In this study, new estimates of monthly freshwater discharge from continents, drainage regions, and global land for the period of 2003–05 are presented. The method uses observed terrestrial water storage change estimates from the Gravity Recovery and Climate Experiment (GRACE) and reanalysis-based atmospheric moisture divergence and precipitable water tendency in a coupled land–atmosphere water mass balance. The estimates of freshwater discharge are analyzed within the context of global climate and compared with previously published estimates. Annual cycles of observed streamflow exhibit stronger correlations with the computed discharge compared to those with precipitation minus evapotranspiration (P − E) in several of the world’s largest river basins. The estimate presented herein of the mean monthly discharge from South America (846 km³ month⁻¹) is the highest among the continents and that flowing into the Atlantic Ocean (1382 km³ month⁻¹) is the highest among the drainage regions. The volume of global freshwater discharge estimated here is 30 354 ± 1212 km³ yr⁻¹. Monthly variations of global freshwater discharge peak between August and September and reach a minimum in February. Global freshwater discharge is also computed using a global ocean–atmosphere mass balance in order to validate the land–atmosphere water balance estimates and as a measure of global water budget closure. Results show close proximity between the two estimates of global discharge at monthly (RMSE = 329 km³ month⁻¹) and annual time scales (358 km³ yr⁻¹). Results and comparisons to observations indicate that the method shows important potential for global-scale monitoring of combined surface water and submarine groundwater discharge at near-real time, as well as for contributing to contemporary global water balance studies and for constraining global hydrologic model simulations.

We estimate global fresh water discharge from land-to-oceans (Q) and evapotranspiration (ET) on monthly time scales using a number of complimentary hydrologic data sets. This estimate is possible due to the new capability of measuring oceanic and land water mass changes from GRACE as well as the space-based measurements of oceanic and land precipitation (P_l ) and oceanic evaporation. Monthly time series of Q show peaks in July and January, and those of ET show peaks in March, May and August. Our estimates of Q andET are correlated with P_l  indicating qualitatively that our estimates capture temporal patterns of Q and ETreasonably well. Comparison of our Q with two other previous estimates based on the Global Runoff Data Centre (GRDC) river gauges network shows that our maximum peak in Q occurs about a month later than previous estimates. In addition, we compare our estimation of Q and ET to 20th century simulations from the WCRP CMIP3 multi-model archive assessed in the IPCC 4th Assessment Report. Runoff (R) and ET from AOGCMs tend to only exhibit the annual cycle, but the Q estimated in this study exhibits additional semi-annual variations that exists in P_l  as well. In addition, R from the models shows a maximum peak 2 months earlier than the estimated Q, which is due partly to the river discharge time lag that most AOGCMs do not take into account. These results indicate that current AOGCMs exhibit basic shortcomings in simulating Qand ET accurately. The new method developed here can be a useful constraint on these models and can be useful to close budget of global water balance.