Modeling crop development and atmosphere interactions under changing climate conditions using the Noah-MP Model: A case study of Mediterranean rainfed barley

Land Surface Models (LSMs) are a fundamental component of climate modeling as they simulate the energy and water fluxes between terrestrial and atmospheric systems. Agriculture is a sector strongly affected by changing climate conditions and the increasing occurrence of extreme weather patterns. For these reasons, we use the state-of-the-art Noah LSM with multi-parameterizations (Noah-MP), enhanced with a crop module (Noah-MP-crop) that incorporates crop growth and its interactions with the atmosphere. The main goal is to use Noah-MP-crop and downscaled climate projections to generate seasonal and decadal predictions of the climate impacts of drought and heat stress on the growth and development of a typical Mediterranean annual rainfed crop. The specific objectives of the study are: (1) to perform a sensitivity analysis to identify the most influential Noah-MP-crop model parameters affecting the model outputs of leaf area index (LAI), total biomass, and the exchange of water and carbon with the atmosphere, and (2) to calibrate the model using field-scale observations of these variables. Our case study area is an agricultural field in the central plain on the island of Cyprus, where rainfed barley is cultivated. Observations used in our study include eddy covariance fluxes of water and carbon, meteorological variables, soil moisture at depths of 10, 30, and 50 cm, LAI and phenology, soil properties and agricultural practices. These observations span three barley growing seasons, covering the period from 2020 to 2022 and 2023 to 2024.