Spatially differentiated changes in regional climate and underlying drivers in southwestern China

Abstract

The climate in Southwest China are predominantly under the influences of three contrasting climate systems, namely the East Asian monsoon, the South Asian monsoon, and the westerlies. However, it is unclear if the diversified climate systems, in combination with the complex terrain and varying vegetation types, would result in contrasting patterns of changes in climate across the region. Based on the CRU TS data for the period 1901−2017, we examined the spatiotemporal characteristics of the regional climate, and identified types of climate change patterns and drivers. Overall, the region experienced significant increases in annual mean temperature during 1901−2017, with occurrence of a significant turning point in 1954 for a more pronounced warming (0.16 °C/10 a). The annual precipitation fluctuated greatly over the study period without apparent trend, albeit the occurrence of a significant turning point in 1928 for a slight increase in the later period (1.19 mm/10 a). Spatially the multi-year averages of selective climate variables during 1901–2017 displayed a trend of decreases from southeast to northwest, but with increasing variability. We identified five major climate change types across the study region, including warmer (T+), drier (P−), warmer-drier (T+P−), warmer-wetter (T+P+), and no significant changes (NSC). The type T+P+ mainly occurred in the western parts over the plateau sub-frigid semiarid ecozone (77.0%) and the plateau sub-frigid semihumid ecozone (19.9%). The central parts of the region are characterized by the type T+, corresponding to six ecozones, including the mid-subtropical humid ecozone (33.1%), the plateau temperate humid-semihumid ecozone (28.8%), the plateau sub-rigid semihumid ecozone (9.5%), the southern subtropical humid ecozone (8.1%), the plateau sub-frigid arid ecozone (7.3%), and the plateau temperate semiarid ecozone (6.6%). No significant change in climate was detected for the eastern parts over the mid-subtropical humid ecozone (67.3%), the plateau temperate humid and semihumid ecozone (19.5%) and the plateau sub-frigid semihumid ecozone (8.8%). The types P− and T+P− together accounted for less than 5% of the entire study region, which predominantly occurred in central Yunnan-Guizhou Plateau and south of the southeastern Xizang, corresponding predominantly to the mid-subtropical humid ecozone. Across the region and within the zonal climate change types, vegetation and topography both played a significant role in determining the climate variability and magnitude of changes. Our results suggest that the southwestern China experienced intensified influences of the southeasterly monsoon and the southerly monsoon in the regional climate, while the westerly alpine influences subsided; topography and vegetation affected the magnitudes of the directional changes in climate at a local scale.

Quantifying the Spatio-Temporal Pattern Differences in Climate Change before and after the Turning Year in Southwest China over the Past 120 Years

“…(1) Simple linear regression: Simple linear regression of the climate factors (temperature and precipitation) was performed using the least-squares method on the pixel scale, where the slope of the simple linear regression equation indicated the strength of the climate factor change [44,50]. The formula for the calculation was as follows:…”

“…With reference to the commonly used concept of natural regeneration [57,58], the region of SWC covered by this study has a broader geographical meaning that attaches importance to vegetation and landscape features, and the geographical coordinates range from 21.14 to 36.48 • N and 83.87 to 110.19 • E. Geomorphologically, SWC is dominated by the Himalayas, the Qinghai-Xizang Plateau (QX-P), the Hengduan Mountains (HD-M), the Yunnan-Guizhou Plateau (YG-P), and the Sichuan Basin (SC-B). The terrain has a pattern of decreasing elevation from the west and northwest to the east and southeast [44,59,60], with elevation differences of thousands of orders of magnitude, encompassing the three primary levels of Chinese topography (Figure 1a). In addition, the uplift of the Himalayas, which blocks the warm and humid monsoon from the Indian Ocean monsoon, creates the unique climate of the QX-P.…”

“…In addition, the uplift of the Himalayas, which blocks the warm and humid monsoon from the Indian Ocean monsoon, creates the unique climate of the QX-P. The QX-P is under the influence of the South Asian monsoon, East Asian monsoon, and westerly winds, which have an essential impact on the regional and global climate of East Asia, making the QX-P a key research area [11,44,[58][59][60] and a fascinating case study for local climate change control [1, 24,53,58]. The annual mean temperature gradually increases from the northwest (less than 0 • C) to the southeast (more than 24 • C) and is constrained by topographic and climatic factors.…”

“…02) of climate variables used in this study was downloaded from the Institute of Climate Research, University of East An-glia (see Table 1), and its time range covers the period 1901 to 2017 (117 years × 12 months = 1404 months in total) with a resolution of 0.5 • × 0.5 • . The dataset has been integrated with several well-known databases to re-construct a complete, high-resolution, uninterrupted dataset of surface climate elements [62], and it is often used as a reliable source of climate information when considering the global or regional shaping of climate change and associated environmental impacts [44,59,63]. Moreover, this dataset is consistent with the interannual variability sequence of China's mean annual temperature and annual precipitation, which can be used to analyze China's century-long climate change [64].…”

“…In particular, a dramatic expansion of the temperate climate class in the temperate zone has been reported since 1950, with the most significant climate change occurring from continental to temperate among all climate scenarios [39,40,43]. Other studies have verified that the heterogeneity of vegetation spatial patterns could alleviate regional and even global climate change by adjusting the biogeochemical properties of the surface energy balance and carbon cycle [44][45][46][47][48]. Over the last three decades, biophysical feedback associated with global greening has slowed global surface warming by about 12% [45], and the average terrestrial biophysical warming caused by forest loss has reached 18% of the global biogeochemical signal caused by CO 2 [46].…”