Trend Analysis and Projection of Climate Variables Using the LARS-WG Model in Coastal Areas of China
Authors: Disasa Kinde Negessa , Yan Haofang , Wang Guoqing , Zhang Jianyun , Zhang Chuan , Zhu Xingye , Xue Run , Wang Biyu , Bao Rongxuan 
Published: May 2024

Abstract

The rising air temperature and shifting precipitation patterns threaten crop production and water distribution worldwide. The coastal region of China, specifically the Huaibei and Shandong Plains, is recognized as one of the most vulnerable areas among those impacted due to the complex interplay of land, sea, and atmospheric dynamics. The study utilized traditional trend analysis methods (Mann-Kendall and Sen's Slope) along with an innovative polygon trend analysis (IPTA) to predict the baseline arithmetic mean and standard deviation of the monthly precipitation trend. Moreover, the latest version of the Long Ashton Research Station Weather Generator (LARS-WG 7) model was used to predict average mean monthly precipitation and maximum and minimum temperatures for two future times: midterm 2050 (2041–2060) and long-term 2080 (2071–2090). The performance of each GCM incorporated in LARS-WG was evaluated independently and compared to a multi-model ensemble. All of the meteorological stations that were analyzed using the MK method (except for Suzhou, Dangshan, and Mengcheng) showed a significant decreasing trend in the arithmetic mean of monthly precipitation in March. However, for the majority of the remaining months, the study indicated a non-significant decreasing trend. In contrast, the IPTA method demonstrated a significant decreasing trend in most months, highlighting its superior ability to detect hidden trends compared to the MK method. The projections showed that mean annual precipitation is likely to increase at all meteorological stations in the Huaibei Plains and Shandong Plains during two periods: 2050 (2041–2060) and 2080 (2071–2090). A maximum increase in average mean annual precipitation is projected at the highest emission scenario (ssp585) as compared to the medium (ssp245) and low emission (ssp126) scenarios, and at the long-term period 2080 (2071-2090) as compared to the mid-term period 2050 (2041-2060). The mean annual precipitation in the Shandong Plain is projected to increase by 10.4%, 14.5%, and 14.8% under the ssp126, ssp245, and ssp585 scenarios, respectively. Similarly, in the Huaibei Plain, the projected increases are 10.9%, 13.6%, and 15.1% under the ssp126, ssp245, and ssp585 scenarios, respectively. The anticipated increase in mean precipitation per decade is expected to be 2.0% (= 1.96 mm/decade) in the Huaibei Plain and 1.31% (= 0.63 mm/decade) in the Shandong Plain. Both maximum and minimum temperatures are projected to increase persistently across all meteorological stations during two time periods: 2050 (2041–2060) and 2080 (2071–2090) under three different SSPs (ssp126, ssp245, and ssp585). The long-term period 2080 (2071–2090) is projected to experience the highest increase in both maximum and minimum temperatures, surpassing the increases observed in the midterm period 2050 (2041–2060). Among the different SSPs, the greatest increase in both maximum and minimum temperature was projected under the highest forcing emission scenario, SSP 585. With a persistent increase in air temperature and precipitation patterns fluctuating under a future climate scenario in the coastal area of China, climate change can influence all aspects of life, especially water resource distribution and agricultural water management. This study provides valuable insight for water resources planners and agricultural experts in the coastal region of China, as this area is a very vulnerable area to climate change and is also the main staple food-producing area in China.