In recent decades, the intensity, frequency, and variability of extreme events (e.g., heat waves, droughts, severe storms, and floods) have increased globally due to the intensification of the changing climate, land-use/landcover and anthropogenic activities. An increase in extreme events results in severe economic crises and enormous disruptions in various social and environmental sectors. Hence, effective and efficient prediction and mitigation of flood and drought events are desirable. It requires a better understanding of the recent trends and variability of the extremes, which is quite challenging owing to the complex and non-stationary behaviour of the associated covariates (hydroclimatic variables, atmospheric circulation patterns), and their spatiotemporal variability and nonlinear interactions. This study proposes a new Non-stationary Standardized Potential Evapotranspiration Index (NSPEI) to assess the wetness and dryness condition and couples it with an entropy-based measure to quantify the variability of the extremes. NSPEI considers non-stationarities of both precipitation and temperature in addition to their ability to identify extreme events at different time/accumulation scales (multi-scalar). Hence, water deficits/excess could be better assessed over different accumulation periods, which helps identify and monitor various droughts (e.g., agricultural, meteorological) and water saturation conditions (e.g., floods, runoff). Furthermore, as the drought/wetness triggering variables and causes for extreme conditions may vary worldwide, a standardized drought variability index is introduced in this study to assess better drought and wetness variability across the world at multiple timescales (monthly, seasonal, annual and decadal). In addition, the influence of LULC and location indicators (latitude, longitude, and elevation) on drought and wetness variability is assessed across different continents for various time scales and severity of both wetness and dryness conditions. The analysis and outcomes of this study enhance understanding of global drought and wetness variability patterns and provide reliable information on water availability for devising effective water management strategies towards mitigation of the extremes in various continents.