Projection of Temperatures and Precipitation Using the <scp>LARS</scp> ‐ <scp>WG</scp> Model in Eastern China Under the <scp>CMIP6</scp> Scenarios

ABSTRACT Increasing atmospheric temperatures and variations in precipitation patterns pose significant threats to agricultural productivity and water resource management. This study aimed to detect the trends and future projections of temporally and spatially specific decisive climate variables in agricultural production and hydrological cycles for the major crop‐producing region of eastern China, specifically Anhui, eastern Henan, southwestern Shandong and northern Jiangsu, which are considered the most climate‐vulnerable regions in the country. Precipitation ( P ), maximum ( T max ), and minimum ( T min ) temperatures were projected from six global circulation models (ACCESS‐ESM1‐5, HadGEM3‐GC31‐LL, MRI‐ESM2‐0, CNRM‐CM6‐1, GFDL‐ESM4 and MPI‐ESM1‐2‐LR) using the latest version of the Long Ashton Research Station Weather Generator (LARS‐WG 8) model for two future periods: mid‐term 2050 (2041–2060) and long‐term 2080 (2071–2090) under three Shared Socioeconomic Pathways (ssp126, ssp245 and ssp585). Furthermore, the baseline (1991–2020) arithmetic mean and standard deviation of the monthly and annual precipitation trends were identified using conventional trend analysis techniques (Mann‐Kendall and Sen's Slope tests), in conjunction with innovative polygon trend analysis (IPTA). The results indicated that all meteorological stations in Anhui Province, except for Suzhou, Dangshan and Mengcheng, showed a significant decreasing trend in the arithmetic mean of monthly P in March, based on the MK method. However, a significant increasing trend was identified only in August at Bengbu station. Bozhou and Yanzhou stations showed a significant annual decreasing trend in P . In contrast, the IPTA method demonstrated a significantly decreasing trend in most months, indicating its higher sensitivity than the MK method in detecting precipitation data series. The projections showed that the average monthly and annual P is likely to increase at all meteorological stations in the future. The annual average precipitation change showed the greatest increase under ssp126 (=14.25 mm), followed by ssp585 (=10.58 mm) and ssp245 (=9.47 mm) in the mid‐term period (2050). In contrast, in the long‐term period (2080), the highest annual average P was projected under ssp585 (=21.22 mm), followed by ssp245 (=20.65 mm) and ssp126 (=15.48 mm). Monthly P was projected to increase in four provinces, except in August in East Henan, where a notable decrease was observed. Significant increases were anticipated in June in Anhui (=41.00 mm), August in Shandong (=32.10 mm), July in East Henan (=47.80 mm), and June in Northern Jiangsu (=34.10 mm). Both T max and T min are anticipated to increase persistently across all meteorological stations during the two periods 2050 (2041–2060) and 2080 (2071–2090) under the three SSP scenarios. The long‐term period (2080) was projected to experience the highest increases in both T max and T min , surpassing the increases observed in the mid‐term period (2050). The mean monthly diurnal temperature range (DTR) exhibited an increasing trend in the future across Eastern China, with the highest increase expected in summer (JJA) by 0.24°C in 2050 and in spring (MAM) by 0.33°C. With a persistent increase in air temperature and fluctuating precipitation patterns under future climate scenarios in eastern China, climate change can influence all aspects of life, particularly water resource distribution and agricultural water management. This study provides valuable insights for water resource planners and agricultural experts in the eastern region of China, which is vulnerable to climate change and is the main staple food‐producing area of China.