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Driving data and physical parametrizations can significantly impact the performance of regional dynamical atmospheric models in reproducing hydrometeorologically relevant variables. Our study addresses the water budget sensitivity of the Weather Research and Forecasting Model System WRF (WRF-ARW) with respect to two cumulus parametrizations (Kain–Fritsch, Betts–Miller–Janjić), two global driving reanalyses (ECMWF ERA-INTERIM and NCAR/NCEP NNRP), time variant and invariant sea surface temperature and optional gridded nudging. The skill of global and downscaled models is evaluated against different gridded observations for precipitation, 2 m-temperature, evapotranspiration, and against measured discharge time-series on a monthly basis. Multi-year spatial deviation patterns and basin aggregated time series are examined for four globally distributed regions with different climatic characteristics: Siberia, Northern and Western Africa, the Central Australian Plane, and the Amazonian tropics. The simulations cover the period from 2003 to 2006 with a horizontal mesh of 30 km. The results suggest a high sensitivity of the physical parametrizations and the driving data on the water budgets of the regional atmospheric simulations. While the global reanalyses tend to underestimate 2 m-temperature by 0.2–2 K, the regional simulations are typically 0.5–3 K warmer than observed. Many configurations show difficulties in reproducing the water budget terms, e.g. with long-term mean precipitation biases of 150 mm month and higher. Nevertheless, with the water budget analysis viable setups can be deduced for all four study regions.

climate dynamics

Atmospheric and terrestrial water budgets: sensitivity and performance of configurations and global driving data for long term continental scale WRF simulations