## 4 Discussion  
The weather conditions encountered during this study provided a natural experiment that provided a good test of the utility of remote sensing for monitoring interannual variation in yield. The precipitation differences in the two summers resulted in large differences in NDVI and biomass measurements between the two years for the two sites. Relative to single-year measurements, this interannual weather variability allowed a deeper understanding of the growth response of vegetation to varying moisture conditions, and allowed us to evaluate the ability of remote sensing to provide an accurate yield indicator across a wide range of growth responses typical of dry and wet years. Our findings of a large rainfall effect are consistent with the reports of [PERSON] and [PERSON] (2001) and [PERSON] et al. (2007), who observed that grasslands, such as the mixed prairie, have the capacity for large production response to uncommonly high precipitation ([PERSON] and [PERSON], 2001; [PERSON] and [PERSON], 2001). Clearly, remote sensing methods provide an effective means for tracking year-to-year variation in above-ground green biomass as a result of different weather conditions in this prairie biome. The time series of the NDVI calculated from the ground spectrometer, SPOT and the MODIS platforms all show trends that are similar to the standing biomass, indicating that there is a clear effect of seasonal and interannual weather patterns on NDVI and biomass, which can be monitored with different remote sensing methods. While the general NDVI trends were similar for the different sampling methods, the exact shapes were not the same, indicating some sensor differences. The two MODIS sensors yielded similar patterns, yet the data from Aqua demonstrate depressed NDVI values in July 2009 and 2010, in comparison to the Terra data. This is more clearly demonstrated by the correlations with ground NDVI (NDVIG), where the offsets for the two platforms were very similar, yet the correlation was slightly stronger for Terra than Aqua. This slight difference between the two MODIS NDVI responses could be due to a variety of reasons, including specific calibration and instrument or sampling characteristics for each platform. [PERSON] et al. (1992) found that at the FIFE prairie site sensor viewing angle and solar zenith angle had a large effect on vegetation indices ([PERSON] et al., 2009). Different viewing and solar zenith angles, in this case, would result from directly comparing data captured at different times of day, such that shadows and effects of surface anisotropy would affect the angular dependent signal due to the geometric configuration of the sun, sensor and target ([PERSON] et al., 2009). Independent field measurements ([PERSON] et al., 2009) have shown a clear diurnal pattern for NDVI for prairie grassland, and this could have partly explained these differences between the two MODIS sensors having different overpass times. Both MODIS sensors yielded NDVI values that were slightly higher than ground-measured NDVI, particularly at low NDVI values (Figures 5 and 9). This offset did not appear to be a result of sensor band differences, because it was maintained in the comparison to simulated NDVI data that were designed to eliminate possible band configuration differences (Figure 9). The tendency of MODIS to produce values that are higher than the corresponding NDVIG values calculated from ground spectrometers, has been previously reported for a chaparral site ([PERSON] et al., 2009). These authors speculated that this could be an effect of the data processing such as the atmospheric correction, which is applied to all MODIS data, or could be a specific characteristic of the sensor itself ([PERSON] et al., 2009); however, further studies need to be conducted to definitively explain this difference. In comparison to the MODIS time series, the SPOT time series exhibited more scatter and a different offset when compared to ground-simulated NDVI (Figure 9).