## Materials and Methods
### Data Processing
#### 2.3.2 Meteorological Data and Snow Drought Detection  
Meteorological data, including the precipitation and temperature from 2000-2019, were downloaded from the public data platform ([[http://data.cma.cn/](http://data.cma.cn/)]([http://data.cma.cn/](http://data.cma.cn/)) (accessed on 8 January 2021)) and processed for measuring the climate change condition in the Sanjiang Plain. We used to average and sum data to evaluate the whole study area by the six stations (Figure 1). For temperature data, we calculated each year's data from six stations' average values from the last year's December to this year's February (e.g., 2019 means the time scale is from 2018/12 to 2019/02, and this form is used in the following text). At the same time, each year, accumulated precipitation data from the six stations were also processed for the same three months to represent the snowfall accumulation. Then, the data were sorted by precipitation from small to large to define the snow drought and snow-abundant years, respectively. To determine the snow drought and snow-abundant years, we detected the year's snowfall accumulation in less than half of the average snowfalls (76.9 mm) in the past two decades as the drought year (red line in Figure 3), and we found the year near the snow drought years and its snowfall accumulation far greater than average snowfall year as the abundant year.  
In the nearly twenty years of the study period, there were four snow drought years in the Sanjiang Plain; compared with that in the average snowfall year, snowfall accumulation in the drought year was less than 50% and compared to that in the abundant year, it was approximately 37%. The average temperature was higher in the snow drought years than the abundant years from 2000 to 2019 in the same period (Figure 3). From the survey of local people, the snow drought year in 2019 was very serious, and this situation had not previously happened in the last 60 years. In this study, we analyzed and compared the snowfall and temperature data from 2000 to 2019, labeling 2003, 2012, 2014, and 2019 as the snow drought years and 2005, 2010, 2015, and 2016 as the snow-abundant years (Figure 3). Through the meteorological data and previous research, climate change does impact the region by decreasing snowfall and increasing temperature.  
Figure 3: Applied meteorology and detection of snow drought in this study.  
Furthermore, to compare how snowfall influenced the phenological period of the forest and grass in the snow drought and snow-abundant years, we selected four snow drought years and used the nearest snowy year as the corresponding snow-abundant year. To obtain more information, we used the interact-grouping method to analyze the forest and grassland phenological period changes. First, we, according to the winter snowfall accumulation in the study area to define the snow drought years. Then, the four drought years were separately intersected with the four snow-abundant years, which better contrasted the snow drought and snow-abundant year phenological period change trend. Finally, the matched pair of years were divided into 16 phenological periods within the interact-grouping method. (16 phenological periods: 2003-2005, 2003-2010, 2003-2015, 2003-2016, 2012-2005, 2012-2010, 2012-2015, 2012-2016, 2014-2005, 2014-2010, 2014-2015, 2014-2016, 2019-2005, 2019-2010, 2019-2015, and 2019-2016).