Search

Due to global warming and other climate changes, it is increasingly important to study the response of regional environmental changes and dynamic changes in vegetation to climate change. Based on meteorological data from the last 60 years, this paper calculates the humidity index of western China under a wide range of long time series in different regions and explores the cross-correlation effect between series by offering a comparison with NDVI data, to analyze the cross-correlation between wet and dry changes and changes in vegetation in western China on a spatial scale. The results show that the spatial distribution of the interdecadal humidity index is different between different regions in western China. For example, the semi-arid and the semi-humid zones of the Weihe River region exhibit significant changes, while the Xinjiang and Qinghai–Tibet regions show a trend of constant wetness, on the whole, and the Sichuan and Yunnan–Guizhou regions are relatively humid and the distribution of wetness and dryness is relatively stable. The distribution of high and low values of the humidity index is very obvious and consistent with that of the distribution of desert bare land and precipitation in western China. In common with the distribution in the humidity index, the maximum correlation number between the NDVI and the humidity index in the whole western region is also significantly different in spatial distribution. There is a positive correlation between the NDVI and the humidity index in 99% of the study area. However, the delay in response time of the NDVI to changes in the humidity index in each region is inconsistent. For example, changes in the NDVI lag changes in the humidity index in the Menggan region by generally either 2 months or 5 months, while in the Sichuan region the delay in response time is generally 3 months. The variation and trend in dry and wet areas are closely related to the geographical location, climate zone, and topographic terrain, which may be the reason for the differences in the distribution of vegetation types and the response time to dry and wet changes. There is significant interaction between the humidity index and the vegetation type or precipitation distribution in western China. The positive correlation between the NDVI and the humidity index means that the positive effect is more sensitive, and the response of grassland is the most sensitive in the ecosystem. [ABSTRACT FROM AUTHOR]

Situated in a climatically stressful environment, alpine grassland is sensitive to subtle climate changes in its productivity. We remedy the current deficiency in studying grassland productivity by taking the integrated effect of all relevant factors into consideration. The relative importance of temperature, rainfall and evaporation to the alpine grassland productivity in western China was determined through analysis of their relationship with the normalized difference vegetation index (NDVI) between 1981 and 2000. Climate warming stimulated grassland productivity in the 1980s, but hampered it in the 1990s. Temperature is more important than rainfall to grassland productivity early in the growing season. However, their relative importance is reversed late in the growing season. Monthly summer month rainfall modified by maximum monthly temperature is a good predictor of alpine grassland productivity at 62.0 per cent. However, the best predictor is water deficiency, which is able to improve the estimation accuracy to 78.3 per cent. Hence, the impact of temperature on grassland productivity is better studied indirectly through evaporation. [ABSTRACT FROM AUTHOR]

Positive degree-day (PDD) indicates the accumulated positive temperature in a given time period; it directly relates to the melting of snow and ice, and it is a key parameter between global warming and cryosphere changes. In this study, we calculated the PDD based on the daily mean temperatures from 1960 to 2018 at meteorological stations, and we used measured and interpolated data to determine spatial and temporal distribution and changes in PDD in western China (WC). Results show that the mean annual, warm season, and cold season PDD values at 209 meteorological stations were 3652.2, 2832.9, and 819.3 °C, respectively. PDD spatial distribution in WC is similar to that of air temperature. In WC, PDD mainly ranged from 0 to 5000, 1000 to 4000, and 0 to 1000 °C year−1, respectively for annual, warm season, and cold season. From 1960 to 2018, the observed mean initial day of PDD moved forward by 8.3 days, and the final day was delayed by 8.2 days, with the duration expanding to 16.6 days; the trend in PDD reversed in the 1980s and the change rate in PDD for annual, warm season and cold season was 6.6, 3.8, and 2.7 °C year−1, respectively. Regionally, PDD increased in almost all areas; the high PDD advanced from south to north, east to west, desert to mountain, and low to high altitudes. The results also showed that the warming rate of PDD was lower in the cold season and in high-altitude areas, which was opposite to the observed temperature patterns, however, the non-linear relationship between PDD and mean temperature over a period of time is the main reason for this phenomenon. This study adds more details for the understanding of climate change in WC, and suggests that more attention should be paid to PDD in the study of cryosphere changes. [ABSTRACT FROM AUTHOR]