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The summer cooling effect under the projected restoration of Aral Sea in Central Asia

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Abstract

The Aral Sea once covered 68 × 103 km2, but lost 90% of its area during the last decades due to unreasonable water resources utilization. Fortunately, some measures to save the Aral Sea have been proposed. Regional climate model ALARO-SURFEX was applied in dynamic downscaling simulations to quantify the climatic effects generated by increasing greenhousegas (GHG) emissions and the Aral Sea restoration. The results show that performance of CNRM-CM5 dynamically downscaled by ALARO-SURFEX in reproducing 2-m temperature is reliable and better than outputs of 17 global climate models. If the Aral Sea kept the almost dry-up state (8.6 × 103 km2) in the future (2021–2050), the Aral Sea region will suffer a warmer summer than in historical period. Daily maximum (T2max), mean (T2avg), and minimum (T2min) temperature will rise by 0.91 °C, 1.06 °C, and 1.22 °C, respectively, and reduce diurnal temperature range (DTR) by 0.31 °C. If the Aral Sea could recover to twice its current area (17.2 × 103 km2), the T2max and T2avg (T2min) over the ambient region of Aral Sea (350 km) will reduce (increase) by 1.54 and 1.10 °C (1.16 °C), respectively, which can dampen the DTR by 2.4 °C. The cooling effect induced by the projected Aral Sea restoration is mainly contributed by enhanced latent heat. While the warming effect caused by GHG emissions increase is primarily attributed to increased incoming longwave radiation. This study quantified the summer cooling effect under the projected restoration of Aral Sea, which could provide scientific reference in working out the sustainable development strategies under the warming threat in Central Asia.

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Data availability

The outputs from the ALARO-SURFEX, model scripts and code for processing data in this study have been uploaded to GitHub (https://github.com/hehuili-XIEG/Projected-Summer-climate-change-in-the-Aral-Sea-region).

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Acknowledgements

The ground station observations are from Global Historical Climatology Network (https://catalog.data.gov/dataset/global-historical-climatology-network-daily-ghcn-daily-version-3). The Remote Sensing and GIS application Laboratory of Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences is gratefully acknowledged for providing the high-resolution land use/cover map, and the data is available through (Chen et al. 2015). Output of GCMs is downloaded from World Climate Research Programme (https://esgf-node.llnl.gov/projects/cmip5/).

Funding

This research has been supported by the National Natural Science Foundation of China (grant no. U1803243), the High-end Foreign Expert Recruitment Program from the Ministry of Science and Technology of China (Grant No. G2022045012L), the regional collaborative innovation project of Xinjiang (grant no. 2020E01042), Jiangsu Higher Education Basic Science (Natural Science) Research Grant Project (21KJB170007), and and Double Innovation Doctoral Program in Jiangsu Province (Grant No. JSSCBS20210861).

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Authors and Affiliations

  1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China

    Huili He, Geping Luo, Xiuliang Yuan, Philippe De Maeyer & Alishir Kurban

  2. Atmospheric Science and Remote Sensing College, Wuxi University, Wuxi, China

    Huili He & Peng Cai

  3. Department of Geography, Ghent University, Ghent, Belgium

    Huili He & Philippe De Maeyer

  4. University of Chinese Academy of Sciences, Beijing, China

    Huili He & Philippe De Maeyer

  5. Meteorological and Climatological Department, Royal Meteorological Institute, Brussels, Belgium

    Rafiq Hamdi & Piet Termonia

  6. Department of Physics and Astronomy, Ghent University, 9000, Ghent, Belgium

    Rafiq Hamdi & Piet Termonia

  7. CAS Research Centre for Ecology and Environment of Central Asia, Urumqi, China

    Geping Luo & Alishir Kurban

  8. Northwest Land and Resources Research Center, Shanxi Normal University, Xi’an, China

    Miao Zhang

  9. Sino-Belgian Joint Laboratory of Geo-Information, Urumqi, China

    Philippe De Maeyer

  10. Sino-Belgian Joint Laboratory of Geo-Information, Ghent, Belgium

    Philippe De Maeyer

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  1. Huili He
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Contributions

Huili He: writing-original draft preparation, software, formal analysis. Rafiq Hamdi: conceptualization, resources and writing-review & editing. Geping Luo: supervision and funding acquisition. Peng Cai: software and formal analysis. Miao Zhang: writing—review. Xiuliang Yuan: writing—review & editing. Piet Termonia: supervision and resources. Philippe De Maeyer: supervision and writing-review & editing. Alishir Kurban: Data curation and resources.

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Correspondence to Geping Luo.

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He, H., Hamdi, R., Luo, G. et al. The summer cooling effect under the projected restoration of Aral Sea in Central Asia. Climatic Change 174, 13 (2022). https://doi.org/10.1007/s10584-022-03434-8

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