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Projection of future precipitation, air temperature, and solar radiation changes in southeastern China

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Abstract

Evidence of climate change can be observed in multiple climate variables, including air temperature rises and precipitation pattern changes. To manage water resources and agriculture effectively, it's important to project climate variables' changes at the local level, as these changes can vary depending on the specific area. The baseline weather data trend was analyzed using the percentage change (PC) method and the Innovative Trend Analysis (ITA) technique at three cluster levels: cluster 1 (PC: 0–20%), cluster 2 (PC: 21–80%), and cluster 3 (PC: 81–100%). The precipitation (Prec.), maximum (Tmax), and minimum (Tmin) temperatures showed downward trends in 9, 4, and 6 stations out of 24 stations, respectively. The SDSM model performed best in predicting Prec., while the LARS-WG model was more effective in predicting Tmax, Tmin, and solar radiation (SR). The average monthly Prec. percentage change shows both rising and falling trends in different weather areas for all three time periods (2040, 2060, and 2090) and for both RCPs (RCP4.5 and RCP8.5). In contrast to precipitation, both Tmax and Tmin consistently showed an upward trend across all meteorological stations for both RCPs and three-time frames. Across the four distinct plain regions, the overall projection suggests a slight increase in precipitation. The study predicts the highest increase in precipitation to occur in June across all meteorological stations. Seasonally, the greatest increase in precipitation is projected during summer (JJA) by 5.10%, while the largest decrease is expected during winter (DJF) by 3.29%. Additionally, precipitation variability shows an increase from RCP4.5 to RCP8.5 and from near-term (2040) to long-term (2090), with the northern Jiangsu Plain exhibiting the highest variation. The biggest rise in Tmax/Tmin was observed at RCP 8.5, by 2.69/2.39 °C, and in the long term (2090), by 3.25/2.86 °C. This was compared to RCP 4.5 by 1.73/1.51 °C, in the near term (2040) by 1.24/1.08 °C, and in the mid-term (2060) by 2.14/1.90 °C. The highest increase in Tmax is expected compared to Tmin, leading to the highest diurnal temperature (DTR) at all three periods and both RCPs. Seasonally, the highest increase is projected in the autumn for both Tmax and Tmin. Similar to Tmax and Tmin, the longest time period (2090) exhibits the highest increase in solar radiation, followed by the midterm (2060) and then the short term (2040). Unlike Tmax and Tmin, the highest increase in SR is predicted during the summer season (JJA), while the lowest increase is projected during the winter season (DJF). The future projections highlight the expectation of a wettest and hottest summer, along with the driest and coldest winter. These findings provide valuable insights for water resource planners, agricultural managers, and policymakers, as these climate variables play a significant role in crop production and water allocation decisions.

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Data availability

The corresponding author can provide the raw and generated data used in this study upon a reasonable request.

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Acknowledgements

We extend our gratitude to the National Climatic Centre of the China Meteorological Administration for their contribution in providing the meteorological data utilized for this study.

Funding

This study has been financially supported by the Natural Science Foundation of China (U2243228, 41860863, 51509107); the Belt and Road Special Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (2020nkzd01); Yinshanbeilu Grassland Eco-hydrology National Observation and Research Station, China Institute of Water Resources and Hydropower Research, Beijing 100038, China (Grant NO.YSS2022011); the Key R&D Project of Jiangsu Province (BE2022351).The authors also extend their gratitude to editors and anonymous reviewers for their valuable time and constructive comments and guidance on this article.

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Authors and Affiliations

  1. Research Centre of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, 212013, China

    Kinde Negessa Disasa, Haofang Yan & Xingye Zhu

  2. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210029, China

    Haofang Yan, Guoqing Wang & Jianyun Zhang

  3. School of Agricultural Equipment Engineering, Jiangsu University, Zhenjiang, 212013, China

    Chuan Zhang

Authors
  1. Kinde Negessa Disasa
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  2. Haofang Yan
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  3. Guoqing Wang
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  4. Jianyun Zhang
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  5. Chuan Zhang
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  6. Xingye Zhu
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Contributions

K.N. Conceptualization, Writing – original draft.

Y.H. Funding acquisition, Supervision, Writing – review & editing.

G.W. Data curation, Resources, Supervision.

J.Z. Collect data and supervision.

C.Z. Revised the manuscript, Supervision.

X.Z. Revised the manuscript, Supervision.

Corresponding author

Correspondence to Haofang Yan.

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We declare that there are no known financial or interpersonal conflicts that could have potentially affected the research presented in this study.

Competing interests

The authors declare no competing interests.

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Disasa, K.N., Yan, H., Wang, G. et al. Projection of future precipitation, air temperature, and solar radiation changes in southeastern China. Theor Appl Climatol (2024). https://doi.org/10.1007/s00704-024-04891-0

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