Intra‐seasonal variability of the South Asian monsoon and its relationship with the Indo–Pacific sea‐surface temperature in the NCEP CFSv2

Abstract

The capability to predict the leading modes of daily variability for South Asian monsoon in the climate forecast system version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP) is investigated. The CFSv2 model forecast at four pentad leads named as P1–P4 has been used in this study. The multi‐channel singular spectrum analysis (MSSA) on the daily anomalies of precipitation over the South Asian monsoon region for the period of 2001–2014 with a lag window of 61 days has been applied for June–July–August–September (JJAS) for all the four pentad lead forecasts of model and observation. It is encouraging that the space–time structure and propagation characteristics are exactly similar to observation up to P1 lead forecast. The model produces stationary modes and the northwest to southeast tilt significantly reduces from P2 lead onwards. The relationship of oscillatory and persisting modes with Indo–Pacific Ocean SST has been investigated. It is found that the SST over Pacific Ocean is independent of oscillatory mode in the case of P1 and P2 lead forecasts as in the case of observation. The model reproduces the observed correlation of Indian monsoon rainfall (IMR) index for the seasonally persisting mode with SST over Indo–Pacific Ocean up to P3 lead forecast which is a significant improvement. The contribution of El Niño‐Southern Oscillation (ENSO) mode to total anomaly over India is large in Pl lead and it decreases from P2 to P4 lead forecast.

Assessing teleconnections among ENSO, the tropical Atlantic and precipitation anomalies, and their effects on a tropical watershed

“…The rainfall anomaly index (rai) was calculated based on gridBR. This method was developed by Shahi et al (2018). Rai is a rank-based drought index that is not affected by time or space, incorporating a ranking procedure to assign magnitudes to positive and negative anomalies (Keyantash and Dracup, 2002;Razieri, 2021).…”

Impact of horizontal resolution on monsoon precipitation for CORDEX-South Asia: A regional earth system model assessment

“…We notice that the root mean square error (RMSE) between the model and observation is relatively less than the observed rainfall standard deviation for all zone except SPI, thus demonstrating our simulation's quality as a lesser RMSE of the model than observed variability (standard deviation) is good skill score to measure the quality of the model (Srivastava et al, 2016(Srivastava et al, , 2018Dwivedi et al, 2018Dwivedi et al, , 2019Mishra et al, 2020a) Noticeably, the increasing resolution results in improving the model's performance over most of the study regions except SPI where performance is found to degrade with increasing resolution. The ISM undergoes enhanced and suppressed rainfall activity over India on an intraseasonal time scale (Goswami and Ajaya Mohan, 2001;Dwivedi et al, 2006;Shahi et al, 2018). Past studies using RCM have reported the advantage of high resolution in simulating the intraseasonal variability (ISV) (Dash et al, 2014;Mishra et al, 2020b); however, limited studies have employed a regional coupled atmosphereocean model or RESM to understand mechanisms associated with ISV (Misra et al, 2017;Di Sante et al, 2019).…”

Inter-annual Variation of Summer Southwest Monsoon Rainfall over the Monsoon Core Region of the Eastern Bay of Bengal and its Relationship with Oceans

“…Numerous studies have investigated the relationships between ENSO and regional climate of Northern Indian Ocean (NIO) [7]- [9]. Many studies investigated the feedback of the IOD on the climate of the NIO and its neighbouring regions [10]- [12]. Sein et al, (2022) and Tsai et al, (2015) found a high correlation between the ENSO, IOD, and mainland Indochina rainfall, especially in Myanmar.…”