Reanalysis temperature products are important datasets for temperature estimates over high-elevation areas with few meteorological stations. In this study, surface 2 m air temperature data from 17 meteorological stations from 1979 to 2017 in the Qilian Mountains (QLM) are used for comparison with the newest reanalysis product: ERA5-Land derived from the European Centre for Medium-Range Weather Forecasts (ECMWF). In general, the ERA5-Land temperature product can reproduce the observation variation at different time scales very well. A high monthly correlation coefficient that ranges from 0.978 to 0.998 suggests that ERA5-Land reanalysis temperature could capture the observations very well. However, attention should be paid before using ERA5-Land at individual sites because of the average root-mean-square-error (RMSE) of 2.2°C of all stations. The biases between ERA5-Land temperature and observations are mainly caused by the elevation differences between ERA5-Land grid points and meteorological sites. The annual mean temperature shows a significant warming trend (0.488°C/decade) from 1979 to 2017 based on the observations. ERA5-Land reanalysis temperature captures the increasing trend very well (0.379°C/decade). The biggest positive warming trends of observations and ERA5-Land are both found in summer with values of 0.574°C/decade and 0.496°C/decade, respectively. We suggest that ERA5-Land generally reproduces the temperature trend very well for observations and is reliable for scientific research over the QLM.

An increased understanding of the responses of forest phenology to climate on regional scales is critical to the evaluation of biochemical cycles (i.e. carbon, water, heat, and nutrient) under environmental changes. In this study, we aimed to identify climatic constraints on phenological events in an evergreen coniferous forest in semi-arid mountain regions of northern China. We quantified the start of season (SOS), end of season (EOS), and growing season length (GSL) based on satellite-derived data sets (normalized difference vegetation index (NDVI)) and investigated the relationships between these phenological events and climate factors. The results revealed discontinuous trends in phenological events throughout the study period, with neither an obvious extension nor decrement in GSL. We demonstrated that minimum temperatures controlled the dynamics of SOS and EOS, thus providing strong evidence for the need to include minimum temperature as a control on phenology in simulation models. Additionally, precipitation was coupled to the shift in maximum NDVI, as rainfall is a major climatic limitation to vegetation growth in semi-arid regions. It appears that selecting appropriate timescales to analyse the relationships between phenology and climate is critical. We illustrated that NDVI was an effective tool in an effort to gain greater understanding of the effects of environmental change on ecosystem functioning in this forest. Our results may be used as reference to track local changes in the evergreen coniferous forest dynamics under different climate change scenarios for semi-arid mountain regions.

Changes in climate extremes pose far-reaching consequences to ecological processes and hydrologic cycles in alpine ecosystems of the arid mountain regions. Therefore, regional assessments in various climates and mountain regions are needed for understanding the uncertainties of the change trends for extreme climate events. The objective of this study was to assess the spatial distribution and temporal trends of extreme precipitation and temperature events responses to global warming on the arid mountain regions of China. Results found that temperature extremes exhibited a significant warming trend, consistent with global warming. Warming trend in autumn and winter were greater than in spring and summer. Besides, precipitation extremes also exhibited statistically increase trend, such as number of days with heavy precipitation and rain day precipitation, etc. The distribution of the number of rainy days was showed a significant increasing trend in many sites, indicating that the increase of rain day precipitation mainly contributed by the increase of single precipitation event duration and moderate-rain days. The greater increasing trend of extreme climate events mainly existed in higher altitudes. This results lend an evidence to earlier predictions that the climate in northwestern China is changing from cold-dry to warm-wet.

Global climate change is likely to affect reference evapotranspiration (ET₀) and the use of water resources for vegetation management. Our goals were to identify spatio‐temporal characteristics of ET₀ and factors controlling the change in ET₀ and to project spatio‐temporal changes in the Qilian Mountains of China under the future climate conditions. Changes in ET₀ were estimated by the Penman–Monteith method for 22 meteorological stations from 1960 to 2015. We quantified the attributions of climatic factors with the differentiation equation method. Then, we assessed the spatio‐temporal changes in projected ET₀ with CanESM2 model outputs and statistical downscaling model for three representative concentration pathways (RCP) scenarios for years 2016–2100. We found that annual ET₀ averaged across the region was 1001.5 mm, with an insignificant decrease of −0.43 mm/year during 1960–2015. The lowest values were present in the alpine region in the central area, while the highest ET₀ was detected in the western region. An annual and seasonal “evaporation paradox” existed in the Qilian Mountains during the past few decades. Mean daily air temperature measured (T_mean) and wind speed (U₂) were the dominant factors in ET₀ change. However, the decreasing trend in ET₀ may be due to a diminished effect of T_mean triggered by short‐wave radiation (R _s), actual vapour pressure (e _a), and wind speed (U₂), but especially by the substantial reduction in U₂ at most stations. Compared with the baseline, ET₀ is likely to increase by 6.31–7.20, 6.11–10.41, and 6.58–17.66%, respectively, under RCP scenarios of 2.6 (very low forcing scenario), 4.5 (medium stabilization scenario), and 8.5 (very high emission scenario), but RCP2.6 ET₀ rates level off and even decline after 2050 while RCP4.5 rates climb only marginally after 2050. Thus, ET₀ projected with the CanESM2 model displayed an upwards trend in the Qilian Mountains, especially the central alpine region.