ABSTRACT
ABSTRACT: Drought can be monitored by identifying unusually dry soil conditions through land-surface schemes. The capability of the models to capture the numerous interactions among the surface budgets in the land-atmosphere interface is limited by several factors (model complexity, input data accuracy, etc.); in addition, a reliable statistical representation of soil moisture behavior is challenging due to its peculiarities (i.e. double-bounded skewed probability distribution). This paper shows an intercomparison of different models (LisFlood, CLM and TESSEL) over the same study domain, with the aim of identifying the areas where the modelled outputs are less reliable; successively, modelled timeseries are used to detect a statistical method to quantify anomalous soil moisture statuses based on statistically robust metrics such as the mode and the median-absolute-difference. Analysis are performed over Europe, illustrating the potential of the methodology for the assessment of the main drought events observed in the last two decades.
