Uncertainty of Evapotranspiration Estimates Using Simulated HyspIRI Data over Jornada, NM Rangeland

The proposed NASA remote sensing satellite HyspIRI provides the capability to produce globally distributed evapotranspiration (ET) estimates every 5-19 days at 60-m spatial resolution. HyspIRI will contain two main systems: a hyperspectral visible-shortwave infrared sensor, a multispectral thermal infrared sensor. The combination of these is anticipated to provide unprecedented high quality data needed to drive surface energy balance models. To evaluate the ramifications of modeling ET with HyspIRI, we conducted uncertainty analyses of simulated HyspIRI land surface temperature (LST) and emissivity data, both of these are key inputs for thermal-infrared-based surface energy balance modeling. The simulated data comprising over 80 image sets were derived from calibrated, 15-m resolution airborne data from NASA's MASTER instrument collected over the USDA/ARS Jornada, NM experimental range between 2001 and 2010. Using Monte Carlo simulations based on thousands of radiosonde and NCEP atmospheric profiles we found that LST estimates could be routinely accurate to better than 1 K. This outcome was possible due to the multispectral thermal capability of HyspIRI spanning wavelengths between 8-11 micrometers which led to good constraints on land surface emissivities. Results and implications for surface energy balance modeling and ET estimation over the semi-arid rangeland will be discussed.