Improving crop dynamics in the CLM5 land surface model

Abstract

The land surface is an essential component of the Earth's System that interacts with the atmosphere via mass, momentum, and energy exchange. Croplands are one of the most common types of land use. Therefore, a comprehensive understanding of land-atmosphere interactions requires understanding the biogeochemical and biogeophysical processes and interactions in agroecosystems.Earth System Models (ESMs) can simulate the complex physical, chemical, and biological processes within and between the earth's land, atmosphere, ocean, and other spheres. Croplands have not received adequate attention in ESMs and were previously represented as grasslands. Land components in ESMs, such as the Community Land Model version 5 (CLM5) in the Community Earth System Model (CESM), have recently begun to include specific crops. The addition of crops to land models improved the simulation of energy, carbon, and water fluxes from land. CLM5 can represent a wide range of crops all over the world. However, there are significant errors in crop representation for the Indian region, including cropping areas, cropping season, irrigation, and crop characteristics. CLM5's estimated annual yield of wheat and rice has significant biases compared to UN-FAO estimates due to differences in growing seasons. Furthermore, observational data on the phenology of spring wheat and rice are scarce in the Indian region. As a result, crop growth model simulations in the Indian region suffer from poor calibration and validation.India is the world's second-largest producer of wheat and rice. Rice and wheat croplands cover more than 70 million ha combined. The current study aims to improve CLM5's representation of spring wheat and rice crops. This is accomplished by incorporating a crop planting window based on observations, wheat and rice cultivated area and irrigated cropland maps from district-level data. To further improve the crop models, we digitized historical crop phenology data and used them for model calibration and validation.Correcting the spring wheat and rice growing seasons in CLM5 over India has greatly improved crop phenology, yield, and irrigation pattern. As a result, the energy, carbon, and water fluxes are better estimated than the default CLM5 model. If the improved CLM5 is incorporated into the CESM, this can also improve the simulation of atmospheric phenomena.