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The data available through this web tool were created using Google's geospatial tool, the Google Earth Engine using the data being stored on the Google Cloud. This data can be browsed here.
USGS MODIS-PRISM-GDAS ETa
Description: Remote sensing derived surface evapotranspiration dataset based on MODIS-PRISM-GDAS
Organization:United State Geological Survey (USGS)
Spatial resolution: 1-km grid (1/96-deg)
Time Span: 2000-Present(Updated every 8-days)
Monthly Actual Evapotranspiration
Actual ET (ETa) is produced using the operational Simplified Surface Energy Balance (SSEBop) model (Senay and others, 2013) for the period 2000 to present.
The SSEBop setup is based on the Simplified Surface Energy Balance (SSEB) approach (Senay and others, 2007, 2011) with unique parameterization for operational applications. It combines ET fractions generated from remotely sensed MODIS thermal imagery, acquired every 8 days, with reference ET using a thermal index approach. The unique feature of the SSEBop parameterization is that it uses pre-defined, seasonally dynamic, boundary conditions that are unique to each pixel for the hot/dry and cold/wet reference points.
The SSEBop model uses MODIS for land surface temperature, albedo and NDVI, Daymet for air temperature, GDAS for reference ET, and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) for elevation.
Senay, G.B., Bohms, S., Singh, R.K., Gowda, P.H., Velpuri, N.M., Alemu, H., and Verdin, J.P., 2013, Operational evapotranspiration mapping using remote sensing and weather datasets—a new parameterization for the SSEB approach: Journal of the American Water Resources Association, v. 49, no. 3, p. 577-591. (Also available online at http://dx.doi.org/10.1111/jawr.12057.)(Full Article)
Velpuri, N. M., Senay, G. B., Singh, R. K., Bohms, S., and Verdin, J. P.: A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: Using point and gridded FLUXNET and water balance ET, Remote Sensing of Environment, 139, 35-49, http://dx.doi.org/10.1016/j.rse.2013.07.013, 2013.(Abstract)
Climate, vegetation, and drought can be monitored many different ways through ground observations, gridded weather and climate data, and airborne and satellite remote sensing. Access to Google Earth Engine’s satellite image and meteorological collections allow for efficient near real-time monitoring through statistical analyses of surface vegetation, precipitation, and evapotranspiration.