Seasonality describes cyclic and largely predictable fluctuations in the environment. Such variations in day length, temperature, rainfall, and resource availability are ubiquitous and can exert strong selection pressure on organisms to adapt to seasonal environments. However, seasonal variations exhibit large scale geographical divergences caused by a whole suite of factors such as solar radiation, ocean currents, extent of continents, and topography. Realizing these contributions in driving patterns of overall seasonality may help advance our understanding of the kinds of evolutionary adaptations we should expect at a global scale. Here, we introduce a new concept and provide the data describing the overall degree of seasonality, based on its two major components—amplitude and predictability. Using global terrestrial datasets on temperature, precipitation and primary productivity, we show that these important seasonal factors exhibit strong differences in their spatial patterns with notable asymmetries between the southern and the northern hemisphere. Furthermore, our analysis reveals that seasonality is highly diverse across latitudes as well as longitudinal gradients. This indicates that using a direct measure of seasonality and its components, amplitude and predictability, may yield a better understanding of how organisms are adapted to seasonal environments and provide support for predictions on the consequences of rapid environmental change.