## 3 Results  
### Meteorological and Vegetation Conditions  
Annual average air temperature ranged from 2.3 \({}^{\circ}\)C in 2011 to 3.4 \({}^{\circ}\)C in 2009 with a mean value of 2.9 \({}^{\circ}\)C, which was warmer than 50 year climate records mean (1.8 \({}^{\circ}\)C). Soil temperature was generally higher than air temperature by 4.0 \({}^{\circ}\)C, and the difference was more pronounced during the growing season (Figure 3). MODIS LST showed a well consistent trend for seasonal and inter-annual temperature variation with ground temperature measurements, but had a significant overestimation of ground temperature measurements. The year 2009 was a drought year with a PPT of 327.7 mm only accounting for 68.7% of 50-year mean rainfall (Figure 3). In general, SWC ranged from 0.05 to 0.25 m\({}^{3}\) m\({}^{-3}\), except for the higher value (0.39) in 2010 caused by a consecutive 10 days from 17 to 26 August of strong rainfall (daily average of 12.7 mm) (Figure 3).  
Two vegetation indices, NDVI and EVI, and the water index, LSWI, had a consistent single peak trend with the peak value generally showing in mid-August (Figure 4a). In contrast, 2009 had a lower growing season NDVI with a mean value of 0.12 and LSWI (0.06) than the latter two years. Seasonal PAR was robust and ranged from 7.5 to 12.5 MJ m\({}^{-2}\) day\({}^{-1}\) with an average value of 9.83 (\(\pm\)1.81, 1 time standard deviation (SD)) in GS and from 5.8 to 7.5 MJ m\({}^{-2}\) day\({}^{-1}\) with an average value of 7.45 (\(\pm\)1.83) in NG (Figure 4b). Seasonal PAR reached the peak (about 12.0 MJ m\({}^{-2}\) day\({}^{-1}\)) in the beginning of July, while the maximum FPAR was generally in August, which closely followed the vegetation conditions (Figure 4b). The MODIS FPAR products underestimated the FPARg, which was derived from ground LAI measurements based on the Beer-Lambert law (Equation (7)), in this alpine meadow by a multi-year average of 32.6% in GS except a few days in the beginning of GS (Figure 4b). Seasonal average of FPARg was higher in the final two years (30.3%) than 2009 (25.6%).  
A combination of three methods, MOD17A2 algorithm, Michaelis-Menten rectangular hyperbolic function (Equations (1) and (8)), and empirical equation (Equations (8-10)), were used to estimate the \(\varepsilon_{\mathrm{max}}\) values, which were 0.73, 0.73 and 0.75 g C MJ\({}^{-1}\) from 2009 to 2011, respectively. Compared to the default value (0.68 g C MJ\({}^{-1}\)) for grassland in MODIS GPP version 5 (GPP_MOD5), it was underestimated. However, MODIS GPP version 6 (GPP_MOD) used a higher default value of 0.86 g C MJ\({}^{-1}\) thus it was overestimated.  
Figure 3: Temperature and moisture conditions from 2009 to 2011 in this alpine meadow. LST is the land surface temperature that is the average of daytime and nighttime land surface temperature. _Ts_ and _Ta_ are soil temperature at the depth of 5 cm and air temperature at the height of 2 m, respectively. PPT is precipitation. SWC is the soil water content. SWCm is the modeled SWC for its missing value from land surface water index (LSWI) as the inset shows (SWCm = 0.1411 + 1.133 * LSWI + 4.611 * (LSWI)\({}^{2}\), \(R^{2}\) = 0.61, \(p\) < 0.0001, \(n\) = 129). Data are eight-day composited and showed with the first day of each eight-day interval in horizontal axis (hereafter the same).