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Description

The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft. The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. This data set provides an estimate of the vapor pressure deficit. It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. These are all daily products on a ¼ x ¼ degree latitude/longitude grid covering the continental United States (CONUS).

The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from.

Product Summary

Platforms
Aqua ,
Suomi-NPP
Instruments
AIRS ,
CrIS ,
ATMS
Spatial Extent

N: 90 S: -90 E: 180 W: -180

Location
UNITED STATES OF AMERICA
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
2012-11-28 to 2020-12-31
Data Partner
Goddard Earth Sciences Data and Information Services Center (formerly Goddard DAAC), Terrestrial Information Systems Laboratory, Earth Sciences Divis ion, Science and Exploration Directorate, Goddard Space Flight Center, NASA (NASA/GSFC/SED/ESD/TISL/GESD
Concept ID
C2284971212-GES_DISC
Data State
COMPLETE
Number of Files/Granules
2953
Processing Level
3
Published
Updated
Science Keywords
Vapor Pressure

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Amy Braverman, J. P. L. (2022). Spatial Statistical Data Fusion (SSDF) Level 3: CONUS Near-Surface Vapor Pressure Deficit from SNPP CrIMSS and Aqua AIRS, V2 [Data set]. NASA Goddard Earth Sciences Data and Information Services Center. https://doi.org/10.5067/55EOWAJ669WC Date Accessed: 2026-02-14

Documents

Variables

The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.

For questions on a specific variable, please use the Earthdata Forum.

Name Description Units Data Type Fill Value Valid Range Scale Factor
lat Degrees latitude degrees_north float32 9.9692099683869E+36 N/A N/A
lon Degrees longitude degrees_east float32 9.9692099683869E+36 N/A N/A
num_obs_aqua Number of L2 retrievals used from Aqua. Less than 1,000 is considered low, use with caution. 1 uint32 4294967295 N/A N/A
num_obs_snpp Number of L2 retrievals used from Suomi NPP. Less than 1,000 is considered low, use with caution. 1 uint32 4294967295 N/A N/A
obs_time_tai93 Nominal midtime for observations included in grid seconds since 1993-01-01 00:00 float64 9.9692099683869E+36 N/A N/A
obs_time_utc Nominal midtime for observations included in grid as an array of integers: year, month, day, hour, minute, second, millisec, microsec N/A uint16 65535 N/A N/A
orbit_pass Nominal solar time when the spacecraft passes over the equator. Orbit pass bounds are defined by closest approach of the spacecraft to the poles. hours float32 9.9692099683869E+36 N/A N/A
surf_h2o_vap_pres_deficit Near-surface water vapor saturation pressure deficit Pa float32 9.9692099683869E+36 N/A N/A
surf_h2o_vap_pres_deficit_stderr surf_h2o_vap_pres_deficit one-sigma standard error Pa float32 9.9692099683869E+36 N/A N/A
utc_tuple_lbl names of the elements of UTC when it is expressed as an array of integers year,month,day,hour,minute,second,millisecond,microsecond N/A OTHER N/A N/A N/A
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