# A Simulation Study of Global Evapotranspiration Components Using the Community Land Model
## 1 Introduction  
Evapotranspiration (ET) refers to the loss of water from land surfaces into the atmosphere through the evaporation of soil (Es), the evaporation of intercepted water from the vegetation canopy (Ec), and vegetation transpiration (Et). Approximately 60% of surface precipitation returns to the atmosphere in the form of ET; this quantity can reach more than 90% in arid areas [1]. The energy formed by ET is called latent heat flux. Half of the solar radiation absorbed at the earth's surface is consumed through ET [2]. ET is an important component of the land surface energy balance and the water budget and plays a key role in weather and climate systems as well as the hydrological cycle [3]. ET is also a key parameter for studying climate change and land surface processes. Studies have shown that the intensity and duration of ET can strongly affect weather and land surface processes, carbon and nitrogen cycles in ecosystems, surface albedo, ground temperature, fluvial flow, and groundwater recharge [4; 5; 6]. ET plays an important role in the soil-vegetation-atmosphere system, and ET has always been one of the most difficult physical quantities to directly measure in hydrological cycles. It is veryimportant to understand the distribution of ET at different temporal and spatial scales to accurately estimate the effects of ET on weather, climate, and ecosystems for environmental assessments and the management of water resources. Currently, the research methods for ET mainly use remote sensing technology and land surface models. Remote sensing technology is primarily based on the surface energy balance model and a conventional method combined with an empirical formula (i.e., the Penman-Monteith formula) [7; 8; 9]. However, previous studies have shown that ET obtained through remote sensing creates more uncertainty than land surface models, in cases where the available time scale was also limited [10]. In the use of land surface models, [PERSON] et al. [11] used the CLM3.0 model to carry out a simulation study on the distribution proportion of the components of evapotranspiration at the global scale, and a series of improvements were made to enhance the simulation performance of the model. [PERSON] and [PERSON] [12] estimated global ET using the simulation data of 13 land surface models from the second Global Soil Wetness Project (GSWP-2). They found that the sensitivity of the models to atmospheric forcing data was weaker at the global scale, and the interannual variability in high latitude regions and the seasonal variability in tropical regions varied greatly between the models. [PERSON] and [PERSON] [13] reviewed observations and research for global land ET. [PERSON] et al. [10] used multiple land surface models (CLM4.0, Dynamic Land Model (DLM) and Variable Infiltration Capacity model (VIC)) to assess the temporal and spatial variability of ET in China from 1979 to 2012. Since the response time scales between the components of ET and the atmosphere are different (Ec is the fastest, followed by Es, with Et being slowest), the interaction between ET and the local climate is likely to be affected by the proportional distribution of ET from each of its components [11]. Therefore, it is necessary to study the components of evapotranspiration. The CLM is one of the most widely used land surface models in the world [14]. Some scholars have improved the parameterization schemes for some components of ET in CLM4.0 [15]. In particular, [PERSON] et al. [16] improved simulations for vegetation canopy radiation, photosynthesis processes and related parameters to improve the simulation of gross primary productivity (GPP) and latent heat fluxes (especially Et). [PERSON] et al. [17] used a new Newton-Raphson iteration scheme to address coupling photosynthesis rates and stomatal conductance and reduced the simulated bias of Et caused by iteration non-convergence. [PERSON] et al. [18] improved the hydraulic properties of soil in permafrost regions and improved the model's ability to simulate soil moisture.