Simulation of synoptic features during summer monsoon onset over GWB, India, with CFSv2 coupled model: skill and bias assessment
- 41 Downloads
The aim of this study is to examine the skill of climate forecast system version 2 (CFSv2) in simulating the synoptic features of Bay of Bengal (BOB) branch of summer monsoon (SM) during the onset over Gangetic West Bengal (GWB), India. Precise prediction of the onset time and the synoptic features associated with the onset is a major challenge in SM study. Better understanding of the synoptic and intra-seasonal variability during the propagation along with the mean simulation of monsoon features is crucial, especially for the operational models. The earlier studies focused mainly on the mean simulation of SM during June–September (JJAS) period. However, the main objective of the present study is to improve the understanding of CFSv2 model biases in simulating the synoptic features during the propagation of BOB branch of SM system till the onset over GWB. The skill of the coupled model is estimated for the years 2011 to 2015 with tropospheric temperature (TT), sea surface temperature (SST), mean sea level pressure (MSLP), winds at 850 and 500 hPa pressure levels, and rainfall rate (RR). The result shows that the observed characteristics are simulated, reasonably well, by CFSv2 model with quite high reliability unlike other coupled models. The CFSv2 has been able to simulate the position/variation during the onset; however, the model has not been able to estimate the intensity in some occasions. The gradients of pressure and SST have been slightly overestimated by the model. The model has not been able to simulate the winds at 850 and 500 hPa pressure levels in some occasions. The CFSv2 model in simulating the features during propagation of BOB branch of SM system shows disparity from observation in some occasions during 2011 to 2015. The result also reveals that the model biases remain unaltered during El Niño episode of 2011.
The corresponding author acknowledges the MoES and DST, GOI, for providing the opportunity to join the National Research Programme “National Monsoon Mission” and “National Network of Climate Modeling”. The authors thank the Editor-in-Chief of the journal and the anonymous reviewers for excellent review and constructive comments on the manuscript which helped to improve the clarity.
- Achuthavarier D, Krishnamurthy V (2010b) Relation between intraseasonal and interannual variability of the south Asian monsoon in the National Centers for Environmental Predictions forecast systems. J Geophys Res 115. https://doi.org/10.1029/2009JD012865
- Chaudhuri S, Das D, Goswami S, Das SK (2016) Long-range forecast of all India summer monsoon rainfall using adaptive neuro-fuzzy inference system: skill comparison with CFSv2 model simulation and real-time forecast for the year 2015. Clim Dyn 47:3319–3333. https://doi.org/10.1007/s00382-016-3028-4 CrossRefGoogle Scholar
- Clough SA, Shephard MW, Mlawer EJ, Delamere JS, Iacono MJ, Cady‐Pereira K, Boukabara S, Brown PD (2005) Atmospheric radiative transfer modeling: A summary of the AER codes. J Quant Spectrosc Radiat Transfer 91:233–244Google Scholar
- Ek HPA, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley JD (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res 108(D22):8851. https://doi.org/10.1029/2002JD003296 CrossRefGoogle Scholar
- Goswami BN, Xavier PK (2005) ENSO control on the South Asian monsoon through the length of the rainy season. Geophys Res Lett 32(L18717). https://doi.org/10.1029/2005GL023216
- Griffies SM, Harrison MJ, Pacanowski RC, Rosati A (2004) A technical guide to MOM4, GFDL ocean group technical report 5, GFDL, pp 337Google Scholar
- Kang I-S, Jin K, Wang B, Lau K-M, Shukla J, Krishnamurthy V, Schubert SD, Wailser DE, Stern WF, Kitoh A, Meehl GA, Kanamitsu M, Galin VY, Satyan V, Park C-K, Liu Y (2002) Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs. Clim Dyn 19:383–395CrossRefGoogle Scholar
- Kim and Arakaw (1995) Improvement of orographic gravity wave parameterization using a mesoscale gravity wave model. J Atmos Sci 52(11):1875–1902Google Scholar
- Lott F, and Miller MJ (1997) A new subgrid-scale orographic drag parametrization: Its formulation and testing. Q J R Meteor Soc 123:101–127Google Scholar
- Saha S, Moorthi S, Pan H-L, Wu X, Wang J, Nadiga S, Tripp P, Kistler R, Woollen J, Behringer D, Liu H, Stokes D, GruhPaine R, Gayno G, Wang J, Hou YT, Chuang HY, Juang H-MH, Sela J, Iredell M, Treadon R, Kleist D, Delst PV, Keyser D, Derber J, Ek M, Meng J, Wei H, Yang R, Lord S, Dool HVD, Kumar A, Wang W, Long C, Chelliah M, Xue Y, Huang B, Schemm JK, Ebisuzaki W, Lin R, Xie P, Chen M, Zhou S, Higgins W, Zou CZ, Liu Q, Chen Y, Han Y, Cucurull L, Reynolds RW, Rutledge G, Goldberg M (2010) The NCEP climate forecast system reanalysis. Bull Amer Meteor Soc 91:1015–1057CrossRefGoogle Scholar
- Sharmila S, Pillai SA, Joseph S, Roxy M, Krishna RPM, Chattopadyay R, Abhilash S, Sahai AK, Goswami BN (2013) Role of ocean-atmosphere interaction on northward propagation of Indian summer monsoon intra-seasonal oscillations (MISO). Clim Dyn 41:1651–1669. https://doi.org/10.1007/s00382-013-1854-1 CrossRefGoogle Scholar
- Wu R, Kirtman BP (2004) Impacts of the Indian Ocean on the Indian summer monsoon-ENSO relationship. J Climate 17:3037–3054Google Scholar