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Tree restoration is an effective way to store atmospheric carbon and mitigate climate change. However, large-scale tree-cover expansion has long been known to increase evaporation, leading to reduced local water availability and streamflow. More recent studies suggest that increased precipitation, through enhanced atmospheric moisture recycling, can offset this effect. Here we calculate how 900 million hectares of global tree restoration would impact evaporation and precipitation using an ensemble of data-driven Budyko models and the UTrack moisture recycling dataset. We show that the combined effects of directly enhanced evaporation and indirectly enhanced precipitation create complex patterns of shifting water availability. Large-scale tree-cover expansion can increase water availability by up to 6% in some regions, while decreasing it by up to 38% in others. There is a divergent impact on large river basins: some rivers could lose 6% of their streamflow due to enhanced evaporation, while for other rivers, the greater evaporation is counterbalanced by more moisture recycling. Several so-called hot spots for forest restoration could lose water, including regions that are already facing water scarcity today. Tree restoration significantly shifts terrestrial water fluxes, and we emphasize that future tree-restoration strategies should consider these hydrological effects.

Spring 2020 broke sunshine duration records across Western Europe. The Netherlands recorded the highest surface irradiance since 1928, exceeding the previous extreme of 2011 by 13%, and the diffuse fraction of the irradiance measured a record low percentage (38%). The coinciding irradiance extreme and a reduction in anthropogenic pollution due to COVID-19 measures triggered the hypothesis that cleaner-than-usual air contributed to the record. Based on analyses of ground-based and satellite observations and experiments with a radiative transfer model, we estimate a 1.3% (2.3 W m−2) increase in surface irradiance with respect to the 2010–2019 mean due to a low median aerosol optical depth, and a 17.6% (30.7 W m−2) increase due to several exceptionally dry days and a very low cloud fraction overall. Our analyses show that the reduced aerosols and contrails due to the COVID-19 measures are far less important in the irradiance record than the dry and particularly cloud-free weather.

A climatology of extreme cold season precipitation events in Norway from 1979 to 2014 is presented, based on the 99th percentile of the 24-h accumulated precipitation. Three regions, termed north, west, and south are identified, each exhibiting a unique seasonal distribution. There is a proclivity for events to occur during the positive phase of the NAO. The result is statistically significant at the 95th percentile for the north and west regions. An overarching hypothesis of this work is that anomalous moisture flux, or so-called atmospheric rivers (ARs), are integral to extreme precipitation events during the Norwegian cold season. An objective analysis of the integrated vapor transport illustrates that more than 85% of the events are associated with ARs. An empirical orthogonal function and fuzzy cluster technique is used to identify the large-scale weather patterns conducive to the moisture flux and extreme precipitation. Five days before the event and for each of the three regions, two patterns are found. The first represents an intense, southward-shifted jet with a southwest–northeast orientation. The second identifies a weak, northward-shifted, zonal jet. As the event approaches, regional differences become more apparent. The distinctive flow pattern conducive to orographically enhanced precipitation emerges in the two clusters for each region. For the north and west regions, this entails primarily zonal flow impinging upon the south–north-orientated topography, the difference being the latitude of the strong flow. In contrast, the south region exhibits a significant southerly component to the flow.

Abstract. To study the global hydrological cycle and its response to a changing climate, we rely on global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. Increase in computer power therefore permits increase in resolution, but it is an open question where this resolution is invested best: in the GCM or GHM. In this study, we evaluated the benefits of increased resolution, without modifying the representation of physical processes in the models. By doing so, we can evaluate the benefits of resolution alone. We assess and compare the benefits of an increased resolution for a GCM and a GHM for two basins with long observational records: the Rhine and Mississippi basins. Increasing the resolution of a GCM (1.125 to 0.25∘) results in an improved precipitation budget over the Rhine basin, attributed to a more realistic large-scale circulation. These improvements with increased resolution are not found for the Mississippi basin, possibly because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of the GCM improved the simulations of the monthly-averaged discharge for the Rhine, but did not improve the representation of extreme streamflow events. For the Mississippi basin, no substantial differences in precipitation and discharge were found with the higher-resolution GCM and GHM. Increasing the resolution of parameters describing vegetation and orography in the high-resolution GHM (from 0.5 to 0.05∘) shows no significant differences in discharge for both basins. A straightforward resolution increase in the GHM is thus most likely not the best method to improve discharge predictions, which emphasizes the need for better representation of processes and improved parameterizations that go hand in hand with resolution increase in a GHM.