Risk of Crop Yield Reduction in China under 1.5 °C and 2 °C Global Warming from CMIP6 Models

Abstract

Warmer temperatures significantly influence crop yields, which are a critical determinant of food supply and human well-being. In this study, a probabilistic approach based on bivariate copula models was used to investigate the dependence (described by joint distribution) between crop yield and growing season temperature (TGS) in the major producing provinces of China for three staple crops (i.e., rice, wheat, and maize). Based on the outputs of 12 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under Shared Socioeconomic Pathway 5–8.5, the probability of yield reduction under 1.5 °C and 2 °C global warming was estimated, which has great implications for agricultural risk management. Results showed that yield response to TGS varied with crop and region, with the most vulnerable being rice in Sichuan, wheat in Sichuan and Gansu, and maize in Shandong, Liaoning, Jilin, Nei Mongol, Shanxi, and Hebei. Among the selected five copulas, Archimedean/elliptical copulas were more suitable to describe the joint distribution between TGS and yield in most rice-/maize-producing provinces. The probability of yield reduction was greater in vulnerable provinces than in non-vulnerable provinces, with maize facing a higher risk of warming-driven yield loss than rice and wheat. Compared to the 1.5 °C global warming, an additional 0.5 °C warming would increase the yield loss risk in vulnerable provinces by 2–17%, 1–16%, and 3–17% for rice, wheat, and maize, respectively. The copula-based model proved to be an effective tool to provide probabilistic estimates of yield reduction due to warming and can be applied to other crops and regions. The results of this study demonstrated the importance of keeping global warming within 1.5 °C to mitigate the yield loss risk and optimize agricultural decision-making in vulnerable regions.

Trend Analysis and Projection of Climate Variables Using the LARS-WG Model in Coastal Areas of China

“…They also observed that the highest decrease in yield is anticipated in the highest emission scenario (ssp585) compared to the medium (ssp245) and lower (ssp126) scenarios in the Songnen Plains. Additionally, Wang et al (2023a) confirmed that the rising temperatures projected under the CMIP6 model have a greater detrimental effect on rice and wheat production in Sichuan province, as well as on maize production in Shandong province.…”

“…The surface air temperature observed in 2022 was the second-highest recorded temperature in China since 1961, providing evidence that China is experiencing increasing warmth as a result of climate change (Wang et al, 2022). The rise in air temperature has adversely affected crop production in numerous regions of China, with the coastal area being particularly vulnerable to the effects of increasing temperatures (Chandio et al, 2022;Saud et al, 2022;Wang et al, 2023a). According to the findings of Chandio et al (2022), the increasing air temperatures have had a significant negative impact on rice and wheat production in Sichuan province.…”

“…Particularly, China is currently experiencing extreme weather, including escalating heat waves and powerful storms in several sections of the nation (Duan et al, 2016;Sun et al, 2014;Wu et al, 2019;Zhao, 2020). The coastal regions of China are particularly susceptible to the effects of climate change due to the complex interplay of land-ocean-atmosphere dynamics, which jeopardizes national food security (Cai et al, 2021;Disasa et al, 2024;Saud et al, 2022;Wang et al, 2023a;Wang et al, 2021).…”

“…This uncertainty arises from variations in study approaches, such as the use of different climate models and climatic scenarios (Qin et al, 2023). Despite ongoing research, there are still uncertainties surrounding the anticipated long-term alterations in air temperature and precipitation within specific regions of China, including the Shandong Plain and Huaibei Plain, under future climate scenarios (Wang et al, 2023a;Wang et al, 2016;Wu et al, 2023;Yan et al, 2021;Zhang et al, 2022). The vulnerability of these regions to climate change is magnified by the intricate interaction of land-ocean-atmosphere dynamics, which is particularly pronounced due to their geographical location in the coastal regions of China (Wang et al, 2021;Yan et al, 2023).…”

Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling

“…The first differencing, as suggested in previous studies 23 , 65 , was applied as a technique to detrend the maize yield to account for the other yield impacting unobserved factors such as advancement in agricultural technology, progression of the adjustments in growers according to the management recommendations, and the infrastructural developments. The data on aforesaid factors was not available.…”