This study investigates the complex terrestrial ecosystems response to extreme weather events using three different land surface models. Previous studies have showed that extreme weather events can have serious and damaging impacts on human and natural systems and they are most evident on regional and local scales. Under climate change, extreme weather events are likely to increase in both magnitude and frequency, making realistic simulation of ecosystems response to extreme events more essential than ever in assessing the potential damaging impacts. Three different land surface models are used to explore the impacts of extreme events on regional to continental ecosystem responses. The Terrestrial Ecosystem Model (TEM) is a process-based ecosystem model that uses spatially referenced information on climate, elevation, soils, vegetation and water availability to make monthly estimates of vegetation and soil carbon and nitrogen fluxes and pool sizes. The Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) is a multi-layered land surface model based on eddy-covariance theory to calculate the biosphere-atmosphere exchanges of carbon dioxide, water, and momentums. The Community Land Model (CLM) is a community-based model widely used in global-scale land data assimilation research. The study focuses on the complex interactions and feedbacks between the terrestrial ecosystem and the atmosphere such as water cycle, carbon and nitrogen budgets, and environmental conditions. The model simulations and performances are evaluated using the biogeophysical and micrometeorological observation data from the AmeriFlux sites across the continental US. This study compares and evaluates the ability of different models and their key components to capture terrestrial response to extreme weather events.