Ombadi, M., Risser, M. D., Rhoades, A. M. & Varadharajan, C. A warming-induced reduction in snow fraction amplifies rainfall extremes. Nature 619, 305–310 (2023).
Qin, Y. et al. Agricultural risks from changing snowmelt. Nat. Clim. Change 10, 459–465 (2020).
Qin, Y. et al. Snowmelt risk telecouplings for irrigated agriculture. Nat. Clim. Change 12, 1007–1015 (2022).
Zhu, P. et al. The critical benefits of snowpack insulation and snowmelt for winter wheat productivity. Nat. Clim. Change 12, 485–490 (2022).
Trnka, M. et al. Adverse weather conditions for European wheat production will become more frequent with climate change. Nat. Clim. Change 4, 637–643 (2014).
Huning, L. S. & AghaKouchak, A. Global snow drought hot spots and characteristics. Proc. Natl Acad. Sci. USA 117, 19753–19759 (2020).
Gottlieb, A. R. & Mankin, J. S. Observing, measuring, and assessing the consequences of snow drought. Bull. Am. Meteorol. Soc. 103, E1041–E1060 (2022).
Howitt, R. E., Medellín-Azuara, J., Macewan, D., Lund, J. R. & Sumner, D. A. Economic Impact of the 2015 Drought on Farm Revenue and Employment (University of California Giannini Foundation of Agricultural Economics, 2015).
Seager, R. et al. Mechanisms of a meteorological drought onset: summer 2020 to spring 2021 in southwestern North America. J. Clim. 35, 7367–7385 (2022).
Farmers grappling with Afghanistan drought urgently need seed and animal feed support. FAO https://www.fao.org/newsroom/detail/Farmers-grappling-with-Afghanistan-drought-urgently-need-seed-and-animal-feed-support/en (2018).
Colombo, N. et al. Unprecedented snow-drought conditions in the Italian Alps during the early 2020s. Environ. Res. Lett. 18, 074014 (2023).
AghaKouchak, A. et al. Toward impact-based monitoring of drought and its cascading hazards. Nat. Rev. Earth Environ. 4, 582–595 (2023).
Kraaijenbrink, P. D. A., Stigter, E. E., Yao, T. & Immerzeel, W. W. Climate change decisive for Asia’s snow meltwater supply. Nat. Clim. Change 11, 591–597 (2021).
Lutz, A. F. et al. South Asian agriculture increasingly dependent on meltwater and groundwater. Nat Clim. Change 12, 566–573 (2022).
Musselman, K. N., Addor, N., Vano, J. A. & Molotch, N. P. Winter melt trends portend widespread declines in snow water resources. Nat. Clim. Change 11, 418–424 (2021).
Li, X. & Wang, S. Recent increase in the occurrence of snow droughts followed by extreme heatwaves in a warmer world. Geophys. Res. Lett. 49, 1–10 (2022).
Proctor, J., Rigden, A., Chan, D. & Huybers, P. More accurate specification of water supply shows its importance for global crop production. Nat. Food 3, 753–763 (2022).
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).
Rodell, M. et al. The global land data assimilation system. Bull. Am. Meteorol. Soc. 85, 381–394 (2004).
Ben-Ari, T. et al. Causes and implications of the unforeseen 2016 extreme yield loss in the breadbasket of France. Nat. Commun. 9, 1627 (2018).
Sugihara, G. et al. Detecting causality in complex ecosystems. Science 338, 496–500 (2012).
Granger, C. W. J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424–438 (1969).
Lundberg, S. M. et al. From local explanations to global understanding with explainable AI for trees. Nat. Mach. Intell. 2, 56–67 (2020).
Chen, T. & Guestrin, C. Xgboost: a scalable tree boosting system. In Proc. 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 785–794 (Association for Computing Machinery, 2016).
Bönecke, E. et al. Decoupling of impact factors reveals the response of German winter wheat yields to climatic changes. Glob. Change Biol. 26, 3601–3626 (2020).
Wang, R. et al. Winter dormant wheat will benefit from mean temperature increase of 2 °C when well-watered and fertilized in the main producing regions of China. Glob. Change Biol. 31, e70324 (2025).
Vico, G., Hurry, V. & Weih, M. Snowed in for survival: quantifying the risk of winter damage to overwintering field crops in northern temperate latitudes. Agric. For. Meteorol. 197, 65–75 (2014).
Vogel, F. A. & Bange, G. A. Understanding USDA Crop Forecasts (USDA, 1999).
Edwards, A. C., Scalenghe, R. & Freppaz, M. Changes in the seasonal snow cover of alpine regions and its effect on soil processes: a review. Quat. Int. 162, 172–181 (2007).
Yakutina, O. P., Nechaeva, T. V. & Smirnova, N. V. Consequences of snowmelt erosion: soil fertility, productivity and quality of wheat on Greyzemic Phaeozem in the south of West Siberia. Agric. Ecosyst. Environ. 200, 88–93 (2015).
Siirila-Woodburn, E. R. et al. A low-to-no snow future and its impacts on water resources in the western United States. Nat. Rev. Earth Environ. 2, 800–819 (2021).
Sloat, L. L. et al. Climate adaptation by crop migration. Nat. Commun. 11, 1243 (2020).
Wang, Y., Shi, W. & Wen, T. Prediction of winter wheat yield and dry matter in North China Plain using machine learning algorithms for optimal water and nitrogen application. Agric. Water. Manag. 277, 108140 (2023).
Zhang, T. et al. Climate change may outpace current wheat breeding yield improvements in North America. Nat. Commun. 13, 5591 (2022).
Lv, L. et al. Winter wheat grain yield and its components in the North China Plain: irrigation management, cultivation, and climate. Chil. J. Agric. Res. 73, 233–242 (2013).
Iizumi, T. & Sakai, T. The global dataset of historical yields for major crops 1981–2016. Sci. Data 7, 1–7 (2020).
Chen, H. & Wang, S. Compound dry and wet extremes lead to an increased risk of rice yield loss. Geophys. Res. Lett. https://doi.org/10.1029/2023GL105817 (2023).
Quick Stats tools. USDA https://www.nass.usda.gov/Quick_Stats/ (2025).
FranceAgriMar https://cereobs.franceagrimer.fr/cereobs-sp/#/ (2025).
Lobert, F. et al. A deep learning approach for deriving winter wheat phenology from optical and SAR time series at field level. Remote Sens. Environ. 298, 113800 (2023).
Zhang, Q. J., Wu, D. L. & Gao, J. Variation of winter wheat phenology dataset in Huang Huai Hai Plain of China from 1981 to 2021. Sci. Data 12, 1203 (2025).
Liao, C. et al. Near real-time detection and forecasting of within-field phenology of winter wheat and corn using Sentinel-2 time-series data. ISPRS J. Photogramm. Remote Sens. 196, 105–119 (2023).
Yu, Q. et al. A cultivated planet in 2010–part 2: the global gridded agricultural-production maps. Earth Syst. Sci. Data 12, 3545–3572 (2020).
Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 490, 254–257 (2012).
Martens, B. et al. GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev. 10, 1903–1925 (2017).
Qing, Y. et al. Accelerated soil drying linked to increasing evaporative demand in wet regions. npj Clim. Atmos. Sci. 6, 205 (2023).
Tack, J., Barkley, A. & Nalley, L. L. Effect of warming temperatures on US wheat yields. Proc. Natl Acad. Sci. USA 112, 6931–6936 (2015).
Troy, T. J., Kipgen, C. & Pal, I. The impact of climate extremes and irrigation on US crop yields. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/10/5/054013 (2015).
Sacks, W. J., Deryng, D., Foley, J. A. & Ramankutty, N. Crop planting dates: an analysis of global patterns. Glob. Ecol. Biogeogr. 19, 607–620 (2010).
Ge, X. et al. Effects of canopy composition on snow depth and below-the-snow temperature regimes in the temperate secondary forest ecosystem, Northeast China. Agric. For. Meteorol. 313, 108744 (2022).
Zhao, W. et al. Spatial and temporal variability in snow density across the Northern Hemisphere. Catena 232, 107445 (2023).
Li, W. et al. Widespread increasing vegetation sensitivity to soil moisture. Nat. Commun. 13, 3959 (2022).
Huijiao, C. Winter wheat yield sensitivity to snow drought is increasing across the Northern Hemisphere. Zenodo https://doi.org/10.5281/zenodo.17861863 (2025).
