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ABSTRACT Land-use and land-cover change ( LUCC, such as the conversion of natural landscape to agricultural land) and human activities ( HAs) are the most important human influences ( HIs) on regional climate. Studying such influences is fundamental to understanding anthropogenic climate change. Our objectives were to quantify contributions of HI on regional temperature change and demonstrate that HI may cause abrupt climate change. We quantified the contribution of HI on regional temperature by comparing the seasonal temperature changes between a human-dominated plain and an adjoining natural plain using the daily maximum ( Tmax) and minimum ( Tmin) temperature data from 12 meteorological stations. We quantified the contribution of HA on regional temperature change using winter weather data because snow cover in both plains masked the effects of LUCC. HI caused decreases in Tmax and increases in Tmin, and an increase in mean temperature. HA contributed to the reduction in the diurnal temperature range, whereas LUCC caused an increase in the range. The abrupt temperature change was in accord with the abrupt changes in agricultural land area and population. The HI led to an abrupt change in Tmax 3 years earlier (1985) than the recognized abrupt climate change in the Northern Hemisphere (1988). The synthetic effects of HI ( LUCC and HA) evidently altered the change trends and accelerated abrupt changes in regional temperature, which affected the regional climate. Our findings can elucidate regional climate patterns and improve the accuracy of downscaling general circulation models. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate involves different combinations of temperature and precipitation, and each year's combination of factors can be assigned a climatic year type ( CYT; e.g. Warm-Humid). Describing the changes in the CYT provides more information than describing the temperature or precipitation data alone. In this study, we defined nine CYTs using the probability density function of annual temperature and precipitation. Recent and future spatiotemporal changes in CYT were analysed using 507-station observational data and projected data obtained from the CMIP5 multi-model ensemble under RCP2.6, RCP4.5, and RCP8.5 scenarios. China was divided into six subregions to analyse the spatiotemporal changes. Obvious differences in spatial patterns among the various CYTs reflect the climate regime throughout China. The warmth-associated CYTs (Warm-Humid, Warm-Dry, and Warm-Normal) mainly occur in West China (e.g. Southwest China). The cold-associated CYTs (Cold-Humid, Cold-Dry, and Cold-Normal) dominate at high latitudes and high altitudes (e.g. Northeast China and the Tibetan Plateau). The climate in China changed from cold to warm in the last half-century, accompanying the transformation of Cold-Humid, Cold-Dry, and Cold-Normal before the early 1990s to Warm-Humid, Warm-Dry, and Warm-Normal from the early 1990s onward. In the 21st century, the projected CYTs are mainly Warm-Humid, Warm-Dry, and Warm-Normal in China. Warm-Humid dominates in West China, North China, and Northeast China. Warm-Dry is mainly projected in the Yellow River Valley and South China. High-frequency Warm-Normal is projected in the Yellow River Valley. Warm-Humid is projected to increase whereas Warm-Dry and Warm-Normal are projected to decrease from 2015 to 2099. All three CYTs are projected to exhibit larger changes in trends under stronger versus weaker RCPs ( RCP8.5 > RCP4.5 > RCP2.6). Compared with temperature or precipitation data alone, CYTs provide more complete information on climate change and more accurately characterize regional differences in climate throughout China. [ABSTRACT FROM AUTHOR]