## 3 Data
### MODIS Data  
The storage system of MODIS data consists of 286 vegetated land tiles covering the whole globe. Each tile covers an area of 1200 \(\times\) 1200 km or 1.44 million pixels. The MOD17 algorithm provides an eight-day GPP/NPP estimate for each 1 \(\times\) 1 km pixel. We sum eight-day values to annual. We use the MODIS NPP produced developed by [PERSON] _et al._[36].  
Previous studies showed that the direct use of 1 \(\times\) 1 km MODIS pixel for validation may be inappropriate [37, 38, 39]. Reported reasons are (i) mismatch between MODIS gridded pixels and observations caused by gridding artifacts [38]; (ii) problems in the mixed land cover and surface reflectance information and (iii) uncertainties in the information provided for building the look-up tables [38]. We follow previous studies [3, 37, 38, 39] and obtain the mean MODIS NPP of a 3 \(\times\) 3 pixel patch (nine 1 x 1 km pixels) for each inventory plot. Within these 9 pixels we select only forest pixels according to the MOD12Q1 product [8] and the classification system of [PERSON] _et al._[40]. Pixels with any other land cover type are ignored. For each of the forest pixels, we take the mean value of the MODIS NPP estimates according to three different climate input data sets provided by:  
1. the NASA Global Modeling and Assimilation Offices (GMAO) at NASA Goddard Space Flight Center with a spatial resolution of 0.5 \(\times\) 0.67\({}^{\rm o}\)[41]. MODIS NPP derived from this data set will be referred to as \"GMAO\".
2. the daily climate data set called NCEP_DOE_II with a spatial resolution of approx. 1.875 \(\times\) 1.875\({}^{\rm o}\)[42, 43], referred to as \"NCEP2\".  
3. Austrian local daily climate data interpolated with DAYMET (see previous chapter) on 1 \(\times\) 1 km (approx. 0.0083 \(\times\) 0.0083\({}^{\circ}\)) resolution with station data provided by the Austrian National Weather Centre: \"ZAMG\".  
The difference between the MODIS NPP driven by GMAO and NCEP2 is caused by the different global daily climatology drivers and correspondingly modified BPLUT file [44]. The first two data sets are maintained by the Numerical Terra Dynamic Simulation Group (NTSG) at the University of Montana, while the Austrian local climate data are maintained by the Institute of Silviculture at The University of Natural Resources and Life Science, Vienna (BOKU).  
From 1 January 2000 to 31 December 2011 for 11 full years all three variants of MODIS NPP estimates are computed. Until February 2000, missing MODIS data is considered negligible. Although the data is available annually, we use the periodic mean annual NPP for these 11 years to have a consistent and comparable temporal scaling with the forest inventory data. The variation between annual and periodic mean MODIS NPP is small (mean standard deviation 37.1 gC/m\({}^{2}\)/year) and shows no trend across Austria. The lack of trend and the low variation supports the use of the temporal aggregation.  
Figure 1 gives the periodic mean annual MODIS driven NPP (2000-2011) estimates across the country and demonstrates the special feature of a \"space-based\" satellite-driven approach, providing continuous cover in productivity estimates for every km\({}^{2}\) across Austria.