Management and disturbances have significant effects on grassland forage production. When using satellite remote sensing to monitor climate impacts such as drought stress on annual forage production, minimizing these effects provides a clearer climate signal in the productivity data. The use of an ecosystem performance approach for assessment of seasonal and interannual climate impacts on forage production in semi-arid grasslands proved to be a successful method in a case study covering the Nebraska Sandhills. In this study we developed a time series (2000-2018) of the Expected Ecosystem Performance (EEP), which serves as a proxy for annual forage production after accounting for non-climatic influences, while minimizing effects of management and disturbances. The EEP was an output of a piecewise regression tree model that establishes relationships between seasonal climate variables, site specific growth potential, and long-term variability in growth to capture changes in Actual Ecosystem Performance measured by time-integrated Normalized Difference Vegetation Index (derived from eMODIS). We converted the unitless EEP to biomass using the SSURGO range production data. These results were then compared to ground-observed biomass in various locations of the study area and revealed strong positive relationships (R-squared = 0.67). An analysis of data from years beyond the model training period suggests that the model can be used for creating historical and future estimates of forage production in the western U.S. The newly-established relationships between seasonal climate and site-specific characteristics can be used for creating timely post-season forage production assessments and, when combined with seasonal climate forecasts or scenarios, they can serve for producing within-season estimates of annual forage production. These could lead to more informed decision making by livestock producers and land managers. This approach is transferable to other areas where climate and remotely-sensed NDVI data exist and therefore could be used to monitor climate impacts on annual forage production across the global grasslands.