Remotely sensed agricultural drought monitoring can be via measurement of soil moisture content, usually through microwave radar (active) and radiometers (passive) such as SMOS or SMAP (soil moisture active passive), e.g., [23; 24], or through the assessment of vegetation using passive multispectral sensors such as Landsat or, more recently, Sentinel-2/-3, e.g., [25; 26]. The former represents a direct measurement of soil moisture, while the latter infers this by assessing vegetation condition or productivity. Land surface temperature is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the atmosphere and the ground. For more complex conditions like vegetated surfaces, the physical temperature of the Earth's surface can refer to an average effective radiative temperature of the canopy and surface [27; 28]. The capabilities of the meteorological geostationary satellites of EUMETSAT provide a set of methods for remote sensing of vegetation water stress. During vegetation stress, the vegetation spectral signatures may be substantially modified. The scientific and societal importance of land surface temperature has been obvious for a long time and it has been observed and investigated quantitatively for years, taking into account the following. Surface temperature is a basic environmental/meteorological parameter that directly affects human life: it influences the function and variability of ecosystems, including agriculture; exercises control on surface-atmosphere exchange of energy, water, gases and aerosols; and is a primary variable of climatology and an indicator of climate change [29]. Due to the close relationship of surface temperature to soil moisture [30; 31], it is an important parameter for monitoring changes in surface conditions: remotely sensed land surface temperature (LST) has been investigated for soil water content [32; 33; 34], water budget components [35], fire risk [36], and many others. The remotely sensed estimates of canopy minus air temperature are applied as an indicator of crop/grassland water stress [37; 38]. Other studies [39; 40] link the temperature difference between LST and air temperature at 2 m height to root zone SMA in order to characterize soil moisture conditions. A statistical model for daily prediction of the maximum air temperature during heat wave episodes has been developed using LST as one of the input parameters [41]. The main objective of this study is to characterize the spatiotemporal variability of dry land surface state anomalies using long-term data records for the region of the Eastern Mediterranean (Bulgaria) and to test the sensitivity of skin temperature retrievals from infrared observations by the Meteosat geostationary satellite as a soil moisture indicator in a climatic context. Considering drought anomalies as a biogeophysical process resulting from the coupling between energy-water cycles on a regional scale, the following aims are specifically focused on:  
1. Characterizing the spatiotemporal variability of drought occurrence based on long-term data records (2007-2018) of a biophysical index, soil moisture availability index (SMAI, [42]) using the SVAT modeling approach). 2. Revealing the score of skin temperature retrieval according to the Land Surface Analysis Satellite Application Facility Land Surface Temperature (LSASAF LST) product as a measure of dry surface state on a regional scale considering its consistency with SMAI based on statistical analyses. 3. Identifying the most drought-prone regions over Bulgaria. 4. Illustrating the effect of drought on fire activity using satellite information [43; 44].