Articles | Volume 12, issue 4
© Author(s) 2021. This work is distributed underthe Creative Commons Attribution 4.0 License.
Impacts of compound hot–dry extremes on US soybean yields
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19 citations as recorded by crossref.
- Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts Z. Hao et al. 10.1016/j.earscirev.2022.104241
- Large-Scale Climate Factors of Compound Agrometeorological Disasters of Spring Maize in Liaoning, Northeast China S. Zhao et al. 10.3390/atmos14091414
- Droughts are coming on faster D. Walker & A. Van Loon 10.1126/science.adh3097
- Increased probability of hot and dry weather extremes during the growing season threatens global crop yields M. Heino et al. 10.1038/s41598-023-29378-2
- Land–atmosphere feedbacks contribute to crop failure in global rainfed breadbaskets H. Li et al. 10.1038/s41612-023-00375-6
- Genetic progress battles climate variability: drivers of soybean yield gains in China from 2006 to 2020 L. Zhang et al. 10.1007/s13593-023-00905-9
- Developing a novel framework to re-examine half a century of compound drought and heatwave events in mainland China L. Zhao et al. 10.1016/j.scitotenv.2023.162366
- Interaction between dry and hot extremes at a global scale using a cascade modeling framework S. Mukherjee et al. 10.1038/s41467-022-35748-7
- Identifying the Impact of Regional Meteorological Parameters on US Crop Yield at Various Spatial Scales Using Remote Sensing Data C. Yoo et al. 10.3390/rs14153508
- Persistent La Niñas drive joint soybean harvest failures in North and South America R. Hamed et al. 10.5194/esd-14-255-2023
- Compound heat and moisture extreme impacts on global crop yields under climate change C. Lesk et al. 10.1038/s43017-022-00368-8
- Century‐long variations of growing‐season compound dry–hot extremes and their links with large‐scale climate patterns in China S. Guo et al. 10.1002/joc.8275
- Climate impact storylines for assessing socio-economic responses to remote events B. van den Hurk et al. 10.1016/j.crm.2023.100500
- Soybean response under climatic scenarios with changed mean and variability under rainfed and irrigated conditions in major soybean-growing states of the USA A. Timilsina et al. 10.1017/S0021859623000011
- Coupling Process-Based Crop Model and Extreme Climate Indicators with Machine Learning Can Improve the Predictions and Reduce Uncertainties of Global Soybean Yields Q. Sun et al. 10.3390/agriculture12111791
- Coordinated evaporative demand and precipitation maximize rainfed maize and soybean crop yields in the USA X. Luan et al. 10.1002/eco.2500
- Increase of Simultaneous Soybean Failures Due To Climate Change H. Goulart et al. 10.1029/2022EF003106
- Yield variability of soybean varieties in the Non-Chernozem zone N. Zarenkova et al. 10.1051/bioconf/20236605006
- Substantial increase of compound droughts and heatwaves in wheat growing seasons worldwide Y. He et al. 10.1002/joc.7518
Latest update: 29 Nov 2023