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The influences of human activity on regional climate over China have been widely reported and drawn great attention from both the scientific community and governments. This paper reviews the evidence of the anthropogenic influence on regional climate over China from the perspectives of surface air temperature (SAT), precipitation, droughts, and surface wind speed, based on studies published since 2018. The reviewed evidence indicates that human activities, including greenhouse gas and anthropogenic aerosol emissions, land use and cover change, urbanization, and anthropogenic heat release, have contributed to changes in the SAT trend and the likelihood of regional record-breaking extreme high/low temperature events over China. The anthropogenically forced SAT signal can be detected back to the 1870s in the southeastern Tibetan Plateau region. Although the anthropogenic signal of summer precipitation over China is detectable and anthropogenic forcing has contributed to an increased likelihood of regional record-breaking heavy/low precipitation events, the anthropogenic precipitation signal over China is relatively obscure. Moreover, human activities have also contributed to a decline in surface wind speed, weakening of monsoon precipitation, and an increase in the frequency of droughts and compound extreme climate/weather events over China in recent decades. This review can serve as a reference both for further understanding the causes of regional climate changes over China and for sound decision-making on regional climate mitigation and adaptation. Additionally, a few key or challenging scientific issues associated with the human influence on regional climate changes are discussed in the context of future research. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the spatial and temporal variation characteristics of the potential evapotranspiration (ET0) and its response to climate change using the collected data from the daily weather observation of 23 meteorological stations in the Beijing-Tianjin-Hebei region for 57 years from 1960-2016. The specific parameters of dataset included the daily average air temperature, the maximum and minimum air temperature, relative humidity, wind speed and sunshine hours. We chose the Penman-Monteith formula to calculate the daily ET0 at each site, and then analyzed the spatial and temporal variation characteristics of the calculated ET0. A sensitivity coefficient was used to quantitatively study the sensitivity of ET0 to various meteorological elements and its spatial and temporal distribution. The contribution rate was set to evaluate the influence of meteorological elements changes on the variation of ET0 during the calculation. The results show that: 1) The spatial distribution of ET0 shows a decreasing trend from south to north across the Beijing-Tianjin-Hebei region, except a high ET0 in the central region, such as Tanggu, Huangye and Baoding stations. There was a linear decline rate of -0.92mm /a. e in the whole distribution of ET0. The spatial distribution of ET0 MK (Penman-Monteith) decreased from the northwest to southeast. In temporal characteristics, spring has the most obvious decrease, followed by autumn, summer, and winter. 2) The sensitivity coefficient of ET0 to the average air temperature, sunshine hours, relative humidity and wind speed are 0.26, 0.28, 0.31 and -044, respectively, indicating the most sensitive to the changes of relative humidity in the Beijing-Tianjin-Hebei region, followed by the wind speed and sunshine hours. The sensitivity coefficient of ET0 to meteorological elements presents in a fluctuating trend from1960-2016, the sensitivity coefficient of ET0 to the wind speed and relative humidity in a downward trend, while the sensitivity coefficient of ET0 to average temperature and sunshine hours in an upward trend. The spatial distribution of the sensitivity coefficient from northwest to southeast: the wind speed and average temperature gradually increased, while the sunshine hours and relative humidity gradually decreased. The spatial distribution characteristics of the sensitivity coefficient of ET0 to relative humidity and average temperature were the opposite situation, where the high sensitivity zone of average temperature belongs to the low sensitive zone of relative humidity. The opposite phenomenon also occurred in the spatial distribution characteristics of the sensitivity coefficient of ET0 to sunshine hours and wind speed sensitivity, i.e., the high sensitivity zone of sunshine hours belongs to the low sensitive zone of wind speed. 3) The contribution rate of meteorological elements to ET0 depends on the sensitivity coefficient and the relative change of meteorological elements. ET0 has the most sensitivity to the changes of relative humidity, but the change rate of the relative humidity was small. ET0 has the lower sensitive to the changes of wind speed, but the change rate of the wind speed was large, resulting the most contribution to ET0 in the whole region was the wind speed. However, the stations number of the wind speed as the dominant factor decreased with the measure time, whereas the stations number of the average temperature as the dominant factor increased with the measure time, especially in the period of 2010—2014 to 2010s, 12 stations with the average temperature as the dominant factor. The stations number of the sunshine hours as the dominant factor also increased with the measured time. It infers that the average temperature and sunshine hours have much significant influences on ET0 in recent years. From 2013 to 2016, the correlation coefficients of the winter average air temperature, sunshine hours, relative humidity, wind speed and PM2.5 concentration were -0.44, -0.53, 0.42 and -0.35, respectively, while the correlation coefficients of ET0 and PM2.5 concentration were -0.37. Therefore, it is possible that the haze, especially winter haze, has a certain impact on meteorological elements, and thereby on ET0 in the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms underlying drying-wetting cycles and their consequence for vegetation dynamic is important for sustainable eco-environmental development in alpine regions. We investigated these in this paper by taking the Yarlung Zangbo River (YZR) basin in southeast Qinghai-Tibet Plateau as an example. The standardized precipitation evapotranspiration index (SPEI) in the region was calculated using the global land data assimilation system (GLDAS) from 1982 to 2015 to represent the drying-wetting cycles. The spatiotemporal variation of the dry-wet cycles and the responsive vegetation dynamic was investigated using the remotely sensed NDVI (normal difference vegetation index) from GIMMS (global inventory modeling and mapping studies). The results showed that: 1) Spatiotemporal variation of both precipitation and surface air temperature calculated from GLDAS agreed well with the ground-truth data. 2) The spatiotemporal changes in the dry-wet cycles calculated from the SPEI from 1982 to 2015 showed that the YZR basin became increasingly wet from 1982-1999 but changed course in 2000 and has been become increasingly drier since. In particular, the arid areas showed a tendency of wetting whereas the humid areas tended to become drying. 3) The overall vegetation calculated from the NDVI had been in increase from 1982 to 2000 but changed course in 2000 and has been in decline since. In terms of spatial distribution, areas with higher NDVI value represented vegetation degradation, while areas with lower NDVI represented an improvement in vegetation. 4) Approximately 71.83% of the areas saw a positive correlation between the SPEI and NDVI, mainly in the middle and low reaches of the basin which have a high vegetation coverage. Areas showing negative correlation between SPEI and NDVI were small and not statistically significant. The high consistency between spatiotemporal variation of the NDVI and SPEI indicated that the drying-wetting cycles played an important role in vegetation dynamics. 5) The driving forces of the dry-wet cycles were precipitation, surface air temperature, potential evapotranspiration and soil water content, which were consistent with that estimated from SPEI. In addition, the SPEI showed that soil water content was the dominant factor impacting the drying-wetting in 92.17% of the areas in the region. Results of this study have important implications for evaluating water cycles and the associated vegetation dynamics in alpine regions. [ABSTRACT FROM AUTHOR]