Variability of the terrestrial water cycle, i.e. precipitation (P), evapotranspiration (E), runoff (Q) and water storage change (ΔS) is the key to understanding hydro-climate extremes. However, a comprehensive global assessment for the partitioning of variability in P between E, Q and ΔS is still not available. In this study, we use the recently released global monthly hydrologic reanalysis product known as the Climate Data Record (CDR) to conduct an initial investigation of the inter-annual variability of the global terrestrial water cycle. We first examine global patterns in partitioning the long-term mean P￣ between the various sinks E￣, Q￣ and ΔS￣ and confirm the well-known patterns with P￣ partitioned between E￣ and Q￣ according to the aridity index. In a new analysis based on the concept of variability source and sinks we then examine how variability in the precipitation σP2 (the source) is partitioned between the three variability sinks σE2, σQ2 and σΔS2 along with the three relevant covariance terms, and how that partitioning varies with the aridity index. We find that the partitioning of inter-annual variability does not simply follow the mean state partitioning. Instead we find that σP2 is mostly partitioned between σQ2, σΔS2 and the associated covariances with limited partitioning to σE2. We also find that the magnitude of the covariance components can be large and often negative, indicating that variability in the sinks (e.g. σQ2, σΔS2) can, and regularly does, exceed variability in the source (σP2). Further investigations under extreme conditions revealed that in extremely dry environments the variance partitioning is closely related to the water storage capacity. With limited storage capacity the partitioning of σP2 is mostly to σE2, but as the storage capacity increases the partitioning of σP2 is increasingly shared between σE2, σΔS2 and the covariance between those variables. In other environments (i.e. extremely wet and semi-arid–semi-humid) the variance partitioning proved to be extremely complex and a synthesis has not been developed. We anticipate that a major scientific effort will be needed to develop a synthesis of hydrologic variability.
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