## Data and Methodology
### Study Region  
We conducted this study at the same sites identified in our companion paper [22] that established the notion that the surface air temperature data retrieved from the microwave radiometers could be used instead of MODIS land surface temperature data to drive the convex quadratic model of land surface phenology (LSP). Indeed, it improved model fits, despite its coarser spatial resolution, because there was higher temporal resolution and lower variability arising from the spatial heterogeneity of the land surface. In that paper, we used AGDD from AMSR-E air temperature data, and NDVI and EVI from MODIS data to characterize cropland dynamics throughout the growing season in the study region [22]. AMSR-E pixels dominated by croplands were identified through land cover stability analysis [22; 34] using the MODIS IGBP Land Cover Type 1 Percentage Product (MCD12C1; [27]). We identified 49 AMSR-E pixels (or study sites) across the major grain producing areas of Ukraine (UA, 14), southern Russia (RU, 24), and northern Kazakhstan (KZ, 11) (Figures 1 and 2; [22]). For contrast, we selected one AMSR-E pixel dominated by mixed forest cover (IGBP class 5) in Mari El Republic of the Russian Federation. We used this representative MFO site only for contrast and did not incorporate it into our full analyses. Where it is included, it is indicated in figure captions or accompanying text. We derived, within each study pixel, the proportions of croplands, grasslands, and cropland/natural vegetation mosaic (CNVM) using the MODIS IGBP Land Cover product (MCD12C1; [27]). These classes were the three predominant land covers in the region. In addition, we calculated the tree cover proportion from the Landsat 7 ETM+ 30 m resolution Global Land Cover data [33]. The proportions of tree cover, open water, bare ground, and undifferentiated other classes (including croplands and grasslands) that occur within each AMSR-E study pixel appear in Figure 2.  
Figure 1: Land cover stability in Ukraine (UA), southern Russia (RU), and northern Kazakhstan (KZ) as revealed by International Geosphere Biosphere Programme (IGBP) global land cover classification scheme MODIS 0.05\({}^{\circ}\) cropland (IGBP class 12) land cover products for 2003–2010. For details on how the land cover stability analysis was conducted, please refer to [22; 34]. In this figure, Yellow = stable core area; Magenta = unstable peripheral areas; Black = no occurrence of the given land cover class. Overlaid are the 49 specific cropland and one mixed forest (site 50—most northern site) study sites. The AMSR-E pixels are numbered from lower to higher latitude. Modified from [22]. Site names, latitudinal and longitudinal coordinates for all the study sites can be found in Table 1.  
Figure 2: Average cropland (purple), and grassland (orange) cover in percent for 2003–2010 from the MODIS IGBP Land Cover Type 1 Percent Product at ~5.6 km spatial resolution MCD12C1 [27], and tree cover fraction (%) in 2010 from the Landsat ETM+ 30 m resolution Global Land Cover product [33]. X-axis indicates study sites numbered from lower (1) to higher (50) latitudes. Figure 1 shows the latitudinal distributions of the study sites and countries in which they are found. Sites are sorted from largest (left) to smallest (right) cropland cover percent. Site 50 is a Mixed Forest site, in Mari El, RU. Note that summation of land cover proportions can exceed 100% at some sites, because the tree cover data source is different and at a different scale from the other two land cover classes. Cropland cover in some sites might be larger than what is presented here, since the MODIS land cover data has a separate class named Cropland/Natural Vegetation Mosaic (CNVM, IGBP class 14), which is not illustrated here to avoid overlap with the tree cover data. Land cover values >5% are labeled on the respective bars. These MODIS land cover data are also used in [22]. Over the eight years of the study period, the average cropland cover for all sites was 88%; in contrast, the mixed forest site was 93% mixed forest.