In the land surface models predicting vegetation growth and decay, representation of the seasonality of land surface energy and mass fluxes largely depends on how to describe the vegetation dynamics. In this study, we developed a new parameterization scheme to characterize allocation of the assimilated carbon to plant parts, including leaves and fine roots. The amount of carbon allocation in this scheme depends on the climatological net primary production (NPP) of the plants. The newly developed scheme is implemented in the augmented Noah land surface model with multiple parameterization options (Noah‐MP) along with other biophysical processes related to variations in photosynthetic capacity. The scheme and the augmented biophysical processes are evaluated against tower measurements of vegetation from four forest sites in various regions—two for the deciduous broadleaf and two for the needleleaf evergreen forest. Results from the augmented Noah‐MP showed good agreement with the observations and demonstrated improvements in representing the seasonality of leaf area index (LAI), gross primary production (GPP), ecosystem respiration (ER), and latent heat flux. In particular, significant improvements are found in simulating amplitudes and phase shift timing in the LAI seasonal cycle, and the amount of GPP and ER in the growing season. Furthermore, the augmented Noah‐MP performed reasonably well in simulating the spatial distributions of LAI, GPP, and NPP in East Asia, consistent with the satellite observations.

This study investigated the climatic influence on the corn sowing date in the Midwestern United States by comparing the survey data of corn cultivation with meteorological records in nine states for the last 36 years (1979–2014). The results show that the year‐to‐year changes in the sowing date were significantly affected by springtime air temperature and precipitation in the nine states, although large state‐to‐state differences were found in the degree of sowing date–meteorology relationship. We determined that the 36‐year climatological warm period (CWP) with daily mean temperatures ≥10 °C plays an important role in the state‐to‐state differences. For the states with longer CWPs, the influence of air temperature (precipitation) was generally weaker (stronger). This observed counteractive relationship should be considered for crop modelling for more effective assessment of the impact of climate change on agriculture.

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