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Data Set ID:
AQ2_SM

Aquarius L2 Swath Single Orbit Soil Moisture, Version 4

This data set contains Level-2 global soil moisture estimates derived from the NASA Aquarius passive microwave radiometer on the Satélite de Aplicaciones Científicas (SAC-D).

Version Summary:

Changes in the Version 4 Aquarius Soil Moisture data include: use of the most recent version (Version 4) of Aquarius Brightness Temperatures as input.

Geographic Coverage

Spatial Coverage:

  • N: 90, S: -90, E: 180, W: -180
Spatial Resolution:
  • Varies x Varies
Temporal Coverage:
  • 25 August 2011 to 7 June 2015
Temporal Resolution: 98 minute
Parameter(s):
  • Microwave > Brightness Temperature
  • Soils > Soil Moisture/Water Content
Platform(s) SAC-D
Sensor(s): AQUARIUS_RADIOMETER
Data Format(s):
  • HDF
  • XML
Version: V4
Data Contributor(s): Rajat Bindlish, Thomas Jackson
Metadata XML: View Metadata Record

Data Citation

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.

Bindlish, R. and T. Jackson. 2015. Aquarius L2 Swath Single Orbit Soil Moisture, Version 4. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/Aquarius/AQ2_SM.004. [Date Accessed].

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Detailed Data Description

Aquarius LeveL-2 Soil Moisture products are produced by the NASA Goddard Space Flight Center's Aquarius Data Processing Segment (ADPS) .

Format

The data files are in Hierarchical Data Format 5 (HDF5).

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File and Directory Structure

Data are available on the HTTPS site in the https://n5eil01u.ecs.nsidc.org/AQUARIUS/AQ2_SM.004/ directory. Within this directory, the folders are organized by date, for example: 
/2013.09.28/
/2013.09.29/
/2013.09.30/

Folders contain HDF5 data files and XML metadata files.

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File Naming Convention

Soil moisture files are named according to the following conventions and as described in Table 1:

Q2014271210000.L2_SOILM_V4.0

Qyyyydddhhmmss.L2_ppppp_vvvv

Where:

Table 1. File Naming Convention
Variable Description
Q Indicates Aquarius instrument
yyyy UTC four-digit year
ddd UTC day of year
hhmmss UTC hours, minutes, and seconds of the first sample block in the product. Sample block is defined as the first set of observations from the three Aquarius beams.
L2 Processing level
ppppp Geophysical parameter: SOILM = soil moisture
vvvv Version, e.g. V4.0

Each data file is paired with an XML file of the same name with .XML extension. The XML file contains metadata associated with the data file.

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File Size

HDF5 files range from approximately 1 MB to 16 MB.

XML files average approximately 16 KB.

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Volume

Total data volume is approximately 21 GB.

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Spatial Coverage

Coverage spans from 180°W to 180°E, and from approximately 90°N to 90°S. The swath width is about 390 km, enabling nearly global coverage every seven days. Figure 1 shows the spatial coverage of the Aquarius Radiometer for one orbit, which comprises one granule of this data set.

Spatial Coverage Map

Spatial Coverage Map for Aquarius Radiometer
Figure 1. Spatial Coverage Map displaying one orbit of the Aquarius Radiometer. The map was created using Reverb | ECHO.

Spatial Resolution

The Aquarius radiometer consists of 3 beams of sizes 76 x 94 km (inner beam), 84 x 120 km (middle beam) and 96 x 156 km (outer beam). The total swath width of the 3 beams is about 390 km.

Soil moisture is estimated for each individual radiometer beam footprint. The exact spatial resolution of the Level-2 product varies depending on the beam position (inner, middle or outer beam).

Figure 2 shows the position of the Aquarius beams.

Figure 2. Location and 3 dB size of the Aquarius beams.
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Temporal Coverage

Temporal Coverage: 25 August 2011 to 07 June 2015.

Due to a power failure on the Satélite de Aplicaciones Científicas (SAC)-D spacecraft on 08 June 2015, data from NASA's Aquarius instrument are no longer being produced. For more information on this event, please refer to the official NASA announcement. The NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) will continue to distribute Aquarius soil moisture and polar-gridded data sets for the full duration of the mission, 25 August 2011 to 07 June 2015.

Temporal Resolution

98 minutes per granule. Global coverage is completed every seven days.

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Parameter or Variable

The Single Channel Algorithm (SCA) is used to estimate soil moisture using Aquarius brightness temperature observations. The SCA is applied to the individual Aquarius footprint brightness temperature observations (L2) to produce a swath-based time-order product. Each swath is stored in a separate file. Files are divided into the groups of attributes shown in Figure 3.

Figure 3. Aquarius soil moisture data file attribute groups.

Parameter Description

The following groups of data objects (Aquarius Data, Aquarius Flags, Block Attributes, and Navigation) contain data stored as HDF5 data blocks. Each data object within these four groups contains data for each block and is therefore dimensioned by the value of the global attribute, Number of Blocks.

Aquarius Data: Attributes contained in the Aquarius Data group are described in Table 2. Each parameter in this group contains 4083 x 3 (Aquarius beams) elements.

Table 2. Aquarius Data Group Description
Name Description Units
anc_sm NCEP GFS GDAS soil moisture. Volumetric Fraction (m3/m3)
anc_subsurf_temp 0-10 cm NCEP GFS sub-surface temperature. The subsurface temperature over the land is the NCEP GFS GDAS product for the layer (0-10 cm) because emission from this layer is most closely correlated with soil moisture. Kelvin
anc_surface_temp NCEP GFS surface temperature. The surface temperature over the ocean is the NOAA OISST (Reynolds) product. Over land, the NCEP GFS GDAS product for the surface layer is used. Kelvin
anc_swe The snow water equivalent from NCEP GFS GDAS. Kg/m2
rad_TbH Aquarius L2 brightness temperature at the Earth surface after atmospheric correction h-pol. Prior to making a correction for roughness. Kelvin
rad_TbV Aquarius L2 brightness temperature at the Earth surface after atmospheric correction v-pol. Prior to making a correction for roughness. Kelvin
rad_ice_frac Fraction of ice contamination. Gain weighted ice fraction integrated over the antenna footprint. The Integration is over the radiometer footprint with 0 = water and 0 = land and 1 = sea ice weighted by the antenna pattern. Computation is made using the NCEP GFS GDAS ice product. Area (m2/m2)
rad_land_frac Fraction of land contamination. The gain weighted land fraction: Integration over the radiometer footprint with 1 = land and 0 = non-land (water and sea ice) weighted by the antenna pattern. Computation is made using the GSFC ODPS (SeaWiFS) 1 km resolution land mask. "Land" includes ice/snow covered land. Area (m2/m2)
rad_sm Aquarius volumetric soil moisture estimates. Volumetric Fraction (m3/m3)
scat_HH_toa Top Of Atmosphere (TOA) scatterometer Normalized Radar Cross Section (NRCS) for HH (transmit horizontal, receive horizontal) polarization. Aquarius L2 normalized radar cross-section at the top of the atmosphere at HH polarization. Decibels
scat_HV_toa TOA Scatterometer NRCS for HV (transmit horizontal, receive vertical) polarization. Aquarius L2 normalized radar cross-section at the top of the atmosphere at HV polarization. Decibels
scat_VH_toa TOA Scatterometer NRCS for VH (transmit vertical, receive horizontal) polarization. Aquarius L2 normalized radar cross-section at the top of the atmosphere at VH polarization. Decibels
scat_VV_toa TOA Scatterometer NRCS for VV (transmit vertical, receive vertical) polarization. Aquarius L2 normalized radar cross-section at the top of the atmosphere at VV polarization. Decibels

Aquarius Flags: The Aquarius Flags group contains one set of attributes for radiometer_flags, described in Table 3.

Table 3. radiometer_flags Attributes
Bit Position Name Value Description
0 No SM Retrieval SMRET No Soil Moisture retrieval performed
1 Brightness Temp TB TB < 0 or Tb > 320
2 Orbit Maneuver ORBIT ACS mode = 5
3 RFI RFI Tbh > Tbv; Tb > 320
4 Surface Temp TSURF Tb > Tsurf
5 Frozen Ground FROZ NCEP surface or sub-surface temperature below 273.15
6 Snow SNOW NCEP SWE > 10 kg/m2
7 Ice ICE NCEP ice fraction > 0.1
8 NDVI NDVI MODIS NDVI climatology flag
9 Dense Vegetation VEG Vegetation Water Content > 5 kg/m2
10 Urban URBAN IGBP Land Cover
11 Soil SOIL Invalid Soil Texture data
12 Water WATER Land Fraction < 0.99

Block Attributes: Parameters contained in the Block Attributes group are described in Table 4. Each parameter in this group contains 4083 x 1 elements.

Table 4. Block Attributes Group Description
Name Description Units
sec Mid-block times of Aquarius physical parameter values in seconds of day. Seconds
secGPS GPS time; block times of Aquarius physical parameter values in seconds since the GPS epoch (0 hours UTC on 6 January 1980). Seconds

Navigation: Parameters contained in the Navigation group are described in Table 5.Each parameter in this group contains 4083 x 3 elements, except zang which is 4083 x 1.

Table 5. Navigation Parameter Description
Name Description Units
att_ang Spacecraft roll, pitch, yaw Degrees
beam_clat Beam Center Latitude Degrees
beam_clon Beam Center Longitude Degrees
zang Intra-Orbit Angle Degrees

Metadata are included as global attributes with the Level-2 data files. Table 6 lists attribute names and values for data file Q2011237000100.L2_SOILM_V4.0 Values that vary from granule to granule are noted.

Table 6. Level-2 Soil Moisture Metadata General Attributes
Name Value
Product Name Q2011237000100.L2_SOILM_V4.0
Title Aquarius Level-2 Soil Moisture Data
Data Center NASA/GSFC Aquarius Data Processing Center
Mission SAC-D Aquarius
Mission Characteristics Nominal orbit: inclination=98.0 (Sun-synchronous); node=6PM (ascending); eccentricity=<0.002; altitude=657 km; ground speed=6.825 km/sec
Sensor Aquarius
Sensor Characteristics Number of beams=3; channels per receiver=4; frequency 1.413 GHz; bits per sample=16; instantaneous field of view=6.5 degrees; science data block period=1.44 sec.
Data Type SM
Software ID 3.01
Processing Version V4.0
Processing Time 2015167000645000 (varies)
Input Files Q2011237000100_L2_SM.txt (varies)
Processing Control ifile=Q2011237000100_L2_SM.txt ofile=Q2011237000100.L2_SOILM_V4.0 pversion=V4.0 (varies)
_lastModified 2015167000645000 (varies)
Conventions CF-1.6
institution NASA/GSFC OBPG
Start Time 2011237000101 (varies)
Start Year 2011 (varies)
Start Day 237 (varies)
Start Millisec 60001 (varies)
End Time 2011237013859 (varies)
End Year 2011 (varies)
End Day 237 (varies)
End Millisec 60001 (varies)
Node Crossing Time 2011237002530000 (varies)
Orbit Node Longitude -95.19445 (varies)
Latitude Units degrees North
Longitude Units degrees East
Orbit Number 1110 (varies)
Cycle Number 1 (varies)
Pass Number 1 (varies)
Nominal Navigation TRUE
Ancillary Files Aquarius_sand_p05d.bin,Aquarius_clay_p05d.bin,Aquarius_bd_p05d.bin,Aquarius_land_cover_5km.dat, ndvi_max.dat,ndvi_min.dat,ndvi_cmg_08_3.dat,flag_cmg_08_3.dat,ndvi_cmg_08_3.dat

Sample Data Record

Below is a sample of data records from the rad_sm parameter within the Aquarius Data group in the Aquarius soil moisture file: Q2011237000100.L2_SOILM_V4.0.

Figure 4 shows the Aquarius soil moisture estimates using all three beams for July 1, 2012.

Figure 4. Aquarius soil moisture estimates using all three beams July 1, 2012.
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Software and Tools

HDF-aware software must be used to read the Aquarius soil moisture files. The following external links provide access to software for reading and viewing HDF5 data files. Please be sure to review instructions on installing and running the programs.

HDFView: Visual tool for browsing and editing HDF4 and HDF5 files.

Panoply netCDF, HDF and GRIB Data Viewer: Cross-platform application. Plots geo-gridded arrays from netCDF, HDF and GRIB data sets.

For additional tools, see the HDF5 Tools and Software Web site.

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Data Acquisition and Processing

Aquarius L2 Swath Single Orbit Soil Moisture Data products are produced by the NASA Goddard Space Flight Center's Aquarius Data Processing Segment (ADPS).

Theory of Measurements

The Aquarius SCA algorithm uses the L-band horizontally polarized (h-pol) brightness temperature observations due to the higher sensitivity of this channel to soil moisture and land surface than the v-pol observations. The Aquarius SCA approach is based on the simplified radiative transfer model developed under the assumption that the canopy and soil temperatures are the same (Jackson 1993). The SCA is applied to the individual Aquarius footprint Level-2 brightness temperature observations to produce a swath-based time-order product (Bindlish and Jackson, 2013 and Meissner et al, 2014). Details on these steps are provided in the Derivation Techniques and Algorithms section.

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Data Acquisition Methods

The Version 4 Aquarius L2 Swath Single Orbit Soil Moisture Data product is generated from measurements derived from the NASA Aquarius Level-2 Sea Surface Salinity & Wind Speed Data V4.0 product. The soil moisture product contains measurements at the observed surface locations, along with coordinates of viewed locations and navigation data. This product is stored as one physical HDF file. Each product contains data from one orbit of Aquarius data. An orbit begins and ends as the SAC-D spacecraft crosses the South Pole. The best quality data are selected for each orbit during Level-0 to Level-1A data processing and are then used to create the Level 1A file that is input to the Level-2 science file (Pratt 2013).

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Derivation Techniques and Algorithms

The derivation techniques and algorithms in this section are from the Aquarius Soil Moisture ATBD Users Guide (Bindlish and Jackson, 2013 and Meissner et al, 2014). The entire ATBD Users Guide may be viewed in PDF format.

Brightness temperatures are converted to emissivity using a surrogate for the effective physical temperature (T) of the emitting layer. The observed emissivity (eobs) is corrected for vegetation and surface roughness to obtain the smooth soil emissivity (esoil). The Fresnel equation is then used to determine the dielectric constant of the soil-water mixture (k). Finally, a dielectric mixing model is used to obtain the soil moisture (SM).

Brightness temperature of the land surface is equivalent to its emissivity (eobs, where eobs = 1 - r) (r = Reflectivity) multiplied by its physical temperature (T). It is assumed that the temperatures of the soil and the vegetation are the same.

Based upon the above, the complete radiative transfer model can be simplified yielding the following expression for the observed TB in Equation 1:

Equation 1(Equation 1)

Where:

Table 7. Observed Brightness Temperature
Variable Description
TB brightness temperature
eobs observed emissivity

Ancillary surface temperature data from the Numerical Weather Prediction model of the National Centers for Environmental Prediction Global Forecast System (NCEP GFS) is used as the effective physical temperature of the emitting medium.

The emissivity retrieved above is that of the soil as modified by any overlying vegetation and surface roughness. In the presence of vegetation, the observed emissivity is a composite of the soil and vegetation. To retrieve soil water content, it is necessary to isolate the soil surface emissivity (esurf). First, the correction for the presence of vegetation is done based on Jackson and Schmugge (1991), as in Equation 2:

Equation 2(Equation 2)

Where:

Table 8. Emissivity - Correction For Presence of Vegetation
Variable Description
ω single scattering albedo
γ one-way transmissivity of the canopy
esurf soil surface emissivity

Both the single scattering albedo (ω) and the one-way transmissivity of the canopy (γ) are dependent upon the vegetation structure, polarization and frequency. The transmissivity is a function of the optical depth (τ) of the vegetation canopy:

Equation 3(Equation 3)

Where:

Table 9. One-way Transmissivity of Canopy
Variable Description
τ optical depth of vegetation canopy
θ system incidence angle

A constant value of the single scattering albedo is used in the Aquarius formulation (ω=0.05). Re-arranging equation 2 yields:

Equation 4(Equation 4)

The vegetation optical depth is a function of the Vegetation Water Content (VWC). In studies reported in Jackson and Schmugge (1991), it was found that the following functional relationship between the optical depth and vegetation water content could be applied:

Equation 5(Equation 5)

Where:

Table 10. Relation Between Optical Depth and Vegetation Water Content
Variable Description
b Proportionality value. Depends on vegetation structure and microwave frequency
VWC Vegetation Water Content

The algorithm uses a default global constant value of b = 0.8 for all vegetation classes. The vegetation water content can be estimated using several ancillary data sources. The baseline approach utilizes a set of land cover-based equations to estimate VWC from values of the Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI), an index derived from visible-near infrared reflectance data. The approach uses a MODIS NDVI climatology that was derived based on observations from 2001-2010.

The emissivity that results from the vegetation correction is that of the soil surface, including any effects of surface roughness. These effects are removed in order to determine the smooth surface soil emissivity (esoil), which is required for the Fresnel equation inversion. One approach to removing this effect is a model described in Choudhury et al. (1979) that yields the bare smooth soil emissivity:

Equation 6(Equation 6)

Where:

Table 11. Bare Smooth Soil Emissivity
Variable Description
h h is dependent on the polarization, frequency, and geometric properties of the soil surface. A constant roughness parameter of h = 0.1 is used in the formulation.

The cos2 Θ term is often dropped to avoid overcorrecting for roughness. The Aquarius soil moisture algorithm does not drop this term.

Emissivity is related to the dielectric properties (ε) of the soil and the viewing or incidence angle. For ease of computational inversion, it is assumed that the real component (εr) of the dielectric constant provides a good approximation of the complex dielectric constant. However, this assumption can be modified if additional evidence is found to support the use of this more complex formulation. The Fresnel equations link the dielectric constant to emissivity. For horizontal polarization:

Equation 7(Equation 7)

Where:

Table 12. Surface Emissivity - Horizontal Polarization
Variable Description
εr real component of the dielectric constant

The dielectric constant of soil is a composite of the values of its components air, soil, and water, which have greatly different values. A dielectric mixing model is used to relate the estimated dielectric constant to the amount of soil moisture. The Aquarius SCA uses Wang and Schmugge (1980) dielectric mixing model to estimate soil moisture.

Version History

Changes in the Version 4 Aquarius Soil Moisture data include: use of the most recent version (Version 4) of Aquarius Brightness Temperatures as input.

Changes in the Version 3 Aquarius Soil Moisture data include: use of the most recent version (Version 3) of Aquarius Brightness Temperatures as input; Aquarius Brightness Temperatures are no longer re-calibrated before soil moisture retrievals as was done for Version 2 data; soil moisture observations are valid over a wider range of brightness temperatures compared to Version 2 data; updates to the soil moisture model parameters (b and ω). For more information, see: Summary of Aquarius V3.0 Algorithm and Processing Changes from V2.0

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Sensor or Instrument Description

Aquarius/SAC-D is a collaboration between NASA and Argentina's space agency, Comisión Nacional de Actividades Espaciales (CONAE), with participation from Brazil, Canada, France and Italy. The Aquarius instrument was built jointly by NASA's Jet Propulsion Laboratory and NASA's Goddard Space Flight Center.

The Aquarius instrument includes three radiometers and one scatterometer. The soil moisture data are collected by the radiometers. The radiometers measure brightness temperature at 1.414 GHz in the horizontal and vertical polarizations (TH and TV). The scatterometer is a microwave radar sensor that measures backscatter for surface roughness corrections. Table 13 summarizes instrument characteristics.

Table 13. Aquarius Instrument Characteristics
Instrument Characteristics
3 radiometers in push-broom alignment
  • Frequency: 1.413 GHz
  • Band width: less than or equal to 26 MHz
  • Swath Width: 390 km
  • Science data block period: 1.44 sec
  • Footprints for the beams are: 74 km along track x 94 km cross track, 84 x 120 km, and 96x156 km, yielding a total cross track of 390 km.
  • Beam incidence angles of 29.36, 38.49, and 46.29 degrees incident to the surface. Beams point away from the sun.
Scatterometer
  • Frequency: 1.26 GHz
  • Band Width: 4 MHz
  • Swath Width: 390 km
  • Science data block period: 1.44 sec

SAC-D spacecraft Orbit Parameters:

  • 98 minute sun-synchronous
  • 6 PM ascending orbit, 6 AM descending orbit
  • 657 km equatorial altitude (655 km minimum, 685 km maximum over the orbit)
  • Ground-track repeat interval: 7-day, 103 orbits
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References and Related Publications

Bindlish, Rajat, Thomas Jackson, Michael Cosh, Tianjie Zhao and Peggy O'Neill. 2014. Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment. IEEE Geosciences and Remote Sensing Letters (in print). doi 10.1109/LGRS.2014.2364151.

Bindlish, Rajat, and Thomas J. Jackson. 2013. Aquarius Soil Moisture ATBD Users Guide, Version 2.0. Beltsville, Maryland USA: USDA Hydrology and Remote Sensing Lab. (PDF file, 315 KB).

Bindlish, Rajat, Thomas Jackson, Michael Cosh, Tianjie Zhao and Peggy O'Neill. 2015. Global Soil Moisture from the Aquarius Satellite: Description and Initial Assessment. IEEE Geosciences and Remote Sensing Letters 12(5):923-927.

Bindlish, Rajat, Thomas Jackson, Ruijing Sun, Michael Cosh, Simon Yueh, and Steve Dinardo. 2009. Combined Passive and Active Microwave Observations of Soil Moisture During CLASIC. IEEE Geoscience and Remote Sensing Letters 6(4).

Choudhury, B. J., T. J. Schmugge, A. Chang, and R. W Newton. 1979. Effect of Surface Roughness on the Microwave Emission from Soils, Journal Geophysical Research 84:5699–5706.

Jackson, Thomas J., et al. 2010. Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products. IEEE Transactions on Geoscience and Remote Sensing 48(12).

Jackson, T. J. 1993. Measuring Surface Soil Moisture Using Passive Microwave Remote Sensing. Hydrological Processes 7:139–152.

Jackson, T. J., and T. J Schmugge. 1991. Vegetation Effects on the Microwave Emission of Soils, Remote Sensing of Environment 36(3): 203–212.

Meissner, T., F. Wentz, D. LeVine and J. Scott. 2014. Addendum III to ATBD Version 3.0, Beltsville, Maryland USA: USDA Hydrology and Remote Sensing Lab.

Pratt, Frederick S. 2013. Aquarius Level-2 Soil Moisture Data Product. NASA Goddard Space Flight Center Aquarius Project Document AQ-014-PS-0021, Version 2.0.

Piepmeier, Jeffrey, Shannon Brown, Joel Gales, Liang Hong, Gary Lagerloef, David Le Vine, Paolo de Matthaeis, Thomas Meissner, Rajat Bindlish, and Thomas Jackson. 2013. Aquarius Radiometer Post-Launch Calibration for Product Version 2.0, Aquarius Project Document: AQ-014-PS-0015. ftp://podaac-ftp.jpl.nasa.gov/allData/aquarius/docs/v2/AQ-014-PS-0015_AquariusInstrumentCalibratrionDescriptionDocument.pdf.

Wang, J. R., and T. J. Schmugge. 1980. An Empirical Model for the Complex Dielectric Permittivity of Soils as a Function of Water Content, IEEE Transactions on Geoscience and Remote Sensing 18(4): 288–295.

Related Data Collections

Related Web Sites

Contacts and Acknowledgments

Rajat Bindlish
NASA Goddard Space Flight Center
Hydrological Sciences Laboratory
Code 617, Bldg 33, G216
Greenbelt, MD 20771 USA

Thomas Jackson
United States Department of Agriculture
Agricultural Research Service
Hydrology and Remote Sensing Laboratory
Beltsville, MD 20705 USA

Acknowledgements: 

This work was funded by NASA under the Interagency agreement NNH10AN10I. Tianjie Zhao helped with development of the soil moisture algorithm. The support provided by Michael Cosh, Peggy O'Neill, Thomas Holmes and Wade Crow is acknowledged. We acknowledge the support provided by Gary Lagerloef, David Le Vine, Gene Feldman and the Aquarius Data Processing Segment (ADPS) group in the implementation of the Aquarius Soil moisture algorithm.

Document Information

DOCUMENT CREATION DATE

02 December 2013

DOCUMENT REVISION DATE

03 June 2014

12 November 2014

01 October 2015

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