## 3 Results
### Trends in the Climatic and Ecosystem Variables  
As a result of climate warming, the warm-related indices all exhibit increasing trends during 1961-2015, including SU25, SU35, TR20, growing season length (GSL), TX90p, TN90p, and warm spell duration indicator (WSDI) (Figure 4). The most significant increasing trend is observed in SU25 at 0.35 days year\({}^{-1}\) (\(p<0.01\)) for the period 1961-2015 and 0.65 days year\({}^{-1}\) (\(p<0.01\)) for the period 1982-2015, followed by TR20, GSL, and WSDI. This means that summer days have increased by approximately 22 days for the past three decades. In addition, increasing trends in SU25, SU35, TR20, GSL, TX90p, TN90p, and WSDI for the period 1982-2015 are revealed at rates of 0.65 days year\({}^{-1}\) (\(p<0.01\)), 0.34 days year\({}^{-1}\) (\(p<0.01\)), 0.34 days year\({}^{-1}\) (\(p<0.01\)), 0.37 days year\({}^{-1}\), 0.24 days year\({}^{-1}\), 0.2 days year\({}^{-1}\) and 0.41 days year\({}^{-1}\) (\(p<0.01\)), respectively, which are much higher than trends for 1961-2015. In contrast, the cold-related indices of frost days (FD0) and ice days (ID0) exhibit clear downtrends during 1961-2015 of \(-0.35\) days year\({}^{-1}\) (\(p<0.01\)) and \(-0.03\) days year\({}^{-1}\) (\(p<0.1\)), respectively. It is worth mentioning that although ID0 has been low since the 1980s, it shows an extremely high value in 2008. This extreme cold event corresponds well with the snow disaster in the winter of 2008, which has also been specially investigated before [(33)]. This indicates that the results and methods for extracting the climate extremes in this study are reliable. Figure 3: Spatial distribution of mean values (**a-c**), trends (**d-f**) and SDs (**g-i**) for LAI, NDVI, and GPP during 1982–2015. Black points indicate pixels where the trends are significant at the 0.05 significance level in panels (**d–f**). There are generally no significant trends for all of the precipitation indices across Hubei Province during the past five decades (Figure 4), except for a significant downtrend in consecutive wet days (CWD) at a rate of \(-\)0.02 days year\({}^{-1}\) (\(p<\) 0.1). However, trends in eight out of the nine precipitation indices during 1982-2015 are larger than those during 1961-2015. During 1982-2015, relatively remarkable trends are shown for R10, R95p, and PRCPTOT at \(-\)0.11 days year\({}^{-1}\), \(-\)1.23 mm year\({}^{-1}\), and \(-\)3.68 mm year\({}^{-1}\), respectively. These results also clearly capture the extreme precipitation-induced flood in 1998, which is seen in the time series for R50, R95p, and R99p. All three ecosystem indicators (i.e., LAI, NDVI, and GPP) for the whole study area show remarkable increases during 1982-2015 of 7.8 \(\times\) 10\({}^{-3}\) m\({}^{2}\) m\({}^{-2}\) year\({}^{-1}\) (\(p<\) 0.01), 1.9 \(\times\) 10\({}^{-3}\) year\({}^{-1}\) (\(p<\) 0.01) and 3.7 gC m\({}^{-2}\) year\({}^{-2}\) (\(p<\) 0.01), respectively (Figure 4). The trend in LAI in Hubei Province is close to the LAI trend in China (7 \(\times\) 10\({}^{-3}\) m\({}^{2}\) m\({}^{-2}\) year\({}^{-1}\)) for the period 1982-2009 [57]. Figure 4: The temporal variations in temperature (red curves), precipitation (blue curves), and ecosystem (green curves) indicators in Hubei Province. In the legend, the letter s refers to the regression coefficient, and the letter r refers to the correlation coefficient. For the temperature and precipitation indices, the regression coefficient on the left and right are for the periods 1961–2015 and 1982–2015, respectively. Significance levels are denoted as follows: \({}^{\star}\)\(p<\) 0.1 and \({}^{\star\star}\)\(p<\) 0.01. Based on five process-based ecosystem models, the greening trends of vegetation in China were mainly attributed to the rising atmospheric CO\({}_{2}\) concentration and nitrogen deposition [57].