## 1 Introduction
Abundant rainfall and resulting flooding can also negatively affect forest ecosystems and significantly alter biogeochemical cycles in the ecosystem. Heavy rainfall tends to result in high soil moisture, which leads to higher soil respiration rates [30; 31; 32; 33]. This effect is known as the \"Birch effect\" [34] and is manifested by a strong release of CO\({}_{2}\) following the rewetting of dry soils. Higher CO\({}_{2}\) emissions are caused by the release of more nitrogen and carbon from soils under wetting and drying cycles than from continuously wet soils. Wetting after a continuous dry period also results in a higher degree of decomposition and mineralization [35; 36]. Extreme precipitation events can induce waterlogging of the area, thereby altering CO\({}_{2}\) uptake by the ecosystem, and lead to flood-induced tree mortality [37]. Furthermore, heavy rainfall and flooding can cause topsoil erosion with losses of particulate and dissolved organic carbon from terrestrial to aquatic ecosystems [38; 39]. Therefore, existing experimental data, conducted in different geographical regions and forest types, indicate a high diversity and even opposite trends in carbon balance and evapotranspiration due to extreme weather events. Varying growth conditions and the adaptation mechanisms of forest plant communities to external atmospheric influences(temperature and precipitation anomalies) lead to significant uncertainties in the identification of sustainable mechanisms and functional interactions of forest ecosystems with atmospheric conditions. Studying the response of terrestrial ecosystems to extreme weather events is challenging and requires new experimental and modeling studies. Different methods for analyzing and interpreting experimental data can provide a better understanding of forest ecosystem processes, as well as a better prediction of how different forest ecosystems respond to external influences. These studies should focus both on the temporal variability of the carbon and water balance in individual forest ecosystems and on the analysis of spatial differences in the response of forest ecosystems to external influences. The global and regional networks of greenhouse gas (GHG) flux monitoring stations (FLUXNET) can be very useful for assessing the spatial and temporal variability of GHG fluxes and for describing the possible response of forest ecosystems to atmospheric forcing [40]. Currently, global and regional FLUXNET networks include more than 1000 active and historical flux stations. They use a common methodology for flux measurements based on eddy covariance techniques. It is based on unified algorithms and software for data post-processing and analysis, which provide good data comparability [41]. The stations are evenly distributed over the different continents with different climate, vegetation, and soil types. More than 50% of these stations have been in operation for more than 3 years. The aim of our study is to assess differences in the response of the daily net ecosystem exchange (NEE) of CO\({}_{2}\) flux and latent heat flux (LE) between different boreal and temperate ecosystems to extreme weather events (e.g., anomalous temperature and precipitation). To achieve the main objective of our study, we use meteorological reanalysis data as well as available information on turbulent atmospheric fluxes and meteorological parameters at mid-latitude flux measurement stations from the global and regional FLUXNET databases [40]. Our recent study [42] based on FLUXNET data and similar methodology for data analysis demonstrated significant variability in the response of tropical CO\({}_{2}\) fluxes to extreme weather events. It was shown that the relationship between the fluxes and extreme temperature/precipitation varies drastically between the various ecosystems and even within a biome, depending on geographic location, plant species composition, and season.