Inter-annual variability of the global terrestrial water cycle

Dongqin Yin, Michael L. Roderick
2019 Hydrology and Earth System Sciences Discussions  
<p><strong>Abstract.</strong> Variability of the terrestrial water cycle, i.e., precipitation (<i>P</i>), evapotranspiration (<i>E</i>), runoff (<i>Q</i>) and water storage change (&amp;Delta;<i>S</i>) is the key to understanding hydro-climate extremes. However, a comprehensive global assessment for the partitioning of variability in <i>P</i> between <i>E</i>, <i>Q</i> and &amp;Delta;<i>S</i> is still not available. In this study, we use the recently released global monthly hydrologic
more » ... ydrologic 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 <i><span style="text-decoration: overline">P</span></i> between the various sinks <span style="text-decoration: overline"><i>E</i></span>, <span style="text-decoration: overline"><i>Q</i></span> and <span style="text-decoration: overline">&amp;Delta;<i>S</i></span> and confirm the well-known patterns with <i><span style="text-decoration: overline">P</span></i> partitioned between <i><span style="text-decoration: overline">E</span></i> and <i><span style="text-decoration: overline">Q</span></i> according to the aridity index. In a new analysis based on the concept of variability source and sinks (Eq. 2) we then examine how variability in the precipitation &amp;sigma;<sub><i>P</i></sub><sup>2</sup> (the source) is partitioned between the three variability sinks &amp;sigma;<sub><i>E</i></sub><sup>2</sup>, &amp;sigma;<sub><i>Q</i></sub><sup>2</sup> and &amp;sigma;<sub>&amp;Delta;<i>S</i></sub><sup>2</sup> 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, with &amp;sigma;<sub><i>P</i></sub><sup>2</sup> mostly partitioned between &amp;sigma;<sub><i>Q</i></sub><sup>2</sup>, &amp;sigma;<sub>&amp;Delta;<i>S</i></sub><sup>2</sup> and the associated covariances. We also find that the magnitude of the covariance components can be large and often negative, indicating the variability in the sinks (e.g., &amp;sigma;<sub><i>Q</i></sub><sup>2</sup>, &amp;sigma;<sub>&amp;Delta;<i>S</i></sub><sup>2</sup>) can, and do, exceed variability in the source (&amp;sigma;<sub><i>P</i></sub><sup>2</sup>). Further investigations under extreme conditions reveal that in extremely dry environments the variance partitioning is closely related to the water storage capacity. With limited storage capacity the partitioning of &amp;sigma;<sub><i>P</i></sub><sup>2</sup> is mostly to &amp;sigma;<sub><i>E</i></sub><sup>2</sup>, but as the storage capacity increases the partitioning of &amp;sigma;<sub><i>P</i></sub><sup>2</sup> is increasingly shared between &amp;sigma;<sub><i>E</i></sub><sup>2</sup>, &amp;sigma;<sub>&amp;Delta;<i>S</i></sub><sup>2</sup> and the covariance between those variables. In other environments (i.e., extremely wet and semi-arid/semi-humid) the variance partitioning proved to extremely complex and a synthesis was not developed. We anticipate that a major scientific effort will be needed to develop a synthesis of hydrologic variability.</p>
doi:10.5194/hess-2019-230 fatcat:ks5mnnmdazdzpfrvjiseactjne