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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).
We kindly request that you cite the use of this data set in a publication using the following citation example. For more information, see our Use and Copyright Web page.
Bindlish, Rajat and Thomas Jackson. 2013. Aquarius L2 Swath Single Orbit Soil Moisture, Version 2, [indicate subset used]. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice Data Center. http://dx.doi.org/10.5067/Aquarius/AQ2_SM.002.
3 beams of spatial resolution 76 x 94 km (inner), 84 x 120 km (middle) 96 x 156 km (outer)
25 August 2011 to present
7 days global coverage
Soil moisture estimate
V2. See the Version History section of this document for previous version information.
Rajat Bindlish and Thomas Jackson
United States Department of Agriculture
Agricultural Research Service
Hydrology and Remote Sensing Laboratory
Beltsville, MD 20705 USA
NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449 USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
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 System group in the implementation of the Aquarius Soil moisture algorithm.
Aquarius LeveL-2 Soil Moisture archive products are produced by the NASA Goddard Space Flight Center's Aquarius Data Processing System (ADPS).
The data files are in Hierarchical Data Format 5 (HDF5).
Data files are organized into directories by date. For example,
Soil moisture files are named according to the following conventions and as described in Table 1:
|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.|
|ppppp||Geophysical parameter: SOILM = soil moisture|
|vvvv||Version, e.g. V2.0|
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.
Data files are approximately 970 KB each.
Spatial coverage is global.
The Aquarius instrument 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. Figure 1 shows the position of the Aquarius beams.
Figure 1. Location and 3 dB size of the Aquarius beams.
25 August 2011 to present.
Aquarius/SAC-D data are acquired daily. Aquarius L2 soil moisture products are delivered monthly, typically within the month following data acquisition.
7 days global coverage.
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 1.
Figure 1. Aquarius soil moisture data file attribute groups.
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.
|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 if attributes for radiometer_flags, described in Table 3.
|0||No SM Retrieval||Mv||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.
|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.
|att_ang||Spacecraft roll, pitch, yaw||Degrees|
|beam_clat||Beam Center Latitude||Degrees|
|beam_clon||Beam Center Longitude||Degrees|
netCDF metadata are included as global attributes with the Level-2 data files. Table 6 attribute names and values for data file Q2013001004300.L2_SOILM_V2.0. Values that vary from granule to granule are noted.
|Title||Aquarius Level-2 Soil Moisture Data|
|Data Center||NASA/GSFC Aquarius Data Processing Center|
|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 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.
|Processing Time||2013123151002000 (varies)|
|Input Files||Q2013001004300_L2_SM.txt (varies)|
|Processing Control||ifile=Q2013001004300_L2_SM.txt ofile=Q2013001004300.L2_SOILM_V2.0 (varies)|
|Start Time||2013001004300 (varies)|
|Start Year||2013 (varies)|
|Start Day||1 (varies)|
|Start Millisec||2580000 (varies)|
|End Time||2013001022059 (varies)|
|End Year||2013 (varies)|
|End Day||1 (varies)|
|End Millisec||2580000 (varies)|
|Node Crossing Time||2013001010730000 (varies)|
|Orbit Node Longitude||-105.74653f (varies)|
|Latitude Units||degrees North|
|Longitude Units||degrees East|
|Orbit Number||8394 (varies)|
|Cycle Number||71 (varies)|
|Pass Number||75 (varies)|
Below is a sample of data records from the rad_sm parameter within the Aquarius Data group in the Aquarius soil moisture file: Q2013001004300.L2_SOILM_V2.0.
Figure 2 shows the Aquarius soil moisture estimates using all three beams for July 1, 2012.
Figure 2. Aquarius soil moisture estimates using all three beams July 1, 2012.
See the NSIDC Aquarius Soil Moisture Order Data page for a list of order options.
HDF 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 datasets.
For additional tools, see the HDF-EOS Tools and Information Center.
Aquarius LeveL-2 Soil Moisture archive products are produced by the NASA Goddard Space Flight Center's Aquarius Data Processing System (ADPS).
The soil moisture algorithm runs when the Aquarius data are available. Currently, the Aquarius mission is processing the data monthly.
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. H-pol microwave observations are more sensitive to the 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). Details on these steps are provided in the Derivation Techniques and Algorithms section.
An Aquarius Level-2 Soil Moisture product is generated from one Aquarius Level 2 Science product. The soil moisture product contains physical measurements computed from the Level-2 data 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 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 (Patt 2013).
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).
At the L-band frequency used by Aquarius, the brightness temperature of the land surface is proportional 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:
Ancillary surface temperature data from the Numerical Weather Prediction model of the National Centers for Environmental Prediction Global Forecast System (NCEP GFS) is used to correct for 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:
|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:
|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:
The vegetation optical depth is also dependent upon 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:
|b||Proportionality value. Depends on vegetation structure and microwave frequency|
|VWC||Vegetation Water Content|
The baseline 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 baseline 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:
|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.
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:
|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.
V2.0 is the first version of Aquarius Level-2 Soil Moisture data available from NSIDC. Previous versions were available via the NASA Aquarius Web site (http://aquarius.nasa.gov/).
The current Version 2.0 Aquarius calibration is valid over a narrow range of TB (oceans only) (Piepmeier et al. 2013). The calibration of the Aquarius radiometer over the entire dynamic range is a key element for the successful implementation of the soil moisture algorithm. The Aquarius brightness temperatures are re-calibrated for each beam using co-located and concurrent Soil Moisture Ocean Salinity (SMOS) observations over the entire dynamic range of the satellite. Based upon this analysis, we implemented a correction to the Aquarius brightness temperatures. This involves applying the gain and offsets coefficients computed using the linear fit between the co-located Aquarius and SMOS observations. The Aquarius brightness temperature observations over the oceans were used as a pivot point to compute the slope and the offset. This is an interim fix and will have to be re-evaluated for future versions of the Aquarius TB dataset. Further, details on the warm end bias (Piepmeier et al. 2013) and the re-calibration are available in Bindlish et al, 2013. The re-calibrated brightness temperatures are used in version 2.0 of the soil moisture algorithm. The Aquarius mission is planning to address the full range calibration in the next couple of data releases. These calibration coefficients will be evaluated after each Aquarius data release.
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 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 measure backscatter for surface roughness corrections. Table 13 summarizes instrument characteristics.
|3 radiometers in push-broom alignment||
SAC-D spacecraft Orbit Parameters:
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. 2013. Global Soil Moisture from the Aquarius Satellite: Description and Initial Assessment. IEEE Geosciences and Remote Sensing Letters (in review).
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).
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.
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.
The acronyms used in this document are listed in Table 14.
|ACS||Attitude Control System|
|ADPS||Aquarius Data Processing System|
|ATBD||Algorithm Theoretical Basis Document|
|CONAE||Comisión Nacional de Actividades Espaciales|
|GPS||Global Positioning System|
|GSFC||Goddard Space Flight Center|
|HDF5||Hierarchical Data Format 5|
|HH||transmit Horizontal, receive Horizontal|
|HV||transmit Horizontal, receive Vertical|
|IGBP||International Geosphere-Biosphere Programme|
|MODIS||Moderate Resolution Imaging Spectroradiometer|
|NASA||National Aeronautics and Space Administration|
|NCEP GFS||National Centers for Environmental Prediction Global Forecast System|
|NCEP GFS GDAS||National Centers for Environmental Prediction Global Forecast System Global Data Assimilation System|
|NDVI||Normalized Difference Vegetation Index|
|NOAA||National Oceanic and Atmospheric Administration|
|NRCS||Normalized Radar Cross Section|
|ODPS||Ocean Data Processing System (ODPS)|
|OISST||Optimum Interpolation (OI) Sea Surface Temperature (SST) V2|
|RFI||Radio Frequency Interference|
|SAC-D||Satélite de Aplicaciones Científicas|
|SCA||Single Channel Algorithm|
|SeaWiFS||Sea-viewing Wide Field-of-view Sensor|
|SMOS||Soil Moisture Ocean Salinity|
|SWE||Snow Water Equivalent|
|TOA||Top Of Atmosphere|
|UTC||Coordinated Universal Time|
|VH||transmit Vertical, receive Horizontal)|
|VV||transmit Vertical, receive Vertical)|
|VWC||Vegetation Water Content|
02 December 2013
03 June 2014