Assessing the thermodynamic variables of landscapes in the southwest part of East European plain in Russia using the MODIS multispectral band measurements

•Seasonal dynamics of variables of main land-cover types are considered.•Derived estimates do not contradict main open systems thermodynamics conceptions.•А comparison of variables calculated from MODIS TERRA and Landsat TM, ETM+ is given.•A functional connection between variables and climatic data (WorldClim) was shown.•Shown that variables gradients make significant input into forming of mesoclimate.

A method to assess the thermodynamic variables on regional scale using MODIS multispectral band measurements (MOD09GA product) was developed. It was applied to describe the spatial and temporal variability of thermodynamic variables within the western part of the East European Plain in Russia. Seasonal dynamics of thermodynamic variables was described for the main types of a landscape cover. It was found that the landscape cover in the winter is close to steady-state conditions. In the spring, the system abruptly passes into a non-equilibrium state, reaching maximal values of information increment in June. It was shown that during the growing period, the relationship between the absorbed and incoming solar radiation is almost constant for each type of landscape cover. The variation of exergy is much higher. Results show that the forest biomes in study region realize two main strategies for energy use: forest ecosystems maximize exergy (latent heat flux), peat bogs maintain the latent heat fluxes at the level of steppe vegetation. The increment of information is closely coupled with biological production. There is a very high negative coupling within a forest biome between exergy and the air temperature, as well as positive ones between exergy and precipitation amount. For steppe vegetation, such coupling is absent. Various strategies for water use, on the one hand, by forests and, on the other hand, by grassland and peatbog plant communities determine the border discreteness in the wide range of spatial and temporal scales.