Role of the atmospheric mean state on the initiation of the Madden-Julian oscillation in a tropical channel model

Tropical channel models, defined as models that are global in the zonal direction but bounded in the meridional direction, are particularly useful for simulating the Madden-Julian oscillation (MJO) and understanding its physical and dynamical basis. Influences from the extratropics through the lateral boundaries have been found to be essential to the reproduction of the initiation of certain MJO events. This led to a hypothesis that multi-year simulations using a tropical channel model would reproduce reasonable MJO statistics under the influence of prescribed lateral boundary conditions derived from global reanalyses. Interestingly, the MJO statistics in such a multi-year simulation by a high-resolution tropical channel model are not better than those from global climate models. The error in the atmospheric mean state is found to be a possible reason for the poor MJO statistics in the simulation. Nevertheless, even with a large error in the mean state, the multi-year simulation captures two MJO events previously found to be initiated by extratropical influences. However, the model does not reproduce a third event, whose initiation is not directly influenced by the extratropics. This implies that in the absence of dynamical interactions between the MJO and the lateral boundary conditions, the error in the mean state could be sufficient to prevent the MJO initiation. To explore this third MJO event further, a series of sensitivity tests are conducted. These tests show that the simulation of this event is neither critically influenced by the cumulus parameterization employed, nor the initial conditions when the model is integrated 2?weeks prior to the MJO initiation. The model captures this event when the MJO signal is already present in the initial conditions. The use of high-resolution sea surface temperature does not improve the simulation of the third MJO event. A higher-resolution nested domain covering the Indo-Pacific warm pool region and including a cloud-system resolving domain over the Indonesian Maritime Continent has little effect on the MJO initiation over the Indian Ocean. In <2?weeks the error in the simulation is comparable to the climate error. The role of the simulated MJO on the mean state is also explored. Implications and limitations of these results are discussed.     

Analysis of the long-term surface wind variability over complex terrain using a high spatial resolution WRF simulation

This work uses a WRF numerical simulation from 1960 to 2005 performed at a high horizontal resolution (2 km) to analyze the surface wind variability over a complex terrain region located in northern Iberia. A shorter slice of this simulation has been used in a previous study to demonstrate the ability of the WRF model in reproducing the observed wind variability during the period 1992–2005. Learning from that validation exercise, the extended simulation is herein used to inspect the wind behavior where and when observations are not available and to determine the main synoptic mechanisms responsible for the surface wind variability. A principal component analysis was applied to the daily mean wind. Two principal modes of variation accumulate a large percentage of the wind variability (83.7%). The first mode reflects the channeling of the flow between the large mountain systems in northern Iberia modulated by the smaller topographic features of the region. The second mode further contributes to stress the differentiated wind behavior over the mountains and valleys. Both modes show significant contributions at the higher frequencies during the whole analyzed period, with different contributions at lower frequencies during the different decades. A strong relationship was found between these two modes and the zonal and meridional large scale pressure gradients over the area. This relationship is described in the context of the influence of standard circulation modes relevant in the European region like the North Atlantic Oscillation, the East Atlantic pattern, East Atlantic/Western Russia pattern, and the Scandinavian pattern.