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A Multi-pass Land Data Assimilation Scheme (MLDAS) based on Noah-MP-Crop model
The leaf area index (LAI), soil moisture, and solar-induced chlorophyll fluorescence (SIF) observations are simultaneously assimilated into the Noah-MP-Crop model based on the MLDAS to predict sensible (H) and latent (LE) heat fluxes as well as gross primary productivity (GPP).
Authors: Tongren Xu (xutr@bnu.edu.cn) and Xinlei He (hxlbsd@mail.bnu.edu.cn)
The code demonstrates implementation of the MLDAS as proposed in paper "Xu, T., Chen, F., He, X., Barlage, M., Zhang, Z., Liu, S., & He, X. (2021). Improve the performance of the Noah-MP-Crop model by jointly assimilating soil moisture and vegetation phenology data. Journal of Advances in Modeling Earth Systems, 13, e2020MS002394. https://doi.org/10.1029/2020MS002394".