Articles | Volume 16, issue 6
https://doi.org/10.5194/esd-16-1971-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-16-1971-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Nov 2025
Research article |
| 03 Nov 2025
| 03 Nov 2025
Spatiotemporal variation of growth–stage specific concurrent climate extremes and their impacts on rice yield in southern China
Ran Sun
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction (ESPDRR), Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China
Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing 100875, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction (ESPDRR), Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China
Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing 100875, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Yiqing Liu
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction (ESPDRR), Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China
Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing 100875, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Weihang Liu
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction (ESPDRR), Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China
Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing 100875, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Shuo Chen
State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction (ESPDRR), Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China
Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing 100875, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Related authors
Ran Sun, Tao Ye, Yiqing Liu, Weihang Liu, and Shuo Chen
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2024-8, https://doi.org/10.5194/esd-2024-8, 2024
Manuscript not accepted for further review
Short summary
Short summary
We found increasing trend of compound hot-dry events for single-rice but decreasing trend of compound chilling-rainy events for late-rice. We also found that the occurrence and duration of concurrent CEs were negatively correlated with local temperature-moisture coupling. Temperature was the dominant factor influencing the change of compound hot-dry events. While for the change in compound chilling-rainy events, the effect of temperature is only slightly larger than that of moisture.
Ning Zhan, Tao Ye, Mario Herrero, Jian Peng, Weihang Liu, and Heng Ma
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-263, https://doi.org/10.5194/essd-2025-263, 2025
Manuscript not accepted for further review
Short summary
Short summary
We separated grazing ruminant livestock (cattle, sheep, and goats) from those raised in non-grazing systems in China and mapped where they graze from 2000 to 2021. Using machine learning methods that combine multiple models, we produced accurate maps showing livestock distribution across seasons. This helps track seasonal changes in grazing and supports better land use, animal health, and climate-related planning.
Ning Zhan, Tao Ye, Mario Herrero, Jian Peng, Weihang Liu, and Heng Ma
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-534, https://doi.org/10.5194/essd-2024-534, 2024
Manuscript not accepted for further review
Short summary
Short summary
The CLRD-GLPS dataset, mapping China’s annual distribution of ruminant livestock in grazing systems from 2000 to 2021, includes key advancements: (1) segmentation of grazing ruminant livestock from total livestock, (2) categorizing grazing pastures into warm-season, cold-season, and year-round types, and (3) analyze and explain spatial-temporal patterns. These innovations improve understanding of livestock seasonal dynamics and provide data for effective livestock management and policy-making.
Ran Sun, Tao Ye, Yiqing Liu, Weihang Liu, and Shuo Chen
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2024-8, https://doi.org/10.5194/esd-2024-8, 2024
Manuscript not accepted for further review
Short summary
Short summary
We found increasing trend of compound hot-dry events for single-rice but decreasing trend of compound chilling-rainy events for late-rice. We also found that the occurrence and duration of concurrent CEs were negatively correlated with local temperature-moisture coupling. Temperature was the dominant factor influencing the change of compound hot-dry events. While for the change in compound chilling-rainy events, the effect of temperature is only slightly larger than that of moisture.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Ruoque Shen, Baihong Pan, Qiongyan Peng, Jie Dong, Xuebing Chen, Xi Zhang, Tao Ye, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 15, 3203–3222, https://doi.org/10.5194/essd-15-3203-2023, https://doi.org/10.5194/essd-15-3203-2023, 2023
Short summary
Short summary
Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. This study developed a new rice-mapping method and produced distribution maps of single-season rice in 21 provincial administrative regions of China from 2017 to 2022 at a 10 or 20 m resolution. The accuracy was examined using 108 195 survey samples and county-level statistical data, and we found that the distribution maps have good accuracy.
Cited articles
Amin, M. W., Aryan, S., Habibi, N., Kakar, K., and Zahid, T.: Elucidation of photosynthesis and yield performance of rice (Oryza sativa L.) under drought stress conditions, Plant Physiol. Rep., 27, 143–151, https://doi.org/10.1007/s40502-021-00613-0, 2022.
Arshad, M. S., Farooq, M., Asch, F., Krishna, J. S. V., Prasad, P. V. V., and Siddique, K. H. M.: Thermal stress impacts reproductive development and grain yield in rice, Plant Physiology and Biochemistry, 115, 57–72, https://doi.org/10.1016/j.plaphy.2017.03.011, 2017.
Barnaby, J. Y., Rohila, J. S., Henry, C. G., Sicher, R. C., Reddy, V. R., and McClung, A. M.: Physiological and Metabolic Responses of Rice to Reduced Soil Moisture: Relationship of Water Stress Tolerance and Grain Production, International Journal of Molecular Sciences, 20, 1846, https://doi.org/10.3390/ijms20081846, 2019.
Berg, A., Lintner, B. R., Findell, K., Seneviratne, S. I., van den Hurk, B., Ducharne, A., Chéruy, F., Hagemann, S., Lawrence, D. M., Malyshev, S., Meier, A., and Gentine, P.: Interannual Coupling between Summertime Surface Temperature and Precipitation over Land: Processes and Implications for Climate Change, Journal of Climate, 28, 1308–1328, https://doi.org/10.1175/JCLI-D-14-00324.1, 2015.
Bevacqua, E., Zappa, G., Lehner, F., and Zscheischler, J.: Precipitation trends determine future occurrences of compound hot–dry events, Nat. Clim. Chang., 12, 350–355, https://doi.org/10.1038/s41558-022-01309-5, 2022.
Cao, Y.-Y., Duan, H., Yang, L.-N., Wang, Z.-Q., Zhou, S.-C., and Yang, J.-C.: Effect of Heat Stress During Meiosis on Grain Yield of Rice Cultivars Differing in Heat Tolerance and Its Physiological Mechanism, Acta Agronomica Sinica, 34, 2134–2142, https://doi.org/10.1016/S1875-2780(09)60022-5, 2008.
Chen, H. and Wang, S.: Compound Dry and Wet Extremes Lead to an Increased Risk of Rice Yield Loss, Geophysical Research Letters, 50, e2023GL105817, https://doi.org/10.1029/2023GL105817, 2023.
Chen, J., Liu, Y., Zhou, W., Zhang, J., and Pan, T.: Effects of climate change and crop management on changes in rice phenology in China from 1981 to 2010, Journal of the Science of Food and Agriculture, 101, 6311–6319, https://doi.org/10.1002/jsfa.11300, 2021.
Chenu, K., Porter, J. R., Martre, P., Basso, B., Chapman, S. C., Ewert, F., Bindi, M., and Asseng, S.: Contribution of Crop Models to Adaptation in Wheat, Trends in Plant Science, 22, 472–490, https://doi.org/10.1016/j.tplants.2017.02.003, 2017.
Feng, S., Hao, Z., Wu, X., Zhang, X., and Hao, F.: A multi-index evaluation of changes in compound dry and hot events of global maize areas, Journal of Hydrology, 602, 126728, https://doi.org/10.1016/j.jhydrol.2021.126728, 2021.
Fu, J., Jian, Y., Wang, X., Li, L., Ciais, P., Zscheischler, J., Wang, Y., Tang, Y., Müller, C., Webber, H., Yang, B., Wu, Y., Wang, Q., Cui, X., Huang, W., Liu, Y., Zhao, P., Piao, S., and Zhou, F.: Extreme rainfall reduces one-twelfth of China's rice yield over the last two decades, Nat. Food, 4, 416–426, https://doi.org/10.1038/s43016-023-00753-6, 2023.
Fu, K., Yu, H., Zhang, Y., Zhu, D., Liu, H., and Wang, K.: Flash drought and heatwave compound events increased in strength and length from 1980 to 2022 in China, Weather and Climate Extremes, 46, 100720, https://doi.org/10.1016/j.wace.2024.100720, 2024.
Guo, C., Ren, J., Wang, D., Cui, J., Mu, J., Liu, W., and Cao, T.: Temporal and Spatial Characteristics of Rice Cold Damage in Jilin from 1961 to 2018, Chinese Agricultural Science Bulletin, 36, 109, https://doi.org/10.11924/j.issn.1000-6850.casb20191000766, 2020.
Hamed, R., Van Loon, A. F., Aerts, J., and Coumou, D.: Impacts of compound hot–dry extremes on US soybean yields, Earth Syst. Dynam., 12, 1371–1391, https://doi.org/10.5194/esd-12-1371-2021, 2021.
Hao, Z. and Singh, V. P.: Compound Events under Global Warming: A Dependence Perspective, Journal of Hydrologic Engineering, 25, 03120001, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001991, 2020.
Hao, Z., Chen, Y., Feng, S., Liao, Z., An, N., and Li, P.: The 2022 Sichuan-Chongqing spatio-temporally compound extremes: a bitter taste of novel hazards, Science Bulletin, 68, 1337–1339, https://doi.org/10.1016/j.scib.2023.05.034, 2023.
Haqiqi, I., Grogan, D. S., Hertel, T. W., and Schlenker, W.: Quantifying the impacts of compound extremes on agriculture, Hydrol. Earth Syst. Sci., 25, 551–564, https://doi.org/10.5194/hess-25-551-2021, 2021.
He, Y., Hu, X., Xu, W., Fang, J., and Shi, P.: Increased probability and severity of compound dry and hot growing seasons over world's major croplands, Science of The Total Environment, 824, 153885, https://doi.org/10.1016/j.scitotenv.2022.153885, 2022.
Holly Wang, H. and Zhang, H.: On the Possibility of a Private Crop Insurance Market: A Spatial Statistics Approach, J. Risk Insur., 70, 111–124, https://doi.org/10.1111/1539-6975.00051, 2003.
IPCC: IPCC, 2021: Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896, 2021.
IPCC: IPCC, 2022: Climate Change 2022: Impacts, Adaptation, and Vulnerability, Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New York, NY, USA, 3056 pp., https://doi.org/10.1017/9781009325844, 2022.
Jiang, W., Lee, J., Chu, S.-H., Ham, T.-H., Woo, M.-O., Cho, Y.-I., Chin, J.-H., Han, L., Xuan, Y., Yuan, D., Xu, F., Dai, L., Yea, J.-D., and Koh, H.-J.: Genotype × environment interactions for chilling tolerance of rice recombinant inbred lines under different low temperature environments, Field Crops Research, 117, 226–236, https://doi.org/10.1016/j.fcr.2010.03.007, 2010.
Jiang, Y., Carrijo, D., Huang, S., Chen, J., Balaine, N., Zhang, W., van Groenigen, K. J., and Linquist, B.: Water management to mitigate the global warming potential of rice systems: A global meta-analysis, Field Crops Research, 234, 47–54, https://doi.org/10.1016/j.fcr.2019.02.010, 2019.
Kern, A., Barcza, Z., Marjanović, H., Árendás, T., Fodor, N., Bónis, P., Bognár, P., and Lichtenberger, J.: Statistical modelling of crop yield in Central Europe using climate data and remote sensing vegetation indices, Agricultural and Forest Meteorology, 260–261, 300–320, https://doi.org/10.1016/j.agrformet.2018.06.009, 2018.
Lesk, C. and Anderson, W.: Decadal variability modulates trends in concurrent heat and drought over global croplands, Environ. Res. Lett., 16, 055024, https://doi.org/10.1088/1748-9326/abeb35, 2021.
Lesk, C., Coffel, E., Winter, J., Ray, D., Zscheischler, J., Seneviratne, S. I., and Horton, R.: Stronger temperature–moisture couplings exacerbate the impact of climate warming on global crop yields, Nat. Food, 2, 683–691, https://doi.org/10.1038/s43016-021-00341-6, 2021.
Li, H. W., Li, Y. P., Huang, G. H., and Sun, J.: Quantifying effects of compound dry-hot extremes on vegetation in Xinjiang (China) using a vine-copula conditional probability model, Agricultural and Forest Meteorology, 311, 108658, https://doi.org/10.1016/j.agrformet.2021.108658, 2021.
Li, T., Li, S., and Wang, J.: Effects of water deficiency stress on transport and distribution of 14C-assimilates in micropropagated apple plants, Journal of China Agricultural University, 44–48, 2005.
Li, Y. and Tao, F.: Rice yield response to climate variability diverges strongly among climate zones across China and is sensitive to trait variation, Field Crops Research, 301, 109034, https://doi.org/10.1016/j.fcr.2023.109034, 2023.
Li, Z., Liu, W., Ye, T., Chen, S., and Shan, H.: Observed and CMIP6 simulated occurrence and intensity of compound agroclimatic extremes over maize harvested areas in China, Weather and Climate Extremes, 38, 100503, https://doi.org/10.1016/j.wace.2022.100503, 2022.
Liu, X., Zhang, Z., Shuai, J., Wang, P., Shi, W., Tao, F., and Chen, Y.: Impact of chilling injury and global warming on rice yield in Heilongjiang Province, J. Geogr. Sci., 23, 85–97, https://doi.org/10.1007/s11442-013-0995-9, 2013.
Liu, X., He, B., Guo, L., Huang, L., and Chen, D.: Similarities and Differences in the Mechanisms Causing the European Summer Heatwaves in 2003, 2010, and 2018, Earth's Future, 8, e2019EF001386, https://doi.org/10.1029/2019EF001386, 2020.
Liu, Y., Liu, W., Li, Y., Ye, T., Chen, S., Li, Z., and Sun, R.: Concurrent Precipitation Extremes Modulate the Response of Rice Transplanting Date to Preseason Temperature Extremes in China, Earth's Future, 11, e2022EF002888, https://doi.org/10.1029/2022EF002888, 2023.
Lobell, D. B. and Gourdji, S. M.: The Influence of Climate Change on Global Crop Productivity, Plant Physiology, 160, 1686–1697, https://doi.org/10.1104/pp.112.208298, 2012.
Lü, X. and Zhou, G.: A Review on Main Meteorological Disaster of Double-cropping Rice in China, Journal of Applied Meteorological Science, 29, 385–395, https://doi.org/10.11898/1001-7313.20180401, 2018.
Lu, Y., Hu, H., Li, C., and Tian, F.: Increasing compound events of extreme hot and dry days during growing seasons of wheat and maize in China, Sci. Rep., 8, 16700, https://doi.org/10.1038/s41598-018-34215-y, 2018.
Luan, X., Bommarco, R., Scaini, A., and Vico, G.: Combined heat and drought suppress rainfed maize and soybean yields and modify irrigation benefits in the USA, Environ. Res. Lett., 16, 064023, https://doi.org/10.1088/1748-9326/abfc76, 2021.
Luo, K., Zeng, Y., Hu, Q., Chen, L., Yi, Y., Sui, F., and Li, X.: Effects of Weak Light Stress at Different Stages on Sink-source Characteristics and Protective Enzyme Activities in Leaf of Late Rice Varieties with Different Tolerance, Chinese Journal of Rice Science, 32, 581, https://doi.org/10.16819/j.1001-7216.2018.7146, 2018.
Luo, Y., Zhang, Z., Chen, Y., Li, Z., and Tao, F.: ChinaCropPhen1km: a high-resolution crop phenological dataset for three staple crops in China during 2000–2015 based on leaf area index (LAI) products, Earth Syst. Sci. Data, 12, 197–214, https://doi.org/10.5194/essd-12-197-2020, 2020.
Miao, Y. and Wang, A.: A daily 0.25°×0.25° hydrologically based land surface flux dataset for conterminous China, 1961–2017, Journal of Hydrology, 590, 125413, https://doi.org/10.1016/j.jhydrol.2020.125413, 2020.
Miralles, D. G., Gentine, P., Seneviratne, S. I., and Teuling, A. J.: Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges, Annals of the New York Academy of Sciences, 1436, 19–35, https://doi.org/10.1111/nyas.13912, 2019.
Pan, B., Zheng, Y., Shen, R., Ye, T., Zhao, W., Dong, J., Ma, H., and Yuan, W.: High Resolution Distribution Dataset of Double-Season Paddy Rice in China, Remote Sensing, 13, 4609, https://doi.org/10.3390/rs13224609, 2021.
Proctor, J.: Extreme rainfall reduces rice yields in China, Nat. Food, 4, 360–361, https://doi.org/10.1038/s43016-023-00757-2, 2023.
Ribeiro, A. F. S., Russo, A., Gouveia, C. M., Páscoa, P., and Zscheischler, J.: Risk of crop failure due to compound dry and hot extremes estimated with nested copulas, Biogeosciences, 17, 4815–4830, https://doi.org/10.5194/bg-17-4815-2020, 2020.
Rötter, R. P., Appiah, M., Fichtler, E., Kersebaum, K. C., Trnka, M., and Hoffmann, M. P.: Linking modelling and experimentation to better capture crop impacts of agroclimatic extremes – A review, Field Crops Research, 221, 142–156, https://doi.org/10.1016/j.fcr.2018.02.023, 2018.
Sadegh, M., Moftakhari, H., Gupta, H. V., Ragno, E., Mazdiyasni, O., Sanders, B., Matthew, R., and AghaKouchak, A.: Multihazard Scenarios for Analysis of Compound Extreme Events, Geophysical Research Letters, 45, 5470–5480, https://doi.org/10.1029/2018GL077317, 2018.
Salvadori, G., Durante, F., De Michele, C., Bernardi, M., and Petrella, L.: A multivariate copula-based framework for dealing with hazard scenarios and failure probabilities, Water Resources Research, 52, 3701–3721, https://doi.org/10.1002/2015WR017225, 2016.
Sehgal, A., Sita, K., Siddique, K. H. M., Kumar, R., Bhogireddy, S., Varshney, R. K., HanumanthaRao, B., Nair, R. M., Prasad, P. V. V., and Nayyar, H.: Drought or/and Heat-Stress Effects on Seed Filling in Food Crops: Impacts on Functional Biochemistry, Seed Yields, and Nutritional Quality, Front. Plant Sci., 9, 1705, https://doi.org/10.3389/fpls.2018.01705, 2018.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture–climate interactions in a changing climate: A review, Earth-Science Reviews, 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Shen, R., Pan, B., Peng, Q., Dong, J., Chen, X., Zhang, X., Ye, T., Huang, J., and Yuan, W.: High-resolution distribution maps of single-season rice in China from 2017 to 2022, Earth Syst. Sci. Data, 15, 3203–3222, https://doi.org/10.5194/essd-15-3203-2023, 2023.
Suh, J. P., Jeung, J. U., Lee, J. I., Choi, Y. H., Yea, J. D., Virk, P. S., Mackill, D. J., and Jena, K. K.: Identification and analysis of QTLs controlling cold tolerance at the reproductive stage and validation of effective QTLs in cold-tolerant genotypes of rice (Oryza sativa L.), Theor. Appl. Genet., 120, 985–995, https://doi.org/10.1007/s00122-009-1226-8, 2010.
Tavakol, A., Rahmani, V., and Harrington Jr., J.: Probability of compound climate extremes in a changing climate: A copula-based study of hot, dry, and windy events in the central United States, Environ. Res. Lett., 15, 104058, https://doi.org/10.1088/1748-9326/abb1ef, 2020.
Tenorio, F. A., Ye, C., Redona, E., Sierra, S., Laza, M., and Argayoso, M.: Screening rice genetic resource for heat tolerance, SABRAO Journal of Breeding and Genetics, 45, 341–351, 2013.
Tootoonchi, F., Sadegh, M., Haerter, J. O., Räty, O., Grabs, T., and Teutschbein, C.: Copulas for hydroclimatic analysis: A practice-oriented overview, WIREs Water, 9, e1579, https://doi.org/10.1002/wat2.1579, 2022.
Trnka, M., Rötter, R. P., Ruiz-Ramos, M., Kersebaum, K. C., Olesen, J. E., Žalud, Z., and Semenov, M. A.: Adverse weather conditions for European wheat production will become more frequent with climate change, Nature Clim. Change, 4, 637–643, https://doi.org/10.1038/nclimate2242, 2014.
Trotsiuk, V., Hartig, F., Cailleret, M., Babst, F., Forrester, D. I., Baltensweiler, A., Buchmann, N., Bugmann, H., Gessler, A., Gharun, M., Minunno, F., Rigling, A., Rohner, B., Stillhard, J., Thürig, E., Waldner, P., Ferretti, M., Eugster, W., and Schaub, M.: Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion, Global Change Biology, 26, 2463–2476, https://doi.org/10.1111/gcb.15011, 2020.
Urban, O., Hlaváèová, M., Klem, K., Novotná, K., Rapantová, B., Smutná, P., Horáková, V., Hlavinka, P., Škarpa, P., and Trnka, M.: Combined effects of drought and high temperature on photosynthetic characteristics in four winter wheat genotypes, Field Crops Research, 223, 137–149, https://doi.org/10.1016/j.fcr.2018.02.029, 2018.
Wang, L., Liao, S., Huang, S., Ming, B., Meng, Q., and Wang, P.: Increasing concurrent drought and heat during the summer maize season in Huang–Huai–Hai Plain, China, Intl. Journal of Climatology, 38, 3177–3190, https://doi.org/10.1002/joc.5492, 2018.
Wu, H., Zhang, J., Zhang, Z., Han, J., Cao, J., Zhang, L., Luo, Y., Mei, Q., Xu, J., and Tao, F.: AsiaRiceYield4km: seasonal rice yield in Asia from 1995 to 2015, Earth Syst. Sci. Data, 15, 791–808, https://doi.org/10.5194/essd-15-791-2023, 2023.
Wu, J. and Gao, X.: A gridded daily observation dataset over China region and comparison with the other datasets, Chinese Journal of Geophysics, 56, 1102–1111, https://doi.org/10.6038/cjg20130406, 2013.
Xie, Y., Huang, S., Tian, J., Wang, Y., and Ye, Q.: Spatial-temporal characteristics of thermal resources and its influence on the growth of double cropping rice in the middle and lower reaches of the Yangtze River, China, Chinese Journal of Applied Ecology, 27, 2950, https://doi.org/10.13287/j.1001-9332.201609.013, 2016.
Xiong, W., Feng, L., Ju, H., and Yang, D.: Possible Impacts of High Temperatures on China's Rice Yield under Climate Change, Advances in Earth Science, 31, 515, https://doi.org/10.11867/j.issn.1001-8166.2016.05.0515., 2016.
Yan, R., Li, L., Gao, J., and Huang, J.: Exploring the Influence of Seasonal Cropland Abandonment on Evapotranspiration and Water Resources in the Humid Lowland Region, Southern China, Water Resour. Res., 58, https://doi.org/10.1029/2021WR031888, 2022.
Ye, T., Shi, P., Wang, J., Liu, L., Fan, Y., and Hu, J.: China's drought disaster risk management: Perspective of severe droughts in 2009–2010, Int. J. Disaster Risk Sci., 3, 84–97, https://doi.org/10.1007/s13753-012-0009-z, 2012.
Ye, T., Nie, J., Wang, J., Shi, P., and Wang, Z.: Performance of detrending models of crop yield risk assessment: evaluation on real and hypothetical yield data, Stoch. Environ. Res. Risk Assess., 29, 109–117, https://doi.org/10.1007/s00477-014-0871-x, 2015.
Yu, R., Dong, S., Han, Z., and Li, W.: Increased exposure of rice to compound drought and hot extreme events during its growing seasons in China, Ecological Indicators, 167, 112735, https://doi.org/10.1016/j.ecolind.2024.112735, 2024.
Zhang, L., Guo, A., He, L., Hou, Y., Zhao, X., Qian, Y., and Cai, Z.: Variation Characteristics of Chilling Dew Wind for Double-Season Late Rice Across Southern China in 2020, Meteorological Monthly, 47, 1537–1545, https://doi.org/10.7519/j.issn.1000-0526.2021.12.009, 2021.
Zhang, L., Zhang, Z., Tao, F., Luo, Y., Zhang, J., and Cao, J.: Adapting to climate change precisely through cultivars renewal for rice production across China: When, where, and what cultivars will be required?, Agricultural and Forest Meteorology, 316, 108856, https://doi.org/10.1016/j.agrformet.2022.108856, 2022a.
Zhang, Q., She, D., Zhang, L., Wang, G., Chen, J., and Hao, Z.: High Sensitivity of Compound Drought and Heatwave Events to Global Warming in the Future, Earths Future, 10, https://doi.org/10.1029/2022EF002833, 2022b.
Zhang, Y., Hao, Z., Feng, S., Zhang, X., and Hao, F.: Changes and driving factors of compound agricultural droughts and hot events in eastern China, Agric. Water Manag., 263, https://doi.org/10.1016/j.agwat.2022.107485, 2022c.
Zhang, Z., Wang, P., Chen, Y., Song, X., Wei, X., and Shi, P.: Global warming over 1960–2009 did increase heat stress and reduce cold stress in the major rice-planting areas across China, European Journal of Agronomy, 59, 49–56, https://doi.org/10.1016/j.eja.2014.05.008, 2014.
Zhao, H., Fu, Y. H., Wang, X., Zhao, C., Zeng, Z., and Piao, S.: Timing of rice maturity in China is affected more by transplanting date than by climate change, Agricultural and Forest Meteorology, 216, 215–220, https://doi.org/10.1016/j.agrformet.2015.11.001, 2016.
Zhu, Y. and Yang, S.: Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5, Advances in Climate Change Research, 11, 239–251, https://doi.org/10.1016/j.accre.2020.08.001, 2020.
Zhu, Y., Li, Y., Zhou, X., Feng, W., Gao, G., Li, M., and Zheng, G.: Causes of the severe drought in Southwest China during the summer of 2022, Atmospheric Research, 303, 107320, https://doi.org/10.1016/j.atmosres.2024.107320, 2024.
Zscheischler, J. and Seneviratne, S. I.: Dependence of drivers affects risks associated with compound events, Sci. Adv., 3, e1700263, https://doi.org/10.1126/sciadv.1700263, 2017.
Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R. M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M. D., Maraun, D., Ramos, A. M., Ridder, N. N., Thiery, W., and Vignotto, E.: A typology of compound weather and climate events, Nat. Rev. Earth Environ., 1, 333–347, https://doi.org/10.1038/s43017-020-0060-z, 2020.
Short summary
Climate change is intensifying extreme weather threats to rice. Using data from 1981 to 2018, we found that hot-dry events are rising over time with different patterns across regions, while cold-rain events also threaten crops. Heat was the main driver of hot-dry events, and cold and rain together drove cold-rain events. Both reduced harvests, especially during flowering and grain filling stage. Our findings show that growth stage and location matter for protecting rice in a changing climate.
Climate change is intensifying extreme weather threats to rice. Using data from 1981 to 2018, we...
Altmetrics
Final-revised paper
Preprint