Improved simulation of Indian summer monsoon in latest NCEP climate forecast system free run

Abstract

Simulation of Indian summer monsoon features by latest coupled model of National Centers for Environmental Prediction (NCEPs) Climate Forecast System version 2 (CFSv2) is attempted in its long run. Improvements in the simulation of Indian summer monsoon as compared with previous version (CFSv1) is accessed and areas which still require considerable refinements are introduced. It is found that, spatial pattern of seasonal mean rainfall and wind circulations are more realistic in CFSv2 as compared with CFSv1. Variance and northward propagation of intraseasonal oscillation (ISO), which also contribute to the seasonal mean rainfall are remarkably improved. However, the central Indian dry bias still persists and amplified. Pervasive cold bias in surface (2 m air temperature) as well as in the whole troposphere is further increased in CFSv2. These cold biases may be partly attributed to the lack of model's ability to realistically simulate the ratio of convective and stratiform rainfall. Sea-surface temperature (SST) over the Indian Ocean is underestimated in CFSv2. However, CFSv1 shows east-west dipole structure in the bias. The teleconnection of El Nino Southern Oscillation (ENSO) and Indian summer monsoon rainfall (ISMR) in terms of Niño3 SST and monsoon rainfall correlation is more realistic in the latest version of the model. Overall, there are substantial improvements in CFSv2 as compared with CFSv1, but it has to evolve further to realistically simulate the mean and variability of ISMR.

Mean state and interannual variability of the Indian summer monsoon simulation by NCEP CFSv2

“…Shukla and Kinter (2014) found that CFSv1 is not able to reproduce the observed ENSO-ISM relationship in rainfall anomalies. Saha et al (2014a) demonstrated that CFSv2 produces better spatial patterns of seasonal mean rainfall and circulation over extended Indian domain than CFsv1 does but the central Indian dry bias and cold SST bias in the Indian Ocean still persist in CFSv2. Shin and Huang (2015) further noticed that, in comparison with observations, CFSv2 generally simulates an earlier monsoon onset and stronger and longer lasting dry breaks and wet episodes that are phased-locked to the seasonal cycle in the ISM region.…”

“…Both CFSv2 and its predecessor, CFSv1, have shown considerable skill of seasonal prediction in tropics (e.g., Saha et al 2010Saha et al , 2014b. Using long-term simulations and seasonal hindcasts, many previous studies have examined different aspects of the seasonal and interannual variability of the ASM in CFSv1 (e.g., Yang et al 2008;Achuthavarier et al 2012;Pokhrel et al 2012;Chaudhari et al 2013;Shukla and Kinter 2014) and CFSv2 (e.g., Jiang et al 2013;Saha et al 2014a;Zhu and Shukla 2013;Mishra and Li 2014), which have identified some major problems in these simulations and hindcasts. For instance, Chaudhari et al (2013) reported that CFSv1 shows dry (wet) rainfall bias concomitant with cold (warm) SST bias over east (west) equatorial Indian Ocean.…”

Indian summer monsoon precipitating clouds: role of microphysical process rates

“…dry precipitation bias over Indian region, cold tropospheric temperature bias over globe). They have also pointed out that the ratio of convective to total rainfall is overestimated as compared to observation (Saha et al 2014). Previous studies by Li et al (2011) have demonstrated that in the convectional GCM framework the improvement of convective parameterization may have a limited impact on the total precipitation.…”

“…One reason is connected with the fact that the potential predictability limit of Asian monsoon is low as compared to other tropical climate systems (Goswami 1998;Goswami et al 2006). Second important reason is that the climate models are ineffective to simulate observed distribution and intensity of monsoon rainfall realistically (Dai 2006;Kripalani et al 2007;Saha et al 2014). Therefore following question arises-why do models have difficulty in simulating the monsoon rainfall?…”

“…The accurate simulation of cloud condensate in a GCM is a major challenge for the modeling community (Waliser et al 2009) as the formulation of microphysics is more primitive in most GCMs. Recently Saha et al (2014) have documented the few major biases in NCEP Climate Forecast System (CFS) version 2 (i.e. dry precipitation bias over Indian region, cold tropospheric temperature bias over globe).…”