4.2.3. SCED

The distribution of SCED was consistent with that of SCD, presenting "high SCED in the mountains and low SCED in the plains" and "high SCED at high latitudes and low SCED at low latitudes" trends. From the perspective of spatial distribution, the SCED in some areas of the Daxingan Mountains, Xiaoxingan Mountains and Changbai Mountains

were mainly in the range of 210 d to 240 d in approximately April of the next year. The SCED of the Songnen Plain and Liaohe Plain were relatively early, probably between January and February of the next year (Figure 9). The annual average SCED distribution in Northeast China also had two peaks, which were 130–140 d and 200–210 d, corresponding to the middle of January and late April of the next year, accounting for 5.54% and 20.50% of the area, respectively. The area with an SCED of less than 240 d accounted for 99.59%; that is, at the end of April of the next year, the snow in Northeast China almost disappeared (Figure 10).

**Figure 9.** Spatial distribution of annual average SCED in Northeast China from HY2001 to HY2017.

**Figure 10.** Histogram of annual average SCED from HY2001 to HY2017 in Northeast China.

For the SCED, 29.44% of the total area showed an early trend, while 36.70% had a delayed trend. In addition, only 1.49% and 2.53% of the area were significantly early and delayed, respectively (Figure 11a). The delayed areas were mainly distributed in the Sanjiang Plain, Daxingan Mountains, Xiaoxingan Mountains and Changbai Mountains; the areas with an advancing trend of SCED were mainly concentrated in the middle of the region and the transition area between plain and mountainous areas. Figure 11b shows the trend of SCED in Northeast China. Compared with the significance test, the overall spatial distribution characteristics and the increasing/decreasing trends of SCED were highly consistent. The area with an SCED trend > 0 d/a accounted for 36.36%; that with an SCED trend < 0 d/a accounted for 29.11%.

**Figure 11.** Trend of SCEDs in Northeast China. (**a**) Significance test and (**b**) trend of SCED from HY2001 to HY2017.

In general, the correlation analysis of the SCD, SCOD, and SCED revealed significant relationships between the SCED and SCD (r = 0.70). The correlation between the SCOD and SCD was −0.14, and the increasing trend of the SCD was determined by the advancement of the SCOD and the delay of the SCED. Considering that there was no significant change in the SCOD across time, the snow phenology variations in Northeast China from HY2001 to HY2017 were attributed mostly to the changes in SCED.

#### *4.3. Roles of Multiple Factors in Snow Phenology*

Figure 12 shows that the geographical and meteorological factors and the NDVI all affected the SCD, SCOD and SCED. Annual mean temperature had the greatest impact on the SCD, SCOD and SCED, followed by latitude. Precipitation, aspect and slope all had little effect on the SCD, SCOD and SCED, and all these *q* values were less than 0.1. Compared with the SCOD, the NDVI and longitude both had a greater impact on the SCED and SCD, with *q* values of 0.35 (0.15) and 0.30 (0.13), respectively. However, altitude was an important factor affecting the SCOD compared with the SCD and SCED.

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We further analyzed the relative importance of monthly temperature and precipitation to snow phenology, and the results are shown in Figure 13. Obviously, the influence of monthly temperature on snow phenology is much greater than that of monthly precipitation. In terms of the roles of different months, the temperature from January to May has a stronger impact on snow phenology, while the impact from June to August is relatively weak. Precipitation has a greater impact on snow phenology in May, September and snow stable period, which the snow completely melted in May, and snowfall occurred in some areas in September.

**Figure 13.** Roles of temperature and precipitation in different months in snow phenology. (**a**) temperature, (**b**) precipitation.
