Global runoff over 1993\textendash2009 estimated from coupled land-ocean-atmosphere water budgets and its relation with climate variability

Whether the global runoff (or freshwater discharge from land to the ocean) is currently increasing and the global water cycle is intensifying is still a controversial issue. Here we compute land-atmosphere and ocean-atmosphere water budgets and derive two independent estimates of the global runoff over the period 1993-2009. Water storage variations in the land, ocean and atmosphere reservoirs are estimated from different types of datasets: atmospheric reanalyses, land surface models, satellite altimetry and in situ ocean temperature data (the difference between altimetry based global mean sea level and ocean thermal expansion providing an estimate of the ocean mass component). Results for the global runoff from the two methods show a very good correlation between both estimates. More importantly, no significant trend is observed over the whole period. Besides, the global runoff appears to be clearly impacted by large-scale climate phenomena such as major ENSO events. To infer this, we compute the zonal runoff over four latitudinal bands and set up for each band a new index (Combined Runoff Index) obtained by optimization of linear combinations of various climate indices. Results show that, in particular, the intertropical and northern mid-latitude runoffs are mainly driven by ENSO and the Atlantic Multidecadal Oscillation (AMO) with opposite behavior. Indeed, the zonal runoff in the intertropical zone decreases during major El Ni\~no events whereas it increases in the northern mid-latitudes, suggesting that water masses over land are shifted northward/southward during El Ni\~no/La Ni\~na. In addition to this study, we propose an innovative method to estimate the global ocean thermal expansion. The method is based on the assumption that the difference between both runoff estimates is mainly due the thermal expansion term not accounted for in the estimation of the ocean mass. Comparison of our reconstructed thermal expansion with two existing datasets shows the relevance of this new method.