Predictability of summer northwest Pacific climate in 11 coupled model hindcasts: Local and remote forcing

Abstract

[1] The skills of 11 coupled ocean-atmosphere general circulation models (CGCMs) are investigated in the prediction of seasonal rainfall and circulation anomalies over the northwest (NW) Pacific for the period 1980-2001, with a focus on the summer following the mature phase of El Niño (hereafter JJA(1)). It is shown that the first empirical orthogonal function (EOF) mode of sea level pressure is closely tied to the second EOF mode of rainfall variability over the NW Pacific during JJA(1), indicative of strong feedback between circulation and convection. Most coupled models and the associated multimodel ensemble well predict these EOF modes and their relationship with high fidelity. Coupled models are capable of predicting suppressed rainfall over the NW Pacific in JJA(1). A few models fail to predict the concurrent weak negative sea surface temperature (SST) anomalies on the southeastern flank of the anomalous anticyclone. This suggests that remote forcing via teleconnections is important for NW Pacific rainfall prediction in those models. In some models, local air-sea interactions seem also to play a role. Specifically, remote forcing by tropical Indian Ocean (TIO) SST variability is identified as influential on NW Pacific climate during JJA(1). TIO SST affects the atmosphere over the NW Pacific by two mechanisms, via the equatorial Kelvin wave and the intensification of the subtropical westerly jet. Overall, models are successful in predicting the antisymmetric patterns of precipitation and winds over TIO during spring, which are critical in sustaining the TIO warming through the subsequent summer.

Impacts of tropical Indian Ocean SST on the meridional displacement of East Asian jet in boreal summer

“…Therefore, though not the only factor, the TIO warming plays a very important role in WNP circulation change. In addition, muti-model results confirm the aforementioned conclusion (Chowdary et al, 2010).…”

“…Serials of studies found that the TIO warming is triggered by ENSO and that the warming is induced by ocean dynamics and local air-sea interaction (Huang and Kinter, 2002;Xie et al, 2002;Du et al, 2009;Xie et al, 2009). Indeed, ENSO does not affect the WNP rainfall directly and that ENSO-induced TIO SSTA in the following summer is an important direct factor (Yang et al, 2007;Xie et al, 2009;Chowdary et al, 2010Chowdary et al, , 2011. A coupled general circulation model, which has quite good predicting skill, is used to analyse the relative role of TIO (Chowdary et al, 2011).…”

“…Furthermore, the convection over the western North Pacific (WNP) can affect the MDE through meridional teleconnection (Lau et al, 2000;Lu, 2004). However, the variation of convection over the WNP is mainly attributed to the tropical Indian Ocean (TIO) sea surface temperature (SST; Yang et al, 2007;Xie et al, 2009;Chowdary et al, 2010;Chowdary et al, 2011).…”

Future change of the Indian Ocean basin-wide and dipole modes in the CMIP5

“…It has been recognized that the variability and changes of the Indian Ocean sea surface temperature (SST) play an important role in climate variability worldwide including Asian summer monsoon (e.g., Abram et al 2008;Schott et al 2009), Northwestern Pacific climate (e.g., Chowdary et al 2010;Xie et al 2009), the African Sahel drying trend (e.g., Giannini et al 2003), and El Niño and Southern Oscillation (ENSO) (e.g. Yu et al 2002;Luo et al 2012).…”

Seasonal predictability of the 2010 Russian heat wave

“…However, some of them reported difficulties to predict summer mean precipitation anomalies in northwestern Asian monsoon events even for a 0-month lead forecast, although they are capable of predicting zonal wind anomalies at 850 hPa several months ahead and, consequently, satisfactorily predict summer monsoon circulation (Lee et al, 2011). A computationally feasible approach in order to accomplish reasonable predictions on a seasonal timescale is through ensemble forecasting in which several model forecasts are performed by introducing perturbations in the initial conditions or in the models themselves (Kalnay, 2003;Chowdary et al, 2010).…”