Flows in the ocean are driven either by atmospheric forces or by small-scale internal disturbances that are inherently chaotic. We use computer simulation results to show that these chaotic oceanic disturbances can attain spatial scales large enough to alter the motion of Earth’s pole of rotation. Given their size and unpredictable nature, the chaotic signals are a source of uncertainty when interpreting observed year-to-year polar motion changes in terms of other processes in the Earth system.

The satellite gravimetry can provide direct measurement of total water storage (TWS) that was never achieved before. In this study, we provide an open-source assimilation system to show how the satellite based TWS can be temporally, vertically and laterally disaggregated for constraining/validating/improving the global hydrological models. With this system, early warning and water management at a global scale would be more accurate, given the upcoming next-generation satellite gravity missions.

Currently, global hydrological models do not benefit from observations of model output variables to reduce and quantify model output uncertainty. For the Mississippi River basin, we explored three approaches for using both streamflow and total water storage anomaly observations to adjust the parameter sets in a global hydrological model. We developed a method for considering the observation uncertainties to quantify the uncertainty of model output and provide recommendations.

The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean-based processes related to the mass balance of glaciers in Northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79N Glacier. We find that together, the different in situ and remote sensing observations and model simulations to reveal a consistent picture of a coupled atmosphere-ice sheet-ocean system, that has entered a phase of major change.

Shrinkage of the Antarctic ice sheet (AIS) leads to sea level rise. Satellite gravimetry measures AIS mass changes. We apply a new method that overcomes two limitations: low spatial resolution and large uncertainties due to the Earth's interior mass changes. To do so, we additionally include data from satellite altimetry and climate and firn modelling, which are evaluated in a globally consistent way with thoroughly characterized errors. The results are in better agreement with independent data.