## 1 Introduction  
Numerical models and, in particular, models including soil-vegetation-atmosphere transfer schemes (hereafter referenced to as \"land surface models\", or LSMs), can be considered useful tools to estimate microclimatic conditions in specific sites. These kinds of models can simulate hydro-energetic and gas exchange processes in the layer including atmosphere, soil, and vegetation. Recent studiesdemonstrate that the accuracy of land surface processes diagnosed by land surface models can be further improved by considering specific aspects of vegetation growth, such as vegetation structure parameterizations [1] and LAI (Leaf Area Index) seasonality [2]. Environmental conditions, especially microclimatic conditions, strongly influence agricultural production. For this reason, there is an increasing interest in assessing plant responses to environmental variables, especially in periods characterized by climatic changes, as the actual one [3]. Grapevine is a robust plant, but it is extremely sensitive to environmental conditions, and the characterization of its microphysics variability, in functions of field-dependent factors and external weather conditions, is useful to understand its growth process [4]. The interest in grapevine is increasing, which is also due to the great economic weight of its product the wine [5]. This is particularly true for the areas in which famous wines are produced, such as the Italian region Piemonte (Piedmont), with its Barolo and Barbaresco (among others) world-renowned wines. For this reason, many studies were conducted to evidence the relationships between physical variables (temperature, radiation, soil water content) and plant development [6; 7; 8; 9; 10]. It is also evident that, conversely, management practices can influence the microclimate within a vineyard [11; 12]. For this reason, the employment of an instrument, such as a LSM, can drive grower decisions for decreasing the environmental impact of vineyard management [13; 14]. Vineyards can thus be seen as a complex system where many variables interact between themselves to determine the plant growth, and ultimately the quantity and quality of grapevine production. A tool able to estimate plant responses to environment at the microscale is represented by numerical models, and more specifically LSMs and crop growth models [15; 16; 17]. In particular, LSMs evolved over time from a very simple approach (first generation models), representing simplified surface energy and hydrological balances (for instance, [18]) to the second generation models [19; 20; 21], in which the surface was interacting with the atmosphere and the presence of vegetation was explicitly represented in the exchange processes, and then to the third generation models, that further improved the simulation of the evapotranspiration pathway and considered the plant carbon uptake by means of an explicit canopy conductance (among others, the UTOPIA--University of Torino model of land Process Interaction with Atmosphere [22]--used in this work and described in the section \"Material and methods\"). LSMs and crop models (such as STICS - Simulateur mulTdisciplinaire pour les Cultures Standard [15; 16] and IVINE - Italian Vineyard Integrated Numerical model for Estimating physiological values [23]) can help the winemakers in supporting their decision system [24]. Eventually, LSMs can also include eco-physiological modules able to simulate variables related to vegetation growth, expressly optimized for different kinds of vegetation, as it is the case of the UTOPIA. In this context, the land surface becomes a key driver of the hydrological cycle and is fundamental to the overall functioning of the atmospheric and climate processes [25]. It is the surface layer that controls the partitioning of the available energy, between sensible and latent heat fluxes, and surface water, between evaporation, runoff, precipitation, and soil storage.