Inter-annual variability of the global terrestrial water cycle

Variability of the terrestrial water cycle, i.e. precipitation (P), evapotranspiration (E), runoff (Q) and water storage change (Delta S) is the key to understanding hydro-climate extremes. However, a comprehensive global assessment for the partitioning of variability in P between E, Q and Delta S 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) over bar between the various sinks (E) over bar, (Q) over bar and (Delta S) over bar and confirm the well-known patterns with (P) over bar partitioned between (E) over bar and (Q) over bar 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 sigma(2)(P) (the source) is partitioned between the three variability sinks sigma(2)(E), sigma(2)(Q) and sigma(2)(Delta S) 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 sigma(2)(P) is mostly partitioned between sigma(2)(Q), sigma(2)(Delta S) and the associated covariances with limited partitioning to sigma(2)(E). We also find that the magnitude of the covariance components can be large and often negative, indicating that variability in the sinks (e.g. sigma(2)(Q), sigma(2)(Delta S) ) can, and regularly does, exceed variability in the source (sigma(2)(P)). 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 sigma(2)(P) is mostly to sigma(2)(E), but as the storage capacity increases the partitioning of sigma(2)(P) is increasingly shared between sigma(2)(E), sigma(2)(Delta S) 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.