A 10 per cent increase in global land evapotranspiration from 2003 to 2019.

Accurate quantification of global land evapotranspiration is necessary for understanding variability in the global water cycle, which is expected to intensify under climate change1-3. Current global evapotranspiration products are derived from a variety of sources, including models4,5, remote sensing6,7 and in situ observations8-10. However, existing approaches contain extensive uncertainties; for example, relating to model structure or the upscaling of observations to a global level11. As a result, variability and trends in global evapotranspiration remain unclear12. Here we show that global land evapotranspiration increased by 10 ± 2 per cent between 2003 and 2019, and that land precipitation is increasingly partitioned into evapotranspiration rather than runoff. Our results are based on an independent water-balance ensemble time series of global land evapotranspiration and the corresponding uncertainty distribution, using data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) satellites13. Variability in global land evapotranspiration is positively correlated with El Niño-Southern Oscillation. The main driver of the trend, however, is increasing land temperature. Our findings provide an observational constraint on global land evapotranspiration, and are consistent with the hypothesis that global evapotranspiration should increase in a warming climate.

Understanding of Contemporary Regional Sea-Level Change and the Implications for the Future.

Global sea level provides an important indicator of the state of the warming climate, but changes in regional sea level are most relevant for coastal communities around the world. With improvements to the sea-level observing system, the knowledge of regional sea-level change has advanced dramatically in recent years. Satellite measurements coupled with in situ observations have allowed for comprehensive study and improved understanding of the diverse set of drivers that lead to variations in sea level in space and time. Despite the advances, gaps in the understanding of contemporary sea-level change remain and inhibit the ability to predict how the relevant processes may lead to future change. These gaps arise in part due to the complexity of the linkages between the drivers of sea-level change. Here we review the individual processes which lead to sea-level change and then describe how they combine and vary regionally. The intent of the paper is to provide an overview of the current state of understanding of the processes that cause regional sea-level change and to identify and discuss limitations and uncertainty in our understanding of these processes. Areas where the lack of understanding or gaps in knowledge inhibit the ability to provide the needed information for comprehensive planning efforts are of particular focus. Finally, a goal of this paper is to highlight the role of the expanded sea-level observation network-particularly as related to satellite observations-in the improved scientific understanding of the contributors to regional sea-level change.

Identifying ENSO-related interannual and decadal variability on terrestrial water storage.

We apply two statistical techniques to satellite measurements to identify a relationship between terrestrial water storage (TWS) and El Niño-Southern Oscillation (ENSO). First, we modified and used the least-squares regression of a previous study using longer records. Second, we applied a cyclostationary empirical orthogonal function analysis (CSEOF). Although the CSEOF technique is distinct from the least-squares regression in that it does not consider proxies, each method produces two modes (decadal and interannual), showing consistency with each technique in spatial pattern and its evolution amplitudes. We also compared the results obtained by the two methods for thirty watersheds, of which five watersheds were compared with previous studies. The combination of the two modes explains the total variance in most watersheds showing the role that interannual and decadal ENSO-related signals in understanding terrestrial water storage variability. The results show that the decadal mode, along with the interannual mode, also plays an important role in describing the local TWS.