**1. Introduction**

68 Atmospheric Model Applications

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The Madden-Julian oscillation (MJO, Madden and Julian, 1971, 1972) is a dominant feature of intraseasonal (20-90 day) variability in the tropics. According to the classic view, the MJO begins as a positive convective anomaly in the equatorial western Indian Ocean. It then propagates eastward toward the maritime continent where convection weakens until the MJO reaches the west Pacific where the convection strengthens again. Convective coupling diminishes in the eastern Pacific in the presence of cooler sea surface temperature (SST), but the wind component in the upper troposphere may propagate eastward as free waves at about 12-15 m s-1, much faster than the MJO propagation speed of 5 m s-1 (Knutson et al., 1986). Global circumnavigation associated with the MJO can also be noticed in the uppertropospheric divergent wind (e.g., Krishnamurti et al., 1985; Knutson and Weickman, 1987) and moisture fields (Kikuchi and Takayabu, 2003), but is difficult to detect in parameters closer to the surface.

The MJO has been found to influence a number of features in the tropics including the Indian summer monsoon (e.g., Yasunari, 1979), Australian monsoon (e.g., Hendon and Liebmann, 1990), tropical storms (e.g., Liebmann et al., 1994), and the initiation of El Nino events (e.g., Lau and Chan, 1985). However, the influence of the MJO is not limited to the tropics. The MJO affects the global medium and extended range weather forecasts (e.g., Jones and Schemn, 2000) and modulates the global angular momentum (e.g., Weickmann et al., 1997). This tropics-extratropics interaction produced by the MJO affects the skill of the northern hemisphere weather forecasts (Ferranti et al., 1990). The long periodicity of the MJO convection relates it with the predictability on seasonal time scales. As a result, longerrange forecasts could be improved if the MJO can be predicted.

There have been considerable advancements in understanding the different aspects of the MJO using observation, theory and numerical modeling. However, an accurate MJO simulation using numerical models remains an extremely difficult task due to a number of model deficiencies (Lin et al., 2006; Zhang et al., 2006; Kim et al., 2009). One such deficiency is the model's inability in capturing the correct mean state. The role of the mean state on the MJO was previously explored using GCMs (e.g., Slingo et al., 1996; Inness et al., 2003; Maloney and Hartmann, 2001; Ajayamohan and Goswami, 2007; Maloney, 2009), observations (Zhang and Dong, 2004), and model-observation comparison (Zhang et al., 2006). It is found that the realistic distributions of precipitation, lower-tropospheric zonal

Mean State and the MJO in a High Resolution Nested Regional Climate Model 71

The NRCM simulation is used to document the mean state and the MJO statistics. The MJO is defined as a planetary scale (zonal wavenumber 1 to 5), eastward propagating, intraseasonal (20-90 day) components in the U850 coupled with precipitation (P). To extract the coupled MJO signal, a singular vector decomposition (SVD) method (Wallace et al., 1992) is applied to U850 and P. This method is similar to EOF analysis, but with one advantage: it considers the wind-precipitation coupling associated with the MJO. The leading modes are selected based on North et al. (1982) rule. Three leading modes are found for both observations and model, and they explain 41% and 31% of the covariance for the observation and the NRCM, respectively. These selected modes represent the intraseasonal coupled components between U850 and P. Time series of U850 and P reconstructed through linear regression of intraseasonal bandpass filtered U850 and P upon their selected leading SVD modes, are considered to represent the MJO. Hereafter, they are referred to as U850\*

Model validation uses observations and reanalyses data. They include: National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) Reanalysis (Kalnay et al., 1996) winds and the merged analysis of precipitation (CMAP; Xie

The initial and boundary conditions of the NRCM are from the NCEP-NCAR reanalysis. The SSTs are from Atmospheric Model Intercomparison Project (AMIP; 1° x 1°, 6-hourly; Taylor et al., 2000). For brevity, both reanalysis and CMAP precipitation will be referred to

The simulated mean state is described first, followed by the MJO and how it has been

The mean state of the model is compared with the observation with respect to P and U850 (Fig. 1). The main error in the model precipitation is over the equatorial Indian and west Pacific Ocean and over the South Pacific Convergence Zone (SPCZ), where the variance of the MJO related precipitation is maximum (Zhang and Dong, 2005). This is the first indication that the simulated MJO may be affected by the mean state. The model precipitation seems to move further from the equator with much higher values over the southern Indian Ocean and north of maritime continent. Most of this error comes during the northern winter. On the other hand, simulated U850 is somewhat stronger than those of reanalysis over the Indian Ocean and the eastern and central Pacific. The model overestimates winds at 200 hPa in the equatorial Indian and west Pacific Ocean also (not shown). The simulation captures the winds quite well over the west African monsoon region, where the lack of precipitation in the model is obvious. Easterlies at 850 hPa are stronger over the southern Indian Ocean, where there is error in precipitation as well.

**2.2 Method** 

and P\*.

**2.3 Data** 

and Arkin, 1997).

as "observations".

affected by the model mean state.

**3. Results** 

**3.1 Mean state** 

wind and specific humidity, and boundary-layer moisture convergence in models are essential for them to reproduce realistic statistics of the intraseasonal variability. On the other hand, MJO events that are initiated by the extratropical influences may have less dependence on the mean state (e.g., Ray et al., 2011). A review of our present understanding of the MJO can be found in Zhang (2005).

The objective of this chapter is to further explore the role of the mean state on the MJO using a high-resolution nested regional climate model (NRCM). We use the NRCM (http://www.nrcm.ucar.edu), based on the Weather Research and Forecasting Model (WRF). The domain of this NRCM is global (periodic) in the zonal direction and is bounded in the meridional direction. The main advantage of the NRCM compared to a regular regional model is that, without the east-west boundaries, it isolates the external influences arriving solely from the extratropics. The added constraint provided by the lateral boundary conditions is expected to improve the simulated MJO statistics. Also, compared to a GCM, the NRCM has higher resolution and sophisticated physics that may be helpful to better capture the multi-scale organized convection associated with the MJO (Chen et al., 1996; Houze, 2004; Moncrieff, 2010).

The strategy of this study is to integrate the NRCM for several years and evaluate the role of the mean state on the MJO statistics. Our goal is to provide unique perspectives to the MJO dynamics and mean state.

Section 2 describes the configuration of the model, method and data. Section 3 explores the atmospheric mean state and its role on the MJO with an emphasis on the roles played by the mean precipitation and zonal winds at the 850 hPa (U850). Section 4 summarizes the results along with the implications and limitations of this study.
