EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessment of prediction skill for land water storage in CMIP5 models based on GRACE satellite observations

Laura Jensen1, Annette Eicker1, Tobias Stacke2, and Henryk Dobslaw3
Laura Jensen et al.
  • 1HafenCity University, Geodesy and Geoinformatics, Hamburg, Germany (
  • 2Helmholtz-Zentrum Geesthacht, Centre for Materials and Coastal Research, Geesthacht, Germany
  • 3Helmholtz Centre Potsdam, German Research Centre for Geosciences - GFZ, Potsdam, Germany

Reliable predictions of terrestrial water storage (TWS) changes for the next couple of years would be extremely valuable for agriculture and water management. Decadal predictions have already shown to be meaningful for predicting e.g. sea surface and air temperature, but have not yet been intensively investigated regarding TWS. Here we evaluate decadal hindcasts of TWS related variables from an ensemble of five CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models against a TWS data set that is based on GRACE (Gravity Recovery And Climate Experiment) satellite observations.

As the overlap time span of 9 years for the model time series and GRACE observations is not long enough for a robust comparison, we also use a GRACE-based reconstruction of TWS utilizing precipitation and temperature data sets (Humphrey and Gudmundsson, 2019) available back to the year 1900. Thus we are able to compare the full 41 year (1970-2011) time span covered by CMIP5 decadal predictions to the TWS reconstruction. Correlations and root mean squared deviations (RMSD) are calculated for yearly global averages and for individual climate zones. Furthermore, we derive global maps of correlations and RMSD.

We find that at least for the first two prediction years the decadal model experiments clearly outperform the classical climate projections, regionally even for the third year. However, the spread among the models is large and absolute similarities between model output and GRACE TWS reconstructions are quite low.

We also perform a preliminary skill assessment for the first CMIP6 decadal hindcasts publicly available, finding a slightly reduced skill for the first forecast year in comparison to the CMIP5 models, while for the second forecast year an improvement is seen. This result is generally encouraging, but requires confirmation as soon as more CMIP6 decadal hindcasts become available.

Humphrey, V., Gudmundsson, L., 2019. GRACE-REC: a reconstruction of climate-driven water storage changes over the last century. Earth System Science Data Discussions 1–41.

How to cite: Jensen, L., Eicker, A., Stacke, T., and Dobslaw, H.: Assessment of prediction skill for land water storage in CMIP5 models based on GRACE satellite observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2605,, 2020


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