How distinct are the two flavors of El Niño in retrospective forecasts of Climate Forecast System version 2 (CFSv2)?
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Two different flavors of El Niño-Southern Oscillation (ENSO, canonical east Pacific type and Modoki/central Pacific type) are reported in the recent decades and are found to influence the global climate in different ways. The success of a seasonal prediction system is dependent on its ability to capture these two ENSO flavors accurately, together with associated teleconnections. The present study analyses the ability of Climate Forecast System version 2 (CFSv2) in simulating the two El Niño flavors and their teleconnections. The study uses two versions of CFSv2 in which the atmospheric model horizontal resolutions are different (T126 at 100 km and T382 at 38 km) and are initialized from a calendar month, ranging from February to June. The canonical ENSO pattern is captured as prominent mode of tropical Pacific sea surface temperature (SST) by both resolutions of CFSv2. Even though the tri-polar structure of ENSO Modoki is simulated as second mode, it has some disagreement with observations. The canonical El Niño induced SST, rainfall and atmospheric circulation in the tropical Pacific in summer and fall seasons are comparable with observations in both models. Meanwhile, the teleconnections in the tropical Indian Ocean and Indian monsoon regions are close to observations in T382 only. Teleconnections associated with El Niño Modoki are proper in T382 hindcasts, in which SST bias in Indian Ocean is slightly warm and the cold bias in central Pacific is marginal (mainly for Feb IC hindcasts). The present study indicates that the distinction of ENSO flavors in summer is the major reason for the higher skill of Indian summer monsoon rainfall (ISMR) in CFSv2 T382 Feb IC hindcasts. However, teleconnections associated with two flavors of ENSO are not distinguishable in fall and winter seasons, even in higher resolution model due to the presence of strong cold SST bias in central Pacific and warm SST bias in extreme east Pacific. Thus present study confirms that, higher resolution CFSv2 is required to differentiate the flavors of ENSO and their teleconnections properly. It has better prediction skill for ISMR at a lead time of 4 months, which is significant for seasonal prediction of Indian summer monsoon.
KeywordsEl Niño flavors El Niño Modoki Teleconnection All India summer monsoon rainfall Model skill CFSv2
The Indian Institute of tropical Meteorology is fully supported by the Ministry of Earth Sciences (MoES), Govt. of India. Original version of CFSv2 is obtained from NCEP under Mou between MoES and NOAA. The model hindcasts are run in IITM in-house HPC system “Aaditya”. Authors thank India Meteorological Department for IMD rainfall data; Other observational/reanalysis data sets like GPCP rainfall, ECMWF wind, HadISST are downloaded from their respective websites.We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 2 of this paper) for producing and making available their model output. The editor and two anonymous reviewers of the journal are acknowledged for their suggestions, which helped us to improve the manuscript significantly.
- Capotondi A et al (2015) Understanding ENSO diversity. BAMS 96:921–938Google Scholar
- Ek MB, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarplay JD (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res 1089(D22):8851. doi: 10.1029/2002JD003296 CrossRefGoogle Scholar
- Griffies SM, Harrison MJ, Pacanowski RC, Rosati A (2004) A technical guide to MOM4. GFDL Ocean Group Tech Rep 5:337Google Scholar
- Jung T, Miller MJ, Palmer TN, Towers P, Wedi N, Achuthavarier D, Adams JM, Altshuler EL, Cash BA, Kinter JL III, Marx L, Stan C, Hodges KI (2012) High-resolution global climate simulations with the ECMWF model in Project Athena: experimental design, model climate, and seasonal forecast skill. J Clim 25:3155–3172CrossRefGoogle Scholar
- Kim S, Yu JY (2012) Two types of ENSO in CMIP5 models. Geophys Res Lett 39:L11704Google Scholar
- Kug JS, Ham YG, Lee JY, Jin FF (2012) Improved simulation of two types of El Niño in CMIP5 models. Environ Res Lett 7:1–7Google Scholar
- Rajeevan M, Bhate J, Kale JD, Lal B (2006) High resolution daily gridded rainfall data for the Indian region: analysis of break and active monsoon spells. Curr Sci 91:296–306Google Scholar
- Ramu DA, Sabeerali CT, Chattopadayay R, Rao DN, George G, Dhakate A, Salunke K, Sreevastava A, Rao SA (2016) Indian Summer Monsoon Rainfall simulation and prediction skill in the CFSv2 Coupled Model: impact of atmospheric horizontal resolution. J Geophys Res 121:2205–2221Google Scholar