Intercomparison of water and energy budgets for five Mississippi subbasins between ECMWF reanalysis (ERA‐40) and NASA Data Assimilation Office fvGCM for 1990–1999

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Abstract
Using monthly means for 1990–1999, we assess the systematic biases in temperature and humidity and the surface energy and water budgets of both European Centre for Medium‐Range Weather Forecasts (ECMWF) 40‐year reanalysis (ERA‐40) and the of the NASA Data Assimilation Office atmospheric finite‐volume general circulation model (fvGCM) for five Mississippi subbasins. We compare ERA‐40 and the fvGCM with basin averages of surface observations of temperature, humidity and precipitation, the river basin estimates for the hydrological balance from Maurer et al. [2002], and the International Satellite Cloud Climatology Project (ISCCP) retrieved skin temperature and surface radiation fluxes. We show the role of the soil water analysis in ERA‐40, which generally supplies water in summer and removes it in winter and spring. The ERA‐40 snow analysis increments are a significant contribution to the (smaller) frozen water budget. Compared with National Climate Data Center (NCDC) observations of screen temperature, ERA‐40 generally has a relatively small (≤1 K) positive temperature bias in all seasons for the Mississippi basins, while the fvGCM has a large cold bias in temperature in winter. The ISCCP skin temperature estimate is generally high in winter and a little low in summer, compared to ERA‐40 and the NCDC screen level temperature. For the western basins, summer precipitation is high in the fvGCM, while for the eastern basins it is high in ERA‐40 (in 12–24 hour forecasts after spin‐up). Summer evaporation is higher in the fvGCM than in ERA‐40, while winter evaporation has a high bias in ERA‐40, leading to a corresponding high bias in specific humidity. Net shortwave radiation probably has a high bias in the fvGCM in summer. The seasonal cycle of incoming shortwave is much flatter in ERA‐40 than the ISCCP data, suggesting that the reanalysis may have too much reflective cloud in summer and too little in the cooler seasons. The temperature biases at the surface in both the fvGCM and the ISCCP data clearly have a negative impact on the surface long‐wave radiation fluxes, although the bias in the net long‐wave flux is rather less.

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