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Takuya Kawabata, Tohru Kuroda, Hiromu Seko, and Kazuo Saito

1. Introduction Heavy rainfalls are extreme meteorological phenomena and often cause disasters with loss of human life. Recent progress in numerical modeling and assimilation techniques has made it possible to predict to some extent the occurrence of heavy rainfalls induced by orographic or synoptic forcing. However, predicting small-scale convective rainfalls with weak forcing is still a numerical weather prediction (NWP) challenge. In Japan, such local heavy rainfalls are sometimes called

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Marc Bocquet, Carlos A. Pires, and Lin Wu

imprecise initial state of the system. It could also stem from the more or less precise identification of forcings of the dynamical systems, such as emission fields (in atmospheric chemistry), radiative forcing, boundary conditions, and couplings to other models that may be imperfect. The deficiency of the model itself is another source of uncertainty. To account for this type of uncertainty, models could explicitly be made probabilistic. This occurs when some stochastic forcing is implemented to

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Jean-François Caron and Luc Fillion

diabatic forcing and divergence. Recently, Pagé et al. (2007) demonstrated the ability of another form of the omega equation to diagnose summertime mesoscale convective systems with a significant accuracy and envisage its utility as a balance constraint in a mesoscale Var system. These new approaches are currently being examined in the Environment Canada (EC) limited-area Var system ( Fillion et al. 2005 ). In terms of rotational wind balance, EC’s limited-area Var system uses, like other mesoscale

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Mark Buehner, P. L. Houtekamer, Cecilien Charette, Herschel L. Mitchell, and Bin He

the EnKF, the tangent linear version of the observation operators is applied to the 4D analysis increment as in 4D-Var. c. Assimilated observations The types of observations assimilated in the 2008 operational 4D-Var system are wind, temperature, and humidity from radiosondes; wind and temperature from aircraft; wind (only over water), temperature, pressure, and humidity from in situ surface observations; winds from profilers over the United States; cloud-tracked winds from

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