Gabriel Edwin Lee Parrish Matthew Schauer MacKenzie Friedrichs Kul Bikram Khand Olena Boiko Stefanie Kagone Ray Dittmeier Saeed Arab Lei Ji Gabriel B. Senay 2023 <div class="html-p">Actual evapotranspiration modeling is providing useful information for researchers and resource managers in agriculture and water resources around the world. The performance of models depends on the accuracy of forcing inputs and model parameters. We developed an improved approach to the parameterization of the Operational Simplified Surface Energy Balance (SSEBop) model using the Forcing and Normalizing Operation (FANO). SSEBop has two key model parameters that define the model boundary conditions. The FANO algorithm computes the wet-bulb boundary condition using a linear FANO Equation relating surface temperature, surface psychrometric constant, and the Normalized Difference Vegetation Index (NDVI). The FANO parameterization was implemented on two computing platforms using Landsat and gridded meteorological datasets: (1) Google Earth Engine (GEE) and (2) Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA). Evaluation was conducted by comparing modeled actual evapotranspiration (<span class="html-italic">ETa</span>) estimates with AmeriFlux eddy covariance (EC) and water balance<span>&nbsp;</span><span class="html-italic">ETa</span><span>&nbsp;</span>from level-8 Hydrologic Unit Code sub-basins in the conterminous United States. FANO brought substantial improvements in model accuracy and operational implementation. Compared to the earlier version (v0.1.7), SSEBop FANO (v0.2.6) reduced grassland bias from 47% to −2% while maintaining comparable bias for croplands (11% versus −7%) against EC data. A water balance-based<span>&nbsp;</span><span class="html-italic">ETa</span><span>&nbsp;</span>bias evaluation showed an overall improvement from 7% to −1%. Climatology versus annual gridded reference evapotranspiration (<span class="html-italic">ETr</span>) produced comparable<span>&nbsp;</span><span class="html-italic">ETa</span><span>&nbsp;</span>results, justifying the use of climatology<span>&nbsp;</span><span class="html-italic">ETr</span><span>&nbsp;</span>for the global SSEBop Landsat<span>&nbsp;</span><span class="html-italic">ETa</span><span>&nbsp;</span>that is accessible through the ESPA website. Besides improvements in model accuracy, SSEBop FANO increases the spatiotemporal coverage of ET modeling due to the elimination of high NDVI requirements for model parameterization. Because of the existence of potential biases from forcing inputs and model parameters, continued evaluation and bias corrections are necessary to improve the absolute magnitude of<span>&nbsp;</span><span class="html-italic">ETa</span><span>&nbsp;</span>for localized water budget applications.</div> application/pdf 10.3390/rs15010260 en MDPI Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation article