Extreme precipitation events, which have intensified with global warming over the past several decades, will become more intense in the future according to model projections. Although many studies have been performed, the occurrence patterns for extreme precipitation events in past and future periods in China remain unresolved. Additionally, few studies have explained how extreme precipitation events developed over the past 58 years and how they will evolve in the next 90 years as global warming becomes much more serious. In this paper, we evaluated the spatiotemporal characteristics of extreme precipitation events using indices for the frequency, quantity, intensity, and proportion of extreme precipitation, which were proposed by the World Meteorological Organization. We simultaneously analyzed the spatiotemporal characteristics of extreme precipitation in China from 2011 to 2100 using data obtained from the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Despite the fixed threshold, 95th percentile precipitation values were also used as the extreme precipitation threshold to reduce the influence of various rainfall events caused by different geographic locations; then, eight extreme precipitation indices (EPIs) were calculated to evaluate extreme precipitation in China. We found that the spatial characteristics of the eight EPIs exhibited downward trends from south to north. In the periods 1960–2017 and 2011–2100, trends in the EPIs were positive, but there were differences between different regions. In the past 58 years, the extreme precipitation increased in the northwest, southeast, and the Tibet Plateau of China, while decreased in northern China. Almost all the trends of EPIs are positive in the next two periods (2011–2055 and 2056–2100) except for some EPIs, such as intensity of extreme precipitation, which decrease in southeastern China in the second period (2056–2100). This study suggests that the frequency of extreme precipitation events in China will progressively increase, which implies that a substantial burden will be placed on social economies and terrestrial ecological processes.

Global climate change is leading to an increase in the frequency, intensity, and duration of drought events, which can affect the functioning of forest ecosystems. Because human activities such as afforestation and forest attributes such as canopy height may exhibit considerable spatial differences, such differences may alter the recovery paths of drought-impacted forests. To accurately assess how climate affects forest recovery, a quantitative evaluation on the effects of forest attributes and their possible interaction with the intensity of water stress is required. Here, forest recovery following extreme drought events was analyzed for Yunnan Province, southwest China. The variation in the recovery of forests with different water availability and canopy heights was quantitatively assessed at the regional scale by using canopy height data based on light detection and ranging (LiDAR) measurements, enhanced vegetation index data, and standardized precipitation evapotranspiration index (SPEI) data. Our results indicated that forest recovery was affected by water availability and canopy height. Based on the enhanced vegetation index measures, shorter trees were more likely to recover than taller ones after drought. Further analyses demonstrated that the effect of canopy height on recovery rates after drought also depends on water availability—the effect of canopy height on recovery diminished as water availability increased after drought. Additional analyses revealed that when the water availability exceeded a threshold (SPEI > 0.85), no significant difference in the recovery was found between short and tall trees (p > 0.05). In the context of global climate change, future climate scenarios of RCP2.6 and RCP8.5 showed more frequent water stress in Yunnan by the end of the 21st century. In summary, our results indicated that canopy height casts an important influence on forest recovery and tall trees have greater vulnerability and risk to dieback and mortality from drought. These results may have broad implications for policies and practices of forest management.

Forests are one of the most important components of the global biosphere and have critical influences on the Earth’s ecological balance. Regularly updated forest cover information is necessary for various forest management applications as well as climate modeling studies. However, map products are not widely updated at continental or national scales because the current land cover products have overly coarse spatial resolution or insufficiently large training data sets. This study presents the results of forests distribution and variation information over China using Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series data with the first layer of MODIS Land Cover Type product (MODIS LC-1). The NDVI time series histogram characteristic curves for forestland were estimated from MODIS LC-1 and MODIS NDVI time series data. Based on the differences of histograms among different forests, we obtained the 2001–2011 forests distribution for China at a spatial resolution of 500-m × 500-m. The overall accuracy of validation was 80.4%, an increase of 12.8% relative to that obtained using MODIS LC-1 data. The 2001–2011 forestland pure and mixed pixels of China accounted for an average of 33.72% of all pixels. There is a gradual increase in China’s forestland coverage during 2001–2011; however, the relationship is not statistically significant.