## 3 Results
### Quantifying GPP over Texas and the Great Plains Using the Multiple Linear Regression Approach  
Figures 11 and 12 show total predicted GPP over Texas and the contiguous US, respectively. As mentioned in the data and methodology section, we have calculated GPP from the MLR equation using GOME-2 SIF, TRMM precipitation, and ESA CCI soil moisture data, with the inclusion of lead-lag relationship between SIF and precipitation. Figure 11 shows that predicted GPP over Texas (within 30-36 \({}^{\circ}\)N/95-105 \({}^{\circ}\)W grid box) in 2011 is significantly lower than that of 2007. The area with GPP values higher than 75 gC/m\({}^{2}\)/month decreased significantly from 2007 to 2011, and specifically from June 2011 to August 2011, which is not typical for a normal yielding year. Figure 11d-f demonstrate that in 2011 drought conditions were limited to Texas as there was no significant change in GPP over the Great Plains (Figure 12d-f). These findings indicate that our MLR-based approach with lead-lag is able to capture the drought-related reduction in GPP over Texas in 2011. Figure 12 shows that maximum GPP values found over the Great Plains (Figure 12a-c) in the normal yielding year amount to \(\sim\)500 gC/m\({}^{2}\)/month, which agrees well with FLUXNET data [22]. Predicted GPP indicates that 2012 was a severe drought year over the Great Plains as compared to 2007. The impact of the drought is clearly seen in 2012, as GPP decreased significantly compared to 2007 and 2011 (Figure 12g-h). Figures 11 and 12 show that our predicted GPP estimates are capable of capturing the 2011 Texas drought effect and also the progression of the drought over the Great Plains region (along with Texas) in 2012. These results demonstrate the robustness of the approach presented in this research study, both in terms of the magnitude of GPP values and their trend. Figure 10: Mean total GPP (gC/m\({}^{2}\)/month) within a CLM grid box surrounding US-ARM, US-AR1 and US-AR2 stations in JJA 2007–2012. Total GPP is calculated as a sum of C3 non-arctic grass GPP, C4 grass GPP and C3 crop GPP. We have also compared our results with MODIS observational reference data: Figure 13 shows that MODIS GPP values are about 50% lower than those of predicted gross primary production. GPP values based on MODIS satellite data range between 200 and 300 gC/m\({}^{2}\)/month over the Great  
Figure 11: Spatial patterns of monthly total (C3/C4 grass plus C3 crop) predicted GPP based on SIF, precipitation and soil moisture over Texas in summer 2007, chosen as reference year (**a–c**), and summer 2011—drought year in Texas) (**d–f**). Figure 12: Spatial patterns of monthly total (C3/C4 grass plus C3 crop) predicted GPP based on SIF, precipitation and soil moisture for summer 2007, chosen as reference year (**a–c**); summer 2011—drought year in Texas (**d–f**); and summer 2012—the Great Plains drought (**g–i**). Plains. MODIS is able to detect a drought signal over the Great Plains in 2012 (Figure 13g-i) and Texas in 2011 (Figure 13d-f), as areas with GPP < 100 gC/m\({}^{2}\)/month spread to the north and east, towards the Great Plains. MODIS observations also provide evidence of no reduction in GPP over the Great Plains in 2011, which is expected and also confirmed by monthly US Drought Monitor reports for JJA in 2011. Moreover, MODIS GPP over the Great Plains in August 2011 was higher than that in August 2007 and is consistent with the trend we observed in the predicted GPP (Figure 12c,f). Thus, our predicted GPP agrees well with MODIS GPP values in terms of capturing the drought conditions effect on plant production. Our MLR-based approach with lead-lag consideration can be used to provide GPP estimates that are more accurate in terms of absolute values than MODIS reference data.