Quarterly Journal of the Royal Meteorological Society Q. J. R. Meteorol. Soc. 140: 2535 – 2545, October 2014 B DOI:10.1002/qj.2319 Impact of analyses on the dynamical balance of global and limited-area atmospheric models K. Chikhar* and P. Gauthier ESCER Centre, Universit´ e du Qu´ ebec ` a Montr´ eal, Canada *Correspondence to: K. Chikhar, Department of Earth and Atmospheric Sciences, Universit´ e du Qu´ ebec ` a Montr´ eal, PO Box 8888 Succ Centre-ville Montr´ eal, Qu´ ebec H3C 3P8, Canada. E-mail: chikhar@sca.uqam.ca Dynamical imbalances can induce spurious variability which can be diagnosed from the physical tendencies observed in the first moments of short-term forecasts using as initial conditions analyses obtained from an assimilation system using this model. In this article this approach is taken to investigate differences in the balance obtained from 3D- and 4D-Var analyses, using the forecast–assimilation system of the Meteorological Service of Canada (MSC). The results indicate that the model is then in good balance globally but the 4D-Var analyses slightly upset the balance in the Tropics, thereby altering the characteristics of the Intertropical Convergence Zone (ITCZ). As the assimilation is driven by a particular model, the resulting analyses keep an imprint of the dynamics of that model and use of this analysis with another model may not be as well in balance due to the differences between the two models. To study this point, ERA-Interim 4D-Var reanalyses were used as initial conditions first at a lower horizontal and vertical resolution, and then at a resolution closer to that of the Global Environmental Multiscale (GEM) model. The higher-resolution reanalyses led to a better balance than that with a lower-resolution version of the ERA-Interim reanalyses. The coarser analyses create significant imbalances in the Canadian global model which persist for more than 5 days. In particular, it was noted that convection is nearly absent early on as if at a lower resolution, the ERA-interim analyses did not inject sufficient humidity to trigger convection. It was also noted that reducing the vertical resolution is more damaging than using a coarser horizontal resolution. In limited-area regional climate models, external analyses are used to define the boundary conditions and the Canadian Regional Climate Model (CRCM) was used to assess the impact of different ways to define the boundary conditions. The CRCM is a limited- area configuration of the GEM global model used in the 3D- and 4D-Var assimilation. Experiments were conducted in which the boundary conditions driving the CRCM are provided every 6 h as is usually done for the CRCM climate simulations. When using 4D-Var analyses and ERA-Interim reanalyses (coarse and full resolution) to define the boundary conditions, the results indicate that imbalances persist even after 15 days and are more significant for the coarser analyses. Moreover, even though the model exhibits relatively good balance initially, after 5 days imbalances appear gradually in the interior of the regional model domain. Key Words: data assimilation; dynamical balance; physical processes; limited-area models; numerical weather prediction; regional climate modeling Received 15 July 2013; Revised 19 November 2013; Accepted 15 December 2013; Published online in Wiley Online Library 25 February 2014 1. Introduction Future climate predictions are obtained by using increasingly complex models. These predictions are associated with uncer- tainties related to different error sources (Murphy et al., 2004; Stainforth et al., 2005). An important source of uncertainty is the model error. Indeed, models contain errors of different kinds and these can lead to unrealistic simulations. A recognized source of error in the models lies in deficiencies in the representation of subgrid physical processes. The model errors are usually quanti- fied by comparing the forecasts to observations. This technique provides an estimation of the model errors without a precise information on their origin. The latter is much harder to identify especially when multiple error factors combine. Complementary c  2013 Royal Meteorological Society