan lines... read more