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Yaling Liu, Dongdong Chen, Soukayna Mouatadid, Xiaoliang Lu, Min Chen, Yu Cheng, Zhenghui Xie, Binghao Jia, Huan Wu, and Pierre Gentine

research topics such as water and carbon fluxes in agroecosystems, and land–atmosphere interactions. Second, we shed light on the effects of different cropping patterns on SM and seek alternative cropping patterns that may alleviate SM decline. This exploration will prompt decision making in ameliorating soil water stress and inform adaption plans in an increasingly water-scarce future. 2. Methods a. Neural network The neural network used in this work is a deep feed forward NN, which consists of

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Sid-Ahmed Boukabara, Vladimir Krasnopolsky, Jebb Q. Stewart, Eric S. Maddy, Narges Shahroudi, and Ross N. Hoffman

incorporate components with longer predictability times than the atmosphere—the cryosphere, the land surface, the ocean, the biosphere, the hydrosphere, etc., and the couplings between these components. Note that the need to integrate multiple types of environmental parameters into consolidated, data fused/blended observation products exists at both ends of the forecast time scale—both for nowcasts and for future coupled climate DA systems. In summary, new approaches will be needed to take full advantage

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