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Vol:.(1234567890)Scientific Reports |        (2022) 12:17268  | https://doi.org/10.1038/s41598-022-22228-7
www.nature.com/scientificreports/
from 5 climate models under 4 RCP scenarios, the future climate situations were selected which are the approxi-
mate scenarios with global warming by 1.5 °C and 2.0 °C at the end of 21 century relative to pre-industrial 
levels; it could minimize the uncertainties of future climate data. The inputs for DSSAT simulation include soil 
parameters, crop calendar data and management information are coped with carefully to improve the effective-
ness and reliability of maize yield simulation.
There are also several uncertainties and limitations. Firstly, there is no unified understanding of how to cal-
culate the temperature rise of 1.5 °C and 2.0 °C relative to pre-industrial levels in the worldwide. At present the 
research on climate prediction and impact assessment under global warming 1.5 °C and 2.0 °C usually adopts 
multi-mode ensemble average  methods61,62, which could obtain the warming response under the condition of 
instantaneous change, rather than the warming process under the stable state expected by the long-term goal. If 
we expect to obtain the accurate results, the model prediction test should be estimated to form proprietary sce-
narios for global warming by 1.5 °C and 2.0 °C63,64, which could support for the impacts assessment on different 
sectors. Some institutions are carrying out climate change predictions under the lower emission scenarios (global 
warming 1.5 °C or 2.0 °C). At the same time, in order to achieve the goal of controlling temperature by 1.5 °C at 
the end of the twenty-first century, it is urgent to take actions to reduce emissions and develop along the track 
of low energy  consumption65,66; but it is a great challenge for human society to achieve this goal.
Secondly, our methodological approach in this study also has some important limitations, including our use 
of a single crop model to estimate maize yields. There are some limitations for the DSSAT model to simulate 
yield loss caused by climate extreme  events67, in which the impacts of pests and diseases are also  ignored68. 
However, the DSSAT model has been applied in a lot of researches to simulate historical maize  yield69–71, in 
which the results are reliable and  credible72. The results of this research could be an important reference to the 
other studies which simulate global maize yield in the future, applying crop models such as APSIM, WOFOST, 
ORYZA and so on.
Thirdly, there are relatively more researches on the prediction of climate change trend under the background 
of 1.5 °C and 2.0 °C; but the research on the impact assessment of the main grain crops including global trade in 
worldwide is few. In the meantime, we do not assess the effect of future changes on agriculture, such as increases 
in farm productivity due to new technology. The maize planting area in the future is assumed to be the same as 
the current situation of maize cultivation in the world.
Conclusion. According to the simulation results, the yield of maize under global warming by 2.0 °C would 
decrease between 3.0 and 18.7% in the worldwide relative to 1986–2005; the maize yield would fluctuate between 
− 6.8 and 7.2% under global warming by 1.5 °C. From the spatial distribution, the gross maize yield in the top 5 
high-yield countries (including the United States, China, Brazil, Argentina and Mexico) would decrease by 2% 
under global warming by 1.5 °C and 11.4% under global warming by 2.0 °C. At the global level, the market price 
for maize would increase by 0.7% and 3.4% under 1.5 °C scenario and 2.0 °C scenario, respectively, which would 
vary quite largely among different countries and regions. So, it is urgent for all countries to pay enough attention 
to the loss risk of maize yield and take actions of mitigation and adaptation to climate change. The time left for